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Aedes albopictus is an important dengue vector because of its aggressive biting behavior and rapid spread out of its native home range in Southeast Asia . Pyrethroids are widely used for adult mosquito control , and resistance to pyrethroids should be carefully monitored because vector control is the only effective method currently available to prevent dengue transmission . The voltage-gated sodium channel gene is the target site of pyrethroids , and mutations in this gene cause knockdown resistance ( kdr ) . Previous studies reported various mutations in the voltage-gated sodium channel ( VGSC ) gene , but the spatial distribution of kdr mutations in Ae . albopictus has not been systematically examined , and the association between kdr mutation and phenotypic resistance has not been established . A total of 597 Ae . albopictus individuals from 12 populations across Asia , Africa , America and Europe were examined for mutations in the voltage-gated sodium channel gene . Three domains for a total of 1 , 107 bp were sequenced for every individual . Two populations from southern China were examined for pyrethroid resistance using the World Health Organization standard tube bioassay , and the association between kdr mutations and phenotypic resistance was tested . A total of 29 synonymous mutations were found across domain II , III and IV of the VGSC gene . Non-synonymous mutations in two codons of the VGSC gene were detected in 5 populations from 4 countries . A novel mutation at 1532 codon ( I1532T ) was found in Rome , Italy with a frequency of 19 . 7% . The second novel mutation at codon 1534 ( F1534S ) was detected in southern China and Florida , USA with a frequency ranging from 9 . 5–22 . 6% . The WHO insecticide susceptibility bioassay found 90 . 1% and 96 . 1% mortality in the two populations from southern China , suggesting resistance and probable resistance . Positive association between kdr mutations with deltamethrin resistance was established in these two populations . Two novel kdr mutations , I1532T and F1534S were found in Ae . albopictus . This is the first report of I1532T mutations in Italy and F1534S mutation in China and US . Significant association between kdr mutation and protection from deltamethrin raised the possibility that kdr mutation may be a viable biomarker for pyrethroid resistance surveillance in Ae . albopictus . The patchy distribution of kdr mutations in Ae . albopictus mosquitoes calls for developing global surveillance plan for pyrethroid resistance and developing countermeasures to mitigate the spread of resistance .
Aedes albopictus , also known as Asian tiger mosquito , is notorious for its ability to transmit a number of arboviruses including dengue , Chikungunya and Zika virus as well as filarial nematodes [1–11] . The aggressive dispersal and thus world-wide invasiveness in recent years [5 , 6] , in addition to increased vector competence to Chikungunya viruses [9 , 10 , 12–15] , have proved high public health impact of Ae . albopictus . For instance , global spread of Ae . albopictus is linked to Zika virus outbreaks in urban areas of central Africa , Asia and the Pacific [16–18] . At present , there are neither effective vaccines nor therapeutic treatments targeted for viruses vectored by Ae . albopictus , making vector population control the only option to limit disease transmission [1 , 2 , 4–6 , 16] . Current vector control strategies primarily rely on the source reduction of larval breeding sites and use of insecticides targeting the larval and adult stages [4 , 16–25] . Among the four major synthetic insecticides groups , pyrethroids are the most widely used adulticide due to their low mammalian toxicity and their rapid knockdown effect [22–24 , 26] . Pyrethroids have been intensively used for space spray to control Aedes mosquitoes and dengue transmission [1 , 10 , 26–30] . Extensive and prolonged use of pyrethroids imposes selection pressure on Ae . albopictus populations and eventually increases the potential of resistance [2 , 3 , 9 , 10 , 25–28 , 31] . Pyrethroids target the VGSC gene , also known as voltage-gated sodium channel ( VGSC ) of insect neurons [28 , 32 , 33] . Generally among insects , there are two major mechanisms for conferring resistance against these insecticides . One is increased metabolic detoxification of insecticides , which is the most common form of resistance mechanism because of the higher expression or presence of more efficient detoxification enzymes [34] . The other known mechanism is reduced target site sensitivity resulting from non-synonymous mutations in the VGSC gene , leading to single amino acid substitutions , which has been shown to be correlated to phenotypic resistance to pyrethroids [35] . This form of resistance , known as knockdown resistance ( kdr ) , has been observed in a number of insects , including Anopheles gambiae [33 , 34] , An . sinensis [35 , 36] , Culex quinquefasciatus [37 , 38] and Ae . aegypti [32 , 39] . In An . gambiae , L1014F and L1014S in domain II of Subset 6 ( IIS6 ) of the voltage-gated sodium channel ( VGSC ) gene are the most well-known mutations related to pyrethroids and DDT resistance [33 , 34 , 37 , 38] . In Ae . aegypti , V1016G and V1016I mutation in IIS6 are positively related to pyrethroid resistance , and F1534C was found conferring pyrethroid resistance [40–42] . In Drosophila melanogaster , M1524I substitution has been associated with knockdown resistance [43] and in other arthropods and mammals , F1538I mutation was associated with reduced sensitivity to deltamethrin [44 , 45] . In Ae . aegypti , V1016I and V1016G mutations alter VGSC configuration and subsequently prevent insecticide binding . Codon 1530 and 1529 on IIIS6 of VGSC have been proposed to be r sensitivity to pyrethroids [46 , 47] . Two residues nearby codons 1535 and 1538 have been implicated in resistance to pyrethroids in other insect species [48 , 49] . For Ae . albopictus , F1534C was first reported in Singapore in 2011 [28] , and the same mutation was subsequently found in Malaysia as well as in the United States but with a different allele ( F1534L ) [25 , 43] . Along with the emergence and spread of kdr mutations , recent studies have demonstrated pyrethroid resistance in Ae . albopictus adults from different parts of southeast Asia such as Malaysia and Thailand and from Central Africa [1 , 25 , 27 , 31 , 50 , 51] . Previous studies examined kdr mutations in limited number of populations , systematic examination of kdr mutations in Ae . albopictus populations from a broader geographic range would provide important information on kdr mutation distribution and potential risk of resistance spread . In the present study , we examined mutations in the VGSC gene of Ae . albopictus across Asia , Europe , and North America , encompassing almost the entire range of its distribution . In addition , the association between kdr mutation and phenotypic resistance was assessed in a subset of populations to provide a deeper insight into the role of kdr mutations on pyrethroid resistance .
Aedes albopictus samples were collected between 2011 and 2014 in 12 sites from 6 countries ( S1 Table ) . These sites were selected based on the global distribution of Ae . albopictus and willingness of in-country collaborators . These sampling sites included the native home range in Southeast Asia ( i . e . Guangzhou , Shenzhen [China] , Nagasaki [Japan] and Serangoon [Singapore] ) , and derived populations ( i . e . Hawai’i [USA] , La Reunion [France] , California , Texas , Florida [USA]] , Arco , Rome [Italy] , and Athens [Greece] ) . At all sampling sites , pyrethroids were the commonly used insecticide for vector control and agricultural pest control [52 , 53] . Historically , organophosphates were used for vector control since 1950s [5 , 54 , 55] in these sites . For each sample site , immature Ae . albopictus ( larvae and pupae ) were collected from more than 50 different aquatic habitats , such as discarded plastic containers , flower pots and used tires except that in La Reunion adult mosquitoes were collected using the BG-sentinel trap ( Biogents , Regensburg , Germany ) . In each site mosquitoes were collected in one time point as indicated in Table 1 . The field collected larvae/pupae were reared to adults and preserved for subsequent DNA analysis . Genomic DNA was extracted from individual mosquitoes using the SYBR Green Extract-N-Amp Tissue PCR Kit ( Sigma Aldrich ) following the manufacturer’s protocol . Extracted DNA was stored at 4°C or used immediately for PCR . All the specimens were identified as Ae . albopictus using PCR with species-specific primers for the ribosomal internal transcribed spacer ( ITS1 and ITS2 ) and 18S rDNA regions [45] . A total of 597 Ae . albopictus mosquitoes , ranging from 26–76 individuals per population , were subjected to kdr genotyping . Portions of domains II , III , IV of the VGSC gene were amplified , following protocols and primers developed by Kasai et al [28] ( covering 989 , 1011 , 1016 and 1534 codon positions ) . PCR products were purified with ExoSAP-IT ( USB , Cleveland , Ohio , USA ) according to the manufacturer’s protocol and directly sequenced by Genewiz Inc . ( South Plainfield , NJ ) . The sequences were aligned and analyzed using BioEdit ( http://www . mbio . ncsu . edu/BioEdit/bioedit . html ) and Codon code ( http://www . codoncode . com/ ) . To determine resistance level of Ae . albopictus in the field , we conducted pyrethroid susceptibility bioassay in two populations from southern China ( Shenzhen and Guangzhou ) . Briefly , in each location ~8 , 000 larvae were collected from 400 natural habitats and reared to adults in insectary . All specimens were identified to species by morphology . Adult females 3–5 days post emergence were subjected to insecticide susceptibility test against 0 . 05% deltamethrin following the standard WHO tube test protocol [10] . Control tests were performed using silicone oil , pre-impregnated papers . Adult bioassays were conducted with 20–25 mosquitoes per replicate , and 8–20 replicates per population . The number of mosquitoes being knocked down was recorded every 10 minutes during the 60 min exposure period . Mortality was scored after 24 hr recovery period . Overall , 420 female adults from Guangzhou and 150 individuals from Shenzhen were subjected to susceptibility bioassay . The susceptible Foshan strain of Ae . albopictus originated from Foshan city ( 40 Km away from Guangzhou ) and has been maintained in the laboratory since 1981 with no insecticide exposure , was used as a susceptible reference population . Insecticide susceptibility bioassay was performed in China only , but not in other countries due to logistic constraints . To establish association between kdr mutations and phenotypic resistance , we screened 2017 female adults from Guangzhou and 1350 from Shenzhen for deltamethrin resistance using the standard WHO tube bioassay . Here resistant individual is defined as a mosquito being alive after the 24 hr recovery period , and susceptible mosquito is defined as being dead after the 24 hr recovery period . This definition of resistance is reasonable because the 0 . 05% deltamethrin diagnostic dose kills 99 . 9% susceptible mosquitoes [56] . This screening yielded 79 and 115 resistant mosquitoes from Guangzhou and Shenzhen respectively . All these resistant mosquitoes and 153 susceptible mosquitoes were genotyped for kdr mutation at 1534 codon by direct sequencing . For kdr mutation survey in multiple populations , mutation frequencies at each codon were calculated for each population . Frequencies of synonymous and non-synonymous mutations were presented . For non-synonymous mutations , Hardy-Weinberg equilibrium test was performed using Fisher’s Exact test with Bonferroni corrections to determine the heterozygote deficit in each population . To determine the association between kdr mutations and resistance in the two populations from southern China , Fisher’s Exact test was performed and odds ratio was determined between resistant and susceptible mosquitoes for each kdr allele . To determine population resistance status to pyrethroids , mortality rates of the two populations from southern China was calculated . Resistance status was classified according to WHO ( 2013 ) criteria: resistant for <90% mortality , probable resistant for 90–98% mortality , and susceptible for >98% mortality [56] . The 50% and 95% knockdown time , KDT50 and KDT95 , were determined based on exponential decay model .
Sequences of domains II ( 480 bp ) , III ( exon 1; 2 , 347 bp ) , and IV ( 280 bp ) of the VGSC gene were obtained from a total of 597 mosquitoes . All mutations in codons 989 , 1011 and 1016 within domains II or IV were synonymous ( codon nomenclature is based on Musca domestica VGSC gene according to the accepted kdr codon nomenclature method ) . In domain III non-synonymous mutations were detected at codons 1532 and 1534 . At codon 1532 , a change from wildtype codon ATC ( isoleucine ) to ACC ( threonine ) was detected in one population only ( Rome , Italy ) . Thirteen out of the 40 samples were heterozygotes and one was a homozygote TT , giving an I1532T mutation frequency of 19 . 7% . At codon 1534 , polymorphism was detected in five ( Guangzhou , Shenzhen , Arco , Athens and Florida ) populations out of the 12 populations examined ( Table 1 and Fig 1 ) . A total of three mutated alleles were detected . Mutations from wildtype TTC ( Phe ) to either TCC ( Ser ) or TTG ( Leu ) was detected in southern China ( Guangzhou and Shenzhen populations ) , with a frequency ranging from 4 . 9–25 . 4% . Mutation from TTC ( Phe ) to TTG ( Leu ) was detected in one individual from Arco , Italy as a homozygote , giving a mutation frequency of 2 . 6% . Mutation from TTC ( Phe ) to TGC ( Cys ) was detected in 12 Athens individuals , of which six are heterozygous F/C and six are homozygous C/C , giving a mutation frequency of 24 . 2% . Mutation from TTC ( Phe ) to TCC ( Ser ) was detected in 10 individuals from Florida , of which all are heterozygotes giving a mutation frequency of 11 . 9% . Compared to published kdr mutation frequency in Ae . albopictus , the mutation frequency at the 1534 codon found in our populations , particularly those from southern China and Athens , Greece very high . Also , considerable number of homozygous mutant individuals was found ( 30 . 6% in Guangzhou , 13 . 7% in Shenzhen , and 11 . 3% in Athens ) . Fisher’s Exact test found that three out of four populations ( Guangzhou , Shenzhen and Greece ) were not in Hardy—Weinberg equilibrium for genotypes in codon 1534 . Significant departure from Hardy—Weinberg equilibrium resulted from a heterozygote deficit . A total of 29 synonymous mutations across domain II , III and IV were recorded [S2 Table] . Insecticide susceptibility bioassay found that Ae . albopictus mortality rate after the 24 hr recover period was 90 . 1% and 96 . 1% for Shenzhen and Guangzhou populations ( Table 2 ) . Based on the WHO criteria , Ae . albopictus population from Shenzhen was classified as “resistant” and the Guangzhou population as probably resistant . The 50% knockdown time ( KDT50 ) was 2 . 3 times in Shenzhen population compare to the susceptible laboratory colony , and 1 . 7 for the Guangzhou population ( Table 2 ) . Similar increase in knockdown time was also found in the 95% knockdown time ( KDT50 ) in field population compared to the control population . This pattern of delayed knockdown in Shenzhen and Guangzhou populations was consistent with bioassay mortality rates and population resistance classification ( Fig 2 ) . We genotyped 1534 codon of the VGSC gene for a total of 347 female mosquitoes from the two southern China populations that have been phenotyped for resistance to deltamethrin . Among them , 194 individuals were classified as “resistant” ( being alive after the 24 hr recovery period in the WHO tube bioassay ) , and 153 were “susceptible” . Three alleles ( wildtype F1534 , F1534S and F1534L ) and five genotypes were detected indicating two mutations at this codon ( Table 3 ) . To determine the impact of kdr mutation at 1534 codon on pyrethroid resistance , F1534S and F1534L alleles were analyzed separately for their associations with deltamethrin resistance . We found that F1534S mutation frequency was significantly higher in the resistant population than in the susceptible population for both Shenzhen and Guangzhou . F1534S mutation showed increased protection against deltamethrin in both populations ( odds ratio for Guangzhou 3 . 3 , p <0 . 0001; odds ratio for Shenzhen 2 . 7 , p <0 . 0001 ) ( Table 3 ) . On the other hand , F1534L mutation was not significantly associated with deltamethrin resistance in both populations ( P > 0 . 05 ) .
The present study is by far the most comprehensive survey of kdr mutations in Ae . albopictus mosquitoes from broad geographical regions . Two important findings arose from this study . First , we identified two novel kdr mutations: I1532T and F1534S . Along domains II , III and IV of the VGSC gene , non-synonymous mutations were detected only at two codons ( 1532 and 1534 ) . A novel I1532T mutation that has not been previously reported in Ae . albopictus was found uniquely present in Rome , Italy among the 12 populations examined , and it was prevalent with a frequency of 19 . 7% . Interestingly , this mutation was not found in the Arco population , which is 570 km away from Rome in Italy . It is worth mentioning that the mosquitoes from Arco were collected in 2011 , two years prior to those collected at Rome . Hence , the difference in collection time and/or limited sample size may influence detection of this mutation at the population level . The second novel F1534S mutation was found abundant in the two populations from southern China and Florida with a frequency ranging from 9 . 5–22 . 6% . The second important finding is that distribution of kdr mutations in Ae . albopictus was patchy as evidenced by that fact among the 12 field populations examined , five populations exhibited polymorphism at codon 1532 or 1534 , and 7 populations were monomorphic . Surprisingly modest F1534C mutation frequency was found in the Greece population . Pyrethroids were used primarily for personal protection in domestic applications in the urban environments . Ultra low volume sprays and long-term use of pyrethroids in surrounding agricultural fields may have accelerated the selection for pyrethroid resistance . However , whether the F1534C mutation can be used as a biomarker for pyrethroid resistance monitoring in Ae . albopictus populations in Greece need further evidence from pyrethroid resistance bioassay . Using the mosquito samples from southern China , we established that kdr mutation conferred protection against deltamethrin in Ae . albopictus by an odds ratio of 3 . 3 in Guangzhou and 2 . 7 in Shenzhen ( Table 3 ) . This finding was consistent with studies on Ae . aegypti which reported that F1534C mutation was significantly deltamethrin resistance [25 , 29 , 32] The role of F1534C mutation in insecticide resistance was further confirmed in Xenopus oocyte by the demonstration of this mutation reduced the channel sensitivity to pyrethroids [32 , 57 , 58] . The present study established significant association between F1534S mutation and pyrethroid resistance in Ae . albopictus in the two south China populations . We found a modest frequency of kdr mutations in the two southern China populations . This modest frequency of kdr mutations may be related to intense pyrethroids usage in the past two decades in the area where major dengue outbreaks have occurred [26 , 59–64] . Pyrethroids have been the major insecticide used for city-wide aerial spray for adult mosquito control to contain dengue outbreaks [26 , 54 , 59–62 , 65] . Therefore , monitoring the kdr mutation frequency may aid the surveillance of pyrethroid resistance in Ae . albopictus . We recognize several limitations in our study . First , only two out of 12 populations were bioassayed for pyrethroid resistance . Due to logistic constrains , it was not possible for us to collect a large number of Ae . albopictus larvae and conduct resistance bioassay . Second , survey on kdr mutation frequency on more countries would be ideal . Third , the association between kdr mutations and resistance was examined based on two populations , and the generality of the finding should be tested . The findings from this study have important implication on Ae . albopictus control . First , the patchy distribution of kdr mutations in Ae . albopictus mosquitoes calls for developing global surveillance plan for pyrethroid resistance and developing countermeasures to mitigate the spread of resistance . It is entirely possible that many Ae . albopictus populations in the field are susceptible to pyrethroid , containing the spread of pyrethroid resistance would greatly preserve the effectiveness of pyrethroid insecticides . Second , significant association between kdr mutation and protection from deltamethrin raised the possibility that kdr mutation may be a viable biomarker for pyrethroid resistance surveillance in Ae . albopictus . We do not discount the potential role of metabolic detoxification enzymes and other resistance mechanisms in pyrethroid resistance , rather we emphasize that more research is needed to validate the correlation between kdr mutation and pyrethroid resistance at the population level . | Aedes albopictus is a major dengue and Chikungunya vector and highly invasive . In the absence of effective treatment for the arbovirus infections , vector control is the only viable option . Pyrethroids are the most widely used insecticide for vector control programs due to low mammalian toxicity and rapid knockdown action . Extensive and prolonged use of pyrethroids imposes selection pressure on mosquito populations and eventually increases the potential of resistance . Monitoring pyrethroid resistance is essential to effective management of resistance . The voltage-gated sodium channel gene is the target site of pyrethroids , and mutations in this gene result in knockdown resistance ( kdr ) . Previous studies reported various mutations in the VGSC gene , but the spatial distribution of kdr mutations in Aedes albopictus has not been systematically examined , and the association between kdr mutation and resistance has not been established . In the present study , we examined kdr mutation distribution in 12 populations from Asia , Africa , America and Europe . We found two novel and abundant kdr mutations , and established significant positive association between kdr mutations with deltamethrin resistance . This finding raised the possibility that kdr mutation may be a viable biomarker for pyrethroid resistance surveillance in Ae . albopictus . The patchy distribution of kdr mutations in Ae . albopictus mosquitoes calls for developing global surveillance plan for pyrethroid resistance and developing countermeasures to mitigate the spread of resistance . | [
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] | 2016 | Multi-country Survey Revealed Prevalent and Novel F1534S Mutation in Voltage-Gated Sodium Channel (VGSC) Gene in Aedes albopictus |
No commercially licensed vaccine or treatment is available for dengue fever , a potentially lethal infection that impacts millions of lives annually . New tools that target mosquito control may reduce vector populations and break the cycle of dengue transmission . Male mosquito seminal fluid proteins ( Sfps ) are one such target since these proteins , in aggregate , modulate the reproduction and feeding patterns of the dengue vector , Aedes aegypti . As an initial step in identifying new targets for dengue vector control , we sought to identify the suite of proteins that comprise the Ae . aegypti ejaculate and determine which are transferred to females during mating . Using a stable-isotope labeling method coupled with proteomics to distinguish male- and female-derived proteins , we identified Sfps and sperm proteins transferred from males to females . Sfps were distinguished from sperm proteins by comparing the transferred proteins to sperm-enriched samples derived from testes and seminal vesicles . We identified 93 male-derived Sfps and 52 predicted sperm proteins that are transferred to females during mating . The Sfp protein classes we detected suggest roles in protein activation/inactivation , sperm utilization , and ecdysteroidogenesis . We also discovered that several predicted membrane-bound and intracellular proteins are transferred to females in the seminal fluids , supporting the hypothesis that Ae . aegypti Sfps are released from the accessory gland cells through apocrine secretion , as occurs in mammals . Many of the Ae . aegypti predicted sperm proteins were homologous to Drosophila melanogaster sperm proteins , suggesting conservation of their sperm-related function across Diptera . This is the first study to directly identify Sfps transferred from male Ae . aegypti to females . Our data lay the groundwork for future functional analyses to identify individual seminal proteins that may trigger female post-mating changes ( e . g . , in feeding patterns and egg production ) . Therefore , identification of these proteins may lead to new approaches for manipulating the reproductive output and vectorial capacity of Ae . aegypti .
Male seminal fluid proteins ( Sfps ) influence female reproductive and feeding behaviors in a range of insects studied to date ( reviewed in [1] , [2] ) . Therefore , these proteins may provide targets or pathways that can be manipulated to reduce pathogen transmission by blood-feeding arthropods . The Aedes aegypti mosquito transmits several pathogens of concern to human health , including the viruses that cause dengue and dengue hemorrhagic fever ( DHF ) ( [3] ) . Dengue , the most important mosquito-borne virus impacting human health , is a re-emerging disease in the tropical regions of the world . There is currently no vaccine against , or cure for , dengue , although research in this area is ongoing ( [4]–[6] ) . Therefore , prevention of dengue infection depends heavily on control of its mosquito vector . Understanding mosquito reproductive biology is critical to developing effective vector control methods . Previous research on Ae . aegypti suggests that mating and , specifically , male-derived proteins may play an important role in modulating female reproduction and feeding behavior . Upon mating , female Ae . aegypti undergo a series of time-dependent behavioral and physiological changes . Relative to virgin females , mated females have increased egg development and oviposition rates ( [7] , [8] ) , blood digestion rates ( [9] , [10] ) , and blood meal size ( [10] ) . Mated females also have a lower likelihood of being inseminated by another male ( [11] ) , of flying ( [12] , [13] ) , and of responding to host cues ( [14]–[17] ) , and they have a reduced daily blood-feeding frequency ( [18] ) . These changes in mated females appear to be induced by molecules produced in males' accessory glands ( AG ) and transferred to the female during mating ( [9] , [19]–[28] ) . In two other Dipteran species , individual AG-derived Sfps have been associated with functions in mated females . In Drosophila melanogaster , experimental studies have demonstrated that specific AG-derived Sfps influence a wide range of female post-mating behaviors including oogenesis ( sex peptide ) , ovulation ( ovulin ) , sperm storage and release from storage ( Acp36DE , Acp29AB , CG1652/CG1656 , CG17575 , CG9997 ) , propensity to re-mate ( sex peptide ) , activity level ( sex peptide ) , and feeding ( sex peptide; reviewed in [2] , [29]–[32] ) . In Anopheles gambiae , transglutaminase derived from male reproductive glands is necessary for the formation of the mating plug which is required for proper sperm storage ( [33] ) . In both Ae . aegypti and D . melanogaster , secretions from the male AGs are necessary for fertility ( [19] , [34] ) . Identification of individual bioactive Sfps causing post-mating changes in female Ae . aegypti has not yet been accomplished and is a long-term goal of our research . Previously , we identified over 250 proteins from male Ae . aegypti reproductive glands ( AGs and seminal vesicles; [35]; L . Sirot , M . Wolfner , L . Harrington , unpubl . data ) . Fifty-three of those proteins were considered to be putative Sfps based on the criteria that they contained predicted secretion signal sequences and were not known to be housekeeping or structural proteins ( [35] ) . However , we did not have direct evidence that those proteins were transferred to females during mating . In the current study , we identify a suite of proteins that are transferred from males to females during mating , and are thus candidate regulators of female behavior and physiology . Male- and female-derived proteins in the female reproductive tract were distinguished using an approach adapted from a study in D . melanogaster ( [36] ) that combined proteomics with a stable-isotope labeling technique ( using 15N ) . We adapted this method to blood-feeding mosquitoes and discovered a set of proteins transferred from male to female Ae . aegypti . Among the Sfps we identified are potential modulators of protein activation/inactivation , sperm utilization , and ecdysteroidogenesis . Few of the Ae . aegypti Sfps we detected are homologs of known or predicted Sfps in other insect species , although many are in protein classes that are conserved across seminal fluid of a wide range of taxa ( [37] , [38] ) . Furthermore , our finding of intracellular and membrane-bound proteins in the transferred Sfps supports the hypothesis that Ae . aegypti Sfps are secreted , at least in part , through apocrine processes ( pinching off of the apical portion of the cells into vesicles containing Sfps; [39] ) in the accessory glands . In the process of identifying the Sfps , we also identified a subset of 52 putative Ae . aegypti sperm proteins . The D . melanogaster homologs of many of the predicted Ae . aegypti sperm proteins are also sperm proteins ( [40] ) , suggesting conservation of sperm-related function across Diptera . Some of the proteins we have identified may be useful targets for control of Ae . aegypti and may be applicable to other mosquito vectors .
In order to identify male-derived proteins that are transferred to females during mating , we used a whole-organism isotope labeling method . The principle of this method is to mate males to females whose proteins are labeled with the stable isotopes so as to exclude the female proteins from proteomic identification . Specifically , female proteins are labeled with 15N , which shifts their masses upward such that the masses of female-derived peptides do not match those expected in a standard search ( uncorrected for 15N ) of a predicted protein database . The method was developed by Krijgsveld et al . [48] and first used to identify Sfps by Findlay et al . [36] in D . melanogaster . We adapted this method to label female-derived proteins in Ae . aegypti . As with D . melanogaster , we reared larvae on yeast whose only nitrogen source was 15N . However , in order to generate females that could fly and mate , we had to supplement the larvae with an inoculum of rearing-water from larvae previously reared on 15N-labeled yeast ( see Methods for more detail ) . To verify that the 15N-labeling technique sufficiently labeled female-derived proteins , we conducted nanoLC-MS/MS on protein samples from the reproductive tracts of labeled and unlabeled virgin females . We initially analyzed protein samples from two arbitrarily-chosen molecular weight ranges ( ∼30 kD to 50 kD and ∼98 kD to 120 kD ) of both types of females . Using the Vectorbase database , we identified 115 proteins from the unlabeled female samples ( Table S3 ) and no proteins from the labeled female samples . To further verify the labeling technique , we conducted nanoLC-MS/MS on the remaining gel sections from the labeled virgin female sample . We did not identify proteins from any of these samples . These results demonstrate that any proteins we identify in the reproductive tracts of labeled females mated to unlabeled males are highly likely to be male-derived . Furthermore , the technique we developed for in vivo stable-isotope labeling of Ae . aegypti proteins could be applied to other studies ( e . g . , to quantify proteomic changes in females in response to mating and/or blood-feeding or to distinguish mosquito-derived proteins from those of their pathogens , parasites , and/or endosymbionts; [49] ) . In our search against the Vectorbase database , we identified 128 proteins in the reproductive tracts of labeled females after mating with unlabeled males ( Tables 1 and 2 ) . Since the Ae . aegypti genome sequence is relatively new and thus the current annotation might still be missing actual genes , we also searched our mass spectrometry results against a 6- frame translation database of the Ae . aegypti contigs ( Version AaegL1 . 2 ) and against a database of predicted small peptides ( <150 amino acids ) . In our search against the 6-frame translation , we identified 12 novel predicted semen proteins ( Tables 1 and 2 ) . We identified 5 novel predicted small peptides from the small peptides database ( Tables 1 and 2 ) . The sequences of the unannotated predicted proteins and peptides are provided in Table S4 . Thus , in total , we identified 145 male-derived predicted proteins that are transferred during mating to females . These proteins include Sfps and sperm proteins . For all searches , the FDR was ≤1% . Nine of the identified proteins share identical amino acid sequence with other Ae . aegypti predicted proteins in the regions that were identified by our mass spectrometry analysis . As a result , we cannot distinguish amongst these proteins in our samples . For simplicity , we have listed just one protein from each of these pairs or groups of indistinguishable proteins in Tables 1 and 2 . However , we list the identities of all proteins in these pairs or groups in Table S5 . Of the 145 transferred proteins we identified using the whole-organism isotope labeling method , 123 are newly-recognized components of Ae . aegypti semen . The remaining 22 were previously identified as putative Sfps ( [35] ) , and we demonstrate here that they are transferred to females during mating . Thirty-one additional proteins were identified as putative Sfps in our previous study ( [35] ) , but we did not detect them as transferred in our current study . Those proteins may not be transferred to females , or may be transferred at quantities below our detection threshold or with post-translational modifications that render them unidentifiable by standard mass spectrometry . Of the 123 newly-recognized seminal proteins , 84 were previously identified from the reproductive glands of Ae . aegypti , however they were not designated as putative Sfps because they lacked predicted secretion signal sequences ( [35]; L . Sirot , M . Wolfner , L . Harrington , unpubl . data ) . In order to distinguish Sfps from sperm proteins among those transferred to females , we conducted a proteomics analysis of sperm-enriched samples from the seminal vesicles ( SVs ) and testes of virgin males . Sperm-enriched samples were obtained by releasing sperm from these organs , pelleting the sperm by centrifugation , and washing them repeatedly , as in Dorus et al . [40] ( see Methods for details ) . We found 101 proteins that overlapped between our sperm-enriched samples from seminal vesicles and our sperm-enriched samples from testes . Of these 101 putative sperm proteins , 52 were detected as transferred to females during mating , providing a high-confidence subset of putative Ae . aegypti sperm proteins ( Table 2 ) . Of the 145 total transferred proteins ( see section “Proteins transferred to females during mating” ) , 16 were isolated from only one of the sperm-enriched tissues ( SV: 5; testes: 11 ) and therefore were considered SV- or testes-derived Sfps , respectively , although we recognize that these could be sperm proteins . Additionally , 77 of the transferred proteins did not overlap with either sperm-enriched sample . Together , the 5 SV-derived Sfps , 11 testes-derived Sfps , and 77 of the 145 total transferred proteins that did not overlap with the sperm-enriched samples comprise a total of 93 proteins assigned with high-confidence as Ae . aegypti Sfps ( Table 1 ) . The Ae . aegypti Sfps identified represent a wide-range of predicted protein classes including proteolysis regulators , lectins , lipases , oxidoreductases , a cysteine-rich secretory protein ( CRISP ) and a venom allergen , and fall into a variety of Gene Ontology predicted molecular function classes ( Table 1; Fig . 1A ) . Unlike Sfps in Drosophila ( [31] , [36] , [50] ) and An . gambiae ( [33] , [51] ) , in which some groups of Sfps tend to be spatially clustered , we found little evidence for spatial clustering of the 93 Sfp genes in the Ae . aegypti genome , with one exception . Four Sfp genes ( AAEL006403; AAEL006414; AAEL006421; AAEL006429 ) clustered within a 23 kB region on supercontig 1 . 204 . One gene in this region ( AAEL006430 ) encodes a protein that was not detected in the present study and may either not be transferred or may be transferred at a level that was undetectable by our methods . The proteins encoded by all five of the genes in this region have predicted trypsin domains and their shared amino acid sequence identities range from 36 to 64% . As might be expected , the genes encoding the Sfps identified in this study tend to have highly male-biased expression when gene expression of whole males is compared to gene expression of whole females ( [52] ) . Half ( 26 of 51 ) of the genes for which microarray data are available have significantly higher expression ( at P≤0 . 001 ) in males than in non-blood-fed females ( O . Marinotti , pers . comm . ) , as compared to a genome average of 16% ( Chi-square test; X21 = 47 . 7; P<0 . 001; [52] ) . By comparison , 63% of the D . melanogaster Sfps identified by [36] have significantly higher expression ( at P≤0 . 01 ) in males than in females as compared to a genome average of 12% ( X21 = 345 . 9; P<0 . 001; [53] ) . Surprisingly , transcript levels of two Ae . aegypti Sfp-encoding genes ( encoding a predicted kinase , AAEL012359 , and a predicted zinc metalloprotease , AAEL012217 ) are significantly higher in non-blood-fed females than in males . From Ae . aegypti sperm-enriched tissue samples , we identified 101 sperm or sperm-associated proteins . Fifty-two were found among proteins transferred to females during mating ( Table 2 ) ; the remaining 49 proteins were not detected as transferred ( Table S6 ) . These latter 49 proteins included 7 that have homologs found in the D . melanogaster sperm proteome ( [40] ) . It is possible that some of these 49 Ae . aegypti proteins are components of somatic cells of the testis and/or SV tissues and play a role in spermatogenesis or sperm maintenance , whereas others could be sperm proteins whose abundance was too low for us to detect in the transferred samples or whose post-translational modifications rendered them unidentifiable by standard mass spectrometry . In the remainder of this section , we will only discuss the 52 proteins detected as transferred ( hereafter referred to as “putative sperm proteins” ) . Secretions of the reproductive glands of male Ae . aegypti have previously been shown to induce post-mating changes in female reproductive and feeding behavior ( [22] , [23] , [26] ) . In order to lay the groundwork for identifying specific proteins causing these effects , we report here 145 male-derived proteins that are transferred to females during mating in Ae . aegypti . We distinguished 93 seminal fluid proteins from 52 predicted sperm proteins , thus contributing to the growing understanding of insect ejaculate proteomes ( [33] , [35] , [36] , [40] , [57] , [88] , [93]–[95] ) . Twenty-two of these proteins were previously identified as male reproductive gland proteins ( [35] ) , and we demonstrate here that they are transferred to the female . The Sfps identified in this study suggest roles in protein activation/inactivation , ecdysteroidogenesis , and sperm utilization . Furthermore , our discovery that many predicted intracellular and membrane-bound proteins are transferred to females in the seminal fluid indicates that findings of such proteins in the seminal fluid of other species ( e . g . , [56] , [57] ) may also result from apocrine and/or holocrine secretion from the male reproductive glands ( [39] , [61] ) . The putative sperm proteins of Ae . aegypti show sequence conservation within Diptera and 17 of their D . melanogaster homologs are sperm proteins in that species ( [40] ) indicating potential conservation of sperm-related functions . Genes encoding Sfps showed higher male-biased expression than the genome average . On the one hand , this is not unexpected because Sfps are made in the male reproductive tract and are then transferred to females . On the other hand , it is not necessarily predicted a priori that Sfp-encoding genes will be male-biased in their expression , and the way we identified the proteins was without bias regarding their genes' expression . That 49% of the Ae . aegypti Sfp-encoding genes for which there are microarray data are not male-biased in expression will be important to bear in mind in designing future screens for Sfps . Together , our results provide a foundation for functional analyses to associate individual Sfps with their function in the mated female . Once functions are identified for individual proteins , investigations of the pathways by which they induce effects on male and female reproductive biology could identify novel targets for control of Ae . aegypti and dengue transmission . Of particular interest is to determine how specific Sfps modulate female behavior and physiology ( e . g . , egg production and blood feeding ) and to investigate candidate genes which increase the reproductive success of male Ae . aegypti that are to be used in genetic control strategies . | Dengue is a potentially lethal infection that impacts millions of humans annually . This disease is caused by viruses transmitted by infected female Aedes aegypti mosquitoes during blood feeding . No commercial vaccine or treatment is available for dengue infection . One way to break the disease transmission cycle is to develop new tools to reduce dengue vector populations . Seminal fluid proteins ( Sfps ) produced in the reproductive glands of male mosquitoes and transferred to females in the ejaculate during mating could be the target of such a tool . In related insects , Sfps modulate female reproduction and feeding patterns . Here we report 145 proteins that are transferred to females in the Ae . aegypti ejaculate . The proteins , which include Sfps and sperm proteins , fall into biochemical classes that suggest important potential roles in mated females . Of particular interest are proteins that could play roles in fertility and hormonal activity ( including pathways involved in egg development and utilization of the blood meal ) . Our results lay important groundwork for new control strategies by identifying candidate proteins that may alter the reproductive biology or blood-feeding patterns of female Ae . aegypti and ultimately reduce the global burden of dengue . | [
"Abstract",
"Introduction",
"Results",
"and",
"Discussion"
] | [
"biochemistry",
"evolutionary",
"biology/sexual",
"behavior",
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"evolutionary",
"biology/animal",
"behavior",
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] | 2011 | Towards a Semen Proteome of the Dengue Vector Mosquito: Protein
Identification and Potential Functions |
The establishment of polarity is a critical process in pathogenic fungi , mediating infection-related morphogenesis and host tissue invasion . Here , we report the identification of TPC1 ( Transcription factor for Polarity Control 1 ) , which regulates invasive polarized growth in the rice blast fungus Magnaporthe oryzae . TPC1 encodes a putative transcription factor of the fungal Zn ( II ) 2Cys6 family , exclusive to filamentous fungi . Tpc1-deficient mutants show severe defects in conidiogenesis , infection-associated autophagy , glycogen and lipid metabolism , and plant tissue colonisation . By tracking actin-binding proteins , septin-5 and autophagosome components , we show that Tpc1 regulates cytoskeletal dynamics and infection-associated autophagy during appressorium-mediated plant penetration . We found that Tpc1 interacts with Mst12 and modulates its DNA-binding activity , while Tpc1 nuclear localisation also depends on the MAP kinase Pmk1 , consistent with the involvement of Tpc1 in this signalling pathway , which is critical for appressorium development . Importantly , Tpc1 directly regulates NOXD expression , the p22phox subunit of the fungal NADPH oxidase complex via an interaction with Mst12 . Tpc1 therefore controls spatial and temporal regulation of cortical F-actin through regulation of the NADPH oxidase complex during appressorium re-polarisation . Consequently , Tpc1 is a core developmental regulator in filamentous fungi , linking the regulated synthesis of reactive oxygen species and the Pmk1 pathway , with polarity control during host invasion .
Rice blast disease is one of the most serious diseases of cultivated rice worldwide and is caused by the filamentous , ascomycete fungus Magnaporthe oryzae[1 , 2] . The disease is initiated when a conidium lands on the rice leaf surface . Here it germinates to produce a single germ tube that differentiates at its tip to develop a specialised infection structure called an appressorium[3] . During the initial stages of appressorium formation , a septum defines the developing appressorium from the rest of the germ tube following a single mitotic division in the germ tube[4] . When the appressorium matures , the three conidial cells and germ tube collapse due to infection-associated autophagy and are no longer viable after 24h[4] . Subsequently , a penetration peg emerges from the base of the appressorium and ruptures the leaf cuticle . A toroidal filamentous actin network forms at the base of the appressorium pore , scaffolded by septin GTPases[5] . Assembly of the four core septin GTPases is regulated by the Nox2 NADPH oxidase complex , which is required for re-modelling of the F-actin cytoskeleton and assembling the exocyst at the appressorium pore [6 , 7 , 8] . F-actin ring formation is necessary for penetration peg emergence and re-establishment of polarized growth at the point of plant penetration . After penetration , the fungal peg grows as a narrow , short primary invasive hypha[9] , before differentiating into bulbous invasive hyphae during colonisation of the first invaded host cell[10] . Disease symptoms appear between 72h and 96h after initial infection and coalesce into large spreading necrotic lesions from which the fungus sporulates . M . oryzae has also the capacity to penetrate roots by means of hyphopodia and can colonize root tissue and spread systemically throughout the plant under laboratory conditions [11 , 12] . In this study , we report the identification of a novel Zn ( II ) 2Cys6 transcriptional regulator involved in the early stages of plant infection by M . oryzae . The Zn ( II ) 2Cys6 binuclear cluster domain ( IPR001138 , PF00172 ) is exclusively found in the fungal kingdom[13 , 14] . The six cysteine residues bind two zinc atoms , which coordinate folding of the domain involved in DNA-binding . Most Zn ( II ) 2Cys6 proteins have been studied in Saccharomyces cerevisiae and Aspergillus species[13 , 15 , 16] . Typically , the Zn ( II ) 2Cys6 proteins are pathway-specific activators under the control of major regulators[15 , 16 , 17 , 18] . The regulator of galactose catabolism in yeast , Gal4p[19] , and the regulators of acetate assimilation FacB[20] and the aflatoxin cluster AflR[21] in A . nidulans , are among the best studied examples . Several Zn ( II ) 2Cys6 transcriptional regulators have been studied in the rice blast fungus ( S1 Table ) . Of the 175 members of the Zn ( II ) 2Cys6 binuclear cluster family present in M . oryzae ( S2 Table ) , only nine of them ( MoCod1 , MoCod2 , Pig1 , Tra1 , Tdg3 , Xlr1 , Ara1 , Far1 and Far2 ) have been examined in any detail[22 , 23 , 24 , 25 , 26 , 27] ( S1 Table ) . A high-throughput gene knockout approach of 104 Zn ( II ) 2Cys6 proteins in M . oryzae revealed large variation in their biological functions , and reported seven additional Zn ( II ) 2Cys6 proteins to be required for plant infection , including Gpf1 and Cln2[28] . However , despite this information , the mechanistic insights into how the Zn ( II ) 2Cys6 proteins govern M . oryzae cellular processes are largely unknown . In this study , we characterize a novel mutant of M . oryzae that shows defects in pathogenicity and vegetative growth following its selection from a M . oryzae T-DNA insertional library . The T-DNA insertion is located within a gene ( MGG_01285 ) encoding a Zn ( II ) 2Cys6 binuclear cluster protein , which we name TPC1 . This gene was not included in the large-scale gene knockout analysis of 104 Zn ( II ) 2Cys6 proteins [28] , although a global gene expression analysis of transcription factors revealed that TPC1 is overexpressed during development ( conidiation , germination and appressorium formation ) , oxidative stress ( methyl viologen treatment ) and carbon starvation [29] . Here , we reveal the involvement of this transcriptional regulator in polarized growth , cell patterning and virulence in M . oryzae . Among the genes regulated by Tpc1 we found NOXD , an important component of the fungal NADPH complex . Significantly , Tpc1 interacts with Mst12 and mis-localises in the Δpmk1 background , linking Tpc1 to this pathogenicity-associated MAPK signalling pathway . We provide mechanistic insight into the role of Tpc1 , a key regulator of polarity in M . oryzae that controls growth , autophagy and septin-mediated reorientation of the F-actin cytoskeleton to facilitate plant colonisation .
In order to identify novel infection-related genes we screened a total of 300 T-DNA transformants for their ability to infect rice roots using a M . oryzae insertional library[30] . The M1422 mutant developed very restricted disease lesions on roots and was selected for further characterization ( Fig 1A ) . On leaves , M1422 produced only a small number of resistant-type lesions ( Fig 1B and S1A Fig ) . Colonies of M1422 were also compact and reduced in size , when compared with the wild-type ( Fig 1C ) . The insertion site of the T-DNA within M1422 was located 0 . 9 kb downstream of the start codon of locus MGG_01285 in the M . oryzae genome ( S1B Fig ) . This gene encodes a putative transcription factor that belongs to a Zn ( II ) 2Cys6 binuclear cluster family . We named this gene Transcription factor for Polarity Control 1 ( TPC1 ) . The predicted coding region of TPC1 is ~2 . 6 kb long and encodes 839 amino acids ( http://fungi . ensembl . org/index . html; MG8 ) . The TPC1 predicted amino acid sequence includes a putative nuclear localisation signal ( NLS ) and one Zn ( II ) 2Cys6 binuclear cluster DNA binding domain ( S1B Fig ) . A single T-DNA insertion in M1422 genome was detected by Southern blot hybridisation using the hygromycin phosphotransferase gene as a probe ( S1C Fig ) . We also generated a second mutant in TPC1 by targeted gene replacement ( S2A and S2B Fig ) . We complemented both M1422 and Δtpc1 with a C-terminal TPC1:GFP gene fusion under control of its native promoter . The complemented mutants recovered normal mycelial growth , colonial morphology and full virulence on rice ( S1D , S1E and S2C Figs ) . We conclude that mutants M1422 and Δtpc1 are impaired in TPC1 function . Two striking characteristics of M1422 and Δtpc1 were their impaired hyphal growth and colony morphology ( Fig 1C , S1E and S2C Figs ) . Vegetative growth of Tpc1-lacking strains was severely compromised in both complete ( CM ) and minimal ( MM ) medium ( p < 0 . 01 ) , and showed compact colonies and non-invasive colony morphology ( S1E , S1F and S2D Figs ) . In Neurospora crassa , a class of mutants with polarity defects also exhibited this type of colony morphology[31] . To analyse integrity of the cell wall , development of M1422 was evaluated in the presence of the anionic dyes , Congo Red ( CR ) and Calcofluor White ( CFW ) , which interfere with fungal cell wall assembly by binding to β-1 , 4-glucan and chitin , respectively [32] . Additive growth defects were observed on M1422 development in the presence of CR but not in CFW ( Fig 1D ) . In addition , mycelial growth was affected by NaCl-induced hyperosmotic stress ( Fig 1E ) . High concentrations of NaCl ( 0 . 6M - 1 . 0M ) changed the growth ratio in colonial size between wild-type and M1422 , leading to an increase in the relative growth rate of M1422 compared to wild-type . Therefore , the lack of Tpc1 affected plant virulence , vegetative growth , colony morphology and hyperosmotic stress adaptation . We observed that M1422 and Δtpc1 mutants sporulated poorly compared to wild-type ( Fig 2A and S2E Fig ) . In addition , M1422 asexual spores showed defects in septation ( numbers of cell per conidium ) and conidial morphology ( Fig 2B ) . Wild-type conidia were uniformly pyriform , three-celled spores . By contrast , in M1422 , although the majority of conidia were three-celled ( 80% ) , a significant percentage of two-celled conidia ( 17% ) , single-celled ( 2% ) and four-celled conidia ( 1% ) were observed . Up to 26% of spores showed abnormal morphology in contrast to wild-type where less than 4% were misshapen ( n> 300 ) . We also found that appressorium development was affected in M1422 ( Fig 2C ) . On hydrophobic coverslips , wild-type conidia germinated to form one germ tube that emerged from the apical cell and formed an appressorium within 4h-8h ( Fig 2C and 2D ) . In M1422 , 40% of conidia germinated from two cells . This percentage increased to 50%-60% with extended incubation time ( 4h-8h ) . Formation of two appressoria was rarely observed in wild-type conidia ( Fig 2E ) . We conclude that M1422 is impaired in the normal spatial patterning of appressorium development . The impairment of appressorium-mediated plant infection by TPC1 mutants suggested that it might play a critical role in penetration peg development[33] . Appressorium function is known to depend on autophagic cell death of conidia , prior to appressorium maturation[4 , 34] . Therefore , we investigated whether infection-associated autophagy proceeded normally and if conidia underwent autophagic cell death . A GFP:MoATG8 construct was introduced into M1422 to determine the spatial and temporal dynamics of autophagy ( Fig 3A ) . MoATG8 encodes an autophagic , ubiquitin-like protein involved in autophagosome function and has been shown to be a reliable marker for autophagy[4 , 34] . Compared to the wild-type Guy11 ( 33 . 5±4 . 4 ) , GFP:MoATG8-labeled autophagosomes accumulated in M1422 conidia in significantly smaller numbers ( 21 . 6±5 . 5; p<0 . 01 ) . In both strains , the number of conidial autophagosomes decreased during germination , appressorium maturation and at the onset of spore cell death and was significantly lower in M1422 conidia and germ tubes ( Fig 3A ) . However , autophagosome numbers increased significantly during appressorium maturation ( 8h; 16 . 1±4 . 9 ) and dropped considerably after conidial death ( 24h; 5 . 0±1 . 8 ) in wild-type , whereas autophagosome number remained relatively constant in M1422 during appressorium maturation ( 8 . 4±4 . 1 ) and even after conidial cell death ( 7 . 5±3 . 3 ) . Appressorium development is accompanied by rapid degradation of glycogen from conidia during germination and from appressoria during turgor generation[35 , 36] . We therefore determined glycogen levels during appressorium development using potassium iodide ( KI ) . Comparative analysis of KI staining between wild-type Guy11 and M1422 showed differences during the onset and later stages of conidial cell death ( 8h and 24h; Fig 3B ) . In Guy11 glycogen depletion was observed ( no staining ) within both conidial cells and appressoria during development . In the M1422 mutant , conidial cells were also depleted of glycogen although the appressorium still contained high levels of glycogen ( 95% ) during maturation . We also looked at lipid metabolism , which is an additional driver of turgor generation in M . oryzae . The triacylglycerol lipase degrades lipid bodies that move to the appressorium during development[24 , 37] . Accordingly , we followed lipid body distribution during appressorium maturation in Δtpc1 using Nile red ( Fig 3C ) . We consistently visualised delayed degradation of lipid bodies in conidia and germ tubes in Δtpc1 , which were evident at 9h and 12h after germination on coverslips . Using a cytorrhysis assay , in which hyperosmotic concentrations of a solute are applied to collapse appressoria , we estimated the internal solute concentration and turgor of appressoria of the two strains . We observed that Δtpc1 appressoria clearly collapsed at higher rates than the WT at 1M concentration of glycerol ( Fig 3D ) . This suggests decreased in turgor within Δtpc1 appressoria , consistent with the observed delayed degradation of glycogen and lipid bodies . When considered together , these observations point that autophagy , and glycogen/lipid metabolisms are delayed during appressorium development in Tpc1-lacking strains . Following maturation of the appressorium , a penetration peg emerges from the appressorial pore to penetrate the plant cuticle and successfully colonise the plant host . To assess whether repolarization was impaired in the M1422 mutant , a penetration assay was performed on onion epidermis and rice leaf sheath ( Fig 4A ) . After 24h , 91% of wild-type conidia formed an appressorium effectively , penetrated and invaded onion epidermal cells . The majority of M1422 conidia ( 60% ) germinated and produced an appressorium , but failed to penetrate and invade onion cells . Only 40% of M1422 appressoria formed a penetration peg , but were not able to invade the onion epidermal cells and spread away from the point of penetration . Similarly , on rice leaf sheath preparations 81% of wild-type conidia penetrated successfully compared to 21% of Δtpc1 mutant spores , which managed to develop a penetration peg but hardly ever spread to adjacent cells . To examine how formation of the germ tube and penetration peg was compromised , we investigated cellular organization of the F-actin cytoskeleton[38] , using the actin-binding protein fimbrin tagged with GFP ( S3 Fig ) . Once wild-type conidia attached to the surface , fimbrin:GFP spots were observed at the periphery of the germinating cells ( 0h ) . However , conidia harvested from M1422 instead localised F-actin randomly at the periphery of the three cells of conidia and not preferentially in the germinating cell ( white arrowheads , S3 Fig ) . The most clear mis-localisation defects were observed in mutant appressoria . Fimbrin was localised in discrete puncta at the periphery of Guy11 appressoria , but in contrast was dispersed within appressoria of the mutant ( 6h ) . Furthermore , the F-actin network was more diffuse and several pores were observed in M1422 mature appressoria ( white arrowheads , 24h ) . These results suggest that re-polarization of the appressorium is adversely affected in the M1422 mutant . To confirm this , we also tracked gelsolin:GFP and Sep5:GFP in Δtpc1 mutant . The use of gelsolin:GFP and Sep5:GFP to follow actin reorganization has helped to understand cytoskeleton dynamics during infection-related development[6] . The disorganisation of the appressorial cytoskeleton and actin ring was evident in Δtpc1 . Sep5 was mis-localised in all mutant appressoria and only 26% of mutant appressoria formed an intact actin ring with a central pore ( Fig 4B ) . Consequently , TPC1 is required for the correct penetration peg emergence in M . oryzae . The Tpc1:GFP fusion protein co-localised with histone H1:RFP in nuclei of vegetative hyphae , attached conidia ( 30 min ) , and germinated conidia ( Fig 5A ) . Moreover , whenever Tpc1:GFP was observed in nuclei , GFP fluorescence was never observed in the cytoplasm or other organelles within conidia . The results are consistent with TPC1 encoding a transcription factor that acts within the nucleus during the initial stages of spore germination and appressorium development , and correlate with the observed overexpression of TPC1 in these fungal structures [29] . To investigate whether TPC1 is associated with specific or multiple regulatory networks , TPC1:GFP localisation was observed in conidia of different mutant backgrounds ( Fig 5B ) . In the Δpmk1 MAPK mutant[39] , Tpc1:GFP was observed within the cytoplasm but not in nuclei . By contrast , strong GFP fluorescence was visualised in conidial nuclei of the autophagy-defective Δatg1 and Δatg8 mutants , compared to the fluorescence observed in M1422 complemented with TPC1:GFP or Guy11 expressing TPC1:GFP . These results suggest that Tpc1 activity is associated with the Pmk1 MAP kinase signalling pathway , which regulates appressorium formation[39] , and the control of autophagy[34] . We further analysed the link with between Tpc1 and the Pmk1 pathway by looking at the ability of Tpc1 to interact with components of this pathway in a yeast two-hybrid system . Strikingly , we observed that Tpc1 interacted with Mst12 , a transcription factor that functions downstream of Pmk1[40] , although Tpc1 did not interact with Pmk1 itself ( Fig 5C ) . The mis-localisation of Tpc1 in Δpmk1 and its interaction with Mst12 strongly support Tpc1 involvement in this pathogenicity-associated MAPK signalling cascade . We investigated the phylogenetic relationship of Tpc1 to other putative Magnaporthe Zn ( II ) 2Cys6 proteins and the closest orthologues of Tpc1 in other fungal species ( S4 and S5 Figs ) . We observed that the six cysteine residues of the DNA-binding domain ( DBD ) in the Zn ( II ) 2Cys6 proteins were ordered in a conserved pattern , CX2CX6CX5-12CX2CX6-8C ( S4A and S4B Fig ) . In M . oryzae , the Zn ( II ) 2Cys6 binuclear cluster family is diverse and composed of 175 members ( S2 Table ) . The closest orthologues of Tpc1 ( MGG_01285 ) were identified using BLASTP and used to construct a phylogenetic tree ( S4C and S5 Figs ) . Tpc1 clustered in a group with sequences from other Sordariomycetes , such as Fusarium graminearum , N . crassa , Chaetomium globosum and Podospora anserina . Based on this tree , Tpc1 is a single copy gene and has not been subject to paralogous duplications . Our phylogenetic analysis reflected the diversification of the Zn ( II ) 2Cys6-containing proteins in the fungal kingdom . Interestingly , we did not find putative homologues of Tpc1 in S . cerevisiae or Schizosaccharomyces pombe using a BLASTP search . In F . graminearum , it is remarkable that only 16% ( 46/296 ) of the mutants lacking Zn ( II ) 2Cys6 transcription factors showed a phenotype , compared to the 42% ( 30/72 ) of N . crassa mutants or the 59% ( 61/104 ) of M . oryzae mutants[28 , 41 , 42] . Among the F . graminearum mutants with clear phenotypes is found the orthologue of M . oryzae TPC1 ( FgTPC1 = FGSG_08769; GzZC108 ) , which is required for plant infection , perithecia formation , synthesis of mycotoxins ( ZEA , zearalenone; and DON , deoxynivalenol ) and growth[41] . Similar to M . oryzae ( Fig 1E and S2F Fig ) , the Δfgtpc1 mutant is more resistant than wild-type to hyperosmotic and oxidative stresses . We further investigated functional conservation of Tpc1 in the saprotrophic filamentous fungus N . crassa , and characterized a N . crassa NcTPC1 deletion mutant ( Δnctpc1; NCU05996 ) , obtained from the Fungal Genetic Stock Centre[43] . The analysis of the alignment of M . oryzae and N . crassa Tpc1 proteins showed that they share 67% amino acid identity ( S6A Fig ) . Strikingly , the Δnctpc1 mutant was severely reduced in vegetative growth compared to an isogenic wild-type strain ( p <0 . 01 ) ( S6B Fig ) , and its vegetative hyphae also formed compacted colonies . In addition , we observed that the Δnctpc1 mutant of N . crassa was less severely affected when exposed to increasing osmotic stress using NaCl , compared with the N . crassa wild-type strain ( p <0 . 01 ) ( S6C Fig ) . Similar tolerance effect was also found in F . graminearum Tpc1[41] and in M . oryzae Tpc1 ( Fig 1E ) . Consequently , N . crassa Tpc1 also plays a significant role in growth and development of the fungus and its responses to abiotic stress . Tpc1 contains a Zn ( II ) 2Cys6 binuclear cluster DNA binding domain , which is found only in fungal proteins considered bonafide transcription regulators[13 , 14] . We carried out a comparative transcriptome analysis using the wild-type strain and the TPC1 deletion mutant to identify the biological processes and genes regulated by Tpc1 . For this experiment , RNA was extracted from fungal material grown on cellophane on top of CM agar plates ( S2D Fig ) . We considered it to be an optimal condition since fungal hypha is able to penetrate the cellophane , i . e . a change in polar growth occurs under these conditions , and allow us to obtain enough amount of RNA for subsequent microarray analysis . We identified 215 down-regulated genes and 185 genes to be up-regulated with at least a two-fold change in expression level in the Δtpc1 mutant ( S3 Table ) . We classified all the genes that were up- and down-regulated into four functional groups according to potential roles in signalling ( 13 genes ) , cell wall biosynthesis or modulation of plant response ( secreted proteins; 140 genes ) , metabolism ( 127 genes ) and other functions ( 54 genes ) . Sixty-six genes encoded proteins that lacked any known domain . Remarkably , two gene ontology ( GO ) terms were found significantly enriched among these differentially expressed genes , the oxidation-reduction process ( GO:0055114; 57 genes; p<0 . 001 ) and the oxidoreductase activity ( GO:0016491; 58 genes; p<0 . 001 ) . Within the signalling functional group , two down-regulated genes encoded phosphatidyl ethanolamine-binding proteins ( PEBP ) that have been shown to regulate protein kinase A ( PKA ) and mitogen-activated protein kinase ( MAPK ) pathways[44 , 45] . Amongst the up-regulated genes , eight of them encoded transcriptional regulators , which suggests a link between the gene networks controlled by these transcriptional regulators and Tpc1 . The largest group of mis-regulated genes comprised 140 genes coding for secreted or cell wall-related proteins . Within this group , more than half of the members ( 74 genes ) had no matches in databases . However , twenty-four genes were potentially involved in cell wall remodeling , and encompassed different types of glycosyl hydrolases ( GH10 , GH18 , GH32 , GH43 , GH61 and GH81 ) , seventeen proteases and two secreted phospholipases A2 . Three Mas3/Gas1 paralogues and several effector proteins such as a Bas2-like , Bas113 and avrPi54 were also found[46 , 47 , 48 , 49] . The up-down regulation of two CFEM G-protein coupled receptors[50] , including PTH11[51] , suggested an alteration in the ability of the Δtpc1 mutant to perceive external signals . The second largest group of genes with altered expression levels encoded proteins related with primary and secondary metabolism ( 127 genes ) . We found a significant number of them participating in oxidation-reduction processes ( 46% ) and transport ( 9% ) . Alteration in nitrogen and glycerol metabolism was evidenced by the expression changes of four NmrA-like regulatory proteins[52] , enzymes involved in amino acid biosynthesis , a glycerol kinase and the glycerol dehydrogenase Gcy1 , an enzyme also associated with redox regulation in yeast[53] . Down-regulation of an α-glucosidase supported the glycogen degradation delay of Tpc1-lacking strains . The last functional group included 54 genes encoding proteins that carry a wide range of biochemical roles . The reduced expression of the autophagy gene ATG22 and the up-regulation of three small chaperones Hsp20-like suggested the unbalanced signals for survival and cell death existent in Δtpc1[54] . Microtubule-dependent vesicle trafficking and cell cycle were also affected in the mutant as inferred from the misregulation of two dynamins , one kinesin light chain , one Marvel protein , two cyclins and the Cdc26 subunit . Genes involved in silencing pathways , spliceosomal snRNP assembly , tRNA processing , RNA-mediated heterochromatin silencing and translational arrest were also misregulated in Δtpc1 , highlighting alterations in other cellular processes that regulate gene expression . The majority of the Zn ( II ) 2Cys6 binuclear cluster proteins are transcriptional activators and only few of them have been shown to act as repressors[14] . To identify novel pathogenicity genes we focused on genes that could play a role in TPC1-associated defects . Five out of the 133 down-regulated genes were selected for gene replacement ( S3 Table; S7 Fig ) , including the conidiation-related gene CON6[55] , a glycosyl transferase 18 gene ( GH18 ) that undergoes a 50-fold increased expression in planta[48] , and the two signaling-associated PEBP genes ( S7 Fig ) . The PRO41/HAM-6 gene , which is required for hyphal fusion in Neurospora crassa and sexual development in Sordaria macrospora was also selected for the analysis[56 , 57] . We confirmed by RT-PCR that the five genes were down-regulated in the Δtpc1 mutant ( S8A Fig ) . Among the six deletion mutants generated , only Δpro41/Δham-6 displayed a severe pathogenicity-deficient phenotype ( S7 Fig ) . Despite the links found between conidiogenesis and pathogenicity in M . oryzae[58 , 59 , 60] , the Δcon6 mutant behaved like wild-type in planta . Similarly , Δgh18 , Δpebp1 , Δpebp2 , and the double mutant Δpebp1Δpebp2 did not show any pathogenicity-associated defects possibly due to redundancy in related gene functions . Consequently , we selected Δpro41/Δham-6 mutants for further characterization . The open reading frame of M . oryzae PRO41 was initially annotated in the EnsemblFungi database as HAM-6 , a N . crassa gene required for cell fusion[61] . However , the orthologue of this protein was first characterized in S . macrospora and named Pro41[57 , 62] . Pro41 is a novel ER membrane protein required for fruiting body maturation in S . macrospora . Later , Pro41 was found to be the functional orthologue of the p22phox subunit of the NADPH oxidase complex in both Podospora anserina and Botrytis cinerea[63 , 64] . Therefore , we renamed the Pro41/Ham-6 protein NoxD ( S8B Fig ) . We looked at the growth of the M . oryzae ΔnoxD mutant in different media and stress conditions ( Fig 6A and S8C Fig ) . ΔnoxD grew slightly faster than the wild-type on CM and MM , under salt stress ( 0 . 2 M LiCl , 0 . 4 M NaCl ) and in Congo Red ( CR ) . However , we did not observe differences in growth under carbon starvation , calcofluor white ( CFW ) or basic conditions ( pH 9 . 5 ) . Increased resistance to CFW was previously observed for M . oryzae Δnox1 but not for Δnox2[65] , suggesting NoxD and Nox2 fulfill similar roles during cell wall biogenesis . Growth of M . oryzae ΔnoxD and Δnox1Δnox2 mutants in 1mM methyl viologen , 1mM H2O2 and 5mM H2O2 was similar or improved when compared to wild-type ( S8D Fig ) . Thus , the lack of NoxD did not affect fungal growth under oxidative stressors in contrast to the growth defects displayed by B . cinerea NADPH oxidase mutants[64] . The infection ability of ΔnoxD was severely affected on leaves and roots ( Fig 6B and S7 Fig ) , in accordance with the strong penetration defects displayed by Δnox1 and Δnox2[65] . The penetration defect displayed by ΔnoxD was confirmed using rice leaf sheaths ( 81% in the wild-type versus 19% in the mutant ) and onion epidermis penetration assays ( 74% in the wild-type versus 22% in the mutant; Fig 6C ) . Subsequently , we crossed the ΔnoxD mutant with the rice isolate TH3 , a M . oryzae strain of opposite mating type ( Fig 6D ) . The inability to produce perithecia indicated that NoxD is required for sexual reproduction in M . oryzae . To define whether superoxide production was impaired in the ΔnoxD mutant , we used nitroblue tetrazolium ( NBT ) , which forms a dark-blue water-insoluble formazan precipitate upon reduction by superoxide radicals[65 , 66] . In the ΔnoxD mutant , we observed an increase in superoxide production at hyphal tips and a significant reduction in appressoria based on mean pixel intensity measurements ( p<0 . 01 ) ( Fig 7A ) . This was previously described for Δnox1Δnox2 mutants[65] , and supports the existence of alternative routes for cellular ROS generation in M . oryzae during hyphal development . Since Δtpc1 was affected in oxidation-reduction processes , we also included Δtpc1 in this analysis . Increased superoxide production was found in Δtpc1 hyphal tips but to a lesser extent than nox mutants , while in appressoria Δtpc1 showed the highest superoxide levels among the strains analyzed , indicating that the lack of Tpc1 affects superoxide production pathways in M . oryzae . A yeast two-hybrid assay was used to identify putative NoxD interactors . We found that M . oryzae NoxD interacts with the Nox1 NADPH oxidase subunit ( Fig 7B ) but not with Nox2 or NoxR , supporting previous work in B . cinerea and P . anserina[63 , 64] . To localize NoxD we generated C-terminal mRFP ( cherry variant ) and GFP translational fusions under the control of strong or native promoters , respectively . Both constructs fully complemented ΔnoxD plant infection defects ( Fig 6B ) , which indicated that the C-terminal tag does not affect NoxD function , although expression of NoxD:mRFP was clearly stronger . M . oryzae NoxD was mainly observed in subapical vesicles and the plasma membrane of appressoria and conidia ( Fig 7C ) . Co-localization of NoxD:mRFP with GFP containing the ER retention signal KDEL showed that the vesicles are closely associated with the ER , overlapping with some of them ( Fig 7 , white arrowheads ) . The subapical vesicles observed near plasma membranes and septa in M . oryzae structures correlated with the localisation of NoxD in P . anserina [63] . In P . anserina , these vesicles co-localised with the GFP:Idi7 reporter protein , suggesting that they originate from the ER and travel towards the vacuolar system [63] . The Nox2-NoxR complex is essential for septin-mediated cytoskeletal reorientation , whereas Nox1 is dispensable although may have important roles to play in maintenance and elongation of the penetration peg[6] . To test if NoxD was also involved in this process , we expressed the acting-binding protein gelsolin:GFP and Sep5:GFP in ΔnoxD . In the wild-type , both a septin and gelsolin ring was present at the appressorium pore[6] ( Fig 7D ) . In the ΔnoxD mutant , however , Sep5:GFP formed a disorganized mass in the infection cell as previously reported for Δnox2 and ΔnoxR expressing Sep5:GFP[6] . Gelsolin:GFP rings in ΔnoxD also possessed distorted pores . Considering that gelsolin colocalizes with F-actin at the appressorial pore[6] , the altered fluorescence pattern of gelsolin:GFP revealed that the toroidal F-actin ring was disorganized ( Fig 7D ) . Previous reports showed that Sep5:GFP and gelsolin:GFP patterns in the Δnox1 mutant displayed normal conformation[6] . NoxD and Nox1 therefore appear to play alternative roles in cytoskeletal re-modeling in appressoria of M . oryzae . The down-regulation of NOXD in Δtpc1 suggested that this gene may be directly regulated by Tpc1 . To investigate this idea , we carried out chromatin immunoprecipitation ( ChIP ) followed by qPCR ( Fig 8A and 8B ) . We observed that the promoter region of NOXD comprising the NOXD1 , NOXD2 and NOXD3 fragments immunoprecipitated with Tpc1:GFP , which indicated that NOXD expression is regulated in vivo by this transcription factor . In addition , we performed electrophoretic mobility shift assays ( EMSA ) with M . oryzae Tpc1 and Mst12 since both proteins can interact in yeast two-hybrid assays ( Fig 5C ) . We found that Mst12 strongly recognised the probe 1 located between -1120 and -643 upstream of the start codon of the NOXD gene ( Fig 8C ) . Mst12 also recognized probes 2 and 3 , but less strongly . Mst12 bound to the probes produced multiple bands , possibly due to the presence of several protein molecules on the biotinylated DNA ( Fig 8D ) . Intriguingly , Tpc1 itself was not capable of recognizing any of the three probes under the conditions tested ( Fig 8C ) . However , the addition of Tpc1 to Mst12 increased its DNA-binding capacity ( Fig 8E ) , which is consistent with both , the ability of these proteins to interact , and with Tpc1 as modulator of Mst12 DNA-binding affinity . Increasing amounts of Tpc1 did not alter significantly Mst12affinity . Importantly , the promoter regions tested using these in vitro DNA-binding assays correlated perfectly with the enriched fragments obtained in the ChIP analysis , which supports that Mst12 and Tpc1 are part of a complex that coordinately regulate NoxD expression . To further confirm these results , we checked NOXD expression levels in the Δmst12 mutant and corroborated that they were reduced ( Fig 8F ) . We also observed that MST12 and TPC1 genes were overexpressed when the corresponding partner was not present in the fungal cell ( Fig 8G ) . We conclude that Tpc1 regulates NoxD expression through its interaction with Mst12 and confirm the link between Tpc1 and the participation of the Pmk1 pathway in the regulation of NoxD expression .
To cause disease in rice , M . oryzae forms a specialised cell called an appressorium , the development of which involves transitions from polarised to isotropic cellular growth , followed by rapid turgor-driven polarisation to penetrate the leaf surface . Understanding how these cellular transitions occur is critical to controlling the disease at an early stage , prior to entering the plant . In this study , we have identified a transcription factor , Tpc1 that plays a key role in regulating plant infection , due to its role in polarity control . We have also identified one putative mechanism by which it acts , via the regulated synthesis of reactive oxygen species and control of the NADPH oxidase complex , which regulates septin assembly and F-actin re-modelling at the base of the appressorium . Furthermore , we have found that Tpc1 directly participates in the Pmk1 pathway and is required for infection-associated autophagy , which are both essential pre-requisites for appressorium formation and function . We observed that the TPC1 mutants formed compact colonies , which resembled the colony morphology shared by a class of mutants with polarity defects in N . crassa[31] . Conidial germination , and growth of vegetative hyphae were severely impaired in the two mutants lacking functional Tpc1 , supporting defects in sustained tip elongation and establishment of polarity in apically-growing hyphae . Autophagy plays a major role in supplying amino acids , fatty acids , and glucose to maintain cellular functions during stress and starvation[67] . The absence of Tpc1 function altered the onset of infection-associated autophagy which occurs during appressorium development[68] . Conidial cell death is necessary to initiate appressorium penetration and it is regulated by the Pmk1 pathway [33] . Although M1422 conidia appeared able to undergo conidial cell death , the cellular localization of autophagosomes and glycogen/lipid deposits suggested that the process was delayed . Consistent with this observation , Tpc1:GFP was also highly expressed in Δatg1 and Δatg8 mutants impaired in autophagy , suggesting that the expression of TPC1 is de-repressed as a consequence of the inability to carry out autophagy and may therefore be an upstream positive regulator of infection-associated autophagy during appressorium maturation ( Fig 9 ) . Autophagic cell death is linked with appressorium function and penetration in M . oryzae[4] , and mutants lacking Tpc1 are also penetration defective . The formation of a penetration peg at the base of the appressorial pore is a cellular process intrinsically linked to polar growth[69 , 70] . The F-actin cytoskeleton plays a crucial role during germ tube re-polarisation and penetration peg emergence . We therefore investigated cytoskeletal dynamics during appressorium maturation in the mutant background . The network of F-actin observed with fimbrin:GFP in mature wild-type appressoria ( 8h-24h ) delineated the appressorial pore , which was strikingly absent in M1422 . This result together with the mis-localization of Sep5:GFP and gelsolin:GFP in Δtpc1 indicated that the F-actin network is disturbed in Tpc1-lacking strains . The microarray analysis helped us to identify gene expression changes due to the lack of Tpc1 , which correlated with the observed involvement of this protein in glycogen metabolism , autophagy and polar growth . Oxidation-reduction processes were also significantly affected in Δtpc1 including superoxide production pathways , likely due in part to the down-regulation of the fungal homologue of the p22phox NADPH subunit , the NOXD gene[63 , 64] . The M . oryzae ΔnoxD mutant was unable to infect rice leaves and roots . We established an interaction of NoxD with Nox1 , but not with NoxR or Nox2 , and confirmed the requirement of NoxD for superoxide generation and sexual reproduction in M . oryzae , consistent with NoxD functions in B . cinerea and P . anserina[63 , 64] . We also identified ΔnoxD defects in repolarization of the F-actin cytoskeleton during infection-related development , supporting the previous role described for the M . oryzae NADPH oxidase complex[6] . Remarkably , the disorganization pattern of gelsolin:GFP and Sep5:GFP in ΔnoxD was similar to that observed in Δnox2 and ΔnoxR mutants , whereas Δnox1 formed nearly intact ring shapes[6] . This result suggests that Nox1 and NoxD participate differently in septin-mediated cytoskeleton organization despite their interaction , and strengthens the view of the fungal NADPH oxidase as a dynamic complex[71] . It seems likely that a Nox2-dependent process initiates septin ring formation , while Nox1 is necessary for maintenance of this conformation ( Fig 9 ) . NoxD may therefore be associated at a relatively early stage in recruiting Nox1 to the appressorium pore , perhaps explaining why its absence results in a more severe phenotype with respect to actin and septin assembly at the pore . The role of NoxD , however , highlights that the Nox1 and Nox2 complexes are both necessary for penetration peg elaboration and extensive polar growth . It is worth noting that the tetraspanin PLS1 deletion mutants exhibit the same phenotype as Δnox2 in M . oryzae and P . anserina[6 , 72] , suggesting that Pls1 may act as the missing link between Nox2 and NoxD subunits of the fungal NADPH oxidase complex ( Fig 9 ) . The recent discovery in B . cinerea of the RasGAP protein homologue IQGAP and its interaction with NoxD also points to IQGAP as a scaffold protein of the fungal NADPH complex[73] . In mammals , Nox complexes can act upstream[74] or downstream [75] of MAPK signaling pathways . IQGAP also interacts with different modules of MAPK- and Ca-dependent signalling cascades[73] , pointing the link between Nox complexes and signalling cascades . Interestingly , the B . cinerea ΔnoxD mutant showed growth defects in the presence of oxidative stressors in contrast to the wild-type growth exhibited by the M . oryzae ΔnoxD mutant , which suggests a diversification of the cellular functions of NoxD in fungi . This result also hints differences in the regulation of ROS-mediated signalling pathways in the fungal kingdom . Importantly , two lines of evidence support the direct involvement of Tpc1 in NoxD expression regulation . The ChIP analysis demonstrates that Tpc1:GFP immunoprecipitates in vivo with the NOXD promoter region . Tpc1 also regulates Mst12 DNA-binding activity in vitro using the corresponding NOXD promoter region , and indicates a direct participation of Tpc1 in the MAPK Pmk1 signalling pathway . Despite the ability of Tpc1 and Mst12 to regulate NOXD expression together , and their participation in common cellular processes such as penetration peg formation and plant invasion[9] , Δmst12 and Δtpc1 mutants have different colony morphology . In contrast to Tpc1 , Mst12 is dispensable for growth and appressorial turgor generation[9] . Consequently , Tpc1 has the ability to modulate expression of genes that participate in additional cellular processes , either by interacting with other transcription factors , or activating directly the expression of different genes . Here , we identified one potential mechanism by which the transcription factor Tpc1 regulates appressorium maturation and plant infection . The loss of pathogenicity associated with M . oryzae and F . graminearum TPC1 mutants and similar growth defects associated with the N . crassa Δnctpc1 mutant , suggest that Tpc1 plays a key role as a transcriptional regulator in the re-establishment of polarity and the response to numerous signalling pathways , such as the Pmk1 MAP kinase and Atg1 kinase cascades . The role of Tpc1 in appressorium-mediated plant infection appears to be associated with the NADPH oxidase-dependent re-polarisation process of the appressorium , and the associated physiological changes such as autophagy , glycogen/lipid mobilisation and asymmetric reorganization of the F-actin cytoskeleton . Future studies will allow further dissection of this role and precise definition of the biological processes regulated by Tpc1 in filamentous fungi .
M . oryzae was routinely incubated in a controlled temperature room at 25°C with a 12h light/dark cycle . Media composition of complete medium ( CM ) , minimal medium ( MM ) , minimal medium without carbon ( MM-C ) or nitrogen ( MM-N ) , and DNA extraction and hybridisation were all as previously described[76] . Growth tests were carried out with 7 mm plugs of mycelium from Guy11 and the M1422 mutant strains as initial inoculum . The wild-type Neurospora crassa strain and isogenic deletion mutant NCU05996 were obtained from the Fungal Genetics Stock Centre ( FGSC , Kansas City , Missouri , USA ) . Vogel’s minimal medium was used for cultivation of N . crassa strains at 25°C with a 12h light/ dark cycle and for stock-keeping at 4°C ( http://www . fgsc . net/Neurospora/NeurosporaProtocolGuide . htm ) . Growth tests were carried out on Vogel plates with 5 mm plugs of mycelium from N . crassa wild-type ( wt ) and NcTPC1 KO strains . Plates were incubated at 25°C for 2 days . M . oryzae leaf and root infection assays were carried out , as previously described [30 , 77] . Conidia were harvested using 2 ml of sterile water per plate after fungal cultures were incubated at 25°C for a period of 10 days on CM . Calculations were then carried out to determine the number of conidia generated per cm2 of mycelium using a Neubauer counting chamber . Values are the mean ± SD from >300 conidia of each strain , which were measured using the ImageJ software [78] . Photographs were taken using the Zeiss Axioskop 2 microscope camera using differential interference contrast ( DIC ) microscopy or epifluorescence . Conidia were stained with 5μl calcofluor white ( CFW ) solution ( Fluka ) and incubated at 25°C for 30 minutes . Cell number per conidium was determined by visualizing septa with CFW . Appressorium-mediated penetration of onion epidermal strips was assessed using a procedure based on Chida and Sisler[79] . A conidial suspension at a concentration of 1 x 105 conidia mL-1 was prepared and dropped onto the adaxial surface of epidermal layers taken from onion . The strips were incubated in a moist chamber at 25°C and penetration events scored 24h to 48h later by recording images with an Olympus IX81 inverted microscope system . Leaf sheath assays were carried out as previously described [10] . Glycogen staining solution contained 60 mg of KI and 10 mg of I2 per milliliter of distilled water . Glycogen deposits are visible immediately . For cytorrhysis assays , 105 spores were allowed to form appressoria for 18h on coverslips prior the addition of external glycerol ( 1M or 3M ) . After 10 minutes in glycerol ~500 appressoria were analyzed in each biological replica; experiment was carried out by triplicate . To visualize lipid droplets , conidia were allowed to germinate in water on coverslips . After 0h , 2h , 9h and 12h water was removed and conidia directly stained with Nile red ( Nile Red Oxazone ( 9-diethylamino-5Hbenzo[alpha]phenoxazine-5-one; Sigma ) . Nile red was used to 2 . 5 mg/ml diluted in 50mM Tris/Maleate , pH 7 . 5 and polyvinylpyrrolidone ( PVP ) ( 2–3% w/v ) . Lipid droplets begin to fluoresce within seconds . Samples were visualized under a confocal laser scanning microscope using a 561 nm excitation wave length and a long pass emission filter ( 592–700 nm ) . All images were taken using the same parameters . Gene deletion constructs were generated using multisite gateway technology ( Invitrogen ) as previously described[77 , 80] . TPC1 , CON6 , GH18 , PEBP2 and NOXD coding sequences were replaced by the hygromycin resistance cassette and PEBP1 by the sulfonylurea resistance cassette in the gene replacement constructs . Primers for constructing entry plasmids are described in S4 Table . Fungal transformants generated by Agrobacterium-mediated transformation [81] were selected growing in DCM solid media supplied with 5-fluoro-2’-deoxyuridine ( 50μM ) and 200μg/ml Hygromycin or 150μg/ml Chlorymuronethyl in the case of Δpebp1 . DCM is 1 . 7 g yeast N-base without amino acids , 1 . 0 g NH4NO3 , 2 . 0 g of L-asparagine and 10 g of D-glucose . Knockout strains were confirmed by PCR or Southern blotting using radioactive probes ( 32P; primers listed in S4 Table ) . Sequence data and gene numbers used in this study were taken from EnsemblFungi ( Magnaporthe oryzae MG8; http://fungi . ensembl . org/index . html ) . To determine the localisation of Tpc1 , live-cell imaging was performed using a M . oryzae Guy11 strain containing two constructs , histone H1 tagged with red fluorescent protein ( H1:RFP; tdTomato ) to visualize nuclei [82] , and TPC1:GFP . For the construction of a functional TPC1:GFP gene fusion , primers were designed in order to amplify the TPC1 ( MGG_01285 ) promoter region and ORF from genomic DNA of M . oryzae Guy11 ( S4 Table ) . The TPC1_GFP_F forward primer was designed approximately 1 . 3 kb upstream from the TPC1 start codon to include a substantial component of the promoter sequence . The TPC1_GFP_R reverse primer spanned the stop codon and contained a complementary region to the GFP sequence . GFP primers were designed to amplify the 1 . 4 kb sGFP:TrpC construct cloned in pGEMT . Both fragments were joined together by fusion nested PCR . The amplicons were cloned into pGEMT-easy digested with EcoRI . The 4 . 3 kb TPC1:GFP fragment was gel purified and cloned into pCB1532 that had previously been digested with EcoRI . The pCB1532 vector contains the 2 . 8 kb ILV1 gene , which encodes the acetolactate synthase-encoding allele bestowing resistance to sulfonylurea[83] . The resulting plasmid pCB1532-TPC1:GFP was used to transform protoplasts of M1422 mutant . For all rounds of PCR amplification , Phusion High-Fidelity DNA polymerase ( Finnzymes , Thermo Fischer Scientific Inc . ) was used , following the manufacturers’ guidelines for PCR conditions . The GFP:MoATG8[34] and the FIM:GFP constructs were used to transform protoplasts of M1422 mutant . Protoplast generation and transformation were carried out as previously described[76] . The GFP:MoATG8 and the FIM:GFP protein fusion vectors were generated using the native M . oryzae MoATG8 gene ( MGG_01062 ) and the native M . oryzae fimbrin-encoding gene ( MGG_04478 ) , respectively . Both fragments were cloned into pCB1532 vector that contains the 2 . 8 kb ILV1 gene , which encodes the acetolactate synthase allele conferring sulfonylurea resistance . Transformants showing identical growth and colony morphology to the background strain were selected for further examination using epifluorescence or confocal microscopy . At least three different transformants of each were independently analysed . The TPC1:GFP gene fusion was cloned into pCB1532 vector ( SURR ) and used to transform protoplasts of Guy11 expressing Histone H1 fused with red fluorescent protein ( H1:RFP ) [33] , and also introduced into isogenic Δpmk1 , Δatg1 and Δatg8 mutants . Transformants were selected for further examination using confocal microscopy and verified as containing a single copy of the gene fusion construct by Southern blot hybridisation . At least three different transformants of each were used in all experiments . Using a modified protocol of LiCl method[77] , RNA was extracted from 8-day old fungal mycelia grown on cellophane placed on top of CM agar plates ( S2E Fig ) . Two to three additional washes with phenol:chloroform were implemented to avoid RNA degradation from cellophane samples . RNA quality control was carried out with Agilent RNA 6000 Nano kit ( ref . 5067–1504 ) . Four biological replicates were independently hybridized for each transcriptomic comparison . Each of these replicates derived from three technical repetitions . Slides were Agilent Magnaporthe II Oligo Microarrays 4x44K ( ref . 015060 ) . Background correction and normalization of expression data were performed as previously described[77] . Hybridizations and statistical analysis were conducted by the Genomics Facility at the National Biotechnology Centre ( Madrid , Spain ) . The GO term analysis was carried out with gProfiler[84] . Enriched motifs were not found when using the promoter regions of the 185 up-regulated genes . Microarray data are available in the ArrayExpress database ( EMBL_EBI ) under accession number E-MTAB-4127 . In-Fusion Cloning based on in vitro homologous recombination was performed to generate vectors including NoxD and Tpc1 into the pGADT7 prey vector , and Nox1 , Nox2 NoxR , Pmk1 and Mst12 into the pGBKT7 bait vector . Genes were amplified from M . oryzae cDNA derived from mycelia grown on liquid CM using primers with a 15bp overhang and restriction site complementary to the target vector ( S4 Table ) . For NoxD , a 435bp fragment was amplified , for Nox1 , a 1662bp fragment was amplified , for Nox2 , a 1749bp fragment was amplified , and for NoxR , a 1578bp fragment was amplified . Respective fragments were cloned into pGBKT7 and pGADT7 plasmids linearized by digestion with EcoRI and SmaI . Yeast two-hybrid assays using pGADT7 or pGBKT7 ( Clontech ) based constructs were performed according to the manufacturer’s instructions ( MATCHMAKER Gold Yeast Two-Hybrid System ) . For the construction of NoxD:GFP , primers were designed to amplify the ORF including 2kb upstream of the start codon , GFP and TrpC terminator with 15bp overhangs complementary to adjacent fragments ( S4 Table ) . Fragments were ligated into pCB1532[83] , which carries the sulphonyl urea resistance cassette and had been digested with BamHI and HindIII and this construct transformed into of the wild-type strain Guy11 using protoplasts[6] . The NoxD:mRFP construct was generated using multi-site gateway technology ( Life Technologies ) with the entry mCherry-withSTOP and destination SULPH-R3R4 vectors[77] , and PCR fragments amplified from M . oryzae genomic DNA using Phusion DNA polymerase ( NEB ) and primers detailed in S4 Table . Appressorium development assays were performed on hydrophobic borosilicate glass coverslips ( Fisher Scientific ) , as described previously[6] . For epifluorescence microscopy , conidia were incubated on coverslips and observed at each time point using an IX-81 inverted microscope ( Olympus ) and a UPlanSApo X100/1 . 40 oil objective . All microscopic images were analyzed using MetaMorph ( Molecular Devices ) . Confocal imaging was performed with a Leica SP8 microscope . To confirm microarray results , the relative abundance of gene transcripts were analysed by qPCR ( S4 Table ) . One μg of total RNA from 8-day old fungal mycelia grown on cellophane placed on CM agar was reverse transcribed using PrimeScript RT reagent Kit ( Takara ) . The average threshold cycle ( Ct ) was normalized against actin transcript and relative quantification of gene expression was calculated by the 2ΔΔCt method[85] . Primer efficiency was tested using dilutions of cDNA samples . qPCR reactions were carried out with 1 μl of reverse transcribed products and fast-start DNA master SYBR green I kit ( Roche Diagnostics ) in a final reaction of 20 μl using the following program: one cycle of 95°C for 4 min and 40 cycles of 94°C for 30 s and 60°C for 30 s . The Ct ( threshold cycle ) provided a measure for the starting copy numbers of the target genes . Three technical repetitions from three independent biological experiments were used for each gene . For ROS detection in M . oryzae fungal structures , NBT staining[65] and quantification method of pixel intensities in hyphal tips[86] were carried out as previously described . Two strains , the Δtpc1 mutant expressing TPC1:GFP and M . oryzae wild-type Guy11 strain as negative control were used for this experiment . Mycelia were grown in liquid CM at 25°C for 48 h in a shaker ( 120 rpm ) , and collected using two layers of Miracloth . Harvested mycelia were washed extensively with sterile water . To crosslink DNA and proteins , one gram of each washed mycelium was treated with 1% formaldehyde in 20 mM HEPES pH 7 . 4 buffer for 20 min with continuous shaking at 100 rpm . Then , 0 . 125 M glycine was added and incubated at room temperature for an additional 10 min to stop crosslinking . Mycelia were harvested with Miracloth , rinsed with water removing excessive water by squeezing and immediately frozen in liquid nitrogen , grinded into a fine powder and stored at -80°C until used . ChIP was conducted according to published procedures with some modifications [87] . 600 mg of each mycelium powder was used for chromatin extraction and sonication . The powder was added into 10 ml of Extraction buffer 1 ( 0 . 4 M sucrose , 10 mM Tris-HCl pH 8 , 10 mM MgCl2 , 5 mM β-mercaptoethanol/β-ME and Protease Inhibitors Complete-PIC/Roche ) and mixed by vortexing . The solution was filtered through a double layer of Miracloth and centrifuged at 5000 g for 10 min at 4°C . The pellet was resuspended in 1 ml of Extraction buffer 2 ( 0 . 25 M sucrose , 10 mM Tris-HCl pH 8 , 10 mM MgCl2 , 1% Triton X-100 , 5 mM β-ME and PIC ) and centrifuged at 5000 g for 10 min at 4°C . The pellet was resuspended in 300 μl of Extraction buffer 3 ( 1 . 7 M sucrose , 10 mM Tris-HCl pH 8 , 0 . 15% Triton X-100 , 2 mM MgCl2 , 5 mM β-ME and PIC ) and , carefully layered on the top of additional 600 μl of extraction buffer 3 . Then , samples were centrifuged at 16000 g for 60 min at 4°C . The chromatin pellet was resuspended in 300 μl of Nuclei Lysis Buffer ( 50 mM Tris-HCl ph 8 , 10 mM EDTA , 1% SDS and PIC ) and sonicated for 25 min at 4°C , operating a pattern of 30 sec ON and 30 sec OFF , at high power level in the Bioruptor Plus ( Diagenode , Liege , Belgium ) to obtain DNA fragments ranging from 500 to 1 , 000 bp . The chromatin solution was centrifuged at maximum speed for 5 min at 4°C to pellet cell debris . The supernatant was kept as chromatin solution and a small aliquot ( 10% ) was stored as input DNA control . For each immunoprecipitation , 15 μl of Dynabeads Protein A magnetic beads ( ref . 10001D , Life Technologies ) was washed twice with 500 μl ChIP dilution buffer ( 1 . 1% Triton X-100 , 1 . 2 mM EDTA , 16 . 7 mM Tris-HCl pH 8 , 167 mM NaCl and PIC ) . Then , anti-GFP antibody ( ref . A6455 , Life Technologies ) was added and incubated with gentle rotation for 1h at 4°C in 50 μl ChIP dilution buffer . Prepared anti-GFP coated beads were washed twice with 500 μl ChIP dilution buffer and resuspended in 100 μl of ChIP dilution buffer . For each immunoprecipitation , the latter and 100 μl of chromatin solution were gathered together and diluted up to 1 ml of ChIP dilution buffer . All immunoprecipitations were incubated overnight at 4°C with gentle rotation , then washed with a serie of wash buffers ( 2 washes with Low Salt Wash Buffer: 150 mM NaCl , 0 . 1% SDS , 1% Triton X-100 , 2 mM EDTA , 20 mM Tris-HCl pH 8; one wash with High Salt Wash Buffer: 500 mM NaCl , 0 . 1% SDS , 1% Triton X-100 , 2 mM EDTA , 20 mM Tris-HCl pH 8; one wash with LiCl Wash Buffer: 0 . 25 M LiCl , 1% NP-40 , 1% sodium deoxycholate , 1 mM EDTA , 10 mM Tris-HCl pH 8 , 2 washes with TE Buffer: 10 mM Tris-HCl pH 8 , 1 mM EDTA ) . Immunoprecipitated DNAs and Input DNA control were reverse-crosslinked at 95°C for 10 min with 200 μl of 10% chelex 100 resin to remove any trace of metals . DNA samples were treated with proteinase K that was inactivated afterwards . After centrifugation , supernatants of DNA samples were stored at -20°C until used . Immunoprecipitated chromatin was diluted 10 times for qPCR analysis ( primers listed in S4 Table ) . This was performed using a Roche LightCycler 480 machine . qPCR reactions were carried out using either 2 μl of input DNA or 2 μl of immunoprecipitated chromatin in a final reaction of 12 μl with the following program: one cycle of 95°C for 5 min and 58 cycles of 94°C for 10 s , 60°C for 10 s and 72°C for 10 s . The Ct ( threshold cycle ) provided a measure for the starting copy numbers of DNA . Three technical repetitions from 4 independent biological experiments were used . Ct values were used to calculate ratios evaluating the fold difference between experimental samples ( GFP-tagged or untagged wild-type strains ) and normalized the input . We normalized with “Fold Enrichment Method” using the untagged strain . The Wilcoxon Mann Whitney test was applied to analyze the difference between two independent groups . Statgraphics software was used to make pairwise comparisons between GFP-tagged strain and untagged wild-type strain . M . oryzae MST12 and TPC1 cDNAs derived from mycelial RNA were cloned by PCR using a high fidelity Q5 DNA polymerase ( NEB ) , primers ( S4 Table ) and the restriction enzymes BamHI-NotI and EcoRI- NotI for MST12 and TPC1 respectively , into a modified pET28 vector ( 5 , 667bp; Novagen ) . MST12- and TPC1-containing plasmids were transformed in E . coli Rosetta DE3 ( Novagen ) and colonies grown in LB medium containing chloramphenicol ( 34 μg/L ) and kanamycin ( 50 μg/L ) until reaching OD600nm = 0 . 8 . Protein expression was induced 4 hours at 28°C with 1 mM IPTG ( Sigma-Aldrich ) . Centrifuged cell pellets ( 30 min at 7000g ) were resuspended in lysis buffer ( 20 mM sodium phosphate pH 8 , 300 mM NaCl and one tablet of PIC/50 ml , 1 mM PMSF and 50 μg/ml Dnase I ) , lysed by sonication and pelleted at 4°C and high speed ( 20 min at 20 , 000g ) . Recombinant proteins were purified from clear lysate by metal affinity chromatography ( HisTrap HP 1 ml , #17-5247-01 GE Healthcare ) in denaturing conditions using 6 M Urea and eluted with 250 mM imidazole containing buffer . Samples were desalted on PD10 column ( #17085101 GE Healthcare ) to remove urea and imidazole using buffer ( 20 mM sodium phosphate pH 8 , 10% glycerol and PIC ) . Protein samples purity was evaluated by SDS-PAGE . EMSA probes were generated as follows . Amplified by PCR fragments using primers listed in S4 Table were prepared using modified Biotin 3’end DNA labeling procedure ( #89818 Thermo-Scientific ) . Briefly , each ~500pb purified PCR products was KpnI-digested , purified and labelled ( 5 pmol of each probe ) with Biotin-11-UTP and Terminal Deoxinucleotidyl Transferase at 37°C for 1 hour . Biotinylated probes were purified by Chloroform:IAA ( 24:1 ) extraction and stored at -20°C until use . EMSA reactions ( 20 μl ) contained 10 mM Tris HCl pH 7 . 5 , 50 mM KCl , 16 mM DTT , 1 mM ZnCl2 , 1 mM MgCl2 , 1% Glycerol , 50 ng/μl Poly dI-dC ( #20148E Thermo-Scientific ) , 10 μg BSA , Protease inhibitor complete ( Roche ) , and 80 fmol of biotinylated probe . Before probe addition proteins ( 0–12 μM ) were incubated in binding buffer for 10 min , then probe was added and incubated during 30 min at room temperature before loading . The EMSA gel ( 0 . 2% agarose , 5% polyacrylamide , 1% glycerol in TBE 0 . 5x ) was run for 2h 100V in TBE 0 . 5x and then transferred to a Hybond-XL nylon membrane ( #RPN203S GE Healthcare ) at 400 mA for 1 hour . The membrane was UV crosslinked at 120mJ/cm2 . Detection was performed with stabilized streptavidin-horseradish peroxidase conjugate ( #21134 Thermo-Scientific ) and enhanced chemiluminescent substrates ( #32106 Thermo-Scientific ) following LightShift Chemiluminescent EMSA procedure ( #20148 Thermo-Scientific ) . First , 141 M . oryzae protein sequences containing a fungal Zn ( II ) 2Cys6 binuclear cluster domain ( PF00172 ) were identified from the Magnaporthe sequence database at the Broad Institute ( http://www . broadinstitute . org/annotation/fungi/magnaporthe ) and the Fungal Transcription Factor Database ( http://ftfd . snu . ac . kr/intro . php ) . HMMsearch from HMMER3[88] was used to screen the genome assembly of M . oryzae proteins with the fungal Zn2Cys6 profile hidden Markov model pHMM zn_clus_ls . hmm ( PF00172 . 13 ) from Pfam database[89] ( http://pfam . xfam . org/ ) . Subsequently , gene numbers were updated using the MG8 genome version of EnsemblFungi database ( http://fungi . ensembl . org/index . html ) . Out of these 141 sequences , only 113 had a full length zinc cluster domain , and extra six closest sequences were included to build S5 Fig . Additional Zn ( II ) 2Cys6 proteins found in Lu et colleagues[28] were included in S2 Table . Basic Local Alignment Search Tool ( BLAST ) was used to find orthologous proteins of TPC1/MGG_01285 ( http://blast . ncbi . nlm . nih . gov/Blast . cgi ) . Protein sequences were pre-aligned using HMMalign and the pHMM zn_clus_ls . hmm ( S4 Fig ) from Pfam . The Zn ( II ) 2Cys6 binuclear cluster domain region was extensively manually aligned in BioEdit ( http://www . mbio . ncsu . edu/BioEdit/BioEdit . html ) . Unambiguous aligned positions were used for the subsequent phylogenetic analyses . The maximum likelihood ( ML ) analyses were performed with the program PhyML version 3 . 0 . 1[90] . All trees were visualised using the program Figtree ( http://tree . bio . ed . ac . uk/software/figtree/ ) . M . oryzae sequence data from this article can be found in the GenBank/EMBL-EBI ( EnsemblFungi ) databases under the following accession numbers: TPC1 ( MGG_01285 ) , PMK1 ( MGG_09565 ) , MST12 ( MGG_12958 ) , ATG1 ( MGG_06393 ) , ATG8 ( MGG_01062 ) , CON6 ( MGG_02246 ) , GH18 MGG_04732 , NOXD ( MGG_09956 ) , PEBP1 ( MGG_06800 ) , PEBP2 ( MGG_14045 ) , NOXR ( MGG_05280 ) , NOX1 ( MGG_00750 ) , NOX2 ( MGG_06559 ) , FIMBRIN ( MGG_04478 ) GELSOLIN ( MGG_10059 ) , ACTIN ( MGG_03982 ) , YDIU ( MGG_03159 ) and SEP5 ( MGG_03087 ) . | Cellular polarity is an intrinsic feature of filamentous fungal growth and pathogenesis . In this study , we identified a gene required for fungal polar growth and virulence in the rice blast fungus Magnaporthe oryzae . This gene has been named TPC1 ( Transcription factor for Polarity Control 1 ) . The Tpc1 protein belongs to the fungal Zn ( II ) 2Cys6 binuclear cluster family . This DNA-binding motif is present exclusively in the fungal kingdom . We have characterised defects associated with lack of Tpc1 in M . oryzae . We show that Tpc1 is involved in polarised growth and virulence . The M . oryzae Δtpc1 mutant shows a delay in glycogen and lipid metabolism , and infection-associated autophagy–processes that regulate appressorium-mediated M . oryzae plant infection . The saprophytic fungus Neurospora crassa contains a Tpc1 homolog ( NcTpc1 ) involved in vegetative growth and sustained tip elongation , suggesting that Tpc1-like proteins act as core regulators of polarised growth and development in filamentous fungi . A comparative transcriptome analysis has allowed us to identify genes regulated by Tpc1 in M . oryzae including NoxD , an important component of the fungal NADPH complex . Significantly , Tpc1 interacts with Mst12 , a component of the Pmk1 signalling pathway essential for appressorium development , and modulates Mst12 binding affinity to NOXD promoter region . We conclude that Tpc1 is a key regulator of polarity in M . oryzae that regulates growth , autophagy and septin-mediated reorientation of the F-actin cytoskeleton to facilitate plant cell invasion . | [
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] | 2017 | Tpc1 is an important Zn(II)2Cys6 transcriptional regulator required for polarized growth and virulence in the rice blast fungus |
The enteric bacterium Proteus mirabilis , which is a pathogen that forms biofilms in vivo , can swarm over hard surfaces and form a variety of spatial patterns in colonies . Colony formation involves two distinct cell types: swarmer cells that dominate near the surface and the leading edge , and swimmer cells that prefer a less viscous medium , but the mechanisms underlying pattern formation are not understood . New experimental investigations reported here show that swimmer cells in the center of the colony stream inward toward the inoculation site and in the process form many complex patterns , including radial and spiral streams , in addition to previously-reported concentric rings . These new observations suggest that swimmers are motile and that indirect interactions between them are essential in the pattern formation . To explain these observations we develop a hybrid model comprising cell-based and continuum components that incorporates a chemotactic response of swimmers to a chemical they produce . The model predicts that formation of radial streams can be explained as the modulation of the local attractant concentration by the cells , and that the chirality of the spiral streams results from a swimming bias of the cells near the surface of the substrate . The spatial patterns generated from the model are in qualitative agreement with the experimental observations .
A variety of spatial patterns in growing bacterial colonies are found both in nature and in the lab [1]–[10] . When inoculated on semi-solid agar with succinate or other TCA cycle intermediates , motile Escherichia coli cells grow , divide , and self-organize into patterns ranging from outward-moving rings of high cell density to chevron patterns , depending on the initial concentration of the nutrient [1] , [2] . When grown or simply placed in static liquids , cells quickly reorganize into networks of high cell density comprised of bands and/or aggregates , following exposure to succinate and other compounds . Chemotactic strains of Salmonella typhimurium , a closely-related species , can also form concentric rings and other complex patterns in similar conditions [3] , [4] , and it has been shown that pattern formation in both species is driven by chemotactic interactions between the cells and a self-produced attractant [1]–[3] . The gram-positive bacterium Bacillus subtilis forms patterns ranging from highly branched fractal-like patterns to compact forms , depending on the agar and nutrient concentrations [5] , [6] , [11] . In all these systems proliferation , metabolism and movement of individual cells , as well as direct and indirect interactions between cells , are involved in the patterning process , but the mutual influences and balances between them that lead to the different types of patterns is difficult to dissect experimentally , and is best explored with a mathematical model . Understanding these balances would advance our understanding of the formation of more complex biofilms and other multicellular assemblies [12] . Proteus mirabilis is an enteric gram-negative bacterium that causes urinary tract infections , kidney stones and other diseases [13]–[16] . Pattern formation by Proteus was described over 100 years ago [17] , and the nature of these patterns has since been discussed in many publications . When grown in a liquid nutrient medium , the dominant phenotype of P . mirabilis is a vegetative swimmer cell that is 1–2 long , has 1–10 flagella and moves using a “run-and-tumble strategy” , similar to that used by E . coli [4] . Swimmers respond chemotactically to several amino acids , and can adapt perfectly to external signals [18] . When grown on hard agar Proteus forms spectacular patterns of concentric rings or spirals . Swimmers differentiate into highly motile , hyperflagellated , multi-nucleated , non-chemotactic swarmer cells that may be as long as 50–100 , and that move coordinately as “rafts” in the slime they produce [19] , [20] . During pattern formation on hard surfaces swarmer cells are found mainly at the leading edge of the colony , while swimmers dominate in the interior of the colony [8] , [17] , [19] , [21] . While much effort has been directed toward understanding the mechanism of swarming , to date little is known about how cells swarm and how cells undergo transitions between swimmers and swarmers [19] , [20] , [22]–[26] , but understanding these processes and how they affect colonization could lead to improved treatments of the diseases caused by P . mirabilis . Traditionally , formation of periodic cell-density patterns in Proteus colonies has been interpreted as a result of periodic changes in the velocity of the colony's front , caused by the cyclic process of differentiation and de-differentiation of swimmers into swarmers ( see [8] ) . Douglas and Bisset described in [21] a regime for some strains of P . mirabilis in which swarmers form a continuously moving front , while concentric rings of high cell density form well behind that front . This suggests that pattern formation can occur in the absence of cycles of differentiation and de-differentiation . The similarity between this mode of pattern formation and that of Salmonella led us to ask whether the underlying mechanism for pattern formation in P . mirabilis might also be chemotactic aggregation of the actively moving swimmers behind the colony front . A number of mathematical models of colony front movement have been proposed , and in all of them swimmer cells are non-motile and swarming motility is described as a degenerate diffusion , in that swarmers only diffuse when their density exceeds a critical value [27]–[31] . The dependence of the front propagation patterns on various parameters in one of these models is given in [29] , and while models can reproduce the colony front dynamics , it remains to justify treating the swarming motility as a degenerate diffusion process , since it is likely that the cell-substrate interaction is important . To replicate a periodically propagating front , Ayati showed that swarmers must de-differentiate if and only if they have a certain number of nuclei [30] , [31] . It was shown that this may result from diffusion limitations of intracellular chemicals , but biological evidence supporting this assumption is lacking , and further investigation is needed to understand the mechanism of front propagation . Here we report new experimental results for a continuously-expanding front and show that after a period of growth , swimmer cells in the central part of the colony begin streaming inward and form a number of complex multicellular structures , including radial and spiral streams as well as concentric rings . These observations show that swimmer cells are also motile , and that communication between them may play a crucial role in the formation of the spatial patterns . However , additional questions raised by the new findings include: ( 1 ) what induces the inward movement of swimmer cells , ( 2 ) why do they move in streams , ( 3 ) why do radial streams quickly evolve into spiral streams , and ( 4 ) quite surprisingly , why do all the spirals wind counterclockwise ( CCW ) when viewed from above . To address these questions we developed a hybrid model comprised of a cell-based component for cell dynamics and a continuum component for nutrients and the chemoattractant secreted by swimmer cells . The model has provided biologically-based answers to the questions above and guided new experiments . Previous models , including a continuum chemotaxis model for patterning we developed earlier [32] , have limitations discussed later that are not inherent in the hybrid model .
Previous experimental work focused on expansion of the colony front and neglected the role of movement of swimmers in the pattern formation process in the interior of the colony [8] , [19] , [21] , and the experimental results reported here represent a first step toward understanding their role . After a drop of P . mirabilis culture is inoculated on a hard agar-like surface containing rich nutrient , the colony grows and expands . Under the conditions used here , the colony front expands continuously ( see Video S1 and Figure S1 ) - initially as a disc of uniform density . The swarmers exist at the periphery of the colony , and the mean length of the cells decreases towards the center , as observed by others [33] . For the first 5–7 hours , swarmers migrate out the inoculation site , the slime layer gradually builds up and swarmers de-differentiate into swimmer cells behind the leading edge . Later we observe that swimmer cells in the colony stream inward , forming a number of complex patterns ( Figure 1 ) . The swimmer population first forms a radial spoke-like pattern in an annular zone on a time scale of minutes , and then cells follow these radial streams inward ( 1A ) . The radial streams soon evolve into spirals streams , with aggregates at the inner end of each arm ( 1B ) . A characteristic feature of this stage is that the spirals always wind CCW when viewed from above . Different aggregates may merge , forming more complex attracting structures such as rotating rings and traveling trains ( 1B , C ) . Eventually the motion stops and these structures freeze and form the stationary elements of the pattern ( 1B , C ) . Later , this dynamic process repeats at some distance from the first element of the pattern , and sometimes cells are recruited from that element . In this way , additional elements of the permanent pattern are laid down ( 1C ) . On a microscopic level , the transition to the aggregation phase can be recognized as transformation of a monolayer of cells into a complex multi-layered structure . Not every pattern is observable in repeated experiments , ( for example , no observable rotating rings can be identified in ( 1D ) , probably due to sensitivity to noise in the system and other factors that require further investigation , variations in nutrient availability , etc . , but the formation of radial and spiral streams always appear in repeated experiments . These new findings pose challenges to the existing theories of concentric ring formation in which swimmer cells are believed to be non-motile . Additional questions arise regarding the mechanism ( s ) underlying the formation of radial and spiral streams , rings and trains by swimmers , and what determines the chirality of the spiral streams . The macroscopic patterns are very different and more dynamic than the patterns formed in E . coli or Salmonella typhimurium colonies [1]–[3] , where cells interact indirectly via a secreted attractant , but the fact that swimmers move up the cell density gradient is quite similar . The non-equilibrium dynamics suggests intercellular communication between individual swimmer cells , and we determined that swimmer cells extracted from these patterns are chemotactic towards several amino acids , including Aspartate , Methionine and Serine ( see Table 1 ) . In the following we provide an explanation of the radial and spiral streams using a hybrid cell-based model , by assuming that cells secrete to a chemoattractant that they respond to . The spatial patterns of interest here are formed in the center of the colony where cells are primarily swimmers , while the role of swarmers is mainly to advance the front and to affect the swimmer population by differentiation and de-differentiation . Thus we first focus on modeling the dynamics in the patterning zone in the colony center ( Figure 2A ) , and later we incorporate the colony front as a source of swimmers . This enables us to avoid unnecessary assumptions on the poorly-understood biology of swarming and the transition between the two phenotypes . As noted earlier , swimmer cells are chemotactic to certain factors in the medium , and we assume that they communicate via a chemoattractant that they secrete , and to which they respond . Therefore the minimal mathematical model involves equations for the signal transduction and movement of individual cells , and for the spatio-temporal evolution of the extracellular attractant and the nutrient in the domain shown in Figure 2B . We first focus on understanding the radial and spiral stream formation , which occurs rapidly , and during which the nutrient is not depleted and cells grow exponentially . During this period the nutrient equation is uncoupled from the cell equations and can be ignored . In the radial and spiral streams , cell density is relatively low and cells are still well separated , so we ignore the mechanical interactions between cells . It has been known for many years that the chemotaxis signal transduction pathway in P . mirabilis is very similar to that of E . coli [34]–[36] . Recently all the chemotaxis-related genes of E . coli have been found in the Proteus genome [18] , and in view of the genetic similarity between P . mirabilis and E . coli , we describe motility and signal transduction in the former using the key ideas from the latter . E . coli cells swim using a run-and-tumble strategy , which consists of more-or-less straight runs punctuated by random turns . In the absence of an attractant gradient the result is an unbiased random walk , with mean run time 1 s and mean tumble time 0 . 1 s . In the presence of an attractant gradient , runs in a favorable direction are prolonged , and by ignoring the tumbling time , which is much shorter than the run time , the movement of each cell can be treated as an independent velocity jump process with a random turning kernel and a turning rate determined by intracellular variables that evolve in response to extracellular signals [37] . The signal transduction pathway for chemotaxis is complex and has been studied extensively both experimentally and mathematically [34]–[36] , [38]–[40] . However the main processes are relatively simple , and consist of fast excitation in response to signal changes , followed by adaptation that subtracts out the background signal . These major processes are embedded in the following description of cell behavior . We assume that cells secrete attractant at a constant rate and that it is degraded by a first-order process . Since we neglect cell volume , the attractant is secreted at the center of each cell . The resulting evolution equation for the attractant is ( 4 ) where is the Dirac delta function , is the total number of cells , and is the diffusion coefficient of the attractant . For simplicity , we also restrict reaction and diffusion of the attractant to two space dimensions , which is justified as follows . Since no attractant is added to the substrate initially , which is much thicker than the slime layer , we assume that the attractant level is always zero in the substrate . We further assume that the flux of the attractant at the interface of the two layers is linear in the difference of its concentration between the two layers . Thus the loss of attractant due to diffusion to the agar can be modeled as a linear degradation , and the degradation constant in ( 4 ) reflects the intrinsic degradation rate and the flux to the substrate . In the numerical investigations described below , ( 4 ) is solved on a square domain using the ADI method with no-flux boundary conditions , while cells move off-grid . For each time step ( mean run time ) , ( 1 ) , ( 2 ) are integrated for each cell and the velocity and position are updated by Monte Carlo simulation . Transfer of variables to and from the grid is done using bilinear interpolating operators . A detailed description of the numerical scheme as applied to pattern formation in E . coli is given in Appendix A of [32] , and for convenience we also included it in the Methods section . After the positions of cells are obtained at each time point , we count the number of cells in each grid and normalize to get the cell density profile in the domain . Before the emergence of radial streams , the colony expands with a continuous moving front ( Video S1 and Figure S1 ) due to the movement of swarmers , and the cell density is uniform except at the inoculation site , where cells may become non-motile or dormant . During this period of time , the attractant and slime build up and the swarmers de-differentiate to form a population of swimmers . Thus by the end of this period , the attractant concentration can be approximated by a cone-like profile centered at the inoculation site , with a uniform lawn of swimmers laid down . Here we show that starting from this initial condition , the mechanism introduced above can explain radial stream formation on the correct time scale , which is 5–15 minutes . The excitation time scale is a fraction of a second , while the adaptation time scale can range from several seconds to several minutes [43] , [44] . We assume quasi-steady state for the fast excitation by taking in the numerical investigations below . For simplicity we also assume , and the intracellular dynamics becomeWe specify an initial attractant gradient of in a disk of radius 1 . 5 cm , centered at the center of the domain , with zero attractant at the boundary of the disk . For compatibility with later computations on a growing disk , we initially distribute randomly within the disk . ( If cells are initially distributed throughout the square domain cells near the four corners , outside the influence of the initial gradient , aggregate into spots , as is observed in E . coli as well [32] . ) Figure 3 shows how this distribution evolves into radial streams that terminate in a high-density region at the center on a time scale of minutes as expected in the experiments . If we double the cell density at the inoculation site , we obtain a qualitatively similar result . One can understand the breakup into streams as follows . By hypothesis , cells modulate their run lengths in response to the local concentration and the changes they measure via the perceived Lagrangian derivative of attractant along their trajectory , whether or not there is a macroscopic attractant gradient . Small local variations in cell density then lead to local variations in attractant to which the cells respond , and in the absence of a macroscopic gradient , an initially-uniform cell density evolves into a high cell density network , which in turn breaks into aggregates that may then merge ( not shown ) . This has also been found both theoretically and experimentally in E . coli ( see [1] and Figure 4 . 4 in [32] ) . If we describe the cell motion by a 1-D velocity jump process , a linear stability analysis of the corresponding continuum equations predicts that the uniform distribution is unstable , and breaks up into a well-defined spatial pattern ( see Figure 4 . 2 , 4 . 3 in [32] ) . Numerical solutions of the nonlinear equations confirm this , and experiments in which the grid size is varied show that the results are independent of the grid , given that it is fine enough [32] . In the presence of a macroscopic gradient a similar analysis , taken along a 1D circular cross-section of the 2D aggregation field , predicts the breakup of the uniform distribution , but in this situation the 2D pattern of local aggregations is aligned in the direction of the macroscopic gradient . This is demonstrated in a numerical experiment in which cells are placed on a cylindrical surface with constant attractant gradient ( Figure S2 ) . Thus the experimentally-observed radial streams shown in Figure 1 and the theoretically-predicted ones shown in Figure 3 can be understood as the result of ( i ) a linear instability of the uniform cell density , and ( ii ) the nonlinear evolution of the growing mode , with growth oriented by the initial macroscopic gradient of attractant . In most experiments the radial streams that arise initially rapidly evolve into spiral streams , and importantly , these spirals always wind CCW when viewed from above . The invariance of the chirality of these spirals indicates that there are other forces that act either on individual cells or on the fluid in the slime layer , and that initial conditions play no significant role . One possible explanation , which we show later can account for the observed chirality , stems from observations of the swimming behavior of E . coli in bulk solution and near surfaces . When far from the boundary of a container , E . coli executes the standard run and tumble sequence , with more or less straight runs interrupted by a tumbling phase in which a new , essentially random direction is chosen . ( There is a slight tendency to continue in the previous direction [41] ) . However , observations of cell tracks near a surface show that cells exhibit a persistent tendency to swim clockwise ( CW ) when viewed from above [45]–[47] . Since the cells are small the Reynolds number based on the cell length is very small ( ) ) , inertial effects are negligible , and the motion of a cell is both force- and torque-free . Since the flagellar bundle rotates CCW during a run , when viewed from behind , the cell body must rotate CW . When a cell is swimming near a surface , the part of the cell body closer to the surface experiences a greater drag force due to the interaction of the boundary layer surrounding the cell with that at the immobile substrate surface . Suppose that the Cartesian frame has the x and y axes in the substrate plane and that z measures distance into the fluid . When a cell runs parallel to the surface in the y direction and the cell body rotates CW , the cell body experiences a net force in the x direction due to the asymmetry in the drag force . Since the flagellar bundle rotates CCW , a net force with the opposite direction acts on the flagella , and these two forces form a couple that produces the swimming bias of the cell . ( Since the entire cell is also torque-free , there is a counteracting viscous couple that opposes the rotation , and there is no angular acceleration . ) The closer the cell is to the surface , the smaller is the radius of curvature of its trajectory and the slower the cell speed . Because of the bias , cells that are once near the surface tend to remain near the surface , which increases the possibility of attachment . ( In the case of Proteus this may facilitate the swimmer-to-swarmer transition , but this is not established . ) Resistive force theory has been used to derive quantitative approximations for the radius of curvature as a function of the distance of the cell from the surface and other cell-level dimensions , treating the cell body as a sphere and the flagellar bundle as a single rigid helix [47] . Cell speed has been shown to first increase and then decrease with increasing viscosity of linear-polymer solutions when cells are far from a surface [48] , but how viscosity changes the bias close to a surface is not known . The question we investigate here is whether the microscopic swimming bias of single bacteria can produce the macroscopic spiral stream formation with the correct chirality . We cannot apply the above theory rigorously , since that would involve solving the Stokes problem for each cell , using variable heights from the surface . Instead , we introduce a constant bias of each cell during the runs , i . e . , where is the normal vector to the surface , and measures the magnitude of the bias in the direction of swimming . Figure 4 shows the evolution of the cell density using a bias of , which is chosen so that a cell traverses a complete circle in 50 secs . The simulations show that the initially-uniform cell density evolves into spiral streams after a few minutes and by 12 minutes the majority of the cells have joined one of the spiral arms . The spiral streams persist for some time and eventually break into necklaces of aggregates which actively move towards the center of the domain . Figure 5A shows the positions , at 30 second intervals , of 10 randomly chosen cells , and Figure 5B illustrates how to understand the macroscopic chirality based on the swimming bias of individual cells . At the blue cell detects a signal gradient ( red arrow ) roughly in the 1 o'clock direction , and on average it swims up the gradient longer than down the gradient . Because of the CW swimming bias , the average drift is in the direction of the blue arrow . At it arrives at the place and ‘realizes’ that the signal gradient is roughly in the 12 o'clock direction , and a similar argument leads to the average net velocity at that spot . As a result of these competing influences , the cell gradually make its way to the source of attractant ( the red dot ) along a CCW trajectory . Certainly the pitch of the spirals is related to the swimming bias , but we have not determined the precise relationship . The spiral movement has also been explained mathematically for a continuum description of cell dynamics in [32] , where the macroscopic chemotaxis equation is derived from the hybrid model in the presence of an external force , under the assumption that the gradient of attractant is shallow . When the swimming bias is constant , the analysis shows that this bias leads to an additional taxis-like flux orthogonal to the signal gradient . However , we show later that the continuum description is not valid for the later stages of patterning in Proteus , since attractant gradients become too large . According to the foregoing explanation , one expects spirals in the opposite direction when experiments are performed with the petri plate upside-down and patterns are viewed from the top , since in this case the relative position of the matrix and slime is inverted and cells are swimming under the surface . This prediction has been confirmed experimentally , and the conclusion is that the interaction between the cell and the liquid-gel surface is the crucial factor that determines the genesis and structure of the spirals . From the foregoing simulations we conclude that when the swimming bias is incorporated , the hybrid model correctly predicts the emergence of streams and their evolution into spirals of the correct chirality for experimentally-reasonable initial cell densities and attractant concentration . Next we make a further step toward a complete model by incorporating growth of the patterning domain . The simulation starts when the colony begins to expand . As we indicated earlier , the biology of swimmer/swarmer differentiation and the biophysics of movement at the leading edge are poorly understood . Consequently , we here regard the advancing front as a source of swimmer cells and prescribe a constant expansion rate . Since we simulate from the very beginning of colony expansion , with no attractant in the petri dish , we take to be zero everywhere as an initial condition . The results of one computational experiment are shown in Figure 6 , in which the colony expands outward at a speed of , as observed in experiments ( Figure S1 ) , and the cells added in this process are swimmer cells . One sees that the early dynamics when the disk is small are similar to the results in Figure 4 on a fixed disk , but as the disk continues to grow the inner structure develops into numerous isolated islands , while the structure near the boundary exhibits the spirals . The juxtaposition in Figure 7 of the numerical simulation of the pattern at 5 hours and the experimental results shown in Figure 1 shows surprisingly good agreement , despite the simplicity of the model . This suggests that the essential mechanisms in the pattern formation have been identified , but others are certainly involved , since the experimental results show additional structure in the center of the disk that the current model does not replicate .
New experimental results reported here show that swimmer cells in the center of the colony stream inward toward the inoculation site , and form a number of complex patterns , including radial and spiral streams in an early stage , and rings and traveling trains in later stages . These experiments suggest that intercellular communication is involved in the spatial pattern formation . The experiments raise many questions , including what induces the inward movement of swimmer cells , why they move in streams , why radial streams quickly evolve into spiral streams , and finally , why all the spirals wind CCW . To address these we developed a hybrid cell-based model in which we describe the chemotactic movement of each cell individually by an independent velocity jump process . We couple this cell-based model of chemotactic movement with reaction-diffusion equations for the nutrient and attractant . To numerically solve the governing equations , a Monte Carlo method is used to simulate the velocity jump process of each cell , and an ADI method is used to solve the reaction-diffusion equations for the extracellular chemicals . The hybrid cell-based model has yielded biologically-based answers to the questions raised by the experimental observations . Starting with an estimate of the attractant level before the onset of the radial streaming as the initial value , we predicted the formation of radial streams as a result of the modulation of the local attractant concentration by the cells . It is observed in E . coli that ‘runs’ of single cells curve to the right when cells swim near a surface , and we incorporated this swimming bias by adding a constant angular velocity during runs of each cell . This leads to spiral streams with the same chirality as is observed experimentally . Finally , by incorporating growth of the patterning domain we were able to capture some of the salient features of the global patterns observed . The streams and spirals reported here share similarities with those formed in Dictyostelium discoideum , where cells migrate towards a pacemaker [49]–[52] , but there are significant differences . Firstly , the mechanism leading to aggregation is similar , in that in both cases the cells react chemotactically and secrete the attractant . However , since bacteria are small , they do a ‘bakery search’ in deciding how to move - detecting the signal while moving , and constantly modulating their run time in response to changes in the signal . In contrast , D . discoideum is large enough that it can measure gradients across it's length and orient and move accordingly [53] . Thus bacteria measure temporal gradients whereas amoeboid cells such as D . discoideum measure spatial gradients . In either case the cells respond locally by forming streams and migrate up the gradient of an attractant . However , spirals are less ubiquitous in D . discoideum , and when they form they can be of either handedness [54] , whereas in P . mirabilis , only spirals wound CCW when viewed from above have been observed , which emphasizes the importance of the influence of the cell-substrate interaction when cells swim close to the surface . Experiments in which the patterning occurs in an inverted petri dish lead to spirals with an opposite handedness when viewed from above , which further support our explanation . Our results imply that the spatial patterns observed in P . mirabilis can be explained by the chemotactic behavior of swimmer cells , and suggest that differentiation and de-differentiation of the cells at the leading edge does not play a critical role in patterning , but rather serves to expand the colony under appropriate conditions . A future objective is to incorporate a better description of the dynamics at the leading edge when more biological information is available . The spatial patterns reported here are also different from those observed in other bacteria such as E . coli or Bacillus subtilis . In the latter , fractal bacterial patterns have been observed [5] , [6] , and these patterns form primarily at the leading edge of the growing colony . There cell motility plays a lesser role and the limited diffusion of nutrient plays an important role in the pattern formation . In [11] , chiral growth patterns have been observed to form at the leading edge of Paenibacillus colonies with chirality depending on the concentration of agar in the medium . Those patterns were explained by introducing a phenomenological rotation to the tumbling of cells at the leading edge . However , the spiral streams we presented here form in the center of a growing colony , and the CCW chirality results from the physical property of bacterial swimming when they move close to a surface , namely , a CW individual swimming bias when observed from above [45]–[47] . Further experimental work is needed to validate our primary assumptions and to set the stage for incorporation of more detail into the model . A first step would be to definitively identify the primary attractant and the receptors for it , and to determine whether the primary attractant is also secreted by cells , as assumed here . If several are equally important the mathematical model for individual cells and the equations for the evolution of the attractants would have to be modified , but this poses no new mathematical or conceptual difficulties . Of course if several are involved there are entirely new ways in which the patterns can be influenced by manipulating the attractants . A second set of experiments would be needed to elucidate the behavior of individual cells and determine whether the run-and-tumble description must be modified . This has been done in detail and at great expense for E . coli , and would have to be repeated for Proteus . The third crucial assumption concerns the mechanism that leads to spirals of fixed chirality . The analysis that leads to our hypothesis for a rotational bias when swimming near a surface relies on the fact that the motion is at low Reynolds number , and therefore , that viscous effects dominate the motion . Accordingly , experiments in which the viscosity is manipulated would shed light on the validity of this assumption , since decreasing the viscosity will decrease the bias and reduce the curvature of the spirals , and conversely for increases in viscosity . Of course the experimental reality is more complicated than that which our model describes , and this can lead a set of significantly more complex experiments . For instance , the nutrient composition is very complex and nutrient depletion may occur at a later stage , such as during train formation . Further , cells may become non-motile for various reasons , and these factors may play a role in the stabilization of the ring patterns . Another important issue is the hydrodynamic interaction of the swimmer cells with fluid in the slime layer . When cell density is low and cells are well separated we can approximate their movement by independent velocity jump processes plus a swimming bias , but when the cell density is high the cell movement is correlated through the hydrodynamic interactions and this must be taken into account . This hydrodynamic interaction may be an important factor in the formation of the trains observed in experiments . In previous work the individual cell behavior , including the swimming bias , has been embedded in a continuum chemotaxis equation derived by analyzing the diffusion limit of a transport equation based on the velocity jump process [32] . The resulting equation is based on the assumption that the signal gradient is shallow and the predicted macroscopic velocity in this regime is linear in the signal gradient . A novel feature of the result is that the swimming bias at the individual cell level gives rise to an additional taxis term orthogonal to the signal gradient in this equation . However in the simulations of the patterns presented here we observe steep signal gradients near the core of the patterns and within the streams , and therefore in these regimes the assumptions underlying the continuum chemotaxis model are not valid . To illustrate the significance of this , we use the function as a measure of the signal gradient detected by a cell , and for each fixed spatial distribution of , we stochastically simulated the trajectory of 5000 cells with the same initial position and random initial velocity . We found , using least-squares fitting , that the mean , variance , and covariance of the displacement parallel and perpendicular to the gradient can be fit very well by a linear function , and we used these statistics to obtain the macroscopic drift and diffusion rate for each signal gradient chosen . In the simulations we assumed , without loss of generality , that is in the direction of the -axis , and took the initial positions to be . Then we computed the macroscopic drift asand the diffusion matrix Figure 8 compares the statistical results predicted by the cell-based model described above with the formula given in [32] , both in the absence of a swimming bias and when there is a bias , as in Figures 4 and 6 . We see that the continuum description given in [32] gives a good approximation for very small ( the shallow gradient assumption ) , but not for large . The statistical analysis of results from the cell-based model reveals saturation in the macroscopic velocity ( Figure 8B , E ) and gradient-dependent diffusion coefficients ( Figure 8A , D ) . When there is no bias , both and increase with the signal gradient ( Figure 8A ) and saturate for very large ( not shown ) , while the cross diffusion coefficient is essentially 0 ( Figure 8A ) . In contrast with this , if there is a swimming bias , the diffusion coefficients and first increase and then decrease before converging to a constant , while is small but nonzero for intermediate ( Figure 8C ) . These results are very different from the prediction of the continuum model shown in red lines in Figure 8 , where the predicted macroscopic velocity exceeds the cell speed in the presence of large signal gradients , and the diffusion of cells is isotropic with a constant coefficient . In addition , statistical analysis of the cell-based model also shows that when there is a swimming bias , the angle between the macroscopic velocity and the signal gradient depends nonlinearly on the magnitude of the signal gradient , in contrast to the prediction from the PDE in [32] ( Figure 8F ) . Thus the hybrid model developed herein successfully describes pattern formation in the presence of large gradients , whereas current continuum descriptions of cell motion do not . Further work is needed to connect the two descriptions in this regime .
To justify the model assumption that swimmer cells are chemotactic to an attractant they produce , we tested if swimmers in the center of the colony have the ability to move chemotacticly . Positive chemotaxis toward each of the common 20 amino acids was tested using the drop assay . Each amino acid was tested at the following concentrations: . 1 M , 10 mM , 1 mM , l0 , and 1 ( see Table 1 ) . Chemotaxis of swimmer cells towards single amino acids was also tested using 0 . 3% agar plates with different thickness of substrate layer ( 10 and 20 ml ) . Each amino acid was used in concentrations varying from 0 . 25 mM to 7 . 5 mM in both thicknesses of agar . The plates were point inoculated and placed in a humid chamber at room temperature for at least 20 hrs . Bacteria growing on 10 and 20 ml plates with 0 . 00l M of Aspartate , Methionine and Serine formed dense moving outer ring which we interpret as a chemotactic ring . Bacteria grown on all remaining amino acids produced colonies with the higher density at the point of inoculation and homogeneous cell distribution in the rest of the colony . In the implementation of the cell-based model , cell motion is simulated by a standard Monte Carlo method in the whole domain , while the equations for extracellular chemicals are solved by an alternating direction method on a set of rectangular grid points . In this appendix , we present the numerical algorithm in a two-dimensional domain with only one chemical - the attractant - involved . Each cell is described by its position , internal variables , direction of movement and age ( the superscript is the index of the cell ) . Concentration of the attractant is described by a discrete function defined on the grid for the finite difference method ( Figure 9A ) . We denote the time step by , the grid sizes by and . Since two components of the model live in different spaces , two interpolating operators are needed in the algorithm . is used to evaluate the attractant concentration that a cell senses . For a cell at , inside the square with vertex indices , , and , is defined by the bi-linear function: ( 5 ) where and are the area fractions ( Figure 9B ) . On the other hand , the attractant secreted by cells is interpolated as increments at the grid points by . Suppose during one time step , a cell staying at secretes amount of attractant , we then interpolate the increment of the attractant concentration at the neighboring grid points as follows: ( 6 ) We consider here a periodic boundary condition . The detailed computing procedure is summarized as follows . S1 . Initialization . S2 . For time step l ( initially ) , update the data of each cell . S3 . Compute the source term of the attractant due to the secretion by the cells using the interpolator where . S4 . Apply the alternating direction implicit method to the equation of the attractant:For the boundary grid points , use the periodic scheme . S5 . . If , repeat S2–S4; otherwise , return . | Bacteria frequently colonize surfaces and grow as biofilm communities embedded in a gel-like polysaccharide matrix , and when this occurs on catheters , heart valves and other medical implants , it can lead to serious , hard-to-treat infections . Proteus mirabilis is an enteric bacterium that forms biofilms on urinary catheters , but in laboratory experiments it can swarm over hard surfaces and form a variety of spatial patterns . Understanding these patterns is a first step toward understanding biofilm formation , and here we describe new experimental results and mathematical models of pattern formation in Proteus . The experiments show that swimmer cells in the center of the colony stream inward toward the inoculation site and in the process form many complex patterns , including radial and spiral streams , in addition to concentric rings . To explain these observations we develop a model that incorporates a chemotactic response of swimmers to a chemical they produce . The model predicts that formation of radial streams can be explained as the modulation of the local attractant concentration by the cells , and that the chirality of the spiral streams can be predicted by incorporating a swimming bias of the cells near the surface of the substrate . | [
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] | 2011 | Radial and Spiral Stream Formation in Proteus mirabilis Colonies |
Cellular signaling networks have evolved an astonishing ability to function reliably and with high fidelity in uncertain environments . A crucial prerequisite for the high precision exhibited by many signaling circuits is their ability to keep the concentrations of active signaling compounds within tightly defined bounds , despite strong stochastic fluctuations in copy numbers and other detrimental influences . Based on a simple mathematical formalism , we identify topological organizing principles that facilitate such robust control of intracellular concentrations in the face of multifarious perturbations . Our framework allows us to judge whether a multiple-input-multiple-output reaction network is robust against large perturbations of network parameters and enables the predictive design of perfectly robust synthetic network architectures . Utilizing the Escherichia coli chemotaxis pathway as a hallmark example , we provide experimental evidence that our framework indeed allows us to unravel the topological organization of robust signaling . We demonstrate that the specific organization of the pathway allows the system to maintain global concentration robustness of the diffusible response regulator CheY with respect to several dominant perturbations . Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters . Rather , we suggest that for a large class of perturbations , there exists an appropriate topology that renders the network output invariant to the respective perturbations .
All living cells rely on the capacity to respond to intra- or extracellular signals and have evolved a dedicated biochemical machinery to continuously sense , transmit , and process a variety of internal and environmental cues . A key requisite for reliable signal processing is the capability of living cells to keep the stationary intracellular concentrations of certain molecules , such as active signaling compounds , within tightly defined bounds – despite conditions of uncertainty and in the face of multiple perturbations . While the apparent insensitivity of key intracellular concentrations , and hence of cellular function , to detrimental influences is widely recognized as a salient property of cellular signaling , knowledge of the precise mechanisms underlying these instances of pathway robustness is still fragmentary [1]–[6] . Here , we report a simple , yet highly efficient , novel formalism that pinpoints the necessary architecture for concentration robustness in living cells . We assert and substantiate by mathematical proof and experimental evidence that certain classes of network architectures render the functional output of the network , as represented by a set of steady state protein concentrations , invariant to a large class of perturbations . Our approach emphasizes robustness as a structural property of a network as a whole , rather than as a consequence of parameter-tuning or individual positive or negative interaction loops [3] , [7] , and offers a novel paradigm to understand the topological organization of cellular signaling networks . Differing from earlier approaches , our framework accounts for perturbations of large magnitude and is not restricted to a particular class of network kinetics , such as mass-action systems [5] . Applications include the robustness of input-output relationships with respect to variations in total component concentrations , reaction parameters , abundances of common resources like ATP , RNA polymerases , and ribosomes , as well as detrimental effects of pathway crosstalk , and variations in temperature . Our focus is on perturbations whose time scales are slow compared to the intrinsic dynamics of the pathway .
To establish the mechanisms of robust signaling , we consider a multi input-multi output signaling network , whose temporal behavior is described by a set of ordinary differential equations for the state variables , , e . g . , , where the indices indicate different variables or reaction fluxes . The equations can be organized into the more compact form , ( 1 ) where denotes the stoichiometric matrix . The reaction fluxes are specified by functions that depend on the variables and a set of parameters . We require the existence of a – not necessarily unique – stationary state that obeys the steady state condition with . In the following , we assume that the functionality of the network is encoded in the steady state of a subset of output variables , defined as , whose concentration values depend on a set of intra- or extracellular signals . The remaining intermediate variables are defined by . The system is said to exhibit local concentration robustness with respect to a particular parameter if a sufficiently small perturbation in this parameter does not affect the stationary concentrations of the output variables , . Mathematically , the perturbation is characterized by the vector of logarithmic partial derivatives with elements , evaluated at the stationary state . As the main result of the work , we now seek to identify stringent conditions on the network architecture – rather than on kinetic parameters – such that the robustness property holds for perturbations of large magnitude . To this end , we first recall the conditions for local concentration robustness . Utilizing results from linear control theory , local robustness can be ascribed to two scenarios: Either the perturbation has no effect on any stationary concentration within the network . In this case , the vector is an element of a vector space spanned by the columns of a matrix – with being a basis of the right nullspace of the scaled stoichiometric matrix , defined such that . Or , more generally , the perturbation propagates through the network and affects the stationary concentration of some or all of the non-robust intermediate variables , albeit without affecting the set of output variables . In this case , it can be shown that the perturbation vector is an element of the joint vector space spanned by the columns of and the columns of a matrix . The latter matrix is given by the logarithmic partial derivatives of reaction rates with respect to the intermediate variables , with elements . We note that the elements of correspond to the kinetic orders or scaled elasticities of the reaction fluxes and attain integer values for the case of reaction networks that follow mass-action kinetics [8] . Taken together , a necessary and sufficient condition for local concentration robustness is therefore that the vector is an element of the vector space spanned by the columns of and , or equivalently , that the rank condition , ( 2 ) is fulfilled . Here , the notation denotes a concatenation of the columns of both matrices . To ascertain local concentration robustness the rank condition is evaluated at the particular stationary state . See Materials and Methods and Text S1 for details and proof . In general , local concentration robustness is not a sufficient condition to allow for robust signal processing in living cells . The fluctuations encountered by biological systems , such as variations in component concentrations arising from stochasticity in gene expression , are typically of large magnitude and cannot be described by local perturbations at a particular stationary state . Our aim is therefore to establish precise conditions for global concentration robustness . Specifically , a system is said to exhibit global concentration robustness with respect to a particular parameter if the stationary concentrations of the set of output variables is invariant with respect to perturbations in . Thereby , may take any value within a biophysically feasible perturbation set and is not restricted to small variations . To obtain a viable criterion to judge global concentration robustness , we therefore extract from the local vector space , spanned by the columns of , the largest subspace that does not depend on the choice of kinetic parameters , and hence , the specific stationary state . This subspace , denoted as the invariant perturbation space , defines the largest vector space that guarantees local robustness at any stationary state of the system . Consequently , a perturbation of increasing magnitude that is confined to the invariant perturbation space may gradually affect the intermediate variables , but does not affect the designated output variables . The condition for global concentration robustness is then given by , or , equivalently , as , where denotes a matrix whose columns span the vector space . We emphasize that the matrix and its associated vector space are independent of kinetic parameters and therefore represent a genuine structural property of any signaling network . Proof and an algorithm is relegated to Materials and Methods and the SI , here we only outline its construction using a simple example . To illustrate the construction of the invariant perturbation space , we consider the simple pathway shown in Figure 1 . Here , the output variable of the pathway is subject to strong fluctuations in its synthesis rate . Rather than aiming to suppress the detrimental perturbations , the pathway employs an intermediate variable that compensates perturbations and ensures global concentration robustness of . The pathway is described by two differential equations for the time-dependent behavior of the concentrations of and , respectively , ( 3 ) For brevity , and as the only assumption on the rate equations and kinetic parameters , we require that the pathway gives rise to a unique stationary state for each value of . To obtain insight about the concentration robustness of the variable with respect to , we construct the invariant perturbation space , derived from the concatenated matrix . The matrix is given by the logarithmic partial derivatives of reaction rates with respect to the intermediate non-robust variable . We obtain ( 4 ) where denotes the unknown state-dependent logarithmic partial derivative with respect to the variable . In general , the precise value of depends on the functional form of the rate equations , the value of the perturbation , and the kinetic parameters . The matrix can be constructed algorithmically from the stoichiometric matrix . We obtain , ( 5 ) where and denote the stationary flux values . To obtain a matrix representation of the invariant perturbation space , we now need to identify the largest parameter-independent subspace spanned by the columns of . To this end , we note that the vector space spanned by the columns of a matrix remains invariant under elementary matrix operations ( EMO ) , such as multiplication of a column by the same non-zero factor or the addition of an arbitrary multiple of one column to another . Applying a set of suitable EMOs , we obtain ( 6 ) We note that in this particular case , the invariant perturbation space is of the same dimension as the local vector space . In general , however , not all dimensions of the local space are retained , see Section III of Text S1 for an example . To test for global concentration robustness of the variable with respect to , we now have to evaluate the rank condition . The perturbation is characterized by the vector ( 7 ) where denotes the unknown state-dependent value of the logarithmic partial derivative . It can be straightforwardly ascertained that the rank condition for global concentration robustness is fulfilled , irrespective of the value of . Hence , the variable exhibits global concentration robustness with respect to perturbations in its synthesis rate . We note that our simple example is a well-known instance of robust perfect adaptation [9] , [10] . Biologically , the variable acts as an integrator , under the condition that the degradation rate of is independent of the concentration of itself . Utilizing our approach , the invariant perturbation space can be constructed algorithmically for any given reaction network . The condition for global concentration robustness can then be ascertained by a simple numerical test and does not require extensive computations or additional expert knowledge . To further illustrate the construction of the invariant perturbation space , we briefly consider the robustness of a canonical two-component system – one of the simplest and best-studied examples of robust signaling . Bacterial two-component systems typically consist of a membrane-bound sensor kinase that senses a specific stimulus and a cognate response regulator that modulates the signal response . Reliable functioning of two-component systems often requires that the output of the pathway , the concentration of phosphorylated response regulator as a function of an external stimulus , is not compromised by fluctuations in total protein concentrations of both components . The robustness of bacterial two-component systems with respect to such concentration fluctuations was investigated previously [11] , [12] . In particular , Batchelor and Goulian [11] identified that the principal mechanism for concentration robustness is due to a bifunctional histidine kinase that phosphorylates and dephosphorylates its cognate response regulator . Figure 2 depicts a simplified model of the respective system . The histidine kinase ( ) is phosphorylated by an external ligand . The phosphorylated kinase ( ) transfers the phospho-group to the unphosphorylated response regulator ( ) . The pathway output is the concentration of the phosphorylated diffusible response regulator ( ) . Importantly , dephosphorylation of the response regulator ( ) requires the participation of the bifunctional histidine kinase ( ) . Utilizing our approach , we seek to confirm that , in this case , the stationary concentration of is invariant to variations in the expression levels of both proteins . For brevity , we again consider a highly simplified system and focus on the construction of the invariant perturbation space . In particular , the formation of protein complexes is neglected and all phosphorylation reactions are assumed to follow mass-action kinetics . A solution of the full system , including an explicit account of conserved moieties , is provided in Text S1 ( Section VII ) . To obtain the invariant perturbation space , we first derive the matrix of logarithmic partial derivatives of reaction rates with respect to the non-robust variables , , and . We assume that both proteins are synthesized and degraded with unknown rates and – using the simplifying assumption that degradation ( or dilution ) acts only on the unphosphorylated forms and . The unknown partial derivatives of the degradation reactions are denoted as and , respectively . The remaining reactions are assumed to follow mass-action kinetics , resulting in partial logarithmic derivatives of unit value . Specifically , the phosphorylation rate is dependent on the concentration of the unphosphorylated form , the phosphotransfer rate depends upon the concentration of and , and the dephosphorylation rate finally depends on the concentration of the phosphorylated response regulator , as well as the unphosphorylated form of the bifunctional kinase . The matrix is given in Figure 2B . As the next step , we need to identify the nullspace of the scaled stoichiometric matrix . The nullspace of the unscaled stoichiometric matrix is readily available using standard tools of linear algebra . The representation of the unscaled nullspace is subsequently scaled with the unknown steady state reaction rates , such that , , and . A representation of the scaled nullspace is provided in Figure 2B . Taken together , we again obtain the invariant perturbation space as the maximal subspace spanned by the columns of independent of kinetic parameters or steady state reaction rates . A matrix representation of the invariant perturbation space is given in Figure 2C . We assume that the system is perturbed by unknown variations in the synthesis rates of both proteins , and , respectively . The corresponding partial derivatives with respect to unknown perturbations are denoted as and and shown in Figure 2C . To ascertain global concentration robustness of , we confirm that the rank condition is indeed fulfilled . Hence , the output of the pathway , the steady state concentration of , is invariant to perturbations in the synthesis rates of both components . We note that , in general , our approach does presuppose that the system gives rise to a biologically feasible steady state solution for . This requirement usually entails additional constraints on the possible reaction rates and kinetic parameters . For example , robustness of is only feasible under the condition that the total expression of the response regulator exceeds the steady state solution for . Below we present a generalization of the rank condition to account for additional constraints on molecule concentrations ( see also Text S1 , Section VIII ) . Our approach is applicable to a variety of different scenarios , including several special cases which are discussed in the following . In particular , our approach relies on an interpretation of the elements of the matrix – the logarithmic partial derivatives of reaction rates with respect to the intermediate variables . For typical biochemical rate equations , these partial derivatives are nonlinear functions of kinetic parameters and therefore usually represent unknown and state-dependent quantities . However , as demonstrated above , our approach is still applicable in such a situation and does not require extensive knowledge of the functional form of the rate equations . In the most general case , each logarithmic partial derivative is represented by an unknown non-zero value within the matrix . The resulting invariant perturbation space is required to be independent of these unknown derivatives . Hence , the invariant perturbation space is predominantly a structural property of the network and is identical for structurally equivalent networks . See Text S1 for details . However , in some cases the elements of the matrix can be constraint further , owing either to particular functional forms of the rate equations or to simplifying assumptions that allow to approximate more complicated rate equations . An example of the former are generalized mass-action ( GMA ) kinetics of a reaction rate , ( 8 ) For GMA kinetics , the partial logarithmic derivatives correspond to the exponents and are often considered to be constant quantities . Consequently , the partial logarithmic derivatives may be represented as constant entries within the matrix . In this case , the invariant perturbation space is particularly straightforward to obtain . As an example of simplifying assumptions , we note that complex rate equations are often approximated by more simple equations corresponding to specific kinetic regimes . In particular , a Michaelis-Menten equation can be approximated by a mass-action term or a constant for substrate concentrations far below or far above the Michaelis constant , respectively . In this case , the logarithmic partial derivative is approximately constant or zero , respectively . However , any result from applying the criterion for global concentration robustness is only valid as long as the assumptions underlying the approximation are fulfilled . As yet , we have only considered reaction networks in the absence of mass-conservation relationships or conserved moieties . However , often the total concentration of some compounds can be considered as approximately constant over the relevant time-scales , giving rise to additional dependencies between variables . In this case , the system of differential equations for the independent state variables , is augmented by a set of dependent state variables , whose values are determined by a set of mass conservation equations . The full system of equations governing the time evolution of the system is ( 9 ) ( 10 ) with the vector denoting the total concentration of each molecular component . The matrix denotes a link matrix and usually consists of integer elements . To incorporate these dependencies within our approach , we must modify the definition of the matrix to account for the logarithmic partial derivatives with respect to the dependent variables . See Text S1 for details . Using the augmented matrix , our approach proceeds as described above . As a corollary , we then obtain a simple criterion to judge global concentration robustness with respect to perturbations in conserved total concentrations [5] , [6] , see Text S1 ( Section VII . B ) . Our approach differs from a number of previous approaches to investigate robustness of biochemical reaction networks [1] , [5] , [6] , [13] . The formalism is not restricted to systems described by mass-action kinetics , but is applicable a wide range of ODE-based descriptions of biochemical networks . Likewise , we do not focus on specific types of perturbations , such as variations in conserved moieties [5] or temperature [13] . Rather , our approach is applicable to any perturbation that can be described by a vector of partial derivatives of reaction rates – of which variations in conserved moieties , as well as of temperature are particular examples . We also mainly envision a scenario , where the perturbations are slow compared to the intrinsic fluctuation-compensation dynamics of the pathway . In particular , we consider the steady state of a selected subset of variables to represent the robust output of the system . Transient fluctuations in the vicinity of this state are not considered . However , the scenario described in this work indeed holds for many instances of cellular robustness . For example , in the case of gene expression noise , the observed fluctuations in expression levels are usually at least an order of magnitude slower than the phosphorylation dynamics in subsequent signaling pathways . Hence such fluctuations can be compensated by post-translational mechanisms – as described within this work . Similar arguments apply for several dominant fluctuations typically encountered by cellular signaling pathways , such as variations in temperature or abundance of common resources like ATP . To substantiate the explanatory power achieved by an interpretation of a complex cellular signaling network in terms of its associated invariant perturbation space , we now consider the robustness of the E . coli chemotaxis pathway . The topology of the pathway is depicted in Figure 3 . The pathway responds to changes in concentrations of chemoeffectors such as certain amino acids or sugars by altering the phosphorylation state of the diffusible response regulator CheY . The concentration of free phosphorylated CheY ( ) – the central output quantity of the pathway – then determines swimming behavior of the cell . Robust and precise regulation of is a prerequisite for high chemotaxis efficiency and is maintained in the face of multifarious perturbations , most notably ATP availability , stochasticity in component abundance [14] , and receptor cluster assembly [15] , [16] . However , seemingly contradicting its functional objective , the pathway is rather sensitive to variations in the expression of some of its constituent proteins . For example , it was shown that a two-fold overexpression of CheZ or CheY levels already result in an 50% decrease of experimentally observed chemotactic performance , as determined by the size of swarm rings on soft agar plates [17] . To reveal the mechanisms underlying the remarkable robustness that nonetheless allows reliable functioning of the pathway , we construct the invariant perturbation space as described above . The concatenated matrix is obtained by considering the stoichiometric matrix and the kinetic dependencies shown in Figure 3 . See SI ( Section V ) for details of the derivation . A parameter independent representation of the invariant perturbation space is shown in Figure 4A . To investigate the robustness of the pathway , we first consider changes in chemoeffector concentration ( L ) , perturbations in the expression of CheA ( A ) and CheW ( W ) , as well as variations in receptors ( T ) and ATP availability ( ATP ) . The corresponding perturbation vectors are shown in Figure 4B . In each case , the corresponding perturbation vector is an element of the invariant perturbation space and the rank condition for global concentration robustness of is fulfilled . Hence , the diffusible response regulator indeed exhibits global robustness of its stationary concentration with respect to these five highly detrimental influences . Next , we consider changes in the expression of the individual proteins CheR ( ) , CheB ( ) , CheY ( ) , and CheZ ( ) . The corresponding perturbation vectors are given in Figure 4C . As can be ascertained by inspection of the rank condition , the respective perturbation vectors are not elements of the invariant space – in good agreement with the rather high sensitivity exhibited by the pathway in response to variations in the expression of these proteins [17] . Nonetheless , the observed total concentrations of CheR , CheB , CheY , and CheZ are not “fine-tuned” and are known to exhibit considerable variability under various conditions . To explain this alleged paradox , we have to take the sequential arrangement of genes into operons , as shown in Figure 3B , into account . A closer inspection of Figure 4 then reveals that perturbations that arise from concerted fluctuations in protein concentrations , induced by stochastic synthesis of meche operon transcripts , are within the invariant perturbation space . And , indeed , coupling of expression levels of chemotaxis proteins adjacent on an operon has been experimentally shown to positively correlate with chemotactic efficiency and to underlie active selection during chemotactic spreading on soft agar plates [18] . Generalizing from this example , we expect that gene organization into operons and expression from polycistronic mRNA is a generic , evolutionary driven , mechanism to alleviate detrimental effects of stochasticity in gene expression . In the context of our framework , coupling of expression on the transcriptional [14] and translational level [18] , reduces the effective dimensionality of a perturbation , thereby enabling an invariant perturbation space of lower dimension to compensate and counteract the detrimental effects of fluctuations . In this sense , strong transcriptional and translational coupling is closely related to the robustness conveyed by bifunctional enzymes [5] . For the E . coli chemotaxis pathway strong coupling of genes expressed from one operon is evident in cells expressing yellow and cyan fluorescent protein fusions to CheY and CheZ , respectively , from one bicistronic plasmid construct , as shown in Figure 5A [14] , [19] . The striking invariance of the pathway output upon a seven fold concerted increase in the transcriptional activity of the chemotaxis operons following the deletion of the anti sigma factor FlgM is shown in Figure 5B [14] , [19] . As argued previously [20] , the benefits of co-variation to reduce the effective dimensionality of perturbations are likely to confer a selective advantage strong enough to drive the assembly of genes into operons . Our results also highlight the functional importance of seemingly redundant or insignificant interaction characteristics , whose functional relevance is difficult to ascertain without an appropriate theoretical framework . A striking example is the catalyzed dephosphorylation of CheY by CheZ , as opposed to the uncatalysed dephosphorylation of CheB . While such a difference often seems extraneous to reliable signal transduction , such differences also shape the invariant perturbation space and are therefore crucial to achieve robust signal processing . A further example of a relevant interaction characteristic is the competitive binding of CheY and CheB to CheA , which results in a phosphotransfer rate to CheB that scales as . While not fine-tuned on the parameter level , this qualitative dependence is a prerequisite for robustness of the pathway output and in excellent agreement with experimental findings [21] . In this sense , our approach also offers a theoretical framework to investigate the functional relevance of given reaction characteristics – beyond their role in straightforward signal transmission . The interpretation of a complex cellular signaling network in terms of its associated invariant perturbation space has profound implications for our ability to understand and eventually rationally engineer robust biological circuits . There is increasing evidence that the utilization of post-transcriptional noise compensatory networks is a widespread mechanism in prokaryotic signaling . Experimentally ascertained examples include instances of two-component systems [1] , [11] , [12] , the regulation of the glyoxylate bypass [22] , and the sporulation network of B . subtilis [20] . In each case , an evolved network topology relegates potentially detrimental fluctuations in compound concentrations to its associated invariant perturbation space – rather than utilizing an expensive machinery to fine-tune native expression levels . We expect that similar mechanisms will provide an indispensable backbone for synthetic biology . Guided by the algorithmic construction of the invariant perturbation space , a key strategy for synthetic biology is to either maximize the invariant perturbation space by rationally rewiring the specificity of protein interactions [23] , [24] , or correlating perturbations among components , by placing genes on polycistronic mRNA or by building fusion constructs – in each case circumventing the need to fine-tune parameters that are experimentally hard to control . Our algorithm is applicable to large systems and requires only qualitative information on kinetic interactions . Our results allow us to clarify several long-standing issues relating to the emergence of cellular robustness . In particular , we hypothesize that the ubiquitous existence of puzzling , seemingly redundant , interaction loops that characterize our current understanding of cellular pathways is deeply rooted in as yet unrecognized mechanisms to counteract functional fragilities [10] , [25] . In this sense , an interpretation of signalling architecture in terms of its invariant perturbation space offers a novel paradigm to understand cellular robustness , with the prospect to rationally engineer robust signaling circuits or target cellular defects .
In the following , we outline the conditions for local concentration robustness , as stated in Eq . ( 2 ) . We employ a logarithmic expansion of the stationary form of Eq . ( 1 ) , , with , to linear order in a perturbation and the resulting changes in the state variables , ( 11 ) with denoting a square matrix with entries on the diagonal . The expansion coefficients are ( 12 ) The relative perturbation and its response are defined as , , and . In the absence of the condition for robustness of the pathway output , , the expansion Eq . ( 11 ) has a unique solution for that quantifies the local linear response to a sufficiently small perturbation in parameters . The existence of the solution is guaranteed by the requirement that the Jacobian of the system is of full rank and hence invertible , implied by the dynamic stability of the considered steady state . Similar consideration are extensively utilized within , for example , Metabolic Control Analysis [8] , [13] , [26] , [27] . However , the requirement of concentration robustness , , removes the degrees of freedom that correspond to ( changes in ) the output variables . In this case , Eq . ( 11 ) translates into the condition ( 13 ) In general , Eq . ( 13 ) is overdetermined , that is , no solution exists and the condition cannot be fulfilled . Eq . ( 13 ) has a unique solution if and only if at least one of the following two conditions holds: Either the columns of the matrix are elements of the right nullspace of the matrix , spanned by the columns of the matrix . In this case , we obtain and , necessarily , . Or , the columns of the matrix are linearly dependent on the columns of the matrix . In mathematical terms , these two conditions can be summarized in the equation ( 14 ) Here , the columns of span the right nullspace of , such that . The notation denotes a concatenation of the columns of the matrices and , as described in the main text . See also SI ( Sections II and IV ) for a rigorous derivation . In the following , we outline the formal definitions and proof for global concentration robustness . For conciseness , we consider only generalized mass action ( GMA ) networks without conserved moieties . The general case , including a formal derivation of the conditions for global concentration robustness , is described in SI , Section IV . The biochemical network is defined as in Eq . ( 1 ) . We consider a perturbation that takes values in a physically reasonable , connected set . For a GMA network , the reaction rates are given by for reaction rates affected by the perturbation and for reaction rates not affected by the perturbation . The concentration vector is split into as described in the main text . The network is assumed to have a perturbation-dependent steady state which is asymptotically stable for all in a physically reasonable , connected perturbation set . The property of global concentration robustness is then formally defined as follows: For any values of the reaction rate parameters and any choice of the functions , the steady state output concentration vector is constant over . The global invariant perturbation space as discussed in the main text for a GMA network is given by , where denotes the image or range of the matrix . Thereby , are the columns of the matrix with elements , i . e . the logarithmic derivatives of the reaction rate vector with respect to , and is a matrix whose columns span the space of the vectors which are in the kernel of for all in the kernel of . To obtain a condition for global concentration robustness , we consider the vectors whose elements are zero whenever the reaction rate is not affected by the perturbation . If all such vectors are element of the space , then the network has global concentration robustness . Conversely , if there exists such a which is not in the space , then there exists rate parameters and functions for which the steady state output concentration is not constant over , and thus the network does not have global concentration robustness . Computationally , the condition can be tested by the rank condition , where is any matrix whose columns span the space . The signal transduction of the E . coli chemotaxis pathway can be described to good accuracy by the interplay of the core components , the methyl accepting chemoreceptors ( Tar , Tap , Tsr , Trg ) , the methyltransferase CheR , the methylesterase CheB , the response regulator CheY and its designated phosphatase CheZ ( see Box 1 ) . The total concentrations of these proteins are approximately , , , , , , and M . The concentration includes all receptors where CheR and phosphorylated CheB can bind to with high affinity , via a pentapeptide sequence at the carboxyl termini of the Tar and Tsr receptors . The set of mass action equations that determine the phosphorylation level of free diffusible response regulator proteins , , are listed below . In the following , we consider the stationary case of the chemotaxis equations . We thereby employ the approximations as , , as , and . The simplified set of stationary equations read ( 22 ) ( 23 ) ( 24 ) ( 25 ) where we have resolved the complexes and and introduced the stationary functions and as defined above for time independent mean methylation level and fixed ligand concentration . A derivation of the entries in Figure 4 is provided in Text S1 . | Cellular signaling networks have to function reliably and with high fidelity in an uncertain environment . In this paper , we investigate the topological principles to achieve such robust signal processing in living cells . Specifically , we identify the topological organizing principles that enable a signaling network to keep the stationary intracellular concentrations of certain molecules , such as active signaling compounds , within tightly defined bounds – despite conditions of uncertainty and in the face of multiple perturbations . We demonstrate that an appropriate topological organization renders the output of the pathway invariant against a large class of possible detrimental fluctuations , such as changes in energy states or total protein concentrations . Furthermore , we show that the topological requirements for robust signal processing can be formalized in terms of a linear vector space , denoted as invariant perturbation space , that predicts the robustness properties of the network . Constructing this invariant perturbation space for the Escherichia coli chemotaxis pathway reveals that the pathway is indeed invariant with respect to most dominant perturbations that would otherwise significantly hamper information transmission . Our framework provides a counterpoint to the hypothesis that cellular function relies on an extensive machinery to fine-tune or control intracellular parameters . | [
"Abstract",
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"biotechnology",
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] | 2011 | Robust Signal Processing in Living Cells |
When colonising host-niches or non-animated medical devices , individual cells of the fungal pathogen Candida albicans expand into significant biomasses . Here we show that within such biomasses , fungal metabolically generated CO2 acts as a communication molecule promoting the switch from yeast to filamentous growth essential for C . albicans pathology . We find that CO2-mediated intra-colony signalling involves the adenylyl cyclase protein ( Cyr1p ) , a multi-sensor recently found to coordinate fungal responses to serum and bacterial peptidoglycan . We further identify Lys 1373 as essential for CO2/bicarbonate regulation of Cyr1p . Disruption of the CO2/bicarbonate receptor-site interferes selectively with C . albicans filamentation within fungal biomasses . Comparisons between the Drosophila melanogaster infection model and the mouse model of disseminated candidiasis , suggest that metabolic CO2 sensing may be important for initial colonisation and epithelial invasion . Our results reveal the existence of a gaseous Candida signalling pathway and its molecular mechanism and provide insights into an evolutionary conserved CO2-signalling system .
Candida albicans is the predominant fungal pathogen of humans . In healthy individuals C . albicans resides as a commensal of the gastrointestinal , oral and vaginal tracts . C . albicans can cause superficial infections which , although not life threatening , provide discomfort to the individual and require treatment with antifungals which is a constant drain on hospitals resources . However , C . albicans infections are life threatening when the individual's immune system becomes compromised as a result of age , cancer , chemotherapy hospitalisation and AIDS . Under these circumstances superficial infections may readily develop into systemic disease where mortality rates are reported to be up to 40% , which is higher than those for most bacterial infections [1] , [2] , [3] . For example , oropharyngeal candidiasis is common in patients with haematological malignancies ( up to 60% ) and those undergoing radiotherapy [4] , [5] , [6] . Here , a few fungal cells develop into biomasses measuring several millimetres in diameter that penetrate and invade the underlying tissue , eventually leading to dissemination of Candida into the blood stream and subsequently systemic infection [7] . Development from superficial infection to invasive disease is mediated by many well characterised virulence factors including morphological transition . C . albicans can exist in yeast , pseudohyphal and true hyphal growth forms , all of which are important for the virulence of the organism [8] . Yeast cells are thought to be essential for growth and dissemination [9] , while the hyphal forms are essential for invading mucosal membranes [9] . This morphological transition is mediated by host environmental cues including temperature , pH , serum , O2 , and CO2 , which the pathogen encounters during disease progression [5] , [10] , [11] . The virulence-associated morphological transitions of C . albicans are largely controlled through the secondary messenger cAMP . In C . albicans , cAMP is synthesised by the fungal adenylyl cyclase ( AC ) , Cyr1p [12] , a member of the Class III nucleotidyl cyclase family [13] . Activity of Cyr1p governs most processes essential to C . albicans virulence including tissue adhesion followed by the invasion of the underlying host-barriers , and biofilm formation [14] . C . albicans AC activity is subject to both positive and negative regulation , with an increasing number of molecules directly interacting with specific domains of the protein [10] , [15] , [16] . For example , bacterial peptidoglycan stimulates Cyr1p via the enzyme's leucine-rich-region [16] , and CO2/HCO3− directly activates the Cyr1p C-terminal catalytic domain [10] . These forms of regulation enable C . albicans to recognise and respond ( via filamentation ) to specific host environmental conditions during disease progression . In addition to host environmental cues , the morphological transition of C . albicans is also regulated by soluble chemical mediators , termed quorum sensing molecules ( QSMs ) . QSMs are secreted into the environment by a variety of microorganisms [for recent reviews see 17] , [18] , and upon reaching threshold concentrations , impact on microbial behaviour by influencing expression of virulence determinants [19] . QSMs including the self-generated sesquiterpene farnesol [20] and 3-oxo-C12 homoserine lactone ( HSL ) secreted by Pseudomonas aeruginosa [21] inhibit C . albicans filamentation though cAMP dependent signalling cascades [22] . Further to soluble chemical mediators , volatile compounds can also act as signalling molecules . For example , in Saccharomyces cerevisiae , nutrient limited yeast cells release volatile ammonia , which when sensed by another colony inhibits its growth in the direction of the signal [23] . CO2 is a volatile gas that has recently been described as a predominant regulator of C . albicans virulence factors and has been shown to effect the virulence of other microbial species [24] , [25] . In C . albicans CO2 functions in two processes key to pathogenicity , one metabolic and the other cell signalling to promote filamentation [10] . In biological systems CO2 is maintained in equilibrium with its hydrated form , HCO3− , via the actions of carbonic anhydrase . HCO3− is required for metabolism , but when at high concentrations HCO3− directly activates adenylyl cyclase increasing cytosolic cAMP and promoting filamentation [10] . To date , only the effects of high ( 5% ) exogenous CO2 concentrations have been investigated in microbial species . However , microbes continuously secrete metabolically generated CO2 into their immediate microenvironment at levels perceived to be lower than 5% . Here , we investigate the effects of self generated CO2 on pathogenicity associated traits of C . albicans . Previously we identified the carbonic anhydrase , Nce103p , as being essential for growth under CO2 limiting conditions [10] . Now we explore a new application of the mutant strain Δnce103 as a CO2 biosensor to report on CO2 concentrations within fungal biomasses . Using our CO2-dependent bio-sensing strain , we demonstrate that build-up of self-generated , metabolic CO2 occurs in a fungal population . Furthermore , we show that CO2 mediates its effects as a hierarchy , with low concentrations of CO2 functioning to fill metabolic demand , then once CO2 exceeds a critical threshold , it promotes filamentation and subsequent surface invasion of the pathogen . We show that microbial CO2 , like environmental CO2 , is sensed by the AC catalytic domain and identify a bicarbonate receptor site in Cyr1p .
CO2 is generated during metabolism and acts as an important cellular signalling molecule in many organisms . CO2 influences microbial virulence and organisms behaviours such as mating , feeding or ventilation [26] . We confirmed that , when grown under diffusion-limiting conditions ( i . e . , closed systems ) , C . albicans accumulated self-generated CO2 ( Figure 1 A , B ) . Next we asked whether self-generated CO2 could be utilized by C . albicans to meet the organism's growth requirements . In normal atmospheres , ( 0 . 03% CO2 ) the C . albicans carbonic anhydrase ( CA ) , Nce103p , is essential for catalyzing the hydration of CO2 to bicarbonate to meet metabolic demands . Therefore , in ‘open’ systems ( i . e . , under the 0 . 03% CO2 in air ) , deletion of NCE103 results in a depletion of bicarbonate levels which inhibits growth . However , at elevated CO2 concentrations ( such as 5% CO2 experienced by C . albicans when inside an infected mammalian host ) there is sufficient CO2 spontaneously hydrated to bicarbonate to meet the metabolic requirements restoring growth ( Figure 2A ) . Therefore , the carbonic anhydrase mutant ( TK1; Δnce103 ) can only grow in environments with elevated concentrations of CO2 [10] , and as a result , functions as a CO2 bio-indicator . The Δnce103 bio-indicator strain failed to grow when co-incubated with wild type ( SC5314; WT ) cells in an open system , but grew in the presence of WT C . albicans in a closed system without exogenously supplied CO2 ( Figure 2B ) . Furthermore , incubation of surplus ( 10 , 000 CFUs/plate ) Δnce103 , on its own , in closed but not open systems also restored the growth of Δnce103 ( Figure S1 ) , suggesting that in closed systems the elevated CO2 levels are sufficient to complement the growth of Δnce103 . To confirm that it was volatile CO2 generated by the WT strain which restored growth to the Δnce103 CO2 bio-indicator strain , we included hydroxide into the closed system , which specifically traps CO2 in the form of carbonate [27] . Solid sodium hydroxide interfered with the growth of the Δnce103 CO2 bio-indicator strain , but not WT ( Figure 2C ) . The diminished growth in the presence of sodium hydroxide is most likely caused by CO2 trapping and not oxygen depletion , as oxygen levels are not influenced by the CO2 trap . Taken together , these results reveal that metabolically generated CO2 can provide sufficient HCO3− to meet the metabolic demands of C . albicans , and that this CO2 can be provided in the form of a volatile signal from neighbouring colonies . Consistent with the idea that the CO2 generated by WT C . albicans is supplying CO2/HCO3− to meet the metabolic demand of the Δnce103 bio-indicator strain , rescue was independent from the cAMP signalling system , as the Δcyr1-Δnce103 strain ( RH12 ) was also complemented when incubated at elevated CO2 ( Figure 2A ) . These data suggest that there is sufficient CO2 generated during normal metabolism of WT C . albicans to support the growth of the Δnce103 bio-indicator strain , as long as diffusion of the generated CO2 is limited . We next asked whether CO2 levels sufficient for signalling would build-up within a fungal biomass . To address this question , we grew the Δnce103 CO2 bio-indicator strain on its own , or mixed with equal numbers of DAY286 , a Δhis1 strain which is wild type for carbonic anhydrase and adenylyl cyclase , in an open system to specifically test whether CO2 accumulation could occur between cells growing in the same biomass . Using the different auxotrophic tags ( HIS+ and HIS− ) to distinguish the two strains after incubation within mixed biomasses , we were able to directly test whether metabolically generated CO2 from DAY286 could complement the growth of Δnce103 , while Δnce103 on its own would be restricted in growth . Co-incubation of Δnce103 with DAY286 enhanced the recovery of Δnce103 600-fold ( p = >0 . 0001 ) when compared to incubation of the CO2 bio-indicator strain on its own ( Figure 3 ) . To exclude that DAY286 was able to fill the metabolic demands of Δnce103 by providing other metabolic intermediates other than CO2 , the Δnce103 strain was also co-incubated with a surplus ( 1×106 cells ) of heat-killed DAY286 cells . However , co-incubation of Δnce103 and heat-killed DAY286 did not enhance the recovery of Δnce103 compared to incubation of the CO2 bio-indicator strain alone ( Figure 3 , p = >0 . 0001 ) , suggesting that within a fungal biomass , even in an open system , there is an accumulation of metabolic CO2 sufficient to promote the growth of Δnce103 . These data also prove that the carbonic anhydrase is essential because it ‘captures’ metabolically generated CO2 as HCO3− which is needed to meet metabolic requirements of cells deep within the colony . CO2 is not only required for metabolism , but it also acts as a signal for cAMP-dependent filamentation of C . albicans . Therefore , we sought to determine whether metabolically generated CO2 could act within a biomass to modulate morphology . To test whether C . albicans produces sufficient CO2 to affect filamentation , we incubated wild type cells under open and closed conditions . In open systems , no colonies filamented , while under closed conditions , we observed changes in colony morphology after 48 hours . Plating 500 CFUs produced extensive filamentous colonies ( Figure 4A ) . Microscopic analysis of resuspended colonies confirmed that the majority of the cells filamented in the closed system ( forming a highly interwoven mass of cells resistant to mechanical stress; Figure 4A ) . As C . albicans hyphal induction is critically dependent on cAMP signalling cascades [12] , we tested a strain deficient for adenylyl cyclase CR276-CTRL ( RH20; Δcyr1 ) in our open and closed systems . The Δcyr1 strain did not show any changes in colony morphology , even when incubation periods were extended to 72 hours to account for its known reduced growth rate ( Figure 4B ) . Additionally , altered morphology was independent of carbonic anhydrase , as Δnce103 , but not Δcyr1-Δnce103 , formed filaments in the presence of 5% CO2 ( Figure 4C ) . Interestingly , the extent of filamentation of the WT strain was biomass dependent . At 48 hours , plating in the presence of 50 CFUs generated wrinkled colonies ( Figure 4D ) , which were not fully filamentous . Addition of the hydroxide trap into the closed system inhibited the morphological transition observed previously ( Figure 4E ) . Furthermore , microscopic inspection of WT colonies , after co-incubation with Δnce103 in closed environments , confirmed that the colonies were smooth , round , yeast colonies , similar to those observed in the open system ( data not shown ) . These observations suggest that the Δnce103 strain acts as a CO2 sink removing the majority of the gas from the system . Therefore , C . albicans produces CO2 which affects morphology , and cAMP is essential for the observed morphological effects . Directly testing the in vivo relevance of CO2 chemosensing would be greatly facilitated by an adenylyl cyclase variant with specifically diminished CO2 sensitivity . Previously we have shown that CO2/HCO3− activates the catalytic domain of the fungal adenylyl cyclase , Cyr1p [10] , confirming that this Class III AC belongs to the bicarbonate-responsive soluble AC ( sAC ) subfamily [13] , [28] . Structural studies and in vitro work on mutated bacterial sAC-family enzymes indicated a mechanism for bicarbonate regulation , along with a potential bicarbonate binding site [29] , [30] . However , it remains to be shown whether the mechanism of activation and potential binding site generally apply to sAC-like enzymes , in particular from eukaryotes , and whether they are responsible for the in vivo effects of CO2 on AC activity . Using sequence alignments of Class III ACs , we generated a homology model of Cyr1p and identified the Cyr1p site corresponding to the proposed bacterial CO2 receptor site ( Figure 5A ) [13] , [29] . A lysine residue [29] , Lys1373 in C . albicans Cyr1p , would be a key interaction partner for bicarbonate in this receptor site . Class III ACs are dimers with shared active sites – i . e . residues from both monomers contribute to each active site – so that only the dimer can display activity . In contrast to ‘heterodimeric’ Class III ACs , which have one active site and a second , related-but-degenerated , ‘regulatory’ site in their dimer interface , homodimeric Class III ACs , like Cyr1p , have two identical catalytic sites in their dimer interface . In these ACs , it is believed that both sites can act as active or as regulatory sites . The putative bicarbonate-interacting lysine residue is strictly conserved in both “active’ and ‘regulatory’ sites ( for example , in mammalian sAC , Lys334 , would be the corresponding residue in the active site ) . In active sites , the conserved lysine at this position is essential for substrate binding [13] . Because Lys1373 of Cyr1p should be essential for substrate binding in at least one of the two sites formed at the homodimer interface , we predicted CYR11373 would be inactive on its own . We integrated full-length Cyr1p with Lys1373 point mutated to alanine , under the control of the TEF2 promoter , into an adenylyl cyclase null , generating strain CR276-CYR11373 ( RH22; cyr1/cyr1:pTEF2 CYR11373 ) . CR276-CYR11373 was refractory to both CO2 and serum induction of filamentation , behaving similarly to the vector-control strain CR276-CTRL ( RH20; Figure S2 ) . Thus , CYR11373 homodimers encode a non-functional AC . To specifically test the role of this lysine in the bicarbonate activation of Cyr1p and to generate an AC with a selective defect in its bicarbonate responsiveness , we generated strains containing mutant/WT heterodimers . Due to the dimeric architecture of Class III ACs , one wild type Cyr1p monomer could interact with one Cyr1p1373 monomer , allowing basal AC activity , but preventing bicarbonate stimulation due to disruption of the bicarbonate interacting site in the second ‘regulatory’ centre ( as described above ) . The point mutated Cyr1p was integrated into a strain expressing wild type adenylyl cyclase , generating strain CAI4-CYR11373 ( RH25; CYR/CYR1/pTEF2 CYR11373 ) . Consistent with the expected heterodimer formation and with specific interruption of CO2-induced cAMP formation , CAI4-CYR11373 , but not the control strain CAI4-CYR1 ( RH24; CYR1/CYR1/pTEF2 CYR1 ) , displayed a signal-specific defect to the filamentation inducing cues ( Figure 5B , C ) , despite the two strains expressing comparable levels of CYR1 , ( Figure S3 ) . CAI4-CYR11373 filamented in response to serum , but much less in response to CO2 , while the control strain expressing wild type AC , CAI4-CYR1 , filamented equally in response to both serum and CO2 . The incomplete suppression of CO2-induced filamentation in CAI4-CYR11373 is consistent with the statistical formation of homodimers and heterodimers between the co-expressed wild type and variant protein , which will also yield fully CO2-sensitive wild type homodimers . To confirm that the observed phenotype is specific to the destruction of the bicarbonate binding site in the CYR11373 heterodimers , rather than a general influence on AC activity , two additional point mutations , that inactivate Cyr1p stimulus-independent , were constructed . Asp1334 and Asp1377 ( involved in active site Mg2+ binding ) were mutated to Ala and also expressed under the control of the TEF2 promoter . Integration of these constructs into the adenylyl cyclase mutant ( CR272-CYR11334; RH26 , and CR276-CYR11377; RH27 ) confirmed that the proteins were catalytically inactive ( Figure S2 ) . However , expression of these inactive proteins in CAI4 ( containing two genomic copies of CYR1; CAI4-CYR11334; RH28 , and CAI4-CYR11377; RH29 ) did not perturb hyphal induction in response to 5% serum or elevated CO2 , as Lys1373 did ( Figure 5B , C ) . Thus , CAI4-CYR11373 shows a specific disruption of CO2-induced filamentation and therefore , the identified lysine , which likely acts as bicarbonate binding site , serves as physiological CO2 “switch” in Cyr1p and perhaps in all related sAC-type enzymes . We next directly tested whether CO2 is the volatile messenger inducing Candida filamentation by taking advantage of the CO2 insensitive mutant strain CAI4-CYR11373 . CAI4-CYR11373 showed an attenuated response in the closed system , with 30% ( ±9% , P = 0 . 001 ) of cells producing smooth colonies indicative of reduced filamentation , while CAI4-CYR1 , CAI4-CYR11334 and CAI4-CYR11377 were 100% filamentous ( Figure 5C ) . However , CAI4-CYR11373 cells that were inoculated onto DMEM agar supplemented with 5% serum always produced 100% filamentous colonies , confirming that the reduced filamentation was signal-specific ( Figure 5B , C ) ; i . e . , CO2-induced differentiation was diminished while serum-induced differentiation was unaffected . The morphological transition of C . albicans is essential to the organism's virulence . As CO2 is a potent inducer of hyphal development we tested whether the identified CO2-recognition-mechanism regulates C . albicans pathogenicity in an in vivo model . Initially to test this hypothesis , we selected the Toll-deficient Drosophila melanogaster infection model to provide a controlled yet reduced ( in respects to filament inducing cues ) environment , as only a subpopulation of the cells were CO2 insensitive . D . melanogaster was infected with CAI4-CYR11373 and CAI4-CYR1 and survival assessed over 48 hours . Although the percentage mortalities of Toll-deficient D . melanogaster infected with either strain were similar at the end-point of the time-course experiment , CAI4-CYR11373 killed D . melanogaster at a significantly slower rate ( p = 0 . 005 ) compared to CAI4-CYR1 ( Figure 6A ) . The reduced virulence of CAI4-CYR11373 over CAI4-CYR1 was not attributed to differences in growth rates or fungal burden , as these were comparable between the two strains ( Figure S4 and Table S1 ) . To investigate how the point-mutated adenylyl cyclase would affect the virulence of C . albicans in the mammalian host , the mouse model of disseminated candidiasis was utilised . CAI4-CYR1 and CAI4-CYR11373 displayed no significant difference in their ability to cause system infection after intravenous injection ( Figure 6B ) . There was , however , a greater degree of variation in fungal burdens , weight loss and outcome scores compared with control strain ( Table S2 ) , which may be reflective of the different populations obtained in the CAI4-CYR11373 strain ( i . e . 70% CO2 responsive and 30% CO2 non responsive ) . As the fly model identified that CYR11373 was delayed in its ability to cause infection , we also sampled mice at days 1 , 2 and 3 days post-infection to determine whether the delayed ability of CYR11373 to cause infection was also present in the mouse model . However , there were no statistically significant differences in kidney burdens , weight changes or outcome scores , but again there was greater variability in the CAI4-CYR11373 data , which was not observed for the CAI4-CYR1 strain ( Table S2 ) . The differences in outcome between the two infection models may be expected . Although the CAI4-CYR11373 strain is reduced in its ability to filament in response to elevated CO2 it is responsive to serum or elevated temperature , cues absent in the fly model .
CO2 is a biologically important molecule and has major implications for disease progression . As well as host derived CO2 , microorganisms themselves generate and secrete metabolic CO2 into their microenvironment which has the potential to impact on the organism's virulence . We observed that fungal derived , metabolic CO2 accumulated in C . albicans biomasses to sufficient levels to first provide HCO3− as a metabolic intermediate to promote growth and then subsequently to induce the morphological transition crucial for C . albicans pathogenicity through activation of Cyr1p via lysine residue 1373 . CO2 is produced by multiple metabolic processes and the data presented here suggest that nutrient availability affects production rates . For instance , we found that fungal biomasses grown on nutrient rich media ( YPD ) were able to support the growth of over ten times the amount of our bio-indicator strain ( Δnce103 ) compared to those grown on nutrient limiting media ( YNB; data not shown ) . This result may reflect the increased flux through metabolic pathways as the organism utilises the available nutrients . In accordance with this Ghosh et al . recently proposed that the catalysis of arginine to urea and urea's subsequent breakdown to CO2 produces sufficient CO2 to induce C . albicans germ tube formation when engulfed by macrophages [31] . Therefore , arginine biosynthesis maybe a key contributor to CO2 production in C . albicans . Accumulation of metabolically generated CO2 in race tubes has been shown to impact on asexual spore development in Neurospora crassa [32] , [33] . Here , simple displacement of the accumulated CO2 ( by inverting the tubes ) restores conidial banding . These results suggest that the heavier density of CO2 compared to O2 and N2 allow it to accumulate in a system more freely rather than diffusing away . In accordance with this , we found that growth of the Δnce103 strain was enhanced at the bottom of the colony ( 17-fold , P = 0 . 001 ) where agar invasion was observed to stem from the centre of the colony , suggesting that the concentration of CO2 is highest at the lower extremities of the biomass ( data not shown ) . The ability to accumulate in a system is essential for communication molecules , with many molecules only having an impact once a threshold concentration is reached . However , unlike conventional QSMs , CO2 may not be specifically generated for the purpose of communication . This is mainly due to the lack of evidence for a single pathway controlling CO2 output , although the work of Ghosh et al suggest that arginine biosynthesis may play a significant role in the production of CO2 in C . albicans [31] . Therefore , it is more likely that the organisms have evolved to sense and respond to CO2 gradients as a form of diffusion sensing rather than CO2 being a true quorum sensing molecule . However , the interplay between CO2 production and other microbial species maybe relevant . When colonising mucosal membranes and epithelia C . albicans will be in contact with other microbes residing in the same niche . For example we found that under diffusion limiting conditions significantly fewer colony forming units ( 10-fold less ) of Escherichia coli or Pseudomonas aeruginosa were required to restore growth of the CO2 bio-indicator strain , Δnce103 , compared to wild type C . albicans ( data not shown ) . Given that C . albicans is found in mixed microbial biofilms on medical devices it is interesting to speculate about the role the metabolically generated CO2 in biofilm establishment and maintenance . Signalling molecules normally interact with membrane associated receptors to initiate intracellular signalling cascades terminating in a transcriptional response which subsequently induces the desired effect . Unlike most signalling molecules , CO2 enters the cell by simple diffusion and is maintained in the cell through hydration to HCO3− via the actions of carbonic anhydrase . Although HCO3− is a metabolic intermediate and will feed into various metabolic processes , a conserved HCO3− binding site was identified in the adenylyl cyclase , Cyr1p , involving lysine residue 1373 , which enables CO2/HCO3− to bind and directly stimulate Cyr1p and hence activate cAMP dependent signalling cascades . Mutation of the HCO3− binding site resulted in a subpopulation of cells that were CO2 non responsive . Introduction of the CO2 sensing deficient strain ( CAI4-CYR11373 ) into the Toll-deficient D . melanogaster infection model highlighted its reduced ability to kill the host . In the mouse model for disseminated candidiasis this attenuated virulence was not observed . However , this was hypothesised as the mutated strain remained fully responsive to other host environmental cues , including the elevated temperature and presence of serum in mammals , which are absent in the fly infection model . Taking this into consideration we hypothesise that the ability to sense and respond to metabolically generated CO2 gradients is important during colonisation and initial invasion of mucosal membranes lining the oral and vaginal tracts during superficial infections where environmental CO2 conditions are low and not as important during systemic infection ( Figure 7 ) . Here , in an expanding fungal biomass self produced metabolic CO2 gradually accumulates and once reaching threshold concentrations directly activates the soluble adenylyl cyclase , Cyr1p via the catalytic , bicarbonate receptor site . The resulting increase in cytosolic cAMP , in conjunction with other epithelial adhesion mechanisms , functions to induce the morphological switch in C . albicans . Hyphal formation results in the penetration and invasion of the underlying epithelial cells , which subsequently enhances the dissemination of the fungal pathogen . Our data supports this as we routinely found enhanced levels of Δnce103 cells in the biomass sections that were invading into the agar , similar to what is observed in oropharyngeal candidiasis , suggesting that cells towards the bottom of the biomass are exposed to higher concentrations of CO2 than cells on the surface , which would support hyphal development . Therefore , we hypothesise that during superficial infections that occur in niches where environmental CO2 concentrations are low ( for example , on the skin and mucosal membranes lining the oral cavity ) C . albicans can use self generated , metabolic CO2 to enhance adhesion and promote filamentation of the underlining cells increasing the opportunity for dissemination into the bloodstream . In line with CO2 playing an enhancing role in microbial virulence , hypercapnia ( elevated CO2 ) has recently been shown to inhibit the production of anti-microbial peptides in Drosophila [34] . Furthermore , elevated CO2 levels suppress the mammalian inflammatory response [35] , [36] , [37] . Therefore , pathogen associated , metabolically generated CO2 may play multiple roles in the infection process . One would operate at a local level , suppressing the host's immune system in the underlining epithelia and rendering the host susceptible to infection . Secondly , high CO2 would enhance the microbe's pathogenicity , providing more opportunity for host cell invasion . In conclusion , Cyr1p is a multifunctional sensor that is essential to fungal pathology . It contains multiple domains that mediate signal-specific enzyme activation in C . albicans in response to diverse filamentation-inducing molecules . We have now identified the mechanism by which this AC is stimulated in vitro and in vivo by CO2 , supplied by the environment or the fungal biomass itself . Our results give novel molecular insights into this pathogenicity mechanism , as well as an evolutionary conserved CO2-chemoreception system . Interfering with fungal CO2-sensing may reveal novel approaches for therapeutic intervention .
All animal experimentation was done in accordance with United Kingdom Home Office regulations and was approved by both the Home Office and the University of Aberdeen ethical review committee . All mice were checked and weighed at least once daily , and if they showed any signs of severe disease and/or had lost 20% of their original body weight mice were humanely terminated immediately . Mice sampled at defined time points were also humanely terminated prior to aseptic removal of kidneys for burden determination . C . albicans strains and transforming plasmids used in this study are listed in Table S3 . Columbia blood agar plates ( CBA ) , a quality-controlled growth medium routinely used in diagnostic microbiology laboratories , supplemented with 5% defibrinated horse blood were either purchased premade , or were made from Columbia blood agar base [38] from Oxoid ( 2 . 3% peptone , 0 . 1% starch , 0 . 5% NaCl , 1% agar , pH 7 . 3 ) . Dulbecco's Modified Eagle Medium ( DMEM ) without bicarbonate and pyruvate was obtained from GIBCO and used at pH7 , ( 1 . 34% DMEM , 3 . 57% HEPES supplemented to a final concentration of 2% glucose ) . YNB and YPD were made as described previously [10] . Where supplementation with 5% CO2 was required , plates were incubated in a CO2 incubator ( Infors HT Minitron ) enriched with 5% ( vol/vol ) CO2 . Solidified or serum supplemented media contained 2% agar and 5% horse serum . Toll transheterozygotes flies were generated by crossing flies carrying a loss of function allele of Toll ( Tl1-RXA; obtained from the Tübingen Drosophila Stock Collection ) and flies carrying a thermo-sensitive allele of Toll , with a strong phenotype at 29°C ( Tl3; obtained from the Bloomington Stock Center ) . All stocks were maintained on standard fly medium at 25°C , except during infection experiments where flies were incubated at 30°C . For diffusion-permitting ( open ) systems , plates were incubated in the standard way with no additional sealing mechanism . To generate a diffusion-limiting ( closed ) environment , standard 10 cm petri dishes containing CBA ( 20 ml ) were sealed with two layers of laboratory sealing film ( Parafilm ) followed by three layers of standard cling-film ( low density polyvinyl chloride ) . To minimise diffusion the sealing process was repeated twice . When plates were to be incubated in parallel , standard petri dishes were placed into , zip-locked polyvinyl chloride bags ( 15 . 5×23 cm ) . To ensure that the bags were air tight they were sealed mechanically with an additional polyethylene bar making the bags both air and water tight . Sodium hydroxide was used as a CO2-trap as described by the equation below . Plates were incubated in air tight plastic bags containing a separate vial of 4M NaOH , or 0 . 5g of solid NaOH crystals for 48 hrs . To measure CO2 accumulation the BacT/ALERT system [39] was used with some modifications . The prefilled bottles were emptied in a sterile environment , media replaced with 20 ml of solidified DMEM pH7 and the agar surface seeded with 10 , 000 SC5314 cells . Bottles for incubation in closed systems were sealed as described for agar plates . CO2 accumulation was directly measured using a BacT/ALERT 3D automated microbial detection system ( bioMerieux ) where microbial CO2 production is assessed by a colorimetric sensor and detection system ( red L . E . D and red-light-absorbing photodiode ) . Emitted light is recorded as a voltage signal that is directly proportional to the reflective light and hence the concentration of CO2 in the bottle . Heterogeneous cell suspensions containing equal proportions ( 500 cells/µl ) of DAY286 and Δnce103 were spotted ( 1 µl total ) onto individual YPD or YNB plates and incubated at 37°C for 48 hrs . Initially 1 ml of sterile water was used to wash the single colony from the plate with light agitation of the agar to remove adhered cells . From the recovered 800 µl , 200 µl was plated onto YNB , 5% CO2 to promote growth of the strictly CO2-requiring strain Δnce103 strain only ( DAY286 will not grow under these conditions as it is Δhis1/Δhis1 ) . Stability of the different phenotypic markers was verified upon replica-plating of colonies . The number of colonies was counted , and after taking into account the dilution factor , related back to the initial number of colonies in the cell suspension . Initial cell suspensions were always replica plated onto YNB and YPD to obtain the average starting cell concentration for each strain . The amino acid sequence of Cyr1p was duplicated and aligned with the sequences of two chains of a homodimeric substrate analogue complex of CyaC from Spirulina platensis ( PDB ID 1WC0; [30] ) by using Genedoc ( http://www . psc . edu/biomed/genedoc ) . A homology model for Cyr1p was generated with this alignment using Modeller [40] , and nucleotide and divalent ions positioned by superposition with the experimentally determined CyaC complex structure . Bicarbonate was then positioned manually at the site proposed for binding in bacterial sAC-like enzymes [13] . The model was visualized using Pymol ( DeLano Scientific; http://www . pymol . org ) . Lys 1373 , Asp 1334 and Asp 1377 were point mutated to Ala by site directed mutagenesis using the following sets of primers ( mutations underlined ) 1373F-tggatatgaagtggcgactgaaggtgatg and Primer 7-ctatttaagttcattaactgttttcatgat , Primer 8-aacttgtttcactcccagca and 1373R-atcaccttcagtcgccacttcatatccac , 1334F-ggttttcactgcgatcaaaaactcaac and Primer 7 , 1334R-gttgagtttttgatcgcagtgaaaacc and Primer 8 , 1377F-gactgaaggtgcggcgttcatgg and Primer 7 , 1377R-ccatgaacgccgcaccttcagtc and Primer 8 . The resulting PCR fragments were ligated into the SpeI and BamHI restriction sites of pSM2 . The 5′ domain of CYR1 together with the TEF2 promoter were subsequently ligated into the pSM2 plasmid using XbaI and HindIII ( site located with C-terminal domain of CYR1 ) restriction sites forming pACL1 , pACL2 , and pACL3 . Full-length , native CYR1 cloned into pFM2 under the control of the TEF2 promoter was subsequently restricted using SacI and BamHI restriction sites and ligated into pSM2 forming plasmid pSMTC . Plasmids pACL1 , pACL2 , pACL3 , pSMTC and pSM2 ( vector control ) were integrated into the URA3 locus of CR276 and CAI4 , generating strains RH20-25 ( Figure 7A ) using standard heat-shock procedures as previously described [41] . Single copy integration of pACL1 was confirmed for five resulting CAI4 transformants by southern analysis using DIG High primer DNA labelling and detection ( Roche ) as per the manufacturer's recommendations . DNA probe ( 1 kb ) was PCR amplified using primer-44 5′TTGGTGACATTGAGGCGTTA and primer-47 5′GTTCAATTGTCATTCCGGCAT . To assess transcript levels of CYR1 total RNA was extracted from cultures ( 50 ml YPD ) grown to OD600 0 . 5 . Cells were harvested through centrifugation and immediately frozen in liquid nitrogen . Samples were disrupted using a Mikro-dismembrator S ( Sartouis ) at 2000 rpm , 2 minutes and RNA immediately extracted using the Qiagen RNeasy Kit according to the manufacturer's recommendations . CYR1 expression levels ( native CYR1 and CYR11373 ) were analysed by semi quantitative RT-PCR using the BioRad one-step RT-PCR Kit with Syber Green ( primers CYR1-F 5′GACGACAACAAACGTGCCAGAACA and CYR1-R 5′ AATCACGTGCTGAAACATGGTCCC ) . CYR1 levels were normalised to ACT1 . The strain , RH12 ( Δnce103 Δcyr1 ) , was constructed in the Δcyr1 background strain , CR276 , using the HisG-URA3-HisG cassette to disrupt the 847 bp NCE103 open reading frame ( GenBank association number EAL03010 ) from positions +153 to +807 as described previously [10] . Correct integration of the HisG-URA3-HisG cassette into the NCE103 locus was confirmed by PCR . | Pathogenic microorganisms can produce a variety of secondary metabolites and signalling molecules which can affect the host , or provide them with a selective advantage against competing commensal organisms . We demonstrate that gaseous , metabolically generated CO2 can serve as a signalling molecule to enhance the organism's virulence during infection establishment by using the fungal pathogen Candida albicans as a model . Furthermore , we identified a CO2 receptor site within the catalytic domain of the soluble adenylyl cyclase , Cyr1p , which is critical for CO2 sensing and hence virulence of the organism . CO2 sensing is conserved in a variety of pathogenic species , and increased levels have been shown to suppress the host's immune system . Thus , CO2 sensing may represent a mechanism to enhance C . albicans virulence when the host's immune system is suppressed . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"infectious",
"diseases/fungal",
"infections",
"microbiology"
] | 2010 | CO2 Acts as a Signalling Molecule in Populations of the Fungal Pathogen Candida albicans |
Most population genetic theories on the evolution of sex or recombination are based on fairly restrictive assumptions about the nature of the underlying fitness landscapes . Here we use computer simulations to study the evolution of sex on fitness landscapes with different degrees of complexity and epistasis . We evaluate predictors of the evolution of sex , which are derived from the conditions established in the population genetic literature for the evolution of sex on simpler fitness landscapes . These predictors are based on quantities such as the variance of Hamming distance , mean fitness , additive genetic variance , and epistasis . We show that for complex fitness landscapes all the predictors generally perform poorly . Interestingly , while the simplest predictor , ΔVarHD , also suffers from a lack of accuracy , it turns out to be the most robust across different types of fitness landscapes . ΔVarHD is based on the change in Hamming distance variance induced by recombination and thus does not require individual fitness measurements . The presence of loci that are not under selection can , however , severely diminish predictor accuracy . Our study thus highlights the difficulty of establishing reliable criteria for the evolution of sex on complex fitness landscapes and illustrates the challenge for both theoretical and experimental research on the origin and maintenance of sexual reproduction .
Sexual reproduction is widespread among multi-cellular organisms [1] . However , the ubiquity of sex in the natural world is in stark contrast to its perceived costs , such as the recombination load [2] or the two-fold cost of producing males [3] , [4] . Given these disadvantages it is puzzling that sexual reproduction has evolved and is maintained so commonly in nature . The “paradox of sex” has been one of the central questions in evolutionary biology and a large number of theories have been proposed to explain the evolution and maintenance of sexual reproduction [5] . Currently , the most prominent theories include ( i ) the Hill-Robertson effect [6]–[8] , ( ii ) Muller's ratchet [9] , ( iii ) the Red Queen hypothesis [10] , [11] , and ( iv ) the Mutational Deterministic hypothesis [12] , [13] . While originally described in various different ways , the underlying benefit of sex can always be related to the role of recombination in breaking up detrimental statistical associations between alleles at different loci in the genome . What fundamentally differentiates the theories is the proposed cause of these statistical associations , assigned to either the interactions between drift and selection ( Fisher-Muller effect , Muller's ratchet , and Hill-Robertson effect ) or gene interactions and epistatic effects ( Red Queen hypothesis and Mutational Deterministic hypothesis ) . The present list of hypotheses is certainly not exhaustive , with new ones continuously being proposed , complementing or replacing the existing ones [14] . However , it is not new hypotheses that are most needed , but the real-world evidence that allows us to distinguish between them . The major question that still remains is whether the assumptions and requirements of different theories are fulfilled in the natural world . Accordingly , there has been considerable effort to experimentally test these assumptions , mainly for the epitasis-based theories ( reviewed in [15]–[17] ) . However , an even more basic and crucial problem underlies all work on evolution of sex: how does one choose , measure , and interpret appropriate population properties that relate to different theories [17]–[19] . The difficulty stems from the often large divide between the theoretical and experimental research: theories are frequently formulated as mathematical models and rely on simplistic fitness landscapes or small genome size ( e . g . two locus , two allele models ) [13] , [20]–[25] . As a result , it may be unclear how a property established based on these simplified assumptions relates to actual properties of natural populations . In this study we attempt to bridge the gap between the theoretical and experimental work and to identify which population measures are predictive of the evolution of sexual reproduction by simulating the evolution of both sexual and asexual populations on fitness landscapes with different degrees of complexity and epistasis . The measures we use are the change of mean fitness , of additive genetic variance , or of variance in Hamming distance as well as four epistasis-based measures , physiological , population , mean pairwise , and weighted mean pairwise epistasis . While this certainly is not an exhaustive list , we took care to include major quantities previously considered in theoretical and experimental literature ( e . g . [26]–[28] ) . With some exceptions [29]–[32] , earlier work generally focused on the smooth , single peaked landscapes , while here we also use random landscapes and NK landscapes ( random landscapes with tunable ruggedness ) . Some studies of more complex rugged landscapes tested whether they would select for sex but have not found a simple and unique answer , even in models with only two-dimensional epistasis [33] , [34] . A recent paper , which uniquely combines experimental and theoretical approaches and simulates evolution of sex on empirical landscapes , also finds that landscape properties greatly affect the outcome of evolution , sometimes selecting for but more often against sex [35] . However , what specifically distinguishes our study is the goal of not only determining when sex evolves but also of quantifying our ability to detect and predict such outcome in scenarios where we know how the evolution proceeds . Whether the more complex landscapes we are using here are indeed also more biologically realistic is open to debate as currently little is known about the shape and the properties of real fitness landscapes ( for an exception see for example [35] , [36] ) . Our goal is to move the research focus away from the simple landscapes mostly investigated so far to landscapes with various higher degrees of complexity and epistasis , and to probe our general understanding of the evolution of sexual reproduction on more complex fitness landscapes . Notably , we find that some of the measures routinely used in the evolution of sex literature perform poorly at predicting whether sex evolves on complex landscapes . Moreover , we find that genetic neutrality lowers the predictive power of those measures that are typically robust across different landscapes types , but not of those measures that perform well only on simple landscapes . The difficulty of predicting sex even under the ideal conditions of computer simulations , where in principle any detail of a population can be measured with perfect accuracy , may be somewhat sobering for experimentalists working on the evolution of sex . We hope , however , that this study will evoke interest among theoreticians to tackle the challenge and develop more reliable predictors of sex that experimentalists can use to study the evolution of sex in natural populations .
We investigated the evolution of sex in simulations on three types of fitness landscapes with varying complexity ( smooth , random and NK landscapes ) and used seven population genetic quantities ( ΔVarHD , ΔVaradd , ΔMeanfit , Ephys , Epop , EMP , and EWP , Table 1 ) as predictors of change in frequency of the recombination allele ( see Methods for more details ) . We calculated predictor accuracy ( the sum of true positives and true negatives divided by the total number of tests ) and used it to assess their quality on 110 smooth landscapes with varying selection coefficients and epistasis , 100 random landscapes , and 100 NK landscapes each for K = 0 , … , 5 . All landscapes are based on 6 biallelic loci and they were generated such that an equal number of landscapes of each type select for versus against sex in deterministic simulations with infinite population size . Hence , random prediction by coin flipping is expected to have an accuracy of 0 . 5 . Figure 1 shows the accuracy of the predictors for the different landscape types . Increasing levels of blue indicate greater accuracy of prediction . For the simulations with infinite population size ( deterministic simulations ) we ran a single competition between sexual and asexual populations to assess whether sex was selected for . For simulations with finite population size ( stochastic simulations ) , we ran 100 simulations of the competition phase and assessed whether the predictor accurately predicts the evolution of sex in the majority of these simulations . Focusing on the top left panel we find that for deterministic simulations most predictors are only highly accurate in predicting evolutionary outcomes for the smooth landscapes . The exception is the poor performance of ΔMeanfit , which is not surprising , as theory has shown that for populations in mutation-selection balance ΔMeanfit is typically negative [2] . According to our use of ΔMeanfit as a predictor , it always predicts no selection for sex when negative and thus is correct in 50% of cases , due to the way the landscapes were constructed . For the NK0 landscapes , all predictors perform poorly , because such NK landscapes have no epistasis by definition ( see Methods ) . For infinite population size , theory has established that in absence of epistasis there is no selection for or against sex . Indeed , in our simulations the increase or decrease in the frequency of sexual individuals is generally so small ( of order 10−15 and smaller ) that any change in frequency can be attributed to issues of numerical precision . Generally , the accuracy of most predictors is much weaker for complex landscapes ( NK and random landscapes ) than for the simpler , smooth landscapes . The predictors that have highest accuracy across different landscape types are ΔVarHD and Epop . To test whether combinations of the predictors could increase the accuracy of prediction of the evolution of sex we plot for each landscape the value of the predictors ΔVarHD , ΔVaradd and ΔMeanfit against each other and color code whether the number of sexual individuals increased ( red ) or decreased ( blue ) during deterministic competition phase ( see Figure 2 ) . If the blue and red points are best separated by a vertical or a horizontal line , then we conclude that little can be gained by combining two predictors . If , however , the points can be separated by a different linear ( or more complex ) function of the two predictors , then combining these predictors would indeed lead to an improved prediction . Figure 2 shows the corresponding plots for the smooth , the random , and the NK2 landscapes . For the smooth landscapes the criterion ΔVarHD>0 or ΔVaradd>0 are both equally good in separating cases where sex evolved from those where it did not . As already shown in Figure 1 , ΔVarHD is generally a more reliable predictor of the evolution of sex than ΔVaradd in the more complex random or NK landscapes . Epistasis-based theories suggest that the selection for sex is related to a detrimental short-term effect ( reduction in mean fitness ) and a possibly beneficial long-term effect ( increase in additive genetic variance ) [28] . The plots of ΔVaradd against ΔMeanfit , however , do not indicate that combining them would allow a more reliable prediction of the evolution of sex . Generally , the plots show that blue and red points either tend to overlap ( in the more complex landscapes ) or can be well separated using horizontal or vertical lines ( in the smooth landscapes ) such that combining predictors will not allow to substantially increase the accuracy of prediction . This is also the case for all other landscapes and all other pairwise combinations of predictors ( data not shown ) . It is possible that some of the effect described in [28] and expected here are too small to be detected with the level of replication in our study . However , as the level of replication used in this computational study goes way beyond what can be realistically achieved in experimental settings we expect that these effects would also not be detected in experimental studies . We also used a linear and quadratic discriminant analysis to construct functions to predict the outcome of competitions between the two modes of reproduction . For these purposes , half of the data set was used for training and the other half for testing of the discriminant functions , and the procedure was repeated separately for each of the three population sizes ( 1 , 000 , 10 , 000 , and 100 , 000 ) and the deterministic case . In no case did these methods improve the accuracy of predictions ( data not shown ) . While there certainly are other , potentially more sophisticated techniques that could be used here , our analysis indicates that there may not be much additional information in our metrics that could be extracted and used to increase the accuracy of the predictions . All predictors performed much worse for simulations with finite population size ( Figure 1 ) , most likely because the selection coefficient for sex is weak [19] , [20] . To further examine the effect of finite population size on the evolution of sex on different landscape types we analyzed 100 independent simulations of the competition phase starting from the genotype frequencies obtained from the burn-in phase on each landscape . Figure 3 shows the fraction of cases in which the frequency of sexual individuals increased for three population sizes ( 1 , 000 , 10 , 000 , and 100 , 000 ) , plotted separately for those landscapes in which frequency of the recombination modifier increased or decreased in deterministic simulations . For almost all landscapes the fraction of cases in which sex evolves is close to 50% , indicating that selection for sexual reproduction is indeed extremely weak , and can thus easily be overwhelmed by stochastic effects ( in contrast to simulations with infinite populations where selection coefficients of any size will always produce a consistent observable effect ) . As a consequence , even for relatively large population sizes the outcome of the competition between sexual and asexual populations is largely determined by drift . Such weak selection may in part due to the small number of loci used for these simulations and stochastic simulations with larger genomes have indeed been shown to result in stronger selection for or against sex [37] , [38] . However , accurate deterministic simulations are computationally not feasible for large genome sizes , because of the need to account for the frequency of all possible genotypes in deterministic simulations ( see Supporting Information ( Text S1 ) for more details ) . According to the Hill-Robertson effect ( HRE ) [8] , [21] selection for recombination or sex may be stronger in populations of limited size , because in such populations the interplay between drift and selection can generate negative linkage disequilibria , which in turn select for increased sexual reproduction . The strength of HRE vanishes for very small populations and for populations of infinite size [21] . In an intermediate range of population sizes , the HRE increases with increasing number of loci ( as does the range of population sizes in which the effect can be observed ) [38] and for large genome size it can be strong enough to override the effect of weak epistasis [37] . In our simulations , however , HRE is weak , as is evidenced by the fact that , in the NK0 landscape , which by definition have no epistasis , the fraction of runs in which sex evolves is only very marginally above 50% ( Figure 3 ) . Our results indicate that for finite population size the predictors generally perform poorly . Of course this does not imply that they could not be better than a simple coin toss . However , the results suggest that these predictors will likely be of limited use , as any experiment will have difficulties to reach even the replicate number that we have used to generate Figure 1 . We also examined additional fitness landscapes , characterized by increased neutrality ( for full details and figures see Text S1 ) . We found that the allelic diversity at neutral loci both decreases the accuracy and generates a systematic bias in the previously best performing predictors , Epop and ΔVarHD . In contrast , other predictors investigated here , ΔVaradd , ΔMeanfit , Ephys , EMP , and EWP are not affected by including neutral loci , but still have poor accuracy of prediction on more complex fitness landscapes .
The central message of our study is that the prediction of the evolution of sex is difficult for complex fitness landscapes , even in the idealized world of computer simulations where in principle one can measure any detail of a given population and fitness landscape . Here we put the emphasis on predictors that are experimentally measurable and are based on conditions for the evolution of sex established in the population genetic literature using simple fitness landscapes . We have however included EMP and EWP , two predictors which would be more difficult to measure experimentally , but are based on the most fundamental and general theoretical treatment of the evolution of sex [28] . Of course , while our choice of predictors , landscapes and selection regimes is comprehensive , we are aware that it can never be exhaustive or complete – there will always be other options to try out and test . Future work will have to focus on identifying more reliable predictors of the evolution of sex that can be used in conjunction with experimental data . Additionally , a better characterization of properties of natural fitness landscapes is badly needed to improve our understanding of the forces selecting for the evolution of sex . As it stands , ΔVarHD , our best candidate for a predictor of the evolution of sex , has nevertheless important shortcomings . In particular , it never reaches high levels of accuracy on many of the landscapes . Still , ΔVarHD at least suggests a potential direction for future research: a focus on predictors that would take advantage of the rapidly increasing number of fully or partially sequenced genomes and allow us to determine the advantage of sex in large numbers of taxa , bringing us closer to fully understanding the evolution of sex .
All simulations of the evolution of a haploid population on a given fitness landscape are divided into a “burn-in” and a “competition” phase . In the burn-in phase an asexually reproducing population is allowed to equilibrate on the landscape starting from random initial genotype frequencies . In the competition phase we determine whether the frequency of an allele coding for increased recombination increases in the population . The burn-in phase consists of repeated cycles of mutation and selection . Genotype frequencies after selection are given by the product of their frequency and relative fitness before selection . In all simulations mutations occur independently at each locus with a mutation rate μ = 0 . 01 per replication cycle . This high mutation rate was chosen in order to obtain sufficient levels of genetic diversity . However , we also tested mutation rates up to 10 times lower and found no qualitative differences in the results ( data not shown ) . In the competition phase the population undergoes recombination in addition to mutation and selection in each reproduction cycle . To this end a recombination modifier locus is added to one end of the genome , with two alleles m and M , each present in exactly half of the population . Recombination between two genotypes depends on the modifier allele in both genotypes , with the corresponding recombination rates denoted by rmm , rmM , and rMM . For the simulations discussed in the main text we used rmm = rmM = 0 and rMM = 0 . 1 . For this parameter choice individuals carrying distinct modifier alleles cannot exchange genetic material and thus any effect of increased recombination remains linked to the M allele . Sexual and asexual individuals compete directly with each other , and we refer to this scenario as the evolution of sex . In contrast , if rmm<rmM<rMM , then genetic material can be exchanged between all individuals . We refer to this scenario as the evolution of recombination . For the sake of simplicity , we primarily consider the evolution of sex in the main text , but analogous simulations of the evolution of recombination scenario led to qualitatively indistinguishable results ( Text S1 ) . Moreover , for the evolution of sex scenario we also tested values of rMM ranging from 0 . 01 to 0 . 3 ( data not shown ) , which produced qualitatively indistinguishable results . All recombination values refer to a probability of recombination happening between neighboring loci with one recombination event per genome . The position of the crossover point is chosen randomly . No mutations occur between m and M alleles at the modifier locus . Recombination , mutation and selection as described above are deterministic and are calculated assuming infinite population size . To examine stochastic effects , we also considered populations with 1 , 000 , 10 , 000 , and 100 , 000 individuals . Those simulations included a step in which the frequencies of genotypes are sampled from a multinomial distribution according to their frequencies as calculated based on infinite population size . The burn-in phase always consists of 2500 generations of mutation and selection . We confirmed that 2500 generations were typically sufficient for the system to go into mutation-selection balance from random initial genotype frequencies ( data not shown ) . The competition phase consists of 250 generations of recombination , mutation and selection . For infinite population size we ran a single competition phase for each burn-in phase . For finite-size populations , the outcome was estimated as the average of 100 simulations of the competition phase . | One of the biggest open questions in evolutionary biology is why sexual reproduction is so common despite its manifold costs . Many hypotheses have been proposed that can potentially explain the emergence and maintenance of sexual reproduction in nature , and currently the biggest challenge in the field is assessing their plausibility . Theoretical work has identified the conditions under which sexual reproduction is expected . However , these conditions were typically derived , making strongly simplifying assumptions about the relationship between organisms' genotype and fitness , known as the fitness landscape . Building onto previous theoretical work , we here propose different population properties that can be used to predict when sex will be beneficial . We then use simulations across a range of simple and complex fitness landscapes to test if such predictors generate accurate predictions of evolutionary outcomes . We find that one of the simplest predictors , related to variation of genetic distance between sequences , is also the most accurate one across our simulations . However , stochastic effects occurring in small populations compromise the accuracy of all predictors . Our study both illustrates the limitations of various predictors and suggests directions in which to search for new , experimentally attainable predictors . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"computational",
"biology/evolutionary",
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"evolutionary",
"biology",
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] | 2009 | Predicting the Evolution of Sex on Complex Fitness Landscapes |
The transitional period between the oncosphere and the cysticercus of Taenia solium is the postoncospheral ( PO ) form , which has not yet been completely characterized . The aim of this work was to standardize a method to obtain T . solium PO forms by in vitro cultivation . We studied the morphology of the PO form and compared the expression of antigenic proteins among the PO form , oncosphere , and cysticerci stages . T . solium activated oncospheres were co-cultured with ten cell lines to obtain PO forms , which we studied at three stages of development–days 15 , 30 , and 60 . A high percentage ( 32% ) of PO forms was obtained using HCT-8 cells in comparison to the other cell lines . The morphology was observed by bright field , scanning , and transmission electron microscopy . Morphology of the PO form changed over time , with the six hooks commonly seen in the oncosphere stage disappearing in the PO forms , and vesicles and microtriches observed in the tegument . The PO forms grew as they aged , reaching a diameter of 2 . 5 mm at 60 days of culture . 15–30 day PO forms developed into mature cysticerci when inoculated into rats . Antigenic proteins expressed in the PO forms are also expressed by the oncosphere and cysticerci stages , with more cysticerci antigenic proteins expressed as the PO forms ages . This is the first report of an in vitro production method of T . solium PO forms . The changes observed in protein expression may be useful in identifying new targets for vaccine development . In vitro culture of PO form will aid in understanding the host-parasite relationship , since the structural changes of the developing PO forms may reflect the parasite’s immunoprotective mechanisms . A wider application of this method could significantly reduce the use of animals , and thus the costs and time required for further experimental investigations .
Human and porcine cysticercosis is a disease caused by the larval cestode Taenia solium which forms cysts in the muscles or the central nervous system of its intermediate host . Both humans and pigs can acquire cysticercosis through fecal-oral transmission by ingesting T . solium eggs released by the adult tapeworm , which lives exclusively in the small intestines of humans . This parasitic disease is a major public health problem in developing countries where pigs are raised as a food source and causes great economic loss to farmers . It is strongly correlated with poor sanitary conditions and deficient sanitation infrastructure in regions where pig rearing is common [1] , [2] , [3] . When cysticercosis involves the central nervous system in humans , it is called neurocysticercosis ( NCC ) . NCC is common throughout Latin America , Sub-Saharan Africa , most of Asia , and parts of Oceania . Human NCC is believed to be the leading cause of acquired epilepsy worldwide [4] , [5] . The eggs of T . solium contain a six-hooked larva ( hexacanth ) called the oncosphere [6] . When the egg hatches , this oncosphere is released into the intestine . Gastric fluid and intestinal fluid might work together to dissolves the cementing material of the embryophore shell blocks and releases the unactivated oncosphere . The oncosphere is then stimulated by the intestinal fluid to activate and to tear open the enclosing oncospheral membrane . This activated oncosphere can penetrate the intestinal wall and reach the target tissues ( usually muscle or the central nervous system ) where it transforms into a cysticercus . This is the larval stage of the parasite that consists of a fluid-filled sac containing an invaginated scolex [7] . As this happens , the parasite produces a variety of molecules , which modulate the host immune response , in order to evade parasite destruction [7] . There is a postoncospheral ( PO ) form during the development of the cysticercus . The PO form is an intermediate stage between the oncosphere and the fully developed cysticercus in tissue [7] . This form is also called the early stage of metacestode [8] . In other cestodes , the PO form has been obtained in vitro by co-culture of oncospheres with a monolayer of mammalian feeder cells ( Taenia ovis and Taenia saginata ) [9] , [10] or without feeder cells ( Echinococcus granulosus , Taenia hydatigena , Taenia ovis , Taenia pisiformis , Taenia serialis , Taenia saginata and Taenia taeniaeformis ) [11] , [12] . Studies of the T . solium PO forms have only been done in vivo using pigs , focusing on the morphology and distribution of the PO forms [8] , [13] . In vitro cultivation of T . solium oncospheres could allow the identification of parasite-related molecules and simplify the availability of high quantities of antigen , specifically proteins and antigens expressed during the early stages of the cyst formation , which are currently very difficult to study in the intermediate host . In vitro studies could also help improve diagnostic assays , providing new targets for the development of vaccines blocking transmission , and studying protein expressions that may explain the mechanisms of evasion from the host immune response during the development of cysticerci . Therefore , our study's aim was to evaluate the in vitro culture of T . solium larval stage and to describe the morphological characteristics and protein expressions of the postoncospheral development .
In order to determine which cell line was the most successful in producing PO forms , we evaluated different cell lines: human intestinal cells ( HuTu-80 , INT-407 , HCT-8 , HT-29 and CaCo-2 cells ) , human neuroblastoma cells ( SH-SY5Y ) , human choriocarcinoma cells ( BeWo ) , rat myocardium cells ( H9C2 ) , human lung cells ( MRC-5 ) , Chinese hamster ovary cells ( CHO-K1 ) , African green monkey kidney cells ( VERO ) , and Rhesus monkey kidney cells ( LLC-MK2 ) . All of these cell lines were obtained from American Tissue Culture Collection ( ATCC , Manassas , VA ) . Cells were incubated at 37°C in 5% CO2 and grown in specific media as recommended by ATCC ( EMEM media for Hutu-80 , INT-407 , HT-29 , CaCo-2 and MRC-5 cells; RPMI for HCT-8 , VERO , LLC-MK2; EMEM + F12 media for SH-SY5Y; DMEM media for H9c2; F12K media for BeWo; and HAM-F12 for CHO-K1 ) . All media were supplemented with 10% fetal bovine serum and changed every 2 days . Once cell confluency was obtained , cells were harvested using trypsin-EDTA ( Sigma Chemical Co ) . Cells were placed into 24-well plates ( 1x105 cells per well ) , and the maturation assay described below was performed when cells formed a monolayer . Tapeworms were collected after medical treatment of newly diagnosed patients as described by Jeri et al [14] . Hatching of eggs and oncosphere activation were performed as described by Verastegui et al [15] . Briefly , the eggs were obtained from gravid proglotids of adult tapeworms by gentle homogenization in a 2 . 5% potassium dichromate solution ( Sigma , St . Louis , Missouri ) . Eggs were then washed three times in distilled water ( with centrifugation steps to collect the eggs between washes of 2500 x g per 5 min ) . The eggs were hatched and oncospheres were released with a solution of 0 . 75% sodium hypochlorite ( Mallinckrodt Baker , Inc , Phillipsburg , NJ ) in water for 10 minutes at 4°C . Oncospheres were then washed three times in RPMI medium ( Sigma , St . Louis , Missouri ) , and activated by incubation at 37°C for 45 minutes with artificial intestinal fluid ( 1 g pancreatin [Sigma Chemical Co . , St . Louis , MO] , 200 mg Na2CO3 , and 1 ml of real pig bile , with enough RPMI 1640 medium [pH 8 . 04] to make 100mL ) . After activation , the oncospheres were washed three times with RPMI medium and counted using a Neubauer chamber . We performed three experiments to define the best conditions to obtain PO forms . A parasite was considered to have developed to PO form if we observed the following characteristics: increased number of cells , increased size , loss of hooks , formation of inner cavity with no scolex , and change of morphology . The first experiment was aimed at identifying the best cell line to obtain PO forms . Ten thousand activated oncospheres were placed in each well of 24-well plates containing one of the different confluent cell lines listed above; they were incubated in 5% CO2 at 37°C , and the cell medium was changed every 3 days for a period of two weeks . This experiment was repeated three times . The free-floating PO forms were collected and rinsed three times with sterile PBS buffer . Washes consisted of transferring the PO forms into a 1 . 5 mL tube , allowing it to settle for 5 minutes , then the supernatant was removed and 1 mL of sterile PBS was added before the process was repeated . Finally , the PO forms were resuspended in 1 mL of PBS , mixed gently , and counted using an inverted microscope . The second experiment aimed to evaluate if the oncosphere can develop to PO form in the absence of a cell monolayer . Based on the results of the first experiment , activated oncospheres ( n = 10 , 000 ) were cultured for two weeks in: A ) HCT-8 cell monolayer ( positive control ) , B ) culture media alone , C ) supernatant from HCT-8 cell monolayer and D ) supernatants from HCT-8 cell monolayer that had been incubated with 2-week old PO forms . The third experiment was done to evaluate if the oncosphere could develop into PO form in the absence of direct contact with the selected feeder cell ( HCT-8 ) . We co-cultured the feeder cells and activated oncospheres ( n = 10 , 000 ) in two types of transwell systems; one with a collagen-coated membrane ( Transwell-PTFE/COL ) and the other one with a polyester membrane ( Transwell-PET ) . The activated oncospheres were added to the top of each transwell insert ( 3 . 0 μm pore size; 24-well ) . One milliliter of medium was placed in the bottom well , which contains the HCT-8 monolayer cells . Two types of controls were included in this experiment; one with activated oncospheres in a transwell system ( collagen or polyester membrane ) in the absence of monolayer cells , and the second one with activated oncospheres in direct contact with the monolayer cells . The 24-well plate was incubated for two weeks in 5% CO2 at 37° and the medium in the bottom well was replaced every three days . The HCT-8 intestinal cell line was selected to study the morphological changes of the parasite because it yielded the highest percentage of PO forms . Ten thousand activated oncospheres were cultured in confluent HCT-8 cell monolayer and cell medium was changed every three days . The free-floating PO forms were collected and rinsed twice with fresh medium , then transferred to another well containing confluent HCT-8 cell monolayers . This process was repeated every three days for up to two months to allow the PO form to continue development . Cultures were inspected daily using an inverted microscope ( Leitz labovert FS ) . PO forms were collected at 15 , 30 , and 60 days of incubation . After 2 months of incubation , the PO forms began to die off . The PO forms collected were divided into 3 aliquots . The first aliquot was dried on a slide coated with poly-L-Lysine 0 . 1% solution ( Sigma , St . Louis , Missouri ) followed by fixation with methanol-acetone ( 1:1 ) for 10 min at -20°C , and the slides were then washed three times with PBS , mounted with Prolong gold antifade reagent with DAPI ( Life Technologies , Carlsbad , CA ) , and examined by UV microscopy ( Leica DM 500 ) . The second aliquot was fixed with 2% of glutaraldehyde ( Grade I: 70% solution ) in 1% sucrose in PBS to be examined by scanning electron microscopy ( SEM ) and transmission electron microscopy ( TEM ) . The third aliquot was fixed with 4% of paraformaldehyde in PBS and embedded in paraffin . Two 4-μm sections from all samples were stained with H&E . The fixed PO forms were then fixed in 1% osmium tetroxide followed by sequential dehydration steps from 25% to 100% ethanol . Ethanol was exchanged for liquid CO2 ( Samdri Critical Pont Dryer ) . Using an inverted microscope , samples were positioned in stubs and gold coated ( SPI-Module Sputter coater ) . Specimens were observed using a Zeiss 1450EP Scanning Electron Microscope . The fixed PO forms were then fixed in 1 . 5% osmium tetroxide , dehydrated in ethanol , and embedded in epoxy , and 50-nm sections were cut . Sections were then stained with lead hydroxide and uranyl acetate and were examined using a Phillips electron microscope ( Phillips Electronic Instruments , Eindhoven , The Netherlands ) operating at 75 kV . To determine the viability and infectivity of the PO forms , 15 day old Hotzman rats , purchased from Universidad Peruana Cayetano Heredia ( UPCH ) , Lima , Peru , were infected intracranially ( in the bregma ) as described by Verastegui [16] with 15 and 30 day old PO forms . Rats were anaesthetized with ketamine ( 100 mg/kg body weight ) and xylazine ( 5 mg/kg body weight ) before infection . Eight rats were inoculated with ten 15 day PO forms in 100 μL of saline solution , nine rats were inoculated with five 30 day PO forms in 100 μL of saline solution , and five rats were inoculated with 100 μL of saline solution as control . The syringe needle gauge was 24G for 15 day PO forms and 21G for 30 day PO forms . PO forms of 60 days of development were not used for this experiment , as parasites of that age were 2 . 5 mm in diameter . Necropsy was done four months later . Briefly , the rats were anaesthetized with ketamine ( 100 mg/kg body weight ) and xylazine ( 5 mg/kg body weight ) . Anaesthetized rats were perfused with 200 ml of PBS and then with 100 ml of 4% paraformaldehyde in PBS . Brains were carefully removed , post-fixed for 24 hours at 4°C with 4% paraformaldehyde in PBS , and stored in 70% ethanol . Brains were observed macroscopically to identify extraparenchymal cysticerci; coronal sections of the brain ( 5 mm ) were done until the intraparenchymal cysticerci were observed . Coronal sections of the brain were paraffin embedded , cut in 3 μm thick sections and Masson’s trichrome stained . All animal procedures were performed in strict accordance with the recommendations in the Guide for Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by the Committee on the Ethics of Animal of the Universidad Peruana Cayetano Heredia , Lima , Peru ( Permit Number: 61242 ) . The total proteins present in PO forms , activated oncospheres , and cysticerci were incubated with anti-oncosphere and anti-cysticercus rabbit sera in order to evaluate the change in the expression of antigenic proteins during PO form development . Total proteins of the PO form were obtained from PO forms cultured in HCT-8 cells as described previously . PO forms were collected at 15 , 30 , and 60 days of incubation , rinsed three times with PBS buffer , sonicated , and centrifuged . Hatched and activated oncospheres were obtained as described above; cysticerci removed from an infected pig were also rinsed , sonicated and centrifuged . The supernatants were used as total protein , and examined by western blot . Protease inhibitors of 1mg/ml of Leupeptin ( 1/1000 ) ( Sigma , St . Louis , Missouri ) , 0 . 1 M Pefabloc SC PLUS ( 1/100 ) ( Roche , Mannheim , Germany ) and 1mg/ml of Pepstatin ( 1/1000 ) ( Sigma , St . Louis , Missouri ) were added to the total protein prior to storing at -70°C . Three μg of total proteins were resolved in 15% SDS-PAGE non-denaturing gels and transferred to nitrocellulose ( NC ) membranes ( Bio-Rad Laboratories , Hercules , CA ) . NC membranes were incubated overnight at 4°C with rabbit sera immunized with total proteins of activated oncosphere and cysticerci ( 1:200 ) [15] . The NC membranes were washed three times with PBS 0 . 3% Tween-20 , incubated with peroxidase-conjugated goat anti-rabbit antibodies diluted 1: 400 ( KPL , Gaithersburg , MD ) for 1 hour at room temperature and resolved with DAB substrate ( Sigma Chemical Co ) . The in vitro maturation assay using various cell lines was independently repeated three times and the development of PO form was expressed as percentages ( % ) . The sizes of the oncospheres for each development time were measured and the result was expressed in micrometers ( μm ) as the mean size of oncosphere with 95% confidence intervals ( CI ) . The Student's t-test was also performed to evaluate the difference between the sizes of the PO form cultured with and without transwell system , using the software Stata 10 . 0 with a significance level of 0 . 05 .
Using inverted microscopy , we observed that at 1 day of culture in HCT-8 cells , the activated oncospheres did not change their size and form but were attached to the cell monolayers . At this time , the activated oncospheres measured from 18 μm to 25 μm in diameter ( mean = 20 . 8 μm , 95% CI = 19 . 7–21 . 8 μm ) with six hooks enclosed within the oncospheral tegument ( Fig 1A ) . At 3 days of culture in HCT-8 cells , the oncospheres changed their morphology and size , and we termed them postoncospheral ( PO ) forms . Between 3 and 12 days of culture the PO forms were spherical and larger in size ( from 22 μm to 40 μm in diameter ) , the hooks were still visible and some PO forms remained attached to the cell monolayers . The oncospheres matured while attached to the cell monolayers for two weeks; after that they detached and became free-floating parasites . From 15 to 60 days of culture , the PO forms were not attached to cell monolayers , the hooks were not present and the size increased ten or more times in comparison to the initial size of the activated oncosphere . The 15 day PO forms measured from 64 μm x 96 μm to 240 μm x 337 μm in size . There were 15 day PO forms with spherical and oval forms ( Fig 1B ) , while some also had a protuberance . The six hooks were no longer present in the 15 day PO forms . The smallest 15 day PO forms ( 64 μm x 96 μm ) presented cells inside of the tegument observed by H&E stain ( Fig 1B ) . The 15 day PO forms showed motility that began with an oval shape , and then one polar ends of their body began to stretch , forming a protuberance and widening until it returns to its initial form ( S1 Multimedia file ) . The 30 day PO forms ranged in size from 840 μm x 980 μm to 1418 μm x 1617 μm , with an oval form . The formation of a protuberance was also observed in one of the polar ends of the body of 30 day PO forms while moving ( Fig 1C and S2 Multimedia file ) . The 60 day PO form reached up to 2500 μm in size ( mean = 1991 . 6 μm and 95% CI = 1636 . 6–2346 . 6 μm ) and had a spherical form like a cysticercus but without a scolex ( S3 Multimedia file ) . Some of the parasites formed a structure like a “belly button” caused by cell accumulations in the middle of their bodies while they were moving ( Fig 1D ) . The number of cell nuclei within PO forms increased with age , as noted with the DAPI stain ( Fig 2 ) . Activated oncospheres had from 8 to 18 cell nuclei while PO forms had from 85 to 377 cell nuclei at 15 days of growth , between 1500 to 4000 cell nuclei at 30 days of growth , and more than 5000 cell nuclei at 60 days of growth . Another important observation was that after 60 days of culture , the parasite showed many vesicles in its tegument; they began to degenerate , lost their ability to move , and finally died . In this study , we observed that T . solium oncospheres have microvilli on the surface ( Fig 3A ) while 15 day-PO forms to 60 day PO forms do not have microvilli ( Fig 3B and 3D ) ; instead , the PO form has structures like microtriches on the surface as observed in the Figs 3C and 4A . They are long and fine and intertwine , forming something like a network ( Fig 3C ) . Microtriches were homogeneously distributed across all the surfaces of the PO forms at all three growth times . The microtriches present in the protuberance of the 30 and 60 day PO forms were more developed than 15 day PO forms ( Fig 4A ) . Vesicles have also been observed in the PO forms at 15 , 30 , and 60 days . These vesicles were observed on the surface of the body and also in the protuberance of the PO form ( Fig 3D and Fig 4B ) . In the protuberance , the number of vesicles was higher in 15 day PO forms than in 30 and 60 day PO forms ( Fig 4B ) . A large central cavity surrounded by a tegument was observed at 15 , 30 , and 60 days . The tegument was covered by microtriches; cells were clearly observed below the tegument in 30 day PO form as observed in Fig 5B . The 15 and 30 day PO forms developed to mature , viable cysticerci when rats were inoculated intracranially ( Fig 6 ) . In rats infected in the brain with 15 day PO forms , 5/8 ( 63% ) developed viable cysticerci with a scolex of which 4/5 ( 80% ) developed more than 5 cysts in the brains examined . In rats infected with 30 day PO forms , 6/9 ( 66% ) developed viable cysticerci of which 4/6 ( 77% ) developed 5 cysticerci in the brain . These findings demonstrate that PO forms are viable and competent to become T . solium cysticerci with normal morphology . In this study , we also evaluated if the PO forms changed the expression of antigenic proteins during development . The antigenic proteins were analyzed using rabbit sera against T . solium oncospheres and cysticerci . Anti-oncosphere antibodies demonstrated a band of 9 kDa expressed exclusively by the activated oncosphere . Some antigenic oncosphere proteins ( 22 . 5kDa and 31 . 3kDa ) were only expressed by oncospheres and 15 day PO forms but not by 30 and 60 day PO forms ( Fig 7A ) . Using anti-cysticerci antibodies , we observed that PO forms also express some antigenic cysticerci proteins ( 24 , 10 , and 6 kDa ) , which were present at 15 , 30 , and 60 days . A 4 kDa antigenic band appeared only after 30 days of culture , and a 21 kDa band appeared only after 60 days of culture ( Fig 7B ) .
This study shows that different cell lines are capable of supporting the in vitro development of Taenia solium postoncospheral ( PO ) forms . We described the development and morphological changes of the PO forms in HCT-8 cells at three time points of development ( 15 , 30 , and 60 days ) . The PO forms were able to develop into mature cysticerci when inoculated in rat brains . The pattern of PO form antigenic protein expression begins similarly to that of oncospheres , but it later becomes more similar to the expression of cysticerci antigenic proteins . To our knowledge , this is the first study to achieve in vitro growth of T . solium PO forms . Two previous studies demonstrated that cell monolayers could be used to obtain the PO forms of T . ovis [9] and T . saginata [10] , although it was unclear whether contact with the monolayers was necessary for the PO form development . Our results show that oncospheres developed to PO forms in the presence of monolayer feeder cells . The PO forms that grew in direct contact with feeder cells were bigger than PO forms that grew in a transwell system with cells . It is likely that the parasite development depends on nutrients , growth factors , and cytokines secreted by feeder cells , and also the direct contact with cells might promote the uptake of nutrients through the parasite tegument . By contrast , the development of the parasite was incomplete in the absence of feeder cells , even when we added the supernatants of HCT-8 cells; it is probable that the secreted factors are very labile and need to be constantly produced to maintain the development of the parasite . The importance of secreted factors from feeder cells has been studied in the development of the Echinococcus multilocularis larval stage; they were cultured with rat hepatocytes which strongly stimulated vesicle regeneration , and suggested that soluble factors secreted by host cells acted on germinal cells as initiators of metacestode formation [17] . Similarly , PO forms of Echinococcus granulosus , T . hidatigena , T . ovis , T . pisiformis , T . serialis , T . saginata and T . taeniaeformis have been successfully obtained in the absence of feeder cells [11] [12] ) . There may be nutritional differences between parasite species or farming systems used in vitro . For instance , Heath et al used serum from each specific intermediate host in the culture medium while in the present study we used fetal bovine serum . Serum contains specific factors for each host-parasite system that stimulate development of the parasite [11] . Interestingly , the PO forms did not grow in LL-CMK2 monolayer cells which may be due to lack of essential nutrients , growth factors , cytokines or other possible growth stimuli , and the fact that different cell lines likely express different surface molecules . The transformed cell lines that are used in the present study usually express a variety of growth factors that normal cells would not produce in their tissues of origin . These factors may also explain the different growth rate of the parasites among the cell lines . We chose to study the PO forms from day 15 forward , because it was at this point that the parasite detached from the cell monolayers and became free floating . We hypothesized that the loss of ability of PO form to attach to the cell monolayers is due to loss of the microvilli that are present only in activated oncospheres [15] . We observed structures that look like microtriches in 15 , 30 , and 60 day PO forms . The change from microvilli to microtriches has been reported in Echinococcus granulosus [18] and a similar process likely happens in the PO form of T . solium . However , we do not know if the microvilli turn into microtriches or if they are lost and replaced by microtriches . Chervy et al . , 2009 mention that the microtriches are either formed de novo , or via the conversion of microvilli by the addition of electron-dense material to form the cap [19] . Another characteristic of 15 , 30 , and 60 day PO forms was the absence of hooks . Our results are similar to those found in vivo in which the 6 hooks were lost 10–15 days after experimental infection of pigs [13] . The hooks play a major role in the oncosphere activation , by shedding the oncospheral membrane [20] . However it is not clear if hooks have another role during the infection process such as penetrating the intestine . Vesicles were present in the PO forms at all three time points , with more vesicles at the surface of the anterior pole in the 15 day PO forms . Previous studies have demonstrated that oncosphere vesicles are important for attachment to host tissues and to facilitate penetration through the epithelium or for protection against digestive enzymes and evasion of the immune response [21] , [22] . However , vesicles of the PO form may contribute to evasion of the immune response and in the formation of the tegument as it has been shown for Echinococcus granulosus [22] . The T . solium PO form has the general pattern of postoncosphere development reported in Taenia serialis , Taenia ovis , Echinoccoccus granulosus , Taenia hydatigena and Taenia pisiformes when these are grown in medium supplemented with serum [11] . In our study , the pattern observed in T . solium postoncospheral development was 1 ) cell multiplication as seen with DAPI stain , 2 ) cavity formation , which was observed from 15 to 60 days PO forms , and 3 ) further growth , and where applicable movement which is observed in all three age points . Additionally , when the 15 and 30 day PO forms were injected into rat brains they continued to mature and formed cysticerci , proving their viability; this is a highly efficient method of infecting an animal model . Finally , the PO forms started to die off at 60 days of culture . No scolex formation was observed in this in vitro study . First , it is likely that the PO forms were not viable long enough to complete its development as it was reported for T . saginata [10] . Secondly , it is possible that the development was stunted because specific host signals or nutrients present in the serum or tissue from their intermediate host were missing as reported in other species of taeniid [11] . However , the protuberance that we observed at one end of the PO form and the “belly button” structure described in the center of the parasite at 60 day old could be the initial development of the scolex region , as described for other taeniids [11] . We observed the transition of immunogenic proteins from oncosphere to cysticerci . The 15 day PO forms stopped producing some oncosphere proteins , such as those of the size of 22 . 5 and 31 . 3 kDa , and , as the PO forms aged , started the expression of a majority of the cysticerci antigenic proteins . Bands of 22 . 5 and 31 . 3 kDa were reported as specific T . solium oncosphere antigens [23]; however , in this study , we observed that these antigenic proteins also were expressed in 15 day PO forms , indicating at least some temporal overlap . The changes in antigenic protein expression during the development of PO forms may help with evasion of the host immune system . In other taeniid species , these changes are associated with the formation of the tegument , and with changes in the parasite’s susceptibility to antibody and complement-mediated attack early in the development of the metacestode [24] . The changing expression of antigenic proteins over the course of the PO forms could be used when designing diagnostic assays , and help determine if a particular protein is a good vaccine candidate . In conclusion , we have developed and standardized a method for culturing T . solium oncospheres to obtain PO forms for up to 60 days in the presence of an HCT-8 feeder cell monolayer . These PO forms can complete their development to mature cysticerci when injected in rat brains , and changes in the expression of antigenic proteins during their development are related to the changes observed in their morphology . | Neurocysticercosis is caused by T . solium , which is a neglected disease . The postoncospheral ( PO ) form is an intermediate form between the oncosphere , which is the larva , and the fully developed cysticercus , which is a cyst with a scolex . The morphology , development , and protein and antigen expression of the PO form have not previously been characterized . Here , we report the novel in vitro cultivation of T . solium PO forms and characterize the morphology , development , and expression of antigenic proteins . This new method will allow for better study of this transitional form , which is very difficult to study in the intermediate host . With the increased availability of secreted proteins and antigens , in vitro cultivation will help improve diagnostic assays and provide new targets for vaccine development to block transmission . | [
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"organisms"
] | 2016 | In Vitro Study of Taenia solium Postoncospheral Form |
Polymorphisms that affect complex traits or quantitative trait loci ( QTL ) often affect multiple traits . We describe two novel methods ( 1 ) for finding single nucleotide polymorphisms ( SNPs ) significantly associated with one or more traits using a multi-trait , meta-analysis , and ( 2 ) for distinguishing between a single pleiotropic QTL and multiple linked QTL . The meta-analysis uses the effect of each SNP on each of n traits , estimated in single trait genome wide association studies ( GWAS ) . These effects are expressed as a vector of signed t-values ( t ) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP ( V ) . Consequently , t'V−1t is approximately distributed as a chi-squared with n degrees of freedom . An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS , so it can be applied to published data where individual records are not available . We demonstrate that the multi-trait method can be used to increase the power ( numbers of SNPs validated in an independent population ) of GWAS in a beef cattle data set including 10 , 191 animals genotyped for 729 , 068 SNPs with 32 traits recorded , including growth and reproduction traits . We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits . We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect . In the beef cattle data set , cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group . A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups .
Polymorphisms that affect complex traits ( quantitative trait loci or QTL ) may affect multiple traits . This pleiotropy is the main cause of the genetic correlations between traits , although another possible cause of genetic correlation is linkage disequilibrium ( LD ) between the QTL for different traits . A positive genetic correlation that is less than 1 . 0 between two traits , such as weight and fatness , implies that some QTL affect both traits in the same direction , but other QTL may affect only one trait and a small number may even affect the traits in the opposite direction . Identifying QTL with different patterns of pleiotropy should help us to understand the physiological control of multiple traits . Although genome wide association studies ( GWAS ) are usually performed one trait at a time , it is not uncommon to find that two traits are associated with SNPs in the same region of a chromosome . This has been described as cross phenotype association [1] . Resolving whether cross phenotype associations are due to one QTL with pleiotropic effects or two linked QTL [1] has proved challenging , given the large number of loci that appear to cause variation in complex traits [2]–[5] . In practice , the apparent effect of a SNP on a trait is estimated with some experimental or sampling error . Consequently , even if there is a single QTL in a region of the chromosome , the SNP with the strongest association may vary from one trait to another causing the estimated position of the QTL to vary between traits . If one QTL can explain the findings for the multiple traits then a multi-trait analysis might result in higher power to detect QTL and greater precision in mapping them . Multiple-trait analysis of linkage experiments has been reported to increase the power to detect QTL [6] , [7] . This paper investigates whether additional power can be extracted from a GWAS by analyzing traits together rather than one at a time . In principle , provided the computing power exists , a multi-trait GWAS is statistically straightforward . However , typically not all subjects have been measured for all traits , and when different traits have been investigated in different experiments , the individual subject data may not even be available . Therefore we present an approximate , multi-trait meta-analysis that uses as data the estimated effects of the SNPs from n individual trait GWAS . These effects are expressed as a vector of signed t-values ( t ) and the error covariance matrix of these t values is approximated by a n×n correlation matrix of t-values among the traits calculated across the SNP ( V ) . Consequently , t'V−1t is approximately distributed as a chi-squared with n degrees of freedom . The meta-analysis used here , although approximate , appropriately models the variances and covariance among the t-values regardless of the overlap in individuals measured for the different traits . The different amount of information for the different traits ( e . g . different number of individuals genotyped , size of error variance relative to SNP effect ) is accounted for in the analysis . To distinguish between pleiotropy and multiple , linked QTL , we use two different analyses . Firstly , we consider whether all SNPs in a region do or do not show the same pattern of effects across traits . Secondly , we fit the most significant SNP from the multi-trait analysis in the model to test whether this does or does not eliminate the evidence for a second QTL . An aim of GWAS is to identify the genes and polymorphic sites in the genome that cause variation in complex traits . Choosing the most likely candidate genes from the region surrounding a SNP is usually based on the relationship between the function of the gene and the trait . Assuming that some QTL show pleiotropy , the pattern of pleiotropic effects would be an important clue to the nature of the causative mutation and the function of the gene in which it occurred . Genes that belong to the same pathway might have a similar pattern of pleiotropic effects . Therefore we investigate whether QTL can be clustered into groups with a similar pattern of pleiotropic effects and hence into physiologically similar groups . The objectives of this study were to test the power of a multi-trait , meta-analysis to detect and map pleiotropic QTL affecting growth , feed conversion efficiency , carcass composition , meat quality and reproduction in beef cattle . We also investigate whether these pleiotropic QTLs can be placed in groups with a similar pattern of effects and hence similar underlying physiological mechanisms .
Many of the significant SNPs in both single trait and multi-trait analyses were linked and might be associated with the same QTL . As an example of the multi-trait approach to improve precision , Figure 2A shows the significance of SNP effects for 4 single trait GWAS and our multi-trait statistic in a region of chromosome 5 ( BTA 5 ) . The 4 separate traits map the QTL to slightly different positions ( range: 47 , 732–48 , 877 kb ) . For the multi-trait statistic , based on SNP effects from single-trait GWAS for 32 traits , the most significant SNP ( P = 1 . 32×10−27 ) was located at 47 , 728 kb . The multi-trait analysis represents a good compromise between the positions from the 4 single trait GWAS and may be the best guide to a single QTL position explaining all the associated traits . SNPs were classified according to their distance from the nearest gene and the proportion of SNPs at each distance from a gene that were significant ( P<10−5 ) in the multi-trait analysis was calculated . Figure 3 shows that SNPs were more likely to be significantly associated with the 32 traits if they were within or less than 100 kb from a gene . There are many regions of the genome , similar to that illustrated in Figure 2A , where multiple traits had significant associations with one or more SNPs . For each SNP their estimated effects on each trait were expressed as a signed t-value . For each pair of SNPs we calculated the correlation across the 32 traits between their estimated effects so that SNPs with the same pattern of effects across traits are highly positively or negatively correlated . Figure 4 shows the correlation between SNPs on a region of chromosomes 7 and 14 . All SNPs in the vicinity of 25 Mb on chromosome 14 are highly correlated indicating a single pleiotropic QTL in this region , corresponding to previous reports of a polymorphism near the gene PLAG1 that affects many traits [9]–[11] . On chromosome 7 there are three blocks of SNPs with high correlations within a block and low correlations between blocks suggesting there are three QTL , close to 93 , 95 and 98 Mb . The QTL at 98 Mb corresponds to a previously reported polymorphism in calpastatin ( CAST ) [12] , [13] . Below , we confirm this interpretation by fitting the most significant SNPs in the model and testing for additional associations . For each pair of SNPs among the 28 lead SNPs , the correlation of their effects across the 32 traits was calculated ( Figure 7 ) . There are a few correlations with high absolute value , such as between the lead SNPs on BTA 5 , 6 and 14 , but most correlations are low . A low correlation suggests QTL with different patterns of effects across traits , however sampling errors in estimating SNP effects also reduce the absolute value of the correlation . If two QTL affect the same physiological pathway one might expect them to have the same pattern of effects and hence a high correlation . Cluster analysis based on effects of the SNPs across traits divided the 28 lead SNPs into 4 loosely defined groups ( Figure 7 ) , which share patterns of effects across traits ( although there are still differences within each group in the exact pattern of effects across traits ) ( Table 5 ) . Group 1 consists of 4 lead SNPs located on BTA 5 ( BTA5_47 . 7 Mb ) , 6 ( BTA6_40 . 1 Mb ) , 14 ( BTA14_25 . 0 Mb ) and 20 ( BTA20_4 . 9 Mb ) . This group clustered as an outer branch separate from the other 24 lead SNPs ( Figure 7 ) , indicating that this group of SNPs clusters more tightly than the other groups . Three of these 4 SNPs were highly correlated amongst each other while the SNP on BTA 20 had slightly lower correlations to the other 3 SNPs . Table 5 shows that these 4 SNPs have an allele that increases height and weight and decreases fatness , RFI and blood concentration of IGF1 . They could be described as changing mature size . Group 2 consists of SNPs on BTA 7 ( BTA7_98 Mb ) , 10 ( BTA10_92 Mb ) , 25 ( BTA25_3 . 7 Mb ) , 26 ( BTA26_28 . 0 Mb ) , and 29 ( BTA29_44 . 8 Mb ) with high correlations between 2 SNP on BTA 7 and 29 . These SNPs have an allele that increases meat tenderness ( i . e . , decrease shear force ) and fatness ( i . e . , marbling or intra-muscular fat ) ( Table 5 ) . The SNPs at BTA7_98 . 5 Mb and BTA29_45 . 8 Mb have a large effect on shear force and map to the positions of known genes affecting this trait ( Calpastatin and Calpain 1 ) [12] , [14] , [15] . Group 3 consists of 7 SNPs that are located on BTA 2 ( BTA2_25 . 2 Mb ) , 3 ( BTA3_80 . 1 Mb ) , 6 ( BTA6_12 . 7 Mb ) , 13 ( BTA13_34 . 9 Mb ) , 17 ( BTA17_24 . 9 Mb ) , 19 ( BTA19_25 . 1 Mb ) , and 25 ( BTA25_14 . 5 Mb ) . There was weaker clustering and lower correlations between these SNP compared to groups 1 and 2 . The SNPs of Group 3 have an allele that increases both fatness and weight but has little effect on height or IGF1 ( Table 5 ) . This distinguishes these SNPs from those in Group 1 where the allele that increases weight also decreases fatness and IGF1 . Group 4 , the biggest group , consists of 12 SNPs in a loose cluster . Moderate correlations appeared between some SNPs on BTA 7 ( BTA7_93 . 2 Mb ) , 9 ( BTA9_100 . 5 Mb ) , 21 ( BTA21_0 . 9 Mb ) , 21 ( BTA21_19 . 0 Mb ) , 23 ( BTA23_43 . 9 Mb ) , 4 ( BTA4_77 . 6 Mb ) and 8 ( BTA8_59 . 2 Mb ) ( Figure 7 ) . This group has an allele that tends to increase muscling , retail beef yield ( RBY ) , tenderness and feed efficiency , and decrease fatness . The clustering did separate the 2 SNPs on BTA 7 with the SNP near 98 Mb belonging to Group 2 and the SNP near 93 Mb belonging to Group 4 . Although the SNPs within a group share some features they also differ in some of their associations . For instance , in Group 1 the SNP on BTA 14 near PLAG1 has a more marked effect on age at puberty ( AGECL ) than others in the group; the SNP on BTA5 changes the distribution of fat between the P8 site on the rump and rib site and the intramuscular depot . Thus it is possible for the each SNP to have a unique pattern of associations with phenotypic traits . The pattern of pleiotropic effects might be an important clue to the nature of the causative mutation and the function of the gene in which it occurred . Genes that operate in the same pathway might be expected to show the same pattern of pleiotropic effects . For each of the 28 lead SNPs , we searched for additional SNPs with a similar pattern of effects . To do this we used the linear index of 22 traits that showed the highest association with a lead SNP , as previously defined for validation of the multi-trait analysis , and performed a new GWAS using the linear index as a new trait . Table 6 shows the number of significant ( P<10−5 ) SNPs for the 28 linear indexes corresponding to the 28 lead SNPs . Out of 28 linear indexes , 19 had more than 70 significant SNPs and hence a FDR of less than 10% . Linear index BTA5_47 . 7 Mb , BTA6_40 . 1 Mb , BTA14_25 . 0 Mb , and BTA20_4 . 9 Mb ( where the name corresponds to the location of the QTL defining the pattern of effects ) have associations with over 1 , 000 significant SNPs across the genome . For the index based on the lead SNP BTA5_47 . 7 Mb , the significant SNPs included 615 SNPs on BTA 5 , 64 on BTA 6 , 24 on BTA 11 , 907 on BTA 14 , 19 on BTA 17 , 18 on BTA 20 . This reiterates the result obtained in the cluster analysis because SNPs on BTA 5 , 6 , 14 and 20 are the lead SNPs in Group 1 and the additional SNPs on these chromosomes may be tagging the same QTL as the lead SNPs . However , there are also significant SNPs associated with this linear index on BTA 11 , 17 , 19 , 21 and 25 . The additional significant SNPs were assigned to the 4 groups as follows . For each SNP , the linear index with which it showed the most significant association ( P<5×10−7 ) was found . The SNP was then assigned to the same group as the lead SNP defining that linear index . The results are shown in Figure 8 . Usually this procedure identified a set of closely linked SNPs , presumably indicating a single QTL . Therefore we kept in the final group only the most significant SNP ( P<5×10−7 ) from each set . The number of significant SNPs assigned to each of the 4 Groups were as follows: 1 ) 2 , 076; 2 ) 398; 3 ) 169 and 4 ) 176 . The positions or regions of the most significant SNPs in the expanded groups are listed in Table 7 . For each SNP or group of SNPs in Table 7 we examined the genes within 1 Mb and , in some cases , identified a plausible candidate for the phenotypic effect ( Table 7 ) . Focusing on those regions with multiple SNPs , the genes CAPN1 , CAST , and PLAG1 , were again identified , which are strongly identified with meat quality and growth in previous cattle studies [16]–[18] . In addition , we identified the genomic regions that include the HMGA2 , LEPR , DAGLA , ZEB1 , IGFBP3 , FGF6 and ARRDC3 genes as having strong genetic effects in cattle . HMGA2 and LEPR are well known to have effects on fatness and body composition in pigs [19] , [20] . SNP in the promoter of IGFBP3 have been shown to affect the level of IGFBP3 in humans , which affects availability of circulating IGF1 and has a multitude of effects on growth and development [21] . Here we show a strong effect for IGFBP3 , where previous results for marbling or backfat have either been small or non-significant [22] , [23] . Differences in gene expression of FGF6 has been shown to be associated to muscle development in cattle [24] , and here we show that genetic variation at FGF6 is associated with effects on Group 4 traits , which include muscling and yield traits . ARRDC3 is a gene involved in beta adrenergic receptor regulation in cell culture [25] , and beta adrenergic receptor modulation is involved in tenderness , growth and muscularity in cattle [26] , [27] . Here we show that variation at ARRDC3 is strongly associated with growth and muscularity traits in these cattle .
We demonstrated that our multi-trait analysis has a lower FDR than any one single trait analysis ( at the same significance test P-value ) and that these SNPs are more likely to be validated in a separate sample of animals . The most significant SNP in the multi-trait analysis provides a consensus position across the traits affected and a consistent set of estimates of the QTL for the various traits . This is in contrast to single trait analyses that often report the effect of different SNPs on each trait while neglecting the pattern of effects of the QTL across traits . For instance , the multi-trait analysis makes it clear that the QTL in Group 1 increase weight and decrease fatness whereas QTL in Group 3 increase both . Other methods are available for multi-trait analysis [1] , but the method used here has advantages . It can and has been applied to data where the individuals measured for different traits are partially overlapping and where the individual level data are not available . It utilises the estimated effects of the SNPs as well as the P-values and takes account of traits where the effects of a SNP may be in opposite directions . An alternative approach is illustrated by Andreasson et al . [28] in which only SNPs that are significant for one trait are tested for a second trait . However , this approach is only applicable when different individuals have been recorded for each trait and does not generalise easily to more than 2 traits . Ideally , in the multi-trait analysis , the matrix V ( the correlation matrix among the SNP effects ) would contain the covariances among the errors in the estimates of SNP effects . The error variance of a t-value with 1000's of degrees of freedom is very close to 1 . 0 . Our approximation to V also has diagonal elements of 1 . 0 because it is a correlation matrix . The covariance between the errors in t-values for two different traits depends on the overlap in individuals measured for the two traits . If the two traits are recorded on different individuals , there is no covariance among the errors; whereas if the two traits are measured on the same individuals , the error covariance will be mainly determined by the phenotypic correlation between the traits because single SNPs explain little of the phenotypic variance . We approximate these error covariances by the correlation between t-values across 729 , 068 SNPs . Since most SNPs have little association with a given trait , these correlations represent phenotypic correlations in the case where both traits are measured on the same individuals . If the two traits are measured on different individuals , then the correlation of t-values is close to zero as it should be . And if there is a partial overlap between the individuals measured for the two traits , then the correlation of t-values will represent this . Thus the meta-analysis used here , although approximate , appropriately models the variances and covariances among the t-values regardless of the overlap in individuals measured for the different traits . Therefore we hope it will be widely useful including in the analysis of published GWAS results where only the effect of each SNP and its standard error are available . Bolormaa et al . [4] carried out a multi-trait GWAS by performing a principle component analysis of the traits and then single trait GWAS on the uncorrelated principle components . The final test statistic was a sum of the individual principle component chi-squared values . The analysis used in the current paper gives very similar results to those of Bolormaa et al . [4] but the previous method requires that individual data is available and that all individuals are measured for all traits . We distinguished between two linked QTL and one QTL with pleiotropic effects using two types of evidence . When one QTL explains the results , the SNPs in the region are highly correlated in their effects across traits and when the best SNP is fitted in the model the significance of the effects of the other SNPs drops markedly as illustrated by the results for BTA 14 in Figure 5 . Conversely , when there are two or more QTLs in a small region , such as BTA7_93-98 Mb , the SNPs show low correlations across traits and are still significant after the most significant is included in the model ( Figure 6 ) . There are few reports in the literature that aim to distinguish between linked and pleiotropic QTLs [29]–[31] . Karasik et al . [29] and Olsen et al . [30] conclude that pleiotropy exists if the same SNP or QTL region affects both traits . David et al . [31]'s method uses only two traits but , like ours , is based on the correlation between SNP effects . Pleiotropy of individual QTL contributes to the genetic correlation between traits . If two traits have a high and positive genetic correlation it implies that most QTL affect them both in the same direction . For instance , most SNPs with significant effects affect height and weight in the same direction and thus help to explain the known high genetic correlation between these two traits [32] . Past research [33] , [34] has also found a positive genetic correlation between meat tenderness and marbling or intra-muscular fat . Consistent with that we found that SNPs that increase tenderness ( decrease LLPF ) usually increase marbling ( CMARB or CIMF; Table 5 ) . Similarly , SNPs that increase IGF1 concentration nearly always decrease age at puberty explaining the negative genetic correlation between these traits . A low genetic correlation between two traits might imply that they are controlled by different QTL but it could also indicate some QTL affect them in the same direction and some in opposite directions . For instance , a low genetic correlation between weight and fatness [34] could be explained by the fact that some QTL affect weight and fatness in the same direction ( Group 3 ) whereas others affect them in opposite directions ( Group 1 ) . Some significant SNPs map near to already known genes with effects on the traits studied , such as calpain 1 , calpastatin and PLAG1 . In other cases there are candidates that are homologous to known genes affecting growth and composition in other species ( e . g . , HMGA2 ) . However , there are QTL in Table 7 for which we could find no obvious candidate in cattle . We defined 4 groups of SNPs by a cluster analysis of the 28 lead SNPs such that SNPs within a group have a somewhat similar pattern of effects across traits . These groups were expanded by including SNPs whose effects were correlated with those of one of the lead SNPs in the group . If the 4 groups of QTL represent different physiological pathways , one might expect the genes that map near the QTL of a group to show some similarity of function . To an extent this is so . Group 2 SNPs , which are associated with tenderness , include SNPs near calpain 1 ( CAPN1 ) and calpastatin ( CAST ) that affect tenderness via muscle fibre degradation [12]–[15] . Other SNPs in group 2 are close to genes involved in fat metabolism ( acyl-CoA synthetase and fatty acid desaturase ) . This may be coincidental but there is a known genetic correlation between intra-muscular fat and tenderness [34] and SNPs in group 2 tend to affect both traits ( Table 5 ) . Of the SNPs in Group 1 , one on BTA 14 probably tags PLAG1 , the 2 SNPs on BTA 5 are near HMGA2 and IGF1 , respectively , the SNP on BTA 21 is near PLIN , the SNP on BTA 6 is near CCKAR and within 2 Mb of NCAPG , all of which have been reported to affect size in other species [35]–[41] . The mechanism by which they do this is uncertain . HMGA2 is a transcription factor needed to prevent stem cells from differentiating and thus a polymorphism in it could affect growth prior to terminal differentiation . IGF1 is the growth factor that mediates the effect of growth hormone . PLAG1 is a transcription factor thought to regulate expression of IGF1 , which is important in growth . PLIN encodes a growth factor receptor-binding protein that interacts with insulin receptors and insulin-like growth-factor 1 receptor ( IGF1R ) . PLIN is required for maximal liposis and utilization of adipose tissue [42] . Group 3 SNPs affect fatness and the SNP on BTA 3 are in the leptin receptor gene ( LEPR ) , the SNP on BTA 13 is near LPIN3 ( which regulates fatty acid metabolism ) , the SNP on BTA 21 is again near PLIN indicating that this QTL has similarities to both groups 1 and 3 ( Table 7 ) . LEPR is a receptor for leptin and is involved in the regulation of fat metabolism . It is known that leptin is an adipocyte-specific hormone that regulates body weight and plays a key role in regulating energy intake and expenditure . Other Group 3 SNPs were near genes that encode muscle proteins such as myosin and actin , which are involved with muscle contraction ( e . g . , myotilin on BTA 7 encodes a cytoskeletal protein which plays a significant role in the stability of thin filaments during muscle contraction ) . We do not know which , if any , of these genes contain causal mutations but it seems likely that the QTL within each group are somewhat heterogeneous . This would not be surprising given the complexity of feedback mechanisms of growth of mammals . It may be that changes to either muscle or fat growth indirectly affect growth of the other tissue . However , even QTL that have a similar pattern of pleiotropic effects , show differences in the detail of this pattern . For instance , the Group 1 QTL might all be described as affecting ‘mature size’ , but the one on BTA 14 , which is presumably PLAG1 [9] , [11] , has a greater effect on reproductive traits than the others in Group 2 . On the other hand , the QTL on BTA 5 has an unusual pattern of effects in that it redistributes fat from the P8 site on the rump to the rib and intramuscular depots . This QTL maps close to the gene HMGA2 , which contains polymorphisms affecting growth , fatness and fat distribution in humans , mice , horse , and pigs [35] , [36] , [38] , [39] . Based on these results , it would appear that , although QTL can be put in meaningful groups , each QTL has its own pattern of effects . For instance , PLAG1 might be described as a gene affecting mature size but with additional effects on reproduction , while HMGA2 affects mature size and fat distribution . This could be explained if genes exist in a network rather than in pathways . Then each gene has a unique position in the network and therefore a unique pattern of effects . In addition , many genes occur in multiple networks in which they can have different functions . Beef cattle breeders seek to change the genetic merit of their cattle for many of the traits studied here . The pattern of effects of each QTL indicates that some would be more useful for selection than others . Some QTL have desirable effects on one trait but undesirable effects on other traits . For instance , Brahman breeders have evidently selected for the allele of PLAG1 that increases mature size [11] , but this has decreased the fertility of their cattle . On the other hand , some QTL have an allele with desirable effects on more than one trait and appear to be good targets for selection . For instance , the QTL on BTA 4 has an allele that increases retail beef yield and marbling but also decreases sub-cutaneous fat , which is a highly valuable pattern . Selection for this allele would be beneficial in cattle intended for most markets because cattle prices reflect yield and intramuscular fat scores , whereas subcutaneous fat generally enters the by-product stream . In conclusion , we have used a novel multi-trait , meta-analysis to map QTL with pleiotropic effects on 32 traits describing stature , growth , and reproduction . The distinctive features of the method are 1 ) increased power to detect and map QTL and 2 ) use of summary data on SNP effects when individual level data are not available . We have also presented two methods ( one new ) for distinguishing between linked and pleiotropic QTL ( the correlation between SNP effects across traits and the effects of one SNP conditional on the effect of another SNP ) , and found pleiotropic QTL which appear to cluster into 4 functional groups based their trait effects . We used linear indices of 22 traits 1 ) to validate the effects of SNPs on multiple traits and 2 ) to find additional QTL belonging to the 4 functional groups . We identified candidate genes in those groups that have known biological functions consistent with the biology of the traits .
In total , 729 , 068 SNP data were used in this study . Those SNP were obtained from 5 different SNP panels: the Illumina HD Bovine SNP chip ( http://res . illumina . com/documents/products/datasheets/datasheet_bovinehd . pdf ) comprising 777 , 963 SNP markers; the BovineSNP50K version 1 and version 2 BeadChip ( Illumina , San Diego ) comprising 54 , 001 and 54 , 609 SNP , respectively; the IlluminaSNP7K panel comprising 6 , 909 SNP; and the ParalleleSNP10K chip ( Affymetrix , Santa Clara , CA ) comprising 11 , 932 SNP . All SNP were mapped to the UMD 3 . 1 build of the bovine genome sequence assembled by the Centre for Bioinformatics and Computational Biology at University of Maryland ( CBCB ) ( http://www . cbcb . umd . edu/research/bos_taurus_assembly . shtml . High density SNP genotypes were imputed for all animals using Beagle ( Browning and Browning , 2011 ) . The approaches used for performing quality control and imputation were described in [8] . The details of the quality control and imputation were recapitulated below . Stringent quality control procedures were applied to the SNP data of each platform . SNP were excluded if the call rate per SNP ( this is the proportion of SNP genotypes that have a GC ( Illumina GenCall ) score above 0 . 6 ) was less than 90% or they had duplicate map positions ( two SNP with the same position but with different names ) or an extreme departure from Hardy-Weinberg equilibrium ( e . g . , SNP in autosomal chromosomes with both homozygous genotypes observed , but no heterozygotes ) . Furthermore , if the call rate per individual was less than 90% , those animals were removed from the SNP data . The SNP data were edited within breed group and within each platform and were subsequently combined . After all the quality control tests were applied , 729 , 068 SNP of the HD SNP chip were retained on 1 , 698 animals and the missing genotypes were filled using the BEAGLE program [43] . Imputation was done using 30 iterations of BEAGLE . The genotypes for each SNP were encoded in the top/top Illumina A/B format and then genotypes were reduced to 0 , 1 , and 2 copies of the B allele . The imputations of the 7 K , 10 K and 50 K SNP genotype data to the 729 068 SNPs were performed in two sequential stages: from 7 K or 10 K or 50 K data to a common 50 K data set and then from the common 50 K data set to 800 K data . In the first stage imputation was done within breed , using 30 iterations of Beagle . In the second stage , the HD genotypes of each breed type ( 501 B . taurus and 520 B . indicus ) were used as a reference set to impute from the 50 K genotypes of each pure breed within the corresponding breed type . For the four composite breeds , all the HD genotypes ( 1 , 698 ) were used as a reference set to impute the 50 K genotypes of each composite breed up to 800 K . The number of genotypes for each platform used as reference animals for imputation and number of animals used in this study is given in Table 8 . The mean R2 values , for the accuracy of imputation provided by BEAGLE , are in Table 9 . After imputation , an additional quality control step was applied based on comparing allele frequencies between SNP platforms to detect SNP with very different allele frequencies indicating incorrect conversion between platforms . In total , 10 , 191 animals , which had a record for at least one trait and also had SNP genotypes , were used in this study . The cattle were sourced from 9 different populations of 3 breed types . They include 4 different Bos taurus ( Bt ) breeds ( Angus , Murray Grey , Shorthorn , Hereford ) , 1 Bos indicus ( Bi ) breed ( Brahman cattle ) , 3 composite ( Bt×Bi ) breeds ( Belmont Red , Santa Gertrudis , Tropical composites ) , and 1 recent Brahman cross population ( F1 crosses of Brahman with Limousin , Charolais , Angus , Shorthorn , and Hereford ) . Details on population structure of those animals have previously been described by Bolormaa et al . [8] . Phenotypes for 32 different traits including growth , feed intake , carcass , meat quality , and reproduction traits were collated from 5 different sources: The data sources included the Beef Co-operative Research Centre Phase I ( CRCI ) , Phase II ( CRCII ) , Phase III ( CRCIII ) , the Trangie selection lines , the Durham Shorthorn group ( the detailed description is reported by Bolormaa et al . [8] and Zhang et al . [44] . Not all cattle were measured for all traits . The trait definitions , number of records for each trait and heritability estimate and mean and its SD of each trait are shown in Table 1 . Mixed models fitting fixed and random effects simultaneously were used for estimating heritabilities and associations with SNP . Variances of random effects were estimated in each case by REML . The estimates of heritability were calculated based on all animals with phenotype and genotype data and their 5-generation-ancestors using the following mixed model: trait ∼ mean + fixed effects + animal + error; with animal and error fitted as random effects . The individual animal data for the 32 traits were used to perform genome wide association studies ( GWAS ) , in which each SNP was tested for an association with the trait . The association between each SNP and each of the traits was assessed by a regression analysis using the ASReml software [45] . The model used was the same as for estimating heritability , but SNPi ( SNPi , i = 1 , 2 , 3 , … , 729068 ) was additionally fitted as a covariate one at time ( trait ∼ mean + fixed effects + SNPi + animal + error ) . The model used to analyse the traits consistently included dataset , breed , cohort and sex as fixed effects . Other fixed effects varied by trait . The fixed effects were fitted as nested within a dataset . Further details of the models used in the analysis are reported by Johnston et al . [46] , Reverter et al . [47] , Robinson and Oddy [48] , Barwick et al . [49] , Wolcott et al . [50] , Bolormaa et al . [8] , and Zhang et al . [44] . We applied a new statistic to find the significance level of SNPs in a multi-trait analysis . This statistic determines the importance of the effects of SNPi ( i = 1 , 2 , 3 , … , 729068 ) across all ( 32 ) traits studied . Our multi-trait test statistic is approximately distributed as a chi-squared with 32 degrees of freedom . It tests a null hypothesis stating that the SNP does not affect any of the traits . For each SNP , the multi-trait statistic was calculated by the formula:where ti is a 32×1 vector of the signed t-values of SNPi for the 32 traits ti′ is a transpose of vector ti ( 1×32 ) V−1 is an inverse of the 32×32 correlation matrix where the correlation between two traits is the correlation over the 729 , 068 estimated SNP effects ( signed t-values ) of the two traits . This approximation method is justified as follows: t-values based on many degrees of freedom have an error variance close to 1 . 0 and t2 is distributed as a χ2 ( 1 ) under the null hypothesis . Therefore , if the SNP effects on n different traits were estimated independently with no error covariance , the sum of the t2 ( i . e . , , where I is an identity matrix ) would be distributed as a chi-squared with n degrees of freedom . Our approximate analysis would generate exactly this test statistic if the t values for different traits had no error covariance . If the t values for different traits had an error ( co ) variance matrix D , then the correct test statistic would be distributed as a chi-squared with n degrees of freedom . We approximate D by the correlation between the estimated SNP effects across the 729 , 068 SNPs . We assume that most SNPs have little or no effect on most traits , so most of the ( co ) variance between effects is error covariance . However , the SNPs that do have a real effect on a trait will inflate the variance of SNP effects above 1 . 0 . Therefore we convert the covariance matrix of SNP effects ( D ) to a correlation matrix ( V ) because this returns the diagonal elements to 1 . 0 which we know is the correct error variance for t statistics . Although it is not proof of the method , perhaps we offer the following intuitive analysis . If the SNP effects on different traits were estimated in independent GWAS then the correlation of SNP effects would be low and V≈I and the test statistic would be the sum of independent chi-squares , as expected . On the other hand , if the SNP effects on different traits were estimated from the same individuals , then the correlation of error variances would be driven mainly by the phenotypic correlations between the traits . In this case the correlation of SNP effects would also reflect these phenotypic correlations and the test statistic we use would be a good approximation of the correct test statistic . The gene start and stop positions were identified using Ensembl ( www . ensembl . org/biomart/ ) and SNPs were classified according to their distance from the nearest gene . The SNPs were placed in bins 1 ) <100 kb upstream of the start site or downstream of the stop site , 2 ) 100–200 kb upstream or downstream , etc . , in 100 kb bins . SNPs between the start and stop sites were placed in a separate bin ( called 0 kb from the nearest gene ) . For each bin the proportion of SNPs that were significant ( P<10−5 ) in the multi-trait analysis was divided by the total number of SNPs in that bin . The SNP effects estimated from single-trait GWAS based on all animals were used to investigate the relationships between SNPs . For each pair of SNPs , the correlation of the effects across 32 traits was calculated . Highly positive or negative correlations indicate 2 SNPs with the same pattern of effects across traits . The 28 lead SNPs were selected as follows: On each chromosome the one or two most significant SNPs ( P<10−5 ) , based on the multi-trait analysis , were selected . Two SNPs on the same chromosome were only selected if they clearly represented two different QTL based on the test for pleiotropy vs linkage . In no case were the SNPs less than 2 Mb apart . The regression analyses ( GWAS ) were performed again but additionally the 28 lead SNPs were fitted simultaneously in the model . The statistical model used was trait ∼ mean + fixed effects + SNPi + leadSNP1 + leadSNP2 + leadSNP3 + … + leadSNP28 + animal + error; with animal and error fitted as random effects . The ith SNP ( SNPi , i = 1 , 2 , 3 , … , 729068 ) and 28 lead SNPs were fitted simultaneously as covariate effects . Then a multi-trait chi-squared statistic was calculated for each SNP to test the effects of the SNP across traits after fitting the 28 lead SNPs . For each pair of SNPs among the 28 lead SNPs , the correlation of their effects across the 32 traits was calculated . Then this correlation matrix was used to do the hierarchical clustering of the 28 lead SNPs leading to 4 groups or clusters as shown in the dendrogram drawn using the heatmap function of the R program [52] . For each of the 28 lead SNPs , we searched for additional SNPs with a similar pattern of effects . To do this we used the linear index that showed the highest association with a lead SNP , as previously defined for validation of the multi-trait analysis . A new GWAS was performed for each of 28 linear indexes ( yI ) treating it as a new trait ( dependent variable ) . The following model was used: yI ∼ mean + fixed effects + SNPi + animal + error , where animal and error were fitted as random effects and the ith SNP ( SNPi , i = 1 , 2 , 3 , … , 729068 ) was fitted as a covariate effect . The SNPs that have significant associations ( P<5×10−7 ) with at least one of the indexes based on lead SNPs were selected for assigning into 4 groups . These additional significant SNPs were assigned to the same group as the lead SNP whose linear index with which they had the most significant association . The genes that occur within 1 Mb of the SNPs in this expanded list were identified using Ensembl ( www . ensembl . org/biomart/ ) and , in some cases , a plausible candidate for the phenotypic effect was identified . | We describe novel methods for finding significant associations between a genome wide panel of SNPs and multiple complex traits , and further for distinguishing between genes with effects on multiple traits and multiple linked genes affecting different traits . The method uses a meta-analysis based on estimates of SNP effects from independent single trait genome wide association studies ( GWAS ) . The method could therefore be widely used to combine already published GWAS results . The method was applied to 32 traits that describe growth , body composition , feed intake and reproduction in 10 , 191 beef cattle genotyped for approximately 700 , 000 SNP . The genes found to be associated with these traits can be arranged into 4 groups that differ in their pattern of effects and hence presumably in their physiological mechanism of action . For instance , one group of genes affects weight and fatness in the opposite direction and can be described as a group of genes affecting mature size , while another group affects weight and fatness in the same direction . | [
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] | 2014 | A Multi-Trait, Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature, Fatness and Reproduction in Beef Cattle |
Ethiopia bears a high burden of visceral leishmaniasis ( VL ) . Early access to VL diagnosis and care improves clinical prognosis and reduces transmission from infected humans; however , significant obstacles exist . The approximate 250 , 000 seasonal mobile workers ( MW ) employed annually in northwestern Ethiopia may be particularly disadvantaged and at risk of VL acquisition and death . Our study aimed to assess barriers , and recommend interventions to increase access , to VL diagnosis and care among MWs . In 2017 , 50 interviews and 11 focus group discussions were conducted with MWs , mobile residents , VL patients and caretakers , community leaders and healthcare workers in Kafta Humera District , Tigray . Participants reported high vulnerability to VL among MWs and residents engaged in transitory work . Multiple visits to health facilities were consistently needed to access VL diagnosis . Inadequate healthcare worker training , diagnostic test kit unavailability at the primary healthcare level , lack of VL awareness , insufficient finances for care-seeking and prioritization of income-generating activities were significant barriers to diagnosis and care . Social ( decision-making and financial ) support strongly and positively influenced care-seeking; workers unable to receive salary advances , compensation for partial work , or peer assistance for contract completion were particularly disadvantaged . Participants recommended the government/stakeholders intervene to ensure: MWs access to bed-nets , food , shelter , water , and healthcare at farms or sick leave; decentralization of diagnostic tests to primary healthcare facilities; surplus medications/staff during the peak season; improved referral/feedback/reporting/training within the health system; free comprehensive healthcare for all VL-related services; and community health education . Contrary to what health policy for VL dictates in this endemic setting , study participants reported very poor access to diagnosis and , consequently , significantly delayed access to treatment . Interventions tailored to the socio-economic and health needs of MWs ( and other persons suffering from VL ) are urgently needed to reduce health disparities and the VL burden .
Visceral leishmaniasis ( VL ) is a neglected tropical disease caused by the protozoan Leishmania donovani in the Indian subcontinent and East Africa , and Leishmania infantum in Latin America and the Mediterranean basin [1 , 2] . The bite of the sand fly transmits VL [2] . The World Health Organization ( WHO ) , using reported cases from 2004 to 2008 , estimates 188 , 900 to 365 , 500 new VL cases each year in the six high VL burden countries of Bangladesh , Ethiopia , India , Nepal , South Sudan and Sudan [3]; newer estimates ( based on reported cases from 2010–2014 in the same six countries ) range from approximately 41 , 000 to 68 , 000 new VL cases annually ( Dr . Josè Antonio Ruiz-Postigo , oral communication at the 6th World Congress on Leishmaniasis , Toledo , Spain , May 17 , 2017 ) . These six countries , together with Brazil , account for more than 90% of the worldwide VL cases [2] . In Ethiopia , VL is primarily anthroponotic [4] . The estimated incidence of symptomatic VL in Ethiopia ( based on reported cases 2004–2008 ) ranges from 3 , 700 to 7 , 400 cases per year , with two- to four-fold underreporting surmised [3]; newer estimates ( based on reported cases 2010–2014 ) range from approximately 2 , 600 to 3 , 900 cases per year , with an estimated underreporting factor of 1 . 2 to 1 . 8 ( Dr . Josè Antonio Ruiz-Postigo , oral communication at the 6th World Congress on Leishmaniasis , Toledo , Spain , May 17 , 2017 ) . Endemic areas include the northwest , southwest , central and southern lowlands , with the northwest region bearing the greatest burden of disease [3] . Seasonal dynamics exist; environmental and climatic conditions that influence the distribution and abundance of sand fly vectors are associated with peak periods of VL transmission in human populations [5–7] . Furthermore , drug-resistant strains , immune suppression linked to malnutrition and HIV co-infection , and population movements contribute to VL emergence and re-emergence [8 , 9] . In the VL endemic Humera-Abdurafi-Metema area of Ethiopia , agricultural development has spurred the migration of approximately 250 , 000 mobile workers ( MWs ) each year [10] . This surge in economically driven migration corresponds to increases in the number of VL cases , and associated deaths , in areas that previously did not experience VL epidemics [3 , 11] . Without treatment , VL is almost always fatal [12] . Delays in detection and treatment increase the risk of morbidity and mortality as well as the dissemination of disease to others [12] . Accordingly , early access to VL care is imperative to improve clinical prognosis and reduce transmission via human reservoirs . Unfortunately , significant barriers to access to care exist . In Ethiopia , known obstacles to access to VL care include a suboptimal number of health facilities offering diagnosis and treatment as well as transportation constraints [3] . Insufficient financial resources for care-seeking also hinder access; though VL diagnostics and treatment are free in the country , patients must pay other healthcare fees and associated costs [3] . VL awareness , among certain populations and healthcare providers , is also limited [3 , 11 , 13] . To address these challenges , numerous partners , including WHO , in collaboration with the Ethiopian Federal Ministry of Health , support VL research and healthcare service delivery [14] . At present , Médecins Sans Frontières ( MSF ) offers comprehensive free care for VL patients at a hospital in Abdurafi [14] . In addition , KalaCORE , a consortium of partners including Drugs for Neglected Diseases Initiative , the London School of Hygiene and Tropical Medicine , Mott MacDonald Ltd and MSF , is supporting the expansion of diagnostic and treatment services for VL through clinical mentoring , supply provision , and other interventions [14] . Currently in Ethiopia , diagnostic test kits and treatment for VL are primarily available at hospitals; very few health centres offer VL diagnostics and even fewer offer VL treatment . Despite progress to expand capacity , access to VL diagnosis and care remains problematic , particularly among certain populations . Previous research has found intense transmission of VL among MWs , who may be disproportionately affected by barriers to access to care , and subsequently at greater risk of VL acquisition and death [11 , 15 , 16] . Reported factors associated with an increased likelihood of clinical manifestations of VL and poor access to diagnosis , management , and care of VL cases , include: movement from non-endemic areas ( where individuals have no/low VL immunity ) to VL endemic areas; poor living conditions and lack of adequate health care provision; low socio-economic status [9 , 17 , 18]; and high HIV-prevalence rates [19 , 20] . In addition , poor nutritional status , characteristic of MWs , is thought to be important although not formally proven [21] . Given that MWs also return home , often moving from endemic to non-endemic VL areas , they may be more likely to encounter health workers who lack prior experience with VL [11 , 13] . During the 2004 to 2007 VL epidemic in Libo Kemkem , healthcare workers mistook early cases of VL among returning MWs for drug-resistant malaria . Data suggest at least a 2-year gap from symptom onset to diagnosis by the time some VL cases were properly identified [11 , 13] . Such impediments have significant consequences at both the individual and population level , such as increased transmission of disease and economic consequences associated with absence from work and healthcare costs . Understanding the extent of barriers to VL care among mobile populations is essential in order to facilitate interventions to overcome potential health disparities and reduce the overall burden of VL . However , current knowledge is lacking . To address gaps in knowledge , our study aimed to assess obstacles to VL diagnosis and care , and ultimately to provide recommendations to guide the development of innovative strategies to increase access to VL care among MWs in Kafta Humera District , Tigray , Ethiopia .
The Health Research Ethics Review Committee of the College of Health Sciences of Mekelle University in Ethiopia ( Reference: ERC 0796/2016 ) and the Comité de Protection des Personnes Ile de France XI in France ( Reference: 16036 ) approved the study . Study implementation observed the principles of the Declaration of Helsinki and the International Ethical Guidelines for Biomedical Research involving human subjects , published by the Council for International Organizations of Medical Sciences . All participants provided written informed consent . The study took place in the highly VL endemic lowland area of northwest Ethiopia , near the town of Humera , Tigray National Regional State . Large-scale agriculture plays an important role in the local economy . Production of sesame , cotton and sorghum annually attracts many MWs from other areas of Tigray and various regions in Ethiopia . MWs stay in the farm areas near Humera for months during the agricultural season . The study used a qualitative research design comprised of focus group discussions ( FGD ) ( aiming to include six to ten participants per group ) and semi-structured , in-depth interviews as the main data collection techniques . A topic guide helped to ensure that interviewers addressed the main themes of the study , but did not limit deeper exploration of emergent themes that arose during the interviews and FGDs [22] . This approach enabled the exploration of the opinions , beliefs , feelings and needs of the study population as they relate to VL diagnosis and treatment [22] . Table 1 presents the definitions used in the study , based , in part , on those in previously published literature [10 , 23 , 24] . Males and females , at least 18 years of age , were recruited using purposive and snowball sampling techniques . Six different categories of study participants were included: 1 . ) Healthy MWs , 2 . ) Healthy MRs , 3 . ) Caretakers of VL patients , 4 . ) Current and former VL patients , 5 . ) Community leaders , and 6 . ) Healthcare workers . New participants were recruited until no relevant new information was provided from additional interviews ( i . e . , the point of saturation was reached ) [25 , 26] . Current patients were identified in the VL ward of Kahsay Abera Hospital , the district hospital in Humera ( and only hospital in Kafta Humera providing VL treatment ) . Former patients—those completing VL treatment in 2015 , 2016 or 2017—and caretakers were identified based on reviews of health records at health facilities and discussions with healthcare workers , current patients , and authorities; they were traced and recruited from the villages of Adebay , Baeker , Bereket , and Maykadra . MWs and MRs were recruited at the meeting points in Humera and Maykadra where laborers gather in search of work . Community leaders were contacted at their offices or places of activity . Healthcare workers were identified in Kahsay Abera Hospital and in the health centres of Baeker , Bereket , and Maykadra . The field coordinator of the study , clinical staff , health extension workers , and staff from Tigray Regional Health Bureau assisted with participant recruitment . All participants were contacted one to two days prior to interviews or FGDs . Eight academic staff from the University of Mekelle , Ethiopia , were recruited for data collection . They received training on principles of qualitative research with a special emphasis on methods for conducting interviews and animating FGDs and on the epidemiology , diagnosis , and treatment of VL . In addition , with patients and health staff from Shire Hospital ( Tigray National Regional State ) , the research team piloted the interview/FGD topic guide , to ensure its comprehensibility and potential to elicit discussion , while also honing their interviewing skills . The topic guide was adapted based on the results of the pilot . It was also modified following reviews of the interview/FGD transcripts and supervision sessions with senior researchers during data collection for the identification of themes or points that required more detailed or new questioning in subsequent interviews . The topic guide included the following core themes: 1 . ) Migration of MWs , 2 . ) Perception of illness & knowledge of VL , 3 . ) Sources of information on VL , 4 . ) History of VL illness and health-seeking behavior , 5 . ) Satisfaction with healthcare providers and the medical system , 6 . ) Adherence to VL treatment , 7 . ) Beliefs and preferences for healing/healthcare services , 8 . ) Accessibility and barriers to VL healing/healthcare services , 9 . ) Decision-making within the family/community for choosing to pay for or seek external care , 10 . ) Perception of the VL economic burden , 11 . ) Practices and perceptions of healthcare providers , and 12 . ) Perception of previous interventions and suggestions of changes/future interventions . Interviews and FGDs were recorded using digital recorders . Sex , age , residence , education level and occupation were collected to have a general idea of the study population and to categorize participants; this information was written down on paper during the interview and later entered into a spreadsheet . Care was taken to find a location that allowed for confidentiality and suitable sound recording quality . The interviews/FGDs took place in the health centres or the hospital , at the homes of participants , or on the premises of the individual’s professional environment . Interviews were conducted with one data collector . For FGDs , data collectors worked in pairs , with one serving as the moderator , and the other as the note taker . Each data collector worked in each role , according to the senior researchers’ plan . All interviews/FGDs were conducted in the local language with which the interviewees felt most comfortable; most interviews were in Tigrigna , and a few were in Amharic . At the completion of the interview , each participant was informed about and received compensation in Ethiopian Birr for their participation . The compensation was in accordance with the principles of the Declaration of Helsinki and the International Ethical Guidelines for Biomedical Research involving human subjects to compensate for loss of income during study participation . Daily debriefing sessions occurred between the senior researchers and data collectors to ensure quality assurance , review of identified themes , and strong communication . After each recording , data collectors transferred audio-files to a computer . Data were transcribed and then translated into English . The senior researchers reviewed all English translations , ensuring comprehensibility without specific local knowledge . Uncertainties and ambiguities were discussed with the data collectors and reformulated to a common agreement . Data were imported into Atlas . ti ( Version 7 . 0 , Berlin ) qualitative data analysis software . Three researchers ( the principal investigator and two senior researchers ) coded the data using inductive qualitative content analysis [27] . Emergent categories and themes were identified based on meticulous and systematic reading and coding of the transcripts . Codes and sub-codes were refined . Each transcript was coded , at minimum , by one researcher and reviewed , at minimum , by one other researcher . The principal investigator reviewed all coding and ensured cohesion in the approach and use of themes . All transcription , translation , and analyses occurred with anonymized data .
From 28 January to 23 February 2017 , 50 interviews and 11 FGDs were conducted , totaling 137 study participants . Table 2 presents the number of FGD and interview sessions conducted according to each participant category . Interviews lasted , on average , 45 minutes . Among interview participants , the median age was 31 years ( range: 19–71 years ) and 76% were male . Most participants originated from Kafta Humera District; only one participant originated from a highland area of Ethiopia . Nearly one quarter of interview participants had either no formal education or only the ability to read and write . Occupations of interview participants included: religious leaders ( i . e . , imam , nun , priest ) , political and public health authorities , civic authorities/leaders , hired farmers , subsistence-level farmers , farm owners , herders , tractor drivers , medical professionals ( e . g . , doctor , nurse , pharmacist ) , traditional healers , and students . FGDs ranged in size from six to 10 participants—approximately 60% of whom were male—and lasted on average 94 minutes . The following occupations were represented: hired farmers , subsistence-level farmers , medical professionals ( i . e . , pharmacy technician , nurse , health extension worker , public health nurse ) , heads of health centers , wives of hired farmers , students and drivers . S1 and S2 Tables provide in more detail the characteristics of participants included in the interviews and FGDs , respectively . Participants from all respondent categories stated that sleeping around black cotton soil , under trees or near sandy areas , living around farming areas in the lowlands , hunger , and fatigue put individuals at risk of VL . In addition , individuals without adequate financial resources , those belonging to younger age groups , those lacking knowledge and experience with VL , those not wearing protective long-sleeved clothes , individuals without family nearby , and those not using bed-nets were considered particularly at risk . The aforementioned risk factors characterized MWs , whom study participants from all respondent categories consistently named as the most vulnerable group for VL . Residents engaged in agricultural work , particularly mobile residents ( MRs ) , were also considered vulnerable . Different levels of community awareness were reported . Considering all respondent categories , many participants felt that community awareness of VL was high , while others stated that it was low . The divergence in opinions appeared related to the population in question , with MWs much less aware than the resident population . Nevertheless , even for those with greater knowledge , awareness alone was insufficient for early access to diagnosis and care . Most community members ( i . e . , MWs , MRs , caretakers of VL patients , VL patients ) and community leaders correctly named the lowland areas of Western Tigray as an area endemic for VL . They also largely attributed VL transmission to the bite of a sand fly and reported cracked black cotton soil as well as the area under balanite and acacia trees as the sand fly habitat . However , community members and leaders often simultaneously proposed other modes of transmission , including: contact with a leaf; contaminated food; dirt/sand/lack of sanitation; animal dung; evil; contact with a fomite; increased body temperature; the bite of a mosquito; person-to-person transmission , unclean/stagnant water; or worms . Furthermore , numerous community members and leaders attributed VL to a process of ‘disease evolution’ , whereby malaria evolved into VL directly , or via an intermediary step ( s ) including typhoid fever and/or pneumonia; some stated this resulted from not seeking treatment early . Considering all respondent categories , some participants considered VL health education adequate , while the vast majority found it insufficient . That health education was largely facility-based rather than community-based represented the main criticism . Even when reaching the community , health education was either void of information on VL , too general , or delivered inconsistently . Local community groups , capable of informing and mobilizing the community , were considered underutilized . Patients previously treated for VL constituted the main source of VL information for the community . Community members and leaders offered many suggestions for preventing VL , linked to the various modes of transmission they attributed to VL acquisition . Table 3 presents the protective measures mentioned by community members and leaders , categorized according to their focus on the environment or person . Among the suggested protective measures , bed-nets constituted the measure mentioned the most often as an important VL prevention strategy . Nevertheless , across all respondent categories—including MWs themselves—participants repeatedly and consistently stated that MWs did not use bed-nets . Reports of use of bed-nets by residents were inconsistent , with some participants stating that residents always used bed-nets and others stating the opposite . Participants provided many explanations for the non-use of bed-nets . Table 4 presents these reasons , categorized according to financial/procurement and utility/credibility constraints . Regarding one of the constraints , that of the effectiveness of bed-nets in relation to mesh size , participants perceived that the width of the mesh of bed-nets prevented the entry of mosquitoes , but not of sand flies . The majority of participants across all respondent categories considered VL a very serious disease—both in terms of its detriment to physical health and financial consequences—with early care important . Nevertheless , few community members sought care at symptom onset , particularly among the MWs . Delays in seeking care ranged from several days to several months to several seasons . Participants across all respondent categories reported that gaps in VL awareness inhibited early healthcare-seeking , with MWs coming from non-VL endemic areas particularly at risk . Sick individuals ( both residents and non-residents alike ) often failed to recognize VL . They confused their symptoms with those of other diseases—especially malaria—and underappreciated the seriousness of their situation . Many hoped for self-resolution of their illness or self-diagnosed and self-medicated for other diseases in lieu of seeking care at a health facility . Socio-economic constraints constituted a major barrier to early healthcare-seeking . Sick individuals often lacked money to pay for healthcare services . While some local residents benefited from a health insurance plan that helped mitigate costs by reducing healthcare expenditures in exchange for an annual fee , MWs coming from outside the area were not eligible for the plan . Policy establishes the provision of social services in the form of fee waivers , however no patients interviewed ( neither MWs , MRs , nor residents ) mentioned having received such aid . One healthy MW interviewed even stated that this aid was not given to MWs . Binding contracts and fear of loss of income also contributed to delayed healthcare-seeking . MWs and MRs relied on the income they earned during the agricultural season for subsistence for themselves and their families . They were highly dependent on the farm owners , who paid them upon completion of their work . Few farm owners paid workers who fell ill for partial work completion , or allowed workers to seek care and return later to complete their work . Accordingly , any break in agricultural activities for VL healthcare-seeking potentially resulted in major financial losses , both in terms of direct costs ( i . e . , healthcare fees ) and indirect costs ( i . e . , loss of income during the month-long VL treatment ) . Social support , particularly decision-making systems within the family and community for choosing to pay for or seek external care , strongly influenced healthcare-seeking behavior . The caretaker , rather than the sick individual , was responsible for making decisions on care seeking and ensuring the quality of the care received . As caretakers are often family members , and MWs and MRs were usually far from their families , among the mobile population , the responsibility for decision-making for seeking care shifted to the sick MW/MR themselves . Community members reported that peers—especially those of MWs and MRs—also played an important role in decision-making and ongoing support , including helping the MW/MR to the health facility and taking over work responsibilities ( as permitted by the farm owner ) . Family and community members , especially those with a previous history of VL and therefore knowledge of VL , were influential in motivating sick individuals to seek healthcare . Family and community members also provided financial support . The charity of the community , including contributions from religious institutions , was important for some sick individuals ( although this was reported by community leaders and MRs , but not by MWs themselves ) . In addition , gaps in legal protections contributed to delayed healthcare-seeking . The law obliges farm owners to provide healthcare services , food , and water to their workers under contract . However , farm owners failed to meet their legal responsibilities—sometimes with government impunity—and often directly interfered with early healthcare-seeking . Furthermore , MWs did not benefit from sick leave . Not all reports of farm owners by MWs were negative , however . Some farm owners provided advance payments to their workers for healthcare-seeking or took MWs to health facilities themselves . Yet this generally occurred when the MW had a special relationship with the farm owner ( either a direct family tie or having worked for a long time with the farm owner ) or to protect the farm owner or manager from problems with the government . Importantly , these interventions facilitated healthcare-seeking , but they still generally occurred late , once the health of the MW had already significantly deteriorated . Unrelenting , increasingly severe illness motivated individuals to seek healthcare eventually . In addition to seeking relief from their suffering , healthcare seeking at this point represented , for many , awareness that their unresolved , worsening condition was not another common disease , but rather VL , for which they deemed healthcare necessary ( i . e . , it would not resolve on its own and they were unable to continue working ) . Most community members and leaders considered hospitals as the best place for VL treatment , but prior to diagnosis and treatment , almost all sick individuals consulted other providers . Not a single MW reported the availability of HC services on farms . Numerous factors influenced decisions regarding where to seek care . Sick individuals usually sought care at the health facility the shortest distance from their residence ( local residents ) or work location ( MWs/MRs ) , or the one in closest proximity to their families to ensure having a caregiver . While most sick individuals started at the primary healthcare level , some reported that for more severe illnesses , they preferred seeking care directly from a higher-level health institution . Public health facilities were preferred due to their lower cost of care; however , individuals with access to financial resources visited private health facilities—considered as more efficient and respectful . Most community members and leaders , including traditional healers themselves , did not discount traditional medicine as a whole , but asserted that traditional medicine was not useful against VL . Visits to traditional healers were motivated by a lack of recognition of the signs and symptoms of VL by the sick individual and/or frustration with the failure of the modern health system to identify their illness . Access to VL diagnosis consistently required multiple visits to health facilities . Sick individuals made as many as 10 repeat visits to the same health center for the same illness episode . Below , we present an analysis of the typical trajectory through the different healthcare modalities; this analysis is representative of VL patients and caregivers of VL patients in the study as they consistently reported their shared experience with these healthcare-seeking steps . While access to diagnosis represented a major obstacle , access to treatment was much better . Once diagnosed , most patients reported rapidly starting treatment . Furthermore , community members and leaders expressed a high level of confidence in modern VL treatment . This confidence extended even to community members and leaders who mentioned patients dying after receiving injections to treat VL . Almost all of these participants stated that this did not make them question the treatment; rather , they reported that the patient initiated treatment too late , after their condition had severely deteriorated . While the length of treatment and pain of injection were extremely burdensome , almost all patients adhered strictly to VL treatment . VL created a heavy financial and workload burden on the public healthcare system . Shortages of supplies and healthcare staff , allocated to health facilities based on the number of residents living in the community , were experienced during the massive influx of MWs . Low work attendance at the public health institutions by physicians busy in their private practice exacerbated understaffing . Furthermore , inadequate reporting within the healthcare system contributed to supply ruptures . Between health facilities , referrals , the flow of information , and feedback about patients functioned suboptimally . In the community , health extension workers—individuals affiliated with a health post/satellite of the health center and responsible for conducting door-to-door health outreach activities in their district [28]—lacked a formal referral form . Furthermore , without ambulances , in the event of referrals , patients or their caregivers bore the responsibility of getting from one health facility to another . Many participants , across all respondent categories—including healthcare workers themselves , reported that healthcare workers , from the lowest to highest cadres , were not adequately aware of or prepared for VL . Factors influencing knowledge and preparedness included the healthcare facility level , length of service in a VL endemic area , education attained , training received , and prevalence of VL ( e . g . , the healthcare worker’s exposure to patients with VL ) . The most capable healthcare workers included hospital staff , as well as those with a longer duration of service , superior level of education , ample training , and significant experience working in a highly VL-endemic area . In accordance with national policy , diagnostic test kits and treatment were available at government hospitals . Despite some reports of bed shortages , as well as test kit , laboratory reagent , and drug supply ruptures , overall most participants , across all respondent categories , considered diagnosis and treatment of VL effective at the hospital level . However , the lack of VL diagnostic test kits at public health centres , as well as from private health facilities , constituted a major impediment to preparedness . This may be attributed to: 1 . ) The difficulty of diagnosing VL based on clinical signs and symptoms , and 2 . ) The resulting lack of prioritization and focus given to VL as the result of the inability to effectively diagnose it at the health centre .
Our study population included fewer MWs from the highlands than expected . This could have been due to the State of Emergency declared by the Ethiopian government on 09 October 2016 that may have resulted in fewer MWs coming from the highlands and other regions of the country to the lowlands of Western Tigray for agricultural work . Additionally , the State of Emergency delayed the commencement of the study , which may have contributed to the presence of fewer MWs in the area ( i . e . , MWs who came for agricultural work had already returned home when the study started . ) . As MWs from the highlands would be expected to be more vulnerable to VL and less familiar with VL than those from the lowlands , our study results may underrepresent the extent of VL vulnerability of MWs and overestimate the extent of VL knowledge of MWs . Importantly , our study participants included not only MWs , but also community leaders , healthcare workers , mobile residents , current/previous VL patients and caretakers of VL patients , all of whom who spoke not only of their own experiences , but also of the experiences of others . The results of our study may not be entirely generalizable to populations at risk for VL , though importantly , this was not an objective of the research , given its qualitative design . Rather , our research aimed to explore in depth the opinions , beliefs , and feelings of the study population’s needs as they relate to VL diagnosis and treatment . Qualitative methods are increasingly used for health research given their suitability for better understanding peoples’ attitudes , behavior and decisions [25] . To our knowledge , our study is the first in Ethiopia to use qualitative methods to assess barriers to VL diagnosis and care among mobile seasonal workers . Accordingly , our results have important public health and policy implications . Specifically , our results may help guide the development of strategies to increase access to VL diagnosis , allowing for earlier treatment and better prognosis for VL patients , and reducing the potential health disparities and the overall burden of VL . Our study findings support the following recommendations: Contrary to what health policy for VL dictates in this endemic setting , access to diagnosis was very poor and access to treatment was , consequently , significantly delayed . The free provision of diagnostic test kits and treatment is a very positive step . At the same time , none of our participants reported access to VL diagnostic test kits at the health center level , which represented a significant barrier to care . Patients incurred high expenses prior to finally being correctly diagnosed with VL , paid many expenses supplemental to VL treatment , and suffered a total loss of income during their lengthy hospital stays . Delays in diagnosis contributed to increased severity of disease , which , at best , led to additional financial losses and at worst , resulted in death . Interventions tailored to the socio-economic and health needs of MWs and MRs , as well as to other persons suffering from VL , are needed to reduce health disparities and the burden of VL . | Ethiopia bears a high burden of visceral leishmaniasis ( VL ) —a neglected tropical disease transmitted through the bite of a sand fly that disproportionately affects vulnerable populations . Without treatment , VL progresses , causing increasingly severe symptoms and ultimately death within two years , in most cases . Early access to VL diagnosis and care improves clinical prognosis and reduces transmission from infected humans; however , significant obstacles exist . To our knowledge , our study is the first in Ethiopia to use qualitative methods to assess barriers to VL diagnosis and care among seasonal mobile workers . Strikingly , we found that contrary to what health policy for VL dictates in this endemic setting , study participants reported very poor access to diagnosis and , consequently , significantly delayed access to treatment . Our findings have important public health and policy implications . Specifically , our results offer strategies that may increase access to VL diagnosis and care , allowing for earlier treatment and better prognoses for VL patients , and reducing the potential health disparities and the overall burden of VL . | [
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] | 2018 | Barriers to access to visceral leishmaniasis diagnosis and care among seasonal mobile workers in Western Tigray, Northern Ethiopia: A qualitative study |
Neurocysticercosis is a common cause of seizure disorders in children of Western Nepal . The clinical presentation is variable . The incidence varies depending on the food habits and ethnicity of the population . The present study was undertaken with the objective of studying the mode of presentation , radiological findings and to determine the recent trend of the disease in children of Western Nepal . Records from the Department of Pediatrics , Manipal Teaching Hospital , Pokhara , Nepal of children aged 0–17 years admitted from 2003 to 2015 and with the discharge diagnosis of seizure and neurocysticercosis ( NCC ) were reviewed . The diagnosis was primarily based on clinical features , neurological involvement and CT and MRI studies . Seizures due to other CNS pathologies were excluded . Patients with NCC were treated with Albendazole15mg/kg/day for 28 days with supportive treatments for seizures and raised intracranial pressure . Patients were followed up for one year after the completion of the treatment . There were 1355 cases of seizure disorders , out of which 229 ( 16 . 90% ) were NCC . There were 99 ( 43 . 23% ) in the age group 6–10 years followed by 91 ( 41 . 09% ) in the age group of 11–15 years . Seizures were the most common presenting symptom in 88 . 65% , followed by raised ICP in 9 . 61% . Neuropsychiatric changes were noted in 38 cases ( 16 . 59% ) . CT scan findings revealed single lesion in 78 . 16% and multiple lesions in 21 . 83% . Poisson regression analysis showed statistically significant decline of year-wise incidence of NCC cases ( p<0 . 05 ) from 2003 to 2015 . The decline in the incidence of NCC in recent years is most probably attributed to improved hygiene with the construction of household toilets to avoid open defecation and biannual deworming with Albendazole as a part of School Health and Nutrition Project .
Neurocysticercosis ( NCC ) or intracerebral cysticercosis is a common parasitic ( zoonotic ) infection involving the nervous system of human beings resulting in seizure disorder worldwide [1 , 2] . NCC is endemic in parts of South America , Eastern Europe , the Indian subcontinent , South East Asia and Sub-Saharan Africa [2] . NCC is an important cause of focal seizures in north India [3] . Human and porcine taeniasis/NCC is a major zoonotic disorder in Nepal [4–6] . Prevalence rates of NCC in children of Nepal is not known , although in certain ethnic groups adult taeniasis was reported to be 10–50% and porcine cysticercosis 14 to 32% [4–6] . The cyst has four stages: Vesicular stage—The scolex is on one side of cyst and appears as an opaque 4 to 5 mm nodule . Once the cyst degenerates an inflammatory response is elicited and goes through a colloidal stage where larva undergoe hyaline degeneration and gelatinous material appears in the cyst . Granular nodular stage- the cyst contracts and is replaced by local lymphoid nodules and necrosis . Nodular calcified stage- the granular tissue is replaced by collagenous structure and calcification . NCC involves the brain parenchyma , meninges , spinal cord and eyes . Cysticerci also develop in muscles . Clinical manifestations mainly depend on the location , numbers and variability of the cysts and on the host immune response [7] . The most common CT finding in children presenting with seizures is a single small ( <20mm ) , low density lesion with ring enhancement named Single Small Enhancing Computer Tomographic Lesion . It represents a cystic lesion associated with mild to moderate perilesional edema and hyperdense eccentric scolex which is pathognomonic of cysticercosis . Numerous cysts of varying stages give the typical ‘Starry Sky” appearance [8] . NCC is one of the main causes of epileptic seizure and accounts for 50% of the patient with partial seizures [9 , 10] . In an earlier study conducted at the Manipal Teaching Hospital , Pokhara , a tertiary care center of western Nepal , 109 patients ( 16 . 07% ) were diagnosed as cases of NCC amongst 678 cases admitted for partial seizures in a period extending from 2004 to 2009 [11] . The incidence of NCC among people admitted for epilepsy in Latin America , sub Saharan Africa and south East Asia is 29% [12] . The larvae develop in brain parenchyma , meninges , spinal cord , eyes and muscles , and will result in symptoms . Parenchymatous lesions usually manifest as seizure disorder or epilepsy , being simple partial seizures , complex partial seizures , generalized seizure , encephalitis and pseudotumor cerebri . Extra parenchymal NCC is less common in children compared to adults and may appear as multilobed CSF isointense lesions that occupy the cisterns , Sylvian fissure or cerebellopontine angle . Arachnoiditis and chronic meningitis , such as enhancement of tentorium and basal cisterns , hydrocephalous and occasionally infarcts may be seen [13] . With such variability in incidence and clinical presentation of NCC all over the world , we attempted to review the documents of all seizure disorders admitted and discharged of the Manipal Teaching Hospital with diagnosis of NCC from January1st 2003 to December 31st 2015 .
Prior to the study , the institutional Ethics Committee at Manipal Teaching hospital , Pokhara , Nepal , gave ethical approval . The Research was conducted in accordance with the latest version of the Declaration of Helsinki . Data obtained were anonymous to protect patient privacy and confidentiality . Data analysis was performed using SPSS version 18 . Continuous data was presented as mean and SD and categorical data expressed as frequency , percentage and 95% confidence interval . Trend of the data was explored using graphs and Poisson regression . NCC and total seizures were considered a dependent variable while time in years was taken as an independent variable .
From January 1st 2003 to December 31st 2015 , 1355 cases with seizure disorder were identified . Out of these , using clinical data and by CT and MRI , 229 cases were diagnosed as NCC ( 16 . 90% ) . The maximum number of NCC cases was detected in 2007 and 2008 ( 32 and 30 cases respectively ) . In 2005 out of 72 cases of seizure disorder , 24 were detected as NCC ( Table 1 ) . The incidence of NCC with seizures as presenting symptoms gradually decreased from 2009 to 2015 ( 20 . 83% to 5 . 37% ) . ( Fig 1 ) . Although the percent of cases slightly augmented in 2005 , the general tendency between 2003 and 2015 shows a significant decrease in the number of cases and the percentage of epileptic patients with NCC , that was confirmed by Poisson regression analysis [B = -0 . 112 , P = 0 . 0001] while there was minimal increase in the epileptic patients during the period [B = 0 . 020 , P<0 . 007] . Mean age of incidence of NCC was 9 . 7± 3 . 44 years with median age of 10 years . Youngest age was 11 months and the oldest patient was 17 years . Maximum incidence of NCC presenting as seizure disorder was detected in the age group of 6–10 years ( 99/229 , 43 . 23% ) followed by 10–15 years ( 40 . 61% ) . Overall 192 cases were detected in age group of 6–15 years accounting for 83 . 84% . Male to female ratio is 6:4 . According to ethnicity the maximum incidence was in Brahamins ( 30% ) followed by Dalits ( 22% ) and Chetris ( 20% ) ; while according to district , the disease was more prevalent in Kaski ( 38% ) followed by Syangja ( 36% ) and Tanahun ( 10% ) ; the remaining places had an incidence between 1–5% . Out of 229 cases of NCC , 203 ( 88 . 65% ) children presented with seizure as chief complaint; Simple partial seizures accounted for 140 cases ( 68 . 96% ) followed by generalized seizures in 33 cases ( 16 . 20% ) and complex partial seizures 30 ( 14 . 78% ) . A total of 38 cases of NCC ( 16 . 59% ) presented as neuropsychiatry illness , 22 cases had raised intracranial pressure ( ICP , 9 . 6% ) , 8 cases ( 3 . 49% ) encephalitis and 3 ophthalmoplegia ( 1 . 31% ) . Fever was present in 8 cases ( 3 . 49% ) ( Table 2 ) . The cases of raised ICP and encephalitis although not presented as seizure disorder , had seizures during management . Two cases of extra-parenchymal lesions also presented seizures . CT and MRI findings revealed a single NCC lesion in 179 cases ( 75 . 98% ) and multiple NCC lesions in 65 cases ( 24 . 01% , Fig 2A and 2B ) , The site of involvement detected by CT ( Table 3 ) varied and the lesions were located mainly in the parietal region ( 106 cases , 46 . 29% ) followed by the frontal region ( 36 , 15 . 72% ) , temporal ( 28 , 12 . 27% ) and occipital ( 24 , 10 . 48% ) . Cerebellar lesions were found in 16 cases ( 7% ) , intraventricular in 14 ( 6 . 11% ) , 5 brain stem lesions ( 2 . 46% ) and 2 cases each of subarachnoid and spinal lesions . Only 2 ocular lesions were seen . ( Fig 2C and 2D ) and 23 extraparenchymal lesions ( 10 . 04% ) . Among 229 patients with NCC , 190 ( 82 . 97% ) could be re-evaluated with a repeated CT at one year; the remaining 39 cases were lost for follow up . In the 190 cases reviewed , improvement was observed in 156 cases ( 82 . 10% ) while in 2 cases ( 1 . 05% ) lesions persisted and 32 cases ( 16 . 84% ) had calcifications .
Cysticercosis is mainly divided into parenchymal and extra-parenchymal including cisternal , ventricular , ophthalmic or spinal lesions . The presentation is either as a single parenchymal cyst or multiple cysts . Seizures were mainly seen in parenchymatous location , although extra-parenchymatous lesions could also present seizures due to association with parenchymatous ones . [13] . Cysticercosis remains asymptomatic in the host for years as parasites evade host immunological responses [14] . Poisson regression analysis showed statistically significant year decline of NCC ( p<0 . 05 ) from 2003 to 2015 in contrast with the marginal increase in the total number of children admitted with seizures during the study period . This indicated that although hospital admission due to NCC were reduced , total hospital admissions due to seizures or other etiologies like epilepsy , CNS infections , genetic conditions , metabolic derangements and structural malformations had increased . Out of 229 cases , 203 presented with sudden onset seizure ( 88 . 65% ) . The remaining 26 cases who presented with features of raised ICP , encephalitis , prolonged headache with loss of consciousness , had also manifested seizures during the course of management . In a series of 500 children from northern India , seizures were noted in 94 . 8% cases [14] . Partial seizures were common in children with NCC compared with generalized seizures in the current study . Earlier studies also described partial seizures in most of children with NCC [14–23] Features of raised ICP were seen in 22 cases ( 9 . 61% ) . Features of raised ICP was detected in 30% of patients by Singhi et al [14] . Clinical features suggestive of encephalitis were observed in 8 out of 229 cases ( 3 . 49% ) in the present study . similar to incidence , ranging up to 4 . 8% was noted in earlier studies [21 , 22 , 23]; high morbidity and mortality can be associated [24] . NCC should be a major differential diagnosis in patient with seizure disorder [22] . Immunodiagnosis and histopathological studies of the lesions obtained by surgery , CT and MRI remains valuable diagnostic tools [23] . CT studies and , when necessary MRI , revealed diagnosis of NCC in 229 cases out of 1355 cases reviewed in the study . CT revealed single lesions in 174 cases ( 75 . 96% ) , 55 cases ( 24 . 01% ) of multiple lesions and 90% of the cases revealed peri-lesional edema . Similar data were obtained by Shrestha et al , who described single lesions in 83 . 8% and peri-lesional edema in 89 . 7% of the cases [25] . Maximum number of NCC lesions were seen in the parietal region ( 46 . 29% ) followed by the frontal region ( 15 . 72% ) , temporal ( 12 . 23% ) , occipital ( 10 . 48% ) and lastly cerebellar region of the brain ( 6 . 99% ) ; while Basu et al reported parietal ( 71% ) , frontal ( 49 . 2% ) , occipital ( 37 . 1% ) and temporal ( 29 . 8% ) as common sties in children [22] . Silva et al described isolated or associated calcifications in 95% of adult patients with NCC [26] . Extra-parenchymal lesions had manifested with the features of raised ICP , convulsions and altered sensorium . Other presentations were hydrocephalus , ophthalmoplegia and other focal deficiencies . Most patients with hydrocephalus had presented with features of encephalitis in our series . Ethnical variations showed 30% of patients were Brahmins . Brahmins are the major ethnic group thus , demographic studies are necessary to identify other risk factors for NCC . A striking correlation between the use of cysticidal drugs and the rate of seizure control was found in adults with epilepsy due to NCC [17 , 27 , 28] . It was also found that focal neurological deficits improved after treatment with cysticidal drug . Among patients with complete disappearance of lesions and without repeated seizures , antiepileptic medication could be stopped at one year in 120 ( 63 . 1% ) . In 38 ( 20% ) patients with delayed resolution of lesions , calcified lesions and recurrent seizures , antiepileptic medication was required for 2–3 years . The remaining 32 ( 16 . 8% ) were still on antiepileptic medications beyond 3 years . Two children stopped attending school due to poor academic capacity . An improved outcome was reported in 80% cases in which treatment was given soon after recognition of a Single Small Enhancing Computer Tomographic Lesion [20] . NCC is a disease perpetuated by poor hygiene and inadequate sanitation; it is entirely preventable and potentially eradicable [29] . Risk factors for T . solium suggests that consumption of the raw meat , improper or absence of meat inspection and control , poor sanitation , and use of untreated human waste as fertilizer for crops could have played important roles in endemic areas [30] . An ideal intervention program to stop transmission should include the new proposal of "one health" that involves humans and pigs within the same environment . Studies from hyper-endemic areas showed that after a one-health intervention program ( triple dose of 400mg Albendazole in the form of two mass drug administration ) covering all village residents >6 years of age , the level of taeniasis decreased by 79 . 4% . After the first regime it remained steady with 5 month inter-treatment interval and decreased again by 100% after the second mass treatment regime [31] . A prospective interventional cohort controlled study using screening and treatment of taeniasis among households located within 100m of pigs heavily infested with cysticercus caused 41% reduction in incidence and four times reduction in prevalence of NCC in the intervention village as compared to a control village in northern Peru [32] . Preventive measures included avoidance of open defecation , improved food-handling practices such as thorough cleaning of raw vegetables prior to use , wearing gloves by food handlers and mass administration of anthelminthic drugs in endemic areas [33 , 34] . The present study covering the period of 2003 to 2015 revealed NCC as the main cause of seizure disorder and accounted for 16 . 9% of the patients presenting as simple , partial or generalized seizures; interestingly the rate of incidence of NCC as cause of seizures gradually declined from 20 . 83% in the year 2009 to 5 . 37% in 2014 . In 2014 and 2015 only 13 cases of NCC were detected accounting for 5 . 65% of seizure cases . Improvement of health facilities like hand washing and construction of toilets in school , health education might have contributed in reduction in the incidence of NCC cases . The role of School Health Nutrition Program by the Child Health Division , under the Department of Health Services of the Ministry of Health and Population with biannual distribution of deworming tablets ( Albendazole 400 mg ) on NCC , needs further evaluation [35] .
Neurocysticercosis is one of the main causes of seizures in children of western Nepal accounting to 16 . 9% of the patients . In the present study children in the age group of 6–15 years ( mostly school going children ) accounted for 83 . 84% of 229 cases of NCC detected by seizure disorder , clinical and imaging techniques . Poisson regression analysis showed a statistically significant decline in the incidence of NCC cases from 2003 to 2015 . This result is very interesting and is probably due to improvement of health facilities like hand washing and construction of toilets in schools and houses; Nonetheless implementation of the School Health Nutrition Program by the Child Health Division , under the Department of Health Services of Ministry of Health and Population was probably very important and should be further evaluated together with improved health education and sanitary infrastructure , which might have also contributed to the reduction in the incidence of NCC in children in Nepal . | Neurocysticercosis is a common parasitic infection of the central nervous system . It is caused by larval form of Taenia solium and it has been identified as a “Neglected Tropical Disease” endemic in south East Asia , including Nepal , by WHO . The clinical features in children are pleomorphic depending on the number , location and size of cysticerci . The parenchymatous lesions are presented as neurological symptoms like sudden onset seizures , encephalitis , raised intracranial pressure and neuropsychiatric symptoms . CT and MRI are the main diagnostic tools . Maximum incidence was found in school age children ( 6–15 years ) . Year wise review of percentage of NCC , revealed a declining trend from 20 . 83% in 2009 to 5 . 37% in 2014 . The decline in the incidence of NCC noted in our study might be due to biannual deworming using Albendazole as a part of School Health and Nutrition Programme started by Ministry of Health Services , Nepal in 2008 and extended to all the districts of the country . In addition construction of household and school toilets to avoid open defecation , health education and hand washing facilities might have played a role . Large multicentre trials to evaluate role of biannual Albendazole to prevent cysticercosis is recommended . | [
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] | 2017 | Time trend of neurocysticercosis in children with seizures in a tertiary hospital of western Nepal |
The etiology of ovarian epithelial cancer is poorly understood , mainly due to the lack of an appropriate experimental model for studying the onset and progression of this disease . We have created a mutant mouse model in which aberrant estrogen receptor alpha ( ERα ) signaling in the hypothalamic-pituitary-ovarian axis leads to ovarian epithelial tumorigenesis . In these mice , termed ERαd/d , the ERα gene was conditionally deleted in the anterior pituitary , but remained intact in the hypothalamus and the ovary . The loss of negative-feedback regulation by estrogen ( E ) at the level of the pituitary led to increased production of luteinizing hormone ( LH ) by this tissue . Hyperstimulation of the ovarian cells by LH resulted in elevated steroidogenesis , producing high circulating levels of steroid hormones , including E . The ERαd/d mice exhibited formation of palpable ovarian epithelial tumors starting at 5 months of age with 100% penetrance . By 15 months of age , 80% of ERαd/d mice die . Besides proliferating epithelial cells , these tumors also contained an expanded population of luteinized stromal cells , which acquire the ability to express P450 aromatase and synthesize E locally . In response to the elevated levels of E , the ERα signaling was accentuated in the ovarian epithelial cells of ERαd/d mice , triggering increased ERα-dependent gene expression , abnormal cell proliferation , and tumorigenesis . Consistent with these findings , treatment of ERαd/d mice with letrozole , an aromatase inhibitor , markedly reduced circulating E and ovarian tumor volume . We have , therefore , developed a unique animal model , which serves as a useful tool for exploring the involvement of E-dependent signaling pathways in ovarian epithelial tumorigenesis .
Ovarian cancer is the most lethal malignancy of the female reproductive system and the fifth leading cause of cancer-related death among women [1] . Approximately 90% of malignant ovarian tumors are derived from either the ovarian surface epithelium ( OSE ) or fallopian tube epithelium ( FTE ) [2] . Due to the absence of specific symptoms and the lack of strategies for early detection of ovarian cancer , the majority ( 70% ) of women with this disease are diagnosed at a late stage when the cancer has spread beyond the confines of the ovary [1] . Despite its clinical significance , the etiology of ovarian cancer is poorly understood , mainly due to the lack of an appropriate experimental model for studying the onset and progression of this disease . Multiple theories regarding the etiology of ovarian cancer have been proposed , but the precise molecular defects underlying the development of this disease remain elusive [3] . The “gonadotropin hypothesis” proposes that high gonadotropin levels can have a stimulatory effect on OSE cells , promoting their neoplastic transformation [4] , [5] . It was reported that the addition of gonadotropins to rodents in which ovarian cancer was induced upon treatment with the chemical carcinogen , 7 , 12-dimethylbenz ( a ) anthracene ( DMBA ) led to increased lesion severity , suggesting that gonadotropins play a role in tumor progression [6] . In humans , epidemiologic evidence , indirectly supporting this hypothesis , includes the well-documented protective effects of oral contraceptives and multiparity , which suppress gonadotropin secretion by the pituitary gland [5] , [7] . The majority of women with epithelial ovarian cancer present the disease at a postmenopausal stage where circulating follicle stimulating hormone ( FSH ) and lutenizing hormone ( LH ) levels are elevated , indicating a causal relationship between chronically elevated gonadotropin levels and ovarian cancer development [5] , [8] . Besides gonadotropins , epidemiological studies have reported altered ovarian cancer risk associated with the use of steroid hormones to ease menopausal symptoms . Estrogen ( E ) is a well-known mitogenic factor associated with the genesis of many cancers . It has been reported previously that the risk of developing ovarian cancer increases in women who use hormone replacement therapy ( HRT ) for more than five years or use E-only regimens [9]–[13] . While most of these studies comprise a small number of subjects and fail to control for all of the factors that may influence cancer risk , in patients with ovarian cancers , intratumoral production of E via in situ aromatization has been suggested to promote growth of breast , endometrial and ovarian cancer cells [14] . However , only few animal models have been used to investigate the role of E in ovarian tumorigenesis . Bai et al reported the effects of prolonged E exposure on the morphology of rabbit ovaries and found an increase in both OSE cell proliferation and the number of papillae covering the ovarian surface , but no ovarian tumors [15] . In a recent study , Laviotte et al conditionally activated an oncogene , SV40 TAg , in OSE cells and treated the mice with exogenous E [16] . These investigators reported that E treatment resulted in an earlier onset of ovarian tumors and a significantly decreased survival time [16] . While the results from this animal model underscore the importance of E in the progression of ovarian cancer , it is clear that new animal models independent of specifically directed single oncogenic mutations are needed for assessment of the role of E signaling in ovarian epithelial tumorigenesis . In this study , we present a novel transgenic mouse model of ovarian tumorigenesis . In this model , termed ERαd/d , the estrogen receptor alpha ( ERα ) gene is dysregulated in the hypothalamic-pituitary-ovarian axis . Conditional deletion of this gene in the anterior pituitary , but not in the hypothalamus and the ovary , led to elevated circulating LH . Hyperstimulation by LH resulted in luteinization of the ovarian stromal cells , expression of P450 aromatase in these cells , and increased E synthesis in the ovarian microenvironment . Our study suggests that E critically controls ovarian tumor growth , presumably by stimulating the proliferation of OSE cells to drive epithelial tumorigenesis . The ERαd/d mouse , therefore , provides a useful model to study the mechanisms by which dysregulated E signaling promotes the initiation and progression of ovarian epithelial tumors .
ERα conditional knockout mice ( ERαd/d ) were generated by crossing progesterone receptor cre recombinase ( PR-Cre ) knock-in mice with ERα floxed ( ERαf/f ) mice [17] , [18] . By five months of age , the ERαd/d mice developed palpable ovarian tumors with 100% penetrance . In contrast , the ERαf/f and the global ERα knockout mice did not develop any tumor ( Fig . 1A ) . The ovarian tumors of ERαd/d mice grew progressively with age and became as large as 11 mm in size with an average weight of 300 mg by eight months of age ( Fig . S1A ) . Because of this large tumor burden , 80% of the ERαd/d mice die by 68 weeks of age ( Fig . S1C ) . Histological analyses of the ERαd/d ovaries showed cystic hemorrhagic follicles at 3 months of age . By 6 months , there was evidence of neoplastic epithelial cells migrating into the ovarian stroma , and by 11 months , extensive cellular proliferation occurred , resulting in the formation of a large tumor mass ( Fig . S1B ) . Immunohistochemical analysis of ovaries of ERαf/f mice at 6 months of age , using cell proliferation markers , revealed that the follicular granulosa cells were proliferative but the OSE cells were quiescent ( Fig . 1B , panel a , c ) . In sharp contrast , both OSE and the tumor cells within ERαd/d ovaries exhibited pronounced proliferative activity ( panels b , d; proliferative cells indicated by arrow ) ( Fig . 1B ) . We next assessed the expression of ERα in the key tissues of the hypothalamic-pituitary-ovarian ( HPO ) axis . As shown in Fig . 2A , ERα expression was detected near the third ventricle of the hypothalamus in ERαf/f mice , and this expression remained intact in ERαd/d mice . Widespread expression of ERα was also observed in the anterior pituitary of ERαf/f mice . However , the pituitary expression of ERα was absent in ERαd/d mice . The ERα expression was evident in OSE of ERαf/f mice and remained intact in ERαd/d OSE ( panels e , f ) . In addition theca cell expression of ERα also remained intact in the ERαd/d ovaries ( panel h ) . Most notably , ERα was present in the tumor cells of ERαd/d ovaries ( inset j , Fig . 2A ) . The Cre-mediated excision of the floxed ERα gene in the anterior pituitary is consistent with earlier reports indicating high levels of progesterone receptor ( PR ) expression in this tissue . The lack of Cre-mediated excision of the ERα gene in the hypothalamus and OSE , on the other hand , is presumably due to relatively low levels of PR expression in these tissues [18] , [19] . Due to selective ablation of pituitary ERα expression , the ERαd/d mice are likely to experience a loss of negative-feedback regulation by E at the level of pituitary . Consistent with this prediction , the serum level of LH was significantly elevated in ERαd/d mice ( Table 1 ) . Hyperstimulation of ovarian cells by LH resulted in increased steroidogenesis , leading to high circulating levels of progesterone , testosterone and E in ERαd/d mice ( Table 1 ) . In contrast , the level of FSH was not statistically different between ERαd/d and ERαf/f mice . According to previous reports , the levels of LH , progesterone , testosterone , and E are also elevated in ERαKO mice [19] , [20] . Consistent with the ERαKO mouse phenotype , ERαd/d mice are infertile . Adult mice fail to ovulate due to chronic high levels of LH . Due to the lack of ERα expression in uterine epithelial and stromal cells , the ERαd/d uteri are unable to receive an implanting embryo . Furthermore , uterine tumors are not found in the ERαd/d mice , presumably because the major uterine cell types do not express ERα . However , in contrast to the ERαKO mice , which lack ERα in all cells , including the ovarian cells , ERα was intact in OSE of ERαd/d mice . This raised the possibility that elevated systemic E levels contribute to tumor initiation by stimulating ER signaling in OSE of ERαd/d mice but fails to do so in OSE of ERαKO mice . In agreement with this view , we observed marked up-regulation of a transcriptionally active form of ERα , phosphorylated at serine 118 , in OSE of ERαd/d mice ( Fig . 2B , b ) . We also examined the status of the phosphoinositide 3-kinase ( PI3K ) /AKT pathway , which is reported to be activated in response to E treatment of ovarian cancer cell lines [21]–[23] . We noted that the level of AKT phosphorylated at Ser 473 ( p-AKT ) is elevated in the OSE and tumor cells of ERαd/d ovaries , while p-AKT level is maintained at a low level in ERαf/f ovaries ( Fig . 2B , c , d ) . It is likely that the increased level of phosphorylated AKT is linked to the elevated E signaling in ERαd/d ovaries . To further characterize the nature of the ovarian tumor in ERαd/d mice , we performed immunohistochemical analyses using epithelial and granulosa cell biomarkers . Anti-mullerian hormone ( AMH ) is a well-known marker for normal granulosa cells and granulosa cell tumors [24] . While both ERαf/f and ERαd/d ovaries expressed AMH exclusively in the granulosa cells of follicles , ERαd/d ovaries did not express AMH in the tumor cells , indicating that these tumors are not of granulosa cell origin ( Fig . 3A ) . Analysis using anti-cytokeratin 8 ( CK8 ) antibody revealed that ERαf/f mice express this epithelial marker exclusively in a single layer of OSE at 3 , 6 , and 11 months of age ( Fig . 3B , panels a , c , e ) . In contrast , the OSE of ERαd/d mice at 3 months of age exhibited multiple layers of cytokeratin-positive cells ( panel b ) . At 6 months of age , we observed pronounced cytokeratin 8 expression within the ovaries of ERαd/d mice , indicating the presence of epithelial cells within the tumor mass ( panel d ) . By 11 months of age , widespread cytokeratin 8 immunostaining was observed within the ovarian tumor , highlighting its remarkable epithelial component ( Fig . 3B , panel f ) . Current literature suggests that the human ovarian epithelial tumors are derived from either OSE or FTE [2] , [25] . Although these epithelia are derived from a common embryologic precursor , OSE is thought to retain mesothelial characteristics , while FTE is terminally differentiated [25]–[27] . Recent studies on the serous subtype of ovarian cancer have suggested that either OSE differentiates to resemble FTE or the cancer originates in the fallopian tube and spreads to the ovary [27] . To investigate further the origin of epithelial ovarian tumor cells in ERαd/d mice , we removed the oviducts of these mice prior to tumor formation . Interestingly , removal of the oviducts from pre-pubertal ERαd/d mice did not prevent the onset of ovarian tumor growth in these animals , indicating that the tumor cells originate from the OSE rather than the oviductal epithelium ( Fig . 4A ) . We also examined the epithelia of ERαf/f and ERαd/d ovaries by monitoring the expression of biomarkers specific for either OSE or FTE . As shown in Fig . 4B , we detected prominent expression of calretinin , a mesothelial marker [2] , [28] , in OSE of ERαf/f ovaries but not in OSE of ERαd/d ovaries . We also noted marked up regulation of tubal-specific makers , including PAX8 , WT1 , and Ber-EP4 in the ovaries of ERαd/d mice , while the ovaries of ERαf/f mice lacked their expression . Since PAX8 , WT1 , and Ber-EP4 are normally expressed in FTE and are present in serous epithelial ovarian tumors [2] , [28]–[30] , it is likely that the OSE cells of ERαd/d ovaries have undergone differentiation to resemble FTE . Furthermore , it has been reported previously that PAX8 is expressed in serous , endometrioid , and mucinous ovarian cancer while expression of WT1 is restricted to the serous subtype of ovarian cancer [29] . Currently there are no available biomarkers that can differentiate between high and low-grade serous ovarian carcinoma . It is clear that the ERαd/d tumors do not grow aggressively . To investigate the molecular pathways underlying ovarian tumorigenesis in ERαd/d mice , we next performed gene expression profiling , using RNA isolated from the ovaries of ERαf/f and ERαd/d mice . We identified more than 2500 genes that were differentially expressed in the tumor tissue compared to the normal ovaries . The GEO accession number for the microarray data is GSE39402 . When we compared the differentially regulated genes to three different datasets of differential gene expression profiles of human serous adenocarcinoma versus control human ovaries that exist in the Oncomine database , we noted that a large number of genes , which are differentially expressed in human serous ovarian cancer specimens , are also present in ERαd/d ovarian tumors ( Fig . S2A ) . Remarkably , the identity of genes expressed in ERαd/d ovaries and human serous ovarian cancer ranged from 25–40% . Prominent among these genes were those encoding platelet derived growth factor receptor alpha ( PDGFRα ) , vascular cell adhesion molecule ( VCAM ) , clusterin , intercellular adhesion molecule 1 ( ICAM-1 ) , and serine/threonine phosphatase 1 ( Wip1 ) , which are overexpressed in human serous ovarian cancer [31]–[36] . We observed that the levels of PDGFRα , VCAM , ICAM1 , and clusterin were markedly elevated in the ovaries of ERαd/d mice compared to those of ERαf/f mice ( Fig . S2B ) . Collectively , the presence of these cancer biomarkers in ERαd/d ovarian tumors underscored the importance of this model in deciphering the pathways involved in genesis and progression of epithelial ovarian tumorigenesis . Although the elevated systemic levels of E in ERαd/d mice likely contribute to the initiation of ovarian tumors by stimulating ERα signaling in OSE , we considered the possibility that , as the follicles are depleted with tumor progression , intratumoral E biosynthesis becomes a major regulator of tumorigenesis . Studies in postmenopausal women reported significantly increased expression and activity of P450 aromatase in serous ovarian carcinomas , but not in benign adenomas , supporting the view that intratumoral E derived from in situ aromatization could function as an autocrine growth regulator for cancer cells [14] , [37] . Previous studies have also reported elevated aromatase activity in tumors and ovarian cancer cell lines [38]–[41] . We observed that ovarian tumors of ERαd/d mice do indeed express high levels of P450 aromatase mRNA ( Fig . S3A ) . To localize aromatase expression we digested ERαd/d ovarian tumors into single-cell suspension , plated both fibroblast stromal and epithelial cells , and completed immunocytochemistry co-localizing both aromatase and a marker indicating the cell type . We observed that ovarian tumor cells isolated from ERαd/d mice express high levels of P450 aromatase protein in luteinized stromal cells of the tumor , suggesting that these cells acquired the ability to synthesize E ( Figs . S3B ) . Furthermore , the activated form of ERα , phosphorylated at Ser-118 , is abundantly expressed in the OSC , while aromatase is expressed in ovarian stroma of ERαd/d mice as early as 3 months ( Fig . S3C ) . We postulated that the epithelial ERα signaling remains elevated in response to this locally produced E in ERαd/d ovarian tumors , supporting increased ERα-dependent gene expression , abnormal cell proliferation , and tumorigenesis . To examine whether E plays a critical role in ovarian tumor progression in ERαd/d mice , we chronically treated these mice at 3 months of age with letrozole , a specific inhibitor of P450 aromatase , by implanting silastic capsules containing this drug . Following three months of letrozole treatment , ovarian tumors of 6-month old ERαd/d mice displayed a remarkable reduction , up to 60% , in tumor volume when compared to sham-treated ERαd/d mice ( Fig . 5A ) . It is important to note that while ERαd/d mice treated with letrozole exhibited significantly lower levels of serum E compared to sham-treated ERαd/d mice , their serum LH levels were not altered in response to this treatment ( Fig . 5A ) . Interestingly , ERαd/d mice treated with the letrozole exhibited significantly lower levels of ovarian expression of PDGFRα and VCAM transcripts compared to sham-treated ERαd/d mice ( Fig . 5B ) . Similarly , the levels of Wip1 mRNA and protein were markedly decreased in ovarian tumors of ERαd/d mice upon letrozole treatment ( Fig . 5 , B and C ) . Taken together , these results confirmed that elevated E signaling in the ovarian tumors of ERαd/d mice leads to dysregulated expression of a subset of genes with known links to ovarian epithelial cancer .
Genetically engineered mouse models are considered to be among the most powerful and promising tools presently available for studying the biology of various forms of cancer and for developing therapeutics . Although the creation of mouse models of ovarian cancer has lagged behind models for many other neoplastic diseases , significant advances have been made in the last decade . Orsulic et al have shown that p53-deficient ovarian cells engineered to overexpress multiple oncogenes , c-myc , Kras , and Akt , develop ovarian tumors when injected in mice [42] . Similar mouse models for ovarian epithelial tumors were developed via inactivation of various tumor suppressors , such as Pten , APC , p53 and Rb , through intrabursal administration of adenoviral vectors [43] , [44] . Conditional inactivation of multiple genes , such as Pten and Kras or PTEN and Dicer , by expression of Cre recombinase driven by the Amhr2 promoter also led to ovarian cancer in mice [45] , [46] . These mouse models have provided compelling evidence that OSE or FTE can be transformed by altering the expression of a variety of oncogenic factors or tumor suppressors . Some of these models display tumor histotypes similar to ovarian cancer subtypes seen in women . However , it is clear that these models typically require multiple genetic changes and are limited by very rapid tumor onset , which limits their usefulness for studying early modulators of ovarian tumorigenesis . In the present study , we report the development of a unique animal model , in which initiation of ovarian tumorigenesis is independent of any oncogenic insult but dependent on elevated E signaling in the ovary . Since the onset and progression of tumorigenesis is relatively slow in ERαd/d mice , this model is potentially useful in providing insights into the factors involved in the initiation and early phases of ovarian epithelial tumorigenesis . In ERαd/d mice , ERα is conditionally ablated in the pituitary but retained in the hypothalamus and ovary . The loss of negative-feedback regulation by E in the HPO axis led to elevated production of LH by the pituitary . Interestingly , high levels of gonadotropins in women in early postmenopause have been postulated to play a role in the development of epithelial ovarian neoplasms [4] , [5] . Consistent with this notion , it has been found that women with polycystic ovary syndrome , which is accompanied by high LH levels , have a greater risk of developing ovarian cancer [47] . Further supporting a role of gonadotropins in ovarian cancer development , gonadotropin levels in cysts and peritoneal fluid from ovarian cancer patients have been shown to be elevated [48] . However , not all studies have led to similar findings and it is clear that elevated gonadotropin levels alone do not cause ovarian cancer . In fact , our studies using the ERαd/d model suggested that hyperstimulation of ovarian cells by LH results in increased steroidogenesis , leading to high levels of circulating E as well as locally produced E in the ovarian tissue . High levels of testosterone coupled with increased expression of aromatase in the ovarian tissue would lead to increased synthesis of local E . We propose that this elevated E is an important factor in epithelial ovarian tumorigenesis as it stimulates signaling in the OSE , promoting its proliferation and phenotypic transformation . These results are supported by epidemiological and clinical studies , which indicate that postmenopausal women with elevated gonadotropin levels and receiving E replacement therapy exhibit an increased incidence of ovarian tumors [9]–[13] . Consistent with a role of E in the genesis of ovarian tumors , recent reports point to the clinical use of anti-estrogen drugs in stabilization of ovarian cancers [49] , [50] . Although many previous studies indicated that epithelial ovarian cancer arises from OSE , recent studies have revealed that the fimbriae of the fallopian tube is a possible site of origin of this malignancy , particularly high-grade serous carcinoma [51] . The common embryologic precursor of OSE and FTE is the coelomic epithelium , which gives rise to the epithelial linings of the fallopian tube and the ovary [27] . Unlike FTE , OSE retains mesothelial characteristics and is not terminally differentiated . It has been proposed that either OSE terminally differentiates to resemble FTE , or the cancer originates in fallopian tube and then spreads to the ovary . In support of the latter hypothesis , a recent study showed that conditional deletion of Pten and Dicer , using the Amhr2-Cre , led to tumor development in the fallopian tube , which subsequently metastasized to the ovary [46] . Our studies , on the other hand , appear to indicate that ovarian tumorigenesis in ERαd/d mice is associated with differentiation of OSE to FTE . We observed prominent expression of FTE marker proteins , such as PAX8 , WT1 , and Ber-EP4 , which are not normally expressed in OSE , in the ovaries of ERαd/d mice . Furthermore , removal of oviducts from ERαd/d mice did not prevent the onset of ovarian tumorigenesis , indicating that FTE is not the precursor tissue for tumorigenesis in ERαd/d mice . Interestingly , we did not observe any intraperitoneal metastatic spread of the ovarian tumor in ERαd/d mice . This could be partly due to the fact that the majority of the mutant mice died by 10 months of age due to the enlarged tumor , making it difficult to follow the progression of tumorigenesis beyond this point . The absence of overt malignancy in our model is not entirely surprising as several recent studies indicate that multiple genetic changes are necessary for metastatic transformation . It is conceivable that additional mutation ( s ) in tumor suppressor genes , such as p53 , is required to drive the tumorigenic pathways in ERαd/d ovaries to rapidly progressing ovarian carcinoma , which will culminate in metastasis . Indeed , recent studies , utilizing genomic sequencing data from human high-grade serous ovarian cancer specimens , have shown that these cancers exhibit genomic instability and harbor genetic mutations in p53 , Rb , BRCA1 , and/or BRCA2 loci [52]–[55] . The ovarian tumors in ERαd/d mice are composed of cells of both epithelial and stromal origins . These tumors appear to be distinct from the tubular or tubulostromal adenomas , which are reported to occur spontaneously in a number of mutant mouse strains , including the WXWX mice [56] , [57] . The adenomas , composed of numerous tube-like structures plus abundant large luteinized stromal cells , arise due to a defect in primordial germ cell proliferation and rapid loss of oocytes at birth , resulting in destruction of graafian follicles [58] , [59] . They also arise when mice are irradiated and there is a rapid loss of oocytes after radiation exposure [60] . However , these adenomas are not lethal and administration of E prevents rather than promotes their development [61] . Furthermore , in contrast to these mutant mouse strains , the ERαd/d mice exhibit normal number of oocytes at 3 months of age , which then start to decline when ovarian epithelial and stromal cells expand and form the tumor mass at 6 months . Therefore , the initial stages of tumorigenesis in ERαd/d mice are independent of the oocyte loss . Most importantly , the growth of the ovarian tumors exhibited by the ERαd/d mice is inhibited by letrozole , indicating that these tumors , unlike adenomas , are E-dependent . The ovarian tumors in the ERαd/d mice are presumably dependent on pituitary LH production , which help luteinize the stromal cells . However , the local production of E by these tumors and the resulting estrogenic effects on ovarian surface epithelial expansion and transformation appear to be the two key features that distinguish these tumors from the endocrinologically inactive tubular adenomas or tubulostromal adenomas . Although the ovarian neoplasm in ERαd/d mice did not show signs of overt malignancy , there was nevertheless clear evidence of tumorigenic transformation . Particularly striking is the finding that a large number of genes , associated with human serous ovarian cancer , are also expressed in ERαd/d ovarian tumors . Specifically , these tumors exhibit dysregulated expression of PDGFRα , VCAM , and Wip1 , which were previously reported to be involved in human ovarian cancer . PDGFRα , a cell surface tyrosine kinase receptor for members of the platelet-derived growth factor family , is over-expressed in human serous ovarian tumors and is targeted in clinical trials to treat ovarian cancers [32] , [33] . VCAM , a vascular cell adhesion molecule , is found in the blood circulation of cancer patients and has recently been proposed as a marker to detect early stages of ovarian cancer [34] , [35] . Wip1 , a p53-inducible phosphatase and an oncogene , is of particular interest . Under normal conditions , it restores cellular homeostasis following DNA-damage by cooperating with p53 to induce G2/M cell cycle arrest , thereby allowing ample time for repair of the damaged DNA [62] . However , amplification of Wip1 leads to sustained inhibition of DNA damage response and tumor suppressors , and consequently , its overexpression has been implicated in a variety of human malignancies , including ovarian carcinoma [37] , [63] . Recent studies have revealed that Wip1 is regulated by ERα [64] . Consistent with this finding , administration of letrozole to ERαd/d mice , which decreased the ovarian tumor size , also markedly reduced the expression of Wip1 along with PDGFRα , and VCAM . These results are consistent with our hypothesis that accentuated E signaling in the ovarian tissue promotes aberrant expression of genes that participate in tumorigenesis . In summary , we describe a unique mouse model that allows us to identify hormonal effectors , particularly elevated E signaling , which play an important role in the development of ovarian epithelial tumorigenesis . In the future , the ERαd/d model will serve as a valuable tool for exploring the involvement of E-dependent signaling pathways in the onset and progression of this deadly disease .
Mice ( C57BL/6; Jackson Laboratory ) were maintained in the designated animal care facility at the University of Illinois College of Veterinary Medicine according to the institutional guidelines for the care and use of laboratory animals . We crossed mice harboring ‘floxed’ ERα gene ( Esr1tm1 . 2Mma ) , termed ERαf/f , with PR-Cre mice expressing Cre recombinase under the control of progesterone receptor promoter ( Pgrtm2 ( cre ) Lyd ) to develop mice of genotype Esr1tm1 . 2Mma/Esr1tm1 . 2Mma Pgrtm2 ( cre ) Lyd/Pgr+ , which we termed ERαd/d . The PR-Cre knock-in mice expression of cre recombinase in pituitary , uterus , oviduct , mammary gland , and corpora lutea of the ovary have been described previously [18] . It has been used extensively to ablate “floxed” genes in tissues expressing PR [17] , [18] . Paraffin-embedded ovarian tissue sectioned at 4 µm , mounted on slides and subjected to immunohistochemistry as described previously [65] . Sections were incubated at 4°C with polyclonal antibodies against PCNA ( Santa Cruz sc-56 ) , cytokeratin 8 ( Developmental Studies Hybridoma Bank , TROMA I ) , ERα ( Novacastra Laboratories ) , p-Akt1/2/3 serine 473 ( Santa Cruz SC-33437 ) , AMH ( Santa Cruz Biotechnology SC-6886 ) , WT1 ( Santa Cruz Biotechnology ) , PAX8 ( Proteintech group 10336-1-AP ) , calretinin ( Invitrogen 18-0291 ) , Ber-EP4 ( Dako ) , aromatase ( Abcam ab35604 ) , vimentin ( Sigma Aldrich V5255 ) . Biotinylated secondary antibodies were used followed by incubation with horseradish peroxidase-conjugated streptavidin ( Invitrogen ) . Sections were stained in AEC Solution . Total RNA was isolated from ovaries by standard Trizol-based protocols and converted to cDNA . The cDNA was amplified by real-time PCR to quantify gene expression using gene-specific primers and SYBR Green ( Applied Biosystems ) . As a loading control , the expression level of RPLP0 ( 36B4 ) , which encodes a ribosomal protein , was determined . For each treatment , the mean threshold cycle ( CT ) and standard deviation were calculated from CT values obtained individually from 3 to 4 replicates of that sample . Each sample was subjected to three independent real-time PCR trials . The fold change was derived from the mean CT values . Primer sequences recognizing each gene are located in Table S1 . Hormones were measured by radioimmunoassay ( RIA ) at the Ligand Core facility , University of Virginia , Charlottesville . Statistical significance was determined on SAS program using the Tukey procedure to control for comparison-wise error rate . Significance cutoff value of p< . 05 was determined to be statistically significant . Ovarian tumors were removed from mice and digested with either 6 g/liter dispase ( Invitrogen ) and 25 g/liter pancreatin ( Sigma Aldrich ) , or 0 . 5 g/liter collagenase ( Sigma Aldrich ) in Hank's balanced salt solution ( HBSS ) . After incubation for 1 h at 37°C , the tubes were vortexed for 10–12 s until the supernatant became turbid with dispersed cells . The contents were then passed through an 80-µm gauze filter ( Millipore ) . Cells were re-suspended in Dulbecco's modified Eagle's F12 medium ( DMEM-F12; with 100 unit/liter penicillin , 0 . 1 g/liter streptomycin , 1 . 25 mg/liter fungizone ) containing 10% heat-inactivated fetal calf serum . Cell culture was continued for 48 h after addition of fresh medium . Ovarian tumor cells were fixed with 10% formalin solution for 10 m . Cells were treated with 25% Triton X-100 ( Sigma Aldrich ) in PBS for 10 m and exposed to a blocking serum for 1 h . Cells were treated with primary antibodies and incubated at 4°C and exposed to cy3 or cy5-conjugated secondary antibodies . Silastic capsules were made by filling silastic laboratory tubing with 0 . 8 mg of ground Novartis Femara tablets ( letrozole ) and sealing with medical adhesive silicone type A ( Dow Corning ) . For surgery , mice were first treated with analgesic 1 h prior to surgery and then anesthetized . A small dorsal incision was made just below the neck , and the silastic capsule was inserted underneath the skin . The incision was held together with wound clips until healed . After 3 months of exposure to either empty silastic capsules ( sham control ) or silastic capsules containing letrozole , mice were euthanized and ovarian tumors were fixed or frozen for analysis . Statistical analysis was performed by ANOVA or two-tailed student's ttest . Values of P<0 . 05 were considered significant . | Ovarian cancer is currently the most lethal gynecological cancer in the United States . Multiple epidemiological studies indicate that women who take hormone replacement therapy , estrogen or estrogen with progesterone , peri- or postmenopause will have an increased chance of developing ovarian cancer . Unfortunately , the five-year survival rate after diagnosis is very low indicating that better tools are needed to diagnose and treat ovarian cancer . The models that would allow investigation of this disease are severely limited . In this article we introduce a mouse model that develops epithelial ovarian tumors , and by employing inhibitors of estrogen synthesis , we show that ovarian tumorigenesis in this model is dependent on estrogen production within the ovarian tumor . These studies suggest that estrogen may play a role in promoting ovarian tumor growth . | [
"Abstract",
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] | 2014 | Dysregulated Estrogen Receptor Signaling in the Hypothalamic-Pituitary-Ovarian Axis Leads to Ovarian Epithelial Tumorigenesis in Mice |
Cells are organized into distinct compartments to perform specific tasks with spatial precision . In neurons , presynaptic specializations are biochemically complex subcellular structures dedicated to neurotransmitter secretion . Activity-dependent changes in the abundance of presynaptic proteins are thought to endow synapses with different functional states; however , relatively little is known about the rules that govern changes in the composition of presynaptic terminals . We describe a genetic strategy to systematically analyze protein localization at Caenorhabditis elegans presynaptic specializations . Nine presynaptic proteins were GFP-tagged , allowing visualization of multiple presynaptic structures . Changes in the distribution and abundance of these proteins were quantified in 25 mutants that alter different aspects of neurotransmission . Global analysis of these data identified novel relationships between particular presynaptic components and provides a new method to compare gene functions by identifying shared protein localization phenotypes . Using this strategy , we identified several genes that regulate secretion of insulin-like growth factors ( IGFs ) and influence lifespan in a manner dependent on insulin/IGF signaling .
Differentiation and organization of eukaryotic cells require regulated localization of specific proteins into subcellular compartments where they perform discrete functions . Global analysis of protein localization in yeast revealed that >40% of proteins localize to specific subcellular compartments [1] . This large repertoire of localized proteins raises several questions . What genes or pathways orchestrate the subcellular abundance and distribution of these proteins ? Is the protein composition of subcellular compartments static or plastic ? What rules govern the composition of these structures ? How do changes in protein localization alter the function of these structures , and ultimately organismal health ? The large variety of proteins in subcellular compartments implies substantial genetic and biochemical complexity . Therefore , addressing these questions will require comprehensive and systematic approaches beyond the study of single genes or proteins . Such approaches have been successful in identifying groups of functionally related genes based on similarities in their expression patterns , or similarities in the phenotypic consequences of disrupting gene function [2]–[4] . Given recent advances in high-content imaging screens [1] , it is now possible to do analogous studies linking gene function to changes in the global patterns of protein localization . In neurons , presynaptic specializations are estimated to contain approximately one thousand proteins that are configured into discrete compartments; these compartments contain different organelles and perform different cellular functions in neurotransmitter release [5] . Synaptic vesicles ( SVs ) contain neurotransmitters that are released upon SV fusion with the plasma membrane . The active zones are structures containing many scaffold proteins and calcium channels and are sites of SV fusion . Periactive zones are F-actin-rich areas where SV recycling occurs through endocytosis . Dense core vesicles ( DCVs ) are vesicles that release neuropeptides and peptide hormones [6] , including insulin/IGF ligands implicated in metabolic diseases and the aging process [7] , [8] . DCVs are a population of vesicles distinct from SVs that undergo differential regulated release at different locations in neurons [6] . DCVs have mostly been studied in cultured secretory cells; thus , genetic factors that regulate DCV secretion in vivo from neurons are poorly understood , despite their importance in health and disease . Synapses are able to operate over a broad range of functional states , which endow circuits with the capacity to store and process information . Relatively little is known about how the protein composition of synapses is altered across these functional states , nor how these changes contribute to differences in synaptic transmission . Is the abundance of proteins associated with the same subsynaptic structure ( e . g . SVs ) always correlated across physiological states ? To what extent do the binary interactions between presynaptic proteins govern changes in presynaptic composition ? Can changes in protein localization profiles be linked to changes in behavior and physiology of the whole animal ? Here , we describe a genetic analysis of presynaptic structure in C . elegans by measuring in vivo changes in the abundance and distribution of a panel of fluorescently tagged presynaptic proteins . These proteins label distinct subsynaptic compartments and are involved in diverse aspects of neurotransmitter release ( Table 1 ) . Using these markers , we determined how synapse structure was altered in twenty-five mutants that alter various aspects of synaptic transmission . By comparing changes in protein localization caused by different mutations , we describe changes in protein composition of presynaptic terminals across a range of physiological states . In this manner , we identify several genes that regulate secretion of insulin/IGFs from neurons , and we show that these genes regulate lifespan , a physiological function of IGF signaling .
To explore the networks of interactions between presynaptic proteins in C . elegans , we generated a panel of nine markers that label different presynaptic compartments , including SVs , DCVs , active zones , endocytic vesicles/sites and actin cytoskeleton ( Table 1 ) . We constructed stable chromosomally integrated transgenes consisting of these markers tagged with GFP or Venus/YFP [9] and expressed in the DA class of cholinergic motor neurons that form presynaptic terminals at body wall neuromuscular junctions ( NMJs ) ( Figure 1A ) [10] . Because axons of these motor neurons form en-passant synapses with body wall muscles , synaptic proteins adopt a punctate pattern of localization along the length of the axon ( Figure 1A ) . Prior studies have shown that the fluorescent puncta formed by these tagged proteins correspond to presynaptic specializations [11] ( Table 1 ) . To quantify the abundance and distribution of these markers in axons , we averaged fluorescence from ∼300–600 synapses ( from ∼30 animals ) . Using custom software , we determined four parameters: the punctal fluorescence , which measures abundance at presynaptic specializations; inter-punctal fluorescence , which measures axonal abundance between synapses; full width at half maximum ( FWHM ) , which measures punctal width; and inter-punctal distance , which measures the distance between synapses along the axon ( Figure 1A ) [12] , [13] . For some markers , a subset of these parameters was excluded from our analysis ( see Materials and Methods ) . Puncta widths were excluded for SYD-2 α-Liprin , SNN-1 Synapsin , and UNC-10 RIM1 because these values were close to the diffraction limit , and thus changes in widths could not be accurately measured . Similarly , the interpunctal fluorescence values observed in SYD-2 α-Liprin , UNC-10 RIM1α , and APT-4 α2-adaptin were not significantly different from background fluorescence , and consequently were excluded from our analysis . To determine how presynaptic composition is altered across a range of conditions that alter synaptic function , these presynaptic markers were crossed into each of twenty-five neurotransmission mutants , excluding cases where the marker and mutation corresponded to the same gene or when the marker and mutation were too closely linked to isolate recombinants . In this manner , we produced a total of 218 marker/mutant combinations , which we analyzed for phenotypes in the localization of synaptic markers to obtain the protein localization profiles of these twenty-five mutants ( Figure 2A ) . We analyzed fluorescence changes for each presynaptic marker compared to wild-type controls . For a given synaptic marker , differences between the mutant and wild type samples for each parameter were quantified using the T-statistic ( Figure 1B , Table S3 ) . The pattern of changes for all nine synaptic markers caused by a mutant constitutes a “protein localization profile , ” which provides a description of how synapse structure is altered by mutations in a particular gene . The mutations selected for this analysis affect diverse aspects of synaptic transmission , including G-protein signaling pathways and components of exocytic or endocytic machinery involved in the SV cycle . Some of these mutations are well characterized , based on previous behavioral , electrophysiological or ultrastructural studies . These well-characterized mutations served as positive controls to validate our approach , and provide canonical protein localization profiles for comparison to less-characterized mutations . The majority of the mutations we analyzed decrease neurotransmission , but we also selected four mutations that increase neurotransmission ( dgk-1 DAG kinase , goa-1 Gαo , tomo-1 Tomosyn , and a constitutively active form of egl-30 Gαq ) [14]–[22] . Thus , our synaptic protein localization profiles allow us to describe changes in synaptic protein localization that occur following bidirectional changes in neurotransmission . Synaptic protein localization profiles capture functional relationships between different genes and different presynaptic proteins . Several kinds of regulatory relationships are observed in this dataset . First , the effect of a single mutation on an individual marker can indicate a functional relationship between a gene and protein . Second , at the level of the whole dataset , similarities between mutant protein localization profiles or marker protein profiles might reveal related functions or interactions . Third , trends and potential outliers identified in the dataset may represent specific pathway ( s ) required to coordinate particular aspects of synaptic function . Fourth , this dataset could be used as a basis for classifying uncharacterized genes . We provide several examples to illustrate these analytical techniques in the following sections . We used hierarchical clustering to identify groups of related genes based on similarities among their protein localization profiles . Six gene clusters were detected robustly across multiple clustering strategies and consisted of profiles that were significantly and positively correlated ( see below ) ( Figure 2A , Table S1 ) . To gain insight into the function of the genes in each cluster , we determined which shared phenotypes contributed most significantly to the positive correlation between the profiles within each cluster ( Figure 2B ) ( see Materials and Methods and Supporting Information in Text S1 ) . We found that proteins within different clusters had distinct shared phenotypes , confirming that each cluster affected distinct cellular processes . This analysis identified three clusters consisting of genes previously reported to have related functions in neurotransmission , thereby validating this approach ( Figure 2A ) . One cluster contained two genes involved in SV endocytosis , unc-26 synaptojanin and unc-57 endophilin A ( Figure 2A ) [23] , [24] . During endocytosis , UNC-26 synaptojanin is recruited to endocytic vesicles by UNC-57 endophilin A [24] , [25] . Prior ultrastructural studies have shown that endocytic intermediates ( e . g . clathrin coated pits and vesicles ) accumulate in unc-57 endophilin A and unc-26 synaptojanin mutant synapses [23] , [24] . To confirm that our profiling strategy can detect this aspect of the unc-26 synaptojanin and unc-57 endophilin A mutant phenotypes , we analyzed two proteins that label endocytic vesicles: the α2 subunit of the AP2 clathrin adaptin ( APT-4 ) and intersectin/DAP160 ( ITSN-1 ) ( Table 1 ) . We observed increased punctal fluorescence of APT-4 α2 adaptin and ITSN-1 intersectin in unc-26 synaptojanin and unc-57 endophilin A mutant synapses ( Table S2 ) , consistent with the accumulation of endocytic intermediates in these mutants [23] , [24] . Moreover , these phenotypes contributed most to the clustering of these two genes ( Figure 2B ) . Thus , identifying shared phenotypes can verify the related functions of genes in a cluster . A second cluster was comprised of three genes required for exocytosis , unc-13 , unc-18 nSec1 , unc-2 α1 voltage gated calcium channel ( VGCC ) subunit [26]–[28] . These genes clustered together because of increased punctal fluorescence of SV ( SNB-1 synaptobrevin and RAB-3 ) and DCV ( INS-22 insulin/IGF ) proteins and because they did not strongly affect an endocytic protein ( ITSN-1 intersectin/DAP160 ) ( Figure 2A–B ) . The increased SNB-1 and RAB-3 punctal fluorescence observed suggests that SVs accumulate in these mutants , consistent with prior ultrastructural studies [26] , [28] . A third cluster comprised two genes involved in synapse formation , syd-2 α-Liprin and sad-1 kinase [29]–[31] . These genes clustered because of significant reductions in synapse numbers ( increased inter-punctal distance of several markers ) and defects in presynaptic morphology ( decreased punctal fluorescence of several markers ) in these mutants compared to wild type ( Figure 2A–B ) . The defects in presynaptic morphology that we observed in the DA motor neurons of the syd-2 α-Liprin and sad-1 kinase mutants are similar to those previously described in other classes of neurons [29]–[31] . Thus , presynaptic protein localization profiles can be used to organize genes into groups with shared phenotypes , which may indicate related gene functions . Hierarchical clustering utilizes positive correlations to generate a single representation of relationships among genes . For this reason , certain kinds of information are not represented in hierarchical clustering strategies . First , significant similarities beyond those within the gene clusters are not illustrated . Second , mutations in two genes may have opposite phenotypic effects on synapse structure , which would lead to anti-correlated phenotypes . To address these issues , we made pairwise comparisons of all twenty-five mutant profiles using the Pearson's Correlation to measure similarity ( Figures 3A ) . The significance of the correlation coefficients was determined using a bootstrapping approach ( see Materials and Methods ) . In this manner , we identified similar or opposite phenotypes among the mutants tested ( Figure 3A ) . As expected , positive correlations were observed between protein localization profiles that mirror the results from the hierarchical clustering . For example , a positive correlation was observed between unc-13 , unc-18 nSec1 , and unc-2 ( Figure 3A ) . A positive correlation was also observed between two genes that function to inhibit neurotransmitter secretion: tomo-1 tomosyn and goa-1 Gαo ( Figure 3A–B ) [14]–[17] , [19]–[21] . Interestingly , the protein localization profiles of the exocytosis genes ( unc-13 and unc-18 nSec1 ) were anti-correlated with those of genes that inhibit exocytosis ( tomo-1 tomosyn and goa-1 Gαo ) ( Figure 3A–B ) . Thus , the markers used here provide bidirectional information about genes that affect neurotransmitter release , and illustrate how anti-correlations can provide useful information about gene functions . To identify relationships between pairs of protein markers , we conducted systematic pairwise comparisons of the punctal fluorescence of each protein , using the Pearson's Correlation to measure similarity ( Figure 3C ) . Most of the marker profiles determined in this manner were not correlated , suggesting that the corresponding presynaptic proteins are regulated independently . For several presynaptic proteins , we observed significant positive or negative correlations . These marker correlations suggest regulatory relationships among these proteins . For example , one might expect positive correlations to be observed for proteins involved in the same process ( e . g . SV exo- or endocytosis ) , those that associate with the same presynaptic organelle ( e . g . SVs ) , or those that bind to each other . Several examples of this analysis are described below . The active zone is a complex matrix of proteins that are enriched at sites of SV fusion . Many biochemical interactions have been observed among active zone proteins , and these interactions are thought to regulate recruitment of these proteins to synapses , e . g . during synapse formation or synaptic plasticity . We analyzed two active zone proteins that are binding partners , UNC-10 RIM1α and SYD-2 α-Liprin [32] . One possible function for their biochemical interaction is the assembly of active zone components . Consistent with this idea , we found that UNC-10 RIM1α punctal fluorescence was significantly reduced in syd-2 α-Liprin mutants ( Figure 4A ) ; however , SYD-2 α-Liprin punctal fluorescence was not reduced in unc-10 RIM1α mutants ( Figure 4B ) , both in agreement with prior work [30] , [33] . These results suggest that SYD-2 α-Liprin is involved in recruiting UNC-10 RIM1α to synapses , but does not require UNC-10 RIM1α for normal presynaptic localization . Furthermore , SYD-2 α-Liprin and UNC-10 RIM1α punctal fluorescence both increased in goa-1 Gαo mutants , suggesting that they can be coordinately regulated ( Figure 4A–B ) . Prior studies showed that goa-1 Gαo also regulates the abundance of UNC-13 [21] , another active zone protein that binds UNC-10 RIM1α . Taken together , these results suggest that goa-1 Gαo coordinately regulates the synaptic abundance of several interacting active zone proteins . UNC-10 RIM1α is a scaffolding protein with many potential binding partners besides SYD-2 α-Liprin [34] . If SYD-2 α-Liprin was the primary determinant of UNC-10 RIM1α localization , we would expect that their abundance would be positively correlated in our dataset . Contrary to this prediction , we found no significant correlation in their fluorescence across the 25 mutants analyzed ( R = −0 . 083 , p = 0 . 085 ) ( Figure 4C–D ) . In fact , several mutations had opposite effects on SYD-2 α-Liprin and UNC-10 RIM1α punctal fluorescence . For example , three mutants that had large increases in SYD-2 α-Liprin fluorescence , egl-30 ( gf ) constitutively active Gαq , aex-3 RabGEF , and tomo-1 tomosyn , all had significantly reduced UNC-10 RIM1α punctal fluorescence ( Figure 4C , Table S2 ) . Taken together , these results indicate that the synaptic abundance of UNC-10 RIM1α and SYD-2 α-Liprin are largely regulated independently across the mutants tested . Consistent with this notion , UNC-10 RIM1α can still localize to discrete puncta in SYD-2 α-Liprin null mutants , albeit less efficiently ( Figure 4A ) , suggesting that SYD-2 α-Liprin is not the sole determinant of UNC-10 RIM1α localization . In worm and mouse knockouts lacking RIM1α , SV fusion is impaired but not eliminated [34] , [35] . In unc-10 RIM1α mutant worms , the reduced SV fusion rate is accompanied by decreased SV docking and priming [34]–[36] . In mammals , RIM1α binds to GTP-bound RAB-3 , a Ras-related GTPase involved in SV exocytosis . The analogous proteins in C . elegans , UNC-10 and RAB-3 , are also binding partners [37] , consistent with the significant positive correlation between the punctal fluorescence changes for RAB-3 and UNC-10 RIM1α in our dataset ( Figure 4D ) ( R = 0 . 56; p = 0 . 049 ) that indicate UNC-10 RIM1α and RAB-3 synaptic abundance are coordinately regulated . SNB-1 Synaptobrevin and RAB-3 are two proteins associated with SVs and both are required for normal levels of SV exocytosis . To determine whether the synaptic abundance of these two proteins are differentially regulated , we plotted the punctal fluorescence of RAB-3 against that of SNB-1 synaptobrevin ( Figure 5A ) . This revealed a general trend whereby mutations that increased RAB-3 punctal fluorescence also tended to increase SNB-1 synaptobrevin punctal fluorescence ( R = 0 . 59 , p = 0 . 17 ) , although this correlation was not significant . Three mutants , egl-30 Gαq , unc-11 AP180 and aex-3 RabGEF , were outliers in this plot ( Figure 5A , labeled in yellow ) . When these outliers were excluded , the correlation between RAB-3 and SNB-1 synaptobrevin became significant ( R = 0 . 66 , p = 0 . 016 ) . Thus , across many conditions ( 22/25 mutants examined ) , SNB-1 and RAB-3 synaptic abundance was coordinately regulated . The three outliers in the SNB-1 versus RAB-3 plot ( Figure 5A ) identify specific circumstances in which RAB-3 and SNB-1 were differentially regulated . The aex-3 mutant lacks the GEF responsible for activating RAB-3 [38] , and consequently would be expected to have a disproportionately stronger effect on RAB-3 , compared to SNB-1 . Disrupting egl-30 Gαq also caused a significantly greater decrease in RAB-3 punctal fluorescence than was observed for SNB-1 synaptobrevin ( Figure 5A–C ) . This result suggests that egl-30 Gαq regulates the presynaptic levels of RAB-3 separately from SNB-1 synaptobrevin . Consistent with this idea , the protein localization profiles of rab-3 and egl-30 Gαq mutants were significantly correlated ( Figure 3A ) ( R = 0 . 55 , p = 0 . 038 ) , suggesting that these two mutations disrupt one or more processes in common . Thus , RAB-3 may be responsive to extracellular signals that couple to egl-30 Gαq . unc-11 AP180 mutants had a disproportionately larger increase in the punctal fluorescence of RAB-3 compared to SNB-1 synaptobrevin ( Figure 5A–C ) . unc-11 AP180 mutants exhibit a specific defect in the endocytic recycling of SNB-1 synaptobrevin from the plasma membrane to SVs [13] , [39] . Because SVs lacking SNB-1 synaptobrevin are predicted to be defective in exocytosis , the increase in RAB-3 punctal fluorescence in unc-11 AP180 mutants ( Figure 5B ) may reflect the accumulation of defective SVs that contain insufficient amounts of SNB-1 synaptobrevin to undergo efficient exocytosis . Consistent with this hypothesis , increased RAB-3 punctal fluorescence was also observed in snb-1 synaptobrevin mutants ( Figure 5B ) . Moreover , the phenotypic profile of unc-11 AP180 mutants clustered robustly with that of snb-1 synaptobrevin mutants ( Figure 2A ) . Taken together , these results suggest that the v-SNARE SNB-1 affects the recruitment of RAB-3 to presynaptic elements . SV precursors are transported to synapses by anterograde transport [40] . SYD-2 α-Liprin promotes anterograde transport of SV precursors to nerve terminals , while RAB-3 has been proposed to promote synaptic targeting of SVs , perhaps by mediating tethering of SV to active zone components [41] , [42] . The puncta fluorescence for SYD-2 and RAB-3 were anti-correlated in our data set ( Figure 3C ) . These results could indicate that RAB-3-mediated tethering negatively regulates SYD-2 α-Liprin-mediated SV transport . Consistent with this idea , SYD-2 α-Liprin punctal fluorescence was significantly increased in rab-3 mutants ( Figure 5D ) . The increased SYD-2 α-Liprin fluorescence was not observed in other exocytosis mutants ( e . g . unc-13 and unc-18 nSec1 mutants ) ( Figure 5D ) . Taken together , these results suggest that RAB-3 activity somehow negatively regulates synaptic targeting of SYD-2 α-Liprin . During the SV cycle , SVs undergo fusion with the plasma membrane to release neurotransmitters and are recycled locally by endocytosis . We examined several proteins that associate with SVs at various points during the SV cycle . SNB-1 synaptobrevin is a v-SNARE protein required for SV exocytosis . RAB-3 is a GTPase that reversibly associates with SVs in a manner that depends upon its bound nucleotide [43] . SNN-1 Synapsin has been proposed to associate with the reserve pool of SVs , mediating association of this pool of vesicles with F-actin [44] . APT-4 α2-adaptin associates with clathrin-coated vesicles , promoting recycling of SVs following fusion [45] . ITSN-1 Intersectin associates with both the cytoskeleton and components of the endocytic machinery to promote endocytosis [46]–[50] and is localized to presynaptic endocytic sites [48] , [49] . These SV-associated proteins are thought to regulate different aspects of the SV cycle; consequently , one would expect that the abundance of these proteins would be differentially affected when specific steps of the SV cycle are disrupted . Our results are largely consistent with this idea . The abundance of a protein associated with endocytic intermediates ( APT-4 α2 adaptin ) , was negatively correlated with one associated with the pool of SNB-1 synaptobrevin positive vesicles ( Figure 3C ) . The simplest interpretation of this result is that the size of the SNB-1 synaptobrevin positive pool of SVs is anti-correlated with the ongoing rate of secretion . When secretion rates are high this SNB-1 synaptobrevin positive SV pool is reduced whereas the converse change occurs when secretion rates are low . Similarly , high secretion rates would be expected to result in increased abundance of endocytic intermediates ( labeled by APT-4 α2-adaptin and ITSN-1 intersectin ) and newly recycled SVs . The pattern of SNN-1 synapsin abundance in our mutant panel was anti-correlated with that of exocytic proteins SNB-1 synaptobrevin and RAB-3 ( Figure 3C ) . Moreover , the SNN-1 synapsin pattern was most similar to that observed for the endocytic proteins APT-4 α2-adaptin and ITSN-1 intersectin ( Figure S3 ) . These relationships suggest that at the C . elegans NMJ , SNN-1 synapsin primarily associates with vesicles as they transit from the recycling endocytic intermediates , however this association is not maintained in the pool of SVs labeled by SNB-1 synaptobrevin and RAB-3 . This result is consistent with prior studies showing that lamprey Synapsin-1 primarily associates with SVs distal from the active zone at rest and with peri-synaptic zones where endocytic recycling occurs during stimulation [44] . Neuropeptides and classical neurotransmitters are secreted by a similar calcium-dependent mechanism; however , the detailed mechanisms by which neuropeptides are synthesized and packaged into vesicles are quite distinct . Neuropeptides are initially synthesized as large proproteins that are packaged into dense core vesicle ( DCV ) precursors in the trans golgi network . Classical neurotransmitters are packaged in small clear synaptic vesicles ( SV ) that are clustered near release sites whereas large DCVs filled with neuropeptides are not restricted to nerve terminals . Moreover , exocytosis of DCVs can occur from both axons and dendrites . Different patterns of activity are typically required for evoking secretion of SVs versus DCVs , with higher frequencies or amplitudes required for the latter [51] . Different populations of DCVs within the same cell can contain different neuropeptides [52] . Here we focused on DCVs responsible for secreting an insulin/IGF family member , INS-22 . To further characterize how classical neurotransmitters and neuropeptides are differentially regulated , we compared the protein localization profiles for SNB-1 synaptobrevin ( a SV marker ) and INS-22 insulin/IGF ( a DCV marker ) ( Figure 6A ) . We previously showed that quantitative analysis of SNB-1 synaptobrevin and INS-22 insulin/IGF fluorescence in axons can be used as steady-state markers to assess the relative rates of SV and Insulin/IGF secretion respectively [13] , [53] . The punctal fluorescence of INS-22 insulin/IGF and SNB-1 synaptobrevin were positively correlated in our mutant panel ( R = 0 . 43 , p = 0 . 03 ) ( Figure 6A ) , suggesting that SV and INS-22 insulin/IGF secretion were coordinately regulated across these conditions . Many genes were required for both SV and INS-22 insulin/IGF secretion . For example , we found that both SVs and INS-22 insulin/IGF accumulated in exocytosis mutants , unc-13 and unc-18 nSec1 ( Figure 6A ) . Despite the overall positive correlation , there were some notable exceptions to this trend . For example , a mutation in the endocytic gene unc-57 endophilin A strongly affected SNB-1 synaptobrevin punctal fluorescence ( 30% decrease , p = 1 . 2×10−7 ) but had a relatively weaker effect on INS-22 insulin/IGF fluorescence ( 14% decrease , p = 0 . 011 ) ( Figure 6A , Table S2 ) . This difference was expected since maintenance of the SV pool is mediated by local endocytic recycling at synapses , whereas maintenance of the DCV pool is mediated by anterograde transport from the golgi . SNB-1 synaptobrevin punctal fluorescence was affected by both rab-3 and aex-6 Rab27 mutations ( Figure 6A , Table S2 ) , consistent with prior studies showing that SV exocytosis was decreased in these mutants [54] . In contrast , INS-22 insulin/IGF fluorescence was increased in rab-3 but not in aex-6 Rab27 mutants ( Figure 6A , Table S2 ) . These results suggest RAB-3 plays a more prominent role than AEX-6 Rab27 in regulating INS-22 insulin/IGF transport or secretion . Two mutations resulted in increased INS-22 insulin/IGF fluorescence while having little effect on SNB-1 synaptobrevin fluorescence ( Figure 6A , yellow circles ) . One mutant corresponds to pkc-1 protein kinase C η/ε ( PKCη/ε ) , which regulates DCV secretion but not SV secretion [53] . The other corresponds to egl-8 phospholipase Cβ ( PLCβ ) . EGL-8 PLCβ is predicted to catalyze hydrolysis of phosphatidyl inositol ( 4 , 5 ) bisphosphate to produce DAG , an activator of PKC . This suggests that DAG produced by EGL-8 PLCβ may activate PKC-1 PKC η/ε to specifically regulate DCV secretion . Relatively few genes have been shown genetically to regulate insulin/IGF secretion in vivo . Clustering analysis of protein localization profiles identified two robust gene clusters predicted to be involved in DCV secretion ( Figure 2A ) . The first cluster consisted of unc-31 CAPS and unc-36 α2δ subunit of a voltage-gated Ca2+ channel ( α2δ VGCC ) [55] , [56] . unc-31 CAPS is a multi-domain protein that has been previously implicated in DCV exocytosis in several systems [53] , [55] , [57]–[60] . The second cluster consisted of genes in the egl-30 Gαq pathway , including egl-30 Gαq , egl-8 PLCβ and pkc-1 PKCη/ε [20] , [53] , [61] , [62] . A major determinant for both of these clusters was a significant increase in the punctal fluorescence of INS-22 insulin/IGF ( Figure 2B ) , suggesting that mutants in these clusters were defective in DCV exocytosis . To verify that the genes in these clusters are required for INS-22 insulin/IGF secretion from DCVs , we measured secretion of INS-22 insulin/IGF from neurons in the corresponding mutants by quantitating steady-state fluorescence in coelomocytes . Coelomocytes are scavenger cells that take up secreted proteins . Secreted fluorescently tagged neuropeptides are endocytosed by coelomocytes , where they accumulate within endolysosomal organelles , which can be visualized as large internal fluorescent patches ( Figure 6B ) [53] , [60] . Because the genes tested in this study are not expressed in the coelomocytes [14] , [15] , [22] , [61]–[65] and do not appear to affect general endocytic traffic [66] , the accumulation of INS-22 insulin/IGF in coelomocytes is therefore a measure of its secretion from DCVs in these mutants . unc-36 α2δ VGCC and egl-8 PLCβ mutants both showed significant reductions in INS-22 insulin/IGF fluorescence in coelomocytes ( Figure 6C ) , similar to the reductions previously observed for pkc-1 PKC η/ε and unc-31 CAPS [53] , [60] . Moreover , both unc-36 α2δ VGCC and egl-8 PLCβ mutants showed accumulation of INS-22 insulin/IGF fluorescence in axons , indicating that reduced secretion was not due to reduced neuropeptide synthesis ( Figure 6D ) . The clustering analysis , together with these results , strongly supports the idea that unc-36 α2δ VGCC and egl-8 PLCβ are required in some manner for INS-22 insulin/IGF secretion . unc-36 and unc-2 encode the α2δ and α1 subunits of VGCCs respectively; mutants lacking either gene share a number of behavioral phenotypes in common [56] , [63] , [67] , [68] . If UNC-36 α2δ VGCC and UNC-2 α1 VGCC function together in INS-22 insulin/IGF secretion , mutations in these subunits would be predicted to have similar protein localization profiles . Instead , we found that unc-2 α1 VGCC mutants were not defective in INS-22 insulin/IGF secretion ( Figure 6C ) , and unc-2 α1 VGCC mutants did not cluster with unc-36 α2δ VGCC ( Figure 2A ) , suggesting that these VGCC subunits have different effects on presynaptic protein composition . These results suggest that INS-22 insulin/IGF secretion is promoted by a VGCC that requires the UNC-36 α2δ subunit but not the UNC-2 α1 subunit . How are EGL-8 PLCβ and PKC-1 PKC η/ε activated to promote INS-22 insulin/IGF secretion ? A putative activator of EGL-8 PLCβ is the alpha subunit of a heterotrimeric G protein EGL-30 Gαq . To determine if egl-30 Gαq also regulates INS-22 insulin/IGF secretion , we tested a partial loss-of-function allele of egl-30 Gαq because the null mutant is inviable [62] . INS-22 insulin/IGF coelomocyte fluorescence in these egl-30 Gαq mutants was indistinguishable from wild type controls ( Figure 6C ) . It is possible that our assay was not sensitive enough to detect the subtler phenotype in the partial loss-of-function egl-30 Gαq mutant used . To further address whether egl-30 Gαq signaling is important for INS-22 insulin/IGF secretion , we examined an egl-30 ( gf ) constitutively active Gαq mutant [18] . We detected increased coelomocyte INS-22 insulin/IGF fluorescence in egl-30 ( gf ) mutants ( Figure 6C ) , suggesting INS-22 insulin/IGF secretion can be stimulated by egl-30 Gαq activity . Nevertheless , we cannot rule out the possibility that egl-8 PLCβ may be regulated in an egl-30 Gαq-independent manner . Our analysis also identified negative regulators of INS-22 insulin/IGF secretion . goa-1 Gαo and tomo-1 tomosyn have been shown to negatively regulate SV exocytosis in C . elegans [15] , [19] , [69] . In goa-1 Gαo mutants , INS-22 insulin/IGF secretion increased dramatically ( Figure 6C ) . A corresponding reduction in INS-22 insulin/IGF fluorescence was observed in axons ( Figure 6D ) , consistent with a depletion of DCVs containing INS-22 insulin/IGF due to excess release . Similar results were observed in tomo-1 tomosyn mutants ( Figure 6C–D ) , in agreement with another recent study [16] . These results indicate that goa-1 Gαo and tomo-1 tomosyn inhibit INS-22 insulin/IGF secretion . How do changes in protein localization profiles impact the physiology of the whole animal ? In C . elegans , disruption of insulin/IGF signaling results in increased longevity [8] . To determine whether the genes identified in this study that regulate the secretion of one insulin/IGF ( INS-22 ) also affect lifespan , we tested the corresponding mutants for changes in lifespan . egl-30 Gαq and egl-8 PLCβ mutants were long-lived ( Figure 7A–B ) . Furthermore , the increased longevity of these mutants was suppressed by a deletion of daf-16 FOXO , a transcription factor that is activated when insulin/IGF signaling is reduced ( Figure 7A–B ) [8] . Conversely , egl-30 ( gf ) constitutively active Gαq mutants were short-lived ( Figure 7D ) . Because egl-30 ( gf ) constitutively active Gαq mutants exhibited increased INS-22 insulin/IGF secretion , they were predicted to have excess insulin/IGF signaling . Consistent with this prediction , the shortened lifespan of egl-30 ( gf ) mutants was partially suppressed by a mutation in the daf-2 insulin/IGF receptor ( InsR ) ( Figure 7D ) . These results imply that the regulation of lifespan by the egl-30 Gαq pathway is bidirectional and requires InsR and FOXO signaling , further supporting a role for these genes in regulating insulin/IGF secretion . The secretion of active insulin from mammalian cells requires processing by proprotein convertase 2 ( PC2 ) [70] , suggesting that C . elegans egl-3 PC2 might also be involved in insulin/IGF processing [71] . Since the phenotypic profile of egl-3 PC2 was significantly correlated with egl-30 Gαq and egl-8 PLCβ ( Figures 3A , S2 ) , we examined egl-3 mutants for alterations in lifespan . In agreement with a previous RNAi study [72] , egl-3 PC2 mutants are long-lived in a daf-16 FOXO dependent manner ( Figure 7C ) . This raises the possibility that egl-3 PC2 might be involved in insulin/IGF processing , although we cannot rule out roles for egl-3 PC2 in processing other neuropeptides that regulate C . elegans lifespan . tomo-1 tomosyn and goa-1 Gαo mutants had increased INS-22 insulin/IGF secretion and were short-lived ( Figure 7E–F ) . These reductions in lifespan required normal insulin/IGF signaling , as disrupting daf-2 InsR in these mutant backgrounds suppressed their short-lived phenotype ( Figure 7E–F ) . These results further support the idea that tomo-1 tomosyn and goa-1 Gαo inhibit insulin/IGF secretion . Together our findings indicate that lifespan can be regulated bidirectionally by genes that control insulin/IGF secretion . These results also provide an example where changes in presynaptic protein localization profiles can be mechanistically associated with changes in the physiology of the animal .
Regulating the levels of a single presynaptic protein can be crucial in tuning neurotransmitter secretion . For example , increasing the levels of UNC-10 or its ortholog RIM1α can lead to increased neurotransmitter secretion [35] , [75] . Several layers of regulation ensure that appropriate levels of UNC-10 or RIM1α are present at presynaptic specializations , including syd-2 α-Liprin-dependent and independent means of UNC-10 RIM1α recruitment [33; this work] , as well as ubiquitin-mediated degradation of RIM1α [75] . We analyzed multiple synaptic markers , allowing us to detect trends and correlations not possible from studying individual markers . One theme that emerged was that markers localized to the same synaptic compartments could differ in their response to disruption of presynaptic function . For example , changes in the punctal fluorescence of active zone markers UNC-10 RIM1α and SYD-2 α-Liprin did not correlate when examined across a panel of neurotransmission mutants , suggesting that additional factors besides SYD-2 α-Liprin can exert a significant impact on UNC-10 RIM1α abundance . This result could represent changes in the ability or specificity of the proteins to localize to certain subcellular structures . Alternatively , this result may reflect altered rates of protein synthesis or turnover . Together , our data suggests that the composition of the active zone can be altered in response to changes in presynaptic function . The ability to independently regulate different components of the active zone could provide a mechanism to fine-tune neurotransmission . Detailed proteomic studies have revealed the protein components of SVs [76] , some of which were studied here . We show that compositional changes among SV proteins can be observed when specific aspects of synaptic function are perturbed . Because SVs exist in functionally distinct pools that have been proposed to contain different molecular constituents [5] , the compositional changes we observed might reflect shifts in the relative abundance of SV pools . For example , the abundance of SNN-1 synapsin was negatively correlated with both RAB-3 and SNB-1 synaptobrevin , possibly indicative of changes in their association with intermediates during the SV cycle . These relationships are consistent with the idea that different sets of proteins transiently associate with SVs as they traverse through different steps in the exocytosis/endocytosis cycle . Most work on DCV secretion has focused on cultured neurosecretory cells; less is known about the cell biology of DCV secretion in neurons of intact animals . We found a role for unc-36 α2δ VGCC in DCV secretion , which had not been previously implicated in this process . Prior work in Drosophila revealed that an α2δ VGCC subunit encoded by straitjacket is required for SV exocytosis [77] , [78] . Thus , it is possible that α2δ VGCC subunits are involved in both SV and DCV secretion . The unc-2 α1 VGCC subunit [67] was a candidate for functioning in the same channel as unc-36 α2δ VGCC because they shared many behavioral and developmental phenotypes [56] , [63] , [68] . However , unc-2 α1 VGCC did not co-cluster with either unc-36 α2δ VGCC or unc-31 CAPS; furthermore , unc-2 α1 VGCC mutants did not show a detectable INS-22 insulin/IGF secretion defect . Thus , while unc-36 α2δ VGCC and unc-2 α1 VGCC may act together for certain processes , they may also participate in the formation of distinct channels , perhaps as a mechanism for increasing channel diversity in the nervous system . Our analysis was able to dissect the functions of these two VGCC subunits by separating them into two clusters . In Drosophila , straitjacket α2δ VGCC is required for proper localization of the cacophony α1 VGCC subunit required for SV secretion [77] , [78] . This raises the possibility that UNC-36 α2δ VGCC might also localize another , presently unidentified , α1 VGCC subunit involved in DCV secretion . egl-8 PLCβ was also identified as a new positive regulator of INS-22 insulin/IGF secretion . Our previous work implicated pkc-1 PKCη/ε in DCV exocytosis and showed that an activated pkc-1 PKCη/ε mutation was epistatic to egl-8 PLCβ; this argued that pkc-1 PKCη/ε acts downstream of egl-8 PLCβ [53] . Here we showed that these two genes clustered together , indicating they have a similar spectrum of phenotypes , and are thus likely to act within the same pathway , rather than in parallel pathways . One model supported by our results is that EGL-8 PLCβ catalyzes the formation of a second messenger , DAG , to activate PKC-1 PKCη/ε , which in turn promotes DCV exocytosis [53] . This pathway appeared to be specific to DCV rather than SV secretion and may thus serve to regulate the types of transmitters secreted by a neuron . We identified goa-1 Gαo as a new negative regulator of insulin/IGF secretion . goa-1 Gαo also negatively regulates SV exocytosis in the same set of neurons [17] , [20] , [21] , [69] , consistent with a decrease in the punctal fluorescence of SNB-1 synaptobrevin in goa-1 Gαo mutants ( Table S2 ) . Together , this suggests that goa-1 may function as a regulator of secretion from both SVs and DCVs . The effect of GOA-1 Gαo on active zone components such as SYD-2 α-Liprin , UNC-10 RIM1α and UNC-13 likely contributes to its role to regulating SV secretion . Since DCV secretion does not occur at active zones [58] , GOA-1 Gαo likely regulates DCV secretion through effectors in other compartments . Whether the same pools of GOA-1 Gαo act to coordinate SV and DCV secretion or are regulated distinctly for each of these functions also remains to be determined . Aging is modulated by a conserved insulin/IGF signaling pathway in C . elegans and other species [8] . Whereas much attention has been focused on the pathways and effectors downstream of insulin/IGF receptor in the regulation of lifespan , little is known about how insulin/IGF secretion is regulated to initiate this process . Mutations that disrupt the core DCV exocytic machinery lead to increased longevity [79] , but the pathways that regulate insulin/IGF secretion in C . elegans lifespan control were previously unknown . Here , we identified G-protein and second messenger pathways that modulate insulin/IGF secretion and control C . elegans lifespan in an insulin/IGF signaling-dependent manner . Our results suggest that the bidirectional regulation of insulin/IGF secretion by these pathways are endogenous determinants of C . elegans lifespan . Elegant studies have indicated that communication between different tissues is required for proper regulation of lifespan [8] . The nervous system is the predominant locus of insulin/IGF expression in C . elegans [80] and may function as a signaling center in this process . Because the molecules identified here as regulators of insulin/IGF secretion are expressed throughout the C . elegans nervous system , they are likely to act as general rather than cell-specific factors . In this context , it is particularly interesting to identify signaling molecules such as G-proteins as regulators of insulin/IGF secretion . Since G-proteins mediate responses to extracellular signals , they provide an attractive mechanism for coupling changes in neuronal signaling to changes in lifespan . The proliferation of genomic and proteomic studies has provided substantial knowledge of cellular organization and function . Addressing how the genome regulates the proteome is a logical next step to link these two types of information . Our results demonstrate that even analyzing the relationship between a small , focused subset of genes and proteins can yield new and detailed information about a specific subcellular specialization . Thus , connecting gene function to protein localization can serve as a platform to understand detailed and global properties of subcellular compartments , the proteins that inhabit them and the genes that regulate these proteins . With advances in automated microscopy , we anticipate that extending our approach and analytical techniques to additional subcellular compartments across many genetically tractable systems will yield a wealth of biological information .
All strains were cultivated at 20°C using standard methods . The following mutations or transgenes were used in this analysis: unc-18 ( md1088 ) , unc-13 ( s69 ) , unc-2 ( lj1 ) , unc-31 ( e928 ) , aex-3 ( js815 ) , aex-6 ( sa24 ) , egl-10 ( n692 ) , unc-36 ( e251 ) , egl-30 ( ad806 ) , egl-30 ( js126gf ) , unc-10 ( e102 ) , egl-3 ( nr2090 ) , egl-8 ( sa47 ) , tomo-1 ( nu468 ) , rab-3 ( js49 ) , unc-26 ( s1710 ) , unc-11 ( e47 ) , sad-1 ( ky289 ) , wwp-1 ( ok1102 ) , dgk-1 ( nu62 ) , goa-1 ( sa734 ) , unc-57 ( e406 ) , pkc-1 ( nj3 ) , syd-2 ( ju37 ) , snb-1 ( md247 ) , daf-2 ( e1368 ) , daf-16 ( mu86 ) , nuIs152[ttx-3::mRFP , Punc-129::GFP::snb-1]II , nuIs159[ttx-3::mRFP , Punc-129::GFP::syd-2]III , nuIs163[myo-2::GFP , Punc-129::snn-1::Venus]II , nuIs165[myo-2::GFP , Punc-129::unc-10::GFP]II , nuIs168[myo-2::GFP , Punc-129::Venus::rab-3]IV , nuIs169[myo-2::GFP , Punc-129::gelsolin::Venus]III; nuIs184[myo-2::GFP , Punc-129::apt-4::GFP]X , nuIs190 X and nuIs195[myo-2::GFP , Punc-129::ins-22::Venus]IV , nuIs214[myo-2::GFP , Punc-129::itsn-1::GFP]III . All integrated transgenes were outcrossed 10 times to wild type N2 . For each marker , we selected one out of several integrated transgenes that displayed the most consistent and representative pattern of synaptic localization . Strains were genotyped by sequencing or PCR where appropriate . All mutants are described in www . wormbase . org . All GFP/YFP-labeled markers were expressed in the DA class of motorneurons under the Punc-129 promoter . All plasmids used to label presynaptic compartments are derivatives of pPD49 . 26 containing an SphI/BamHI unc-129 promoter fragment . All constructs were sequenced as to ensure that they contained wild type sequences . For the following constructs , all GFP or Venus fragments were cloned in-frame to the synaptic genes and the fusions were subcloned as NheI/KpnI fragments: KP#1283 Punc-129::GFP::snb-1 [11]; KP#1483 Punc-129::GFP::syd-2 ( gift of D . Simon ) ; pDS171 Punc-129::snn-1::Venus ( snn-1 cDNA fragment was used ) ; pDS203 Punc-129::unc-10::GFP [unc-10::GFP ( gift of D . Simon ) was subcloned as an NheI/KpnI fragment]; pDS165 Punc-129::Venus::rab-3 ( the 6b isoform of rab-3 cDNA was used , and the 5′ end of rab-3 contains the attL1 gateway site ) ; pDS233 Punc-129::itsn-1::GFP ( itsn-1 cDNA::GFP was a gift from J . Bai ) ; and pDS210 Punc-129::apt-4::GFP ( apt-4 cDNA was used and is flanked by gateway attL1 and R1 sites ) . For the following constructs , entry clones from the ORFeome project corresponding to the gene used was cloned into the destination vector KP#1284 [11] using the gateway strategy with LR clonase ( Invitrogen ) : pDS178 Punc-129::gelsolin::Venus and KP#1496 Punc-129::ins-22::Venus . KP#708 Pttx-3::mRFP or pPD118 . 33 Pmyo-2::GFP were used as transgenic markers . Presynaptic marker constructs were injected at 10–25ng/ul , and transgenic markers were injected at 50 ng/µl for KP#708 and 10 ng/µl for pPD118 . 33 . Young adult animals were paralyzed using 30 mg/ml BDM ( Sigma ) and mounted on 2% agarose pads for imaging . Images were acquired on a Zeiss Axiovert 100 microscope using an Olympus Planapo 100× objective ( NA = 1 . 4 ) and an ORCA 100 CCD ( Hamamatsu ) controlled by Metamorph 4 . 5 software ( Universal Imaging/Molecular Devices ) . Animals were imaged as previously described [11] , [53] . For dorsal cord imaging , ∼30 dorsally oriented animals per genotype were imaged near the posterior gonad bend . A maximum intensity projection was obtained from image stacks of the dorsal axon , the axon was traced in Metamorph 4 . 5 and traces containing fluorescence intensity along the axon were analyzed in custom software written in Igor Pro ( Wavemetrics ) as previously described [12] , [13] . For coelomocyte imaging , ∼20–60 laterally oriented animals where the coelomocyte was not obscured by other tissues were imaged . A maximum intensity projection was obtained from image stacks of the coelomocyte and the mean fluorescence within each vesicle in the coelomocyte were recorded in Metamorph 7; these values were analyzed in Igor Pro to obtain mean coelomocyte fluorescence for each genotype as previously described [53] . All fluorescence values in this study were normalized to the fluorescence of 0 . 5 µm FluoSphere beads ( Molecular Probes ) captured during each imaging session to provide a standard for comparing absolute fluorescence levels between animals from different sessions . Some nuIs152 data for this analysis was obtained from Sieburth et . al . , [11] and McEwen et al . , [19] . Under the conditions used for imaging , we determined that UNC-10::GFP , GFP::SYD-2 and APT-4::GFP were exclusively or predominantly localized to synaptic puncta , as we could detect little or no difference between their axonal fluorescence and the autofluorescence of C . elegans . For these markers , we excluded the axonal fluorescence in our analysis . Similarly , we excluded the FWHM for diffraction limited or near-diffraction limited markers ( UNC-10:GFP , GFP::SYD-2 , Gelsolin::Venus , SNN-1::Venus ) where the physical limitations of conventional light microscopy might prevent an accurate estimate of these values . The Student's T-statistic was used as a numerical score to represent the difference between wild type and mutant animals for each parameter of each marker ( Table S3 ) ; this created a numerical profile of phenotypes or marker behavior for further analysis . Correlation analysis was performed in Igor Pro ( Wavemetrics ) . Hierarchical clustering was performed with Cluster 3 . 0 [2] , [81]; the 24 clustering methods used were all combinations of 6 distance measures ( uncentered correlation , centered correlation , Spearman's Rank , Kendall's Tau , City-Block and Euclidean distance ) and 4 linkage methods ( maximum , minimum , centroid and average ) ( Table S1 ) . We identified several robust clusters based on unbiased , stringent criteria , requiring these clusters be detected in 12 or more out of 24 different clustering strategies used to analyze this dataset . Also , the phenotypic profiles in these clusters had to be significantly correlated ( p<0 . 05 with Bonferroni Correction ) . See Supporting Information in Text S1 for additional criteria . Using the Pearson's Correlation as a distance measure reproduced all the robust clusters identified in our dataset , justifying the use of this measure for comparing phenotypic and marker profiles . The dendrogram and heat maps were visualized with JavaTree [82] . Custom software written in Igor Pro ( Wavemetrics ) was used for all other clustering analysis , including the generation of the numerical scores for clustering , counting the number of times a cluster of genes appeared across the 24 combinations of clustering algorithms and calculating the importance of each parameter . For each cluster , we calculated a score indicating how each parameter contributed to the similarity among genes in that cluster based on how removal of the parameter from the analysis affected the similarity between phenotypic profiles within that cluster . For a given cluster , parameters that capture the majority of the contributing phenotypes ( i . e . those that comprise top 95% of the cumulative contributing score ) were deemed as important to that cluster ( see Supporting Information in Text S1 ) . To confirm the importance of these parameters , we repeated the clustering analysis using only these parameters for each cluster . In each case , we identified the cluster of genes , often with better robustness ( as determined by the number of clustering methods that gave rise to that cluster ) despite the reduction in the number of parameters used ( Figure S1 ) . To determine the significance of the correlation coefficients , we performed a bootstrapping analysis . For phenotypic correlation , we computed the correlation coefficients for 100 , 000 pairs of permutated phenotypic profiles , where each parameter in the profile was randomly drawn from the dataset . The resulting distribution of correlation coefficients allowed us to estimate how frequently a correlation coefficient would arise by chance alone . The significance of the correlation for the actual data was calculated as the fraction of correlation coefficients from the random permutations that gave a stronger score . Similar analyses were performed for the correlation between marker punctal fluorescence profiles . Lifespan assays were performed essentially as previously described [83] . For egl-30 ( gf ) , goa-1 and tomo-1 strains and controls , animals were transferred to a fresh plates each day during their fertile period to separate them from their progeny . For egl-3 , egl-30 and egl-8 strains and controls , animals were assayed on plates containing 0 . 1mg/ml 5-fluorodexoyuridine ( Sigma ) to kill their progeny [84] and prevent premature death due to internal hatching of progeny in these egg-laying defective mutants . Statistical analysis of survival was performed with SPSS 11 ( SPSS . Inc ) . | Cells are divided into multiple subcellular compartments that perform diverse functions . In neurons , synapses mediate transmission of information between cells and they comprise hundreds of proteins dedicated for this purpose . Changes in the protein composition of synapses are thought to produce changes in synaptic transmission , such as those that occur during development , learning , and memory . Here , we describe a systematic genetic strategy for analyzing the protein composition of synapses . Using this strategy , we identified sets of genes that alter synapses in similar ways , and identified novel regulatory relationships between particular synaptic proteins . One set of genes regulated secretion of insulin-like hormones from neurons and had corresponding effects on lifespan , which is controlled by insulin signaling . These results illustrate how changes in synaptic composition can be utilized as a probe to explain changes in physiology . Our approach can be expanded to include a larger set of synaptic proteins or to analyze other subcellular compartments . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"developmental",
"biology/aging",
"neuroscience/neuronal",
"signaling",
"mechanisms",
"neuroscience/neuronal",
"and",
"glial",
"cell",
"biology",
"genetics",
"and",
"genomics",
"genetics",
"and",
"genomics/bioinformatics"
] | 2008 | Profiling Synaptic Proteins Identifies Regulators of Insulin Secretion and Lifespan |
Awareness of the public health importance of tungiasis has been growing in East Africa in recent years , but data on epidemiological characteristics necessary for the planning and implementation of control measures do not exist . The work presented here was part of a larger cross-sectional study on the epidemiology of tungiasis in coastal Kenya and aims at identifying risk factors of tungiasis and severe disease in school children . A total of 1 , 829 students of all age groups from five schools and 56 classes were clinically examined for tungiasis on their feet based on standardized procedures and observations made about the school infrastructure . To investigate the impact of school holidays , observations were repeated after school holidays in a subset of children in one school . In an embedded case-control study , structured interviews were conducted with 707 students in the five schools to investigate associations between tungiasis and household infrastructure , behaviour and socio-economic status . The overall prevalence of tungiasis was 48%; children below the age of 15 years were the most affected , and boys were twice as likely as girls to be infected . The highest risk of disease was associated with the socio-economic circumstances of the individual student at home . The study indicated that mild to moderate tungiasis could be reduced by a third , and severe tungiasis by over half , if sleeping places of children had hardened floors , whilst approximately a seventh of the cases could be prevented by sealing classroom floors in schools , and another fifth by using soap for daily feet washing . There is a clear role for public health workers to expand the WASH policy to include washing of feet with soap in school-aged children to fight tungiasis and to raise awareness of the importance of sealed floors .
Sand flea disease ( tungiasis ) is a highly neglected parasitic skin disease which inflicts pain and suffering on millions of impoverished people in South America , the Caribbean and sub-Saharan Africa . Research on tungiasis is scant and most of the publications originate from South America [1] [2] , very little work has been done in sub-Saharan Africa . This is partly because even though the disease bears all the hallmarks of a Neglected Tropical Disease [1] it was until very recently [3] not included in the World Health Organisation’s list of Neglected Tropical Diseases . This made it difficult for funding organisations to invest research funds into determining the disease ecology and consequently the development of urgently needed treatment and prevention tools . Most research currently undertaken on tungiasis is small-scale , supported by national and international non-governmental organizations and well-wishers , reinforced by community-based self-help groups and is hence highly resource-constrained [2] . The development of the juvenile stages of the sand flea Tunga penetrans , is similar to that of other Siphonaptera; they live off the host but depend during their development on loose , sandy soil [4 , 5] . In contrast to other flea species , the adult female sand flea becomes permanently parasitic on its host , where it burrows into the skin and undergoes a dramatic growth , increasing its volume about 2000-fold within eight days [6] . Tungiasis affects mostly the feet and is associated with a pattern of debilitating morbidity [6] . Itching , pain , swelling , deep fissures , ulcers and abscess formation are symptoms of an acute inflammatory response to embedded fleas and bacterial superinfections of the lesions . Chronic infections result in chronic pain , disability , disfigurement and mutilation of the feet [6 , 7 , 8] . Children with tungiasis are often ridiculed by their peers and it has been shown that physical incapacity , mental strain and distress reduce quality of life [9] . Awareness of the public health importance of tungiasis has been growing in East Africa in recent years [10] , but data on epidemiological characteristics , necessary for the planning and implementation of a control program , do not exist . The work presented here was part of a larger observational study performed in disease endemic areas in coastal Kenya and included simultaneously implemented cross-sectional household-based risk factor surveys recently published [11] and school-based surveys presented here . To the best of our knowledge , combined , the two studies provide the most comprehensive risk factor study to date on tungiasis for Sub-Saharan Africa .
The study was performed in Malindi Sub-county , Kilifi County , eastern Kenya , where tungiasis is endemic and previous reports indicated disease prevalence in villages to range from 8% to 65% [11] . Malindi Sub-county is divided into two ecological zones: Kakuyuni Sub-location , a densely populated area in the coastal strip with tropical climate , and Malanga Sub-location , a less densely populated area inland with a much drier climate . Most rural homesteads in these areas consist of several mud-walled houses with a palm thatch roof and sandy floor . Domestic animals such as goats , cats , dogs and chickens walk freely on the compounds . Subsistence farming is the only activity practiced by most of the population to sustain their livelihood . The cross-sectional study was implemented between August 5 and October 3 , 2014 in five primary schools; two schools in Kakuyuni Sub-location ( labelled as KS1 and KS2 ) , and three schools in Malanga Sub-location ( labelled as MS1 , MS2 , MS3 ) . Schools were a minimum of 2 km apart with distinct catchment areas from where children originated . All except MS3 were public schools . The schools were purposely selected based on recommendation from the county Public Health Department as schools that were affected by tungiasis and no interventions had previously taken place in the catchment areas of these schools . The schools were located in the same communities as the household study . For the risk factor study a case: control design was used with a 1:1 ratio . The sample size calculation to yield results with 95% confidence limits , 80% power , an assumed prevalence of exposure of 40% among controls and least extreme odds ratio to be detected of 1 . 5 , indicated the need for a sample of 776 students ( 388 cases , 388 controls ) . To allow for incomplete data sets and be able to adjust for confounders we increased this by 20% , aiming to interview 930 students ( 465 cases , 465 controls ) . All schools were single-storey buildings and all were divided into several classrooms . MS2 had some classrooms of concrete and some of mud while all in MS3 were mud walls . The floor quality of the classrooms ranged from smooth cement surfaces to loose sand/soil ( Fig 1 ) . All schools had access to water and according to the information from the class teachers , classroom floors were swept daily by the students . For all classes , the classroom size , the number of students per class , and the type of classroom floor , walls and roof were recorded . All female and male students of all age groups , for whom informed consent and assent was given , were clinically examined for tungiasis , class by class . Prior to the clinical examination , the feet of the students were carefully washed with soap in a basin . Each individual was then examined for tungiasis based on a standardized procedure [11] , focussing on their feet and hands since a high number of lesions at the feet frequently coincide with the presence of ectopic lesions at the hands [12] . Patients were also asked whether they had tungiasis lesions in other regions of the body . Lesions were counted and staged according to the Fortaleza classification [6] as stage I: penetrating sand flea; stage II: brownish/black dot with a diameter of 1–2 mm surrounded or not by an erythema; stage III: circular yellow-white watch glass-like patch with a diameter of 3–10 mm and with a central black dot; stage IV: brownish-black crust with or without surrounding necrosis . Stage I to III are viable sand fleas . In stage IV the parasite is dying or already dead ( non-viable ) . Lesions manipulated with a sharp instrument ( by the patient or their caregiver ) with the intention to remove the embedded parasite were documented as manipulated lesions . Based on the number of lesions present , the intensity of tungiasis was classified as light ( 1–5 lesions ) , moderate ( 6–30 lesions ) or severe ( >30 lesions ) [13] . For every patient , the age , sex , and class were recorded . To investigate potential changes in the presentation of tungiasis in students after school holidays we aimed to repeat the clinical examinations in as many students as possible in KS1 who had been originally examined in the week immediately before the 4-week August holiday . Only 248 of the original group of students examined could be traced in the first week after the holiday . Within each school a subset of students was selected for interviews . In KS1 and MS1 , all tungiasis cases over the age of 4 years and the following uninfected student ( as an age-matched control ) were interviewed . In the remaining schools , only the first half of the cases ( in chronological order of their identification ) and the following uninfected student , were interviewed due to time constraints . It was not possible to recruit equal numbers of controls for interviews in MS2 and MS3 because the majority of students had tungiasis . Structured interviews were conducted using a pre-tested questionnaire in Giriama or Swahili language , including questions about the physical structure of the house in which children slept ( house walls , roof and floor ) , water sources and access at home , hygiene habits ( washing frequency , soap use , toilet facility at home ) , livestock and companion animals kept in homestead and walking time to school . Furthermore , observations were recorded about the condition of the students’ school uniforms and the type of shoes worn if any . Generalized Estimating Equations were used to analyse potential associations between the prevalence of tungiasis or the number of lesions ( of different stages ) and multiple variables recorded during interviews and observations . Prevalence data were modelled using binomial probability distributions with logit link functions fitted , count data were modelled using negative binomial probability distributions with log link functions fitted . Depending on the analysis the unique school ID , the unique class ID or the unique student ID were included as repeated measure and an exchangeable correlation matrix assumed . In the final multivariable risk factor analyses only factors found significant when tested individually in a univariate analysis were included as predictors . Interactions were explored for variable combinations that were plausible to be potentially interacting . In the final model , only significant interactions were included . All reported mean proportions or mean counts and their 95% confidence intervals ( CIs ) were estimated as the exponentials of the parameter estimates for models with no intercept included . Frequency counts were compared using the Pearson Chi-Square test . The analyses were done with R statistical software version 2 . 14 . 2 [14] . Population Attributable Fractions ( PAF ) were calculated , representing the fraction of cases which would not have occurred if an exposure had been avoided , assuming the exposure is casual and the other risk factors in the population remain unchanged [15] . PAFs are the percent exposed among cases multiplied by the attributable risk ( AR ) . The AR is the risk of tungiasis in the exposed due to the exposure and is calculated as ( odds ratio ( OR ) −1 ) /OR . The study was approved by the Ethics Review Committee at Pwani University , Kilifi County , Kenya; approval number ERC/PhD/010/2014 . During the study preparation phase contact was made with the County and District leadership in the Ministry of Health and the Ministry of Education , the Zonal Education Officer and the Community Health Officers to obtain their approvals and support for the study . Meetings were held with Community Health Workers ( CHWs ) in each sub-location , training on tungiasis provided and the aims and procedures of the study explained , emphasizing that participation was completely voluntary , and subjects had the opportunity to withdraw from the study at any point in the study . Head Teachers were visited and provided with an information sheet . The information was read out at a parents’ meeting prior to the study , explaining the procedure and voluntary nature of participation , and asking for consent . The Head Teacher signed the consent form ( S1 Annex ) on behalf of the parents and school . Data were collected with the help of Community Health Volunteers of the respective Community Health Unit . All data analyses were conducted anonymously . All students with tungiasis were treated after the survey by the Community Health Workers according to standard practice in Kilifi County [10] . For those with secondary bacterial infection and other illnesses requiring treatment , a referral form was prepared by a Community Health Worker , and patients were referred to the nearest Health Facility .
Of the examined 1 , 829 primary school students 48% were boys and 52% were girls; 31% of the students were 2–9 years old , 52% 10–14 years old and 17% were 15–21 years old . Of the 870 ( 48% of 1 , 829 ) students with tungiasis , 58% had mild infections ( 1–5 lesions ) , 31% moderate ( 6–30 lesions ) and 11% severe infections ( >30 lesions; ) . The majority of all cases were males aged 10–14 years ( 28 . 4% of cases , Fig 3 ) and also had the highest percent of moderate and severe cases . The student population size examined ranged from 140 to 582 between schools and the prevalence of tungiasis varied significantly between the five schools ranging from 31% to 83% ( Table 1 ) . The physical school environment was considered a potential risk factor for tungiasis either directly providing a conducive environment for the off-host host stages to develop and adult sand fleas to find a host or indirectly as a proxy measure for the socio-economic circumstances affecting the community from which the children were drawn to the respective schools ( children from poor background might only be able to afford sending children to a school with very basic school environment ) . Size , materials of the floors , walls and roofs were recorded for every classroom from which children were examined during the surveys . The majority ( 70% ) of the students were taught in classrooms between 40–70 m2 while 22% were taught in classrooms larger than 70 m2 and only 8% in classrooms smaller than 40 m2 . Classroom size was not significantly associated with tungiasis prevalence in a univariate analysis , and neither was the number of children per m2 in a classroom , which ranged from 0 . 4 to 2 . 0 . Most classroom floors were made of concrete; 46% of all screened students were taught in a room with a good quality concrete floor and 40% in a classroom with cracked concrete floor . Concrete floors were always associated with concrete walls and iron sheet roofs . Only 14% of the surveyed students studied in classrooms with a natural sand/soil floor . These classrooms also had mud walls and thatched roofs ( Fig 1 ) . The differences in tungiasis prevalence between schools were confounded by the physical classroom environment as revealed by the multivariable analysis ( Table 1 ) . The floor type of the classroom was an important risk factor for finding a tungiasis case , the degree of risk per floor type , however , was dependent on the school , as shown by the significant interaction between floor type and school . Natural sand or soil floor of a classroom was an independent risk factor , increasing the probability of finding a tungiasis case 3-fold as compared to finding a case among students that were taught in a classroom with a well-kept , smooth concrete floor . Classrooms with natural sand/soil floors were only present in MS2 and MS3 , the two schools with the highest tungiasis prevalence . Whether a cracked concrete floor represented a risk for finding a tungiasis case depended significantly on the school . The impact of the interactions can be calculated by multiplication of the odds ratios [16] . This means a cracked concrete floor was only a factor significantly associated with increased disease risk in MS2 ( OR 11 . 54 x OR 0 . 51 = OR 5 . 89 ) , where classrooms with sand/soil and concrete floors coexisted but not in MS1 ( OR 2 . 16 x OR 0 . 51 = OR 1 . 10; Table 1 ) . Consequently , floor type was not an explanatory variable for tungiasis prevalence in KS1 , KS2 and MS1 , where tungiasis prevalence ranged between 31% and 51% ( Table 1 ) . Both age and sex were significantly , and independently associated with tungiasis . Children below the age of 15 years were 1 . 4–1 . 6 times more likely to be diagnosed with tungiasis than older students and boys more than 2 times more likely than girls ( Table 1 ) . No specific school-based risk factors were significantly associated with severe tungiasis , when the multivariable analysis was repeated with severe manifestation as the dependent variable . Anecdotal information provided by the teachers suggested that children usually return to school with a higher tungiasis burden after school holidays . To investigate this , we compared the tungiasis prevalence and infection status immediately before and after the one-month August school holiday in the 248 students who were able to be traced in the first week after the holiday in KS1 ( Tables 2 and 3 ) . This sub-group comprised 41% boys , 59% girls , with 23% <10 years old , 55% 10–14 years old and 22% 15–20 years old . Sex and age were identified , similar to the analysis on the larger data set , as independent risk factors for tungiasis before and after the school holidays , with boys and younger age groups more likely to be found with the disease than girls and older age groups ( Table 2 ) . There was no significant interaction between sex , age and survey time . The probability of finding a tungiasis case after the school holidays was 1 . 7 times higher than before the holidays , with a mean prevalence in students of 31% ( 95% CI 25–38% ) before and 44% ( 95% CI 36–51 ) after the holidays ( Table 2 ) . Taking a closer look at the number and developmental stage of the embedded sand fleas ( Table 3 ) , we observed that the number of viable lesions in students with tungiasis had significantly decreased ( RR 0 . 30 ( 95% CI 0 . 10–0 . 84 ) , p = 0 . 023 ) after the holidays from a mean number of 2 . 52 ( 95% CI 1 . 61–3 . 93 ) viable lesions before to 0 . 80 ( 95% CI 0 . 50–1 . 29 ) after the holidays , irrespective of sex and age . The number of non-viable lesions was generally highest in students with tungiasis between 10–14 year of age irrespective of sex and survey round , however significantly decreased ( RR 0 . 17 ( 95% CI 0 . 04–0 . 66 ) , p = 0 . 010 ) after the holidays from a mean of 8 . 87 to a mean of 3 . 21 ( Table 3 ) . A proportionally similar decrease in non-viable lesions was also seen in the younger age group of 2–9 years old students but not in the older students as shown by the significant interactions between age and survey round ( Table 3 ) . On the contrary , the number of manipulated lesions increased significantly after the school holidays . Significant interactions in the analysis ( Table 3 ) highlighted a proportionally higher increase in manipulated lesions in girls from 3 . 06 ( 95% CI 1 . 84–4 . 94 ) before to 9 . 52 ( 95% CI 7 . 24–12 . 53 ) after holidays , than in boys , even though boys had overall a larger number of manipulated lesions ( mean before holidays 7 . 98 ( 95% CI 5 . 35–11 . 91 ) ; after holidays 10 . 55 ( 95% CI 7 . 86–14 . 16 ) ) . There was also a proportionally higher increase in the number of manipulated lesions in the 10-14-year-old students than in the other age groups ( Table 3 ) . Most of the characteristics assessed by observation and interview , for each of the 707 students interviewed , showed considerable heterogeneity between schools , except for sex and ownership of dogs and chickens ( Table 4 ) . The significant between-group variations for schools was taken into consideration by including the school as a random factor in the subsequent multivariable analyses of the interview data ( Table 5 ) . Since tungiasis cases and healthy controls were matched by age at the enrolment stage , age was not a factor significantly associated with tungiasis as an outcome in the analysis of the interview data and hence not included in the multivariable analysis . Expectedly , sex was similarly associated with tungiasis risk in the interview data , with boys being >2 times more likely to be found with tungiasis than girls . The condition of the school uniform was not independently associated with tungiasis , but an interaction existed with sex . The chance of finding tungiasis was significantly higher ( OR 4 . 30 ( 95% CI 1 . 47–12 . 60 ) , p = 0 . 008 ) in boys with torn school uniforms than in boys with better uniforms or in girls with torn uniforms ( Table 5 ) . Similarly , the absence or presence of open or closed shoes was not by itself a risk factor for tungiasis . When a child was however found not wearing shoes and had a badly torn school uniform it was highly likely ( OR 5 . 32 ( 95% CI 3 . 22–8 . 79 ) , p<0 . 001 ) to find tungiasis ( Table 5 ) . The time a child took to walk to school was not significantly associated with presence of tungiasis in the multivariable analysis . Whilst the building material of the students’ homes floors , walls , and roofs were all associated with tungiasis in a univariate analysis only the home’s floor was an independent risk factor in the multivariable analysis . A student from a home with a natural sand or mud floor indoors was nearly twice as likely to be diagnosed with tungiasis , than a student from a home with a concrete floor in the house ( Table 5 ) . Most of the students had access to piped water or a well either on their compound or shared in the village . Nevertheless , students coming from a home where water was fetched from a community tap or well were 1 . 6 times more likely to have tungiasis than those students that had tap water on their compound at home . The time it takes for the family to fetch water was not associated with the disease outcome . Whilst the frequency of washing feet was not associated with the presence of tungiasis , the use of soap strongly was . Students that responded never to wash their feet with soap were over 6 times more likely ( 95% CI = 3 . 2–12 . 6 , p<0 . 001 ) to have tungiasis and students that responded to only sometimes wash they feet with soap were 1 . 6 times more likely ( 95% CI 1 . 50–1 . 76 , p<0 . 001 ) to have tungiasis than those students always washing with soap ( Table 5 ) . Although washing frequency responses were not significantly associated with tungiasis , not answering this question was ( OR 6 . 01 ( 95% CI = 3 . 64–9 . 92 ) , p<0 . 001 ) . Neither the type of toilet at home , nor the presence of a dog on the compound , were significantly associated with disease outcome when the analysis was adjusted for all other variables . In an attempt to better understand what drives severe infection ( >30 embedded lesions ) we performed a multivariable analysis for severe disease as the outcome ( n = 71 , 18% of all cases N = 398 ) , comparing the characteristics of these severe cases with mild to moderate cases ( 1–30 lesions , n = 327 ) . Sex , condition of clothing , shoe-wearing and frequency of soap use were not significantly associated with disease severity . Of all tungiasis cases , severe infections were more likely to be found in the younger age groups ( Table 6 ) , in children having a natural sand/mud floor indoors at home than those that have a stone/cement floor at home , using a water source other than a private or community tap or well , and washing their feet less than once a day . Of all children with tungiasis , those that reported their family did not own at least one chicken had a significantly higher risk of heavy infection than children who reported they kept chicken ( Table 6 ) . Amongst all children with tungiasis , school floor characteristics were not a predictor for heavy infection . For those factors which were significant risks for tungiasis or a high intensity of infection , and are amenable to being changed , the PAF were calculated . The PAF is the percent reduction in prevalence that would occur if exposure to the risk factor were removed . The highest PAF for both , any infection and severe infection was found to be having a home floor of sand or smeared mud ( 30 . 7% and 54 . 4% respectively , Table 7 ) . Only using soap sometimes when washing had a PAF of 21 . 5% , and a classroom floor of sand had a PAF of 14 . 3% for any type of infection .
Our study confirmed that the prevalence of tungiasis is extremely heterogeneous , varying from school to school and community to community even though they are only a few kilometres apart [17] . The disease burden was highly aggregated even within an individual school , with more than half of the cases having only a few embedded sand fleas but a minority being severely affected . The overall prevalence of 48% of all screened school-aged children was twice as high as the prevalence in the simultaneously implemented household study [11] , reflecting the high proportion of the most affected age group in the school-based study . As has been shown before in Brazil [17] , Uganda [18] , Nigeria [19] , and Kenya [20 , 21] , school-aged children below the age of 15 years were the most affected by tungiasis and boys were twice as likely as girls to have the disease . The risk factor interviews as well as the follow up examinations after the long school holidays suggest strongly that the highest risk of disease is associated with the socio-economic circumstances of the individual student at home . Whilst an unsealed , natural sand or soil floor of a classroom came out as an independent risk factor in the analysis it is important to note that such classroom floors were only present in two schools where the majority of pupils came from homes that had unsealed floors . The calculation of the PAF indicates that mild to moderate tungiasis could be reduced by a third , and severe tungiasis by over a half , if homes ( sleeping places of children ) had sealed floors , whilst approximately a seventh of the cases could be prevented by sealing classroom floors in schools . The presence of unsealed floors at home , has been previously indicated as an important risk factor for the disease [13 , 21 , 22] , and can only be a consequence of the biology of the sand flea , with egg , larval and pupal ( off-host stages ) development taking approximately three weeks and requiring shaded , dry , loose soil or sand [4 , 5] . Such unsealed floors provide a constant supply of the sand fleas searching for hosts as soon as they emerge as adults . This finding also corroborates the assumption that in settings where the prevalence of tungiasis is stable the whole year round , the transmission mainly takes place inside the house , particularly in the room where children sleep [1] . Neither the condition of the school uniform , nor wearing shoes potentially protecting against host-seeking sand fleas [23] was independently associated with tungiasis , however , the combination of a torn uniform and the absence of shoes can be considered an indicator of the poverty level or care given to the child at home . Complex interactions between risk factors suggest underlying behavioural differences in the care given by parents and guardians and/or hygiene behaviour expressed in boys and girls . Boys with torn uniforms were four times more likely to be affected by the disease than girls wearing uniforms in equally poor condition . Whilst the frequency of washing was not associated with tungiasis , the availability of piped or well water within the homestead and the use of soap when washing was strongly associated with reduced risk . Both factors might be linked to the socio-economic status of the family to afford piped water and soap , but also to behavioural characteristics of the care givers and children , as already noted in the household study [18] . The higher risk of infection and severe disease observed for boys between the ages of 10 and 14 years may be a reflection of their hygiene practices , being less likely to wash daily , particularly with soap than girls in the same age group . Whilst such a sex-specific association was not detected in the analysis in the current study , previous studies using interviews and observation in other countries have found boys to have poorer skin hygiene than girls [24] . A recent study examining the relationship between socioeconomic status and WASH practices in India also highlighted the fact that over 80% of mothers did use soap to wash themselves but only 20% used soap to wash their children [25] . The data from before and after school holidays , whilst a small dataset , highlighted a number of findings that are significant and warrant replication in future . Not only did the overall prevalence of tungiasis increase after the holiday , there was also a significant increase in the number of manipulated lesions . These are the sores and cicatrices that remain after an embedded sand flea has been purposively extracted with a sharp instrument and are a clear indication that the person recently had a viable embedded sand flea . The likely explanation is that the children have acquired more sand fleas whilst spending more time at home during the holiday , but they or a caregiver have extracted them . There was a significant interaction between the number of manipulated lesions and girls , again suggesting differential hygiene and caring behaviours . Teasing apart these complex linkages of economic status and behavioural traits will be important in future studies and might indicate school-aged boys to be an important target for prevention programs . Surveys in other countries have identified tungiasis as a zoonosis with the involvement of dogs [13] and pigs [26 , 27] in disease transmission . Pigs are not frequently kept in communities in coastal Kenya ( only four students in the survey reported owning pigs ) , whilst goats and dogs were relatively common with 75% and 30% of students reporting household ownership , respectively . However , neither the previously published household study [11] nor the here presented school survey identified the possession of any animal species to be a risk factor . Whether this is an indication that transmission in these coastal communities is purely intra-domiciliary and does not involve an animal reservoir needs further investigation by examining livestock and companion animals for tungiasis . The current school survey did identify the absence of chickens in a household as a risk factor for severe disease , which may simply be another reflection of extreme poverty as a risk factor , which needs to be studied however more systematically . The fact that the same household risk factors were identified in this study by asking the children about their homes , as in the corresponding household study where adults were interviewed , and observations made , suggests that school-based surveys are a reasonable alternative to the more expensive and time-consuming household surveys and can be used for nation-wide evaluation of tungiasis prevalence . Modelling based on past household surveys with full age profiles will enable extrapolation to the whole population . School-based surveys have the advantage of a high concentration of at-risk subjects to survey during day time when there is good light for examinations . To be able to examine all house occupants for tungiasis a team must visit during evening hours and at weekends , and still many family members may be absent . Houses may be far apart , and therefore surveying costly to achieve suitable sample sizes . Targeting school-aged children in school for diagnosis and treatment of tungiasis , using recently evaluated safe and effective treatment options , namely dimeticone or neem oil [2 , 28 , 29] , might be the most cost-effective way to reduce the disease burden given that the affected resource-poor communities do not have access to optimal medical care and limited ability to pay for expensive medications . However , the treatment must be provided every time a new infection in a child is detected by the teachers to prevent the life cycle being introduced into classrooms with a cracked or natural sand/mud floor , and to break the cycle at home . The disadvantage of conducting surveys and treatment programs only in schools means the most severely affected children who cannot walk to attend school , the elderly and disabled , who also tend to have severe infections , will be missed . This factor was a possible limitation of the study , possibly causing bias in the study findings . However , the study included a similar proportion of severe cases to that seen in the household survey ( 11% and 15% respectively ) , so any effect on outcomes is likely to be minimal . The higher proportion of severe cases in the household survey was more likely to be due to the inclusion of the elderly who tend to have more severe infections [11] . Another limitation of the study was the low number of schools with non-cemented floors that were able to be included in the study , and that the one school that was entirely dirt floors , was the only private school , with the majorty of children in the lower age groups . However , any potential confounding was adjusted for in the statistical modeling . Observations from our study suggest that up to 70% of tungiasis cases may be prevented through simple prevention methods , namely washing feet at least once a day with soap and installing hard floors in homes and schools . Hence , foot washing needs to be incorporated into hygiene and sanitation education campaigns of the current global efforts to achieve Sustainable Development Goal 6; “by 2030 , achieve access to adequate and equitable sanitation and hygiene for all” . Tungiasis has been implicated to impact children’s learning capacity [9] , consequently , there is a clear role and need for schools ( head teachers and class teachers ) , public health officials , community health workers and NGOs to educate in and enforce good hygiene practices , particularly the use of soap for daily washing of feet . Furthermore , acknowledging that sealed classroom floors can contribute to tungiasis reduction , governments and education officials need to make the cementing of all classroom floors a priority , along with adequate water supplies and provision of soap for washing . The installation of hardened floors in family homes is not as simple as it sounds , and requires research and potentially government investment . Those resource-poor , marginalized families affected by tungiasis cannot , under most circumstances , afford the cost of a cement floor , which in Kenya costs a minimum of $200 for a typical rural house of 6 x 4 m . In discussions with community members , it was highlighted that in the past communities used traditional methods for hardening floors such as regular smearing with a mix of soil and cow dung and termite mound soil , but these methods have ceased , and floors are no longer hardened ( Elson , personal communication ) . Clearly there is a need for research into understanding why house floors are not hardened with the simple , cheap methods currently available , as well as developing alternative , locally available and affordable floor technologies that the most resource-poor families can install themselves . | Tungiasis is a neglected tropical skin disease caused by penetrated sand fleas , the adult female of which burrows into the skin of the feet . The parasite rapidly expands its body size by a factor of 2000 . The growth causes immense itching , inflammation , pain and debilitation . The current lack of good treatment methods means people attempt to remove the fleas themselves with non-sterile instruments causing more damage . Control efforts focus on prevention but there is little data to guide this in East Africa . The current study reinforces our previously published results on the household level from the same communities , indicating that prevention needs to focus on hardening the floors of resource-poor families and integrating daily foot washing with soap into water , hygiene and sanitation programs . | [
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] | 2019 | Prevalence, intensity and risk factors of tungiasis in Kilifi County, Kenya II: Results from a school-based observational study |
Phagocytic cells capture and kill most invader microbes within the bactericidal phagosome , but some pathogens subvert killing by damaging the compartment and escaping to the cytosol . To prevent the leakage of pathogen virulence and host defence factors , as well as bacteria escape , host cells have to contain and repair the membrane damage , or finally eliminate the cytosolic bacteria . All eukaryotic cells engage various repair mechanisms to ensure plasma membrane integrity and proper compartmentalization of organelles , including the Endosomal Sorting Complex Required for Transport ( ESCRT ) and autophagy machineries . We show that during infection of Dictyostelium discoideum with Mycobacterium marinum , the ESCRT-I component Tsg101 , the ESCRT-III protein Snf7/Chmp4/Vps32 and the AAA-ATPase Vps4 are recruited to sites of damage at the Mycobacterium-containing vacuole . Interestingly , damage separately recruits the ESCRT and the autophagy machineries . In addition , the recruitment of Vps32 and Vps4 to repair sterile membrane damage depends on Tsg101 but appears independent of Ca2+ . Finally , in absence of Tsg101 , M . marinum accesses prematurely the cytosol , where the autophagy machinery restricts its growth . We propose that ESCRT has an evolutionary conserved function to repair small membrane damage and to contain intracellular pathogens in intact compartments .
After phagocytic uptake , the closely related pathogenic bacteria Mycobacterium tuberculosis and M . marinum reside in an altered and maturation-arrested phagosome , thereby avoiding its toxic chemical environment [1] , but remaining protected from the cell-autonomous cytosolic defences [2] . This Mycobacterium-containing vacuole ( MCV ) becomes permissive for the bacilli to survive and replicate [3 , 4] . However , bacteria access to nutrients is limited . To circumvent this restriction , tubercular mycobacteria damage the MCV and escape to the cytosol . The site of MCV rupture becomes a complex battlefield where various machineries cooperate to repair membrane damage and control cytosolic bacteria . Here , we used the Dictyostelium discoideum-M . marinum system to study the role of Endosomal Sorting Complex Required for Transport ( ESCRT ) and autophagy in membrane repair during both sterile and pathogen-induced damage . We show that the function of ESCRT-III in membrane repair is evolutionarily conserved , that it contributes to the integrity of the MCV and plays an unrecognised role in cell-autonomous defence . We also provide evidence that the ESCRT-III and autophagy pathways act in parallel to repair endomembrane compartments , but differ in their ability to restrict mycobacteria growth in the cytosol of infected cells . To access the cytosol , mycobacteria make use of a crucial pathogenicity locus , the Region of Difference 1 ( RD1 ) , which encodes the ESX-1 system responsible for the secretion of the membranolytic peptide ESAT-6 [5] . Together with the mycobacterial branched apolar lipids phthiocerol dimycocerosates ( PDIMs ) [6 , 7] , ESAT-6 produces membrane perforations that cause MCV rupture and bacterial escape to the cytosol [3 , 8 , 9] , a step that precedes egress of the bacteria and their dissemination to neighboring cells ( reviewed in [10 , 11] ) . At the site of MCV rupture cells need to discriminate self from non-self as well as from topologically misplaced self molecules . Damage exposes either pathogen-associated molecular patterns ( PAMPs ) or damage-associated molecular patterns ( DAMPs , from the vacuole ) to cytosolic machineries that sense them , resulting in the deposition of “repair-me” and "eat-me" signals . Among the latter , the best studied during infection by various intracellular bacteria , including mycobacteria , is ubiquitin . It is conjugated to mycobacterial or host proteins by the E3 ligases NEDD4 [12] , Smurf1 [13] , Parkin [14] and TRIM16 [15] leading to the recruitment of the autophagy machinery to restrict their growth ( xenophagy ) . In addition , mammalian galectins such as Gal-3 [15 , 16] , Gal-8 [17] and Gal-9 [18 , 19] bind to exposed lumenal glycosylations of damaged endosomes [20 , 21] or to components of the cell wall of bacterial pathogens , and thus might play a defence role against mycobacterial infection . Although the signaling that leads from these “eat-me” tags to the recruitment of autophagy is well understood [2 , 22] , how the recruitment of the repair machinery ( ies ) is mediated remains mysterious [23] . Strikingly , autophagy has been shown to participate in restricting the growth of some bacteria [23 , 24] , whilst also contributing to the establishment and maintenance of the compartments containing Salmonella Typhimurium [25] and M . marinum [23] . Recent studies have highlighted the potential of another cytosolic machinery , the ESCRT , in both repair of membranes damaged by sterile insults [26–29] and in the control of mycobacteria infection [30] . ESCRT is an evolutionary-conserved machinery , composed of four protein complexes ( ESCRT-0 , -I , -II , -III ) , the AAA-ATPase Vps4 and multiple accessory proteins , involved in various processes of membrane remodeling . This is achieved by the ESCRT-III component Chmp4/Snf7/Vps32 , which polymerizes in spirals that drive membrane deformation [31] , whereas Vps4 triggers membrane scission and ESCRT-III disassembly [32–34] . The most studied functions are in the invagination of intralumenal vesicles of multivesicular bodies , which is initiated by the ubiquitination of the cargo to be sorted [35] , in the release of viruses by budding off the plasma membrane [36] and in the constriction of the cytokinetic bridge during mitosis [37] . Additional roles for ESCRT have been uncovered , such as exosome and microvesicle biogenesis , neuron pruning , removal of defective nuclear pores , and micro- and macroautophagy [38] . Importantly , ESCRT-III has also recently been proposed to mediate repair at a number of membranes such as plasma membrane wounds of less than 100 nm , possibly by surface extrusion [26] , as well as small disruptions in endolysosomes [28 , 29] . The ESCRT complexes are implicated in infection of Drosophila S2 cells with M . fortuitum [39] and Listeria monocytogenes [40] . Follow-up studies showed that depletion of the ESCRT proteins Vps28 or Tsg101 led to an increase of M . smegmatis proliferation in RAW macrophages . These bacteria were found to be highly ubiquitinated at 3 hours post-infection ( hpi ) in S2 cells , and electron microscopy ( EM ) inspection revealed that most of them were inside a vacuolar compartment . In the case of L . monocytogenes , a mutant unable to secrete the pore-forming toxin LLO , but still expressing two membranolytic phospholipases C , was found to escape more to the cytosol in S2 cells devoid of several ESCRT proteins ( Bro/ALIX/AlxA , Vps4 and Snf7/Chmp4/Vps32 ) [41] . In this context , ESCRT was involved in membrane trafficking and the establishment of the pathogen-containing compartment . However , whether ESCRT plays a role in the repair of damage inflicted by the mycobacteria remains to be addressed . Recent reports brought evidence for a role of ESCRT-III in repairing sterile damages to various membranes , such as the plasma membrane ( laser wounding , detergents , pore-forming toxins ) [26 , 27] , the nuclear membrane ( laser wounding and confined cell migration ) [42 , 43] and endolysosomes ( lysosomotropic compounds and silica crystals ) [28 , 29] . Importantly , a recent report also showed the recruitment of the ESCRT-III component Chmp4B to vacuoles containing Coxiella burnetti [29] . ESCRT-III recruitment to damage at the plasma membrane and lysosomes was proposed to depend on the recognition of a local increase of Ca2+ by ALIX and/or ALG2 [26–28] . In all other cases , ESCRT-III is recruited to the disrupted membranes , but the cues and signaling pathways involved remain unclear . The ESCRT and autophagy machineries are highly conserved in the social amoeba D . discoideum [44] . In the last decade , D . discoideum has emerged as a powerful model system to study host-pathogen interactions , including with the human pathogens Legionella pneumophila , Pseudomonas aeruginosa , Vibrio cholerae , as well as various mycobacteria species such as M . tuberculosis and M . marinum ( reviewed in [45] ) .
Previous work demonstrated that the MCV suffers continuous ESX-1-dependent insults and injuries during infection , from the first hour post-entry , when no macroscopic sign of breakage is observed , until about 24 hpi , when the bacteria escape to the cytosol [3] . Ubiquitination is among the first readout of damage and was shown to trigger the recruitment of the classical autophagy machinery components such as Atg18 , p62 and Atg8 [23] . In order to gain a deeper morphological and ultrastructural insight into the sites of MCV membrane damage during M . marinum infection , cells at 24 hpi were subjected to Focus Ion Beam Scanning Electron Microscopy ( FIB-SEM ) ( Fig 1 ) . This revealed a complex interface between the MCV and the cytosol at the site of bacteria escape . Fig 1A , 1B and 1C show views and 3D reconstructions of bacteria escaping from an MCV and captured by an autophagosome . The zone surrounding the portion of the bacteria in contact with the cytosol shows both discontinuities and highly electron-dense material ( Fig 1C and 1D ) . Careful inspection of the samples , together with their 3D reconstruction , revealed that this compact mass was apparently not separated from the MCV content or the host cytosol by any membrane ( Fig 1D and 1E , S1 Movie ) . These observations suggest that bacterial and host factors accumulate at the place of MCV rupture . In macrophages and D . discoideum , damaged MCVs and escaping M . marinum accumulate ubiquitin , although the substrate of ubiquitination remains elusive [23 , 46 , 47] . Therefore , we speculate that the dark electron-dense material observed at the areas of MCV rupture might correspond to local accumulation of ubiquitinated cargoes , proteins belonging to the autophagy pathway and possibly other cytosolic machineries , such as the ESCRT , recently implicated in endolysosomal membrane damage repair [28] . One of the first host responses to membrane damage is the ubiquitination of the bacilli and the broken MCV , followed by recruitment of the autophagy machinery to delay escape to the cytosol [23] . To test whether the ESCRT machinery is also recruited to damaged MCVs , cells expressing the ESCRT-I component GFP-Tsg101 , the ESCRT-III effector GFP-Vps32 or the ATPase Vps4-GFP were infected with wild-type ( wt ) M . marinum or M . marinum ΔRD1 ( Fig 2A–2D ) . All three proteins were recruited to MCVs containing wt M . marinum , but were significantly less so in cells infected with the attenuated M . marinum ΔRD1 . This bacterial strain causes very limited membrane damage and escapes very inefficiently to the cytosol , due to the lack of secretion of ESAT-6 but despite the presence of similar level of PDIMs compared to wt bacteria [6 , 48] ( S1 Fig ) . The ESCRT-positive structures comprised small foci , patches of several micrometers and even rings that were observed to slide along the length of the bacteria compartment ( Fig 2E and S2 Movie ) . These structures seemed to become larger at later time-points ( Fig 2A , 24 and 31 hpi ) , suggesting increased recruitment upon cumulative damage as infection progresses . Careful 3D inspection at late time-points revealed that GFP-Vps32 patches always surrounded the MCV , but were not in its lumen ( Fig 2F ) . During membrane remodeling in mammalian cells , the ESCRT-III complex can be recruited to biological membranes via several pathways , one of the most studied relies on the ESCRT-I component Tsg101 [49] . Importantly , in cells lacking Tsg101 , GFP-Vps32 structures were significantly reduced at early times of infection ( Fig 2G and 2H ) , which may indicate that M . marinum-induced damage triggers one or more pathways of ESCRT-III recruitment to the MCV . Altogether , we conclude that the ESCRT-III is recruited to the MCV in an ESX-1 dependent manner , consistent with a role in membrane repair . In order to gain a deeper insight on the GFP-Vps32 structures observed during M . marinum infection , the precise localization of GFP-Vps32 on the MCV was analyzed . The MCV membrane was visualised by the presence of the ammonium transporter AmtA-mCherry , or antibodies against the predicted copper transporter p80 [23] ( Fig 3A and 3B ) . MCVs with an apparent continuous staining for p80 or AmtA-mCherry ( Fig 3A and 3B , 1 . 5 hpi ) were not associated with GFP-Vps32 . On the contrary , compartments that displayed clear disrupted staining for p80 or AmtA-mCherry presented numerous GFP-Vps32 patches at the sites of membrane wounds ( Fig 3A and 3B , 8 , 24 and 31 hpi ) . Close inspection of these images revealed that , at sites of GFP-Vps32 recruitment , the damaged MCV membrane was sometimes invaginated towards the lumen of the compartment , away from the cytosol ( S2A Fig ) . These invaginations are reminiscent of the membrane deformations observed sometimes at the MCV by EM , which are surrounded by dense cytosolic material ( S2B and S2C Fig ) . Time-lapse microscopy enabled tracking of the GFP-Vps32 structures associated with the MCV , indicating direct assembly onto the membrane of the compartment rather than delivery via pre-existing structures ( Fig 3C ) . GFP-Vps32 structures remained associated with the MCV for several minutes ( Fig 3C and S3 Movie ) . M . marinum in intact MCVs stained by p80 are rarely ubiquitinated , contrary to bacteria in the cytosol ( Fig 3D ) . Therefore , we wondered whether Vps32 would be recruited at sites of ubiquitination , together with the main autophagy marker Atg8 . Remarkably , all three proteins localized at disrupted MCVs , but the level of colocalisation of Vps32 with ubiquitin ( Fig 3E ) or Atg8 ( Fig 3F ) was limited . Instead , GFP-Vps32 seemed to be recruited more proximally to the membrane remnants of the MCV than ubiquitin and Atg8 , which predominantly decorated the bacteria poles fully exposed to the cytosol . Besides , at the boundary between the zones enriched in GFP-Vps32 and Atg8 , GFP-Vps32 was more proximal to the bacteria , possibly indicating an earlier recruitment ( Fig 3E–3G ) . Taken all together , recruitment of ESCRT-III proteins to the M . marinum MCV seems to happen earlier and at different places than the autophagic recognition of the bacteria , suggesting that ESCRT-III and the autophagy pathway might play separate functions in repair and additionally in xenophagic capture . Mammalian ESCRT and autophagy machineries localize to damaged membranes for the repair of wounds and removal of terminally incapacitated organelles , respectively [26–29 , 42 , 43] . To test whether components of both machineries were also involved in membrane repair in D . discoideum , cells expressing GFP-Tsg101 , GFP-Vps32 or Vps4-GFP , as well as GFP-Atg8 were subjected to membrane damaging agents , such as the detergent digitonin or the lysosome-disrupting agent Leu-Leu-O-Me ( LLOMe ) ( Fig 4 ) . Digitonin inserts first into the sterol-rich plasma membrane and then , upon endocytosis , reaches the endosomes . Consistent with this , digitonin initially induced at the plasma membrane dots and crescent-shaped structures of GFP-Vps32 and Vps4-GFP ( Fig 4A and 4C , S4 Movie ) . After a few minutes , dispersed foci appeared throughout the cytoplasm , suggesting progressive disruption of endomembranes . These structures were very dynamic and continued forming for many minutes after onset of the treatment ( Fig 4C ) . In agreement with a role of ESCRT-III in repair , discreet foci of the ESCRT-I component Tsg101 were also observed in the vicinity of the plasma membrane with a similar timing but much reduced size and frequency ( Fig 4C ) , supporting a role upstream of the recruitment of the ESCRT-III effectors . In contrast , treatment with digitonin did not lead to the recruitment of GFP-Atg8 to the plasma membrane , but it remained at a roughly constant level in the autophagosomal compartment over time ( Fig 4A and 4C , S4 Movie ) . These results support a role for ESCRT but not autophagy in plasma membrane repair of this type of wound . On the other hand , LLOMe induced the formation of both ESCRT- ( GFP-Tsg101 , GFP-Vps32 and Vps4-GFP ) and autophagy- ( GFP-Atg8 ) positive structures at the periphery of lysosomes labelled with fluorescent dextran ( Fig 4B and 4D , S5 Movie ) . The structures were diverse in morphology and dynamics . GFP-Tsg101 , GFP-Vps32 and Vps4-GFP appeared almost immediately as discrete foci surrounding lysosomes , and again , GFP-Tsg101 structures were significantly reduced in size compared to GFP-Vps32 and Vps4-GFP , suggesting it functions in the initiation of the pathway . In contrast , GFP-Atg8 formed a more continuous ring that became apparent only several minutes later ( Fig 4D ) . To further analyse the temporal dynamics of both ESCRT-III and autophagy machineries on disrupted lysosomes , D . discoideum co-expressing RFP-Vps32 and GFP-Atg8 were treated with LLOMe ( S3A Fig and S6 Movie ) . RFP-Vps32 foci forming circular structures were visible before the appearance of GFP-Atg8 . This spatial appearance and partial temporal segregation suggest an independent involvement of ESCRT-III and autophagy during lysosome damage . To confirm and extend the involvement of ESCRT-III in membrane repair in D . discoideum , cells expressing GFP-Vps32 or Vps4-GFP were monitored while exposed to other sterile damage . The lysosomotrophic agent glycyl-L-phenylalanine 2-naphthylamide ( GPN ) induced similar structures as LLOMe ( S3B Fig ) . We noticed that , the structures formed by GFP-Vps32 , known to build the polymers that deform membranes [31] were large and intense ( Fig 4 and S3B Fig ) , and especially long-lived on injured lysosomes , where several foci remained in close apposition to dextran-labelled compartments for several minutes ( Fig 4 and S3C and S3D Fig ) . Sometimes Vps4-GFP structures were less obvious but quantifications confirmed their clear presence , and they were also long-lived ( Fig 4 and S3B Fig ) . In contrast , GFP-Tsg101 structures were less frequent , less intense and short-lived ( Fig 4 ) , consistent with its upstream role in recruiting the membrane-remodelling ESCRT-III . To confirm that the ESCRT-III structures formed at the site of membrane repair , cells expressing GFP-Vps32 were treated with digitonin in the presence of fluorescently-labelled Annexin V to reveal exofacially exposed phosphatidyl-serine ( PS ) ( Fig 5A and 5B and S7 Movie ) . The majority of the GFP-Vps32 crescent structures were also labelled with Annexin V ( Fig 5B ) . The Annexin V-positive structures were released to the extracellular medium , suggesting that damaged membranes were extruded instead of internalized . In mammalian cells , ESCRT-III can be recruited to membranes by at least three mechanisms depending on the identity of the membrane and the specific role exerted by ESCRT ( reviewed in [49] ) . In D . discoideum cells lacking Tsg101 , GFP-Vps32 structures were almost completely abolished upon digitonin or LLOMe treatments ( Fig 5C , 5D , 5G and 5H ) , providing a strong evidence that Tsg101 lies upstream of ESCRT-III during membrane repair caused by these types of sterile damage . It has been proposed that the local increase of intracellular Ca2+ upon membrane damage recruits ESCRT-III to the plasma and lysosomal membranes in HeLa cells and myoblasts [26–28] . To test whether the formation of GFP-Vps32 structures also relied on a Ca2+-mediated signaling in D . discoideum , cells were treated with digitonin in the presence of the non-permeant Ca2+ chelator EGTA , or with LLOMe in the presence of EGTA and the cell-permeant BAPTA-AM ( Fig 5E , 5F , 5I and 5J ) . In both cases , GFP-Vps32 structures appeared at the wound site with very similar morphology , size and dynamics . In conclusion , in D . discoideum , ESCRT-III recruitment to membranes damaged by these sterile agents was Tsg101-dependent but appears independent of Ca2+ signalling . To further dissect the functional contributions of the ESCRT-III and autophagy machineries to the repair of wounds inflicted by LLOMe , cells were incubated with a mixture of two fluid-phase markers: the 10 kDa pH-insensitive Alexa Fluor 647 dextran and the 0 . 5 kDa pH sensor 8-Hydroxypyrene-1 , 3 , 6-trisulfonic acid , trisodium salt ( HPTS ) , which is quenched at pH < 6 . 5 ( Fig 6A–6C and S8 Movie ) . Around 5 min after LLOMe addition , the HPTS fluorescence increased drastically and synchronously in the lysosomes of wt cells , indicating proton leakage from the compartments . In the autophagy mutant atg1- , which are defective in MCV/endomembrane repair [23] , the fluorescence dequenching happened faster and was more pronounced , a sign of earlier and more extensive proton leakage . Interestingly , in tsg101- cells , the switch in fluorescence also happened earlier and more intensely , again suggesting as for the atg1- cells a defect in membrane repair in these mutants . To decipher the role of ESCRT during infection , cells lacking Tsg101 or the accessory proteins AlxA and the AlxA interactors Alg2a and Alg2b were infected and examined by EM . In wt cells , alxA- or alg2a-/b- mutants , the membrane of the MCV in close vicinity to the bacilli escaping the compartment was even and smooth ( S4A , S4D–S4F Fig ) . However , in the tsg101- mutant , rough and “bubbling” membrane structures were observed ( S4B and S4C Fig ) , suggesting cumulating membrane damage . In all cases , escaping bacteria were surrounded by the highly electron-dense material already described in Fig 1 . It was shown that in the atg1- mutant , M . marinum escapes earlier from the MCV , accumulates ubiquitin but proliferates more efficiently in a cytosol devoid of a bactericidal xenophagy pathway [23] . We reasoned that , if the ESCRT-III machinery were involved in repair of the MCV , then , in the tsg101- mutant , bacteria might access the cytosol and become ubiquitinated earlier . The percentage of ubiquitinated M . marinum at 8 hpi was significantly higher in the tsg101- ( 75 . 5 ± 4 . 3% ) than in wt cells ( 40 . 3 ± 11 . 6% , Fig 7A and 7B , S5C Fig ) . In agreement with the increased ubiquitination of bacteria , M . marinum also colocalized more with Atg8 in the tsg101- ( Fig 7C and 7D , S5D Fig ) . Although the percentage of ubiquitinated bacteria in tsg101- cells was close to that observed in the atg1- and atg1- tsg101- double mutants ( 84 . 6 ± 3 . 3% and 89 . 3 ± 7 . 5% , respectively ) , the extent of ubiquitin decoration on the bacteria was very different ( Fig 7A and 7B , S5C Fig ) . Whereas in cells lacking Tsg101 ubiquitin formed foci or patches around M . marinum , in cells devoid of autophagy bacteria were more densely coated with ubiquitin ( Fig 7A and S5C Fig ) . This accumulation is probably due to the fact that ubiquitinated bacteria cannot be targeted to autophagic degradation in the atg1- mutant , but autophagy is still functional in the tsg101- mutant . Given that both ESCRT-III and autophagy are involved in the biogenesis of MVBs and autophagosomes , respectively , which rely at least partially on the recognition of ubiquitinated cargoes , we monitored the morphology of endosomes , as well as the levels of ubiquitination , in non-infected ESCRT and autophagy mutants ( S5 Fig ) . In the atg1- and atg1- tsg101- mutants accumulation of high levels of ubiquitinated material was observed , in agreement with the inability of these mutants to degrade it by autophagy . In tsg101- cells , only a minor increase of ubiquitin was observed in endosomal compartments ( S5A and S5B Fig ) , as already reported [50] , which does not explain the more frequent and larger ubiquitin decorations around M . marinum in these cells ( Fig 7A ) . In yeast and mammallian cells devoid of some ESCRT proteins , ubiquitinated cargoes are not properly sorted into MVBs and accumulate on the limiting membrane [51] . Therefore , to confirm that the increase in ubiquitination observed during infection of the tsg101- mutant was due to MCV damage and bacteria access to the host cytosol , and not to failed endocytic cargo sorting , we monitored the colocalization of bacteria with GFP-tagged perilipin ( Plin ) . Plin is a lipid droplet protein that binds the cell wall of M . marinum as soon as the bacteria access the cytosol [52] . Like in atg1- cells [52] , recognition of cytosolic M . marinum by GFP-Plin was higher in tsg101- and atg1- tsg101- compared to wt cells ( S5E and S5F Fig ) , confirming the earlier bacteria escape from the MCV in cells lacking a functional ESCRT machinery . Altogether , these results suggest that both Tsg101 and Atg1 trigger separate membrane repair pathways and restrict M . marinum access to the cytosol during infection . Since we have shown that Tsg101 is not essential for ESCRT-III recruitment to the damaged MCV ( Fig 2G and 2H ) , but has an important role in repairing the MCV and constraining bacteria escape ( Fig 7 and S5 Fig ) , we wondered whether the accessory proteins AlxA and Alg2a/b , also known to recruit ESCRT-III , were involved in the repair of the MCV . In cells lacking Alg2a/b , the percentage of ubiquitinated M . marinum was comparable to that in its respective parental strain ( 43 . 3 ± 15 . 0% and 50 . 2 ± 11 . 4% respectively , S6A , S6B and S6E Fig ) and , similarly , the degree of Atg8 colocalization with the bacteria remained lower in the alg2a-/b- mutant ( 54 . 70 ± 9 . 5% , S6C , S6D and S6F Fig ) . On the contrary , 81 . 8 ± 9 . 9% of bacteria were ubiquinated in cells devoid of AlxA , which correlated with a higher but not significant increase of Atg8 recruitment to the bacteria ( 72 . 7 ± 13 . 0% , S6A–S6F Fig ) . This suggests that AlxA , together with Tsg101 but not Alg2a/b , contributes to the ESCRT-III-mediated repair of the MCV . To study how the ESCRT pathway may impact the outcome of M . marinum infection , the ESCRT mutants were infected with luminescent M . marinum [53] and intracellular bacterial growth monitored [54] ( Fig 8A and 8B , S6G and S6H Fig ) . M . marinum luminescence increased around 5- fold in wt D . discoideum in the course of 72 h , reflecting sustained intracellular growth . In the atg1- mutant , since bacteria escape earlier to a cytosol that is devoid of xenophagic defense , M . marinum grew better ( Fig 8B ) , as already described [23] . M . marinum proliferation in both ESCRT mutants alxA- and alg2a-/b- was similar to that in the wt ( S6G and S6H Fig ) , suggesting no crucial involvement of these proteins in the infection course . Importantly , loss of Tsg101 significantly suppressed M . marinum growth compared to wt cells ( Fig 8A ) . Interestingly , in the double mutant atg1- tsg101- , bacterial luminescence increased substantially , reaching similar levels as in the single atg1- mutant . Therefore , a functional autophagy pathway is necessary to control bacterial burden in the tsg101- mutant indicating that without ESCRT-III-mediated MCV repair the bacteria become more accessible to degradation by xenophagy . Consistent with its decreased ability to access the cytosol , M . marinum ΔRD1 grew very poorly in D . discoideum wt cells , and this attenuated growth was not improved in the atg1- , tsg101- and atg1- tsg101- mutants . ( S7 Fig ) . Taken together with the previous results on ubiquitination and Atg8 recruitment ( Fig 7 and S6 Fig ) , we conclude that Tsg101 and AlxA but not Alg2a/b participate in the ESCRT-III-mediated repair of the MCV damage and thus absence of these proteins enables an earlier escape of M . marinum to the cytosol . In the case of tsg101- , this leads to the early recruitment of the autophagy machinery , which restricts bacterial mass .
While most intracellular bacterial pathogens reside in a vesicular compartment where they exploit the host resources , a few bacteria have adapted to translocate to the host cytosol . The dynamics of escape to the cytosol varies depending on the pathogen . For instance , while Shigella and Listeria trigger an early escape , Salmonella and mycobacteria program a partial and/or delayed escape [10] . This is the case of M . marinum , which disrupts the MCV thanks to a combination of the membranolytic activity of ESAT-6 , a small bacterial peptide secreted by the ESX-1 system [55] , and the action of the mycobacterial cell wall PDIMs [6 , 7] . Perforation of the MCV implies first the leakage of host and bacterial factors contained in its lumen and , eventually , bacteria access to nutrients in the cytosol , which must be sensed and restricted by the host . 3D EM inspection of infected D . discoideum cells revealed a very complex interface between M . marinum and the host cytosol at the site of MCV rupture ( Fig 1 ) , suggesting a dynamic and complex interplay between bacterial and host factors . Here , we show that the two highly conserved ESCRT-III and autophagy pathways contribute to the repair of the MCV membrane , delaying the escape of M . marinum to the cytosol . Like its mammalian homologs [26–28 , 42 , 43] , the D . discoideum ESCRT proteins Tsg101 , Vps32 and Vps4 localized to injuries both at the plasma membrane and endomembranes upon damage by distinct chemical agents such as digitonin and LLOMe ( Fig 4A and 4B ) . Importantly , M . marinum infection also leads to the appearance of Tsg101 , Vps32 and Vps4 foci , patches or rings in the vicinity of the MCV ( Fig 2 ) . These structures were significantly less abundant upon infection with M . marinum ΔRD1 , an attenuated mutant that produces PDIMs ( S1 Fig ) but lacks the ESX-1 secretion system . Although we cannot exclude a direct role of the ESX-1 secretion system or of another secreted product in the recruitment of the ESCRT machinery , this result is consistent with the reduced capacity of M . marinum ΔRD1 to induce damage at the MCV . In agreement with its ability to form packed spiral polymers on membranes , upon both sterile injuries and infection , GFP-Vps32 structures were generally larger and longer-lived than the Vps4-GFP ones . Consistently , large ring-like structures were observed exclusively with GFP-Vps32 ( Fig 2E ) . Time-lapse microscopy revealed that GFP-Vps32 was recruited from the cytosolic pool , likely polymerized at wounds of the MCV , and remained associated with the MCV for several minutes ( Fig 3C ) . The wounds inflicted by membrane disrupting agents such as LLOMe ( less than 5 nm [56] ) may be of comparable size to the ones caused by the mycobacterial membranolytic peptide ESAT-6 ( 4 . 5 nm [8] ) and thus lead similarly to the recruitment of the ESCRT-III repair machinery . However , the sustained insults and cumulative lesions inflicted by M . marinum [57] likely results from the continued damage caused by ESAT-6 and PDIMs [6 , 48] . Together , they probably generate heterogeneous and expanding wounds that are harder to resolve . This may explain why the recruitment of GFP-Vps32 to sterile damage depends strictly on Tsg101 ( Fig 5C and 5D ) , whereas during M . marinum infection this dependency is partial ( Fig 2G and 2H ) , because other ESCRT recruiting pathways likely act simultaneously . In addition , we propose that cumulative damage by M . marinum would eventually overwhelm membrane repair by ESCRT-III and result in recruitment of autophagy , as previously suggested for endosomal damage caused by LLOMe [28 , 29] . In the case of sterile damage to lysosomes , autophagy may end up degrading the severely injured compartments by lysophagy [28] . Regarding damage to the MCV , we propose that autophagy plays two distinct roles . First , in membrane repair , where autophagic membranes would somehow patch/seal the damaged MCV and contain the bacteria in the compartment , as proposed also during Salmonella infection [25] . The second one implies the total engulfment of the MCV for the degradation of its content , similarly to the already described role of autophagy in canonical lysophagy . These two paths would generate compartments/environments that are either restrictive or even bactericidal for the pathogen . Upon digitonin treatment , GFP-Vps32 colocalized with Annexin V-labelled regions of the plasma membrane that were subsequently shed in the medium ( Fig 5B ) . This suggests that plasma membrane repair in D . discoideum might be achieved by ESCRT-III-dependent budding and scission of the wound , as in mammalian cells [26 , 27] . A similar repair mechanism , in this case by budding the injury towards the lumen , has also been described for the nuclear envelope [43] . We propose that the same process may operate at the MCV , which would partially explain the presence of abundant membranous material in the lumen of the MCV and the putative invagination of the MCV membrane remnants , as observed by EM and live microscopy ( Fig 1 and S2A–S2C Fig ) . M . marinum that accesses the host cytosol becomes ubiquitinated [23] and coated by Plin [52] . We used ubiquitination and recruitment of GFP-Plin as a proxy to monitor bacterial escape from the MCV in cells lacking Tsg101 . Similar to the high ubiquitination previously shown to occur in amoebae deficient for autophagy [23] , large ubiquitin patches were observed at the sites of MCV rupture in tsg101- cells ( Fig 7A and 7B ) . Consistently , the percentage of bacteria coated by Plin was higher in this ESCRT mutant ( S5E and S5F Fig ) . These results are consistent with the large ubiquitin patches observed on M . smegmatis in macrophages [30] and with the increased cytosolic bacterial spread observed during L . monocytogenes infection in S2 cells [41] when ESCRT genes are downregulated . Several reports have recently described the participation of ESCRT proteins during micro- and macro-autophagy ( reviewed in [58] ) . However , during endolysosomal membrane repair , ESCRT-III has been shown to operate independently of lysophagy [28 , 29] . In agreement , upon treatment with LLOMe , we also observe GFP-Vps32 and Vps4-GFP recruitment preceding GFP-Atg8 . In the case of MCV rupture , we suggest that ESCRT-III and autophagy work in parallel to repair the damaged membrane . This function of autophagy somehow supplying membrane to seal/patch the damaged MCV explains the early escape of M . marinum to the cytosol in the D . discoideum atg1- mutant and has also been described during Salmonella infection [25] . In addition , it has been shown that ubiquitin serves as an “eat-me” signal that targets cytosolic bacteria to autophagic degradation [2] . This second and distinct function probably implies the total engulfment of the ( damaged ) MCV , similarly to the role of autophagy in canonical lysophagy [28 , 29] . Consistent with this , the accumulation of ubiquitin around M . marinum in tsg101- cells correlated with a proportional increase of Atg8 decoration on the bacteria ( Fig 7C and 7D ) , and with a decreased bacterial load ( Fig 8A ) , contrary to what has been described in RAW macrophages infected with the non-pathogenic , vacuolar M . smegmatis , in which depletion of Tsg101 led to bacteria hyperproliferation [30] . Importantly , elimination of the autophagic function in both wt or tsg101- mutant cells led to a significant increase of intracellular mycobacterial growth , thus suggesting that bacterial restriction observed in the single tsg101- mutant is due to autophagic restriction ( Fig 8B ) . However , it is important to note that the 20-fold increase of bacterial mass observed in the absence of autophagy is notably reduced compared to the 512-fold that is obtained over the same period of time during exponential growth in 7H9 medium . The identity of the additional , autophagy-independent , growth-restriction pathways , in the MCV or in the cytosol , are not fully elucidated , but will likely include access to nutrients and other bacteria-limiting mechanisms such as ROS production and anti-bacterial activities [1] . These anti-bacterial machineries must also restrict the growth of M . marinum ΔRD1 , either in the MCV or in the cytosol for the small percentage ( roughly 5% ) that may escape ( S7 Fig ) . Similarly to the substrates of ubiquitination , the cues and signals that recruit ESCRT-III to damage in D . discoideum are still to be identified . The appearance of ESCRT-III components before ubiquitinated material can be detected at the site of lysosome disruptions [28] speaks for a ubiquitin-independent mechanism , although it cannot be excluded that ubiquitin might participate in a subsequent reinforcement loop to recruit ESCRT-III . In mammalian cells , several reports have suggested that influx of extracellular Ca2+ through the plasma membrane or efflux through endolysosomal membranes are essential for the positioning of ESCRT-III to the site of the injury [26–28] . The local increase of intracellular Ca2+ at the wound site might be recognized directly by ALIX [26] , a multifunctional protein involved in cargo protein sorting into intralumenal vesicles ( reviewed in [59] ) , thereby bypassing the need for ESCRT-0 , -I and -II , and recruiting ESCRT-III by direct protein-protein interactions . Alternatively , Ca2+ has been proposed to be sensed by ALG2 , an ALIX-interacting protein with a penta EF-hand domain , which could promote the accumulation of ALIX , ESCRT-III and the Vps4 complex at the damage site [27 , 28] . In the presence of EGTA and BAPTA-AM to chelate Ca2+ , GFP-Vps32 relocation to the plasma membrane or lysosomal injuries was not impaired ( Fig 5E and 5F ) . Consistent with this result , Ca2+ seemed also to be dispensable during MCV repair , since knockout of either alxA or alg2a/b did not impact intracellular M . marinum growth ( S5G and S5H Fig ) . Altogether , our results suggest that the MCV damage caused by the M . marinum ESX-1 secretion system is repaired very robustly and in a multilayered response by both the ESCRT-III and the autophagy pathways of D . discoideum in a Tsg101-dependent and apparently Ca2+-independent manner . The ability of the ESCRT-III to repair membranes injured by various biological and chemical insults strongly suggests that this is a generic mechanism that operates upon infection by other intracellular pathogens . This is in agreement with a recent report showing ESCRT-III proteins at vacuoles containing C . burnetii [29] and will need to be addressed in the case of other membrane-damaging bacteria such as Salmonella , Shigella and Listeria . In addition , the high conservation of the ESCRT machinery identifies this pathway as a novel potential therapeutic target to fight against bacterial infection in humans .
D . discoideum strains and plasmids are summarized in S1 Table . D . discoideum Ax2 ( Ka ) was axenically cultured at 22°C in Hl5c medium ( Formedium ) supplemented with 100 U mL−1 of penicillin and 100 μg mL−1 of streptomycin ( Invitrogen ) . D . discoideum JH10 was cultured similarly as Ax2 ( Ka ) , with the addition of 100 g mL-1 of Thymidine ( Sigma ) . Cells were transformed by electroporation and selected with the relevant antibiotic . Hygromycin , G418 and blasticidin were used at a concentration of 50 , 5 and 5 μg mL−1 , respectively . D . discoideum Ax2 ( Ka ) tsg101- and atg1- tsg101- were obtained by transformation with the pSP72 KO vector kindly provided by Dr . L . Aubry [60] . JH10 alxA- and JH10 alg2a-/b- mutants were kindly provided by Dr . L . Aubrey [61 , 62] . Ax2 ( Ka ) cells expressing GFP-Atg8 and AmtA-mCherry were described in [23] and [52] , respectively . Ax2 ( Ka ) cells expressing GFP-Vps32 , Vps4-GFP , GFP-Tsg101 and GFP-Atg8 and RFP-Vps32 were generated by transformation with the vectors described in S1 Table . Cells expressing GFP-Plin were obtained upon transformation with the pDNeoGFP-Plin construct described in [63] . M . marinum strains and plasmids are summarized in S1 Table . M . marinum ( M strain ) wt and ΔRD1 were kindly provided by Dr . L . Ramakhrisnan [23] . Mycobacteria were cultured in 7H9 ( Difco ) supplemented with glycerol 0 . 2% ( v/v ) ( Biosciences ) , Tween-20 0 . 05% ( v/v ) ( Sigma ) and OADC 10% ( v/v ) ( Middlebrock ) . mCherry-expressing bacteria were obtained by transformation with pCherry10 , which was kindly obtained from Dr . L . Ramakrishnan [64] , and cultured in the presence of 50 μg/mL-1 hygromycin ( Labforce ) . Luminiscent bacteria harbored the pMV306::lux plasmid [53] and were cultured in presence of 50 μg mL-1 kanamycin ( AppliChem ) . Infections were performed as previously described [65] . In brief , M . marinum bacteria were washed in Hl5c and centrifuged onto adherent D . discoideum cells . After additional 20–30 min of incubation , extracellular bacteria were washed off and the infected cells resuspended in Hl5c containing 5 U mL-1 of penicillin and 5 μg mL-1 of streptomycin ( Invitrogen ) . Infections were performed at a multiplicity of infection ( MOI ) of 10 for M . marinum wt in D . discoideum wt . In order to correct for slight differences in phagocytic uptake , infections with atg1- and atg1- tsg101- D . discoideum mutants were performed at MOI 5 , and with tsg101- at MOI 20 . For experiments with M . marinum ΔRD1 the MOI used was always twice the MOI of M . marinum wt . For live microscopy , mCherry expressing or unlabeled bacteria were used . To monitor bacteria intracellular growth in D . discoideum , luciferase-expressing M . marinum [23 , 54] were used . Growth of luminescent bacteria was measured as described previously [23 , 54] . Briefly , dilutions of 0 . 5–2 . 0 × 105 D . discoideum cells infected with M . marinum pMV306::lux were plated on a non-treated , white F96 MicroWell plate ( Nunc ) and covered with a gas permeable moisture barrier seal ( Bioconcept ) . Luminescence was measured for 72 h at 1 h intervals with a Synergy Mx Monochromator-Based Multi-Mode Microplate Reader ( Biotek ) . The temperature was kept constant at 25°C . Infected or uninfected D . discoideum were plated in 35 mm Glass Bottom Dishes ( MatTek ) or in 4-wells μ-slides ( Ibidi ) . To induce damage in D . discoideum membranes , cells were incubated with 2 . 5–5 μM of digitonin ( Sigma ) , 5–6 . 25 mM of LLOMe ( Bachem ) , or 200 μM of GPN . These treatments were started immediately before live imaging , except in the case of LLOMe , for which a 10-fold concentrated solution was added once imaging had just started . To visualize the lumen of endocytic compartments , 0 . 5 mg mL-1 of 70 KDa TRITC-Dextran or 10–15 μg mL-1 of 10 kDa Alexa Fluor 647 Dextran ( Molecular Probes ) were added at least 3 h prior to visualization of the sample . To detect neutralization of endocytic vesicles , 0 . 2 mM of 524 Da HPTS ( Molecular Probes ) was added at least 3 h prior to the visualization of the sample . To detect plasma membrane damage , 5 μM of Annexin V Alexa Fluor 594 conjugate ( Molecular Probles ) was added to cells in the presence of 2 . 5 mM Ca2+ . To chelate Ca2+ , 5 mM of EGTA ( Fluka ) or 5 mM of EGTA and 250 μM of BAPTA-AM ( Sigma ) were added at least 20 min before imaging . Bacteria not expressing a fluorescent reporter were stained with 12 . 5 μM of Vybrant DyeCycle Ruby stain ( Molecular Probes ) directly on the μ-dish prior to microscopic inspection . Live microscopy was performed with a Spinning Disc Confocal Microscope [Intelligent Imaging Innovations Marianas SDC mounted on an inverted microscope ( Leica DMIRE2 ) ] with a glycerin 63x or an oil 100x objective . Generally , z-stacks from 3 to 10 slices of 1 μm or 1 . 5 μm were acquired . For time-lapse experiments , images were acquired from every 15 s to several min . Image analysis was performed using ImageJ . Samples were fixed in ultracold methanol as already described [66] . Briefly , D . discoideum cells on coverslips were quickly fixed by immersion in -85°C methanol using a Freezing Dewar ( FH Cryotec , Instrumentenbedarf Kryoelektronenmikroskopie ) . Subsequent immunofluorescence staining was performed as described [66] . Rabbit anti-Atg8 was previously described [23] , anti-p80 [67] was purchased from the Geneva Antibody Facility ( http://www . unige . ch/antibodies ) , the anti-Ub ( FK2 ) monoclonal antibody was from Enzo Life Sciences [23] . Nuclei were stained with DAPI ( Molecular Probes ) . Cells were embedded using ProlongGold antifade ( Molecular Probes ) . Images were acquired with a LSM700 or LSM780 microscope ( Zeiss ) using an oil 63x objective . Image analysis was performed using ImageJ . Sample preparation for TEM was performed as described in [68] . Briefly , D . discoideum cells were fixed in a 6 cm dish in 2% ( w/v ) glutaraldehyde in Hl5c for 1 h and stained with 2% ( w/v ) OsO4 in imidazole buffer 0 . 1 M for 30 min . Cells were detached with a cell scraper and washed 3 times with PBS . Subsequent sample preparation was performed at the Pôle Facultaire de Microscopie Ultrastructurale ( University of Geneva ) . Samples were incubated in 2% ( v/v ) of Milloning buffer and rinsed with distilled water . Then , they were incubated in 0 . 25% ( w/v ) uranyl acetate overnight and rinsed with distilled water . Samples were dehydrated using increasing concentrations of ethanol , then in propylene oxide for 10 min and finally embedded in 50% Epon-propylene oxide for 1h , followed by incubation overnight in pure Epon . Samples were embedded in 2% agar for subsequent sectioning in an ultramicrotome and placed on TEM grids . Finally , sections were visualized in a Tecnai 20 electron microscope ( FEI Company , Eindhoven , The Netherlands ) . Initial sample preparation was performed similarly as for TEM and sent to the Pôle Facultaire de Microscopie Ultrastructurale ( University of Geneva ) . Subsequent contrast enhancement , dehydration and resin embedding was performed as described in [69] . Samples were visualized in a Helios DualBeam NanoLab 660 SEM ( Fei Company , Eindhoven , The Netherlands ) . 3 D reconstitutions were performed using the LimeSeg plugin from ImageJ . For the analysis of the lipid composition , M . marinum strains were grown in suspension in 25 ml 7H9 supplemented with ADC and 0 . 05% Tyloxapol . At an OD600 of 1 the bacteria were harvested , washed in PBS and resuspended in 1 ml of water . The non-polar lipid fraction was extracted using Bligh and Dyer [70] and separated on a TLC plate using petroleum ether/ethyl acetate ( 98:2 ) as a solvent system . The M . marinum tesA mutant inhibited in the synthesis of both , PDIMs and PGLs [71] , served as a negative control . Lipids were visualised after charring in a solution containing MnCl2 , methanol and sulfuric acid and heating for five minutes at 150 °C . Purified PDIMs of M . tuberculosis ( Biodefense and Emerging Infections Research ( BEI ) resources ( NIAID , NIH ) and glyceryl trioleate ( Fluka ) were used to identify bands on the TLC . Microscopy images were analysed using ImageJ . Experiments in Figs 2B , 2C , 2D , 2H , 7B and 7D; S5F , S6B and S6D Figs were quantified manually . Experiments in Fig 6C were quantified automatically using ImageJ macros . Briefly , endosomes were identified using the Far-Red Dextran signal and fluorescence intensities of the HTPS and Far-Red Dextran for each endosome were measured . The ratio of the mean intensity of each channel per time-point was calculated and normalized to the baseline ( 5 first time-points prior to LLOMe treatment ) and then to the wt for all the time-points . Experiments in Figs 4 and 5 were quantified using MetaXpress software . All graphs were plotted and statistical tests were performed using Prism . In all plots , the mean and standard deviation are shown , unless explicitly mentioned . Two-tailed t-test , ANOVA or Two-way ANOVA was used . Post hoc Fisher’s LSD test were performed when necessary ( n . s: non-significant , *: p-value < 0 . 05 , **: p-value < 0 . 01 , ***: p-value < 0 . 001 , ****: p-value < 0 . 0001 ) . | Upon uptake by a host cell , intracellular pathogens reside in a membranous compartment called phagosome . Within the phagosome , microbes are protected from the extracellular and cytosolic immune defences , whilst access to nutrients is limited . Some microbes gain access to the host cytosol by damaging the membrane of the phagosome , a step preceding egress and dissemination . Autophagy , a major catabolic pathway in eukaryotes , has been previously proposed to contribute to autonomous cell defence and to repair the membrane damage induced by intracellular pathogens . Here , we provide evidence that , in Dictyostelium discoideum , autophagy does not work alone in the containment of vacuolar mycobacteria , but it operates together with the Endosomal Sorting Complex Required for Transport ( ESCRT ) , a protein machinery recently shown to repair endolysosomal damage . We demonstrate that the membrane perforations induced by the ESX-1 secretion system of Mycobacterium marinum are targeted by both ESCRT and autophagy , which seal the damaged vacuole . We propose that ESCRT might mend small membrane pores , whilst autophagy patches larger cumulative wounds . Interestingly , and contrary to what has been described in mammalian cells for ESCRT-dependent endolysosomal repair , in D . discoideum , repair of sterile membrane damage appears not to require Ca2+ . The evolutionary conservation of the function of ESCRT in membrane repair suggests that this machinery plays an ancestral and widespread role to contain a broad range of intracellular pathogens . | [
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] | 2018 | The ESCRT and autophagy machineries cooperate to repair ESX-1-dependent damage at the Mycobacterium-containing vacuole but have opposite impact on containing the infection |
Hepatitis C virus ( HCV ) induces autophagy to promote its replication , including its RNA replication , which can take place on double-membrane vesicles known as autophagosomes . However , how HCV induces the biogenesis of autophagosomes and how HCV RNA replication complex may be assembled on autophagosomes were largely unknown . During autophagy , crescent membrane structures known as phagophores first appear in the cytoplasm , which then progress to become autophagosomes . By conducting electron microscopy and in vitro membrane fusion assay , we found that phagophores induced by HCV underwent homotypic fusion to generate autophagosomes in a process dependent on the SNARE protein syntaxin 7 ( STX7 ) . Further analyses by live-cell imaging and fluorescence microscopy indicated that HCV-induced phagophores originated from the endoplasmic reticulum ( ER ) . Interestingly , comparing with autophagy induced by nutrient starvation , the progression of phagophores to autophagosomes induced by HCV took significantly longer time , indicating fundamental differences in the biogenesis of autophagosomes induced by these two different stimuli . As the knockdown of STX7 to inhibit the formation of autophagosomes did not affect HCV RNA replication , and purified phagophores could mediate HCV RNA replication , the assembly of the HCV RNA replication complex on autophagosomes apparently took place during the formative stage of phagophores . These findings provided important information for understanding how HCV controlled and modified this important cellular pathway for its own replication .
Autophagy is a catabolic process that is important for maintaining cellular homeostasis . It begins with the formation of membrane crescents termed phagophores or isolation membranes in the cytosol . The membranes of phagophores will subsequently expand to sequester part of the cytoplasm , resulting in the formation of enclosed double-membrane vesicles known as autophagosomes . Autophagosomes mature by fusing with lysosomes to form autolysosomes , in which the cargos of autophagosomes are digested by lysosomal enzymes [1] . The phagophore assembly site ( PAS ) , also known as the pre-autophagosomal structure , may be located on the endoplasmic reticulum ( ER ) or other intracellular membranes [2] . In the canonical autophagic pathway , the class III phosphatidylinositol-3-kinase ( PI3KC3 ) mediates the production of phosphatidylinositol-3-phosphate ( PI3P ) , which then recruits PI3P-binding proteins such as DFCP1 or WIPI to the PAS to form omegasomes [3] . This is followed by the recruitment of autophagy-related proteins ATG5 and ATG12 , which are covalently linked , and ATG16 , leading to the formation of phagophores . LC3 is the microtubule-associated protein light chain 3 . Its non-lipidated form ( i . e . , LC3-I ) is located in the cytosol . However , during autophagy , LC3 becomes lipidated ( i . e . , LC3-II ) and eventually replaces the ATG5-ATG12-ATG16 complex on growing phagophores . LC3-II remains associated with autophagosomes after they are formed [4 , 5] . ATG5 , ATG12 or ATG16 is thus often used as the marker for phagophores and LC3-II is often used as the marker for autophagosomes [6] . Autophagy occurs in cells at a basal level and can be induced by stresses such as nutrient starvation . It can also be induced by microbial infections for the removal of intracellular microbial pathogens . However , many microbial pathogens including viruses have also developed mechanisms to subvert this intracellular anti-microbial pathway and even use this pathway to enhance their own replications . In recent years , many reports have been published to show that hepatitis C virus ( HCV ) could induce autophagy to support its own replication [7–11] . HCV is a hepatotropic virus that can cause severe liver diseases including cirrhosis and hepatocellular carcinoma . It has a 9 . 6-Kb positive-stranded RNA genome that encodes a polyprotein with a length of slightly more than 3 , 000 amino acids . After its synthesis , the HCV polyprotein is proteolytically cleaved into structural and nonstructural proteins by cellular and viral proteases [12] . The nonstructural proteins NS3 , NS4A , NS4B , NS5A and NS5B are required for viral RNA replication [13] , which can take place on autophagosomal membranes [14] . Although it has been very well documented that HCV could induce autophagy to enhance its own replication [15] , the biogenesis pathway of autophagosomes induced by HCV remains unclear . Phagophores were thought to extend their membranes to form the enclosed autophagosomes , but more recent studies indicated that they could also undergo homotypic fusion to generate autophagosomes in a process dependent on soluble N-ethylmaleimide-sensitive factor activating protein receptor ( SNARE ) proteins [16] , which play important roles in mediating the fusion of vesicular membranes in cells [17] . Whether and how phagophores are involved in the biogenesis of autophagosomes induced by HCV are largely unknown . In this report , we conducted electron microscopy to examine Huh7 hepatoma cells that harbored an HCV subgenomic RNA replicon and identified crescent membrane structures that resembled phagophores , which appeared to be able to undergo homotypic fusion to form autophagosomes . By conducting an in vitro membrane fusion assay , we demonstrated that ATG5-positive phagophores induced by HCV could indeed undergo homotypic fusion to form autophagosomes . We also discovered that , comparing with autophagy induced by nutrient starvation , the progression of phagophores to autophagosomes induced by HCV was prolonged , and that the HCV RNA replication complex was assembled on phagophores prior to the formation of autophagosomes .
To understand how HCV induces the biogenesis of autophagosomes , we performed electron microscopy on HCV replicon cells , which contained the self-replicating HCV subgenomic RNA that expressed the HCV nonstructural proteins NS3-NS5B [18] . As shown in Fig 1A , in agreement with our previous reports [14] , autophagosomes approximately 400–500 nm in diameters could be detected in replicon cells . Two crescent membranous structures that resembled phagophores were also detected . Interestingly , one of the autophagosomes observed appeared to be assembled by three phagophore-like structures . This result raised the possibility that autophagosomes induced by HCV might be generated via the homotypic fusion of phagophores . To test this possibility , we expressed the mEmerald-ATG5 fusion protein and the mCherry-ATG5 fusion protein separately in Huh7 cells by transient transfection to label phagophores . Cells were then lysed with a hypotonic buffer and cell lysates containing either the mEmerald-ATG5-labeled phagophores or the mCherry-ATG5-labeled phagophores were then mixed for the in vitro membrane fusion assay . If phagophores could undergo homotypic fusion , then mEmerald-ATG5-labeled and mCherry-ATG5 labeled phagophores would be expected to merge to generate yellow puncta when they were visualized under a fluorescence microscope ( Fig 1B ) . We first performed a positive control experiment using cells that were nutrient-starved , which would induce autophagy . As shown in Fig 1C and 1D , only a few mEmerald-ATG5 and mCherry-ATG5 puncta ( i . e . , phagophores ) could be detected in control Huh7 cell lysates . However , their levels were significantly increased if cells were nutrient-starved . In the presence of ATP , approximately 30% of phagophores from nutrient-starved cells could undergo homotypic fusion , as evidenced by the merging of mEmerald-ATG5 and mCherry-ATG5 puncta ( Fig 1C and 1E ) , in agreement with the previous report [16] . This homotypic fusion , which is ATP-dependent , was not observed in the absence of ATP , which served as the negative control . Few phagophores from control Huh7 cells could undergo homotypic fusion even in the presence of ATP ( Fig 1E ) , presumably due to the low concentration of phagophores . We then examined the HCV replicon cells that were also transfected with the expression plasmids of mEmerald-ATG5 and mCherry-ATG5 . As shown in Fig 1C and 1D , HCV replicon cells also contained an increased level of phagophores . The same as nutrient-starved cells , approximately 30% of phagophores isolated from HCV replicon cells could undergo homotypic fusion in the presence of ATP but not in the absence of it ( Fig 1C and 1E ) . Similar results were observed with Huh7 . 5 cells infected by HCV ( Fig 1C and 1E ) . The SNARE protein STX7 plays important roles in mediating the fusion of intracellular membrane vesicles . Our recent studies indicated that STX7 was associated with autophagosomes [19] . To determine whether STX7 also mediates the homotypic fusion of phagophores , we first examined whether STX7 was associated with phagophores . Huh7 cells were transfected with the mEmerald-ATG5-expressing plasmid and stained with the anti-STX7 antibody . As shown in Fig 2A , few mEmerald-ATG5 puncta could be detected in Huh7 cells . However , in agreement with the results shown in Fig 1C , the number of mEmerald-ATG5 puncta in Huh7 cells was increased by nutrient starvation , indicative of the induction of autophagy . Most of the mEmerald-ATG5 puncta were also positive for STX7 . The same results were also observed in HCV-infected cells . These results indicated that STX7 was associated with phagophores induced by nutrient starvation and HCV . To determine whether STX7 could mediate the homotypic fusion of the phagophores induced by HCV , we expressed mEmerald-ATG5 and mCherry-ATG5 separately in HCV replicon cells followed by the suppression of STX7 using the siRNA ( siSTX7 ) . The knockdown of STX7 had no effect on the expression of ATG5 ( Fig 2B ) . We then repeated the in vitro membrane fusion assay . As shown in Fig 2C , although the knockdown of STX7 had no apparent effect on the level of ATG5 puncta in HCV replicon cells , it reduced the percentage of homotypically fused phagophores from approximately 30% to slightly less than 10% ( Fig 2D ) . These results indicated that , although STX7 was not required for the production of phagophores , it was required for their efficient homotypic fusion . To determine whether the homotypic fusion of phagophores is required for the formation of autophagosomes induced by HCV , we transfected HCV replicon cells that stably expressed the GFP-LC3 fusion protein with the mCherry-ATG5-expressing plasmid and then knocked down the expression of STX7 using the siRNA . If the homotypic fusion of phagophores is required for the formation of autophagosomes , then its inhibition should reduce the level of autophagosomes induced by HCV . As shown in Fig 3A , the suppression of STX7 expression did not affect the level of mCherry-ATG5 puncta ( i . e . , phagophores ) , but it significantly reduced the level of GFP-LC3 puncta ( i . e . , autophagosomes ) . This result demonstrated that STX7 was not essential for the formation of phagophores but it was required for the formation of autophagosomes induced by HCV . The knockdown of STX7 also suppressed the formation of autophagosomes in nutrient-starved cells ( Fig 3B ) . To further confirm the fluorescence imaging results shown in Fig 3A and 3B , we also performed the western-blot analysis . As shown in Fig 3C , the suppression of STX7 expression with siSTX7 had only a marginal effect , if any , on the levels of ATG5 in control Huh7 cells , nutrient-starved Huh7 cells , HCV replicon cells and HCV-infected cells . It also had no apparent effect on LC3 in control Huh7 cells , which had a low level of lipidated LC3 ( i . e . , LC3-II ) , a marker of autophagosomes . However , STX7 knockdown suppressed the induction of LC3-II in nutrient-starved Huh7 cells , HCV replicon cells , and HCV-infected cells . These results confirmed that STX7 was important for the formation of autophagosomes induced by nutrient starvation or HCV . The analysis of p62 , a protein degraded by autophagy , revealed that the suppression of STX7 marginally increased the p62 level in control Huh7 cells , likely due to the inhibition of the basal autophagy , and prevented the loss of p62 induced by nutrient starvation . These results indicated the importance of STX7 in the completion of the autophagic flux and the autophagic protein degradation . Comparing with control Huh7 cells , HCV replicon cells and Huh7 cells infected by HCV for one day had an increased level of p62 . This result was consistent with our previous finding that HCV induced the expression of RUBICON in replicon cells and in the early time point of infection to suppress the fusion between autophagosomes and lysosomes [18] . The knockdown of STX7 did not further increase the level of p62 in replicon cells and HCV-infected cells , presumably because the autophagic flux and the autophagic protein degradation had already been suppressed by HCV in replicon cells and in infected cells at this time point . Note that HCV NS5A of replicon cells migrated faster in the gel than that of HCV-infected cells . This was due to the adaptive mutation in replicon NS5A , which prevented its hyperphosphorylation [20 , 21] , and likely also due to the fact that HCV replicon RNA was derived from HCV genotype 1b whereas HCV JFH1 , which we used for the infection studies , was a genotype 2a virus . The fluorescence microscopy results ( Fig 3A and 3B ) and the western-blot results ( Fig 3C ) together demonstrated that STX7 was essential for the formation of autophagosomes induced by HCV as well as by nutrient starvation . VAMP7 is another SNARE protein that had previously been shown to be important for the homotypic fusion of phagophores [16] . We therefore also tested the possible effect of VAMP7 knockdown on the formation of phagophores and autophagosomes in nutrient-starved cells and HCV replicon cells . Our results indicated that VAMP7 knockdown had no effect on phagophores in nutrient-starved cells and HCV replicon cells , but it suppressed the formation of autophagosomes in both cases ( S1A Fig ) . We also conducted the western-blot analysis . As shown in S1B Fig , VAMP7 knockdown had no effect on STX7 and ATG5 , but it reduced LC3-II level in nutrient-starved cells and replicon cells . It also restored the p62 level in nutrient-starved cells . These results were consistent with STX7 knockdown and further confirmed that the homotypic fusion of phagophores was important for the formation of autophagosomes induced by nutrient starvation and HCV . Phagophores may be derived from the ER or other cellular membranes [22] . To investigate whether phagophores induced by HCV might be derived from the ER , we transfected HCV replicon cells that stably expressed GFP-LC3 with the mCherry-ATG5-expressing plasmid and stained the ER using ER Tracker Blue . As shown in Fig 4A , mCherry-ATG5 colocalized with the ER in HCV replicon cells , providing the evidence that phagophores induced by HCV might be originated from ER membranes . Most of the mCherry-ATG5 puncta were also positive for GFP-LC3 , indicating the progression of phagophores into autophagosomes . The same results were obtained when endogenous ATG5 and LC3 were analyzed by immunofluorescence staining . As shown in S2 Fig , endogenous ATG5 and LC3 colocalized with each other and with the ER in replicon cells and HCV-infected cells . To further confirm that phagophores were indeed associated with the ER , we also analyzed the subcellular localization of endogenous ATG16 , another marker of phagophore . Huh7 cells or HCV replicon cells were transfected with the mCherry-ATG5-expressing plasmid and then stained with ER Tracker blue and the anti-ATG16 antibody . As shown in S3 Fig , few ATG16 and mCherry-ATG5 puncta could be detected in control Huh7 cells . However , their numbers were significantly increased in replicon cells , and all of the ATG16 puncta colocalized with mCherry-ATG5 puncta on the ER . The analysis ATG16 in HCV-infected cells generated the same result . These results provided another line of evidence that HCV could induce phagophores , which likely originated from the ER . In agreement with the results shown in Fig 3 , the suppression of STX7 expression with siSTX7 had no effect on the association of mCherry-ATG5 puncta with the ER , but it reduced the GFP-LC3 puncta to an almost undetectable level ( Fig 3A ) . This result further demonstrated that the formation of phagophores on the ER was independent of STX7 in HCV replicon cells . Similarly , the suppression of STX7 expression had no effect on the level of ATG5 puncta , nor their association with the ER , in Huh7 cells that were nutrient-starved or infected by HCV ( S4 Fig ) . To confirm that mCherry-ATG5-labeled phagophores could indeed progress to become autophagosomes , we conducted the live-cell imaging . As shown in Fig 4B , mCherry-ATG5 puncta ( red ) first appeared on the ER , which was stained by the ER Tracker Blue . The mCherry-ATG5 puncta then progressed to become GFP-LC3-positive ( yellow ) followed by the separation of GFP-LC3 puncta ( green ) from the mCherry-ATG5 puncta and the ER . Surprisingly , the time period starting from the association of GFP-LC3 with mCherry-ATG5 puncta to their separation was roughly about 30 minutes ( Fig 4B and 4C , and S1 Video ) , significantly longer than what was previously reported for the progression of phagophores to autophagosomes in nutrient-starved cells , which was less than 10 minutes [23] . Indeed , as a control , we also conducted the live-cell imaging on nutrient-starved Huh7 cells . As shown in Fig 4B , lower panels , and S2 Video , the time needed for the separation of GFP-LC3 from mCherry-ATG5 puncta was less than 10 minutes ( Fig 4C ) , in agreement with the previous report [23] . These results indicated that the progression of phagophores to autophagosomes was prolonged in HCV replicon cells . Our previous studies indicated that autophagosomes could serve as the sites for HCV RNA replication [14 , 24] . For that reason , we also determined whether phagophores could support HCV RNA replication . To test this possibility , we suppressed the expression of STX7 using a scrambled siRNA or siSTX7 followed by HCV infection for one day . Cells were then harvested and analyzed for HCV RNA replication by quantitative RT-PCR ( qRT-PCR ) . As shown in Fig 5A , the suppression of STX7 expression , which prevented the homotypic fusion of phagophores and the generation of autophagosomes , did not decrease , but rather slightly increased the HCV RNA level . This result was consistent with the western-blot result shown in Fig 3C , which indicated that the STX7 knockdown did not decrease , but instead appeared to marginally increase the HCV NS5A protein level . To further determine whether HCV could indeed replicate on phagophores , we developed a procedure to purify phagophores from HCV replicon cells . This procedure included first , the isolation of membranes from HCV replicon cells by membrane flotation using a discontinuous sucrose gradient , and second , the affinity purification of phagophores using the anti-ATG5 antibody . As shown in Fig 5B , the membrane flotation using the sucrose gradient led to the separation of membrane-associated LC3-II from its cytosolic form LC3-I . ATG5 , STX7 and the HCV NS5A protein were also enriched in the membrane fractions . Membranes enriched in fractions 2 and 3 were then incubated with the anti-ATG5 antibody followed by incubation with protein G-conjugated magnetic beads for the affinity purification of ATG5-positive membranes ( i . e . , phagophores ) . As shown in Fig 5C , the purified phagophores contained ATG5 and STX7 . This result was consistent with the result shown in Fig 2A , which indicated that STX7 was associated with phagophores . The suppression of STX7 expression with siSTX7 did not affect the isolation of phagophores , again in agreement with the Fig 3A results , which indicated that STX7 was not essential for the formation of phagophores . HCV NS5A was also co-purified with phagophores , indicating the possible association of the HCV RNA replication complex with these membrane structures . In contrast , the cytosolic protein actin , which was not expected to be associated with phagophores , was not detected . ATG5 , STX7 and NS5A were not detected when the control IgG was used for the affinity purification of phagophores . The purified phagophores were then tested for their abilities to direct HCV RNA replication in vitro . As shown in Fig 5D , the purified phagophores could indeed mediate HCV RNA replication and this replication was not inhibited by STX7 knockdown . The replicated HCV RNA was not detected when the control IgG was used for the affinity purification of phagophores ( S5 Fig ) .
Autophagosomes may be derived from multiple membrane sources , including the ER [3 , 22 , 25] , the outer membrane of mitochondria [26] , the Golgi [27] , early endosomes [28] , plasma membranes [29] , and vesicles budding from ER and Golgi [30 , 31] . The ER-mitochondria junction [32] and the ER-Golgi intermediate compartment ( ERGIC ) [2] had also been found to participate in autophagosome biogenesis . It is possible that in different cell types , phagophores may originate from different subcellular compartments , and even within the same cell , their sites of origin may change in response to different external stimuli . As we found that phagophores induced by HCV were associated with the ER and could progress to become autophagosomes , autophagosomes induced by HCV most likely originated from ER membranes ( Fig 4 ) . When the phagophore originates from the ER , it forms a distinct membrane structure , which elongates while being encircled by the associated ER . The edges of the phagophore are eventually sealed to form the autophagosome [22 , 33] . However , it was recently reported that phagophores could also undergo homotypic fusion [16 , 34] . Our results indicated that phagophores induced by HCV could also undergo homotypic fusion ( Fig 1 ) , and this homotypic fusion was dependent on the SNARE protein STX7 ( Fig 2 ) . As STX7 colocalized with phagophores induced by HCV ( Fig 2A ) , it is conceivable that STX7 interacts with its SNARE protein partners such as VAMP7 to mediate the fusion of phagophores in HCV-infected cells ( S1 Fig ) . This homotypic fusion of phagophores apparently was essential for the generation of autophagosomes , as its inhibition via the suppression of STX7 or VAMP7 expression abolished the production of autophagosomes without affecting phagophores ( Fig 3 ) . Our previous studies indicated that HCV could use autophagosomes as the sites for its RNA replication [14 , 24] . The unique role of STX7 in the formation of autophagosomes but not in the formation of phagophores allowed us to examine whether the HCV RNA replication complex was assembled on autophagosomes before or after their formation . Our HCV RNA replication studies using HCV replicon cells treated with siSTX7 , which inhibited the formation of autophagosomes , and our cell-free HCV RNA replication assay using purified phagophores clearly demonstrated that HCV RNA replication could take place on phagophores ( Fig 5 ) . Recently , it was demonstrated that the HCV NS5A protein could transiently colocalize with omegasomes [35] , and HCV NS5B RNA polymerase could transiently interact with ATG5 [36] . Thus , it is tempting to speculate that the assembly of the HCV RNA replication complex is an early event in the biogenesis of autophagosomes , and by the time when phagophores are formed , the assembly of the HCV RNA replication complex has been completed . This replication complex then remains associated with autophagosomes to continue to mediate HCV RNA replication . More recently , it was reported that the suppression of ATG12 , which is required for the formation of phagophores , led to the suppression of HCV RNA replication [37] . Their results suggested an essential role of phagophores in HCV RNA replication and , together with our results , would argue that the HCV RNA replication complex was assembled initially on phagophores . It should be noted that the HCV RNA replication had also been reported to be associated with double membrane vesicles ( DMVs ) that were devoid of LC3 [38] . These DMVs were derived from the ER . The relationship between phagophores and DMVs is unclear and the possibility that phagophores may also be the predecessors of DMVs cannot be ruled out . ATG5 is located on phagophores and dissociates from these membranes upon the formation of autophagosomes . We were able to identify early phagophores ( ATG5-positive , LC3-negative ) , late phagophores ( ATG5-positive , LC3-positive ) and autophagosomes ( ATG5-negative , LC3-positive ) in HCV replicon cells . We also discovered that the kinetics of autophagic flux was different between those induced by nutrient starvation and HCV . The transition from late phagophores to autophagosomes induced by nutrient starvation was completed within 10 minutes whereas that induced by HCV took approximately 30 minutes . How HCV prolonged the transitioning from late phagophores to autophagosomes is unclear . This may be due to its use of distinct molecular pathways to induce autophagy such as the induction of unfolded protein response and the non-canonical initiation of autophagy [8 , 14 , 15 , 18 , 35] or the participation of phagophores in the biogenesis of DMVs . The biogenesis pathway of autophagosomes induced by HCV is summarized in Fig 6 . As illustrated in the figure , our results indicated that HCV stimulated the formation of phagophores from the ER , which then underwent homotypic fusion in an STX7-dependent manner to form autophagosomes . We also found that the HCV RNA replication could take place on phagophores , indicating that the HCV RNA replication complex was assembled on autophagosomes in the early stage of its biogenesis and remained associated with autophagosomes after they were generated . It remains to be determined regarding whether phagophores , which contain the HCV RNA replication complex , are also the predecessors of DMVs that had been reported to also mediate HCV RNA replication [38] .
Huh7 and its derivative Huh7 . 5 ( gift of Dr . Charles Rice , Rockefeller University ) are human hepatoma cell lines [8] . They were maintained at 37°C in Dulbecco's modified Eagle medium ( DMEM ) supplemented with 10% fetal bovine serum ( FBS ) and nonessential amino acids . Huh7N1b replicon cells harboring an HCV subgenomic RNA replicon were maintained in the same medium containing 0 . 8 mg/ml G418 ( Sigma-Aldrich ) [39 , 40] . Depending on the experiments , cells might be nutrient-starved in Hank’s balanced salt solution ( HBSS ) for 1 hour . Huh7 cells and HCV replicon cells that stably expressed the GFP-LC3 fusion protein were established by transfecting the cells with the GFP-LC3 expression plasmid followed by selection with hygromycin B ( 150 μg/ml ) and G418 ( 0 . 4 mg/ml ) . The primary antibodies used in this study included the mouse anti-STX7 antibody ( Sigma-Aldrich ) , rabbit anti-ATG5 antibody ( Cell Signaling ) , rabbit anti-p62 antibody ( Cell Signaling ) , mouse anti-HCV NS5A monoclonal antibody ( Millipore ) , rabbit anti-LC3 antibody ( Sigma-Aldrich ) , and rabbit anti-calnexin antibody ( Abcam ) . Proteins were extracted from cell lysates for western-blot analysis using the M-PER mammalian protein extraction reagent ( Thermo Fisher Scientific ) following the manufacturer’s protocol . The ER Tracker Blue was purchased from Thermo Fisher Scientific . HCV replicon cells were fixed in 2% glutaraldehyde in neutral phosphate buffer , post-fixed in osmium tetraoxide , and embedded in Epon . Sections were cut at 80 nm and examined under a Philips Tecnai 10 electron microscope . The DNA plasmids mEmerald-ATG5-C-18 ( Addgene plasmid #54000 ) or mCherry-ATG5-C-18 ( Addgene plasmid #54995 ) were mixed with the BioT transfection reagent ( Bioland ) in serum-free DMEM to a final concentration of 2 μg/mL per the manufacturer’s protocol . This transfection mixture was incubated at room temperature for 20 minutes prior to inoculation into cells . Two days after transfection , cells were harvested for further studies . For infection studies , Huh7 . 5 cells were infected with HCV using a multiplicity of infection ( m . o . i . ) of 1 one day after transfection . Infected cells were then harvested one day post-infection for further analysis . All of our infection studies were conducted using a variant of the HCV JFH1 isolate , which replicated more efficiently than the original JFH1 isolate [41] . The homotypic membrane fusion assay was performed as described [42] . Briefly , two sets of cells were transfected with either the mEmerald-ATG5 or the mCherry-ATG5-expressing plasmid . Cells were harvested in the homogenization buffer ( 250 mM sucrose , 3 mM imidazole [pH 7 . 4] ) containing the protease inhibitors , and passed through a 25-guage syringe needle 20 times . Cell lysates were centrifuged at 1200xg for 15 min at 4°C . The postnuclear supernatants ( PNS ) which contained either the mEmerald-ATG5-labeled phagophores or the mCherry-labeled phagophores were mixed with or without an ATP regenerative system for 60 min on ice with shakings in the dark . The mixed cell lysates were then placed on glass slides and fluorescence-labeled phagophores were visualized and imaged using the Keyence All-in-One fluorescence microscope . For the siRNA knockdown experiment , the STX7 siRNA ( siSTX7 ) ( SASI_Hs01_00171210 ) ( Sigma-Aldrich ) was transfected into cells using Lipofectamine RNAiMAX ( Invitrogen ) in Opti-MEM ( Invitrogen ) . Briefly , 4 × 104 cells seeded in a 35-mm dish were transfected with 2 μl of siRNA ( 100 μM each ) for 6 hours followed by the replacement of the transfection mixture with fresh DMEM . Replicon cells were harvested 48 hours post-transfection for analysis . For HCV infection studies , one day after the siRNA transfection , Huh7 cells were infected with HCV using an m . o . i . of 1 . Cells were then harvested one day after infection for further analysis . HCV replicon cell lysates were prepared using previously described procedures with modifications [43] . Briefly , cells grown in 100-mm-diameter dishes were washed with ice-cold phosphate-buffered saline ( PBS ) , followed by treatment with 1-ml per dish ice-cold hypotonic buffer ( 10 mM Tris-HCl [pH 7 . 5] , 10 mM KCl , 5 mM MgCl2 ) for 20 minutes . Cells then were scraped off the dish and lysed by passing through a 25-guage syringe needle 20 times . Nuclei and unbroken cells were removed by centrifugation at 1 , 000xg for 5 min at 4°C . For the membrane-flotation assay , cell lysates were mixed with 3 ml 80% sucrose in low-salt buffer ( LSB; 50 mM Tris-HCl [pH 7 . 5] , 25 mM KCl , and 5 mM MgCl2 ) and overlaid with 4 ml 55% sucrose and then 1 . 5 ml 10% sucrose in LSB . The sucrose gradient was centrifuged at 38 , 000 rpm in a Beckman SW40Ti rotor for 14 hours at 4°C . After centrifugation , 1-ml fractions were collected from the top of the gradient . To each fraction , 1 . 7 ml LSB was added to dilute sucrose , and membranes in individual fractions were concentrated by ultrafiltration using the Amicon Ultra 100K filter ( Millipore ) . Proteins in individual fractions were subjected to western-blot analysis using the ECL-plus system ( Thermo Fisher Scientific ) . For the affinity purification of phagophores , the anti-ATG5 antibody was added to the membrane fraction and after the incubation at 4°C with shaking overnight , protein-G-conjugated Dynabeads ( Thermo Fisher Scientific , #10007D ) were added and the phagophores were purified using the magnetic separator . For the cell-free HCV RNA replication assay , purified phagophores were incubated with the RNA replication buffer ( 100 mM HEPES [pH 7 . 4]; 10 mM KCl; 10 mM MgCl2; 0 . 1 mM MnCl2; 5 μg/ml actinomycin D , 1 mM [each] ATP , GTP , and UTP; 10 μM CTP; 3 μCi α-32P-CTP [3000 Ci/mmol] ) for 2 hours at 30°C . The RNA was extracted from the reaction mixture with TRIzol ( Invitrogen ) . After the addition of 10 μg tRNA carrier and CHCl3 and the incubation at room temperature for 10 minutes , the samples were centrifuged at 12000xg for 10 minutes . The RNA was then precipitated after the addition of an equal volume of 4 M ammonium acetate and four volumes of 100% ethanol . The precipitated RNA was resuspended in H2O , loaded on a 1% agarose gel containing formaldehyde for electrophoresis , and analyzed by autoradiography . | Autophagy is a catabolic process that is important for maintaining cellular homeostasis . During autophagy , crescent membrane structures known as phagophores first appear in the cytoplasm , which then expand to form enclosed double-membrane vesicles known as autophagosomes . It has been shown that hepatitis C virus ( HCV ) induces autophagy and uses autophagosomal membranes for its RNA replication . In this report , we studied the biogenesis pathway of HCV-induced autophagosomes and demonstrated that phagophores induced by HCV originated from the endoplasmic reticulum and undergo homotypic fusion to generate autophagosomes , and that the HCV RNA replication complex is assembled on phagophores prior to the formation of autophagosomes . These findings provided important information for understanding how an RNA virus controls this important cellular pathway for its replication . | [
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] | 2017 | HCV-induced autophagosomes are generated via homotypic fusion of phagophores that mediate HCV RNA replication |
Intestinal parasitic infections remain among the most common infectious diseases worldwide . This study aimed to estimate their prevalence and provide a detailed analysis of geographical distribution of intestinal parasites in the metropolitan region of Rio de Janeiro , considering demographic , socio-economic , and epidemiological contextual factors . The cross-section survey was conducted among individuals attending the Evandro Chagas National Institute of Infectious Diseases ( FIOCRUZ , RJ ) during the period from April 2012 to February 2015 . Stool samples were collected and processed by sedimentation , flotation , Kato-Katz , Baermann-Moraes and Graham methods , iron haematoxylin staining and safranin staining . Of the 3245 individuals analysed , 569 ( 17 . 5% ) were infected with at least one parasite . The most common protozoa were Endolimax nana ( 28 . 8% ) , Entamoeba coli ( 14 . 8% ) , Complex Entamoeba histolytica/Entamoeba dispar ( 13 . 5% ) , Blastocystis hominis ( 12 . 7% ) , and Giardia lamblia ( 8 . 1% ) . Strongyloides stercoralis ( 4 . 3% ) , Schistosoma mansoni ( 3 . 3% ) , Ascaris lumbricoides ( 1 . 6% ) , and hookworms ( 1 . 5% ) were the most frequent helminths . There was a high frequency of contamination by protozoa ( 87% ) , and multiple infections were observed in 141 participants ( 24 . 8% ) . A positive association between age ( young children ) and gender ( male ) with intestinal parasites was observed . Geospatial distribution of the detected intestinal parasitic infections was not random or homogeneous , but was influenced by socioeconomic conditions ( through the material deprivation index ( MDI ) ) . Participants classified in the highest levels of deprivation had higher risk of having intestinal parasites . This study provides the first epidemiological information on the prevalence and distribution of intestinal parasitic infections in the Rio de Janeiro metropolitan area . Intestinal parasites , especially protozoa , are highly prevalent , indicating that parasitic infections are still a serious public health problem . MDI showed that intestinal parasites were strongly associated with the socioeconomic status of the population , thus making it possible to identify social vulnerable areas .
Neglected tropical diseases , including intestinal parasitic infections , are a significant cause of morbidity and mortality in endemic countries [1] . Intestinal parasitic infections have particular relevance as they affect the poorest and most deprived areas in tropical and subtropical regions [1] . It is increasingly recognized that both protozoan and helminthic diseases are common among children under the age of five years . Children are more vulnerable to soil-transmitted helminths ( STHs ) than adults , and the nutritional impairment caused by the parasite can lead to iron-deficiency anaemia , malnutrition , and a negative impact on growth and cognitive development [2 , 3] . Despite all the medical and pharmaceutical advances and developments in sanitary engineering , intestinal parasitic infections remain among the most common infectious diseases worldwide , particularly in developing countries , where inadequate water treatment , poor sanitation and lack of adequate health services are common . Additionally , it is more difficult to implement enteric parasite-control actions in these regions due to the high cost of improvements in infrastructure , and the lack of educational projects offered to the population [1 , 4 , 5] . Water is essential to life , but is also a major vehicle for pathogen dissemination . The potential for waterborne parasite transmission is high since infective helminth eggs and protozoa ( oo ) cysts are distributed through water in the environment . Pathogens like Giardia lambia and Cryptosporidium spp . are recognized as important waterborne disease pathogens and are associated with severe gastrointestinal illness . Amoebiasis , balantidiosis , cyclosporidiosis and microsporidiosis outbreaks have been reported throughout the world [6 , 7] . It is well documented that conventional water and sewage treatment process are not completely effective in destroying protozoa ( oo ) cysts and helminth eggs [8–10] . Improper disposal of human and animal waste has also been identified as a source of infection , contaminating water sources [11] and recreational waters such as swimming pools , water parks and lakes [9] . Occasionally , sewer overflows also contribute to contamination of surface water and agricultural lands , which leads to potential human infection . Food contamination is also important and can occur directly in the handling process ( contaminated equipment , infected food handlers or wash water ) , or indirectly through contaminated irrigation water [12] . The lack of sanitary conditions to which the population is exposed favours the acquisition of various pathogens , and patients are often multiply infected ( polyparasitized ) . Recently , a systematic review and meta-analysis showed that sanitation facilities and water treatment are associated with lower risks of infection with intestinal protozoa , and could also prevent diarrhoeal diseases [1] . The same relationships were observed by Strunz et al . [13] for soil-transmitted helminths . In Brazil , intestinal parasite infections persist , although their frequency has decreased due improvement of sanitary conditions [14–16] . Up until now , studies of enteric parasites in Brazil have been limited , isolated and fairly rare , generally reflecting the situation in small towns . Mariano and colleagues [17] observed 77 . 2% of positive cases , and a polyparasitism of 51 . 2% in children from Itabuna ( Bahia ) . Similar results were observed in two localities of São Paulo , where 65 . 9% of the individuals were positive for at least one parasite [18] . In Rio de Janeiro , previous studies have shown intestinal parasite prevalence ranging from 18 . 3% to 66% [19–24] . The aim of this study was to estimate the number of individuals infected with intestinal parasites who attended a referral hospital located in Rio de Janeiro ( Brazil ) , and to provide a detailed analysis of the geographical distribution . The study also looked at the influence of demographic variables , socio-economic status and environmental factors on the intestinal parasitic infections . This knowledge will be essential for the development of effective prevention and control strategies to eliminate or reduce intestinal parasitic infection .
The Research Ethics Committee Evandro Chagas National Institute of Infectious Diseases ( INI/FIOCRUZ ) approved the study ( protocol number: 127 . 542 ) . This project was in accordance with the Brazilian Ethical Resolutions , especially Resolution CNS 196/1996 and its complementary and the Code of Medical Ethics of 1988 ( articles 122–1307 ) . Study individuals provided a written signed informed consent prior to sample collection and for participants younger than 18 years , informed consent was provided by parents or guardians after a detailed explanation of the objectives of the work . A term of privacy and confidentiality was signed by the researches for individuals to whom it was not possible to obtain informed consent beforehand . The cross-section survey was carried out from April 2012 to February 2015 in Evandro Chagas National Institute of Infectious Diseases ( INI/FIOCRUZ ) , a reference hospital in infectious diseases in Brazil , located in Rio de Janeiro ( RJ ) . Despite it being an infectious disease referral hospital , individuals also attend for routine consultations ( cardiology , dermatologist , gynecology , neurology , ophthalmology , otolaryngologist , infectious disease speciality ) or emergency situations . As the prevalence of intestinal parasites in Brazil remains high , it is common the doctor´s submit requests for parasitological analysis in faeces , regardless of age or genera and of having or not symptoms suggestive of intestinal infections . The INI/FIOCRUZ hospital receives individuals from all municipalities , mainly the metropolitan area . Rio de Janeiro State is composed of 92 municipalities . The metropolitan region of Rio de Janeiro is composed of 21 municipalities: Belford Roxo , Cachoeira de Macacu , Duque de Caxias , Guapimirim , Itaboraí , Itaguaí , Japeri , Magé , Maricá , Mesquita , Nilópolis , Niterói , Nova Iguaçu , Paracambi , Queimados , Rio Bonito , Rio de Janeiro , São Gonçalo , São João de Meriti , Seropédica and Tanguá ( Fig 1 ) . It is the second largest metropolitan area in Brazil with 11 . 812 . 482 inhabitants in an area of 8 . 147 . 356 km2 . This region has 2 . 746 slums , with a resident population of 1 . 702 . 073 inhabitants ( 14 . 4% from the total population ) occupying 123 . 627km2 [25] . The main characteristics of each municipality of the metropolitan region of Rio de Janeiro State are summarized in Table 1 . According to the last census conducted in 2010 , Rio de Janeiro municipality has a population of 6 . 320 . 446 inhabitants ( Table 1 ) in an area of 1 . 197 . 463 km2 . The municipality has 2 . 227 slums , with a resident population of 1 . 393 . 314 inhabitants ( 11 . 8% from the total population ) occupying 54 . 213 km2 [25] . Municipal human development index ( MHDI ) is a summary measure of average achievement in key dimensions of human development ( a long and healthy life , being knowledgeable and have a decent standard of living ) , and gini index is a measure of statistical dispersion whose value ranges from zero ( perfect equality ) to one ( perfect inequality ) . The MHDI of Rio de Janeiro is 0 . 799 according to the United Nations Development Programme [26] and gini index is 0 . 6391 [25] . Most of the population ( 91 . 2% ) has access to potable water and 70 . 1% has sanitation coverage [27] . The study population included individuals ( n = 3245 ) , of both genders and all age groups , attended in Evandro Chagas National Institute of Infectious Diseases , between April 2012 and February 2015 . Stool samples were collected by the participant in plastic disposable flasks with or without preservatives and maintained at 4°C until laboratory analysis on the same day . Flasks were labelled with the name , collection date and the hospital number . The parasitological tests were conducted at the Parasitology Laboratory of INI by experienced laboratory technologists and College of American Pathologist certifies the Laboratory . Moreover , participant’ data ( sex , age , educational level and residence ) were obtained from the hospital’s database . For laboratory diagnosis of intestinal parasites , the fresh specimens were analysed by means of centrifugation sedimentation [28] , centrifugal flotation in zinc sulphate solution [29] , Kato-Katz ( Helm-TEST kit , Fiocruz , Brazil ) and Baermann-Moraes method [28 , 30] . All these techniques were routinely performed on all fresh stool samples . Specimens preserved in MIF solution ( mertiolate-iodine-formaldehyde ) were processed by the centrifugation sedimentation method [28] . The Graham method , faecal occult blood test , the iron haematoxylin staining and the safranin staining procedure was carried out depending on doctor request [28] . The slides were then observed under the optical microscope . All individuals attended in INI/FIOCRUZ are dewormed when diagnosed ( drugs are provided by the institution itself ) . The zip code for each participant was obtained from the hospital’s database and through Brazilian Institute of Statistics and Geography ( IBGE ) converted into geographic coordinates ( latitude and longitude ) . IBGE was the source of data in respect of geography , demography and socioeconomic conditions of the studied population ( National Census of 2010 ) . The spatial distribution of the participants was assessed through a Kernel Density Function that allows to estimate the intensity of events across a surface by calculating the overall number of cases within a given search radius from a target point . To identify if the participants were spatially clustered or dispersed the Average Nearest Neighbor test was used . To evaluate the social and economic conditions of the place of residence a material deprivation index ( MDI ) was constructed , at the census tract level , to the metropolitan region of Rio de Janeiro . The MDI is based upon the following indicators: ( 1 ) illiteracy rate/education ( percentage of population older than 10 years that can read or write ) ; ( 2 ) water supply/sanitation ( percentage of permanent households without public water treatment plant ) ; and ( 3 ) family income ( percentage of households with per capita monthly income ≤1 minimum wage ) . Based on the Carstairs and Morris method , the indicators considered in each index were standardised ( using the z-score method ) so that each indicator has a weighted mean of zero and a variance of one , and exerted the same influence upon the final result [31] . The MDI was analysed in quintiles: q1 , lowest level of deprivation; q5 , highest level of deprivation . To address the potential effects of the socioeconomic conditions of the place of residence on the incidence of intestinal parasites , the proportion of participants living in each deprivation quintile was assessed . Simultaneously , the proximity to slums was analysed through geographical buffers of 50m and 100m . The spatial analysis was performed through the ArcMap 10 . x software of ESRI . The data entry was carried out using Excel software and analysed using Statistical Package for the Social Sciences ( SPSS ) version 16 . Percentages were used to perform the exploratory analysis of the categorical variables and quantitative variables are presented as mean ± standard deviation ( SD ) . Pearson´s chi-squared and Fisher’s Exact Test were used for categorical data . The level of statistical significance was set as p<0 . 05 , an odds ratio and 95% confidence interval ( CI ) was computed . Logistic regression was used to identify a potential contribution of each of the variables for the acquisition of intestinal parasite infections .
Between April 2012 and February 2015 , a total of 3245 individuals ( 1564 female and 1681 male ) had the parasitological tests done ( Table 2 ) . In 2012 a total of 995 samples were collected , with 193 positive samples; in 2013 , 1189 individuals were collected being 187 positive samples; in 2014 , 938 individuals with 168 positive samples; and in 2015 , 123 individuals with 21 positive samples . Summarizing , we had 569 individuals ( 17 . 5% ) with positive stool examination for one or more enteric parasite and 2676 individuals ( 82 . 5% ) with negative results . The ages of the participants ranged from 1 to 93 years with an average of 41 . 34±15 . 54 ( Mean±SD; median = 41 ) . The adults between 26–65 years were the majority of participants ( n = 2130 ) ( Table 3 ) . There were more male than female parasitized ( 64 . 5% versus 35 . 5% , respectively ) and seventy-five percent of participants ( n = 427 ) were educated above the primary grade ( Table 3 ) . Endolimax nana was the most common enteric parasite , present in 216 samples ( 28 . 8% ) followed by Entamoeba coli in 111 samples ( 14 . 8% ) , Complex Entamoeba histolytica/Entamoeba dispar in 101 samples ( 13 . 5% ) , Blastocystis hominis in 95 samples ( 12 . 7% ) , Giardia lamblia in 61 samples ( 8 . 1% ) , Iodamoeba butschilii in 33 samples ( 4 . 4% ) , Strongyloides stercoralis in 32 samples ( 4 . 3% ) , Schistosoma mansoni in 25 samples ( 3 . 3% ) , Cryptosporidium sp . in 14 samples ( 1 . 9% ) , Ascaris lumbricoides in 12 samples ( 1 . 6% ) , Cystoisospora belli in 12 samples ( 1 . 6% ) , hookworms in 11 samples ( 1 . 5% ) , Trichuris trichiura in 10 samples ( 1 . 3% ) , Entamoeba hartmani in 9 samples ( 1 . 2% ) , Enterobius vermicularis in 6 samples ( 0 . 8% ) and Hymenolepis nana in one sample ( 0 . 1% ) ( Table 4 ) . The number of samples with one parasite ( monoparasitism ) is higher ( 428 positive samples , 57 . 1% ) than those samples with various parasites ( polyparasitism ) ( 321 positive samples , 42 . 9% ) . Interesting , the frequency of the amoebae ( Complex E . histolytica/E . dispar , E . coli and E . hartmani ) as well of some geohelminths ( A . lumbricoides and T . trichiura ) is higher on samples with various parasites ( polyparasitism ) ( Table 4 ) . We observed a very high frequency of protozoan infections ( 87% ) , occupying the first six positions; E . nana was the predominant , followed by E . coli and Complex E . histolytica/E . dispar . The most frequent helminths were S . stercoralis and S . mansoni; only appearing in seventh position . Of the 16 species of intestinal parasites detected , 11 were pathogenic ( Complex E . histolytica/E . dispar , Cryptosporidium sp . , C . belli , G . lamblia , A . lumbricoides , E . vermicularis , H . nana , hookworms , S . mansoni , S . stercoralis and T . trichiura ) and 5 were non-pathogenic ( B . hominis , E . nana , E . coli , E . hartmani and I . butschilii ) . The pathogenic species comprises 38 . 1% of the studied participants ( 285 of 749 ) , while the non-pathogenic reached 61 . 9% ( 464 of 749 ) . Most of the participants ( 428 of 569; 75 . 2% ) did not present any co-infection , whereas 141 ( 24 . 8% ) had two or more parasites simultaneously . Among the multiple infected , 109 individuals were infected with two parasites ( 19 . 2% ) , 26 were infected with three parasites ( 4 . 6% ) , 5 had four parasites ( 0 . 9% ) and 1 had five ( 0 . 1% ) . Regarding parasitic associations , only 11 . 8% ( 67 of 569 ) were co-parasited by helminths , 84 . 3% ( 480 of 569 ) by protozoa and only 3 . 9% ( 22 of 569 ) by both . Age and gender were examined as potential associations for intestinal parasitic infections . A positive association between gender and intestinal parasites ( p<0 . 0001 ) , as well as protozoa ( p<0 . 0001 ) , helminths ( p<0 . 0001 ) and poliparasitism ( p<0 . 0001 ) were detected . Male were more likely to be infected with intestinal parasites ( OR = 1 . 9; 95%CI of 1 . 56 to 2 . 27 ) , protozoa ( OR = 1 . 8; 95%CI of 1 . 50 to 2 . 20 ) , helminths ( OR = 2 . 8; 95%CI of 1 . 75 to 4 . 51 ) and have multiple parasites ( OR = 3 . 4; 95% CI of 2 . 28 to 5 . 05 ) compared to female ( Table 5 ) . No statistical significant difference was found between intestinal parasites and age ( p = 0 . 166 ) . However , when we analyse the parasite species separately we observed that children ( 0–14 years ) were more likely to be infected with A . lumbricoides ( p = 0 . 031; OR = 8 . 5; 95% CI = 1 . 8; 39 . 4 ) , E . vermicularis ( p = 0 . 005; OR = 28 . 2; 95% CI = 4 . 6; 171 . 6 ) , B . hominis ( p = 0 . 002; OR = 3 . 9; 95% CI = 1 . 8; 8 . 4 ) , and G . lamblia ( p = 0 . 011; OR = 4 . 1; 95% CI = 1 . 6; 10 . 7 ) as compared to the older participants ( S1 Table ) . Moreover , there were no cases of multiple parasitic infections in children under 5 years old ( S1 Table ) . The prevalence of intestinal parasites varies by municipalities , most of participants ( 2847 of 3245; 87 . 7% ) live in metropolitan region and 1748 ( 53 . 9% ) live in Rio de Janeiro municipality ( Tables 6 and S2 ) . The metropolitan region of Rio de Janeiro had 532 positive cases ( 16 . 4% ) and the others municipalities had 21 positive cases ( 0 . 6% ) ( Table 6 ) . As expected , Rio de Janeiro municipality had a greater number of participants infected with intestinal parasites ( 332; 10 . 2% ) since it has the larger population ( S2 Table , S1 Fig ) . In 16 participants ( 0 . 5% ) positive for intestinal parasites was not possible to identify the residence . The distribution of parasites species also varied among the municipalities ( Table 7 ) . The metropolitan region had 93 . 7% ( 702 of 749 ) of the enteric parasites observed: in Rio de Janeiro it was possible to detect 434 enteric parasites ( 57 . 9% ) , Duque de Caxias was the second municipality with 81 ( 10 . 8% ) , followed by Nova Iguaçu ( 57; 7 . 6% ) , Belford Roxo ( 33; 4 . 5% ) , São João de Meriti ( 25; 3 . 4% ) , São Gonçalo ( 18; 2 . 4% ) , Nilópolis ( 15; 2% ) , Magé ( 12; 1 . 6% ) , Cachoeira de Macacu ( 5; 0 . 7% ) , Itaboraí ( 4; 0 . 5% ) , Niterói ( 3; 0 . 4% ) , Queimados ( 3; 0 . 4% ) , Itaguaí ( 2; 0 . 3% ) , Maricá ( 2; 0 . 3% ) , Mesquita ( 2; 0 . 3% ) , Seropédica ( 2; 0 . 3% ) , and Japeri ( 4; 0 . 5% ) . We did not have positive samples from participants of Guapimirim , Paracambi , Rio Bonito and Tanguá . Others municipalities amounted 28 ( 3 . 7% ) enteric parasites , and 19 ( 2 . 5% ) was not possible to identify the municipality ( Table 7 ) .
The current study estimated the prevalence of intestinal parasitic infections among individuals from Rio de Janeiro State ( Brazil ) , in addition to evaluating some epidemiological aspects . Spatial analysis was applied for the first time to the case of Rio de Janeiro to describe the geographical distribution of individuals with enteric parasites infections . The study also looked at socio-economic indicators ( social vulnerability indicator ) for intestinal infections , in particular family income , education and sanitation ( access to safe drinking water ) . The construction of a material deprivation index allowed us to identify the most vulnerable regions for intestinal parasitic infections in the metropolitan area of Rio de Janeiro State . The mean prevalence of intestinal parasitic infections remains high in Rio de Janeiro State ( 17 . 5% ) and also in the metropolitan region and the municipality ( 18 . 7% and 19% , respectively ) . Previous studies suggest that we may observe a decrease in the prevalence of intestinal parasites in Rio de Janeiro with time . A parasitological survey carried out in 1984 on children from day-care centres detected a prevalence of 35% [19] . Further studies carried out on pregnant women [20] , children living in low income communities [21] and day-care centres located in slums in the municipality [22] showed a prevalence ranging from 37 . 6% to 54 . 5% . A survey made in 2007 in a paediatric hospital [23] detected values of 18 . 3% . Although our results indicate that the mean prevalence is similar to this last study , it should be noted that individuals attending the Evandro Chagas National Institute of Infectious Diseases ( INI/FIOCRUZ ) were mainly adults , where it was expected that prevalence would be lower when compared to studies on children . Age is an important risk factor for intestinal parasitic infections . Children are more susceptible to intestinal infectious diseases than adults because of their poor hygiene habits; they are often in contact with contaminated soil and their immune system is immature [2 , 32] . In spite of our small number of samples from young participants , we observed a positive association between infections with A . lumbricoides , E . vermicularis , B . hominis and G . lamblia and the younger age . The distribution of intestinal parasites varied among the municipalities that compose Rio de Janeiro State , with the highest incidence density of intestinal parasites in municipalities with larger population ( Rio de Janeiro , Duque de Caxias , Nova Iguaçu , Belford Roxo and São João de Meriti ) . These results could be explained by the ease of access to the INI hospital , since these areas have the main road corridors of the municipality ( Brazil Avenue , Governador Carlos Lacerda Avenue , Presidente João Goulart Avenue and Presidente Dutra highway ) , and also because many of the infected population lives near INI hospital . Despite São Gonçalo is the second largest municipality , only 2 . 4% ( 18 of 749 ) of the intestinal parasites were detected there . This municipality is located across the Guanabara Bay , such that access by participants to the INI hospital is probably limited by poor public transportation . The prevalence of enteric parasites varies between regions of Brazil , and contrasting data are observed: 11 . 3% in Sergipe [33]; 42% reported from São Paulo ( southeast ) [34]; 73 . 5% in Mato Grosso do Sul ( midwest ) [35]; 75 . 3% in Paraná ( south ) [36]; 77 . 2% in Bahia ( northeast ) [17] . However , data extracted from previous studies in Brazil should be analysed with some caution , once they were limited , isolated , and usually reflect the results from small towns and/or of restricted groups ( day-care centres , schools , indigenous tribes , small hospitals , fishing villages , etc . ) . Attention should also be given to studies conducted in other countries: Argentina ( 78 . 3% ) in children living in a poor area [37]; Peru ( 66 . 3% ) in orphanages [38]; Honduras ( 43 . 5% ) in school going children [39]; Pakistan ( 52 . 8% ) in children residing in slum areas [5]; and India ( 68% ) in school going children [40] . In the present work , the most common pathogenic species detected were Complex E . histolytica/E . dispar ( 13 . 5% ) and G . lamblia ( 8 . 1% ) . These two parasites are frequently found in Brazil [17 , 18 , 35 , 41] . However , detection of G . lamblia cysts is particularly alarming since these are resistant to conventional routine disinfectants , and are frequently found in sewage effluent and surface water [10] . In addition , individuals infected with G . lamblia are largely asymptomatic , and can spread the infection , contributing to high epidemic rates . Similarly , concern should also be given to the presence of B . hominis ( 12 . 7% ) , since its pathogenicity is still controversial [42] . In Minas Gerais ( Brazil ) , Cabrine-Santos and colleagues [43] observed that 8% of participants with diarrhoea had only Blastocystis spp . ( monoparasitism ) ; suggesting that the parasite may have a pathogenic character . Although soil-transmitted helminths ( A . lumbricoides , T . trichiura , hookworms and S . stercoralis ) are the most frequent parasites found in many countries [32 , 39] , they were not the predominant enteric parasites in this study . Probably these parasites cannot complete their life cycles due the absence of an adequate soil environment or the presence of road/sidewalk paving or a high construction index [16] . The low prevalence of S . mansoni infections was also observed . The transmission of S . mansoni is dependent on the presence of a water and an intermediate host snail , which may be not available in the areas of this study . According to the Brazilian Ministry of Health [44] , the positive rate of S . mansoni in Rio de Janeiro State is 1 . 56% , making it the State with the lowest number of confirmed cases . We noticed a positive association between intestinal parasites and the male gender . Similar results are observed in Brazil [43] and Iran [45 , 46] , with a slightly higher prevalence of intestinal parasites in males than females . This association could be due to hygienic behaviours , specific occupations or even sexual activities , particularly among homosexuals , that may result in faecal/oral contact that subsequently leads to transmission of these agents [47 , 48] . Chemotherapy is one of the intervention strategies that reduce the incidence of intestinal diseases . Regular deworming with the drugs albendazole and mebendazole is the current global control strategy to reduce the prevalence of helminths , and is implemented in Brazil [44] . However , the deworming programmes are not effective against protozoa infections . In this study we clearly observed that the frequency of protozoan infections ( 87% ) was much higher than that of helminths ( 13% ) . It is worth mentioning that nitazoxanide is an antiparasitic drug with a broad-spectrum activity against a variety of intestinal parasites ( including protozoa and helminths ) . However , this product is not included in the list of pharmaceutical care products of the Unified Health System ( SUS ) in Brazil . A number of individuals ( 141; 24 . 8% ) were infected by multiple enteroparasites: 3 . 5% ( 5 of 141 ) of participants were infected with helminths , 80 . 9% ( 114 of 141 ) were infected with protozoa and 15 . 6% ( 22 of 141 ) by both . Polyparasitism remains persistent in the country: 18 . 4% of such cases were reported in São Paulo [34] , 49 . 2% in Mato Grosso do Sul [35] , 26 . 7% in Paraná [36] , 51 . 2% in Bahia [17] . These works all showed the high frequency of protozoa . Polyparasitism had been observed in many countries [5 , 49 , 50]; for example , in Kenya , 7% of the study population was infected with multiple parasites [32] , and Mejia Torres et al . [39] observed that 14 . 6% of children in Honduras were infected with more than one parasite . This study confirms that the population has a high frequency of intestinal parasites , principally protozoa . Although the majority of parasites ( 62% ) were non-pathogenic ( B . hominis , E . coli , E . hartmani , E . nana and I . butschilii ) , it is important to note that these species have the same transmission path as other pathogenic protozoa , such as Complex E . histolytica/E . dispar and G . lamblia , indicating exposure to faecal contamination . The frequency of these parasites added to the high frequency of polyparasitism can be used as indicators of transmission through the faecal/oral route , thereby pointing to in the transmission of intestinal parasites via the supply of water for human consumption , or the ingestion of contaminated food . Several authors have demonstrated the vulnerability of drinking water supply systems due contamination , which can lead to problems , such as the deterioration of water quality , which lead to the proliferation of pathogens , and , therefore , increase the risk of waterborne diseases [51 , 52] . Water for the citizens of the metropolitan region of Rio de Janeiro is provided by two principal supply systems , called Guandu-Piraí and Imunana-Laranjal . Both of these undergo the conventional treatment process , including coagulation , flocculation , filtration ( granulated active carbon ) , fluoridation and chlorination [53] . Two companies carry out the operation and management of the water systems , one of which is public ( State Company of Water and Sewage—CEDAE ) and the other is a concession ( Niterói Water ) . The Niterói Water Company only operates on the distribution of treated water , which is supplied by CEDAE from the water collected in the Imunana-Laranjal system . Although both systems operate satisfactorily , in agreement with Brazilian standards of technical quality and health [54] , water distribution generally has problems inherent in the characteristics of the use and occupation of urban land in the metropolitan region of Rio de Janeiro , particularly in the municipalities and neighbourhoods with higher levels of social and economic inequality . In these areas , lack of access to collection services and sewage treatment leads to the contamination of the water supply network through cross connections and low pressure zones , thereby leading to the entry of sewage and rainwater into the system . This situation is exacerbated in neighbourhoods and slums located in higher areas , where the pressure in the network is insufficient to maintain a constant water flow , and , according to the Brazilian Standard , drinkability [55 , 56] . Although we did not directly investigate this matter , we know that in developing countries , such as Brazil , access to clean water , sanitation facilities and health infrastructure does not follow the population growth . Research conducted in two low-income communities of Campos dos Goytacazes ( north of Rio de Janeiro State/Brazil ) confirmed by water analysis that the entire underground water of the study area was contaminated and a high faecal contamination was detected in well water . The authors concluded that possibly inadequate sanitation , with sewage discharged directly into the soil in some points , visible leakage , along with inadequate , and negligent routine maintenance in some septic tank systems could certainly have contributed to the dissemination of diseases caused by parasites [57] . The high prevalence of intestinal parasitic infections is also closely related to the low level of education , the low household incomes family and improper hygienic practices [4 , 5 , 57] . This study evaluated the socio and economic conditions of the Rio de Janeiro population using an index of material deprivation ( MDI ) composed of three indicators ( sanitation , income and education ) . The Rio de Janeiro metropolitan area is comprised of many census tracts ( CTs ) , very close together and with very different MDIs , resulting in the highly heterogeneous character of the Rio de Janeiro territory . For example , while the INI hospital was classified in the first deprivation quintile ( q1 ) , a large part of the resident population in its surroundings live in slums or very poor neighbourhoods and was classified in the last deprivation quintiles ( q4 or q5 ) . Such proximity of participants to slums makes them more likely to be infected with intestinal parasites . Clearly , the geospatial distribution of the detected intestinal parasitic infections was not random or homogeneous , but was influenced by the MDI and the proximity to INI . Discrepancy of the MDIs among the closest CTs reveals the need for a horizontal decision-making process , not only in the poorest areas of the municipality , but throughout their surrounding areas . Improvements in sanitation systems , deworming and the creation of poverty reduction programmes ( Bolsa Família and Favela Bairro Program ) in Brazil have helped greatly to reduce the prevalence of intestinal parasites over the years , but much obviously remains to be done . Safe drinking water is a defining aspect of a developed country , and even today it is still a significant challenge to public health worldwide . Additionally , the lack of access to health services near their home forces individuals to travel great distances to demand medical treatment , and , in many cases , the lack or deficiencies in public transport prevents these people from accessing the medical units . Access to medical care , preventative chemotherapy and improvements in water supply and sanitation are matters of urgency , and also require a massive education campaign for low and middle-income families . Water of good microbial quality must be continuously supplied to the households ( avoiding storage , which is another factor for contamination ) , and thus preventing its theft . Diseases are not distributed occasionally or randomly , the existence of risk factors determines their distribution , so that constant and continuous monitoring is required . Efforts directed to build a health surveillance system are urgent for Rio de Janeiro , and require strategies based on: sanitary conditions , water supply , population vulnerability , socio-demographic and environmental factors such as age , gender , education , household characteristics and income . Knowing the geographical distribution of intestinal parasites in Rio de Janeiro population is an important first step that will assist in the decision-making process necessary to design effective preventive and control programs; however , more epidemiological studies are imperative . The ability to readily identify and reach individuals at highest risk of infection is an important aspect of parasitic disease control programmes . | Intestinal parasitic infections are considered indicators of health and socio-environmental vulnerability , and are associated with precarious sanitation and water quality of a country . They continue to pose a serious public health problem , especially in developing countries where sanitation is not expanded in line with population growth , such that access to basic services becomes more difficult . Although Brazil is a country with a high prevalence of intestinal parasitic infections , the prevalence in the metropolitan region of Rio de Janeiro ( the second largest metropolitan area in the country ) has not been estimated . Based on the identification of social determinants ( income , education and sanitation ) , our group was able to identify vulnerable areas for intestinal parasitic infection in the metropolitan region of Rio de Janeiro . Infections caused by intestinal parasites are not included in the list of diseases compulsory notification in Brazil . However , special attention should be focused on this topic , and information on the geographic distribution and prevalence of intestinal parasites , as well as the recognition of vulnerable areas , are the first steps , and a prerequisite for development of appropriate control strategies by the government . | [
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] | 2017 | Geospatial distribution of intestinal parasitic infections in Rio de Janeiro (Brazil) and its association with social determinants |
Elite controllers ( ECs ) represent a unique model of a functional cure for HIV-1 infection as these individuals develop HIV-specific immunity able to persistently suppress viremia . Because accumulating evidence suggests that HIV controllers generate antibodies with enhanced capacity to drive antibody-dependent cellular cytotoxicity ( ADCC ) that may contribute to viral containment , we profiled an array of extra-neutralizing antibody effector functions across HIV-infected populations with varying degrees of viral control to define the characteristics of antibodies associated with spontaneous control . While neither the overall magnitude of antibody titer nor individual effector functions were increased in ECs , a more functionally coordinated innate immune–recruiting response was observed . Specifically , ECs demonstrated polyfunctional humoral immune responses able to coordinately recruit ADCC , other NK functions , monocyte and neutrophil phagocytosis , and complement . This functionally coordinated response was associated with qualitatively superior IgG3/IgG1 responses , whereas HIV-specific IgG2/IgG4 responses , prevalent among viremic subjects , were associated with poorer overall antibody activity . Rather than linking viral control to any single activity , this study highlights the critical nature of functionally coordinated antibodies in HIV control and associates this polyfunctionality with preferential induction of potent antibody subclasses , supporting coordinated antibody activity as a goal in strategies directed at an HIV-1 functional cure .
Vaccine-mediated protection from HIV-1 infection has been observed in humans in association with extra-neutralizing antibody functions , including the ability to induce effector functions such as antibody-dependent cellular cytotoxicity ( ADCC ) [1] . Similarly , HIV-infected patients who are able to spontaneously suppress infection in the absence of antiretroviral therapy ( i . e . , HIV-1 controllers ) have been found to exhibit potentiated ADCC activity [2–10] . Importantly , as HIV-1 controllers represent an alternative vaccine goal—the induction of immunity able to contain viral replication subsequent to infection—these data suggest that beyond cellular correlates associated with control [11 , 12] , antibodies with enhanced ability to direct the potent anti-viral activities of innate effector cells may also contribute to a functional cure . Thus , evidence from both protected vaccinees and spontaneous HIV-1 controllers converges on a potential role for non-neutralizing antibody responses with the capacity to direct the cytolytic activity of the innate immune system in viral control and clearance . However , beyond ADCC , antibodies mediate a wide array of additional effector functions , and antibodies from HIV controllers also exhibit elevated phagocytosis , viral inhibition , and NK activation [13 , 14] . While IgG3-driven antibody polyfunctionality was associated with reduced risk of infection in the RV144 vaccine trial [15 , 16] , the specific humoral profiles that associate with antibody-mediated viral containment in the setting of durable control of infection are unknown . Accordingly , we aimed to define the functional landscape of anti-viral antibodies among infected subjects with variable degrees of viral control and determine whether specific effector functions , alone or in combination , are associated with durable suppression . Because the functional profile of humoral immune responses may offer insights into both prevention and functional HIV-1 cure , determining the specific characteristics of the most functional anti-viral antibodies offers a unique target for prophylactic and therapeutic HIV vaccines .
To broadly profile the functional activity of polyclonal antibodies present in different HIV-positive subject groups , samples from approximately 200 HIV-positive subjects , balanced for sex and age , including elite controllers [12] ( EC ) , viremic controllers ( VC ) , HIV-positive subjects on antiretroviral therapy ( CT ) , and untreated HIV-positive subjects ( CU ) , were evaluated using a suite of functional assays encompassing diverse effector cells and mechanisms . The spectrum of antibody functions evaluated included: ( 1 ) antibody-dependent complement deposition ( ADCD ) , which was assessed by measuring the deposition of complement component C3b ( derived from HIV-seronegative donor plasma ) on the surface of CD4-expressing target cells pulsed with rgp120 [17]; ( 2 ) HIV-specific ADCC , which was assessed by measuring CFSE loss from rgp120-pulsed target CEM-NKr cells in the presence of antibody and negatively selected NK cells from healthy donors [16]; ( 3 ) antibody-dependent NK cell activation , which was assessed based on the extent of cell surface expression of CD107a on and intracellular production of IFN-γ and MIP-1β in NK cells from healthy donors that had been incubated with antibodies and rgp120-pulsed target CEM-NKr cells [16]; ( 4 ) antibody-dependent phagocytosis ( ADCP ) , which was assessed by quantifying the uptake of rgp120-functionalized fluorescent beads by THP1 cells [18 , 19]; and ( 5 ) antibody-dependent neutrophil-mediated phagocytosis ( ADNP ) , which was measured using the ADCP assay method but with primary neutrophils isolated from healthy donors used as effector cells [17] . In contrast to previous studies , enhanced functional activity among ECs was not observed for any individual Fc-effector function compared to VCs , CTs , or CUs ( Fig 1A–1G ) . Because prior analyses of the moderately protective RV144 vaccine trial have suggested that qualitative , rather than quantitative , differences in antibody activity may better mark “protective” responses [15 , 16 , 20] , we next examined whether there were differences in Fc effector activity coordination . Correlation coefficients of all pairs of effector activities were determined ( Fig 2A ) and plotted according to their strength and frequency ( Fig 2B ) , demonstrating that antibodies from ECs possessed polyfunctional attributes in the form of a significantly higher degree of functional correlation than antibodies from VCs ( p<0 . 01 ) or CUs ( p<0 . 001 ) and a trend towards higher coordination than CTs . These data demonstrate that even though the magnitude of the effector activity was often individually lower in ECs , the antibody functions were significantly more correlated with one another . Conversely , antibody effector functions were more weakly correlated among the viremic subjects ( VCs and CUs ) despite generally higher individual antibody Fc-effector activity . Therefore , despite generally lower magnitudes for individual functions , ECs generated a more coordinated antibody effector profile capable of inducing multiple functions simultaneously . Furthermore , when broken out across each pair of functions , these correlation analyses identified unique profiles within the subject groups ( Fig 2C ) . For example , ADCD was highly positively correlated with all other functions in ECs , but generally had no or only weak correlation with the other functions , particularly in the viremic subject groups ( VC and CU ) . Overall , the differences in functional coordination observed between subject groups further support observations from the RV144 analysis [15 , 16 , 20] and NHP studies [17 , 21] , demonstrating that qualitatively superior responses may provide better antiviral defense . Antibodies were titered in order to begin to dissect the level and types of antibodies associated with potent and coordinated effector function ( Fig 3A ) . Viremic subject groups ( VC and CU ) possessed significantly higher antibody responses than ECs , with a median level that was approximately twice as great as the level observed in ECs . The differences between the various groups were larger when titer , rather than function , was examined , suggesting that on a per-molecule basis , antibodies from ECs may be more functionally potent than those present in other subject groups . Because mechanistic studies aimed at dissecting the underlying biology of polyfunctional antibody responses in RV144 pointed to a critical role for the induction of HIV-specific IgG3 antibodies [15 , 16 , 20] and negative impacts of the induction of IgG2 , IgG4 , and IgA antibodies [1 , 20 , 22] , we aimed to move beyond determination of total IgG levels and examined IgG subclass selection across the cohort . The percent of subjects who elicited antibodies of each subclass was determined ( Fig 3B ) , and while gp120-specific IgG4 responses were more prevalent in the CTs and CUs , IgG4 responses were virtually absent in the controllers ( VC and EC ) . Most VC , CT , and CU subjects generated an IgG2 response , whereas the majority of ECs did not generate gp120-specific IgG2 antibodies . While the IgG3 responses varied among the groups , these responses were generally more prevalent in the viremic subjects . Because IgG subclasses possess distinct functional profiles , with IgG3/1 demonstrating strong binding to FcγRs and C1q but IgG2/4 exhibiting weak binding and effector activity , we wondered whether coordination among the subclasses , representing skewing towards synchronously more or less active subclasses , could be observed in the study cohort . When the degree of correlation between response levels for each subclass was determined , we observed that subclasses with similar activity profiles ( i . e . , IgG1/IgG3 or IgG2/IgG4 ) had strong positive associations , whereas only weak or no associations were observed between subclasses with opposing activity profiles ( e . g . , IgG1/IgG4; Fig 3C ) . This observation suggests that the humoral immune system may integrate signals to define antibody activity at a relatively high level , predisposing B cells to class-switch to either IgG3/1 or IgG2/4 based on the level of antibody effector potency desired . This type of activity-based subclass skewing could be observed within groups , where notable differences in subclass response magnitudes were also observed ( Fig 3D ) : relatively elevated levels of gp120-specific IgG3/1 responses were observed among controllers , whereas higher levels of gp120-specific IgG2/4 responses were apparent in chronically infected subjects , particularly compared to ECs . These data highlight significant subclass selection biases between controllers/non-controllers , especially the induction of subclasses with compromised function among subjects with progressive disease . We next aimed to define the relationship between antibody subclass levels and functionality for each subject group ( Fig 4A ) . Total HIV-specific antibody levels correlated with every antibody function in ECs and nearly all functions in CTs; however , total HIV-specific antibody levels in VCs and CUs failed to correlate with most functions tested . These data suggest that the “average” antibody present in ECs is functional , whereas the observation that titer does not relate to activity in VCs and CUs indicates that there are striking differences in the overall quality of antibody pools present among groups . Deconvolution of the relationships of individual subclasses with effector functions revealed strong relationships between HIV-specific IgG3 subclass levels and nearly all effector functions uniquely among the ECs . Correlations observed for IgG1 likewise suggest that beyond IgG3 , qualitatively superior IgG1 antibodies bearing the capacity to drive polyfunctional antibody responses were also induced . In some cases , weakly negative relationships were observed between IgG subclass responses and effector function , further demonstrating that higher antibody titers do not necessarily drive enhanced functionality and that qualitative differences in subclass profiles may play a critical role in driving more effective antibody activity and achieving potent viral suppression . Based on this observation , and because the formation of immune complexes is required to trigger Fc-effector function , we examined the effect of subclass ratios on antibody functionality . Independent of overall titer , elevated relative levels of IgG2 and IgG4 were strongly negatively associated with antibody functionality across all subjects ( Fig 4B ) , supporting previous observations of the potentially inhibitory activity of these less-functional subclasses [16 , 20] and further illustrating the critical nature of qualitative antibody differences in driving a broader array of Fc-effector functions that may enable more robust control of viral replication . To begin to establish whether consistent relationships between subclass and IgG activity could be identified when overall response level and subclass distribution were considered across all subject groups , we built models of polyfunctional activity using a generalized linear model machine learning method [23] . In this effort , the subclass response data was used to train a classifier to discriminate between subjects with either poly- or mono-/non-functional antibody responses in the setting of fivefold cross-validation . The resulting models predicted polyfunctional class significantly better than when class assignments were permuted ( balanced accuracy = 0 . 65 ±0 . 02 vs . permuted balanced accuracy = 0 . 49 ±0 . 02; p<1x10-15 ) and , thus , reliably capture the quantitative impact of subclass distribution and levels on antibody polyfunctionality . Consistent with a previous study of RV144-induced antibodies [20] , IgG3/1 responses made strong positive contributions to the models , whereas IgG2/4 responses were associated with reduced activity in models of antibody polyfunctionality ( Fig 4C ) . Importantly , despite the relatively lower levels of IgG2/3/4 responses as compared to IgG1 , these subclasses made strong contributions to polyfunctional classification . These results are consistent with the finding that IgG4 can negatively impact activity and that IgG3 can positively impact activity , despite low titer , which were experimentally confirmed in polyclonal samples from RV144 by subclass depletion experiments [16] . Collectively , these models further support the importance of antibody quality and subclass composition in defining the functional profile of polyclonal sera .
Overall , despite lower activity and titer , coordinated humoral immunity was uniquely present among ECs and associated with virus-specific IgG3/1 responses and the absence of IgG2/4 responses . Functional coordination was lost in the setting of viremia , but appeared to be partially restored by antiretroviral therapy in association with the recuperation of enhanced IgG1 functionality . While it is unclear whether these functions are induced by the same antibodies or through a network of functionally tuned B cells , these data suggest that qualitatively superior IgG3/1 antibodies may collaborate to broadly direct the antiviral capacity of diverse local innate immune cells to suppress viremia . This study provides critical insights into the features of highly functional IgG3/1-biased antiviral immunity that may contribute to durable control of the HIV reservoir , whether achieved by vaccination or passive transfer . In doing so , it reinforces findings from effective human [1 , 15 , 16] and NHP [17 , 21] vaccines regarding the potential significance of harnessing polyfunctional antibodies to prevent infection and thus highlights the contribution that polyfunctional antibody responses may make to both HIV-1 prevention and therapy .
187 HIV-positive subjects , balanced for sex and age , were analyzed for this study , including 50 Elite Controllers [12] ( <50 copies RNA/ml , EC ) , 64 Viremic Controllers ( 50–2000 copies of RNA/ml , VC ) , 45 HIV-positive patients on antiretroviral therapy ( ART ) ( <50 copies RNA/ml , Chronic Treated , CT ) , and 38 untreated HIV-positive patients ( >50 copies RNA/ml , Chronic Untreated , CU ) . Controllers were chosen from a cohort of HIV-1-infected individuals that has been described previously[12] . EC were defined as subjects with plasma HIV RNA levels <50 or <75 copies/ml based on a minimum of 3 determinations of plasma HIV RNA spanning at least a 12-month period in the absence of anti-retroviral therapy . IgG was purified from plasma samples using the Melon Gel IgG Spin Purification Kit ( Thermo Scientific ) . The study was reviewed and approved by the Massachusetts General Hospital Institutional Review Board , and each subject gave written informed consent . HIV-specific phagocytic activity was assessed using a flow cytometry-based phagocytic assay as described previously [18 , 19] . Briefly , fluorescent , streptavidin-microspheres were coated with biotinylated gp120 SF162 protein ( Immune Technology ) , and the ability of purified IgG antibodies to drive uptake by the monocytic THP-1 cells was assessed by flow cytometry . Antibody-dependent complement deposition was assessed by measurement of complement component C3b on the surface of target cells [17] . CD4-expressing target cells were pulsed with gp120 SF162 ( 60 mg/ml ) , and incubated with antibodies . Purified IgG was combined with pulsed or unpulsed target cells and freshly harvested HIV negative donor plasma diluted with veronal buffer 0 . 1% gelatin ( 1:10 dilution ) to allow for complement deposition . Replicates using heat inactivated donor plasma were used as negative controls . Cells were incubated for 20 min at 37°C , then washed with 15 mM EDTA in PBS . Complement deposition was detected by staining for C3b-FITC ( Cedarlane ) . Cells were fixed and the proportion of target cells with C3b-FITC deposition was analyzed by flow cytometry . An adaptation of the rapid fluorometric ADCC ( RFADCC ) assay[44] was used to assess NK-cell mediated target cell killing . In brief , the CEM-NKr T lymphoblast cell line was labeled with the intracellular dye carboxyfluorescein diacetate succinimidyl ester CFSE and the membrane dye PKH26 and then pulsed with gp120 SF162 protein ( 60 μg/ml ) . NK cells were enriched directly from healthy donor whole blood by negative selection using RosetteSep ( Stem Cell Technologies ) . Purified IgG were added to the labeled CEM-NKr cells and incubated with NK cells for 4 hr at 37°C . The 1:5 target to effector cell mix was fixed , and the proportion of lysed cells ( those that maintained membrane expression of PKH26 but had lost intracellular CFSE ) was determined by flow cytometry . An assay to determine the expression of surface CD107a and intracellular production of IFN-γ and MIP-1β was performed by pulsing the CEM-NKr CCR5+ T lymphoblast cell line with gp120 SF162 ( 60 μg/ml ) , as previously described [16] . NK cells were isolated from whole blood from healthy donors using negative selection with RosetteSep ( STEMCELL Technologies ) , then combined with CEM-NKr cells at a ratio of 5:1 . Purified IgG , anti–CD107a–phycoerythrin ( PE ) –Cy5 ( BD ) , brefeldin A ( 10 mg/ml ) ( Sigma ) , and GolgiStop ( BD ) were added for 5 hours at 37°C . The cells were then first stained for surface markers using anti–CD16–allophycocyanin ( APC ) –Cy7 ( BD ) , anti–CD56-PE-Cy7 ( BD ) , and anti–CD3–Alexa Fluor 700 ( BD ) and then stained intracellularly with anti–IFN-γ–APC ( BD ) and anti–MIP-1β–PE ( BD ) using Fix and Perm A and B solutions ( Invitrogen ) . The cells were then fixed in 4% paraformaldehyde and analyzed by flow cytometry . NK cells were defined as CD3-negative and CD16- and/or CD56-positive . A customized multivariate multiplex assay was utilized to characterize the subclass of HIV-specific antibodies , as previously described [45] . Responses against HIV gp120 from SF162 are reported since this was the specific antigen utilized in functional assessments . HIV-IG ( NIH AIDS Reagent Program ) and pooled HuIgG from HIV negative donors ( Sigma ) were used as positive and negative controls . Comparative analyses of antibody properties between subject groups were performed by ANOVA in GraphPad Prism with corrections for multiple comparisons applied as described in figure legends . Spearman correlation coefficients were calculated with a two-tailed p values with 95% confidence intervals in either GraphPad Prism or using the R software package[46] , version 3 . 1 . 2 , again , with statistical tests applied as described in figure legends . Predictive models of polyfunctional activity were built using the Glmnet R package for generalized linear models [23] . Polyfunctional activity was determined by first discretizing functional assay measurements into high/low activity using a median split , then counting the number of assays in which each subject had high activity . Subjects with high functional activity in two or more functions were classified as polyfunctional , and those high in one or none , as non-polyfunctional . A classification model was trained using antibody subclass profile data at a Ridge regression elastic net setting of zero , and used to determine the coefficient weight of each IgG subclass assessment contributing to the model . Predictive accuracy and robustness was assessed with 250 iterations of 5-fold cross validation , and compared to analogous results from 250 iterations of 5-fold cross validation with polyfunctional class labels randomly permuted . | A small fraction of HIV-infected subjects mount immune responses that are able to suppress viral replication such that virus cannot be detected in the blood . Understanding how these individuals , known as elite controllers , achieve this outcome may provide a model for strategies to treat or prevent HIV infection . We investigated whether differences in virus-specific antibodies were associated with effective viral suppression . In contrast to other HIV-infected subject groups , antibodies from elite controllers were able to harness the potent anti-viral activities of a wide range of innate immune cells including natural killer cells and phagocytic cells . These effective antibody responses were linked to the presence of different types of antibodies , specifically , functionally potent IgG3 and IgG1 antibodies . Our results indicate that either treatment with or vaccines that are able to drive generation of potent IgG3 and IgG1 antibodies able to recruit the pathogen clearance mechanisms of diverse effector cell types may hold promise in efforts aimed at achieving durable control of viral replication , sometimes described as functional cure of HIV-1 infection . | [
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] | [] | 2016 | Polyfunctional HIV-Specific Antibody Responses Are Associated with Spontaneous HIV Control |
Hereditary spastic paraplegias ( HSPs ) are characterized by progressive weakness and spasticity of the legs because of the degeneration of cortical motoneuron axons . SPG15 is a recessively inherited HSP variant caused by mutations in the ZFYVE26 gene and is additionally characterized by cerebellar ataxia , mental decline , and progressive thinning of the corpus callosum . ZFYVE26 encodes the FYVE domain-containing protein ZFYVE26/SPASTIZIN , which has been suggested to be associated with the newly discovered adaptor protein 5 ( AP5 ) complex . We show that Zfyve26 is broadly expressed in neurons , associates with intracellular vesicles immunopositive for the early endosomal marker EEA1 , and co-fractionates with a component of the AP5 complex . As the function of ZFYVE26 in neurons was largely unknown , we disrupted Zfyve26 in mice . Zfyve26 knockout mice do not show developmental defects but develop late-onset spastic paraplegia with cerebellar ataxia confirming that SPG15 is caused by ZFYVE26 deficiency . The morphological analysis reveals axon degeneration and progressive loss of both cortical motoneurons and Purkinje cells in the cerebellum . Importantly , neuron loss is preceded by accumulation of large intraneuronal deposits of membrane-surrounded material , which co-stains with the lysosomal marker Lamp1 . A density gradient analysis of brain lysates shows an increase of Lamp1-positive membrane compartments with higher densities in Zfyve26 knockout mice . Increased levels of lysosomal enzymes in brains of aged knockout mice further support an alteration of the lysosomal compartment upon disruption of Zfyve26 . We propose that SPG15 is caused by an endolysosomal membrane trafficking defect , which results in endolysosomal dysfunction . This appears to be particularly relevant in neurons with highly specialized neurites such as cortical motoneurons and Purkinje cells .
Hereditary spastic paraplegias ( HSPs/SPGs ) are a heterogeneous group of neurodegenerative movement disorders , which present with progressive weakness and spasticity of the legs . The unifying neuropathology is a time- and length-dependent degeneration of cortical motoneuron axons . Whereas in pure HSP other cells of the central nervous system are usually spared , neurodegeneration in complex HSP is more widespread and results in additional clinical symptoms . The age at onset and the course of disease are highly variable [1]–[3] . The clinical variability is mirrored by more than 50 spastic paraplegia gene loci , characterizing HSP as a genetically highly heterogeneous disease . HSP is therefore considered a model disease for unraveling the various requirements for long-term axon survival [4] . SPG15 is a complex autosomal recessive form of HSP associated with mutations in ZFYVE26 [5] . In addition to the spastic gait disorder , patients also suffer from progressive thinning of the corpus callosum , cognitive impairment , cerebellar ataxia , Parkinsonism , bladder dysfunction , and macular degeneration [5] , [6] . However , there is considerable variability of the clinical presentation between affected individuals from different families and even within families [5]–[7] . The ZFYVE26 gene encodes the 285 kD protein ZFYVE26 ( also called SPASTIZIN or FYVE-CENT ) that is predicted to contain a coiled-coil and a FYVE domain [5] . Coiled-coil domains often mediate protein-protein interactions [8] , whereas FYVE domains target proteins to intracellular membranes enriched for phosphatidylinositol 3-phosphate [9] , such as endosomal membranes . In agreement with this prediction , a GST fusion protein of the FYVE domain of ZFYVE26 bound to phosphatidylinositol 3-phosphate in vitro [10] . In HeLa cells , however , no co-localization with endosomes was found for ZFYVE26 . Instead , it was described to localize to centrosomes and to play a crucial role in mitosis , as knockdown of ZFYVE26 resulted in a defect of cytokinesis [10] . From the clinical presentation SPG15 cannot be distinguished from SPG11 , which is caused by mutations in SPATACSIN , also a protein of largely unknown function [11] . In zebrafish , the knockdown of either Zfyve26/Spastizin or Spatacsin caused motor impairment and abnormal branching of spinal cord motoneurons at the neuromuscular junction [12] . As the partial knockdown of either protein did not result in an overt phenotype , but the partial depletion of both proteins at the same time caused motor impairment , it was further concluded that both proteins might be involved in the same cellular pathway [12] . Indeed , ZFYVE26/SPASTIZIN co-immunoprecipitated with SPATACSIN as well as the three other largely uncharacterized proteins C20orf29 , DKFZp761E198 , and KIAA0415 [13] . By phylogenetic and structure prediction analyses these proteins were recently identified as subunits of a new adaptor protein 5 ( AP5 ) complex , which is proposed to be involved in cargo trafficking in the endolysosomal compartment [14] . In accordance AP5 , ZFYVE26 , and SPATACSIN were shown to co-localize with lysosomal markers in HeLa cells [15] . In this cell type the siRNA mediated knockdown of either members of the AP5 complex [14] , SPATACSIN , or ZFYVE26 [15] resulted in the formation of early endosome clusters positive for the cation-independent mannose 6-phosphate receptor . To gain deeper insight into the physiological function of the AP5 complex-interacting protein ZFYVE26 and to elucidate the pathophysiology of SPG15 we disrupted the Zfyve26 gene in mice . Knockout mice developed a progressive spastic gait disorder closely resembling SPG15 disease . Preceding the loss of cortical motoneurons and Purkinje cells , we detected pathological accumulations of autofluorescent , electron-dense material in lysosomal structures of Zfyve26-deficient neurons . The data suggest that Zfyve26 plays a crucial role in the trafficking within the endolysosomal pathway of specialized neurons .
To characterize the protein encoded by the Zfyve26 gene we immunized rabbits either against an N-terminal or C-terminal epitope of Zfyve26 and affinity-purified the resulting antisera . In agreement with the predicted molecular mass of Zfyve26 the anti-C-terminus antibody was reactive with a 285 kD polypeptide in a variety of tissues such as brain , liver , lung , and kidney ( Fig . 1A ) . The anti-N-terminus antibody recognized the 285 kD Zfyve26 protein as well ( Fig . 2C ) . Since both the anti-N- and anti-C-terminus antibodies did not detect endogenous Zfyve26 in immunofluorescence studies , we next performed non-radioactive in situ hybridizations to study the expression of Zfyve26 transcript abundance in the brain in more detail . No signal was detected with the sense control ( Fig . 1B ) . With the antisense probe Zfyve26 transcripts were broadly expressed in the brain ( Fig . 1C ) including the olfactory bulb ( Fig . 1C′ ) , cortical neurons ( Fig . 1C″ ) , the hippocampus ( Fig . 1C′″ ) , the cerebellum including Purkinje cells ( Fig . 1C″″ ) , and spinal cord neurons ( Fig . 1D , D′ ) . To study the physiological role of Zfyve26 in more detail we generated Zfyve26 deficient mice by deleting exon 15 of the Zfyve26 gene ( Fig . 2A ) . Deletion of exon 15 is predicted to cause a frame-shift ( p . Val843GlyfsX10 ) . Northern blot analysis of brain tissue suggested that the aberrant transcript is subjected to nonsense-mediated mRNA decay , as no Zfyve26 transcripts were detected in homozygous knockout ( KO ) mice ( Fig . 2B ) . The absence of the 285 kD band in brain lysates prepared from knockout mice with either the antibody against the N-terminal ( Fig . 2C ) or C-terminal epitope ( Fig . 2D ) confirmed the absence of the Zfyve26 protein in the knockout . Since no additional Zfyve26-specific bands of lower size were detected with our anti-Zfyve26 antibodies raised against the anti-N-terminus of Zfyve26 in knockout compared to wild-type ( WT ) brain lysates , it can be excluded that exon 15 deletion led to the expression of a variant truncated Zfyve26 protein . Because of the close interaction between ZFYVE26 and SPATACSIN , we assessed whether disruption of Zfyve26 might affect the expression of Spatacsin . Indeed , the intensity of the band of the expected molecular mass of Spatacsin of 250 kD was reduced by roughly 40% compared to wild-type in brain lysates of Zfyve26 knockout mice ( Fig . 2E ) , whereas Spatacsin mRNA levels were comparable ( Fig . 2F ) . Zfyve26 knockout mice were viable and their survival did not differ from control littermates ( data not shown ) . Young knockout mice did not show any obvious abnormalities or altered body weight compared to wild-type littermates up to 8 months of age . At 16 months of age , however , the body weight of knockout mice was reduced ( 17% for male knockout mice; Fig . 3A ) . Moreover , in the Morris water maze paradigm performed at 5 months of age time and distance traveled to detect the hidden platform did not differ between genotypes ( Fig . 3B , C ) . At 12 months of age Zfyve26 knockout animals displayed a progressive gait disorder and motor deficits , as quantified by measuring the foot-base-angle ( FBA ) at toe-off positions of the hind-paws ( Fig . 3D–F and movie S1 and movie S2 ) . In 16-month-old knockout mice the foot-base-angle was decreased to values around 50° in contrast to values around 75° in wild-type mice . The motor deficits were accompanied by a progressive decline in the beam walking performance ( Fig . 3G ) . Knockout mice already had a tendency to fall more often than their wild-type littermates at 8 months of age . The number of falls as a correlate of impaired motor coordination was significantly increased at 16 months , when knockout mice fell off the beam in about 1 of 3 trials ( Fig . 3G ) . At that age knockout mice displayed an abnormal posture with kyphosis of the spine . Finally , Zfyve26 knockout mice also suffered from dysfunction of the bladder , as evident from an enlarged bladder at post mortem analysis after 16 months of age ( data not shown ) . Importantly , analysis of different brain structures at 2 months of age did not reveal any differences between genotypes , thus brain development appears not to be grossly impaired by disruption of Zfyve26 . In line with a neurodegenerative disease , the brain size was significantly reduced in the knockout cohort at 16 months of age ( Fig . 4A–C ) , when knockout mice displayed severe motor deficits . To quantify cortical neurons we labeled neurons by NeuN-immunostaining at different ages ( Fig . 4D–F ) . The number of neurons in the motor cortex was not changed in Zfyve26 knockout mice at 2 or 8 months of age ( data not shown ) , in 16-month-old knockout mice , however , the number of neurons in cortical layers V and VI was significantly reduced ( Fig . 4F ) . Neuron loss was accompanied by activation of astrocytes as shown by the increase of GFAP-positive cells ( Fig . 4D , E and S1A , B ) . Consistent with neuron loss being restricted to deep cortical layers V and VI , astrogliosis predominantly occurred in layers V and VI ( Fig . 4D , E ) and was not yet observed at 2 months of age ( data not shown ) . As the cerebellum plays a key role for motor coordination , we assessed whether the neurodegenerative process also affects the cerebellum . In accordance with the ataxic gait disorder , Purkinje cells were strongly reduced to 26% of controls in 16-month-old Zfyve26 knockout mice ( Fig . 4G–I ) . Similarly to the cortex , the Purkinje cell loss was accompanied by a marked astrocytosis of the cerebellum ( Fig . 4G–H and S1E , F ) . Neither neurodegeneration nor obvious activation of astrocytes were observed in the hippocampus ( Fig . S1I , J ) or the olfactory bulb ( Fig . S1M , N ) . Moreover , we did not observe a thinning of the corpus callosum in 16-month-old knockout mice ( Fig . S2A , B ) . At 8 months of age we noted ongoing axonal degeneration in the corticospinal tract of knockout mice , which was not yet observed at 2 months of age ( Fig . S2C–F ) . At 16 months of age , when cortical motoneurons were already reduced , large diameter axons were almost absent from horizontal lumbar spinal cord sections of knockout mice ( Fig . 4J–K ) . The ultrastructure of a degenerating axon is shown in Fig . 4L . At that age we also noted a clear activation of astrocytes in the spinal cord , mainly in the white matter ( Fig . S1Q , R ) . The number of neurons in the gray matter of the spinal cord appeared to be normal ( data not shown ) . To assess whether disruption of Zfyve26 affects axon outgrowth , we cultured embryonic motoneurons of both genotypes . Under these conditions the overall survival of motoneurons was not affected ( data not shown ) . After 4 days in culture the length of the axons identified by immunoreactivity for the axonal marker protein Tau ( Fig . 4M ) was measured . The length of the outgrowing axons ( Fig . 4N ) as well as the bidirectional axonal transport rate of mitochondria ( Fig . S3A , B ) were significantly reduced in Zfyve26 knockout motoneurons . Axonal branching , however , was not altered upon disruption of Zfyve26 ( Fig . 4O ) . At 2 months of age we first noted the accumulation of autofluorescent intracellular material ( emission wavelength between 460 and 630 nm ) in Purkinje cells of knockout mice compared to wild-type ( WT ) mice ( Fig . 5A , E ) . At 16 months of age autofluorescent material was present in Purkinje cells of both genotypes , however , in knockout tissues the particles were more frequent and larger , both in deep cortical layers ( Fig . S4A , C ) as well as in Purkinje cells ( Fig . S4E , G and Fig . 5B , F ) , i . e . the sites of ongoing neuronal loss . In addition to differences in size and number , the localization of autofluorescent deposits appeared to be altered in Zfyve26 knockout neurons and extended to atypical subcellular regions including the dendrites of Purkinje cells . A moderate increase of autofluorescent material was also observed in brain regions not affected by neuron loss like the hippocampus ( Fig . S1K , L ) or the olfactory bulb ( Fig . S1O , P ) . Autofluorescent particles observed in Zfyve26 knockout mice corresponded with deposits stained positive with Sudan Black ( Fig . S4 ) , a dye that predominantly stains lipopigments . Ultrastructural analyses revealed that the large deposits either consisted of smaller particles of variable electron density surrounded by membranes ( arrowheads , Fig . 5H ) , which looked different from regular lipofuscin particles ( Fig . 5C , G , black arrows in Fig . 5D , H ) or represented larger structures of variable electron density enclosed by a membrane ( Fig . 5I ) . In addition to lysosomal vesicles of normal appearance ( Fig . 5J , K ) , in knockout brains some lysosomal structures were reminiscent of fingerprint bodies ( Fig . 5L ) as e . g . observed in juvenile neuronal ceroid lipofuscinosis [16] . To investigate the identity of the autofluorescent lipopigment-like deposits , cerebellar sections from 10-month-old mice of both genotypes were stained for different subcellular marker proteins . A spectral analysis was performed to distinguish the spectrum of the respective labeled compartment from the autofluorescence of the material by a linear unmixing algorithm [17] , [18] . Importantly , the autofluorescent deposits rarely co-localized with EEA1 ( Fig . 6A–B′″ ) , a marker for early endosomes , the cis-Golgi compartment marker Giantin ( Fig . S5A–B′″ ) , or late endosomal 300 kD mannose 6-phosphate-receptor ( M6PR ) ( Fig . S5C–D′″ ) . Instead , the majority of autofluorescent lipopigment material was found to be co-localized in enlarged Lamp1-positive organelles representing endolysosomal structures , shown independently with two different Lamp1 antibodies ( Fig . 6C–D′″ and Fig . S5E–F′″ ) . To examine the subcellular localization of Zfyve26 , we followed two different approaches . First , a ZFYVE26-GFP fusion construct was expressed in mouse 3T3 cells . The fusion protein localized to a limited number of punctate structures centered around the nucleus ( Fig . 7A , D ) . These Zfyve26-GFP positive structures showed a considerable spatial co-staining with early endosomal EEA1-positive membranes ( 50±10%; Fig . 7A–C ) that have been reported to contain phosphatidylinositol 3-phosphate [9] . There was also some co-staining with Lamp1 ( 8±5%; Fig . 7D–F ) . To test whether the FYVE domain is crucial for the proper subcellular targeting of the full-length ZFYVE26 protein , we introduced a point mutation into the FYVE domain ( p . His1834Ala ) . This mutation resulted in a diffuse cytosolic distribution of the protein indicating that this mutation is sufficient to disrupt the typical localization of ZFYVE26 ( Fig . 7G–I ) . Moreover , incubation of cells with wortmannin , a known inhibitor of phosphatidylinositol-3-kinases , resulted in a more diffuse distribution of the ZFYVE26-GFP signal accompanied with the loss of EEA1-positive vesicular structures ( Fig . 7J–L ) . There was no overlap of ZFYVE26-GFP with γ-adaptin , a marker for clathrin-coated structures at the TGN and vesicle there of ( Fig . S6A–C ) . Some overlap was observed with the M6PR ( Fig . S6D–F ) . Although reported previously [10] , we could not detect co-localization with γ-tubulin , which labels centrosomes ( Fig . S6G–I ) . In our second approach , the localization of endogenous Zfyve26 in the mouse brain was analyzed by subcellular fractionation . Immunoblot analysis of these fractions detected a 285 kD polypeptide band representing Zfyve26 predominantly in the light membrane fraction , which was also positive for EEA1 and the AP5M1/μ5 subunit of the newly discovered AP5 complex ( Fig . 7M ) . No Zfyve26 immunoreactive material was found in Lamp1-enriched heavy membrane fractions ( Fig . 7M ) . The light membrane fraction isolated from Zfyve26 knockout brains lacked the 285 kD band . Because of the endolysosomal localization of ZFYVE26 , we studied basic endolysosomal function in mouse embryonic fibroblasts ( MEFs ) isolated from wild-type and knockout embryos ( embryonic day E13 . 5 ) . Stainings of MEFs from either genotype did not reveal gross structural abnormalities in the distribution of Lamp1 ( Fig . S7A , D ) , Cathepsin D ( CtsD ) ( Fig . S7B , E ) , EEA1 ( Fig . S7G , J ) , the M6PR ( Fig . S7H , K ) , or the AP5Z1/ζ subunit ( Fig . S7M , N ) . Western blot analyses of the lysosomal protease CtsD and Lamp1 showed similar amounts and processed CtsD forms in wild-type and Zfyve26 knockout MEFs at steady state ( Fig . S8A ) . This was in agreement with normal activities of the lysosomal hydrolases in MEFs ( Fig . S8B ) . We also labeled MEFs of both genotype with [35S]-methionine and either harvested ( Fig . S8C , lanes 1 and 3 ) or chased for 5 h ( Fig . S8C , lanes 2 and 4 ) in non-radioactive medium followed by immunoprecipitation of the lysosomal protease Cathepsin Z ( CtsZ ) . The fluorography showed similar synthesis rates of the CtsZ precursor ( p ) ( Fig . S8C , lanes 1 and 3 ) . In addition the proteolytic processing to the mature ( m ) lysosomal form ( Fig . S8C , lanes 2 and 4 ) and the M6PR-mediated sorting efficiency in the trans Golgi network shown by the amounts of CtsZ precursor in the medium after 5 h chase ( Fig . S8C , lanes 5 and 6 ) were not affected . Moreover , both the internalization and the proteolytic processing of the arylsulfatase B ( ASB ) precursor form by lysosomal proteases were comparable in wild-type and knockout MEFs ( Fig . S8D ) . Taken together these data indicate that in MEFs the transport of lysosomal enzymes along the biosynthetic and the endocytic pathway are not affected by the loss of Zfyve26 . Of course , the cellular pathology which finally results in the accumulation of autofluorescent material and neuron loss can be neuron-specific and may be time-dependent . To study whether alterations of the endolysosomal compartment are present in the brain before neurodegeneration starts , we performed subcellular fractionations of brain lysates from 20-day-old wild-type and knockout mice . Confirming that the endolysosomal system is compromised upon disruption of Zfyve26 , the Lamp1-positive compartment was shifted towards fractions of higher densities compared to wild-type before ( Fig . 8A , B ) and after the appearance of large autofluorescent deposits ( Fig . 8C ) . No shift was detected for the AP5M1/μ5 subunit ( Fig . 8D ) . Lamp1 and EEA1 levels were unchanged in brain lysates of 16 month old knockout mice . Only Cathepsin D was significantly increased ( Fig . 8E ) . Furthermore , increases in the overall activities of β-hexosaminidase ( Fig . 8F ) and β-galactosidase ( Fig . 8G ) in extracts of 16-month-old Zfyve26 knockout mouse brains suggested an altered composition/function of lysosomes upon disruption of Zfyve26 .
In addition to progressive spastic paraplegia , which usually starts within the first decades of life , SPG15 patients also suffer from ataxia , retinopathy , bladder incontinence , progressive cognitive decline , and atrophy of the corpus callosum and the cerebellum [5] , [7] , [19] . While it is clear that HSP/SPG15 is associated with mutations in the ZFYVE26 gene , the cellular pathomechanisms of the disease were largely unknown . Here we demonstrate that Zfyve26-deficient mice develop a progressive gait disorder starting at 12 months of age , which is further complicated by bladder dysfunction and ataxia . Corresponding with the progressive gait disorder , we observed a degeneration of axons within the corticospinal tract at 8 months of age , a finding in line with mouse models of other types of HSP [20]–[22] . This degeneration mainly affected large diameter axons of the lumbar corticospinal tract . At 16 but not at 8 months of age we also observed a loss of neuronal somata in cortical layers V/VI , where the large projection motoneurons reside . This suggests that the cellular pathology is not restricted to motoneuron axons , but also affects their somata in the course of the disease . This is in sharp contrast to mouse models of pure HSP like SPG4 , SPG7 or SPG31 , where no cortical motoneuron loss had been reported [20]–[22] and corresponds with reports from SPG15 patients , which also display variable degrees of brain atrophy [5] , [6] , [19] . Moreover , neurodegeneration in Zfyve26 knockout mice was not restricted to cortical motoneurons , but , like in SPG15 patients , also included the cerebellum , where Purkinje cells were almost lost in aged knockout mice . No degeneration was found in the hippocampus or the olfactory bulb . Thus , it appears that large elaborate neurons like cortical motoneurons and Purkinje cells are particularly sensitive to the disruption of Zfyve26 . As Purkinje cells play a critical role for motor coordination , the loss of Purkinje cells at least contributes to the cerebellar ataxia phenotype observed in both Zfyve26 knockout mice and SPG15 patients . Although axon outgrowth of cultured embryonic Zfyve26 knockout motoneurons was delayed , young Zfyve26 knockout mice did not show any obvious phenotypes or motor impairment and brain and spinal cord of knockout mice did not reveal gross structural abnormalities at 2 months of age . Moreover , hippocampal spatial learning as assessed by the Morris water maze was not impaired before onset of the motor phenotype . This suggests that Zfyve26 is largely dispensable for normal brain and spinal cord development in mice , though knockdown studies in HeLa cells suggested alterations in cytokinesis [10] and knockdown studies in zebrafish resulted in abnormal branching of spinal cord motor neurons [12] . In Zfyve26 knockout mice , however , axonal branching of cultured motoneurons was not altered . Taken together our mouse data are fully consistent with the view that HSP generally manifests as a neurodegenerative rather than a neurodevelopmental disease [23] . The very similar phenotypes of aged Zfyve26 knockout mice and SPG15 patients further confirm that SPG15 is caused by Zfyve26 loss-of-function and that Zfyve26-deficient mice are a valid model for the complex form of HSP . What is the cellular pathology behind this neurodegeneration ? Starting around 2 months of age we observed the progressive accumulation of autofluorescent intracellular material in neurons of Zfyve26 knockout mice . Notably , autofluorescent material was also detected in the retina of SPG15 patients suffering from macular defects [5] . The lipofuscin-like particles in Zfyve26-deficient mice were stained by Sudan Black , which particularly labels lipopigments [24] and which thus appear to be a major constituent of the deposits . At the ultrastructural level , the deposits were revealed as abnormal conglomerates of vesicular material of variable electron density and shape . Lipofuscin is a common finding in aged post mitotic neurons and is considered as non-degradable intralysosomal material [25] . Indeed , the large autofluorescent deposits in knockout neurons , which we never observed in wild-type tissues , were intensely labeled by the lysosomal marker Lamp1 and differed drastically in terms of time of onset , localization , and size compared to normal lipofuscin particles . Our biochemical analysis showed that Lamp1-positive membrane-compartments of unusually high density were already formed in pre-symptomatic young mice . In accordance with a progressive alteration of the endolysosomal compartment we observed an increase in the activity of β-hexosaminidase or β-galactosidase in brain lysates of aged knockout mice . In brain lysates from 16 month-old knockout mice levels of Lamp1 and the early endosome marker EEA1 were unchanged , whereas Cathepsin D levels were increased . Similar increases in the activity of specific enzymes have been reported for other neurodegenerative lysosomal disorders like e . g . neuronal ceroid lipofuscinosis [26] . Although lipofuscin is generally considered as harmless inert intracellular debris , it is increasingly suspected to interfere with various cellular functions and to thereby promote age-related pathologies [25] . Due to binding of transition metals , such as iron and copper , lipofuscin is for example considered to sensitize cells to oxidative stress [27] . What causes the pathological accumulation of non-degradable material in Zfyve26-deficient neurons ? To get an idea we readdressed the subcellular localization of Zfyve26 , which was still controversial . Whereas ZFYVE26 has been reported to localize to centrosomes with recruitment to the midbody during cytokinesis [10] , others reported localization to early endosomes and the endoplasmic reticulum [5] , or even the nucleus [28] . Part of the apparent controversy is most likely owed to low levels of expression and to the lack of specific and sensitive antibodies , which reliably detect endogenous Zfyve26 . It has been reported that in HeLa cells stably expressing ZFYVE26-GFP , GFP signals localized to puncta with a substantial overlap to Lamp1 or a lysotracker-positive compartment [15] . Upon transient overexpression of ZFYVE26-GFP in 3T3 cells or COS7 cells we only observed a co-localization with a minor population of Lamp1-positive structures , whereas the majority of ZFYVE26 co-localized with the endosomal marker EEA1 . Though we cannot exclude that the protein is shifted to an EEA1-positive compartment upon overexpression , our localization is supported by our fractionation studies and is in good agreement with the fact that FYVE domains target proteins to phosphatidylinositol-3-phosphate-enriched membranes like early endosomes [9] , [29] . Indeed , either disruption of the FYVE domain by site-directed mutagenesis or depletion of phosphatidylinositol-3-phosphate by wortmannin drastically altered the localization of ZFYVE26-GFP . How can a predominantly endosomal localization of Zfyve26 be reconciled with aberrant endolysosomal material in aged Zfyve26 knockout mice ? It has been shown that Zfyve26 co-immunoprecipitated with the AP5 components C20orf29 ( AP5S1/σ5 ) , KIAA0415 ( AP5Z1/ζ ) , C14orf108 ( AP5M1/μ5 ) , and DKFZp761E198 ( AP5B1/β5 ) [13] , [14] . It thus seems likely that Zfyve26 plays some role in the largely unknown functions of AP5 . While the cargoes of the AP5 complex have not yet been identified , it is conceivable that defects in AP5-mediated cargo sorting manifest in impairments in membrane compartments that a ) normally represent the targets of cargo and lack this cargo in Zfyve26 loss-of-function situations or b ) represent target compartments that are loaded with missorted cargo . The siRNAs directed against either C14orf108 , the proposed AP5M1/μ5 subunit , or DKFZp761E198 , the proposed AP5B1/β5 subunit , as well as against ZFYVE26 in HeLa cells resulted in clustered , mannose 6-phosphate receptor-positive puncta in the perinuclear region , membrane compartments that may represent multivesicular bodies and thus are part of the endolysosomal trafficking pathway [14] . Although knockdown of SPATACSIN or ZFYVE26 changed the localization/distribution of AP5 in HeLa cells [15] , we did not observe any clear changes in the distribution of AP5Z1/ζ in MEFs or of AP5M1/μ5 in subcellular brain fractions . Our observation of Lamp1-positive deposits of electron-dense , autofluorescent lipopigments surrounded by membranes are well in line with defects in the trafficking from endosomes towards lysosomes . Our analysis of MEFs , which did not reveal a clear endolysosomal defect in the absence of Zfyve26 , does not preclude a defect in neurons , as the effects may be cell type- or substrate-specific and/or time-dependent . The late onset neurodegeneration in Zfyve26 knockout mice may rather point to a minor defect in the endolysosomal sorting machinery , which accumulates over time . Indeed , the increase of the enzymatic activities of the lysosomal enzymes β-hexosaminidase and β-galactosidase in brain was only noted at 16 but not at 2 months of age . The increase in Cathepsin D , β-hexosaminidase , and β-galactosidase levels/activity is not necessarily in conflict with impaired lysosomal degradation . Whether this is rather caused by an altered composition or an increased size or number of lysosomes or both is still unclear . Is it plausible that endosomal cargo sorting defects involving Zfyve26 and AP5 are the cellular basis for the progressing defects seen in aging Zfyve26 knockout mice and SPG15 patients ? A strikingly similar pathology with the accumulation of large autofluorescent deposits and loss of Purkinje cells as well as long projection fibers within the spinal cord was reported for mice deficient for phosphatidylinositol 4-kinase 2α [30] . This kinase is predominantly located in the Golgi complex and endosomes and interacts with another adaptor complex , AP3 , which targets cargo from endosomes to lysosomes [31] . Defects of the AP3 complex underlie a subtype of Hermansky-Pudlak syndrome , which is characterized by impaired function and/or biogenesis of lysosomes and lysosome-related organelles such as melanosomes and platelet dense granules . It thus results in oculocutaneous albinism , platelet storage pool deficiency , and ceroid lipofuscinosis [32] . Although the cargoes of the AP5 complex have not yet been identified it thus seems plausible that defects in endolysosomal sorting , which can impact on a variety of cellular functions including axonal transport or lysosomal function , result in axon degeneration and neuronal death . Indeed , defects in the AP4 complex , which is involved in transport between the trans-Golgi network and endosomes , cause neuroaxonal degeneration in SPG47 , SPG50 , SPG51 , and SPG52 with early onset severe spasticity [33] . The long axonal projections of motoneurons and the uniquely complex dendritic arbors of Purkinje cells , respectively , may render these cells particularly vulnerable to defects of intracellular trafficking .
A clone isolated from a 129/SvJ mouse genomic λ library ( Agilent Technologies , USA ) was used to construct the targeting vector . A 13 . 4 kb fragment was cloned via NotI and BamHI into the pKO-V901 plasmid ( Lexicon Genetics , USA ) with a phosphoglycerate kinase ( pgk ) promoter–driven diphtheria toxin A cassette . A loxP site and an additional BamHI restriction site were placed at the EcoRV site into intron 14 and a pgk promoter–driven neomycin resistance cassette flanked by frt sites and an additional loxP site at the KpnI site into intron 15 ( Fig . 2A ) . The construct was linearized with NotI and electroporated into R1 mouse embryonic stem ( ES ) cells . Neomycin-resistant clones were analyzed by Southern blot using BamHI and an external 782 bp probe ( Mus musculus chr 12: 80 , 383 , 750–80 , 384 , 531 ) . Two correctly targeted ES cell clones were injected into C57BL/6 blastocysts to generate chimeras . Chimeric mice were mated to a cre-deleter mouse strain to remove exon 15 and the selection cassette [34] . Studies were performed in a mixed 129SvJ/C57BL/6 background in the F4 and F5 generation . For PCR genotyping on DNA isolated from tail biopsies , the primers f: 5′-CTTGTGTATTTTGCATAGGTGC-3′ , r: 5′-TGACACTGAATGTTAAGA-3′ , and del: 5′-TTCTGGAAGCGTCTGTAAAG-3′ were used in a single PCR mix . The primer pair f/r amplified a 187-bp wild-type allele , and the primer pair f/del a 250-bp KO allele . Mice were housed in a 12 h light/dark cycle and fed on a regular diet ad libitum . The Zfyve26 probe was cloned by PCR from a mouse brain cDNA using the forward primer 5′-AGGGAGTCTGAGTGCTG-3′ and the reverse primer 5′-GACTCTCAAGGCTGCTG-3′ . The probe to detect Spatacsin transcripts was cloned with the forward primer 5′-GCAAACACTAACACACACTCCGCAGTGG-3′ and the reverse primer 5′-GCAACACCAGCACTAGATCCTGGC-3′ . The Northern blot analysis was performed as described previously [35] . in situ hybridizations were carried out on 20 µm sagittal cryosections of brain or transversal cryosections of spinal cord from 2-month-old wild-type mice using digoxigenin-labeled antisense and sense RNA probes as described [36] . The riboprobes covered either exon 16 ( cDNA positions 2922–3683 ) or exons 22–25 ( cDNA positions 4404–4847 ) of the Zfyve26 transcript ( accession number: ENSMUST00000021547 ) . For overexpression of the ZFYVE26-GFP fusion protein ( ZFYVE26-GFP ) , a human full length cDNA clone ( DKFZp781H1112Q , RPDZ ) was PCR-amplified and inserted via BglII and BamHI into the pEGFP-N1 vector ( Clontech laboratories , USA ) . Mutations in the clone were corrected by PCR-based mutagenesis to obtain a cDNA corresponding to the human reference sequence ENSHU004078079 . The point-mutation p . His1834Ala in ZFYVE26-GFP was inserted by PCR-based mutagenesis . The following primers were used for PCR mutagenesis: KpnI_f: 5′-GGTACCGGATGAGACTGAG-3′ , H_in_A_f: 5′-CCATGTTTAACAGGCGTCATGCTTGTCGCCGCTGTGGCCGG-3′ , H_in_A_r: 5′-CCGGCCACAGCGGCGACAAGCATGAGCCTGTTAAACATGG-3′ , SspI_r: 5′-AATATTCAGCACATCTACCTTG-3′ . 3T3-cells were maintained in DMEM ( Invitrogen , Germany ) supplemented with 10% fetal bovine serum , penicillin ( 100 UI/ml ) , and streptomycin ( 100 mg/ml ) . Before transfection cells were plated on coverslips and after 24 h transfected with 1 µg DNA/well in 24-well plates with lipofectamine 2000 reagent ( Invitrogen , Germany ) according to the instructions of the manufacturer . 24 to 48 h post-transfection cells were fixed in 4% para-formaldehyde at room temperature for 15 min and immunocytochemistry was performed as described in [37] . To inhibit phosphatidylinositol 3-kinase , cells were incubated with 100 nM wortmannin ( Invitrogen , Germany ) for 1 h . To quantify the degree of co-localization , at least 10 cells were imaged . The relative area of co-localization was determined by scatter plot analysis using the co-localization module of AxioVision ( Release 4 . 8 . 2 , Zeiss , Germany ) . Anti-Zfyve26 antisera were raised by immunization of rabbits against either the N-terminal epitope TSSELSTSTSEGSLSA ( residues 782–797 of mouse Zfyve26 , NP_001008550 . 1 ) or the C-terminal epitope ENELVRSEFYYEQAPS ( residues 1908–1923 of mouse Zfyve26 , NP_001008550 . 1 ) and affinity-purified as described in [38] . The following antibodies were used for immunoblotting and immunofluorescence: rabbit anti-SPATACSIN , 1∶500 , ( Protein Tech , UK ) ; mouse anti-M6PR and rabbit anti-EEA1 , both 1∶500 , ( Abcam , UK ) ; mouse anti-EEA1 , 1∶500 , ( BD Transduction laboratories , USA ) ; mouse anti-NeuN and mouse anti-GFAP , both 1∶1 , 000 , ( Millipore , USA ) ; mouse anti-γ-Adaptin and mouse anti-Calnexin , both 1∶1 , 000 , ( BD Biosciences , USA ) ; rat anti-Lamp1 ( clone CD107a ) , 1∶500 , ( BD Biosciences , USA ) ; rat anti-Lamp1 ( clone 1D4B ) , 1∶25 , ( Developmental Studies Hybridoma Bank , USA ) ; rabbit anti-γ-Tubulin , 1∶2 , 000 , ( Sigma Aldrich , USA ) ; mouse anti-Giantin , 1∶1 , 000 , ( Enzo Life Sciences , Germany ) ; rabbit anti-phospho-Tau , 1∶500 , ( Biozol Diagnostika Vertrieb GmbH , Germany ) ; mouse anti-microtubule-associated protein 2ab ( MAP2ab ) , 1∶2 , 000 , ( Acris Antibodies GmbH , Germany ) ; goat anti-CtsD ( sc6486 , Santa Cruz; USA , for Western studies ) ; rabbit anti-CtsD , 1∶100 [39] ( used for immunofluorescence studies ) ; mouse anti-α-Tubulin ( T9026 , Sigma-Aldrich , USA ) ; rabbit anti-M6PR ( kind gift of K . von Figura ) . Secondary antibodies for immunofluorescence: goat anti-rabbit , goat anti-mouse , or goat anti-rat coupled with Alexa 488 and Alexa 555 , respectively , 1∶1 , 000 , ( Invitrogen , Germany ) ; goat anti-rabbit coupled with Cy5 , 1∶1 , 000 , ( Dianova , Germany ) ; Goat anti-rat and anti-mouse Cy5 , 1∶1 , 000 , ( Jackson ImmunoResearch Laboratories , USA ) . Secondary antibodies for Western blotting: goat anti-rabbit and goat anti-mouse , both 1∶4 , 000 , ( Amersham Bioscience , UK ) ; goat anti-rat , 1∶2 , 000 , ( Santa Cruz , USA ) . Cells were harvested and lysed in 50 mM Tris/HCl pH 8 , 1 mM EDTA , 0 . 5% NP40 , 120 mM NaCl . Tissue lysates were prepared with the Ultra-Turrax T8 tissue homogenizer ( IKA-WERKE , Germany ) in homogenization buffer ( 300 mM Tris-HCl pH 8 . 8 , 5 mM EDTA , 3 mM NaF , 10% Glycerol , 3% SDS , and complete protease inhibitor ( Roche , Switzerland ) as described [40] . Homogenates were centrifuged at 1 , 500 g to remove nuclei and insoluble debris . The supernatant was either denatured at room temperature for 15 min or/and at 95°C for 5 min in Laemmli sample buffer . After separation in a 6% SDS-polyacrylamide gel electrophoresis proteins were transferred onto nitrocellulose or PVDF membranes ( Whatman , Germany ) . The Zfyve26 antibody directed against the C-terminus was used at a dilution of 1∶350 and the antibody directed against the N-terminus at a dilution of 1∶100 . Both primary antibodies were detected with a horseradish peroxidase-conjugated secondary anti-rabbit antibody ( Amersham Bioscience , UK ) and the SuperSignal Western Blot Enhancer Kit ( Thermo scientific , Germany ) . Membrane fractionations were done as described with slight modifications [41] . A brain from a 20-day-old mouse was homogenized in Buffer A ( 130 mM KCl , 25 mM Tris-HCl pH 7 . 4 , 1 mM EGTA ) including Complete protease inhibitor cocktail ( Roche , Switzerland ) and centrifuged at 1 , 000 g for 10 min . The supernatant ( 1000 g SN ) was isolated and sucrose was added to a final concentration of 15% . Following centrifugation at 3 , 000 g for 10 min the resulting supernatant ( 3000 g SN ) was diluted to a total volume of 4 . 5 ml using Buffer A containing 15% sucrose . A discontinuous sucrose gradient was generated by overlaying sucrose solutions in Buffer A: 3 ml 45% , 6 ml 30% , 4 . 5 ml of the diluted supernatant in 1 ml 5% sucrose and 2 . 5 ml 7 . 5% . The gradient was centrifuged at 100 , 000 g for 1 h . Light membranes were visible in the range of 15% and heavy membranes in the range of 35% sucrose . A discontinuous iodixanol gradient was generated by overlaying 2 . 2 ml of 15% , 12 . 5% , 10% , 7 . 5% , 5% , and 2 . 5% ( v/v ) iodixanol for light membrane fractionation and 3 . 25 ml of 25% , 23% , 21% , and 19% ( v/v ) iodixanol , all in Buffer A for heavy membrane fractionation . The light or the heavy membrane fraction were loaded at the bottom and centrifuged for 2 h at 110 , 000 g . 1 . 2 ml fractions were collected from the top , diluted to 8 ml with Buffer A and centrifuged at 130 000 g for 40 min . Pellets were resuspended in 50 µl SDS-sample buffer . For crude fractionations 1/2 brain from a 16-month-old mouse was homogenized and centrifuged as described before . 1 , 000 g supernatants were diluted to 3 ml containing 15% sucrose . A discontinuous sucrose gradient with 3 ml 55% , 2 ml 45% , 4 ml 30% , 3 ml of the diluted supernatant in 15% sucrose , and 1 ml 7 . 5% sucrose was centrifuged at 100 , 000 g for 1 h . 13 fractions were collected , precipitated in 80% ethanol and pellets were resuspended in SDS-sample buffer and analyzed by SDS-PAGE and quantitative immunoblotting based on fluorescence using a LI-COR Odyssey detection system ( LI-COR , Germany ) . Mouse embryonic fibroblasts were prepared from E13 . 5 mouse pups as described in [42] . Spinal cord motoneurons were isolated from embryonic day 12 . 5 embryos as described previously in [43] . To determine motoneuron survival neurons were counted four hours after plating . This was repeated every day for five fields of view ( 1 . 16 mm2 ) with a phase-contrast microscope ( Olympus , Germany ) . The number of initially counted cells was set 100% ( day 0 ) . The percentage of surviving cells was calculated for every day in culture . Axons of motoneurons were identified by positive anti-phospho-Tau staining , dendrites by positive anti-MAP2ab staining . The longest axonal extension was measured with the Neurolucida 8 software ( MBF Bioscience , USA ) after 4 days in culture and the number of axonal branches was counted . The results from at least four independent experiments were pooled . Enzyme activity measurements , pulse chase and endocytosis experiments were performed as described in [44] , [45] . Mitochondria were stained with Mito Tracker Green FM ( final concentration 100 nM , Invitrogen , Germany ) in living motoneurons after four days in culture for 30 min . After replacement of the medium , mitochondria were visualized with a fluorescence microscope ( Axio Observer Z1 , Zeiss , Germany ) equipped with an incubation chamber ( 37°C , 5% CO2 ) . Time-lapse images were acquired at a frequency of 15 Hz with an exposure time of 200 ms . For statistical analysis of mitochondrial movements ten independent experiments were performed . Spatial memory was assessed in a Morris water maze , consisting of circular tank ( diameter 120 cm , depth 60 cm ) filled with water at 25±1°C at a depth of 30 cm as described in [46] with some modifications . To escape from the water , the mice had to find a hidden platform ( diameter 20 cm ) submerged approximately 1 cm below the water surface . The platform was located at the center of one of the four quadrants of the pool . For efficient tracking of mice the water was colored white by the addition of 2 l milk . The maze was located in the middle of the room with prominent extra maze cues . Swim paths were recorded by a video camera . Latency , swim speed , path length , etc . were analyzed with the VideoMot2 software ( TSE Systems , Germany ) . All mice were handled and habituated to the experimental situation 2 days before training . The mice were trained to find the hidden platform , which remained at a fixed location throughout testing . Each mouse received 2 blocks per day , each with 3 trials for 7 days , with an intertrial interval of approximately 60 s . Time intervals between blocks were 4 h . The mice were placed into the pool facing the side wall at one of the 8 start positions ( N , W , S , E , NW , SW , NE , and SE; chosen randomly across trials ) and allowed to swim until they found the platform . Any mouse that failed to find the platform within 1 min was guided and placed onto the platform and was then warmed for 45 s under an infrared lamp before commencing the next trial . 24 h after the last training day a probe trial was carried out . For this purpose , the platform was removed from the pool and the mice were allowed to swim freely for 60 s . The distance and percentage of the time spent in each quadrant was analyzed . Mice were trained to walk on a horizontal 20 cm elevated plastic beam ( 1 , 000 mm long , either 38 mm for cohorts at 8 and 12 months of age or 48 mm broad at 16 months of age ) leading to their home cage ( see movie S1 and movie S2 ) . After the initial learning phase the foot-base-angle at toe-off positions of the hind-paws was measured using single video frames from recordings of beam walking mice [47] . To quantify ataxia , falls off the beam were counted . Hematoxylin and eosin ( HE ) stainings followed standard protocols ( Carl Roth , Germany ) . Sudan black staining was performed as described in [48] . Immunohistochemical analysis was done on formalin fixed , free floating sections as described previously [37] . Nuclei were stained with Hoechst-33258 ( 1∶10 , 000 , Molecular Probes , Germany ) . Purkinje cell loss and gliosis were analyzed on 40 µm sagittal brain sections using rabbit-anti-Calbindin and mouse anti-GFAP antibodies . Purkinje cell numbers were quantified on 8 µm HE stained paraffin sections on a Zeiss Axioskop 40 microscope . For statistical analysis the number of Purkinje cells per 1 , 000 µm distance along the Purkinje cell layer was counted from 3 different mice per genotype . For quantification of neurons in cortical layers NeuN immunohistochemistry was performed on 40 µm sagittal brain sections . Images of the motor cortex of sagittal sections of wild-type and Zfyve26 knockout brains were taken with a Leica TCS SP5 confocal scanning fluorescence microscope . Neurons were quantified with the cell counter plug in and the area measurement tool of ImageJ software ( W . S . Rasband , National Institutes of Health , Bethesda , USA ) . Results are presented as mean ± SEM . “n” refers to the number of sections analyzed from 3 animals per genotype . Fluorescence images were recorded on the stage of a confocal laser scanning microscope ( LSM710 , Zeiss , Germany ) . Autofluorescence and Cy5 fluorescence of the secondary antibodies were excited with the 488 nm line of an argon laser and the 633 nm line of a helium/neon laser . Fluorescence emitted from the sample was recorded with the spectral detector of the LSM710 in the wavelength range from 501–725 nm . Under these experimental conditions one can distinguish two autofluorescence components , one originating from the deposits and one from the background . The fluorescence signal recorded from the sample is a linear combination of these components and the Cy5 dye coupled to the secondary antibodies . Their contribution to the overall signal can be calculated by a linear unmixing algorithm , which optimizes the parameters of the relative contributions , so that the sum of the spectra of all components matches the recorded spectrum [17] , [18] . To visualize the results the respective fluorescence contributions are encoded by false colors with the brightness being proportional to the intensity of the respective spectral components . For semi- and ultrathin sectioning , 4 animals per genotype were perfused with 50 ml fixative ( 4% paraformaldehyde , 1% glutaraldehyde ) . Brain and spinal cord were removed and post fixed overnight at 4°C . 150 µm sagittal and coronal sections of brain and spinal cord respectively were cut with a vibratome ( Leica Microsystems , Germany ) and processed as described in [49] . For repeated experiments two-way ANOVA followed by Bonferroni post-hoc tests were used to compare between genotypes . For cortical morphology and quantitative western blot analysis Student's two-tailed t-test was used . | Hereditary spastic paraplegias ( HSPs ) are inherited disorders characterized by progressive weakness and spasticity of the legs . In HSP patients , nerve fibers connecting cortical motoneurons with spinal cord neurons are progressively lost . HSP subtype 15 ( SPG15 ) is caused by mutations in ZFYVE26 , and is characterized by additional cerebellar symptoms . We show that the Zfyve26 protein is broadly expressed in the brain . At the subcellular level Zfyve26 localizes to an intracellular compartment in the endocytic pathway from the plasma membrane to lysosomes , which is part of the degradative system of the cell . Closely resembling the human disease , mice deficient for Zfyve26 develop a progressive spastic gait disorder with cerebellar symptoms and degeneration of both neurons of the motor cortex and Purkinje cells in the cerebellum . Importantly , this degeneration is characterized by the intracellular accumulation of abnormal deposits , which stain positive for the lysosomal marker Lamp1 . As Zfyve26 has been shown to interact with the newly identified adaptor complex AP5 , which is supposed to be involved in cargo trafficking in the endolysosomal compartment , endolysosomal dysfunction may be caused by a targeting defect upon disruption of Zfyve26 . As highly specialized neurons like cortical motoneurons and cerebellar Purkinje cells degenerate , these neurons appear to be particularly dependent on proper endolysosomal function . | [
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] | [] | 2013 | A Hereditary Spastic Paraplegia Mouse Model Supports a Role of ZFYVE26/SPASTIZIN for the Endolysosomal System |
Temporally ordered multi-neuron patterns likely encode information in the brain . We introduce an unsupervised method , SPOTDisClust ( Spike Pattern Optimal Transport Dissimilarity Clustering ) , for their detection from high-dimensional neural ensembles . SPOTDisClust measures similarity between two ensemble spike patterns by determining the minimum transport cost of transforming their corresponding normalized cross-correlation matrices into each other ( SPOTDis ) . Then , it performs density-based clustering based on the resulting inter-pattern dissimilarity matrix . SPOTDisClust does not require binning and can detect complex patterns ( beyond sequential activation ) even when high levels of out-of-pattern “noise” spiking are present . Our method handles efficiently the additional information from increasingly large neuronal ensembles and can detect a number of patterns that far exceeds the number of recorded neurons . In an application to neural ensemble data from macaque monkey V1 cortex , SPOTDisClust can identify different moving stimulus directions on the sole basis of temporal spiking patterns .
Precisely timed spike patterns spanning multiple neurons are a ubiquitous feature of both spontaneous and stimulus-evoked brain network activity . Remarkably , not all patterns are generated with equal probability . Synaptic connectivity , shaped by development and experience , favors certain spike sequences over others , limiting the portion of the network’s “state space” that is effectively visited [1 , 2] . The structure of this permissible state space is of the greatest interest for our understanding of neural network function . Multi-neuron temporal sequences encode information about stimulus variables [3–8] , in some cases “unrolling” non-temporally organized stimuli , such as odors , into temporal sequences [9] . Recurrent neuronal networks can generate precise temporal sequences [10–14] , which are required for example for the generation of complex vocalization patterns like bird songs [15] . Temporal spiking patterns may also encode sequences of occurrences or actions , as they take place , or are planned , projected , or “replayed” for memory consolidation in the hippocampus and other structures [16–25] . Timing information between spikes of different neurons is critical for memory function , as it regulates spike timing dependent plasticity ( STDP ) of synapses , with firing of a post-synaptic neuron following the firing of a pre-synaptic neuron typically inducing synaptic potentiation , and firing in the reverse order typically inducing depotentiation [26–28] . Thus , the consolidation of memories may rely on recurring temporal patterns of neural activity , which stabilize and modify the synaptic connections among neurons [16–22 , 29–35] . Storing memories as sequences has the advantage that a very large number of patterns is possible , because the number of possible spike orderings grows exponentially , and different sequences can efficiently be associated to different memory items , as proposed by for instance the reservoir computing theory [36–40] . Detecting these temporal patterns represents a major methodological challenge . With recent advances in neuro-technology , it is now possible to record from thousands of neurons simultaneously [41] , and this number is expected to show an exponential growth in the coming years [42] . The high dimensionality of population activity , combined with the sparsity and stochasticity of neuronal output , as well as the limited amount of time one can record from a given neuron , makes the detection of recurring temporal sequences an extremely difficult computational problem . Many approaches to this problem are supervised , that is , they take patterns occurring concurrently with a known event , such as the delivery of a stimulus for sensory neurons or the traversal of a running track for hippocampal place fields , as a “template” and then search for repetitions of the same template in spiking activity [20 , 43 , 44] . Other approaches construct a template by measuring latencies of each neuron’s spiking from a known event , such as the beginning of a cortical UP state [5 , 45] . While this enables rigorous , relatively easy statistical treatment , it risks neglecting much of the structure in the spiking data , which may contain representations of other items ( e . g . remote memories , presentations of different stimuli , etc . ) . A more complete picture of network activity may be provided by unsupervised methods , detecting regularities , for example in the form of spiking patterns recurring more often than predicted by chance . Unsupervised methods proposed so far typically use linear approaches , such as Principal Component Analysis ( PCA ) [24 , 46 , 47] , and cannot account for different patterns arising from permutations of spike orderings . While approaches like frequent itemset mining and related methods [48–51] can find more patterns than the number of neurons and provide a rigorous statistical framework , they require that exact matches of the same pattern occur , which becomes less and less probable as the number of neurons grows or as the time bins become smaller ( problem of combinatorial explosion ) . To address this problem , [52 , 53] proposed another promising unsupervised method based on spin glass Ising models that allows for approximate pattern matching while not being linearly limited in the number of patterns; this method however requires binning , and rather provides a method for classifying the binary network state vector in a small temporal neighborhood , while not dissociating rate patterns from temporal patterns . In this paper we introduce a novel spike pattern detection method called SPOTDisClust ( Fig 1 ) . We start from the idea that the similarities of two neural patterns can be defined by the trace that they may leave on the synaptic matrix , which in turn is determined by the pairwise cross-correlations between neural activities [26 , 27] . The algorithm is based on constructing an epoch-to-epoch dissimilarity matrix , in which dissimilarity is defined as SPOTDis , making use of techniques from the mathematical theory of optimal transport to define , and efficiently compute , a dissimilarity between two spiking patterns [54–57] . We then perform unsupervised clustering on the pairwise SPOTDis matrix . SPOTDis measures the similarity of two spike patterns ( in two different epochs ) by determining the minimum transport cost of transforming their corresponding cross-correlation matrices into each other . This amounts to computing the Earth Mover’s Distance ( EMD ) for all pairs of neurons and all pairs of epochs ( see Methods ) . Through ground-truth simulations , we show that SPOTDisClust has many desirable properties: It can detect many more patterns than the number of neurons ( Fig 2 ) ; it can detect complex patterns that would be invisible with latency-based methods ( Figs 3 and 4 ) ; it is highly robust to noise , i . e . to the ‘insertion’ of noisy spikes , spike timing jitter , or fluctuations in the firing rate , and its performance grows with the inclusion of more neurons given a constant signal-to-noise ratio ( Fig 5 ) ; it can detect sequences in the presence of sparse firing ( Fig 6 ) ; and finally it is insensitive to a global or patterned scaling of the firing rates ( Fig 7 ) . We apply SPOTDisClust to V1 Utah array data from the awake macaque monkey , and identify different visual stimulus directions using unsupervised clustering with SPOTDisClust ( Fig 8 ) .
Suppose we perform spiking measurements from an ensemble of N neurons , and we observe the spiking output of this ensemble in M separate epochs of length T samples ( in units of the time bin length ) . Suppose that there are P distinct activity patterns that tend to reoccur in some of the M epochs . Each pattern generates a set of normalized ( to unit mass ) cross-correlation histograms among all neurons . Instantiations of the same pattern are different because of noise , but will have the same expectation for the cross-correlation histogram . The normalized cross-correlation histogram is defined as s i j ′ ( τ ) ≡ s i j ( τ ) ∑ τ = - T T s i j ( τ ) , ( 1 ) if ∑ τ = - T T s i j ( τ ) > 0 , and s i j ′ ( τ ) = 0 otherwise . Here , sij ( τ ) ≡ ∑t si ( t ) sj ( t + τ ) is the cross-correlation function ( or cross-covariance ) , and si ( t ) and sj ( t ) are the spike trains of neurons i and j . In other words , the normalized cross-correlation histogram is simply the histogram of coincidence counts at different delays τ , normalized to unit mass . We take the N × N × ( 2T + 1 ) matrix of s i j ′ ( τ ) values as a full representation of a pattern , that is , we consider two patterns to have the same temporal structure when all neuron pairs have the same expected value of s i j ′ ( τ ) for each τ . For simplicity and clarity of presentation , we have written the cross-correlation function as a discrete ( histogram ) function of time . However , because the SPOTDis , which is introduced below , is a cross-bins dissimilarity measure and requires only to store the precise delays τ at which s i j ′ ( τ ) is non-zero , the sampling rate can be made infinitely large ( see Methods ) . In other words , the SPOTDis computation does not entail any loss of timing precision beyond the sampling rate at which the spikes are recorded . The SPOTDisClust method contains two steps ( Fig 1 ) , which are illustrated for five example patterns ( Fig 1A and 1B ) . The first step is to construct the SPOTDis dissimilarity measure between all pairs of epochs on the matrix of cross-correlations among all neuron pairs . The second step is to perform clustering on the SPOTDis dissimilarity measure using an unsupervised clustering algorithm that operates on a dissimilarity matrix . Many algorithms are available for unsupervised clustering on pairwise dissimilarity matrices . One family of unsupervised clustering methods comprises so called density clustering algorithms , including DBSCAN , HDBSCAN or density peak clustering . Here , we use the HDBSCAN unsupervised clustering method [58–61] ( see Methods ) . To examine the separability of the clusters in a low dimensional 2-D embedding , we employ the t-SNE projection method [62 , 63] ( see Methods ) . The SPOTDis measure is constructed as follows: To test the SPOTDisClust method for cases in which the ground truth is known , we generated P input patterns in epochs of length T = Tepoch = 300 samples , defined by the instantaneous rate of inhomogeneous Poisson processes , and then generated spiking outputs according to these ( Fig 1A and 1B ) ( see Methods ) . Because the SPOTDis is a binless measure , in the sense that it does not require any binning beyond the sampling frequency , the epochs could for example represent spike series of 3s with a sampling rate of 100Hz , or spike series of 300ms with a sampling rate of 1000Hz . Each input pattern was constructed such that it had a baseline firing rate and a pulse activation firing rate , defined as the expected number of spikes per sample . The pulse activation period ( with duration Tpulse samples ) is the period in the epoch in which the neuron is more active than during the baseline , and the positions of the pulses across neurons define the pattern . For each neuron and pattern , the position of the pulse activation period was randomly chosen . We generated M/ ( 2 * P ) realizations for each of the P patterns , and a matching number of M/2 noise epochs ( i . e . 50 percent of epochs were noise epochs ) . We performed simulations for two types of noise epochs ( S3 Fig ) . First , noise was generated with random firing according to a homogeneous Poisson process with a constant rate ( see Fig 1 ) . We refer to this noise , throughout the text , as “homogeneous noise” . For the second type of noise , each noise epoch comprised a single instantiation of a unique pattern , with randomly chosen positions of the pulse activation periods . We refer to this noise as “patterned noise” . For both types of noise patterns , the expected number of spikes in the noise epoch was the same as during an epoch in which one of the P patterns was realized . The second type of noise also had the same inter spike interval statistics for each neuron as the patterns . Importantly , because SPOTDisClust uses only the relative timing of spiking among neurons , rather than the timing of spiking relative to the epoch onset , the exact onset of the epoch does not have to be known with SPOTDis; even though the exact onset of the pattern is known in the simulations presented here , this knowledge was not used in any way for the clustering . Fig 1 illustrates the different steps of the algorithm for an example of P = 5 patterns . For the purpose of illustration , we start with an example comprising five patterns that are relatively easy to spot by eye; later in the manuscript we show examples with a very low signal-to-noise ratio ( Fig 5 ) or sparse firing ( Fig 6 ) . We find that in the 2-D t-SNE embedding , the P = 5 different patterns form separate clusters ( Fig 1E ) , and that the HDBSCAN algorithm is able to correctly identify the separate clusters ( S4 Fig ) . We also show a simulation with many more noise epochs than cluster epochs , which shows that even in such a case t-SNE embedding is able to separate the different clusters ( S5 Fig ) . In S3 Fig we compare clustering with homogeneous and patterned noise . The homogeneous noise patterns have a consistently small SPOTDis dissimilarity to each other and are detected as a separate cluster , while the patterned noise epochs have large SPOTDis dissimilarities to each other and do not form a separate cluster , but spread out rather uniformly through the low-dimensional t-SNE embedding ( S3 Fig ) . A key challenge for any pattern detection algorithm is to find a larger number of patterns than the number of measurement variables , assuming that each pattern is observed several times . This is impossible to achieve with traditional linear methods like PCA ( Principal Component Analysis ) , which do not yield more components than the number of neurons ( or channels ) , although decomposition techniques using overcomplete base sets might in principle be able to do so . Other approaches like frequent itemset mining and related methods [48–50] require that exact matches of the same pattern occur . Because SPOTDisClust clusters patterns based on small SPOTDis dissimilarities , it does not require exact matches of the same pattern to occur , but only that the different instantiations of the same pattern are similar enough to one another , i . e . have SPOTDis values that are small enough , and separate them from other clusters and the noise . Fig 2 shows an example where the number of patterns exceeds the number of neurons by a factor 10 ( 500 to 50 ) . In the 2-D t-SNE embedding , the 500 patterns form separate clusters , with the emergence of a noise cluster that has higher variance . Consistent with the low dimensional t-SNE embedding , the HDBSCAN algorithm is able to correctly identify the separate clusters ( S4 Fig ) . When many patterns are detectable , the geometry of the low dimensional t-SNE embedding needs to be interpreted carefully: In this case , all 500 patterns are roughly equidistant to each other , however , there does not exist a 2-D projection in which all 500 clusters are equidistant to each other; this would only occur with a triangle for P = 3 patterns . Thus , although the low dimensional t-SNE embedding demonstrates that the clusters are well separated from each other , in the 2-D embedding nearby clusters do not necessarily have smaller SPOTDis dissimilarities than distant clusters when P is large . Temporal patterns in neuronal data may consist not only of ordered sequences of activation , but can also have a more complex character . As explained above , a key advantage of the SPOTDis measure is that it computes averages over the EMD , which can distinguish complex patterns beyond patterns that differ only by a measure of central tendency . Indeed , we will demonstrate that SPOTDisClust can detect a wide variety of patterns , for which traditional methods that are based on the relative activation order ( sequence ) of neurons may not be well equipped . We first consider a case where the patterns consist of bimodal activations within the epoch ( Fig 3A ) . These types of activation patterns might for example be expected when rodents navigate through a maze , such that enthorinal grid cells or CA1 cells with multiple place fields are activated at multiple locations and time points [64–66] . A special case of a bimodal activation is one where neurons have a high baseline firing rate and are “deactivated” in a certain segment of the epoch ( Fig 3B ) . These kinds of deactivations may be important , because e . g . spatial information about an animal’s position in the medial temporal lobe ( [67] ) or visual information in retinal ganglion cells is carried not only by neuronal activations , but also by neuronal deactivations . We find that the different patterns form well separated clusters in the low dimensional t-SNE embedding based on SPOTDis ( Fig 3A and 3B ) , and that HDBSCAN correctly identifies them ( S4 Fig ) . Next , we consider a case where there are two coarse patterns and two fine patterns embedded within each coarse pattern , resulting in a total number of four patterns . This example might be relevant for sequences that result from cross-frequency theta-gamma coupling , or from the sequential activation of place fields that is accompanied by theta phase sequences on a faster time scale [68 , 69] . These kinds of patterns would be challenging for methods that rely on binning , because distinguishing the coarse and fine patterns requires coarse and fine binning , respectively . We find that the SPOTDis allows for a correct separation of the data in four clusters corresponding to the four patterns and one noise cluster ( Fig 4A ) , and that HDBSCAN identifies them ( S4 Fig ) . As expected , we find that the two patterns that share the same coarse structure ( but contain a different fine structure ) have smaller dissimilarities to each other in the t-SNE embedding as compared to the patterns that share a different coarse structure . Finally , we consider a set of patterns consisting of a synchronous ( i . e . without delays ) firing of a subset of cells , with a cross-correlation function that is symmetric around the delay τ = 0 ( i . e . , correlation without delays ) . This type of activity may arise for example in a network in which all the coupling coefficients between neurons are symmetric . Previous methods to identify the co-activation ( without consideration of time delays ) of different neuronal assemblies relied on PCA [24] , which has the key limitation that it can identify only a small number of patterns ( smaller than the number of neurons ) Furthermore , while yielding orthonormal , uncorrelated components that explain the most variance in the data , PCA components do not necessarily correspond to neuronal spike patterns that form distinct and separable clusters; e . g . a multivariate Gaussian distribution can yield multiple PCA components that correspond to orthogonal axes explaining most of the data variance . Fig 4B shows four patterns , in which a subset of cells exhibits a correlated activation without delays . Separate clusters emerge in the t-SNE embedding based on SPOTDis ( Fig 4B ) and are identified by HDBSCAN ( S4 Fig ) . This demonstrates that SPOTDisClust is not only a sequence detection method in the sense that it can detect specific temporal orderings of firing , but can also be used to identify patterns in which specific groups of cells are synchronously co-active without time delays . A major challenge for the clustering of temporal spiking patterns is the stochasticity of neuronal firing . That is , in neural data , it is extremely unlikely to encounter , in a high dimensional space , a copy of the same pattern exactly twice , or even two instantiations that differ by only a few insertions or deletions of spikes . Furthermore , patterns might be distinct when they span a high-dimensional neural space , even when bivariate correlations among neurons are weak and when the firing of neurons in the activation period is only slightly higher than the baseline firing around it ( see further below ) . The robustness of a sequence detection algorithm to noise is therefore critical . We can dissociate different aspects of “noise” in temporal spiking patterns . A first source of noise is the stochastic fluctuation in the number of spikes during the pulse activation period and baseline firing period . In the ground-truth simulations presented here , this fluctuation is driven by the generation of spikes according to inhomogeneous Poisson processes . This type of noise causes differences in SPOTDis values between epochs , because of differences in the amount of mass in the pulse activation and baseline period , in combination with the normalization of the cross-correlation histogram . In the extreme case , some neurons may not fire in an given epoch , such that all information about the temporal structure of the pattern is lost . Such a neural “silence” might be prevalent when we search for spiking patterns on a short time scale . We note that fluctuations in the spike count are primarily detrimental to clustering performance because there is baseline firing around the pulse activation period , in other words because “noisy” spikes are inserted at random points in time around the pulse activations . To see this , suppose that the probability that a neuron fires at least one spike during the pulse activation period is close to one for all M epochs and all N neurons , and that the firing rate during the baseline is zero . In this case , because SPOTDis is based on computing optimal transport between normalized cross-correlation histograms ( Eq ( 5 ) ) , the fluctuation in the spike count due to Poisson firing would not drive differences in the SPOTDis . A second source of noise is the jitter in spike timing . Jitter in spike timing also gives rise to fluctuations in the SPOTDis and in the ground-truth simulations presented here , spike timing jitter is a consequence of the generation of spikes according to Poisson processes . As explained above , because the SPOTDisClust method does not require exact matches of the observed patterns , but is a “cross-bins” dissimilarity measure , it can handle jitter in spike timing well . Again , we can distinguish jitter in spike timing during the baseline firing , and jitter in spike timing during the pulse activation period . The amount of perturbation caused by spike timing jitter during the pulse activation period is a function of the pulse period duration . We will explore the consequences of these different noise sources , namely the amount of baseline firing , the sparsity of firing , and spike timing jitter in Figs 5 and 6 . We define the SNR ( Signal-to-Noise-Ratio ) as the ratio of the firing rate inside the activation pulse period over the firing rate outside the activation period . This measure of SNR reflects both the amount of firing in the pulse activation period as compared to the baseline period ( first source of noise ) , and the pulse duration as compared to the epoch duration ( second source of noise ) . We first consider an example of 100 neurons that have a relatively low SNR ( Fig 5A ) . It can be appreciated that different realizations from the same pattern are difficult to identify by eye , and that exact matches for the same pattern , if one would bin the spike trains , would be highly improbable , even for a single pair of two neurons ( Fig 5A ) . Yet , in the 2-D t-SNE embedding based on SPOTDis , the different clusters form well separated “islands” ( Fig 5A ) , and the HDBSCAN clustering algorithm captures them ( S4 Fig ) . To systematically analyze the dependence of clustering performance on the SNR , we varied the SNR by changing the firing rate inside the activation pulse period , while leaving the firing rate outside the activation period as well as the duration of the activation ( pulse ) period constant . Thus , we varied the first aspect of noise , which is driven by spike count fluctuations . A measure of performance was then constructed by comparing the unsupervised cluster labels rendered by HDBSCAN with the ground-truth cluster labels , using the Adjusted Rand Index ( ARI ) measure ( see Methods ) . As expected , we find that clustering performance increases with the firing rate SNR ( Fig 5B ) . Importantly , as the number of neurons increases , we find that the same clustering performance can be achieved with a lower SNR ( Fig 5B ) . Thus , SPOTDisClust does not suffer from the problem of combinatorial explosion as the number of neurons that constitute the patterns increases , and , moreover , its performance improves when the number of recorded neurons is higher . The reason underlying this behavior is that each neuron contributes to the separability of the patterns , such that a larger sample of neurons allows each individual neuron to be noisier . This means that , in the brain , very reliable temporal patterns may span high-dimensional neural spaces , even though the bivariate correlations might appear extremely noisy; absence of evidence for temporal coding in low dimensional multi-neuron ensembles should therefore not be taken as evidence for absence of temporal coding in high dimensional multi-neuron ensembles . We also varied the SNR by changing the pulse duration while leaving the ratio of expected number of spikes in the activation period relative to the baseline constant . The latter was achieved by adjusting the firing rate inside the activation period , such that the product of pulse duration with firing rate in the activation period remained constant , i . e . Tpulseλpulse = c . Thus , we varied the second aspect of noise , namely the amount of spike timing jitter in the pulse activation period . We find a similar dependence of clustering performance on the firing rate SNR and the number of neurons ( Fig 5B ) . Hence , patterns that comprise brief activation pulses of very high firing yield , given a constant product Tpulseλpulse , clusters that are better separated than patterns comprising longer activation pulses . We performed further simulations to study in a more simplified , one-dimensional setting how the SPOTDis depends quantitatively on the insertion of noise spikes outside of the activation pulse periods , which further demonstrates the robustness of the SPOTDis measure to noise ( S6 Fig ) . In addition , we performed simulations to determine the influence of spike sorting errors on the clustering performance . In general , spike sorting errors lead to a reduction in HDBSCAN clustering performance , the extent of which depends on the type of spike sorting error ( contamination or collision ) [70] and the structure of the spike pattern ( S7 and S8 Figs ) . This result is consistent with the dependence of the HBDSCAN clustering performance on signal-to-noise ratio and pulse duration shown in Fig 5 , as well with the notion that contamination mixes responses across neurons , such that the number of neurons that carries unique information decreases . We further note that in general , SPOTDisClust provides flexibility when detecting patterns using multiple tetrodes or channels of a laminar silicon probe: A common technique employed when analyzing pairwise correlations ( e . g . noise correlations ) is to ignore pairs of neurons that were measured from the same tetrode or from nearby channels . When the number of channels is large , this will only ignore a relatively small fraction of neuron pairs . Because the SPOTDis measure is defined over pairs of neurons , rather than the sequential ordering of firing defined over an entire neuronal ensemble , this can be easily implemented by , in Eq 2 , letting the sum run over neuron pairs from separate electrodes . As explained above , an extreme case of noise driven by spike count fluctuations is the absence of firing during an epoch . If many neurons remain “silent” in a given epoch , then we can only compute the EMD for a small subset of neuron pairs ( Eq ( 2 ) ) . Such a sparse firing scenario might be particularly challenging to latency-based methods , because the latency of cells that do not fire is not defined . We consider a case of sparse firing in Fig 6 where the expected number of spikes per epoch is only 0 . 48 . Despite the firing sparsity , the low-dimensional t-SNE embedding based on SPOTDis shows separable clusters , and HDBSCAN correctly identifies the different clusters ( Fig 6 ) . We also performed a simulation in which patterns consist of precise spike sequences , and examined the influence of temporal jitter of the precise spike sequence , as well as the amount of noise spikes surrounding these precise spike sequences . Up to some levels of temporal jitter , and signal-to-noise ratio , HDBSCAN shows a relatively good clustering performance ( S9 Fig ) . In general , given sparse firing , a sufficient number of neurons is needed to correctly identify the P patterns , but , in addition , the patterns should be distinct on a sufficiently large fraction of neuron pairs . Furthermore , the lower the signal-to-noise ratio , the more neurons are needed to separate the patterns from one another . A key aim of the SPOTDisClust methodology is to identify temporal patterns that are based on consistent temporal relationships among neurons . However , in addition to temporal patterns , neuronal populations can also exhibit fluctuations in the firing rate that can be driven by e . g . external input or behavioral state and are superimposed on temporal patterns . A global scaling of the firing rate , or a scaling of the firing rate for a specific assembly , should not constitute a different temporal pattern if the temporal structure of the pattern remains unaltered , i . e . when the normalized cross-correlation function has the same expected value , and should not interfere with the clustering of temporal patterns . This is an important point for practical applications , because it might occur for instance that in specific behavioral states rates are globally scaled [71 , 72] . In Fig 7A , we show an example where there are three different global rate scalings , as well as two temporal patterns . The temporal patterns are , for each epoch , randomly accompanied by one of the different global rate scaling factors . The t-SNE embedding shows that the temporal patterns form separate clusters , but that the global rate scalings do not ( Fig 7A ) . Furthermore , HDBSCAN correctly clusters the temporal patterns , but does not find separate clusters for the different rate scalings ( Fig 7A and S4 Fig ) . This behavior can be understood from examination of the sorted dissimilarity matrix , in which we can see that epochs with a low rate do not only have a higher SPOTDis to epochs with a high rate , but also to other epochs with a low rate , which prevents them from agglomerating into a separate cluster ( Fig 7A ) ; rather the epochs with a low rate tend to cluster at the edges of the cluster , whereas the epochs with a high rate tend to form the core of the cluster ( Fig 7A ) . Another example of a rate scaling is one that consists of a scaling of the firing rate for one half of the neurons ( Fig 7B ) . Again , the t-SNE embedding and HDBSCAN clustering show that rate scalings do not form separate clusters , and do not interfere with the clustering of the temporal patterns ( Fig 7B and S4 Fig ) . We conclude that the unsupervised clustering of different temporal patterns with SPOTDisClust is not compromised by the inclusion of global rate scalings , or the scaling of the rate in a specific subset of neurons . We apply the SPOTDisClust method to data collected from monkey V1 . Simultaneous recordings were performed from 64 V1 channels using a chronically implanted Utah array ( Blackrock ) ( see Methods ) . We presented moving bar stimuli in four cardinal directions while monkeys performed a passive fixation task . Each stimulus bar was presented 20 times . We then pooled all 80 trials together , and added 80 trials containing spontaneous activity . Our aim was then to recover the separate stimulus conditions using unsupervised clustering of multi-unit data with SPOTDisClust . The low dimensional t-SNE embedding shows four dense regions that are well separated from each other and correspond to the four stimuli , and HDBSCAN identifies these four clusters ( Fig 8 ) . Furthermore , when we performed clustering on the firing rate vectors , and constructed a t-SNE embedding on distances between population rate vectors , we were not able to extract the different stimulus directions from the cluster labels . This shows that the temporal clustering results are not trivially explained by rate differences across stimulus directions , but also indicates that the temporal pattern of population activity might reveal important stimulus information beyond the neuronal firing rates . Thus , SPOTDisClust can be successfully used on real neuronal data to identify different temporal patterns in high-dimensional multi-neuron ensembles . For the simulations and applications above , we have assumed that the temporal window of interest for the application was known , i . e . that we had some a priori knowledge about the length of the spike patterns . For many applications in neuroscience , we want to detect sequences around specific events that are either defined by some external event ( e . g . a stimulus onset ) or by some “internal” event , e . g . a sharp wave ripple complex , an UP-DOWN state transition , or the cycle of some oscillation , e . g . a hippocampal theta cycle . However , in these cases the precise duration of the spike patterns is not known , and in addition there is most likely some jitter in the onset of the sequence . To handle this onset jitter , SPOTDisClust explicitly defines patterns at the level of cross-correlations rather than on univariate spike trains directly , which endows the measure with time translational invariance . To show the feasibility of determining the window length automatically from the data , we have performed simulations in which sequences occurred around some event with additional temporal jitter . These sequences were flanked by homogeneous noise ( i . e . before and after the sequences ) . We then varied the chosen window length around the event , and measured the cluster quality using the unsupervised Silhouette score , which is based on a comparison of distances within each cluster vs . distances between the clusters ( see Methods ) . As expected , the ( unsupervised ) Silhouette and ARI ( ground-truth ) cluster quality scores decreased when we used longer and shorter windows than the true sequence length ( S11 Fig ) . Importantly , however , the Silhouette and ARI score showed a tight correspondence with one another , showing the feasibility of selecting the window length for spike sequence detection in an unsupervised manner . For our application to neuronal data , we optimized the window length used for the clustering using the Silhouette score and show that we can recover the window length that maximizes the cluster quality as compared to ground-truth ( ARI ) ( S12 Fig ) .
We have presented a novel dissimilarity measure for multi-neuron temporal spike patterns , SPOTDis , with unique properties that make it suitable for the unsupervised exploration of the space of admissible firing patterns . SPOTDis is rooted in optimal transport theory , a burgeoning field in mathematics that offers promising solutions for fields as diverse as economics , engineering , physics and chemistry [54–57 , 73] . In machine learning , optimal transportation based distances for image classification have been devised , which accommodate the fact that relevant image features may appear at slightly different positions in similar images . While pixel-wise comparisons of two images may fail to recognize similarity under those conditions , optimal transportation based distances operate in a “cross-bins” fashion , so they can treat those shifts in an appropriate way . In neural data analysis we face a similar problem , as spike patterns may present themselves repeatedly with the same overall structure , but not exactly the same timing . The traditional approach to accommodate for such “jitter” is to discretize spike times with a binning procedure , or , in a nearly equivalent way , to use a smoothed version of the spike train time series [74] . Such approaches require setting an arbitrary scale for the timing precision of neural firing . This is in general difficult , because neural patterns may occur at different temporal scales , and with different jitters . For example , hippocampal place fields fire in sequences at the “behavioral” time scale of hundreds of milliseconds , and because of the phase precession phenomena , they fire so-called “theta” sequences at a much faster ( tens of milliseconds ) time scales [25 , 68 , 69] . Repeated sequences at any time scale will be detected by SPOTDis , in particular in combination with a density based algorithm such as HDBSCAN , which can detect state space regions of higher density surrounded by lower density areas , regardless of the absolute density . Using ground-truth simulations , we have shown that SPOTDis can deal with cases in which both coarse and fine patterns co-exist ( Fig 4A ) . Optimal transport theory provides both theoretical grounding , as well as a host of solutions for the efficient calculation of distances . Here , we propose a novel implementation , inspired to work in optimal transport , and tailored to the case of calculating the dissimilarity between point process realizations , in our case spike trains . Distance measures based on “morphing” one spike train into another by moving spikes have been previously proposed . The Victor-Purpura distance , which is an adaptation of the Levenshtein distance to point processes , is a paradigmatic example [75] . Our approach differs in two fundamental ways . First , the Victor-Purpura distance allows for the insertion and deletion of spikes , to enable computation of distances between spike trains with different numbers of spikes , adding in each case a penalty term ( the penalty terms are arbitrary parameters to be optimized ) . While this may be a principled way to deal with this issue , it introduces additional complexity in the computation of the distance as many different combinations of spike shifting and insertion/deletion must be considered in order to find the optimal solution . This may render optimization difficult and the computation prohibitive as one attempts to compare a large number of multi-neuron patterns . We take the more simple-minded approach of rescaling the time series to be compared , in order to equalize mass . While this may be an oversimplification in some cases , this enables us to implement the computation in a very efficient way . Yet , we preserve many desirable features of spike train metrics such as the Victor-Purpura distance . For example , SPOTDis is not based on measures of central tendency , but can also compute dissimilarities between multimodal probability distributions ( Fig 3A and 3B ) . Furthermore , SPOTDis is particularly noise robust , because it can handle jitter in spike timing , as it does not require exact overlap in discretized time bins , but is based on distance computations in a metric space . A second important difference with spike train metric methods such as Victor-Purpura distance is that we calculate the pairwise epoch-to-epoch dissimilarity not directly on spike trains but on cross-correlograms between pairs of cell spike trains . This has the considerable advantage of enabling detection of similarity between spiking patterns that are misaligned , and eliminates the need for precise time reference points ( e . g . the time of stimulus delivery ) , providing a way to freely search for repeated patterns in spontaneous or evoked activity . Comparing cross-correlation patterns between epochs has been used in seminal work on memory replay , where cross-correlation “bias” was compared across entire sleep or behavioral epochs , to assess the presence of significant replay [22 , 23] . Here , we provide a method for comparison at a greater granularity , enabling efficient identification of the repeated patterns within time windows of hundreds of milliseconds . A distance based on cross-correlation also has an attractive physiological interpretation: From the perspective of synaptic plasticity , it can be interpreted as the extent to which two patterns have a similar effect on the synaptic plasticity in the network through the STDP rule , which holds that changes in synaptic plasticity depend on the timing jitter between pre- and post-synaptic spikes [26 , 27] . Our dissimilarity measure acts on multi-neuron patterns , and can make use of any additional information available when the monitored neural population increases in size . Because SPOTDis between epoch k and epoch m ignores neuron pairs in which one neuron did not fire in both epochs , it also handles cases in which there is sparse firing and many neurons do not fire at all ( Fig 6 ) . Moreover , SPOTDis is based on computing a distance function on the normalized cross-correlation functions . Because of this normalization to unit mass , it copes with global fluctuations in the firing rate , and specific increases in the firing rate for subsets of neurons ( Fig 5 ) . We combined SPOTDis with a density-based clustering algorithm , HDBSCAN , which forms a good match for several reasons: First , it can deal with non-metric dissimilarities . While SPOTDis on a single cell pair cross-correlation is metric ( and the sum of metrics is a metric ) , absence of firing in some neurons and in some cell pairs may cause violation of metricity , which is handled gracefully by HDBSCAN . Second , it can identify clusters at different characteristic densities in different regions of the state space , adapting to patterns that may arise at different time scales and different precision due to disparate underlying mechanisms . Yet , other clustering strategies than HDBSCAN may work successfully as well . We show that in many cases , a non-linear embedding technique such as t-SNE acting on SPOTDis yields a quite intuitive representation of the underlying structure of the data . It is important to emphasize that our method is an explicit clustering method , that can find unique patterns of network activity that are well separated from one another . Several methods using decomposition techniques like PCA or matrix factorization have been utilized with the goal of extracting patterns or sequences from neuronal ensemble data [24 , 46 , 47 , 76] . We highlight several differences between SPOTDisClust and decomposition techniques: 1 ) In principle , decomposition techniques like PCA achieve a different goal , namely to identify components that explain a large fraction of variance in the data . These components might in some cases correspond to separate patterns , but do not necessarily so: For instance , a multivariate Gaussian model distribution may yield few components explaining most variance , but these components do not necessarily correspond to clusters . Further , decomposition techniques like PCA decompose into an orthogonal base set , while different spike patterns may in fact be strongly correlated to one another . Thus , decomposition and clustering techniques can provide complementary information . 2 ) SPOTDisClust can also handle cases where there is a very large number of noise patterns and only few realizations of spike patterns yielding small clusters . These small clusters might drive only a small degree of variance , and may be invisible to decomposition techniques . 3 ) Many decomposition techniques are designed to find a few components corresponding to dominant axes of variance in the data , yielding fewer “spike patterns” than the number of neurons , although decomposition techniques using overcomplete base sets may in principle find more patterns than the number of neurons . SPOTDisClust on the other hand can find many more patterns than the number of clusters . 4 ) Finally , SPOTDisClust is in principle a “binless” method , while decomposition techniques will typically require some form of binning resulting in information loss . We provide an initial application of the SPOTDis measure to real neuronal data , by analyzing multi-electrode recordings in visual cortex . In this analysis , we fed the algorithm the neural data without any knowledge of the task structure , or of the times of stimulus delivery . Strikingly , the identified clusters faithfully reflected the structure of the PSTH calculated with traditional methods , with availability of the stimulus delivery times and labels . Thus , we can recover stimulus information even after normalizing away firing rate information , which is conventionally used to decode different stimuli , demonstrating that the temporal structure of population activity encodes different moving stimulus directions . We also developed an analogous clustering method to SPOTDisClust by constructing a dissimilarity matrix based on L1 distances among population firing rate vectors . Using this clustering technique , the different stimulus directions could not be separated from one another using t-SNE embedding or HDBSCAN . While we argued that our approach using bivariate cross-correlations yields many advantages , it also has a limitation in the sense that it does not capture higher-order correlations among neurons . Future extensions of this technique may explicitly construct a dissimilarity measure based on high-order correlations among neurons . Indeed , incorporating this may be an interesting avenue for future work . Nonetheless , it should be noted that higher order correlations in a population may be captured by models fitting the first and second moments alone [77 , 78] ) . In the present work , we only considered spike trains as if they were recorded using electrophysiological methods . However , this method may also be applied to two-photon calcium imaging data using sensors like GCaMP6f . Analysis of this type of data always involves some additional preprocessing steps like denoising , deconvolution , region of interest identification , and normalization . An excellent strategy would be to apply the method on calcium imaging data after deconvolution and source extraction , which yields sparse time series with “spikes” , although not measured with the same temporal resolution as in case of electrophysiological recordings [79 , 80] . After deconvolution , the application of SPOTDisClust is straightforward . If one operates on the raw fluorescence data , using a defined set of ROIs corresponding to e . g . somata or spines , then one would have to perform some normalization to get rid of background fluorescence . One possible normalization could be ΔF = F − Fbackground , where Fbackground is the background fluorescence . After this , one would normalize ΔF to unit mass , and then directly compute the EMD on this unit mass . In conclusion , we have proposed a new tool for the efficient unsupervised analysis of multi-neuron data , which opens up more flexible ways to analyze spontaneous and evoked activity than it has been so far possible .
The SPOTDisClust method contains two steps . The first step is to construct the pairwise epoch-to-epoch SPOTDis measure on the matrix of cross-correlations among all neuron pairs . Computing the SPOTDis with the sparse simulation ( Fig 6 ) takes 60 seconds and the computation for the example case ( Fig 1 ) takes approximately 5 minutes , utilizing an Intel Xenon E5-2650 v2 2 . 60GHz system with 16 cores . HDBSCAN is an automated density clustering algorithm that clusters on the basis of pairwise dissimilarity matrices . An extensive overview of HDBSCAN can be found in [60 , 61] and we provide only a brief overview of HDBSCAN here . HDBSCAN comprises the following steps: T-SNE ( t-distributed stochastic neighbor embedding ) is a dimensionality reduction technique for high-dimensional datasets [62] . While it typically is computed starting from a high-dimensional dataset that is then converted into a matrix of pairwise Euclidean distances , here we compute it directly on the pairwise dissimilarity matrix . We first outline the algorithm of SNE [63] , and after that the adjustments made in t-SNE . T-SNE makes two main adjustments relative to SNE ( the rationale behind these two adjustments is extensively discussed in [62] ) . First , it uses a symmetric measure of similarity between two data points , as the joint probability p m k = p k | m + p m | k 2 n ( 16 ) Second , it uses a Student’s t-distribution with one degree of freedom instead of a Gaussian for the low dimensional counterparts . One male macaque monkey performed a passive fixation task while moving bar stimuli ( white bars on gray background , 0 . 25 degrees in visual angle width ) were presented . All procedures complied with the German law for the protection of animals and were approved by the regional authority ( Regierungspräsidium Darmstadt ) . Recordings were performed from 64 V1 channels simultaneously , obtained from a chronic Utah array implant ( Blackrock ) . Receptive fields had eccentricities around 3-5 degrees visual angle . We performed band-pass filtering of each channel in the frequency range of action potentials ( 300-6000Hz ) and then thresholded the band-pass filtered signal x ( t ) according to [83] , using the threshold 3 m e d { x ( t ) } 0 . 6745 , where med is the median ( i . e . effectively three standard deviations ) . When the signal x ( t ) crossed this threshold , we denoted a spike . After the detection of a threshold crossing , further threshold crossings were suppressed for 0 . 75ms . Moving bar stimuli were presented in four cardinal directions . Each stimulus bar was presented 20 times . We then pooled all 80 trials together , and added 80 trials containing spontaneous activity . Our aim was then to recover the separate stimulus conditions using unsupervised clustering with SPOTDisClust . We use npts = 3 with leaf selection for the HDBSCAN parameters . | The brain encodes information by ensembles of neurons , and recent technological developments allow researchers to simultaneously record from over thousands of neurons . Neurons exhibit spontaneous activity patterns , which are constrained by experience and development , limiting the portion of state space that is effectively visited . Patterns of spontaneous activity may contribute to shaping the synaptic connectivity matrix and contribute to memory consolidation , and synaptic plasticity formation depends crucially on the temporal spiking order among neurons . Hence , the unsupervised detection of spike sequences is a sine qua non for understanding how spontaneous activity contributes to memory formation . Yet , sequence detection presents major methodological challenges like the sparsity and stochasticity of neuronal output , and its high dimensionality . We propose a dissimilarity measure between neuronal patterns based on optimal transport theory , determining their similarity from the pairwise cross-correlation matrix , which can be taken as a proxy of the “trace” that is left on the synaptic matrix . We then perform unsupervised clustering and visualization of patterns using density clustering on the dissimilarity matrix and low-dimensional embedding techniques . This method does not require binning of spike times , is robust to noise , jitter and rate fluctuations , and can detect more patterns than the number of neurons . | [
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] | 2018 | Unsupervised clustering of temporal patterns in high-dimensional neuronal ensembles using a novel dissimilarity measure |
Kabul , Afghanistan , is the largest focus of anthroponotic cutaneous leishmaniasis ( ACL ) in the world . ACL is a protozoan disease transmitted to humans by the bite of phlebotomine sand flies . Although not fatal , ACL can lead to considerable stigmatization of affected populations . Using data from a standardized survey of 872 households in 4 wards of Kabul , Afghanistan , univariate and multivariate logistic regression analyses tested associations between presence of active ACL and ACL scars with 15 household-level variables . Univariate analyses showed that active ACL was positively associated with household member's age , ACL prevalence , and brick wall type , but negatively associated with household number of rooms , bednet use , and proportion of windows with screens . Multivariate analysis showed a positive association between active ACL and household member's age , ACL prevalence , and brick wall type , and a negative association with household proportion of windows with screens . Household-level charateristics were shown to be risk factors for ACL . Monitoring a selected number of household characteristics could assist in rapid assessments of household-level variation in risk of ACL . ACL prevention and control programs should consider improving house construction , including smoothing of walls and screening of windows .
After decades of war , Kabul , Afghanistan , became the world's largest focus of cutaneous leishmaniasis ( CL ) with an estimated annual incidence of 67 , 500 cases [1] . CL is a vector-borne protozoan disease that is characterized by cutaneous lesions which develop at the site of the insect bite [2] . Albeit not fatal , CL has a significant social impact in Afghanistan [3] , [4] as it may lead to severe stigmatisation of affected individuals when lesions occur on the face and exposed extremeties . Several reports document the dramatic increase of CL in the region , including Iran [5]–[7] , Pakistan [8]–[11] and , in particular , Afghanistan [1] , [12]–[16] . Whilst some of these reports have indicated that CL is associated with sex [1] , age [1] , [9] , domestic animals [9] and clustering of cases at the household level [1] , [9] little is known about other household characteristics associated with this disease in South Asia . Whereas is many Asian foci CL is transmitted zoonotically ( i . e . through an animal reservoir ) , CL in Kabul is transmitted anthroponotically , with CL being referred to as anthroponotic CL ( ACL ) and the human population representing the main reservoir of infection . The objectives of the work described here were to investigate household-level characteristics associated with ACL in Kabul in order to support the development and implementation of strategies to prevent and control ACL .
The study was carried out in September 2003 in four ( III , IV , VI , VII ) of the city's 14 wards . These wards were purposefully selected as an ACL prevalence of >2% had been observed during a survey conducted in 2002 ( Reithinger et al . , unpublished ) . ACL transmission is from April to October , but cases are seen throughout the year due to the disease's long pre-patent period ( up to 6 months ) [2] . Wards were divided into clusters of 10 households on a map provided by the Kabul Institute of Cartography , with 25 randomly-selected clusters in each ward being included in the study . Thus , the total sample was 1 , 000 households , or 250 households in each ward . Household members' demographic , clinical and household data were recorded by trained survey staff using a standardized , pre-tested questionnaire . Demographic data included information on individual household member's age and sex and household family size . For clinical data , medical staff diagnosed disease in household members on the basis of presence or absence of ACL lesions or scars , number of lesions , and date of lesion onset [1] . Because of logistic constraints and the high sensisitivity and specificity of clinical diagnosis , parasitologic diagnosis of ACL lesions ( e . g . microscopic examination or parasite culture ) was not carried out; most of the infections in Kabul are caused by Leishmania tropica [17] . All persons with active lesions were offered free anti-leishmanial treatment at any of the 8 HealthNet TPO leishmaniasis clinics in the city . Household data included information on household design ( i . e . number of rooms , number of windows ) , construction materials ( i . e . wall type , ceiling type ) , ACL preventive methods ( i . e . number of windows screened , household bednet ownership , reported bednet use ) , and ownership of animals ( i . e . household ownership of dogs , chicken , goats , sheep and cattle ) . Questionnaire data was entered into a Microsoft Excel database ( Microsoft Corporation , Seattle , WA ) . In addition to explanatory variables collected during the household surveys , a number of explanatory variables were derived , including household prevalence of active or past ACL , household members per room , number of windows per household members and proportion of household windows screened . Note , for calculation of household prevalence of active or past ACL , the household member under study was excluded from the prevalence calculation . In a first set of analyses , the association of possible household-level explanatory variables with individuals having active ACL or ACL scars was tested by estimating univariate odds ratios ( OR ) by logistic regression . In a second set of analyses , we used backward stepwise multiple regression to identify significant ( p<0 . 05 ) explanatory variables predicting household occurrence of individuals having active ACL or ACL scars [9] . Because ACL transmission in Kabul is focal [1] , we adjusted all of our analyses by individual households to provide robust standard errors . Finally , multicollinearity was assessed by testing the variance inflation factor of explanatory variables prior to their inclusion in the multivariate model [18] . Variance inflation factors >5 indicate collinearity and that variables may be redundant; such variables were dropped prior to inclusion of variables for the full multivariate model . All analyses were done with Stata software , version 9 . 2 ( Stata , College Station , Texas ) . The data reported in the manuscript are part of a larger research study that investigated the efficacy of insecticide-treated bednets for protecting Kabul residents from ACL . Approval to conduct the study was given by the Institute of Malaria and Parasitic Diseases , Afghan Ministry of Health . In 2003 , the Institue of Malaria and Parasitic Diseases did not have an Ethical Review Board; HealthNet TPO is a small non-governmental organization ( NGO ) that does not have an Ethical Review Board either . At the time of the study , the Afghan Ministry of Health and the entire country were still in a status of transition , with many ( previously defunct ) institutions being established or strengthened . As an operational NGO working in complex emergency settings our pimary goal was -whilst adhering to the tenets of the Declaration of Helsinki- to tackle the ACL epidemic that was raging in the city at that time as quickly as possible . As no biological samples were collected and because the study was part of the monitoring and evaluation process of an operational program , only verbal informed consent was obtained from study participants . Consent to participate in interviews was sought from the household heads and each eligible individual; whether consent was given or not was noted on the survey questionnaires .
A total of 996 households were visited; 124 households had incomplete demographic or clinical data and were excluded from the analyses . Of the 10 , 596 people surveyed in the 872 households included ( mean: 12 . 2 persons per household ) , 51 . 1% and 48 . 9% where male and female , respectively; the median age of the study population was 15 years ( interquartile range [IQR] 8–30 ) . Households had a mean 2 . 0 rooms ( range 1–22 ) , 2 . 2 windows ( range 0–18 ) , 4 . 6 household members per room ( range 0 . 18–15 ) and 0 . 4 windows per household member ( range 0–4 ) . Of the population surveyed , 224 ( 2 . 1% ) and 1 , 421 ( 13 . 4% ) had active ACL lesions or scars , respectively; 11 individuals had both lesions and scars ( Figure 1 ) . Of those persons with ACL lesions , the median lesion number was 1 ( IQR: 1–2 ) and the median lesion duration ( to survey date ) was 8 . 5 months ( IQR 0 . 75–48 ) . The median age of those individuals with ACL lesions was 15 years ( IQR 9–30 ) and of those with ACL scars was 18 ( IQR 12–30 ) ( Figure 1 ) . The univariate analysis showed that whereas risk of active ACL was positively associated with household members' age , particularly age groups of 19 years of age and younger ( Figure 1 ) , the prevalence of active ACL , brick walls and population density , it was negatively associated with the household number of rooms and the proportion of windows that are screened ( Table 1 ) . Risk of ACL scars was positively associated with household member's age ( Figure 1 ) , prevalence of ACL scars , number of windows per household member , and brick or stone walls , but negatively associated with household wood-beamed ceilings and population density ( Table 1 ) . Multivariate analyses demonstrated that household member's age , prevalence of active ACL ( Figure 2 ) and brick walls increased the risk for active ACL , whereas the proportion of household windows screened reduced it ( Table 2 ) . Similarly , household member's age , prevalence of ACL scars , and brick or stone walls increased risk of ACL scars , whereas increased household prevalence of active ACL , wood-beamed ceilings and population density reduced it ( Table 2 ) .
In 2003 ten clinics diagnosed and treated leishmaniasis cases in Kabul [1] , but it was estimated that only 40% ( i . e . ∼25 , 000 cases ) of all active cases were being treated annually . As ACL in Kabul is transmitted anthroponotically , this means that up to 60% of cases remained untreated and , hence , remain the main ACL reservoirs driving transmission . This may explain why the witnessed epidemic has been so prolonged since first documented in 1990 [12] . Given that Kabul is the world's largest ACL foci and given the local importance of the disease , it is recommend that large-scale strategies to reduce sand fly human vector contact , and provision of treatment be implemented . Clearly , we show that when designing an ACL intervention strategy , household variables that could represent a risk factor for infection and , therefore , could impact the intervention's success or failure should be assessed . As shown here simple measures , such as screening of windows , could significantly reduce the risk of acquiring ACL . | Cutaneous leishmaniasis is a vector-borne protozoan disease that is characterized by cutaneous lesions which develop at the site of the insect bite . Lesions can vary in severity , clinical appearance , and time to cure; in a proportion of patients lesions can become chronic , leading to disfiguring mucosal leishmaniasis or leishmaniasis recidvans . Albeit not fatal , cutaneous leishmaniasis can have a significant social impact as it may lead to severe stigmatisation of affected individuals when lesions or scars occur on the face and exposed extremeties . Over the last 10–20 years there has been an increase in the number of leishmaniasis cases reported in South Asia , particularly in Afghanistan . Little is known about the household-level risk factors for infection and disease . Here we confirm previous reports that had shown the association of cutaneous leishmaniasis with age and clustering of cases at the household-level . Additionally , we show that risk of cutaneous leishmaniasis is associated with household construction ( i . e . brick walls ) and design ( i . e . proportion of windows with screens ) . | [
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] | 2010 | Risk Factors for Anthroponotic Cutaneous Leishmaniasis at the Household Level in Kabul, Afghanistan |
Strongyloidiasis is one of the most neglected diseases distributed worldwide with endemic areas in developed countries , where chronic infections are life threatening . Despite its impact , very little is known about the molecular biology of the parasite involved and its interplay with its hosts . Next generation sequencing technologies now provide unique opportunities to rapidly address these questions . Here we present the first transcriptome of the third larval stage of S . stercoralis using 454 sequencing coupled with semi-automated bioinformatic analyses . 253 , 266 raw sequence reads were assembled into 11 , 250 contiguous sequences , most of which were novel . 8037 putative proteins were characterized based on homology , gene ontology and/or biochemical pathways . Comparison of the transcriptome of S . strongyloides with those of other nematodes , including S . ratti , revealed similarities in transcription of molecules inferred to have key roles in parasite-host interactions . Enzymatic proteins , like kinases and proteases , were abundant . 1213 putative excretory/secretory proteins were compiled using a new pipeline which included non-classical secretory proteins . Potential drug targets were also identified . Overall , the present dataset should provide a solid foundation for future fundamental genomic , proteomic and metabolomic explorations of S . stercoralis , as well as a basis for applied outcomes , such as the development of novel methods of intervention against this neglected parasite .
Strongyloidiasis caused by Strongyloides stercoralis is a soil-transmitted helminthiasis distributed worldwide , affecting more than 100 million people , with endemic areas in Southeast Asia , Latin America , sub-Saharan Africa , and parts of the southeastern United States [1] , [2] . Recently , it was classified as one of the most neglected tropical diseases ( NTD ) [3] . Chronic infections in endemic areas may be maintained asymptomatically for decades through the autoinfective cycle with the filariform larvae L3 [1][4] , [5] . The diagnosis of these chronic infections requires more sensitive diagnostic methods , particularly in low-level infections and immunocompromised patients [1] . Epidemiological studies in developed countries have identified endemic areas where misdiagnosis , inadequate treatment and the facilitation of hyperinfection syndrome by immunosupression ( i . e . by the administration of steroids ) are too frequent and can cause a high mortality rate ranging from 15 to 87% [5] , [6] . Among these areas , an endemic area with chronic patients have been described at the Valencian Mediterranean coastal region of Spain related to environmental conditions [7] . The diagnosis of strongyloidiasis is suspected when clinical signs and symptoms , or eosinophilia is observed [8] , but current definitive diagnosis of strongyloidiasis is usually made on the basis of detection of larvae in agar plate coproculture and serological diagnosis by ELISA [9] , [10] . Those methods have the drawbacks of being time consuming and requiring expertise in the first case , and of low specificity due to remaining antibodies from previous infection or cross-reactive antibodies [11] . A recent paper has described a promising coproantigen ELISA based on a polyclonal rabbit antiserum raised against excretory/secretory ( ES ) antigens from the closely relative Strongyloides ratti [12] , but the identification of S . stercoralis specific ES proteins that could be new potential targets for diagnosis is still required . Control of strongyloidiasis has relied mostly on the treatment of infected individuals with only three anthelmintic drugs: thiabendazole ( no longer available ) , albendazole , and more recently ivermectin [3] , [13] . A recent study by Suputtamongkol et al . ( 2011 ) has confirmed that both a single and double dose of oral ivermectin are more effective than a 7-day course of high dose albendazole for patients with chronic infection due to S . stercoralis [14] . The risk of developing genetic resistance against the current drugs administered ( if used excessively and at suboptimal dosages ) exists and is based on the experience with drug resistance in parasitic nematodes of livestock [15] . Thus , the current focus is on the discovery of novel drugs against human parasites like S . stercoralis . Such a discovery effort could be strengthened with an integrated genomic and bioinformatics approach , using functional genomic and phenomic information available for the free-living nematode Caenorhabditis elegans ( see WormBase; www . wormbase . org ) . This nematode , which is the best characterized metazoan organism [16] , [17] , is considered to be related to nematodes of the order Strongylida ( to which Strongyloides belong ) [18] . Recent studies have reported that nearly 60% of genes in strongyloides have orthologues/homologues in C . elegans , with a wide range of biological pathways being conserved between parasitic nematodes and C . elegans [19] . The comparison of molecular data sets between nematodes should therefore allow the identification of specific biological pathways as potential new targets for nematocidal drugs [20] . As pointed out recently by Cantacessi et al . ( 2011 ) [20] , advances in genomic sequencing like Next Generation Sequencing ( NGS ) and annotation as well as the integrated use of ‘-omic’ technologies are now shedding light on our understanding of the systems biology of nematodes on an unprecedented scale , and is likely to provide unique opportunities for the development of entirely new strategies for the treatment and control of neglected parasitic diseases . New bioinformatic tools based on robust assembly protocol for NGS data , along with compilation of a dataset of experimentally determined ES proteins of parasitic helminths , and annotation software like KAAS [21] , allow efficient and up-to-date homology-based predictions [22] . To date , there are few molecular and genomic studies on Strongyloides species , and only the transcriptome from S . ratti adults has become recently available ( http://worm1 . liv . ac . uk/file_summary . html ) [23] . In fact , 39166 ESTs are currently available in the NCBI database of November 2011 ( 27366 from S . ratti and 11392 from S . stercoralis ) . Yoshida et al . ( 2011 ) have obtained 162 unique singletons and contigs from S . venezuelensis [24] , and a recent study by Ramanathan et al . ( 2011 ) has described DNA microarray for S . stercoralis and used them to compare infective third-stage larvae ( L3i ) with non-infective first stage larvae ( L1 ) , with 935 differentially expressed genes identified [25] . In the present study , we have explored and functional annotated the transcriptome of L3i of S . stercoralis by 454 sequencing coupled to semi-automated bioinformatic analyses and predicted potential therapeutic targets for strongyloidiasis .
The nucleotide sequence data obtained for this study are available in the GenBank database under accession number ERP000798 . The assembled data from this study can be requested from the corresponding author . Fecal samples were obtained at the Hospital La Ribera , Alzira , Valencia ( Spain ) from an infected individual in compliance with Spanish ethical regulations [7] , and approved by the Ethics Committee in human research from the Universitat de Valencia . Oral consent from the patient was obtained ( she was happy to participate in the study but felt uncomfortable with signing a form ) , and documented as a tick on the case record form following the Hospital Reviewing Board protocols . Samples were cultured on Agar Petri dishes and L3i larvae were harvested and concentrated by centrifugation for 5 min at 1000 g , washed three times in 1 ml of phosphate buffered saline ( PBS ) pH 7 . 2 containing protease inhibitors ( 10 mM EDTA , and 1 mM PMSF ) and samples were processed for RNA isolation . Total RNA from around 500 larvae was prepared using Vantage™ Total RNA purification kit ( Marligen Biosciences , Ijamsville , MD , USA ) following the manufacturers' instructions and treated with Ambion DNA-free™ DNase ( Ambion/Applied Biosystems , Austin , TX ) . The integrity of the RNA was verified by gel electrophoresis and the yield determined using the nanoDrop ND-1000 UV-VIS spectrophotometer v . 3 . 2 . 1 ( NanoDrop Technologies , Wilmington , DE ) . The cDNA library was constructed from 0 . 5 µg total RNA using MINT cDNA Synthesis Kit ( Cat#SK001 , Evrogen ) . First strand cDNA synthesis starts from 3′-primer comprising oligo ( dT ) to enrich mRNA as template . Double strand cDNA synthesis was performed using 17 cycles of PCR amplification . Total cDNA was digested with restriction enzyme GsuI in order to remove Poly ( A ) tails . cDNA obtained was used to perform a library with the required sequencing adaptors and was then sequenced using the Genome Sequencer ( GS ) FLX instrument ( Roche Diagnostics ) [26] . The overall bioinformatics analysis strategy followed was as described originally by Nagaraj et al . [27] , [28] , implemented in the analysis pipelines ESTExplorer [29] and EST2Secretome [28] . This workflow approach has been successfully used for the analysis of transcriptomic data from Dictyocaulus viviparus [30] , Fasciola hepatica [31] , Clonorchis sinensis [32] and Opisthorchis viverrini [32] . However , to better identify non-classically secreted proteins from helminth parasites [33] , [34] , we have recently implemented a novel analysis strategy for short reads applied on Strongyloides ratti [22] ( see Figure S1 ) . FASTA and associated quality files were extracted from the SFF file after removing the sequence adapters . These reads were preprocessed and their contigs were assembled using MIRA v . 3 . 2 ( http://chevreux . org/projects_mira . html ) [35] with the following parameters: -job = denovo , est , accurate , 454 -fasta -OUT:rrol = 1:rld = 1:orc = 1:org = 0:ora = 0:ors = 0:otf = 0:otc = 0 -GE:not = 1 -CO:asir = 1 -LR:mxti = 1 -AS:sd = 0:uess = 0:urd = 0:ard = 1 -SK:mmhr = 2:mnr = yes 454_SETTINGS -DP:ure = 0 -CO:mrpg = 10 -AS:bdq = 40 -CL:pvlc = 0:cpat = 0:mbc = 1:mbcgs = 30:mbcmfg = 30:mbcmeg = 30:qc = 0 -ED:ace = 1 -AL:egp = no -ALIGN:bip = 20:bmax = 120:mo = 10 . Contigs generated from MIRA were aligned and reassembled into second order contigs using the Contig Assembly Program v . 3 ( CAP3 ) [36] , employing a minimum sequence overlap length cut-off of 40 bases and an identity threshold of 90% . Following the assembly of S . stercoralis reads into second order contigs by CAP3 and contigs by MIRA , this contig dataset was matched using BLASTX with the NCBI non-redundant sequence database; http://www . ncbi . nlm . nih . gov , BLASTN with Nematode . net S . stercoralis ESTs ( www . nematode . net/ ) and BLASTN with dbEST Strongyloides ESTs ( www . ncbi . nlm . nih . gov/dbEST/ ) , using permissive ( E-value: <1E−05 ) , moderate ( <1E−15 ) and/or stringent ( <1E−30 ) search strategies . S . stercoralis contigs were conceptually translated into putative proteins using the program ESTScan [37] . Putative protein sequences were subjected to secretome analysis using TMHMM ( a membrane topology prediction program ) [38] to predict transmembrane domains , SignalP 3 . 0 ( signal peptide prediction program ) [39] , SecretomeP ( a prediction programme used to identify non-classical secretory proteins in mammals [40] , but used in the case of parasitic helminths as well [41] ) , and TargetP ( mitochondrial protein prediction program ) [42] . Briefly , excretory/secretory ( ES ) proteins were selected based on the presence of a signal peptide at the N-terminus using SignalP 3 . 0 ( employing both the neural network and hidden Markov models ) or predicted as secretory using SecretomeP , predicted as non-mitochondrial by TargetP and absence of transmembrane domains . In addition to computational prediction of ES proteins were identified and collated based on sequence homology ( BLASTP , E-value<1E−15 ) to known ES proteins found in parasitic helminths secretome studies . Putative proteins were classified functionally using InterProScan [43] , employing the default search parameters . Based on their homology to conserved domains and protein families , predicted proteins were classified into Gene Ontology ( GO ) categories ( http://www . geneontology . org/ ) based on molecular function , cellular component and biological process using interpro terms . Putative proteins were also subjected to pathway analysis , utilizing KEGG-Automatic Annotation Server ( KAAS ) [21] , which maps the putative proteins to biochemical pathways in which they are involved and categories of Brite objects like enzymes , transcription factors and translation factors . Putative proteins were subjected to BLAST2GO software to identify homologues from the most abundant ES transcripts [44] . BLASTP ( Wormpep v 224 ) was used to identify C . elegans known proteins homologues present in S . stercoralis proteins using moderate search strategy ( E-value: <1E−15 ) . These proteins were also searched for sequence homology ( BLASTP , E-value<1E−05 ) in human ( host ) proteins . All the proteins which were found homologous to C . elegans proteins and non-homologous to human proteins were mapped to C . elegans RNAi phenotypes and known drug targets present in the DrugBank database ( http://drugbank . ca/ ) , a unique bioinformatics and cheminformatics resource that combines detailed drug ( i . e . chemical , pharmacological and pharmaceutical ) data with comprehensive drug target ( i . e . sequence , structure , and pathway ) information [45] .
Initially a total of 253266 short reads ( 82490223 bases ) were generated with 325±132 . 4 bases ( average length ± standard deviation ) , with a GC content of 31 . 84% . These short reads were pre-processed , which resulted in 237341 ( 93 . 7% ) quality short reads ( EBI Sequence Read Archive [SRA] accession ID ERP000798 ) . High quality reads were assembled into 12333 contigs using MIRA as described in the pipeline ( Figure S1 ) . Using CAP3 , we were able to achieve 507 second order contigs , leaving 10845 MIRA contigs not assembled further by CAP3 . We considered 11250 ( 99 . 1% ) contigs with a minimum length of 90 bases , discarding sequences yielding peptides <30 amino acids , for further secretory protein prediction and analysis . These contigs were conceptually translated into 8037 proteins by ESTScan ( Table 1; sequences available from http://biolinux . uv . es/marcilla/ ) . Putative proteins were annotated based on protein families and domains using Interproscan and mapped to biochemical pathways using KAAS [21] . Of the 8037 putative proteins , we were able to annotate 4494 ( 55 . 91% ) proteins with protein domains and families ( Table 1 ) . The most represented Interpro terms are shown in Table S1 . A total of 3534 proteins were annotated with GO terms ( 3083 {Molecular Function} , 1068 {Cellular Component} and 1905 {Biological Process} ) based on Interpro term annotations ( Tables 1 and S1 ) . We established pathway associations for 1559 ( 19 . 39% ) putative proteins ( Table 1 ) . All the contigs generated by using MIRA+CAP3 were checked for homologous proteins against the non-redundant nucleotide database ( NR-NCBI ) , existing Strongyloides expressed sequence tags ( ESTs ) present in dbEST , S . stercoralis ESTs available from dbEST and nematode . net , S . ratti cDNA sequencing data from the University of Liverpool ( available at http://worm1 . liv . ac . uk/file_summary . html ) , and also for homologous proteins in C . elegans and human data ( Figure S1 ) . Similarity searches were done using using BlastX and BlastP algorithms at different E values ( Table 2 ) . A total of 3412 ( 42 . 45% ) S . stercoralis putative proteins had homologues in the free-living nematode , Caenorhabditis elegans using stringent match conditions ( E value: <1E−15 ) . The recent availability of S . ratti transcriptome data prompted us to compare these with our data and 3855 similar putative proteins ( 47 . 96% ) were found . As S . stercoralis infects humans , we checked the similarity of S . stercoralis proteins with known human proteins using BlastP at different E values . Our results showed that 3759 putative proteins were similar to human ones using a permissive search strategy ( E-value: <1E−05 ) , discarding them as potential targets for treatment ( Table 2 ) . Predicted proteins were also categorized according to their inferred molecular function , cellular localization and association with biological pathways . Mapping to KEGG BRITE objects [46] is shown in Table 3 . Enzymes were by far the most abundant category , with 720 putative proteins , followed by chromosome , spliceosome and ribosome components ( with 90 , 89 and 73 putative proteins , respectively ) . 73 putative protein kinases and 72 peptidases were also identified by BRITE ( Table 3 ) . These 72 peptidases corresponded to 60 different enzymes from 9 groups , including calpains , cathepsins , different proteasome components and aminopeptidases , and other “nematode common” proteases such as astacin , legumain , and insulysin ( Table S2 ) . All the putative proteins were grouped according to KEGG pathways [46] into five categories , with metabolic proteins being the most abundant , followed by genetic information processing , environmental processing and cellular processes ( Table 4 ) . In the first group , the most abundant putative proteins were related to carbohydrate metabolism ( 201 proteins , 2 . 5% ) , amino acid metabolism ( 174; 2 . 16% ) and lipid metabolism ( 104; 1 . 29% ) . Also 23 putative proteins were related to drug metabolism ( Table 4 ) . In the second group , the most abundant proteins were related to translation ( 195; 2 . 42% ) , meanwhile 144 putative proteins ( 1 . 79% ) related to signal transduction were the most abundant in the group of cellular processes ( Table 4 ) . We next analyzed ES proteins , which are key molecules to understand host-parasite interactions [47] . Molecules from the secretome contribute to important processes like parasite feeding , tissue penetration or larval migration , and could participate in blocking and/or evading host immune responses [48] . ES prediction was carried out in Phase III of the pipeline ( Fig . S1 ) . Firstly , 247 ( 3 . 07% ) proteins were predicted as classical secreted proteins using SignalP [39] . The remaining 7785 ( 96 . 86% ) proteins , which were predicted as non-secretory by SignalP were processed by SecretomeP [40] for prediction of non-classical secretory proteins , with 252 ( 3 . 14% ) proteins identified here . The classical and non-classical secretory proteins ( 499 , 6 . 21% ) from these two programs were analyzed by TargetP [42] for mitochondrial proteins . Only 7 proteins were predicted as mitochondrial proteins using TargetP at 95% specificity . These seven proteins were removed from the set of 499 secreted proteins , with 492 secretory proteins passed to TMHMM [38] for the prediction of transmembrane proteins . 161 ( 2% ) proteins , were predicted as transmembrane proteins having one or more transmembrane helices , and removed from the secretory protein dataset . A total of 331 ( 4 . 12% ) proteins were finally predicted as ES proteins from the computational prediction pipeline . Proteins that were considered non-secretory by SecretomeP and SignalP were matched to our in-house dataset of 1080 non redundant experimentally determined parasitic helminth proteins [22] using the BLASTP [49] similarity search . We found an additional 882 ( 10 . 97% ) putative proteins similar to known ES proteins by this homology search approach ( E value: <1E−15 ) ( Table S3 ) . From those proteins , 50 have been recently described in the ES from infective larvae of the related species S . ratti [50] ( data not shown ) . Among the most abundant transcripts encoding ES proteins appeared a major antigen; cytoskeletal proteins like myosin heavy chain , troponin , tropomyosin , actin; galectins; enzymes like trehalase , PEPCK , GAPDH , enolase , as well as phosphatases and kinases; proteases like Metalloproteinase , Calpain-1and Cathepsin L; stress proteins like HSPs; calcium binding proteins; detoxifying enzymes along with elongation factors , histones , ubiquitins and signaling molecules ( Table S4 . Thus , for annotation and analyses in Phase III , we compiled a total of 1213 ES proteins , which is 15 . 09% of our putative proteins . We found 4234 ( 52 . 68% ) S . stercoralis putative proteins which had no homologues present in humans ( Table 2 ) and therefore are preferred targets for parasite intervention strategies . These human dissimilar proteins of S . stercoralis were checked for known drug targets , which have lethal RNAi phenotypes present in C . elegans , not present in human and similar to known drug targets , data available from DrugBank 3 . 0 database [44] , a unique bioinformatics and cheminformatics resource that combines detailed drug ( i . e . chemical , pharmacological and pharmaceutical ) data with comprehensive drug target ( i . e . sequence , structure , and pathway ) information . The database ( available at http://drugbank . ca/ ) contains 6707 drug entries ( as of November 2011 ) . We found 14 contigs and singletons corresponding to four different proteins . These could represent potential therapeutic targets for strongyloidiasis as shown in Table 5 . Sequence comparison demonstrate that these proteins are homologous to 2 , 3-bisphosphoglycerate independent phosphoglycerate mutase from Ascaris suum ( with 1 contig and 1 singleton ) , hypothetical protein CBG01975 from Caenorhabditis briggsae similar to glutamate synthase [NADPH] from Ascaris suum ( 1 contig and 3 singletons ) , isocitrate lyase from S . stercoralis ( 5 singletons ) , and alcohol dehydrogenase I from the fungus Candida albicans WO-1 ( 2 singletons ) ( Table 5 ) . With a comparative analysis searching protein domain mapping or sequence similarity with other drug targets , we found seven additional potential targets for treatment , including well known drug targets as tubulin β , γ-amino butyric acid A ( GABA ) receptor , glutamate-gated chloride channel or GST ( Table S5 ) . Only one of those proteins , homologous to Ancylostoma caninum metalloprotease precursor , which is also predicted to be secretory , was not found similar either to C . elegans or human proteins ( Table S5 ) .
Strongyloides stercoralis can replicate within the host ( autoinfection ) allowing the infection to remain undiagnosed and untreated for years , resulting in perpetuating parasite dispersal , increasing the risk of infection and eventually the appearance of resistances [3] . Uncontrolled multiplication of the parasite ( hyperinfection ) can be life-threatening in immunocompromised individuals . We also face serious endemic recurring infections in the future if this infection is not controlled in transition economies like China , India , Southeast Asia and Latin America [3] where the use of immunosuppressive therapy is becoming common . As pointed out by Olsen et al . ( 2009 ) [3] , there is an urgent need to employ modern molecular methods to improve and simplify diagnosis , differentiate species and strains to facilitate epidemiological studies of S . stercoralis . The present study provides the first detailed analysis of the transcriptome of the human pathogenic S . stercoralis L3i larvae and has identified specific molecules predicted to play key biological functions in this parasite . A total of 12 , 333 contigs were inferred from the present EST dataset , thus increasing the number of predicted proteins currently available ( for this stage/species ) in public databases by approximately 141-fold [we obtained 8037 conceptually translated proteins , and there are currently 57 proteins in Genbank as of November 2011] . This quantity of contigs is similar to the numbers obtained with other nematodes like Trichostrongylus colubriformis [19] , N . americanus and Ancylostoma caninum [51] , Haemonchus contortus [52] , Dictyocaulus viviparous [20] , and Teladorsagia circumcinta [53] . The subset ( 55 . 91% ) of S . stercoralis sequences with orthologues/homologues in public databases was slightly higher to that reported in similar transcriptomic studies of other animal-parasitic helminths such as Necator americanus [51] , [54] . It is noteworthy to mention that 44 . 09% of the putative proteins of S . stercoralis L3i transcriptome remain unannotated , warranting further genomic and functional characterization studies . With the exception of three metabolic proteins ( citrate synthase , arginine kinase and ATP:guanido phosphotransferase ) all proteins identified in a previous proteomic study with S . stercoralis L3i [55] were included in the transcriptome described here . In addition , 41 antigenic proteins including SiR and tropomyosin were present in the transcriptome ( as searched in Table S1 ) , confirming its value as a tool for searching targets for immunodiagnosis . It is well characterized that upon infection , infective larvae ( L3i ) must penetrate skin as quickly as possible and then migrate within the host . In this context , proteases play an essential role . Among the proteins identified in our study , 60 different putative proteases were annotated in nine groups . These include nine metalloproteinases and three aspartic proteases , some of them assumed to play a major role in skin penetration in Strongyloides stercoralis [56] , [57] , and in other Strongyloides species like S . venezuelensis [58] or S . ratti [22] , [23] . In S . venezuelensis , Yoshida et al . ( 2011 ) [24] have recently identified an astacin-like metalloproteinase as being specific of L3i in a transcriptomic study . Another abundant group was the cysteine proteases , including cathepsin B , legumain and calpain , proteins characterized as immunomodulators of host response and promising vaccine and drug targets [59]–[61] . Similar results have been reported for Ascaris suum , where 456 peptidases have been identified in its draft genome [62] . Kinases are also an important group of proteins considered to be good druggable targets from the medical and chemical viewpoints , since they play essential functions in the parasite , in mediating signal transduction [63]–[65] . In S . stercoralis L3i transcriptome analysis 73 putative kinases including 11 putative tyrosine kinases were identified ( Table 3 and Table S1 ) . In our study , we have compiled 1213 putative ES proteins among the 8037 ( 15 . 09% ) S . stercoralis annotated proteins using a new semi-automated computational approach , recently developed and applied to predict the secretome of S . ratti adults [22] . In a mixture of S . ratti parasitic females , free-living males and free-living females , Garg and Ranganathan ( 2011 ) compiled 2572 putative ES proteins , being 12 . 3% of the total putative proteins , which is less than that found in S . stercoralis L3i larvae [22] . This could be due to higher secretion processes in larvae in comparison to adults , required by penetration and migration in the host . Supporting this notion , Soblik et al . ( in press ) have recently described the presence of 586 ES proteins in all the stages of S . ratti by proteomic analysis , 196 of which are also found in L3i [50] . When comparing larval S . ratti ES proteins with our predicted S . stercoralis L3i ES proteins , we find that 50 out of the 196 proteins identified from S . ratti were also detected in S . stercoralis L3i , supporting the value of the prediction . In S . stercoralis L3i , the most abundant transcripts encoding ES proteins include cytoskeletal proteins ( i . e . myosin heavy chain , actin , tropomyosin , tubulin or paramyosin ) , metabolic enzymes ( i . e . Trehalase , PEPCK , PGK , PGM , GAPDH , enolase ) , proteases , stress-response proteins , detoxifying enzymes , proteaseome components , most of them identified previously in S . stercoralis by proteomic studies [55] . These ES proteins play a major role in infection since they are present at the host-parasite interface and regulate host immune system [66] . ESPs also are among the target choice of new therapeutic solutions for helminth infections [67] , as confirmed in the case of ivermectin ( the currently the drug of choice for treating strongyloidosis ) which has been shown to act reducing the secretion of ESPs from the ES apparatus in Brugia malayi microfilariae [68] . Recent studies using microarrays have identified highly expressed molecules in S . stercoralis L3i in comparison to L1 larvae , including cytochrome bc1 , Hsp-90 and FAR-1 , which potentially constitute new targets for intervention [25] , all of which were present in our transcriptome data , but did not appear as druggable targets following our pipeline , possibly as these are not present in DrugBank , where only lethal RNAi phenotypes are included . Other important targets if interfered with , would still lead to expulsion of live worms form a host , like motility genes . In agreement with this , Garg and Ranganathan ( 2011 ) [22] have recently identified 19 contigs as putative drug targets in the S . ratti adult transcriptome , including myosin heavy chain , which is also one of the most abundant transcript of ES proteins in S . stercoralis ( Table S4 ) . This protein along with others like a metalloproteinase precursor , major sperm protein or triosephosphate isomerase ( also identified in the S . stercoralis transcriptome in our study ) did not appear as druggable molecules in our study , due to the presence of these proteins in host cells as well . In this context , efficient drugs as antihelmintics like benzimidazoles ( they inhibit tubulin ß resulting in impaired microtubule formation during cell division ) have much more affinity for tubulin in helminth cells than the tubulin found in the cells of mammals [69] . We found 11 potential targets for treatment against L3i larvae . As already mentioned , these are the first evolutive phase of S . stercoralis in the host , and constitute a good target for treatment . From these target molecules , four , with no homologues in the host , suggesting parasite specificity , are: 2 , 3-bisphosphoglycerate independent phosphoglycerate mutase , glutamate synthase , isocitrate lyase and alcohol dehydrogenase I . Only the first one was predicted as present in ES . Further studies are required to confirm whether these molecules are good drug targets for strongyloidiasis . Next-generation sequencing technologies are improving genomic and transcriptomic studies , and complemented by proteomic investigations , should allow the characterization of differential gene expression and essential pathways in all the developmental stages of S . stercoralis . The transcriptomic dataset described here constitutes the basis for future investigations enlightening the search for control measures for one of the most neglected diseases . | Strongyloides stercoralis ( Nematoda ) is an important parasite of humans , causing Strongyloidiasis , considered as one of the most neglected diseases , affecting more than 100 million people worldwide . Chronic infections in endemic areas can be maintained for decades through the autoinfective cycle with the L3 filariform larvae . In these areas , misdiagnosis , inadequate treatment and the facilitation of hyperinfection syndrome by immunosupression are frequent and contribute to a high mortality rate . Among the affected areas , chronic patients have been described in the Valencian Mediterranean coastal region of Spain . Despite its serious impact , very little is known about this parasite and its relationship with its hosts at the molecular level , and more effective diagnostic tests and treatments are needed . Next generation sequencing technologies now provide unique opportunities to rapidly advance in these areas . In this study , we present the first transcriptome of S . stercoralis L3i using 454 sequencing followed by semi-automated bioinformatic analyses . Our study identifies 8037 putative proteins based on homology , gene ontology , and/or biochemical pathways , including putative excretory/secretory proteins as well as potential drug targets . The present dataset provides a useful resource and adds greatly to our understanding of a human parasite affecting both developed and developing countries . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [
"medicine",
"infectious",
"diseases",
"neglected",
"tropical",
"diseases",
"parasitic",
"diseases"
] | 2012 | The Transcriptome Analysis of Strongyloides stercoralis L3i Larvae Reveals Targets for Intervention in a Neglected Disease |
Studies in malaria patients indicate that higher frequencies of peripheral blood CD4+ Foxp3+ CD25+ regulatory T ( Treg ) cells correlate with increased blood parasitemia . This observation implies that Treg cells impair pathogen clearance and thus may be detrimental to the host during infection . In C57BL/6 mice infected with Plasmodium berghei ANKA , depletion of Foxp3+ cells did not improve parasite control or disease outcome . In contrast , elevating frequencies of natural Treg cells in vivo using IL-2/anti-IL-2 complexes resulted in complete protection against severe disease . This protection was entirely dependent upon Foxp3+ cells and resulted in lower parasite biomass , impaired antigen-specific CD4+ T and CD8+ T cell responses that would normally promote parasite tissue sequestration in this model , and reduced recruitment of conventional T cells to the brain . Furthermore , Foxp3+ cell-mediated protection was dependent upon CTLA-4 but not IL-10 . These data show that T cell-mediated parasite tissue sequestration can be reduced by regulatory T cells in a mouse model of malaria , thereby limiting malaria-induced immune pathology .
Severe malaria syndromes , including cerebral malaria ( CM ) , claim the lives of approximately 900 , 000 people annually , mostly children under the age of 5 living in sub-Saharan Africa [1] . The mechanisms of CM pathogenesis remain poorly understood , since studies in humans are often restricted to post-mortem examinations . In particular , the roles played by the host immune response in either driving or preventing CM are unclear . It is possible that the immune response could be over-exuberant in some CM patients or lethargic in others , the balance of which may depend on the patient's and the parasite's genetic background . Several studies in malaria patients have reported associations between higher frequencies of peripheral blood regulatory T ( Treg ) cells and increased parasitemia [2] , [3] , [4] . However , these studies provided limited mechanistic insight into the role of Treg cells in severe malarial disease . Under homeostatic conditions , Treg cells limit potentially aberrant T cell responses , thus preventing autoimmunity [5] . However , they can also impair effective pathogen clearance [6] , [7] , [8] , while potentially playing a beneficial role in preventing immune-pathology during infection . The molecular mechanisms by which Treg cells perform these functions are incompletely understood , but have been reported to involve production of cytokines such as TGFβ and IL-10 , and increased expression of the negative regulatory molecule CTLA-4 [9] , [10] , [11] . Furthermore , it is not known whether Treg cells act directly upon conventional T cells or on accessory cells such as antigen-presenting cells . Nevertheless , Treg cells are often viewed as detrimental during infection , since they may impede the generation of effective pathogen-specific T cell responses . Thus , an emerging paradigm is that Treg cells block T cell-mediated clearance of malaria parasites in humans , facilitating an increase in parasitemia . The direct study of immune mechanisms in malaria patients is problematic for obvious practical and ethical reasons . Therefore , mouse models of severe and non-severe malaria have been employed to study the immune response to infection . Studies in an experimental model of cerebral malaria ( ECM ) caused by infection of C57BL/6 mice with P . berghei ANKA ( PbA ) have highlighted the important role played by various immune cells in disease pathogenesis , including CD4+ T cells , CD8+ T cells , conventional dendritic cells and Natural Killer ( NK ) cells [12] , [13] , [14] , [15] , [16] , [17] , [18] . In mice that succumb to ECM , parasite biomass is poorly controlled and there is clear evidence of immune-mediated parasite tissue sequestration [19] . Until recently , the deleterious role proposed for Treg cells in studies of human malaria has been difficult to test in mice , due to the lack of appropriate reagents [20] , [21] . Our initial studies indicated a detrimental role for Treg cells because depletion of CD25hi cells prior to infection , the majority of which were Treg cells , protected mice from ECM and was associated with increased antigen-specific CD4+ T cell responses [20] . Recently however , specific depletion of FoxP3+ Treg cells did not protect against ECM , bringing into question the role for these cells in mediating disease [22] . Although the effect of Treg cell depletion on T cell responses and pathogen burden was not studied [22] , given that ECM is mediated by pathogenic T cells that promote parasite tissue sequestration [19] , we hypothesized that under certain conditions , Treg cells can suppress deleterious T cell responses and protect against ECM . One approach to manipulate Treg cell numbers in vivo has been to use IL-2/anti-IL-2 antibody complexes to potentiate IL-2 signalling and drive expansion of FoxP3+ Treg cells [23] . Certain monoclonal antibodies ( mAbs ) bind to IL-2 in such a way that its signalling capacity is preserved , while its in vivo half-life is dramatically extended [24] . Moreover , different mAbs against IL-2 bind to different regions of the molecule , thus skewing its signalling capacity [25] . For example in mice , IL-2 bound to S4B6 mAb is not capable of interacting with the high affinity , heterotrimeric IL-2 receptor , but does interact with the lower affinity heterodimeric receptor . In contrast , IL-2 bound to JES6-1A12 mAb retains the ability to interact with the higher affinity receptor . IL-2/anti-IL-2 complexes profoundly alter lymphocyte dynamics during homeostasis , autoimmunity and vaccination [23] , [25] , [26] , [27] , [28] . Recently , IL-2/JES6-1A12 was shown to expand Treg populations , prevent auto-immunity and induce long term graft tolerance [23] . Here , we show for the first time that while removal of naturally-occurring Treg cells minimally affects the course of disease , increasing their numbers in vivo throughout the course of infection via IL-2/anti-IL-2 antibody complexes allows these cells to protect against ECM .
The foxp3-DTR transgenic ( DEREG ) mouse was recently used to deplete Foxp3+ cells prior to and over the course of PbA infection , with no impact on susceptibility to ECM [22] . We employed the same system here to study the effect of Foxp3+ cell depletion on T cell responses and pathogen burden during ECM . Consistent with the published data , in our hands DEREG mice depleted of Foxp3+ cells the day prior to , and over the course of infection ( Figure 1A ) , remained as susceptible to ECM as Foxp3+ cell replete DEREG mice ( data not shown ) . Furthermore , we observed no change in whole body parasite burden ( Figure 1B ) ; with a trend towards an increase in the splenic IFNγ+ CD4+ T cell response ( Figure 1C ) . These data show that the depletion of Foxp3+ cells had little effect on pathogen burden or disease outcome during ECM . Since removal of Foxp3+ cells had no effect on disease progression , we next examined whether increasing numbers of Foxp3+ cells would impact upon ECM development . Therefore C57BL/6 mice were infected with PbA and immediately treated with a single dose of IL-2/JES6-1A12 ( hereafter referred to as IL-2Jc ) or IL-2/S4B6 ( IL-2Sc ) complexes . The IL-2Jc complex binds the high affinity heterotrimeric IL-2 receptor to drive Treg cell expansion , while the IL-2Sc complex binds the lower affinity heterodimeric IL-2 receptor resulting in the expansion of activated CD8+ T cells and NK cells [25] . Control mice that received rat IgG displayed clinical signs of illness from day 6 post-infection ( p . i ) , and succumbed to infection with neurological symptoms typical of ECM with a Median Survival Time ( MST ) of 8 days ( Figure 2A ) . Mice treated with IL-2Sc were also susceptible to ECM ( MST: 7 days ) , demonstrating that IL-2Sc afforded no protection against infection ( Figure 2A ) . In stark contrast , IL-2Jc treated , infected mice , rarely displayed ECM symptoms and were protected from ECM-related morbidity , dying instead from hyperparasitemia with an MST of 28 days ( Figure 2A ) . Mice treated with S4B6 alone , JES6-1A12 alone or recombinant IL-2 alone , were as susceptible to ECM as control mice ( Figures 2B & 2C ) . Together , these data demonstrate a specific capacity for IL-2Jc , but not its component parts in isolation or an alternative IL-2 antibody complex ( IL-2Sc ) , to protect against ECM . To investigate the timing and dosing requirements for IL-2Jc-mediated protection , PbA-infected mice were treated on days 0 or 2 p . i . , or on both days with either a standard IL-2Jc dose ( 1 . 5ug cytokine: 50ug antibody ) ( Figure 2D left ) or a ten-fold lower dose ( Figure 2D right ) . Control mice displayed clinical signs of disease from day 6 p . i . , with 100% of mice succumbing to ECM by day 8 p . i . Only mice that had received a standard IL-2Jc dose on day 0 were protected from ECM . Importantly , mice receiving a delayed IL-2Jc dose on day 2 p . i . were completely susceptible to ECM . Thus , IL-2Jc protects against ECM only when administered at the time of infection . C57BL/6 mice typically display ECM symptoms when blood parasitemia reaches ∼7–10% parasitized red blood cells ( pRBCs ) ( Figure 3A ) . Blood parasitemia in IL-2Jc-treated mice was similar to control , infected mice on days 4 & 5 p . i . ( Figure 3A ) . However , from day 6 p . i . onwards , when clinical symptoms appeared in control mice , IL-2Jc treated mice displayed significantly lower blood parasitemia for the following 3 days , only rising again from day 10 p . i . onwards ( Figure 3A ) . While blood parasitemia has been routinely used to monitor disease progression , it is now recognised that measurements of total parasite biomass in the whole body offer a better correlate of the disease status of malaria patients [29] . To assess parasite biomass in infected mice , we used a transgenic PbA strain engineered to constitutively express firefly luciferase ( PbA-luc ) [20] . The bioluminescence generated by PbA-luc parasites at any given time is directly proportional to the sum of parasites in the tissues and circulating blood of the infected animal [19] , [20] , [30] ( Figure 3B ) . IL-2Jc-treated , PbA-luc-infected mice harboured significantly lower parasite biomass compared to control mice on day 6 p . i . , when control animals displayed severe ECM symptoms . Moreover , following whole body perfusion to remove circulating RBCs , brains from IL-2Jc-treated mice also exhibited significantly lower parasite sequestration than brains from control animals ( p<0 . 05 ) ( Figure 3C ) . These data demonstrate that IL-2Jc-mediated protection against ECM was associated with lower parasite biomass and reduced pRBC brain sequestration . ECM is associated with the recruitment of CXCR3+ leukocytes to the brain [13] , [31] , [32] , [33] , [34] , including T cells responsible for disease pathology [16] , [18] . On day 6 p . i . , the recruitment of CD8+ and CD4+ T cells , but not NK cells , to the brain was significantly reduced by IL-2Jc treatment , compared with mice receiving either IL-2Sc or control treatment ( Figure 4 ) . Furthermore , Treg cell numbers were significantly higher in IL-2Jc-treated mice compared to all other groups studied ( Figure 4 ) . These data indicated that IL-2Jc-mediated protection was associated both with a specific blockade of conventional T cell recruitment to the brain , and also an increase in the number of Treg cells in this tissue site . CD8+ T cells play a key role in ECM pathology [16] , [18] . A previous study using a transgenic PbA strain expressing model T cell epitopes showed that antigen-specific CD8+ T cells are primed in the spleen [35] . We employed this experimental system to assess the fate of antigen-specific CD8+ T cells in IL-2Jc-treated mice during ECM . OVA-specific , congenic ( CD45 . 1 ) CD8+ T ( OTI ) cells were transferred into mice prior to infection with OVA-transgenic PbA ( PbTG ) or a non-OVA-expressing control parasite ( PbG ) . On day 6 p . i . , splenic OTI cell numbers and activation status , via Granzyme B ( GzmB ) expression , were assessed ( Figure 5A ) . OTI cells were not detected in the spleens of naïve mice or mice infected with PbG ( Figure 5A ) . The expression of GzmB was detected in ∼30% of endogenous ( CD45 . 1 negative ) CD8+ T cells in PbG-infected mice , indicating dramatic activation of CD8+ T cells at the onset of ECM . In control treated mice infected with PbTG , OTI cells were readily detected , indicating antigen-specific activation and proliferation of these cells had occurred . Moreover , nearly all of these cells expressed GzmB , at a level similar to activated endogenous CD8+ T cells . IL-2Jc treatment at the time of infection dramatically impaired , though did not abrogate , the OTI CD8+ T cell response ( Figure 5A ) . This effect was not apparent in mice treated on day 2 p . i . with IL-2Jc . Furthermore , mice treated with IL-2Sc displayed a trend towards an enhanced OTI T cell response compared to control mice , which is consistent with reports of the stimulatory effect of IL-2Sc on CD8+ T cells [25] , [26] , [27] , [28] , [36] . Together these data demonstrate that IL-2Jc , when administered on the day of infection , potently inhibits pathogenic , antigen-specific CD8+ T cell responses during ECM . To be sure that IL-2Jc did not stimulate NK cells or NKT cells , we examined their expression of the activation markers CD69 , GzmB and IFNγ , 24 hours after infection and treatment with IL-2Jc . As expected , no further activation of NK or NKT cells in IL-2Jc-treated mice was detected relative to control-treated , infected mice; while in contrast , IL-2Sc-treatment clearly stimulated both NK and NKT cells ( Figure S1A ) . Furthermore , neither depletion of NK cells with anti-NK1 . 1 antibody , nor the absence of invariant chain NKT cells in B6 . Jα18−/− mice , impeded either CD4+ Foxp3+ T cell expansion ( Figure S1B ) or control of parasite burden ( Figure S1C ) by IL-2Jc . Together these data indicate that IL-2Jc does not protect against ECM via activation of NK cells or NKT cells . PbA infection induces a potent pro-inflammatory cytokine response in C57BL/6 mice that is strongly associated with ECM pathogenesis . IFNγ is absolutely critical for disease onset [37] , [38] , [39] , possibly by promoting PbA tissue sequestration [19] . We found that IL-2Jc administered on the day of infection resulted in lower serum IFNγ levels by day 4 p . i . , whereas neither IL-2Sc nor delayed IL-2Jc treatment had any significant effect ( Figure S2 ) . Examination of the antigen-specific splenic CD4+ T cell response indicated an impaired ex vivo proliferative and IFNγ recall response from IL-2Jc treated mice ( Figure S3 ) , suggesting that in vivo CD4+ T cell responses were impaired by IL-2Jc treatment . Therefore , we enumerated splenic IFNγ-producing CD4+ T cells and Treg cells over the course of PbA-infection in mice treated with IL-2Jc or IL-2Sc . IFNγ-producing CD4+ T cells were detectable from day 4 p . i . onwards in infected , but not naïve mice ( Figure 5B ) . Control saline-treated and IL-2Sc-treated infected mice had very similar numbers of IFNγ+ CD4+ T cells on day 4 p . i . . In contrast , IL-2Jc treatment suppressed the number of IFNγ+ CD4+ T cells ( p<0 . 001 ) . Interestingly , the number of IFNγ+ CD4+ T cells was greatly enhanced if IL-2Jc was administered on day 2 p . i . ( p<0 . 001 ) ( Figure 5B ) , possibly indicating increased expression of high affinity IL-2 receptor on these cells by day 2 p . i . . Treg cells expanded in control , infected mice and numbers peaked on day 4 p . i . , before declining by day 6 p . i . ( Figure 5C ) , consistent with previous reports [20] , [21] , [40] . Infected mice treated with IL-2Sc exhibited almost identical Treg cell expansion kinetics to that of control treated mice ( Figure 5C ) , consistent with the notion that IL-2Sc has little impact on Treg cell numbers [25] . Strikingly , IL-2Jc treatment at the time of PbA infection resulted in a dramatic expansion in Treg cell numbers with a >6-fold increase by day 2 p . i . , peaking at day 4 p . i . ( ∼3 . 5-fold greater numbers than in control treated mice ) , before retracting somewhat by day 6 p . i . , although numbers still remained ∼4-fold greater than in IL-2Sc and control treated groups . In contrast , delaying IL-2Jc treatment until day 2 p . i . , resulted in very little enhanced Treg cell expansion . Thus , the protection afforded by IL-2Jc treatment at the time of PbA infection was associated with a dramatic and sustained elevation of Treg cell numbers over the course of infection . Taken together , these data show that IL-2Jc-mediated protection against ECM was associated with an expansion of CD4+ Treg cells and an accompanying impairment of the conventional CD8+ and CD4+ T cell responses . We next determined whether the increase in Treg cell numbers caused by IL-2Jc treatment during infection was the result of natural Treg cell expansion , or de novo conversion of naïve , Foxp3− CD4+ T cells into Treg cells . Foxp3+ CD4+ natural Treg cells and Foxp3− CD4+ T cells were sorted from the spleens of naïve foxp3gfp/gfp mice [41] , and transferred into C57BL/6 mice . On the same day , these mice were infected , and treated either with IL-2Jc or saline . At the peak of Treg cell expansion ( 4 days later ) , splenic GFP+ Foxp3+ CD4+ Treg cells were enumerated . These cells were readily detected in mice that received GFP+ natural Treg cells , and indeed their numbers were boosted by IL-2Jc treatment ( Figure 6A ) . However , in mice receiving GFP− non-Treg CD4+ T cells , we observed no evidence of their conversion into Foxp3+ Treg cells either spontaneously during infection or after stimulation with IL-2Jc . These data indicate that IL-2Jc treatment during ECM triggers natural Treg cell expansion , but not conversion of Foxp3− CD4+ T cells to a Foxp3+ phenotype . We next examined whether natural Treg cell expansion caused by IL-2Jc was dependent upon infection . Naïve and infected groups of mice were treated with IL-2Jc or control saline . Four days later , the number of splenic Foxp3+ CD4+ T cells was determined ( Figure 6B ) . Consistent with previous reports [23] , [25] , substantial Treg cell expansion was observed in both naïve and infected mice , demonstrating that this phenomenon is not dependent on infection . Importantly , however , when we assessed direct ex vivo production of cytokines by Treg cells ( by intracellular cytokine staining with no in vitro stimulation ) ( Figure 6B ) , we noted that while expanded Treg cells in naïve mice made little IL-10 , those in IL-2Jc treated , infected mice , made significantly higher amounts of this cytokine than those from control , infected mice . A small number of Treg cells from IL-2Jc-treated , infected mice , also appeared to make IFNγ , but this response was much lower than the IL-10 response ( Figure 6B ) . These data indicate that IL-2Jc triggers the expansion of IL-10-producing Treg cells during PbA infection . We further analysed the effects of IL-2Jc on Treg cells , and observed that their expression of CD25 , Foxp3 and CTLA-4 was substantially elevated by IL-2Jc treatment compared to control saline treated , infected mice ( Figure 6C ) . Taken together , these data demonstrate that IL-2Jc treatment triggers the expansion of natural CD4+ Treg cells , which then express higher levels of Foxp3 , IL-10 and CTLA-4 in response to PbA infection . To determine if Treg cells were important for IL-2Jc mediated protection against ECM , we employed the DEREG mice [5] . C57BL/6 mice and DEREG mice were infected with PbA , and treated with IL-2Jc or saline . DT or saline was administered to IL-2Jc treated DEREG and C57BL/6 mice from day 3 p . i . , around the peak expansion of Treg cells . The following day ( day 4 p . i . ) , while Treg cell expansion was evident in DEREG mice given IL-2Jc , depletion of Treg cells ( >95% efficacy in this study ) was confirmed in mice that had received DT ( Figure 7A ) . C57BL/6 mice were completely protected from ECM when treated with IL-2Jc , either with or without DT treatment ( Figure 7B ) , indicating no side-effects of DT treatment in C57BL/6 mice during PbA-infection over this time-frame . DEREG mice were equally susceptible to ECM as C57BL/6 mice , and were protected by IL-2Jc treatment ( Figure 7B ) . Crucially , IL-2Jc-mediated control of parasite burdens and protection from disease was completely abrogated when DEREG mice were treated with DT ( Figure 7B & 7C ) . These data formally demonstrate that Foxp3+ cells are responsible for IL-2Jc-mediated protection against ECM . Since IL-2Jc treatment increased IL-10 and CTLA-4 expression by Foxp3+ CD4+ T cells during infection ( Figure 6B & 6C ) , we hypothesized that protection was dependent upon these two molecules . To test this , IL-2Jc-treated , PbA-infected C57BL/6 mice received anti-CTLA-4 or anti-IL-10R blocking antibodies , or control IgG from day 3 p . i . . Anti-CTLA-4 significantly reduced IL-2Jc-mediated protection , with >60% of IL-2Jc-treated mice succumbing to infection with pathogen burdens similar to control infected mice ( Figure 8A & 8B ) . Anti-IL-10R blockade , on the other hand , only partially reversed IL-2Jc-mediated protection , with >60% survival ( Figure 8A ) , and interestingly , further reduced pathogen burdens in IL-2Jc treated mice ( Figure 8B ) . Both antibody blockade treatments restored the splenic IFNγ CD4+ T cell response that had been impaired by IL-2Jc treatment ( Figure 8C ) . Since we could detect only a modest role for IL-10 in IL-2Jc mediated protection of wild-type C57BL/6 mice , we further examined the effect of IL-2Jc treatment in IL-10−/− mice , and found that these animals were significantly protected against ECM in a CTLA-4-dependent manner ( Figure S4 ) . These data demonstrate that IL-10 is not essential for IL-2Jc-expanded natural Treg cells to protect against ECM . In addition , non-IL-2Jc treated mice were also treated with anti-CTLA-4 or anti-IL-10R blocking antibodies to study their effects alone on the course of ECM . Anti-CTLA-4 treatment did not alter disease outcome in saline treated mice ( Figure 8A ) , despite partially reducing parasite burdens ( Figure 8B ) , while anti-IL-10R treatment significantly accelerated ECM onset ( Figure 8A ) ( MST 6 . 5 days vs . 8 days; p<0 . 01 ) , with a partial reduction in parasite burden ( Figure 8B ) . Of note , when anti-IL-10R mAb was administered from the start of infection , a more substantial reduction on parasite burden is observed [19] . Taken together , these data demonstrate that when CTLA-4 was blocked in IL-2Jc treated mice , pathogenic CD4+ T cell responses were restored , pathogen burdens were poorly controlled and protection from ECM was reversed . Thus IL-2Jc mediated protection against ECM is strongly dependent on Foxp3+ cells , and CTLA-4 , but not IL-10 .
T cell responses to infection are generally required for pathogen control , but can also contribute to disease . The roles of T cells in the pathogenesis of severe malaria syndromes , including CM , are unclear . Leukocytes have been observed in the brains of patients who have died from CM [42] , [43] , but their contribution to CM pathogenesis is not known . Studies in the ECM model show that T cells play a critical role in disease pathogenesis [16] , [18] , although the role of Treg cells in this model remains the subject of debate [20] , [21] , [22] . Data from this study and others [22] suggest that Treg cells do little to impact on ECM onset , and may in some cases exacerbate disease [20] , [21] . Higher Treg cell frequencies have been associated with elevated blood parasitemia in human malaria patients [4] , [44] , [45] , suggesting that Treg cells impair pathogen clearance during malaria . However , one report demonstrated that anti-CD25 treatment of ECM-resistant BALB/c mice increased the incidence of neurological symptoms during secondary PbA challenge [46] , suggesting Treg cells might be protective against ECM . Here , we report that Treg cells can protect against ECM following their expansion in vivo . Thus , while Treg cell responses during ECM are usually insufficient to control pathogenic T cells , and Treg cell ablation has no effect on pathogen burden or disease outcome , if present in large enough numbers , Treg cells can prevent disease . This is the first report to clearly show that CD4+ Foxp3+ Treg cells can play a direct protective role during experimental malaria infection . However , it is important to bear in mind that Treg-mediated protection was only achieved by treatment with IL-2Jc from the start of infection , and this therapeutic opportunity will not exist in human malaria patients . Thus , alternative approaches to rapidly expand Treg cell numbers in a clinical setting would have to be considered for therapeutic effect . Previous data from our laboratory showed that anti-CD25 ( PC61 ) monoclonal antibody treatment , partially depleted/blocked Treg cells ( i . e . , , affecting only those cells expressing high levels of CD25 ) , enhanced anti-parasitic CD4+ T cell responses , and reduced both parasite burden and ECM incidence [20] . These data were interpreted to mean that natural Treg cells normally impair pathogen clearance , and thus help to promote ECM . However , it is now clear from this work , and from another recent report , that total depletion of natural Treg cells does not protect against ECM [22] . The discrepancy between the outcome of partial and total Treg cell depletion in ECM are unresolved at present , but could be linked to the fact that anti-CD25 mAb-treated mice retain a population of CD25lo Foxp3+ CD4+ T cells that can display plasticity in vivo [47] , and might therefore contribute to protection from disease . Pathogen control is clearly inefficient during ECM , with little evidence that T cells provide any protection against infection . To date , only NK cells have been reported to mediate some pathogen control during ECM [13] . However , NK cell depletion in IL-2Jc-treated mice did not prevent protection from ECM , indicating that these cells were not targets for IL-2Jc and did not contribute to enhanced parasite control . We recently showed that T cells promote the accumulation of pRBC in multiple tissue sites during PbA infection , and that depletion of either CD4+ or CD8+ T cells to protect from ECM dramatically reduced parasite tissue sequestration [19] . Furthermore , lymphocyte-deficient B6 . RAG1-deficient mice failed to develop ECM and had markedly reduced parasite burdens compared to control animals and B cell-deficient mice following PbA infection [19] . Therefore , in C57BL/6 mice , PbA tissue sequestration is promoted by host T cell responses , possibly by the conditioning host tissue endothelial cells via cytokines to allow binding of pRBC , as described by others [48] . Our earlier studies on anti-CD25 mAb treatment of PbA-infected mice indicated that early blockade/depletion of CD25hi Treg cells allowed the generation of an enhanced anti-parasitic CD4+ T cell response that was accompanied by recovery and expansion of CD25hi Treg cells during the course of infection [20] . Furthermore , our current data indicates that the most likely explanation for the protective effects of in vivo expanded Treg cells is the suppression of pathogenic T cell expansion that would otherwise promote parasite tissue sequestration . Thus , we propose a model whereby naturally occurring CD25hi Treg cells suppress the development of potent anti-parasitic immunity early during PbA infection and their depletion/blockade results in enhanced anti-parasitic CD4+ T cells responses , reducing both parasite burdens and the risk of severe pathology . However , there also appears to be an important role for the remaining CD25lo Foxp3+ CD4+ T cells in achieving a balance between emerging anti-parasitic immunity and immune-pathology in anti-CD25mAb-treated mice , as indicated by the failure of DT-mediated Treg cell depletion in DEREG mice to protect against ECM . A role for IL-10-producing inducible regulatory T cells [40] and/or IL-10/IFNγ-producing Th1 cells [4] identified in P . yoelii-infected mice and malaria patients , respectively , may also contribute to this latter process . Our data reported in this study shows that if Treg cells can be expanded sufficiently via IL-2Jc during PbA infection , they can suppress normally pathogenic T cell responses , and prevent parasite tissue sequestration and ECM . Hence , Treg cells could have two potentially important roles during PbA infection ( Figure 9 ) . First , they could suppress the early generation of anti-parasitic CD4+ T cells responses that are detrimental to the host , and second , they can modulate pathogenic T cell responses to reduce parasite tissue sequestration later during infection . This latter effect may allow better clearance of parasites in the spleen , thus lowering parasite burden . Again , we do not rule out the possibility that inducible regulatory T cells may also play a role in protecting against disease later in infection , and even restricting parasite tissue sequestration . Treg cell-mediated protection against ECM was exquisitely sensitive to the timing of IL-2Jc treatment . Delaying treatment by 48 hours caused the selective expansion of conventional CD4+ T cells rather than Treg cells , presumably due to infection-induced expression of high affinity IL-2 receptor by the former cell population . However , this expansion of conventional CD4+ T cells was unable to control parasite growth and failed to protect from ECM . Treg cell depletion from day 3 p . i . , completely abrogated IL-2Jc-mediated protection , showing that IL-2Jc-expanded Treg cells were responsible for protection from ECM . Clearly , there is a fine balance between the activation and expansion of anti-parasitic T cell responses and the emergence of disease-protective Treg cells that determines the outcome of PbA infection . Whether such an intimate relationship between these two different types of T cells exists during human malaria remains to be determined . Nevertheless , our data suggests a more complex temporal and spatial relationship between emerging anti-parasitic T cell responses required for control of parasite growth and the functions of Treg cells that may protect against disease , than has previously been recognised . Treg cells function via multiple mechanisms , including CTLA-4 [11] , IL-10 , TGFβ and IL-2-deprivation [10] . We found that Treg cell-mediated protection against ECM required CTLA-4 , but was only modestly affected by IL-10 blockade . Previous reports have demonstrated that a murine AIDS infection induces IL-10 expressing Treg cells , and that enhanced IL-10 levels protect against ECM [49] , [50] . Our data is consistent with a moderate therapeutic role for IL-10 in ECM , but demonstrates that CTLA-4 is a more potent regulator of pathogenic T cell responses . We attempted to determine the antigen specificity of the IL-10 response made by Tregs cells in IL-2Jc treated mice , by sorting these cells , stimulating with APC and parasite antigen , and looking for IL-10 production at both the protein and mRNA level . However , these experiments are notoriously difficult to perform [51] , [52] , [53] , and we were unable to assess the antigen specificity of IL-10 producing Tregs . There may also be different roles for the major regulatory molecules produced by Treg cells in our study ( CTLA-4 ) and inducible regulatory T cells identified by others ( IL-10; [4] , [40] ) , by acting on different cellular/tissue targets during malaria . However , there is no direct evidence for this as yet . In conclusion , we and others have shown that Treg cells numbers expand during malaria infection , but are unable to protect against T cell mediated immune pathology [20] , [21] , [40] . Here we show for the first time that Treg cells can protect against T cell-mediated immune pathology in malaria if their numbers are sufficiently expanded at the appropriate time during the immune response . Thus , while increased Treg cell frequencies may contribute to increased parasitemia in malaria patients [4] , [44] , [45] , a further possibility is that these cells expand in an attempt to protect against disease caused by parasite sequestration .
Female C57BL/6 mice and congenic CD45 . 1+ C57BL/6 mice aged 6–8 weeks were purchased from the Australian Resource Centre ( Canning Vale , Perth , Western Australia ) and maintained under conventional conditions . DEREG mice [5] , OTI [54] , C57BL/6 il10−/− , and C57BL/6 Jalpha18−/− mice were bred and maintained in house . foxp3gfp/gfp mice [41] were backcrossed ten times onto the C57BL/6 background , bred and maintained in house . All animal procedures were approved and monitored by the Queensland Institute of Medical Research Animal Ethics Committee . This work was conducted under QIMR animal ethics approval number A02-633M , in accordance with the “Australian code of practice for the care and use of animals for scientific purposes” ( Australian National Health & Medical Research Council ) . P . berghei ANKA ( PbA ) strains were used in all experiments after one in vivo passage in mice . A transgenic PbA ( 231c1l ) clonal line expressing luciferase and green fluorescent protein under the control of the EF1-α promoter ( PbA-luc ) was used for all experiments unless stated otherwise [20] . Transgenic PbA strains expressing model T cell epitopes , and control strains , PbTG and PbG , were obtained from Prof . William R . Heath , University of Melbourne , Australia , and were maintained and used as previously reported [35] . All mice were infected with 105 pRBCs intravenously ( i . v . ) via the lateral tail vein . Blood parasitemia was monitored by examination of Diff-Quick ( Lab Aids , Narrabeen , NSW , Australia ) stained thin blood smears obtained from tail bleeds . Mice were monitored twice daily after day 5 p . i . , and clinical ECM evaluated . Clinical ECM scores were defined by the presentation of the following signs: ruffled fur , hunching , wobbly gait , limb paralysis , convulsions , and coma . Each sign was given a score of 1 . Animals with severe ECM ( accumulative scores = 4 ) were sacrificed by CO2 asphyxiation according to ethics guidelines , and the following timepoint given a score of 5 to denote death . Allophycocyanin ( APC ) or Pacific Blue ( PB ) -conjugated anti-TCRβ chain , phycoerythrin ( PE ) -Cy5- or PE-conjugated anti-CD4 , PE-Cy5-conjugated anti-CD8 , PE or fluorescein isothiocyanate-conjugated anti-CD45 . 1 , APC or PE-conjugated anti-IFNγ , and PE-conjugated anti-IL-10 were purchased from Biolegend ( San Diego , CA ) or BD Biosciences ( Franklin Lakes , NJ ) . Alexa-647-labelled anti-mouse Foxp3 mAb was purchased from eBioscience ( San Diego , CA ) . PE-conjugated anti-human Granzyme B ( GzmB ) , with mouse cross reactivity , was purchased from Invitrogen ( Mount Waverley , Vic . , Australia ) . Anti-CTLA-4 ( UC10-4F10-11 ) and control IgG was purchased from BioXCell , ( West Lebanon , NH , USA ) . Anti-IL-10R ( 1B1 . 3a ) , anti-CD4 ( YTS191 ) , anti-IL-2 ( S4B6 and JES6-1A12 ) , anti-NK1 . 1 ( PK136 ) , and isotype control mAb ( MAC49; ratIgG1 ) were purified from culture supernatants by protein G column purification ( Amersham , Uppsala , Sweden ) followed by endotoxin removal ( Mustang Membranes; PallLife Sciences , East Hills , NY ) . Purified control rat IgG were also used in some experiments and purchased from Sigma-Aldrich ( Castle Hill , NSW , Australia ) . Diphtheria toxin ( DT ) was purchased from Sigma-Aldrich , diluted in saline , and 1µg doses injected via the intraperitoneal route . 1 . 5µg of recombinant murine IL-2 ( eBioscience , San Diego , CA ) was incubated with 50µg of either S4B6 or JES6-1A12 ( prepared as detailed above ) in saline , for 30 minutes at 37°C prior to intraperitoneal administration to each mouse in a volume of 200µl . Blood mononuclear cells were analysed in heparinised blood after 2 rounds of red cell lysis using hypotonic red cell lysis buffer according to the manufacturer's instructions ( Sigma-Aldrich ) . Spleen cells were isolated by passing tissue through a 100-µm sieve in RPMI-1640 tissue culture medium supplemented with 2% ( v/v ) fetal calf serum ( Wash Buffer ) . Red blood cells were lysed as above ( Sigma-Aldrich ) and washed once more with Wash Buffer . Brain mononuclear cells were isolated by digesting tissue in collagenase type 4 ( 1 mg/ml; Worthington Biochemical Corp . , Lakewood , NJ ) and deoxyribonuclease I ( 0 . 5 mg/ml; Worthington Biochemical ) at room temperature for 40 minutes , before passing through a 100-µm sieve and washing twice with Wash Buffer . The cell pellet was resuspended in 33% ( v/v ) Percoll in PBS and centrifuged at 693×g for 12 minutes at room temperature . Supernatant containing debris was removed , and the leukocyte pellet was washed once in Wash Buffer , red blood cells lysed as described above , and washed and resuspended in RPMI-1640 medium supplemented with 5% ( v/v ) fetal calf serum . For the staining of cell surface antigens , cells were incubated with fluorochrome-conjugated mAbs on ice for 20 minutes . Intracellular staining for Foxp3 was performed on fixed/permeabilized cells using Alexa647-labeled anti-mouse Foxp3 kit ( eBioscience ) , according to the manufacturer's instructions . Intracellular cytokine staining for IFNγ , CTLA-4 and GzmB was performed using a BD Fixation/Permeabilisation kit ( BD Biosciences ) according to manufacturer's instructions . Data were acquired on a FACSCanto II flow cytometer ( BD Biosciences ) and analysed using FlowJo software ( Treestar , Ashland , OR , USA ) . Cell populations in the blood , spleen and brain were defined as follows: CD4+ T cells ( CD4+TCRβ+ ) , CD8+T cells ( CD8α+TCRβ+ ) , NK cells ( NK1 . 1+TCRβ− ) , CD4+ Treg cells ( CD4+Foxp3+TCRβ+ ) . Cytokines in tissue culture supernatants and serum samples were quantified using the cytometric bead array flexsets ( BD Biosciences ) on a FACSarray equipped with BD Flexset analysis software ( BD Biosciences ) . Splenic CD4+ T cells ( 5×104 cells/well ) , either bulk populations purified to >85% purity by magnetic bead positive selection techniques ( Miltenyi Biotec; North Ryde , NSW , Australia ) , or cell sorted to isolate Treg cells from foxp3gfp/gfp mice to a purity >99% , were stimulated with 2 . 5×105 PbA-parasitized RBC ( pRBC ) or naive RBC ( nRBC ) , and 1×106 irradiated naive C57BL/6 spleen cells at 37°C in 5% ( v/v ) CO2 . Cell culture supernatant was collected after 24h or 72 h and cytokines were measured as above ( BD Biosciences ) . After 72 h of culture , cells were pulsed with 1 µCi [3H]thymidine for 18 h , before measuring thymidine incorporation using a Betaplate Reader ( Wallac ) . Luciferase-expressing PbA pRBCs were visualized by imaging whole bodies or dissected organs with an I-CCD photon-counting video camera and in vivo imaging system ( IVIS 100; Xenogen , Alameda , CA ) . Mice were anesthetized with isofluorane and injected intraperitoneally with 0 . 1 ml of 5 mg/ml D-luciferin firefly potassium salt ( Xenogen ) . 5 minutes afterwards , images were captured on the IVIS 100 according to the manufacturer's instructions . Parasites were visualized in the brain after removal from mice that had been perfused with 15ml of saline via the heart . Bioluminescence generated by luciferase transgenic PbA in mice or brain tissue was measured according to the manufacturer's instructions . The unit of measurement was photons/second/cm2/steer radiant ( p/sec/cm2/sr ) . Differences in survival of treatment groups were analysed using the Kaplan-Meier log-rank test . All other analyses of differences in parasitemia , cytokine levels , cell numbers , bioluminescence etc . were performed using the Mann-Whitney nonparametric test . For all statistical tests , p<0 . 05 was considered significant . In all figures , * , ** , *** denote p values of p<0 . 05 , p<0 . 01 & p<0 . 001 respectively . | Severe malaria can kill people via complications such as cerebral malaria . The number of malaria parasites in the body is a major determinant of whether a patient will develop severe disease . T cells are thought to help control parasite numbers , but regulatory T cells , which are known to dampen immune responses , are present at a greater frequency in the blood of malaria patients with the highest parasitemia , suggesting that these cells might impair parasite control . Our experiments in a mouse model of cerebral malaria show for the first time that regulatory T cells can contribute to protection against disease . Specifically , our data shows that accumulation of parasites in host tissues can be promoted by anti-parasitic T cell responses , and that regulatory T cells can reduce this parasite tissue sequestration and protect against experimental cerebral malaria if their numbers are sufficiently elevated . These results suggest that regulatory T cells can help reduce pathogenic T cell responses during experimental infection and protect against malaria induced immune pathology . | [
"Abstract",
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"Results",
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"and",
"Methods"
] | [
"immunology/immunomodulation",
"immunology/immunity",
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"diseases/protozoal",
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] | 2010 | CD4+ Natural Regulatory T Cells Prevent Experimental Cerebral Malaria via CTLA-4 When Expanded In Vivo |
Hebbian changes of excitatory synapses are driven by and further enhance correlations between pre- and postsynaptic activities . Hence , Hebbian plasticity forms a positive feedback loop that can lead to instability in simulated neural networks . To keep activity at healthy , low levels , plasticity must therefore incorporate homeostatic control mechanisms . We find in numerical simulations of recurrent networks with a realistic triplet-based spike-timing-dependent plasticity rule ( triplet STDP ) that homeostasis has to detect rate changes on a timescale of seconds to minutes to keep the activity stable . We confirm this result in a generic mean-field formulation of network activity and homeostatic plasticity . Our results strongly suggest the existence of a homeostatic regulatory mechanism that reacts to firing rate changes on the order of seconds to minutes .
The awake cortex is constantly active , even in the absence of external inputs . This baseline activity , commonly referred to as the “background state” , is characterized by low synchrony at the population level and highly irregular firing of single neurons . While the direct implications of the background state are presently unknown , several neurological disorders such as Parkinson's disease , epilepsy or schizophrenia have been linked to various disruptions thereof [1]–[5] . Theoretically , the background state is currently understood as the asynchronous and irregular ( AI ) firing regime resulting from a dynamic balance of excitation and inhibition in recurrent neural networks [6]–[9] . Balanced networks exhibit low activity and small mean pairwise correlations [7] , [9] . However , even small changes in the amount of excitation can disrupt the background state [7] , [10] . Changes in excitation can arise from Hebbian plasticity of excitatory synapses: Subsets of jointly active neurons form strong connections with each other which is thought to be the neural substrate of memory [11] . However , Hebbian plasticity has the unwanted side effect of further increasing the excitatory synaptic drive into cells that are already active . The emergent positive feedback loop renders this form of plasticity unstable and makes it hard to reconcile with the stability of the background state [12] . To stabilize neuronal activity , homeostatic control mechanisms have been proposed theoretically [13]–[19] and various forms have indeed been found experimentally [20]–[22] . The term homeostasis comprises any compensatory mechanism that stabilizes neural firing rates in the face of plasticity induced changes . This includes compensatory changes in the overall synaptic drive ( e . g . synaptic scaling [21] ) , the neuronal excitability ( intrinsic plasticity [23] ) or changes to the plasticity rules themselves ( i . e . metaplasticity [20] ) . Common to all experimentally found homeostatic mechanisms is their relatively slow response compared to plasticity . While synaptic weights can change on the timescale of seconds to minutes [24]–[26] , noticeable changes caused by homeostasis generally take hours or even days [21] , [27]–[29] . This is thought to be crucial since it allows neurons to detect their average firing rate by integrating over long times . While fluctuations on short timescales cause Hebbian learning and alter synapses in a specific way to store information , at longer timescales homeostasis causes non-specific changes to maintain stability [23] . The required homeostatic rate detector acts as a low-pass filter and therefore induces a time lag between the rate estimate and the true value of neuronal activity . As a result , homeostatic responses based on this detector become inert to sudden changes . The longer the filter time constant is , the more sluggish the homeostatic response becomes . Here we formalize the link between stability of network activity and the timescales involved in homeostasis in the presence of Hebbian plasticity . We first study the stability of the background state during long episodes of ongoing plasticity in direct numerical simulations of large balanced networks with a metaplastic triplet STDP rule [30] in which the timescale of homeostasis is equal to the one of the rate detector . This allows us to determine the critical timescale beyond which stability is lost . In a second step we reduce the system to a generic two-dimensional mean-field model amenable to analytical considerations . Both the numerical and the analytical approach show that homeostasis has to react to rate changes on a timescale of seconds to minutes . We then show analytically and in simulations that these stability requirements are not specific to metaplastic triplet STDP , but generalize to the case of triplet STDP in conjunction with synaptic scaling . In summary we show that the stability of the background state requires the ratio between the timescales of homeostasis and plasticity to be smaller than a critical value which is determined by the network properties . For realistic network and plasticity parameters this requires the homeostatic timescale to be short , meaning that homeostasis has to react quickly to changes in the neuronal firing rate ( on the order of seconds to minutes ) . Our results suggest that plasticity must either be gated rapidly by a third factor , or be accompanied by a yet unknown homeostatic control mechanism that reacts on a short timescale .
To study the stability of the background state in balanced networks with plastic excitatory-to-excitatory ( EE ) synapses we simulate networks of 25000 randomly connected integrate-and-fire neurons ( Figure 1 A ) . Prior to any synaptic modification by plasticity , we set the network to the balanced state in which membrane potentials exhibit large sub-threshold fluctuations ( Figure 1 C ) , giving rise to irregular activity at low rates ( ) and asynchronous firing at the population level ( Figure 1 D ) . In our model more than 90% of the input to each neuron comes from within the network , thus closely resembling conditions found in cortex [31] . Plasticity of all recurrent EE synapses is modeled as an additive triplet STDP rule ( see [30] and Methods ) which accurately describes experimental data from visual cortex [26] , [30] . In this metaplastic triplet STDP rule the amount of LTD is chosen such that LTP and LTD cancel on average , when the pre- and postsynaptic neurons fire with Poisson statistics at rate . Therefore , under the assumption of low spike-spike correlations and irregular firing , becomes a fixed point of the network dynamics ( see [32] and Methods ) . We begin with a fixed learning rate , which is chosen as a compromise between biological plausibility and computational feasibility ( Methods ) . To go towards the fixed point , all neurons constantly estimate their firing rate as the moving average with exponential decay constant , given by ( 1 ) where corresponds to the -th firing time of neuron ( see also Methods , Eq . ( 19 ) ) . If the rate estimate of the postsynaptic neuron lies above ( below ) , homeostasis increases ( decreases ) the LTD amplitude . The homeostatic time constant is the only free parameter of our model . We then explore systematically how a particular choice of affects the stability of the background state in the network . To allow the moving averages to settle , we run the network for an initial period of duration , during which synaptic updates are not carried out . After that , plasticity is switched on . To check whether the network dynamics remain stable , simulations are run for 24 h of biological time during which we constantly monitor the evolution of the population firing rate ( Figure 2 A ) . The network is considered unstable if the mean population firing rate either drops to zero or increases above which happens when run-away potentiation occurs ( Figure 2 B ) . By systematically varying the time constant in 1 s steps , we find that for the background state to remain stable ( Figure 2 C ) , must be shorter than some critical value . Moreover , we find a sharp transition to instability when is increased beyond . For the network has a tendency to fall silent ( Figure 2 A , black line ) . During stable simulation runs ( ) , some synapses grow from their initial value up to the maximum allowed value , while the rest of the synapses decay to zero . The resulting bimodal distribution of synaptic efficacies ( Figure 2 F ) remains stable until the end of the run . This is a known phenomenon for purely additive learning rules [33] , [34] and we will see later that unimodal weight distributions arise by the inclusion of a weight decay or by choosing synaptic scaling as the homeostatic mechanism [35] . Despite the qualitative change in the weight distribution , the inter-spike-interval ( ISI ) distribution remains largely unaffected , while the coefficient of variation of the ISI distribution ( CV ISI ) is shifted to slightly higher values ( Figure 2 D ) . However , we noted that the single-neuron average firing rates , which are widely spread out initially , are at the end clustered slightly above the homeostatic target rate of ( ) with a weak dependence on the actual value of ( Figure 2 E ) . This behavior is characteristic for homeostatic firing rate control in single cells . We conclude that metaplastic triplet STDP with a homeostatic mechanism as presented here can lead to stable dynamics in models of balanced networks exhibiting asynchronous irregular background activity . However , the timescale of the homeostatic mechanism critically determines stability . It has to be on the order of seconds to minutes and therefore comparable to the timescale of plasticity itself ( here ) . This finding is in contrast to most known homeostatic mechanisms that have experimentally been found to act on effective timescales of hours or days [20] , [29] , [36] , [37] . To understand why the critical time constant above which homeostasis cannot control plasticity is so short , we here analyze the stability of the background state in a mean field model . In line with the spiking network model we consider a single population of neurons that fires with the mean population firing rate ( Figure 3 A ) . To find an analytic expression that characterizes the response of the background activity to changes in the recurrent weights around the initial value , we begin with a linear neuron model ( 2 ) with the offset and the slope parameter . Since we are interested in weight changes around the initial value , the natural choice for would be . However , here we set to take into account the recurrent feed-back . This choice makes dimensionless while is measured in units of Hz . Because weights evolve slowly , while population dynamics are fast we can solve for and obtain the self-consistent solution ( 3 ) As we will show later , a better qualitative fit to the spiking model can be achieved with this heuristic , which will facilitate finding the right parameters and . To introduce plasticity into the mean field model , we use the corresponding rate-based plasticity rule ( 4 ) which can be directly derived from the triplet STDP rule [30] and also can be interpreted as a BCM model [15] , [30] , [38] . Here , is the relative learning rate and sets the scale of the system . The second equality in Eq . ( 4 ) follows because in the recurrent model pre- and postsynaptic rates are the same ( and ) . The function scales the strength of LTD relative to LTP just as in the spiking case ( cf . Methods , Eq . ( 18 ) ) . In the mean field model , the rate detector ( Eq . ( 1 ) ) becomes the low pass filtered version of the population firing rate ( 5 ) To link the network dynamics with synaptic plasticity we take the derivative of Eq . ( 3 ) , and combine it with Eq . ( 4 ) to arrive at ( 6 ) which describes the temporal evolution of the mean firing rate as governed by synaptic plasticity . Taken together , equations ( 5 ) and ( 6 ) define a two-dimensional dynamical system with two fixed points . One lies at and represents the quiescent network . The remaining non-trivial fixed point is , which we interpret as the network in its background state . Given these choices , we now ask whether this fixed point can be linearly stable ( Methods ) and find that the stability of the background state requires ( 7 ) For infinitesimal excursions from the fixed point diverge , which corresponds to run-away potentiation in this model . We note that crucially depends on the parameters , , , and the target rate . However , we can rescale the system to natural units , by expressing firing rates in units of and time in units of , and plot the eigenvalues as a function of ( Figure 3 B ) . The fact that the fixed point of background activity loses stability for too large values of is in good qualitative agreement with what we observe in the spiking model . One should further note that Eq . ( 7 ) is independent of the power of appearing in , as long as the fixed point of background activity exists ( ) and under the condition that at criticality the imaginary parts of the eigenvalues are always non-vanishing ( see Methods ) . This indicates the presence of oscillations which are indeed observed in the spiking network ( cf . Figure 2 A , ) . The fact that the network falls silent for very small values of ( e . g . in Figure 2 A ) is not captured by the mean field model . We can make further use of the mean field model to qualitatively understand the behavior of the system far from equilibrium . Figure 3 C shows the phase plane of a network with a stable fixed point ( ) . When the system is driven away from it , and perturbations are small , the dynamics converge back towards the fixed point . However , when excursions become too large , the network activity diverges ( compare Figure 3 C , dotted solution ) since the fixed point of background activity is only locally stable . A numerical analysis shows that the basin of attraction is small when approaches from below ( Figure 3 D ) . Hence the system is very sensitive to perturbations which easily lead to run-away potentiation . Although we expect the basin of attraction of the mean-field model and the spiking model only to be comparably where Eq . ( 3 ) describes the firing rates of the spiking network accurately we can assume that for robust stability has to be satisfied . To be able to make more quantitative predictions for the spiking network we have to choose values for the parameters on the right hand side of Eq . ( 7 ) . These are the effective timescale of plasticity on the one hand , and and , which characterize the network dynamics , on the other hand . We will now show that the latter can be determined from the static network model , which is independent of plasticity . Note that the parameters and in our mean field model are shared with the spiking model which we will use to quantitatively compare the two . First , we relate the variables and to the response of the spiking network when all its EE synapses are modified . Since this is not feasible analytically , we extract the response numerically by systematically varying the EE weights around the initial state with . While doing so , plasticity is disabled and we record the steady state population rate of the network ( Figure 3 E ) . We then minimize the mean square error for Eq . ( 3 ) over a small interval and determine the following values: and . For the stability analysis only the derivative of Eq . ( 3 ) at matters . However , it is worth noting that the response of the balanced network is well captured by Eq . ( 3 ) over a much wider range than the one used for the fit . This behavior is an expected consequence of the balanced state , which is known to linearize network responses [6] , [39] . Our approximation by a linear rate model breaks down for higher rates since it does not incorporate refractory effects . Second , under the assumption of independent and irregular firing in the background state , the plasticity time constant is fully determined by the target rate and known parameters of the triplet STDP model ( see Methods and [30] ) . For we find . Using these results together with Eq . ( 7 ) we predict the critical timescale of homeostasis for different values of and and compare it to the results that we obtain as before from direct simulations of the spiking network . Figure 4 A shows that the dependence of on the learning rate is remarkably well captured by the mean field model . The fourth power dependence on the background firing rate is described well for ( Figure 4 B ) , but the theory fails for smaller values , where we start to observe synchronous events in the population activity , which introduce correlations that are not taken into account in the mean field approach . In Figure 4 C we plot the typical lifetimes ( i . e . the time when the spiking simulations are stopped , because they either show run-away potentiation or the maximum simulated time is reached ) as a function of . The figure illustrates nicely that the critical time constant coincides with the sharp transition in lifetimes observed in the spiking network . When running additional simulations with smaller learning rates ( as opposed to ) we observe that the network destabilizes occasionally for values of smaller than , but only after 22 h of activity ( see Figure S1 ) . We find , however , that this “late” instability can be avoided by either initializing the EE weights with a weight matrix obtained from a stable run ( at ) or by reducing the maximally allowed synaptic weight ( ) . Since these changes do not affect the “early” instability ( ) , the “late” instability seems to have a different origin and might be linked to the spontaneous emergence of structure in the network . Here we focus on the “early” instability which is seen in all simulations that do not respect the analytical criterion , after less than one hour of biological time , and therefore puts a severe stability constraint on . Moreover the theory is able to quantitatively confirm the timescale emerging from the spiking network simulations and allows us to see the detailed parameter dependence . In particular for a background rate of 3 Hz and the learning rate we find a critical timescale of ( simulations: , mean field model: ) . In summary , our mean field model discussed here makes accurate quantitative predictions about the stability of a large spiking network model with plastic synapses for a given timescale of homeostasis . Furthermore it gives useful insights into parameter dependencies which are computationally costly to obtain from parameter sweeps in simulations of spiking networks . Our theory confirms that metaplastic triplet STDP with biological learning rates has to be matched by a homeostatic mechanism that acts on a timescale of seconds to minutes . In the next sections we will show that the mean field framework described here can be readily extended to other forms of homeostasis . The induction of synaptic plasticity is only a first step towards the formation of long-term memory . In the absence of neuromodulators necessary to consolidate early LTP into late LTP , these modifications have been found to decay away with a time constant of [40] . To study the effect of a slow synaptic decay on the stability of the background state we focus on the early phase of plasticity . In particular we neglect consolidation in the model and introduce a slow decay term ( 8 ) where we already replaced the STDP rule by its equivalent rate based rule ( see [30] and Methods , Eq . ( 17 ) ) , while the effect of the decay term can be written identically in the rate based model and the STDP model . Note that for we retrieve the model studied in Figures 1–4 . Again we determine the critical timescale of homeostasis in numerical simulations of the spiking network by systematically varying for different values of . We further find that the slow weight decay causes the synaptic weights to stabilize in a unimodal distribution ( Figure 5 A and B ) which is fundamentally different to what we observed for the decay-free case . However , the critical time constant of homeostasis is only marginally larger than in the decay-free case ( Figure 5 C ) . To assess the impact of the decay on the critical timescale , the mean field approach , as it was derived above , can be adapted to take into account the constant synaptic decay ( Methods ) . Provided the decay time constant is sufficiently long , we find the critical time constant to be ( 9 ) which is in good agreement with the results from direct simulations ( Figure 5 C ) . From Eq . ( 9 ) we can further confirm that the decay term only causes a small positive shift in the critical time constant as it was also observed in the spiking network . Furthermore , we see that the population firing rate settles to values closer to the actual target rate ( Figure 5 D ) than this was the case in the decay-free scenario . In summary , adding a slow synaptic weight decay to the plasticity model is sufficient to cause substantial change to the steady state weight distribution in the network . Nevertheless this slow process does not affect the need for a rapid homeostatic mechanism . To test whether the previous findings are limited to our particular choice of metaplastic homeostatic mechanism , or whether they are also meaningful in the case of synaptic scaling [21] we now adapt the model by van Rossum et al . [35] and combine it with triplet STDP ( 10 ) where the rate of LTD is fixed in the triplet term ( cf . Eq . ( 17 ) ) and synaptic scaling is the only form of homeostasis . One important difference to the previous metaplastic STDP model is the addition of the scaling time constant which controls the timescale of synaptic scaling . In the metaplastic model we analyzed above , this time constant is implicit since it is the same as the one of plasticity ( ) . In contrast to the original model of synaptic scaling ( [35] ) here we choose to avoid additional unstable fixed points in the phase plane ( Figure 6 D ) . Bearing this in mind we move on to linearizing the system around the fixed point of background activity ( Methods ) . We find that for the eigenvalues of the linearized system qualitatively have the same shape as for the plasticity rule with homeostatically modulated LTD ( Figure 6 A ) . In fact for sensible values of , the stability condition is exactly the same: ( cf . Eq . ( 7 ) ) . However , in the case of synaptic scaling Eq . ( 7 ) represents a necessary , but not a sufficient condition for stability . For too large values of stability is lost also in the case of ( Figure 6 B ) . On the other hand decreasing indefinitely leads to oscillations without any further effect on stability ( see Methods and [35] ) . To compare these findings with the equivalent STDP rule we perform numerical simulations with the full spiking network in which we set and choose on the order of ( ) . By changing systematically ( Figure 6 C ) we determine the critical value to be smaller than predicted ( ) , but within the same order of magnitude ( Figure 6 A , C ) . Conversely when we start with held fixed , we determine the critical value of to be on the same order as ( Figure 6 B ) . At the end of a stable simulation run ( ) we find that synaptic weights have formed a unimodal distribution ( Figure 6 E ) , an expected behavior of synaptic scaling [35] . In summary we have shown here that a fast rate detector is necessary to produce fast homeostatic responses to guarantee stable network dynamics also for the case of synaptic scaling . Although the quantitative agreement between the mean field model and the full spiking simulation is less accurate than in the case of for the metaplastic model above , both models confirm that the rate detector has to act on a timescale of seconds to minutes . Furthermore the time constant of the scaling term has to be comparable to the time scale of plasticity ( ) or stability is compromised , when is chosen too large ( and oscillations occur , when chosen too small ) .
The fact that Hebbian learning has to be opposed by some kind of compensatory mechanism has long been known [13]–[16] and such mechanisms indeed have been found [20] , [36] , [41] . In the following we will briefly review the different types of homeostasis affecting synaptic weights and how they relate to what was used in the present study . Homeostasis can be classified in two main categories . We call models “weight homeostasis” if they try to keep all afferent weights into a cell normalized [13] . Such models have been criticized because they are non-local [15] , i . e . they require cell wide spatial averaging over synapses , which can only be achieved in a plausible way if all synaptic weights decay at a global rate modulated by the total afferent synaptic strength [16] . To avoid this , “rate homeostasis” models have been proposed [15] which strive to maintain a certain postsynaptic firing rate . This approach , which we chose in the present study , has more experimental support [28] , [29] . In contrast to the spatial filtering as described above , this mechanism requires temporal filtering of the postsynaptic rate over a given time window ( represented by in this study ) . We can further distinguish between two principal types of homeostasis . A homeostatic mechanism can either act on the synaptic weights directly ( e . g . synaptic scaling ) , or indirectly through metaplasticity [20] , by changing parameters of the plasticity model over time . The former , direct form of homeostasis allows for synaptic changes even in the absence of activity as it is seen in synaptic scaling experiments [21] on a timescale of days . This is in contrast to theoretical models that apply scaling by algorithmically enforcing weight normalization [13] , [18] on the timescale of one or a few simulation time-steps . In our study we looked at both approaches . In the metaplastic triplet STDP model homeostasis manifest itself as a shift in the plasticity threshold between LTD and LTP [19] , [30] , [42] , [43] . This is achieved by modulating the rate of LTD induction using the temporal average of the postsynaptic firing rates over a given time window ( ) . As we have shown , this average has to follow the neuronal spiking activity very rapidly , meaning that plasticity parameters change on a short timescale , which is comparable to the duration of many standard STDP protocols [26] . We therefore predict that if biological circuits rely on such a metaplastic homeostatic mechanism , weight changes are different for cells that are silent prior to a plasticity induction than for cells that have been primed by postsynaptic firing ( over an extended period before the induction protocol ) . In Figure 7 A we demonstrate this idea in the model of metaplastic triplet STDP ( ) for a typical LTD induction protocol ( 75 pairs at 5 Hz with −10 ms spike offset ) . Figure 7 B shows the relative differences between primed and unprimed experiments in dependence of the length of the priming duration or the priming frequency respectively . Since this plasticity rule implements homeostasis as an activity dependent change of the LTD learning rate , the amount of LTD changes dramatically while LTP is unaffected by priming . However , we expect that the main results of our mean field analysis also hold for cases in which LTP is affected , as long as the net synaptic weight change decreases with the intensity of priming . In either case the functional form of the dependence allows us to draw conclusions on the order of magnitude of and the exponent of appearing in ( cf . Eq . 18 ) . Conversely , if homeostasis was exclusively mediated by synaptic scaling , we would expect that it manifests as a heterosynaptic effect . Its impact , however , would likely be smaller than in the case of metaplastic triplet STDP , because synaptic scaling does not have an explicit dependence on the presynaptic firing rate . Since stability requires to be relatively short , it is also worth considering the extreme case where it is on the timescale of a few hundred milliseconds . In that case the learning rule can be interpreted as a quadruplet STDP rule combining a triplet term for LTP ( e . g . post-pre-post ) with a quadruplet term for LTD ( e . g . post-post-post-pre ) . While such a choice of would make sense from a stability point of view , this behavior is not seen in experiments [26] . The timescales of synaptic plasticity and the time constants behind most homeostatic mechanisms reported in experiments are far apart . While plasticity can cause substantial synaptic changes in less than one minute [24]–[26] , homeostatic responses typically differ on the order of several magnitudes ( hours or days ) [29] , [37] . In this paper we have shown that even if homeostatic changes manifest relatively slowly they have to be controlled by a fast rate detector , else triplet STDP is incompatible with the low background activity observed in cortical circuits . We argue that this statement is likely not to be limited to our particular model , but rather applies to an entire family of existing plasticity models . The basic building blocks of our study were a network model and a homeostatic plasticity rule . We used a generic balanced network model [7] , [10] , [44]–[46] to mimic brain-like spiking activity in a recurrent neural network . It is clear that the particular choice of network model does affect our results in a quantitative way and absolute predictions would require a more accurate and detailed network model . Nevertheless , we expect homeostasis to have similar timescale requirements in more detailed models as well . Indeed , as long as a strengthening of the excitatory synapses yields increased firing rates without a major change in the correlations , the qualitative predictions of the mean field model hold . However , our simulations were limited to roughly 1000 recurrent inputs per neuron , which is presumably less than what real cortical neurons receive [31] , so that excitatory run-away could build up even more rapidly in real networks than in our simulations . The second building block of our model was the plasticity rule . Here we chose triplet STDP [30] as a plasticity model that quantitatively captures a large body of experiments [24] , [26] . One key feature of this model , which is seen across a range of in-vitro plasticity studies , is the fact that it yields LTP for high postsynaptic firing rates . The emergence of a critical timescale for homeostasis is mainly rooted in this fact and it is largely relaxed for pair-based STDP , be it additive or multiplicative [12] . However , such models do not capture experimental data as well as triplet STDP . With the models we analyzed , namely the metaplastic triplet STDP and triplet STDP with synaptic scaling , we combined a realistic STDP learning rule with two quite different , but commonly used synaptic homeostatic mechanisms [15] , [18] , [19] , [30] , [35] , [38] , [42] , [43] , [47] , [48] . The fact that we were able to show in both cases , either using a generic mean field model or numerical simulations of large balanced networks , that a fast rate detector is needed for stability , suggests that these results are quite general . The argument is further strengthened by the fact that existing computational models demonstrating stable background activity in plastic recurrent network models either use a form of multiplicative STDP which can be intrinsically stable [12] , but has poor memory retention [12] , [34] , or rely on a fast homeostatic mechanism [18] , [43] . In fact one of the first studies that illustrates stable learning in large recurrent networks combined with long memory retention times [43] is a model of metaplasticity built on top of the triplet model [30] . To describe effects observed in priming experiments [41] , [49] , [50] , the authors introduce two floating plasticity thresholds that modulate the rate of LTP and LTD depending on the low-pass filtered neuronal activity . El Boustani and colleagues obtain the time constants behind these filters by fitting their model to experimental data . It is striking , and in agreement with what we report here , that the timescales they find are on the order of 1 s [43] . We conclude that current plasticity models that capture experimental data well require homeostasis to be able to react fast in order to maintain a stable background state . Likewise , if there is no rapid homeostatic control , most current plasticity models are probably missing a key ingredient to what makes cortical circuits stable . The metaplastic triplet STDP rule we used makes use of an homeostatically modulated rate of LTD and can be mapped to a BCM-like learning rule [30] , [38] . The BCM theory relies on a plasticity rule with a neuron wide sliding threshold [15] , [51] . There seems to be some experimental ground for this idea [52] , [53] and it is intriguing , that the effects reported there are on the order of 30 min or less which points towards a relatively fast mechanism . We should further point out , that the arguments that led us to the critical timescale of homeostasis are not limited to a neuron wide sliding threshold . In fact the mean field equations for a global or local synaptic sliding threshold , or even one based on local dendritic compartments , are identical . Therefore the arguments we put forward also hold for the latter cases , which have experimental support through priming experiments [41] , [49] , [50] . Priming experiments highlight changes in the induction of plasticity which depends on the synaptic activity over some 30 min . With synaptic scaling we studied another possibility of introducing homeostasis into the triplet STDP model . Homeostatic scaling of synapses has good experimental support [21] , [29] , [37] . Although it is generally associated with long timescales ( order of days ) , also more rapid forms of scaling are known [54]–[56] of which some indeed act on the order of minutes [57] . Further modeling is required to test the ability of these rapid forms of homeostasis to guarantee stability in recurrent networks . Finally one should note that the critical time scale of the rate detector strongly depends on the firing rates of the background state ( , cf . Eq . ( 7 ) and Methods ) . The low firing rates reported experimentally [58]–[60] are therefore potentially necessary to guarantee the stability of the network . Conversely , cells or sub-networks with higher mean firing rates should have lower learning rates in order to be stable . Despite the mean field formalism being a drastic simplification of the original spiking model , the results we were able to derive from it were surprisingly accurate in the case of metaplastic triplet STDP and off by a factor of two in the case of triplet STDP with synaptic scaling . In all cases our mean field predictions overestimate the critical timescale obtained from simulations . This discrepancy has multiple potential reasons . First , in the mean field model we completely omit the existence of noise , fluctuations , and correlations . That these factors do play a role follows from the observation that the spiking network does not stabilize at the target rate , but at higher values ( cf . Figure 2 E ) . Although correlations in the AI state are small , they are on average positive [9] . When we estimated we explicitly ignored correlations and required that LTD and LTP cancel at a firing rate . Adding correlations causes this cancellation to take place at slightly higher rates , which reduces the effective critical time constant . In the rate formulation of the STDP rule we make the simplifying assumption that the synaptic traces are perfect estimates of the postsynaptic firing rates . Indeed it can be shown that fluctuations that are present in the rates , bias the learning rule towards LTP ( see Text S1 ) . Finally , any deviation of the population activity from its target value , initial or spontaneous , can be thought of as perturbations around the fixed point of background activity in the mean field model . This can compromise stability when the basin of attraction is small , as is the case when is close to criticality ( Figure 3 D ) . Again , such perturbations bias the critical value for the spiking network towards lower values . All the above points concern the simplifications made when going from the spiking model to the mean field model . More importantly , the spiking model itself already represents a drastic simplification of the biological reality . For instance , we did not include neuronal firing rate adaptation or synaptic short-term plasticity ( STP ) in the present model . The timescales involved in firing rate adaptation are typically short ( on the order of 100 ms ) and their effect therefore negligible at the low firing rates of background activity [61] , [62] . While the time constants behind STP can be longer than that , their stabilizing effect is somewhat less clear since they can be facilitating and depressing [63] . Although we do not expect STP to have a strong impact on our main results , it would be an interesting avenue to verify this in future studies . All our present studies were limited to spontaneous background activity . In a more realistic scenario we would expect the network to receive external input with spatio-temporal correlations . Such input will generally cause synaptic weights to change , which in the mean field model corresponds to a perturbation of the dynamical network state around the stable fixed point . If the perturbation leaves the system in the basin of attraction of background activity , equilibrium will be restored over time . If , however , the perturbation is strong , or perturbations are in rapid concession and start to pile up , the system loses stability once its dynamical state reaches the separatrix ( cf . Figure 3 C , D ) . Another possibility worth mentioning is homeostatic regulation through inhibitory synaptic plasticity ( ISP ) [64]–[68] . Recent theoretical studies [69]–[71] suggest that ISP could produce an intrinsically stable feed-back system . Although we cannot exclude ISP as an important factor in network homeostasis , we have excluded it in the current study . It is likely that to stabilize Hebbian plasticity at excitatory synapses , ISP has to act on a comparable timescale [72] and it will be interesting to integrate future experimental findings into a similar framework as presented here . In summary , homeostatic mechanisms are necessary to stabilize the background activity in network models subject to Hebbian plasticity . Homeostasis needs to react faster than what is experimentally observed . This raises the important question of how the background activity in the brain can be stable . Our results suggest that the existence of a rapid homeostatic mechanism could be one possible answer . That , however , would require this mechanism to act on the same timescale as most STDP induction protocols . This then raises the question , why it has not been observed so far . Suitable plasticity protocols to detect such a mechanism should be similar to priming experiments [41] , [49] , but on the timescale of 1 min ( Figure 7 ) . Another possibility would be , that the plasticity rate is not a constant after all , but subject to some neuromodulatory change [73] . This could be possible , since it cannot be excluded that conditions in slice preparations , like the ones used to obtain the parameters of triplet STDP [26] , are different from in-vivo conditions . Finally , also fast forms of ISP could play a role in network stability . No matter whether through ISP or additional , hitherto unseen excitatory homeostatic effects , a variation of current models of homeostasis and plasticity seem inevitable , to achieve stability in plastic network models whilst making them biologically plausible .
The networks we study consist of leaky integrate-and-fire neurons with a relative refractory mechanism connected by conductance-based synapses [46] . The membrane voltage of neuron evolves according to ( 11 ) A spike is triggered when crosses the spiking threshold . After a spike is reset to and the threshold is increased to implement refractoriness . In the absence of spikes the threshold relaxes back to its resting value according to ( 12 ) with similar to [42] . Inhibitory neurons were modeled identically except for a shorter membrane time constant . All relevant parameters are summarized in Table 1 . The spike train of neuron is defined as , where the sum runs over all corresponding firing times of neuron . It affects the synaptic conductances of downstream neurons as ( 13 ) if the index corresponds to an inhibitory neuron or ( 14 ) ( 15 ) in the case of an excitatory cell . Here is the weight of the synapse connecting neuron with ( if the connection does not exists ) . Excitatory synapses contain a fast rising AMPA component with exponential decay and a slowly rising NMDA component with its respective exponential decay with time constant . For simplicity we implemented the NMDA component as a low pass filtered version of the AMPA conductance ( Eq . ( 15 ) ) . The complete excitatory postsynaptic potential ( EPSP ) is then given by a weighted sum of the AMPA and NMDA conductances ( 16 ) With the chosen parameters ( cf . Table 1 ) , a typical EPSP has an amplitude of about , as shown in Figure 1 B . For computational efficiency the voltage dependence of NMDA channels was omitted . All units ( 20000 excitatory and 5000 inhibitory units , see Table 2 for details ) are connected randomly with a sparse connectivity of 5% . Additionally each excitatory cell receives external input from a pool of 2500 independent Poisson processes firing at 2 Hz that are connected with 5% probability . The relevant synaptic weight values are summarized in Table 2 . Due to the high recurrence ( on average 1000 out of 1125 connections are from within the network ) the mean firing rate and network activity are sensitive to small changes in the recurrent synaptic strength . By appropriate choice of the excitatory weights ( ) the network is initially tuned to the balanced state with AI activity at a mean population activity of approximately 3 Hz . We model synaptic plasticity after the triplet STDP model of [30] , using the minimal parameter set corresponding to in-vitro visual cortex data [26] . Plasticity only affects the EE recurrent connections . Weight updates act additively on the matrix elements and are given by ( 17 ) where is a small positive number and , and are synaptic traces of neuron defined as with associated time constants , and respectively ( see Table 3 and [30] ) . Since the original triplet model describes relative synaptic changes , weight updates in Eq . ( 17 ) are scaled by the factor , where is the initial synaptic weight and is an additional parameter that can be interpreted as a learning rate , or a conversion factor between the weight scales of the model and the true biological scale . In the model we approximate the biological scale by choosing plausible values for ( cf . Figure 1 B ) and therefore expect to be of the order of one . For a synapse with an initial weight of , a value of corresponds to the learning rate that best fits visual cortex data [30] . However , since small values of are computationally expensive we used in Figure 2 to ensure that a stable weight distribution can be observed within a day of simulated biological time ( of computation time ) . Note that for we would expect a comparable degree of convergence after 6 . 25 days of simulated time ( roughly four weeks of computation ) . During ongoing plasticity the allowed weight values are limited to the interval . Note that to avoid the creation of new synapses , connections that have zero weight initially , remain absent ( ) throughout the entire simulation . In simulations with metaplastic triplet STDP the amount of long term synaptic depression ( LTD ) is varied homeostatically as a function of the moving average of the postsynaptic firing rate [15] , [19] , [30] , [38] with ( 18 ) This choice of ensures that for uncorrelated Poisson firing at the rate LTP and LTD cancel on average . The moving average of the firing rate of neuron is implemented as a low pass filtered version of its spike train ( 19 ) where is the timescale which controls of the temporal evolution of ( cf . Eq . ( 18 ) ) . In simulations that require an additional slow weight decay of the weights we approximate this exponential decay , to avoid the costly operation of updating all weights after each time step , by periodically ( period ) multiplying all weights by the factor . Finally , simulations of synaptic scaling are performed using a fixed value . The scaling of the weights is approximated with the same approach as for weight decay . In such cases is adapted appropriately according to the occurring scaling time constant . We determine the timescale of plasticity in the mean field model by approximating from the plasticity parameters of the triplet STDP model [30] . To do so we consider the expectation value of the mean weight update averaged over many spike pairs , and we assume that pre- and postsynaptic firing is uncorrelated with stationary rates and respectively . The average relative weight change over time then reads ( 20 ) ( 21 ) ( 22 ) The resulting differential equation can be directly identified with Eq . ( 4 ) to obtain the effective time constant . All differential equations were integrated using forward Euler integration with a 0 . 1 ms time step . Spiking simulations were written in C++ using Open MPI and the Boost libraries . The sources were compiled using the GNU C compiler . Simulations were run on 5 Linux workstations equipped with Intel ( R ) Core ( TM ) 2 Duo E8400 CPUs and 24 GB of RAM each . It took approximately four and a half days to simulate one day of biological time . Numerical results for the phase plane analysis , such as the position of the separatrix , were obtained by integrating the ODEs of the mean field model numerically using custom-written Python code . To analyze the stability of the fixed point of background activity ( ) in the case of the metaplastic triplet STDP rule , we consider the Jacobian of the two dimensional system ( cf . Eqs . ( 5 ) , ( 6 ) ) in the general case of for . ( 23 ) where we introduced the auxiliary variable . When evaluated at the fixed point reduces to ( 24 ) with characteristic polynomial ( 25 ) which determines the eigenvalues to be of the linearized system at the fixed point of background activity ( 26 ) Stability of the fixed point requires all eigenvalues to have negative real parts ( e . g . [74] ) . We now prove that the real part of both eigenvalues is negative if and only if . The square root in Eq . ( 26 ) is either purely imaginary , in which case follows directly . For the case in which the square root is real we can express the larger of the two eigenvalues as ( 27 ) ( 28 ) where we introduced the variable for the term in the square brackets ( Eq . ( 27 ) ) . If then and the fixed point is unstable . If , however , then we know ( 29 ) ( 30 ) ( 31 ) Here , we used the fact that all occurring constants are positive , and the argument in the square root is positive as well . Finally we can conclude the fixed point is stable if . This identifies as an important limiting case for the stability of the fixed point . It is interesting to note that is independent of . | Learning and memory in the brain are thought to be mediated through Hebbian plasticity . When a group of neurons is repetitively active together , their connections get strengthened . This can cause co-activation even in the absence of the stimulus that triggered the change . To avoid run-away behavior it is important to prevent neurons from forming excessively strong connections . This is achieved by regulatory homeostatic mechanisms that constrain the overall activity . Here we study the stability of background activity in a recurrent network model with a plausible Hebbian learning rule and homeostasis . We find that the activity in our model is unstable unless homeostasis reacts to rate changes on a timescale of minutes or faster . Since this timescale is incompatible with most known forms of homeostasis , this implies the existence of a previously unknown , rapid homeostatic regulatory mechanism capable of either gating the rate of plasticity , or affecting synaptic efficacies otherwise on a short timescale . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2013 | Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector |
The impact of climate on the vector behaviour of the worldwide dog tick Rhipicephalus sanguineus is a cause of concern . This tick is a vector for life-threatening organisms including Rickettsia rickettsii , the agent of Rocky Mountain spotted fever , R . conorii , the agent of Mediterranean spotted fever , and the ubiquitous emerging pathogen R . massiliae . A focus of spotted fever was investigated in France in May 2007 . Blood and tissue samples from two patients were tested . An entomological survey was organised with the study of climatic conditions . An experimental model was designed to test the affinity of Rh . sanguineus for biting humans in variable temperature conditions . Serological and/or molecular tools confirmed that one patient was infected by R . conorii , whereas the other was infected by R . massiliae . Dense populations of Rh . sanguineus were found . They were infected with new genotypes of clonal populations of either R . conorii ( 24/133; 18% ) or R . massiliae ( 13/133; 10% ) . April 2007 was the warmest since 1950 , with summer-like temperatures . We show herein that the human affinity of Rh . sanguineus was increased in warmer temperatures . In addition to the originality of theses cases ( ophthalmic involvements , the second reported case of R . massiliae infection ) , we provide evidence that this cluster of cases was related to a warming-mediated increase in the aggressiveness of Rh . sanguineus , leading to increased human attacks . From a global perspective , we predict that as a result of globalisation and warming , more pathogens transmitted by the brown dog tick may emerge in the future .
The recent outbreak of Chikungunya virus in the Indian Ocean Islands and India [1] that reached Europe in 2007 [2] , has illustrated the current medical importance of globalising vector-transmitted infections [3] . The impact of ticks on human public health was recognised with the emergence of Lyme disease 25 years ago [4] . Since then , around 15 emerging tick-borne rickettsioses have emerged [5] . Ticks strive for the best conditions for their life cycle and to find and bite a host [6] . Climate and the availability of hosts are among the major factors influencing ticks [6] , [7] . The impact of climate change on tick-borne diseases has been the topic of controversial debate in the scientific literature [7] , [8] . Additionally , it has been suggested that global warming would result in a northward expansion of several tick species , including I . ricinus and I . scapularis the vectors of Lyme disease in Europe and North America , respectively [7] , [9] , and Rhipicephalus sanguineus group ticks [10] . Rh . sanguineus , the dog brown tick , is considered the first globalised tick as it has become the most widespread tick throughout the world due to its specialised feeding on the domestic dog [11] , [12] . In addition to the dog pathogens Babesia canis and Ehrlichia canis [12] , Rh . sanguineus is known to transmit two life threatening rickettsial diseases in humans , Mediterranean spotted fever ( MSF ) caused by R . conorii in the old world [13] , and Rocky Mountain spotted fever ( RMSF ) caused by R . rickettsii in America [14] . Rh . sanguineus also transmits R . massiliae , a worldwide emerging pathogen [15] with a single documented case of infection [16] . Rh . sanguineus is well adapted to urban environments and lives in close contact with humans . However , Rh . sanguineus rarely feeds on humans , particularly in temperate countries [11] . Herein , we describe the investigation of a focus of rickettsioses in southern France during the exceptionally warm April and May months of 2007 . Patients suffered from severe R . conorii and R . massiliae infections , and we found that this cluster of cases resulted from unexpected proliferation and aggressive behaviour of Rh . sanguineus ticks infected by these rickettsiae . We demonstrate experimentally that Rh . sanguineus readily bites humans when exposed to higher temperatures .
Serum , spinal fluid , aqueous humor and tissue specimens were obtained from both patients . Sera were tested for IgG and IgM antibodies by immunofluorescence ( IF ) assay [17] using 10 rickettsial antigens [18] . When cross-reactivity was noted between several antigens , and the difference in titers between antigens was lower than two-fold , western blotting following cross-adsorption was performed [17] . DNA was extracted from ground eschar biopsies and aqueous humor specimens from patient 1 and from acute sera from both patients [19] . These extracts were used as templates in a nested PCR assay incorporating primers selected from specific regions of the pgsA gene present in both R . conorii and R . massiliae genomes ( GenBank accession numbers NC 003103 and CP 000683 , respectively ) . Primers specifically designed for this study included pgsAF1 ( 5′- AGATAATGTAGATGAGATACC-3′ ) , pgsAR1 ( 5′-GTTAAAAAAGCGGCAATCCA-3′ ) , pgsA F2 ( 5′-TTTTTAGTTAGCGGTCTTCGG-3′ ) and pgsAR2 ( 5′- TTGAGCCTAGTATCAATATCG-3′ ) . The so-called “suicide PCR” procedure has been followed , that is a nested PCR using single-use primers targeting a gene never amplified previously in the laboratory . This procedure avoids “vertical” contamination by amplicons from previous assays , one of the limitations of extensive use of PCR [20] . Sequences of positive PCR products were compared to GenBank [21] . Tick DNA was extracted and rickettsiae were detected in each sample through the PCR amplification of a 382-bp fragment of the gltA gene [22] . Sterile water and DNA extracted from uninfected ticks from our laboratory were used as negative controls . Sequences obtained from PCR products were identified by comparison with GenBank [22] . All gltA-positive DNA samples were tested using multi-spacer typing [23] . For each sample , three intergenic spacers , ( dksA-xerC , mppA-purC and rpmE-tRNAfMet ) were amplified and sequenced using the primer pairs dksAF-dksAR , mppAF-mppAR and rpmEF-rpmER , respectively . All amplicon sequences were compared to GenBank [22] , [23] . On July 5th 2007 , the house where the patients reported to have been bitten by ticks was visited . The owners were interviewed . Ticks were collected from walls of the house and from the garden ( Figure 2 ) and were morphologically identified [24] . The climatic conditions in Nîmes in April and May 2007 were studied using the Météo-France's web site ( http://www . meteo . fr/meteonet_en/index . htm ) . We used larvae , nymphs and adults from a pathogen-free laboratory colony of Rh . sanguineus , that were colonized starting August 2006 when engorged Rh . sanguineus females were collected in Oran , Algeria , and maintained in environmental incubators at 25°C and 90% RH with a day/night photoperiod of 16∶8 ( L∶D ) h until they oviposited . Eggs and all life-cycle stages of subsequent generation were maintained under the same environmental conditions . For their blood meal , all stages were placed on a rabbit to feed until repletion [25] . The third generation of ticks was used for the experiment . For all stages , two batches were put on the arm of 3 human volunteers ( 3 of the authors including PP , IB , DR ) who gave written consent to participate . This healthy volunteer study was approved by the Ethical Review Committee of the Faculty of Pharmacy , Algiers , Algeria . One batch was maintained the night before the test 25°C , and the other was maintained at 40°C . All ticks from the different groups were stored in environmental incubators with 90% relative humidity . All ticks were removed after 40 minutes and the number of attached ticks was compared between conditions ( Mantel-Haenszel test ) . Three experiments were processed for larvae and nymphs , two for adults . An additional experiment was made that compared in the same experimental design , the affinity for biting of nymphs maintained at 32°C and 25°C .
Using IF , antibodies against all spotted fever group rickettsial antigens were detected in patient 1 at the same level ( IgG 2 , 048 , IgM 16 , on July 8th ) . In patient 2 , the difference in titers between several antigens was lower than two-fold ( IgG 1 , 024 , IgM 256 for R . conorii ; IgG 1 , 024 , IgM 128 , for all other antigens ) . Western blot and cross-adsorption assays indicated that antibodies were specifically directed against R . massiliae in patient 1 and R . conorii in patient 2 ( Figure 3 ) . “Suicide PCR” was positive from two samples ( of seven tested ) obtained from the eye acqueous humor and the eschar biopsy of patient 1 . Amplicon sequencing confirmed that patient 1 was infected with R . massiliae , as the obtained pgsA sequence was 98 . 9% similar to R . massiliae . The owner , a 50 year-old nurse of the house were patient 1 and patient 2 had been bitten by tick was interviewed . Her dog that used to roam freely and used to rest and sleep in the garage and many rooms of the house , died due to a gastric torsion in April 2007 . She reported that the ticks on this dog were numerous and particularly aggressive to people in April 2007 , including before its death . The ticks regularly bit her , and her son , a 30 year-old man ( not tested here ) who presented at that time with a febrile syndrome and a maculo-papular rash . He did not sick medical care . However , when a veterinary doctor was consulted about the dog , he suggested that the son could have a “boutonneuse fever” , the other name of Mediteranean spotted fever , and suggested a doxycycline treatment . Fever disappeared on day 2 of a 200 mg daily doxycycline treatment and the son remained well . The case-patients reported tick bites when they were outside , although they also noticed ticks in several walls inside the house . The entomological investigation was performed after the patients had cleared of brushwood and sprayed the garden with acaricides . A total of 218 nonengorged ticks , all identified as adult Rh . sanguineus , were collected in less than one hour . Ten ticks were collected with flannel flags dragged over vegetation . In the garage , 25 ticks were recovered from a blanket and 90 were collected from the walls inside ( Figure 2 ) . Outside , 93 ticks were collected from the walls of the house . Rickettsial DNA was detected in 37/133 ticks tested by PCR ( 28% ) . Twenty-four ( 18% ) exhibited a 100% sequence similarity to R . conorii subsp . conorii strain Malish ( AE008677 ) . Thirteen specimens ( 10% ) showed 100% sequence similarity with R . massiliae ( U59720 ) . Each of the dksA-xerC , mppA-purC , and rpmE-tRNAfMet intergenic spacers were amplified from gltA-positive ticks . For all 24 R . conorii-positive ticks , mppA-purC sequences were 100% similar to R . conorii genotype A ( AY345089 ) , and rpmE-tRNAfMet sequences were 100% similar to R . conorii genotype B ( AY345092 ) , but dksA-xerC sequences represented a new genotype named AX ( EU081773 ) . For all 13 R . massiliae-positive ticks , dksA-xerC sequences were 100% similar to R . massiliae genotype AE ( CP000683 ) , rpmE-tRNAfMet sequences were new ( genotype AD , EU250277 ) , and mppA-purC sequences were also new ( genotype AH , EU250278 ) . All together , the two rickettsia represented new genotypes . In April 2007 , the weather in southern France was associated with the highest temperatures noted since 1950 ( +3 to +4°C compared to seasonal norms ) [26] , particularly in the Gard region ( Nimes being the main town ) . After April 15th , in Nîmes , maximal temperatures were continuously between 25°C and 30°C ( Figure 4 ) . A total of 15 “warm days” ( >25°C ) were recorded , in contrast to the seasonal norm of 0 . 6 . The total duration of sunshine during the month was also increased when compared to seasonal norms ( 260h14min; that is+40 h ) . Few periods of rainfall were recorded between December 2006 and April 2007 , with a total of 114 . 4 mm during this period , making this the 4th dryest since 1921 . In May , new records were reached with temperatures higher than 33°C between the 22nd and 24th [26] . In the 3 experiments with larvae , 27–67% of the ticks previously maintained at 40°C attached to the skin , whereas 0–6% of those at room temperature attached ( p<0 . 05 in all cases ) . Among the nymphs , 10–20% of the batches previously maintained at 40°C attached to the skin ( Figure 5 ) , whereas none of those at room temperature attached . Overall , for larvae and nymphs , the number of ticks attached to the skin was dramatically higher for the group maintained at 40°C ( Table 1 ) . No difference appeared in adults , as no specimen but one attached to the skin within 40 mn . In the fourth additional experiment the affinity for biting of nymphs maintained at 32°C was also significantly higher than at 25°C ( Table 1 ) .
When investigating these grouped cases of severe spotted fevers first presumed to be MSF caused by R . conorii , two rickettsial pathogens were in fact identified . This report describes the second human case of R . massiliae infection and was documented using the IF reference serology assays [5] , completed by western blot and cross absorption studies and definitely confirmed with the use of molecular tools . R . massiliae is a worldwide rickettsia that was isolated in 1992 and thereafter detected in Rhipicephalus spp . in Europe and Africa [5] , Argentina [27] , and recently in Arizona , USA [15] . The recognition of the pathogenicity of R . massiliae occurred in 2005 when molecular tools were used to identify a rickettsial isolate obtained 20 years before from a man hospitalised in Italy with fever , an eschar , and a maculopapular rash [16] . In fact , R . massiliae is the sole pathogenic rickettsia known to be prevalent in America , Africa and Europe . In the present report , the predominant symptom was acute visual loss , and both diagnosis and treatment were delayed . Although eye involvement has been reported in spotted fever group rickettsioses , these manifestations are underdiagnosed or frequently misdiagnosed [28]–[30] . Clinicians should suspect rickettsioses in patients with febrile acute visual loss , particularly during the warmest and most common months for Rh . sanguineus-transmitted diseases . Indeed , we have identified here that the source of the focus was an unexpected attack of Rh . sanguineus . Additionally , we have shown for the first time that the population of rickettsias found in a focus of infection was clonal , as all R . massiliae- and R . conorii-positive samples had a unique MST genotype . The rate of infection of Rh . sanguineus was high , particularly for R . conorii ( 18% ) . In contrast , the rate of infection is usually lower that 1% [5] , [31] . This , combined with an unusual rate of tick attack , was responsible for multiple inoculation escar in our patients . This is an unusual finding in most tick-borne rickettsial diseases , including MSF , because the probability of being bitten simultaneously by several infected ticks has been considered to be rare . This finding is characteristic of few other tick-borne rickettsioses , an example being African tick bite fever caused by R . africae , due to the aggressive behavior of the tick vectors and a high tick infection rate [5] , [32] . Rh . sanguineus lives in peridomestic environments shared with dogs but is known to have a low affinity for humans . Hosts other than dogs are usually only infested when dogs are present to maintain a population of the tick [33] . In this setting , the dog allowed a large infestation of ticks , which had no place to go when the dog died . The risk of the people to be bitten was therefore greatly increased , very much like relapsing fever in the American West , where infected soft ticks accumulate in cabins when their squirrel hosts die during the winter [34] . This highlights the importance of the so-called “zooprophylaxis” – that risk is small when there are alternative hosts than people upon which a vector can focus . However , in the present report , ticks started to be particularly aggressive to people before the death of the dog . Also , the son of the owner presented with a tick-borne eruptive fever , before the dog died . Therefore , the death of the dog could not be considered as the cause of this unusual cluster of Rh . sanguineus transmitted rickettsioses . We provide some evidence that this cluster of cases was related to unusually warm temperatures . As shown herein , April 2007 was the warmest April since 1950 , with summer-like temperatures [26] . Also , considerable evidence was accumulated by investigators in the 1940's about the role of Rh . sanguineus as a vector of rickettsioses in warm countries such as Mexico [5] . In Europe and North Africa , although Rh . sanguineus starts to be active in May and June [24] , most cases of MSF are diagnosed during July and August . This is probably linked to an increased aggressiveness and propensity of Rh . sanguineus to bite hosts in warmer conditions , as demonstrated for other Rhipicephalus species biting cattle [35] , [36] . During the 1970s , the increase in the number of MSF cases observed in southern Europe [37] was correlated with higher temperatures and lower rainfall in Spain , and with a decrease in the number of days of frost during the preceding year in France [38] , [39] . The cases of MSF recognized in Oran , Algeria in 1993 peaked in 2005 together with the hottest summer of the past decades [18] . More recently , maximum temperature levels during the previous summer were associated with increases in MSF incidence in Sardinia [40] . Finally , during the French heat wave in 2003 , with the hottest summer of the preceding 50 years , 22 Rh . sanguineus , including specimens infected by R . conorii and R . massiliae , were found attached to an homeless person who died of MSF in August [41] . This case was highly unusual in regard to the intensity of the parasitism by Rh . sanguineus which had never been reported before in patients or by entomologic investigators who spent their lives collecting ticks [38] . Herein , we have demonstrated by our experimental model that the aggressiveness of immature stages of Rh . sanguineus to bite human is modulated by external temperature . It is important to remind that ixodids do not cause pain while feeding and immature stages are frequently not detected on people because of their small size [6] . Furthermore , we have recently demonstrated the similar effects of higher temperature on the speed of attachment of all stages of Rh . sanguineus ticks , including adults using a rabbit model in a similar experimental design and a 48 hour observation period [42] . We conclude that the host seeking and feeding behaviors of Rh . sanguineus in the present focus were modified by the warmer climatic circumstances and became highly aggressive for the owners and visitors of the house . Rh . sanguineus , a tick of African origin , is now of global importance [11] . The public health importance of the globalisation of vector-borne diseases has been illustrated with West-Nile fever that emerged in 1999 in the USA and has become the dominant vector-borne viral disease [43] . More recently , a returned traveller served as a source of a local Chikungunya virus outbreak in Europe [2] , where Aedes albopictus , the recently globalised Asian tiger mosquito is prevalent , as it also is in America [44] . Although ticks have long been considered vectors of geographic diseases because of their preferred environmental conditions and biotopes [6] , some vectors have also been globalised . R . africae , the agent of African tick bite fever , has been found in the West Indies where it was introduced from Africa during the 18th century through Amblyomma variegatum ticks on cattle . Now , this rickettsia threatens the American mainland [45] . Rh . sanguineus has spread globally between 50°N and 35°S because of its ability to survive in human home sites [11] . Climate variability will change local weather in sites where brown dog tick infestations occur . If global trends in weather over the long term unfold as predicted , weather will be more variable and may comprise warmer temperatures , droughts and heat waves , as well as more monsoons , or more intense snowstorms , depending on the site [9] , [46] . Based on the present investigation and previous epidemiological clinical and experimental data ( Table 2 ) , and on a global perspective , we predict that increased temperature will lead to an increased period of activity of Rh . sanguineus and an increased aggressiveness and proclivity to bite humans , and that increased incidence of Rh . sanguineus-transmitted diseases will be observed ( Figure 6 ) . On a flip side , cooler weather , if any , in sites where Rh . sanguineus are currently endemic would imply less human biting . However , in the context of warming [9] , the public health burden of this tick will increase . After R . conorii , R . rickettsii and the worldwide emerging pathogen R . massiliae [5] , other rickettsial agents such as R . rhipicephali [5] , or yet undescribed microorganisms , could be found soon as emerging pathogens transmitted by the globalised and multipotent vector , Rh . sanguineus . | The impact of climate on the behaviour of the worldwide dog tick Rhipicephalus sanguineus is a cause of concern . This tick is a vector for life-threatening organisms including Rickettsia rickettsii , the agent of Rocky Mountain spotted fever , R . conorii , the agent of Mediterranean spotted fever , and the ubiquitous emerging pathogen R . massiliae . A focus of spotted fever was investigated in France in May 2007 . One patient was found to be infected by R . conorii , whereas the other was infected by R . massiliae . Theses cases were original because of ophthalmic involvements , and the report of the second case of R . massiliae infection in the scientific literature . During an entomological survey , dense populations of Rh . sanguineus were found in the house where the patient had been bitten by ticks . Ticks were infected with either R . conorii or R . massiliae . Interestingly , April 2007 was the warmest since 1950 , with summer-like temperatures . In this work , we show that the human affinity of Rh . sanguineus is increased in warmer temperatures , and provide evidence that this cluster of cases was related to a warming-mediated increase in the aggressiveness of Rh . sanguineus , leading to increased human attacks . From a global perspective , we predict that as a result of globalisation and warming , more pathogens transmitted by the brown dog tick may emerge in the future . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"infectious",
"diseases/bacterial",
"infections",
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"infectious",
"diseases"
] | 2008 | Warmer Weather Linked to Tick Attack and Emergence of Severe Rickettsioses |
Vibrations are important cues for tactile perception across species . Whisker-based sensation in mice is a powerful model system for investigating mechanisms of tactile perception . However , the role vibration plays in whisker-based sensation remains unsettled , in part due to difficulties in modeling the vibration of whiskers . Here , we develop an analytical approach to calculate the vibrations of whiskers striking objects . We use this approach to quantify vibration forces during active whisker touch at a range of locations along the whisker . The frequency and amplitude of vibrations evoked by contact are strongly dependent on the position of contact along the whisker . The magnitude of vibrational shear force and bending moment is comparable to quasi-static forces . The fundamental vibration frequencies are in a detectable range for mechanoreceptor properties and below the maximum spike rates of primary sensory afferents . These results suggest two dynamic cues exist that rodents can use for object localization: vibration frequency and comparison of vibrational to quasi-static force magnitude . These complement the use of quasi-static force angle as a distance cue , particularly for touches close to the follicle , where whiskers are stiff and force angles hardly change during touch . Our approach also provides a general solution to calculation of whisker vibrations in other sensing tasks .
Vibration of tactile sensors contributes to perception of surface texture and object identification in humans [1 , 2] , prosthetic devices [3 , 4] , and potentially rodents [5–8] . Vibration could also be an important cue for determining the distance to objects using swept sensors . This method of distance determination is important for mice and rats , who rely on active touch of swept whiskers for navigation and object localization in their natural habitat . It is also important for visually impaired people , who navigate , locate , and identify nearby objects by touch with a swept white cane [9] . When an elastic beam strikes an object , the beam bends and vibrates . The frequencies of this vibration are dependent on where along the beam contact is made [10] . Sensing of vibrational frequency was proposed as a possible method for distance determination using artificial swept antennae [11] . This method has been demonstrated with artificial cylindrical whiskers swept into objects [12] and for similar whiskers held fixed as a textured drum steadily rotates against them [13] . This supports the possibility that rodents could use vibration as a cue for distance to object . However , rodent whiskers are approximately conical [14 , 15] , with the center of mass one quarter length from the whisker base . This provides conical whiskers with distinct vibrational properties . In addition , the relative lack of mass near the tip of the whisker might make vibrations a less informative cue about object distance during distal contacts . Since whiskers are conical , they tend to bend much more during distal rather than proximal contacts . This is because the bending stiffness of a beam with a circular cross section is proportional to the fourth power of its radius . For the same push angle ( i . e . the maximum angle the base rotates towards an object during touch ) , the angle of the force applied by the pole to the follicle is strongly dependent on object distance [16] . This results in different ratios of axial to lateral forces and moments for proximal and distal touches [17] , which was proposed as a behavioral basis of radial distance discrimination in head-fixed rodents [18 , 19] . In comparison , force magnitude or push angle during touch provides degenerate signals during active radial distance discrimination by mice , neither of which alone predict the behavior of the animal . Recent biomechanical modeling and experiments on isolated whiskers show that both force angle and vibration can be used to mechanically discriminate radial distance of contact [20] . In rodents , quasi-steady state forces drive activity in slowly adapting and Merkle-cell mechanosensory afferents in the whisker follicle [21 , 22] , while vibrational dynamics could be well suited for activation of fast-adapting mechanoreceptors [21 , 23] . Are the forces and whisker dynamics during actual object localization by head-fixed mice suitable for radial distance discrimination by vibration ? Under what conditions would vibration frequency , magnitude , or force angle be a more informative cue ? We address these questions by examining quasi-static and dynamic forces evoked by active touch by head-fixed mice locating objects with their whiskers . We present a new analytical approach to model whisker dynamics generated by contact with objects . This solution builds upon prior work [20 , 24] . We experimentally constrain the model by measuring parameters which control these dynamics , including Young’s modulus , damping coefficient , and the temporal dynamics of whisker bending during active touch . We estimate time varying forces applied to the whisker by the object using a quasi-static approximation of whisker bending , then apply the model to calculate vibrational whisker dynamics , bending moment , and shear force at the follicle . The calculated vibrations closely match vibrations we observe under high speed imaging . We find that the vibration frequency during touch provides a unique signature for object distance during contacts along the proximal two thirds of a whisker . Since the proximal half of whiskers are relatively stiff , vibration frequency provides a more sensitive cue for discriminating object distance than the angle of applied force for touches in this range . We also find that the relative magnitude of vibrational forces to quasi-static forces dramatically increases at distal object locations . Thus , neural circuits which compare the relative magnitude of vibrational to sustained forces evoked by touch could provide another distance cue .
We trimmed head-fixed mice to a single whisker ( C2 ) and observed their interactions with a thin vertical pole presented at varying distances from the mouse’s face ( 6 . 5–13mm from follicle; Fig 1a ) . Mouse whiskers are thin tapered elastic beams of roughly conical shape [14] , which we describe using the variables illustrated in Fig 1b . Tracking whisker motion and bending from a top-down view at 1000 frames per second revealed that the follicle translates , the whisker bends , and the angle of the whisker at follicle base and angle at object contact change during single touches ( Fig 2a and 2b ) . The difference between base and contact angles defines the angle of the normal force ( force angle ) and is proportional to the axial ( pushing into follicle ) and lateral ( pushing sideways on the follicle ) forces and bending moment ( torque applied to follicle ) . The ratio of axial force to lateral force or bending moment has been proposed to be used by mice to discriminate object distance during contact with a single whisker [18] . Since whiskers become much more flexible near the tip , Weber’s law predicts distance sensing resolution will be maximum near the tip [17] . To test the prediction that force angle changes more dramatically during touches near the whisker tip , we analyzed a set of 12 , 361 touches from a dataset of head-fixed single whisker object localization [25 , 26] . These touches were all active , exploratory touches that informed the animal’s decision about object location , as they all occurred prior to the first lick in a trial . Consistent with the prediction , we found that the maximum change in force angle for each touch was , on average , small at distances <10mm from the follicle ( 10 . 3–16 . 4 deg from 6 . 7–10mm from base ) , and increased rapidly near the tip ( 16 . 4–36 . 2 deg from 10–12 . 7mm ) Fig 2c ) . This suggests that force angle may be a poor discriminator of distance between object positions <10mm from the follicle ( about 2/3 of the whisker length ) . From this whisker bending and estimates shape of the whiskers , we used the a quasi-steady state method to estimate the temporal profile and magnitude of touch forces [16 , 18] ( Fig 2d ) . Tracking dust particles on the whisker ( Fig 1a , arrow ) during a subset of trials allowed us to determine if whiskers are pushed into the face by axial forces that build up when the whisker bends . The radial location of the follicle moved over 0 . 6 mm as mice moved their cheek while investigating the pole , and up to 0 . 2 mm into or out of the pad during single contacts . However , there was no correlation between increasing whisker curvature , which corresponds to increasing axial force , and the radial location of the dust particle . This suggests that the axial position of the follicle is actively controlled , and allows us to neglect axial compliance . Whiskers vibrate when force is applied to them . These vibrations decay based on damping properties of the whisker and the follicle . To measure the damping coefficient α and first eigenfrequency ω of the C2 whisker , we quantified the decay of whisker curvature change following rare events where the whisker slipped past the pole . The pole was 10 mm from the follicle base and curvature measured 6 mm from follicle base ( Fig 3a ) . These slips provide a large , sharp impulse to the whisker after which the whisker vibrates freely . We describe these vibrations using the oscillatory damped function: f ( t ) = Asin ( ω 2 - ( α / 2 ) 2 t + ϕ ) exp ( - α t / 2 ) , where A is the amplitude of the oscillations and ϕ is their phase at t = 0 . Eight slip-offs were fit , each giving an estimate of the oscillation frequency and damping of the whisker ( Fig 3b and 3c ) . Damping and eigenfrequencies estimates were independent of force magnitude , the point of force application and the point of whisker curvature measurement . The mean damping value , fitted to the decay of the exponent was α = 430 ± 120 rad/s and the mean angular frequency of vibration was ω = 962 ± 50 rad/s ( 153 ± 8 Hz ) . This is well within the range with which mechanosensory neurons in the follicle can fire in every cycle [27] . Since Eq ( 24 ) relates the vibration ( angular ) frequency to Young’s modulus E , using the measured whisker’s parameters , length L = 17 . 14 mm , radius at base R = 37 . 15 μm , and density ρ = 1 . 0g/cm3 we can estimate E for this whisker to be 3 . 04 GPa . This number is near the center of the range of values reported for rat whiskers 3 . 34 ± 1 . 48 GPa [28] . In the analytical modeling examples throughout the remainder of this paper , we selected parameters close to those extracted from these measurements . All whiskers were linearly tapered cones truncated at 0 . 95 of the extrapolated length ( i . e . , ℓ/L = 0 . 05 ) unless otherwise specified . We set length to be L = 18mm , base radius R = 37 μm , density ρ = 1 . 0 g/cm3 , damping α = 430 rad/s , and Young’s modulus E = 3 . 00 GPa . To understand how vibrational dynamics of whiskers could influence tactile perception , we first calculated the eigenmodes and eigenfrequencies of a model whisker ( i . e . a linearly tapered cone ) during two sets of boundary conditions , when the whisker is in contact with a thin cylindrical pole ( Fig 4a ) , or where it is vibrating freely ( Fig 4b ) . In both cases , the follicle is fixed . During touch , all eigenmodes share a node at the follicle base and at the point of contact . We next developed analytical solutions for the vibration of a mouse whisker during object contact at a single point along the whisker’s length , and for free vibration ( see Materials and Methods for a complete description ) . We modeled the timecourse of touch forces based on typical observed touches ( Figs 2d and 5a ) , with the shape of a truncated Gaussian curve . We modeled touch onset as a smooth connecting function with one free parameter , τ , the duration of time between zero force and the main Gaussian ( Fig 5a ) . This is in contrast to previous work [24] , which treat impact as an instantaneous event . Excitation of eigenmodes is sensitive to the duration of the transition period , whereas dynamics at moment of impact are beyond our temporal resolution of observation . Therefore , we performed a parameter sensitivity analysis of τ on eigenmode excitation . The magnitude of excitation of the first six eigenmodes was insensitive to shortening τ below 0 . 1 ms ( Fig 5b ) . Eigenmodes with order above six are >100x weaker than primary and secondary modes , and have higher frequency than what could plausibly be sensed by mechanoreceptors in the follicle . Therefore , we defined τ to be 0 . 1 ms for all later analysis . Excitation of eigenmodes is also sensitive to the location of contact , with the fundamental mode dominating higher modes for most contact positions , except around c/L = 0 . 3 , where the second mode excitation becomes most prominent ( Fig 5c ) . The relative amplitude of these modes affects the temporal pattern of peak vibrational forces at the follicle . A prominent feature of observed touches and prior models of whisker vibrations is the propagation of a wave from the point of contact towards follicle immediately after the onset of touch [24] . Our model recapitulates this phenomenon ( Fig 5d ) . Shear force and bending moment at the follicle drive mechanotransduction [22] . Our model describes the vibrational components of shear force and bending moment ( Fig 5e ) at the follicle following contact onset and offset . These components likely drive mechanotransduction . Contact with a pole causes bending and deflection from applied steady-state force and vibration . Our model provides a complete solution for the displacement of the whisker along its entire length , including beyond the object contact point , decomposed to the steady-state component ( Fig 5f ) , the vibrational component ( Fig 5g ) , and sum of these during ( Fig 5h ) and after contact ( Fig 5i ) . To validate the accuracy of our model , we performed 4000 frame per second imaging of active whisker touch during object localization . Following the experiment , we measured the whisker dimensions L = 15 . 726mm , radius at base R = 38 . 96 microns . Using the whisker properties , the location of the pole ( c/L = 0 . 356 ) and the velocity of whisker at the contact point ( 86mm/s ) we calculated the vibrational response of the whisker with zero free parameters . Remarkably , observed responses had appropriate sign , shape , phase and amplitude ( Fig 6 ) . For vibration to serve as a cue for object distance during contact with a single whisker , there must be some detectable distance-dependent change in whisker vibration . This could manifest as a change in vibration frequency or magnitude . To determine if such a cue could be present , we calculated the frequencies of the first five eigenmodes during object contact . We found a strong dependence of vibration frequency on the distance between contact point and follicle , with the first mode increasing in frequency by 2 . 31x between contact near the base ( c/L = 0 . 95 ) and c/L = 0 . 32 ( Fig 7a ) . This is qualitatively similar to results for a cylindrical whisker [13] , albeit with a less pronounced change in frequency . Here , since the vibration is of a beam with free tip , the distance-frequency relationship is non-monotonic , increasing away from base then decreasing as the contact point approaches the tip . Higher eigenmodes show multi-peaked relationships , with number of peaks equal to the order of the mode , and less relative modulation with increasing order . In a frictionless system , this relationship is independent of touch force or τ , making it robust to variation in how firmly or quickly the mouse strikes the pole . Truncation of the whisker also affected the eigenmode frequency , with modest effects on the first mode , and increasingly strong effects on higher modes ( Fig 7b ) . Could mice determine the distance to the pole using vibration frequency rather than the ratio of axial to lateral forces ( i . e . the angle of the touch force [18] ) ? To assess this , we compared the relative rate of change in vibration frequency and force ratios as the contact point moves along the whisker ( Fig 8 ) . In the proximal half of the whisker , fundamental vibration frequency changes 7 . 4–4 . 1x more quickly with increasing distance ( 4 . 5–10% / mm ) than force ratios ( 0 . 6–2 . 2% / mm ) . Near c/L = 0 . 3 , vibrational frequency becomes more steady , before changing more rapidly again towards the whisker tip . The fundamental frequency near the tip is degenerate with frequency in the proximal 2/3 of the whisker , though including higher order modes could uniquely resolve object distance . In contrast , the rate of change in force ratios increases rapidly for contacts beyond 2/3 of whisker length , exceeding 100% / mm near the tip . This is consistent with the distal third of the whisker being several orders of magnitude more flexible than the proximal third . Overall , this suggests that vibration frequency would be a more salient cue for object distance for contacts in the proximal half of the whisker than axial to lateral force ratios , provided similar detection sensitivity . Vibration magnitude could also serve as a contact distance cue . Touches with equal push angle generate dramatically reduced steady-state forces with increasing contact distance [16 , 25] . The magnitude of vibration forces are less dependent on contact distance . We illustrate this by calculating the ratio of vibration to steady state shear forces and bending moments for contacts at varying distance from the whisker base . These ratios increase dramatically as the contact point moves from base to tip ( Fig 9 ) . Both the average and maximum vibrational bending moment and shear force are a small fraction the steady-state component for very close contacts ( c/L = 0 . 9; shear 0 . 057 average , 0 . 057 maximum; bending moment 0 . 020 average , 0 . 021 maximum ) . Near the tip , these forces can approach or exceed the steady state component ( c/L = 0 . 1; shear 1 . 36 average , 4 . 57 maximum; bending moment 0 . 409 average , 0 . 996 maximum ) . Since mice have distinct sensing afferents for fast vs . slowly changing touch forces [20 , 21] , comparison of activity between these afferents is a plausible additional mechanism for determining object distance .
Our model of whiskers deformed by time-varying point forces relies on several simplifying assumptions . First , we used the Euler-Bernoulli beam theory for thin beams , which ignores shear terms . Rodent whiskers have a slenderness ratio of >> 100 , a regime where shear terms are irrelevant [29] . We assume a constant path length from follicle to point of force application . The majority of touches have a change in push angle of < 15 degrees , and the peak increase in path length during touch was < 1% for 81% of touches ( Fig 2c ) , justifying our use of the small-angle approximation [30] . For the 3% of touches with peak angle difference of > 50 degrees , a more sophisticated non-linear model may be necessary for accurate calculation of vibration . We treat the whisker in two dimensions . We also ignore friction , since the applied forces are assumed to be normal to the longitudinal axis of the whisker [16] . Frictional forces could tension the whisker , altering vibrational frequencies . Full treatment of vibrations in three dimensions , including torsional movement [31] , intrinsic whisker curvature [32] , and friction would require a numerical approach [33] . We use approximate boundary conditions at the follicle . The follicle holding the whisker has unknown and potentially variable compliance during whisking [34–37] . The angle of the whisker relative to the follicle is thus fixed , whereas bending moment ( directly proportional to the whisker curvature and the magnitude of the applied force ) , and shear force ( the rate of change of the curvature ) vary . Since the parameters relevant to object localization [18] , including bending moment , can be calculated for the fixed end boundary condition , we focused our analysis on this case . Mouse whiskers are not quite linear cones , but are thinner in the middle than a linear fit [14] . This has an appreciable impact on the bending angle , due to the fourth power dependence of stiffness on radius , but the effect on the vibrational modes is estimated to be relatively small . We assumed Young’s modulus to be constant along the whisker . Rat and mouse whiskers have an inner hollow medulla , filled with spongy material . This could cause a difference in effective Young’s Modulus between proximal and distal halves of the whisker [28] . The estimates of the damping coefficient , vibration frequency and steady state displacement all depend on Young’s Modulus . Our reference frame fixes the x-axis along the long axis of the whisker . From this perspective , the deflections produced by a whisker rotated into a pole ( as in active touch ) are equivalent to a pole moving into a whisker held steady ( as in passive deflection ) . Differences in blood sinus pressure and muscle tension between passive and active touch could potentially influence follicle compliance , damping , and how forces applied to the follicle are transduced by mechanoreceptors and perceived by the brain [21 , 38] . Since all touches examined in this project were by produced by head-fixed mice using whisking to locate objects , our results estimating follicle compliance and damping are best suited for modeling vibrations of active touch . Accurate calculation of vibrations from passive touch may require different damping coefficients . There are also several sources of potential experimental measurement error . Due to droop and whisker elevation change , the single top-down projection in our dataset results in an underestimate of the true path length to contact , c/L , in the behavioral measurements ( Fig 2 ) . Dual view imaging shows that this error is <4 percent for touches in the proximal half of the whisker , but increases beyond that point . The fur on the face obscures the whisker insertion to the follicle . We compensated for these factors by assuming the whisker continued into the fur an additional 1–1 . 75mm depending on fur length , justified by our prior high-resolution measurements of mouse whisker shape [14] . Whisker displacement following touch is composed of quasi-steady state and vibration parts . Mice actively control the quasi-steady state trajectory in an irregular manner , so we must estimate this part by smooth fits of the trajectory across time . Our choice of fit influences the residual vibration component , particularly at the edges of the measured period . Damping of whisker vibrations ( Figs 3 and 6 ) could arise from dissipation within the whisker , the follicle , the whisker-object interface , friction and coupling to tissue surrounding the follicle [24 , 30] . We modeled damping during free vibration using a single parameter linearly applied to each vibrational mode . Changes in path length c during strong or distal contacts could cause destructive interference of the range of eigenmodes excited during a single contact and frictional dissipation , reducing vibration . Given these caveats , our model predicts the phase , absolute and relative amplitude of vibration by active whisker touch well ( Fig 6 ) . There is a small mismatch in frequency and damping , which we expect are due to estimating damping during free vibration , simplified whisker geometry , curve fitting of whisker traces to overcome sub-pixel alignment noise , and uncompensated active accelerations of the whisker by the mouse . The accuracy of model is particularly impressive because it is untuned , with zero free parameters . Our model diverges from other recent work [20 , 24] in several ways . We model the whisker in its entirety , including beyond the contact point , allowing placement of the pole at any location along the whisker . This is especially important for studying vibrational cues in close proximity to the whisker base . We consider a Gaussian form of the force time-dependence mimicking the experiment , but any force profile can be treated with our methods . We use a frequency-independent damping constant , which is reasonable since the higher vibrational eigenfrequencies are outside the animal’s perception limits . Critically , we avoid singularity in the whisker acceleration upon impact by using a smooth force onset that keeps the first two time-derivatives of the force continuous . Most importantly , we analytically solve the spatial eigenmodes of conical whiskers , with and without truncation in both motion phases , in contact with pole and in free motion . The analytical solution provides closed-form expressions of the eigenmodes , which is significantly more robust and less computationally expensive than obtaining them numerically . Using the closed-form expressions avoids numerical errors , which becomes increasingly important for higher eigenmodes needed for the expansion of vibrational motion trajectories . Numerical instabilities limited the number of modes considered in prior work [20] . Thus , our approach allows a more complete view of the time-evolution of whisker vibration . The derived analytical solutions can be easily reproduced and used by others within Mathematica or MATLAB package without additional programming . The resultant expressions are transparent , can be easily manipulated , and subjected to various boundary conditions . As a result , the developed analytical approach can be easily generalized and adjusted for more complex experimental conditions , such as multi-point touching , slipping , or sliding . Identifying the location of objects relative to the face is important for social interaction , foraging , navigation , and other behaviors . Rodents actively sweep their whiskers forward and back during these behaviors . In head-centered spherical coordinates , the radial distance , azimuthal angle , and polar angle of objects can determined by distinct active touch strategies . Polar angle could be determined by labelled-line activation of whiskers across different rows [39] , which extend to different elevations above and below the face . Azimuthal angle could be determined by the number of touches in a whisking bout [40] , the timing of touch relative to neuronal phase-locked loops [41] , the roll angle of the whisker at touch [31 , 42] , or an integration of whisking amplitude and midpoint signals with phase amplified touch responses [43] . Radial distance could be determined with low resolution by labelled line activation of whiskers of different lengths [44] . Higher resolution distance discrimination requires other cues , potentially including vibration . Quasi-static analysis has shown that axial forces pushing the whisker into the face could contribute to tactile perception [17 , 18 , 45] . However , axial vibrational displacements and forces are expected to be negligible . Axial frequencies of whiskers are much higher than transverse frequencies . The difference is controlled by the factor r/L where r is the whisker radius and L is its length ( compare Timoshenko Eq . 5 . 4 on page 36 and Eq . 5 . 102 on page 421 ) . This gives a factor 160 for our whiskers , corresponding to vibration frequencies >100 kHz . Mechanoreceptors are not sensitive to frequencies in this band . In addition , the associated displacements are four orders of magnitude smaller compared to transverse vibrations , because the displacement is inversely proportional to the square of eigenmode frequency ( Timoshenko Eq . c on page 73 ) . Thus , radial displacements from vibration are expected to be on the order of one hundred nanometers . While steady state axial forces likely play important roles in tactile sensation , axial vibrations can be neglected as tactile cues . Mice can determine radial distance with a single touch of an individual whisker [18 , 19] . Experimental manipulation of the compliance of the object and stiffness of the whisker supports a decision model where the ratio of quasi-static axial and lateral forces are used for discrimination [18] . Could vibrational cues also contribute to distance discrimination ? At least two potential strategies could be used . The first relies on comparing the temporal patterns of spikes evoked by touch ( Fig 7 ) . The timing precision of evoked spikes is sufficiently high within primary sensory neurons ( median spike jitter 17 . 4 μs , [27] ) to encode vibration frequency and pattern changes from the sum of the first few eigenmodes . High temporal fidelity is a hallmark of intermediate locations between follicle and cortex [46–48] . Vibrational frequency can be used to discriminate contact distance in isolated preparations [5 , 20] . Ideal observers of spike trains can use precise timing in primary afferents to decode stimulus features [22 , 49–51] . Changes in synchrony across multiple afferents could potentially be read out by downstream neurons in S1 or other brain regions to produce a neural representation of vibration frequency and corresponding object distance . Since we do not know the relative sensitivity mice have for pitch shift vs . force ratio changes on whiskers , it remains unclear whether the animal has the capability of using sub millisecond differences in tactile sensory input patterns to influence perception and drive behavior . The second strategy involves comparison of the amplitude of two streams of sensory input , static forces from bending , and dynamic forces from vibration . As mentioned above , these are likely selectively encoded by slowly and rapidly adapting mechanosensory afferents . Due to the increased flexibility of whiskers towards the tip , steady-state forces during contact are two or more orders of magnitude smaller during contacts near the tip than near the base . In contrast , the magnitude of vibrational forces are primarily dependent on whisker velocity at contact , which is less distance dependent . Thus , the relative magnitude of vibration to steady state forces could provide another important cue to distinguish radial distance ( Fig 8 ) . Since the mammalian brain exhibits flexible learning , it seems likely that which cues drive behavior will be a combination of static and dynamic signals that reflect task demands , motivation , and training history . Behavioral experiments could be used to ascertain if and how mice use vibrations to judge radial object distance . Vibration , but not steady state force , depends on whisker properties beyond the point of contact ( Fig 6 ) . Thus , whisker trimming will increase vibration frequency without affecting steady state forces . If frequency serves as a critical cue , our results predict that in mice trained to discriminate radial distances in the proximal half of a single whisker , reported object distance will increase if the whisker tip is trimmed off , quantifiable by a shift in psychometric curves . Determining if and how neural circuits compare vibration and quasi-static forces to influence perception of object distance has recently become a tractable problem . Recent work has measured firing properties of identified classes of mechanosensory afferents from the follicle during whisker motion [22] . Genetic labelling has identified a diversity of convergence of slowly and rapidly adapting afferents onto second-order projection neurons from mouse whisker follicles [52] . Given appropriate upstream connectivity , these could provide an appropriate set of sensory representations to make comparisons between dynamic and static information during active touch . Further dissection of these circuits should be possible with advanced genetic methods . Thus , our results computing whisker vibrations based on real whisker touches during active sensing provides a strong foundation and justification for future investigations into how neural circuits perform computations on tactile sensory input to produce perception .
All procedures were in accordance with protocols approved by the Institutional Animal Care and Use Committees of the University of Southern California ( Protocol 20169 ) and Janelia Research Campus ( Protocol 11–71 ) . Details of the object localization task , behavioral apparatus , high-speed videography , whisker tracking and force calculation have been described elsewhere [18 , 58 , 61 , 62] . Head-fixed mice were trimmed to a single C2 whisker for behavioral experiments . Using this whisker they localized a steel pole ( class ZZ gage pin , Vermont Gage , diameter 0 . 5 mm ) placed in one of five positions on the anterior-posterior axis , licking for a water reward if the pole was in one of the four anterior positions . Radial distance of the pole ranged from 6 . 7–12 . 9mm from the follicle . Backlit ( 940nm IR LED ) whiskers were imaged from above at 1000 or 4000 fps , ( 90–150 μs exposure ) using a Basler 504k or Basler Ace acA2000-340km camera , digitized and tracked using the Janelia Whisker Tracker [62] . Dual-perspective imaging was performed by projecting two orthogonal views onto a single Basler camera via mirrors . Curvature measurements at 5–6mm from the follicle base were used to calculate the steady state bending moment assuming an Euler-Bernoulli quasi-static approximation for whisker bending in a single plane , see Eq ( 3 ) [16] . Contact detection was performed automatically via custom MATLAB scripts using a threshold based on whisker curvature and distance from whisker to pole , followed by manual correction . In some experiments we tracked a piece of dust or another imperfection on the whisker ( Fig 1a , arrow ) . This allowed us to estimate movement of the whisker into the face in response to applied axial force . To measure whisker vibration during 4000fps imaging , we fit traced whisker coordinates from the Janelia Whisker Tracker with a fifth order polynomial . To prevent distortions by mistracking near fur or pole shadow , we excluded the 2 percent of points closest to follicle and pole from the fit . We then computed the displacement along the y-axis at 8 evenly spaced points along the fitted curve for twenty timepoints ( 0 . 25ms step size ) . The time of the first frame with contact was defined as 0 . 125ms from touch start . We extracted vibrational displacement from quasi steady-state displacement by subtracting a 3rd order polynomial fit of displacement along the anteroposterior axis over time , defining vibration to be the residual . Following behavioral sessions , the C2 whiskers were plucked and photographed at 6 . 3x magnification under a light macroscope . Whisker length and width was determined using ImageJ and the NeuronJ plugin . Total length includes the portion of the whisker embedded in the follicle . Whiskers were then weighed on a microgram balance . Time-dependent forces applied by the pole during active whisking were modeled by the top half of a gaussian distribution F ( t ) = Fmax{exp[− ( t − 2td ) 2/ ( 1 . 2011td ) 2] − 0 . 5} for F ( t ) > 0 , where 2td is the touch duration and peak force Fmax occurs at t = 0 . Whisker oscillation and decay during slip-off events were fit by a Levenberg-Marquardt algorithm with 0 . 95 confidence intervals provided by the MATLAB cftool function . The vibrational eigenmodes and eigenfrequencies of trimmed and full-size conical whiskers with fixed-base and free-tip boundary conditions were found in analytical form using the results of [54] . The found eigenfrequencies for the first six modes for full-size whisker are identical to published data [53] . To simulate whisker motion during the contact with pole , the eigenmodes and eigenfrequencies of a truncated and full-size conical whisker with an additional simple support at the pole position were used . The analytical calculations show that these eigenmodes depends strongly on the pole position along the whisker . After the whisker’s detachment from the pole , its motion was considered as a free vibration . All numerical simulations were performed in MATLAB . Time-dependent displacements of both forced and free periods of the whisker motion were calculated using sums of the first ∼100 eigenmodes to ensure full convergence . | Vibrations play an important role in the sense of touch in many species , but exactly how they influence touch perception remains mysterious . An important reason for this mystery is the difficulty in measuring vibrations during touch . Mice are a powerful model system for investigating touch perception because they actively sweep their whiskers into objects and the resulting bending from touch can be video recorded . However , vibrations of the whiskers during touch are usually too small and fast to be seen . To overcome this limitation , we develop a new mathematical approach to calculating whisker vibrations from the speed at impact , maximum whisker bending during touch , and location of contact along a whisker , which is more easily observed . We find that vibration frequency and amplitude is strongly dependent on the location of contact along the whisker , which mice may use to deduce the distance between their face and touched objects . We confirm our calculations with high-speed imaging of whisker vibration during touch . | [
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"organisms"
] | 2018 | Dynamic cues for whisker-based object localization: An analytical solution to vibration during active whisker touch |
Mitogen-activated protein kinase ( MAPK ) pathways are crucial signaling instruments in eukaryotes . Most ascomycetes possess three MAPK modules that are involved in key developmental processes like sexual propagation or pathogenesis . However , the regulation of these modules by adapters or scaffolds is largely unknown . Here , we studied the function of the cell wall integrity ( CWI ) MAPK module in the model fungus Sordaria macrospora . Using a forward genetic approach , we found that sterile mutant pro30 has a mutated mik1 gene that encodes the MAPK kinase kinase ( MAPKKK ) of the proposed CWI pathway . We generated single deletion mutants lacking MAPKKK MIK1 , MAPK kinase ( MAPKK ) MEK1 , or MAPK MAK1 and found them all to be sterile , cell fusion-deficient and highly impaired in vegetative growth and cell wall stress response . By searching for MEK1 interaction partners via tandem affinity purification and mass spectrometry , we identified previously characterized developmental protein PRO40 as a MEK1 interaction partner . Although fungal PRO40 homologs have been implicated in diverse developmental processes , their molecular function is currently unknown . Extensive affinity purification , mass spectrometry , and yeast two-hybrid experiments showed that PRO40 is able to bind MIK1 , MEK1 , and the upstream activator protein kinase C ( PKC1 ) . We further found that the PRO40 N-terminal disordered region and the central region encompassing a WW interaction domain are sufficient to govern interaction with MEK1 . Most importantly , time- and stress-dependent phosphorylation studies showed that PRO40 is required for MAK1 activity . The sum of our results implies that PRO40 is a scaffold protein for the CWI pathway , linking the MAPK module to the upstream activator PKC1 . Our data provide important insights into the mechanistic role of a protein that has been implicated in sexual and asexual development , cell fusion , symbiosis , and pathogenicity in different fungal systems .
Mitogen-activated protein kinase ( MAPK ) cascades are central components of signaling networks in all eukaryotic organisms [1]–[3] . They consist of a three-tiered module containing a MAPK kinase kinase ( MAPKKK ) , a MAPK kinase ( MAPKK ) , and a MAPK , each activating the subsequent one via phosphorylation . MAPK signaling has been extensively studied in the yeast Saccharomyces cerevisiae , in which five MAPKs have been reported ( reviewed in [4] ) . Three MAPK modules have also been identified in most filamentous fungi , including Aspergillus fumigatus , Magnaporthe grisea , Neurospora crassa , and Sordaria macrospora [5] , [6] . Based on homology to S . cerevisiae , they supposedly constitute a cell wall integrity ( CWI ) , pheromone signaling ( PS ) , and osmosensing cascade . Notably , CWI pathway components have been studied in various fungi and are known to be not only responsible for cell wall stress response . For example , in A . fumigatus , the CWI pathway is involved in pyomelanin and gliotoxin formation , response to reactive oxygen species and siderophore biosynthesis [7] , [8] . The CWI pathway of N . crassa is necessary for polar growth , conidiation , fusion of conidial germling protrusions ( CATs; conidial anastomosis tubes ) , and fruiting body formation [9]–[11] . CWI MAPKs from Cochliobolus heterostrophus , Coniothyrium minitans , Fusarium graminearum , and Magnaporthe oryzae have further been shown to be involved in female fertility , heterokaryon formation , mycoparasitism and pathogenicity [12]–[15] . Scaffold and adapter proteins are vital for the spatiotemporally correct assembly and signaling output of MAPK pathways and are involved in decision making , thereby enabling highly specific adaptation of signaling pathways [16]–[19] . However , despite many studies already addressing the role of the CWI pathway in fungal development , little is still known about the coordination of this pathway as well as the regulation of specific responses . Further , in S . cerevisiae , the polarisome component Spa2p is known to act as a scaffold-like protein for the CWI MAPKK and MAPK during polar growth [20] . However , information about scaffold or adapter proteins of the CWI pathway is still lacking for filamentous fungi . In this study , we analyzed the CWI pathway of the model fungus S . macrospora . This filamentous ascomycete has four major advantages over other fungal systems for the study of sexual development ( reviewed in [21] , [22] ) . First , it rapidly forms mature fruiting bodies ( perithecia ) within 7 days . Second , it is self-fertile ( homothallic ) and thus does not need a mating partner . Moreover , the sexual phenotypes are immediately recognizable . Third , it does not form aerial hyphae with vegetative spores ( conidia ) , which overgrow small pre-fruiting structures like the ascogonial coils ( 10–20 µm ) or the spherical protoperithecia ( 20–90 µm ) and thus prevent their observation . Forth , a collection of developmental S . macrospora mutants is available and well characterized showing defects at different stages of sexual development . Recent analyses have specifically focused on ‘pro’ mutants generating only protoperithecia , a stage the wildtype reaches after 3–4 days . Characterizing these ‘pro’ mutants has led to the identification of several developmental proteins [23]–[28] . Using a forward genetic approach , we identified mutant pro30 as a CWI pathway mutant and generated three CWI kinase deletion strains for functional studies regarding sexual development , cell fusion , vegetative growth , and cell wall stress response . Affinity purification of CWI MAPKK MEK1 revealed that this kinase interacts with the developmental protein PRO40 , a protein essential for sexual development and cell fusion [24] . Using further affinity purification-mass spectrometry and yeast two-hybrid analyses , we show that PRO40 binds to MAPKKK MIK1 , MAPKK MEK1 , and the upstream activator protein kinase C ( PKC1 ) . Phosphorylation studies revealed that PRO40 is required for correct signaling via the CWI pathway . Here , we propose a new model in which PRO40 acts as a scaffold protein for the CWI pathway , linking the MAPK module to its upstream activators .
To identify regulators of fruiting body formation , we previously generated a large collection of developmental S . macrospora mutants [22] , [25] . One class of mutants was named with the prefix ‘pro’ , because these mutants develop only protoperithecia . In this study , we analyzed the underlying mutation in mutant pro30 by next-generation sequencing as described recently [25] ( Table S1 , SRX483430 ) . SNP analysis revealed a C to T transition at position 904 of the SMAC_03673 gene in the pro30 mutant genome , resulting in a Q302stop substitution at the protein level ( Figure S1 ) . Progeny from a cross of pro30 to fus were analyzed , and the mutation was found to strictly co-segregate with the sterile phenotype ( Figure S1 ) . SMAC_03673 encodes a 1714 amino acid protein that exhibits 88 . 4% identity to N . crassa CWI MAPKKK MIK1 ( NCU02234 , XP_959647 . 2 ) and 21 . 3% identity to S . cerevisiae CWI MAPKKK Bck1p ( EWG95039 . 1 , Figure S9 ) , as revealed by BLAST searches [29] . SMAC_03673 was therefore renamed mik1 . To confirm that the C to T transition in mik1 is responsible for the mutant phenotype , we transformed pro30 with a full-length copy of mik1 . As can be clearly seen from Figure 1 , pro30 transformants regained the ability to form perithecia . Thus , a functional MIK1 MAPKKK is required for sexual development in S . macrospora . The finding that the MIK1 MAPKKK is required for sexual development in pro30 prompted us to analyze the role of CWI pathway kinases in sexual development in more detail . BLAST searches [29] against the N . crassa genome sequence ( http://www . broadinstitute . org/annotation/genome/neurospora/MultiHome . html ) [30] and the S . cerevisiae genome sequence ( http://www . yeastgenome . org/ ) [31] revealed that MAPKK SMAC_02183 ( CCC11961 . 1 ) and MAPK SMAC_05504 ( CCC12327 . 1 ) are homologous to N . crassa MEK-1/S . cerevisiae Mkk1p and Mkk2p ( Figure S10 ) and N . crassa MAK-1/S . cerevisiae Mpk1p ( Figure S11 ) , respectively . We subsequently renamed SMAC_02183 and SMAC_05504 mek1 and mak1 , respectively . Deletion strains for mik1 , mek1 , and mak1 were generated by homologous recombination as described previously using S . macrospora Δku70 as host [32] . For generating deletion strains devoid of the Δku70 background , PCR-verified primary transformants were crossed to spore color mutant fus or to sterile mutant pro40 [24] , [25] . Subsequent single spore isolation led to Δmik1 , Δmek1 and Δmak1 single deletions as verified by PCR and Southern blot analysis ( Figure S2 , Figure S3 , and Figure S4 ) . We compared sexual development of the three different kinase deletion strains to wildtype . Figure 2A shows sexual structures generated after 7 days of growth on BMM . Like pro30 , the kinase deletion mutants did not develop further after protoperithecium formation . Note that mature perithecia were never observed , even after prolonged incubation ( Figure 2A ) . However , sexual development in the deletion strains was re-established by introducing wildtype copies of the deleted genes . Recently , the sexual structures of N . crassa Δmik1 , Δmek1 , and Δmak1 mutants were described as difficult to detect due to early-onset autolysis [9] . Although we observed autolysis in S . macrospora Δmik1 , Δmek1 , and Δmak1 , protoperithecia were found frequently in Δmik1 and Δmek1 ( >200 protoperithecia per microscope slide ) . It should be noted , however , that we rarely found protoperithecia in Δmak1 ( 2 protoperithecia on average per microscope slide; data not shown ) . A general observation made by ourselves and others is that a defect in sexual development is often linked to a defect in hyphal fusion [23] , [33]–[36] . We therefore examined pro30 , Δmik1 , Δmek1 , and Δmak1 for the occurrence of fusion events between vegetative hyphae . Fusion bridges were frequently observed in the wildtype by light microscopy ( Figure 2B ) . However , we were unable to detect fusion bridges in the three kinase deletion mutants as well as in pro30 , although hyphae frequently made contact ( Figure 2B ) . To evaluate the role of MIK1 , MEK1 , and MAK1 in cell wall stress response , we performed growth tests on medium containing Calcofluor White ( CFW ) . CFW is a common agent used to test fungal mutants for cell wall stress-related defects [37] . We assessed growth during 7 consecutive days in race tubes on synthetic SWG medium ± CFW . Vegetative growth of Δmik1 , Δmek1 , and Δmak1 was severely impaired even without CFW and was reduced by 70–80% in comparison to wildtype . Figure 3A shows mean values of average growth rates from three independent experiments . Growth of the wildtype on SWG + CFW ( gray bar ) was reduced by 19% compared to growth on SWG . A much more drastic effect of CFW on vegetative growth was observed in the kinase deletion strains . Growth in these strains was reduced by 62–91% in the presence of CFW ( Figure 3A , gray bars ) , compared to growth on SWG ( Figure 3A , black bars ) . Integration of wildtype copies of mik1 , mek1 , and mak1 into the respective deletion strains partially complemented the growth defect . This result may be explained by mis-expression of the kinase genes from the constitutive A . nidulans gpd promoter ( mik1 and mek1 ) and the inducible S . macrospora Smxyl promoter ( mak1 ) [38] , [39] . Signal transduction via a MAPK module requires several subsequent phosphorylation events , eventually leading to phosphorylation of the MAPK . Western blot analysis with deletion mutants and complemented strains showed that MIK1 and MEK1 are required for MAK1 phosphorylation , confirming the composition of the three-tiered MAPK module ( Figure 3B ) . We further analyzed the localization of MIK1 , MEK1 , and MAK1 by generating GFP fusions . Functionality of the fusion proteins was confirmed by complementation of the corresponding deletion strains . Fluorescence microscopy showed that MIK1 and MEK1 reside in the cytoplasm and are clearly absent from spherical organelles ( Figure 4A ) . Co-localization experiments using strains with MEK1-GFP and tdTomato-tagged histone H2B identified these organelles to be nuclei ( Figure 4B ) . MAK1-GFP localized to the cytoplasm and the nucleus . This localization pattern is consistent with previously published data , e . g . from the fission yeast Schizosaccharomyces pombe , where MAPKKK Mkh1 and MAPKK Pek1 localize to the cytoplasm , whereas MAPK Pmk1 shuttles between the cytoplasm and the nucleus [40] . As mentioned above , little is known about the regulation of the fungal CWI pathway through scaffolds or adapters . We surmised that these regulators might be identified by searching for interaction partners of the kinases . In a recent transcriptomics analysis , we found the mek1 transcript among the most abundant transcripts in protoperithecia [41] , and therefore were prompted to search for MEK1 interaction partners . MEK1 was fused to an N-terminal tandem affinity purification ( TAP ) tag consisting of protein A , a TEV protease cleavage site and the calmodulin-binding peptide [42] , [43] . TAP in combination with mass spectrometry using multi-dimensional protein identification technology ( MudPIT ) [44] , [45] facilitates the detection of low-abundant proteins . This approach has been applied successfully to the identification of S . macrospora proteins from complex mixtures , and yields a huge number of peptides even after tandem purification [43] . Functionality of NTAP-MEK1 was shown by complementation analysis ( Figure 2A ) , and single spore isolate E292 that expressed high levels of the fusion protein ( Figure S5 ) was chosen for TAP-MudPIT . Proteins that were identified with at least two different peptides in at least two out of four replicate experiments are listed in Table S2 . Notably , the most abundant protein detected by MudPIT was MEK1 itself . We further detected other members of the CWI pathway , namely MIK1 and upstream components protein kinase C ( PKC1 , SMAC_04666; CCC11683 . 1 ) and small GTPase RHO1 ( SMAC_06239; CCC07244 . 1 ) . Strikingly , one of the most abundant proteins detected in the MEK1 TAP-MudPIT analysis was PRO40 ( CCC06426 . 1; Table S2 ) . This protein has previously been shown to be involved in sexual development and hyphal fusion [24] . Fungal PRO40 homologs have been connected to sexual and asexual development , cell fusion , symbiosis , and pathogenicity , but their exact molecular function is still currently unknown [35] , [46]–[48] . To verify the MEK1-PRO40 interaction , we performed affinity purification of FLAG-tagged PRO40 ( FLAG-AP ) followed by MudPIT . The PRO40-FLAG fusion construct has already been shown to complement pro40 [24] . For FLAG-AP , we used strain T184 . 2NS11 ( Δpro40::pro40-3xFLAG ) yielding detectable amounts of PRO40-FLAG in the eluate ( Figure S5 ) . FLAG-AP in combination with MudPIT was performed three times with T184 . 2NS11 and twice with wildtype ( control ) . A full list of proteins detected with at least two different peptides in at least two out of three ( PRO40-FLAG ) or two out of two ( wildtype ) replicate experiments is given in Tables S3 and S4 , respectively . Due to the single FLAG purification step , the number of identified proteins in the PRO40-FLAG dataset was even larger ( 444 proteins ) than the number of proteins identified in the TAP-MEK1 dataset ( 308 proteins ) . However , five proteins were identified consistently in all three experiments with PRO40-FLAG , but not with wildtype control experiments . Of these five proteins , three have been assigned functions in cell differentiation . PKC1 is an upstream activator of the CWI module , COP9-2 ( SMAC_01284; CCC07717 . 1 ) is a subunit of the COP9 signalosome , which has been described to regulate sexual development in A . nidulans , and PRO4/LEU1 ( SMAC_07082; CCC13458 . 1 ) is an enzyme that is involved in the leucine biosynthesis pathway , which is essential for fruiting body formation in S . macrospora [49]–[51] . Since we detected PRO40 in one of the wildtype control experiments ( Table S4 ) , we calculated ratios between the spectral counts in PRO40-FLAG and control experiments to evaluate the specificity of such proteins detected in both experiment types ( see Materials and Methods , Table S5 ) . This approach reduced the number of high-confidence hits for PRO40 interaction partners to 123 proteins , including MEK1 and RHO1 . In addition to TAP-MudPIT with NTAP-MEK1 in a Δmek1 background , we also performed TAP-MudPIT in a Δpro40 background ( strain E2544; Δpro40::NTAP-MEK1; Figure S5 ) . Proteins that were identified with at least two different peptides in at least two out of three replicate experiments were considered as high-confidence interactors ( Table S2 ) . Among these , we identified MIK1 and RHO1 , but not PKC1 . Interestingly , MEK1 seems to interact with the Woronin body protein HEX1 ( SMAC_01601; CCC08037 . 1 ) independent of whether or not PRO40 is present , since HEX1 was detected in both the Δmek1::NTAP-MEK1 and the Δpro40::NTAP-MEK1 datasets ( Table S2 ) . From our results , we subtracted known background ( a list of proteins considered background derived from numerous unrelated affinity purification-MS experiments is provided in Table S6 ) , and by comparing the three datasets ( Δpro40::PRO40-FLAG , Δmek1::NTAP-MEK1 , and Δpro40::NTAP-MEK1 ) found overlaps between the PRO40 and MEK1 interaction networks ( Figure 5 , Table 1 ) . Specifically , we found 12 proteins in all three datasets . From the CWI pathway , this group contains MEK1 and RHO1 . Another 17 proteins appeared in the Δpro40::PRO40-FLAG and Δmek1::NTAP-MEK1 datasets , but not in the Δpro40::NTAP-MEK1 dataset ( Figure 5 , Table 1 ) , indicating that interaction of MEK1 with these 17 proteins depends on the presence of PRO40 . Among these 17 proteins was PKC1 , ATP citrate lyase ACL1 ( SMAC_06775; CCC07573 . 1 ) , previously found to be involved in S . macrospora sexual development [52] , and a putative regulatory subunit of protein phosphatase PP2A , RTS1 ( SMAC_02633; CCC10054 . 1 ) . This regulatory subunit is of high interest because of a recently described fungal striatin-interacting phosphatase and kinase ( STRIPAK ) complex , containing protein phosphatase 2A ( PP2A ) and several ‘PRO’ proteins [43] . As mentioned above , we recently performed a transcriptomics analysis of protoperithecia by laser microdissection and RNA-seq [41] . When we superimposed data from this study on the Venn diagram in Figure 5 , we found that the group of interaction partners shared by PRO40 and MEK1 contains proteins whose transcripts belong to the top500 genes ( with respect to read counts ) in either vegetative growth conditions ( blue ) or protoperithecia ( magenta ) . For example , besides the mek1 transcript , the rho1 and acl1 transcripts are in the top500 list in protoperithecia ( Figure 5; [41] ) . These data highlight the significance of the MEK1-PRO40 interaction network for fungal sexual development . We further searched for PRO40 interaction partners by performing yeast two-hybrid assays with full-length PRO40 as bait . For prey , we generated two S . macrospora Matchmaker libraries using cDNA derived from different cultures to include cDNA from vegetatively and sexually propagating mycelia . Screening of 107 yeast cells yielded 1600 clones with ade and his reporter gene activity , and 96 clones additionally showing lacZ reporter gene activity in two subsequent assays were subjected to DNA isolation and sequence analysis , which led to the identification of 13 different genes ( Table S7 ) . 11 of the 96 clones carried mek1 sequences . To assess the strength of the PRO40-MEK1 interaction , we performed quantitative β-galactosidase assays with a strain carrying BD-PRO40 and AD-MEK1_v01 . Note that MEK1-v01 corresponds to an N-terminally truncated MEK1 , which is due to an annotation error in the S . macrospora genome version 01 vs . version 02 [5] , [41] . Mean values of β-galactosidase activity of three independent experiments were 86 . 7±16 . 9 U/mg protein compared to 5 . 0±2 . 4 U/mg protein for the control experiment ( BD-PRO40 and AD ) , indicating a strong interaction between PRO40 and MEK1 . To gain further insight into the protein interactions within the deduced multi-subunit complex , we tested reciprocal interaction between the six proteins , PRO40 , RHO1 , PKC1 , MIK1 , MEK1 , and MAK1 , in a yeast two-hybrid assay . We used constitutively active ( RHO1_CA ) and inactive ( RHO1_CI ) versions of RHO1 to determine interactions dependent on RHO1 activity . Protein structures of all tested proteins are given in Figure 6A . Mating of yeast strains carrying GAL4-AD and -BD translational fusions with the abovementioned proteins resulted in diploid cells that were tested for reporter gene activity . As can be seen from growth of yeast colonies on SD medium lacking adenine and histidine , PRO40 interacted with PKC1 , MIK1 , and MEK1 , but not RHO1 and MAK1 ( Figure 6B; A growth control of yeast colonies is shown in Figure S6 ) . MEK1 showed interaction with PRO40 and MIK1 , as seen in the TAP-MudPIT analysis , and with MAK1 only in the yeast two-hybrid analysis . However , we did not detect interactions between MEK1 and RHO1 or MEK1 and PKC1 . Formation of homodimers was observed for PRO40 , PKC1 , MIK1 , and MAK1 . Figure 6C displays a schematic overview of signal transduction and protein-protein interactions in the PRO40-CWI complex . To map PRO40 domains mediating interaction , we generated yeast two-hybrid vectors containing cDNA fragments of pro40 ( Figure 6A ) . PRO40 contains a WW domain , which is implicated in mediating protein-protein interactions [53] , and several regions enriched for certain amino acids such as asparagine and glycine . Further , the PRO40 N-terminal half , enriched for glutamine and proline , is predicted to be highly disordered by IUPred [54] , [55] , as was also described for the N . crassa PRO40 homolog SOFT [56] . For yeast two-hybrid analysis , we generated five overlapping fragments PRO40a-e , containing different domains . As can be seen from Figure 6B , the N-terminal proline-rich and disordered PRO40 derivative , PRO40a , interacted with PRO40 itself as well as MEK1 . PRO40c interacted with all full-length PRO40 interaction partners , namely PRO40 , PKC1 , MIK1 , and MEK1 . Since fragment PRO40c contains the WW domain , we hypothesized that binding of PRO40 to these interaction partners might be mediated by this domain . To test this hypothesis , we generated a modified PRO40 , PRO40AAA ( W575A , W598A , P601A ) , inserting mutations described to render the WW domain non-functional [57] . Surprisingly , PRO40AAA showed the same interactions as full-length PRO40 in a yeast two-hybrid assay ( Figure 6B ) . PRO40AAA was further able to interact with itself . We next generated MEK1 derivatives for yeast two-hybrid analysis ( Figure 6A ) . As shown in Figure 6B , MEK1d comprising the kinase domain was sufficient for interaction with PRO40 , MIK1 , and MAK1 . Moreover , interaction between MEK1 and MAK1 was accomplished via MEK1a and MEK1c , both comprising the proline-rich region . For interaction of MEK1 and PRO40 , the MEK1 kinase domain ( MEK1d ) and either proline-rich PRO40a or central PRO40c were sufficient ( Figure 6B ) . Figure 6D summarizes the results from interaction studies with PRO40 and MEK1 derivatives . Taken together , our data indicate that PRO40 connects the CWI MAPK module to its upstream activator PKC1 . To gain insight into the biological function of the MEK1-PRO40 interaction , we generated a Δmek1/pro40 double mutant . Single spore isolates from crosses of the single mutants were subjected to sequencing of the pro40 ORF and Southern blot analysis ( Figure S7 ) . The Δmek1/pro40 double mutant was analyzed with regard to sexual development and hyphal fusion and showed the same developmental phenotype as the Δmek1 and Δpro40 single deletion strains ( Figure 7A , B , compare Figure 2A , B ) . To test whether Δpro40 shares the stress response phenotype of the CWI kinase deletion strains , we performed growth tests on SWG ± CFW . As can be seen from Figure 3A , Δpro40 was less impaired in vegetative growth than the kinase deletion strains , and the growth reduction in the presence of CFW was also less distinctive . The Δmek1/pro40 double mutant was much more impaired than Δpro40 and showed the same growth defect as the Δmek1 single deletion strain . From these observations , we conclude that PRO40 does not play a major role in the cell wall stress response . Since PRO40 interacts with three members of the CWI kinase pathway , we investigated whether the localization of MIK1 , MEK1 , and MAK1 was altered in the pro40 mutant or the Δpro40 deletion strain . Localization of the kinases in vegetative hyphae was identical in mutants and wildtype , with MIK1 and MEK1 residing in the cytoplasm and MAK1 localizing to the cytoplasm and the nucleus ( Figure 7C , compare Figure 4A ) . Since PRO40 and the kinases are required for sexual development , we also investigated the localization of MIK1 , MEK1 , and MAK1 in protoperithecia of pro40 , Δpro40 , and wildtype . As illustrated in Figure 7D , GFP-MIK1 and MEK1-GFP showed a uniform distribution in protoperithecia of all investigated strains , most likely due to cytoplasmic localization . Similarly , the MAK1-GFP signal was found in the cytoplasm , and additionally in patches that resemble nuclei . In summary , the kinases showed the same localization in the presence and the absence of PRO40 , in vegetative as well as in sexual tissues . To clarify the putative scaffolding role of PRO40 for the CWI pathway in more detail , we compared MAK1 phosphorylation levels in wildtype to MAK1 phosphorylation levels in Δpro40 and the pro40 overexpression strain T182 . 4NS11 ( Figure 8 ) . First , we examined MAK1 phosphorylation during a developmental time course . As can be seen from Figure 8A , MAK1 activity is strongly reduced in Δpro40 in comparison to wildtype at all investigated time points . In contrast , MAK1 is hyper-phosphorylated in the pro40 overexpression strain T184 . 2NS11 . Second , we assayed MAK1 phosphorylation under stress conditions ( Figure 8B ) . In the wildtype , MAK1 phosphorylation was strongly induced by H2O2 . Again , MAK1 activity was strongly reduced in Δpro40; however , a response to 15 minutes H2O2 stress was still evident in the mutant . The pro40 overexpression strain displayed MAK1 activity similar to wildtype . Thus , we concluded that PRO40 acts as a scaffold protein for CWI pathway components during sexual development , hyphal fusion , and stress response ( Figure 8C ) .
In this study , we investigated the S . macrospora CWI kinase pathway and showed that the three kinases MIK1 , MEK1 , and MAK1 are required for the transition from protoperithecia to perithecia . Although the three deletion strains reach the same level of protoperithecia development , we observed that Δmak1 displayed significantly fewer protoperithecia than Δmik1 and Δmek1 . This observation indicates that MAK1 obtains input not only from the upstream CWI kinases , but also from other pathways . Crosstalk between the CWI pathway and other stress response pathways has been observed in a number of fungi ( reviewed by [58] ) . For example , the N . crassa PS and CWI pathways have both been described to control the cell wall stress response , hyphal fusion , and sexual development [10] . Here , we performed a large-scale analysis of MEK1 interactions in two different background strains . Our data establish a basis to functionally analyze further interaction partners of MEK1 for a regulatory role in CWI signaling . In this study , we revealed the developmental protein PRO40 as a scaffold protein for the CWI pathway . S . macrospora PRO40 was previously identified by complementation of sterile mutant pro40 , harboring a transition in the pro40 gene that leads to an early translational stop [24] . Like its homolog SOFT from N . crassa , PRO40 is important for cell fusion [34] , [35] . PRO40/SOFT homologs have further been shown to be important for cell fusion in Alternaria brassicicola , Epichloë festucae , F . graminearum , and F . oxysporum [46]–[48] , [59] . In addition , PRO40/SOFT has been connected to pathogenicity in A . brassicicola , F . graminearum , and F . oxysporum and to symbiosis in E . festucae [46]–[48] , [59] . Recently , N . crassa SOFT was shown to display an oscillatory localization at the tips of CATs approaching cell fusion , which alternates with the PS pathway MAPK MAK2 [60] . It was also proposed that SOFT and MAK2 act in two different signaling pathways with one sending and one receiving a yet unknown signal eventually leading to fusion of two CATs . Our data reveal that PRO40 of S . macrospora is a scaffold protein for another signaling pathway , namely the CWI pathway . Thus , a conceivable mechanism of PRO40 during CAT fusion is the regulation of the CWI kinases . All CWI kinase mutants of N . crassa have been described to be CAT fusion deficient [10] , [61] , and it should be highly elucidating to analyze the localization of the kinases during CAT fusion . PRO40/SOFT homologs have been found in stress granules ( A . oryzae ) , at septal pores in response to various stresses or hyphal injury ( A . oryzae , N . crassa , S . macrospora ) , as well as associated with Woronin bodies ( S . macrospora ) [24] , [62]–[64] . Woronin bodies are peroxisome-derived organelles found only in filamentous ascomycetes and contain a crystalline core assembled from the HEX1 protein [65] . An association of S . macrospora PRO40 with Woronin bodies was already found by co-localizing PRO40 with GFP-tagged HEX1 [24] . HEX1 was not identified as a significant PRO40 interaction partner in our experimental setup ( Table S5 ) ; however , MEK1 was found to interact with HEX1 and Leashin , the Woronin body tether [66] . A connection of Woronin body function to the CWI pathway has already been observed in A . oryzae . There , PKC1 is required for HEX1 phosphorylation and subsequent HEX1 self-assembly [67] . The main function of Woronin bodies is the plugging of septal pores after hyphal injury , but they also play a role in plant infection and survival of nitrogen depletion in M . grisea [65] , [68] . The Woronin body protein HEX1 is involved in asexual reproduction and virulence in F . graminearum , and hex1 has been found to be regulated by PS MAPK MAK2 and downstream transcription factor PP-1 , homologous to yeast Ste12p , in N . crassa [69] , [70] . These findings are in agreement with a possible developmental role of Woronin bodies and the HEX1 protein . By yeast two-hybrid analysis , we found two regions of PRO40 to be important for the observed interactions with CWI pathway components , namely the N-terminal proline-rich part and the central region encompassing the WW domain . Most interestingly , the N-terminal region of PRO40 , including the proline-rich part , is also highly disordered . Protein disorder has been recognized as an important feature in signaling , since conformational fluctuations in disordered regions allow highly specific binding to multiple interaction partners in a regulated manner , thereby increasing functional capability [71] . Further analysis is needed to ascribe such versatile functions to PRO40 disordered regions . Another protein-protein interaction domain , the WW domain , has been found in PRO40 . However , our yeast two-hybrid studies show that it is dispensable for interaction with PRO40 , PKC1 , MIK1 , and MEK1 . This indicates that PRO40 contains further unrecognized protein-protein interaction motifs within the region encompassing the WW domain . Scaffold proteins are defined as proteins that not only bind to different signaling proteins , but that also attune signaling outputs [17] , [72] . Although PRO40 does not affect the localization of MIK1 , MEK1 , and MAK1 , it affects MAK1 phosphorylation , both during development and during stress response . Thus , PRO40 is a scaffold protein of the CWI pathway . We further attempted to address the question how PRO40 affects signaling via the CWI pathway by complementation analysis with constitutively active MAK1 and MEK1 , inserting previously described mutations [73] , [74] . However , these MAK1 and MEK1 versions were unable to reinstate wildtype morphology in the corresponding deletion mutants and thus were inept for further studies ( our unpublished results ) . Since pro40 mutants did not display the same general growth defect as the CWI kinase mutants and were not as impaired as these mutants on media containing CFW , we conclude that PRO40 does not act as a scaffold of the CWI pathway during all CWI pathway functions . Recently , the presence of different CWI pathways has been suggested for N . crassa . There , different membrane sensors , WSC-1 and HAM-7 , activate signaling via the CWI module , leading to cell wall stress response and hyphal fusion , respectively [75] . Our data strongly suggest that PRO40 acts as a scaffold protein for the CWI pathway during fungal development , hyphal fusion , and stress response . In conclusion , we have identified PRO40 as a new scaffold protein of the highly conserved CWI pathway , linking the MAPK module to upstream activator PKC1 . Collectively , our findings provide important insights into the mechanistic role of a fungal protein that has been implicated in sexual and asexual development , cell fusion , symbiosis , and pathogenicity in diverse fungal systems .
Cloning and propagation of recombinant plasmids was performed using standard laboratory conditions [76] and Escherichia coli strain XL1 Blue MRF' [77] as host for plasmid amplification . Alternatively to restriction-ligation-mediated cloning , recombinant plasmids were generated by homologous recombination in S . cerevisiae strains PJ69-4a , AH109 or Y187 [78] , [79; Clontech , Palo Alto , CA , USA] as described previously [43] , [80] . Recombinant yeasts were selected by prototrophy to leucine , tryptophan or uracil . Yeast experiments were carried out according to standard protocols ( Clontech Yeast Protocol Handbook , PT3024-1 ) , and plasmid isolation was performed as described by Bloemendal et al . [43] . The wildtype strain ( S91327 ) of S . macrospora was obtained from our laboratory collection . Details for all S . macrospora strains used in this study are given in Table S8 . Unless stated otherwise , standard growth conditions and DNA-mediated transformation were performed as described previously [81] , [82] . Transformants were selected on medium containing either nourseothricin ( 50 µg/ml ) or hygromycin B ( 80 U/ml ) . Sensitivity to Calcofluor White ( CFW; Sigma Aldrich , St . Louis , MO , USA ) was measured in 30 cm race tubes containing 15 ml solid SWG medium ( derived from synthetic crossing medium according to Nowrousian et al . [83] ) ±250 µg/ml CFW . For each strain , two race tubes were measured in each experiment and the growth front was marked every 24 hrs for 7 consecutive days . Preparation of DNA and Southern hybridization were performed as described [81] . S . macrospora cDNA libraries SmI and SmII were generated using the Matchmaker Library Construction & Screening Kit ( Clontech , Palo Alto , CA , USA ) . RNA was extracted from S . macrospora wildtype according to Pöggeler et al . [84] from 3 and 6 days old floating cultures ( inducing sexual development ) and 3 days old shaking cultures ( repressing sexual development ) , and mRNA was isolated with the polyATtract mRNA isolation kit ( Promega , Madison , WI , USA ) . For SmI , a mixture of 15 mRNA extractions and for SmII , a mixture of 7 mRNA extractions was used to generate cDNA according to the Matchmaker Library Construction & Screening Kit manual ( PT3955-1 , Clontech , Palo Alto , CA , USA ) . Each cDNA mixture was co-transformed with pGADT7-Rec into yeast strain AH109 and plated on SD medium lacking leucine . Colonies were harvested after 6 days of growth . Library titers were 4 . 3×107/ml and 1 . 5×107/ml for SmI and SmII , respectively . All plasmids and oligonucleotides used in this study are listed in Tables S9 and S10 , respectively . For yeast two-hybrid analyses , PCR was performed on S . macrospora cDNA and PCR fragments cloned into pGBKT7 and pGADT7 as follows: For RHO1 , constitutively active ( RHO1_CA ) and constitutively inactive ( RHO1_CI ) versions were generated by inserting mutations G15V/C191S and E41I/C191S , respectively [85] . Specifically , a RHO1_CA fragment was generated from S . macrospora cDNA using primers rho1_CA-for/rho1_CA-rev and ligated EcoRI/BamHI into pGADT7 and pGBKT7 to generate pA-RHO1_CA and pB-RHO1_CA , respectively . For pA-RHO1_CI , two PCR fragments generated with primer pairs rho1_CI-for x rho1_CIint-rev and rho1_CI-rev x rho1_CIint-for , were co-transformed into yeast with SmaI-digested pGADT7 . pB-RHO1_CI was generated by ligating a 0 . 6 kb EcoRI/BamHI fragment from pA-RHO1_CI into EcoRI/BamHI-digested pGBKT7 . To generate pA-PKC1 , yeast recombination was performed with SmaI-digested pGADT7 and three cDNA fragments amplified by PCR using primer pairs 4666-01-AD/4666-02 , 4666-03/4666-04 , and 4666-05/4666-06-AD . For pB-PKC1 , a similar strategy was employed with SmaI-digested pGBKT7 and three PCR fragments produced with primer pairs 4666-01-BD/4666-02 , 4666-03/4666-04 , and 4666-05/4666-06-BD . To generate pA-MIK1 , yeast recombination was performed with EcoRI/BamHI-digested pGADT7 and five PCR fragments produced with primer pairs 3673-1-AD/3673-2 , 3673-3/3673-4 , 3673-5/3673-6 , 3673-7/3673-8 , and 3673-9/3673-10-AD . For cloning of pB-MIK1 , yeast recombination was again employed with SmaI-digested pGBKT7 , two PCR fragments produced with primer pairs 3673-1-BD/3673-2 and 3673-9/3673-10-BD , and a 5254 bp NdeI/BamHI fragment from pA-MIK1 . For mek1 vectors , a 1458 bp mek1 cDNA fragment was amplified with primers 6419-9/6419-10 and ligated EcoRI/BamHI into pGBKT7 and pGADT7 to generate pB-MEK1_v01 and pA-MEK1_v01 , respectively . For full-length cDNA vector pA-MEK1 , pA-MEK1_v01 was digested with EcoRI and transformed into yeast together with a 425 bp BglII/BamHI fragment of pA-MEK1a ( see below ) . Likewise , pB-MEK1 was generated by yeast recombination using EcoRI-linearized pB-MEK1_v01and a 653 bp XhoI/BamHI fragment of pB-MEK1a . For mak1 vectors , a PCR-fragment produced with primers HR-mak1-for/HR-mak1-rev as well as BamHI-digested pGADT7 were transformed into yeast , generating pA-MAK1 . pB-MAK1 was generated by ligation of a 1426 bp EcoRI/PstI fragment from pA-MAK1 into EcoRI/PstI-digested pGBKT7 . For pB-PRO40 , full-length cDNA was amplified using primers Y2H-05/Y2H-06neu and ligated EcoRI/PstI in pGBKT7 . pA-PRO40 was generated by yeast recombination of two PCR fragments produced with primer pairs AD-40-for1/AD-40-rev1 and AD-40-for2/AD-40-rev2 , and a 3961 bp EcoRI/PstI fragment from pB-PRO40 into pGADT7/BamHI . To generate pA-MEK1a and pB-MEK1a , PCR was performed on S . macrospora cDNA using primer pair mek1_F1-fw/mek1_F1-rv , the PCR fragment subcloned into pDrive , cut EcoRI/BamHI and ligated into EcoRI/BamHI digested pGADT7 and pGBKT7 , respectively . pA-MEK1b/pB-MEK1b , pA-MEK1c/pB-MEK1c and pA-MEK1d/pB-MEK1d were generated accordingly , using primer pairs mek1_F2-fw/mek1_F2-rv , mek1_F1-fw/mek1_F2-rv and mek1_F4-fw/6419-10 , respectively . To generate yeast two-hybrid vectors encoding PRO40 derivatives , five pro40 fragments were amplified from cDNA and subsequently ligated into EcoRI and BamHI sites of pGADT7 and pGBKT7 . Primers used were Y2H-13/Y2H-07 for PRO40a , Y2H-08/Y2H-09 for PRO40b , Y2H-01/Y2H-12 for PRO40c , Y2H-10/Y2H-11 for PRO40d , and Y2H-03/Y2H-04 for PRO40e . pA-PRO40e was generated by ligating a 1007 bp EcoRI fragment from pB-PRO40e into the pGADT7 EcoRI site . Vector pB-PRO40AAA encoding PRO40 with a mutated WW domain ( PRO40 W575A , W598A , P601A ) was generated by yeast recombination of a PCR fragment ( primers 40-6/40-7 ) into ScaI-digested pB-PRO40 . To generate pA-PRO40AAA , a 3961 bp EcoRI/PstI-fragment from pB-PRO40AAA and a 10322 bp SalI fragment from pA-40 were recombined in yeast . The S . macrospora pro40 cDNA was used as bait to screen both S . macrospora cDNA libraries for interacting proteins using the Matchmaker System ( Clontech , Palo Alto , CA , USA ) . Yeast Y187 cells were transformed with pB-PRO40 , mated with 1 ml cDNA library and plated on selective media ( SD-trp-leu-ade and SD-trp-leu-his-ade ) . Colonies were re-inoculated on selective media lacking histidine or adenine and histidine . Growing yeast cells were subjected to two subsequent lacZ filter tests ( Clontech Yeast Protocol Handbook , PT3024-1 ) . 96 randomly chosen colonies showing reporter gene activity were chosen for PCR amplification of cDNA inserts using primer pair pAD-2/pAD-FPneu and PCR products were directly sequenced with primer pADfor96er . Quantitative measurements of β-galactosidase activity were carried out as described previously [86] . To test interactions between full-length proteins as well as derivatives of MEK1 and PRO40 , strains carrying single plasmids were generated by electroporation [87] using matα strains ( Y187 , PJ69-4α ) and mata strains ( AH109 , PJ69-4a ) as recipients for BD and AD fusion constructs , respectively . Diploid strains were generated and tested for reporter gene expression as previously described [88] . For drop plating , yeast colonies were resuspended in 200 µl SD medium and 5 µl were spotted on SD supplemented with histidine and adenine as well as SD lacking histidine and adenine . Due to transactivation , pB-MEK1 was exchanged for pB-MEK1_v01 , and pB-MEK1b , pB-MEKc and pA-RHO1_CA were omitted from the analysis . Deletion vectors for mik1 and mak1 were generated by yeast recombination as described [43] . For pKO-MIK1 , 5′ ( 1000 bp ) and 3′ ( 1000 bp ) flanking regions of mik1 were PCR-amplified using S . macrospora genomic DNA and primer pairs 3673-5fw/3673-5rv and 3673-3fw/3673-3rv , respectively . Flanking regions were transformed into yeast together with an hph cassette cut EcoRI from plasmid pDrivehph [89] , and EcoRI/XhoI-linearized vector pRS426 [90] . Plasmid pKO-MAK1 was generated accordingly , using mak1 5′ ( 1000 bp ) and 3′ ( 1039 bp ) flanking regions amplified with primer pairs 5504-5fw/5504-5rv and 5504-3fwIT/5504-3rvIT , respectively . To generate a mek1 deletion , 5′ ( 832 bp ) and 3′ ( 913 bp ) flanking regions of mek1 were PCR-amplified using primer pairs KO-mek-1/KO-mek-2 and KO-mek-3/KO-mek-4 , respectively , and subcloned into pDrive . Due to annotation changes concerning mek1 in genome version 02 of S . macrospora [25] , a 5′-truncated version ( mek1_v01 , nt280–1858 , encoding amino acids 35–519 ) was used as basis for generating mek1 deletion and TAP vectors . The 5′ and 3′ regions were cut SnaBI/BamHI and XbaI/ApaI and successively ligated into the corresponding sites of vector pDrive-Hyg ( I . Godehardt and U . Kück , unpublished data ) . Linearized pKO-MIK1 , pKO-MEK1 and pKO-MAK1 were transformed into S . macrospora Δku70 [32] and transformants were selected for by hygromycin resistance . Single-spore isolates in which mik1 , mek1 or mak1 had been replaced by the hph cassette and which had the wildtype genetic background were obtained as described previously through crosses against spore color mutant fus or mutant pro40 [24] , [25] , [32] . For pNTAP-mik1 , yeast recombination was employed . Fragments used for transformation were BamHI-digested pDS21 [91] and five PCR products generated with S . macrospora genomic DNA and primer pairs NTAP-mik-fw/3673-2 , 3673-3/3673-4 , 3673-5/3673-6 , 3673-7/3673-8 , and 3673-9/NTAP-mik-rv . pRSnat-gfp-mik1 was generated by amplification of egfp from pDS23 ( M . Nowrousian , unpublished ) using primers Pgpd_egfp_for/mik1_egfp_rev and subsequent recombination in yeast with HindIII-digested pNTAP-mik1 . For pGFP-MIK1_NA , 5′ and 3′ mik1 sequences were amplified from S . macrospora genomic DNA with primer pairs 3673-5fw/3673-5rv-gfp and 3673-11/3673-3rv , respectively , and subsequently recombined into pRSnat-gfp-mik1 , replacing the gpd promoter and trpC terminator . For complementation and TAP , mek1 was amplified from genomic DNA with primers mek1-BamHI-fw/NTAP-mek-BamHI-rv , subcloned into pDrive , cut with BamHI and cloned into BamHI-digested pDS21 [91] , generating pNTAP-MEK1 . Vector pRSnat-mek1-gfp_V3 was generated by amplifying mek1 from S . macrospora genomic DNA with primer pair Pgpd-mek1_V3/gfp-mek-rev and recombination into linearized pDS23 in yeast . For pMEK1-GFP_NA , 5′ and 3′ mek1 sequences were amplified from S . macrospora genomic DNA with primer pairs 2183-5fw_IT/mek1_F1-rv and 2183-3fw-gfp/2183-3rv_IT , respectively , and transformed into yeast together with a 2 . 8 kb PvuII-SpeI fragment from pRSnat-mek1-gfp_V3 and linearized pRSnat [92] . A mak1 complementation vector was constructed by amplifying mak1 using primers Pxyl-mak-for/NTAP-MAK-rv , and recombining the PCR fragment into NotI/BamHI-digested pNpX-GFP [38] , yielding pNpX-MAK1 . Vector pRSnat-mak1-gfp was generated by amplifying mak1 from genomic DNA with primer pair CTAP-mak1-fw/GFP-mak1-rv and transforming the PCR fragment in yeast together with HindIII-linearized pDS23 . For pMAK1-GFP_NA , 5′ ( 5504-5fw/GFP-mak1-rv ) and 3′ ( 5504-3fw-gfp/5504-3rv_IT ) mak1 sequences were amplified and transformed in yeast together with a 0 . 8 kb BamHI fragment from pRSnat-mak1-gfp and linearized pRSnat . To search for PRO40 interaction partners , pC-FLAG-PRO40 [24] was transformed into Δpro40 and single spore isolate T184 . 2NS11 was used for further analysis . For FLAG-AP , dried mycelium was ground in liquid nitrogen , suspended in FLAG extraction buffer ( 50 mM Tris-HCl pH 7 . 4 , 250 mM NaCl , 10% glycerol , 0 . 05% NP-40 , 1 mM PMSF , 0 . 2% protease inhibitor cocktail IV ( Calbiochem ) , 1 mM benzamidine , 1 µg/ml leupeptin ) and centrifuged for 30 min at 16000 rpm . 50 ml crude protein extract was incubated with 300 µl anti-FLAG M2 affinity gel ( A2220 , Sigma Aldrich , St . Louis , MO , USA ) overnight at 4°C on a rotator . Bound complexes were collected by centrifugation and washed twice in 45 ml and once in 1 ml cold washing buffer ( 50 mM Tris-HCl pH 7 . 4 , 150 mM NaCl , 0 . 05% NP-40 , 1 mM PMSF , 1 mM benzamidine , 1 µg/ml leupeptin ) with rotation at 10 min intervals . The affinity gel was transferred to a 1 . 5-ml centrifuge tube and incubated in 500 µl of cold washing buffer containing 2 µl protease inhibitor cocktail IV ( Calbiochem ) and 0 . 5 mg/ml 3× FLAG peptide ( F4799 , Sigma Aldrich , St . Louis , MO , USA ) for 6 hr at 4°C on a rotator . After centrifugation , the supernatant was transferred to a new 1 . 5-ml tube , the gel briefly washed in 500 µl cold washing buffer , centrifuged and the supernatant was combined with the first supernatant . Purified complexes were subjected to trichloroacetic acid precipitation and directly used for mass spectrometry . For TAP analysis , pNTAP-mek1 was transformed into S . macrospora Δmek1 and Δpro40 , and transformants were selected on media with nourseothricin . Primary transformants expressing NTAP-MEK1 were used for single spore isolation . For protein extraction , S . macrospora strains E292 ( Δmek1::NTAP-MEK1 ) and E2544 ( Δpro40::NTAP-MEK1 ) were grown in P-flasks with BMM liquid medium for 3 d at 27°C . TAP analysis was performed as described previously [43] . Tryptic digestion of proteins and MudPIT analysis [44] , [45] were performed as described previously [43] using an Orbitrap Velos ion trap mass spectrometer coupled to an Accela quaternary U-HPLC pump ( Thermo Fisher Scientific ) . Proteome Discoverer software version 1 . 2 was used for MS/MS data interpretation , and data were searched against the S . macrospora database ( smacrosporapep_v4_110909 ) with tryptic peptides , mass accuracy of 10 ppm , fragment ion tolerance of 0 . 8 Da , and with oxidation of methionine as variable modification allowing 4 missed cleavage sites . All accepted results had a high peptide confidence with a score of 10 . Proteins identifies with at least two different peptides in at least two of three to four independent experiments were considered for further analysis . To identify contaminants in TAP-MudPIT data , we used an extended background list from Bloemendal et al . [43] ( Table S6 ) . For validation of PRO40-FLAG-MS data , we performed FLAG-AP experiments with wildtype protein extract as control . Since these experiments yielded a large number of proteins , a previously described quantification approach was employed to evaluate proteins that were identified with at least two different peptides in 2–3 PRO40-FLAG-AP experiments ( Table S3 ) , but also in wildtype control experiments ( Table S4 ) [93] , [94] . This procedure was necessary , because the PRO40 bait protein was identified in one of the control experiments . Therefore , spectral counts for each identified protein were first divided by the sum of spectral counts for each MS run ( PRO40_1 , 9559; PRO40_2 , 5010; PRO40_3 , 7999; wt_1 , 5633; wt_2 , 5901 ) . Then , values for each experiment type were added and used to calculate a ratio between PRO40 and wildtype control data ( Table S5 ) . 79 proteins showing a ratio ≥2 were considered significant hits . From these proteins , PRO40 ( ratio 18 . 63 ) and MEK1 ( ratio 2 . 15 ) were verified as direct PRO40 binding proteins by yeast two-hybrid analysis , and RHO1 ( ratio 2 . 23 ) was verified as indirect PRO40 binding protein via the interaction with PKC1 , showing the applicability of this approach . Immunodetection of TAP-tagged proteins was performed as described using a polyclonal anti-calmodulin binding peptide antibody ( 1∶2000 , Merck Millipore , Billerica , MA , USA ) and an anti-rabbit HRP-linked secondary antibody ( Cell Signaling Technology , Danvers , MA , USA ) [43] . FLAG-PRO40 was detected as described [24] using a monoclonal anti-FLAG antibody ( 1∶2000 , Sigma Aldrich , St . Louis , MO , USA ) and an anti-mouse HRP-linked secondary antibody ( Cell Signaling Technology , Danvers , MA , USA ) . For analysis of MAK1 phosphorylation status , strains were pre-cultured in liquid BMM for 2 days at 27°C . Three standardized inoculates were transferred into liquid HEPES ( 50 mM ) -buffered BMM and cultivated for an additional three to six days at 27°C and 30 rpm . For induction of cell wall stress , cultures were subjected to 0 . 01% H2O2 for 15 , 30 , or 45 minutes . Mycelia were harvested by filtration , ground in liquid nitrogen , and resuspended in FLAG extraction buffer with phosphatase inhibitors ( 1% Phosphatase-Inhibitor-Cocktails II and III , Sigma Aldrich , St . Louis , MO , USA ) . After centrifugation at 15000 rpm for 30 min , equal amounts of total protein were subjected to SDS PAGE and Western Blotting according to standard protocols [76] . Phosphorylated MAK1 was detected using a polyclonal anti-phospho-p44/42 antibody ( Cell Signaling Technology , Inc . , USA ) and an anti-rabbit HRP-linked secondary antibody ( Cell Signaling Technology , Danvers , MA , USA ) according to the manufacturer's protocol . Chemiluminescence was detected using a ChemidocXRS system ( Biorad ) and Clarity Western ECL substrate ( Biorad ) . For an internal standard , an anti-α-tubulin antibody ( Sigma Aldrich , St . Louis , MO , USA , T9026 ) was used in combination with an anti-mouse HRP-linked secondary antibody ( Cell Signaling Technology , Danvers , MA , USA ) . Microscopy was performed with an AxioImager microscope ( Zeiss , Jena , Germany ) . For characterization of sexual development by DIC microscopy , strains were grown on BMM-coated glass slides for 2–7 days as described previously [24] . Hyphal fusion was investigated in 2 days old cultures grown on cellophane-covered MMS plates as described [43] . Localization of fluorescently labeled proteins in vegetative hyphae was investigated on BMM-covered glass slides as described previously [24] . For fluorescence microscopy of protoperithecia , strains were grown on cellophane-covered BMM plates for 3 days , and pieces of cellophane were fixed in 0 . 2% formaldehyde in PBS ( 58 mM Na2HPO4 , 17 mM NaH2PO4 , 68 mM NaCl; pH 7 . 4 ) . Fluorescence was observed using filter sets ( Chroma Technology ) 41017 ( HQ470/40 , HQ525/50 , Q495lp ) or 49002 ( ET470/40× , ET525/50m , T495lpxr ) for EGFP and filter set 49008 ( ET560/40× , ET630/75m , T585lp ) for tdTomato . Mutant pro30 from our laboratory collection was back-crossed several times to wildtype or brown-spored fus [25] and finally crossed to fus ( Figure S8 ) . DNA was extracted from 40 sterile progeny as described previously [25] . 40 fertile strains were collected from three crosses of mutants pro30 , pro32 , and pro34 to fus ( Figure S8 ) . Mutants pro32 and pro34 are described elsewhere [82; Teichert and Kück , unpublished] . 5 µg of pooled genomic DNA for pro30 and wt , respectively , was subjected to 50 bp paired-end Illumina/Solexa sequencing with a HiSeq2000 at GATC Biotech ( Konstanz , Germany ) . Cleaning of raw data , mapping to the S . macrospora reference genome [5] , [41] , and analysis of sequence variants was performed as described [25] using the Burrows Wheeler Alignment tool [95] , SAMtools [96] and custom-made Perl scripts , with minor modifications ( Text S1 ) . Genome sequencing data have been deposited at the sequence read archive ( SRA; acc . no . SRX483430 and SRR1046323 for pro30 and wildtype ( wt_3 ) [82] , respectively ) . | The specific response to environmental cues is crucial for cell differentiation and is often mediated by highly conserved eukaryotic MAP kinase ( MAPK ) pathways . How these pathways react specifically to huge numbers of different cues is still unclear , and current literature about adapter and scaffolding proteins remains scarce . However , gaining fundamental insight into molecular signaling determinants is pivotal for combating diseases with impaired signal transduction processes , such as Alzheimer's disease or cancer . Importantly , signal transduction can easily be studied in lower eukaryotes like filamentous fungi that are readily genetically tractable . The fungus Sordaria macrospora has a long history as an ideal model system for cell differentiation , and we show here that the proposed cell wall integrity ( CWI ) MAPK module of this fungus controls differentiation of sexual fruiting bodies , cell fusion , polar growth and cell wall stress response . We further discovered that developmental protein PRO40 binds the MAPK kinase kinase ( MAPKKK ) , the MAPK kinase ( MAPKK ) and upstream activator protein kinase C ( PKC1 ) of the CWI pathway and is required for MAK1 activity , thereby providing evidence that PRO40 is a scaffold protein . Collectively , our findings reveal a molecular role for a protein implicated in development , cell fusion , symbiosis , and pathogenicity in different fungi . | [
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] | 2014 | PRO40 Is a Scaffold Protein of the Cell Wall Integrity Pathway, Linking the MAP Kinase Module to the Upstream Activator Protein Kinase C |
Transmission of M . ulcerans , the etiological agent of Buruli ulcer , from the environment to humans remains an enigma despite decades of research . Major transmission hypotheses propose 1 ) that M . ulcerans is acquired through an insect bite or 2 ) that bacteria enter an existing wound through exposure to a contaminated environment . In studies reported here , a guinea pig infection model was developed to determine whether Buruli ulcer could be produced through passive inoculation of M . ulcerans onto a superficial abrasion . The choice of an abrasion model was based on the fact that most bacterial pathogens infecting the skin are able to infect an open lesion , and that abrasions are extremely common in children . Our studies show that after a 90d infection period , an ulcer was present at intra-dermal injection sites of all seven animals infected , whereas topical application of M . ulcerans failed to establish an infection . Mycobacterium ulcerans was cultured from all injection sites whereas infected abrasion sites healed and were culture negative . A 14d experiment was conducted to determine how long organisms persisted after inoculation . Mycobacterium ulcerans was isolated from abrasions at one hour and 24 hours post infection , but cultures from later time points were negative . Abrasion sites were qPCR positive up to seven days post infection , but negative at later timepoints . In contrast , M . ulcerans DNA was detected at intra-dermal injection sites throughout the study . M . ulcerans was cultured from injection sites at each time point . These results suggest that injection of M . ulcerans into the skin greatly facilitates infection and lends support for the role of an invertebrate vector or other route of entry such as a puncture wound or deep laceration where bacteria would be contained within the lesion . Infection through passive inoculation into an existing abrasion appears a less likely route of entry .
Buruli ulcer , a severe cutaneous infection caused by the environmental pathogen Mycobacterium ulcerans is a major cause of morbidity in West and Central Africa [1] , [2] . The disease begins with a painless nodule that can lead to severe ulceration . Though mortality is low , morbidity is extremely high . In 1998 , the World Health Organization declared Buruli ulcer a neglected tropical disease and established the Global Buruli Ulcer Initiative focused on prevention , awareness , and improved treatment options for those suffering from this disease . The transmission of M . ulcerans from the environment to humans is a central enigma in M . ulcerans research [1] . Infection has been consistently linked with exposure to aquatic environments , but the exact mode of transmission is unknown [3] . Person-to-person transmission is extremely rare [4] . Several routes of transmission have been proposed including: transmission via insect vectors [5]–[7]; direct contact with contaminated vegetation [1] , [8] , [9]; aerosol [9] , [10] or entrance of the bacterium through a preexisting wound following environmental exposure [1] , [9] . Of these , transmission by inoculation into pre-existing wounds or inoculation by the bite of an invertebrate vector has received the greatest attention . Superficial skin lesions are extremely common among children in the tropics . Abrasions and small open lesions are ubiquitous in children , but lacerations and puncture wounds also represent sites where bacteria could be introduced . Some of these hypotheses are supported by detection of M . ulcerans DNA in environmental samples [11]–[13] . Laboratory studies confirm that M . ulcerans survives in many invertebrate species and in one case transmission from an invertebrate vector to a mouse has been demonstrated experimentally under laboratory conditions [5] . However , invertebrate species implicated in transmission in West Africa are not hematophagous . The importance of invertebrates in maintaining aquatic food webs was summarized in a review of transmission by Merritt , et al [1] , but the authors suggest that the role of invertebrates as vectors remains unclear . A study by Benbow et al , 2008 [14] also casts doubt on invertebrate vectors . That study did not , however , include sampling sites from a historically non-endemic region . More recently Benbow et al , 2013 [15] compared results from detection of M . ulcerans DNA in invertebrates from Buruli ulcer endemic sites with results from invertebrates from the Volta region in Ghana where Buruli ulcer is rarely encountered , and found that M . ulcerans DNA was not detected in invertebrates collected in the Volta region . Cutaneous infections in pre-existing abrasions caused by waterborne pathogens are being recognized with increasing frequency [16] . Aeromonas hydrophila , Pseudomonas aeruginosa , and M . fortuitum are often associated with trauma and water exposure [17]–[20] . M . marinum , whose genome shares 98% sequence 16S similarity to M . ulcerans , is a pathogen of fish which can cause cutaneous infection in humans through contact with contaminated water [18] , [21] . Although there have been a few reports of M . ulcerans developing at the site of a previous wound [22] or insect bite [23] , there is no epidemiological data supporting this as a frequent mode of transmission . However , the incubation period between infection and disease is usually at least five weeks , and can be over six months [1] , [24] . If the time span is several months , a patient might not remember the presence of a previous abrasion at the site of Buruli ulcer . The objective of this study was to develop an infection model to determine the effect of the route of inoculation on the development of disease . For this model , we used hairless Hartley guinea pigs ( Cavia porcellus ) . Guinea pigs are often used in cutaneous infection models because guinea pig skin is structurally and immunologically more similar to human skin than murine skin [25] . Both human and guinea pig skin have a thick fat layer that provides an ideal environment for the replication of mycobacteria . Buruli ulcer has been experimentally induced in guinea pigs by intradermal inoculation , a method that reproduces similar clinical manifestation and pathology to that produced in human skin [26]–[28] . Abrasions were made on the backs of hairless Hartley guinea pigs with a steel brush and the animals were exposed either topically to M . ulcerans or through intra-dermal injection . Additionally , two guinea pigs were topically infected with Staphylococcus aureus as a positive control for skin infection and inflammation . Results from these studies show that injection of M . ulcerans greatly facilitates the induction of Buruli ulcer , and suggest that entrance of organisms through a superficial skin abrasion is an unlikely route of transmission .
A well-characterized clinical isolate , M . ulcerans 1615 was used in all studies [26] . M . ulcerans 1615 were grown in Middlebrook 7H9 liquid media and on Middlebrook 7H10 agar supplemented with 10% oleic acid-albumin-dextrose enrichment ( OADC ) and incubated at 30°C to reach exponential phase of growth . Bacterial viability was validated by staining using a cell viability assay kit ( Promega , Madison , WI , USA ) . Staphylococcus aureus 502a ( ATCC# 27217 ) was obtained from American Type Culture Collection , cultured on nutrient agar and incubated at 37°C . This strain of S . aureus was isolated from the nares of a nurse , and described in ATCC as being coagulase positive , penicillin sensitive , and sensitive to 10 mcg of tetracycline . Male and female Hartley Hairless guinea pigs weighing between 250–300 g were used for inoculation experiments . Seven subjects were used in the first experiment reported here , and 12 for the experiment in which a time course was performed . The initial animals were housed in Walters Life Sciences Animal facility in separate cages . Guinea pigs were transferred to the procedure room and placed under anesthesia of 2% isofluorane for approximately 4 minutes . Guinea pigs were maintained on continuous flow of oxygen and isofluorane for all procedures including abrasions , inoculation or injection . A steel brush was used to make skin abrasions on the backs of guinea pigs until blood was drawn ( Figure S1 ) . Immediately following this , twenty microliters of 104 and 108 M . ulcerans were dropped onto duplicate abraded areas in a 20 µL volume . Controls sites included: 1 ) a negative control where sterile media was dropped onto abraded skin , 2 ) a negative control where M . ulcerans was spread onto unabraded skin ( Figure S1 ) , 3 ) a positive control where 200 µL containing 106 M . ulcerans 1615 was injected into the hind flank using a 25- gauge needle as previously described [26] , [28] , and 4 ) a positive control in which S . aureus ( 108 CFU/ML in a 20 µL volume ) was introduced to abraded areas of two guinea pigs in duplicate as a positive control for infection and inflammation . This inoculum for S . aureus was chosen based upon a published study showing that this concentration induced pathology 24-hours post infection in a dermal guinea pig model [29] . Infected guinea pigs were allowed to recover from anesthesia and transported to individual housing quarters when ambulation was restored . Guinea pigs were monitored by an attending veterinarian and animal care facility staff during the procedure , and daily throughout the study . Buprenophrine ( 0 . 5 mg/kg ) was available to manage pain . However , M . ulcerans infections are painless and the duration of infection with S . aureus was short enough that pain management was not necessary . Due to concerns of potential pain associated with S . aureus infection , guinea pigs infected with S . aureus were sacrificed 24-hours post infection . In an initial experiment , guinea pigs infected with M . ulcerans were sacrificed at 90 days p . i . In a subsequent experiment , animals were sacrificed at 1 hour , 24 hours , 48 hours , 7 days , and 14 days . Tissues were divided into quarters for culture , DNA extraction and qPCR , lipid analysis , or histopathology . Duplicate abraded sites exposed to M . ulcerans were divided in half and one of these tissue divisions was randomly used for one of the four analyses . Skin specimens for histology were routinely fixed in 10% buffered neutral formalin , paraffin embedded , and sectioned at 5 microns . Serial sections were stained with Modified Kenyon's stain and Hematoxylin–Eosin stains as described [26] , [28] . Skin specimens were decontaminated using the modified Petroff's method as previously described [30] . Briefly , two milliliters of 4% NaOH was incubated with approximately 2 grams guinea pig tissue for 15 min , followed by centrifugation and decanting of the supernatant . Fifteen milliliters of sterile saline were added to the tissue pellet , and centrifuged at 3 , 000× g for 15 minutes . The supernatant was decanted and the decontaminated tissue was plated onto M7H10 agar plates supplemented with 10% OADC supplement and Lowenstein Jenson plates . All media was incubated at 30°C and observed weekly for signs of growth . Tissues infected with S . aureus were plated onto nutrient agar and incubated at 37°C for recovery of bacteria . Approximately 1 gram of tissue was lysed mechanically and chemically by bead beating in lysis solution for 15 minutes followed by incubation at 65°c for 20 minutes . Tissues were centrifuged for 2 minute at 5600×g and the supernatant was added to potassium acetate and incubated for 1 hour at −20°C . Samples were centrifuged for 30 minutes at 5600×g and the supernatant mixed with guanidine hydrochloride solution and added to a MOBIO spin filter . Each spin filter was centrifuged three times for 2 minutes at 5600×g with the flow through discarded each time . The spin filter was washed with wash solution and ethanol and the spin filter was allowed to dry by centrifugation at 5600×g for 5 minutes . DNA was eluted using elution solution and centrifugation and the resulting DNA was subjected to quantitative PCR analysis targeting the enoyl reductase domain of the plasmid responsible for mycolactone production as previously described [31] . The University of Tennessee Institutional Animal Care and Use Committee ( IACUC ) approved all procedures and protocols carried out in this study under IACUC protocol #1832 . The University of Tennessee policies for animal care and use encompass regulations of the Animal Welfare Act as amended ( Public Law 99–198 – The Improved Standard for Laboratory Animals Act ) , Guide for the Care and Use of Laboratory Animals ( 8th Ed . ) and The Guide for the Care and Use of Agricultural Animals in Research and Teaching .
In order to determine whether M . ulcerans could establish infection through an open wound , abrasions were made on the backs of Hairless Hartley guinea pigs and M . ulcerans in Middlebrook 7H9/OADC media was dropped on the open abrasions . An intra-dermal injection was included as a positive control . A wheal was apparent following injection confirming the intra-dermal location of injection ( Figure S1 ) . Guinea pigs were sacrificed at 90 d p . i . No gross pathology was detected at any of the abrasion sites . All of the abrasion sites healed within the first week p . i . , and remained healed throughout the remainder of the study ( Figure 1B and 1C ) . Lesions developed at the injection site within the first two weeks and ulcers or plaques were present at the injection sites on all subjects at the end of the 90-day study period ( Figure 1D ) . The ventral side of dissected lesions from the injection sites developed a typical “bacon-fat” appearance with evidence of necrosis and hemorrhage typical of Buruli ulcer [32] ( Figure 1G ) The ventral side of unabraded control tissues ( 1E ) was identical to that of healed infected abrasions ( 1F ) . Histologically the abrasion sites where M . ulcerans was applied appeared normal ( Figure 2B ) and were identical to those of negative controls ( Figure 2A ) . No acid-fast bacteria were detected in uninfected abraded skin ( 2D ) or in infected abraded skin ( 2E ) . In contrast , extensive microscopic pathology was observed in lesions formed by injection of M . ulcerans ( 2C ) . Extensive acellular necrotic foci , edema and calcification were characteristic features of these lesions . Hyperplasia was present at the site of inoculation and infiltration of inflammatory cells could often be detected at the edge of the necrotic center . Severe necrosis of subcutaneous adipose tissue was evident and in some animals necrosis extended to muscle tissue . Erosion of blood vessels was often evident as previously described [33] . Clusters of extracellular acid-fast bacilli were found adjacent to large areas of necrosis ( 2F ) . Mycobacterium ulcerans was cultured from all of the guinea pig injection sites , whereas mycobacteria were not recovered from any abrasion site despite the high inoculum initially applied ( Table 1 ) . Mycobacterium ulcerans was detected by quantitative PCR in 7/7 injection sites with concentrations ranging from 7 . 25×105 to 3 . 87×108 genome units/sample ( Table 1 and Figure S2 ) . Mycobacterium ulcerans DNA was not detected in tissue from low dose infections from abrasions ( 104 ) , but M . ulcerans DNA was detected in 2/7 abrasion sites where 108 bacteria were applied to abrasions ( Table 1 ) . Control tissues were negative for M . ulcerans DNA ( Table 1 and Figure S2 ) . Results from our first experiment showed that M . ulcerans was unable to establish an infection through an abrasion , but did not provide temporal data regarding colonization . To determine how long M . ulcerans remained in tissue following infection , an experiment was conducted to monitor the presence of M . ulcerans at 1 h , 24 h , 48 h , 7 d , and 14 d p . i . As in the previously described experiment , abrasions were made in the back skin of guinea pigs to a depth that bleeding was evident . For infection through injection , the intra-dermal location of the mycobacterial inoculum was validated by formation of a skin wheal at the injection site . In this experiment , S . aureus was included as a positive control for an organism known to infect through a superficial wound [34] , [35] . Two guinea pigs infected with S . aureus were sacrificed 24 h p . i . The animal care and use committee suggested this short time period due to concerns regarding pain associated with S . aureus infection . In contrast to the abrasion control ( Figure 3A ) , S . aureus infected skin showed gross pathology characterized by inflammation , scabbing and serous exudate ( Figure 3B ) . Vascularization was also evident ( Figure 3C ) and histology revealed extensive infiltration of inflammatory cells ( Figure 3D ) . Large numbers of S . aureus gram-positive cocci were found in association with the extracellular matrix ( Figure 3E ) . S . aureus was recovered upon culture ( Table 2 ) . The pathology following M . ulcerans infection differed greatly from that shown with S . aureus . Following superficial application of M . ulcerans to abrasions , scabs began to form by 24 h p . i . ( Figure 4A ) , and scabs began to slough off 48 h p . i . ( Figure 4B ) . There was no evidence of inflammation or tissue damage at the inoculated abrasion sites . All abrasions were healed within 7 d , and remained healed by the end of the 14 d study ( Figure 4C ) . In contrast , erythema and edema were apparent at the injection site within 7 d post infection and often earlier ( Figure 4D ) . Gross pathology was absent at the abrasion sites where M . ulcerans was applied and tissue remained normal during the remainder of the 14 d study ( Figure 4F ) . Histopathology of M . ulcerans infected abrasion sites was identical to that of uninfected abraded skin controls ( Figure 4E ) . In contrast , the positive control injection site showed erythema and initial signs of typical Buruli ulcer pathology by 7 d post infection ( Figure 4G ) [36] . Microscopically , acid-fast bacilli were only found on sections from one of the four abrasion sites at 24 h and one of the four taken at 48 h ( Table 2 , Fig . 5 ) . In both cases , a single cluster of acid-fast bacteria was found after extensive microscopic examination . These clusters did not appear to be cell associated ( Figure 5E ) . Histology of H&E stained tissue from M . ulcerans infected abrasion sites ( 5B ) was identical to that of negative controls ( 5A ) . Small numbers of M . ulcerans bacteria were found in clusters in abrasion sites 48 h p . i , but were absent by 7 d ( Table 2 ) . Histology of sectioned tissue from injection sites 24 h p . i . showed typical Buruli ulcer pathology ( 5C , 5F ) . Hyperplasia and infiltration of inflammatory cells were detected along with extensive necrosis of adipose tissue and micro-hemorrhage . Necrosis extended to the muscle tissue in some animals . Acid-fast staining revealed a large area of necrosis filled with large clusters of extracellular acid-fast bacilli ( 5F ) . Mycobacterium ulcerans was recovered upon culture from abrasion sites at 1 h and 24 h p . i . , but was not recovered at subsequent timepoints ( Table 2 ) . In contrast , M . ulcerans was cultured from all of the injection sites from every timepoint ( Table 2 ) . Quantitative PCR was conducted on sectioned tissue ( Table 2 ) . Mycobacterium ulcerans DNA was detected from abrasion sites at 1 h p . i . , with an average of 2 . 54×108 genome units/sample . Mycobacterium ulcerans DNA was also detected at the 24 h , 48 h , and 7 d timepoints from abrasion sites with an average of 6 . 86×106 , 2 . 54×107 , and 5 . 02×106 genome units/sample respectively . Mycobacterium ulcerans DNA was not detected from abrasion sites 14 d p . i . ( Table 2 ) Control tissues were negative for M . ulcerans DNA . Mycobacterium ulcerans DNA was detected at all of the injection sites throughout the study with average concentrations of 1 . 84×108 , 1 . 96×107 , 1 . 77×108 , 1 . 26×108 , and 5 . 79×106 genome units/sample for the 1 h , 24 h , 48 h , 7 d , and 14 d timepoints respectively ( Table 2 ) .
In this work , we have developed an animal model to test alternative hypotheses regarding transmission of M . ulcerans . There is considerable controversy in the M . ulcerans research community regarding potential routes of transmission [1] . Whereas several publications based on both laboratory and field studies suggest that M . ulcerans may be transmitted through the bite of an aquatic invertebrate , vector competency studies have not been conducted [5]–[7] , [15] , [37] , [38] . Field data are based primarily on detection of M . ulcerans DNA in environmental samples . Although there has been one environmental isolate from an aquatic invertebrate [38] , the strain differs from those isolated in human infection , and the organism has not been isolated from a biting invertebrate . Thus , more work needs to be done to establish the role of insects in the transmission of M . ulcerans [1] , [14] . The situation is further complicated by the following evidence: 1 ) M . ulcerans DNA has been detected in over 30 taxa of aquatic invertebrates in West Africa [11] , [12] , [15] , [39]; and 2 ) none of these species are hemotaphagous , suggesting that the frequency of human bites by these insects would be extremely low . A great deal of laboratory work has been done on the interaction of M . ulcerans with Naucoridae [5] , [40] , but these species are uncommon or missing in aquatic sites sampled in Benin and Ghana [11] , [14] . However , in Benin and Ghana M . ulcerans DNA has been repeatedly detected in Belostomatidae , a group of predatory , aquatic invertebrates , and laboratory studies confirm colonization of these insects by M . ulcerans both on the external skeleton and internal compartments [11] , [37] . In Australia , transmission of M . ulcerans by mosquitoes has been proposed based on research in temperate regions of the country , but the M . ulcerans genome units detected in mosquitoes are extremely low making it difficult to evaluate the significance of these findings [23] , [41] . Further , preliminary evidence from tropical areas of Australia where M . ulcerans infection occurs does not support a role for mosquitoes [42] . Laboratory studies show that whereas mosquito larvae readily consume mycobacteria , the bacteria are not maintained through pupation or adult mosquito emergence casting doubt on the role of mosquitoes as a biological vector [43]; however the potential of mosquitoes as reservoirs or their role in mechanical transmission cannot be negated . Many investigators have suggested that M . ulcerans may establish infection through pre-existing wounds [1] . Although there are many types of skin lesions and wounds , the development of an abrasion model for an initial study was based on the following considerations: 1 ) An abrasion is a superficial lesion which does not extend below the dermis , and most dermatological bacterial pathogens such as S . aureus are able to establish infection through this type of minor breach in the skin; 2 ) Superficial skin lesions such as abrasions are ubiquitous among children in rural communities of West Africa and 3 ) intra-dermal injection of M . ulcerans also places the inocula within the dermis and this route of infection has been shown to consistently lead to Buruli ulcer [26] , [28] . . The fact that epidemiologic evidence fails to confirm either of these hypotheses for transmission is attributed to the highly variable and often long period of time between infection and disease [24] . Transmission of M . ulcerans from the environment to humans thus remains a central enigma of M . ulcerans research . Definitive evidence for a route of transmission could be obtained by culturing the bacteria from the environment and matching genomic data from environmental isolates with patient isolates . However , the very slow growth rate of the organism makes culture from the environment extremely difficult due to overgrowth by faster growing organisms . Despite decades of work by highly competent investigators , only one environmental isolate has been obtained and that strain was isolated from a water strider ( Gerridae ) , an invertebrate incapable of biting humans [38] . The probability that aquatic invertebrates may serve as reservoirs , rather than vectors , for M . ulcerans is a strong possibility [1] , [15] . When we began the investigations reported here , our hypothesis was that M . ulcerans could establish infection through an abrasion . Thus , the failure to establish an infection through passive inoculation was completely contrary to our expectations . Because of this surprising result , we repeated the experiment multiple times with differing amounts of inocula . Identical results were obtained in each experiment , i . e . we were unable to establish infection when M . ulcerans was applied to an abrasion , whereas injection of M . ulcerans produced an ulcer in every case . A time course over a two-week period showed evidence for transient colonization of abrasions , but after 48 h , bacteria could no longer be recovered from infected abrasions . What might account for the inability of M . ulcerans to establish an infection through application to an abrasion ? One intriguing possibility is that the high temperature and low oxygen environment of the injection site or the presence of fatty acids released by dead adipocytes might enhance production of the mycolactone toxin . This upregulation would clearly lead to greater pathology . Thus far , studies conducted in vitro show that the production of mycolactone is constitutive [44] . However , this area of investigation needs further attention . A second possibility for the lack of colonization through an open abrasion is that M . ulcerans lacks adhesins for cellular proteins . In support of this hypothesis , adhesins have not been reported in M . ulcerans , and a search of the annotated M . ulcerans genome does not reveal the presence of the adhesins found in M . marinum or M . tuberculosis [45] . Evidence from histopathology shown in this paper and similar results reported from many papers on human infection describe massive clumps of M . ulcerans lying in necrotic tissue [46]–[48] . Early studies conducted in our laboratory with L929 and HeLa cells showed that M . ulcerans was unable to adhere to non-phagocytic cells ( Small unpublished data ) . This finding is remarkable because even the saprophyte M . smegmatis adheres to and enters fibroblasts though replication does not occur . Data from the M . ulcerans genome , as well as from lipid analysis of the M . ulcerans surface , show that the lipid repertoire of the M . ulcerans cell surface is extremely small compared with other mycobacterial species [49] . Mycobacterium ulcerans is thought to have evolved from an M marinum-like ancestor through acquisition of a plasmid encoding mycolactone , and reductive evolution in which over 700 genes present in M . marinum are mutated or lost in M . ulcerans [50] . Many of these genes encode surface molecules that could play a role in bacterial-host cell interactions . An example of such a molecule would be a glycolipid present in M . marinum but absent from M . ulcerans [51] . Although both M . ulcerans and M . marinum are associated with aquatic sources , the epidemiology of the two species differs considerably . The primary risk factor for M . marinum infection involves handling fish , and fishing is a high-risk activity [52] . M . marinum has been isolated from infected fish around the world and is primarily a pathogen of aquatic vertebrates [52] . In contrast , M . ulcerans has not been associated with fish infection , though specific clades of M . marinum that have the mycolactone plasmid have caused fish infections [53] . M . marinum appears to be considerably more infectious than M . ulcerans . There have been outbreaks of M . marinum associated with contaminated water where dozens of people have been infected [52] . Finally , M . marinum appears to be able to infect skin where no apparent pre-existing lesion was noted [54] . This makes the inability of M . ulcerans to infect an abrasion all the more surprising . The presence of mycolactone on the cell surface may also play a role in the failure of M . ulcerans to associate with cells either through its effect on the hydrophobicity of the bacterial surface , or through its activity on eukaryotic cells . This question could be addressed by comparing the ability of WT and mycolactone deficient mutants to adhere to cells . Thus , evidence from in vivo , in vitro , and in silico studies suggests that M . ulcerans is deficient in the ability to adhere to eukaryotic cells and that this defect is likely to explain the inability of M . ulcerans to colonize through passive inoculation of an open abrasion . In summary , this work lends support to the hypothesis that M . ulcerans infection occurs through injection of bacteria rather than through entrance of pre-existing , superficial skin abrasions . The ability to establish infection through intra-dermal injection shows that inoculation does not need to be deep . In rural communities , skin wounds of many types are common . Our work does not rule out the possibility that infection could occur through puncture wounds , or lacerations . We plan to examine these possibilities more thoroughly in subsequent studies . Still , the possibility that transmission could occur through the bite of an invertebrate vector , an idea proposed by Francoise Portaels over 10 years ago , gains some support from the studies presented here . | Buruli ulcer , a severe skin disease in West and Central Africa results in significant disability . The causative bacterium , M . ulcerans has been detected in many aquatic sources , but how bacteria enter the skin is an enigma . Two major hypotheses for infection are 1 ) that bacteria are injected into the skin through the bite of an aquatic insect , or 2 ) that bacteria enter open wounds on a person's body . In this study , we use a guinea pig infection model to evaluate whether application of M . ulcerans to an open abrasion produces Buruli ulcer . Our results show that despite topical application of very large numbers of M . ulcerans , we are unable to produce infection in open abrasions . These results are extremely surprising because most bacteria such as Staphylococcus or Streptococcus can readily infect abrasions . In contrast , intra-dermal injection of M . ulcerans into the skin of guinea pigs consistently produced an ulcer . Our studies are the first to explore the route of infection of M . ulcerans in an experimental model . These results suggest that Buruli ulcer is not likely to be due to passive entry of bacteria into pre-existing abrasions and supports the role of biting invertebrates , puncture wounds , or lacerations as a requirement for infection . | [
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] | 2014 | Mycobacterium ulcerans Fails to Infect through Skin Abrasions in a Guinea Pig Infection Model: Implications for Transmission |
In many ecosystems , natural selection can occur quickly enough to influence the population dynamics and thus future selection . This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes . Here , we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape . We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise , and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection . We draw an analogy between the fitness function and the free energy in statistical mechanics , allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics . We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems , finding that the evolution-driven chaotic dynamics confer community stability at the “edge of chaos” while creating a wide distribution of opportunities for speciation during epochs of disruptive selection—a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies .
In many natural ecosystems , at least one constituent species evolves quickly enough relative to its population growth that the two effects become interdependent . This phenomenon can occur when selection forces are tied to such sudden environmental effects as algal blooms or flooding [1] , or it can arise from more subtle , population-level effects such as overcrowding or resource depletion [2] . Analysis of such interactions within a unified theory of “eco-evolutionary dynamics” has been applied to a wide range of systems—from bacteria-phage interactions to bighorn sheep [3]—by describing population fluctuations in terms of the feedback between demographic change and natural selection [4] . The resulting theoretical models relate the fitness landscape ( or fitness function ) to population-level observables such as the population growth rate and the mean value of an adapting phenotypic trait ( such as horn length , cell wall thickness , etc ) . The fitness landscape may have an arbitrarily complex topology , as it can depend on myriad factors ranging from environmental variability [5 , 6] , to inter- and intraspecific competition [7 , 8] , to resource depletion [9] . However , these complex landscapes can be broadly classified according to whether they result in stabilizing or disruptive selection . In the former , the landscape may possess a single , global maximum that causes the population of individuals to evolve towards a state in which most individuals have trait values at or near this maximum [10] . Conversely , in disruptive selection , the fitness landscape may contain multiple local maxima , in which case the population could have a wide distribution of trait values and occupy multiple distinct niches [11] . In eco-evolutionary models , the shape of the fitness landscape may itself depend on the population densities of the interacting species it describes . Specifically , the concept that the presence of competition can lead a single-peaked fitness landscape to spontaneously develop additional peaks originates in the context of “competitive speciation” first proposed by Rosenzweig [12] . This is formalized in genetic models in which sympatric speciation is driven by competitive pressures rather than geographic isolation [13] . Competition-induced disruptive selection has been observed in natural populations of stickleback fish [14] , microbial communities [15] , and fruit flies [16 , 17] . Here , we model eco-evolutionary dynamics of a predator-prey system based on first-order “gradient dynamics” [10 , 18] , a class of models that explicitly define the fitness in terms of the population growth rate r , which is taken to depend only on the mean value of the trait across the entire population , c ¯ [19] . Despite this simplification , gradient dynamics models display rich behavior that can account for a wide range of effects observed in experimental systems—in particular , recent work by Cortez and colleagues has shown that these models can result in irregular cycles and dynamical bifurcations that depend on the standing genetic variation present in a population [20 , 21] . In our model , gradient dynamics cause the prey fitness landscape to change as a result of predation , and we find that the resulting dynamical system exhibits chaotic dynamics . Chaos is only possible in systems in which three or more dependent dynamical variables vary in time [22] , and previously it has been observed in predator-prey systems comprising three or more mutually interdependent species , or in which an external environmental variable ( such as seasonal variation or generic noise ) is included in the dynamics [23 , 24] . Here we show that evolution of just one species in a two-species ecosystem is sufficient to drive the ecosystem into chaos . Moreover , we find that chaos is driven by a density-dependent change of the fitness landscape from a stabilizing to disruptive state , and that this transition has hysteretic behavior with mathematical properties that are strongly reminiscent of a first-order phase transition in a thermodynamical system . The resulting dynamics display intermittent properties typically associated with ecosystems poised at the “edge of chaos , ” which we suggest has implications for the study of ecological stability and speciation .
Adapting the notation and formulation used by Cortez ( 2016 ) [21] , we use a two-species competition model with an additional dynamical variable introduced to account for a prey trait on which natural selection may act . The most general fitness function for the prey , r , accounts for density-dependent selection on a prey trait c , r ( x , y , c ¯ , c ) ≡ G ( x , c , c ¯ ) - D ( c , c ¯ ) - f ( x , y ) , ( 1 ) where x = x ( t ) is the time-dependent prey density , y = y ( t ) is the time-dependent predator density , c is a trait value for an individual in the prey population , and c ¯ = c ¯ ( t ) is the mean value of the trait across the entire prey population at time t . r comprises a density-dependent birth rate G , a density-independent death rate D , and a predator-prey interaction term f , which for simplicity is assumed to depend on neither c nor c ¯ . Thus the trait under selection in our model is not an explicit predator avoidance trait such as camouflage , but rather an endogenous advancement ( i . e . , improved fecundity , faster development , or reduced mortality ) that affects the prey’s ability to exploit resources in its environment , even in the absence of predation . The continuous-time “gradient dynamics” model that we study interprets the fitness r as the growth rate of the prey: [19 , 25] x ˙ = x r ( x , y , c ¯ , c ) | c → c ¯ ( 2 ) y ˙ = y ( f ( x , y ) - D ˜ ( y ) ) ( 3 ) c ¯ ˙ = V ∂ r ( x , y , c ¯ , c ) ∂ c | c → c ¯ . ( 4 ) Eq ( 2 ) is evaluated with all individual trait values c set to the mean value c ¯ because the total prey population density is assumed to change based on the fitness function , which in turn depends on the population-averaged value of the prey trait c ¯ [21] . The timescale of the dynamics in c ¯ are set by V , which is interpreted as the additive genetic variance of the trait [10] . While Eq ( 2 ) depends only on the mean trait value c ¯ , the full distribution of individual trait values c present in a real-world population may change over time as the relative frequencies of various phenotypes change . In principle , additional differential equations of the form of Eq ( 4 ) could be added to account for higher moments of the distribution of c across an ensemble of individuals , allowing the gradient dynamics model to be straightforwardly extended to model a trait’s full distribution rather than just the population mean . However , here we focus on the case where the prey density dynamics x ˙ depend only on the mean trait value to first order , and we do not include differential equations for higher-order moments of the prey trait value distribution . The use of a single Eq ( 4 ) to describe the full dynamics of the trait distribution represents an approximation that is exact only when the phenotypic trait distribution stays nearly symmetric and the prey population maintains a constant standing genetic variation V [10] . However , V may remain fixed even if the phenotypic variance changes , a property that is observed phenomenologically in experimental systems , and which may be explained by time-dependent heritability , breeding effects , mutation , or other transmission effects not explicitly modeled here [26–29] . More broadly , this assumption may imply that gene selection is weak compared to phenotype selection [30 , 31] . S1D Appendix further describes the circumstances under which V remains fixed , and also provides a first-order estimate of the magnitude of error introduced by ignoring higher-order effects ( such as skewness ) in the trait distribution . The results suggest that these effects are small for the parameter values ( and resulting range of x and y values ) used here , due in part to limitations on the maximum skewness that a hypothetical trait distribution can achieve on the fitness landscapes studied here . In S1D Appendix , we also compare the results presented below to an equivalent model in which a full trait distribution is present , in which case Eq ( 2 ) becomes a full integro-differential equation involving averages of the trait value over the entire prey population . Detailed numerical study of this integro-differential equation is computationally prohibitive for the long timescales studied here , but direct comparison of the contributions of various terms in the velocity field suggests general accuracy of the gradient dynamics model for the fitness landscapes and conditions we study here . However , in general the appropriateness of the gradient dynamics model should be checked whenever using Eq ( 4 ) with an arbitrary fitness function . Fig 1A shows a schematic summarizing the gradient dynamics model , and noting the primary assumptions underlying this formulation . Next , we choose functional forms for f , G , D , and D ˜ in Eqs ( 2 ) and ( 3 ) . We start with the assumption that , for fixed values of the trait c an d its mean c ¯ , the population dynamics should have the form of a typical predator-prey system in the absence of evolutionary effects . Because the predator dynamics are not directly affected by evolutionary dynamics , we choose a simple form for predator growth consisting of a fixed death rate and a standard Holling Type II birth rate , [32] f ( x , y ) = a 2 x y 1 + b 2 x ( 5 ) D ˜ ( y ) = d 2 ( 6 ) The predator birth rate f saturates at large values of the prey density , which is more realistic than the standard Lotka-Volterra competition term xy in cases where the prey density is large or fluctuating [22] . A saturating interaction term ensures that solutions of the system remain bounded for a wider range of parameter values , a necessity for realistic models of long-term interactions [33] . For the prey net growth rate ( Eq ( 1 ) , the fitness ) in the absence of the predator , we use the following functional forms , G ( x , c ¯ , c ) = a 1 c ¯ 1 + b 1 c ¯ ( 1 - k 1 x ( c - c ¯ ) ) ( 7 ) D ( c , c ¯ ) = d 1 ( 1 - k 2 ( c 2 - c ¯ 2 ) + k 4 ( c 4 - c ¯ 4 ) ) . ( 8 ) The first term in Eq ( 7 ) specifies that the prey population density growth rate r | c → c ¯ depends only on a primary saturating contribution of the mean trait to the birth rate G . In other models a similar effect is achieved by modifying the mean trait evolution Eq ( 4 ) , such that extremal values of the trait are disadvantaged [21]; alternative coupling methods based on exponential saturation would be expected to yield similar qualitative results [19] . However , the additional series terms in Eqs ( 7 ) and ( 8 ) ensure that the any individual’s fitness r may differ from the rest of the population depending on the difference between its trait value c and the population mean c ¯ . Because the functional form of this difference is unknown , its contribution expressed as second-order truncation of the series difference of the form r ( c , c ¯ ) = r ˜ | c → 0 + ( r ˜ ( c ) - r ˜ ( c ) | c → c ¯ ) ( where r ˜ represents an unscaled fitness function ) . This ensures that when c ˙ = 0 or c = c ¯ , the system reduces to a standard prey model with a Holling Type II increase in birth rate in response to increasing mean trait value [25] . In the results reported below , we observe that all dynamical variables remain bounded as long as parameter values are chosen such that the predator density does not equilibrate to zero . This is a direct consequence of our use of saturating Holling Type II functional forms in Eqs ( 7 ) and ( 8 ) , which prevent the fitness landscape from increasing without bound at large c , c ¯ and also ensure that the predator and prey densities do not jointly diverge . That the dynamics should stay bounded due to saturating terms is justified by empirical studies of predator-prey systems [34 , 35]; moreover , other saturating functional forms are expected to yield similar results if equivalent parameter values are chosen [33 , 36] . The nonlinear dependence of the mortality rate Eq ( 8 ) on the trait is based on mechanistic models of mortality with individual variation [19 , 37 , 38] . The specific choice of a quartic in Eq ( 8 ) allows the fitness function r to have a varying number of real roots and local maxima in the domain c , c ¯ > 0 , affording the system dynamical freedom not typically possible in predator prey models with constant or linear prey fitness—in particular , for different values of k2 , k4 the fitness landscape can have a single optimal phenotype , multiple optimal phenotypes , or no optimal intermediate values . Because any even , continuous form for the fitness landscape can be approximated using a finite number of terms in its Taylor series around c = 0 , our choice of a quartic form simply constitutes truncation of this expansion at the quartic order in order to include the simplest case in which the fitness function admits multiple local maxima—for this reason , a quartic will always represent the leading-order series expansion of a fitness landscape with multiple local maxima . Below , we observe numerically that ∣ c - c ¯ ∣ < 1 , ex post facto justifying truncation of the higher order terms in this series expansion . However , if the trait value c was strictly bounded to only take non-zero values on a finite interval ( as opposed to the entire real line ) , then a second-order , quadratic fitness landscape would be sufficient to admit multiple local maxima ( at the edges of the interval ) [14] . However , the choice here of an unbounded trait value c avoids creating boundary effects , and it has little consequence due to the steep decay of the quartic function at large values of |c| , which effectively confines the possible values of c ¯ accessible by the system . In physics , similar reasons—unbounded domains , multiple local optima , and continuity—typically justify the use of quartic free energy functions in minimal models of systems exhibiting multiple energetic optima , such as the Ginzberg-Landau free energy used in models of superconducting phase transitions [39] . We note that the birth rate Eq ( 7 ) contributes a density-dependent term to the fitness function even in the absence of predation ( y = 0 ) [21] . Unlike the death rate function , the effect of the individual trait value on this term is directional: the sign of c - c ¯ determines whether birth rates increase or decrease . As the population density x increases , the effect of these directional effects is amplified , consistent with the observed effect of intraspecific competition and crowding in experimental studies of evolution [40 , 41] . The chaotic dynamics reported below arise from this density-dependent term because the term prevents the Jacobian of the system ( 2 ) , ( 3 ) and ( 4 ) from having a row and column with all zeros away from the diagonal; in this case , the prey trait ( and thus evolutionary dynamics ) would be uncoupled from the rest of the system , and would thus relax to a stable equilibrium ( as is necessary for a first-order single-variable equation ) . In that case , c ¯ would essentially remain fixed and the predator-prey dynamics would become two-dimensional in x and y , precluding chaos . For similar reasons , density-dependent selection has been found to be necessary for chaos in some discrete-time evolutionary models , for which chaotic dynamics require a certain minimum degree of association between the fitness and the trait frequencies [42] . Inserting Eqs ( 5 ) , ( 7 ) and ( 8 ) , into Eq ( 1 ) results in a final fitness function of the form r ( x , y , c ¯ , c ) = a 1 c ¯ 1 + b 1 c ¯ ( 1 - k 1 x ( c - c ¯ ) ) - d 1 ( 1 - k 2 ( c 2 - c ¯ 2 ) + k 4 ( c 4 - c ¯ 4 ) ) - a 2 x y 1 + b 2 x . ( 9 ) This fitness landscape is shown in Fig 1B , for typical parameter values and predator and prey densities used in the numerical results below . Depending on the current predator and prey densities , the local maximum of the system can appear in two different locations , which directly affects the dynamics described in the next section . Inserting Eq ( 9 ) into Eqs ( 2 ) , ( 3 ) and ( 4 ) results in a final form for the dynamical equations , x ˙ = x ( a 1 c ¯ 1 + b 1 c ¯ - a 2 y 1 + b 2 x - d 1 ) ( 10 ) y ˙ = y ( y a a 2 x 1 + b 2 x - d 2 ) ( 11 ) c ¯ ˙ = c ¯ V ( ( 2 k 2 d 1 ) - ( 4 k 4 d 1 ) c ¯ 2 - ( a 1 k 1 ) x 1 + b 1 c ¯ ) . ( 12 ) Due to the Holling coupling terms , the form of these equations qualitatively resembles models of vertical , tritrophic food webs—the mean trait value c ¯ affects the growth rate of the prey , which in turn affects the growth rate of the predator [24 , 32 , 43] . The coupling parameter ya introduces asymmetry into the competition when ya ≠ 1; however , it essentially acts as a scale factor that only affects the amplitude of the y cycles and equilibria rather than the dynamics . Additionally , because the predator-prey interaction term Eq ( 5 ) is unaffected by the trait , our model contains no triple-product x y c ¯ interaction terms , which typically stabilize the dynamics .
For our analysis of the system ( 10 ) , ( 11 ) and ( 12 ) , we first consider the case where evolution proceeds very slowly relative to population dynamics . In the case of both no evolution ( V = 0 ) and no predation ( y = 0 ) , the prey growth Eq ( 10 ) advances along the one-dimensional nullcline y ˙ , c ¯ ˙ = 0 , y = 0 . Depending on whether the fixed mean trait value c ¯ exceeds a critical value ( c ¯ † ≡ d 1 / ( a 1 - b 1 d 1 ) ) , the prey density will either grow exponentially ( c ¯ > c ¯ † ) or collapse exponentially ( c ¯ < c ¯ † ) because the constant c ¯ remains too low to sustain the prey population in the absence of evolutionary adaptation . The requirement that c ¯ > c ¯ † carries over to the case where a predator is added to the system but evolutionary dynamics remain fixed , corresponding to a two dimensional system advancing along the two-dimensional nullcline c ¯ ˙ = 0 . In this case , as long as c ¯ > c ¯ † , the prey density can exhibit continuous growth or cycling depending in the relative magnitudes of the various parameters in Eqs ( 10 ) and ( 11 ) . The appearance and disappearance of these cycles is determined by a series of bifurcations that depends on the values of c ¯ and b1 , b2 relative to the remaining parameters a1 , a2 , d1 , d2 ( S1A Appendix ) . In the full three-variable system ( 10 ) , ( 11 ) and ( 12 ) , c ¯ passes through a range of values as time progresses , resulting in more complex dynamics than those observed in the two-dimensional case . For very small values of V , the evolutionary dynamics c ¯ ˙ are slow enough that the system approaches the equilibrium predicted by the two-variable model with c ¯ constant . The predator and prey densities initially grow , but the prey trait value does not change fast enough for the prey population growth to sustain—eventually resulting in extinction of both the predator and prey . However , if V takes a slightly larger value , so that the mean trait value can gradually change with a growing prey population density ( due to the density-dependent term in Eq ( 10 ) ) , then the population dynamics begin to display regular cycling with fixed frequencies and amplitudes ( Fig 2A , top ) . This corresponds to a case where the evolutionary dynamics are slow compared to the ecological dynamics , but not so slow as to be completely negligible . Finally , when V is the same order of magnitude as the parameters governing the ecological dynamics , the irregular cycles become fully chaotic , with both amplitudes and frequencies that vary widely over even relatively short time intervals ( Fig 2A , bottom ) . Typically , the large V case would correspond to circumstances in which the prey population develops a large standing genetic variation [10 , 44] . That the dynamics are chaotic , rather than quasi-periodic , is suggested by the presence of multiple broad , unevenly-spaced peaks in the power spectrum [45] ( Figure A in S1E Appendix ) , as well as by numerical tabulation of the Lyapunov spectrum ( described further below ) . Due to the hierarchical coupling of Eqs ( 10 ) , ( 11 ) and ( 12 ) , when plotted in three-dimensions the chaotic dynamics settle onto a strange attractor that resembles the “teacup” attractor found in models of tritrophic food webs [24 , 46] ( Fig 2B ) . Poincare sections though various planes of the teacup all appear linear , suggesting that the strange attractor is effectively two-dimensional—consistent with pairings of timescales associated with different dynamical variables at different points in the process ( Figure B in S1E Appendix ) . In the “rim” of the teacup , the predator density changes slowly relative to the prey density and mean trait value . This is visible in a projection of the attractor into the x - c ¯ plane ( Fig 2B , bottom inset ) . However , in the “handle” of the teacup , the mean trait value varies slowly relative to the ecological dynamics ( c ¯ ˙ ≈ 0 ) , resulting in dynamics that qualitatively resemble the two-dimensional “reduced” system described above for various fixed values of c ¯ ( Fig 2B , top inset ) . The structure of the attractor suggests that the prey alternately enters periods of evolutionary change and periods of competition with the predator . A closer inspection of a typical transition reveals that this “two timescale” dynamical separation is responsible for the appearance of chaos in the system ( Fig 3A ) . As the system explores configuration space , it reaches a metastable configuration corresponding to a high mean trait value c ¯ , which causes the prey density to nearly equilibrate to a low density due to the negative density-dependent term in Eq ( 10 ) . During this period ( the “rim” of the teacup ) , the predator density gradually declines due to the lack of prey . However , once the predator density becomes sufficiently small , the prey population undergoes a sudden population increase , which triggers a period of rapid cycling in the system ( the “handle” of the teacup attractor ) . During this time , the predator density continuously increases , causing an equivalent decrease in the prey density that resets the cycle to the metastable state . The sudden increase in the prey population at low predator densities can be understood from how the fitness function r ( from Eq ( 9 ) ) changes over time . Fig 3B shows a kymograph of the log-scaled fitness Eq ( 9 ) as a function of individual trait values c , across each timepoint and corresponding set of ( x , y , c ¯ ) values given in panel A . Overlaid on this time-dependent fitness landscape are curves indicating the instantaneous location of the local maximum ( black ) and minimum ( white ) . By comparing panels A and B , it is apparent that the mean trait value during the “metastable” period of the dynamics stays near the local maximum of the fitness function , which barely varies as the predator density y changes . However , when y ( t ) ≈ 0 . 25 , the fitness function changes so that the local minimum and local maximum merge and disappear from the system , leading to a new maximum spontaneously appearing at c = 0 . Because V is large enough ( for these parameters ) that the gradient dynamics occur over timescales comparable to the competition dynamics , the system tends to move rapidly towards this new maximum in the fitness landscape , resulting in rapidly-changing dynamics in x and c ¯ . Importantly , because of the symmetric coupling of the prey fitness landscape r to the prey density x , this rapid motion resets the fitness landscape so that the maximum once again occurs at the original value , resulting in a period of rapid cycling . The fitness landscape at two representative timepoints in the dynamics is shown in Fig 3C . That the maxima in the fitness Function ( 9 ) suddenly change locations with continuous variation in x , y is a direct consequence of the use of a high-order ( here , quartic ) polynomial in c to describe the fitness landscape . The quartic represents the simplest analytic function that admits more than one local maxima in its domain , and the number of local maxima is governed by the relative signs of the coefficients of the ( c 2 - c ¯ 2 ) and ( c 4 - c ¯ 4 ) terms in Eq ( 9 ) , which change when the system enters the rapid cycling portion of the chaotic dynamics at t = 500 in Fig 3A . This transition marks the mean prey trait switching from being drawn ( via the gradient dynamics ) to a single fitness peak at an intermediate value of the trait ceq ≈ 0 . 707 to being drawn instead to one of two peaks: the existing peak , or a new peak at the origin . Thus the metastable period of the dynamics corresponds to a period of stabilizing selection: if the fitness landscape were frozen in time during this period , then an ensemble of prey would all evolve to a single intermediate trait value corresponding to the location of the global maximum . Conversely , if the fitness landscape were held fixed in the multipeaked form it develops during a period of rapid cycling , given sufficient time an ensemble of prey would evolve towards subpopulations with trait values at the location of each local fitness maximum—representing disruptive selection . That the fitness landscape does not remain fixed for extended durations in either a stabilizing or disruptive state—but rather switches between the two states due to the prey density-dependent term in Eq ( 9 ) — underlies the onset of chaotic cycling in the model . Density-dependent feedback similarly served to induce chaos in many early discrete-time ecosystem models [23] . However , the “two timescale” form of the chaotic dynamics and strange attractor here is a direct result of reversible transitions between stabilizing and disruptive selection . If the assumptions underlying the gradient dynamics model do not strictly hold—if the additive genetic variance V slowly varies via an additional dynamical equation , or if the initial conditions are such that significant skewness would be expected to persist in the phenotypic distribution , then the chaotic dynamics studied here would be transient rather than indefinite . While the general stability analysis shown above ( and in the S1 Appendix ) would still hold , additional dynamical equations for V or for high-order moments of the trait distribution would introduce additional constraints on the values of the parameters , which would ( in general ) increase the opportunities for the dynamics to become unstable and lead to diverging predator or prey densities . However , in some cases these additional effects may actually serve to stabilize the system against both chaos and divergence . For example , if additional series terms were included in Eq ( 8 ) such that the dependence of mortality rate on c ¯ and c had an upper asymptote [25] , then c ¯ ˙ = 0 would be true for a larger range of parameter values—resulting in the dynamical system remaining planar for a larger range of initial conditions and parameter values , precluding chaos . The transition between stabilizing and disruptive selection that occurs when the system enters a period of chaotic cycling is strongly reminiscent of a first-order phase transition . Many physical systems can be described in terms of a free energy landscape , the negative gradient of which determines the forces acting on the system . Minima of the free energy landscape correspond to equilibrium points of the system , which the dynamical variables will approach with first-order dynamics in an overdamped limit . When a physical system undergoes a phase transition—a qualitative change in its properties as a single “control” parameter , an externally-manipulable variable such as temperature , is smoothly varied—the transition can be understood in terms of how the control parameter changes the shape of the free energy landscape . The Landau free energy model represents the simplest mathematical framework for studying such phase transitions: a one-dimensional free energy landscape is defined as a function of the control parameter and an additional independent variable , the “order parameter , ” a derived quantity ( such as particle density or net magnetization ) with respect to which the free energy can have local minima or maxima . In a first-order phase transition in the Landau model , as the control parameter monotonically changes the relative depth of a local minimum at the origin decreases , until a new local minimum spontaneously appears at a fixed nonzero value of the order parameter—resulting in dynamics that suddenly move towards the new minimum , creating discontinuities in thermodynamic properties of the system such as the entropy [47] . First-order phase transitions are universal physical models , which have been used to describe a broad range of processes spanning from superconductor breakdown [48] to primordial black hole formation in the early universe [49] . In the predator-prey model with prey evolution , the fitness function is analogous to the free energy , with the individual trait value c serving as the “order parameter” for the system . The control parameter for the transition is the prey density , x , which directly couples into the dynamics via the density-dependent term in Eq ( 7 ) . Because the fitness consists of a linear combination of this term in Eq ( 7 ) and a quartic landscape Eq ( 8 ) , the changing prey density “tilts” the landscape and provokes the appearance of the additional , disruptive peak visible in Fig 3C . The appearance and disappearance of local maxima as the system switches between stabilizing and disruptive selection is thus analogous to a first-order phase transition , with chaotic dynamics being a consequence of repeated increases and decreases of the control parameter x above and below the critical prey densities x* , x** at which the phase transition occurs . Similar chaotic dynamics emerge from repeated first-order phase transitions in networks of coupled oscillators , which may alternate between synchronized and incoherent states that resemble the “metastable” and “rapid cycling” portions of the predator-prey dynamics [50] . The analogy between a first-order phase transition and the onset of disruptive selection can be used to study the chaotic dynamics in terms of dynamical hysteresis , a defining feature of such phase transitions [47] . For different values of x , the three equilibria corresponding to the locations of the local minima and maxima of the fitness landscape , ceq , can be calculated from the roots of the cubic in Eq ( 12 ) . The resulting plots of ceq vs x in Fig 4 are generated by solving for the roots in the limit of fast prey equilibration , c ¯ → c e q , which holds in the vicinity of the equilibria ( S1B Appendix ) . The entry into the transient chaotic cycling occurs when x increases gradually and shifts ceq with it; x eventually attains a critical value x* ( x* ≈ 0 . 45 for the parameters used in the figures ) , causing ceq to jump from its first critical value c* to the origin ( the red “forward” branch in Fig 4 ) . This jump causes rapid re-equilibration of c ¯ ( t ) , resulting in the rapid entry into cycling observable in Fig 3A . However , x cannot increase indefinitely due to predation; rather , it decreases until it reaches a second critical value x** , at which point ceq jumps back from the origin to a positive value ( the blue “return” branch in Fig 4; x** = 0 . 192 for these parameter values ) . This second critical point marks the return to the metastable dynamics in Fig 3A . This asymmetry in the forward and backwards dynamics of x lead to dynamical time-irreversibility ( hysteresis ) and the jagged , sawtooth-like cycles visible in the dynamics of the full system . Because the second jump in ceq is steeper , the parts of the trajectories associated with the “return” transition in Fig 3A appear steeper . Additionally , the maximum value obtained by c ¯ ( t ) anywhere on the attractor , c e q m a x , is determined by the limiting value of ceq as x → 0 . Analytic values for c e q m a x , as well as ( x* , c* ) and ( x** , c** ) , are derived in the S1 Appendix , and their corresponding numerical values are overlaid in each panel of Fig 3 . Comparing the values of c e q m a x , x* , c* , x** , c** to the dynamics of the system in Fig 3 , it is apparent that calculation of critical points under the fast-evolution approximation correctly predicts key properties of the chaotic dynamics such as the maximum value attained by c ¯ ( t ) , the quasi-static value c ¯ during the “metastable” period before chaotic cycling , and the approximate values at which x ( t ) enters and exits the rapid cycling portion of the dynamics . Thus the analogy between the fitness function and the Landau free energy provides insight into the dynamics of the chaotic ecosystem . Moreover , for intermediate values of the prey density at which the two local maxima are equal heights , the relative fitnesses of the two trait values are equal ( c * = c e q * * ) and so both phenotypes would be equally favorable for the prey population . This is analogous to the coexistence of two phases during intermediate portions of a phase transition . As the prey density x approaches either critical value , the fitness landscape shallows and the dynamics begin to exhibit a form of “critical slowing down” associated with the onset of the phase transition—here represented by the relatively slow dynamics along the flattened handle of the teacup in Fig 2B . The chaotic dynamics reported here are emergent; they result from predation reducing the fitness of intermediate trait values , which restructures the fitness landscape in a manner that later reverses as the predator density decreases . However , here , as in other models , the presence of chaos has other long-term implications for the ecosystem that would not be relevant in systems with only limit cycles or point equilibria . The chaotic dynamics associated with fast evolutionary dynamics ( large V , or high genetic variance [20 , 21] ) impose a statistical structure on the deterministic problem: given a sufficiently long observation time , a trajectory along the strange attractor will sample every point on the attractor [45] . For the predator-prey model studied here , ergodicity in the system is established by using a numerical scheme to estimate the spectrum of global Lyapunov exponents , which measure the rate at which two infinitesimally separated points in the configuration space move apart over time along the three dimensions present in the system . Simulations with varying timescales that start at various initial conditions on the attractor converge to the same estimates of the Lyapunov exponents , implying ergodicity [45] ( S1C Appendix ) . A similar technique has been used to establish ergodicity in some models of chaotic multitropic food webs [51] . The Lyapunov spectrum can , in turn , be used to determine the Kaplan-Yorke fractal dimension of the attractor , DKY ≈ 2 . 01 , which accounts for the two-dimensional shape of the full attractor ( Fig 2B ) and linear shapes of its Poincare sections ( Figure B in S1E Appendix ) discussed above . Due to the ergodic property of chaotic attractors , one typical interpretation of their appearance in ecological dynamics is that they allow a sort of bet-hedging across timescales , conferring ecological stability against sudden external perturbations [23 , 52 , 53] . In the presence of external factors not explicitly included in the model , especially non-ergodic processes such as climate variation , a chaotic ecosystem will present a variety of different ratios of predator and prey concentrations at different times , ensuring robustness through biodiversity [54–56] . Moreover , in spatially-extended models in which different subpopulations may simultaneously exist at different points in the chaotic attractor , the chaotic attractor can allow one subgroup to recover from a sudden environmental catastrophe or to expand its range to a new location when favorable conditions spontaneously arise . In general , chaotic dynamics may present an adaptive benefit by making ecological networks robust , for example by preventing sudden exclusion of a keystone species [57] . Here , we suggest that chaos produces an additional effect when it arises due to eco-evolutionary dynamics: it creates a broad distribution of “windows” of time during which sympatric speciation may occur . The dynamics imposed in the predator-prey model in Eqs 10–12 do not explicitly include speciation , which represents an irreversible process in which the prey bifurcates into multiple co-evolving types ( hence changing the number of distinct dependent variables present in the dynamics ) . This would violate the underlying conditions of the gradient dynamics model by creating a bimodal prey density vs trait distribution with substantial skew . However , this process would typically occur during periods of disruptive selection , during which speciation could occur either through assortative mating or through spatial isolation of phenotypically homogeneous subpopulations . For this reason , the statistical property of the chaotic dynamics that is relevant to speciation is the distribution of time that the fitness function spends in the disruptive state , or the “epochs” of disruptive selection . This represents the distribution of opportunities for speciation to first occur in the system , at which point ergodicity would be broken and the dynamical equations would no longer remain valid . In many models of evolutionary processes , the distribution of epochs of dominance for certain phenotypes has rich statistical structure , including a heavy-tail distribution that some authors have taken to indicate the presence of self-organized criticality [58 , 59] . These epochs can be detected by defining the “local” Lyapunov exponents , which represent the three eigenvalues of the Jacobian matrix for the Systems ( 10 ) , ( 11 ) and ( 12 ) evaluated at each point along a trajectory in the chaotic attractor [60 , 61] , λ i ( t ) ≡ eig ( ∂ x ˙ ( t ) ∂ x ( t ) ) where x = ( x ( t ) , y ( t ) , c ¯ ( t ) ) and i ∈ {1 , 2 , 3} . Plots of these local Lyapunov exponents during a typical period of metastable dynamics followed by cycling are shown in Fig 5A . Positive values suggest chaotic dynamics , while negative values suggest that nearby trajectories converge . The largest local Lyapunov exponent typically dominates the dynamics . Consistent with the destabilizing nature of disruptive selection , the largest local Lyapunov exponent increases dramatically during periods in which the fitness function has multiple local maxima . For this reason , the length of these long excursions in which the largest local Lyapunov exponent significantly exceeds zero can be used to estimate the distribution lengths of periods of disruptive selection ( Fig 5B ) , based on a very long sample of the dynamics along the strange attractor . The broadness of this distribution suggests that speciation events could occur over a range of timescales in the system ( for example , via hybrid breakdown ) , representing a potential signature of a chaotic past that could be observed in descendant populations with non-chaotic dynamics . Despite the large fluctuations in the maximum value of the local Lyapunov exponents , the largest global Lyapunov exponent is only barely larger than zero , λmax ≈ 0 . 003 . Similar behavior has been reported a real-world ecosystem consisting of competing species in a rocky intertidal environment , in which a small global Lyapunov exponent paired with a fluctuating largest local Lyapunov exponent was taken to suggest that the ecosystem had adapted to “the edge of chaos . ” [51] A similar case has been reported experimentally in populations of voles in Northern Europe that appear to switch between chaotic and stable periods [62] . In that system , it was noted that occasional switches to chaotic dynamics serve to amplify the effect of environmental fluctuations , further suggesting that the irregular spacing of epochs resulting from chaotic dynamics may allow a range of timescales over which speciation may occur under temporally-varying external conditions . If the underlying assumptions of the gradient dynamics model do not hold—such as V slowly varys in time or the trait distribution retains significant skewness—then the chaotic dynamics would be non-ergodic , causing the system to eventually exit the chaotic attractor and either diverge or settle to a fixed point or limit cycle . If the timescale of exit from the chaotic attractor is much longer than the average time between periods of rapid cycling ( as determined , for example , by the peak in the power spectrum in Figure A of S1E Appendix ) , then the dynamics will demonstrate transient chaos , and the form of the distribution in Fig 5B will be roughly the same due to quasi-ergodicity . However , if the timescale of transience is much shorter , the dynamics may not fully sample the attractor , resulting in the distribution of epochs of disruptive selection being strongly dependent on the initial conditions .
We have shown that a simple two-species predator-prey ecosystem can display rich dynamical complexity when the prey evolves in response to predation , and that this complexity can be understood by analyzing the temporal variation of the fitness landscape . Future theoretical work will establish whether these dynamics qualitatively change when the predator also evolves over timescale comparable to the prey evolution [63] . Such predator-prey co-evolutionary systems have been shown to exhibit a distinct route to chaos , due a desynchronization of the predator and prey adaptation that comprises a form of the “Red Queen” effect [64 , 65] . One limitation of our model arises from the form of the evolutionary dynamics Eq ( 4 ) , which assume that the dynamics of the trait distribution can be adequately described by a mean trait evolution equation . S1D Appendix compares the results found here to those generated by a formulation of the problem in terms of a full integro-differential equation , and finds general agreement for the fitness landscape studied here . However , for more complicated fitness landscapes these conditions may not hold , requiring more advanced models that introduce additional dynamical equations to account for various effects such as non-constant additive genetic variance [30 , 66 , 67] . In such models , chaos may appear as a transient in the dynamics before the dynamical variables approach an equilibrium point or limit cycle . Our findings for the minimal model studied here have implications for a wide variety of eco-evolutionary systems , because they suggest that even a minimal deterministic model can exhibit unstable cycling and chaos—effects that would typically become more pronounced when more species are added to the system [22 , 23] . The mechanism by which chaos appears in our system is generic , resulting purely from changes in the number of local maxima in the fitness landscape , suggesting the applicability of our findings to observational systems ( such as bacteria and viruses in microenvironments ) in which the fitness landscape can be monitored , but not necessarily all of the underlying species interrelationships [68] . For these systems , recent advances in genetic barcoding of entire microbial communities [69 , 70] may allow direct observation of the role of dynamic fitness landscapes in creating opportunities for sympatric speciation . In addition to being an emergent property of the underlying species interactions , we suggest here that these chaotic properties may confer adaptive benefits via community robustness , either by enforcing phenotypic diversity or by preventing environmental variation from fully excluding a single species . The system described here also represents an example of a small ecosystem that adapts towards the “edge of chaos” , which can further adjust how the system responds to external perturbations [71 , 72] . Potential experimental systems in which the adaptive role of eco-evolutionary chaos may be explored include phytoplanktonic ecosystems , which can be isolated in the laboratory and which are known to to maintain biodiversity using chaotic effects [54] . In particular , it would be interesting to determine whether non-synchronized replicates of experimentally-controlled chaotic ecosystems could recover from a synchronized perturbation ( i . e . temporary salinity shock ) more quickly than non-chaotic controls [74]—suggesting that the ability of chaotic systems to continuously sample a wide variety of dynamical conditions confers robustness . In these systems , reconstruction of of an experimental chaotic attractor derived from lagged coordinate embedding [43] could yield insight into whether chaos arises due to changes in the general topology of the fitness landscape , which would result in a nearly two-dimensional attractor due to distinct timescales associated with stabilizing and disruptive effects . Moreover , the underlying cause of the chaotic dynamics—a reversible transition between stabilizing and disruptive selection—is mathematically analogous to the change in the shape of the free energy landscape during a first-order phase transition in thermodynamics . Our findings thus fit within more general extensions of mathematical theories of evolution that include formalism from statistical and condensed matter physics [8 , 58 , 72 , 73] , suggesting that universal mechanisms may underly subtle transient properties observed in many natural ecosystems , including hysteresis and dynamical robustness [75] . | Evolution is usually thought to occur very gradually , taking millennia or longer in order to appreciably affect a species' survival mechanisms . Conversely , demographic shifts due to predator invasion or environmental change can occur relatively quickly , creating abrupt and lasting effects on a species survival . However , recent studies of ecosystems ranging from the microbiome to oceanic predators have suggested that evolutionary and ecological processes can often occur over comparable timescales—necessitating that the two be addressed within a single , unified theoretical framework . Here , we show that when evolutionary effects are added to a minimal model of two competing species , the resulting ecosystem displays erratic and chaotic dynamics not typically observed in such systems . We then show that these chaotic dynamics arise from a subtle analogy between the evolutionary concept of fitness , and the concept of the free energy in thermodynamical systems . This analogy proves useful for understanding quantitatively how the concept of a changing fitness landscape can confer robustness to an ecosystem , as well as how unusual effects such as history-dependence can be important in complex real-world ecosystems . Our results predict a potential signature of a chaotic past in the distribution of timescales over which new species can emerge during the competitive dynamics , a potential waypoint for future experimental work in closed ecosystems with controlled fitness landscapes . | [
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] | 2017 | A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape |
Sporadic Creutzfeldt-Jakob disease ( sCJD ) cases are currently subclassified according to the methionine/valine polymorphism at codon 129 of the PRNP gene and the proteinase K ( PK ) digested abnormal prion protein ( PrPres ) identified on Western blotting ( type 1 or type 2 ) . These biochemically distinct PrPres types have been considered to represent potential distinct prion strains . However , since cases of CJD show co-occurrence of type 1 and type 2 PrPres in the brain , the basis of this classification system and its relationship to agent strain are under discussion . Different brain areas from 41 sCJD and 12 iatrogenic CJD ( iCJD ) cases were investigated , using Western blotting for PrPres and two other biochemical assays reflecting the behaviour of the disease-associated form of the prion protein ( PrPSc ) under variable PK digestion conditions . In 30% of cases , both type 1 and type 2 PrPres were identified . Despite this , the other two biochemical assays found that PrPSc from an individual patient demonstrated uniform biochemical properties . Moreover , in sCJD , four distinct biochemical PrPSc subgroups were identified that correlated with the current sCJD clinico-pathological classification . In iCJD , four similar biochemical clusters were observed , but these did not correlate to any particular PRNP 129 polymorphism or western blot PrPres pattern . The identification of four different PrPSc biochemical subgroups in sCJD and iCJD , irrespective of the PRNP polymorphism at codon 129 and the PrPres isoform provides an alternative biochemical definition of PrPSc diversity and new insight in the perception of Human TSE agents variability .
Transmissible spongiform encephalopathies ( TSE ) are neurodegenerative disorders affecting a large spectrum of mammalian species that share similar characteristics , including a long incubation period ( which in man may be measured in decades ) and a progressive clinical course resulting in death [1] . The most common form of human TSE is an idiopathic disorder named sporadic Creutzfeldt-Jakob disease ( sCJD ) . sCJD is not a uniform disorder in terms of its clinical and neuropathological phenotype . It remains unclear whether this variability is related to variations in the causative TSE agent strains , or to the influence of the methionine/valine polymorphism at codon 129 of the PRNP [2] , [3] . A key event in the pathogenesis of TSE is the conversion of the normal cellular prion protein ( PrPC , which is encoded by the PRNP gene ) into an abnormal disease-associated isoform ( PrPSc ) in tissues of infected individuals . Conversion of PrPC into PrPSc is a post-translational process involving structural modifications of the protein and resulting in a higher β-sheet content [4] . PrPC is completely degraded after controlled digestion with proteinase K ( PK ) in the presence of detergents . PrPSc is N-terminally truncated under such conditions , resulting in a PK resistant core , termed PrPres [5] . PrPres , also named PrP 27–30 , is a disease marker for TSE and the presence of PrPSc seems to correlate with infectivity [5] , [6] . According to the prion hypothesis , PrPSc is the infectious agent in TSE [7] and , in the last decades , several lines of evidence have indicated that particular biochemical properties of PrPSc , such as solubility in N-lauroylsarcosine , PK resistance and electromobility in western blotting ( WB ) can be used to distinguish between different prion agents or strains [8] , [9] . In sCJD , two major PrPres types have been described by WB: in type 1 PrPres , the unglycosylated fragment is 21 kDa , while in type 2 , the apparent molecular weight of this unglycosylated fragment is 19 kDa [3] . Protein N-terminal sequencing revealed that type 2 isoform derives from preferential cleavage of the protein during PK digestion at amino acid 97 , while in type 1 preferential cleavage occurs at amino acid 82 [10] . sCJD cases can be subclassified according the PrPres isoform and the PRNP codon 129 methionine ( M ) /valine ( V ) polymorphism , resulting in 6 major subypes: MM1 , MM2 , MV1 , MV2 , VV1 and VV2 . Interestingly , these subtypes appear to carry distinct pathological and clinical features , [2] , [3] , and it has been proposed that type 1 and type 2 isoforms in sCJD might correspond to different TSE agent strains . However , the description of PrPres isoforms which appear to be distinct from type 1 and type 2 , and the increasing number of reports describing the coexistence of type 1 and type 2 PrPres in different areas or the same area in the brain from a single sCJD patient , calls into questions the subclassification system described above in sCJD [11]–[14] . Here , in a large group of cases including 41 sCJD and 12 iCJD patients , we confirmed that type 1 and type 2 PrPres can be observed as a mixture in a substantial number of patients . However , using two novel assays described here , PrPSc from these patients with mixed PrPres types are homogeneous irrespective of the brain area considered . Moreover , based on these novel PrPSc biochemical properties , four distinct subgroups were observed in our cohort of sCJD patients . Similar findings were observed in iCJD cases from two countries and differing sources of infection .
A total of 41 French cases of sCJD , each of which had frozen tissue ( 2–4 g ) available from preferentially 5 brain regions: ( occipital , temporal and frontal cortex , cerebellum and the caudate nucleus ) , were included in this study . All six currently defined classes of s-CJD patients ( MM1-MM2-MV1-MV2-VV1-VV2 ) were represented in our panel ( Table 1 ) . Moreover , 12 cases of iatrogenic CJD ( iCJD ) , linked to contamination by growth hormone ( GH ) or dura mater grafts , from patients originating either from United Kingdom ( UK ) or France , were also investigated ( Table 1 ) . None of the patients had a familial history of prion disease and , in each case , the entire PRNP coding sequence was analyzed , either by denaturating gradient gel electrophoresis and/or direct sequencing . All patients died from CJD during the period 1997–2004 . Additionally , five cases of Alzheimer's disease were included as non-CJD controls . In all cases , informed consent for research was obtained and the material used had appropriate ethical approval for use in this project . For each sample , a 20% brain homogenate ( weight/volume ) in 5% glucose was prepared using a high-speed homogenizer ( TeSeE Precess 48 system ) . The homogenates were then filtered through a 20 Gauge needle before storage at −80°C . Various factors have been reported to influence the results of PrPres analysis by WB , including tissue pH and the effect of Cu2+ ions [15]–[17] . In order to limit these factors , each homogenate was diluted a 100-fold in a single non-CJD control brain homogenate prior to further investigation . A WB kit ( TeSeE WB kit Bio-Rad ) was used following the manufacturer's recommendations . Three different monoclonal PrP-specific antibodies were used for PrP detection: Sha31 ( 1 µg/ml ) [18] , 8G8 ( 4 µg/ml ) [19] and 12B2 ( 4 µg/ml ) [20] , which recognized the amino acid sequences YEDRYYRE ( 145–152 ) , SQWNKPSK ( 97–104 ) and WGQGG ( 89–93 ) respectively . After incubation with goat anti-mouse IgG antibody conjugated to horseradish peroxidase , signal was visualized using the ECL western blotting detection system by enhanced chemiluminescent reaction ( ECL , Amersham ) . Molecular weights were determined with a standard protein preparation ( MagicMark , Invitrogen ) . PrPSc detection was carried out using sandwich ELISA test ( TeSeE CJD , Bio-Rad ) used following the manufacturer's recommendations . The assay protocol includes a preliminary purification of the PrPSc ( TeSeE purification kit ) consisting in ( i ) digestion of PrPC with PK , ( ii ) precipitation of PrPSc by buffer B and centrifugation , ( iii ) denaturation of PrPSc in buffer C at 100°C , before immuno-enzymatic detection . In this ELISA , the capture antibody 3B5 recognizes the octarepeat region of PrP [19] , while the detection antibody 12F10 binds to the core part of the protein [18] . PK resistance of the PrPSc portion recognized in the ELISA test was determined by measurement of the ELISA specific signal recovered from a series of homogenate aliquots digested with different concentrations of PK in buffer A′ reagent ( TeSeE Sheep/Goat purification kit ) . Each sample was first diluted in normal brain homogenate ( between 100- and 10 , 000-fold ) until obtaining a signal between 1 . 5 and 2 absorbance units after digestion with 50 µg/ml of PK . Triplicate of equilibrated samples were then submitted to a PK digestion with concentrations ranging from 50 to 500 µg/ml , before PrPSc precipitation and ELISA detection . Results were expressed as the percentage of residual signal when compared to the 50 µg/ml PK digestion ( lowest PK concentration ) . In each assay , two standardized controls ( scrapie and BSE from sheep ) were used as an internal standard . About 20% of samples were randomly selected and submitted to two independent tests separated in time as to assess inter-assay variation . The ELISA test used in this study was adapted from the Bio-Rad TeSeE test , validated at CEA for EU strain typing studies in ruminants and designed to distinguish BSE in sheep from scrapie . The principle was to measure conformational variations in PrPSc by applying two differential PK digestions under the modification of detergent conditions ( SDS sensitivity ) . For each sample , PK digestion was performed under two conditions: ( i ) two aliquots of 250 µl of 20% homogenate were mixed either with 250 µl of A reagent ( TeSeE purification kit ) containing 20 µg of PK , ( ii ) with 250 µl of A′ reagent ( N-lauroylsarcosine sodium salt 5% ( W/V ) , sodium dodecyl sulfate 5% ( W/V ) containing 55 µg of PK , All the tubes were then mixed by inversion 10 times and incubated at 37°C ( in a water bath ) for exactly 15 min . Subsequently , 250 µl of reagent B ( Bio-Rad purification kit ) /PMSF ( final concentration 4 mM ) were added , mixed and the tubes were centrifuged for 5 minutes at 20 , 000 g at 20°C . Supernatants were discarded and tubes dried by inversion onto an absorbent paper for 5 min . Each pellet was denatured for 5 min at 100°C with 25 µl of C reagent ( Bio-Rad purification kit ) . The samples were diluted in 250 µL of R6 buffer containing 4 mM of serine protease inhibitor AEBSF ( 4-2-aminoethyl benzenesulfonyl fluoride hydrochloride ) , and , if desired , further serially diluted in R6 buffer . ELISA plates were then incubated for two hours at room temperature and , after three washes , antibody detection ( TeSeE CJD , Bio-Rad ) was added for two hours at 4°C . The ratio of the absorbance obtained in the two conditions ( A/A′ ) was calculated using appropriate dilutions providing absorbance measurements ranging from 0 . 5 to 2 . 5 absorbance units in A conditions . For each plate , the same three control samples ( one MM1 , one VV2 and one MM GH ) were included . To avoid inter-assay variations , final results were expressed as a normalized ratio established by dividing the ratio obtained for the analyzed sample by the one obtained for a VV2 sample selected as standard .
For each sCJD case , PrPres profile was determined from five brain areas using both Sha31 and 8G8 antibodies . A single PrPres type ( type 1 or type 2 ) was observed in investigated brain areas of most of the MM1 ( n = 11 ) , and all the areas from MV1 ( n = 8 ) , VV1 ( n = 1 ) and MM2 ( n = 3 ) sCJD cases of our panel . However , in several cases initially classified as MM1 ( n = 2 ) , and in a majority of VV2 ( n = 5 ) or MV2 ( n = 6 ) cases , some brain areas harboured mixed electrophoretic pattern characterized by two distinct bands at 19 and 21 kDa , indicating the coexistence of PrPres type 1 and type 2 ( Table 1 and Figure 1A ) . Moreover , in individual patients some brain areas were found to be type 1 , while another area could be found to be type 2 ( Table 1 and Figure 1A ) . Since both Sha31 and 8G8 gave similar results this phenomenon cannot be attributed to some antibody peculiarity in PrP recognition ( Figure 1B and 1C ) . Antibody 12B2 is specific for the amino acid sequence 89–93 that is located N-terminally of the type 2 cleavage site ( amino acid 97 ) . In principle , this antibody is unable to recognize type 2 PrPres . Systematic western blotting with 12B2 consistently demonstrated the presence of the 21 kDa band , characteristic for type 1 PrPres , in nearly all type 2 classified samples , regardless of the PRNP codon 129 polymorphism ( Figure 1D ) . In a limited number of type 2 samples , 12B2 failed to detect a type 1 band ( Figure 1E and 1F , lane 2 , 3 ) . Using Sha31 or 8G8 , mixed type 1/type 2 PrPres profiles were observed in several iCJD cases ( Figure 2A ) , regardless of their national origin or mode of infection . In most ( but not all ) samples initially classified as type 2 , the 12B2 antibody revealed the presence of a 21 kDa band , characteristic of type 1 PrPres ( Figure 2B ) . Together these findings point to the existence of variable amounts of type 1 PrPres molecules in all or nearly all type 2 classified patients ( Table 1 ) . In sCJD and iCJD patients who harboured a single WB PrPSc type in the different brain areas , as assessed by Sha31 , a single ELISA PK resistance profile ( Table 1 and Figure 3A ) and a comparable ratio in strain typing assay ( Table 1 and Figure 3B ) were observed in all brain areas . Surprisingly , in each patient harbouring both type 1 and 2 PrPres , either in the same or in different brain areas , a single ELISA PK digestion profile ( Table 1 and Figure 3C and 3D ) and a comparable signal ratio in strain typing assay ( Table 1 and Figure 3B ) was also observed , irrespective of region assayed . MM1 and VV2 samples but also MM2 and VV1 samples , which harboured similar apparent PrPSc content ( as assessed by ELISA ) were artificially mixed in different proportions . Using WB , a mixed type 1+2 profile could , or could not , be observed depending on the mixture proportions ( Figure 3E and 3F ) . Both PrPSc resistance ELISA assay ( Figure 3G and 3H ) and strain typing ELISA ( not shown ) were able to discriminate the different mixtures from the original isolates and from each other . These results clearly demonstrate that the uniformity of PrPSc biochemical properties , as demonstrated by both PrPSc resistance ELISA and strain typing ELISA , in patients harbouring different PrPres isoforms cannot be attributed to a lack of discriminative power of these techniques . Together , these data strongly indicate that , despite possible variations in PrPres type on WB analysis , patients with either sCJD or iCJD appear to harbour a single PrPSc isoform in their brain . According to the results from PrPSc PK resistance assay and strain typing ELISAs , sCJD patients could be split into four groups ( Table 1 , and Figure 3A and 3B ) . The first group was characterized by a strong PK resistance ( Figure 3A ) and a low ratio in strain typing assay ( Figure 3B ) . Group 1 could be readily differentiated from Group 2 which showed a higher sensitivity regarding PK digestion , as well as an increased signal ratio in strain typing assay , when compared to Group 1 . Two other PrPSc groups were also observed . Group 3 harboured an intermediate PK lability in the PrPSc resistance ELISA and ratio in the strain typing ELISA , when compared to Group 1 and 2 . Group 4 had a very high PK-sensitivity and ratio in the strain typing ELISA . No overlapping in PK resistance profile or ratio value in strain typing assay were observed between the four determined groups ( Table 1 ) . Group1 was composed of sCJD MM and MV patients , harbouring predominantly type 1 PrPres while Group 2 consisted in VV and MV patients harbouring predominantly type 2 or type 1+2 PrPres . Groups 3 and 4 were respectively composed with VV1 and MM2 patients from our sCJD panel . Striking differences were observed in the PrPSc properties between the different iCJD cases and all four groups relying on PrPSc signatures observed in sCJD cases were identified ( Table 1 , and Figures 3B and 4 ) . As it might have been expected from sCJD cases observations , Group 1 PrPSc properties was identified in MM1 UK dura mater graft patients ( n = 2 ) ( Figure 4A ) while Group 2 PrPSc features were observed in UK VV2 ( n = 2 ) ( Figure 4D ) and MV2 ( n = 1 ) ( Figure 4B ) GH patients . Surprisingly , a typical Group 2 PrPSc signature was also observed in one out of the three MV1 French GH patients ( type 1 in all brain areas ) . Meanwhile , all investigated MM1 and two out of the three MV1 French GH cases ( Figure 4A ) harboured identical PrPSc properties than Group 3 sCJD ( Figure 4E ) . Finally , a Group 4 sCJD PrPSc signature ( Figure 4F ) was observed , using both PrPSc resistance ELISA ( Figure 4E ) and strain typing ELISA ( Figure 3B ) , in a French dura mater VV1 case ( n = 1 ) , which harboured a type 1 PrPres WB profile in every investigated area . Taken together , these observations support the concept that , in iCJD patients , variability in the PrPSc biochemical properties is not related to the route of infection or the PRNP codon 129 genotype . It also indirectly suggests that the range of different PrPSc properties observed in iCJD might be related to those in the source of infection ( likely to have been a sCJD case ) .
In this study , detection , by WB , of the coexistence of two PrPres types in about 30% ( 13/41 ) of cases is consistent with already published data [12] , [14] . This observation could suggest the existence in brain from a single patient of different abnormal PrP species . Although two main PK cleavage sites are associated with PrPres type 1 and type 2 ( respectively amino acid 82 and 97 ) , N-terminal sequencing revealed in all investigated cases the presence of a whole spectrum of overlapping cleavage sites . Moreover in a part of investigated cases this technique demonstrated the presence ( i ) of variable but consistent level of type 1 PrPres in patients classified type 2 using WB and ( ii ) in some patient classified type 1 , of low amount of type 2 PrPres [10] . These observations could suggest that , rather than a pure type 1 or type 2 PrPres , PK digestion of a PrPSc specific conformer generate variable mixture of PrPres fragments ( with presence of dominant or sub dominant type 1 or type 2 PrPres ) , which WB usually failed to reveal accurately because its intrinsic technical limits [14] . Antibodies either harbouring higher affinity to PrP ( like Sha31 ) [18] or probing specifically type 1 PrPres ( like 12B2 ) [20] , now allow a better perception of such mixture . However , investigations carried out using artificial mixture of type 1 and type 2 brain homogenate , even using high affinity anti-PrP antibodies , clearly indicate the current limits of WB discriminative power [14] . Together , these data suggest that WB analysis of PrPres on its own could be misleading for adequate discrimination between PrPSc variants in CJD . Both PrPSc PK resistance ELISA and strain typing ELISA are based on the characterization the N terminal part of the PrPSc PK digestion either by increasing PK amount or modifying detergent conditions . While WB profile could be compared to a snapshot picture of PrPres fragments generated by PK digestion process , these assays reflect the dynamics of the PK cleavage rather than its final result ( different forms of PrPres ) . Consequently they could provide different but also more accurate perception of the PrPSc conformers . Our findings from the PrPSc capture immunoassays clearly indicate that in a single patient , irrespective of brain area , sCJD associated PrPSc displays uniform biochemical properties , regardless of the regional variation of type 1 and type 2 isoforms determined by WB . Such findings support the idea of the presence of a specific TSE agent in each brain and the accumulation of a single associated PrPSc conformer . Because the limited size of our cohort of cases , an in depth comparison between the PrPSc signature ( as established in this study ) and the Parchi classification system is not possible . However , despite this limitation , two major groups were identified in our panel according to the PrPSc properties . The first major group was constituted with patients harbouring a highly PK resistant PrPSc ( MM1 and MV1 patients ) . The second group included patients harboring a PK labile PrPSc ( VV2 and MV2 patients ) . Using both lesion profile and clinical parameters [2] , two major forms of sCJD are commonly recognized . The first sCJD form , named “classical” , is characterized by a “rapid evolution” ( usually around 4 months ) , and affects most of the MM1 and MV1 patients . The second sCJD form , named “atypical” , affects VV2 and MV2 with a longer symptomatic evolution ( usually longer than 6 months ) and a late dementia . Despite inter-individual variations , sCJD Groups 1 and 2 , as we defined them on biochemical criteria were consistent with this classification . Both VV1 and MM2 sCJD cases are extremely rare; they respectively represent 1% and 4% of the identified sCJD cases . According to the literature , these patients have clinical features and lesion profiles that are very different from other sCJD patients [2] . However , in our study as in previously published studies , WB did not identify any distinct biochemical difference from other type 1 and type 2 cases . In contrast , both the strain typing ELISA and PrPSc resistance assays clearly differentiated these cases from Group 1 and Group 2 cases . This finding , which is consistent with clinico/pathological observations carried out in patients , could indicate that there are indeed differences in PrPSc that distinguish these VV1 and MM2 cases from other sCJD groups . Although prion strains can only be identified definitively by bioassay , molecular in vitro tools to characterize PrPSc are more and more widely used for the rapid identification of particular agents , such as BSE in cattle , sheep , rodent and humans ( vCJD ) [20] , [21] . This has come to be termed “molecular strain typing” and although widely employed , the exact relationship between PrPSc biochemistry and the biological properties of the agents responsible remain to be determined . In sCJD , the presence of four distinct PrPSc biochemical forms apparently correlated to clinico-pathological phenotypes as defined by Parchi et al . [2] could be an indication of the involvement of different TSE agents . iCJD cases are a consequence of accidental human to human TSE transmission , most likely representing transmission of sCJD . The identification in iCJD cases of the four PrPSc signatures identified in sCJD is consistent with the existence of distinct prions associated with these biochemical forms . Three examples of human-to-human transmission of variant CJD through blood transfusion have now been identified . While all blood donors were MM at codon 129 PRNP , the recipients had either a MM ( n = 2 ) or a MV genotype ( n = 1 ) . Despite this genotype difference there appears to have been conservation of the disease phenotype and PrPres type in all “secondary” vCJD cases [22]–[25] . These observations could suggest that in case of inter-human transmission , difference in donor/recipient genotype could result in un-altered abnormal PrP signature . Our identification of MM GH iCJD cases harbouring similar PrPSc signature as a VV1 sCJD case or of a VV dura mater iCJD case similar to MM2 sCJD might indicate preservation of a specific PrPSc biochemical signature after human to human transmission between individuals of different codon 129 genotypes . Treatment with extracts of GH contaminated by CJD has lead to a high number of iCJD cases in France and the UK . The codon 129 genotypes of the affected individuals in the two countries differ , with the French cohort predominantly MM and MV and the British cohort MV and VV [26] . In the absence of any clear explanation for this finding , it was suggested that it might be due to contamination of different batches of GH with different prion strains from individuals of differing PRNP codon 129 genotypes . Our identification of different biochemical forms of PrPSc in GH French patients and in UK patients is consistent with this hypothesis . The variability observed within the French GH cases could signify involvement of different prion strains , consistent with multiple contaminated GH batches in the French epidemic . The identification in this study of different PrPSc species in CJD patients with the same PRNP polymorphism at codon 129 and WB PrPres profile offers a new perspective on our understanding of the relationship between PrP biochemistry , prion disease phenotype and agent strain . We highlight two novel approaches to analysing PrPSc in sCJD and iCJD and offer evidence that these analyses provide potentially-strain associated information , which appears to be lacking from the conventional WB assay . | Prion diseases are transmissible neurodegenerative disorders characterized by accumulation of an abnormal isoform ( PrPSc ) of a host-encoded protein ( PrPC ) in affected tissues . According to the prion hypothesis , PrPSc alone constitutes the infectious agent . Sporadic Creutzfeldt-Jakob disease ( sCJD ) is the commonest human prion disease . Although considered as a spontaneous disorder , the clinicopathological phenotype of sCJD is variable and substantially influenced by the methionine/valine polymorphism at codon 129 of the prion protein gene ( PRNP ) . Based on these clinicopathological and genetic criteria , a subclassification of sCJD has been proposed . Here , we used two new biochemical assays that identified four distinct biochemical PrPSc subgroups in a cohort of 41 sCJD cases . These subgroups correlate with the current sCJD subclassification and could therefore represent distinct prion strains . Iatrogenic CJD ( iCJD ) occurs following presumed accidental human-to-human sCJD transmission . Our biochemical investigations on 12 iCJD cases from different countries found the same four subgroups as in sCJD . However , in contrast to the sCJD cases , no particular correlation between the PRNP codon 129 polymorphism and biochemical PrPSc phenotype could be established in iCJD cases . This study provides an alternative biochemical definition of PrPSc diversity in human prion diseases and new insights into the perception of agent variability . | [
"Abstract",
"Introduction",
"Materials",
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"Methods",
"Results",
"Discussion"
] | [
"neurological",
"disorders/prion",
"diseases"
] | 2008 | Beyond PrPres Type 1/Type 2 Dichotomy in Creutzfeldt-Jakob Disease |
Bacteria use trans-translation and the alternative rescue factors ArfA ( P36675 ) and ArfB ( Q9A8Y3 ) to hydrolyze peptidyl-tRNA on ribosomes that stall near the 3' end of an mRNA during protein synthesis . The eukaryotic protein ICT1 ( Q14197 ) is homologous to ArfB . In vitro ribosome rescue assays of human ICT1 and Caulobacter crescentus ArfB showed that these proteins have the same activity and substrate specificity . Both ArfB and ICT1 hydrolyze peptidyl-tRNA on nonstop ribosomes or ribosomes stalled with ≤6 nucleotides extending past the A site , but are unable to hydrolyze peptidyl-tRNA when the mRNA extends ≥14 nucleotides past the A site . ICT1 provided sufficient ribosome rescue activity to support viability in C . crescentus cells that lacked both trans-translation and ArfB . Likewise , expression of ArfB protected human cells from death when ICT1 was silenced with siRNA . These data indicate that ArfB and ICT1 are functionally interchangeable , and demonstrate that ICT1 is a ribosome rescue factor . Because ICT1 is essential in human cells , these results suggest that ribosome rescue activity in mitochondria is required in humans .
The presence of a stop codon at the end of an open reading frame signals that the nascent protein is complete . Decoding of the stop codon by a release factor results in peptidyl-tRNA hydrolysis , releasing the completed protein and allowing the ribosome to be recycled [1] . Specific contacts between the release factors and bases in the stop codon are required for efficient catalysis of peptidyl-tRNA hydrolysis [2] . This stop codon recognition is necessary to prevent release factors from acting at sense codons and prematurely terminating translation . However , ribosomes can sometimes translate to the end of an mRNA without terminating at an in-frame stop codon . Translation cannot terminate normally at these “non-stop” complexes , because there is no stop codon in the decoding center to promote release factor activity . Ribosomes must be rescued from non-stop complexes so they can be recycled for productive protein synthesis [3 , 4] . In bacteria , non-stop complexes are rescued primarily by trans-translation . During trans-translation , a small protein , SmpB ( P0A832 ) , and a specialized RNA , tmRNA ( EG30100 ) , recognize a non-stop complex and release the ribosome at a stop codon within tmRNA . trans-Translation also targets the nascent polypeptide and mRNA from the non-stop complex for degradation [3 , 5] . Genes encoding tmRNA or SmpB have been identified in >99 . 9% of sequenced bacterial genomes [4] . trans-Translation is essential in some bacteria [6–8] , but other species can survive without ssrA ( encoding tmRNA ) and smpB [9–11] . Some species , such as C . crescentus , have a severe growth defect when ssrA is deleted [12] . In other species , such as Escherichia coli , there is a relatively mild phenotype [13] . Synthetic-lethal screens have identified two alternative rescue factors , ArfA and ArfB , that can rescue non-stop complexes in the absence of trans-translation [14–16] . ArfA , found in E . coli and closely related bacteria , allows the release factor RF-2 to hydrolyze peptidyl-tRNA on non-stop ribosomes [17–20] . ArfB , found in C . crescentus and species from many phyla , contains a catalytic domain similar to release factors but does not include domains required for stop codon recognition . ArfB catalyzes hydrolysis of peptidyl-tRNA on non-stop ribosomes [15 , 16 , 21] . The C-terminal tail of ArfB is important for its activity [22] , and structural studies suggest that it binds in the empty mRNA channel of non-stop ribosomes , similar to the C-terminal tail of SmpB [23] . arfA is essential in E . coli ΔssrA cells [14] , and arfB is essential in C . crescentus ΔssrA cells [21] , indicating that these species require at least one ribosome rescue mechanism . These observations have led to the suggestion that ribosome rescue activity may be essential for most or all bacteria [5] . Eukaryotes use Dom34/Pelota ( P33309/Q9BRX2 ) and Hbs1 ( P32769 ) to rescue ribosomes from non-stop mRNAs during translation in the cytoplasm [24 , 25] , but factors required for this system are not present in mitochondria . Mammals have an ArfB homolog , ICT1 , which is encoded in the nucleus and transported to mitochondria [26] . Knockdown experiments have demonstrated that ICT1 is essential in human cells [26 , 27] , but conflicting models have been proposed to explain why ICT1 is essential [28–30] . Like ArfB , ICT1 can hydrolyze peptidyl-tRNA on E . coli non-stop ribosomes in vitro [22] . Because ICT1 can also hydrolyze peptidyl-tRNA on E . coli ribosomes assembled on short mRNAs with a stop or sense codon in the A site , it has been proposed to act as a general release factor that can terminate translation at any codon [26] . ICT1 has also been proposed to act on ribosomes stalled in the middle of an mRNA based on its ability to promote protein synthesis in reactions stalled by omission of a cognate release factor or tRNA [31] . Two mRNAs encoded in human mitochondria terminate with an AGA or AGG codon , so if ICT1 can act as non-specific release factor it might terminate translation of these messages . However , the sequence similarity between ICT1 and ArfB suggests that these factors are likely to have the same activity . ICT1 and ArfB share the conserved GGQ motif found in release factor catalytic domains , as well as residues in the C-terminal tail that are required for ArfB activity on non-stop ribosomes ( Fig 1 ) [22 , 31] Using a direct assay for peptidyl-tRNA hydrolysis in vitro , we find that the substrate specificity of ICT1 is almost identical to that of ArfB . Both factors catalyze peptidyl-tRNA hydrolysis on ribosomes stalled with no mRNA in the A site , or with mRNA extending a short distance past the A site , but have little activity on ribosomes stalled in the middle of an intact mRNA . In addition , we find that ArfB and ICT1 are interchangeable in vivo , both in C . crescentus and in human cells . These data indicate that ICT1 is a ribosome rescue factor and cannot terminate translation in the middle of mRNA , and suggest that mitochondrial ribosome rescue activity is essential in humans .
To evaluate the substrate specificity of ICT1 , we used a gel-based assay to measure peptidyl-tRNA hydrolysis on E . coli ribosomes translating protein from mRNA . In these experiments , protein is produced using in vitro transcription-translation reactions and the components are separated on Bis-Tris gels that preserve the ester bond in peptidyl-tRNA . The fraction of protein that remains in the peptidyl-tRNA band indicates the extent of peptidyl-tRNA hydrolysis during the reaction [21] . To confirm that ICT1 can hydrolyze peptidyl-tRNA on non-stop ribosomes in a manner similar to ArfB , a coupled transcription-translation system lacking RF1 , RF2 , and RF3 was used to express a folA gene ( encoding DHFR ) that lacked a stop codon . Consistent with previous observations of peptidyl-tRNA hydrolysis on non-stop ribosomes [15 , 16 , 21] , addition of a release factor mixture containing RF-1 , RF-2 , and RF-3 to the reaction had little effect on the percentage of DHFR found in peptidyl-tRNA , but when ArfB was included 74 ± 1% of the DHFR was released ( Fig 2 ) . When ICT1 was included in the reaction , 78 ± 8% DHFR was released , indicating that ICT1 has a similar activity to ArfB on non-stop ribosomes . To determine if ICT1 and ArfB can also release ribosomes stalled with mRNA extending into or past the A site , the peptidyl-tRNA hydrolysis assay was repeated with longer folA templates . A stop codon was added to the end of the non-stop template , and 0 , 6 , 14 , or 33 nucleotides were added after the stop codon . Each template was designed to produce an mRNA with a stem-loop at the 3’ end to limit exonuclease activity during the reaction . Translation of these mRNAs will result in a ribosome stalled at the stop codon with peptidyl-tRNA in the P site . As expected , addition of release factors to reactions with any of these templates resulted in release of most of the peptidyl-tRNA ( Fig 2 ) . ICT1 and ArfB hydrolyzed peptidyl-tRNA as efficiently as release factors when the stop + 0 template was used . Substantial peptidyl-tRNA hydrolysis activity by ICT and ArfB was also observed with the stop + 6 template , but significantly less activity was observed when the template had a longer sequence past the stop codon ( p < 0 . 001 ) . Almost no hydrolysis was observed with ICT1 or ArfB on the stop + 33 template . These results indicate that ICT1 and ArfB can hydrolyze peptidyl-tRNA on ribosomes stalled near the 3’ end of an mRNA , and that a codon in the A site does not interfere with ribosome rescue . However , mRNAs that extend ≥ 14 bases past the A site substantially decrease activity of both ICT1 and ArfB .
Rescue of ribosomes from non-stop translation complexes is a critical function for most bacteria , and the results presented here indicate that rescue of mitochondrial ribosomes is also essential in some eukaryotes . C . crescentus cells can survive without tmRNA and SmpB because they have ArfB to rescue ribosomes in the absence of trans-translation [21] . We have previously shown that C . crescentus ArfB can hydrolyze peptidyl-tRNA from non-stop ribosomes in vitro [21] . The data described here show that ArfB is also active on ribosomes stalled with a full codon in the A site or with 6 nucleotides past the A site , but longer mRNA extensions strongly inhibit ArfB activity . This substrate specificity is similar to that observed for tmRNA-SmpB [34–36] , and indicates that ArfB is unlikely to interfere with translation elongation or with ribosomes paused during translation of full-length mRNAs . Instead , ArfB activity is consistent with a role in rescuing ribosomes that have translated to the 3’ end of an mRNA without terminating , ribosomes that have stalled after cleavage of the mRNA in the A site by a nuclease such as RelE [37] , and stalled ribosomes that have had the 3’ portion of the mRNA removed by exonuclease activity [36 , 38] . Several lines of evidence demonstrate that human ICT1 is a ribosome rescue factor like ArfB , and not a non-specific release factor that can act on ribosomes stalled in the middle of an mRNA . First , the specificity of ICT1 in vitro for non-stop ribosomes or ribosomes with short mRNA extensions past the A site is similar to that of ArfB . Second , ICT1 can functionally replace ArfB in C . crescentus . Expression of ICT1 suppresses the synthetic lethality of deleting ssrA and arfB , and over-expression of ICT1 increases the growth rate in ΔssrA cells to the same extent as over-expression of ArfB . Third , expression of ArfB in human cells suppresses the lethal effects of silencing ICT1 , indicating that ArfB can functionally replace ICT1 in human cells . Finally , ICT1 would have little opportunity to act as a non-specific release factor during translation of intact transcripts in the mitochondria because mammalian mitochondrial transcripts are polyadenylated with ~50 nucleotides [39–44] . Based on the substrate specificity of ICT1 in vitro , this poly ( A ) tail would block ICT1 activity unless the mRNA was truncated , so ICT1 substrates for in vivo are likely to be non-stop complexes . Because ICT1 is essential in human cells [26 , 27] , these results suggest that ribosome rescue in mitochondria is essential for human cell viability . The activity of ICT1 as a rescue factor and not a non-specific release factor would also explain why ICT1 does not interfere with translation elongation in mitochondria . ICT1 substrate specificity has important implications for translation termination in mitochondria . Two human mitochondrial genes end in an AGG ( ND6 ) or AGA ( COI ) codon . There are no cognate mitochondrial tRNAs for these codons and the mitochondrial release factor mtRF1a is unable terminate translation at AGA or AGG [45] , so it is unclear how translation is terminated for these genes . ICT1 has been proposed to function as the termination factor at these codons based on analysis of activity in vitro on ribosomes stalled with an mRNA extending up to 14 nucleotides past the A site [30 , 31] . Our data show that ICT1 activity is greatly reduced on ribosomes stalled with an mRNA extending 14 nucleotides past the A site , and ICT1 activity is completely absent when the mRNA extends 33 nucleotides past the A site . Because the COI AGA codon is 72 nucleotides from the end of the transcript and the ND6 AGG codon is 500–550 nucleotides from the end of the transcript [39 , 42] , ICT1 should have no activity at these codons in either their unmodified or polyadenylated form . In addition , ICT1 can support viability in C . crescentus , so it cannot have an intrinsic ability to terminate translation at AGA or AGG because these codons encode arginine in bacteria . Likewise , ArfB does not recognize AGA or AGG in C . crescentus , so the ability of ArfB to replace ICT1 in human mitochondria suggests that termination at AGA or AGG in the middle of a transcript is not an essential function for ICT1 . One possible mechanism for both ICT1 and ArfB to terminate translation at these codons is that stalling of the ribosomes leads to truncation of the mRNA 3’ of the ribosome , thereby producing a substrate for the rescue factors . A second possible mechanism for termination at AGA or AGG by ICT1 and ArfB would be that mitochondrial ribosomes might respond differently when they stall in the middle of an mRNA than do bacterial ribosomes . Mitochondrial ribosomes are descended from bacterial ribosomes , but are highly specialized for translating a small number of mRNAs encoded in the mitochondrial genome . The decoding center and peptidyl transfer center of mitochondrial ribosomes are very similar to bacterial ribosomes , but other architectural features are highly diverged [46] . For example , mammalian mitochondria have dramatically reduced rRNAs and lack 5S rRNA , but contain 36 proteins not found in bacteria and incorporate a tRNA as a structural component of the large subunit [47] . It is possible that this different architecture causes mitochondrial ribosomes to adopt a conformation that promotes rescue by ICT1 and ArfB when they are stalled in the middle of an mRNA . If ICT1 does not terminate translation at these codons , one of the other members of the mitochondrial RF family might perform this function . Mitochondria descend from a progenitor of α-proteobacteria [48 , 49] , the bacterial class that includes C . crescentus . Most α-proteobacterial species contain both trans-translation and ArfB , and some protist mitochondria encode ssrA and smpB [4] , suggesting that the primordial mitochondrion had both ribosome rescue systems . Why did mitochondria keep ArfB and discard trans-translation , whereas almost all bacteria have kept trans-translation whether they have an alternative rescue factor or not ? Mitochondria encode only 13 proteins , all of which are integral membrane proteins . Perhaps this limited proteome decreases the selective advantages of trans-translation , for example by enabling proteases to recognize incomplete versions of proteins without the tmRNA-encoded tag . Alternatively , the constraints of importing factors encoded in the nucleus might have favored ICT1 over tmRNA-SmpB , because ICT1 acts as a single protein . Interestingly , some plants encode an ArfB/ICT1 homolog with a chloroplast-targeting signal , ( Q84JF2 , e . g . ) suggesting that ribosome rescue activity may be found in other organelles , and that the ArfB-type ribosome rescue may be generally favored in eukaryotic organelles .
Strains are described in Table 1 . C . crescentus strains were grown at 30°C [50] in peptone-yeast extract ( PYE ) medium supplemented with tetracycline ( 2 μg/ml ) , streptomycin ( 50 μg/mL ) , spectinomycin ( 100 μg/mL ) , kanamycin ( 20 μg/mL ) , or xylose ( 0 . 3% ) where appropriate . Growth was monitored by measuring optical density at 600 nm . To construct pET28ICT1 for expression and purification of mature ICT1 , the coding sequence ( codon-optimized for E . coli ) ICT1 lacking the mitochondrial localization signal was purchased as a gBlock Gene Fragment ( IDT ) and inserted into pET28b by Gibson assembly [51] . Construction of parfB ( formerly pCC1214 ) has been described previously [26] . pICT1 was constructed by digesting pET28ICT1 with NdeI and BamHI and ligating the resulting fragment into parfB digested with the same enzymes . pMCSVICT1 was constructed by Gibson assembly of the human ICT1 sequence into the EcoRI and NotI sites of pMSCVneo . Alternative codons were selected for the region of ICT1 targeted by the siRNA to ensure that only endogenous ICT1 would be silenced . pMCSVarfB was similarly constructed by Gibson assembly of a gBlock Gene Fragment into pMSCVneo at the EcoRI and NotI sites . The arfB construct encodes the 62 residue N-terminal extension of human ICT1 to target it to mitochondria followed by the 142 residues of C . crescentus ArfB sequence codon-optimized for expression in human cells . The ArfB coding sequence was codon-optimized for expression in human cells . Purification of C . crescentus ArfB has been described previously [21] . ICT1 was purified using a similar protocol . Strain KCK477 was grown to OD600 ~ 0 . 8 and expression was induced by addition of isopropyl-ß-D-thiogalactopyranoside ( IPTG ) to 1 mM . Cells were grown for 3 h at 37°C , harvested by centrifugation at 4°C , and resuspended in 30 ml lysis buffer ( 6 M guanidine hydrochloride , 20 mM sodium phosphate , 400 mM NaCl ) [pH 7 . 8] . Cells were lysed by sonication and the lysates were cleared by centrifugation at 11 , 000 g for 30 min and applied to a column packed with 500 μl Ni-nitrilotriacetic acid ( NTA ) agarose ( Qiagen ) slurry equilibrated in DB buffer ( 8 M urea , 20 mM sodium phosphate 500 mM NaCl ) [pH 7 . 8] . The column was washed 3X by rocking with 10 bed volumes DB buffer , washed 3X by rocking with 20 bed volumes DW buffer ( 8 M urea , 20 mM sodium phosphate , 500 mM NaCl ) [pH 6 . 0] , and washed 3X with 20 bed volumes of DW buffer [pH 5 . 3] . Protein was eluted in 1 ml fractions in elution buffer ( 8 M urea , 20 mM sodium phosphate , 500 mM NaCl ) [pH 4 . 0] . Fractions containing ICT1 were dialyzed against ICT1 dialysis buffer ( 10 mM HEPES [pH 7 . 6] , 150 mM NaCl ) . The 6 histidine tag was cleaved with Thrombin CleanCleave Kit ( Sigma ) at 4°C for 3 h according to the manufacturer’s instructions . Residual 6x-His tagged protein was removed by incubation with Ni-NTA agarose . Peptidyl-tRNA hydrolysis by ArfB , ICT1 , and release factors was assayed using the PURExpressΔRF1 , 2 , 3 kit ( New England Biolabs ) . Template used for in vitro transcription and translation was generated by PCR using the primers listed in Table 1 . Each template was designed to produce an mRNA with a stem-loop at the 3’ end to limit exonuclease activity during the reaction . PURExpressΔRF1 , 2 , 3 kit components were mixed according to the manufacturer’s instructions and incubated with 200 nM ArfB , 200 nM ICT1 , or 100 nM RF1 , RF2 and RF3 for 1 h at 37°C . Anti-ssrA oligonucleotide was added to 5 μM to inhibit any trans-translation activity from tmRNA in the kit components . Samples were precipitated in 20 μl cold acetone , resuspended in loading buffer pH 6 . 5 ( 5 mM sodium bisulfite , 50 mM MOPS [morphonlinepropanesulfonic acid] , 50 mM Tris , 1 μM EDTA , 0 . 1% SDS , 5% glycerol , 0 . 01% xylene cyanol , and 0 . 01% bromophenol blue ) , heated to 65°C for 5 minutes , and resolved on Bis-Tris gels with MOPS running buffer ( 250 mM MOPS , 250 mM Tris , 5 mM EDTA and 0 . 5% SDS ) . ΦCR30 lysate was prepared from strain KCK428 as described previously [32] . The resulting lysate was used to transduce wild-type or ΔssrA cells harboring pICT1 , parfB , or empty vector . Overnights of each strain were grown in PYE supplemented with tetracycline and xylose to mid log phase . 25 μl ΦCR30 prepared from KCK428 was added and cultures were incubated at 30°C for 2 . 5 h with shaking . Cells were then plated on PYE with kanamycin and xylose to select for transductants . The resulting colonies were tested for spectinomycin and streptomycin resistance to determine the frequency with which arfB:aadA co-transduced . Pre-annealed non-targeting control siNT , or targeting siICT1[26] RNAs were purchased from Eurofins MWG Operon . To demonstrate efficient knockdown , 7 . 5 × 105 HEK293 cells were seeded in a 6-well plate and transfected once every 24 h with siNT and siICT1 as follows: a mixture containing 90 μl serum-free DMEM ( Corning ) , 3 . 4 μl siRNA ( 20 μM stock ) , and 4 μl TransIT-siQUEST ( Mirus Bio ) was incubated at room temperature for 30 min and added to the cells . After 48 h , cells were lysed by addition of buffer containing 150 mM sodium chloride , 50 mM Tris [pH 8 . 0] , 5 mM EDTA , 2 mM phenylmethylsulfonyl fluoride , 2 mM sodium orthovanadate , 10 mM sodium fluoride , and 1% Igepal TM CA-360 ( USB ) . The efficacy of ICT1 silencing was then determined by western blot using polyclonal mouse anti-human ICT1 ( Sigma ) . HEK293 cells ( ATCC ) were seeded in 6-well plates at 5 × 104 cells per well and allowed to adhere for 18 h . Cells were transfected by combining 1 μg pMSCV vector , pMSCVICT1 , or pMSCVarfB , 90 μl serum-free DMEM , and 3 . 8 μl TransIT-293 ( Mirus Bio ) and allowing the mixture to incubate for 30 min at room temperature . 8 h after transfecting with plasmid , cells were transfected with siNT or siICT1 according to the siRNA transfection protocol described in the previous section . Viable cell numbers were determined by 0 . 4% trypan blue staining of trypsinized cells 6 days after silencing . | Ribosomes can stall during protein synthesis on truncated or damaged mRNAs that lack a stop codon . In bacteria , these “non-stop” ribosomes are rescued by trans-translation or by an alternative rescue factor , ArfA or ArfB . Most eukaryotes do not have trans-translation , but mammals have a homolog of ArfB named ICT1 . ICT1 is targeted to mitochondria , and is essential in human cells . Here , we show that human ICT1 and ArfB from the bacterium Caulobacter crescentus have the same biochemical activity and specificity . We also demonstrate that ICT1 and ArfB are functionally interchangeable in both bacteria and human cells . Collectively , this work demonstrates a new essential function in human cells—rescue of mitochondrial non-stop translation complexes . | [
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] | 2016 | Human Cells Require Non-stop Ribosome Rescue Activity in Mitochondria |
Synonymous rare codons are considered to be sub-optimal for gene expression because they are translated more slowly than common codons . Yet surprisingly , many protein coding sequences include large clusters of synonymous rare codons . Rare codons at the 5’ terminus of coding sequences have been shown to increase translational efficiency . Although a general functional role for synonymous rare codons farther within coding sequences has not yet been established , several recent reports have identified rare-to-common synonymous codon substitutions that impair folding of the encoded protein . Here we test the hypothesis that although the usage frequencies of synonymous codons change from organism to organism , codon rarity will be conserved at specific positions in a set of homologous coding sequences , for example to tune translation rate without altering a protein sequence . Such conservation of rarity–rather than specific codon identity–could coordinate co-translational folding of the encoded protein . We demonstrate that many rare codon cluster positions are indeed conserved within homologous coding sequences across diverse eukaryotic , bacterial , and archaeal species , suggesting they result from positive selection and have a functional role . Most conserved rare codon clusters occur within rather than between conserved protein domains , challenging the view that their primary function is to facilitate co-translational folding after synthesis of an autonomous structural unit . Instead , many conserved rare codon clusters separate smaller protein structural motifs within structural domains . These smaller motifs typically fold faster than an entire domain , on a time scale more consistent with translation rate modulation by synonymous codon usage . While proteins with conserved rare codon clusters are structurally and functionally diverse , they are enriched in functions associated with organism growth and development , suggesting an important role for synonymous codon usage in organism physiology . The identification of conserved rare codon clusters advances our understanding of distinct , functional roles for otherwise synonymous codons and enables experimental testing of the impact of synonymous codon usage on the production of functional proteins .
Most amino acids are encoded by multiple codons , but these synonymous codons are not used with equal frequency . Rare codons generally correlate with lower levels of cognate tRNA , or weaker codon:anticodon interactions [1 , 2] . As a result , rare codons are generally associated with slower translation rates and are typically considered deleterious , due to their negative impact on high level gene expression [3] and sometimes lower translational accuracy [4] . The conventional view holds that selection favors common codons , which are considered translationally optimal , but a low level of rare codons is incorporated due to random mutational drift and weak selection [5] . However , the distribution of rare codons is non-random: clusters of synonymous rare codons are widespread in the coding sequences of most prokaryotic and eukaryotic species [6 , 7] . Clustering would be expected to exacerbate negative effects of rare codons . This suggests that the distribution of rare and common codons may be shaped by selection and plays a functional role in protein production . Supporting a functional role for synonymous rare codons , altering synonymous codon usage has been shown to adversely affect the expression level [8 , 9] , solubility [10] and co-translational modifications [11] of encoded proteins , and is hypothesized to regulate targeting of exported proteins [12 , 13] . Codon usage can also affect translational efficiency indirectly via mRNA structure effects at the 5’ end of coding sequences [14–18] . Within coding sequences , an intriguing hypothesis suggests that rare codons may slow translation rate to coordinate proper co-translational folding of the nascent polypeptide chain [19–23] , potentially to simplify the folding energy landscape for multi-domain proteins [24 , 25] . Such effects have been observed for in vitro translation reactions of some proteins [22 , 26] . While previous studies have suggested that synonymous codon usage is functionally important for some proteins , it is not yet clear in which cases codon usage results from selection versus random drift . Efforts in this direction have been stymied in part because many past analyses of synonymous codon usage neglected to account for specific known biases in synonymous codon selection , including the percent GC content at the third nucleotide position of a codon [27] , codon pair bias [28] , low sequence divergence between recently duplicated genes ( paralogs ) , and potentially other unknown sources of synonymous codon usage bias . Moreover , altering synonymous codon usage can affect gene expression in diverse ways [29] . In addition to the effects described above , synonymous mutations can also affect translational accuracy [4 , 30 , 31] , splicing efficiency [32 , 33] , and introduce undesirable nucleotide motifs such as internal Shine Dalgarno sites [34] . Some large clusters of synonymous rare codons have no measurable effect on protein folding [6] . In addition , even the rarest codons still encode ≥1% occurrences of an amino acid , challenging the identification of statistically significant usage patterns for functionally important rare codons against the background of neutral drift . We hypothesized that synonymous rare codons that are important for co-translational protein folding might ( i ) occur in clusters [6] , in order to produce larger translation rate changes than a single codon , and ( ii ) occur at similar positions amongst homologous proteins across the tree of life , as homologous proteins often have similar three dimensional structures [35] . Under this hypothesis , evolution would select for codon rarity at a particular position in an alignment of mRNA sequences without necessarily conserving a specific DNA or protein sequence . To test whether synonymous rare codon clusters are conserved during evolution , we developed a rigorous set of criteria , including an appropriate null model and statistical tests , to analyze codon usage in all open reading frames of 76 diverse , fully sequenced genomes . This analysis revealed a widespread conservation of synonymous rare codon clusters , particularly amongst water-soluble proteins , across diverse species . Most conserved rare codon clusters were found within conserved protein structural domains , rather than between domains . These results indicate that synonymous rare codons are frequently subject to positive selection , and have functional importance across the tree of life .
A complete set of all annotated protein coding sequences ( an ORFeome ) was collected for each of 76 diverse eukaryotic , archaeal , and bacterial species with fully sequenced genomes ( see Methods and S1–S3 Tables ) . Species were selected to span as much of the tree of life as possible ( S1 Fig ) in order to keep DNA identity low , as species with high DNA identity may have diverged too recently for synonymous codon conservation to be reliably detected . Protein sequences from these 76 ORFeomes were assigned to homolog families , and the sequences within each family were aligned ( Fig 1A ) . To reduce potential false-positive results arising from recent gene duplications ( paralogs ) , homolog families were trimmed to include only one sequence from each organism ( see Methods ) . The conserved codon usage patterns we sought to identify in these homolog families are those that do not alter the encoded amino acid sequence , as amino acid sequence changes can alter protein function , binding and/or stability . For this reason , we used the %MinMax algorithm [6] to analyze position-specific synonymous codon usage in each coding sequence . This algorithm compares the codon usage of the actual mRNA sequence to that of theoretical sequences encoding the same amino acid sequence using the most rare and common codons for each amino acid ( see Methods ) , returning a value that reflects the relative rareness of the codons used to encode a specific amino acid sequence . A codon is defined as rare if its usage frequency within an ORFeome is less than the average usage frequency for codons within the same synonymous set [6] . In contrast , other codon usage calculators compare the absolute rarity of one codon versus all other 61 sense codons , which can reflect amino acid rarity due to unavoidable functional constraints on the amino acid sequence [36] . It has previously been shown that relative codon rarity is highly correlated with local translation rate [37–39] and changes to it can alter co-translational folding [10 , 20 , 21 , 23] . Changes to relative codon rarity correlate with changes in co-translational folding equally well as translation adaptive index ( tAI ) [16] ( S2 Fig ) , but does not require fitting to an adjustable parameter . Locations of synonymous rare codon clusters within the aligned coding sequences were determined , and this data was used as the input for conservation statistical analysis , which included three steps ( Fig 1A ) . The initial step tested whether rare codon clusters in homolog families co-occur ( align ) more often than expected by random chance across the entire dataset . We counted the total number of rare codon cluster peaks that fall within a distance of +/- 2 positions across each homolog family , and compared this number of co-occurring rare codon clusters with the number from a null model where rare codon clusters were distributed randomly across coding sequences . We generated the null distribution by randomly shifting the protein sequence from each organism without distorting the positional relationships of codon usage ( see Supplementary Information for a detailed description ) . This test returned a p-value <1x10-300 , providing strong evidence that rare codon clusters as a whole tend to occur at the same positions across organisms . The broad analysis described above determined that rare codon clusters in general show a non-random distribution , with 26% of homolog families showing significant rare codon co-occurrence ( p-value < 1x10-4 ) . However , it is possible that rare codon clusters might occur at the same positions in homologs for reasons unrelated to codon rarity , including amino acid bias , selection for %GC content , known codon pair biases [39 , 40] or other , unknown factors . Hence in the second step of the statistical analysis the homolog families with significant rare codon co-occurrence were filtered to remove families where co-occurrence did not differ significantly from co-occurrence found in random reverse translations ( RRTs ) , a Monte Carlo simulation method we developed to control for rare codons that co-occur for reasons other than rarity ( see Methods ) . Each RRT randomly generated an alternative mRNA sequence to encode an analyzed coding sequence without altering its amino acid sequence , based on the underlying codon usage frequencies of the host organism [6] . Crucially , these RRTs replicated the %GC content of each coding sequence and the codon pair biases of the species genome of origin ( see Methods ) . This simulation generated a null model where co-occurrence of rare codons for reasons other than rarity could be detected using the same bioinformatics framework . This important null model control eliminated 1 , 047 homolog families; however , a substantial fraction ( 3 , 824; or 79% ) of homolog families still showed significant ( p-value ≤ 1x10-4 ) co-occurrence of rare codon clusters after adjusting for these effects ( Fig 1A ) , indicating that these homolog families contain regions of conserved codon rarity . In the third step of the statistical analysis , we filtered the dataset to determine what fraction of rare codon conservation arises due to previously observed conservation of rare codons at coding sequence termini in many species [14–16 , 43] . Homolog family alignments were trimmed to remove the first and last 50 codons and re-analyzed for co-occurrence ( see Methods ) . The majority ( 3079 , or 81% ) of homolog families with significant conservation still showed significant conservation after this terminal trimming ( Fig 1B ) , indicating widespread conservation of rare codon clusters within the interior of coding sequences . The conservation of rare codon clusters within homologous coding sequences implies that these synonymous codons are functionally important for protein biogenesis . To identify broad trends associated with conserved rare codon clusters ( CRCCs ) , we first tested whether certain Gene Ontology ( GO ) categories are enriched and/or under-enriched among homolog families with CRCCs . We found significantly more CRCCs than expected in genes encoding water-soluble proteins that fold in the cytosol ( i . e . , cytosolic and nuclear proteins ) , proteins with functions associated with binding , and proteins that participate in processes associated with growth and development ( Fig 2 ) . The enrichment of water-soluble proteins may reflect differences in domain structure between water-soluble proteins and those that are membrane-bound . Several of the enriched protein functions , including DNA binding and promoter regulation , are associated with the enrichment in nuclear localization . If CRCCs function to modulate co-translational folding of the encoded protein , we hypothesized that their positions might correlate with the locations of conserved structural features , particularly domain boundaries . Previous investigations of correlations between rare codons and domain boundaries have arrived at conflicting conclusions ( e . g . [24 , 44] ) , perhaps because the analyses used small sets of proteins with solved structures . To broadly test whether CRCCs are enriched at or near the boundaries of protein structural domains , the locations of CRCCs were compared to the locations of annotated SCOP [45] and CATH [46] domains in proteins with PDB structures and domains predicted from gene sequences [47] . Surprisingly , this analysis revealed that CRCCs are significantly ( p = 1E-9 for human , p = 3E-14 for E . coli ) under-enriched near domain boundaries ( Fig 3A ) . Hence the major function of CRCCs does not appear to be to separate the co-translational folding of entire domains . Instead , CRCCs often occurred at positions where a translational pause would expose a smaller structural sub-domain outside of the ribosome exit tunnel ( Fig 4 , S4 Fig ) . Crucially , small structural motifs such as these often fold much faster than an entire domain [48–52] , and hence might be more sensitive to the small differences in the rate of appearance of the nascent chain achievable via synonymous codon selection . It has been hypothesized that rare codons are enriched in unstructured regions of proteins due to reduced selection for translational accuracy in these regions [53] . Such an effect could potentially cause false positives in a study of rare codon conservation , if unstructured , poorly conserved regions in the homologs aligned . To avoid this issue , we focused on alignment regions with high amino acid conservation across homolog families; alignment columns containing gaps in any species were removed from consideration . To determine the fraction of CRCCs that occur in structured regions with conserved amino acid content , we compared to frequency of CRCCs inside and outside conserved domains ( Fig 3B ) . The majority occurred inside conserved domains , suggesting that these rare codons are in fact conserved and do not result from neutral drift in regions where amino acid content is non-critical . However , although most CRCCs occurred inside conserved domains , a subset of CRCCs did show a small but statistically significant enrichment outside known conserved domains . This result highlights the complexity and challenges of a truly comprehensive analysis of synonymous codon usage . Going forward , novel computational methods will be required to distinguish between CRCCs with different roles . Coding sequences with CRCCs have higher average length than sequences without CRCCs ( S3 Fig ) . This result is expected , as a longer length gives more opportunities for a CRCC to occur . Longer sequences do not , however , have a higher density of CRCCs per unit length than shorter sequences . We also assessed whether homolog families with CRCCs are enriched in certain protein secondary structural types . Initially , our analysis suggested that human proteins from homolog families with CRCCs showed a significant enrichment of domains with β-sheet secondary structure ( Fig 3C ) . However , because proteins from families with CRCCs also have a longer average length ( S3A Fig ) , we hypothesized that differences in protein length could be driving the observed differences in domain composition . Comparison of human proteins with CRCCs to a length-matched control set ( similar sequence length but no CRCCs; see Methods ) , revealed that the difference in domain composition results from an association between domain composition and sequence length , rather than an association between the presence of CRCCs and secondary structure composition , including the presence of transmembrane helical domains ( S3B Fig ) .
Synonymous mutations were once thought to be neutral . This assumption is the basis of the frequently used Ka/Ks ratio , in which the synonymous substitution rate serves as a proxy for neutral mutational drift [54 , 55] . However , it is now widely accepted that codon usage in bacteria is shaped by selection [56 , 57] . The origins of eukaryotic ( particularly mammalian ) codon usage have remained more controversial [58] , and it has been argued that the fitness effects of synonymous codon changes are too small to result in selection in species with a small population size [59] . However , more recent studies have shown that synonymous codon changes can have phenotypic effects [20 , 60 , 61] and that synonymous codon usage in eukaryotes is at least partly the result of selection [58 , 62] . Beyond synonymous codon selection in general , whether there are detectable patterns of codon usage within ORFs is still an open question . Previous studies have shown that the distribution of rare codons in ORFs is non-random in most organisms [6] , however the functional significance has remained controversial , as have the evolutionary reasons ( i . e . , selection or drift ) . In recent years there has been a growing consensus that rare codons at the 5’ termini of coding sequences are conserved and increase translation efficiency [13 , 15 , 16 , 43] . In contrast , conservation of non-terminal rare codons is still under active debate , in part because of the many origins of codon usage bias , which can make it challenging to distinguish conservation of codon rarity versus other aspects of codon bias . For example , although a previous study identified low average codon usage frequencies within Pfam domain alignments [36] , it was not determined whether these codons occurred more frequently than expected by random chance . Further , this study considered only absolute codon usage frequencies , which means that conservation of rare amino acids ( e . g , cysteine ) , which are by definition encoded by codons that are rare in an absolute sense , can lead false-positive results . Likewise , Pechmann et al . analyzed rare codon conservation in several closely-related yeast species using a codon usage metric that compares tRNA supply with demand ( as determined by mRNA levels ) and found some evidence for conservation [63] , although the relatively recent divergence of these species may make it more challenging to detect significant conservation . To overcome the challenges of identifying conservation of codon rarity , we aligned synonymous codon usage frequencies across the ORFeomes of 76 diverse organisms and developed a null model capable of distinguishing conservation of codon rarity from other effects , including amino acid conservation , GC bias and codon pair bias . Our study demonstrates that clusters of rare codons are significantly conserved across much more distantly related species , spanning the tree of life , even after accounting for other known codon usage biases , including recently-diverged paralogs , %GC content and codon pair bias . The analysis framework described here can be used to analyze synonymous codon conservation in any organism with a fully sequenced genome . Our results suggest that synonymous codon usage is often subject to selection . The conservation of rare codon clusters suggests they serve a functional role . Given the diverse effects of codon usage , it is likely that CRCCs have multiple functions . The hypothesis that codon usage modulates co-translational protein folding led to the expectation that the locations of rare codon clusters might be correlated with protein structural features . Studies examining correlations between codon usage and protein secondary structure have identified an enrichment of rare codons in unstructured regions and common codons in conserved , structured regions [53 , 64] . While rare codons in unstructured regions can also function to promote co-translational folding [21 , 64] , their presence in such locations is also consistent with the hypothesis that rare codons exist due to mutational drift in genome regions under less selection for translational speed or accuracy [53] . The CRCCs identified by our study are not enriched at domain boundaries in human or E . coli coding sequences . If rare codons do function to separate the folding of protein structural units , these foldable units do not necessarily correspond to a defined domain . Our data set serves as a starting point for more detailed structural and functional analyses , including the effects of mRNA secondary structure on translation rate and co-translational folding of the encoded protein . The association between CRCCs and the processes of growth and development is particularly intriguing , given that the coding sequences of cell cycle-regulated proteins are enriched in rare codons in general [65] . These results are consistent with results showing that substituting common codons for rare codons in the sequences encoding bacterial and fungal circadian regulatory proteins adversely affects the circadian clock and cell growth rate [8 , 21] . Of note , codon sensitivity in the fungal clock protein FRQ is localized to portions of the coding sequence encoding a predicted intrinsically disordered region ( IDR ) [64] . The functions of many IDRs include binding to other proteins and nucleic acids , often to regulate proliferation and cell cycle events [66] . Intriguingly , we found that CRCCs are enriched in proteins with binding functions ( Fig 2B ) , suggest that synonymous codon usage may provide a mechanism to regulate cell growth and development across diverse species . In conclusion , conservation of rare codons is a widespread phenomenon , and occurs in structurally and functionally diverse protein families . Homolog families with CRCCs were enriched in specific structural and functional categories . CRCCs were more likely to be found in water-soluble nuclear and cytosolic proteins rather than membrane proteins , suggesting a possible connection with domain organization and folding in the cytosol . Proteins with CRCCs are enriched in functions associated with development and cell growth . This association is particularly intriguing , given that codon usage has been shown to affect circadian growth rhythms of an organism [8 , 21] , and both tRNA levels and the codon usage of highly expressed genes vary with cell growth rate and cell cycle stage [65 , 67] . The results reported here should be broadly useful toward the development of a mechanistic understanding of how synonymous codon usage can affect various aspects of protein biogenesis .
To minimize DNA identity within our dataset , we evaluated phylogenetic trees [68] constructed for species with fully sequenced genomes . A separate tree was constructed for species from each domain of life ( eukaryotes , archaea , and bacteria ) using 16S or 18S rRNA sequences aligned using MUSCLE [42] . 18S or 16S rRNA sequences were obtained from the Green Genes [69] or Silva rRNA [70] databases . Certain eukaryotic species ( including Giardia lamblia and Brugia malayi in the final data set ) were not present in the Silva database and their 18S rRNA sequences were obtained from NCBI . Based on these initial trees , closely related species were removed and the analysis repeated in order to maximize species diversity . Species for the final data set were chosen based primarily on diversity ( to include representative species from the main branches of each tree ) and secondarily on the significance of the organism ( number of PubMed citations , etc . ) . Trees were drawn using Plottree [68] for an unrooted tree . The final 76 species used for rare codon conservation analysis are listed in S1–S3 Tables , and include 24 bacteria , 26 archaea , and 26 eukaryotes . For each of the 76 selected species , the set of all annotated protein coding sequences in the fully sequenced genome ( the ORFeome ) was collected . Most ORFeomes were obtained by downloading the coding sequences corresponding to all protein coding genes in the species genome from the NCBI database . To avoid fragments not corresponding to full reading frames , only those gene sequences with length equal to an integer multiple of 3 were included in the final ORFeomes . If the same gene identifier was associated with >1 sequence ( for example , multiple splice isoforms for some eukaryotic sequences ) , only the longest sequence was used . Ixodes scapularis cDNA was not available from NCBI , so the transcript set was downloaded from Vector Base [71] . Families of homologous genes from the 76 ORFeomes were assembled using OrthoMCL [41] . Families were edited to remove potential false positives arising from paralogs by including a maximum of one protein sequence from each species . The representative sequence was chosen at random and other sequences from the same species were discarded . For each resulting homolog family , protein sequences were aligned using MUSCLE [42] . Overall codon usage for each species was determined by counting occurrences of each codon in the corresponding ORFeome . To calculate the relative codon usage along each gene , we used the %MinMax algorithm [6] , which was designed to identify clusters of synonymous rare codons . %MinMax compares actual codon usage to hypothetical sequences encoding the same amino acids using either the most common ( %MinMax = +100 ) or most rare ( %MinMax = -100 ) synonymous codons for the species of origin . To identify clusters of rare codons , %MinMax scores were averaged over a sliding window of 17 codons , and one or more consecutive windows with %MinMax < 0 were considered a rare codon cluster . For each cluster , the “peak” was defined as the window with the minimum ( most negative ) %MinMax score . To pinpoint specific rare codon clusters that co-occur , we used the following statistical test . As for the broad test across the entire dataset ( see Results and Supplementary Methods ) , rare codon clusters in two homolog sequences were considered to co-occur if their peaks fell within a distance of +/- 2 positions in a homolog family . For an alignment column with aligned peaks in m out of n homologs ( m≥1 ) , the p-value of co-occurrence = P ( X≥m|X≥1 ) . X follows a binomial distribution ( n , p0 ) where p0 is the probability of a position being a peak ( determined by the total number of peaks and the length of the alignment ) . To separate rare codon conservation within coding sequences versus rare codon co-occurrence at sequence termini [16 , 43] , we located the most N-terminal position where no gaps were found in a homolog family alignment , and discarded any p-values within the next 50 codons . The same process was repeated for the 50 codons preceding the most C-terminal gap in the alignment . This filtering considered gaps because trimming the first 50 codons in the alignment without considering gaps did not trim all N-terminal regions where co-translational folding effects are expected to be minimal ( i . e . , before 20 aa of the nascent chain has emerged from the ribosome exit tunnel ) . This method proved appropriate for homolog families of similar sized proteins while not over or under penalizing diverse families containing homologs from diverse species spanning the tree of life . In subsequent analyses , homolog families were only used if a position within the trimmed homolog family alignment had a p-value below the specific threshold considered . To construct RRTs based on %GC-specific codon usage data , all coding sequences in an ORFeome were sorted into partially overlapping GC3 content bins ( for example , sequences with %GC3 of 20–30% , 25–35% , 30–40% , etc . ) . Overlapping bins were used to increase the number of sequences per bin for more accurate codon usage data while still keeping the average %GC3 content for adjacent bins close together , so that every sequence will have a %GC3 close to the average %GC3 of a sequence bin . Binning was based on %GC3 rather than overall %GC because %GC is correlated with amino acid content and binning by %GC3 is therefore more effective for replicating the %GC content of the original sequence . The codon frequencies within each sequence bin were counted , and the corresponding %GC-biased codon frequency table was used to construct the RRT sequences for each coding sequence . In addition , certain codon pairs are over- or under-represented in some ORFeomes , and this bias was accounted for in the RRT as a codon pair multiplier . A codon pair multiplier indicates the enrichment ( or under-enrichment ) of codon A at the -1 position with respect to codon B ( 5’-A-B-3’ ) , relative to the average local usage frequency of A codons near B codons . For example , to calculate the codon pair multiplier for encoding Leu with CTA before TGC , the average usage frequency of CTA is calculated for all Leu residues within 17 codon windows centered on all TGC codons , with the exception of Leu at the -1 position . The usage frequency of CTA at the -1 position is calculated separately , and the ratio of these two usage frequencies ( CTA frequency at -1/average local CTA frequency ) gives the codon pair multiplier . RRTs were constructed from 3’ to 5’ . At each position , a codon encoding the appropriate amino acid was selected randomly but biased by the count of a codon in a %GC3 bin and multiplied by the codon pair multiplier for each following codon , in order to obtain a position-specific codon usage number . In this way , the enrichment or under-enrichment of a specific codon is relative to both the local %GC content of the coding sequence and the codon pair multiplier , which indicates how much the usage of a codon should be enriched or under-enriched based on the identity of the following 3’ codon ( which is chosen first during the RRT ) . For each gene in each homolog family , 200%GC-matched , codon pair-matched RRTs were constructed . Each set of RRTs was analyzed for co-occurrence of rare codons to determine which sites of significant co-occurrence were likely caused by amino acid bias . For each position in a homolog family alignment , we determined how many RRTs had significant co-occurrence at that position . For all alignment positions that had significant co-occurrence in ≥ 1 RRT , we identified the 5% of positions with the highest number of RRTs with significant ( p-value < 1x10-4 ) co-occurrence , as these positions are likely to be subject to sequence bias and were therefore regarded as suspect . We disregarded any positions within +/- 8 codons of a suspect alignment position , as they fall within the same %MinMax window . Blast2Go [72] was used to assign gene ontology ( GO ) terms to each protein in a homolog family . For each GO term we counted the number of homolog families with significant rare codon conservation that have an ORF assigned with this GO term , and all other instances of that GO term . We then create a contingency table with these counts for each GO term and performed an enrichment analysis using Fisher’s exact test . GO terms were also divided by class ( cellular composition , molecular function , and biological process ) and the 10 most common terms from each class were analyzed for enrichment . A PDB BLAST database was constructed from all non-identical protein chains in the PDB by selecting the PDB representative structure , which selects the highest quality structure if more than one structure is available for identical protein sequences . Proteins from the 76 ORFeome dataset were assigned PDB matches based on BLASTP . A match was required to contain an alignment with ≥95% sequence identity . SCOP and CATH domain annotations were downloaded from the PDB . 8 . 4% of homolog families had a PDB CATH assignment , and 7 . 8% had a PDB SCOP assignment . Domain assignments for the human and E . coli genomes were downloaded from the Gene3D database ( ftp://ftp . biochem . ucl . ac . uk/pub/gene3d_data/CURRENT_RELEASE/ ) . These domains were assigned to human and E . coli coding sequences in the conservation data set by matching gene names . Global and local enrichment of significant CRCCs ( p < 0 . 05; post RRT correction ) relative to domain boundaries was assayed using CATH , SCOP and Ensembl domains and multiple binomial tests . To test for overall enrichment , we first considered any CRCC within 10 codons of a domain boundary to be “near” such boundaries; all others to be “far . ” Using the size of the proteins and domains without gaps , we next determined if more ( or fewer ) CRCCs occurred near boundaries than expected when compared to a null model where CRCCs were distributed evenly across alignments . The same method was used to determine whether more or fewer CRCCs occurred within domains than expected . Finally , we assessed fixed 50 residue windows near N-terminal boundaries versus C-terminal boundaries for windows that: ( 1 ) followed domain boundaries; ( 2 ) were centered on domain boundaries; or ( 3 ) flanked domain boundaries . Since the windows were equal size , we first accessed if more ( or fewer ) CRCCs were found near N terminal boundaries as compared to C terminal boundaries for each protein using a binomial test with p = 0 . 5 . We also considered N versus C terminal boundaries combined across all predicted domains , and compared results with or without the N-terminal trimming procedure described above . Sequences with conserved rare codon clusters ( CRCCs ) have longer average length than sequences without CRCCs . To control for differences in domain composition related to differences in length , a length-matched control set was assembled . Each human protein in a homolog family with CRCCs ( p-value ≤ 1E-4 ) was matched to the human protein with the most similar length ( minimum absolute value of length difference ) from a homolog family without CRCCs . Each protein was only included once in the control set . | Proteins are long linear polymers that must fold into complex three-dimensional shapes in order to carry out their cellular functions . Every protein is synthesized by the ribosome , which decodes each trinucleotide codon in an mRNA coding sequence in order to select the amino acid residue that will occupy each position in the protein sequence . Most amino acids can be encoded by more than one codon , but these synonymous codons are not used with equal frequency . Rare codons are associated with generally slower rates for protein synthesis , and for this reason have traditionally been considered mildly deleterious for efficient protein production . However , because synonymous codon substitutions do not change the sequence of the encoded protein , the majority view is that they merely reflect genomic ‘background noise’ . To the contrary , here we show that the positions of many synonymous rare codons are conserved in mRNA sequences that encode structurally similar proteins from a diverse range of organisms . These results suggest that rare codons have a functional role related to the production of functional proteins , potentially to regulate the rate of protein synthesis and the earliest steps of protein folding , while synthesis is still underway . | [
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] | 2017 | Widespread position-specific conservation of synonymous rare codons within coding sequences |
Recognizing cholera cases early , especially in the initial phase of an outbreak and in areas where cholera has not previously circulated , is a high public health priority . Laboratory capacity in such settings is often limited . To address this , we have developed a rapid diagnostic test ( RDT ) termed Cholkit that is based on an immunochromatographic lateral flow assay for the diagnosis of cholera cases using stool . Cholkit contains a monoclonal antibody ( ICL-33 ) to the O-specific polysaccharide ( OSP ) component of V . cholerae O1 lipopolysaccharide , and recognizes both Inaba and Ogawa serotypes . We tested the Cholkit dipstick using fresh stool specimens of 76 adults and children presenting with acute watery diarrhea at the icddr , b hospital in Dhaka , Bangladesh . We compared Cholkit’s performance with those of microbial culture , PCR ( targeting the rfb and ctxA genes of V . cholerae ) and the commercially available RDT , Crystal VC ( Span Diagnostics; Surat , India ) . We found that all stool specimens with a positive culture for V . cholerae O1 ( n = 19 ) were positive by Cholkit as well as Crystal VC . We then used Bayesian latent class modeling to estimate the sensitivity and specificity of each diagnostic assay . The sensitivity of Cholkit , microbiological culture , PCR and Crystal VC was 98% ( 95% CI: 88–100 ) , 71% ( 95% CI: 59–81 ) , 74% ( 95% CI: 59–86 ) and 98% ( 95% CI: 88–100 ) , respectively . The specificity for V . cholerae O1 was 97% ( 95% CI: 89–100 ) , 100% , 97% ( 95% CI: 93–99 ) and 98% ( 95% CI: 92–100 ) , respectively . Of note , two Crystal VC dipsticks were positive for V . cholerae O139 but negative by culture and PCR in this area without known circulating epidemic V . cholerae O139 . In conclusion , the Cholkit dipstick is simple to use , requires no dedicated laboratory capacity , and has a sensitivity and specificity for V . cholerae O1 of 98% and 97% , respectively . Cholkit warrants further evaluation in other settings .
Cholera is an acute watery diarrheal disease caused mainly by Vibrio cholerae serogroup O1 and less commonly by V . cholerae O139 . Cholera can lead to severe diarrhea and death if untreated . V . cholerae O1 is transmitted through fecal-oral contamination , and cholera is thus predominantly associated with lack of safe drinking water , proper sanitation and personal hygiene . Cholera is an important public health problem in many parts of Asia , Africa and Latin America [1–3] . Globally , 3–5 million cases and over 100 , 000 deaths occur annually due to cholera [4] . Countries facing complex emergencies are more vulnerable to cholera outbreaks [5] . The case fatality rate is often highest at the beginning of an outbreak , and delayed recognition of a cholera outbreak often results in a delayed public health response that can result in high morbidity and mortality [6] . Thus , the rapid and correct detection of cholera cases in the initial stages of an outbreak is critical . Patients with cholera often present with acute watery diarrhea , and although rapid presentation of multiple individuals with severe dehydration , especially adults , is highly suggestive of a cholera outbreak , a firm diagnosis is critical to initiating appropriate public health responses and communications [7–9] . Unfortunately , populations at highest risk for cholera are usually poorly supported by diagnostic capacity: laboratory facilities are usually rudimentary or totally absent , and trained health personnel are often not available . In such settings , there is a pressing need for simple and inexpensive rapid diagnostic tests to correctly identify patients with cholera . Here , we report the development of a new rapid diagnostic dip-stick test , Cholkit , that can be used to evaluate stool samples in suspected cholera patients . This assay is based on the detection of V . cholerae O1 lipopolysaccharide ( LPS ) in stool , and here , we report our analysis of Cholkit’s performance among patients with acute watery diarrhea in Dhaka , Bangladesh using a latent class modeling approach , comparing its performance to those of microbial culture , PCR ( assessing V . cholerae O1 and O139-specific rfb genes and cholera toxin gene ctxA ) analysis of stool , and Crystal VC assay , a commercially available dipstick designed to detect both V . cholerae O1 and O139 .
This study was approved by the Research Review and the Ethical Review Committees of the International Centre for Diarrhoeal Disease Research , Bangladesh ( icddr , b ) and the Institutional Review Board ( IRB ) of the Massachusetts General Hospital . Written consent was obtained from the guardians of children ( 1–17 years ) as well as assent from those 11–17 years of age; adult participants ( 18–59 years ) provided their own consent . We collected stool from 76 hospitalized adults and children at the Dhaka Hospital of the icddr , b who presented with acute watery diarrhea . We performed conventional stool culture by streaking stool directly on selective TTGA ( taurocholate-tellurite gelatin agar ) plates , and incubated these plates overnight at 37°C . Fecal specimens were concurrently enriched overnight at 37°C in alkaline peptone water ( 1% peptone , 1% NaCl; pH- 8 . 5 ) , followed by plating on TTGA to isolate V . cholerae . Colonies morphologically consistent with V . cholerae were analyzed by slide agglutination with monoclonal antibodies specific to V . cholerae serovar O1 ( Ogawa or Inaba ) and O139 [10 , 11] . The Crystal VC test was performed on fresh samples of stool according to the manufacturer’s instructions . Briefly , two drops of liquid stool were added into the sample processing vial and mixed gently . Four drops of the processed sample were then put in a test tube . The Crystal VC test strip was dipped into the tube and the results were interpreted according to the manufacturer’s protocol . Two ml of watery stool were spun at 10 , 000 rpm for 10 minutes . The pellet was resuspended in 200 μl of phosphate buffered saline ( PBS ) and used for DNA extraction with the QiaAmp stool DNA extraction kit ( Qiagen ) following the manufacturer’s instructions . Multiplex PCR assays were performed on a Thermo cycler C-1000 instrument ( Bio-Rad ) . V . cholerae O1-rfb specific primers: O1-F ( 5´-GTTTCACTGAACAGATGGG-3´ ) , O1-R ( 5´-GGTCATCTGTAAGTACAAC-3´ ) ; V . cholerae O139-rfb specific primers O139-F ( 5´-AGCCTCTTTATTACGGGTGG-3´ ) , O139-R ( 5´-GTCAAACCCGATCGTAAAGG-3´ ) ; and cholera toxin gene primers: ctxA-F ( 5´-CTCAGACGGGATTTGTTAGGC-3´ ) , ctxA-R ( 5´-TCTATCTCTGTAGCCCCTATTA-3´ ) were used to amplify O1 rfb ( amplicon size 192 bp ) , O139 rfb ( amplicon size 449 bp ) and ctxA ( amplicon size 302 bp ) genes , respectively , using previously described procedures [10 , 12] . PCR products were analyzed on a 1% agarose gel using Gel Red ( BioTium , USA ) stain . A previously isolated and characterized monoclonal antibody , ICL33 generated at the icddr , b was used for preparing the dipstick . The procedure for isolating the monoclonal antibody involved use of female BALB/c mice that were immunized with an acetone extract of V . cholerae O1 Inaba strain T-19479 ( 50 μg per dose ) four times at weekly intervals [13] . The first dose was administered subcutaneously with Freundʹs complete adjuvant . Subsequent doses were given intraperitoneally with Freundʹs incomplete adjuvant . Four days after the last dose , spleen cells from two immunized BALB/c mice were fused with SP2/0 myeloma cells [13 , 14] . After screening the reactivity of supernatant fluids harvested from the hybridomas against an acetone extract of V . cholerae 01 Inaba strain T-19479 and LPS isolated from V . cholerae O1 Inaba strain T-19479 and Ogawa strain X25049 by ELISA , we selected one reactive hybridoma that was cloned twice by limiting dilution . The monoclonal antibody ( ICL-33 ) secreted by this clone was of IgG3 isotype and specific to LPS of both V . cholerae O1 Inaba and Ogawa . This clone was used to make ascites fluid containing anti-V . cholerae O1 LPS antibody using a previously described procedure [13] . In brief , six to eight week old BALB/c mice ( n = 23 ) were primed with pristane ( Sigma ) . These pristane-primed mice were then injected intraperitoneally with this clone ( 1 . 5 x 106 to 2 . 0 x 106 cells /mouse ) . Ascites fluid was formed 10–14 days after the injection of the cell line . After collection of ascites fluid , it was heated at 56°C for 30 min . The heat inactivated fluid was centrifuged at 3000 rpm for 10 min at 20°C . The supernatant was then separated , followed by filtration with 0 . 45μm and 0 . 2μm filters ( Sartorius , Germany ) respectively . Protein G GraviTrap ( GE Healthcare Life Sciences ) was used to purify the murine IgG3 monoclonal antibody ( ICL-33 ) targeting V . cholerae LPS from ascites following the standard procedure recommended by the manufacturer . Briefly , the affinity column was equilibrated with 1× binding buffer , and the ascites sample ( diluted 2 . 5 times with 1× binding buffer ) was then applied . After washing the column with binding buffer , the monoclonal antibody was eluted into falcon tubes containing neutralizing buffer using 1× elution buffer; the protein concentration of the recovered antibody was determined by Bio-Rad protein assay . We confirmed anti-LPS and OSP IgG specificity of monoclonal antibody , ICL-33 using standard enzyme-linked immunosorbent assay ( ELISA ) protocols [15 , 16] . Briefly , we coated ELISA plates with V . cholerae O1 Inaba and Ogawa LPS ( 2 . 5 μg/mL ) and OSP:BSA ( 1 μg/mL ) in PBS [15 , 16] . Reagents were produced as previously described [17 , 18] . To each well , we added 100 μL of purified monoclonal antibody ( 1 , 000 , 10 , 000 , 100 , 000 and 1 , 000 , 000 dilutions in 0 . 1% BSA in phosphate buffered saline-Tween; the initial antibody concentration was 1 . 14 μg/mL ) , and detected the presence of antigen-specific antibodies using horseradish peroxidase-conjugated anti-mouse IgG antibody ( diluted 1:1000 in 0 . 1% BSA in phosphate buffered saline-Tween ) ( Southern Biotech , Birmingham , AL ) . After 1 . 5 h incubation at 37°C , we developed the plates with a 0 . 55 mg/mL solution of 2 , 2ʹ-azino-bis ( 3-ethylbenzothiazoline-6-sulfonic acid ) ( ABTS; Sigma ) with 0 . 03% H2O2 ( Sigma ) , and determined the optical density at 405 nm with a Vmax microplate kinetic reader ( Molecular Devices Corp . Sunnyvale , CA ) . Plates were read for 5 min at 30 s intervals , and the results were reported as millioptical density units per minute ( mOD/min ) . The ability of the ICL-33 monoclonal antibody to detect V . cholerae O1 strains was further assessed using a slide agglutination test with TTGA-grown V . cholerae bacteria . V . cholerae Ogawa strain X25049 , V . cholerae Inaba strain T-19479 and V . cholerae O139 strain 134B were cultured on TTGA plate at 37°C for overnight . Bacteria from a single colony were added with 10 μl of monoclonal antibody at different dilutions on a glass slide for agglutination . The appearance of agglutination within 2 minutes was considered a positive reaction [13] . We prepared 20 nm colloidal gold by adding 0 . 01% HAuCl4 with 0 . 024% sodium citrate and boiled the solution until it became a red wine color [19] . The colloidal gold was then filtered through a 0 . 2 μm filter . We adjusted the pH of the gold solution to 9 . 5 ( optimum pH for conjugation ) and added 18 μg of purified ICL-33 monoclonal antibody to conjugate with 1 ml of the colloidal gold ( minimal concentration for conjugation ) [19] . We then added 20% BSA to block non-specific binding sites . Monoclonal antibody conjugated to gold was then centrifuged at 10000 rpm for 45 min at 4°C . The supernatant was discarded and the pellet was re-suspended in 0 . 02M Tris buffer containing 1% BSA . We used a baking card containing a nitrocellulose membrane on which ICL-33 monoclonal antibody ( test line ) and goat anti-mouse IgG ( control line ) were dispensed in two lines , respectively by using a Rapid test dispenser ( HM3030 ) . The dispensed membrane was dried for 1 hour 30 min followed by blocking with 1% BSA-PBS for 20 min . Conjugate pads were made by soaking glass fiber in gold-monoclonal antibody conjugate solution and drying for 2 hours , and then pasting on the baking card in a way that overlapped the nitrocellulose membrane ( High flow plus 120 Membrane card ) . The sample pad ( glass fiber ) was placed at the bottom of the backing card to overlap with the conjugate pad to facilitate the flow of sample from sample vial to strip . To accelerate the migration of the sample through the strip , we used cellulose fiber as an absorbent pad and pasted on the baking card opposite to the conjugate pad . All pads were cut to make the required shape by using a Guillotine cutter ( CT300 and ZQ2000 ) . We diluted 5 drops of watery stool with Tris-NaCl-Tween at a 1:1 dilution in a microcentrifuge tube and dipped the Cholkit strip into it for 15 min; the test line and/or control line appeared as a red color . Appearance of both lines indicated that the sample was positive for V . cholerae O1; appearance of only the control line but not the test line indicated a negative result for the test ( Fig 1 ) . We used Graphpad Prism4 for data management , analysis , and graphical presentation . Sensitivity and specificity of different diagnostic tests were calculated using latent class modeling . We estimated the sensitivity and specificity of each of the diagnostic tests using a Bayesian framework with latent class models [20] . For prior information , we assumed that the sensitivity of culture was 60–90% and specificity was 99 . 99–100% [21] . We used broader prior estimates of sensitivity and specificity for PCR , Crystal VC and Cholkit . The prior assumed sensitivity and specificity for PCR were 50–100% and 90–100% , respectively . The prior estimates of sensitivity and specificity for both Crystal VC and Cholkit were 0–100% . We used a Gibbs sampler with 100 , 000 iterations to generate posterior estimates with 95% credible intervals ( CI ) for sensitivity and specificity; all analyses were performed using Python .
Characteristics of all study participants are presented in Table 1 . Of 76 patients who were enrolled as study participants , 45 ( 59% ) were male . The median age was 26 years with a range of 5 months to 60 years . Out of all the study patients , 62% presented to the icddr , b with severe dehydration and 29% with moderate dehydration . The monoclonal antibody used in the Cholkit assay was highly reactive with purified V . cholerae O1 Inaba and Ogawa OSP , as well as LPS , with reactivity detectable to the 1 . 14 ng antibody level for Inaba V . cholerae O1 OSP , and 114 ng for Ogawa V . cholerae O1 OSP ( Fig 2 ) . The monoclonal antibody showed characteristic agglutination reaction with both V . cholerae O1 Ogawa and Inaba strains , but no agglutination was found for V . cholerae O139 when slide agglutination test was performed . Stool specimens from 76 patients were tested by all four of microbial culture , Cholkit , Crystal VC and PCR assays . Nineteen samples were positive by culture and all of them were confirmed as positive for V . cholerae O1 Inaba except one sample that was V . cholerae O1 Ogawa . Out of 19 stools positive by culture , all 19 ( 100% ) were positive by both Cholkit and Crystal VC assays , and 15 ( 79% ) were positive by PCR ( Table 2 and Fig 3 ) . Of all patients with a negative stool culture ( n = 57 ) , Cholkit , Crystal VC and PCR were positive for 11 ( 19% ) , 12 ( 21% ) , and 6 ( 11% ) , respectively . Six specimens that were culture negative but PCR positive were also positive by both Cholkit and Crystal VC . In addition to these 6 samples ( culture negative but PCR positive ) , both RDTs were positive for 5 additional stool specimens , of which one Crystal VC assay result was positive for both O1 and O139 . The Crystal VC assay was also positive for one other study participant for only O139 , but negative by all other tests , and this result was considered a false positive as no V . cholerae O139 was circulating at the time . A detailed listing of results by serogroup and serotype are included in Table 2 . The sensitivity and specificity of all four diagnostic tests were estimated simultaneously by using Bayesian latent class modeling . In this analysis , the sensitivity of culture , PCR , Crystal VC and Cholkit were 70 . 8% ( 95% CI: 58 . 5–81 . 1 ) , 73 . 6% ( 95% CI: 58 . 5–85 . 7 ) , 97 . 5% ( 95% CI: 87 . 5–99 . 9 ) and 97 . 7% ( 95% CI: 88 . 4–99 . 9 ) , respectively . The specificity was estimated at 99 . 9% ( 95% CI: 99 . 7–100 ) for culture , 97 . 2% ( 95% CI: 93 . 2–99 . 2 ) for PCR , 98 . 4% ( 95% CI: 92 . 0–99 . 9 ) for Crystal VC and 96 . 5% ( 95% CI: 88 . 6–99 . 6 ) for Cholkit ( Table 3 ) .
Cholera is an acute watery diarrheal disease that can be fatal if it remains undiagnosed or untreated . Rapid and accurate diagnosis of cholera at the earliest phase of an epidemic is a key feature to assist in early management of cholera outbreaks . Such early detection of a cholera outbreak is often challenging since cholera epidemics frequently occur in resource-limited areas lacking laboratory facilities and trained personnel . Here , we report development of a new rapid diagnostic test that can assist with this clinical and public health need . Cholera RDTs have a number of distinct advantages over other cholera related diagnostic options . Microbial culture is usually considered a gold standard since it is 100% specific , but this method requires at least 2–3 days in a well equipped microbiology laboratory with trained personnel , the use of selective media , and may be negative in patients who previously ingested an antimicrobial before seeking medical care , impact a vibrio specific phages , or due to delays in sample transport and handling [22–24] . In a study by Alam et al in Bangladesh that performed a detailed analysis of stool samples from patients with cholera including microbiologic culture , DFA microscopy , PCR , and phage analysis , microbiologic culturing of stool had a sensitivity of 66% [25] . In another study in India , microbiologic culturing alone of stool detected 70% of cholera cases detected by a combination of culture and molecular analysis [22] . In our current analysis , we found a sensitivity of culture alone of 70 . 8% ( CI 58 . 5–81 . 1 ) , a value in agreement with these previous studies , and supporting the need for additional diagnostic assays that are culture independent . Microscopic examination of fresh watery diarrheal stool using dark field microscopy can also be used to presumptively diagnose cholera [11 , 26–28] , although this approach requires the use of a relatively unaffordable and expensive microscope by skilled laboratory staff . The sensitivity of dark field microscopy is , unfortunately , only about 50% when compared with stool culture [27 , 29] . To address these assay deficiencies , several molecular diagnostic tests have been developed . PCR assays targeting the toxR gene of V . cholerae or an outer membrane protein gene , ompW , have been used to detect the presence of V . cholerae in stool [24 , 30] . Serogrouping of the strain as well as assessing for the presence of a toxigenic strain can also be determined by multiplex PCR detecting the cholera toxin gene ( ctxA ) as well as the O1 and O139-specific rfb genes [24 , 31] . Although these techniques are more rapid than conventional culture , they require expensive reagents , modern equipment , electricity , and trained laboratory staff . Such components are usually absent from areas experiencing a cholera outbreak . In comparison , RDTs are point-of-care tests that can be used by minimally trained staff at the bedside of a suspected cholera patient , and require no cold chain maintenance or use of advanced equipment [23] . Most RDTs for cholera detection are based on immunochromatographic or lateral flow immunoassays , targeting V . cholerae O1 and/or O139 specific antigens [32–34] . Approximately 20 cholera RDTs have been developed , and RDTs can play a critical role in the early detection and monitoring of cholera outbreaks , but standardization and reproducibility of cholera RDTs have been problematic [23] . Laboratory and field evaluation of RDTs has shown sensitivities ranging from 58 to 100% , and specificities of 60 to 100% [23 , 35] . Many cholera RDTs have not been independently evaluated , and none to our knowledge have analyzed using a Bayesian latent class modeling approach to estimate true sensitivity and specificity under field conditions . To address this , we have recently developed the immunochromatographic dipstick described in this report for the rapid diagnosis of cholera . This Cholkit assay is based on the detection of V . cholerae O1 LPS , and we have evaluated its performance using a latent class modeling approach , comparing its performance to those of microbial culture , PCR ( rfb and ctxA genes ) analysis of stool , and use of the Crystal VC assay , a commercially available dipstick designed to detect both V . cholerae O1 and O139 . In our study of 76 cases , we found six cases that were negative by culture but positive by the other tests used , confirming the lack of sensitivity of culture also reported by others [21] . We also found 4 cases negative by PCR but positive by culture , Crystal VC and Cholkit , again suggesting false negative PCR results as reported by others [21] . Among the previous RDTs developed for the diagnosis of cholera , the Institute Pasteur ( IP ) dipstick has perhaps shown the most sensitivity compared with other RDTs by both laboratory and field technicians [36] . The IP dipstick technology has been transferred to a commercial company , Span Diagnostics ( Surat , India ) and is being produced commercially under the name of Crystal VC . This commercial version showed similar sensitivity but less specificity compared to the earlier version [37] . We used this as our RDT comparator for the current study . One of the limitations of the Crystal VC dipstick is that it may give false positive results for V . cholerae O139 [38] . Indeed , in our current study , two Crystal VC assays were positive for V . cholerae O139 , although both stool specimens were negative by culture and PCR for V . cholerae O139 [10] . False positivity could lead to unfortunate and unnecessary clinical and public health responses , given the potential seriousness of missing a cholera outbreak among an at-risk population . Since O139 is not a current cause of endemic or epidemic cholera globally , we elected to focus our RDT on V . cholerae O1 alone . V . cholerae O1 can itself be characterized into Inaba and Ogawa serotypes , based on the presence of absence of a methyl group on the terminal saccharide of the O-specific polysaccharide [17 , 18] . In Cholkit , we used a monoclonal antibody that recognizes both Inaba and Ogawa serotype organisms . In our study , we used a Bayesian latent class modeling approach to estimate sensitivity and specificities of the various assay . Such an approach permits an analysis of a new diagnostic assay when a true gold standard is absent , such as is the case in cholera diagnostics [20 , 21] . Our results suggest that Cholkit is highly specific , and more sensitive than culture and PCR . When considering only V . cholerae O1 results , Cholkit and Crystal VC are also highly comparable , but the probable false positivity of Crystal VC for V . cholerae O139 is disconcerting . It should be noted that our specificity analysis for Crystal VC is only based on V . cholerae O1 detection , since Cholkit was not developed to detect O139 organisms and no direct comparison for that diagnostic assay could be made . It should also be noted that positive and negative predictive values for any cholera diagnostic will reflect the current burden of disease when the assay is evaluated , and that cholera can exist in either endemic forms , or be associated with large and explosive outbreaks . Our study has a number of limitations . First , it used a prototype assay , and the results need to be validated using a final manufactured product to assure standardization and reproducibility . We also did not assess the assay across a wide range of stool types; we focused our initial analysis on patients with acute watery diarrhea . In our study , we also analyzed the fresh stool specimens after they had been transported back to the laboratory ( 1–4 hours ) . A future analysis could perform the assay directly in the field . Also , at the time of this analysis , cholera in Dhaka was largely caused by V . cholerae O1 Inaba . The utility of the assay should also be evaluated in other outbreak settings , geographic regions , among other populations , and should include temperature and product stability analysis . Despite these limitations , we believe our results are significant . We report the development of a new and highly sensitive and specific rapid diagnostic assay for the detection of cholera cases caused by V . cholerae O1 among populations in areas lacking laboratory support and trained personnel . Early detection of such cases would assist targeted responses including diagnostic confirmation using microbiologic culturing with antimicrobial resistance profiling and initiation of cholera treatment and control efforts . | Cholera is a severely dehydrating diarrheal disease that can lead to death if remains untreated . The incidence of case fatality is higher at the beginning of the outbreak . Diagnosis of cholera in the early stage of outbreak is a high public health priority . Although countries facing complex emergencies are more vulnerable to cholera outbreak , laboratory capacity in such settings is usually limited . To address this , here we report the development of a rapid diagnostic test ( RDT ) termed Cholkit for the diagnosis of cholera cases using stool and the assessment of its performance with those of microbial culture , PCR and Crystal VC assay , a commercially available dipstick using a latent class modeling approach . | [
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] | 2018 | Development of a new dipstick (Cholkit) for rapid detection of Vibrio cholerae O1 in acute watery diarrheal stools |
Kaposi's sarcoma-associated herpesvirus ( KSHV ) is a human herpesvirus that causes Kaposi's sarcoma and is associated with the development of lymphoproliferative diseases . KSHV reactivation from latency and virion production is dependent on efficient transcription of over eighty lytic cycle genes and viral DNA replication . CTCF and cohesin , cellular proteins that cooperatively regulate gene expression and mediate long-range DNA interactions , have been shown to bind at specific sites in herpesvirus genomes . CTCF and cohesin regulate KSHV gene expression during latency and may also control lytic reactivation , although their role in lytic gene expression remains incompletely characterized . Here , we analyze the dynamic changes in CTCF and cohesin binding that occur during the process of KSHV viral reactivation and virion production by high resolution chromatin immunoprecipitation and deep sequencing ( ChIP-Seq ) and show that both proteins dissociate from viral genomes in kinetically and spatially distinct patterns . By utilizing siRNAs to specifically deplete CTCF and Rad21 , a cohesin component , we demonstrate that both proteins are potent restriction factors for KSHV replication , with cohesin knockdown leading to hundred-fold increases in viral yield . High-throughput RNA sequencing was used to characterize the transcriptional effects of CTCF and cohesin depletion , and demonstrated that both proteins have complex and global effects on KSHV lytic transcription . Specifically , both proteins act as positive factors for viral transcription initially but subsequently inhibit KSHV lytic transcription , such that their net effect is to limit KSHV RNA accumulation . Cohesin is a more potent inhibitor of KSHV transcription than CTCF but both proteins are also required for efficient transcription of a subset of KSHV genes . These data reveal novel effects of CTCF and cohesin on transcription from a relatively small genome that resemble their effects on the cellular genome by acting as gene-specific activators of some promoters , but differ in acting as global negative regulators of transcription .
Infection with Kaposi's sarcoma-associated herpesvirus ( KSHV , HHV8 ) is causally associated with Kaposi's sarcoma ( KS ) , primary effusion lymphoma ( PEL ) and multicentric Castleman's disease ( for a review , see reference [1] ) . KSHV maintains a persistent latent infection as an episome in B lymphocytes , from which it occasionally reactivates , enters a lytic cycle of replication , and produces infectious virions . Released virions infect other lymphocytes to maintain the latent reservoir or are transmitted from person-to-person in saliva . Cell-mediated immunity is essential for limiting KSHV reactivation and pathogenesis , but cellular epigenetic regulatory mechanisms may also play an important role in limiting viral replication . The balance between lytic and latent infection is an important determinant of pathogenicity . Lytic herpesvirus reactivation , while often more common in states of immunosuppression , is nevertheless apparently stochastic , and may occur quite variably among fully immunocompetent individuals [2] . Lytic replication and viral gene expression are important in pathogenesis for several reasons . First , expansion of the reservoir of infected cells is at least partly dependent on recurrent reactivation of human gammaherpesviruses . Thus long-term acyclovir suppression of lytic replication led to a significant decrease over time in the latent Epstein-Barr virus ( EBV ) load in B lymphocytes of immunocompetent patients [3] . Second , lytic replication and gene expression appears to contribute to oncogenesis in several settings where even a minority of infected cells is permissive for lytic replication [4]–[6] . Several lytic KSHV gene products have anti-apoptotic , proliferative or immunosuppressive properties , increasing the likelihood of malignant transformation by paracrine and autocrine mechanisms [7] , [8] . The role of lytic replication in oncogenesis is supported by the decreased incidence of KS in KSHV infected individuals who received long-term antiviral therapy for other infections [9] . Understanding the basic mechanisms by which the host cell maintains control of lytic viral replication and viral strategies to overcome such control is therefore central to devising novel therapies aimed at these control points . Host proteins that play multiple roles in chromatin organization , transcriptional regulation and chromosome segregation have recently been shown to also bind herpesvirus genomes at specific sites and regulate gene expression [10]–[13] . CTCF is an 11 zinc finger sequence-specific DNA binding protein with roles in transcription activation and repression , gene insulation , enhancer blocking and long range chromatin interactions [14] , [15] . CTCF binds to between 14 , 000 to 20 , 000 sites in the human genome and is functionally important in regulation of several hundred genes based on knockdown studies [16]–[18] . Initial studies suggested that CTCF exerted activating or repressing effects on promoters by direct binding in the manner of classic transcription factors [19] . However , its role in global gene regulatory functions was demonstrated by its ability to block enhancer function when interposed between enhancer elements and target promoters [20] . Subsequent studies have shown that CTCF binding mediates insulation throughout the human genome [18] , [21] . In addition , CTCF may act as a barrier element , demarcating regions of heterochromatin and open chromatin , thereby isolating areas of low and high transcriptional activity . Based on binding studies delineating intra-chromosomal interactions , CTCF mediates three dimensional chromatin structure via long-range interactions . Cohesin , a complex of four proteins , SMC1 , SMC3 , SCC1/Rad21 and SA1/2 , essential for chromatid segregation , has also been recognized as a global regulator of transcription ( for a review , see reference [22] ) . The four proteins form a ring-shaped structure that encloses chromatids . Several other proteins are associated with cohesin , and regulate the dynamic association of cohesin with chromatin as it is sequentially loaded and dissociated from chromosomes during mitosis and segregation . Specificity of cohesin localization is complex and likely mediated by multiple proteins including NIPBL , mediator , transcription factors and CTCF . Thus while cohesin binds to many CTCF sites , it also binds to sites on the genome independently of CTCF . Although cohesin may have both positive and negative effects on transcription , many of its effects are thought to be mediated by facilitating and stabilizing long-range interactions between promoters and enhancers to which it binds . The most likely mechanism is that cohesin causes topological linking of DNA sequences in cis similar to its role in chromatid linkage in trans . Cohesin also is involved in regulation of polII pausing at promoters and relieves pausing , promoting RNA elongation [23] . CTCF and cohesin bind at distinct sites on herpesvirus genomes , including herpes simplex virus , EBV and KSHV . CTCF has been implicated in regulating gene expression during latent EBV infection by mechanisms that likely involve both insulator function and modification of genome conformation by causing formation of intragenomic loops [13] . During KSHV infection in primary effusion lymphoma cells , both cohesin and CTCF play a regulatory role in latent and possibly lytic gene expression [12] , [24]–[26] . Chromosome conformation capture assays have demonstrated that a cohesin/CTCF site in the 5′ region of the major latency KSHV transcript forms contacts with a site close to the primary gene necessary for lytic reactivation ( ORF50/RTA ) and with the 3′ region of the latency region . [12] . Mutation of the CTCF site led to increased latency gene expression , suggesting that CTCF and cohesin play a repressive role in latent gene expression . Interestingly however , deletion of this site also led to a loss of stable viral episome maintenance . Although knockdown of cohesin components led to increased transcription of lytic genes in PEL cells , depletion of CTCF had virtually no such effect [24] . Conversely , mutation of the CTCF site , which would be predicted to disrupt both cohesin and CTCF binding , led to decreased lytic gene expression . In this study , we have performed a detailed analysis of the role of cohesin and CTCF in regulating KSHV lytic replication . By employing siRNAs specific for CTCF and cohesin , we have explored their role in regulating KSHV lytic replication . Using ChIP-Seq , we have defined at high resolution the dynamic changes in cohesin and CTCF binding that occur during lytic KSHV replication and reactivation from latency . The distinct regulatory roles of cohesin and CTCF have also been further defined by transcriptional profiling of infected cells undergoing lytic replication under conditions of cohesin and CTCF depletion . These studies reveal novel mechanisms of gene regulation by CTCF and cohesin during KSHV replication and establish their role as host restriction factors for KSHV replication .
293 and 293T cells were grown at 37°C in Dulbecco's modified Eagle's medium ( DMEM ) supplemented with 10% fetal bovine serum ( FBS ) and glutamine . iSLK cells [27] were maintained in DMEM containing 10% charcoal stripped FBS ( Sigma ) and glutamine with 250 µg/ml neomycin and 1 µg/ml puromycin . iSLK cells were infected with WT KSHV derived from bacmid BAC16 , expressing eGFP and hygromycin resistance [28] . KSHV-infected iSLK cells were maintained in 1 . 2 mg/ml hygromycin , 250 µg/ml neomycin and 1 µg/ml puromycin . Protein samples were analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis ( SDS-PAGE ) and immunoblotted with rabbit polyclonal anti-CTCF ( Millipore ) , anti-Rad21 ( Bethyl ) or anti-actin monoclonal antibody ( Sigma ) and horseradish peroxidase-conjugated secondary antibody ( GE Healthcare ) , followed by visualization with a Clarity Western ECL Substrate Kit ( Bio-Rad ) . Image capture was performed with a BioRad GelDoc system . 293T cells were plated at 600 , 000/well in 6-well plates . CTCF or Rad21 were knocked down by transfection with On-target SMARTpool CTCF siRNA or Rad21 siRNA , or mock-depleted with negative control siRNA ( see below ) . 48 h later , 293T cells were transfected with 1 ug/well pDD398 ( ORF57 promoter-luciferase reporter ) plus 1 ug/well pDD267 ( ORF50 expression plasmid in pCDNA3 ) or empty pCDNA3 vector , using Transit-293 ( Mirus ) per the manufacturer's protocol . Each transfection was performed in triplicate . 48 h later , cells were harvested and lysed in reporter lysis buffer ( Promega ) . Luciferase assays were performed in triplicate with 0 . 5 ul of each lysate using Promega's Luciferase Reporter Assay System per the manufacturer's protocol . CTCF ( L-020165-00-0005 ) , Rad21 ( L-006832-00-0005 ) and negative control On-target plus Smart Pool siRNAs ( D-001810-03 ) were purchased from Thermo Scientific . Each siRNA was transfected into SLK KSHV WT cells using Lipofectamine RNAiMAX ( Invitrogen ) according to the manufacturer's protocol and a 10 nM final concentration of siRNA . Similar experiments were also performed with siGENOME Non-Targeting SiRNA #5 , D-001210-05-05 , SiGENOME human CTCF siRNA , M-020165-02-0005 and SiGENOME human Rad21 siRNA , M-006832-01-0005 , purchased from the same manufacturer . Immunoblotting was performed to verify knockdown of the relevant protein . The chromatin immunoprecipitation ( ChIP ) assay was performed as follows . Briefly , 25 million iSLK cells were harvested and washed with cold PBS containing protease inhibitors ( Sigma ) . Protease inhibitors were added to all solutions in this protocol with the exception of low salt wash buffer . Cells were transferred to DNA LoBind tubes ( Eppendorf ) in 1 ml of PBS . Cell fixation was performed by addition of 37% formaldehyde to 1% final concentration and rocking gently for 10 min at room temperature . 2M glycine was added to 0 . 128M final concentration . After centrifugation and washing with cold PBS , cell pellets were resuspended in 2 . 5 ml ice cold swelling buffer ( 5 mM PIPES pH 8 . 0 , 85 mM KCl , 0 . 5% NP-40 ) for 10 min on ice . Cell nuclei were pelleted and resuspended in 2 ml SDS lysis buffer ( 1% SDS , 10 mM EDTA and 50 mM Tris-HCl , pH 8 ) . Lysed nuclei were sonicated on ice to yield approximately 500-bp DNA fragments using a Branson Sonifier 450 . The extent of DNA fragmentation was confirmed by gel electrophoresis of aliquots of the sonicated nuclear preparation . After extract clearing by centrifugation , supernatants were diluted 1∶5 in CHIP dilution buffer ( 0 . 01% SDS , 1% Triton X-100 , 1 . 2 mM EDTA , 16 . 7 mM Tris-HCL , pH 8 and 167 mM NaCl ) . Rabbit polyclonal IgG ( Bethyl ) 1 µg/ml and 50 µl/ml of 50% Protein-A agarose slurry were used to preclear supernatants for 2 hour . Protein-A beads were pelleted , and supernatants were used for immunoprecipitation . 2% of each supernatant was reserved for use as input samples . 8 ug anti-CTCF ( Millipore ) or Rad21 ( Bethyl ) antibody was added and the tubes were rocked at 4°C overnight . 30 µl/2 ml of 50% Protein-A agarose slurry was added and incubated for 2 hours at 4°C with rotation . The tubes were centrifuged rapidly and the beads were washed 3 times with cold low salt wash buffer ( 0 . 1% SDS , 1% Triton X-100 , 2 mM EDTA , 20 mM Tris-HCl , pH 8 . 1 and 150 mM NaCl ) and once with cold TE buffer . Antibody-protein complexes were eluted 6 times with freshly prepared , pre-heated elution buffer ( 1% SDS , 0 . 84% NaHCO3 ) at 65°C . Total elution volume was 1 ml for each immunoprecipitation . Sodium chloride was added to the elutions and input samples to a final concentration of 200 mM NaCl and heated at 65°C for 4 hours . RNase A and proteinase K were added to digest RNA and protein . Finally , DNA was purified from the eluted samples using Qiaquick PCR Purification Kit ( Qiagen ) according to the manufacturer's protocol . After DNA purification , libraries were constructed from the chromatin-immunoprecipitated DNA and input samples using the ChIP-Seq DNA sample prep kit ( Illumina , San Diego , CA ) . Single-end reads of 50 cycles were sequenced on an Illumina HiSeq2000 platform . Sequence reads were mapped to the KSHV genome ( NC_009333 . 1 ) . Library preparations , Illumina sequencing and sequencing data analysis were performed by the University of Utah Huntsman Cancer Institute Microarray facility . Total cellular RNA was isolated from washed cell pellets using Qiazol and Qiagen miRNeasy columns according to the manufacturer's protocols . mRNA was purified from 6 µg total RNA using Qiagen Oligotex mRNA Midikit ( Qiagen ) . cDNA libraries were prepared using the ABI high Capacity cDNA Reverse Transcription Kit with RNase inhibitor ( Applied Biosystems ) . Real-time Quantitative PCR ( qPCR ) was performed with SYBR green PCR Master Mix ( Applied Biosystems ) according to the manufacturer's protocol . Each sample was analyzed in triplicate with gene specific primers and β-actin was used as the endogenous control . The gene-specific primers were as follows: ORF6-2093F: 5′-CTGCCATAGGAGGGATGTTTG-3′; ORF6-2158R: 5′- CCATGAGCATTGCTCTGGCT-3′ ORF25-3733F:5′-CTCGGCGACGTGCTATACAAT-3′; ORF25-3803R: 5′-TGCCGACAAGGACTGTACATG-3′; ORF47 Q1F: 5′-AGCCTCTACCCTGCCGTTGTTCT-3′; ORF47 Q1R 5′-ACGACCGCGACTAAAAATGACCT-3′; ORF57 Q1-5: 5′-GCAGAACAACACGGGGCGGA-3′ ORF57Q2-3′:5′-GTCGTCGAAGCGGGGGCTCT-3′ ORF59 Q1F , 5′-CTCCCTCGGCAGACACAGAT-3′; ORF59 Q1R , 5′-GCGTGGTGCACACCGACGCCC-3′; K2-430F: 5′-ACCCTTGCAGATGCCGG-3′; K2-494R: 5′- GGATGCTATGGGTGATCGATG-3′ K5 Q1F: 5′-TAAGCACTTGGCTAACAGTGT-3′ K5 Q1R: 5′-GGCCACAGGTTAAGGCGACT-3′ vIRF-1_lytF: 5′-CGGCATAGCTGTGCTTACCA-3′; vIRF-1R: 5′- CATTGTCCCGCAACCAGACT-3′; PAN Q1F , 5′-CCGCCGATTGTGGGTTGATT-3′; PAN Q1R , 5′-TTTTGTTCTGCGGGCTTATGGAG-3′; B-actin Q1F: 5′-TCAAGATCATTGCTCCTCCTGAG-3′ B-actin Q1R: 5′-ACATCTGCTGGAAGGTGGACA-3′ RNA samples from iSLK cells were prepared using Qiagen miRNeasy kits . 1 . 5 µg of each RNA were poly ( A ) selected , and libraries were prepared using the Illumina TruSeq RNA sample preparation protocol ( catalog no . RS-930-2001 ) and validated using an Agilent Bioanalyzer . RNA sequencing libraries were sequenced ( 50 cycle single-end reads ) using an Illumina HiSeq2000 instrument . To induce KSHV lytic gene expression or virus replication . iSLK cells were treated with 1 ug/ml doxycycline . Cells were harvested at 24 or 48 hr for RNA preparation . For virus production , supernatants of the cells were harvested 5 days after induction , cleared by centrifugation twice , and filtered through a 0 . 80 µM pore-size cellulose acetate filter . Serial dilutions of supernatants were used to infect 293T cells . 48 hours after infection , flow cytometry was performed on samples in which 20∼40% of the infected cells were GFP positive . Based on the dilution factor , virus titers in the iSLK cell supernatant were calculated . Pellets of the cells from which supernatant was harvested were processed for DNA isolation using Qiagen DNeasy Blood and Tissue kit . 50 ng of each DNA were used for qPCR using primers specific for ORF59 ( see above ) and SYBR green PCR MasterMix ( ABI ) .
In order to investigate the potential role of CTCF as a host restriction factor for KSHV lytic replication and reactivation from latency , we specifically depleted KSHV infected cells of CTCF prior to inducing lytic replication . Robust and synchronous reactivation of KSHV from latency was achieved by using SLK cells stably transduced with a doxycycline-inducible viral transactivator , KSHV ORF50/RTA [27] . These RTA-inducible SLK cells ( iSLK ) were infected with the Bac16 KSHV strain that expresses hygromycin resistance and GFP [28] . Infected cells were 100% GFP positive when maintained under hygromycin selection ( data not shown ) . Highly efficient CTCF depletion was achieved by lipid-mediated transfection of iSLK cells with siRNA specific for CTCF ( Figure 1A ) . In order to assess the effect of CTCF depletion on KSHV reactivation and virion production , cells were transfected with either CTCF-specific siRNA or control siRNA and treated with doxycycline 48 hours later . KSHV reactivation was allowed to proceed and virion-containing supernatant was harvested 120 hours after induction of lytic replication with doxycycline . Infectious virus production was measured by infection of 293 cells with serial dilutions of virus supernatant followed by flow cytometry of infected cells . Virus titer in the supernatant can thus be accurately quantitated as GFP-transducing units . As shown in Figure 1B , CTCF depletion prior to induction of lytic replication led to a marked increase in virion production ( 20–25 fold ) , compared to control cells induced to replicate . There was no visible or flow cytometry-detectable release of virus without doxycycline-induced RTA expression from either CTCF depleted cells or in control cells , indicating that RTA is still absolutely required for lytic replication ( data not shown ) . Previous investigations of the role of CTCF in KSHV replication in PEL cells detected no effect of CTCF knockdown on KSHV lytic replication [24] . This is therefore the first demonstration of CTCF acting as a restriction factor for KSHV virus production . CTCF may act as a transcriptional activator or inhibitor by a variety of mechanisms , including alteration of chromosomal conformation by formation of intrachromosomal loops . Previous studies have reported decreased transcription of several lytic KSHV genes upon partial CTCF knockdown , indicating CTCF-mediated transcriptional activation [12] , [24] . Our experiments suggested that CTCF might also repress KSHV lytic genes , leading to increased virus production when CTCF was completely depleted . In order to determine if the increased KSHV replication observed when CTCF was knocked down in SLK cells might be due to transcriptional mechanisms , we assessed changes in mRNA levels of representative KSHV lytic genes by qPCR after CTCF knockdown . Cells were transfected with CTCF or control siRNA and cellular RNA was isolated 48 h after lytic replication was induced as previously described . While ORF57 ( early ) and ORF6 ( early ) lytic mRNA expression were enhanced approximately four-fold by CTCF depletion , there was a less significant increase in other early ( ORF59 ) or late ( ORF25 ) lytic mRNAs ( Figure 2 A–D ) . In addition , expression of PAN RNA , a nuclear non-coding polyadenylated RNA important for lytic reactivation [32] , was not enhanced by CTCF depletion ( Figure 2E ) . It therefore appeared that CTCF knockdown might enhance expression of KSHV genes in a gene-specific manner , consistent with transcriptional repression due to site-specific binding . CTCF binds at specific sites on the KSHV genome during latency and mediates intrachromosomal interactions , primarily between the ORF50 region and the major latency region [12] , [24] , [25] . Since CTCF appeared to play a role in restricting productive KSHV replication , it seemed likely that CTCF dissociation from one or more sites might occur upon lytic reactivation . A comprehensive analysis of dynamic changes in CTCF binding during reactivation from latency has not been previously performed . We therefore performed ChIP-Seq studies on iSLK cells at serial times after induction of lytic replication to characterize CTCF binding to the KSHV genome during the process of reactivation from latency . It should be noted that the system employed in these studies does not require sodium butyrate or other chemical inducers , which have broad effects on gene expression and epigenetic state . Rather , induction of lytic KSHV replication in iSLK cells relies solely on transcriptional activation by KSHV RTA . After treatment with doxycycline to induce RTA expression and lytic replication , we harvested cells at 0 , 3 and 5 days after induction . Cells were treated with formaldehyde to cross-link DNA and protein , followed by DNA fragmentation and immunoprecipitation with anti-CTCF antibody . Immunoprecipitated DNA and input DNA were then analyzed by high-throughput DNA sequencing . The results , shown in Figure 3 , reveal several important aspects of dynamic CTCF changes during KSHV reactivation . First , the high resolution map provided by the deep sequencing identifies at least thirty distinct areas of CTCF localization during latency . All contain high-probability sequence motifs and are consistent with previously published literature [24] , [26] , [33] . Second , there are clearly broad regions in which CTCF binding decreases as lytic replication progresses . Importantly , however , wholesale eviction of CTCF from the genome does not occur . Rather , binding at most sites in the latency gene locus , from approximately nt 117 , 000 to the 3′ end of the genome remains preserved ( blue bar ) . Similarly , binding at the major CTCF site at approximately nt 52 , 000 ( red arrow ) is also maintained . Further evidence of the site-specific nature of these dynamic changes in CTCF binding is evident at another site ( blue arrow ) where CTCF occupancy is maintained despite its loss at neighboring sites . Previous work in lymphoma cells had indicated that cohesin components , including Rad21 , but not CTCF , repress KSHV immediate-early gene expression [24] . Since CTCF depletion alone led to greatly increased KSHV virion production , and cohesin is known to bind to many CTCF sites , it was of interest to determine the effect of cohesin disruption on KSHV replication in our system . Cohesin is a complex of four core proteins , SMC1 , SMC3 , SCC1/Rad21 and SA1/2 that encloses chromatids and may act to facilitate intrachromosomal looping . Depletion of Rad21 effectively disrupts cohesin function in DNA binding and transcriptional regulation [34] . Rad21 knockdown was therefore carried out with Rad21-specific siRNA , and KSHV virion production after induction of replication was measured , as was done in CTCF knockdown experiments ( Figure 4 ) . Virus production after Rad21 depletion was compared to virus production in cells transfected with control siRNA and revealed that Rad21 depletion enhanced KSHV virion yield even more robustly than CTCF depletion ( approximately 90-fold , Figure 4A ) . In subsequent experiments , CTCF depletion was performed in parallel with Rad21 depletion and confirmed that Rad21 represses KSHV virion production more efficiently than does CTCF ( Rad21 depletion enhanced virus production approximately 130-fold versus 20-fold for CTCF depletion , Figure 4B ) . To determine whether the effect of Rad21 or CTCF KD on infectious KSHV virion production was due to increased KSHV replication , we measured KSHV genome copy number by qPCR on DNA samples from cells that were induced to replicate after KD of either CTCF or Rad21 . The results demonstrated that the KSHV copy number in each sample correlated extremely well with the increases in infectious virion titer . KD of CTCF or Rad21 led to approximately 20-fold or 150-fold increases in copy number , respectively ( Figure 4C ) . Completeness of Rad21 and CTCF depletion was verified by Western blotting of lysates from siRNA-transfected cells ( Figure 4D ) . These experiments were repeated with a completely different pool of siRNAs and a different control siRNA . The results were consistent with those shown above ( Figure S1 ) . In order to ensure that the effects of siRNA depletion were not due to adventitious effects of siRNA carryover during infection , we performed infections of 293 cells with virus-containing supernatant and added supernatant from siRNA-transfected but uninduced cells , which had no effect on virus titers measured by flow cytometry ( Figure S2 ) . These data demonstrate that Rad21 , although it is thought to bind primarily at CTCF sites , has effects independent of CTCF binding , and is an even more potent repressor of KSHV replication . Although cohesin is known to bind to many CTCF sites , the binding patterns of cohesin and CTCF to the human genome are not completely concordant [34]–[36] . Since Rad21 depletion appeared to have much more potent effects on KSHV lytic replication than CTCF depletion , it was critical to map the binding of Rad21 during lytic replication and compare its pattern to that of CTCF binding during the same period . We therefore performed a ChIP-seq analysis of Rad21 localization analogous to that conducted for CTCF . KSHV-infected iSLK cells were treated with doxycycline , and DNA was harvested for ChIP at 0 , 3 and 5 days post-induction . Several significant differences between Rad21 and CTCF binding were immediately revealed by the ChIP-Seq analysis ( Figure 5 ) . Comparison with the previously described CTCF experiment demonstrates that there are twelve major peaks of Rad21 binding , significantly fewer than for CTCF . These are consistent with previously identified cohesin-binding sites but include at least one additional novel Rad21 binding locus at nt 28819–29553 ( 24 , 26 ) . In addition , the profile of Rad21 differs from that of CTCF , with most peaks being much narrower , and the relative ratios of the major peaks differing from those of CTCF . Finally , and most interestingly , the eviction of Rad21 was much more rapid and generalized . Thus residual Rad21 binding at 72 h was only detectable at the two loci centered at approximately nucleotides 124 , 000 and 136 , 000 , whereas the loss of CTCF binding was more gradual , and fully evident only by 5 days , in addition to being more site-specific . At 72 h , the input KSHV DNA copy number was only increased by 2 . 5 fold when measured by qPCR or estimated by viral read number in the ChIP-seq input samples , whereas Rad21 binding was absent at most sites . These data suggest that not only does Rad21 not bind to newly replicated genomes but that it is removed from pre-existing latent genomes . To determine whether the changes in CTCF and Rad21 occupancy of the KSHV genome during lytic replication were associated with overall changes in the cellular levels of these proteins during KSHV reactivation , we performed immunoblotting of cell lysates harvested at serial time points when ChIP-Seq was performed . There was no detectable difference in the overall levels of either protein during the time period during which ChIP-seq was performed ( Figure 5B ) . The stimulatory effects of CTCF and Rad21 knockdown on KSHV production suggested that both proteins exert restrictive effects on KSHV lytic replication . Rad21 depletion led to significantly greater increases in KSHV yield , suggesting that Rad21 and CTCF might have unique effects on the transcription of KSHV lytic genes . In order to perform a comprehensive analysis and comparison of the effects of CTCF and Rad21 on the KSHV transcriptional profile , we performed high-throughput deep sequencing of mRNA from KSHV-infected cells in which either CTCF or Rad21 was depleted prior to induction of lytic replication . KSHV-infected iSLK cells were transfected with either control siRNA , CTCF siRNA or Rad21 siRNA as was done in the experiments to examine the effect on virion production . 48 hours after siRNA transfection , cells were treated with doxycycline to induce KSHV lytic replication , and cells were harvested at 24 and 48 hours after induction of replication . RNA was isolated , oligo-dT selected , and processed for deep sequencing . The effects of both CTCF and Rad21 knockdown on lytic cycle transcription were compared to each other and to the transcriptional profile of induced cells transfected with control siRNA . A comparison of the transcriptional profiles over time from each sample ( control , CTCF-depleted and Rad21-depleted ) is presented in Figure 6A , with the read counts normalized against the read counts in the induced control siRNA sample . The first somewhat surprising finding is that transcription of most KSHV genes actually decreases at 24 hours in the CTCF and Rad21 depleted cells compared to control . This is particularly evident in the CTCF-KD case , but is reduced overall by either CTCF-KD or Rad21-KD , suggesting that CTCF and Rad21 initially act as positive factors in lytic gene expression ( Figure 6A and Figure S3 ) . However , by 48 hours , lytic transcription of most genes is increased compared to control when CTCF is depleted . This biphasic effect on KSHV transcription was also evident upon Rad21 KD , with levels of the majority of lytic transcripts being increased by 48 hours . The ultimate enhancing effect of Rad21 on lytic gene transcription was even more pronounced than that of CTCF depletion , demonstrating that the two proteins have similar but distinct effects on lytic gene transcription . In order to allow a more precise comparison , these data were analyzed by comparing read counts for each KSHV gene and the results are presented as binary comparisons between control versus CTCF KD and control versus Rad21 KD in Figures 6B and 6C , respectively . The net effect of CTCF on KSHV lytic gene expression is clearly repressive , as there was increased accumulation of virtually all lytic cycle gene transcripts by 48 hours when CTCF was depleted ( Figure 6B ) . The effect of Rad21 depletion on the transcriptional profile at 48 hours was very similar to that of CTCF , with an increase in expression of most lytic cycle genes ( Figure 6C ) . Consistent with its effect on virus production , the enhancement of gene expression due to Rad21 KD was significantly greater than the effect of CTCF KD for most genes . Whereas most mRNA levels were increased approximately 2–3 fold by CTCF KD , the increase was in the 4–8 fold range when Rad21 was knocked down ( Figure 6B and Figure 6C ) . It should be noted that these increases in lytic mRNA levels due to CTCF KD and Rad21KD are superimposed on those observed as a consequence of induced lytic replication in NC SiRNA cells - which were several orders of magnitude ( 16-fold to 1000-fold ) greater than in uninduced cells ( Figure S4 ) . When the effect of CTCF or Rad21 on early versus late lytic genes was compared , there was no significant difference overall based on the known temporal class of gene expression . The mean fold-change in early gene transcript levels was 3 . 3+/−2 . 1 S . D versus 4 . 5+/−1 . 2 S . D . for late genes . Comparison of CTCF KD and Rad21 KD also demonstrates that these differences in the magnitude of the Rad21 versus CTCF effects were not uniform across the genome , i . e . there were specific individual differences in mRNA abundance due to CTCF KD versus Rad21 KD . This is most clearly evident in two such regions highlighted by black bars in Figure 6A . These regions , which include the vIRF genes and ORF65 , ORF66 , ORF67 and ORF67A , demonstrate decreased expression with CTCF KD and increased expression with Rad21 KD . A third group of genes was also readily evident in the comparison of transcriptomes generated from CTCF-depleted and Rad21-depleted cells . This group consisted of genes whose abundance decreased with CTCF and Rad21 KD at 24 h and remained depressed compared to control at 48 h , suggesting that unlike the majority of genes , they are particularly dependent on CTCF and Rad21 for efficient expression . This group of genes in two clusters ( denoted by blue bars , Figure 6A ) includes K2 , K4 , K5 , K6 , K7 , ORF68 and ORF69 ( Figure 6B and Figure 6C ) . The magnitude of the overall changes in transcription of individual lytic genes due to CTCF or Rad21 knockdown were reproducible but relatively modest ( 2–8 fold over control ) compared with the increases observed in virion production under the same conditions . At least 18 million reads were measured for each sample in the RNA-Seq analyses , which should allow accurate quantification of mRNA levels for all KSHV transcripts , which are abundantly expressed during lytic replication [37] . We therefore performed qPCR for selected mRNA targets to validate and confirm the RNASeq data . ORF57 is representative of the vast majority of genes whose expression was similarly upregulated by both CTCF and Rad21 KD ( Figure 7A ) . The increase in ORF57 expression measured by qPCR upon CTCF or Rad21 KD was approximately 3 . 6 fold over control , which correlates well with the increases measured by RNASeq ( 4 fold ) . A second group of genes that were differentially regulated by CTCF and Rad21 is represented by vIRF1 and ORF47 . Expression of both genes was not significantly changed by CTCF KD but was upregulated 5-fold by Rad21 KD ( Figure 7B and 7C ) . The third group of genes , those whose expression was reduced by both CTCF KD and Rad21 KD , and are thus dependent on CTCF and Rad21 for expression , is represented by K2 and K5 ( Figure 7D and 7E ) . Expression of both genes was confirmed to be reduced to 20% of control by both CTCF and Rad21 KD . Although induction of lytic KSHV replication in this system was dependent on expression of RTA/ORF50 from a transgene under the control of a tetracycline-responsive promoter , it was still possible that significant amounts of RTA/ORF50 protein were produced from endogenous KSHV transcripts . In order to determine whether ORF50 levels were altered by CTCF or Rad21 KD , and thereby responsible for some of the observed transcriptional changes , we directly measured ORF50 protein levels at the same time points at which RNA-Seq was performed . Immunoblotting of protein lysates from cells at 24 hrs and 48 hrs after induction of lytic replication revealed no significant increases in ORF50 protein levels when either CTCF or Rad21 depletion was carried out prior to induction ( Figure 8A ) . In fact , a slight decrease in ORF50 protein was observed at 48 h in all cases . In order to address the possibility that CTCF or Rad21 might inhibit ORF50 function per se , we conducted the following experiment in which we asked whether CTCF or Rad21 KD affects the ability of ORF50 to activate RTA-responsive promoters in KSHV-negative cells . We performed luciferase assays with cells transfected with an RTA-responsive reporter plasmid and an RTA expression plasmid after either CTCF , Rad21 or control KD . The results shown in Figure 8C , demonstrate that CTCF and Rad21 do not inhibit RTA function in the reporter assay . Rather CTCF or Rad21 depletion actually resulted in slightly decreased RTA activation function . These results together demonstrate that the global effects of CTCF and Rad21 on KSHV lytic gene expression are not likely to be mediated via effects on RTA expression or function .
In this study we report several novel aspects of the role of CTCF and cohesin as regulators of KSHV virus production . First , both CTCF and Rad21 act as host restriction factors for lytic KSHV replication as depletion of either protein resulted in markedly increased production of infectious virions . Rad21 appears to exert a greater effect , as Rad21 knockdown resulted in nearly 100-fold increases in virus yield , approximately five times more than the increase caused by CTCF knockdown . We also demonstrate that both CTCF and Rad21 dissociate from viral genomes during the process of lytic KSHV replication . Rad21 binding is lost earlier and more completely than CTCF after lytic KSHV replication begins . The almost complete loss of Rad21 from the majority of KSHV genome sites indicates eviction from latent episomes early during lytic replication as well as a lack of binding to newly replicated genomes . Conversely , the persistence of Rad21 at the major latency region and the terminal repeats indicates that Rad21 not only remains bound to template genomes but that it binds to nascently replicated genomes at these two sites . CTCF also exhibited site-specific changes in KSHV genome occupancy during lytic replication . CTCF occupancy was decreased by 3 days , and by 5 days , the relative occupancy at most sites was reduced by over 50% , indicating that CTCF binding also does not occur to newly replicated genomes at these locations . The finding that CTCF depletion results in increased virus production is in contrast to those of Chen et . al . who did not observe any effects of CTCF knockdown on KSHV lytic transcription in PEL cells [24] . These differences may be due to the different cell lines employed , and to the fact that knockdown in the our experiments was essentially complete , with no detectable CTCF remaining at the time of lytic induction . Our findings that cohesin and CTCF may play distinct roles in regulating KSHV reactivation and virion production are mirrored by the differing effects of their knockdown on KSHV lytic gene transcription . Consistent with the more profound effects of Rad21 KD on virion production , Rad 21 depletion consistently led to greater increases in KSHV lytic gene expression than did CTCF KD . Further , depletion of the two proteins had distinguishable effects on the lytic transcriptional profile . Whereas Rad21 KD led to increases in several vIRF gene transcript levels , compared to control , CTCF KD led to decreases or no change in this subset of mRNAs . A similar pattern was observed in several other specific genes , highlighting the complexity of overlapping gene regulation by CTCF and cohesin . Another novel finding in our study is the kinetic profile of the effects of CTCF and Rad21 on lytic gene transcription . Upon induction of KSHV replication , lytic gene transcription increased several orders of magnitude at 24 hours , as expected , and increased further at 48 hours . When CTCF or Rad21 were depleted , the increases in lytic gene transcription were significantly depressed at 24 hours compared to control . This relative decrease in lytic transcription was reversed by 48 hours , when CTCF KD , and particularly Rad21 KD , resulted in greater accumulation of lytic transcripts than in the presence of either protein . These data suggest that at baseline , CTCF and cohesin act as stimulators of transcription of many KSHV lytic genes but that their net effect , exerted subsequently , is negative , resulting in overall restriction of transcription and virus production . What is the likely mechanism of cohesin and CTCF gene activation , followed by inhibition ? It has been suggested that cohesin binding to the promoter region of ORF50/RTA and secondary interactions with cohesin bound at the latency promoter have a repressive effect on ORF50 expression , which is required for lytic reactivation , thus acting as a proximal inhibitor of lytic transcription [24] . Our data suggest that the effects of cohesin on KSHV lytic gene transcription are more complex and global . First , lytic replication was initiated by expression of RTA in trans , essentially removing RTA as a limiting factor for lytic transcription . In addition , total levels of RTA protein were not affected by CTCF or Rad21 depletion . Finally , depletion of cohesin and CTCF actually resulted in less accumulation of KSHV transcripts at early times . These data are consistent with cohesin and CTCF initially acting as general stimulators of KSHV lytic transcription , similar to cohesin's effect on host cell genes [23] , [38] . Cohesin appears to stimulate transcription from promoters of genes to which it is bound by facilitating the transition from paused RNA polII to elongating polII [23] , [39] . In addition , cohesin increases polII occupancy at genes to which it binds , most likely by increasing enhancer-promoter contact via looping . Importantly , however , depletion of cohesin also decreases transcription at most genes which do not bind cohesin and do not contain paused promoters , likely due to cohesin effects on basal and specific transcription factors [23] , [40] . It is this latter mechanism which is most likely responsible for the globally decreased KSHV transcription seen at earlier times after cohesin depletion in our studies . The mechanisms by which CTCF and cohesin regulate herpesvirus transcription are likely to be significantly different from those operative on the human genome as herpesvirus lytic genes are virtually all unspliced and in close proximity to each other . Thus facilitation of enhancer-promoter interaction may be less important in regulation of herpesvirus transcription by cohesin . Combined with the relatively limited number of high density cohesin sites on the KSHV genome , the positive effects of cohesin on early lytic gene transcription are likely due to the indirect effects of cohesin on cellular transcription factors referred to above . What is the likely basis of the subsequent enhancing effects of cohesin depletion on lytic gene expression and RNA accumulation ? A possible mechanism is suggested by the requirement for DNA replication in cis for efficient transcription of late lytic herpesvirus promoters . The positive effects of DNA replication in cis on transcription may derive from topological changes facilitating access to transcription factors as well as relocalization of genomes to intranuclear replication compartments [41]–[43] . It is possible that the physical linkages between cohesin molecules at various sites on circular latent genomes constrain the molecule , limiting maximal transcription . The more robust effect of Rad21 depletion on transcription , and especially virus production , suggest that the linking effects of cohesin may be more important in this regard than CTCF . It also implies that cohesin binding , although coincident with CTCF , may not be completely abrogated by removal of CTCF . The distinct and separable nature of cohesin and CTCF functions is underscored by the subtle but clear differences in the KSHV transcriptional profile exerted by their individual depletion . An additional insight into the potential role of cohesin in regulating KSHV transcription is provided by an examination of the few genes whose transcript levels are depressed by cohesin depletion and remain suppressed at later times . These include several of the K transcripts , suggesting that they are particularly dependent on cohesin for their efficient expression . It is likely relevant that several of these same genes were previously identified as unique among KSHV genes in containing paused RNA polII at their promoters [44] . It has recently been demonstrated that cohesin is particularly important for transcription of eukaryotic promoters that contain paused RNA polII . Thus cohesin may play the same role at these particular KSHV promoters as it does at a subset of cellular promoters that contain paused RNA polII , facilitating transition to elongation [23] . Whether such pausing also occurs at the other KSHV genes whose expression is adversely affected by cohesin depletion ( e . g . ORF 68 , ORF69 ) or if there are other promoter properties that determine cohesin dependence is an interesting avenue for further study . In summary , CTCF and cohesin play distinct roles in regulating KSHV reactivation from latency at the level of mRNA transcription . Cohesin and CTCF appear to initially act as positive factors , facilitating transcription for the majority of KSHV lytic genes , but subsequently their presence limits transcription and virus production , potentially by topological effects on transcription . In contrast to its role in host cell gene regulation , cohesin may primarily play an inhibitory role in transcriptional control of the KSHV lytic cycle . With regards to its baseline stimulatory effects on transcription in KSHV , cohesin effects may primarily derive from global effects on transcription factors such as myc , as has been previously demonstrated with cellular promoters [23] , [40] . It is less likely that cohesin stimulates transcription by facilitating long-range enhancer recruitment to specific promoters as observed in cellular eukaryotic systems [22] , [23] . In addition , cohesin and CTCF appear to be required for activity of certain KSHV promoters that are particularly cohesin and CTCF-dependent , and these effects are possibly due to effects on paused RNA polII . During the process of KSHV virion production , cohesin , and to a lesser degree , CTCF , dissociate from latent KSHV genomes , implying a dynamic role for both in replication control . The importance of both proteins as host restriction factors regulating KSHV reactivation is demonstrated by the dramatic increases in virus yield that result from their depletion . | Kaposi's sarcoma-associated herpesvirus ( KSHV ) is a human virus that causes Kaposi's sarcoma and lymphoma . KSHV establishes a lifelong infection in B lymphocytes , and persists in a latent form as circular DNA molecules . Reactivation and replication yield infectious virions , allowing transmission and maintenance of latent infection . The cellular mechanisms controlling reactivation remain incompletely characterized . Host proteins that regulate RNA transcription play an important role in controlling viral reactivation . In this study , we used high-throughput techniques to analyze the binding of two cellular proteins , CTCF and Rad21 , to the KSHV genome as the virus reactivated to produce infectious virions . We found that these proteins dissociate from the latent genome when reactivation occurs . We also found that depleting cells of these proteins increases virus production as much as a hundredfold . Depleting the cell of CTCF or Rad21 caused complex changes in the synthesis of RNAs by KSHV , with the amounts of most KSHV RNAs increasing greatly . We also showed that Rad21 and CTCF are needed for the virus to synthesize RNAs efficiently . Our study provides new insights into how the cell uses CTCF and Rad21 to limit KSHV's ability to synthesize RNA and reactivate from latency to produce infectious virus . | [
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] | 2014 | CTCF and Rad21 Act as Host Cell Restriction Factors for Kaposi's Sarcoma-Associated Herpesvirus (KSHV) Lytic Replication by Modulating Viral Gene Transcription |
The macronuclear genome of the ciliate Oxytricha trifallax displays an extreme and unique eukaryotic genome architecture with extensive genomic variation . During sexual genome development , the expressed , somatic macronuclear genome is whittled down to the genic portion of a small fraction ( ∼5% ) of its precursor “silent” germline micronuclear genome by a process of “unscrambling” and fragmentation . The tiny macronuclear “nanochromosomes” typically encode single , protein-coding genes ( a small portion , 10% , encode 2–8 genes ) , have minimal noncoding regions , and are differentially amplified to an average of ∼2 , 000 copies . We report the high-quality genome assembly of ∼16 , 000 complete nanochromosomes ( ∼50 Mb haploid genome size ) that vary from 469 bp to 66 kb long ( mean ∼3 . 2 kb ) and encode ∼18 , 500 genes . Alternative DNA fragmentation processes ∼10% of the nanochromosomes into multiple isoforms that usually encode complete genes . Nucleotide diversity in the macronucleus is very high ( SNP heterozygosity is ∼4 . 0% ) , suggesting that Oxytricha trifallax may have one of the largest known effective population sizes of eukaryotes . Comparison to other ciliates with nonscrambled genomes and long macronuclear chromosomes ( on the order of 100 kb ) suggests several candidate proteins that could be involved in genome rearrangement , including domesticated MULE and IS1595-like DDE transposases . The assembly of the highly fragmented Oxytricha macronuclear genome is the first completed genome with such an unusual architecture . This genome sequence provides tantalizing glimpses into novel molecular biology and evolution . For example , Oxytricha maintains tens of millions of telomeres per cell and has also evolved an intriguing expansion of telomere end-binding proteins . In conjunction with the micronuclear genome in progress , the O . trifallax macronuclear genome will provide an invaluable resource for investigating programmed genome rearrangements , complementing studies of rearrangements arising during evolution and disease .
Oxytricha trifallax is a distinctive ciliate [1]—an ancient lineage of protists named for their coats of cilia . Like all ciliates , Oxytricha has two types of nuclei: a micronucleus , a germline nucleus that is largely transcriptionally inactive during vegetative growth , and a macronucleus , which is the transcriptionally active somatic nucleus [2] . Compared to the micronucleus , Oxytricha's macronucleus is massively enlarged due to ∼2 , 000-fold [2] amplification resulting from two rounds of DNA amplification [3] during development . In the model ciliates Oxytricha trifallax , Tetrahymena thermophila , and Paramecium tetraurelia , varying amounts of micronuclear DNA are deleted ( including the “internally eliminated sequences , ” or IESs , interspersed between “macronuclear destined sequences , ” or MDSs ) during conjugation or autogamy ( two forms of sexual development ) to give rise to the information-rich macronuclear genome ( Figure 1 ) . A much larger fraction of the Oxytricha micronuclear genome—∼96% of the micronuclear complexity [2]—is eliminated during the macronuclear formation than in the oligohymenophoreans , Tetrahymena and Paramecium ( which both eliminate ∼30% of their micronuclear genomes [4] , [5] ) . The most remarkable difference in macronuclear development between Oxytricha and the two oligohymenophoreans is that the micronuclear-encoded MDSs that give rise to the macronuclear chromosomes may be nonsequential , or even in different orientations in the micronuclear genome [6] . Consequently , unlike the oligohymenophoreans , Oxytricha needs to unscramble its micronuclear genome during macronuclear development . Two fundamental differences distinguish Oxytricha's macronuclear chromosomes from those of Tetrahymena and Paramecium: Oxytricha's chromosomes are tiny ( “nanochromosomes , ” with a mean length ∼3 . 2 kb reported in this study ) , each typically encoding just a single gene with a minimal amount of surrounding non-protein-coding DNA [7] , and they are differentially amplified ( Figure 2 and 3 ) [8] , [9] . In some cases , alternative fragmentation of macronuclear-destined micronuclear DNA produces different nanochromosome isoforms ( Figure 2 ) 10–12 , which may be present at very different levels of amplification ( differing by as much as 10-fold [13] ) . Gene expression and nanochromosome copy number may be moderately correlated [14] . Macronuclear chromosomes in all the model ciliates segregate by amitosis during cellular replication ( without a mitotic spindle ) [15] , —a process that may lead to allelic fixation 17–20 . In ciliates with nanochromosomes , major fluctuations of nanochromosome copy number [8] may arise , since copy number is unregulated during normal cellular replication [21] . Theoretical models propose that these fluctuations are a cause of senescence in these ciliates [22] . In contrast to the lack of copy number regulation during cellular replication , both genetic [23]–[25] and epigenetic mechanisms [9] , [26] may influence chromosome copy number during sexual development in ciliates . As a consequence of the extensive fragmentation of the Oxytricha macronuclear genome , each macronucleus possesses tens of millions of telomeres , an abundance that enabled the first isolations of telomere end-binding proteins [27] , [28] . Oxytricha also has micronuclear transposons bearing telomeric repeats ( C4A4 ) that resemble those of nanochromosomes . These telomere-bearing elements , or TBE transposons [29] , play an important role in macronuclear genome development [30] . The exact site of telomere addition may vary for some nanochromosome ends [31] and is followed by a roughly 50 bp subtelomeric region of biased base composition with an approximately 10 bp periodicity of the bias ( Figure 3 ) [32] , [33] . We report on the assembly and analysis of the first Oxytricha macronuclear genome , from the reference JRB310 strain . During and after assembly , we have addressed a number of challenges arising from the unusual structure of this genome , which we discuss . We focus on the most interesting and unique biological characteristics of this genome and place them in the context of the characteristics of the other sequenced ciliate macronuclear genomes .
To assemble the Oxytricha macronuclear genome for the type strain—JRB310 [1]—we chose to build upon three assemblies , from ABySS [34] , IDBA [35] , and PE-Assembler [36]/SSAKE [37] , based on Illumina sequences , and supplemented by a Sanger/454 assembly . To combine these assemblies , we developed a specialized meta-assembly pipeline ( see Materials and Methods and Figure S1 ) . Current genome assembly strategies for second-generation sequence data often employ multiple , hybrid strategies to overcome the experimental biases leading to low sequence coverage in particular genomic regions and repetitive DNA [38] . Since Oxytricha's macronuclear genome was expected to have a low repeat content [2] , repetitive DNA was expected to be a relatively insignificant issue , and thus even greedy genome assemblers were able to produce useful preliminary assemblies . However , unlike conventional genomes , the Oxytricha macronuclear genome provides assembly challenges by virtue of its fragmented architecture , variable processing ( “alternative chromosome fragmentation” ) , and nonuniform nanochromosome copy number . We resolved these challenges during and after assembly . The initial 454/Sanger genome assemblies contained a mixture of bacterial DNA , mitochondrial DNA , and up to two additional alleles other than those expected from the strain we originally proposed to sequence ( JRB310 ) due to accidental contamination by a commonly used strain in our lab ( JRB510—a complementary mating type ) , whereas the Illumina assemblies were produced from purified macronuclear DNA from the type strain ( JRB310 ) alone . Given these contamination issues , we built our final assembly with the Illumina assemblies as the primary data source , rather than the 454/Sanger assemblies , to maintain the purity of our final assembly . This excluded virtually all bacterial and mitochondrial contamination in our final assembly since very few contigs in the Illumina assemblies derive from these sources ( sucrose gradient purification of macronuclei eliminated almost all such contaminants ) that could potentially be extended by the 454/Sanger data . We also kept JRB510 allelic data to a minimum in our final assembly , ( i ) by preferring best extensions , which were most likely to be from the more similar JRB310 derived contigs or reads , either from the Illumina assemblies or from the Sanger/454 assemblies and raw Sanger data ( see Materials and Methods ) , and ( ii ) by the sequence consensus majority rule ( the most abundant base at each position from the assembled contigs ) of the CAP3 assembler [39] used to combine the three Illumina assemblies versus one 454/Sanger assembly during contig construction . The conclusion that our final assembly strategy succeeded in keeping JRB510 allelic information to a minimum is supported by matches to the three pure JRB310 Illumina starting assemblies . Our final assembly is 82 . 0% covered by identical BLAT matches ≥100 bp long to one of these pure JRB310 assemblies and 92 . 5% covered by 99 . 5% identity , ≥100 bp BLAT matches to these assemblies ( note that consensus building by CAP3 may result in alternating selection of JRB310 polymorphisms from the original assemblies , and hence even meta-contigs assembled from the pure JRB310 assemblies may have BLAT matches that differ from all the original assemblies ) . We chose to keep alleles apart by applying moderately strict criteria for merging during our meta-assembly ( e . g . , by merging contigs with overlaps at least 40 bp long and ≥99% identical with CAP3 [39]; see Materials and Methods ) . However , in order to maximize the number of complete nanochromosomes in our assembly , we collapsed some alleles ( i . e . , producing “quasi-nanochromosomes” derived from two alleles; see “Extensive Genome Homozygosity and High SNP Heterozygosity” ) . Merging of contigs is also complicated by alternative fragmentation , which affects ∼10% of the nanochromosomes and may either result in collapsing or splitting of nanochromosome isoforms ( see “Extensive Alternative Nanochromosome Fragmentation” ) . We discriminated between homozygous and heterozygous nanochromosomes after assembly ( see the next section ) . We have not attempted to determine the haplotypes of the heterozygous contigs due to computational complications arising from both alternative nanochromosome fragmentation and variable representation of alleles ( which need not be 1∶1 ) . A comparison of the Oxytricha macronuclear genome assemblies and meta-assembly is given in Table 1 ( also see Tables S11–S17 for the progressive improvements in the genome assembly through the successive steps of our meta-assembly approach shown in Figure S1 ) . Since the size selection used in the construction of our paired-end ( PE ) sequence library results in poor sequence coverage for a span of approximately 160 bp , roughly 100 bp from the telomeric ends ( see Materials and Methods ) , the incorporation of single-end ( SE ) sequence data allowed ABySS to assemble far more contigs with telomeric sequences than either IDBA or the PE-Assembler/SSAKE assembler combination , neither of which could use SE and PE sequences simultaneously ( Table 1 ) . The ABySS assembly is larger ( 78 . 0 Mb ) than the other assemblies ( 47 . 8 Mb for PE-Asm/SSAKE and 57 . 7 Mb for IDBA ) and also more complete , as evidenced by a higher fraction of reads that can be mapped to this assembly ( Table 1 ) . The ABySS assembly also incorporates a substantially higher proportion of telomeric reads than the other two assemblers ( 91 . 8% for ABySS versus 45 . 4% for PE-Asm/SSAKE and 42 . 4% for IDBA ) and contains a larger proportion of telomere-containing contigs ( 66 . 5% versus 18 . 3% for PE-Asm/SSAKE and 8 . 6% for IDBA ) and longer contigs ( mean length of 2 , 273 bp for ABySS versus 2 , 090 bp for PE-Asm/SSAKE and 1 , 204 bp for IDBA ) . Consequently , the ABySS assembler produced almost an order of magnitude more full-length nanochromosomes than the other two assemblers . Even though the ABySS assembly incorporates more telomeric reads than the other assemblies , it also excludes a higher proportion of telomeric reads than nontelomeric reads ( 92% telomeric PE reads versus 98% total PE reads map to the assembly; telomeric reads comprise ∼13% of all the reads ) . While the ABySS assembly appears to be the most complete , the majority of its contigs ( 81 . 3% ) are still missing one or both telomeres . The initial meta-assembly of the ABySS , IDBA , and PE-Asm assemblies yielded a modest improvement in the total number of full-length nanochromosomes relative to ABySS alone , with the ratio of full-length nanochromosomes to contigs increasing from 21% to 24% of the total number of contigs . Since the meta-assembly was still highly fragmented , and our aim was to assemble full-length nanochromosomes with complete genes , we developed a strategy that consisted of two rounds of extension of nontelomeric contig ends and reassembly ( see Materials and Methods ) . This strategy produced an assembly where the majority ( 77% ) of the contigs had both 5′ and 3′ telomeres . For the final meta-assembly , the average contig length ( 2 , 982 bp ) is longer than that of any of the original assemblies ( 2 , 273 for ABySS versus 2 , 090 for PE-Asm/SSAKE and 1 , 204 for IDBA ) and the read coverage is as high as or higher than the most complete ABySS assembly ( 98 . 0% coverage for PE reads for ABySS and the final assembly; 88 . 2% SE read coverage for ABySS and 88 . 5% SE read coverage for the final assembly ) . However , a larger fraction of telomeric reads than nontelomeric reads still do not map to the final assembly ( e . g . , 9 . 0% of telomeric PE reads versus 2 . 0% of all PE reads do not map to the assembly ) , indicating that some telomeric regions are still missing from the final assembly . Since there are currently no published effective population size estimates for Oxytricha trifallax , we wanted to obtain an estimate from allelic diversity of the macronuclear genome . Furthermore , current estimates of effective population size for other free-living model ciliates , Paramecium and Tetrahymena , differ [40]–[42] , so additional estimates from other species will be necessary to determine if there are general trends in population size within ciliates . Given our assembly conditions , we expect many allelic sequences to co-assemble , but visual inspection of reads mapped to the final assembly suggested that a substantial fraction of the genome is homozygous . A trivial explanation for this observed homozygosity is that the micronuclear genome regions ( MDS ) that form the nanochromosomes are homozygous , however it is also possible that a combination of other factors may be responsible for some of the observed homozygosity . These factors include both nanochromosomal allelic drift , arising from stochastic nanochromosome segregation during amitosis ( during normal cellular replication ) and nanochromosomal allelic selection , both of which could lead , in principle , to haplotype fixation ( also known as “allelic assortment” ) , as well as allelic biases introduced during conjugation . Some well-studied macronuclear nanochromosomes , including the 81 locus [43] , and the nanochromosomes encoding the telomere end-binding proteins α and β ( Contig22209 . 0 and Contig22260 . 0 ) are homozygous in the Oxytricha JRB310 strain upon which our reference macronuclear genome assembly is based . Knowledge of the fraction of homozygous and heterozygous nanochromosomes is also necessary to obtain a reasonable estimate of macronuclear genome size . To determine nanochromosomal homozygosity , we focused on nonalternatively fragmented nanochromosomes in order to avoid both ambiguous alignments and possible false identification of heterozygosity due to the presence of alternative telomere locations . Of the nonalternatively fragmented nanochromosomes , 66% ( 7 , 487 out of 11 , 297 ) had no substantial BLAT [44] nonself matches ( ≥100 bp and ≥90% identical; default BLAT parameters ) to any other contig in the final assembly ( “matchless” nanochromosomes ) . Matchless nanochromosomes with variants present at ≥0 . 5% of the positions were considered heterozygous ( see Materials and Methods for our precise definition of heterozygosity ) ; otherwise they were considered to be homozygous . Note that our read mapping cutoff may reduce polymorphism estimates by filtering out reads with more polymorphisms ( see Text S1 , “Read Mapping Rationale” ) . These criteria overestimate low frequency variants at lower coverage sites and underestimate higher frequency variants at lower coverage sites ( Figure S2 ) but comprise a small proportion of all the sites ( e . g . , 11 . 8% of sites identified as heterozygous are at 20–40× coverage ) . By these criteria , the well-characterized Oxytricha actin I [45] , [46] nanochromosome ( Contig19101 . 0 ) was correctly classified as heterozygous , with variants at 0 . 89% of the examined positions ( 12/1 , 350 ) . Mismapped reads do not affect the identification of the heterozygous sites in this nanochromosome , since only two of the reads mapped to this nanochromosome map to any of the other contigs . For the actin I nanochromosome , the frequency of allelic variants varies from just over 5% ( three positions ) to 13 . 1% ( mean 8 . 7% ) corresponding to a roughly 1∶11 ratio of the minor∶major allele . Of the matchless nanochromosomes , 63% have sequence variants identified at 0%–0 . 5% of positions; hence , 37% of matchless nanochromosomes are classified as heterozygous by this criterion . Read mapping appears to be adequately sensitive to detect most SNPs ( single nucleotide polymorphisms ) , since the mean number of reads per bp mapped to heterozygous and homozygous nanochromosomes is almost identical ( see “Nanochromosome Copy Number Is Nonuniform” ) . Approximately 42% of nanochromosomes are homozygous when the proportion of putative homozygous nanochromosomes is calculated from the total number of matchless and matched nanochromosomes . The high levels of macronuclear genome homozygosity agree with preliminary observations of micronuclear sequence data for this strain ( Chen et al . , unpublished ) , suggesting that the majority of nanochromosomal homozygosity may derive from homozygosity in the micronuclear genome , rather than other possible factors ( allelic assortment and/or developmental biases ) . Once the micronuclear genome is more complete , it will be possible to assess how much these factors have contributed to the observed homozygosity . Nevertheless , the abundance of homozygous nanochromosomes in the final assembly ( ∼42% ) suggests that the wild-isolate JRB310 [47] may actually be substantially inbred and that this inbreeding arose at its source . Deleterious inbreeding effects may contribute to the complexity of Oxytricha trifallax mating types [47] . It will be interesting to determine whether the two “promiscuous” Oxytricha strains ( JRB27 and JRB51 [47] ) that mate with the broadest set of other mating types are less inbred . Sequence polymorphisms are abundant in the Oxytricha macronuclear genome: excluding the homozygous nanochromosomes ( which may have arisen from inbreeding ) , the mean SNP heterozygosity is 4 . 0% ( SD = 1 . 8%; Figure 4 ) . From mapped reads , for heterozygous matchless nanochromosomes , mean SNP heterozygosity is 3 . 1% ( SD = 1 . 3% ) , and for heterozygous matched nanochromosomes , it is 4 . 6% ( SD = 1 . 9%; Figure 4 ) . For alignments of heterozygous matched nanochromosomes ( with BLAT matches ≥100 bp and ≥90% identical to each other ) produced by MUSCLE ( for nanochromosome pairs where one of the nanochromosomes is no more than 10% longer than the other and for alignments with ≤15% differences ) , mean SNP heterozygosity is 3 . 0% ( SD = 2 . 5% ) . These estimates of SNP heterozygosity indicate that assembly has masked a substantial amount of allelic variation . Similar statistics were obtained for the subset of the final assembly's nanochromosomes that were present in the pure JRB310 strain ABySS assembly ( e . g . , heterozygous matchless mean SNP heterozygosity is 2 . 8% , SD = 1 . 2% , and for MUSCLE alignments of heterozygous matched nanochromosomes , mean heterozygosity is 3 . 2% , SD = 2 . 9% ) . Hence it is unlikely that any residual JRB510 strain allelic information in our final assembly has had a considerable effect upon our estimates of heterozygosity . Nevertheless , these are first estimates from a complex genome assembly , complicated by homozygosity due to potential inbreeding , and hence inferences based upon them ( including our subsequent population size estimate ) should be treated with caution until better estimates from the micronuclear genome and additional strains become available . At 4-fold synonymous sites from heterozygous nanochromosomes with matches ( see Materials and Methods ) , the mean SNP heterozygosity is 8 . 3% ( SD = 9 . 4% ) . This underestimates sequence diversity at 4-fold synonymous sites , since pairwise alignments of contigs underestimate SNP heterozygosity at all sites ( see previous paragraph ) . If we apply a correction for the missing SNP heterozygosity based on our overall estimate of SNP heterozygosity , we obtain an estimate of 11 . 1% mean SNP heterozygosity at 4-fold synonymous sites [8 . 3%× ( 4 . 0%/3 . 0% ) ] . This 4-fold synonymous site SNP heterozygosity is very high—even higher than the current SNP heterozygosity record holder , Ciona savignyi , which has 8 . 0% 4-fold synonymous site mean SNP heterozygosity [48] . These high levels of SNP heterozygosity suggest that Oxytricha trifallax has a large effective population size . Assuming a mutation rate μ ∼10−9 per base per generation , as in Snoke et al . 2006 [42] , for nucleotide diversity at 4-fold synonymous sites and π4S = 4Neμ , we estimate an effective population size of 2 . 6×107 . This effective population size is on the same order estimated for P . tetraurelia ( using silent site diversity , πS , which will yield a smaller population size estimate than one based on π4S ) [42] . However , this estimate of the P . tetraurelia effective population size may be an overestimate due to incorrect classification of species within the Paramecium aurelia species complex and may be closer to the order of 106 [40] . In contrast , the T . thermophila effective population size is estimated to be considerably smaller than Oxytricha's , at Ne = 7 . 5×105 for πS = 0 . 003 ( with μ = 10−9 ) [41] , [42] . In laboratory culture conditions , Oxytricha trifallax tends to replicate asexually and rarely conjugates ( resulting in meiotic recombination ) . Conjugation in the laboratory is induced by starvation as long as cells of compatible mating types are available . However , we do not know the frequency of conjugation relative to replication of Oxytricha trifallax in its natural environment . The relationships between the frequency of asexual reproduction , and additional population genetic factors arising from asexuality , such as the variance of asexual and sexual reproductive contributions , are complex and can result in increases or decreases in estimates of effective population size [49] , [50] . As a result , effective population size estimates for Oxytricha should be treated with caution until these factors are better understood . As indicated for the well-characterized actin I locus , which has a roughly 1∶11 ratio of minor∶major allelic variant , there may be substantial deviations from the expected 1∶1 ratio for the two possible allelic variants at each site . For matchless nanochromosomes , we found that the distribution of median nanochromosomal variant frequency ( i . e . , the median frequency of putative allelic polymorphisms ) is bimodal , with one mode close to the expectation at 40%–45% and the other at 5%–10% ( Figure 5; since the lower peak is bounded by the cutoff we chose to assess variants , the true lower peak may be lower than this ) . The bimodality of this distribution persists even if we only consider nanochromosomes where the mean coverage of the variant sites is high ( e . g . , at mean coverage of ≥110× at variant sites ) . Though some deviation from the 1∶1 variant ratio might result from allele-specific read mapping biases [51] , given the relatively relaxed read mapping parameters we used ( see Materials and Methods , “Read Mapping and Variant Detection” ) , the two variant frequency modes differ too much to explain the lower mode's existence . Instead , the deviation from the expected ratio may indicate that allelic assortment has occurred , or that there are developmentally specific allelic biases . Since a high proportion of nanochromosomes deviate substantially from the 1∶1 expected allelic ratio , it is also possible that allelic assortment has occurred for some nanochromosomes , which may contribute to the observed abundance of homozygous nanochromosomes . Nanochromosomes that deviate the most from the expected 1∶1 allelic ratio tend to have lower mean SNP heterozygosities , which likely reflects the diminished ability to detect SNPs with more distorted variant frequencies ( Figure 5 ) . We desired an estimate for the total haploid Oxytricha trifallax macronuclear genome size since it is unknown . To obtain a reasonable estimate , we needed to determine the extent of redundancy in our genome assembly . As judged by visual inspection of our original assemblies , the main sources of redundancy are ( i ) the two alleles from the partially diallelic genome ( see “Extensive Genome Homozygosity and High SNP Heterozygosity” ) , ( ii ) alternative nanochromosome fragmentation ( see “Extensive Alternative Nanochromosome Fragmentation” ) , ( iii ) erroneous base calling that may result from high copy number regions and relatively abundant sequencing errors , and ( iv ) paralogous genes . The assembly with the most redundancy—from ABySS ( Figure S3 ) —has approximately half of its contigs with nonself matches that are identical or almost identical ( matches that are ≥100 bp and ≥99% identical ) . Visual inspection of the ABySS assembly revealed that much of the redundancy arose from the combined effect of high copy number DNA and sequencing errors . Our assembly strategy eliminated most of the redundancy from erroneous base calling , because it collapsed regions that are nearly identical . A small quantity of additional redundancy may have also been introduced by the inclusion of non-reference ( JRB510 ) allelic sequences from the Sanger/454 genome assemblies , though the strategy we used prefers the inclusion of reference allelic sequences ( see Materials and Methods , “Princeton Illumina Assembly and TGI Sanger/454 Assembly Integration” ) . Though some redundancy remains in our final genome assembly , this is counteracted by ∼1/4 of the nanochromosomes that have had their alleles collapsed during the assembly ( see “Extensive Genome Homozygosity and High SNP Heterozygosity” ) . Given the ∼42% estimate of nanochromosomal homozygosity , we estimate that the haploid number of nanochromosomes is ∼15 , 600 [from 15 , 993+1 , 279 two- and multitelomere contigs and 5 , 303 single-telomere contigs ( Table 1 ) ; we also estimate that ∼10% of nanochromosomes are alternatively fragmented ( see “Extensive Alternative Nanochromosome Fragmentation” ) ] . With a mean nanochromosomal length of ∼3 . 2 kb , we estimate that the haploid macronuclear genome size is 50 Mb , which is similar to earlier experimental estimates [52] , [53] . Traditional assessments of genome completeness are not very meaningful in Oxytricha because they usually measure genomes of uniform coverage with relatively long chromosomes . In two key ways , the Oxytricha macronuclear genome assembly is more similar to a de novo transcript assembly than to a conventional genome assembly: it contains multiple nanochromosome isoforms produced by alternative nanochromosome fragmentation ( see “Extensive Alternative Nanochromosome Fragmentation” ) , and it is an assembly of nonuniformly amplified DNA ( see “Nanochromosome Copy Number Is Nonuniform” ) . Unlike RNA transcripts , nanochromosome levels remain relatively stable during asexual growth [22] , and variation of nanochromosome copy number is considerably lower than that of transcripts , so we are able to completely sample the genome's DNA over time . Simple genome metrics indicate that our assembly is largely complete . Firstly , we have sequenced the genome to a substantial depth: we have >62× haploid coverage of the genome assembly by Illumina 100 bp PE reads and >48× haploid coverage by SE reads . Secondly , nearly all high-quality reads map to our final assembly ( 98% of high quality PE reads ) and the majority of contigs ( 71 . 3% ) represent complete nanochromosomes , with only 5 . 1% of the contigs missing both telomeres and 23 . 6% missing one telomere ( Table 1 ) . Finally , our 50 Mb haploid genome assembly size estimate is similar to an earlier estimate of ∼55 Mb for the DNA complexity of the Oxytricha macronucleus [2] . To assess genome completeness we analyzed the completeness of two specific , functionally related gene sets—encoding ribosomal proteins and tRNAs—and one general gene data set in Oxytricha . All of these measures of completeness indicate that the macronuclear genome assembly is essentially complete . Firstly , the final genome assembly contains all 80 of the standard eukaryotic ribosomal proteins ( 32 small subunit and 48 large subunit proteins ) . Secondly , the Oxytricha macronuclear genome has a haploid complement of ∼59 unique tRNA nanochromosomes ( including a selenocysteine tRNA on Contig21859 . 0 ) . These tRNAs are sufficient to translate all of its codons if wobble position anticodon rules [54] are accounted for . As judged by searches of tRNAdb [55] , codons without cognate tRNAs in Oxytricha are either absent or rare in other eukaryotes . Furthermore , with the exception of a Tetrahymena glycine tRNA that has a CCC anticodon [56] , Oxytricha's tRNAs share the same anticodons as Tetrahymena . We also assessed the completeness of the macronuclear genome by searches of predicted proteins against 248 “core eukaryotic genes” ( CEGs: defined by KOGS [57] based on the complete protein catalogs of H . sapiens , D . melanogaster , C . elegans , A . thaliana , S . cerevisiae , and S . pombe [58] ) . Using a strategy similar to that used to assess completeness during analyses of ncRNAs in Oxytricha [59] , and based on the CEGMA analysis strategy [58] , we searched for all the core proteins using a match coverage of ≥70% of the mean CEG sequence length , accumulated over the span of the query CEG sequence matches from BLASTP ( BLAST+ [60]; with at least one of the matches for each query having an E-value≤1e-10 ) . Of our predicted proteins 231 had substantial sequence similarity to the core eukaryotic protein sequences . The numbers of core eukaryotic proteins we found in the latest Tetrahymena ( 223 ) and Paramecium ( 230 ) gene predictions were similar to those found in Oxytricha ( within the limits of the sensitivity of the searches we used and possible gene prediction failures ) . However , since CEGS are defined for just five genomes of animals , fungi , and one plant and exclude a diversity of other eukaryotes , the true set of CEGs may be somewhat smaller than this . Given the great evolutionary divergences of ciliates from these eukaryotes ( possibly in excess of 1 . 5 billion years ago [61] ) , it is also possible that the BLAST criteria employed by CEGMA are not sufficiently sensitive to detect more distant ciliate homologs . This suggests that the predicted proteomes of all three ciliates are largely complete . Given that the deep divergences of ciliates might prevent detection of their homologs to the remaining 17 CEGS without matches , we attempted more sensitive searches at the domain level using HMMER3 [62] . We assigned Pfam domains to each KOG if the domains were best Pfam hits to the majority of the members of each KOG . Using domain searches , 13 of the remaining 17 core proteins had matches in Pfam-A ( with domain , full-sequence E-values<1e-3; see Text S1 , “Pfam Domains Detected for CEGs Missing in Oxytricha” ) . With the exception of KOG2531 , these CEGs are relatively short , single-domain proteins . Of the four undetectable CEGs remaining after HMMER3 searches , one , KOG3285 , is an ortholog group corresponding to the MAD2 [63] spindle assembly checkpoint ( SAC ) protein . We were unable to detect homologs of additional SAC proteins such as MAD1 and MAD3 , suggesting that these checkpoint proteins have either been lost or that they are very divergent . The Tetrahymena macronuclear genome paper reported the absence of the checkpoint kinase CHK1 [56] , but this is difficult to establish unambiguously given both the considerable divergence of ciliate proteins from the model organisms in which this protein was discovered and that the single defining domain for this protein is the widely distributed and extremely common protein kinase domain ( PF00069 ) . There is no evidence of a mitotic spindle in ciliate macronuclei [16] , so they may not need SAC proteins , unlike conventional nuclei . It is also possible that the lack of these proteins contributed to the evolution of ciliate amitosis . However , micronuclei do appear to undergo a spindle-guided mitosis [2] , [16] . Since ciliates need to coordinate the division of multiple nuclei , their nuclear cycle checkpoints may be more complex than most eukaryotes; hence , they may use genes that are nonorthologous to conventional checkpoint genes in nonciliates . The other three undetectable CEGs—KOG0563 , KOG3147 , and KOG2653—correspond to three key oxidative pentose phosphate pathway ( OPPP ) enzymes: glucose-6-phosphate dehydrogenase ( G6PD ) , gluconolactonase ( 6PGL ) , and 6-phosphogluconate dehydrogenase ( 6PGD ) , which are also missing in Paramecium and Tetrahymena , and hence may have been lost in ciliates ( Figure S4 ) . Two of these enzymes—G6PD and 6PGL—were also noted to be missing in Paramecium , Tetrahymena , and Ichthyophthirius [64] . Thus , excluding these three CEGs that appear to be absent from ciliates , Oxytricha's macronuclear genome is only missing one CEG ( KOG3285/Mad2 ) . Together , since the macronuclear genome has 244/245 ( 99 . 6% ) of the ciliate-restricted CEGs , it ( together with the mitochondrial genome [65] ) is likely to encode a complete set of genes required for vegetative growth . This is consistent with the observation of amicronucleate Oxytricha species in the wild , which are capable of vigorous replication for hundreds of generations in culture [2] , [66] , and with temporary dispensability of the micronucleus . Currently TBE transposon genes are the only published examples of micronuclear-limited genes ( not encoded on any of the nanochromosomes in our assembly ) in Oxytricha . These genes are exclusively expressed during sexual development and appear to be essential for accurate genome rearrangements [30] , and hence may only need to be expressed from the micronucleus . A characteristic feature of the Oxytricha macronuclear genome is the existence of multiple , stable “versions” of nanochromosomes that share genic regions [10]–[12] . “Alternative processing” or “alternative fragmentation” of DNA is analogous to alternative splicing of introns from pre-mRNAs , but unlike alternative RNA splicing , macronuclear DNA is simply fragmented ( with telomere addition ) , rather than joined together . Variable deletion of micronuclear DNA in Paramecium also gives rise to alternatively fragmented macronuclear chromosomes , though it produces much longer multigene chromosomes and this alternative fragmentation is much less frequent than that in Oxytricha [67]–[69] . Initial surveys of Oxytricha fallax nanochromosomes revealed a substantial amount of alternative nanochromosome fragmentation , with 40% ( 6/15 ) of the surveyed nanochromosomes alternatively fragmented [11] , so we wanted to assess this on a genome-wide scale . We also sought evidence of possible functional relationships between alternative fragmentation and gene expression , since , in principle , alternative nanochromosome fragmentation may affect gene expression by ( i ) permitting variable amplification of nanochromosome isoforms , thereby affecting basal transcription levels of the genes encoded on these isoforms ( see “Nanochromosome Copy Number Is Nonuniform” ) , ( ii ) gene truncation , and ( iii ) affecting regulation of gene expression by modulating which regulatory elements are present on nanochromosomes . The creation of contigs during assembly merges shorter alternative nanochromosomes into longer isoforms , obscuring telomeric repeats when they contribute a minority of bases , thus making it difficult to identify the alternative isoforms directly from the contig sequences . Therefore , we exploited two sources of raw sequence data to uncover this kind of variation: 454 telomeric read pairs and Illumina telomeric reads ( see Materials and Methods ) . From alternative fragmentation sites predicted by either data source , almost 1/4 of all the nanochromosomes ( 3 , 369/14 , 390 ) in our final assembly are predicted to be alternatively fragmented ( only counting contigs with terminal telomeres ≤100 bp from either end of the contig ) . We predict 11% ( 1 , 909/17 , 372 ) and 14% ( 2 , 380/17 , 372 ) of nanochromosomes are alternatively fragmented from 454 telomeric reads alone and Illumina telomeric reads alone , respectively . Of the nanochromosomes predicted to be alternatively fragmented by Illumina telomeric reads , 63% are also predicted to be alternatively fragmented by 454 telomeric reads , and 68% of the nanochromosomes predicted to be alternatively fragmented by 454 telomeric reads are also predicted to be alternatively fragmented by Illumina telomeric reads . The actual portion of alternatively fragmented nanochromosomes may be closer to 10% since many of the predicted sites are only supported by a few reads ( which results in a poor correspondence between the predictions from the two data sources when there are few telomeric reads at a putative alternative fragmentation site; see Text S1 , “Classification of Strongly and Weakly Supported Alternative Fragmentation Sites” ) . We propose that most of the nanochromosomes arising from weakly supported sites with few supporting telomeric reads ( e . g . , <9 llumina telomeric reads ) may represent “developmental noise” or healing of broken nanochromosomes by capping the broken ends with telomeres , rather than functional nanochromosomes . We may not have recovered some alternatively fragmented nanochromosome isoforms due to limitations of our genome assembly . Since we focused on nanochromosomes with telomeres at both ends , some alternative fragmentation will be missed on nanochromosomes that lack telomeric ends ( e . g . , the alternatively fragmented 81-Mac locus [10] , [11] , represented by Contig13637 . 0 . 1 , is missing both ends ) . Another possible failure to detect alternative fragmentation is a consequence of the semigreedy nature of our genome assembly strategy , since we stop extending nanochromosomes once we have detected at least one 5′ and at least one 3′ telomeric repeat ( see Materials and Methods ) , which means that we may miss some longer unfragmented nanochromosome isoforms . Consequently , we consider our estimates of the level of alternative fragmentation to be conservative . Alternative fragmentation sites tend to map between predicted genes in intergenic regions rather than within intragenic regions [Table S1; we use inter-CDS regions rather than intergenic regions since CDS ( coding sequence ) predictions are more reliable than UTRs ( untranslated regions ) ] . For contigs with single internal alternative telomere fragmentation sites , strongly supported alternative fragmentation sites are 58 times more likely to be located in inter-CDS regions than in intra-CDS regions ( per bp of these sequence regions ) . For nanochromosomes with single-gene predictions , strongly supported alternative fragmentation sites are 27 times more likely to reside within non-CDS regions ( i . e . , introns , UTRs , subtelomeric regions , or regions with no predicted gene ) , than within CDSs ( Table S2 ) . Strongly supported , noncoding alternative fragmentation sites typically have more telomere-containing reads than do coding alternative fragmentation sites for both single ( mean 213 versus 95 reads ) and two-gene [mean 186 ( intergenic region ) versus 116 reads] nanochromosomes . For strongly supported alternative fragmentation sites predicted by Illumina telomeric reads , 74% ( 1 , 208/1 , 622 ) of alternatively fragmented nanochromosomes have one site of alternative fragmentation ( giving rise to two nanochromosome isoforms: a long unfragmented form and a shorter fragmented isoform ) , and 21% of alternatively fragmented nanochromosomes have two sites of alternative fragmentation ( similar statistics were obtained from strongly supported sites predicted from 454 telomeric reads ) . This means that typically only a few possible nanochromosome isoforms are produced for each of our assembled nanochromosomes and also that most alternative fragmentation is “directional , ” giving rise to only one of the two possible single shorter isoforms . The most extreme example has seven alternative fragmentation sites predicted from the Illumina telomeric reads ( at most nine from 454 telomeric reads ) for Contig14329 . 0 ( GenBank Accession: AMCR01001519 . 1 ) . The observation of directional alternative fragmentation suggests there must either be differential amplification of particular isoforms or degradation of specific forms following excision . The higher amplification levels of alternatively fragmented nanochromosomes relative to nonalternatively fragmented nanochromosomes ( see next section ) provides support for the first model but does not exclude the second . In the future , it will be interesting to determine how these fragmentation signals relate to chromosome amplification , since the timing of DNA fragmentation correlates with nanochromosome copy number in Euplotes [25] . The longest isoform of the most extreme case of alternative fragmentation we discovered ( Contig14329 . 0 ) is about 8 kb long with eight distinct protein-coding regions . This contig has 15 predicted telomere addition sites ( TASs ) ( nine 5′ and six 3′ sites relative to the contig orientation in the assembly ) from the 454 telomeric reads ( with 11 strongly supported sites , including the two terminal sites ) , giving rise to up to 14 distinct nanochromosome isoforms from the same 8 . 1 kb region ( Figure 6 ) . An alternative fragmentation site at ∼6 , 000 bp is weakly supported by 454 telomeric reads but strongly supported by Illumina telomeric reads , suggesting that this site largely gives rise to longer nanochromosome isoforms that the 454 telomeric reads are less likely to detect . Every one of the alternative fragmentation sites predicted from Illumina telomeric reads , with the exception of a single weakly supported site at 4 , 767 bp , was corroborated by 454 telomeric reads within 100 bp of the site . The 454 telomeric reads suggest that each of the seven intergenic regions in this contig is a site of alternative fragmentation ( no Illumina telomeric reads map to the site between genes 5 and 6 ) . Consistent with the genome-wide pattern , this contig's alternative fragmentation sites typically reside between , not in the middle of , genes . For the 454 telomeric reads , only a small portion ( 2/15 sites ) of the fragmentation sites are predicted to be in coding regions , and these sites are weakly supported , whereas the Illumina telomeric reads do not predict any sites in coding sequence regions . To experimentally validate the predicted extreme fragmentation of Contig14329 . 0 , we performed Southern hybridization ( Figure S5 ) on the same vegetative Oxytricha JRB310 macronuclear DNA sequenced by Illumina . With two exceptions , our Southern analysis confirmed all tested nanochromosomes and identified four novel isoforms: the full length ∼8 kb isoform A , and isoforms P , Q , and R ( Figure 6 , Figure S5; Text S1 , “Examination of Discrepancies Between Predicted and Experimentally Determined Alternative Fragmentation Isoforms of the Highly Fragmented Contig14329 . 0” ) . Since the process of generating 454 telomeric reads included a size selection ( see Text S1 , “Whole Nanochromosome Telomere-Based Library Construction” ) , it is unsurprising that sequencing missed the longer isoforms we were able to detect by Southern hybridization ( A , P , Q , and R , at 8 . 1 kb , 6 kb , 6 . 5 kb , and 4 . 5 kb long , respectively ) . The eight genes encoded on these alternatively fragmented nanochromosomes are ( 1 ) an RNAse HII domain containing protein ( Pfam: PF01351 ) , ( 2 ) a dsDNA-binding domain ( PF01984 ) protein , ( 3 ) a Tim10/DDP family zinc finger domain protein ( PF02953 ) , ( 4 ) a protein with no significant BLASTP ( to GenBank NR; E-value<1e-3 ) or Pfam matches ( E-value<1e-3 ) , ( 5 ) a COPI-associated protein domain ( PF08507 ) protein , ( 6 ) an uncharacterized conserved protein ( DUF2036 ) protein ( PF09724 ) , ( 7 ) another protein with no significant BLASTP or Pfam matches , and ( 8 ) a translation initiation factor eIF3 subunit ( PF08597 ) protein . From the domain annotations , no obvious functional relationship amongst these genes is evident . From Figure 6 , it can be seen that the representation of genes 2 , 3 , 4 , and 8 in the different nanochromosomal isoforms is greater than for the remainder of the genes . Two of the shortest Oxytricha proteins ( encoded by genes 2 and 3; see also Text S1 , “Analysis of Short Protein and ncRNA-Encoding Nanochromosome” ) are encoded on the most abundant nanochromosomal isoforms . Remarkably , in contrast to the surrounding , heterozygous DNA encoding genes 1–3 and gene 8 , the ∼4 . 2 kb DNA region encoding genes 4–7 appears to be completely homozygous , suggesting the possibility that these regions derive from different micronuclear sources . In contrast to the oligohymenophorean ciliates , which typically have uniformly amplified macronuclear genomes [56] , [69] , there is considerable variation in nanochromosome copy number in Oxytricha . The distribution of copy number for nonalternatively fragmented nanochromosomes is right-skewed and is restricted around a mean relative copy number of 0 . 94 , with ∼90% of the nanochromosomes contained within a relative copy number range of 0 . 12–1 . 76 centered on the mean ( Figure 7A ) . It is possible that some lower copy number nanochromosomes may not have completely assembled since the combined depth of sequence coverage is <120× and lower bound copy number estimation is constrained by the >62× coverage of the PE reads . Mindful of these limitations , within the sequenced JRB310 clonal population of cells , nanochromosome copy number does not appear to vary as much as gene transcription . The most highly amplified nanochromosome , encoding the 18S , 5 . 8S , and 28S rRNA ( Contig451 . 1 ) , has a copy number that is ∼56× the mean of nonalternatively fragmented nanochromosomes , yet its transcripts typically yield more than 90% of the RNA in our non-poly ( A ) -selected RNA-seq samples . There is a roughly 2-fold difference between the most highly amplified nanochromosome and the next most highly amplified nanochromosome , encoding the 5S rRNA ( Contig14476 . 0/Contig17968 . 0; quasi-allelic contigs ) . Since the method we used to estimate nanochromosome copy number combines reads from both possible alleles for heterozygous nanochromosomes , it is necessary to map the reads sensitively to avoid exclusion of reads and to minimize incorrect mapping in order to obtain accurate estimates ( see “Genome Homozygosity and SNP Heterozygosity” ) . Our mapping procedure seems to be appropriate for matchless nanochromosomes , since there is no substantial difference in copy number distributions for homozygous and heterozygous matchless nanochromosomes ( mean copy number of 0 . 93 , SD = 0 . 61 , and 0 . 97 , SD = 0 . 67 , respectively; Figure 7A ) . However , for heterozygous nanochromosomes with matches , the mean nanochromosome copy number is lower ( 0 . 81; SD = 0 . 59; Figure 7A ) than for matchless nanochromosomes . This is likely because some of the nanochromosomes with matches exhibit higher heterozygosity regions than matchless heterozygous nanochromosomes ( >6% mean SNP heterozygosity; see “Genome Homozygosity and SNP Heterozygosity” ) and the mapping criteria ( ≥94% read identity to the mapped contig ) eliminated some of the more heterozygous reads . To assess nanochromosome copy number of alternatively fragmented versus nonalternatively fragmented nanochromosomes , we examined the relationship between the number of telomeric reads and the number of nontelomeric reads per bp of the nanochromosomes ( see Materials and Methods ) . We found that there was a good correlation between telomeric reads from either end of the nonalternatively fragmented nanochromosomes ( Figure S6B ) with r = 0 . 90 . However , there are examples where the number of reads from each nanochromosome end differs substantially ( e . g . , Contig22209 . 0 and Contig5780 . 0 from Table S3 ) . This may indicate the failure to extend the ends of some nanochromosomes completely or that the ends derive from the DNA of the nonreference strain ( JRB510 ) and are relatively divergent with few reads from the reference DNA mapped to them ( e . g . , Contig5780 . 0 ) . Alternatively , there may be experimental biases that skew the numbers of reads mapped to the two ends ( e . g . , Contig22209 . 0 , which has JRB310 telomeric reads mapped to the nanochromosome end with fewer reads but no reads extending further , even with relaxed read mapping parameters ) . The correlation between the number of reads per bp and the number of telomeric reads per nanochromosome is also strong ( r = 0 . 89; Figure S6A ) , indicating that assessment of telomeric reads alone is appropriate for large-scale analyses of nanochromosome copy number . Furthermore , our estimates of relative nanochromosome copy number , either via reads per bp or the number of telomeric reads per contig , are in good agreement with those obtained by qPCR ( Table S3; Figure S7 ) . For relative nanochromosome copy number measured by telomeric reads , the mean number of telomeric reads per alternatively fragmented nanochromosome with a single ( directional ) alternative fragmentation site ( i . e . , only two nanochromosome isoforms ) is 2 . 4 times ( 885 reads , SD = 768 reads ) that of nonalternatively fragmented nanochromosomes ( 363 reads; SD = 290 reads; K-S one-sided test D = 0 . 59 and p value<1e-9 , with the alternative hypothesis that alternatively fragmented nanochromosome copy number>nonalternatively fragmented nanochromosome copy number; Figure 7B ) . It follows that the DNA of the shorter alternative nanochromosome isoforms is even more highly amplified than that of nonalternatively fragmented nanochromosomes . The greater amplification of alternatively fragmented nanochromosomes relative to nonalternatively fragmented nanochromosomes supports a model of net overamplification of specific alternatively fragmented nanochromosomes isoforms rather than a model of net destruction . The higher amplification of alternatively fragmented nanochromosomes may indicate a commensal DNA relationship between two genes , arising when one of the genes benefits from the amplification signal of a more highly amplified nanochromosome isoform bearing another gene . This relationship requires no functional association between the genes on alternatively fragmented nanochromosomes , consistent with our general observations ( e . g . , no specific functional associations between nonribosomal genes and ribosomal genes on alternatively fragmented nanochromosomes ) . For nonalternatively fragmented nanochromosomes , the ribosomal protein-encoding nanochromosomes are ∼3 . 9× more highly amplified than nonribosomal protein nanochromosomes , and tRNA-encoding nanochromosomes are ∼3 . 6× more highly amplified than non-tRNA-encoding nanochromosomes ( Figure 7C; for ribosomal versus nonribosomal nanochromosomes: K-S one-sided test D = 0 . 64 and p value<1e-9 , with the alternative hypothesis that ribosomal nanochromosome copy number>nonribosomal nanochromosome copy number; for tRNA versus non-tRNA nanochromosomes: K-S one-sided test D = 0 . 62 and p value<1e-6 , with the alternative hypothesis that tRNA nanochromosome copy number>non-tRNA nanochromosome copy number ) . Similarly , the ribosomal protein- and tRNA-encoding nanochromosome isoforms arising from alternative fragmentation are typically overamplified relative to the isoforms that encode other genes ( 50/54 alternatively fragmented ribosomal nanochromosomes and 25/28 alternatively fragmented tRNA nanochromosomes; Figure S8 ) . Given the modest variation in nanochromosome copy number , most notably the limited overamplification of nanochromosomes encoding highly expressed genes ( rRNAs , tRNAs , and ribosomal proteins ) , even if a strong correlation exists between nanochromosome copy number and transcription levels , copy number may only be a modest contributor to the final RNA and protein expression levels . Regulation of expression at the transcriptional/posttranscriptional level may be essential to buffer the variation in DNA copy number that arises during extended periods of vegetative growth . Oxytricha nanochromosomes range in length from ∼500 bp to 66 kb , with a mean size of ∼3 . 2 kb ( Figure 8 ) . Few nanochromosomes were assembled at either extremity of the length distribution , with just 32 shorter than 600 bp long and 61 longer than 15 kb , consistent with observations of macronuclear DNA on electrophoretic gels [2] , [70] . While the mean length of two-telomere nanochromosomes in the final Oxytricha macronuclear genome assembly is ∼3 . 2 kb ( Table 1 ) , the true average length of nanochromosomes is shorter than this because the longest isoform of alternatively fragmented nanochromosomes is the one that tends to be assembled . On electrophoretic gels , Oxytricha nanochromosomes are visibly longer than those of Euplotes [2] , [71] , which we propose is primarily a consequence of the lack of alternative fragmentation in Euplotes ( inspection of mapped reads to our preliminary Euplotes crassus assembly indicated no signs of alternative fragmentation; unpublished data ) . The longest isoforms of alternatively fragmented nanochromosomes average 5 . 0 kb ( SD = 2 . 4 kb ) , while nonalternatively fragmented nanochromosomes have a mean length of 3 . 0 kb ( SD = 2 . 4 kb; Figure 8 ) . The mean length of the shortest nanochromosome isoforms produced by alternative fragmentation is 2 . 4 kb ( SD = 1 . 6 kb ) . For single-gene nonalternatively fragmented nanochromosomes , the mean nanochromosome length is 2 . 2 kb ( SD = 1 . 0 kb ) . The shortest assembled nanochromosome ( Contig20269 . 0 ) is a mere 248 bp , excluding the telomeric sequences . Though we were unable to identify any ORFs or any ncRNAs on this nanochromosome by RFAM searches , we found two matching RNA-seq PE reads , suggesting that there is expression from this nanochromosome . The shortest nanochromosome ( Contig19982 . 0 ) with a known protein is 469 bp ( excluding the telomeres ) and encodes a 98 aa ThiS/MoaD family protein , while the shortest ncRNA-bearing nanochromosome we found is 540 bp ( excluding telomeres ) and encodes tRNA-Gln ( CUG ) ( see Text S1 , “Analysis of Short Protein and ncRNA-Encoding Nanochromosomes” ) . Searches for shorter possible nanochromosomes in the Illumina and Sanger reads did not reveal additional plausible nanochromosome candidates ( Text S1 , “Reads Containing Both Putative Telomeric Repeats Are Not Genuine Nanochromosomes” ) . The longest nanochromosomes ( >15 kb ) typically encode a single large structural protein ( Table S4 ) , such as dynein heavy chain proteins ( e . g . , Contig354 . 1 ) . None of the 20 longest nanochromosomes are alternatively fragmented . Seven of these 20 nanochromosomes contain multiple predicted genes ( up to a maximum of four ) ; however , all but one of these gene predictions are oriented head-to-tail , consistent with the possibility that their predictions may have been incorrectly split . Hence most of the longest nanochromosomes are likely still single-gene nanochromosomes . One ∼20 kb nanochromosome ( Contig289 . 1 ) does indeed contain multiple genes , since it encodes a Pkinase domain ( PF00069 ) protein on the opposite strand to two predicted PAS_9 domain ( PF14326 ) proteins ( though these latter two proteins may also be incorrectly split ) . Six of the longest nanochromosomes encode single proteins with no detectable Pfam domains ( Pfam-A 26; independent E-value<0 . 01 ) but all have BLASTP NCBI non-redundant database ( nrdb ) matches ( E-value<1e-10 ) , typically to large proteins ( >2 , 000 aa ) . The longest nanochromosome ( Contig7580 . 0 ) is 66 kb ( 65 , 957 bp; excluding telomeres ) and encodes a single giant protein ( “Jotin , ” after a Norse giant ) with BLASTP best hits to Titin-like genes in the NCBI nrdb ( see Text S1 , “Characterization of the Jotin Protein” ) . We note that this single-gene nanochromosome is comparable in size to the entire , relatively large and gene-rich ∼70 kb Oxytricha mitochondrial genome [65] , which was largely eliminated by the sucrose gradient isolation of macronuclei ( see Materials and Methods ) . The Oxytricha Jotin ORF is 64 , 614 bp . AUGUSTUS predicts four short introns ( 117 , 151 , 77 , and 63 bp ) , two of which are supported by and one of which conflicts with RNA-seq reads . This gene's entire coding sequence is well supported by pooled RNA-seq reads ( covered from end to end ) . The gene prediction software , AUGUSTUS , predicted complete genes on 15 , 387 of the complete nanochromosomes we surveyed ( 96% ) and 91% of the final assembly's contigs . Examination of three developmental time points ( 0 , 10 , and 20 h after initiation of conjugation ) confirms transcription of 97% of Oxytricha nanochromosomes ( 94% of all contigs ) . AUGUSTUS predicts genes on 94% of nanochromosomes with expression evidence . Most Oxytricha nanochromosomes ( 80% ) contain single genes , consistent with earlier studies ( Figure S9 ) [2] , [33] . Alternatively fragmented nanochromosomes tend to encode more genes per nanochromosome: only 15% of alternatively fragmented nanochromosomes have single gene predictions , versus 90% of all nonalternatively fragmented nanochromosomes . Roughly half ( 48% ) of multigene nanochromosomes have alternative fragmentation . All nanochromosomes with five or more ( maximum eight ) predicted genes are alternatively fragmented ( Figure S9 ) , and only two nonalternatively fragmented nanochromosomes encode four genes . The nanochromosome with the largest number of separate gene products ( Contig8800 . 0; ∼6 . 8 kb ) is alternatively fragmented , with a shorter ∼3 . 5 kb nanochromosome isoform that encodes 12 C/D snoRNAs [59] and a putative protein-coding gene encoded by the remainder of the full-length isoform . Key properties of Oxytricha's gene predictions are consistent with a pilot survey [33] , including relative AT-richness ( 34% GC ) with noncoding regions that are more AT-rich than coding regions ( e . g . , introns are 23 . 6% GC ) , and 1 . 6 introns per gene ( Table 2 ) . Oxytricha gene lengths ( mean length 1 , 839 bp excluding UTRs ) are similar to those predicted for Tetrahymena [56] . Functional differences between the model ciliates may have evolved in numerous ways , given their tremendous divergence . Here we focus on two key differences: absence/presence of protein domains in specific ciliates and expansions of protein families at the level of protein domain . We were particularly interested in comparing the protein domains present in either ciliates with gene scrambling ( Oxytricha ) or that lack evidence of gene scrambling ( Paramecium , Tetrahymena , and Euplotes; Figure 2; Tables S5 and S6; also see Table S7 for genes found in Paramecium and Tetrahymena that are absent in Oxytricha ) , since many species-specific proteins appear associated with macronuclear genome differentiation . Examples include the transposases in Oxytricha ( micronuclear-limited TBE transposases ) [30] , Tetrahymena and Paramecium ( piggyBac transposase—“PiggyMac” ) [72] , [73] , and the Paramecium RNA binding Nowa proteins [74] . Since we were interested in DNA rearrangement , we searched for differences in the nucleic acid binding and nucleic acid metabolism domain content between the ciliates with and without evidence of extensive gene scrambling ( see Materials and Methods ) . We identified 43 such nucleic-acid-related domains that are present in Oxytricha ( “Oxytricha-specific” domains ) but absent from both Tetrahymena and Paramecium ( Table S5 and Table S6 ) . For additional results , see Text S1 , Figures S1–S30 and Tables S1–S28 . The unique architecture of the Oxytricha macronuclear genome expands our perspective on the limits of genome organization . We summarize our main findings below . The Oxytricha macronuclear genome now enables both comparative genomics in the same cell with its micronuclear precursor , as well as comparative macronuclear genomics with other species that possess a nanochromosome architecture and more divergent model organisms with no or less genome fragmentation . Broader taxonomic sampling of other ciliate macronuclear and micronuclear genomes will greatly enhance evolutionary studies of nuclear development and genome rearrangement . In conjunction with the macronuclear genome , transcriptome data provide the first tantalizing glimpses into sweeping cellular changes during nuclear development and merit more investigation . Specific protein studies will be necessary to identify key genome rearrangement players from the extensive candidate list of development-specific genes . To facilitate these and other studies , the Oxytricha macronuclear genome , which is available both in GenBank ( AMCR00000000 ) and at oxy . ciliates . org , will continue to incorporate future refinements in the genome assembly , gene predictions and annotations .
Briefly , to obtain macronuclear DNA for Sanger and 454 sequencing , Oxytricha trifallax strain JRB310 was cultured in inorganic salts medium according to an established protocol [104] with Chlamydomonas reinhardtii and Klebsiella oxytoca as food sources . The JRB310 cells we used here are likely to have undergone less than 200 divisions since they were originally isolated and have been raised from cultures with two intervening encystments . Oxytricha cells were harvested by filtering through several layers of gauze to remove large particles , and then a 15 µm Nitex membrane was used to concentrate cells and remove bacteria and small contaminants . The harvested cells were washed by low-speed centrifugation through a 0 . 25 M sucrose solution , then lysed in 0 . 25 M sucrose and 0 . 5% Nonidet P-40 . This lysis disrupts the cell membrane , leaving nuclei intact . Nuclei were then spun through 0 . 25 M sucrose twice to remove bacteria , mitochondria , and other cell debris . Most micronuclei were also removed in this process . DNA was extracted using the AquaPure genomic DNA isolation kit ( Bio-Rad ) following the manufacturer's protocol . To obtain pure macronuclear DNA for Illumina sequencing , Oxytricha trifallax strain JRB310 was cultured in inorganic salts medium and starved for 3 d at 4°C to allow consumption of most of the food source ( Chlamydomonas reinhardtii ) in culture . Cells were harvested by filtering through several layers of gauze to remove large particles . Then , a 10 µm Nitex membrane was used to concentrate cells and remove small contaminants . We collected a macronuclear fraction in 40% sucrose from a standard sucrose gradient centrifugation protocol designed to separate macronuclei and micronuclei [105] . We then purified the macronuclei an additional time , by passing them through a 70% sucrose gradient at 12 , 000 rcf for 10 min . DNA was isolated from the macronuclei with a NucleoSpin tissue DNA isolation kit ( Machery-Nagel ) according to the standard protocol for cultured cells and then RNAse A treated prior to preparation of the Illumina libraries . Since considerable streaking of the DNA was evident from electrophoretic gels , excess salt was suspected in the samples and so the DNA was precipitated in ethanol ( >8 h ) at 4°C , then centrifuged at 16 , 000 rcf for 30 min , and washed twice , for 10 min in 70% ethanol , before resuspension in the kit's elution buffer . Genomic shotgun libraries were prepared for different size fractions of Oxytricha macronuclear DNA using standard methods employed at The Genome Institute ( TGI ) for both Sanger and 454 sequencing ( see Text S1 , “Preparation of Nanochromosome DNA for Sanger/454 Sequencing” to “454 Sequencing of DNA from Nanochromosome Size Fractions” ) , while a special method was developed for the construction and 454 sequencing of paired telomeric ends ( Text S1 , “Whole Nanochromosome Telomere-Based Library Construction” ) . Both PE and SE Illumina libraries were prepared at Princeton University from pure JRB310 Macronuclear DNA using standard Illumina kits ( Text S1 , “llumina Genomic Library Construction and Sequencing” ) . We developed a meta-assembly method ( Figure S1 ) to build a reference genome assembly that is primarily derived from Illumina sequence data ( Princeton Illumina assembly ) but also takes advantage of an earlier Sanger/454 hybrid assembly ( TGI 2 . 1 . 8 assembly ) . The data that were used for each of the assemblies are summarized in Table S8 . gmapper version 2 . 1 . 1b [111] was used to map reads to the final genome assembly in SE mapping mode with default parameters , and then filtered to contain read pairs that had both members matching with ≥94% identity to the assembly ( further details about the read mapping are provided in Text S1 , “Read Mapping Rationale” ) . To identify potential heterozygous sites that were hidden by the majority rule applied in calling contig consensi during assembly , we identified SNPs ( base substitutions and not indels ) at positions with ≥20× read coverage and ≥5% frequency for telomere-masked , PE reads mapped to nanochromosomes both with ( “matched” ) and without ( “matchless” ) non-self BLAT matches ( ≥100 bp and ≥90% identical; default parameters ) , from VarScan ( version 2 . 2 . 8 , with a minimum variant frequency of 0 . 001 ) [112] output processed by a custom Python script . We pairwise aligned heterozygous “matched” nanochromosomes with MUSCLE ( default parameters; for nanochromosome pairs where one of the nanochromosomes is no more than 10% longer than the other ) and estimated heterozygosity for these nanochromosomes for alignments that were ≤15% identical . SNP data can be obtained from http://trifallax . princeton . edu/cms/raw-data/genome/mac/assembly/combined_assembly/snps/varscan_snps . tar . gz/view . SNP heterozygosity at 4-fold synonymous sites was determined from 649 coding sequence pairs , corresponding to 1 , 298 matched nanochromosomes , aligned with MACSE ( with parameters “-Xmx1000 m” and “-d 6” ) [113] with no more than 5% gaps in each of the aligned sequences . After splitting out and removing the adaptors used in the circular telomere-capturing constructs ( see Text S1 , “Whole Nanochromosome Telomere-Based Library Construction” and Figure S28 for the procedure used to produce these constructs ) , we selected all 454 PE reads with telomeric sequence repeats on either end and hard-masked all the telomeric repeats ( matching the regular expression [AC]*CCCCAAAACCCC ) with a single “N , ” then selected all pairs where both reads were ≥30 bp long ( 719 , 566 pairs in total ) and were terminated by telomeric repeats . We then mapped all the 454 telomeric PE reads to our final genome assembly with gmapper version 2 . 0 . 2 [111] in paired mode and the following parameters: -r 50; -p col-bw; -I 0 , 30000 ( -r was set to 50 to accommodate the high indel error rate of 454 reads ) . Illumina telomeric reads , masked in the same manner as the 454 telomeric reads , were mapped with gmapper version 2 . 1 . 2b with default parameters , then filtered so that both members of the pair were ≥94% identical to the contig to which they mapped . Next we identified both 5′ and 3′ TASs for each contig in 200 bp windows around sites with maximal telomeric read coverage ( this provides a lower bound estimate of the number of TASs , since these sites may span at least a couple hundred bases ) . Predicted sites are available at http://trifallax . princeton . edu/cms/raw-data/genome/mac/assembly/combined_assembly/telomere_addition_sites/ . Alternative fragmentation sites were classified as strongly supported if they had ≥10 supporting Illumina telomeric reads and weakly supported if they had fewer matching reads than this ( additional details about this classification are provided in Text S1 , “Classification of Strongly and Weakly Supported Alternative Fragmentation Sites” ) . Putative alternative nanochromosome isoforms were predicted based on 454 telomeric read pairs that provide a link between the ends of nanochromosomes , with any read pair ending 100 bp up- or downstream of each site providing a link . This provides a minimum estimate of the number of alternative nanochromosome isoforms produced by each locus and cannot predict longer alternative nanochromosome isoforms ( much larger than 5 kb ) due to the size selection limits on the initial sequence constructs . Predicted nanochromosome isoforms , with the number of reads supporting each isoform , can be found at http://trifallax . princeton . edu/cms/raw-data/genome/mac/assembly/combined_assembly/454_alt_forms . txt/view . Relative nanochromosome copy numbers were estimated for nanochromosomes ≥1 , 800 bp long , from the total number of telomereless paired reads mapped in the intervening , nonsubtelomeric interval 600 bp from either end of each nanochromosome ( http://trifallax . princeton . edu/cms/raw-data/genome/mac/assembly/combined_assembly/copy_number/copy_num_sam_filter6 . nonsubtelomeric . txt/view ) . We excluded these subtelomeric regions , since the experimental protocol used to generate the reads lead to uneven coverage ( e . g . , see Figure 6 and Figure S8 ) , which may in turn lead to poor estimates of nanochromosome copy number for shorter nanochromosomes . The total number of mapped reads was normalized by the total nanochromosome length minus the combined 1 , 200 bp subterminal interval . We also estimated relative copy number from the number of telomeric reads mapped to each nanochromosome ( http://trifallax . princeton . edu/cms/raw-data/genome/mac/assembly/combined_assembly/copy_number/copy_num_sam_filter6 . teloreads . unrestricted . txt/view ) . RNA was isolated for five developmental time points ( 0 , 10 , 20 , 40 , and 60 h postmixing of JRB310 and JRB510 cells for conjugation ) and used to create RNA-seq libraries with the Ovation RNA-Seq System ( NuGEN Technologies , Inc . San Carlos , CA ) . Details of the RNA-seq library construction and sequencing are provided in Text S1 , “RNA Isolation , NuGEN cDNA Synthesis and Illumina Sequencing . ” To produce spliced mapped reads , RNA-seq data were mapped with BLAT [44] ( “-noHead -stepSize = 5 -minIdentity = 92” ) and then postprocessed to remove mapping artifacts ( see Text S1 , “RNA-Seq Mapping and Read Counting” for further details ) . Gene predictions were produced by AUGUSTUS ( version 2 . 5 . 5 ) [114] , [115] using mapped RNA-seq data as “hints” for predictions ( details about the training and prediction are provided in Text S1 , “Gene Prediction” ) . The final genome assembly has been deposited in GenBank with accession number AMCR00000000 . Note that there are 20 , 162 contigs in GenBank , rather than the 22 , 450 reported for our final assembly , as some contigs were removed ( e . g . , if they were too short after vector trimming ) . Tables S8 , S9 , S10 and Text S1 provide links to the other assemblies and raw data . For additional methods , see Text S1 , Figure S28 and Tables S28 , S29 . | The macronuclear genome of the ciliate Oxytricha trifallax , contained in its somatic nucleus , has a unique genome architecture . Unlike its diploid germline genome , which is transcriptionally inactive during normal cellular growth , the macronuclear genome is fragmented into at least 16 , 000 tiny ( ∼3 . 2 kb mean length ) chromosomes , most of which encode single actively transcribed genes and are differentially amplified to a few thousand copies each . The smallest chromosome is just 469 bp , while the largest is 66 kb and encodes a single enormous protein . We found considerable variation in the genome , including frequent alternative fragmentation patterns , generating chromosome isoforms with shared sequence . We also found limited variation in chromosome amplification levels , though insufficient to explain mRNA transcript level variation . Another remarkable feature of Oxytricha's macronuclear genome is its inordinate fondness for telomeres . In conjunction with its possession of tens of millions of chromosome-ending telomeres per macronucleus , we show that Oxytricha has evolved multiple putative telomere-binding proteins . In addition , we identified two new domesticated transposase-like protein classes that we propose may participate in the process of genome rearrangement . The macronuclear genome now provides a crucial resource for ongoing studies of genome rearrangement processes that use Oxytricha as an experimental or comparative model . | [
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] | 2013 | The Oxytricha trifallax Macronuclear Genome: A Complex Eukaryotic Genome with 16,000 Tiny Chromosomes |
Argonaute ( Ago ) proteins and microRNAs ( miRNAs ) are central components in RNA interference , which is a key cellular mechanism for sequence-specific gene silencing . Despite intensive studies , molecular mechanisms of how Ago recognizes miRNA remain largely elusive . In this study , we propose a two-step mechanism for this molecular recognition: selective binding followed by structural re-arrangement . Our model is based on the results of a combination of Markov State Models ( MSMs ) , large-scale protein-RNA docking , and molecular dynamics ( MD ) simulations . Using MSMs , we identify an open state of apo human Ago-2 in fast equilibrium with partially open and closed states . Conformations in this open state are distinguished by their largely exposed binding grooves that can geometrically accommodate miRNA as indicated in our protein-RNA docking studies . miRNA may then selectively bind to these open conformations . Upon the initial binding , the complex may perform further structural re-arrangement as shown in our MD simulations and eventually reach the stable binary complex structure . Our results provide novel insights in Ago-miRNA recognition mechanisms and our methodology holds great potential to be widely applied in the studies of other important molecular recognition systems .
RNA interference ( RNAi ) is a key cellular mechanism involved in the regulation of gene expression and the defense against viruses[1 , 2] . As the central component of RNAi , the RNA induced silencing complex ( RISC ) mediates the sequence-specific recognition and inhibition of target mRNA[3 , 4] . At the core of the RISC , the Argonaute protein ( Ago ) in complex with the non-coding microRNAs ( miRNAs ) can selectively silence certain genes through specific binding to their mRNAs[5–12] . In human there are four Agos ( hAgo1-4 ) and they together facilitate miRNA-based regulation of more than 30% of human genes[9 , 13] . While the miRNA libraries associated with different hAgos largely overlap , recent studies have identified exceptional miRNAs that bind specifically to only one hAgo[14–16] . Elucidating the molecular mechanisms of how Ago recognizes specific miRNAs is thus of vital importance not only for the fundamental understanding of RNAi but also for further development of miRNA-based therapeutics[17–19] . Protein-RNA recognition mechanisms are often interpreted via two popular models: conformational selection and induced fit[20 , 21] . In conformational selection , the RNA selectively binds to the bound conformation of the protein[22–24] . On the other hand , in induced fit , the RNA first binds to an unliganded protein conformation and further induces conformational changes of the protein to its bound form[25] . For example , the conformational selection model has been suggested in the recognition between human U2 snRNP auxiliary factor and polypyrimidine tract RNA[26] . On the other hand , the induced fit model plays a major role in the recognition between the Xenopus ribosomal protein L5 and the 5S rRNA[27] . Since both protein and RNA are large and flexible biopolymers , their recognition mechanisms often lie between the above two models[28–30] . Therefore , to dissect the protein-RNA recognition mechanisms , one needs to consider the chemical details of individual binding partners . Despite intensive studies , the molecular mechanism of Ago-miRNA recognition still remains largely elusive . In the recently solved crystal structures of miRNAs in complex with eukaryotic Agos , miRNAs are deeply buried in the Ago binding groves , and this partially open bound conformation of Ago apparently prevents a direct loading of miRNA[31–34] . Therefore , a conformational selection model alone appears insufficient to describe the mechanisms of miRNA loading into Ago . Using a series of stopped-flow experiments , Deerberg et al . proposed a multi-step model for miRNA to load into human Argonaute-2 ( hAgo2 ) [35] . However , to fill in their model with molecular details , further studies that elucidate the conformational dynamics of hAgo2 and miRNA are necessary . An effective approach to investigate the possible role of the conformational selection in Ago-miRNA recognition is to examine if apo Ago can transiently reach a sufficiently open conformation to load miRNA . Molecular dynamics ( MD ) simulations offer a valuable tool to investigate the conformational dynamics of large biomolecules at atomic resolution . Previous MD studies at sub-microsecond timescales have demonstrated the impact of miRNA and double strand RNA on the conformational stability of the Ago complex[36–38] . However , solely using MD to model the complete loading process is extremely challenging due to the gap between the experimental timescale ( at millisecond or longer ) and that of all-atom MD simulations ( typically at sub-microsecond ) . A feasible alternative approach is to address the above issue in two steps: to obtain the structural ensemble of the apo Ago protein with sufficient sampling followed by examining if any conformation in this ensemble can geometrically accommodate miRNA . Markov state models ( MSMs ) hold great promise to describe the apo Ago conformational dynamics because it can bridge the timescale gap between MD simulations and experimental observations[39–50] . In an MSM , we coarse grain the conformational space into a number of metastable states , and simultaneously coarse grain the time in Δt . In this way , fast protein motions can be integrated out . When Δt is longer than the intra-state relaxation time , the model becomes Markovian . In other words , the probability for the system to visit a certain state at the next time step ( t+Δt ) is solely determined by its location at the current time step t . If the model is Markovian , we can model the long timescale dynamics using the first order master equation ( see Eq ( 1 ) ) . In recent years , MSMs have been widely applied to study conformational dynamics of biopolymers[41 , 51–61] . Protein-RNA docking is a powerful tool to further examine if there exists apo Ago conformations that are open enough to accommodate miRNAs . The HADDOCK approach is particularly suitable for studying Ago-miRNA complexes because it is implemented with a flexible search algorithm that can benefit from the available information such as mutagenesis experiments and crystallographic contacts[62 , 63] . Performing HADDOCK simulations on apo Ago conformations identified by MSMs may provide an effective strategy to overcome the major limitation of protein-RNA docking , i . e . sufficiently considering the flexibility of both protein and RNA[64] . Furthermore , we can perform MD simulations initiated from docking poses to investigate subsequent conformational changes potentially induced by the binding . In this work , we combine MSM with large-scale protein-RNA docking to elucidate the molecular mechanisms of miRNA loading into hAgo2 . Our MSM identifies an open state of apo hAgo2 in fast equilibrium ( at microsecond ) with other metastable states . This open state has a characteristic structural feature: the miRNA binding groove is largely exposed to the solvent . Subsequent protein-RNA docking simulations confirm that a fraction of conformations in this state are sufficiently open to accommodate miRNAs . In further MD simulations initiated from the docking models , the complex undergoes structural re-arrangements to reach conformations closer to the crystal binary structure . Based on these observations , we propose a two-step mechanism for the recognition between miRNA and hAgo2: selective binding followed by structural re-arrangement .
A 480-microstate MSM was initially constructed with the APM algorithm[65] from over 394 , 000 conformations based on the Euclidean distances of the two regions , namely the PAZ domain and two loops of the PIWI domain ( the minor loop P601-P609 and the major loop V818-D838 , see S1C Fig ) . These two regions were chosen since they are the most flexible moieties of apo hAgo2 dynamics in our MD simulations ( see S1A Fig ) . Moreover , the MID domain displays the smallest conformational flexibility among all domains ( see S1A Fig ) . For the N domain , even though it is more flexible than the MID domain , its location is away from the miRNA binding groove and thus may not directly affect the miRNA loading . Our model has been further validated by residence probability tests[45 , 54] , in which the probability for the system to remain in a certain state predicted by the production MSM is in reasonable agreement with the probability obtained directly from MD trajectories ( see S2B Fig ) . Due to the large number of states , it is challenging to use our validated 480-microstate MSM for human appreciation of hAgo2’s conformational features . Therefore , we further lumped the microstates into seven metastable macrostates using the APM algorithm ( see Methods for details ) . However , the residence probability tests show that the produced macrostate MSM predicts faster kinetics than the original MD simulations ( see S2D Fig ) , even though the slowest implied timescales obtained from both MSMs are consistent ( see S2C Fig ) . Therefore , all the quantitative properties reported in this study such as equilibrium populations and mean first passage times are obtained from the well-validated 480-microstate MSM . According to the degree of opening , the metastable conformational states of hAgo2 can be divided into three groups: an open state ( 19 . 0% ) , a partially open state ( 55 . 8% ) , and various closed states ( see Fig 1A ) . Interestingly , the opening motion of hAgo2 can be effectively described by two PIWI loops and their interactions with the PAZ domain . The conformation of the PIWI loops in combination with their center-of-mass ( c . o . m . ) distance to the PAZ domain can not only separate the open state from the partially open state ( see Fig 1B ) , but also distinguish five closed states ( see S5 Fig ) . In these closed states , the PIWI domain can form direct interactions with the PAZ domain through multiple residues on both minor ( e . g . D605 ) and major PIWI loops ( e . g . E821 , D823 , E826 , see S1B Fig ) . Strikingly , the open state conformations can reach a widely open form with the c . o . m . distance between PAZ and PIWI loops as large as 46Å ( see Fig 1A ) . In these conformations , the miRNA binding groove is already fully exposed to the solvent ( see the right panel of Fig 1C ) , which strongly suggests that they may geometrically allow a direct loading of miRNA . In the next section , we will further examine this possibility via protein-RNA docking . Moreover , our MSM shows that the MFPTs between the open and closed state are only at an order of tens of microseconds ( see S1 Table ) . These results indicate that the open conformations may be readily available to bind to miRNA through diffusion-controlled collision in the cellular environment . We also notice that these open conformations are even substantially more open than the binary partially open crystal structure ( see the green cross in Fig 1B ) . These observations suggest that if miRNA can directly load into hAgo2’s open conformations , subsequent structural re-arrangements are necessary to reach the stable binary structure . To examine if the open conformations are able to accommodate miRNA , we performed large-scale protein-RNA docking using HADDOCK[62 , 63] on 150 selected open conformations of hAgo2 . In particular , these conformations were selected from microstates with the c . o . m . distance between the PAZ domain and PIWI loops larger than 25Å ( see Methods for details ) . For each docking simulation , we produced 50 hAgo2-miRNA structures . By computing their fraction of native contacts ( fnat , see Eq ( 5 ) ) , we further show that the energy-based scoring function of HADDOCK can faithfully evaluate the quality of the docking structures . As shown in S6 Fig , the plot of the HADDOCK score against the fraction of native contact displays a nice funnel shape , indicating that the structure with the lowest HADDOCK scoring energy also preserves the most native contacts . We thus collected the lowest scoring energy structure from each of the 150 docking simulations for further examination . Some of the lowest-energy docked structures have both 5’ and 3’ miRNA termini successfully anchored in the binding groove of hAgo2 ( see red points in Fig 2 ) , while most other structures have only one end of miRNA forming proper contacts with the protein ( see black points in Fig 2 ) . This observation indicates that not all hAgo2 conformations with a large distance between the PAZ and PIWI domains could geometrically accommodate miRNA . Other structural features such as the orientation of PIWI loops may also be necessary to define a sufficiently open binding groove of hAgo2 . Indeed , in most successful docking models , the major PIWI loop forms an angle of over 100° with the rigid part of the PIWI domain ( see Fig 2 ) . Finally , we found that in our successfully docked structures , even though miRNA forms correct contacts with hAgo2 , the Argonaute protein itself adopts a structurally more open conformation than that in its binary crystal ( see S7 Fig ) . This indicates that structural re-arrangement is necessary after the initial binding of miRNA to hAgo2 . Initiating MD simulations from successfully docked structures , we observed substantial structural re-arrangement that brings the docked conformations closer to the binary crystal structure . In particular , we performed five independent 20-ns MD simulations from each of the three representative successfully docked conformations . MD simulations from these three representative conformations displayed decreased distance between the PAZ domain and PIWI loops , indicating that hAgo2 tends to close upon initial miRNA binding ( see representative MD trajectories in Fig 3A and S8 Fig ) . We further show that such structural re-arrangement brings the hAgo2 conformation closer to the crystal structure ( see the binding interface RMSDs in the upper panel of Fig 3B , the miRNA RMSDs in S9A Fig , and the hAgo2-miRNA salt bridges in S9C&S9D Fig ) while still preserving protein-RNA native contacts ( see lower panel of Fig 3B ) . In Fig 3C , we compare the binary crystal structure with a representative conformation after MD simulation , and these two structures display a high degree of structural similarity . Due to their limited lengths , our MD simulations could not fully reach the binary crystal structure , but they strongly suggest that protein-RNA interactions upon the initial miRNA loading may facilitate the further structural re-arrangement to reach the stable binary complex conformation . Based on our results , we propose a two-step model of selective binding followed by structural re-arrangement model for the recognition mechanism between miRNA and hAgo2 ( see Fig 4 ) . In our model , the apo hAgo2 protein is very flexible and undergoes fast transitions among open , partially open and closed conformations . When miRNA encounters hAgo2 , it can selectively bind to the open conformation . Upon the initial binding , the complex performs structural re-arrangement and eventually reaches the stable partially open binary complex conformation . The proposed model is strongly supported by our MSMs built upon MD simulations of apo hAgo2 , large-scale protein-RNA docking and MD simulations of the binary complex . In particular , our MSM identified a metastable open state of apo hAgo2 in fast equilibrium with other conformational states . Using protein-RNA docking , we demonstrate that some conformations in this open state can fully accommodate the miRNA . We further show that these open apo hAgo2 conformations can be accessed by miRNA since the rate of transition between the open and closed states ( 5 × 10−2Ms−1 , see S1 Text for calculation details ) is significantly faster than the collision rate between hAgo2 and miRNA under physiological conditions ( 1 × 10−6Ms−1 , see S1 Text for calculation details ) . These results indicate that the initial hAgo2-miRNA recognition could involve selective binding of open hAgo2 by miRNA . Subsequent MD simulations initiated from docked conformations suggest that protein-RNA interactions may further induce conformational changes , and eventually this will drive the system to reach the stable binary conformation . Notably , the selective binding step in our two-step mechanism has clear features of the conformational selection because the open hAgo2 state pre-exists in equilibrium with other conformational states , and miRNA selects to bind to this state with high binding affinity ( see Fig 4 ) . While in the original conformational selection mechanism the ligand usually selects the protein conformation with the highest affinity , our study suggests that miRNA cannot selectively bind to the partially open conformation of the highest affinity due to steric hindrance to the binding groove ( see Fig 2 and S12 Fig ) . Instead , it chooses the open hAgo2 with the medium affinity as illustrated by our model ( see Fig 4 ) . This scenario , where the ligand selects a relatively high-affinity conformation but not the highest , has been previously observed in a number of molecular recognition system including ubiquitin binding[66] and LAO protein-arginine interactions[67] , and sometimes regarded as the “extended conformational selection” model[21] . As pointed out by Boehr et al . , conformational selection mechanism allows more promiscuous binding than induced fit[28] . Proteins that adopt this recognition mechanism may potentially bind to a larger pool of targets . Therefore , our model may help understand the ability of hAgo2 to bind to miRNAs of different lengths and sequences . Our simulations complement previous experiments and fill in molecular details for the understanding of hAgo2-miRNA recognition mechanisms . Deerberg et al . showed that three rate constants could nicely fit the kinetics of RNA binding to hAgo2 from their stopped-flow experiments[35] . Based on these observations , they proposed a 3-step model: formation of hAgo2-RNA collision complex , anchoring of the 5’ terminus of the RNA and anchoring of the 3’ terminus[35] . Interestingly , the initial hAgo2-RNA collision rate was orders of magnitude faster than the subsequent anchoring of RNA termini in their model . Based on our simulations , we suggest that the initial hAgo2-miRNA collision observed in stop-flow experiments could contain the preferential binding of miRNA to an open conformation of hAgo2 . The structural re-arrangement of the complex after the initial loading could include anchoring of miRNA termini in a sequential order . Since a significantly larger number of contacts are formed between hAgo2 and 5’ miRNA ( 43 contacts ) compared to the 3’ miRNA ( only 5 contacts ) in the crystal structure , we speculate that 5’ miRNA may successfully anchor to the binding groove of hAgo2 first . To further investigate this issue , one needs to explicitly simulate the collision and binding between flexible miRNA and hAgo2 in solution . Considering the experimental timescale ( at ~100 seconds[35] ) , this will be extremely challenging for all-atom MD simulations . We also note that the structural re-arrangement step in our proposed model can also be regarded as an induced fit mechanism . Indeed , our results do not rule out the possibility that induced fit mechanism plays a role during the initial hAgo2-miRNA recognition . However , it may be difficult for the induced fit model alone to explain multiple distinct timescales observed in the stop-flowed experiments . Our simulations also generate predictions that can be tested by experiments . For example , two mutants ( Y529A and Y529E ) were designed with modified binding pocket for the 5’ terminus of miRNA . MD simulations of these two mutants display distinct features: Y529A mutant largely preserves the interactions between miRNA and hAgo2 , while Y529E mutant significantly disrupts the protein-RNA interactions , resulting in substantial increase in the distance between miRNA and its binding pocket ( see Fig 5 ) . We note that even though one may need much longer simulations to thoroughly examine the stability of the hAgo2-miRNA complex , within the timescale we simulate ( at 100ns ) , we already clearly see that the Y529E mutant forms a less stable complex with miRNA compared to the WT and the Y529A mutant . These predictions are consistent with previous experiments showing that miRNA can bind to the Y529A mutant , but not the Y529E mutant[68 , 69] . More interestingly , since our MSM shows that interactions between the PIWI loops and the PAZ domain can stabilize the apo hAgo2 in the closed state , we designed three modifications on PIWI loops ( single mutant D823A , triple mutant E821A-D823A-E826A and deletion mutant ΔP602-D605ΔD819-Q833 ) that may cause hAgo2 to favor more the open state . Initiated from a closed conformation , the WT hAgo2 stays in the closed state throughout the 50-ns MD simulations ( see Fig 6A ) . This is expected as our MSM predicts that it may take tens of microseconds for the WT hAgo2 to diffuse out of this state ( see S10 Fig ) . However , the deletion mutant ( Δ602–605Δ819–833 ) undergoes fast conformational changes and reaches the open conformation within 20ns ( see Fig 6A ) . The other two mutants ( D823A and E821A-D823A-E826A ) also quickly escape from the closed conformational state and reach partially open conformations ( see Fig 6A ) . As shown in Fig 6B , the mutant simulations initiated from a partially open conformation are mostly consistent with those started from the closed conformation . Since this initial hAgo2 conformation is extracted from a partially open crystal structure of hAgo2-miRNA complex , the removal of miRNA may leave space and further lead to the collapse of the hAgo2 to reach the closed state in the WT MD simulations . As controls , we have also performed MD simulations of the WT hAgo2 and the mutants initiated from an open conformation ( see Fig 6C ) . As expected , all the systems remain in the open conformation throughout the MD simulations . Taken together , the above observations suggest that the PIWI loops mutations are likely to accelerate the transition from the closed to the open conformation by destabilizing the closed state . We hence predict that these mutations could facilitate the initial binding of miRNA by modulating hAgo2’s conformational dynamics to make its open state more accessible , even though these mutants are located far from the protein-RNA binding interface . We note that the interaction between PAZ and the PIWI loops not only regulates the molecular recognition between hAgo2 and miRNA , but could also play a role during mRNA recognition by hAgo2-miRNA complex ( see S2 Text for detailed discussions ) . In conclusion , by combining MSMs , large-scale protein-RNA docking , and MD simulations , we propose a two-step mechanism for the molecular recognition between miRNA and hAgo2: selective binding followed by structural re-arrangement . Using MSMs , we identified an open state of apo hAgo2 in rapid equilibrium with partially open and closed states of this enzyme . Conformations in this open state can contain a widely open binding groove , which are shown to be able to accommodate miRNA in our protein-RNA docking simulations . We thus suggest that the initial binding of miRNA to hAgo2 adopts a selective binding mechanism . This initial binding complex may undergo further structural re-arrangement to finally reach the stable binary complex structure . Our model is consistent with previous experimental results , and fills in more details at molecular level . We have also made predictions that can be tested experimentally . Our studies provide novel insights in fundamental mechanisms of how the Argonaute protein recognizes miRNA , which plays an important role in the gene regulation by RNA interference . The methodology here also holds great promise to be widely applied to investigate molecular recognition mechanism of other biological event , such as protein-protein interactions and protein-ligand binding .
The initial apo hAgo2 conformation was taken from the crystal structure of hAgo2 in complex with miR-20a ( PDB ID: 4F3T ) [32] , and the missing residues were added using MODELLER[70–73] . The apo hAgo2 protein was solvated in a dodecahedron box containing 42 , 847 SPC water molecules[74] with 129 Na+ ions and 159 Cl- ions to neutralize the charge . All the MD simulations were performed using the GROMACS 4 . 5 . 4 package[75] and the Amber99SB-ILDN force field[76] . Long-range electrostatic interactions were treated with the Particle-Mesh Ewald method[77] . Both short-range electrostatic interactions and van der Waals interactions used a cutoff of 10Å . All bonds were constrained by the LINCS algorithm[78] . Velocity-rescaling thermostat[79] and the Parrinello-Rahman barostat [80] were used for temperature and pressure coupling respectively . The system was first energy minimized with the steepest descent algorithm and equilibrated for 1ns under NPT ensemble ( T = 310K , P = 1atm ) with the positions of all the heavy atoms restrained . Next , we performed a 5-ns NPT simulation ( T = 310K , P = 1atm ) to further equilibrate the system . Finally , all the production MD simulations were performed under NVT ensemble at 310K . After the equilibration , we first performed six independent MD simulations ranging from 50 to 100ns which summed up to ~400ns . We then divided the conformations obtained from these six MD simulations ( saved every 20ps with a total of ~20 , 000 conformations ) into 20 clusters using the K-centers algorithm[81] . We randomly selected one conformation from each cluster and initiated a second round of 150-ns MD simulations with one simulation from each of these 20 conformations . Next , we extracted ~170 , 000 conformations from the first two rounds of MD simulations and built an MSM containing 553 microstates that were further lumped into 9 macrostates . However , the 553-microstate MSM predicted kinetics inconsistent with the original MD simulations , indicating the necessity of additional sampling ( see S13 Fig ) . We thus seeded the third round of MD simulations from conformations taken from each of the 9 macrostate in the initial MSM with the number proportional to their predicted equilibrium populations . In this round , we performed 30 150-ns MD simulations with a saving interval of 20ps . Combining MD simulations from all three rounds , we obtained a dataset containing over 394 , 000 conformations extracted from ~8μs MD simulations . When constructing MSMs , one divides the conformational space into a group of metastable states , and coarse-grains time into a discrete interval Δt . If the model is Markovian , an MSM can predict the long-timescale dynamics via the first-order master equation: p ( nΔt ) =Tn ( Δt ) p ( 0 ) , ( 1 ) where p ( nΔt ) is the vector describing state population and T ( Δt ) is the transition probability matrix of the lag time Δt . To construct MSMs from MD simulations , we applied our recently developed Automatic state Partitioning for Multi-body systems ( APM ) algorithm[65] . The main insight of the APM algorithm is to take into account the kinetic information when performing the geometric clustering , which is often based on the RMSD between pairs of MD conformations . This is achieved by splitting the conformations using a divide-and-conquer scheme until all the resulting microstates has a common maximum residence time t0 . The residence time of a certain microstate i is measured by relaxation of the transition probability out of this state or escaping probability P ( i , t ) : P ( i , t ) =1−∑j=1n∑k=0 ( Tj−t ) /sδ ( mj ( ks ) −i ) δ ( mj ( ks+t ) −i ) ∑j=1n∑k=0 ( Tj−t ) /sδ ( mj ( ks ) −i ) , ( 2 ) where mj ( t ) indicates which microstate the system is in at time t . Tj is the length of the j-th MD trajectory with conformations stored at a time interval of s . We use the lifetime ( ti ) of microstate i , estimated by P ( i , ti ) = 1-1/e , as the indicator of its residence time . If ti < t0 ( t0 is the predetermined maximum residence time ) , the system can relax out of a microstate within t0 . The detailed procedure of the APM algorithm is as follows[65] ( see S14 Fig ) : ( 1 ) Perform a geometric clustering using the K-centers algorithm[81] to divide MD conformations into two microstates . ( 2 ) Examine the residence time of each microstate . For microstate i , if ti ≥ t0 , we further split it until ti < t0 . We can then obtain a set of microstates with an upper limit on the residence time . ( 3 ) Lump kinetically related microstates into metastable macrostates using spectral clustering[82] . ( 4 ) Perform multiple iterations of re-splitting and re-lumping to remove potential internal free energy barriers within microstates . To apply the APM algorithm , we chose the maximum residence time t0 = 20ns , and this resulted in 480 microstates that were subsequently lumped into seven macrostates by spectral clustering[82] . To compute the distance between each pair of conformations , we first aligned all MD conformations to the crystal structure against its PIWI Cα atoms , and then computed Euclidean distances based on Cα atoms of the PIWI loops and every 3rd Cα atoms of L1L2 linking regions in the PAZ domain . In this way , both PIWI loops and PAZ-L1L2 regions , the two critical components that determine the magnitude of opening of hAgo2 , have relatively equal contributions to the pair-wise distance . The implied timescale τt is defined by the following equation: τt=−τlnλk , ( 3 ) where λk is the k-th largest eigenvalue of the transition probability matrix of τ . As shown in S2A Fig , the implied timescale plots of the 480-microstate MSM level off at around 20ns , indicating that the model is Markovian at this or longer lag time . In our production MSM , we selected 20ns as the lag time . To further validate our model , we also performed residence probability tests[45 , 54] . During these tests , we compared the MSM-predicted probability of the hAgo2 staying in a certain microstate with the probability derived by counting the transitions in MD trajectories . As shown in S2B Fig , the two probabilities agree well with each other , suggesting that our MSM captured the kinetics of apo hAgo2 sufficiently well . We further lumped the 480 microstates into seven macrostates because of the presence of a clear gap between 6th and 7th slowest timescales in the implied timescale plots of the microstate MSM . The implied timescale plot of the 7-macrostate MSM was congruent with that of microstate MSM ( see S2C Fig ) . However , this model predicted faster dynamics than that shown by MD trajectories during the residence probability tests ( see S2D Fig ) . Therefore , the 7-macrostate MSM model was used for visualization of the state decomposition and the 480-microstate MSM was used for calculating quantitative properties reported in this study . For example , we summed over the equilibrium populations of all the microstates that belong to a certain macrostate to obtain their populations . MFPT was used to estimate the dynamics between the open and the closed states . It is defined as the average time it takes for the system to visit the final state f from the initial state i . We computed MFPT between the open and the closed states by solving the following equation: Xif=ΣjT ( τ ) ij ( τ+Xjf ) , ( 4 ) where T ( τ ) ij is the transition probability from state i to state j , τ is the lag time with Xff = 0 . To compute the MFPT between a pair of macrostates from the 480-microstate MSM , we set MFPTs to be zero for all the microstates that belong to the final macrostate . We then computed MFPTs starting from each of the microstates that belong to the initial macrostate , and performed a weighted average over these MFPTs according to the normalized equilibrium populations of these microstates predicted by the 480-microstate MSM . We also performed a cross validation of the MFPTs calculated from our MSM by evenly dividing the dataset into two non-overlapping sub-datasets . MFPTs predicted from MSMs built from these two sub-datasets are in reasonable agreement with each other , and are also consistent with the MFPTs reported using the whole dataset ( see S15 Fig ) . Protein-RNA docking simulations were performed with HADDOCK 2 . 1[62 , 63] . Since the RNA binding groove is completely blocked or largely hindered by the PIWI loops in the closed or partially open hAgo2 conformations ( see S4 Fig for representative conformations ) , these conformations are unlikely to allow the direct miRNA binding . Therefore , we selected hAgo2 conformations that are as open as possible ( with PAZ-PIWI loops c . o . m . distance > 25Å ) and obtained 15 microstates . From each of these 15 microstates , we randomly selected 10 conformations for docking . The input miRNA structure was modeled using ModeRNA[83] based on miRNA fragments in the crystal structure ( PDB ID: 4F3T ) . We defined both Ambiguous Interaction Restraints ( AIR ) and unambiguous distance restraints to drive the docking simulations . For AIR , the “active” protein residues were defined according to the hAgo2-miRNA interactions suggested by Elkayam et al . [32]: R179 , S180 , A221 , T222 , H271 , K278 , R280 , F294 , Y311 , H316 , R351 , G524 , K525 , T526 , Y529 , K533 , Q545 , C546 , Q548 , N551 , S561 , K566 , K570 , D597 , R635 , D669 , R710 , Q757 , R761 , R792 , S798 , Y804 , H807 , and R812 . All RNA nucleotides were set to be “active” . We also imposed unambiguous distance restraints to guide the docking simulations ( see S2 Table ) . The inter- and intra-molecular interactions were calculated by CNS 1 . 3[84 , 85] with PARALLHDG5 . 4[86 , 87] and the OPLS-AA force field[88] applied to protein and miRNA respectively . For each docking simulation , topologies and coordinates of hAgo2 and miRNA were generated from input structures using CNS . The two molecules were initially separated 25Å away before the randomization and rigid body energy minimization . 200 docking poses were generated after the rigid body docking and ranked by the HADDOCK score , a weighted sum of various energy terms ( electrostatic , van der Waals , desolvation , ambiguous interaction restraints and buried surface area ) . The 50 best-scoring poses were subsequently used for semi-flexible simulated annealing and the final solvated refinement . Besides the HADDOCK score , we also employed an adapted definition of the fraction of native contacts ( fnat ) [89] to examine the quality of docking structures . The fraction of native contacts is defined as: fnat=qposeqcrystal , ( 5 ) where qpose and qcrystal denote the numbers of protein-miRNA contacts ( distance < 4Å ) observed in the docking pose and in the crystal structure , respectively . In total we collected 48 hAgo2-miRNA contacts from the crystal structure ( see S3 Table ) . Since HADDOCK cannot fully consider the conformational dynamics of hAgo2-miRNA complex upon the initial binding , we note that subsequent MD simulations are required to refine the docking poses . | In RNA interference , Argonaute proteins and microRNAs together form the functional core that regulates the gene expression with high sequence specificity . Elucidating the detailed mechanism of molecular recognition between Argonaute proteins and microRNAs is thus important not only for the fundamental understanding of RNA interference , but also for the further development of microRNA-based therapeutic application . In this work , we propose a two-step model to understand the mechanism of microRNA loading into human Argonaute-2: selective binding followed by structural re-arrangement . Our model is based on the results from a combined approach of molecular dynamics simulations , Markov State Models and protein-RNA docking . In particular , we identify a metastable open state of apo hAgo2 in rapid equilibrium with other states . Some of conformations in this open state have largely exposed RNA binding groove that can accommodate microRNA . We further show that the initial Argonaute-microRNA binding complex undergoes structural re-arrangement to reach stable binary crystal structure . These results provide novel insights into the underlying mechanism of Argonaute-microRNA recognition . In addition , our method is readily applicable to the investigation of other complex molecular recognition events such as protein-protein interactions and protein-ligand binding . | [
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] | [] | 2015 | Markov State Models Reveal a Two-Step Mechanism of miRNA Loading into the Human Argonaute Protein: Selective Binding followed by Structural Re-arrangement |
Across academia and industry , text mining has become a popular strategy for keeping up with the rapid growth of the scientific literature . Text mining of the scientific literature has mostly been carried out on collections of abstracts , due to their availability . Here we present an analysis of 15 million English scientific full-text articles published during the period 1823–2016 . We describe the development in article length and publication sub-topics during these nearly 250 years . We showcase the potential of text mining by extracting published protein–protein , disease–gene , and protein subcellular associations using a named entity recognition system , and quantitatively report on their accuracy using gold standard benchmark data sets . We subsequently compare the findings to corresponding results obtained on 16 . 5 million abstracts included in MEDLINE and show that text mining of full-text articles consistently outperforms using abstracts only .
Text mining has become a widespread approach to identify and extract information from unstructured text . Text mining is used to extract facts and relationships in a structured form that can be used to annotate specialized databases , to transfer knowledge between domains and more generally within business intelligence to support operational and strategic decision-making [1–3] . Biomedical text mining is concerned with the extraction of information regarding biological entities , such as genes and proteins , phenotypes , or even more broadly biological pathways ( reviewed extensively in [3–9] ) from sources like scientific literature , electronic patient records , and most recently patents [10–13] . Furthermore , the extracted information has been used as annotation of specialized databases and tools ( reviewed in [3 , 14] ) . In addition , text mining is routinely used to support manual curation of biological databases [15 , 16] . Thus , text mining has become an integral part of many resources serving a wide audience of scientists . The main text source for scientific literature has been the MEDLINE corpus of abstracts , essentially due to the restricted availability of full-text articles . However , full-text articles are becoming more accessible and there is a growing interest in text mining of complete articles . Nevertheless , to date no studies have presented a systematic comparison of the performance comparing a very large number of abstracts and full-texts in corpora that are similar in size to MEDLINE . Full-text articles and abstracts are structurally different [17] . Abstracts are comprised of shorter sentences and very succinct text presenting only the most important findings . By comparison , full-text articles contain complex tables , display items and references . Moreover , they present existing and generally accepted knowledge in the introduction ( often presented in the context of summaries of the findings ) , and move on to reporting more in-depth results , while discussion sections put the results in perspective and mention limitations and concerns . The latter is often considered to be more speculative compared to the abstract [3] . While text-mining results from accessible full-text articles have already become an integral part of some databases ( reviewed recently for protein-protein interactions [18] ) , very few studies to date have compared text mining of abstracts and full-text articles . Using a corpus consisting of ~20 , 000 articles from the PubMed Central ( PMC ) open-access subset and Directory of Open Access Journals ( DOAJ ) , it was found that many explicit protein–protein interactions only are mentioned in the full text [19] . Additionally , in a corpus of 1 , 025 full-text articles it was noticed that some pharmacogenomics associations are only found in the full text [20] . One study using a corpus of 3 , 800 articles with focus on Caenorhabditis elegans noted an increase in recall from 45% to 95% when including the full text [21] . Other studies have worked with even smaller corpora [17 , 22 , 23] . One study have even noted that the majority of claims within an article is not reported in the abstract [24] . Whilst these studies have been of significant interest , the number of full-text articles and abstracts used for comparison are nowhere near the magnitude of the actual number of scientific articles published to date , and it is thus unclear if the results can be generalized to the scientific literature as a whole . The earlier studies have mostly used articles retrieved from PMC in a structured XML file . However , full-text articles received or downloaded directly from the publishers often come in the PDF format , which must be converted to a raw unformatted text file . This presents a challenge , as the quality of the text mining will depend on the proper extraction and filtering of the unformatted text . A previous study dealt with this by writing custom software taking into account the structure and font of each journal at that time [21] . More recent studies typically provide algorithms that automatically determines the layout of the articles [25–27] . In this work , we describe a corpus of 15 million full-text scientific articles from Elsevier , Springer , and the open-access subset of PMC . The articles were published during the period 1823–2016 . We highlight the possibilities by extracting protein–protein associations , disease–gene associations , and protein subcellular localization from the large collection of full-text articles using a Named Entity Recognition ( NER ) system combined with a scoring of co-mentions . We quantitatively report the accuracy and performance using gold standard benchmark data sets . Lastly , we compare the findings to corresponding results obtained on the matching set of abstracts included in MEDLINE as well as the full set of 16 . 5 million MEDLINE abstracts .
The MEDLINE corpus consists of 26 , 385 , 631 citations . We removed empty citations , corrections and duplicate PubMed IDs . For duplicate PubMed IDs we kept only the newest entry . This led to a total of 16 , 544 , 511 abstracts for text mining . The PubMed Central corpus comprises 1 , 488 , 927 freely available scientific articles ( downloaded 27th January 2017 ) . Each article was retrieved in XML format . The XML file contains the article divided into paragraphs , article category and meta-information such as journal , year published , etc . Articles that had a category matching Addendum , Corrigendum , Erratum or Retraction were discarded . A total of 5 , 807 documents were discarded due to this , yielding a total of 1 , 483 , 120 articles for text mining . The article paragraphs were extracted for text mining . No further pre-processing of the text was done . The journals were categorized according to categories ( described in the following section ) by matching the ISSN number . The number of pages for each article was also extracted from the XML , if possible . The Technical Information Center of Denmark ( DTU Library ) TDM corpus is a collection of full-text articles from the publishers Springer and Elsevier . The corpus covers the period from 1823 to 2016 . The corpus comprises 3 , 335 , 400 and 11 , 697 , 096 full-text articles in PDF format , respectively . An XML file containing meta-data such as publication date , journal , etc . accompanies each full-text article . PDF to TXT conversion was done using pdftotext v0 . 47 . 0 , part of the Poppler suite ( poppler . freedesktop . org ) . 192 articles could not be converted to text due to errors in the PDF file . The article length , counted as the number of pages , was extracted from the XML file . If not recorded in the XML file we counted the number of pages in the PDF file using the Unix tool pdfinfo v0 . 26 . 5 . Articles were grouped into four bins , determined from the 25% , 50% , and 75% quantiles , respectively . These were found to be 1–4 pages ( 0–25% ) , 5–7 pages ( 25–50% ) , 8–10 pages ( 50–75% ) and 11+ pages ( 75%-100% ) . Each article was , based on the journal where it was published , assigned to one or more of the following seventeen categories: Health Sciences , Chemistry , Life Sciences , Engineering , Physics , Agriculture Sciences , Material Science and Metallurgy , Earth Sciences , Mathematical Sciences , Environmental Sciences , Information Technology , Social Sciences , Business and Economy and Management , Arts and Humanities , Law , Telecommunications Technology , Library and Information Sciences . Due to the large number of categories , we condensed anything not in the top-6 into the category “Other” . The top-six categories health science , chemistry , life sciences , engineering , physics and agricultural sciences make up 74 . 8% of the data ( S1 Fig ) . The assignment of categories used in this study was taken from the existing index for the journal made by the librarians at the DTU Library . For the temporal statistics , the years 1823–1900 were condensed into one . Following the PDF-to-text conversion of the Springer and Elsevier articles we ran a language detection algorithm implemented in the python package langdetect v1 . 0 . 7 ( https://pypi . python . org/pypi/langdetect ) . We discarded 902 , 415 articles that were not identified as English . We pre-processed the remaining raw text from the articles as follows: We assumed that acknowledgments and reference lists are always at the end of the article . Upon encountering either of the terms: “acknowledgment” , “bibliography” , “literature cited” , “literature” , “references” , and the following misspellings thereof: “refirences” , “literatur” , “références” , “referesces” . In some cases the articles had no heading indicating the start of a bibliography . We tried to take these cases into account by constructing a RegEx that matches the typical way of listing references ( e . g . [1] Westergaard , … ) . Such a pattern can be matched by the RegEx “^\[\d+\]\s[A-Za-z]” . The other commonly used pattern , “1 . Westergaard , …” , was avoided since it may also indicate a new heading . Keywords were identified based on several rounds of manual inspection . In each round , 100 articles in which the reference list had not been found was randomly selected and inspected . We were unable to find references in 286 , 287 and 2 , 896 , 144 Springer and Elsevier articles , respectively . Manual inspection of 100 randomly selected articles revealed that these articles indeed did not have a reference list or that the pattern was not easily describable with simple metrics , such as keywords and RegEx . Articles without references were not discarded . The PDF to text conversion often breaks up paragraphs and sentences , due to new page , new column , etc . Paragraph and sentence splitting was performed using a ruled-based system . If the previous line of text does not end with a “ . ! ? ” , and the current line does not start with a lower-case letter , it is assumed that the line is part of the previous sentence . Otherwise , the line of text is assumed to be a new paragraph . A number of Springer and Elsevier documents were removed due to technical issues post pre-processing . An article was removed if: Some PDF files without texts are scans of the original article ( point 1 ) . We did not attempt to make an optical character recognition conversion ( OCR ) as the old typesetting fonts often are less compatible with present day OCR programs , and this can lead to text recognition errors [28 , 29] . For any discarded document , we still used the meta-data to calculate summary statistics . In some cases the PDF to text conversion failed , and produced non-sense data with a white space between the characters of a majority of the words ( point 2 ) . To empirically determine a cutoff we gradually increased the cutoff and repeatedly inspected 100 randomly selected articles . At the 2% quantile we saw no evidence of broken text . Articles with the following keywords in the article were discarded: Author Index , Key Word Index , Erratum , Editorial Board , Corrigendum , Announcement , Books received , Product news , and Business news ( point 3 ) . These keywords were found as part of the process of identifying acknowledgments and reference lists . Further , any article that was available through PubMed Central was preferentially selected by matching doi identifiers . This left a total of 14 , 549 , 483 full-text articles for further analysis . Some articles were not separable , or were subsets of others . For instance , conference proceedings may contain many individual articles in the same PDF . We found 1 , 911 , 365 articles in which this was the case . In these cases we removed the duplicates , or the shorter texts , but kept one copy for text mining . In total , we removed 898 , 048 duplicate text files . The majority of articles had a separate abstract . We matched articles from PubMed Central to their respective MEDLINE abstract using the PMCID to PubMed ID conversion file available from PMC . Articles from Springer and Elsevier typically had a separate abstract in the meta-data . Any abstract from an article that was part of the 1 , 911 , 365 articles that could not be separated was removed . This led to a total of 10 , 376 , 626 abstracts for which the corresponding full text was also included downstream , facilitating a comparative analysis . References for the full text articles analyzed can be found at 10 . 6084/m9 . figshare . 5419300 . An article is preferentially referenced by its Digital Object Identifier ( DOI ) ( 98 . 8% ) . However , if that was not available , we used the PubMed Central ID for PMC articles ( 0 . 005% ) , or the list of authors , article title , journal name , and year . ( 0 . 006% ) We performed text mining of the articles using a Named Entity Recognition ( NER ) system , described earlier [30–33] . The software is open source and can be downloaded from https://bitbucket . org/larsjuhljensen/tagger . The NER approach is dictionary based , and thus depends on well-constructed dictionaries and stop word lists . We used the gene names from the STRING dictionary v10 . 0 [30] , disease names from the Disease Ontology ( DO ) [34] and compartment names from the Gene Ontology branch cellular component [35] . Stop word lists were all created and maintained in-house . Pure NER based approaches often struggles with ambiguity of words . Therefore , we included additional dictionaries that we do not report the results from . If any identified term was found in multiple dictionaries , it was discarded due to ambiguity . The additional dictionaries include small molecule names from STITCH [36] , tissue names from the Brenda Tissue Ontology [37] , Gene Ontology biological process and molecular function [35] , and the mammalian phenotype ontology [38] . The latter is a modified version made to avoid clashes with the disease ontology . The dictionaries can be downloaded from https://doi . org/10 . 6084/m9 . figshare . 5827494 . In the cases where the dictionary was constructed from an ontology co-occurrences were backtracked through all parents . E . g . the term type 1 diabetes mellitus from the Disease Ontology is backtracked to its parent , diabetes mellitus , then to glucose metabolism disease , etc . Co-occurrences were scored using the scoring system described in [39] . In short , a weighted count for each pair of entities ( e . g . disease-gene ) was calculated using the formula , C ( i , j ) =∑k=1nwdδdk ( i , j ) +wpδpk ( i , j ) +wsδsk ( i , j ) ( 1 ) where δ is an indicator function taking into account whether the terms i , j co-occur within the same document ( d ) , paragraph ( p ) , or sentence ( s ) . w is the co-occurrence weight here set to 1 . 0 , 2 . 0 , and 0 . 2 , respectively . Based on the weighted count , the score S ( i , j ) was calculated as , S ( i , j ) =Cijα ( CijC . . Ci . C . j ) 1−α ( 2 ) where α is set to 0 . 6 . All weights were optimized using the KEGG pathway maps as benchmark ( described further below ) . The S scores were converted to Z scores , as described earlier [40] . PPIs were benchmarked using pathway maps from the KEGG database [41–43] . Any two proteins in the same pathway were set to be a positive example , and any two proteins present in at least one pathway , but not the same , were set as a negative example . This approach assumes that the pathways are near complete and includes all relevant proteins . The same approach has been used for the STRING database [39] . The disease–gene benchmarking set was created by setting the disease-gene associations from UniProt [44] and Genetics Home Reference ( https://ghr . nlm . nih . gov/ , accessed 23th March 2017 ) as positive examples . The positive examples were then shuffled , and the shuffled examples were set as negative examples . Shuffled examples that ended up overlapping with the positive examples were discarded . This approach has previously been described [31] . The protein–compartment benchmark set was created by extracting the compartment information for each protein from UniProt and counting these as positive examples . For every protein found in at least one compartment , all compartments where it was not found were set as negative examples . The same approach has been used previously [33] . Receiver Operating Characteristic ( ROC ) curves were created by gradually increasing the Z-score and calculating the True Positive Rate ( TPR ) and False Positive Rate ( FPR ) , as described in eqs ( 3 ) and ( 4 ) . We compare the ROC curves by the Area Under the Curve ( AUC ) , a metric ranging from 0 to 1 . ROC-AUC curves provide a quantitative way of comparing benchmarks of classifiers , and is often used in machine learning and text mining . A perfect classifier will have an AUC = 1 , and a classifier that performs equal to or worse than random will have an AUC ≤ 0 . 5 . Individual mentions of entities used for the benchmark in each article can be downloaded from 10 . 6084/m9 . figshare . 5620417 .
The growth of the data set over time is of general interest in itself , however , it is also important to secure that the concepts used in the benchmarks are likely to be present in a large part of the corpus . We found that the number of full-text articles has grown exponentially over a long period ( Fig 1A , a log-transformed version is provided in S2 Fig ) . We also observed that the growth represents a mixture of two components: one from 1823–1944 , and another from 1945–2016 . Through linear regression of the log2-transformed counts for the period 1945–2016 we found that the growth rate is 0 . 103 ( p < 2 * 10−16 , R2 = 0 . 95 ) . Thus , the doubling time for the full-text corpus is 9 . 7 years . In comparison , MEDLINE had a growth rate of 0 . 195 ( p < 2 * 10−16 , R2 = 0 . 91 ) and a doubling time of 5 . 1 years . We noticed that there was a drop in the number of full-text publications around the years 1914–1918 and 1940–1945 . Likewise , we see a decrease in the number of publications indexed by MEDLINE in the entire period 1930–1948 . In the full-text corpora we found a total of 12 , 781 unique journal titles . The most prevalent journals are tied to health or life sciences , such as The Lancet , Tetrahedron Letters , and Biochemical and Biophysical Research Communications , or the more broad journals such as PLoS ONE ( see S1 Table for the top-15 journals ) . The Lancet publishes only very few articles per issue , it was established in 1823 and has been active in publishing since then , thus explaining why it so far has nearly published 400 , 000 articles . In contrast , PLoS ONE was launched in 2006 , and has published more than 172 , 000 articles . Of the 12 , 781 journal titles , 6 , 900 had one or more category labels assigned by librarians at the Technical University of Denmark . The vast majority of the full-texts , 13 , 343 , 040 , were published in journals with one or more category labels . The frequency of each category within the corpus can be seen in S1 Fig . We observed that before the 1950’s health science dominated and made up almost 75% of all publications ( Fig 1B ) . At the start of the 1950’s the fraction started to decrease , and to date health science makes up approximately 25% of all publications in the full-text corpus . Inspecting the remaining eleven categories in a separate plot we found that there was no single category that was responsible for the growth ( S3 Fig ) . We binned the full-text articles into four categories based on the number of pages ( see Methods ) . The average length of articles has increased considerably during the almost 250 years studied ( Fig 1C ) . Whereas 75% of the articles were 1–3 pages long at the end of the 20th century , less than 25% of the articles published after year 2000 are that short . Conversely , articles with ten or more pages only made up between 0 . 7%-7% in the 19th century , a level that had grown to 20% by the start of the 21st century . We also observed that the average number of mentioned entities changed over time ( S4 Fig ) . Mentions of genes and compartments were nearly non-existing prior to 1950 , and has been increasing at an exponential rate since year 2000 . Moreover , disease mentions dropped around year 1950 , which correlates well with the decreasing proportion of published articles from health science journals in our corpus ( Fig 1C ) . We ran the textmining pipeline on the two full-text and two abstract corpora . In all cases we found that the AUC-value was far greater than 0 . 5 , from which we conclude that the results were substantially better than random ( Fig 2 ) ( see Methods for a definition of the AUC ) . The biggest gain in performance when using full-text was seen in finding associations between diseases and genes ( AUC increase from 0 . 85 to 0 . 91 ) ( Table 1 ) . Compared to MEDLINE , the traditional corpus used for biomedical text mining , there was an increase in the AUC from 0 . 85 to 0 . 91 . The smallest gain was associations between proteins , which increased from 0 . 70 to 0 . 73 . Likewise , the Core Full-texts always performed better than Core Abstracts , signifying that some associations are only reported in the main body of the text . Consequently , traditional text mining of abstracts will never be able to find this information . All Z-scores used for benchmarking can be downloaded from https://doi . org/10 . 6084/m9 . figshare . 5340514 . It has previously been speculated if text mining of full-text articles may be more difficult and lead to an increased rate of false positives [3] . To investigate this we altered the weights of the scoring system ( See Methods , Eqs 1 and 2 ) . The scoring scheme used here has weights for within sentence , within paragraph and within document co-occurrences ( see Methods ) . When setting the document weight to zero versus using the previously calibrated value found in an earlier study we found that having a non-zero small value does indeed improve extraction of known facts in all cases ( S5 Fig ) [33] . We observed that the increase in AUC is less than when using a lower document weight ( S2 Table ) . In one case , protein–protein associations , the MEDLINE abstract corpus outperforms the full-text articles . Abstracts are generally unaffected by the document weight , mainly because abstracts are almost always one paragraph . Overall , the difference in performance gain is largest for full-texts and lowest for abstracts and MEDLINE . Hence , all the full-text information is indeed valuable and necessary . For practical applications , it is often necessary to have a low False Positive Rate ( FPR ) . Accordingly , we evaluated the True Positive Rate ( TPR ) of the different corpora at the 10% FPR ( TPR@10%FPR ) ( Fig 3 ) . We found that full-texts have the highest TPR@10%FPR for disease-gene associations ( S2 Table ) . When considering protein–protein associations and protein-compartment associations , full-texts perform equivalently to Core Abstracts and Core Full-texts . The result was similar to when we evaluated the AUC across the full range , removing the document weight has the biggest impact on the full-texts ( S5 Fig and S6 Fig ) , while abstracts remain unaffected .
We have investigated a unique corpus consisting of 15 million full-text articles and compared the results to the most commonly used corpus for biomedical text mining , MEDLINE . We found that the full-text corpus outperforms the MEDLINE abstracts in all benchmarked cases , with the exception of TPR@10%FDR for protein–compartment associations . To our knowledge , this is the largest comparative study to date of abstracts and full-text articles . We envision that the results presented here can be used in future applications for discovering novel associations from mining of full-text articles , and as a motivation to always include full-text articles when available and to improve the techniques used for this purpose . The corpus consisted of 15 , 032 , 496 full-text documents , mainly in PDF format . 1 , 504 , 674 documents had to be discarded for technical reasons , primarily because they were not in English . Further , a large number of documents were also found to be duplicates or subsets of each other . On manual inspection we found that these were often conference proceedings , collections of articles etc . , which were not easily separable without manual curation . We also managed to identify the list of references in the majority of the articles thereby reducing some repetition of knowledge that could otherwise lead to an increase in the false positive rate . We have encountered and described a number of problems when working with full-text articles converted from PDF to TXT from a large corpus . However , the majority of the problems did not stem from the PDF to TXT conversion , which could potentially be solved using a layout aware conversion tool . Examples include PDFX [25] , SectLabel [26] and LA-PDFText [27] of which the first is not practical for very large corpora as it only exists as an online tool . Nonetheless , to make use of the large volume of existing articles it is necessary to solve these problems . Having all the articles in a structured XML format , such as the one provided by PubMed Central , would with no doubt produce a higher quality corpus . This may in turn further increase the benchmark results for full-text articles . Nevertheless , the reality is that many articles are not served that way . Consequently , the performance gain we report here should be viewed as a lower limit as we have sacrificed quality in favor of a larger volume of articles . The solutions we have outlined here will serve as a guideline and baseline for future studies . The increasing article length may have different underlying causes , but one of the main contributors is most likely increased funding to science worldwide [45 , 46] . Experiments and protocols are consequently getting increasingly complex and interdisciplinary–aspects that also contribute to driving meaningful publication lengths upward . The increased complexity has also been found to affect the language of the articles , as it is becoming more specialized[47] . Moreover , we observed a steep increase in the average number of mentions of genes and compartments . This finding can most likely be attributed to recent developments in molecular biology , such as the sequencing of the human genome , Genome Wide Association Studies ( GWAS ) , and other high-throughput technologies in ‘omics [48 , 49] . It was outside the scope of this paper to go further into socio-economic impact . We have limited this to presenting the trends from what could be computed from the meta-data . Previous papers are–in terms of benchmarking–only making qualitative statements about the value of full-text articles as compared to text in abstracts . In one paper a single statement is made on the potential for extracting information , but no quantitative evidence is presented [50] . In a paper targeting pharmacogenomics it is similarly stated that that there are associations that only are found in the full-text , but no quantitative estimates are presented [20] . In a paper analyzing around 20 , 000 full-text papers a search for physical protein interactions was made , concluding that these contain considerable higher levels of interaction [19] . Again , no quantitative benchmarks were made comparing different sources . In this paper , we have made a detailed comparison of four different corpora that provides a strong basis for estimating the added value of using full-text articles in text mining workflows . We have used quite difficult , but still well established benchmarks , to illustrate the differences in performance when comparing text mining of abstracts to full-text articles . Within biology , and specifically in the area of systems biology , macromolecular interactions and the relationships between genes , tissues and diseases are key data that drive modeling and the analysis of causal biochemical mechanisms . Knowledge of interactions between proteins is extremely useful when revealing the components , which contribute to mechanisms in both health and disease . As many biological species from evolution share protein orthologs , their mutual interactions can often be transferred , for example from an experiment in another organism to the corresponding pair of human proteins where the experiment has not yet been performed . Such correspondences can typically be revealed by text mining as researchers in one area often will not follow the literature in the other and vice versa . The results presented here are purely associational . Through rigorous benchmarking and comparison of a variety of biologically relevant associations , we have demonstrated that a substantial amount of relevant information is only found in the full body of text . Additionally , by modifying the document weight we found that it was important to take into account the whole document and not just individual paragraphs . The improvement in AUC that we present here were not overwhelming . One reason could be that associations have a higher probability of being curated if they are mentioned in the abstract . Moreover , most tools are geared towards abstracts . Thus , what we present is a lower limit on the performance gain . Consequently , as more full-text articles become available and text-mining methods improve , the quantitative benchmarks will improve . However , because the literature is highly redundant diminishing returns in terms of performance gain should be expected when adding evermore text . Event-based text mining will be the next step for a deeper interpretation and extending the applicability of the results [5] . With more development it may also be possible to extract quantitative values , as has been demonstrated for pharmacokinetics [51] . Other work is also going into describing the similarity between terms , and how full-text articles can augment this [52] . However , this is beyond the scope of this article . The Named Entity Recognition ( NER ) system used depends heavily on the dictionaries and stop word lists . A NER system is also very sensitive to ambiguous words . To combat this we have used dictionaries from well-known and peer-reviewed databases , and we have included other dictionaries to avoid ambiguous terms . Other approaches to text mining have previously been extensively reviewed [10 , 14 , 51] . The full-text corpus presented here consists of articles from Springer , Elsevier and PubMed . However , we still believe that the results presented here are valid and can be generalized across publishers , to even bigger corpora . Preprocessing of corpora is an ongoing research project , and it can be difficult to weed out the rubbish when dealing with millions of documents . We have tried to use a process where we evaluate the quality of a subset of randomly selected articles repeatedly and manually , until it no longer improves . | Text mining has become an integral part of all fields in science . Owing to the large number of articles published every day , it is necessary to employ automated systems to assist in curation , knowledge management and discovery . To date , most systems make use of information collected from abstracts only . Moreover , studies on smaller collections of abstracts and full-text articles have demonstrated some information is available only in the full-text body . Nonetheless , to date there has been no large-scale comprehensive comparison of abstracts and full-text articles . In this work , we analyze a hitherto unprecedented collection of 15 million full-text articles . Through quantitative benchmarks we assess the difference between full-text articles and abstracts . Our findings confirm what has long been discussed , namely that access to the full-text body improved text mining greatly . | [
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In July and September 2007 , miners working in Kitaka Cave , Uganda , were diagnosed with Marburg hemorrhagic fever . The likely source of infection in the cave was Egyptian fruit bats ( Rousettus aegyptiacus ) based on detection of Marburg virus RNA in 31/611 ( 5 . 1% ) bats , virus-specific antibody in bat sera , and isolation of genetically diverse virus from bat tissues . The virus isolates were collected nine months apart , demonstrating long-term virus circulation . The bat colony was estimated to be over 100 , 000 animals using mark and re-capture methods , predicting the presence of over 5 , 000 virus-infected bats . The genetically diverse virus genome sequences from bats and miners closely matched . These data indicate common Egyptian fruit bats can represent a major natural reservoir and source of Marburg virus with potential for spillover into humans .
Viruses of the Marburgvirus and Ebolavirus genera ( family Filoviridae ) cause outbreaks of hemorrhagic fever in Africa characterized by person-to-person spread and high case fatality . Humans have on occasion acquired infection from contact with tissues of diseased nonhuman primates and perhaps herbivores , but the susceptibility of these animals to fatal infection renders it unlikely that they could serve as filoviruses reservoir hosts . Although the source of filoviruses in nature has not been definitively identified , the cumulative evidence suggests that bats are involved . The infected monkeys consigned from Uganda to Europe in 1967 , which resulted in the first recognized outbreaks of Marburg hemorrhagic fever ( MHF ) , were caught on the shores of Lake Victoria and on islands where fruit bats are prevalent [1] . In 1975 , the second recorded outbreak of MHF involved tourists who slept at two locations in Zimbabwe in rooms containing insectivorous bats followed by a purported visit to Chinhoyi caves ( formerly Sinoia caves ) where bats may also have been present [2] . In the first recognized outbreak of Ebola hemorrhagic fever ( EHF ) in 1976 , the first six patients worked in a room where bats roosted in a cotton factory in Sudan [3] . In 1980 and 1987 , two patients who developed MHF in Kenya both visited a cave inhabited by bats shortly before becoming ill [4] , [5] . In 1994 , chimpanzees which developed EHF in Cote d'Ivoire had been observed feeding in a wild fig tree together with fruit bats for two weeks before developing the disease [6] . The Reston ebolavirus , which is apparently nonpathogenic for humans , was introduced into the USA and Europe on several occasions via imported infected monkeys from the Philippines , and each time the animals originated from a single export facility located on the grounds of a former fruit orchard where they were potentially exposed to the excreta of fruit bats [7] . In1996 , it was shown that experimentally infected fruit bats were capable of supporting replication of ebolavirus without developing overt disease [8] . In 1998–2000 , a protracted outbreak of MHF in Durba village in northeastern Democratic Republic of the Congo ( DRC ) consisted of repeated occurrences of short transmission chains arising in workers in Goroumbwa Mine where large numbers of bats roosted . The impression that there were recurrent introductions of infection into humans from a natural source was supported by finding that multiple genetic lineages of virus circulated during the outbreak [9] . Significantly , diverse genetic lineages of Marburg virus were detected in Egyptian fruit bats , Rousettus aegyptiacus , and two species of insectivorous bat in the mine , and the outbreak ceased when the mine flooded , but no live virus was isolated from bats [10] . In 2002 , ebolavirus RNA was detected in three forest-dwelling species of fruit bat in Gabon during an investigation which followed outbreaks of EHF [11] and in 2005 nucleic acid of Marburg virus was detected in R . aegyptiacus bats in the same country in the absence of a corresponding outbreak of disease [12] . On both occasions it again proved impossible to isolate live virus . In July 2007 , a small outbreak of MHF occurred in workers mining lead and gold in Kitaka Cave near Ibanda village in western Uganda . Large numbers of R . aegyptiacus and insectivorous Hipposideros species bats were present in this mine . Ecological investigations were conducted in August 2007 and May 2008 , and the findings are presented here .
Kitaka Cave was first mined in the 1930s and eventually became a large producer of lead ore in Uganda , but was closed in 1979 . It was reopened in January 2007 , and in July a miner working in the cave fell ill and died with disease confirmed at Centers for Disease Control and Prevention , USA ( CDC ) to be MHF ( patient A , Table 1 ) . The Ugandan Ministry of Health closed the mine shortly thereafter . Following the month-long ecological investigation in August 2007 , a second miner ( patient B , Table 1 ) was confirmed to have MHF . The timing of his onset of symptoms in September , plus a lack of epidemiologic linkage to the first case , suggested that he re-entered the mine surreptitiously shortly after the departure of the investigating team . Thus , it appears that the ecological study was conducted at a time when Marburg virus activity was continuing . Marburg virus was isolated from each of the two miners , and full-length genome sequences were determined ( 01Uga2007 and 02Uga2007 respectively ) . Retrospective analysis of Patient A's contacts found two additional Kitaka miners positive for Marburg virus-specific IgG ( data not shown ) . Both of these miners reported symptoms consistent with MHF in the month prior to Patient A falling ill . Marburg virus nucleic acid was detected by Q-RT-PCR in a total of 32 bats , and for the first time , live virus was isolated from five of the bats ( Tables 2 and 3 ) . There was a direct correlation between RNA levels ( viral load ) determined by Q-RT-PCR and the ability to isolate virus; 4/5 bats which yielded isolates had the highest RNA levels ( lowest Ct values ) ( Table 3 ) . Although rigorous quantitative analysis was not performed , the highest viral load measured ( a Ct value of 24 recorded in bat 371 ) , if compared to a liquid sample , corresponded to an approximate infectious titer of 1×105 pfu/ml . This suggests that some infected individuals contain high levels of virus and may be shedding , perhaps infecting other animals , including humans . The fact that four isolates were obtained from R . aegyptiacus bats caught in 2007 and the fifth isolate came from a bat of the same species caught nine months later in 2008 implies that R . aegyptiacus colonies can harbor Marburg virus for extended periods of time . Previous studies [10] , [11] , [12] indicated that a modest prevalence of low-titered virus could be expected in liver and spleen samples . Possible reasons for the success in isolating live virus in the present study include the fact that an effort was made to sample relatively large numbers of bats and to flash freeze and preserve samples in liquid nitrogen directly after dissection . Moreover , the limited size of the outbreak in humans allowed the investigators to concentrate on implementing the initial ecological study shortly after the outbreak started , while virus activity in the bat colony was probably still high . By equating RNA-positivity with virus infection , it is possible to derive preliminary conclusions on the dynamics of Marburg virus activity in bat populations . Although there was a similar frequency of RNA-positivity in bats collected in August 2007 and May 2008 , the fact that a total of 31/611 ( 5 . 1% ) R . aegyptiacus bats in both collections tested positive in comparison to only 1/609 ( 0 . 2% ) Hipposideros spp . bat ( Table 2 ) , suggests that infection in the latter species represented spillover from circulation of virus in R . aegyptiacus bats . In contrast , approximately equal proportions ( 3 . 0–3 . 6% ) of R . aegyptiacus and two species of insectivorous bats were found positive for Marburg virus RNA in Goroumbwa Mine , DRC , in 1999 [10] , [11] , [12] , but meaningful comparisons are precluded by differences in sample size and the inadequacy of population estimates . Serologic testing found 13/546 ( 2 . 4% ) R . aegyptiacus bats ( data not shown ) , all adults , clearly positive for Marburg virus-specific IgG antibody ( titer≥400 , sum OD>0 . 95 ) , two of which ( #s 273 and 278 ) were also weakly positive by Q-RT-PCR . The testing found 455/546 ( 83 . 3% ) bats to be clearly negative , while another 78 R . aegyptiacus bats had indeterminate antibody levels ( titer = 100 , sum OD≥0 . 33≤0 . 95 ) . None of the Hipposideros spp . bats had detectable IgG to Marburg virus . It is unclear why only a low percentage of the R . aegyptiacus bat population is found positive for Marburg virus reactive IgG antibody . Perhaps a greater proportion of the population was previously infected , but antibody levels are below the conservative IgG assay cut-off used here . This would be consistent with low Marburg virus reactive antibody levels reported in previous bat studies [10] , [12] . The finding that only 2/13 IgG positive bats had detectable virus nucleic acid would suggest the majority of virus is being cleared prior to Marburg virus reactive antibody becoming detectable . All bats caught in 2007 and 2008 appeared healthy enough to leave their roosts to forage for food , the ratio of male to female R . aegyptiacus was similar in the two collections , and there appeared to be no gender bias in the evidence for Marburg virus infection ( Table 2 ) . However , the proportions of R . aegyptiacus juveniles and pregnant females present in the 2007 and 2008 collections differed markedly , and this appears to be consistent with the fact that the species is known to give birth in March and September in Uganda [13] , [14] . After a gestation period of 105–7 days , females usually give birth to a single pup which is carried attached to a nipple on the female for 6 weeks , then left at the roosting site and fed with regurgitated food for 9–10 weeks , before flying and fending for itself [15] . Thus , in August 2007 , 182/226 ( 80 . 5% ) R . aegyptiacus females were found to be pregnant ahead of giving birth in September , and juveniles , mostly weaned , represented 78/411 ( 19% ) of the collection . The prevalence of Marburg virus RNA detected in the juveniles , 8/78 ( 10 . 3% ) , was significantly higher than in adult R . aegyptiacus bats , 14/333 ( 4 . 2% ) ( p< . 05 , Fisher's exact test; Table 2 ) . Only 4/182 ( 2 . 1% ) of the pregnant females were RNA-positive , and their placentas all tested negative . Additionally , a single RNA-positive mother nursing an RNA-negative newborn pup was identified . In May 2008 , no R . aegyptiacus females were found to be pregnant , although microscopic examination of uterine tissues were not performed , and juveniles , presumably born mostly in March , represented 60/200 ( 30% ) of the collection , but only 1/60 ( 1 . 6% ) of the juveniles were RNA-positive ( Table 2 ) . It can be concluded that there was no evidence of vertical transmission of infection in R . aegyptiacus , but that juveniles are exposed to virus at a stage of their development possibly determined by factors such as waning maternal immunity or seasonal occurrence of infection in external hosts such as arthropods . Limited tests on arthropod parasites of bats in the present study were negative for evidence of Marburg virus infection ( data not shown ) , and the same was true for larger numbers of parasitic and cave-associated arthropods tested in the investigations in the DRC in 1999 [10] . It seems more likely that there is horizontal transmission of infection among susceptible bats , as was proposed for Hendra virus [16] and Nipah virus [17] . However , no Marburg virus RNA was detected in oral swabs taken from bats , including those with virus RNA-positive liver and spleen samples ( data not shown ) , suggesting that transmission via masticated fruit spats as suggested for Nipah virus , is an unlikely route for Marburg virus . Transmission via bat urine or feces would be another possible mechanism . It is notable that ebolavirus was found to be shed in the feces of experimentally infected fruit bats for up to 3 weeks [8] , but limited immunohistochemical analyses of formalin-fixed kidneys of our RT-PCR positive bats have thus far been negative , tentatively suggesting that transmission via urine may be less likely than through feces . However , it would be premature to rule out transmission though urine , feces or saliva given the limited number of bats tested to date , and the lesser sensitivity of immunohistochemical methods relative to RT-PCR . The determination of virus transmission mechanisms will be best addressed in the future through experimental infection of R . aegyptiacus bats . For ebolavirus , it has been suggested that outbreaks in nonhuman primates follow seasonal patterns which may reflect changes in diet or reproductive status of reservoir hosts , and that infection of the primates could be initiated through consumption of fruit contaminated with blood and placentas during parturition of infected bats [18] , [19] . Our data indicating the lack of evidence for vertical transmission of Marburg virus would suggest blood and placentas generated during parturition are unlikely to be source of virus infecting primates , at least for Marburg virus . Histopathological examination of liver and spleen samples of 30 R . aegyptiacus bats and one Hipposideros spp . bat which produced positive PCR results , and 49 bats which were uniformly negative in Q-RT-PCR plus NP and VP35 RT-PCR assays , revealed no lesions which could specifically or consistently be ascribed to Marburg virus infection . Viral antigens were detected by IHC in the livers of two bats which yielded Marburg virus isolates in culture ( bats 331 and 371 , Table 3 ) and were distributed predominantly in a perimembranous pattern around small , relatively isolated foci of hepatocytes . These foci were often associated with small accumulations of mononuclear inflammatory cells and highly localized hepatocyte necrosis ( Figures 1A–E ) . Rare Marburg virus antigens were observed in the spleen of only one bat , number 371 , and were localized to the cytoplasm of isolated mononuclear cells ( Figure 1F ) . This represents the first time that filovirus antigens have been visualized in tissues of naturally infected bats . From the sparse and highly focal nature of the infected sites , it can be surmised that the methods used to sample and test bats , including the Q-RT-PCR , are likely to produce underestimates of the prevalence of active infection . The paucity of hepatic lesions and viral antigens detected by IHC in wild-caught R . aegyptiacus contrasts markedly with the abundant and extensively distributed Marburg virus antigens observed in the livers of infected humans and non-human primates [20] , [21] . The histopathologic and immunohistochemical findings of Marburg virus infection in these naturally infected R . aegyptiacus are consistent with observations made for hemorrhagic fever viruses of the families Arenaviridae , Bunyaviridae , and Paramyxoviridae in their small-mammal reservoir hosts [22] , [23] , [24] , and lend additional support to the contention that R . aegyptiacus is a reservoir for Marburg virus . During the 2008 field trip a total of seven of 1 , 329 marked bats at the Kitaka mine were recaptured at a rate of about 1% of total nightly catches ( data not shown ) , and from these data it was calculated that approximately 112 , 000 R . aegyptiacus bats roosted in Kitaka mine . By extrapolation from the approximately 5% viral RNA-positive levels detected by Q-RT-PCR in the bats tested in 2007 and 2008 , it follows that there could be >5 , 000 infected bats within the colony at any one time , suggesting that there is a high risk of infection for humans who spend extended periods in close proximity to the bats . In fact , in December 2007 and again in July 2008 , an American and Dutch tourist acquired non-fatal and fatal Marburg virus infections respectively after encountering R . aegyptiacus bats in Python Cave in the Queen Elizabeth National Park , <30 miles from Kitaka mine [25] , [26] . The results of Bayesian analysis of the nucleotide differences among full-length virus genome sequences of the isolates from the two miners ( 01Uga2007 and 02Uga2007 ) , plus the five isolates from bats ( 44 , 188 , 331 , 371 and 982 , Table 3 ) , and 18 representative historical Marburg virus isolates , is shown in Figure 2A . Isolate 01Uga2007 falls into the prototypic clade containing the majority of known Marburg virus sequences . The second human isolate , 02Uga2007 , which differs by 21% ( nucleotide level ) from 01Uga2007 , is closely related to members of the highly distinct Ravn lineage , first isolated in 1987 from a patient ( RavKen1987 ) who ostensibly acquired infection in Kitum Cave , Kenya [5] . Thus , it is clear that the Kitaka mine outbreak represented two independent introductions of infection from the natural reservoir hosts into the human population . Two of the bat isolates group with the majority of historical Marburg virus sequences and are most closely related ( 99 . 3% identical ) to the sequence from miner A ( 01Uga2007 ) , while the other 3 bat isolates reside within the Ravn lineage ( RavKen1987 ) and are closely related ( 99 . 2–99 . 9% identical ) to the sequence from miner B ( 02Uga2007 ) . In order to extend the phylogenetic analysis to virus RNA-positive bats from which no isolates were obtained , concatenated partial NP and VP35 gene sequences determined for 14 bats during the present study , plus 2 equivalent sequences derived from the human isolates , and 48 sequences derived from data for historical Marburg virus isolates ( Genbank accession numbers in Table S1 ) , were subjected to Bayesian analysis ( Figure 2B ) . No sequences could be determined for a further 17 bats which were positive for viral RNA by Q-RT-PCR , possibly because the viral loads were too low for conventional NP and VP35 RT-PCR to detect . Nevertheless , it was clear that diverse Marburg virus lineages were circulating in the Kitaka mine bats , and that some were identical or near-identical to the human isolates across the genome fragments examined . Sequences from bats 291 and 772 were either identical or within one nucleotide , respectively , of isolate 01Uga2007 ( miner A ) , while sequences from bats 44 , 188 , 276 , 288 and 328 closely matched 02Uga2007 ( miner B ) . The identification of virus lineages circulating in bats within Kitaka mine was probably incomplete , but even these limited genetic data suggest recent common ancestry for closely matching genomes found in bats and humans and strongly implicate R . aegyptiacus as the primary source of human infection . The structure of the outbreak was strikingly similar to that seen in 1999 in Durba , DRC , as that outbreak also involved multiple introductions of virus from the natural reservoir , putatively bats , into the human population , plus the co-circulation of highly divergent Marburg viruses in a single geographic location [9] , [10] . The generation and perpetuation of such diverse genetic lineages of virus , with ≥21% nucleotide differences , imply the need for a long association of the virus with its reservoir host , plus the need for a large host population with constant recruitment of naïve individuals . The estimated population of 112 , 000 R . aegyptiacus bats in Kitaka mine could probably produce up to 100 , 000 offspring with two breeding seasons a year . Moreover the species is widely distributed in Africa , with many large colonies in proximity in East Africa alone , including the Kitum Cave complex on Mount Elgon , and numerous caves in western Uganda . It has been observed in South Africa that large proportions of the bats within R . aegyptiacus colonies migrate ≥300 miles to other colonies on a seasonal basis [27] . Hence the potential pool of vertebrate hosts for Marburg virus may extend to tens of millions of bats across a large geographic range . Although diverse Marburg virus lineages were found to co-circulate at single geographic locations in Kitaka mine in Uganda and Goroumbwa Mine in the DRC , it is noteworthy that very closely related lineages have also been found at widely separated geographic locations , in some instances over 2000 km apart . For example , Marburg virus sequences found in bats in Gabon are closely related to isolates from Zimbabwe , Uganda and DRC . Isolates of the Ravn lineage have been found in Kenya , DRC and Uganda . In fact , an isolation-by-distance analysis of the data presented here ( Mantel test ) found no correlation between genetic and geographic distances ( p>0 . 3 ) . The geospatial separation of the closely related Marburg virus lineages is most consistent with mobility of their natural host , a dynamic easily accomplished by the enormous meta-population of R . aegyptiacus present in Africa . Longitudinal studies of naturally infected R . aegyptiacus colonies would provide valuable insights into the dynamics of immune status , as well as the shedding , transmission and persistence of Marburg virus in bat populations , and help to determine if the proportions of infected individuals relative to age are periodic or stochastic . The studies should be supplemented by experimental infections to observe the dynamics of infection within individual bats . Given the detection of infectious ebolavirus in privileged sites , such as testes , up to three months after onset of symptoms in human infections [28] , careful examination of multiple tissues from infected bats is also warranted .
Blood samples collected during acute illness and submitted as diagnostic samples to the Centers for Disease Control and Prevention ( CDC ) , Atlanta , USA , were tested for Marburg virus antigen and IgG antibody by enzyme-linked immunoassay as described previously [29] , [30] . The samples were also tested for presence of Marburg virus nucleic acid by reverse transcriptase-polymerase chain reaction ( RT-PCR ) , and cultured for isolation of virus as described below . According to an institutionally reviewed IACUC protocol , bats were captured with mist nets or harp traps at the opening of the mine , euthanized with Isoflurane , and samples of liver , spleen and placenta ( where applicable ) collected by dissection , using safety precautions described previously [31] . Liver and spleen were selected for sampling based upon previous studies [10] , [11] , [12] and because these organs are affected in filovirus infections of primates . Aliquots of tissue were preserved in chaotrope ( Cellular Lysis Buffer , Applied Biosystems ) for analysis by RT-PCR , while replicate samples were frozen in liquid nitrogen for culture of virus , and fixed in formalin for histopathological examination . Blood was also taken from each bat for RT-PCR and antibody analyses as described below . Bats were identified morphometrically [32] , their measurements and breeding status recorded , and the carcasses preserved in 10% formalin for at least 1 week and later changed to 70% ethanol for long-term storage . To minimize the potential for cross-contamination between bat samples , all dissection instruments were used only once during each nightly necropsy session , and in between sessions , all instruments were soaked in 3% Lysol for ≥15 minutes followed by disinfection in 10% bleach for ≥15 minutes . To maximize the chances of isolating virus , large numbers of each of the two species of bat found in the mine , the fruit bat R . aegyptiacus and the insectivorous Hipposideros spp . bats , were sampled during the first field trip in August 2007 . Smaller numbers were sampled during the second field trip which was undertaken in May 2008 , during the putative breeding season of R . aegyptiacus bats in Uganda , mainly to seek evidence of continued circulation of virus and possible vertical transmission of infection . Opportunity was taken to collect oral swabs from the bats sampled in May to determine the likelihood of virus transmission through saliva or respiratory aerosols . A mark and recapture study was also conducted in May to estimate the size of the R . aegyptiacus population , and to possibly allow for later determination of foraging and migration distances of the bats . A total of 1 , 329 R . aegyptiacus bats were tagged with coded aluminum necklaces or leg bands over a period of two weeks , and recaptures which were recorded once the number of marked bats reached 1 , 000 , were used in the Jolly-Seber model for estimating the abundance of an open population [33] , [34] . Limited numbers of arthropod parasites of bats were collected and frozen , including 25 wingless flies ( Family Nycteribiidae ) found in the pelage of bats during dissection , and 100 adult and nymphal argasid ticks ( Carios faini ) taken from crevices in the rocks near bat roosting sites . Apart from dermestid beetles , spiders , crickets , moth flies and cockroaches , the only other fauna seen in the cave consisted of a target rat ( Stochomys longicaudatus ) and forest cobras ( Naja melanoleuca ) . Total RNA was extracted in one of two ways . 50 µ liquid samples ( blood and eluates of oral swabs ) were extracted using non-cellular lysis buffer ( Applied Biosystems ) [35] while RNA from tissue ( 100 mg ) were extracted with cellular lysis buffer ( Applied Biosystems ) [12] . RT-PCR based assays for the NP , VP35 and VP40 genes , were performed as described previously [9] , [12] , [36] , except that the VP40 quantitative RT-PCR assay ( Q-RT-PCR ) assay was modified to include two reporter-labeled probes 5′Fam-ATCCTAAACAGGC“T”TGTCTTCTCTGGGACTT-3′ and 5′Fam-ATCCTGAATAAGC“T”CGTCTTCTCTGGGACTT-3′ in addition to the forward primer 5′-GGACCACTGCTGGCCATATC-3′and reverse primer 5′-GAGAACATITCGGCAGGAAG-3′ . The quencher BHQ1 was placed internally in the probes at the “T” sites . All human and bat samples were screened by Q-RT-PCR , designed to detect RNA of all known lineages of Marburg virus , and bat samples found positive ( Ct<40 ) were re-analyzed by extracting RNA from frozen tissue using RNAeasy mini-kits ( Qiagen ) after overnight incubation at 4°C in lysis buffer . The extracts were subjected to the Q-RT-PCR and conventional RT-PCR based on the NP and VP35 genes . Tissues from 39 bats found negative in the initial Q-RT-PCR were also re-extracted and subjected to Q-RT-PCR and NP and VP35 gene RT-PCR . Nycteribid flies and argasid ticks were individually ground in cellular lysis buffer and extracted RNA tested by Q-RT-PCR . For human samples , 100 µl of blood was inoculated onto Vero E6 monolayers in 25 cm2 flasks and incubated for 14 days at 37°C/5% CO2 in MEM/2% fetal calf serum with a media change after day 7 . Cultures were monitored daily for CPE with cell scrapes at days 7 and 14 tested by IFA . For bat samples , 10% suspensions of freshly thawed ∼250 mg frozen tissue sections were homogenized on ice in viral transport medium ( HBSS/5% fetal calf serum ) with a plastic pestle and ∼250 mg sterile alundum ( Fisher cat# A634-3 ) in 15 ml conical tubes . The homogenate was clarified by low speed centrifugation and 100 µl of supernatant fluid was inoculated onto Vero E6 cell cultures in 25 cm2 flasks at 37°C/5% CO2 for 1 hr with gentle rocking followed by media replacement with MEM/2% fetal calf serum . Inoculated flasks were monitored daily for 14 days ( with media change after day 7 ) for the appearance of CPE and by IFA of cell scrapes on days 7 and 14 . Cultures positive by IFA for Marburg virus were additionally analyzed by RT-PCR ( see below ) . Sequencing of Marburg virus whole genomes and partial gene sequences ( NP and VP35 ) were performed as previously described [12] , [36] . Blood samples from bats were tested by enzyme-linked immunoassay for the presence of IgG antibody reactive with Marburg virus as described previously [29] , [30] but with the following modifications: 1 ) 96-well plates were coated with Marburg virus infected cell lysate ( diluted 1∶1000 final concentration ) generated from Marburg virus isolates # 188 ( Ravn lineage ) and #371 ( main lineage ) , 2 ) sera were initially diluted 1∶100 in 5% nonfat milk rehydrated in PBS-T containing normal Vero E6 cell slurry diluted 1∶25 and then further diluted 4-fold through 1∶6400 in PBS-T/5% nonfat milk , and 3 ) bound bat-specific IgG was detected using HRP-conjugated goat anti-bat IgG ( Bethyl-L cat# A140-118P ) diluted 1∶2000 . The mean and SD of the adjusted sum ODs from the entire collection ( both species ) were used to plot a frequency distribution and calculate a value greater than the mean+3 SD . Sera with repeatable adjusted sum ODs greater than this cutoff value ( 0 . 95 ) and whose titers were ≥1∶400 were considered positive . Genbank accession numbers are described in Table S1 . Phylogenetic analyses were performed separately on two sets of data: one comprising 25 whole genome sequences including those of 18 representative historical Marburg isolates , plus the 2 isolates obtained from miners and 5 isolates obtained from bats during the present investigations , and the second data set was comprised of 64 concatenated partial NP and VP35 gene sequences including 48 derived from historical Marburg isolates plus 2 derived from the isolates obtained from miners and 14 determined for PCR products obtained from bats during the present study . A representative sample of Ebola Zaire ( Genbank accession NC 002549 ) was used as an outgroup . Modeltest 3 . 730 [37] was used to examine 56 models of nucleotide substitution to determine the model most appropriate for the data . For whole genome analysis , the General Time Reversible model incorporating invariant sites and a gamma distribution ( GTR+I+G ) was selected using the Akaike Information Criterion ( AIC ) . Nucleotide frequencies were A = 0 . 326 , C = 0 . 195 , G = 0 . 185 , T = 0 . 294 , the proportion of invariant sites = 0 . 451 , and the gamma shape parameter = 7 . 244 . The Kimura 3-parameter model with unequal base frequencies and a proportion of invariant sites ( K81uf+I ) was selected for the concatenated NP-VP35 dataset . Nucleotide frequencies were A = 0 . 310 , C = 0 . 233 , G = 0 . 202 , T = 0 . 255 , and the proportion of invariant sites = 0 . 659 . Maximum likelihood analyses were subsequently performed in PAUP*4 . 0b10 [38] using the GTR+I+G or K81uf+I model parameters . In addition , Bayesian phylogenetic analyses were conducted for each of the datasets in MrBayes 3 . 2 [39] using the GTR+I+G model of nucleotide substitution . For each dataset , two simultaneous analyses , each with four Markov chains , were run for 10 , 000 , 000–40 , 000 , 000 generations , sampling every 100 generations . Prior to termination of the run , the AWTY program was used to assess convergence to ensure that the length of the analysis was sufficient [40] . Trees generated before the stabilization of the likelihood scores were discarded as burn-in , and the remaining trees were used to construct a consensus tree . Nodal support was assessed by posterior probability values ( ≥95 = statistical support ) . To determine if marburg virus infection caused lesions in infected bats , sections were cut from paraffin-embedded blocks prepared from formalin-fixed liver and spleen samples from 32 bats found positive by Q-RT-PCR , and examined in parallel with the tissues of 39 bats found negative in both the Q-RT-PCR and conventional RT-PCR . Hematoxylin and eosin ( H&E ) stained sections of the tissues were examined for lesions , and sections stained by an immunoalkaline phosphatase technique [41] with a polyclonal rabbit anti-Marburg virus antiserum diluted to 1/1000 . Samples were evaluated without prior knowledge of the PCR and virus culture results . | Marburg virus , similar to its close cousin Ebola virus , can cause large outbreaks of hemorrhagic fever ( HF ) in rural Africa with case fatalities approaching 90% . For decades , a long-standing enigma has been the identity of the natural reservoir of this deadly virus . In this report , we identify the cave-dwelling Egyptian fruit bat ( Rousettus aegyptiacus ) as a natural host of Marburg virus based on multiple lines of evidence which include , for the first time ever , the isolation of virus directly from wild-caught and apparently healthy bats . The species R . aegyptiacus is common throughout Africa with distribution into the eastern Mediterranean and Middle East . Our finding of active virus infection in approximately 5% of R . aegyptiacus bats and their population exceeding 100 , 000 in Kitaka cave in Uganda suggests there are likely over 5 , 000 Marburg virus–infected bats in this cave , which is only one of many such cave populations throughout Africa . Clearly , these bats could serve as a major source of virus with potential to initiate human epidemics , and the implications for public health are striking . Additionally , we found highly divergent ( 21% ) genome sequences among viruses circulating in these bat populations , a level of diversity that would result from a long-term association with a suitable reservoir host of large population size . | [
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] | [
"virology/emerging",
"viral",
"diseases",
"virology"
] | 2009 | Isolation of Genetically Diverse Marburg Viruses from Egyptian Fruit Bats |
The administration of anti-trypanosome nitroderivatives curtails Trypanosoma cruzi infection in Chagas disease patients , but does not prevent destructive lesions in the heart . This observation suggests that an effective treatment for the disease requires understanding its pathogenesis . To understand the origin of clinical manifestations of the heart disease we used a chicken model system in which infection can be initiated in the egg , but parasite persistence is precluded . T . cruzi inoculation into the air chamber of embryonated chicken eggs generated chicks that retained only the parasite mitochondrial kinetoplast DNA minicircle in their genome after eight days of gestation . Crossbreeding showed that minicircles were transferred vertically via the germ line to chicken progeny . Minicircle integration in coding regions was shown by targeted-primer thermal asymmetric interlaced PCR , and detected by direct genomic analysis . The kDNA-mutated chickens died with arrhythmias , shortness of breath , cyanosis and heart failure . These chickens with cardiomyopathy had rupture of the dystrophin and other genes that regulate cell growth and differentiation . Tissue pathology revealed inflammatory dilated cardiomegaly whereby immune system mononuclear cells lyse parasite-free target heart fibers . The heart cell destruction implicated a thymus-dependent , autoimmune; self-tissue rejection carried out by CD45+ , CD8γδ+ , and CD8α lymphocytes . These results suggest that genetic alterations resulting from kDNA integration in the host genome lead to autoimmune-mediated destruction of heart tissue in the absence of T . cruzi parasites .
Trypanosoma cruzi infection ( American Trypanosomiasis ) is an endemic ailment transmitted by hematophagous ( Reduviid:Triatominae ) bugs , by blood transfusion and transplacentally from the mother to offspring [1] . In pregnant women T . cruzi infections may lead to fetal complications , with desorption of the embryo , stillbirth , neonatal death , intrauterine growth retardation , or prematurity [2]–[7] . These infections are highly prevalent in rural areas of Latin America , where an estimated 18 million people harbor T . cruzi , and over 100 million are at risk of acquisition [8] . The migration of T . cruzi-infected patients from endemic areas has made Chagas disease cosmopolitan , now emerging in five continents as an important global health problem requiring specific training of personnel for diagnosis and delivery of medical assistance [9] . The acute T . cruzi infections are usually asymptomatic and go unrecognized , but high rates of morbidity and lethality are recorded in chronically infected cases [1] , [10] , [11] . Chagas disease is a multifaceted clinical condition encountered in approximately one third of the human population with T . cruzi infections; the disease attacks the heart in 94 . 5% of cases , and the esophagus and/or the colon ( mega syndromes ) in 5 . 5% of the chronically infected individuals . The hallmark of the disease is a destructive myocarditis [10] , which typically is lethal two to five years after presenting signs of impairment of blood circulation [11] . The administration of an anti-trypanosome nitroderivative to treat human T . cruzi-infections did not prevent destructive heart lesions and death [12] , [13] , thus an effective treatment for Chagas disease requires further knowledge about parasite-host relationships and its pathogenesis [1] . Two theories are proposed to explain the pathogenesis of Chagas disease: i ) Parasite persistence with rupture of parasitized cells and release of parasitic antigens that attracts inflammatory cells infiltrates [14] , [15]; and ii ) Autoimmune rejection of target cells by the immune system inflammatory effector cells [1] , [16] , [17] . The second hypothesis is difficult to test , because other mechanisms of tissue inflammation may coexist in the setting of an active infection [18] , [19] . On the one hand , the cryptic infections are sources of parasitic antigens and inflammation , or they persist for decades without causing the host significant damage ? On the other , a clear demonstration of the part autoimmunity plays on the development of Chagas heart disease is essential for the effective delivery of treatment . Upon entry of T . cruzi into the body , the infective trypomastigote form can be destroyed by the monocyte-macrophage system , but internalized parasites in non-phagocyte cells can replicate as amastigotes before returning to trypomastigotes that then emerge , invading any tissue or cell type . The T . cruzi genome measures 60 . 3 Mbp [20] , [21] , and its total DNA ranges from 125–280 fg/cell [22]–[24] . Those broad differences are explained by relative chromosome number and size due to insertions , duplications and deletions , or by the relative contents of haploid , diploid or aneuploid cells during the growth process [25] . T . cruzi has a unique mitochondrion with a large amount of extranuclear DNA ( kDNA ) that can reach 15% to 30% of total cellular DNA [26] , which differs from the nuclear component by buoyant density , base ratio , and degree of renaturation [27] . A kDNA network is composed of catenated rings with a few dozen maxicircles ( 20 to 40 kb ) and thousands of minicircles ( 1 . 4 kb ) . The maxicircles are structurally and functionally analogous to the mitochondrial DNA in higher eukaryotes , encoding rRNAs and subunits of the respiratory complexes [28] , [29] . Topologically , each T . cruzi minicircle has four average 240 bp hypervariable regions interspersed by 122 bp conserved regions each of which presents conserved cytosine/adenine-rich sequence blocks ( CArsbs ) [29]–[33] . It is through sequence microhomologies in the CArsbs that foreign DNA integration is thought to occur [34] . The minicircles encode guide RNAs ( gRNAs ) , which modify the maxicircle transcripts by extensive uridine insertion or deletion , in a process known as RNA editing . Information for this process is provided by small gRNA molecules encoded primarily on the kDNA minicircles . The unusual organization of kinetoplastid genes in directional gene clusters requires equally unorthodox mechanisms to generate functional eukaryotic mRNA [28 , 35 , and 36] . The sequence heterogeneity of the thousands of kDNA minicircles in each cell represents an additional layer of complexity , thus augmenting genetic diversity . Horizontal transfer of kDNA minicircle sequences into the genome of T . cruzi-infected macrophages and of chagasic rabbits and humans is documented [34] , [37]–[39] . T . cruzi minicircle sequences integrated mainly in retrotransposable elements present in chromosomes of rabbits and of people with T . cruzi infections . Subsequent recombination and hitchhiking propagate minicircle sequence insertions in coding regions , rupturing open reading frames or knocking out genes in the host genome [1] , [10] , [34] , [37]–[39] . In a broad sense , the demonstration of kDNA minicircle sequences integrated into the genome of mammalians could be challenged by the possibility of contamination with DNA residues of the T . cruzi life long infections in susceptible hosts . Therefore , to further document possible roles played by LkDT-induced genotype alteration in the proposed autoimmune pathogenesis of Chagas disease it was required the live infection to be omitted . This important requirement could be fulfilled in the crosskingdom chicken model system that would eradicate the T . cruzi infections . The chicken genome has a haploid content of 1 . 2×109 bp ( 20 , 000–23 , 000 genes ) divided among 39 chromosomes . Autosomes are classified into macrochromosomes 1 through 5 , intermediate chromosomes 6 through 10 , and microchromosomes 11 through 32 . The sex chromosomes are denominated Z and W , with homogametic males ( Z/Z ) and heterogametic females ( Z/W ) . Repetitive elements make up 10% of the chicken genome , compared with 40–50% in the genomes of most mammals . A relatively compact genome structure is the result of the limited accumulation of repetitive elements . Unlike other vertebrate genomes , active short interspersed nuclear elements ( SINEs ) are not found in the chicken genome . Most retroelements are found in G+C-rich regions and many of the chicken repeats-1 ( CR-1 ) flank multiple genes , but CR-1 elements may also accumulate within A+T rich satellite regions [40] , [41] . In this study we describe an experimental crosskingdom host model for parasite-free heart disease in chickens , which are refractory to T . cruzi infection [42] except during early embryonic life , prior to the development of their immune system [10] . Chicks hatched from T . cruzi-infected eggs retained minicircle sequences in the absence of parasite nuclear DNA ( nDNA ) . Moreover we document integration of kDNA into the DNA of somatic and germ line cells , from where they are vertically transmitted to subsequent progeny . kDNA mutations were detected mainly in coding regions on several chromosomes . Interestingly , kDNA-mutated chickens developed gross cardiomegaly with an inflammatory myocarditis similar to that of Chagas disease in man , in which parasite-free myofibers are destroyed by immune system effector cells , as well as heart failure .
White Ross chicken eggs were obtained from Asa Alimentos ( Recanto das Emas , Federal District , Brazil ) . Chicks and adult birds were housed in the Faculty Animal Facility at room temperature . Protocols for all animal studies were approved by the Institutional Ethical Committee in Animal Research in accordance with international guidelines . Trypomastigotes forms of T . cruzi Berenice and the β-galactosidase-expressing Tulahuen T . cruzi MHOM/CH/00 C4 were used [43] . Trypomastigote forms of T . cruzi were grown in murine muscle cell ( L6 ) cultivated in Dulbecco minimal essential medium with 10% FSB , 100 IU/ml penicillin , 100 µg/ml streptomycin , and 250 nM L-glutamin ( pH 7 . 2 ) , 5% CO2 at 37°C . Epimastigote forms were grown in liver-infusion tryptose axenic medium at 27°C . The parasite forms were harvested at exponential growth phase . In the test group , a 2-mm diameter hole pierced in the shell of 60 fertile eggs for injecting with 100 forms of T . cruzi trypomastigotes in 10 µL of culture medium into the air chamber of stage X embryos . In the control group , 36 mock chickens received 10 µL of culture medium alone . Holes were sealed by adhesive tape , and the T . cruzi-infected eggs as well mock and 12 uninfected control samples were incubated at 37 . 5°C and 65% humidity for 21 days . The viable embryos ( 86% ) initiated growth upon incubation , and after 21 days the chicks that hatched were kept in incubatory for 24 h and thereafter at 32°C for three weeks . The peripheral blood mononuclear cells and solid tissues from 48 kDNA-mutated and from 22 control and mock ( shells pierced but not T . cruzi or kDNA inoculated ) chickens were processed for DNA extraction . DNA was also extracted from semen collected from roosters , and from nonfertilized eggs ( <5 mm ) from hens hatched from fertile eggs inoculated with T . cruzi [44] . The mitochondrial kDNA was obtained from T . cruzi epimastigote forms as described elsewhere [45] . The primers used for PCR amplifications and the thermal conditions are shown in Table 1 . The probes used in Southern blot hybridizations were: 1 ) Wild-type kDNA ( ∼1 . 4 kb ) minicircle sequences purified from T . cruzi epimastigote forms; 2 ) kDNA minicircle fragments ( 362 bp ) obtained by NsiI digests of wild-type kDNA; and 3 ) nDNA repetitive sequence ( 188 bp ) obtained by amplification of the parasite DNA with the Tcz1/2 primers . The probes were purified from 1% agarose gels . Genomic DNAs from infected chicks and uninfected controls were templates for PCR with specific T . cruzi nDNA Tcz1/2 [46] and kDNA primers s35/s36 [47] . The standard PCR procedure consisted in using 100 ng template DNA , 0 . 4 µM of each pair of primers , 2 U Taq DNA polymerase , 0 . 2 mM dNTP and 1 . 5 mM MgCl2 in a 25 µL final volume . The sensitivity of Tcz1/2 primers was determined in a mix of 200 ng chicken DNA with serial dilutions of T . cruzi DNA ( from 1 ng to 1 fg ) and the standard procedure was carried out with same concentrations of reagents used in test experiments with chicken DNA alone . The temperature used was 95 °C for 5 min , 30 cycles of 30 secs at 95 °C/30 secs at 68 °C/1 min at 72 °C with 5 min final extension before refrigeration . The amplification products were analysed in 1 . 3% agarose gel , transferred to a positively-charged nylon membrane ( GE Life Sciences ) by the alkaline method for hybridization with specific probes labeled with [α-32P] dATP using Random Primer Labeling Kit ( Invitrogen , Carlsbad , CA ) . Southern hybridizations were performed with MboI and/or with EcoRI ( Invitrogen ) digests of DNA samples of body tissues from uninfected control chickens and from chickens hatched from eggs inoculated with virulent T . cruzi forms . The enzymes used made single cuts in minicircles . The digests of DNA from T . cruzi were subjected to electrophoresis in 0 . 8% agarose gel at 50 V overnight at 4°C . The gel transferred to positively charged nylon membrane was hybridized with radio labeled kDNA probe . The membrane was washed twice for 15 min at 65 °C with 2X SSC and 0 . 1% SDS , twice for 15 min at 65 °C each with 0 . 2X SSC and 0 . 1% SDS , and autoradiograph for variable periods of time . The identification of T . cruzi kDNA minicircle integrated into the chicken genome was first shown using a standard protocol for 5′-RACE [48] . The amplification products were cloned directly in pGEM T Easy vector . The clones confirmed by DNA hybridization with a radioactively labeled wild-type kDNA probe were sequenced commercially ( AY237306 , FN600577 ) . A modification of the TAIL-PCR technique was used [34] , [49] , which combined kDNA primers with primer sets obtained after alignment of chimera sequence AY237306 within the loci NW_001471687 . 1 at the G . gallus genome . In the first round of amplifications , each reaction included 200 ng template DNA , 2 . 5 mM MgCl2 , 0 . 4 µM of kDNA primers ( S34 or S67 ) , 0 . 2 mM dNTPs , 2 . 5 U Taq Platinum ( Invitrogen , Carlsbad , CA ) . The kDNA primers were used in combination with 0 . 04 µM of Gg primers ( Gg1 to Gg6 , Table 1 ) , separately . The targeting primers annealing temperatures ranged from 57 . 9 to 60 . 1 °C for kDNA primers , and from 59 . 9 to 65 . 6 °C for CR-1 primer sets ( Table 1 ) . These temperatures are higher than those ( ∼45 °C ) required for the arbitrary degenerated primers used in the TAIL-PCR [49] . The temperature and cycles used ( MyCycle Termocycler , Bio-Rad Laboratories , Hercules , CA ) are described in a previous paper ( 34 ) . In the second round of amplifications , PCR products were diluted 1∶40 ( v/v ) in water . kDNA primers S35 and S35 antisense were substituted for the nested ones , along with the same Gg primers . In the third step , PCR products of tpTAIL-PCR 2 were diluted 1∶10 ( v/v ) in water and the Gg primers were combined in the reaction with S67 antisense or S36 , separately . PCR products of the last amplification that hybridize with kDNA probe were cloned directly in pGEM T easy vector ( Promega , Madison , WI ) . Clones selected by hybridization with kDNA probe were sequenced commercially . The validation of the tpTAIL-PCR was determined in a mix of 300 pg of kDNA from T . cruzi with 200 ng of DNA from control birds never exposed to kDNA . The temperature and amplification cycles were the same used for the test birds' DNA . Growth and development of chickens hatched from T . cruzi infected eggs and of healthy controls hatched from non-infected eggs were monitored daily for mortality and weekly for disease manifestations . Clinical abnormalities in those chickens were detected by inspection and by disclosure of arrhythmias and of increasing heart size by electrocardiograph ( ECG ) recordings . A one-channel model apparatus was used for ECG recordings with standard 1 mV/cm and speed of 25 mm/sec . The electrodes were placed under the wing pits and on the back of the legs after removal of feathers and skin cleansing with the chicken in supine position . Chickens were submitted monthly to ECG recordings of frontal leads AVR , AVL and AVF , and assessment of deviation of mean electrical axis to the left , which is suggestive of heart enlargement , were obtained . The ECG recordings allowed evaluation of mean electrical axes , heart rates and arrhythmias . These experiments included equal number of control chickens for comparison . Heart and body weight indexes were obtained after natural deaths of kDNA-mutated chickens . For each experimental case , a control ( kDNA- the negative ) chicken of the same age and gender was sacrificed , and the heart weight ( g ) /body weight ( kg ) indexes were obtained . Tissues removed from the heart , esophagus , intestines , skeletal muscle , lungs , liver , and kidneys were fixed in buffered 10% formalin ( pH 7 . 4 ) , embedded in paraffin and cut to 4 µm thick sections for histological analyses after Hematoxylin-Eosin ( HE ) staining . Tissues that were harvested from embryos and from chicks at set times were bisected so that half could be fixed in 0 . 02% glutaraldehyde prepared in phosphate buffered saline ( pH 7 . 2 ) and stained with X-Gal ( 43 ) . X-Gal-stained tissues were then fixed in paraformaldehyde . Paraffin embedded tissues sections were mounted by standard methods for microscopic examination . Sections showing blue cells were subjected to incubation with a human Chagas diseased antiserum with specific anti-T . cruzi antibody 1∶1024 [12] and immunofluorescent staining with a fluorescein-conjugated rabbit anti-human IgG for colocalizing embryo cells harboring T . cruzi . Tissue sections of heart from kDNA-positive and from control kDNA-negative chickens were separated for phenotype immune effectors cells . The slides embedded in paraffin were placed at 65°C for 30 min to melt wax previous to submission to four baths in 100% to 70% xylene and then in absolute ethanol PBS for 5 min each . The slides rinsed in distilled water were air dried treated with the following antibodies: 1 ) Mouse anti-chicken Bu-1 ( Bu-1a and Bu-1b alleles , Mr 70–75 kDa ) Mab AV20 recognizing monomorphic determinant on the B cell antigens of inbred chickens . 2 ) Mouse anti-chicken CD45 , Ig isotype IgM1κ specific to chicken thymus lineage cells ( Mr 190 to 215-KDa variant ) . 3 ) Mouse anti-chicken TCRγδ ( Mr 90-kDa heterodimer ) Mab specific to thymus dependent CD8+γδ T cells . 4 ) Mouse anti-chicken Mab CT-8 specific to chicken α chain ( Mr 34 kDa ) recognizing the CD8 cells in thymocytes , spleen and peripheral blood . 5 ) Mouse anti-chicken KuL01 exclusively recognizing monocytes/macrophages of the phagocyte system . The monoclonal antibodies were fluorescein- or R-phycoerythrin-conjugate obtained from SouthernBiotech , Birmingham , AL . After incubation with specific anti-phenotype antibody the slide was washed three times with O . 1 M PBS , pH 7 . 4 , 5 min each . At the end the slide was washed trice with PBS and assembled with buffered glycerin for exam under a fluorescent light microscope with emission filter of wavelength 567 and 502 nm , respectively , to detect red and green fluorescence-labeled cells . The chicken genome database ( http://www . ncbi . nlm . nih . gov/genome/seq/BlastGen/BlastGen . cgi ? taxid=9031 ) was used for BLASTn sequence analyses . CLUSTALW alignments were performed and statistical significance ( p<0 . 001 ) was determined for scores ( e-values ) recorded . The GIRI repeat masking algorithm CENSOR ( http://girinst . org/censor/index . php ) was employed for localization of different classes of repeats in chimeric sequences . The Kinetoplastid Insertion and Deletion Sequence Search Tool ( KISS ) were employed to identify potential gRNAs in the kDNA sequences [50] . The KISS database comprises Trypanosoma brucei and Leishmania tarentolae minicircle and maxicircle as well as a work bench for RNA editing analysis in kinetoplastids [50] , [51] with the aid of WU-Blastn-modified-matrix [52] . Also , T . cruzi sequences ( http://www . biomedcentral . com/content/supplementary/1471-2164-8-133-s1 . fas ) were used to search-in gRNAs in the kDNA-host DNA chimera sequences . Student's t test was used to detect significant differences between deviations of electric axes in the ECG tracings in kDNA-positive and in control healthy chickens , and between heart/body weight indexes obtained in the experimental and control groups . The Kolmorov-Smirnov test was used to detect mortality ratios significant differences between groups of chickens hatched from T . cruzi inoculated eggs and from mock control .
To separate possible roles played by parasite persistence and autoimmunity in the pathogenesis of the inflammatory Chagas heart disease seen in T . cruzi-infected mammals , active infection coexisting with any mechanism of tissue inflammation had to be eliminated [19] . The variable of parasite persistence was removed by using a ‘clean’ host model [10 , 42 , and 53] . Thus , we used chickens refractory to T . cruzi infections and performed invasion studies early in their embryonic life . We inoculated 100 T . cruzi trypomastigotes into the air chamber of 60 stages X chicken eggs prior to incubation . The infection was established in the embryo cells ( Figure S1A to E ) , and embryonic tissues collected on the second , fourth , and eighth days postinfection produced nDNA and kDNA amplifications; interestingly , tissue collected on the tenth , 12th , 18th and 20th days yielded amplification products only for kDNA ( Figure 1A ) . To avoid the possibility of very low level of parasitism remaining in the embryo , we used a PCR assay with Tcz1/2 primers , and the amplicons obtained were subjected to hybridization with the radio labeled 188-bp nDNA probe to increase sensitivity of the technique [54] , [55] . This assay can detect 10 fg of T . cruzi DNA ( Figure 1B ) , which is 24-fold below the amount found in the diploid parasite [22]–[24] . Among 48 T . cruzi-infected eggs that sustained embryo development , 28 ( 58 . 8% ) hatched healthy chicks and 20 ( 41 . 2% ) resulted in embryo liquefaction during the first week of growth ( 45% ) , and in deaths either at hatching ( 31% ) or within one week after hatching ( 24% ) . The histopathology of whole body tissues from chicks that were found dead at hatching revealed severe inflammatory infiltrates and lyses of self tissues in the liver , kidneys , intestines , skin , lung , skeletal muscles and heart ( not shown ) . Four chicks showing retarded growth and respiratory distress died during the first week of life . Those chicks had heart failure with cardiomegaly and inflammatory infiltrates with destruction of nonparasitized heart cells ( Figure 2 ) . None of these findings were present in 36 mock control eggs inoculated with 10 µl of culture medium in the air chamber , neither in 12 non-infected control eggs . In the control groups were found dead embryos ( 15 . 4% ) in the first week of growth . The mortality ratios differences between groups of T . cruzi inoculated eggs and controls were highly significant ( p<0 . 005 ) . Although the refractory nature of birds to T . cruzi is well known [10] , [42] , [53] , we documented the absence of the active infection in each of 12 parental kDNA-positive ( FO ) chicks showing negative blood culture in axenic liver infusion-tryptose medium and negative blood inoculations in weaning mice . In the positive control tests , 50 µl aliquots from suspensions of blended tissues ( 50 mg/1 ml PBS , pH 7 . 4 ) from five day-old embryos , which had received T . cruzi in the air chamber , were inoculated in the peritoneal cavity of weaning mice and in axenic culture medium and yielded , respectively , blood trypomastigotes and epimastigote forms . To further dissociate the kDNA retention event from the presence of active infection , we inoculated naked minicircle sequences in the air chamber of eleven embryonated chicken eggs . Absence of kDNA PCR products from these embryos tested weekly prior to hatching indicated that transfer of minicircle sequences to the chicken genome required a living T . cruzi infection in first week of embryonic growth . With this respect , further important information yet could be obtained in the crosskingdom model system , aiming at the documentation of the kDNA integration in the chicken genome , which were considered deemed necessary to clarify the pathogenesis of the parasite-free cardiomyopathy in chicks hatched from the T . cruzi-infected embryonated eggs . Having shown that the live T . cruzi infections were eradicated by the chick innate immune response after 10 days of embryonic development we fathomed the parasite mitochondrial kDNA alone that was shown in Figure 1A . The DNA templates from peripheral blood cells of F0 , F1 , F2 and F3 chickens ( Table S1 ) were subjected to direct PCR amplifications , cloning and sequencing . A total of 25 kDNA minicircle sequences were obtained with 404±150 nts comprising conserved and variable minicircle sequence fragments ( EMBL accession numbers: FR719694 to FR719718 ) . In view or the reported hypervariability of the kDNA minicircles [30] , [31] it was interesting to observe that 64% of these sequences retained in the chicken genome showed high similarity ( e-values 5e-45 to zero ) with those resulting from our investigations in humans [34] . This finding suggested that some classes of kDNA minicircles from T . cruzi may be preferentially retained in the vertebrate host , and that the minicircle sequences could be possibly integrated in the chicken genome [34] , [37]–[39] . The documentation of parasite-free inflammatory cardiomyopathy ( Figure 2 ) in chicks hatched from eggs that had received the T . cruzi inoculations incited us to continue the investigation about kDNA integrations and resulting genotype alterations in the chicken model system . DNA templates were obtained from twelve chickens hatched from infected embryos , which showed T . cruzi-kDNA amplicons in the absence of parasite nDNA ( Figure 3A ) . In the T . cruzi-free control experiment 12 embryonated chicken eggs and 36 mocks were subjected to PCR , and neither nDNA nor kDNA was detected . Therefore , it was clear that kDNA alone was transferred to the chick genome during the transient T . cruzi embryonic infections . The horizontal transfer of kDNA minicircle sequences to parental ( F0 ) chicken genomes could have physiopathological consequences that would be valuable in a model to study the pathogenesis of chagasic heart disease . Therefore , F0 birds were raised for crossbreeding . The F1 , F2 , and F3 progeny tested positive for the kDNA in lack of nDNA , indicating that the T . cruzi infection occurring early in the embryonic developmental process generated mature chicken with kDNA integrated into gonadal tissue ( Figure 3B ) . Sperm and ova from birds hatched from T . cruzi-infected eggs was examined because it was fundamental to confirm vertical transfer of minicircle sequences to progeny via the germ line . DNA templates of germ line cells from roosters and hens yielded PCR amplicons with kDNA s35/s36 primers but lacked nDNA amplification with the Tcz1/2 primers ( Figure 3C ) . Crossings of kDNA-mutated F0 birds generated F1 , F2 and F3 progeny and each sibling showed amplicons of minicircle alone . A pedigree depicting LkDT into parentals and VkDT into chicken's progeny is shown in Figure S2 . In control experiments template DNAs were subjected to PCR , and neither nDNA nor kDNA was detected . Southern blot analyses of EcoRI and of MboI digests of DNA from body tissues ( blood mononuclear cells , heart , skeletal muscle , liver and kidney ) of parental F0 , and offspring F1 and F2 progeny revealed various size bands with a kDNA-specific probe ( Figure S3A and B ) . The various positions occupied by the kDNA bands in Southern blots revealed that minicircle sequences were integrated in the parental and offspring chicken genomes . Thus , chickens with kDNA integrated into their germ line and somatic cells in the absence of the infection were generated . The detection of kDNA signals on fragments of distinct sizes from unintegrated minicircles in the heart DNA of chickens combined with the absence of T . cruzi nDNA attests to the success of the integration event and of the subsequent eradication of the infection . The difficulty in demonstrating randomly contemporaneous eukaryotic interspecies DNA transfer may be explained partially by the inaccessibility of those events to an effective methodological approach . We obtained by chance a chimeric kDNA-chicken DNA sequence ( AY237306 ) , which was amplified by the 5′-RACE technique . This model sequence was used to construct primer sets Gg1 to Gg6 ( Table 1 ) annealing upstream and downstream to a minicircle integration event into the locus NW_001471687 . 1 . The substitution of traditional PCR degenerate primers by host DNA-specific primer sets Gg1 to Gg6 eliminated the main difficulty and permitted demonstration of the junctions of kDNA-host DNA chimeras , employing a targeted-primer thermal asymmetric interlaced-PCR ( tpTAIL-PCR ) . A scheme with the strategy used to amplify the kDNA integration event in the G . gallus genome is shown in Figure 4 . The description of the modified tpTAIL-PCR is given in the Methods section , and a detailed flowchart with primer set combinations used is shown in Figure S4A to C . The tpTAIL-PCR was then employed to amplify minicircle-host DNA junction sequences from our chickens . The amplicons that tested positive with a radioactive kDNA probe were cloned and sequenced ( FN598971 to FN590000 , FN599618 , FN600557 , and FR681733 ) . These results are shown in Table S1 . In control experiments the tpTAIL-PCR products did not test positive with the specific kDNA probe . Validation experiments consisted of tpTAIL-PCR amplifications of a mix of T . cruzi kDNA with control chicken DNA ( Figure S4A to C ) . Twenty-three amplicons that tested positive with the wild-type kDNA probe showed only kDNA sequences with no host contribution . Chimeric sequences with minicircle-host DNA junctions were obtained from chickens testing positive by PCR with the minicircle-specific s35/s36 primers . Thirty-four chimeras ( total F0 , 8; F1 , 17; F2 , 7; and , F3 , 2 ) with average 555±153 nts ( kDNA 296±78 nts and host DNA 281±148 nts ) were documented in 14 chromosomes . E-values for each of the chimeras were statistically significant ( p<0 . 001; kDNA , 1e−06 to 2e−150; host DNA , 1e−53 to 0 ) . Three of these chimeras were obtained by using chicken repeat-1 ( CR-1 ) specific primers ( FN598975 , FN598994 , and FN598998 ) . The minicircles spread to various loci of chicken chromosomes are shown in Table S1 . Overall , 64 . 6% of kDNA-mutations entered in the macrochromosomes ( 1 , 38%; 2 , 18%; 3 18%; 4 , 23%; and , 5 , 3% ) , 17 . 7% in the intermediate , and 17 . 7% in the microchromosomes of the chicken genome . A map showing the heredity of the kDNA integrations in those chromosomes loci is depicted in Figure 5 . BLASTn analyses revealed that Gg1 to Gg6 primer sets aligned to multiple loci in 18 chicken chromosomes with the following frequencies: Gg1 , 19; Gg2 , 39; Gg3 , 28; Gg4 , 19; Gg5 , 3; and , Gg6 , 23 . Thus the tpTAIL-PCR achieved reproducible random amplification of kDNA-host DNA integrations in a variety of chromosomes . The alignment of chimeric sequences from F0 ( AY237306 ) and F1 ( FN600557 ) chickens documented vertical transfer of the kDNA mutation in non-coding locus NW_001471687 . 1 of chromosome 4 ( Figure S5A ) . In addition , kDNA mutations in the dystrophin gene locus NW_001471534 . 1 at chromosome 1 from F1 ( FN598991 ) and F2 ( FR681733 ) progeny showed perfect alignments ( Figure S5B ) . The heritability of the kDNA mutations was documented; the fixation of the mutations in the chicken model can be further spanned through obtaining host's specific primer sets anneal to the kDNA-mutated loci and the full sequencing of the targeted chromosome . Due to the CA-rich microhomologies in chimeric sequences detected in the genomes of Chagas disease patients [34]; we conducted a bioinformatic search for similar features in the kDNA-mutated chick sequences , revealing CArsb repeats between kDNA-host DNA junctions . Sequence analyses of CArsb repeats intermediate to the kDNA minicircle integration into the chicken genome revealed consensus I – ACACCAACCCCAATCGAACCCAAACCAAA , present in seventeen clones , and consensus II – TAYACCMACCCCTCCCAAAACC , found in the flanking region of eleven chimeras . CArsb microhomologies in chimeric sequences secured from kDNA-mutated chickens are depicted in Figure S6A and B . These repeats found coding regions in the chicken genome concentrated ( 52 . 4% ) in chromosomes 4 ( 13 . 5% ) , 3 ( 5% ) , 2 ( 20 . 4% ) and 1 ( 13 . 5% ) . Additionally , CArsbs were also present in long terminal repeat Hitchcock transposons ( FN598974 and 599618 ) , and in CR-1 non-LTR retrotransposons ( FN598975 , 598994 , and 598998 ) , and L1-24xT ( FN598995 ) . The consensus microhomologies in coding regions , chicken LTRs and non-LTRs , and minicircles implied that microhomology-mediated end-joining [56] was mediating integration of exogenous sequence into host chromosomes . The data shown in Table S1 were obtained from DNA templates of F0 , F1 , F2 and F3 chickens with inflammatory cardiomyopathy . A range of minicircle integration events promoting rupture of ORFs of those chickens is shown in Table S2 . Twenty kDNA integrations ( ∼60% ) were detected in coding regions of various chromosomes . These integrations were seen frequently in genes encoding protein kinases ( 20% ) playing important roles in cell division and differentiation , in the dystrophin gene ( 10% ) , which encodes a high molecular weight protein connecting the cytoskeleton to muscle and nervous cell membrane , and in growth factors ( 10% ) , transcription factors ( 5% ) , and immune factors ( 5% ) . Other important genes encoding GTPase , adenylate cyclase , and adhesion molecules related to macrophage recruitment and blood vessel maturation were disrupted . In one case a gene expressed in blood mononuclear cells from patients with systemic lupus erythematosus ( NW_001471554 . 1 ) was ruptured by kDNA integration ( FN598994 ) . A minimum of 12 mutations were observed in one chicken with severe inflammatory cardiomyopathy . These mutations may skew coding regions of chromosomes with subsequent functional alterations such as cell cycle regulation , clonal proliferation of immune system cells , and tissue injury [57]–[61] . Interestingly , documented clinic and pathologic manifestations were clearly associated with the kDNA-mutations in the locus of the dystrophin gene ( Figure S5 ) in two chickens with muscle weakness , cardiomegaly and heart failure . The chimerical sequences that were obtained from F0 , F1 , F2 , and F3 kDNA-mutated chickens ( Table S3 ) presented ORFS with the potential for translation of hybrid proteins . A total of 13 ORFS ( 43 . 3% ) comprised kDNA alone , and 17 ORFs ( 56 . 7% ) were chimeras formed by kDNA-host DNA . A majority of the ORFs ( 77% ) encoded proteins without significant similarity , but 20% of the ORFs translated hypothetical proteins with significant similarities ( e-values ranging from 2e-06 to 2e-22 ) with other proteins . Furthermore , one ORF encoding the reverse transcriptase from G . gallus ( locus AA49027 . 1 ) showed highly significant scores ( 4e-29 ) . In the model system used each ORF encoding putative neo-antigen was generated after the invasive T . cruzi replicated in the embryonic tissues prior to the development of the chick immune system in the first week of growth . Therefore , a functional role for ORF's encoded neo-antigen in the pathogenesis of Chagas disease did not hold promise in the absence of humoral autoimmune factors in the actively tolerized kDNA-mutated chicken [62]–[66] . The chimerical sequences showing kDNA integrated into the host chicken chromosomes presented hypervariable minicircle regions ( Table S1 ) with the potential for gRNA transcription [29]–[31] , [33] , [35] , [36] . The analysis of these hypervariable sequences determined significant similarities with those edited maxicircle gene sequences in KISS database , using the WU-Blastn-modified-matrix [52] . This approach allowed the G-U base pairing and retrieval of sequences with highly significant alignments . In total the approach revealed putative gRNAs in six out of the 34 chimeras kDNA-host DNA ( Table 2 ) . The sequences showing best alignment scores ( e-values 7 . 9e- 3 to 9 . 3e-06 ) showed cognate gRNAs adequately positioned in the hypervariable region of the minicircles ( Figure 6 ) . Consistently , the gRNAs ( 54±6 nts ) were located 56±5 bp from the CArsb-I . Furthermore , the predicted aminoacid similarities of 96 . 1 , 89 . 4 and 95 . 2% , respectively , for the NADH dehydrogenase subunit 7 ( NAD7 ) , ATPase 6 , and ND8 edited T . brucei and T . cruzi matched genes held high confidence to the identification of gRNAs in the integrated kDNA minicircles . The functional consequence of the parasite-derived gRNA editing minicircles in the vertebrate host is presently unknown . We inspected the kDNA-mutated and as well control chickens daily for mortality and weekly for clinic manifestations of disease . Often , the kDNA-mutated chickens showed signs of shortness of breath and impaired oxygenation of blood that evolved to severe cyanosis ( Figure 7A ) . The electrocardiograms recorded at three and six months of age ( Figure 7B ) in 12 F0 kDNA-positive birds and in 22 control chickens never exposed to T . cruzi showed that controls retained the electric axis at +75° and test birds changed axis positions to the left from +80 to –115° over time . The heart/body weight indexes from kDNA-positive F2 , F1 and F0 birds ranged , respectively , from 6±2 , to 6 . 7±2 , and to 12±5 , whereas the control group index was maintained a constant 4 . 2±2 ( Figure 7C ) . The differences among high heart indexes from F0 and from F1 kDNA-mutated chickens are statistically significant from the control low indexes ( p<0 . 05 ) . Survival lengths for the F0 and F1 kDNA-positive birds were shorter for F0 ( 12±4 months ) and F1 ( 13±2 months ) than those in the control group ( 19±5 months ) , and these differences were statistically significant ( p<0 . 05 ) . Cardiomegaly was documented in 65% of the kDNA-mutated adult birds , and absent in control animals free of minicircle sequences . In the case of F1 hen 9 ( Figure 7D ) the heart weight was over three times that of a control bird of same gender and age ( Figure 7E ) . Pleural and peritoneal effusions were collected in kDNA-positive birds with cardiomegaly and heart failure . The microscopic examinations of sections from the myocardium showed severe infiltrates of immune system effector lymphocytes and target cell lyses ( Figure 7F ) . This destruction of parasite-free target fiber by effector cells was typical , characterizing a minimal rejection unity in the hearts of kDNA-mutated chickens ( red circle ) . These microscopic features were absent from control chicken hearts ( Figure 7G ) . Furthermore , the coalescence of several rejection units resulted in diffuse myocarditis with massive destruction of the myocardium in chickens showing cardiomegaly . The intracardiac parasympathetic ganglion also showed mononuclear cell infiltrates and destruction of neurons ( Figure H ) . These pathologic features were neither encountered in intracardiac ganglia nor in myocardial sections from controls ( Figure 7I ) . The phenotype of immune system mononuclear cell infiltrates in sections of myocardium from kDNA-positive birds revealed a lack of Bu-1b treated B-cells associated with humoral immune responses ( Figure 7J ) . By contrast , sections of myocardium of kDNA-positive birds treated with anti-CD45 , anti-CD8γδ , or anti-CD8α showed specific staining of immune lymphocytes that carry out lysis of target heart cells ( Figure 7K , L and M ) . Treatment of those sections with specific antibodies revealed that some cells in the myocardium infiltrate bore the macrophage phenotype ( Figure 7N ) . In control experiments , sections from myocardium of control birds ( white-frame inserts ) showed neither markers of immune system cells nor tissue destruction . A possible role played by Th17 and Treg immune responses [67]–[71] in the destructive myocardial lesions requires investigations in the chicken model . Actually , the typical inflammatory type autoimmune myocarditis depicted in F0 and F1 chickens is also observed in F2 progeny , albeit to a much lesser frequency . A F2 chicken that showed cardiomegaly and succumbed to heart failure ( Figure S7 ) had the kDNA mutation in an exon of the dystrophin gene ( FR681733 ) . The inflammatory cardiomyopathy with lymphocyte rejection of target heart cells , typical of the autoimmune Chagas-like disease in the kDNA-mutated chicken model system , was attenuated in the F3 generation , which reached the adult life two years after hatching without clinical signs of a heart disease . Accordingly , the kDNA mutations were ranked in four levels: a ) High letality and early embryonic death; b ) Age group specific heart disease; c ) Neutral in lack of disease manifestation; d ) Possible beneficial , yet difficult to demonstrate . In this regard , attenuation of a kDNA mutation was defined by the decreasing levels of manifestations encountered in the chicken model system .
To separate the roles that parasite persistence and autoimmune rejection of target tissues play in the pathogenesis of the Chagas heart disease , implementation of an animal model that does not retain cryptic T . cruzi infections was essential [10] . In this respect , the mature chicken immune system is considered a tight biological barrier against T . cruzi . In this study we describe a G . gallus model that fulfills the criterion: T . cruzi infection is eradicated by the innate immunity present in the chicken embryo upon development of its immune system by the end of the first week of growth [10] . Here we demonstrate that chicks hatching from T . cruzi-inoculated eggs eliminate the live infection , lacking the parasite nDNA . Additionally , these chicks retain T . cruzi minicircle sequences in their genome , and these mutations are transferred to their progeny . The kDNA mutations integrated in coding regions of multiple chromosomes . The integrations ruptured open reading frames for transcription and immune system factors , phosphatase ( GTPase ) , adenylate cyclase and phosphorylases ( PKC , NF-Kappa B activator , PI-3K ) associated with cell physiology , growth , and differentiation [57]–[59] . Severe myocarditis due to rejection of target heart fibers by effector cytotoxic lymphocytes is seen in the F0 and F1 of the kDNA-mutated chickens , showing an inflammatory cardiomyopathy similar to that seen in Chagas disease . Interestingly , heart failure and skeletal muscle weakness were directly associated with the kDNA mutations and rupture of the dystrophin gene in chromosome 1 of adult chickens [72] , [73] . Moreover , the contribution of various mutations present at other loci in the genomes should be emphasized , because those chickens with kDNA integrations spread throughout their chromosomes also presented the self-tissue destructive pathology . Cardiomegaly and heart failure recorded for F0 and F1 kDNA-positive birds consistently attenuate in F2 and F3 progeny . Thus kDNA-integrations in some chromosome coding regions , generating skewing , instability , and clonality [60] , [61] , [74] , may undergo long-range intragenomic signaling interactions [75] , so as to achieve physiological balance over forthcoming generations of descendents; in our experimental system , however , the absence of active T . cruzi infection is clear . Experimental T . cruzi inoculation of the chicken embryo highlights the crosskingdom exclusion of infection that prevents evolutionary consequences resulting from the lateral transfer of parasite DNA to the bird genome . We document these conditions to confirm that only a narrow window is open for the infection to become established within the first week of a chicken embryonic life . In the absence of a mature immune system barrier , early intracellular multiplication of T . cruzi in embryo stem cells is possible . Inoculation was performed at the epiblast stage of chick development at which all embryonic cells are susceptible to T . cruzi invasion , and the kDNA can integrate in stem cells that differentiate both somatic and genital crest precursors of germ line . If this phenomenon were possible in nature it would create the opportunity for increasing genetic diversity and evolution of the species undergoing continuous change on a grand scale over time [34] . In this regard , four categories of functional kDNA mutations are described in this study: The high letality mutations that generate abortions , congenital inflammatory cardiomyopathy , and early death , in which the genotype modifications by means of DNA transfer result in pathology incompatible with life ( negative selection ) [10] . Age group specific mutations may be attenuated in a majority of chickens that succumbed to the Chagas-like inflammatory cardiomyopathy late in adult life . Neutral kDNA-mutations are probably present in 35% of the chickens not compromised by heart disease; these neutral mutations may contribute to genome growth and positive selection . Theoretically , beneficial mutations may exist [76] , but they could not be identified in three generations of kDNA mutated chickens . The autoimmunity in Chagas disease was proposed to explain about a preformed capacity of immune lymphocytes to carry out an accelerated destruction of non-parasitized target heart cells within few hours of incubation [16] , and , thereafter , it was suggested that existing cross-reactive antigens in target tissues would call in the T . cruzi-sensitized lymphocyte cytotoxicity [77]–[79] . However , the attempts to reproduce the myocarditis by immunization of laboratory animals with parasite recombinant antigens resulted in small infiltrates of mononuclear cells in absence of clinical symptons and of gross lesions [80]–[83] . The molecular mimicry mechanism was suggested to explain the autoimmunity , whereby cross-reaction of parasite antigen-immune effector cell against self-antigen on target cell , sharing putative similar amino acid motifs or three dimensional epitopes , was required to trigger off self-tissue rejection [84]–[92] . Accordingly , mimicring immunogenic cryptic self peptides may become accessible to auto-reactive T-lymphocytes that escape from the host's central and peripheral tolerance mechanisms [93] , [94] . In this regard , molecular mimicry between cardiac myosin heavy chain ( residues 1442–1447 AAALDK ) and T . cruzi protein B13 ( residues AAAGDK ) could generate autoimmunity [85]–[87] , but it was shown that anti-myosin autoimmune factors was not essential for cardiac damage [93]–[95] . So far , gross and microscopic pathology , and clinic manifestations of Chagas disease have not been obtained yet , by traditional immunizations with wild or recombinant T . cruzi antigens and , therefore , the primary cause of autoimmunity in Chagas disease was not explained . In this study , we suggest that the pathogenesis of Chagas disease is genetically driven . Herein , kDNA-mutated adult chickens are shown to develop gross cardiomegaly in association with clinic manifestations similar to those described for the human disease [10 , 12 , and 96] . The lethal cardiomyopathy in the parasite-free chicken model system in which the destruction of heart cells by lymphocytes is documented is used to validate the autoimmune pathogenesis of human Chagas disease . These phenomena were never seen in mock or control chickens . Interestingly , the chicks that die after hatching show cardiomegaly and myocarditis , with heart cell destruction by lymphocytes similar to that described for congenital human Chagas disease . Moreover , the inflammatory cardiomyopathy that is the hallmark of human disease was present in a significant portion of the T . cruzi kDNA mutated adult chickens and their progeny . In those chickens , the intensity of the self destructive inflammatory process varied from one region to another in the myocardium; while some lesions are triggered high , others are intermediary or in a feeble state . Thus , some areas in the heart may be spared while others may be affected harshly by the inflammation; the intensity of the process never reaches all the heart simultaneously , which would not be compatible with prolonged survival . Such features are evidence of a genetically-driven autoimmunity with the following progression: i ) accumulation of minicircles integrated in germline and somatic cells; ii ) rupture of important genes , such as those regulating cell growth and differention , and the immune responses; iii ) heart damage produced by lymphocytic infiltrates and lyses of target cells; iv ) age-group specific rates of the disease . The Chagas-like disease in the chicken shows multifaceted clinical presentations involving primarily the heart and skeletal muscles , along with the peripheral nervous systems , leading to ominous repercussions in the cardiovascular system . These manifestations can be explained only by the T . cruzi minicircle sequence integrations at several loci in the genome . The tolerance mechanism in kDNA-mutated chickens could not discriminate between self and non-self target tissues because the immune surveillance , fundamental to keep the self constituents free of the destructive reactions from the body self-defense apparatus , may be dampened due to the genotype modifications . The anti-self lymphocyte destruction of the heart happens when breakdown of self-tolerance or deregulation of the surveillance mechanism occurs [62]–[66] . Thus , cardiomegaly with lymphocyte destruction of heart cells in a genotypically modified crosskingdom parasite-free model of the human Chagas disease is shown here for the first time . Experimental T . cruzi infections of laboratory animals and natural infections of hundreds of mammal species and of man reveal a high prevalence of Chagas heart disease and no cancer [1] , [8] . This study shows that the key environmental factor contributing to the development of autoimmunity and self-heart destruction in the chicken model and in the human Chagas disease is the T . cruzi infection , during which the transfer of the kDNA minicircle to the host's genome occurs . Within this context , the host's immune system interacts in the conventional way to afford partial protection against T . cruzi infection , whereas autoimmune disease may ensue from genotypically modified T-cells producing clonal cytotoxicity . An intrinsic feature of the minicircle sequences in the kDNA mutations may produce genotype alterations with rupture of genes regulating cell growth and differenciation factors , but not cancer . We suggest that the generation of autoimmune disease in mammals and in birds might be an intrinsic feature stemming from the protozoan kDNA . This hypothesis requires further investigations . The typical inflammatory cardiomyopathy is present only in chickens with somatic mutations hatched from T . cruzi-infected eggs . These kDNA-mutated chickens show early mortality in comparison with controls . When these chickens die the conspicuous pathologic finding is the inflammatory infiltrates with destruction of heart myofibers by immune system cytotoxic T-lymphocytes . The phenotype of immune system cells in the heart inflammatory infiltrates reveals that a thymus-dependent immune response , destroying the target tissue is a hallmark for pathogenesis of Chagas-like heart disease in kDNA-mutated chickens . In this respect , each kDNA-integrated immune system mononuclear cell involved in the ‘self’ tissue destruction is essentially a mutated clone [97] , promoting an inflammatory lesion in the chicken heart . Each clone not withstanding thymic selection is considered an autoreactive T-lymphocyte repertoire producing the heart lesion , which is an important risk factor for disease outcome [98] , [99] . The scattered nature of the minicircle integrations in CA-rich sites throughout the chicken genome indicates that a large number of host loci are susceptible to kDNA mutagenesis [32] , [34] , [40] . To determine the full extent of this phenomenon , complete sequencing of a kDNA-mutated chicken is required to identify the full cohort of minicircle integrations resulting from a single , specific infection event; each new introduction of the parasite will give rise to a unique combination of integrations for a given individual , resulting in a spectrum of clinical consequences . Although we have documented the disruption of multiple chicken genes resulting in compromised immune system self-tolerance that became permissive to autoimmune rejection of target tissue , inflammatory cardiomyopathy and failure , several integration events may be associated with these phenotypes . Accordingly , 20 genes and five X-linked disorders correlate with manifestations of failure in the genetic etiology of the heterogeneous group of cardiomyopathy in humans [98]–[102] . Thus , groups of integration mutations , and combinations thereof , may explain the clinical symptoms associated with Chagas disease . The kDNA-mutated chicken model suggests a parasite-induced familial genetic disease; the genotype modifications in association with the autoimmune rejection of the heart originate from disruption of the tolerance mechanism of ‘self’ recognition by the host immune system [97] . The genetic control of immune tolerance present in healthy chickens is impaired in kDNA-mutated birds with rampant inflammatory cardiomyopathy . Autoimmunity plays a pivotal role in a substantial proportion of patients with genetically driven inflammatory cardiomyopathy of unknown etiology [100]–[102] . Also , the high risk reported for familial occurrence of cardiomyopathy in first-generation relatives suggests disruption of immune response mechanisms early in the development of the disease , and the identification of inflammatory infiltrates in the heart is an ominous sign of poor disease outcome . Further studies of chromosome skewing and instability-generated long range signaling interactions [60 , 61 , 74 , and 75] are required to understand the genetically-induced mechanism of rupture of immune tolerance , and to explaining the attenuation of heart disease in descendents with genetic modifications . Genetic mutations may generate myocarditis and dilated cardiomyopathy in humans , and the identification of underlying mutations , susceptibility and modifier genes are indispensable for development of new therapies [98 , 101 , and 102] . Experimental treatment of the inflammatory autoimmune cardiomyopathy in kDNA-mutated chickens may require drug suppression of bone marrow progenitor of specific T-cell phenotype infiltrating the myocardium , and transplantation of histocompatible healthy bone marrow to prevent the rejection of self-tissue . Thus , investigation in the congenic chicken model is underway , aimed at the inhibition of inflammatory cardiomyopathy by passive transfer of healthy , naïve bone marrow cells , and , consequently , an effective therapy for Chagas disease . | The Trypanosoma cruzi acute infections can be asymptomatic but approximately one third of the chronically infected cases may present Chagas disease . Parasite persistence and autoimmunity are theories trying to explain the clinical and pathological manifestations of Chagas disease in the heart and the digestive system . To clearly demonstrate roles played by parasite persistence and autoimmunity in Chagas disease we used a chicken model refractory to the T . cruzi . In this study we inoculated the invasive T . cruzi in the air chamber of embryonated eggs . The infection was eradicated by the innate immunity and the chicks were parasite-free at hatching , but they retained the parasitic mitochondrial kinetoplast DNA minicircle in their genome . We documented the kDNA minicircle integrated in the chicken genome by a targeted prime TAIL-PCR , Southern hybridizations , cloning and sequencing . The kDNA minicircles integrated in coding regions of various chromosomes , and mutated chickens developed an inflammatory cardiomyopathy hallmark of Chagas disease , whereby immune system mononuclear cells lyse parasite-free target heart fibers . Genotype alterations resulting from transfers of the parasitic DNA were associated with the tissue destruction carried out by effectors CD45+ , CD8γδ+ , CD8α lymphocytes . This research provides insights about a protozoan infection that can induce genetically driven autoimmune disease . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"evolutionary",
"biology/animal",
"genetics",
"cardiovascular",
"disorders/myopathies",
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"evolutionary",
"biology",
"molecular",
"biology",
"immunology/autoimmunity",
"cardiovascular",
"disorders/heart",
"failure"
] | 2011 | Trypanosoma cruzi in the Chicken Model: Chagas-Like Heart Disease in the Absence of Parasitism |
Estimation of immunological and microbiological diversity is vital to our understanding of infection and the immune response . For instance , what is the diversity of the T cell repertoire ? These questions are partially addressed by high-throughput sequencing techniques that enable identification of immunological and microbiological “species” in a sample . Estimators of the number of unseen species are needed to estimate population diversity from sample diversity . Here we test five widely used non-parametric estimators , and develop and validate a novel method , DivE , to estimate species richness and distribution . We used three independent datasets: ( i ) viral populations from subjects infected with human T-lymphotropic virus type 1; ( ii ) T cell antigen receptor clonotype repertoires; and ( iii ) microbial data from infant faecal samples . When applied to datasets with rarefaction curves that did not plateau , existing estimators systematically increased with sample size . In contrast , DivE consistently and accurately estimated diversity for all datasets . We identify conditions that limit the application of DivE . We also show that DivE can be used to accurately estimate the underlying population frequency distribution . We have developed a novel method that is significantly more accurate than commonly used biodiversity estimators in microbiological and immunological populations .
How can we estimate diversity from a population sample ? In viral infections , the number of viral variants and their population structure inform our understanding of disease pathogenesis , and can suggest treatment strategies [1] , [2] . In immunology , the repertoire and population structure of B cell and T cell receptor clonotypes vary with age [3]–[7] , and are intimately linked to antimicrobial protective efficacy . In the human microbiome , decreased diversity of the gastrointestinal microbiota is associated with atopy [8] , Crohn's disease and ulcerative colitis [9] , [10] . A complete census is usually impossible and so estimators of the number of unseen “species” are required . Here we use the word “individual” to refer to a single T cell sequence read , microbial sequence read , or virus- infected cell . We use “species” to denote a class of individuals , such a T cell clonotype , bacterial operational taxonomic unit ( OTU ) or viral clone . The term “species richness” denotes the number of species in the population under consideration . Immunological and microbiological data differ in important respects from ecological data . First , in many immunological and microbiological populations , it may be reasonable to assume that “species” are taxonomically similar , that the spatial distribution of individuals is homogeneous , and that individuals are sampled randomly , independently and with equal probabilities . If made , these simplifying assumptions allow the extrapolation of individual-based rarefaction curves , which depict the expected number of species against the number of individuals sampled [11]–[14] . However , the above assumptions are frequently violated in ecological populations [14]–[18] , where unobserved individuals may differ from observed individuals in their colour , physical size , geographical distribution , movement , variety of habitats and relationship to other species [15] , and thus remain unobserved despite substantial subsequent sampling . Second , many common assumptions about population structure are inappropriate for immunological and microbiological populations , for example that all species have equal frequencies [19]–[21] , or that the functional form of the population distribution is known [22]–[26] . We therefore consider non-parametric estimators . Non-parametric estimators , such as Chao1 [27] , and the abundance-based coverage estimator ( ACE ) [28] , have been proposed . ACE has been suggested to be the best current approach [14] , [22] , [29] and is widely applied in microbiology and immunology; for example to estimate the diversity of the human gastrointestinal flora [30] , human gut metagenome [31] , mouse TCR repertoire [32] , [33] , fungi [34] , and the number of HTLV-1 infected cell clones [35] . Although they were originally intended as methods to estimate lower bounds , the Chao1 estimator , and the modified , bias-corrected form Chao1bc [36] , have been used to make a point estimate of the number of TCR clonotypes [37] , [38] , the number of OTUs in hepatitis C virus infection [1] , parasite diversity in malaria infection [39] metagenome size [40] , the number of integration sites of therapeutic gene therapy vectors [41] , soil diversity [42] , and again the number of HTLV-1 infected cell clones [35] , [43] . In addition to the ACE and the Chao estimator , we also consider two additional non-parametric estimators: the Bootstrap [44] and Good-Turing estimators [45] . Most diversity estimators aim to estimate the species richness in one of two populations of interest: either in the population from which the sample was drawn ( e . g . number of microbial species in the gut , given a sample from the gut ) or the value where the rarefaction curve saturates ( e . g . number of species at the point when further sampling does not yield any new species ) . These definitions of the population of interest lack flexibility and may be inappropriate or poorly defined for the question in hand . Indeed , if some species are represented by a single individual , the rarefaction curve will not saturate . For many microbiological and immunological questions , an estimator that allows the user to specify the size of the population of interest is desirable . For instance , we may wish to know the T cell repertoire diversity of both the blood and the whole body . The aim of this study was to identify a suitable method for estimating species richness in immunological and microbiological populations . We tested widely-used estimators on samples of microbiological and immunological populations . We found these estimators performed poorly . We therefore developed and validated a new method to estimate species richness and species frequencies . We used data from three independent sources: ( i ) viral populations from human T-lymphotropic virus type-1 ( HTLV-1 ) –infected subjects; ( ii ) T cell antigen receptor ( TCR ) clonotype repertoires; and , ( iii ) infant faecal microbial samples . HTLV-1 is a retrovirus that mainly infects CD4+ T lymphocytes . HTLV-1 spreads within hosts via two routes: de novo infection of uninfected cells , and proliferation of infected cells [46] . When an infected cell proliferates , the integrated provirus is replicated with the host genome and a clone of infected cells is generated , each cell carrying a provirus in the same genomic site . Consequently , in each host , HTLV-1 persists in many distinct infected cell clones . We used high-throughput data on the abundance of HTLV-1 infected cell clones in 14 HTLV-1 seropositive subjects [43] . The human gastrointestinal tract contains a densely populated ecosystem of microbes that performs a variety of functions [47] . We obtained high-throughput 16S rRNA sequence data from infant faecal samples . In this study we used observed frequencies of different bacterial operational taxonomic units ( OTUs ) [48] . T cells are vital to adaptive immunity . The T cell population comprises a diverse repertoire of TCR clonotypes , each defined by the DNA sequence of the expressed TCR . In humans , there are a potential 1015–1020 different TCR clonotypes [49] , but the actual number of clonotypes in one person is estimated to be between 106 and 108 [50] . In this study we used RACE-based data on TCR clonotype abundance . We studied circulating central and effector memory , naïve and total CD4+ and CD8+ T cells .
Blood samples were donated by HTLV-1+ subjects attending the HTLV-1 clinic at the National Centre for Human Retrovirology ( Imperial College Healthcare NHS trust ) at St . Mary's Hospital , London UK , with fully informed written consent . This study was approved by the UK National Research Ethics Service ( NRES reference 09/H0606/106 ) . Parents gave full written informed consent for infant faecal sample collection , and all protocols and procedures were approved by the National Research Ethics Service Committee , U . K . ( Southampton and South West Hampshire ) ( ref: 05/Q1702/119 ) . For the TCR data , leukaphereses were performed on healthy donors who provided written informed consent at the National Institutes of Health , USA . The protocol and use of these samples for immunological investigation were approved by the National Institute of Allergy and Infectious Diseases Institutional Review Board . Previously reported [43] and new high-throughput data on HTLV-1 clonality were analysed . Each HTLV-1 dataset quantifies the abundance of HTLV-1-infected T cell clones . There were 105 datasets , comprising nine samples from each of 11 subjects ( three independent samples at each of three time points ) , and 15 samples from four subjects . All had either HTLV-1-associated myelopathy/tropical spastic paraparesis or were asymptomatic carriers of HTLV-1 . The microbial data were derived from faecal samples obtained from 10 infants . DNA was amplified with two sets of PCR primers , generating 20 datasets [48] . Amplicons of the V3-V5 regions of the 16S rRNA gene were generated by PCR using two sets of universal primers . Sequencing data were generated using the Roche 454 GS Junior platform . Analysis was performed using the QIIME pipeline as described previously [48] . A total of 16 datasets were collected from two subjects , comprising TCR sequences from four phenotypically defined subsets of CD4+ and CD8+ T-cells: naïve , central memory ( CM ) , effector memory ( EM ) and total . After flow cytometric sorting and cell lysis , mRNA was extracted and subjected to a non-nested , template-switch anchored RT-PCR using a 3′ TCRB constant region primer as described previously [51] . This approach allows linear and unbiased amplification of all TCRs irrespective of TRBV or TRBJ gene usage . Paired-end sequencing reactions ( each 150 bp ) were performed using an Illumina HiSeq 2000 sequencer . Raw FASTQ files were annotated using reference TCRB sequences from the ImMunoGeneTics ( IMGT ) website ( http://www . imgt . org ) and a custom-written Java application . Following annotation , the data were filtered to eliminate potential sequencing and PCR errors . Prochlorococci are vital to energy and nutrient cycling in the oceanic ecosystem , and the genus contains a highly diverse and abundant population of clades . We analysed publicly available metagenomic data describing clades Prochlorococcus . The data were obtained by the Global Ocean Sampling Expedition and contains the frequency of distinct sequence reads of genes of Prochlorococcus clades . [52] Sampling sites , sample collection , library construction , fragment recruitment , and determination of Prochlorococcus abundances are detailed in [52] , [53] . We developed a heuristic approach to estimate species richness , which we named DivE ( Diversity Estimator ) ( Figure 1 ) . To calculate the DivE estimator , many mathematical models are fitted to multiple nested subsamples of individual-based rarefaction curves . Each model is fitted to all nested subsamples , and is scored on a set of four criteria . The five best-performing models are extrapolated and their respective estimates are aggregated to produce the DivE species richness estimate . DivE requires an estimate of population size . If the species richness of a wider population is desired , the same models are used but extrapolated to a different population size; this is only justified if the two populations are similar in their spatial distribution of individuals . The criteria against which each model fit is scored are: The rationale behind each criterion is as follows: Criteria 2 ) , 3 ) and 4 ) are independent of the fitting process . That is , they are not constraints by which models are fitted; instead they are tests of model performance . Each model fit is scored on all four criteria . For criteria 1–3 , we scored a fit in multiples of empirically chosen precision levels . The precision level for criterion 1 was 0 . 01%: a score of 1 denotes a model fit where the mean percentage error of the residuals , ε , was less than 0 . 01%; a score of 2 denotes 0 . 01%<ε≤0 . 02% and so on . Criteria 2 and 3 were similarly scored in multiples of 0 . 5% . Criterion 4 was implemented by giving a score of 500 to model fits that violated either of its conditions; this value was chosen to exceed the score of any model fit that satisfied this criterion . The final score for each model is an aggregate of the scores of all model fits across subsamples and criteria , and is calculated as follows . First , the score for each criterion is defined as the mean of the scores of all subsample fits for that criterion . The final score for each model is the mean of all criteria scores . The DivE species richness estimate is the geometric mean of the estimates provided by the five best-performing ( i . e . lowest-scoring ) models . A list of 58 candidate models ( Text S1 ) was chosen from an online repository [54] . Many of these ( e . g . logistic , logarithmic , hyperbolic ) are widely used in population ecology [11] , [55] . Models were fitted by least squares regression using R version 2 . 14 . 2 [56] with the package FME [57] . Global fitting was performed using Price's algorithm [58] followed by local fitting using the Levenberg-Marquardt algorithm [59] . We evaluated DivE and five non-parametric estimators: the Chao1 bias-corrected estimator ( Chao1bc ) [36] , the abundance-based coverage estimator ( ACE ) [28] , the Bootstrap estimator [44] , the Good-Turing estimator [45] , [60] , [61] and the widely-used negative exponential model [11] , [12] , [36] , [62] , [63] . ACE and Chao1 [27] , have been suggested as best practice [12] , [14] , [22] , [29] , [64] and are widely applied in microbiology and immunology [1] , [30] , [32] , [34] , [35] , [37] , [39]–[43] . For ACE , “abundant” species were defined as those with an observed frequency of greater than 10 , as recommended in [64] . Due to differences between estimators and between datasets , we conducted multiple , distinct evaluations and validations . We first evaluated , for each estimator , the relationship between estimated diversity and sample size , using the estimates produced from a series of successively smaller , randomly generated in silico subsamples of observed data . For the microbial and TCR data respectively , five and six equidistant subsample sizes were chosen from each observed dataset . For the HTLV-1 data , subsample sizes were chosen to be approximately equidistant; however some were removed due to runtime constraints . See Table S1 for further details . Second , we measured the accuracy of DivE by comparing the estimated species richness Ŝobs at the size of the full dataset Nobs from each subsample to the ( known ) species richness Sobs in the full data . Using the same method , we compared DivE to the second order bias-corrected Akaike Information Criterion ( AICc ) [65] , [66] . Third , the TCR data have rarefaction curves which plateau . Using smaller subsamples of this data and making the assumption that the species richness of the full data is equal to that of the entire population , we were able to evaluate the accuracies of all estimators together . Finally for 11 of the 14 HTLV-1 patients detailed in Table S1 , three samples were taken at a single time point . For each time point , the three samples were pooled and used as a practical test of DivE's ability to predict species richness in larger samples . In addition to species richness , we wanted to estimate the population frequency distribution . Because of the considerable structural variation between and within immunological and microbiological populations , we developed a general method which does not assume the analytical form of the population structure . This algorithm uses the DivE estimator combined with observed abundances ( Figure 2 ) . See Text S1 for details . The algorithm was applied to multiple random subsamples of observed data . The estimated distributions were then compared to the full data frequency distribution using two measurements: ( i ) error , defined as the sum of discrepancies in species frequencies between estimated and observed ( full ) distributions , divided by the number of individuals in the observed distribution , i . e . error = and ( ii ) percentage error between the Gini coefficients of the estimated and observed distributions . The Gini coefficient is an index of dispersion used widely in epidemiology , sociology , biology , and ecology [43] , [67] .
Each species richness estimator ( Chao1bc [36] , Bootstrap [44] , ACE [28] , Good-Turing [45] , the negative-exponential model [12] and DivE ) was applied to random subsamples of observed data . We used linear regression to calculate the average proportional increase in estimated diversity as a function of the proportional increase in sample size . Sample size and diversity were normalized respectively to the smallest sample and the estimated diversity at the smallest sample . For example , a “normalized gradient” of 0 . 5 would mean that , on average , an increase of 10% in sample size would produce a 5% increase in estimated diversity . A value of zero would signify no bias with sample size . The existing estimators performed poorly when applied to the HTLV-1 and microbial data: estimates systematically increased with sample size . In contrast , DivE produced consistent estimates that showed no obvious relationship with sample size ( Figures 3 and 4 ) . Across subjects and for all methods except DivE , estimates showed significant positive normalized gradients ( p<0 . 01 for every estimator , n = 14; two-tailed binomial test ) ranging between 0 . 17 and 0 . 52 for the HTLV-1 data and 0 . 3 to 0 . 45 for the microbial data ( Figure 4 ) . Conversely , the normalized gradients produced by DivE did not differ significantly from zero ( p = 0 . 18 , n = 14; two-tailed binomial test ) , and were much smaller ( 0 . 0081 and 0 . 022 for the HTLV-1 and microbial data respectively ) ( Figure 4 ) . In any specified population there is only one value of species richness , and an accurate estimator will arrive at this value regardless of sample size . An increase in estimate magnitude with sample size implies that estimates of a population's species richness would increase if e . g . greater blood volumes were drawn or technique sensitivity was improved . The existing estimators were less biased when applied to the TCR data , and estimates were largely consistent . Although the normalized gradients were still significantly positive ( p<0 . 0001 for each estimator except DivE , n = 16 ) , their magnitudes were substantially lower than for the HTLV-1 and microbial data . However , existing estimators again increased with sample size for the effector memory ( EM ) CD8+ T cell population from the same subject . These observations can be explained with reference to the TCR rarefaction curves ( Figure 3 ) . With the exception of the CD8+ EM dataset ( for which the subsample sizes were considerably smaller ) , each TCR rarefaction curve reached a plateau , implying that the vast majority of observed clonotypes were encountered early . In contrast , the CD8+ EM rarefaction curve did not plateau , suggesting that further sampling would reveal more CD8+ EM clonotypes . In common with the microbial and the HTLV-1 datasets , DivE performed well for all TCR datasets , producing consistent results from all subsample sizes . To make sure that the smallest subsamples did not disproportionately contribute to the observed gradients , we repeated the above analysis using only estimates from the largest three subsamples in each patient dataset , which showed almost identical results ( Figure S1 ) . The best-performing models were largely consistent within patients and between subsamples for the microbial and TCR data , although less so for the HTLV-1 data . Ideally , model selection would be consistent across all subsamples . Deviation from this will result in a discrepancy between Sobs and Ŝobs . This discrepancy is quantified in Figure 3 ( middle column ) and in Table S2 . To ensure the four criteria provide a useful metric of model performance , we compared DivE to the second order bias-corrected Akaike Information Criterion ( AICc ) [65] , [66] . DivE's mean errors ( between the species richness of the full data Sobs and Ŝobs ) were 3 . 3% , 1 . 0% , and 4 . 0% for the HTLV-1 , TCR and microbial data respectively . These were lower than the corresponding errors of 6 . 7% , 1 . 1% , and 7 . 5% , produced when models were scored by the AICc . This effect was more marked when we considered estimates from small subsamples , defined as those comprising at most 50% of the observed data ( Table S2 ) . However , the differences between errors were smaller for the TCR data , perhaps also due to the saturating rarefaction curves in these samples . When rarefaction curves reach a plateau , we can assume that the value of the plateau is approximately equal to the species richness of the entire population , which the existing estimators aim to estimate . Thus it is appropriate to evaluate DivE and the existing estimators together using TCR rarefaction curves which plateau . We took random subsamples of 0 . 5% , 1% , 2% , 5% , and 10% of the total CD4+ and CD8+ cells for subjects C and E . We then applied each estimator to each subsample and measured its error ( = |Sobs - Ŝobs| /Sobs ) ( Table 1 , Figure S2 ) . DivE's median error was 6 . 7% , substantially lower than respective median errors of 43 . 8% , 42 . 8% , 65 . 3% , 61 . 7% , and 50 . 7% for the Chao1bc , ACE , Bootstrap , Good-Turing and negative exponential estimators ( p<0 . 0005 for each estimator comparison with DivE , n = 20; two-tailed binomial test ) As neither the HTLV-1 nor the microbial data exhibit rarefaction curves that plateau , we cannot apply the same analysis to these datasets . Instead we took advantage of the fact that , for 11 of the 14 HTLV-1 subjects , the data comprised three time points , with three samples drawn at each time point in immediate succession from the subject . For a given subject and a single time point , the three samples were combined in silico to produce a single pooled sample . We compared the observed species richness of the pooled sample to each estimator's estimates from a subsample ( Figure 5 , Figure S3 ) . The total blood diversity must be at least as great as that observed by pooling the samples . However , all existing estimators estimate the total diversity to be less than that observed . Based on a single subsample , the Chao1bc , ACE , Bootstrap , Good-Turing and negative exponential estimators respectively estimate medians of 27 . 0% , 12 . 7% , 71 . 1% , 65 . 5% , and 47 . 6% fewer clones than observed in the pooled samples ( n = 11 ) . Since the pooled samples do not saturate , and since the blood contains approximately 105 times more infected cells than the pooled sample , the diversity observed in the pooled sample is likely to be a small fraction of the total diversity . Since the existing estimators produce estimates lower than the pooled sample diversity , let alone total blood diversity , this represents a considerable error . We used DivE to produce two estimates: the pooled sample diversity and blood diversity . From the subsamples DivE estimated a median of 2 . 6×103 clones in the pooled samples , a median error of 2 . 5% ( n = 11 ) ( Figure 5 , Figure S3 ) . Additionally , DivE estimated 2 . 8×104 clones in the blood , approximately one log higher than the observed pooled sample diversity . Whilst we cannot determine whether or not this is accurate it is at least plausible , considering that it is not less than the diversity of the pooled sample , that the sampling fraction is very small , and that the rarefaction curve has not reached a plateau . Next we sought to identify conditions under which DivE would be prone to error and should not be applied . When the observed rarefaction curve is linear , the data imply a constant rate of species accumulation , and so provide little information on how quickly the rate of species accumulation will decrease . This is usually indicative of severe under-sampling . We predicted that DivE will fail to give accurate estimates given such a near linear rarefaction curve . We tested this prediction by calculating the error in the DivE estimates as a function of rarefaction data curvature . The curvature Cp was quantified by the area between the observed rarefaction curve and a linear rarefaction curve , as a fraction of the maximum possible area , which occurs when the rarefaction curve saturates immediately . Cp can take values between 0 and 1 , where 1 reflects perfect saturation and 0 reflects a constant rate of species accumulation ( Figure S4 ) . We took additional samples of 0 . 1% of the total CD4+ and CD8+ cells for subjects C and E to obtain lower curvature values . As expected , at very low curvatures ( 0 . 016≤Cp≤0 . 101 ) , DivE was prone to overestimation and performed poorly ( Figure 6 ) , with median error 0 . 23 . However , for under-sampled populations of intermediate curvature ( 0 . 11≤Cp≤0 . 62 ) DivE improved markedly ( median error = 0 . 06 ) , and typically outperformed the other estimators ( Figure 6 , Table S3 ) . Finally , all estimators perform well when the curvature is high and most of the diversity has been observed ( Figure 3D , 3H and 3L ) . We next tested DivE using the Prochlorococcus data [52] , with multiple subsamples of increasing curvature ( as for the TCR data ) . At low curvatures DivE again performed poorly , but it became more accurate as the curvature increased . For under-sampled populations of intermediate curvature , DivE again outperformed the other estimators , although the differences between the estimator errors were not as dramatic as with the TCR data ( Figure S5 ) . Very low curvatures suggest severe under-sampling and researchers should exercise caution with such data . It is unlikely that any species richness estimator will be accurate or informative in such cases . In both HTLV-1 infection and infection with the related bovine leukaemia virus ( BLV ) , accurate determination of the number of infected cell clones in the host is critical to understanding retroviral dynamics and pathogenesis [68]-[71] . Here we make two different estimates of the number of HTLV-1 infected cell clones: ( i ) in the circulation; and , ( ii ) in the whole body . See Text S1 for details of HTLV-1 population size estimation . The mean estimated number of clones in the circulation in a single host was 2 . 9×104 . It is unknown whether the population structure of HTLV-1 clones in the blood reflects that in solid lymphoid tissue and the spleen . If we assume that these two populations have similar structures , and thus that it is justified to extrapolate to the whole body , we obtain an average of 6 . 2×104 clones , i . e . approximately only twice as many clones , although there are >300 times as many infected cells in the body as the blood . These new estimates in the blood and body are approximately 1 and 1 . 3 logs higher respectively than those calculated using ACE and Chao1bc ( p<0 . 0001 , two-tailed paired Mann-Whitney U-test ) , and >2 logs higher than previously published estimates ( Figure S6 ) [35] , [43] , [69] , [72] . Because of its heuristic nature , DivE lacks formal statistical confidence intervals . Uncertainty in the estimates produced by DivE has two sources: parameter values in each respective model ( within-model variation ) , and the choice of model ( between-model variation ) . Using standard errors of parameter estimates to calculate confidence intervals ignores uncertainty from model selection . Information theoretic approaches that take account of model selection uncertainty have become increasingly common in ecology [73] , [74] and elsewhere . There are broadly two approaches: i ) computing AIC weights , and ii ) repeated resampling and model ranking to determine bootstrap model selection probabilities [66] . However , neither approach is appropriate in our case . We do not rank models using AIC since this produces less accurate estimates than DivE ( Table S2 ) , and so we cannot use AIC weights to derive confidence intervals . Further , since there is a systematic bias towards lower species richness in bootstrap samples ( Figure S7 ) , a similar bias may be introduced in the estimation of bootstrap model selection probabilities , leading in turn to a bias in species richness estimation . Systematic underestimation in bootstrap samples is particular to species richness estimation: this does not highlight a general problem with resampling to quantify model selection uncertainty . As a pragmatic indicator of estimate variability , we use the range of estimates produced by the five best-performing models; the geometric mean of these five models is taken as the point estimate ( Table S4 ) . The distribution generation algorithm was reasonably accurate for the HTLV-1 data , and considerably more accurate for the TCR and microbial data . The mean error between the estimated and true distributions was 32 . 1% , 2 . 9% , and 4 . 9% for the HTLV-1 , TCR and microbial data respectively . The mean error between the estimated and true Gini coefficients was 7 . 5% , 0 . 9% , and 2 . 2% for the HTLV-1 , TCR and microbial data respectively ( Table 2 ) . For the HTLV-1 data , the algorithm underestimated the abundance of the largest clones , but we did not observe this effect in the TCR and microbial data ( Figure 7 ) .
We wished to estimate species richness in three microbiological and immunological datasets . Initially we used estimators that are reported to perform well in ecology [12] , [34] , [36] , [60] , [61] , [75] . In the datasets with rarefaction curves that did not plateau , these estimators were biased by sample size . For datasets with rarefaction curves that did plateau , estimates were consistent , but in such cases estimators contribute little information because approximate species richness is already known . Comparable results have been reported elsewhere [12] , [16] , [62] . By combining data from multiple independent HTLV-1 samples , we showed that these estimators substantially underestimated species richness . We then developed a new approach , DivE , to estimate species richness and frequency distribution . In our first validation , DivE consistently and accurately estimated the diversity of the observed data from incomplete subsamples of that data . We subsequently determined conditions where DivE would fail and should not be applied . When the rarefaction curvature was low and the data implied a near-constant species-accumulation rate , DivE was prone to overestimation . However , in under-sampled populations of intermediate curvature , DivE substantially improved . The DivE distribution generation algorithm performed with reasonable accuracy ( Table 2 , Figure 7 ) . We argue that biologically meaningful and useful estimators should be able to estimate species richness in a specified population . This is not the case with the existing estimators we tested . In contrast , DivE can estimate diversity in any given population size . However , population size estimation can be nontrivial [76]–[78] . In spatially homogeneous populations with equiprobable detection of individuals , estimating population size through scaling by area or volume is justifiable e . g . scaling from cells in 50 ml of blood to cells in the total blood volume . When population size estimates are unavailable , it is still usually possible to provide meaningful diversity estimates , e . g . the number of microbes per gram of faeces . DivE may also be useful in deciding the depth of sampling required for an adequate census . Deeper sampling may require more DNA sequencing or a larger tissue sample from a patient , and so minimizing sampling depth has financial and ethical benefits . This is not possible with the other estimators we tested . The HTLV-1 data consisted of absolute species counts , and so we could estimate HTLV-1 diversity . Microbial and TCR datasets were used only for validation as these data consisted of sequence reads and not absolute counts . To the extent that read abundances differ from absolute counts , such data cannot be used to estimate species richness with any abundance-based estimator ( e . g . DivE , Chao1bc , and ACE ) . Over-amplification by PCR may generate a saturating rarefaction curve that is not due to sampling depth , falsely implying that the majority of species have been observed . This can be seen in our TCR data: plateaus were far lower than previously reported diversity estimates [50] , [79] . However , absolute counts can often be obtained ( e . g . by spiking a sample with a known quantity of identifiable individuals or by barcoding to identify PCR duplicates ) . It is unlikely that sequencing error influenced our HTLV-1 diversity estimates , because sequencing error cannot systematically alter proviral integration site mapping . However , species richness estimates from TCR or microbial data are likely to be susceptible to sequencing error . Sequencing error can falsely increase diversity , and this will influence species richness estimates using any estimator; researchers must therefore exercise caution when analysing such data; ideally by preprocessing the data to remove error prior to further analysis . Caution must also be exercised when assuming that the spatial distribution of individuals is uniform . We believe that these assumptions are reasonable for the blood , but skin tissue for example may be more clustered . DivE is conceptually simple but can be computationally intensive to implement . When applying DivE to a new type of data it is necessary to ascertain which models perform best . This requires that many models be fitted to multiple subsamples . If , for a particular data type , a given set of models performs consistently well , application becomes much quicker because only these models need to be fitted , and it is no longer necessary to fit all models to all subsamples . In our analysis we found that five models performed consistently well , and so we have used the aggregate of the five best-performing models in our estimates . Since the optimal number of models may differ between datasets , we advocate careful analysis of model scores to decide how many models should be aggregated . The DivE estimator has been provided as an R package , available at http://cran . r-project . org/web/packages/DivE/index . html . In summary , we have developed and validated a new approach to estimate species richness and distribution that significantly outperformed existing estimators of biodiversity in the datasets we examined . | The “unseen species problem” is ubiquitous in biology and is frequently encountered outside its original setting in population ecology . For example , the human retrovirus HTLV-1 persists within hosts in multiple , genetically identical clones of infected cells . However , the number of clones in one host is unknown; this knowledge is required for an understanding of how the virus survives despite a strong host immune response . The problem arises again in estimating the diversity of the T-cell repertoire , which influences adaptive immunity . For example , the T-cell diversity may influence the outcome of viral challenge . While there have been numerous attempts to address the unseen species problem , there is currently no consensus on how to do so in immunology and microbiology . The aim of this study was to identify a suitable method to estimate the number of species in immunological and microbiological populations . We found that five existing estimators we tested performed poorly across three data sources ( HTLV-1 clonality , T cell receptor , and microbial data ) . We therefore developed a new estimator , DivE , which significantly outperformed the other estimators . Accurate diversity quantification allows better evaluation of the impact on immunity from factors such as ageing and infection . | [
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] | 2014 | Quantification of HTLV-1 Clonality and TCR Diversity |
Small RNA viruses have evolved many mechanisms to increase the capacity of their short genomes . Here we describe the identification and characterization of a novel open reading frame ( ORF4 ) encoded by the murine norovirus ( MNV ) subgenomic RNA , in an alternative reading frame overlapping the VP1 coding region . ORF4 is translated during virus infection and the resultant protein localizes predominantly to the mitochondria . Using reverse genetics we demonstrated that expression of ORF4 is not required for virus replication in tissue culture but its loss results in a fitness cost since viruses lacking the ability to express ORF4 restore expression upon repeated passage in tissue culture . Functional analysis indicated that the protein produced from ORF4 antagonizes the innate immune response to infection by delaying the upregulation of a number of cellular genes activated by the innate pathway , including IFN-Beta . Apoptosis in the RAW264 . 7 macrophage cell line was also increased during virus infection in the absence of ORF4 expression . In vivo analysis of the WT and mutant virus lacking the ability to express ORF4 demonstrated an important role for ORF4 expression in infection and virulence . STAT1-/- mice infected with a virus lacking the ability to express ORF4 showed a delay in the onset of clinical signs when compared to mice infected with WT virus . Quantitative PCR and histopathological analysis of samples from these infected mice demonstrated that infection with a virus not expressing ORF4 results in a delayed infection in this system . In light of these findings we propose the name virulence factor 1 , VF1 for this protein . The identification of VF1 represents the first characterization of an alternative open reading frame protein for the calicivirus family . The immune regulatory function of the MNV VF1 protein provide important perspectives for future research into norovirus biology and pathogenesis .
Collectively , the innate and adaptive immune systems result in a strong evolutionary pressure on pathogens to develop countermeasures to allow their continued existence . Therefore pathogens , including viruses , have evolved a multitude of mechanisms for evading the host response to infection , often by the expression of proteins that interfere with cellular antimicrobial response mechanisms [1] . The size of RNA virus genomes is thought to be limited by the error prone nature of the viral polymerase . As a likely direct consequence , RNA viruses have evolved a variety of mechanisms to increase the coding capacity of their genomes [2] . These include the use of ribosomal frameshifting where a proportion of translating ribosomes change the reading frame to produce proteins with common N-terminal but a different C-terminal from the read-through sequence [3] . Many viruses have also evolved to use a mechanism that creates overlapping reading frames through the use of two or more transcription initiation sites or translation start codons within the same RNA sequence [4] , [5] . Murine norovirus ( MNV ) was identified in 2003 as a virus that caused a lethal infection in immunocompromised mice [6] . However , MNV is now known to be a widespread infectious agent of laboratory mice with a reported seroprevalence of 20-64% [7] , [8] . MNV is currently the only norovirus which replicates efficiently in tissue culture , where it has a tropism for dendritic and macrophage cells [9] . The availability of immortalized macrophage cell lines such as the murine macrophage RAW264 . 7 , has allowed significant advances to be made in understanding the life cycle of this virus . For the first time critical processes in the norovirus life cycle have been dissected e . g . the mechanism of tissue culture mediated attenuation of MNV-1 [10] , the requirement for dynamin II and cholesterol during virus entry [11] , [12] , the identification and functional requirement for RNA secondary structures in virus replication [13] and pathogenesis [14] as well as the induction of apoptosis during infection [15] , [16] . In addition , MNV has allowed an unprecedented analysis of the immune response to norovirus infection [17] , [18]–[21] . This broadening in understanding of norovirus replication has been facilitated greatly by the development of murine norovirus reverse genetics [22] , [23] and its recent optimisation [24] . The role of murine norovirus in potential exacerbation or complication of other diseases , especially murine models of infection , has also been investigated . This is certainly warranted given the seroprevalence of MNV in animal houses . Studies with models of Crohn's disease [25] or bacterial induced inflammatory bowel disease [26] showed a significant impact of MNV and MNV infection prolongs the shedding of mouse parvovirus [27] . In contrast , MNV co-infection had little or no impact on murine CMV [28] , Friend retrovirus infection [29] or models of diet induced obesity and insulin resistance [30] . These contrasts warrant further studies into the nature and mechanisms of interference observed in mouse models of disease . MNV has also provided a useful experimental system in determining the immune responses required for efficient norovirus vaccination [18] , [31] . Collectively , this highlights both the relevance of MNV as a significant infectious agent in its own right and also the utility of MNV as a model for human norovirus . Continued research into what differentiates murine and human noroviruses and how norovirus infection affects the host cell is therefore of upmost importance to both fields of research . Unlike other members of the Caliciviridae , which typically encode three open reading frames [6] , our analysis and that presented during large scale sequencing of many MNV genomes [32] indicates the presence of a fourth potential ORF in the MNV genome ( Figure 1A ) In this study we demonstrate that the protein encoded by ORF4 is expressed during virus infection , is not essential for virus replication in tissue culture but plays a role in viral virulence and therefore represents a novel viral virulence factor . Based on the findings that it possesses anti-innate immune activity , contribute towards the regulation of virus induced apoptosis during infection and modulates the outcome of experimental infection of mice , we have described the ORF4 gene product as virulence factor 1 ( VF1 ) . The study provides important insights into the mechanisms of norovirus avoidance of the innate immune response and norovirus pathobiology .
The region of the genome encoding VF1 contains an intact reading frame in all available MNV sequences derived from different isolates or strains ( Figure 1A , 1B and data not shown ) . In contrast to the typical 8–15% sequence divergence seen between MNV variants in the amino acid sequences of ORF1 , ORF3 and the predicted single coding region of ORF2 , variability is markedly suppressed in the predicted ORF4 and double coding region of ORF2 ( 3%; Table 1; Figure 1C ) . Almost all sequence variability between MNV variants in the single coding regions ( ORF1 and ORF3 ) occurs at synonymous sites . dN/dS ratios , namely the substitution rates at non-synonymous and synonymous sites , ranging between 0 . 03–0 . 10 are indicative of strong negative selection . In the double coding region of ORF2 ( i . e . the region which codes for both VP1 and VF1 ) , the restricted variability that is observed occurs at synonymous sites in the ORF2 reading frame ( dN/dS: 0 . 044 ) consistent with stronger sequence constraints in the conventional reading frame encoding the MNV structural protein than in the ORF4 gene ( dN/dS ≈ 2 ) . However , the elevated ratio relative to that of ORF2 arose through greater suppression of synonymous variability in this reading frame , rather than increased amino acid sequence variability . dN values were 0 . 04 and 0 . 03 in ORF2 and ORF4 respectively . As well as suppressing variability , the existence of a second reading frame in ORF2 leads to altered codon usage by the ORF4/VF1 coding sequence . For example , there was a significant overrepresentation of the UUG triplet coding for Leu in ORF4 ( 15 from 33 , compared to 17 from 128 in ORF1; p<0 . 001 in a 6×2 contingency table for the 6 synonymous Leu codons ) , whereas there were no differences in Leu codon usage between ORFs 1 , 2 ( single coding region ) and ORF3 . The program MLOGD identifies overlapping coding sequences by specific codon usage signatures arising from mutational constraints consequent to the requirement to maintain protein function in two putative genes [33] . The relative likelihood that a given sequence region is single-coding or double-coding was calculated using a codon usage table and nucleotide mutation and amino acid substitution matrices ( Figure 1C ) . This analysis provides independent support for the existence of ORF4/VF1 , independent of its effect on sequence variability and evolutionary conservation . The first methionine codon in ORF4 at 5069 lies two residues downstream from a stop codon in that reading frame , and is 2 and 4 residues away from Met codons in ORF1 ( including the -1 frameshift ) . The ORF4 start codon is in a strong Kozak context ( G at +4 and -3 ) and likely represents the translation start site of VF1 . The ability of the MNV-1 subgenomic RNA ( sgRNA ) to produce a protein from the open reading frame predicted to encode VF1 was examined by in vitro translation of a plasmid containing the entire MNV-1 sgRNA under control of a T7 RNA polymerase promoter ( Figure 2A ) . A coupled transcription and translation reaction of the MNV-1 sgRNA produced three proteins and the identity of the major ( VP1 ) and minor ( VP2 ) capsid proteins were confirmed using immunoprecipitation ( Figure 2A ) . Polyclonal antisera to a peptide from MNV-1 VF1 was generated in rabbits and used to confirm the identity of the VF1 protein product by immunoprecipitation ( Figure 2A ) . Full length his-tagged VF1 , purified from E . coli was poorly immunogenic , hence a modified immunization protocol that used a variety of forms of VF1 ( described in Materials and Methods ) , followed by affinity purification was required in order to obtain reactive antisera . Immune sera from MNV-1 infected mice did not contain antibodies to VF1 as determined by western blot using recombinant his tagged VF1 ( data not shown ) . To examine the expression of VF1 during MNV-1 replication in tissue culture , the well established RAW264 . 7 cell culture system for MNV [9] was used and the production of VF1 analyzed by western blot ( Figure 2B ) . Using a high multiplicity of infection ( MOI of 5 TCID50/cell ) infection , VF1 was readily detected as early as 9 hours post infection , appearing at the same time as the minor capsid protein VP2 ( Figure 2B ) . In contrast , the viral RNA polymerase NS7 was detected as early as 6 hours post infection ( Figure 2B ) . Whilst we were unable to detect VF1 and VP2 prior to 9 hours , this may simply be a reflection of the sensitivity of the antisera used in the assay , but may also reflect the kinetics of viral sgRNA synthesis , as this is likely to occur after the initial rounds of viral genomic RNA synthesis . VF1 and VP2 expression levels observed over the course of the infection were also significantly different , with VF1 being expressed to a higher degree than VP2 . Whilst this may be a reflection of the differences in the ability of the antisera to detect both proteins , it is known that VP2 synthesis requires translation re-initiation at the end of VP1 [34] which is likely to produce reduced levels of VP2 relative to the other proteins expressed from the viral sgRNA . To determine if VF1 was required for MNV-1 replication in tissue culture we used a recently developed reverse genetics system [22] to truncate the VF1 coding region at various positions . Three mutants were created containing single nucleotide changes that lead to the introduction of a stop codon in the VF1 coding region but which did not alter the VP1 coding sequence ( Figure 3A ) : M1 containing the mutation T5118A truncating the VF1 protein at amino acid 16; M10 containing the mutation T5364A , truncating VF1 at amino acid 98; M20 containing the mutation G5655A , truncating VF1 at amino acid 195 . All mutations were introduced at positions where it was possible to change the VF1 coding sequence without affecting the major capsid protein VP1 . Single nucleotide substitutions were used due to the nature of the overlapping coding regions . The interruption of VF1/ORF4 was confirmed by in vitro coupled transcription and translation of a PCR product encompassing the sgRNA of each mutant compared to wild-type MNV-1 ( Figure 3B ) . VF1 was readily detected after in vitro translation of the wild type sgRNA product as well as the sgRNA from the M20 mutant that encodes a C-terminally truncated form of VF1 . VF1 was not detected after in vitro translation of the sgRNA from either the M1 or M10 VF1 truncations as expected ( Figure 3B ) . Recovery of wild-type and VF1 mutant viruses was performed using fowlpox mediated expression of T7 RNA polymerase to drive the synthesis of MNV-1 RNA in cells transfected with full length cDNA constructs of MNV-1 as described [22] . As we have previously reported , the BHK cell line used during virus recovery , although permissive to virus replication , cannot be infected with MNV due to the lack of a suitable receptor [22] , therefore the yield of virus from this system represents a single round of virus replication only . The initial yields of VF1 knockout or truncation viruses were comparable to that derived from wild-type cDNA ( ∼1–5×104 TCID50 per 35mm dish , data not shown ) , indicative that VF1 was not required for virus replication in tissue culture . Western blot analysis of cells infected with the sequence verified M1 , M10 , M20 viruses confirmed that VF1 was not expressed in cells infected with either M1 or M10 , but low levels of VF1 were observed in M20 infected cells ( Figure 3C ) . The levels of VP2 produced by the VF1 knockout viruses were comparable to the wild-type MNV-1 derived from cDNA , confirming comparative levels of infection ( Figure 3C ) . It is possible that the truncation of VF1 in the mutant M20 results in some protein misfolding , decreasing the half-life of the resulting truncated protein . The growth kinetics of low passage , sequence verified M1 , M10 and M20 viruses was examined by both single-step ( data not shown ) and multi-step growth curve analysis and were indistinguishable from that of the wild-type parental MNV-1 derived from cDNA ( Figure 3D ) , indicating that VF1 is not required for MNV-1 replication in tissue culture . The observation that all MNV isolates identified to date retain ORF4/VF1 and that repeated passage of wild-type virus in tissue culture does not result in the loss of VF1 ( data not shown ) , indicates that although VF1 is not essential for virus replication in tissue culture , it confers some benefit to virus replication . To address this , we examined the stability of the mutations in the M1 , M10 and M20 viruses following repeated low multiplicity of infection ( 0 . 01 TCID50 per cell ) , multi-cycle replication in tissue culture . We observed that the mutations M1 and M10 were under negative selection in tissue culture whereas M20 was stable ( Figure 3E ) . Sequence analysis of the virus population after 5 low multiplicity , multicycle passages in tissue culture , subsequent to the initial amplification after reverse genetics recovery , demonstrated that the M1 virus , which at passage 1 contained the mutation T5118A introducing a stop codon at position 17 in VF1 , had introduced the mutation A5118G by the 5th additional passage , restoring full-length VF1 production by the insertion of a tryptophan residue . Analysis of the M10 virus population , which had the mutation T5364A at the first passage , also indicated that the population was heterogeneous and that in a proportion the VF1 open reading frame was restored by the introduction of the mutation A5364G . As with the M1 virus , this mutation is predicted to result in the introduction of a tryptophan at position 99 . In contrast however , sequence analysis of the M20 virus after repeated multicycle passage in tissue culture demonstrated that the introduced mutation ( G5655A ) was in fact stable ( Figure 3E ) , which may indicate that the major functional domain lay within the 195 amino acids . Western blot analysis of cells infected with ‘passage 5’ stocks of M1 and M10 viruses indicated that , as expected from sequence analysis , VF1 expression was detectable ( Figure 3F ) , although the levels were notably lower than observed in WT infected cells . This reduced level may be in part due to the effect of the amino acid change on VF1 protein stability , but clearly for the M10 virus population the heterogeneous nature of the M10 virus stock ( Figure 3E ) is likely a contributing factor . M20 virus stocks maintained the ability to express low levels VF1 as previously seen using the initial virus stocks ( Figure 3C and 3F ) . In all cases , the level of virus replication was similar as determined by the expression of the minor capsid protein VP2 ( Figure 3F ) and virus titre ( data not shown ) . To gain further insights in the potential function of VF1 , the localization of VF1 was examined by confocal microscopy . Due to the high degree of cross-reactivity of the VF1 antisera with endogenous host cell proteins ( Figure 2B ) , fusions of MNV-1 VF1 to EGFP were used to examine VF1 localization in cells . Transfection of COS7 cells with cDNA constructs expressing either N or C-terminal fusions of MNV-1 VF1 with EGFP demonstrated a pattern of EGFP expression characteristic of mitochondrial localization ( Figure 4A ) . This was confirmed via co-staining of cells with the mitochondrial vital stain Mitotracker ( Invitrogen ) ( Figure 4A ) . Similar co-localization of VF1-GFP and mitochondria was observed in BHK and 293 cells ( data not shown ) . The expression levels observed in cells transfected with the VF1-GFP fusion proteins were substantially lower than those observed in infected cells as expression was not detectable by western blot analysis with either α-VF1 or α-GFP antisera ( data not shown ) . To confirm the mitochondrial localization of VF1 during virus infection , mitochondria were purified from infected RAW264 . 7 cells at 15 hours post infection and analyzed for the presence of VF1 by western blot ( Figure 4B ) . Whereas the well characterized host cell nucleic acid binding proteins PCBP1/2 were shown to be predominantly cytoplasmic as expected [35] , VF1 was only detected in the mitochondrial fraction ( Figure 4B ) . Apoptosis inducing factor 1 , a predominantly mitochondrial protein was enriched in the mitochondrial fraction , confirming the validity of the purification procedure ( Figure 4B ) . RNA viruses frequently encode proteins that antagonize the innate immune response to infection . Mitochondria play a significant role in signaling innate immune responses through the well characterized mitochondrial antiviral signaling protein ( MAVS ) , an integral membrane protein found in the outer mitochondrial membrane [36]–[39] . MAVS is a key adapter protein in the sensing of viral RNA by RIG-I and MDA5 that , in part , leads to IRF3 and NFΚB activation and the upregulation of antiviral genes such as IFN-Beta , CXCL10 and ISG54 [37] . Given the mitochondrial localization of VF1 in infected cells we assessed the activation of this sub-section of the innate immune response in both M1 and WT infected cells . RAW264 . 7 cells infected at a low MOI ( 0 . 1 TCID50 per cell ) with the M1 VF1 knockout virus exhibited a greater induction of antiviral genes such as ISG54 , CXCL10 and IFN-Beta in response to viral infection than those infected with the WT virus ( Figure 5A and Figure 5B ) . Alterations to the levels of mRNA were calculated relative to uninfected cells using the standard ΔΔCT method with hypoxanthine phosphoribosyltransferase 1 ( HPRT ) ( Figure 5A and Figure 5B ) or actin ( data not shown ) mRNA levels used as endogenous controls . CXCL10 , ISG54 and IFN-Beta mRNA levels were then normalized to the amount of viral RNA present in each sample in order to calculate the rate of induction of the innate immune response over time . This method of data normalization was also used to overcome variations often observed in the rate of virus replication seen in a variety of RAW264 . 7 cell clones ( not shown ) . Normalizing the mRNA fold change to a constant amount of MNV RNA established that in all cases examined ( CXCL10 , ISG54 and IFN-Beta ) the M1 infection causes a much more rapid induction of the innate immune response . For instance CXCL10 in M1 infected cells is induced 15 . 5 fold more quickly in response to the same amount of viral RNA than in WT infected cells . This value is calculated by comparing the slope/gradient for M1 and WT ( Figure 5A ) which represents the rate of induction of each gene . Significantly , the IFN-Beta and ISG54 mRNAs are also activated more quickly , 4 . 6 and 8 . 3 fold respectively , in M1 infected cells compared to WT equivalents . Of note , the total fold increase in CXCL10 , ISG54 and IFN-Beta mRNA induced in M1 infected cells was significantly higher than that observed in WT cells at both 20 and 24 hours post infection ( Figure 5A ) . These time points , and the eight hour window from 16 to 24 hpi , reflect the period of amplification for innate immune related gene activation following low MOI MNV-1 infection of RAW264 . 7 cells , since quantification of mRNA fold change at 16 hpi showed little or no increase ( Figure 5A and 5B ) . The activation of the IFN-Beta mRNA in infected cells was also shown to correlate to increased protein production and secretion using ELISA ( Figure 5B ) . The amount of IFN-Beta protein in the supernatants of infected RAW264 . 7 cells was significantly higher in M1 than WT infected cells at 24 hours post infection ( Figure 5B ) . Protein production was again normalized to a constant level of viral RNA to demonstrate the relative response to WT and M1 replication . Treating cells with poly ( I:C ) , and analysis of gene expression , confirmed the sensitivity of RAW264 . 7 cells to dsRNA over an equivalent time course . Induction of ISG54 , CXCL10 and IFN-Beta was demonstrated in poly ( I:C ) treated cells confirming their suitability for the investigation of innate immune responses to RNA stimuli ( Figure S1 ) . In addition , UV inactivated M1 and WT virus showed no significant induction of ISG54 , CXCL10 and IFN-Beta when used in equivalent experiments and compared to mock infected cells ( Figure S1 ) . The IFN-Beta protein secretion in response to poly ( I:C ) and UV inactivated viruses was equivalent to that seen for the mRNA ( Figure S1 ) . This ability of VF1 to antagonize the innate immune response was confirmed independently of infection using an IFN-Beta promoter driven luciferase assay . Murine embryonic fibroblast ( MEF ) cells were co-transfected with plasmid DNA expressing firefly luciferase under the control of an IFN-Beta promoter as well as expression constructs for RIGI , MDA5 , MAVS or TBK1 whose ectopic over-expression has been shown to drive IFN-Beta production [40] . In addition these cells were co-transfected with either the empty vector or a plasmid expressing the MNV-1 VF1 protein . Over-expression of RIG1 , MDA5 , MAVS and TBK1 in cells transfected with the IFN-Beta promoter driven reporter resulted in an expected increase in luciferase production in all cases . However , this induction was significantly reduced in all instances where VF1 was co-transfected in comparison to the empty vector ( Figure 5C ) . This indicates that VF1 in some way antagonizes the induction of IFN-Beta , correlating with the results observed in infected RAW264 . 7 cells . MNV-1 infection is known to result in the induction of apoptosis via the down regulation of survivin , activation of caspases [41] , as well as induction of cathepsin B activity [16] . Given our observation that VF1 localized with mitochondria and the key role mitochondria play in regulating apoptosis , we also examined how the absence of VF1 during infection affected the activity of the executioner caspases 3 and 7 . Proteolytic activation of caspase 3 and 7 , both of which play critical roles in the induction of apoptosis via the intrinsic cellular pathway , was also investigated ( Figure 6A and 6C ) . As previously described [16] , [41] , a rapid increase in caspase 3/7 activity was observed in cells infected with wild type MNV-1 from 12 hours onwards ( Figure 6A ) . Cells infected with MNV-1 lacking VF1 ( M1 ) , displayed significantly higher caspase 3/7 activity at 15 and 18 hours than cells infected with wild type MNV-1 ( Figure 6A ) . Cells infected with the M1 virus lacking VF1 also displayed increased levels of the cleaved caspase 3 at 16 hours post infection ( ∼50% more than WT when quantified by densitometry ) as determined by western blot analysis ( Figure 6C ) . There was a notable alteration to the kinetics of viral protein production in the later stages of virus infection; whereas VP1 and NS7 levels continue to increase from 15 hours onwards in cells infected with WT MNV-1 , the levels observed in cells infected with the M1 virus remained largely constant ( Figure 6B ) . Importantly , the levels of infectious virus produced during infection were identical ( Figure 3D ) . Induction of caspase 3/7 activities was shown to be due to virus replication as prior virus inactivation by UV treatment prevented virus induced caspase activity and the appearance of cleaved caspase 3 ( Figure 6C ) . The observed restoration of VF1 expression in the M1 and M10 viruses after repeated low multiplicity , multi-cycle replication in cell culture indicates that VF1 expression , although not essential for virus replication , confers some benefit to MNV-1 replication in cell culture . To examine if VF1 contributed to virus replication in vivo we examined replication in immunocompetent C57BL/6 mice . Whilst the isolate of MNV-1 used in this study and the only strain for which a reverse genetics system has been developed ( CW1 ) , is attenuated in the presence of a competent innate immune response [6] , [42] , low level virus replication in some tissues can be observed . Mice were inoculated with a high dose of low passage , sequenced verified WT and VF1 knockout viruses ( M1 ) and the effect on body weight examined . As previously reported , no significant effect of MNV infection on weight loss was observed in this genetic background ( Figure 7A ) . We also failed to detect robust levels of viral RNA in the small intestine , feces and spleen over the course of the experiment ( data not shown ) . In contrast however , modest but significant levels of viral RNA were readily detected in the mesenteric lymph nodes of animals infected with WT MNV-1 at days 5 and 7 post infection ( Figure 7B ) . In contrast , viral RNA was not detected in animals inoculated with the VF1 knockout virus M1 . These data suggest that VF1 contributes to virus replication in vivo although virulence per se was not evident in this model even for the WT virus . To examine if VF1 contributes to MNV virulence , the robust STAT1 -/- mouse model for MNV was utilized . However , in order to undertake these studies it was first necessary to generate VF1 mutant viruses in a cDNA backbone virulent in STAT1-/- mice . We have previously demonstrated that the single nucleotide mutation A5941G , changing glutamate 296 to lysine in the major capsid protein VP1 , was sufficient to restore virulence to the tissue culture adapted strain of MNV-1 , which is attenuated in STAT1-/- mice [10] . The VF1 mutation M1 was generated in an MNV-1 cDNA clone bearing two mutations ( G2151A and A5941G ) as this sequence more faithfully represents the consensus sequence in viruses isolated from infected STAT1-/- mice [6 , referred to as CW1 . P1 in 10] . Initial analysis of the levels of virus obtained after reverse genetics recovery of the VF1 mutant virus M1 in the virulent backbone ( referred to herein as M1-v ) , demonstrated identical levels to the wild-type virulent virus ( WT-v ) of approximately 1-5×103 TCID50/ml ( data not shown ) . This suggests that , as observed in the attenuated background , VF1 expression is not essential for MNV-1 replication in the STAT1-/- virulent backbone . To further verify this , multi-cycle growth kinetics analysis of low passage , sequence verified , WT-v and M1-v viruses in RAW264 . 7 cells was performed confirming equivalent growth kinetics ( data not shown ) . The ability of WT-v and M1-v viruses to infect and cause disease in the STAT1-/- mouse model was then examined by oral infection of age and sex matched mice . Oral inoculation of STAT1-/- mice with 1000 TCID50 units of low passage , sequence verified , wild-type virulent MNV-1 derived from cDNA ( WT-v ) resulted in the appearance of clinical signs ( sunken eyes , reduced appetite , hunched inactivity and piloerection ) as early as three days post inoculation . This was followed by a rapid and statistically significant ( P<0 . 001 ) weight loss , when compared to animals inoculated with mock RAW264 . 7 cell lysate ( day 4 onwards ) , and the development of more severe clinical signs culminating in significant weight loss ( Figure 8 ) . All WT-v infected mice succumbed to infection or were euthanized ( because of disease severity limits being surpassed ) by day 7 post infection . In stark contrast mice inoculated with the VF1 mutant virus ( M1-v ) showed a delayed onset of clinical signs . A statistically significant weight loss , compared to the mock-inoculated control group , was not observed until 6 days post infection ( P<0 . 05 , Figure 8 ) . Of note , although the onset of M1-v associated disease was significantly delayed , all M1-v infected animals eventually succumbed to the infection or surpassed the severity limits of our trial . Experiments performed using a 10 fold higher dose ( 10 , 000 TCID50 ) also demonstrated that M1-v inoculated mice displayed a delayed onset of clinical signs including a statistically significant variation in body weight loss ( two-way ANOVA ) . However this variation was markedly less than that observed at the lower infectious dose of 1000 TCID50 ( Figure S2 ) . To examine if the distribution of virus replication differed between animals inoculated with WT-v or M1-v viruses , viral genome copies were quantified in various tissues at 3 and 5 days post infection by quantitative real-time reverse transcription PCR ( qRT-PCR , Figure 9 ) . Whilst >106 genome equivalents ( gEq ) per µg of total RNA could be readily detected in samples from mice infected with WT-v 3 days post infection , viral genome levels in M1-v infected animals were typically 104–105 fold lower ( Figure 9A ) . For example , average levels in the spleen for WT-v infected animals were 1 . 7×109 gEq/µg of total RNA whereas M1-v inoculated animals showed an average of 2 . 6×104 qEq/µg of total RNA . Increased viral RNA replication was detected in all WT-v infected mice at day 5 post infection but only in a subset of the M1-v infected mice ( Figure 9B ) . This subset correlated with those animals that had developed more significant clinical signs and had lost body weight at day 5 post infection . Tissue samples from the spleen , small intestine and liver of mock , WT-v and M1-v infected mice were harvested at day 5 post infection for histopathological analysis on hematoxylin and eosin stained sections ( Figure 10 ) . Tissues from mock-infected mice were relatively normal for STAT1-/- mice ( Figure 10 ) . In contrast the WT-v infected tissues demonstrated reduced cellularity in spleen and liver , with foci of marked necrosis and apoptosis . Necrosis was evidenced by eosinophilia ( dead cells staining bright pink ) with pyknosis ( nuclear condensation ) and karryorrhexis ( pyknotic nuclei become fragmented into several particles ) . Apoptosis was evidenced by cell rounding , a shrunken nucleus and in some cases cell fragmentation with some of the fragments containing apoptotic bodies . Blunting of the intestinal villi , as determined by measuring the villous height on the digital images taken at the same magnification and a comparison carried out on the mean of 8 villi , was apparent only in sections of the small intestine from animals infected with WT-v ( Figure 10 ) . Although the spleen from animals infected with M1-v appeared activated with partial paracortical hyperplasia , it was otherwise normal with little evidence of the necrosis or apoptosis evident in WT-v tissues ( Figure 10 ) . The liver revealed a partial loss of cellularity; however , evidence of apoptosis was again absent ( Figure 10 ) . In conclusion the lack of substantial pathology in M1-v infected mice at 5 days post infection correlated with our previous observations for differential viral RNA replication and weight loss in WT-v and M1-v infected mice . The delayed virulence of VF1 knockout viruses in STAT1-/- mice was suggestive of reversion during replication in vivo . To examine this possibility further , sequence analysis of the viral population from all tissues in two animals displaying the highest degree of clinical signs ( and viral genomes determined by qRT-PCR ) was undertaken . The animals analyzed are highlighted in Figure 8B with a hash and asterisk indicating animals culled on days 5 and 7 respective . The animal culled on day 5 displayed similar disease onset to that of WT-v inoculated animals and had lost ∼12% of its initial body weight . The animal culled on day 7 for sequence analysis was removed from the study due to human end points being exceeded and had lost ∼7 . 6% of its initial body weight . Consensus sequence analysis , which under the conditions used could reproducibly detect reversion when ∼25% of the population had restored VF1 , failed to detect any reversion in any of the tissues ( Figure S3 ) . In addition , tissues/samples containing the highest viral loads ( 4×106 to 4×107 copies per µg of RNA ) , namely the spleen and feces from the day 5 animal and the spleen from the day 7 animal , were PCR amplified and 10 individual clones sequenced . Of the 30 clones sequenced , none contained a mutation in VF1 that would lead to restoration of VF1 expression , further confirming the lack of detectable reversion upon replication a single pass in Stat1-/- mice in vivo ( data not shown ) .
Studies on numerous RNA viruses have identified the use of overlapping open reading frames to maximize the coding capacity of their small RNA genomes [2] . These ORFs and their proteins typically play accessory roles in the viral life cycle such as modulating the host immune response to infection [43]-[45] . Frequently they dispensable for viral replication in immortalized cell lines; however , it is the in vivo setting that the true requirement for these proteins in the viral life cycle is apparent . This study indicates that MNV should now be added to the list of viruses that have adopted this strategy to maximize the coding potential of their genome . Initial bioinformatic investigation of MNV complete genome sequences identified a conserved ORF overlapping with ORF2 ( Figure 1 ) , potentially translated from the sgRNA produced during infection . Traditionally the sgRNA is thought to encode only the major and minor capsid proteins , VP1 and VP2 . However suppression of variability in this region and conservation of the alternate ORF was shown to be absolute in all available MNV sequences ( Table 1 ) . Although the resultant full length protein , VF1 , was recalcitrant to high level expression and poorly immunogenic , polyclonal antibody specific to this protein was generated and used to confirm expression during infection ( Figure 2 ) . The efficient translation of this protein was confirmed by immmunoprecipitation following translation of the sgRNA in vitro ( Figure 2 ) . This is the first confirmation of the expression of an internal open reading frame protein for any member of the Caliciviridae . The internal open reading frame encoding VF1 can be found in all currently published MNV genome sequences , highlighting the requirement for this feature in the MNV genome . The evolutionary conservation of ORF4 coding sequences and the marked suppression of sequence variability localising specifically to the area of overlap ( Figure 1C ) provides evidence independent of the in vitro data for a functional requirement to maintain an intact ORF4 reading frame . As indicated by the analysis of leucine and other synonymous codon usage , this selection pressure was sufficiently strong to drive unfavoured codons into the ORF4 coding sequence ( Figure 1C ) , a feature exploited by MLOGD [33] to detect regions of multiple coding . There were considerable similarities in the arrangement and translation contexts of the ORF2 and ORF4 genes of MNV with documented regions of multiple coding in other viruses . The MNV ORF4 has an initiating AUG triplet at position 5069 in a strong Kozak context ( G at -3 and +4 [46] . It is positioned 13 bases downstream from the first AUG triplet of ORF2 ( weak context; U at -3 , A at +4 ) and 7 from the second ( adequate context; A at -3 and +4 ) . This arrangement of initiating codons in the MNV sgRNA transcripts is similar to viral [47] and eukaryotic [48] dicistronic mRNAs in which alternative weak context initiating codons around an initiating codon in a strong context ( ORF4 in MNV ) can be accessed by random forwards and backwards movements of the ribosome from its initial binding site , termed "leaky scanning" . In this case , this would require a backwards movement to the second AUG triplet of ORF2 , remarkably similar to the documented dicistronic expression of p206 ( strong context ) and p69 ( weak context 7 bases upstream ) from genomic RNA of turnip yellow mosaic virus [47] . This hypothesis is supported by the observation that noroviruses that lack ORF4 ( genogroups 1–4 ) show a strong Kozak context around the second AUG triplet in ORF2 ( A at -3 , G at +4 ) . The evolutionarily conserved nucleotide difference at position 5065 ( +4 ) between MNV ( A ) and other noroviruses ( G ) may thus play a key enabling role in the hypothesised dicistronic expression of ORF4 and ORF2 by MNV . The juxtapositioning of ORF4 at the start of the sgRNA gives an indication of the additional evolutionary constraints that this ORF , and the respective protein , must be under . This region of the genome contains multiple conserved cis-acting RNA elements that play an important role in the viral life cycle ( unpublished observations ) . It is important to note however that the single nucleotide mutation introduced in this region to generate the M1 virus , did not affect the structure of these RNA elements as we have determined biochemically that nucleotide 5118 is positioned within a single-stranded region ( data not shown ) . ORF4 also overlaps with the region of ORF2 that encodes the shell ( S ) domain of the major capsid protein , VP1 . Dimerization of the S domain is thought to be integral for the development of the icosahedral core of the virus particle and is consequently the most conserved domain in VP1 . As the S domain is buried inside the virus particle , it is unlikely to be under strong antibody selection pressure , unlike the more variable C terminus of VP1 which contains the protruding ( P ) domain . The contribution of all these factors is likely responsible for the low divergence observed between MNV VF1 sequences ( Table 1 ) . Within the norovirus genus , ORF4/VF1 appears to be a feature unique to MNV as other noroviruses appear not to encode an equivalent open reading frame . The human noroviruses , which represent a significant cause of viral gastroenteritis in man , do not share the extensive suppression of synonymous site variability at the start of ORF2 that first indicated the presence of ORF4 ( Figure 1C ) [13] . Direct analysis of the available human norovirus sequences confirms that no such ORF exists ( data not shown ) . A broader analysis of the Caliciviridae family indicates the presence of an equivalent open reading frame in some strains of human sapoviruses ( data not shown ) [49] . Although there is low sequence homology between the respective proteins ( 25% similarity , 18% identity ) the presence of this alternative ORF indicates a potential conserved mechanism for maximizing coding potential . It is also possible that a common ancestor of all caliciviruses possessed an equivalent ORF , which has subsequently been lost in the case of the majority of caliciviruses . Although human noroviruses , as well as other members of the Caliciviridae , lack an equivalent ORF4 within the VP1 coding region of the sgRNA , we cannot at this point rule out functional duplication i . e . that the functions of MNV VF1 have been duplicated in human noroviruses by one of the other viral proteins . Further studies are therefore warranted to determine if human noroviruses and other members of the Caliciviridae also possess the ability to modulate the innate immune response . The role of the VF1 protein in MNV-1 replication was examined using the permissive macrophage RAW264 . 7 cell line and the reverse genetics system developed previously in our laboratory [22] . A series of VF1 truncations , generated by inserting stop codons into ORF4 , which importantly left the VP1 coding sequence unaltered , confirmed this protein was a classical viral accessory protein not required for replication . However , repetitive multicycle , low multiplicity of infection passage in the permissive RAW264 . 7 cell line resulted in a phenotypic reversion for the more severe truncations ( M1 and M10 ) ( Figure 3 ) , demonstrating that VF1 expression and function benefits virus replication in cell culture . Whilst this observation was reproducible , it was clear that rapid phenotypic reversion did not occur as virus stocks generated by reverse genetics and subsequently amplified in cell culture by a single passage maintained the introduced mutations . The phenotypic reversion observed was the likely result of the multicycle nature of the infections as very low multiplicity of infections were used , resulting in multiple rounds of virus replication to occur in each pass in cell culture . As the ‘powerhouses’ of the eukaryotic cell , viruses often modulate the function of mitochondria to maintain an intracellular environment beneficial for viral replication . The mitochondrial localization of VF1 ( Figure 4 ) together with its apparent modulation of innate immune signaling and apoptosis ( Figure 5 and 6 ) indicates that this protein may function , like so many other viral proteins , to facilitate viral replication and antagonize anti-viral mechanisms adopted by the cell . The beneficial functions of VF1 expression , e . g . delayed apoptosis and innate immune responses in infected cells , are apparent since analysis of VP1 protein levels produced during infection are clearly reduced at the later stages of infection in the absence of VF1 ( Figure 6B ) . Surprisingly this does not appear to affect the final yield of virus ( Figure 3D ) or the levels of viral RNA produced during replication in RAW264 . 7 cells ( data not shown ) . The RAW264 . 7 murine macrophage cell line is extremely permissive to infection and it is likely that the total pool of available VP1 protein in the M1 infected cells later in infection does not limit virion production . Of relevance is our observation that the IRF3 modulated gene ISG54 , also known as IFIT2 or p54 , is significantly upregulated in cells infected with a virus lacking VF1 ( Figure 5A ) . The ISG54 protein ( p54 or IFIT2 ) functions to repress cellular translation by binding and inhibiting the cellular eIF3c protein [50] . Previous work has indicated that norovirus translation initiation may require the eIF3 complex via a direct interaction of VPg [51] . The expression of the MNV VF1 protein may therefore delay or block the ISG54 mediated inhibition of cellular and viral VPg-dependent translation by preventing the induction of ISG54 mRNA at the point of mitochondrial mediated activation of the innate immune response [51]–[53] . ISG54 expression has also been linked to apoptosis induced via the mitochondrial pathway [54] , again in agreement with our observed increase in apoptosis in the absence of VF1 expression ( Figure 6 ) . It is possible therefore that the increased apoptosis observed during virus replication in the absence of VF1 expression is as a result of the increased induction of the innate immune response . It is well established that MNV is sensitive to an effective innate immune response: type I and II interferon are known to inhibit viral translation [20] , a fact supported by the observed sensitivity of STAT1-/- mice to infection [6] . The role of STAT1 mediated , interferon-based , innate immune signaling in combating MNV-1 infection has been well characterized to prevent the progression of MNV-1 infection and dissemination to peripheral tissues [42] . We also observed this effect in our studies with immunocompetent C56BL/6 mice as only low levels of viral RNA were detected in the MLN ( Figure 7 ) . Previous work has also highlighted that at least part of the innate sensing of MNV infection by the host cell can be attributed to the MDA5 protein [17] . When activated , MDA5 signals the detection of viral RNA through the mitochondrial antiviral signaling ( MAVS ) adapter protein ( also known as IPS-1 , VISA or Cardif ) embedded in the outer membrane of this organelle [36]–[38] . One downstream consequence of these signaling events at the mitochondria is the dimerisation and subsequent nuclear shuttling of IRF3 . This activation of IRF3 results in the trans-activation of genes responsible for combating viral infection including interferon beta . In our studies , the regulation of genes specifically stimulated by virus infection was monitored by qPCR and ELISA and shown to be elevated in cells infected with a virus lacking the VF1 accessory protein ( Figure 5A and Figure 5B ) . This potential role for VF1 as an antagonist of the innate immune response was investigated using co-expression studies with various auto-stimulatory components of this pathway which , after transient over-expression , are known to trigger interferon production ( such as RIG-I , MAVS ) ( Figure 5C ) . In this instance , VF1 was shown to reduce the expression of a reporter protein under the direct transcriptional control of the interferon beta promoter . This occurred at the level of , or subsequent to TBK1 activation , since its stimulation of the IFN promoter was also inhibited by VF1 expression . The mechanism of action of VF1 therefore potentially involves modulation of the interaction of TBK1 with IRF3 , or directly acts on IRF3 itself . Inhibition or degradation of IRF-3 is a frequent target of viral evasion strategies among both RNA and DNA viruses , including the Npro protein of pestviruses [55] , [56] , the P protein of rabies virus [57] and the G1 protein of hantaviruses [58] . Mitochondria also serve as a platform for the activation of IRF3 via TBK1 as the mitochondrial import protein Tom70 , interacts with MAVS upon RNA virus infection and subsequently recruits the TBK1-IRF3 complex via Hsp90 [59] . The interaction of Tom70 with cytosolic chaperone Hsp90 , which is itself constitutively associated with TBK1 and IRF3 , plays a critical role in the activation of IRF3 . Therefore another possible mechanism of VF1 function may be via the modification of the mitochondrial activation pathway or the formation of the MAVS-Tom70-Hsp90 complex . The role of VF1 during in vivo infection was initially examined in a wild type immunocompetent mouse background . However , the strain of MNV-1 used during these studies and the only strain for which a reverse genetics system is currently available , namely CW1 , is attenuated in this model , failing to produce any obvious clinical signs ( Figure 7 ) . It is worth noting however that this variant of MNV-1 , although attenuated in STAT1-/- mice due to a glutamate at position 296 in the major capsid protein VP1 [10] , is actually more representative MNV isolates from immunocompetent mice as they typically also contain glutamate at position 296 [32] . Using this variant of MNV-1 CW1 in this genetic background we observed viral RNA in the mesenteric lymph node at 5 and 7 days post infection with WT MNV-1 but not when animals were infected with a virus lacking VF1 . These data add further strength to our hypothesis that VF1 expression is beneficial to virus replication as it delays the innate immune response and as a consequence , virus induced apoptosis . To examine the role of VF1 in MNV-1 virulence , the M1 VF1 truncation was first engineered into the virulent MNV-1 backbone , previously described by our laboratory [10] . This virus , which represents the closest available progenitor of the original isolate of MNV identified in 2003 , causes a lethal infection in STAT1-/- mice [6] . Typically , one might expect to observe a restoration of virulence after infection of STAT1-/- mice with a virus that lacks an interferon antagonist , in this case VF1 . One of the best-studied examples of this is in influenza virus where the lack of NS1 has no effect on virulence in STAT1-/- mice but in immunocompetent mice a deletion of NS1 results in attenuation [60] . However , In the case of the MNV-1 studies undertaken here , the in vivo analyses are complicated by the already attenuated nature of the strain used ( CW1 ) in an immunocompetent host . Infection of STAT1-/- mice with either 104 or 103 TCID50 of WT-v or M1v demonstrated that MNV-1 lacking VF1 was partially attenuated in this system exhibiting delayed replication kinetics in the murine host ( Figure 7 , 8 , 9 and 10 ) . This manifested as a delay in both the onset of typical MNV-1 disease and the associated presentation of symptoms ( weight loss , piloerection , anorexia , eye discharge that subsequently develop to ataxia , moribundity and death ) . Quantification of the viral RNA genomes in infected tissues at days 3 and 5 post infection , as well as the gross differences in MNV-1 related pathology at day 5 are testament to the debilitated replicative ability of this virus in vivo even in the absence of STAT1 . The exact mechanism of this attenuation is unclear since all the inoculated animals ( M1-v or WT-v ) eventually developed disease and either succumbed to infection or had to be euthanized due to the established humane end points being surpassed . Detailed analysis of the function of VF1 in the avoidance of the innate immune response in vivo is likely to require the development of a reverse genetics system for a MNV variant capable of infecting immunocompetent mice . In the absence of this however , we are able to offer at least one possible explanation as to why we observed clinical disease in the STAT1-/- model even in the absence of VF1 . In STAT1-/- mice , the absence of an intact STAT1-dependent interferon response pathway prevents the generation of robust autocrine and paracrine interferon responses . There are however many examples of virus infection leading to the induction of host genes classically defined as interferon stimulated genes ( ISGs ) in the absence of interferon and/or STAT1 mediated signalling; examples include LCMV [61] where the induction of ISG-49 , ISG-54 , and ISG-56 was observed in the absence of STAT1 , and also HSV-1 which elicits an IRF3-dependent , but IFN-independent cellular antiviral response [62]–[64] . Direct IRF3 mediated responses are also known to protect against West Nile virus infection in both interferon dependent and independent mechanisms [65] . In addition , recent studies have highlighted that STAT2-mediated signalling may stimulate the expression of a subset of ISGs in the absence of STAT1 [66] . Therefore we would propose that during our studies in the STAT1-/- mouse model , it is likely that infection with the virus lacking VF1 leads to the induction of a subset of ISGs during virus replication at the primary site of infection , either directly via an unknown mechanism , or via STAT2 . This limited response may slow virus replication , resulting in the delayed virus replication at the initial site of infection , reduced virus production and delayed onset of disease , all consistent with our observations . We would predict however that this limited response is not sufficient to clear virus after multiple rounds of infection . Our preliminary analysis would confirm that infection of STAT1-/- mice with virulent WT MNV-1 , can result in the induction of ISGs , even in the absence of STAT1 , as we observed increased levels of CXCL10 and ISG54 at 3 days post infection ( Figure S4 ) . The mechanism of ISG induction in the absence of STAT1-mediated signalling and how VF1 contributes to virulence in the absence of STAT1 will require further studies . Expression of accessory proteins from alternate open reading frames can be found in many RNA viruses , many of which parallel the ability of VF1 to antagonize the innate immune system ( discussed in more detail below ) . Many negative strand RNA viruses from the Paramyxovirus genus encode alternative proteins from internal ORFs in the phosphoprotein mRNA . These proteins , denoted C , play multiple roles in the viral life cycle that include the facilitation of RNA replication and control of the innate-immune response [67] . Sendai and measles virus mutants lacking C are viable in tissue culture but partially attenuated in vivo [68] , [69] . This inability to replicate as efficiently as the wild-type virus in vivo is comparable to the observed results in this study for MNV-1 VF1 ( Figure 7 , 8 , 9 and 10 ) . The influenza protein PB1-F2 , another viral protein produced from an alternate open reading frame , provides additional evidence for the role of these accessory proteins in disease [43] , [44] , [70] . PB1-F2 is a recently discovered virulence factor , encoded by the PB1 gene segment , which interacts with mitochondria and stimulates apoptosis by facilitating cytochrome c release via interactions with ANT3 and VDAC1 [71] , [72] . In addition PB1-F2 has been shown to affect influenza polymerase activity in the nucleus , modulate interferon responses during infection and , interestingly , to exacerbate secondary bacterial infections in vivo [71] . Despite the mitochondrial interactions of PB1-F2 , it is unlikely that VF1 functions in an analogous manner since apoptosis was exacerbated in cells infected with a virus lacking VF1 ( Figure 6 ) . A recent report demonstrates a link between the innate immune response and apoptosis suggesting that both MAVS and IRF3 may play direct roles in stimulating apoptosis [73] , [74] . ISG54 expression is also known to induce apoptosis [54] . It is possible that this exacerbation of apoptosis , in the absence of VF1 , is a by-product of enhanced activation of the innate immune response in cells infected with the M1 virus ( Figure 5 and 6 ) or an as yet uncharacterized direct or indirect modification of MAVS function by VF1 . Interestingly , the HCV NS3/4A [75] and SARS-CoV NSP15 protein have been shown to be inhibitors of MAVS mediated apoptosis , identifying these proteins as potential orthologs of VF1 [73] . Other potential ARFP proteins have also recently been shown to associate with the mitochondria [76] as has the L* protein of Theiler's murine encephalomyelitis virus ( TMEV ) [77] . L* is only encoded by the TO subgroup of TMEV viruses where it is required for growth in macrophages and has been implicated in the establishment of persistence and the demyelination associated with TMEV [78] . This macrophage specific requirement for L* is paralleled , albeit to a lesser degree , for MNV VF1 . In our study the M1 and M10 knockout viruses phenotypically reverted upon repeated , low multiplicity , multy cycle replication in the RAW264 . 7 murine macrophage cell line , highlighting that VF1 expression and function confers some benefit to MNV growth in this cell line ( Figure 3E and 3F ) . This benefit is the likely combination of the observed increase in apoptosis and innate immune signalling observed in cells infected with a virus lacking the VF1 protein . Numerous other examples of viral proteins that interact with the mitochondria during infection include the HBV X gene protein whose interactions are thought to stimulate apoptosis and play a role in the development of cancer in affected individuals [79] , the HCMV UL37 protein which is thought to modulate Ca2+ signaling and apoptosis at the mitochondrial ER synapse [80] , as well as three hepatitis virus proteases that have been shown to cleave MAVS ( Hepatitis A , B and C ) , the adapter for RIG1 and MDA5 signaling , thereby antagonizing the innate immune response to infection [81] . Given the critical role that mitochondria play in cellular responses to infection and stress e . g . innate immune signaling , calcium homeostasis and regulation of apoptosis , it is maybe not surprising that so many viruses target this organelle . Our studies have demonstrated that MNV-1 encodes a novel virulence factor from an alternate open reading frame in the sgRNA . This protein localizes to the mitochondria during infection and apparently inhibits the signaling events that take place in and around this organelle during infection of the host cell . This appears to affect the downstream activation of genes regulated by mitochondrial arm of the innate immune response and also the development of apoptosis in response to infection . A mutant virus lacking the ability to express VF1 does not replicate as efficiently in immuncompetent or STAT1-/- mice , which manifests as a delayed onset in the development of disease . However this does not protect the mice from developing serious disease highlighting the sensitivity of this specific model . The role of VF1 in the establishment of persistent MNV infection as well as the exact nature of VF1 interaction with the mitochondria and the mechanism by which this interaction modulates the function of this organelle is the subject of continued research in our laboratory . The identification and preliminary characterization of the MNV-1 VF1 protein provides a unique perspective on this widely used model pathogen and may provide additional insights into the mechanism of norovirus evasion of the immune system .
All of the STAT1-/- animals used in this study were maintained at an American Association of Laboratory Animal Care-accredited animal facility at UTSW Medical Center and the protocol was approved by the IACUC at UT Southwestern Medical Center ( Permit number: 1151 ) . Animal use adhered to applicable requirements such as the Animal Welfare Act ( AWA ) , the Guide for the Care and Use of Laboratory Animals ( Guide ) , the Public Health Service Policy , and the U . S . Government Principles Regarding the Care and Use of Animals . Studies involving C57BL/6 mice were performed at Imperial College London St Mary's Campus ( PCD 70/2727 ) after ethical review by the Imperial College Ethical Review Panel and subsequent approval of the British Home Office ( PPL 70/6838 ) . All animal procedures and care in the UK conformed strictly to the United Kingdom Home Office Guidelines under The Animals ( Scientific Procedures ) Act 1986 . MNV-1 was propagated in the murine leukaemia macrophage cell line RAW264 . 7 using Dulbecco modified Eagle medium ( DMEM ) with 10% fetal calf serum ( FCS ) , penicillin ( 100 U/ml ) , streptomycin ( 100 µg/ml ) and 10 mM HEPES ( pH7 . 6 ) . COS7 and MEF cells were cultured in DMEM ( with FCS and pen/step as above ) . Baby-hamster kidney cells expressing T7 DNA polymerase ( BSRT7 cells ) used during reverse genetics recovery of MNV-1 from cDNA clones , were obtained from Klaus Conzelmann ( Ludwig-Maximilians-University Munich ) [82] and cultured in DMEM ( +FCS and pen/step as above ) containing G418 at a concentration of 1 mg/ml . All cells were maintained at 37°C with 10% CO2 . Repeated attempts to immunize rabbit with full length his-tagged MNV-1 VF1 , purified from E . coli , failed to illicit a robust immune response . Therefore a modified immunization regime that used a combination of peptide immunization followed by booster injections with various recombinant proteins was required . Full details are available upon request , but briefly animals were immunized with the peptide ( PGKLTKLTPGSSKIL ) , representing amino acids 42–56 of VF1 conjugated to KLH , then boosted with the same peptide . This was followed by two subsequent booster injections using full length recombinant his-tagged VF1 expressed in and purified from E . coli . One booster injection with amino acids 42–70 ( PGKLTKLTPGSSKILSSAPLVSFPSRLET ) fused to a Cherry/his tag ( Cherry-VF1-his ) , expressed and purified from E . coli using the Cherry express system ( Eurogentec ) was also performed . Animals were subsequently boosted again with the primary peptide immunogen conjugated to KLH , followed by a final boost with Cherry-VF1-his . VF1 specific antiserum was then affinity purified from sera on a column generated using the initial peptide immunogen . Antisera to the MNV-1 VP2 protein , the product of ORF3 , was generated by immunization of rabbits with full-length recombinant his-tagged protein expressed and purified from E . coli . Note that some batch-to-batch variation of the anti-VP2 antisera was observed resulting in minor differences in the staining intensity of background non-specific bands . In some cases antisera was pre-adsorbed by prior incubation with membranes on which uninfected samples has been run to remove the non-specific reactivity . Antisera to the MNV-1 VP1 protein was kindly supplied by Skip Virgin ( Washington University in St Louis ) and was used as previously described [6] . The following 28 full length genomic sequences were downloaded from GenBank and used for bioinformatic prediction of open reading frames: DQ223042 , EU854589 , EU004665 , FJ446720 , FJ446719 , AB435514 , EU004660 , EU004672 , EU004679 , EU004681 , EU004682 , EU004674 , EF531291 , EU004673 , EF531290 , DQ911368 , EU004683 , EU004670 , EU004668 , EU004663 , EU004671 , EU004664 , EU004677 , EU004676 , DQ223041 , DQ223043 , EU004678 and EU004680 . Sequences were selected based on showing >1% sequence divergence from all other sequences and thus representing different MNV isolates . Synonymous and amino acid variability for each ORF coding sequence were calculated using the program Sequence distance in the Simmonic sequence editor as previously described [13] . Variability at each position was averaged over 11 adjacent windows of 50 codons incrementing by 3 bases/window . MLOGD [33] , [83] was used through the web interface ( http://guinevere . otago . ac . nz/aef/MLOGD/ ) . The MNV phylogeny used to generate the Pairs files was created by PHYLIP version 3 . 62 [84] using DNADIST ( Jukes-Cantor corrected distances ) and NEIGHBOR programs . Likelihood scores were calculated for the existence of ORF4 in addition to ORFs 1 , 2 and 3 ( gene positions 6-5066 , 5056-6678 and 6681-7307 added as annotation ) . 2×107 RAW264 . 7 cells were infected with MNV-1 at a MOI of 5 TCID50 per cell . After 12 h at 37°C , total cell lysates were prepared by washing in PBS and lysing directly into reducing SDS sample buffer . The mitochondria and cytosol of infected cells were separated using a mitochondria isolation kit for mammalian cells ( Thermo scientific ) . The isolated mitochondria were directly suspended into reducing SDS sample buffer whilst due to the high volume the cytosolic fraction was concentrated using the UPPA-protein concentration reagent ( G-Biosciences ) . Fractions were separated on a 15% SDS PAGE gel and analyzed by western blot using antibodies against VF1 . A rabbit antibody against poly rC-binding protein1 and 2 ( PCBP ) acted as a control for the cytosolic fraction and the commercial goat anti-apoptosis inducing factor ( AIF ) antibody ( D-20 from Santa Cruz Biotechnology ) acted as a control for the mitochondrial fraction . VF1 and PCBP were detected using secondary HRPO conjugated anti-rabbit antibodies , whilst AIF was detected using a secondary HRPO conjugated donkey anti-goat antibody ( Santa Cruz Biotechnology ) . VF1 mutant viruses were generated by the insertion of stop codons at various positions within ORF4 , which disrupted VF1 production without affecting the amino acid coding sequence of the major capsid protein VP1 . The mutations were generated in the previously described MNV-1 cDNA clone pT7:MNV 3’Rz [22] by PCR mutagenesis ( primer details available upon request ) using KOD hot start DNA polymerase ( Novagen ) . The VF1 mutant virus M1 contains a stop codon through mutation of T to A at genome position 5118 and hence translation of VF1 terminates after 16 amino acids . The VF1 truncated virus M10 contains a T to A mutation at genome position 5364 terminating VF1 translation after 98 amino acids , and the truncated M20 contains a G to A mutation at genome position 5655 terminating VF1 translation after 195 amino acids . The VF1 expression plasmid pcDNA3 . 1+MNV-1 VF1 was generated by cloning the VF1 encoding sequence into the expression plasmid pcDNA3 . 1+ , which contains a CMV and T7 promoter ( primer details available upon request ) . GFP fusions of VF1 were generated by cloning the VF1 encoding sequence into the GFP plasmids pEGFP-N1 and pEGFP-C1 ( Clontech ) . ORF4 mutant viruses were recovered using reverse genetics as previously described [22] . Briefly , BHK cells expressing T7 polymerase ( BSRT-7 ) were infected with FPV expressing T7 polymerase and were subsequently transfected with the MNV-1 full length clones ( pT7 :MNV 3’Rz ) containing the VF1 mutations M1 , M10 or M20 ( described above ) . 24 h post transfection cells were frozen and the clarified lysates were used to generate passage 1 and 2 stocks by infecting RAW264 . 7 cells at low MOI and freezing 48 hours post infection . The virulent WT and VF1 knockout viruses used in vivo were generated by the same means , although the virus underwent only a single pass in tissue culture to prevent the appearance of the tissue culture adapted mutations at genome positions 2151 and 5941 as described previously [10] . Viral titres were determined by TCID50 titration in RAW264 . 7 cells . Prior to use , all viruses were sequenced to ensure they contained the relevant mutations . RAW264 . 7 cells were seeded at 3 . 2×105 cells per well in a 24-well plate and subsequently infected with the VF1 knockout ( or truncated ) viruses M1 , M10 or M20 at an MOI of 0 . 01 TCID50 per cell . The assay was performed in triplicate for each virus . At given time points ( 0 , 6 , 12 , 24 , 48 , 72 hours post-infection ) the infections were frozen and upon thawing the viral titers were determined by TCID50 . Protein samples over the given time course were also taken to analyze the kinetics of viral protein expression ( data not shown ) . RAW264 . 7 cells were seeded at 3 . 75×106 cells per well of a 6-well dish and were subsequently infected with ORF4 mutant viruses M1 , M10 or M20 at a MOI of 0 . 01 TCID50 per cell . Note that the initial virus stock used for the infections were generated by reverse genetics recovery followed by a single passage in cell culture , so were effectively passage 1 . The ORF4 region of the input viruses was sequenced prior to use . After 48 h the resulting ‘pass 1’ cultures were freeze-thawed and used to set up the subsequent low MOI ( <0 . 01 TCID50 per cell ) infections . Virus passage was continued for 5 cycles after which cells were infected at high MOI and RNA was isolated 12 h post infection . RT-PCR reactions were subsequently used to sequence the region of the genome encompassing ORF4 ( primer details available upon request ) . MEFs were seeded into 12 well dishes and transfected the following day using Lipofectamine 2000 ( Invitrogen ) with a reporter plasmid expressing firefly luciferase under the control of the complete IFN beta promoter . Where appropriate , cells were co-transfected with plasmids expressing VF1 or empty vector ( pcDNA3 . 1 ) along with plasmids expressing cellular proteins ( e . g . RIG-I etc . [85] ) . Empty plasmid was added to ensure each transfection received the same amount of total DNA . To normalize for transfection efficiency and to ensure lack of protein toxicity , the pRLTK Renilla luciferase reporter plasmid was added to each transfection . Samples were lysed 24 hours post transfection in passive lysis buffer ( Promega ) and activity measured using a dual luciferase reporter assay system ( Promega ) as described [85] . In order to analyze the virulence of wild type and VF1 mutant M1 viruses in mice , age ( six to eight weeks , up to16 animals per group ) and sex matched animals were orally inoculated ( oral gavage ) with the WT or the VF1 knockout viruses ( diluted in DMEM to a total volume of 100 µl ) . Control mice ( a group of 6 ) were inoculated with non-infected cell lysates prepared in an identical manner to the virus stocks . Mice were sourced from Taconic ( STAT1 -/- ) or Harlan ( C57BL/6 ) and verified as MNV free at the beginning of the study . Control mice were verified as MNV free at the end of the study confirming barrier controls were effective . At various times post infection post infection tissue samples were taken post mortem . In addition a fecal sample was taken post mortem . All samples were snap-frozen and either stored in Trizol solution ( Invitrogen ) or RNA later ( Ambion ) before the RNA was extracted , as per the manufacturer's instructions . Remaining mice were left for the duration of the experiment or euthanized based on the following humane end points: a 20% loss of bodyweight , the development of severe symptoms ( ataxia , moribundity ) , or the presence of moderate MNV-1 specific symptoms ( continued weight loss , discharge from the eye ) for 3 consecutive days . These limits were set in order to prevent undue suffering to the animal . In accordance with funding regulations and to minimize the number of animals used in these studies , the data for the control and WT-v inoculated groups of animals in Figure 7 has been reported in a previous study [14] . Note that both the previous experiment and that illustrated in Figure 8 were performed side by side . Tissue samples were stored in Trizol reagent ( Invitrogen ) or RNa Later ( Ambion ) and after homogenization RNA was extracted according to the manufacturer instructions . Upon quantification , an aliquot of total RNA from each tissue sample was used for reverse transcription using AMV RT enzyme ( Promega ) and a primer specific for the genomic RNA of MNV-1 ( IC464 , CAAACATCTTTCCCTTGTTC ) . qPCR reactions were prepared using the MESA Blue qPCR MasterMix Plus for SYBR Assay ( Eurogentech ) . Briefly , cDNA was mixed with 2X buffer and primers IC464 and IC465 ( TGGACAACGTGGTGAAGGAT ) prior to activation by incubation at 95°C for 10 min . Reactions were then subjected to 40 cycles of 94°C , 15 sec; 58°C , 30 sec; 72°C , 30 sec . Viral genome copy number was calculated by interpolation from a standard curve generated using serial dilutions of standard RNA representing nucleotides 1085 to 1986 generated by in vitro transcription and extrapolated back to per µg of input RNA . The limit of detection was determined either by the lowest dilution of control standard RNA reproducibly detected in the assay ( Figure 7 ) or by incubating serial dilutions of standard RNA in RNA extracted from the tissues of mock infected animals ( Figure 9 ) . An equivalent protocol was used to determine the genome copy number in RNA samples extracted from infected RAW264 . 7 cells , using 500 ng of input RNA was used . Analysis of mRNA levels in RAW264 . 7 cells was performed at low MOI ( 0 . 1 TCID50 units/cell ) . Cells were seeded at 2×105 cells per well in a 24 well dish , grown overnight at 37°C before being infected . RNA was harvested from infected cells at 16 , 20 and 24 hours post infection using the GenElute RNA extraction kit ( Sigma ) as detailed by the manufacturer . RNA was quantified and diluted to a standard concentration before being reverse transcribed using MuMLV RT enzyme ( Promega ) using an oligo dT primer . SYBR green based qPCR was performed using an ABI 7900 HT real time PCR machine . The MESA Blue ( Eurogentec ) SYBR master mix was combined with sample cDNAs and optimised high efficiency mouse specific primers for the following genes: HPRT , CXCL10 , ISG54 and Interferon Beta ( primer details available upon request ) . Relative mRNA fold change was calculated using the ΔΔCt method e . g . normalising target mRNA levels based on an endogenous control ( HPRT ) before comparison with mock infected cells at equivalent time points . Where appropriate this fold change was then normalised to the level of MNV RNA detected in each sample in order to provide statistical information on mRNA or protein fold induction relative to MNV RNA and allow for the variance in the susceptibility of RAW264 . 7 cell clones to MNV infection ( data not shown ) . Data handling and fold change was calculated using the SDS 2 . 3 and RQ programs from ABI . For the UV inactivation experiments high titre stocks of MNV were cross-linked for 15 minutes under high intensity UV light using a Spectrolinker XL-1500 ( Spectronics Corporation ) . The artificial viral dsRNA analogue poly IC was used to confirm the suitability of RAW264 . 7 as a model for innate immunity , specifically their capacity to sense dsRNA . polyIC was added directly to the media at a final concentration of 25 µg/ml . RNA was harvested at 24 hours post addition and analysed by qPCR as detailed above . Analysis of IFN-Beta protein levels was performed using a murine IFN-B specific ELISA ( PBL Interferon Source ) as per manufacturer's instructions . Supernatants from infected or treated cells were centrifuged for 5 minutes at 2 , 000 rcf before analysis to remove any cellular debris . For apoptosis assays , RAW264 . 7 cells were seeded at 5×105 cells per well of a 24-well plate and grown overnight at 37°C . Cells were infected with an MOI of 5 TCID50 per cell or treated with 5 µM staurosporine ( Sigma ) and at given time points ( 9 , 12 , 15 , 18 and 21 h post infection ) cells were PBS washed and lysed in 1 ml of 1 x cell culture lysis reagent ( Promega ) . 100 µl of lysate was then incubated with 100 µl of Glo3/7 assay reagent ( Promega ) and after incubating at room temperature for 40 minutes , luminescence was read using a TD20/20 luminometer ( Turner Designs ) . Samples were subsequently analyzed for protein content and the luminescence signal normalised to account for variations in the efficiency of cell lysis . Where UV-inactivated virus was used , virus stocks were UV-inactivated on ice for 20 minutes using a UV-crosslinker at 254 nm ( Stratagene ) . Mock treated stocks were used as controls and were simply kept on ice for the same period of time prior to dilution and use in virus infections . Levels of cleaved caspase 3 , were compared by western blot analysis using antibodies from Cell Signalling Technology . Rabbit polyclonal antibodies generated against the viral polymerase ( NS7 ) and major capsid protein ( VP1 ) were used to control for equal amounts of virus , whereas a mouse monoclonal antibody to GAPDH ( Ambion ) was used to ensure equal protein loading . | This report describes the identification and characterization of a novel protein of unknown function encoded by a mouse virus genetically similar to human noroviruses . This gene is unique to the mouse virus and occupies the same part of the genome that codes for the major capsid protein . The protein that we have described as virulence factor 1 ( VF1 ) is found in all murine norovirus isolates , absent in all human strains but is indeed expressed during infection . Its expression enables MNV-1 to establish efficient infection of its natural host through interference with interferon-mediated response pathways and apoptosis . Our data would indicate that the VF1 protein is multi-functional with an ability to modulate the host's response to infection . Murine noroviruses are frequently used firstly as a model to study human norovirus replication and pathogenesis , studies hampered by their inability to replicate in cell culture . Secondly , persistent infection of laboratory animals with murine norovirus may affect other models of disease using experimental mice . The role of VF1 in infection and pathology in the differential outcome of infection is the source of continued research in our laboratory . | [
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] | 2011 | Norovirus Regulation of the Innate Immune Response and Apoptosis Occurs via the Product of the Alternative Open Reading Frame 4 |
The epidemiology of chronic viral infections , such as those caused by Hepatitis C Virus ( HCV ) and Human Immunodeficiency Virus ( HIV ) , is affected by the risk group structure of the infected population . Risk groups are defined by each of their members having acquired infection through a specific behavior . However , risk group definitions say little about the transmission potential of each infected individual . Variation in the number of secondary infections is extremely difficult to estimate for HCV and HIV but crucial in the design of efficient control interventions . Here we describe a novel method that combines epidemiological and population genetic approaches to estimate the variation in transmissibility of rapidly-evolving viral epidemics . We evaluate this method using a nationwide HCV epidemic and for the first time co-estimate viral generation times and superspreading events from a combination of molecular and epidemiological data . We anticipate that this integrated approach will form the basis of powerful tools for describing the transmission dynamics of chronic viral diseases , and for evaluating control strategies directed against them .
Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions [1]–[3] . Central to this endeavour is the basic reproductive number ( R0 ) of an infectious disease , the mean number of secondary infections per primary infection in a completely susceptible population [4] ( for notations see Table 1 ) . Under simple epidemiological scenarios , in which all infected individuals behave identically , R0 depends on the transmission probability per contact with a susceptible individual , the duration of infectiousness and the rate at which new contacts are made [2] , [4] , [5] . However , studies on sexually transmitted and vector-borne infections indicate that infected individuals behave far from identically and that variation in the number of secondary infections per infected individual can play a major role in epidemic dynamics . For example , some researchers have invoked the so-called 20–80 rule to describe the finding that approximately 20% of infected individuals are responsible for 80% of onward transmission [3] , [6] , [7] . The term ‘superspreaders’ has been coined to describe hosts that contribute disproportionately to onward infection . In previous work , variation in the number of secondary infections per infected individual , Z , has been represented by a negative binomial distribution that is described by two parameters , ( i ) mean R0 among infections and ( ii ) the dispersion parameter k [8] , [9] . A small k ( <0 . 1 ) indicates that a small proportion of infected individuals actively transmit the pathogen , whilst a large k ( >4 ) means that all infected individuals contribute approximately equally to onwards transmission [8] , [10] . Lloyd-Smith et al . introduced a definition of superspreaders as the top 1% of hosts when ranked by the number of secondary infections they create [8] . Although superspreading events ( SSE ) ( i . e . the minimum number of secondary infections generated by a superspreader ) have been estimated for directly-transmitted acute infections [8] , they have never been described for chronic viral infections . The indolent and subclinical nature of chronic infections makes it difficult to track primary and secondary infections of the multiple strains that concurrently transmit in a given population . The problem is further compounded for HIV and the hepatitis C virus ( HCV ) that circulate in socially-marginalised groups such as injecting drug users ( IDUs ) and commercial sex workers . In addition to R0 and the variation in onward transmission , another epidemiologically-important parameter is the average time between the primary and secondary infections , typically termed the infection generation time ( T; several other definitions are used in the literature ) . A short T indicates rapid transmission , whilst a longer T suggests slower spread but also longer carriage . The duration of carriage of pathogens , which is usually known , represents an upper-limit on T and thus it is reasonable to conclude that directly transmitted acute infections have T<1 month whilst chronic infections have T values on the order of months or years . Here we show how transmission variability and infection generation time can be estimated by combining viral genomic data with surveillance data and mathematical epidemiology .
The concept of effective population size ( Ne ) has been used in population genetics for at least 50 years ( for a brief review see Text S1 ) [11] , [12] . Ne ( t ) is generally defined as the size of an idealised population ( one without selection or population structure ) that experiences the same level of genetic drift as the studied population at time t . Ne ( t ) is typically lower than N ( t ) , the population's actual size at time t . The ratio N ( t ) /Ne ( t ) thus indicates how similarly the real population's reproduction matches the assumptions of the idealised model [13] , [14] . Under a wide range of scenarios this ratio represents the variation in offspring numbers among individuals [15] , [16] . If the population in question is a viral epidemic , then N ( t ) is the number of infections at time t ( or number of prevalent cases ) and Ne ( t ) represents the effective number of infections ( i . e . the number of infections of an idealised epidemic that experiences the same level of genetic drift as the studied population ) . Crucially , if genetic variation among strains has little or no effect on their ability to infect hosts , as appears to be the case for HIV and HCV [11] then the ratio N ( t ) /Ne ( t ) , is formally equal to var ( Z ) , the variance in the number of secondary infections [17] , [18]: ( 1 ) N ( t ) can be directly observed or estimated from surveillance data using classical epidemiological methods [19] . Ne ( t ) can be estimated by analysing the pattern of genetic diversity in a sample of the viral population . Specifically , methods based on coalescent theory , such as the skyline plot [11] , [20] , estimate the product of the coalescent Ne ( t ) multiplied by T , the generation time . The value var ( Z ) /T is inferable from empirical data and we here call it the phylodynamic transmission parameter , PTP . With all these estimates in hand it is therefore possible to estimate var ( Z ) from equation 1 as follows: ( 2 ) PTP reflects two important features of the intensity of transmission within a population , ( i ) the variance of secondary infections among infections , and ( ii ) time between infections . Equation 2 suggests that an epidemic with a specific PTP is equally well described either by slow and highly variable onward transmission or by fast and more homogeneous onward transmission . This means that by comparing prevalent cases and genetic diversity ( as measured by the skyline plot ) alone , we cannot directly infer var ( Z ) and T; more information is required to separate these parameters . In the next two sections we consider practical aspects of inferring these two variables . Volz and Frost [21] , [22] incorporated mathematical epidemiology in coalescent models assuming that pathogens spread in the population according to compartmental models of epidemic spread . As theory predicts they showed that there is no constant transformation from NeT to N because as susceptible hosts decline in the population , T expands; a constant transformation from NeT to N is observed when the epidemic is on the exponential phase ( i . e . T remains constant ) . Koelle and Rasmussen [23] showed similarly that a linear constant transformation of NeT to N is also observed when the epidemic is within a steady endemic state . Thus , if we compare NeT with N at the exponential phase or the endemic state we can assume that T remains constant . To describe the variability in onward transmission we require a probability density function of the random variable Z , the number of secondary infections per infected individual . Previous work has modeled variation in this number with a negative binomial distribution described by two parameters , mean R0 and a dispersion parameter k [8] , [9] . Chronic viral infections , such as those caused by HIV and HCV , are unlikely to be well described by a single distribution . For these epidemics a significant proportion of transmissions result in inactive infections that transmit the virus no further and thus a mixed distribution is a more realistic representation . In our study we define a sub-population of “inactive” infections whose expected number of secondary infections is equal to 0 . The rest of the population is defined as “active” . Active infections comprise a proportion u of all infections and their expected number of secondary infections are assumed to be Poisson distributed with mean R0 , a . The distribution of the number of secondary infections Z in the whole population ( active and inactive combined ) is therefore a zero-inflated Poisson distribution , such that: ( 3 ) ( 4 ) Equations 3 and 4 can be used to estimate the number of secondary infections of active infections ( R0 , a ) provided that estimates of E ( Z ) , u and var ( Z ) are available . Well-described cohorts of HCV infections ( of subtypes 1a , 1b , 3a and 4a ) have been described in Greek populations [24] , [25] . Crucially , for these epidemics we have both surveillance information and concurrent samples of viral genome sequences from the same population . First , we used inferred HCV incidence and prevalence by subtype from previous studies [25] . Next , we used the skyline plot method to estimate the value Ne ( t ) T for each subtype from the viral genome sequences sampled concurrently from the same populations ( see Table S1 ) [26]–[28] . For both methods we assume that the population corresponds to the set of individuals chronically infected with HCV . The majority of patients with HCV infection develop persistent or chronic infection ( 60–92% ) whilst a minority clears HCV-RNA ( 8–40% ) ; viral clearance is much faster within the first 2 years of infection and slower thereafter ( ≪1% per year ) , while increased rates of viral clearance are associated with younger age , female gender , lack of HIV co-infection , chronic HBV infection and genetic variation in IL28B [29]–[42] . In total , 24 , 27 , 24 and 22 samples from Greek patients were amplified and sequenced for subtypes 1a , 1b , 3a and 4a , respectively ( Table S1 ) . The majority of subtype 1a and 3a infections were associated with injecting drug use , while for subtype 1b and 4a infections the source of infection was usually unknown . These distributions are consistent with previous epidemiological findings [24] . Phylogenetic trees ( Figure S1 ) were estimated using a part of the NS5B region ( nt 8297–8597 ) for which more reference sequences from other locations are available . These revealed the epidemics of different subtypes in Greece are not monophyletic and thus they arose through multiple introductions . Since the outbreaks were not monophyletic we can only provide upper limits of the date of introduction of each subtype ( i . e . the date of the oldest possible introduction ) . Analysis using molecular clock coalescent methods ( Figure 1 , Figure S2 ) indicates that the 1a , 1b , 3a and 4a epidemics first entered the Greek population around 1965 , 1958 , 1975 and 1967 , respectively ( Table S2 ) . It is important to note that the methods developed here depend on the exponential growth phase of each subtype , and not on the date of its most recent common ancestor , as the latter is more sensitive to sampling biases . The most striking difference in epidemic history among the subtypes is the rapid exponential growth of subtype 3a during 1978–1990 , whereas the other subtypes appeared to expand more slowly during 1960–1990 ( Figure 1 ) . For each HCV subtype , the estimated plots of Ne ( t ) T and N ( t ) for each subtype correspond with each other in relative size ( Figure 1a ) , indicating that larger N corresponds to larger NeT . The plots of Ne ( t ) T and N ( t ) for each subtype are also remarkably similar in shape ( Figure 1b ) , indicating that PTP = ( N ( t ) /Ne ( t ) T ) is relatively constant through time . Subsequently , to estimate the ratio N/NeT for each subtype , we assessed the correlation of NeT and N during the period of exponential growth using linear regression ( suppressing the constant term , since theory proposes that N is directly proportional to Ne ) . The correlation of N ( t ) and Ne ( t ) T is thus given by N ( t ) = a Ne ( t ) T , such that a is an estimate of the phylodynamic transmission parameter PTP = ( N/NeT ) . Since all these metrics are time-series data we corrected the cross-correlations between NeT and N for auto-correlation by means of the Newey-West method [43] . Specifically , we assessed the auto-correlation structure for each parameter and each subtype and then used the maximum lag between the cross-correlated data to correct statistical significance . Linear regressions of N ( t ) against Ne ( t ) T for each HCV subtype are strong and significant ( p<0 . 01; R2 = 0 . 70–0 . 95 ) . The regression gradients ( a ) provide estimates of PTP = ( N/NeT ) , which vary from 15 . 6 to 43 . 4 for the different HCV subtypes ( Table 2 , S3 ) . The subtype-specific estimates of mean R0 during the exponential growth phase of Ne or N were 2 . 4–11 . 5 ( Table 2 , Table S3 ) assuming that infectivity period is 40 years and life expectancy is 70 years . These estimates are similar to those reported previously for subtypes 1a and 1b ( both global samples ) and 4a ( sampled from Egypt ) [44] . The expansion of subtype 3a is characterised by faster epidemic growth over a shorter timeframe compared to the other subtypes ( Figure 1 ) and this is reflected in the large R0 value for that subtype , which suggests an average of >10 secondary infections per primary infection . Historically , HCV epidemics have taken two distinct forms: older transfusion and iatrogenic-related transmission , and more recent intravenous drug use-related ( IDU-related ) outbreaks . The earlier transmission was characterised by slower spread; individuals infected by transfusion or nosocomial transmission are less likely to practice high-risk behaviors and thus often represent transmission chain dead-ends . The more recent IDU-related epidemics are characterised by rapid spread . HCV is hyperendemic in IDUs worldwide with anti-HCV prevalence of 15–90% [45]; IDUs may share syringes , needles and other contaminated equipment and are likely to cause long transmission chains [46] , [47] . As explained above , the Z-values of HCV epidemics are thus unlikely to be described well by a single distribution; instead we suggest a bimodal distribution model for the number of secondary infections ( see Eq . 3–5 ) that can represent both types of transmission behavior . We can use Equation 4 to test whether our model is congruent with epidemiological data . Equation 4 predicts that PTP increases with the proportion of “transmitters” in the population of infected individuals ( provided that the proportion of transmitters is <50% , which is the case for all the HCV epidemics in this study ) . Regression of PTP against the percentage of IDU infections for each HCV subtype is strongly significant ( Figure 2 ) whereas the regressions for other risk groups are not ( Table S4 ) . This suggests that the estimates of PTP are compatible with the known epidemiology of HCV . However , we note that this regression contains only 4 points and therefore data from more sub-epidemics are required to strengthen this finding . There is no previously-available estimate for the generation time ( T ) of HCV since tracking of secondary infections is very difficult and date of infection is in most cases unknown . Some workers have suggested approximating T using the duration of infectiousness ( 1/ ( γ+μ ) ) [48] , which for HCV is around 25 years ( i . e 1/γ = 40 years and 1/μ = 70 years ) ( Table S3 ) . If we assume that secondary infections follow a Poisson process within the duration of infectiousness ( 1/ ( γ+μ ) ) ( i . e . if we perform a simulation of random secondary infections within 25 years of infectiousness ) , then the mean average time between primary and the subtending secondary infections is similarly high ( ∼12 . 5 years ) regardless of the average number of secondary infections . Such values are epidemiologically and empirically unrealistic for many HCV epidemics: we know that IDUs usually get infected within 2 years after initiating injection [49] . By combining Equations 2 , 3 4 taking into account that we can investigate how T is dependent on the proportion of the transmitters ( u ) and vice versa ( Table 3 , Figure 3 ) : ( 5 ) We assume that T is constant , which is reasonable for the exponential phase of the epidemic that we focus on [50]–[53] . Equation ( 5 ) shows that T is maximized at the smallest plausible value of u . The known epidemiology of HCV in IDUs suggests that the proportion of the transmitters ( u ) will not be smaller than the proportion of the IDUs ( i . e . every IDU is likely to have transmitted ) , at least in our subtype 1a , 3a and 4a outbreaks , which are driven by intravenous drug use . Thus an epidemiologically-meaningful maximum T value can be obtained by setting u equal to the proportion of IDUs in the population ( Figure 3 ) . Using Greek surveillance data on the proportion of HCV infections of each subtype associated with IDU [24] we estimate that the maximum T ( Figure 3 , Table 3 ) for subtype 1a ( IDU: 26% ) is 1 . 4 years , for subtype 3a ( IDU: 47% ) is 3 . 7 years and for subtype 4a ( IDU: 20% ) is 0 . 9 years . For the iatrogenic ( non IDU-driven ) epidemic of 1b ( IDU:<10% ) we estimate the maximum T close to the approximate duration of infectiousness ( ∼20 years ) [Note that we use IDU as transmitters even if the epidemic is non-IDU driven; this is due to their engagement in repeated paid blood donation up to the end of the 1970s . ] [54] . These estimates of T for subtypes 1a , 3a and 4a are more compatible with the natural history of the disease than those based on the duration of infectiousness ( ∼12 . 5 years ) . The probability of secondary infection per contact is expected to be higher during the first year of infection , when viral load is 10 times greater than later in infection [55] , [56] . Also , in the first year patients are less likely to have ceased or reduced the high-risk behavior ( e . g . IDU ) that led them to be infected . Taken together , this suggests that secondary infections are more likely during the first year of infection . For subtype 1b the estimated T is artificially inflated due to its transmission route ( see below ) . We used equations ( 3 ) and ( 4 ) to estimate the basic reproductive number of the transmitters ( R0 , a ) and the variability in onward transmission , given the values for u , PTP , R0 and T obtained above ( Table 2 ) . We estimate that for HCV subtypes 1a , 1b , 3a and 4a the R0 , a values ranged from 12 to 74 and the 99th percentile SSE from 18 to 83 secondary infections ( Table 2 , Figure 4 , Figure S4 ) . Compared to directly-transmitted pathogens , HCV epidemics generally have large 99th percentile SSE values , at least at the levels of SARS and Smallpox . For outbreaks of subtypes 1a , 1b , 3a and 4a investigated here , we estimate that 80% of the infections are caused by approximately 20% , 5% , 35% and 15% of the most infectious individuals , respectively ( Figure 5 ) . The subtype 1b epidemic is the oldest and most prevalent in Greece , characterised by a small proportion of IDUs ( 6% ) and was spread due to the use of contaminated blood and blood products . The very large number of secondary infections for each member of the transmitter population ( R0 , a = 75 ) , the high degree of superspreading ( SSE 99th percentile = 83 ) and the long generation time ( T∼20 years ) are compatible with the expected transmission dynamics of blood transfusions in the 1960s and 1970s . Historically , subtype 1b infections in Greece are attributed to the use of imported pooled plasma products , a practice that increased the probability of contaminating dozens of individuals from a single contaminated batch; the plasma products could be stored and distributed over many years leading to an artificially large “generation time” . Moreover , within Greece , infected IDUs during the 1960s and 1970s practiced repeated paid blood donations as a source of income . The reported dynamics of HCV-1b are typical of older ( pre-1990s ) HCV epidemics and do not apply to contemporary transmission ( except in rare instances when transfusion safety breaks down . Similar trends in blood transfusion as a risk factor for HCV have been documented in many developed countries [46] , [57]–[60] . On the other hand , the epidemics of subtypes 1a , 3a and 4a epidemics have higher proportions of IDUs ( 26% , 47% and 20% respectively ) [24] and are typical of the modern HCV epidemics in the Western societies . For these epidemics the higher proportion of IDUs resulted in almost proportionally higher mean and variance in the number of secondary infections . The dynamics of these epidemics are still operating in the developed world and the estimated transmission parameters can be used to design mitigating strategies . Phylogenetic analysis suggests the sub-epidemics of HCV in Greece are the result of multiple introductions ( i . e . non-monophyletic; Figure S1 ) suggesting that estimates of Ne ( t ) T near the root of the each subtype phylogeny may be biased upwards ( because lineages fail to coalesce due to population structure ) . Two arguments suggest this is not a significant issue in our analysis . First , the trajectories of N ( t ) and Ne ( t ) T , which were estimated from separate data sources , closely correspond in four independent epidemics ( in scale and shape ) and N was obtained from epidemiological surveillance data of wholly Greek origin . Second , it is reasonable to assume that coalescent events within the exponential phase ( the period during which we compared N ( t ) and Ne ( t ) T ) did occur within Greece . That is , coalescences close to the root of each phylogeny ( which may represent transmission outside Greece ) were not used in our analysis . In the worst case scenario – that Ne ( t ) T has been overestimated – our estimate of PTP can be considered a lower bound and that variation in onward transmission might be even greater than reported here . A second limitation of our study is that our estimate of PTP does not incorporate statistical uncertainty in the estimation of N ( t ) and Ne ( t ) T . In the future , we aim to develop a Bayesian approach to incorporate both sources of uncertainty and provide a proper posterior distribution for PTP . Our approach provides information about superspreading from analytical relationships between the rate of coalescence ( Ne ) , viral generation time ( T ) , and prevalence ( N ) and thus is independent of phylogenetic topology . It is therefore complementary to alternative approaches that investigate how non-random contact structures affect the topology of a transmission tree [61] . At this point we should emphasize that further exploration and extension of the approach is required . For example a zero-inflated Poisson distribution of secondary infections does not fit most of the HIV-1 epidemics . A power-law distribution resulting from sexual-contact analysis would provide a more realistic approximation , for which a detailed analysis of the effect of network structure on PTP needs to be performed . Finally , simulation studies could explore the robustness of the approach under a wider range of epidemiologic scenarios , whilst larger datasets could empirically replicate our findings to support wider applicability of this approach e . g . to inform Public Health policies . We have shown that phylodynamic methods can be combined with epidemiological surveillance data to estimate the variability in ongoing transmission of a chronic viral epidemic , and to investigate its generation time . Both parameters are critical to the design of effective control measures but are very difficult to estimate from surveillance data alone . We tested the framework on a well-characterised set of HCV epidemic in Greece , showing that the results are epidemiologically coherent and suggesting that this approach could be a new tool for public health . We expect our approach to be most readily adapted to other chronic viral diseases such as HIV , but could also be applied to directly transmitted ( e . g . Influenza ) or vector-borne ( e . g . Dengue ) viral epidemics , for which superspreading events and generation times are largely unknown .
Study approval was granted by the IRB of Athens University Medical School . The overall and genotype-specific incidence of chronic HCV infection has been estimated in previous studies using back-calculation [24] , [25] . Briefly , the distribution of transmission risk groups among HCV infected individuals was obtained from 943 Greek patients enrolled in treatment studies [24] , [25] . Enrolment took place between 1995 and 2000; patients were adults ( 18–70 years old ) with a histological diagnosis of chronic hepatitis . Injecting drug use , transfusion , other and sporadic transmissions were reported by 24% , 32% , 6% and 38% of the patients , respectively . The distribution of the dates of infection within each transmission group was determined using data from 456 Greek patients enrolled in treatment studies with known dates of infection . We extended the back-calculation approach to estimate subtype-specific incidence of chronic HCV [25] in Greece as follows: a ) we estimated the number of individuals infected with HCV in Greece , b ) we obtained the distribution of HCV subtypes by year of onset for each transmission group within the infected population and c ) we calculated subtype-specific incidence according to transmission group using the number of new infections in the past for each transmission group and the corresponding distribution of HCV subtypes by year of infection . The estimates for each transmission group were then combined to obtain an estimate of the overall genotype-specific incidence and prevalence during 1940–1990 . Correct sampling is crucial to the inference of epidemic history from genetic data [62] . All available 1a , 1b , 3a and 4a subtype samples from distinct HCV-infected patients , tested within a 12-year period ( 1994–2006 ) , were sorted according to their sampling dates , and at least one sample was randomly selected and sequenced for every 6-month interval . For cases in which no sample was available in a specific 6-month interval , the closest sample to that period was selected . Besides the sampling date , additional information was recorded for each sample: patient's age , sex , transmission group and treatment history ( Table S1 ) . Samples were excluded where the patient had a prior history of antiviral therapy and/or HIV co-infection , since these factors are believed to affect the intrahost evolution of the virus , thus ( theoretically ) introducing a bias into the estimation of substitution rate [63] . Sequencing of the HCV E2P7NS2 and NS5B regions was performed as previously described [26] . We estimated R0 assuming that the population is large enough to follow a deterministic Susceptible-Infected-Removed model ( SIR ) [3]: ( 6 ) where N ( t ) is the number of infected people at time t ( prevalent cases ) , N ( 0 ) is the number of infected people at the baseline of the exponential growth phase , γ is the recovery rate of the disease and μ is the death rate in the general population . This equation is valid for the exponential phase of the epidemic growth . To estimate subtype-specific R0 we used the nl routine in STATA to fit the above equation to the estimated N ( t ) curve during the exponential growth phase , assuming an average life expectancy ( 1/μ ) of 70 years and an average infectivity period ( 1/γ ) of 40 years ( i . e . excluding host mortality ) , which are plausible estimates for the study population ( Table S3 ) . Note that if the N ( t ) and Ne ( t ) are highly correlated ( such that N ( t ) /N ( 0 ) is equal to Ne ( t ) /Ne ( 0 ) ) then equation 6 shows that we can get equivalent estimates of R0 from the skyline plot . . To identify the exponential growth phase of each Greek HCV epidemic , we first defined the end of the exponential phase as 1990 , to reflect the introduction of anti-HCV screening after the virus' discovery in 1989 . The start of the exponential phase was detected using two methods . First , by visually inspecting the epidemic time series and selecting the first time point after 6 years of consecutive increases of N or NeT . Second , we employed a previously-published algorithm used in quantitative PCR experiments , where the identification of the exponential phase of a growth curve is crucial [64] . Both methods provided closely similar results ( ±3 years ) . | To design strategies that efficiently mitigate an epidemic requires estimates of how many people each carrier is likely to infect , what is the variation of this number among infections , and what is the time needed for these transmissions to take place . The disciplines of epidemiology and population genetics independently provide partial answers to these questions by analysing surveillance data and molecular sequences , respectively . Here we propose a novel integration of the two fields that can reveal the underlying transmission dynamics of rapidly-evolving viruses such as HIV or HCV . We explore a well-described nationwide HCV epidemic and show that our method provides new insights into the nature and variation of HCV transmission among infected individuals . We suggest that this approach could form the basis of new tools that can help in the design of effective public health interventions targeting the spread of viral pathogens . | [
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] | 2013 | Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics |
Many enteric pathogens are equipped with multiple cell adhesion factors which are important for host tissue colonization and virulence . Y . enterocolitica , a common food-borne pathogen with invasive properties , uses the surface proteins invasin and YadA for host cell binding and entry . In this study , we demonstrate unique cell adhesion and invasion properties of Y . enterocolitica serotype O:3 strains , the most frequent cause of human yersiniosis , and show that these differences are mainly attributable to variations affecting the function and expression of invasin in response to temperature . In contrast to other enteric Yersinia strains , invasin production in O:3 strains is constitutive and largely enhanced compared to other Y . enterocolitica serotypes , in which invA expression is temperature-regulated and significantly reduced at 37°C . Increase of invasin levels is caused by ( i ) an IS1667 insertion into the invA promoter region , which includes an additional promoter and RovA and H-NS binding sites , and ( ii ) a P98S substitution in the invA activator protein RovA rendering the regulator less susceptible to proteolysis . Both variations were shown to influence bacterial colonization in a murine infection model . Furthermore , we found that co-expression of YadA and down-regulation of the O-antigen at 37°C is required to allow efficient internalization by the InvA protein . We conclude that even small variations in the expression of virulence factors can provoke a major difference in the virulence properties of closely related pathogens which may confer better survival or a higher pathogenic potential in a certain host or host environment .
Yersinia enterocolitica is a common gram-negative zoonotic pathogen that is able to grow in the environment and cause enteric diseases ( Yersiniosis ) , ranging from enteritis , severe diarrhea , mesenteric lymphadenitis , hepatic or splenic abscesses to postinfectious extraintestinal sequelae such as reactive arthritis and erythema nodosum [1] . Infection by Y . enterocolitica is usually initiated through uptake of contaminated food or water . Following ingestion , the bacteria first colonize the lumen and transmigrate through antigen-sampling M cells across the epithelial lining of the small intestine , resulting in the colonization of the underlying lymphoid tissues ( Peyer's patches ) [2] , [3] . Subsequently , Y . enterocolitica can spread via the lymph and/or blood into the mesenteric lymph nodes or to extraintestinal sites such as liver and spleen [4] , [5] , [6] . Alternatively , the bacteria may bypass colonization of the Peyer's patches and spread directly from the intestine to the systemic tissues , similar to what has been observed for enteropathogenic Yersinia pseudotuberculosis [7] , [8] . Adhesion , invasion and survival in deeper tissues depend on several Yersinia virulence factors encoded on the Yersinia chromosome or the 65–70 kb virulence plasmid ( pYV ) [9] . Y . enterocolitica produces at least three invasion factors , invasin , Ail ( attachment-invasion locus ) , and YadA ( Yersinia adhesin A ) which were shown to promote adherence to and invasion into mammalian cells [10] , [11] , [12] . Invasin , the primary invasion factor , binds with high affinity to beta 1 chain integrin receptors found on the surface of M cells but not on the apical side of brush border cells , and mediates efficient and rapid internalization into host cells [13] , [14] . As invasin is strongly expressed at environmental temperature but only weakly at 37°C , it is assumed to support initial colonization and survival of host tissues during the very early stages of an infection [15] , [16] , [17] . Recent studies showed that the dimeric winged-helix transcriptional regulator RovA controls transcription of the invasin gene ( invA ) in response to temperature . For this purpose , RovA uses an in-built thermosensor to control its DNA-binding activity and its susceptibility to the proteolytic degradation by ATP-dependent proteases [18] . After the initiation of the infection , the YadA and Ail proteins seem to be the predominant adhesins in infected tissues . Both virulence factors mediate serum resistance and promote tight adherence to extracellular matrix proteins , such as fibronectin and/or collagen , but their contribution to bacterial uptake is relatively small [19] , [20] , [21] , [22] , [23] , [24] , [25] . The yadA gene is located on pYV and its expression , together with the plasmid-encoded type III secretion system ( Ysc proteins ) and the antiphagocytic effector proteins ( Yops ) is controlled by the VirF ( LcrF ) activator . VirF-dependent induction of yadA , yop and ysc expression occurs exclusively at 37°C [26] , [27] . Ail is also predominantly expressed at 37°C , and regulated by pH and oxygen content , but the control mechanisms are still unclear [24] . Besides the classical pathogenicity factors , other surface factors also contribute or are required for full virulence . Lipopolysaccharides ( LPS ) of Y . enterocolitica serotypes O:3 and O:8 are required for successful colonization of the gut and play an important role in the outer membrane integrity of the bacteria [28] , [29] , [30] . LPS O polysaccharide ( O-antigen ) mutants were attenuated in virulence and impaired in their ability to colonize the Peyer's patches , liver and spleen [30] , [31] . Production of the O-antigen is also temperature-regulated with maximal expression at moderate temperatures [32] , [33] . A complex network regulates O-antigen expression at the transcriptional level and the RosA/RosB efflux pump/potassium antiporter system and Wzz , the O-antigen chain length determinant , are indirectly involved in the temperature-dependent control process [33] . In addition , flagella-dependent motility is required to initiate host cell invasion by ensuring migration and cell contact of the bacteria [34] . Most studies on Y . enterocolitica virulence factors and their contribution to virulence were performed using highly mouse-virulent bioserogroup 1B/O:8 strains , in particular Y . enterocolitica 8081v . However , several other human pathogenic Y . enterocolitica strains which are less virulent in mice ( e . g . serotypes O:3 , O:9 and O:5 , 27 ) were also frequently isolated from patients [1] . Among these strains , Y . enterocolitica bioserotype 4/O:3 is by far the most frequent cause of human yersiniosis in Europe and Japan ( 80–90% ) . Y . enterocolitica infections are less common in North America . However , since the 1980s , serogroup O:3 strains have emerged as an occasional cause of foodborne outbreaks and replaced O:8 as the predominant serotype of Y . enterocolitica reported to CDC [35] , [36] , [37] , [38] . They mainly originate from domestic pigs ( prevalence of 0–65% in fattening pig herds ) , which are often asymptotic carriers , and in which they commonly colonize the lymphoid tissue of the gut and oropharynx [39] , [40] . As only very little is known about the pathogenicity of Y . enterocolitica bioserotype 4/O:3 , we compared host cell interactions of different human- , pig- and food-derived Y . enterocolitica isolates and found that expression and function of surface-exposed virulence factors of serotype O:3 strains differ significantly from other Y . enterocolitica serotypes . This may reflect an adaptation of Y . enterocolitica O:3 to the intestine of pigs which make them also highly pathogenic for humans .
In order to obtain information about interactions of Y . enterocolitica serotype O:3 ( YeO:3 ) strains with host cells , we first investigated the adhesion and invasion efficiency of two reference strains Y11 and YeO3 and 25 different YeO:3 strains isolated from human patients , animals or food between 2005 and 2008 in Germany ( Table S1 ) . None of the serotype O:3 isolates was able to efficiently bind and invade into cultured human epithelial cells when the bacteria were grown at standard culture conditions and similar patterns of host-cell associated bacteria ( adhesion and invasion ) were obtained when infection was performed at 22–25°C or 37°C ( Fig . 1 , S1 , data not shown ) . A prolongation of the infection time from 30 min to 3 hours and/or use of other human , porcine and murine epithelial cell lines did not significantly enhance the efficiency of cell adherence ( data not shown ) , indicating that low-efficiency of adhesion and invasion is independent of the cell line and host species . In contrast , all other tested Y . enterocolitica isolates ( serotypes O:5 , 27 , O:8 and O:9 ) adhered very efficiently and were able to enter all tested epithelial cell lines after 30 min with a frequency ranging from 20–30% depending on the serotype and the isolate ( Fig . 1 , data not shown ) . It is known that motility is an important factor enhancing the invasion efficiency of yersiniae [34] . We tested motility of the YeO:3 strains and found that none of the isolates was motile on swimming and swarming agar plates in contrast to other Y . enterocolitica serotypes , e . g . Y . enterocolitica YeO:8 8081v ( Fig . 2A , data not shown ) . Transmission electron microscopy further revealed that YeO:3 strains are not flagellated ( Fig . 2B , data not shown ) , indicating that flagella synthesis is abolished or does not occur under used growth conditions ( LB , 25°C ) . This phenotype was also observed with YeO:3 strains isolated from liver and spleen of BALB/c mice three days post infection ( data not shown ) . Notably , 30–40% of the bacteria isolated from the intestine were flagellated ( Fig . S2 ) and motile after in vitro cultivation for 24 h ( data not shown ) . However , none of them remained motile and flagellated after 48 h , indicating that the bacteria are motile within the intestinal tract and rapidly repress flagella synthesis when grown on agar plates . It has been assumed that motility enhances the frequency of bacteria-cell interaction and/or provides an additional force for active cell entry . To investigate whether non-invasiveness of the serotype O:3 strains was caused by a reduction of host cell contacts due to amotility , we performed adhesion and invasion assays with or without centrifugation of the bacteria onto host cells ( Fig . 3A ) . When we pre-grew the bacteria at 25°C , adhesion and internalization was slightly increased after centrifugation , but the overall efficiency was still significantly lower compared to YeO:8 8081v . This demonstrated that amotility of the bacteria reduced host cell contact and invasion of YeO:3 grown at 25°C . However , this does not fully explain the observed differences . In this context , we also analyzed host cell adhesion and invasion of bacteria grown at 37°C ( Fig . 3B ) . Without centrifugation , the number of adherent YeO:8 8081v was significantly reduced and no invasion of the bacteria was detectable at 37°C . In contrast , YeO:8 8081v adhered tightly to HEp-2 cells after bacteria were artificially brought into cell contact by centrifugation , but they were not internalized ( Fig . 3B ) . This is consistent with previous studies showing that synthesis of the flagella and the primary internalization factor invasin is repressed at 37°C in Y . enterocolitica 8081v , whereas production of the major adhesion factor YadA is induced at 37°C but not at moderate growth temperatures [15] , [41] . As shown in Fig . 3B , pre-growth at 37°C and artificially induced host cell contact led to a significant raise of cell adhesion of all tested O:3 strains . Notably , only under these conditions efficient host cell invasion of YeO:3 strains was as efficient as cell uptake obtained with YeO:8 8081v grown at 25°C ( 20–30% of adherent bacteria ) . Since efficient cell adhesion and internalization of YeO:3 strains was only achieved after artificial host cell contact , in all following experiments bacteria were centrifugated onto host cells . Based on the previous experiments it seemed possible that an additional thermo-regulated internalization mechanism is responsible for host cell invasion at 37°C . To compare the invasion mechanism used by YeO:3 and YeO:8 strains , we monitored cell entry of YeO:8 8081v grown at 25°C and YeO:3 Y1 grown at 37°C into HEp-2 ( Fig . 4A ) and Caco-2 ( data not shown ) cells by scanning electron microscopy . We found that adherence and invasion of both Y . enterocolitica serotypes showed very common features and were not cell type specific . After host cell binding , the cell surface in the vicinity of the microbes seems to be slightly drawn down , pseudopodia and lamellipodia are formed and the eukaryotic cell membrane then seems to enclose and surround the bacteria into a membrane-bound vacuole . In contrast , no cell adherence of YeO:3 strain Y1 was observed when grown at 25°C , and only simple attachment , but no formation of membrane protrusions was detectable when YeO:8 8081v was precultivated at 37°C ( data not shown ) . This suggested that the internalization mechanism initiated by Y . enterocolitica serotype O:3 and O:8 strains is similar but expressed at different temperatures . In order to test this hypothesis , we analyzed the amount of invasin in both Y . enterocolitica serotypes and found that high amounts of the primary invasion factor invasin were present in all tested YeO:3 strains at 25°C and 37°C , whereas in YeO:8 8081v invasin was only detectable at 25°C , but not at 37°C ( Fig . 5AB ) . Production of invasin in YeO:3 strains at 37°C explains why the invasion rate is significantly enhanced at this growth temperature . However , this also raised the question why no internalization of the bacteria was observed when the bacteria were grown at 25°C , although similar amounts of the invasin protein were produced ( Fig . 3 , 5 ) . To decipher the differences in the host cell invasion properties between the Y . enterocolitica O:3 and O:8 serotype , we first performed adhesion and invasion experiments with E . coli K-12 expressing the invAO:3 and invAO:8 genes and found a similar ability of both invasin proteins to promote cell attachment ( 25% ) and entry ( 5% ) ( data not shown ) . This led to the hypothesis that a temperature-regulated surface structure might block invasin function of YeO:3 strains at moderate growth temperatures . Indeed , composition of the outer membrane and particularly make-up of LPS was shown to be strongly temperature-dependent in Y . enterocolitica [32] . Both the branched outer core hexasaccharide ( OC ) and the homopolymeric O-antigen ( O-Ag ) of the unique YeO:3 LPS are maximally produced below 30°C , whereas only very reduced levels of these LPS components are displayed on the bacterial surface at 37°C [32] . In order to investigate whether they sterically block the access of invasin to host cells , we used different mutant strains of Y . enterocolitica O:3 strain YeO3 deficient in O-Ag formation ( YeO3-R2 ) , OC biosynthesis ( YeO3-OC ) , or both ( YeO3-OCR ) [42] . As shown in Fig . 6A , both O-Ag deficient mutant strains ( YeO3-R2 , YeO3-OCR ) have an increased capacity to interact and enter human epithelial cells , whereas no difference was detectable with the OC knock-out mutant ( YeO3-OC ) . When the adhesion and uptake assays were performed at 37°C , the overall adhesion and invasion levels of the YeO3 wild-type strain were significantly increased and identical to that of YeO:8 8081v grown at 25°C , and no significant differences were observed in the absence of the O-Ag or the OC ( Fig . 6A ) . Notably , differences in host cell interactions did not result from differences in invA or yadA expression as identical amounts of invasin and YadA were detectable in the Y . enterocolitica O:3 wild-type YeO3 and the O-Ag and OC mutants grown at 25°C and 37°C ( Fig . 6B ) . Taken together , these data strongly suggest that the YeO:3 O-Ag reduces host cell interactions at 25°C , most likely through steric hindrance of adhesin/invasin host cell receptor binding . However , this does not seem to be the only reason why YeO3 is less invasive at 25°C than YeO8 8081v , as invasion of the O-Ag mutant strains was still lower compared to invasion of the Y . enterocolitica O:8 strain ( Fig . 6A ) . Besides invasin , also the virulence plasmid-encoded YadA protein promotes tight adhesion of Y . enterocolitica to host cells [43] . We first investigated expression of the yadA gene in response to temperature and found that similar amounts of YadA are produced in all tested Y . enterocolitica O:8 and O:3 strains at 37°C ( Fig . 5B , 6B ) whereas no synthesis could be detected at 25°C ( data not shown ) . Furthermore , we analyzed cell adhesion and internalization of Y . enterocolitica O:3 strain Y1 grown at 25°C or 37°C in the presence and absence of invasin or YadA ( Fig . 7A ) , and confirmed production or loss of adhesins in the equivalent Y . enterocolitica strains ( Fig . 7B ) . Deletion of the invA gene had no effect on host cell binding , but eliminated the ability of the YeO:3 strains to invade human epithelial cells independently from growth temperature . This phenotype was fully complemented by an invA expression plasmid . In contrast , loss of YadA had no effect on host cell invasion and cell adherence at 25°C . However , host cell binding and invasion were significantly reduced when yadA-deficient bacteria were grown at 37°C . Overexpression of the yadA gene under control of an inducible promoter ( PBAD ) complemented this phenotype and increased cell binding and entry levels at 37°C . Even more strikingly , it promoted highly efficient cell adhesion and invasion of bacteria grown at moderate temperature , similar to YeO:8 8081v ( Fig . 7A ) . Thus , co-expression of both adhesins is required to permit efficient cell binding and internalization of serotype O:3 strains into host cells: YadA is needed to maximize adhesion whereas invasin is necessary to initiate the internalization process . Our previous experiments clearly demonstrated that the absence of YadA results in low invasiveness of YeO:3 strains at 25°C , despite the presence of invasin . Yet , invasin expression at 37°C is a special feature of serotype O:3 strains , as it is not produced in other previously characterized Yersinia strains , e . g . YeO:8 8081v ( Fig . 5 ) [15] and Y . pseudotuberculosis [44] . Therefore , we started to elucidate the molecular mechanisms underlying such differences . First , the invA coding and regulatory region of all Y . enterocolitica O:3 isolates used in this study were sequenced and an IS1667 element inserted at position −143 of the invA promoter was identified ( Fig . 8A ) . To address whether presence of the IS1667 insertion is restricted to strains of the same geographic region isolated over a relatively short timeframe , we also sequenced the invA locus of 22 additional Y . enterocolitica O:3 isolates collected from all over the world between 1973 and 2008 ( Table S1 ) . All tested isolates contained the IS1667 element at the same position within the invA regulatory region . To test the influence of the inserted IS element , we compared the activities of the invA promoter of YeO:8 8081v ( PinvO:8 ) and YeO:3 Y1 wild-type ( PinvO:3 ) or after deletion of the IS1667 insertion ( PinvO:3ΔIS ) . We found that integration of the mobile element is accompanied with a much stronger expression of the invA promoter . As shown in Fig . 8B , expression of the PinvO:3ΔIS::luxCDABE and the PinvO:8::luxCDABE fusions were very similar and significantly lower than PinvO:3::luxCDABE expression at 37°C . This result is consistent with a western blotting analysis showing that invasin production is considerably higher in the YeO:3 strains than in YeO:8 strain 8081v at 37°C ( Fig . 5 ) . As the luxCDABE reporter generates a non-linear and often stronger signal than the relative change in transcription , we also performed a quantitative RT-PCR analysis and observed a 6 . 5-fold reduction of relative invA mRNA levels in the ΔIS1667 mutant YE15 compared to the wild-type strain ( Fig . S3 ) . To find out whether higher activation of the invO:3 promoter was due to the insertional inactivation of inhibitory sequences ( e . g . H-NS binding sites ) or to the presence of specific IS sequences different portions of the invA upstream region were deleted and transcription of the PinvO:3::luxCDABE fusion in the Y1 wild-type strain was analyzed . High expression of the PinvO:3::luxCDABE fusion was obtained with deletion constructs harboring sequences upstream of position −448 , whereas PinvO:3 promoter activity was severely reduced with the fusions starting at or downstream from position −248 ( Fig . 8C ) . This demonstrated that the PinvO:3 activity cannot solely be caused by insertional inactivation of inhibitory sequences , and indicated that an IS-encoded function contributes to PinvO:3 activation . In fact , insertion of the IS1667 sequences from position −448 and −144 upstream of the promoterless luxCDABE operon resulted in strong expression of the fusion construct , indicating that an additional promoter ( PIS1667 ) oriented outward of the IS element drives invAO:3 expression ( Fig . 8B ) . In fact , primer extension analyses revealed a strong IS-encoded promoter ( PIS1667 ) with a −35 region located upstream and the −10 region downstream of position −248 . PIS1667 initiated transcription from position −219 with respect to the transcriptional start site of a second promoter ( PinvA ) located within the invA regulatory region ( Fig . 8D , S4 ) . PinvA was equal to the invA promoter of Y . enterocolitica O:8 [15] and exhibited a similar activity when the inserted IS1667 element was deleted ( Fig . 8B ) . Since the IS1667 is inserted into the 3′-end of the binding site I of the transcriptional activator protein RovA ( Fig . 8A ) [45] , [46] , we also analyzed whether invA expression in Y . enterocolitica O:3 strain Y1 is still dependent on RovA . We found that invA mRNA levels and the activity of all highly activated PinvO:3::luxCDABE fusions starting from position −1830 , −1169 and −448 were significantly reduced in the absence of the rovA gene , demonstrating that strong enhancement of invA expression by the IS-encoded promoter still requires the function of the transcriptional activator protein ( Fig . 8C , S3 ) . Previous footprint analysis revealed that RovA interacts with two distinct binding sites of the Y . pseudotuberculosis invA promoter [46] , and sequence homology as well as RovA band shift analysis indicated that similar binding sites are also recognized by RovA in the invA regulatory region of YeO:8 8081v [45] . RovA-binding site I was partially destroyed by the insertion of the IS1667 element in the invAO:3 promoter ( Fig . 9A ) . However , band shift analysis with purified recombinant RovA and different DNA fragments of the invA promoter region demonstrated that RovA still interacts specifically with RovA sequences upstream of the IS1667 element containing major parts of binding site I ( Fig . 9B ) . Interestingly , RovA was also found to specifically interact with fragments harboring the 3′-end ( −342 to −146 ) of the integrated mobile element , although a slightly higher concentration was required for RovA-DNA complex formation . This demonstrated that this portion of the IS1667 element includes sequences , which are also preferentially recognized by RovA . It is very likely that RovA is needed to alleviate H-NS-mediated repression at sites located downstream of the IS1667 insertion ( Fig . 9A ) to permit maximal transcription of the invA promoter . To test this hypothesis , we also studied the interaction of H-NS with different fragments of the invO:3 promoter region . As shown in Fig . 9C , H-NS was able to preferentially interact with a fragment harboring the 3′-portion of the IS1667 element ( −342 to −146 ) , but the affinity was slightly lower compared to H-NS binding to the invA promoter fragment ( −72 to +103 ) . This strongly suggests that RovA is still required to eliminate H-NS mediated repression to allow optimal expression of invasin by the PIS1667 and the PinvO:3 promoter . Requirement of RovA for invA transcription in Y . enterocolitica O:3 at 37°C was unexpected as it has been shown that rovA expression in Y . enterocolitica O:8 and Y . pseudotuberculosis strains is strongly thermoregulated and only expressed at moderate temperatures [44] , [47] . The RovA protein was found to act as a thermosensor which undergoes a conformational change upon a temperature shift from 25°C to 37°C . This thermo-induced conformational change reduces the DNA binding activity of the regulatory protein and renders it more susceptible to proteolysis by the Lon protease [18] . As a result , RovA activation of invA expression is abolished at 37°C . Although RovA was shown to activate invA expression in Y . enterocolitica O:3 ( Fig . 8C ) , invasin expression does not appear to be strongly temperature-regulated compared to other Yersinia strains ( Fig . 5 , 6B [15] , [44] ) . To better understand the different control mechanisms , rovA expression in the different Y . enterocolitica isolates was analyzed . We found that all YeO:3 isolates produced very high levels of RovA at 25°C and 37°C; whereas no RovA was detected at 37°C in other Yersinia strains , e . g . YeO:8 strain 8081v and Y . pseudotuberculosis ( Fig . 5 , data not shown [44] , [47] ) . Expression analysis of the ProvAO:3::lacZ and ProvAO:8::lacZ fusions revealed that both rovA promoters are not auto-activated and are either not or only very weakly dependent on the temperature ( Fig . 10A , S6 ) . Next , we addressed whether thermo-sensing and proteolysis varies between the RovAO:8 and RovAO:3 proteins . We introduced low-copy plasmids carrying the rovAO:3 gene of YeO:3 Y1 or the rovAO:8 gene of YeO:8 8081v into a Y . enterocolitica O:3 rovA mutant strain ( YE12 ) and compared RovA levels after growth at 25°C and 37°C ( Fig . 10B ) . Almost identical levels of the RovA proteins were detected at 25°C . However , significantly lower amounts of the RovAO:8 protein were visible at 37°C , while RovAO:3 concentrations remained almost the same ( Fig . 10B ) . This strongly suggested that post-transcriptional mechanisms controlling RovA levels must be different in YeO:3 strains . To test this hypothesis , we sequenced the rovA locus of all 49 available Y . enterocolitica O:3 strains ( Table S1 ) . We found that the rovA genes of 45 strains , including all isolates tested in this study vary from rovA of other Y . enterocolitica serotypes by a single point mutation in codon 98 , resulting in a P98S change in the amino acid sequence of the translated regulatory protein . To find out whether this substitution affects function of RovA as a thermosensor , we overexpressed and purified RovA of YeO:8 8081v and YeO:3 Y1 and compared their DNA-binding capacity at 25°C and 37°C ( Fig . S5 ) . However , interaction of both RovA variants with DNA fragments of the invA regulatory region was still temperature-dependent . Significantly more of both RovA proteins was required at 37°C for RovA-DNA complex formation , indicating that the thermosensing function is not severely affected by the P98S exchange . Next , we addressed thermo-dependent susceptibility of the RovA variants to degradation by the Lon protease . To this aim , we reintegrated a copy of the rovAO:3 or rovAO:8 gene into the genome of a rovA deficient YeO:3 strain ( YE12 ) and performed stability assays . Identical amounts of RovAO:3 were still visible 90 min after protein biosynthesis was stopped ( Fig . 10C ) . In contrast , the RovAO:8 protein was rapidly degraded at 37°C , and significantly lower amounts of the regulatory protein were detectable 90 min after cessation of protein synthesis . To test the effect of the IS1667 insertion in the invA promoter and the more stable RovAO:3 ( S98 ) variant on host cell invasion , we compared the amount of produced invasin and RovA in YeO:3 strains YE13 ( rovAO:3 ) , YE14 ( rovAO:8 ) and YE15 ( PinvO:3ΔIS ) ( Fig . 11A ) and investigated the efficiency of these bacteria to enter HEp-2 cells ( Fig . 11B ) . High levels of invasin were detectable in YE13 , whereas the instable RovA variant and deletion of the IS1667 element produced lower amounts of invasin , leading to a significant reduction of invasiveness into human epithelial cells . It was previously shown that invasin and RovA are important to invade the intestinal epithelium by Y . enterocolitica O:8 early after infection . The rovA-deficient mutants were found to be attenuated in the ability to reach and/or replicate in the deeper tissues and organs and induce a milder inflammation of the Peyer's patches [48] , whereas the LD50 values of the wild-type and the invA mutant were essentially identical but the colonization of the host tissues was delayed [4] . In order to determine whether higher invasin and RovA levels in Y . enterocolitica O:3 also affect pathogenesis , we tested the virulence of wild-type and mutant strains in the murine infection model . First , single strain infections were performed and bacterial colonization of Peyer's patches ( PPs ) , mesenteric lymphnodes ( MLNs ) , liver and spleen was assessed . Since only minor differences could be highlighted ( data not shown ) , we performed co-infection experiments to determine whether presence of the wild-type affects the ability of the mutants to colonize tissues in a single host . This minimizes inherent inter-animal biological variations and can expose even subtle differences of the biological fitness and virulence , e . g . in the kinetics of infection . BALB/c mice were orally infected with 5×108 bacteria in an inoculum comprised of an equal mixture of ( i ) the parental KanS wild-type strain Y1 ( rovAO:3 ( S98 ) ) and the KanR mutant strain YE14 ( rovAO:8 ( P98 ) ) or ( ii ) Y1 and YE15 ( PinvO:3ΔIS ) harboring a stable vector which only differs in its antibiotic resistance cassette to establish the ability to discriminate strains . Three days after infection , mice were dissected and the numbers of bacteria present in the PPs , MLNs , liver or spleen were determined ( Fig . 12 ) . The results of the infection showed that both , the parental ( YE13 rovAO:3 ( S98 ) ) and the rovAO:8 ( P98 ) mutant strain ( YE14 ) are capable of establishing an infection , but considerably higher numbers of bacteria encoding the less stable RovAO:3 ( P98 ) variant from YeO:8 ( YE14 ) were recovered from all dissected tissues . About 2- to 10-fold more bacteria of this strain were isolated from the lymphatic tissues or the organs ( Fig . 12A ) compared to the parental strain YE13 ( rovAO:3 ( S98 ) ) . Also comparison of the relative virulence ratio ( Fig . 12B ) and calculation of the competitive index of the mutant relative to the wild-type strain ( Fig . 12C ) indicated that higher concentrations of RovA during mouse infections at 37°C are disadvantageous for the colonization and multiplication of YeO:3 in the organs . In contrast , significantly lower numbers of strain YE15 lacking the IS1667 element in the invA promoter region were isolated . About 10–20 times less bacteria were recovered from the PP and MLNs ( Fig . 12A ) . The difference in the dissemination of the bacteria was even more striking . The IS1667 deletion strain YE15 was strongly attenuated in its ability to reach deeper tissues . Only in some occasions it reached the liver and spleen , but the bacterial load of the mutant in the liver and spleen was always significantly lower compared to wild-type ( Fig . 12 ) . In summary , these data strongly indicates that high invasin expression levels during the course of an infection combined with a fine-tuned control of the virulence regulator RovA are advantageous for YeO:3 virulence in mice .
The ability of Y . enterocolitica to bind and invade into host cells is essential for pathogenesis and persistance in its human host . Results of the present investigation highlight important differences in the adhesion properties between serotype O:3 strains ( responsible for more than 70% of human yersiniosis cases ) and other Y . enterocolitica serotypes , e . g . serotype O:8 , whose pathogenicity has been extensively investigated . Comparative analysis of cell binding properties demonstrated that the same repertoire of virulence factors is implicated in host cell binding in the serotype O:3 isolates , but their interplay and expression profile in response to environmental signals is significantly different from O:8 strains ( Fig . 13 ) . We show that synthesis of the primary internalization factor invasin is highly activated and nearly constitutive in all tested Y . enterocolitica O:3 strains . This is in contrast to O:8 serotypes in which invasin synthesis is repressed at 37°C due to H-NS mediated silencing and rapid degradation of the invA activator protein RovA . Interestingly , a previous study also reported that invA expression of a serotype O:9 strain was higher than in serotype O:8 , but it was still significantly reduced at 37°C [49] . Constitutive expression of the invA gene in the O:3 strains was acquired by an IS1667 insertion into the invA regulatory region harbouring RovA and H-NS binding sites . Gene activation by transposons has been described for other genetic systems but the induction mechanism of the Y . enterocolitica O:3 invA gene seems distinct from previously reported systems . Transposable elements usually activate gene expression by replacing a negative regulatory element or through introduction of promoter elements [50] , [51] . One of the best-characterized examples of transposon-mediated gene activation is the beta-glucoside ( bgl ) operon of E . coli . This system is usually repressed but can be activated by IS insertions up- or downstream of the promoter in either orientation relieving H-NS repression [52] , [53] . However , deletion analysis revealed that transposon-mediated invA activation in Y . enterocolitica O:3 is not solely due to disruption of the inhibitory H-NS binding sites , but also requires an IS-specific activating element . One recent study revealed a novel transposon-mediated gene activation mechanism . An IS5 insertion at a single site and in only one orientation was found to activate expression of the glpFK operon in a crp background [54] . A short sequence at the 3′ end of the IS5 transposon , including a permanently bent polyA-tract and an IHF binding site , was shown to be required for glpFK induction . This shows that unique sequences within a mobile element can act as an enhancer or gain an activator binding function sufficient to activate close promoters . In this study we found that IS1667-promoted activation of invA expression in Y . enterocolitca O:3 at 25°C and 37°C is largely dependent on the presence of an IS1667-generated promoter and alternative RovA ( activator ) and H-NS ( silencer ) binding sites . RovA of YeO:8 was previously shown to activate invA expression only at moderate temperatures through antirepression of H-NS-mediated silencing [45] . A temperature upshift to 37°C , however , results in a conformational change within RovA that strongly reduces the DNA-binding capacity of the regulator . It has been previously shown that the apparent dissociation constant ( Kd ) of the thermoregulated RovA protein of Y . pseudotuberculosis is about four-fold increased upon a temperature shift from 25°C to 37°C [18] . Furthermore , it was found that the temperature upshift renders the RovA protein more susceptible to degradation by the Lon and ClpP proteases [18] . Comparable studies with the RovA protein of YeO:8 8081v demonstrated similar properties and identical function as an intrinsic thermosensor ( F . Uliczka , unpublished data ) . Here , we found that a single proline to serine exchange at position 98 ( P98S ) increases the stability of YeO:3 RovA without affecting the thermosensing ability of the protein . As a consequence , significantly higher RovA concentrations are present within the bacteria and this is sufficient to compensate for the thermo-induced reduction of RovA DNA binding . As YeO:3 strains originate mainly from boars and pigs with a higher body temperature of about 39°–40°C , a more temperature-stable RovA variant might be advantageous for persistence in these animals . According to our proposed structure model of RovA [55] the amino acid P98 is located in a surface exposed loop structure and is as such easily accessible for the proteases . How the P98S mutation affects proteolytic degradation is not yet clear . However , comparative CD spectroscopy of purified RovAO:8 ( P98 ) and a RovAO:3 ( S98 ) variant of Y . pseudotuberculosis indicated that no major structural changes are induced by this amino acid substitution ( N . Quade , unpublished results ) . Furthermore , proteolysis is drastically reduced but not completely blocked by the P98S mutation as a slightly higher concentration of the regulatory protein was detected in a Yersinia lon mutant strain . In summary , a more stable RovA variant ( RovAO:3 ( S98 ) ) and an IS1667 insertion in the invA promoter region , providing an additional promoter followed by slightly weaker RovA and H-NS binding sites , allow high expression levels of invasin in YeO:3 strains at 37°C . How these different properties influence pathogenesis is not fully clear , but first experiments addressing host cell invasion and colonization of YeO:3 in the mouse model revealed that loss of the IS1667 element reduced host cell entry and had a severe effect on the infection process in mice . Colonization of the PPs and the MLNs by YeO:3 strain YE15 ( PinvO:3ΔIS ) was significantly reduced and only occasionally these bacteria were able to reach deeper organs in co-infection experiments . This indicates that high levels of invasin are more advantageous and/or important for YeO:3 to initiate a successful infection than for YeO:8 in mice . In fact , a YeO:8 8081v invA mutant strain shows a delayed but still efficient colonization of deeper tissues [4] , [56] . In contrast to invasin , loss of the RovA regulator in YeO:8 8081v leads to a 70-fold increase of the LD50 and causes a much more severe alteration of the infection kinetics , e . g . penetration of the Peyer's patches and mesenterial lymph nodes was much more reduced , and dissemination into liver and spleen was abolished [56] . Interestingly , significantly higher numbers of bacteria could be detected in lymphatic tissues and organs of mice when the unstable variant RovAO:3 ( S98 ) was expressed by YeO:3 . This strongly suggests that elevated RovA levels , although they lead to higher amounts of invasin are disadvantageous for the colonization of the organs in mice . Microarray analysis to define the RovA regulon of Y . enterocolitica in YeO:8 revealed 40 genes to be activated and 23 repressed by RovA [57] . Among the RovA-repressed loci are several metabolic genes , e . g . permeases for glutamine , glutamate and aspartate ) and their upregulation due to reduced RovA levels at 37°C might be important for the biological fitness and survival in host tissues during infection in mice . A more stable but still thermo-sensitive RovA variant , as found in YeO:3 strains ( RovAO:3 ( P98 ) ) , would allow similar regulatory control over virulence and metabolic genes in pigs and boars with a higher body temperature ( 39°C–40°C ) . In order to test whether the IS1667 insertion in the invA promoter region and the RovAO:3 ( S98 ) variant reflects an optimal adaptation to these host organisms we are currently establishing a pig infection model . Although high levels of invasin are produced by YeO:3 strains at moderate growth temperatures , cell invasion was either not initiated or very inefficient when the bacteria were pregrown at 25°C . This is in strong contrast to other Y . enterocolitica serotypes or Y . pseudotuberculosis isolates which enter host cells with their highest efficiency when cultured at moderate temperatures . Previous analyses showed that induced flagellar-dependent motility is required for efficient invasion of YeO:8 , but flagella production of this pathogen is repressed at 37°C [34] . Flagella are needed to ensure migration of the bacteria to host cells , but are not essential for the invasion process once the bacteria contact the mammalian cells . Motility assays and electron microscopy revealed that flagellated and motile strains of Y . enterocolitica O:3 strains can be isolated from the intestinal tract of a mouse , but they rapidly loose their motility and become aflagellated during growth under standard laboratory conditions . As a result , YeO:3 strains are less invasive than other motile serotypes in vitro , but cell entry could be improved upon artificial host cell contact by centrifugation . However , when the bacteria were pregrown at 25°C , YeO:3 uptake after host cell contact is still less efficient compared to YeO:8 or other serotypes , indicating that other factors repress invasin-mediated internalization at moderate temperatures or enhance cell entry at 37°C . Y . enterocolitica isolates grown at room temperature generally express LPS with O-ag , whereas only very small amounts of O-ag are present in bacteria grown at 37°C [33] , [58] . The O-ag of YeO:8 is required for full virulence and plays a major role in pathogen-host interplay by affecting the expression and function of other Yersinia virulence factors , e . g . absence of the O-ag reduced invA expression and internalization into HeLa cells [31] . In contrast , O-ag deficient YeO:3 rough mutants are more efficiently internalized by human epithelial cells . Furthermore , no reduction of invA expression was observed in the rough mutants at 37°C when O-ag expression is fully repressed . Unlike other Yersinia serotypes and other Gram-negative bacteria , the YeO3 O-ag forms a long homopolymer that is linked together with the OC hexasaccharide to the inner core forming a unique branched LPS structure . Its formation was previously shown to prevent proper function of some small size outer membrane proteins . For instance , O-ag was shown to inhibit serum resistance indirectly by masking the adhesin Ail from complement regulator C4bp binding [59] . Therefore , reduced O-ag density in YeO:3 at 37°C is very likely diminishing sterical hindrance thus allowing better access and host cell receptor binding by surface adhesins such as invasin and YadA ( Fig . 13 ) . In fact , besides invasin , also production of the adhesin YadA is required to promote efficient uptake of YeO:3 . The virulence plasmid encoded trimeric YadA protein is highly and exclusively expressed at 37°C , and forms a capsule-like , fibrillar matrix covering the bacterial surface [60] . YadA of Y . enterocolitica O:8 strains has been shown to promote tight binding to extracellular matrix proteins such as collagen and laminin , but it does not contribute to epithelial cell entry compared to invasin [19] , [61] . In fact , at 37°C when YadA is highly expressed but no or only very low levels of invasin are produced by YeO:8 , no internalization of the bacteria is initiated ( Fig . 3B , 6A ) . Internalization of YeO:3 at 37°C also seems to be exclusively mediated by invasin as an invA mutant is unable to enter host cells . Yet , YadA synthesis is not dispensable , as its absence in a yadA mutant or during growth at 25°C results in a significantly lower cell adhesion and uptake rate even in the presence of high amounts of invasin , whereas yadA expression by an inducible promoter at 25°C leads to strong adhesion and efficient invasion of YeO:3 similar to YeO:8 . YadA seems to be required to guarantee tight and efficient host cell binding which then in turn leads to a more efficient invasin-mediated uptake . Both invasin and YadA promote direct or indirect binding to beta 1 integrins [13] , [62] . High affinity binding and ligand-induced beta 1-integrin-clustering by invasin are required for efficient uptake by this host cell receptor family [63] , [64] . However , invasin of Y . enterocolitica does not contain a self-association domain mediating receptor-clustering and uptake in contrast to invasin of Y . pseudotuberculosis [65] . It is therefore tempting to speculate that co-expression of the somewhat longer cell surface adhesin YadA which promotes binding to ECM molecules bound to beta 1 chain integrins promotes or enhances intimate direct interaction of invasin and subsequent internalization ( Fig . 13 ) . In summary , results in the present investigation provide evidence that even small variations between virulence factors and regulators are responsible for the substantial difference in host cell interactions of Y . enterocolitica serotype O:3 in comparison to other Y . enterocolitica serotypes . Serotype O:3 specific variations in the surface molecule expression pattern imply that this Y . enterocolitica subspecies varies in its dynamic capacity to adapt to changing environments and individual niches within the host . A particular repertoire of host interaction genes may confer a survival advantage or pathogenic potential in a specific microenvironment . Thus , an individual subspecies may be better adapted for survival in a particular host or host site , e . g . human gastrointestinal tract or oral cavities of swine ( e . g . tongue and tonsils ) .
All animal work was performed in strict accordance with the German regulations of the Society for Laboratory Animal Science ( GV-SOLAS ) and the European Health Law of the Federation of Laboratory Animal Science Associations ( FELASA ) . The protocol was approved by the Niedersächsisches Landesamt für Verbraucherschutz und Lebensmittelsicherheit: animal licensing committee permission no . 33 . 9 . 42502-04-055/09 . All efforts were made to minimize suffering . The strains used in this study are listed in Table 1 . Overnight cultures of E . coli were routinely grown at 37°C , Yersinia strains were grown at 25°C or 37°C in LB ( Luria-Bertani ) broth . The antibiotics used for bacterial selection were as follows: ampicillin 100 µg/ml , chloramphenicol 30 µg/ml , kanamycin 50 µg/ml , gentamicin 50 µg/ml and tetracycline 10 µg/ml . For infection experiments , bacteria were grown at 25°C or 37°C , washed and diluted in PBS prior to infection . Human HEp-2 cells were cultured in RPMI 1640 media with GlutaMAX ( Invitrogen ) supplemented with 7 . 5% newborn calf serum ( Sigma Aldrich ) at 37°C in the presence of 5% CO2 . Human Caco-2 cells were grown in DMEM/HAM's F-12 ( Biochrom ) supplemented with 10% FBS Superior ( Biochrom ) . All DNA manipulations , PCR , restriction digestions , ligations and transformations were performed using standard techniques as described previously [66] , [67] . Plasmids used in this study are listed in Table 1 , and primers are given in Table S2 . Plasmids pFU49 ( invAO:3 ) and pFU182 ( invAO:8 ) were constructed by amplification of the invA gene from genomic DNA of YeO:3 Y11 and YeO:8 8081v with primers II40/II42 and the PCR-derived fragments were subsequently integrated into the SacI/SalI sites of pBAD33 . For the overexpession of RovAO:8 the rovA gene was amplified from genomic DNA of YeO:8 8081v with primers II417/II418 and the generated fragment was inserted into the NcoI/XhoI sites of pET28a , generating pFU156 . Plasmid pFU157 was obtained by QuikChange mutagenesis of pFU156 using primer II375/II376 . Plasmid pFU199 was constructed by inserting a hns+O:3 fragment amplified with primers II726/II727 into the EcoRI/SalI sites of pASKIBA43+ . For the construction of pFU220 a BamHI/SalI fragment of pFU188 containing the yadA gene was integrated into pBAD33 . pFU188 was obtained by insertion of a PCR fragment amplified with primers II517/II518 from genomic DNA of YeO:3 Y11 into the NcoI/SalI sites of pBAD/Myc-HisA . Plasmids pFU170 and pFU171 encoding the PinvAO:8::luxCDABE and PinvAO:3::luxCDABE reporter fusions were generated by insertion of a PCR fragment amplified with primers II177/II178 from genomic DNA of YeO:8 8081v or YeO3 Y11 in the BamHI/SalI sites of pFU175 . To construct plasmid pFU172 , carrying the PinvAO:3 ΔIS::luxCDABE fusion , two PCR fragments amplified with primer pairs II177/II179 and II180/II178 were first ligated with their blunt ends and cloned into the BamHI/SalI sites of luxCDABE fusion vector pFU175 . Plasmids pFU194–198 were constructed to analyse the effect of promoter PinvAO:3 truncations . This was accomplished by separate cloning of five DNA fragments amplified with primers II542–546 and II178 from genomic DNA of YeO:3 Y11 into the BamHI/SalI sites of pFU175 . Plasmids pFU201 and pFU202 carry the invAO:3 promoter region from position −248 to −146 and from −448 to −146 , respectively , fused to the luxCDABE operon . For their construction PCR fragments were amplified with primer pairs II570/II543 and II571/II543 , respectively , and integrated into the BamHI/SalI sites of pFU175 . The ProvA::lacZ fusions plasmids pFU129 and pFU130 were constructed by insertion of rovA promoter fragments , amplified with primer pair II260/I277 from genomic DNA of YeO:8 strain 8081v or YeO:3 strain Y11 , into the BamHI/SalI sites of pFU109 . Following plasmids were engineered for the construction of rovA , invA and yadA mutant strains of Y . enterocolitica . For rovA mutagenesis , plasmid pFU167 was constructed by amplification of sacB with primers II421/II422 from pJE4 and integration into the AvrII/NotI sites of pFU102 . pFU102 was constructed by insertion of three PCR-derived fragments into the SpeI/NotI sites of pFU100: ( i ) a SpeI/SacI fragment containing 179 bp of the rovA regulatory region amplified with primers II171/II172 , ( ii ) a SacI/AatII fragment encoding the chloramphenicol resistance gene of pZA31 luc , and ( iii ) a AatII/NotI containing 119 bp of the downstream region of rovA amplified with primers II173/II174 . For the invA mutagenesis , plasmid pFU213 was constructed by insertion of the SacI/AatII fragment encoding the kanamycin resistance gene of pZS*24MCS into pFU114 . The plasmid pFU114 was constructed by insertion of an ‘invA’ fragment into the SalI/NotI sites of pFU100 . The PCR fragment contained base pairs 40–339 of the invA coding region , amplified from genomic DNA of YeO:3 Y11 with primer pairs II211/II212 which introduce stop codons at the 5′ and 3′ end in the open reading frame of the ‘invA’ fragment . For yadA mutagenesis , plasmid pFU187 was used . This plasmid was engineered by the insertion of three PCR fragments into the SpeI/NotI sites of pFU167: ( i ) a SpeI/SacI fragment which contained 150 bp of the yadA regulatory region amplified from genomic DNA of YeO:3 Y11 with primer pair II513/II514 ( ii ) a SacI/AatII fragment of pFU32 encoding the tetracycline resistance gene , ( iii ) and a AatII/NotI fragment containing the last 81 bp of the yadA gene plus 69 bp of the yadA downstream region amplified from genomic DNA of YeO:3 Y11 with primer pair II515/II516 . For deletion of the IS1667 element in the invAO:3 regulatory region , we used pFU190 . Plasmid pFU190 was created by the insertion of three fragments . Two fragments starting from position −1887 to −1627 and −249 to −1 of the invA promoter region were amplified with primer pairs II519/II522 and II523/II524 , respectively , and ligated at their blunt ends . The resulting XhoI/NotI fragment was ligated with the SpeI/XhoI fragment from pFU32 harboring the tetracycline resistance cassette and was inserted into the SpeI/NotI sites of pFU167 . Plasmids pFU184 and pFU185 were used for chromosomal integration of a rovA wild-type and a rovAS98P mutant copy . Both plasmids were constructed by insertion of the SacI/AvrII fragment harboring the R6K ori and the mobRP4 mobilization region from pFU100 into pFU119 and pFU138 , respectively . For the generation of pFU119 rovAO:3 including its regulatory region was amplificated from genomic DNA of YeO:3 strain Y11 with primer pair II260/II226 and cloned into the BamHI/NotI sites of pFU109 . pFU138 was obtained by QuikChange mutagenesis ( Stratagene ) of pFU119 using primer II377/II378 . All clones were confirmed by sequencing ( GATC , Konstanz , Germany ) . To construct the rovA , invA , and yadA mutants , the suicide plasmids carrying an internal fragment of invA with integrated stop codons ( pFU213 ) , or the insertion mutations rovA::CmR ( pFU167 ) or yadA::TetR ( pFU187 ) were propagated in E . coli S17-1 λpir and introduced by mobilization into YeO:3 strain Y1 and Y11 . Transconjugants were selected on Yersinia selective agar ( Oxoid ) supplemented with antibiotics , selecting for the resistance of the plasmids . Since the suicide vectors cannot replicate in the YeO:3 strains , the obtained colonies are the result of plasmid integration into the Yersinia chromosome at regions of homology . The recombination event yielded merodiploid strains , which includes a wild-type and a mutant copy . Spontaneous second site recombinants where the integrated suicide vector and the wild-type copy of the gene were eliminated were isolated by selecting fast growing transconjugants on 10% sucrose plates . The rovA gene of YeO:3 ( rovAO:3 ) and YeO:8 ( rovAO:8 ) were introduced into the ΔrovA strain YE12 by conjugation . Loss of the gene function in resulting mutant strains YE1 ( ΔrovA ) , YE12 ( ΔrovA ) , YE18 ( ΔyadA ) and YE21 ( ΔinvA ) and regain of RovA production in strains YE13 ( rovAO:3 ) and YE14 ( rovAO:8 ) was verified by PCR and western blotting analysis . Deletion of the IS1667 element in PinvAO:3 was achieved by conjugation of plasmid pFU190 into YeO:3 strain Y1 as described above . All deletions and reintegration were verified by PCR . Quantitative RT-PCR was performed in triplicate with independent RNA preparations using a Rotor-Gene Q thermo cycler ( Qiagen ) . RNA was prepared using the RNeasy Mini Kit ( Qiagen ) according to the manufacturer's protocol . 1 µg total RNA was taken for cDNA synthesis using the QuantiTect Reverse Transcription Kit ( Qiagen ) according to the manufacturer's instructions . For quantitative RT-PCR , reagents from Qiagen QuantiTect SYBR Green PCR KIT ( Qiagen ) were used . Gene specific-primers used for qRT-PCR amplification are listed in Table S2 and were designed to produce a 120–150 bp amplicon . The amount of PCR product was quantified by measuring fluorescence of SYBR Green dye . Reported gene expression levels were normalized to levels of the 5S rRNA . Standard curves were detected during every run for each gene tested and established by comparing transcript levels in serial dilutions of total RNA from a control sample . Primer extension analysis was performed to determine the transcription start points of the invA gene in strain Y1 . Y . enterocolitica Y1 was grown in LB at 25°C to an OD600 of 3 . 0 ( stationary phase ) . Total RNA was extracted of the samples using the SV total RNA purification kit ( Promega ) as described by the manufacturer . Annealing was performed with 20 µg extracted RNA and the 5′-Dig-labelled oligonucleotides ( primer III94 for the IS1667 specific promoter , primer III91 for the invA promoter ) in 20 µl of 1× First Strand Buffer ( Invitrogen ) by slow cooling of the sample ( 0 . 01°C/sec ) including 8 mM dNTPs and 5× FS Buffer ( Invitrogen ) . 200 U Superscript II reverse transcriptase ( Invitrogen ) was added and incubated for 1 h at 42°C . The size of the Dig-labelled reaction products was determined on a denaturing 4% DNA sequencing gel by a detection procedure as described [68] . Optical density ( OD600 ) of three independent cultures of the bacteria harboring the different luciferase reporter plasmids was determined and diluted to an OD600 of 0 . 1 to monitor growth of the bacteria at indicated growth conditions ( complex media , 25°C and 37°C ) . In parallel , bioluminescence was detected in non-permeabilized cells with a Varioskan Flash ( Thermo Scientific ) using the SkanIt software ( Thermo Scientific ) . Bioluminescence was measured for 1 s every 30 min and is given as relative light units ( RLU/OD600 ) from three independent cultures performed in duplicate . Beta-galactosidase activity was determined as described [44] . The activities were calculated as follows: beta-galactosidase activity OD420 • 6 . 75 OD600−1 • Δt ( min ) −1 • vol ( ml ) −1 . RovA proteins were overexpressed in E . coli BL21 CodonPlus ( DE3 ) -RIL , H-NS was expressed in E . coli KB4 . Overnight cultures of E . coli strains , harbouring the plasmids pFU156 ( rovAO:8-his6 ) , pFU157 ( rovAO:3-his6 ) or pFU199 ( his6-hns ) were diluted 1∶100 and grown at 37°C in LB medium for 2 h . Subsequently , protein synthesis was induced with 100 µM IPTG ( pFU156 , pFU157 ) or 200 µg/l AHT ( pFU199 ) and grown for 4 h . Bacteria overexpressing His-tagged RovA proteins were purified as described [55] . For the analysis of invA and rovA expression bacteria were grown under environmental conditions as described . The optical density of the cultures was adjusted and a 1 ml aliquot was withdrawn from each culture . The cells were collected by centrifugation , and resuspended in 100 µl sample buffer ( 100 mM Tris-HCl pH 6 , 8 , 2% SDS , 10% glycerol , 3% DTT , 0 . 001% bromophenol blue ) and analyzed by gel electrophoresis and western blotting . For the immunological detection of the InvA , YadA and RovA proteins , the cell extracts were separated on 10% or 15% SDS-polyacrylamide gels , and the proteins were separated by electrophoresis and transferred onto an Immobilon membrane ( Millipore ) . Identity and expression of the adhesins were confirmed by westernblotting analysis using polyclonal antibodies against the Y . enterocolitica invasin or the Y . pseudotuberculosis RovA and YadA protein , and a second goat alkaline-phosphate antibody ( Sigma ) using 5-bromo-4-chloro-3-indoylphosphate ( XP ) and nitroblue tetrazolium ( Boehringer Mannheim ) as substrates . Protein biosynthesis of bacterial cultures in exponential phase at 37°C was stopped by adding 50 µg/ml gentamycin and 50 µg/ml tetracycline . Samples were taken at indicated time points . Binding of RovA to defined PCR fragments carrying different portions of the invA regulatory region was carried out in a 20 µl reaction mixture containing increasing amounts of purified RovA protein ( 0 . 5–1 . 5 µg ) and 80 ng of DNA . The reaction buffer contained 10 mM Tris-HCl , pH 7 . 5 , 1 mM EDTA , 50 mM NaCl , 5 mM MgCl2 , 5 mM dithiothreitol ( DTT ) and 5% glycerol . The reaction mixture was incubated for 20 min at room temperature or at 37°C and separated on polyacrylamide gels as described [44] . PCR fragments encoding the invA promoter fragments a , b and c were amplified with primer pairs II519/II551 , II546/II178 and II558/II559 , and the csiD promoter fragment was produced by PCR with primer pairs 131/132 . A 2 µl aliquot of an overnight culture grown at 25°C in LB medium was spotted onto semisolid agar plates containing 0 . 35% agar to evaluate motility [69] . The capacity of YeO:3 Y1 and YeO:8 8081v to spread was monitored after 48 h at 25°C and 37°C . YeO3 Y1 and YeO8 8081v grown at 25°C and 37°C overnight were fixed in growth medium with 1% formaldehyde . For transmission electron microscopy thin carbon support films were prepared by sublimation of carbon on freshly cleaved mica . Using 300 mesh copper grids , the samples were negatively stained with 2% ( w/v ) aqueous uranylacetate , according to the method of [70] , and examined in a transmission electron microscope ( TEM910 , Zeiss , Germany ) at an acceleration voltage of 80 kV at calibrated magnifications . Images were recorded digitally with a Slow-Scan CCD camera ( ProScan 1024×1024 , Scheuring , Germany ) with ITEM software ( Olympus Soft Imaging Solutions , Münster , Germany ) . Images were corrected for brightness and contrast applying Adobe photoshop CS3 . For field emission scanning electron microscopy glass coverslips samples were fixed with a solution containing 5% formaldehyde and 2% glutaraldyhde in cacodylate buffer ( 0 . 1 M cacodylate , 0 . 01 M CaCl2 , 0 . 01 M MgCl2 , 0 . 09 M sucrose pH 6 . 9 ) . Dehydration was carried out in a graded series of acetone ( 10% , 30% , 50% , 70% , 90% , 100% ) on ice for 15 min for each step . Samples were then critical-point dried with liquid CO2 ( CPD 030 , Balzers Union , Liechtenstein ) and covered with a gold film by sputter coating ( SCD 040 , Balzers Union , Liechtenstein ) . For examination in a field emission scanning electron microscope ( DSM 982 Gemini , Zeiss , Germany ) , an Everhart Thornley SE detector was used with the inlens SE detector in a 50∶50 ratio at an acceleration voltage of 5 kV . For cell adhesion and uptake assay 5×104 HEp-2 cells were seeded and grown overnight in individual wells of 24-well cell culture plates . Cell monolayers were washed three times with PBS and incubated in binding buffer ( RPMI 1640 medium supplemented with 20 mM HEPES ( pH 7 . 0 ) and 0 . 4% BSA before the addition of bacteria . Approximately 5×105 bacteria were added to the monolayer and incubated without or after centrifugation of the bacteria onto the monolayer at 22–25°C to prevent bacterial internalization and 37°C to test for cell binding and invasion as described [62] , [71] . 30 min post infection , the cells were washed extensively with PBS . The total number of host cell-associated bacteria was determined by cell lysis using 0 . 1% Triton X-100 and plating on bacterial media . Bacterial uptake was assessed 30 min after infection as the percentage of bacteria , which survived killing by gentamicin , as described [63] . For each strain , the relative level of bacterial adhesion and uptake was determined by calculating the number of colony-forming units relative to the total number of bacteria introduced onto monolayers . Number of invaded bacteria is given relative to the number of cell-bound bacteria . The experiments were routinely performed in triplicate . Bacteria used for oral infection were grown overnight in LB medium at 25°C , washed and resuspended in PBS . Female BALB/c mice 6–8 weeks old were purchased by Janvier . Groups of 7–10 animals were pretreated with desferal 24 h prior infection as described previously [72] . Subsequently , mice were orally infected with Y . enterocolitica strains Y1 , YE15 or YE14 in single infection and co-infection experiments using a ball-tipped feeding needle . 5×108 bacteria of each strain were administered orogastrically . In co-infection experiments , mice were orally infected with an equal mixture of 5×107 ( low dose ) or 5×108 ( high dose ) bacteria of Y . enterocolitica strains Y1 and YE14 , or Y1 and YE15 . For discrimination of strains Y1 and YE15 low-copy vectors pFU99 and pFU109 with different antibiotic resistance cassettes were introduced in Y1 and Y15 , respectively . Presence of these vectors had no effect on Yersinia fitness and virulence and they were maintained in all bacteria recovered from host tissues throughout a five days time course of infection ( F . Uliczka , unpublished results ) . Three or five days after infection , mice were euthanized by CO2 . Peyer's patches , mesenteric lymph nodes , liver and spleen were isolated . The ileum was rinsed with sterile PBS and incubated with 100 µg/ml gentamicin in order to kill bacteria on the luminal surface . After 30 min , gentamicin was removed by extensive washing with PBS for three times . Subsequently , all organs were weighed and homogenized in sterile PBS at 30 . 000 rpm for 30 sec using a Polytron PT 2100 homogenizer ( Kinematica , Switzerland ) . The numbers of bacteria were determined by plating three independent serial dilutions of the homogenates on LB plates with and without antibiotics . The colony forming units ( cfu ) were counted and are given as cfu per g organ/tissue . The competitive index relative to wild-type strain Y1 was calculated as described by Monk et al . 2008 [78] . | Bacterial infections are generally initiated by molecular interactions that occur between the pathogen and its host cell . These interactions are usually mediated by adhesion and invasion factors exposed from the surface of the bacteria which are necessary for the colonization of host tissues and fundamental to pathogenesis . It is well known that many bacterial species contain several different adhesin determinants , which often vary between bacteria of the same species , reflecting the fact that each microbe has adapted to a distinct ecological niche . Here , we show that also small alterations changing the expression pattern of adhesins and virulence gene regulators in response to environmental factors ( e . g . temperature ) lead to fundamental differences in pathogen-host cell interactions and pathogenesis . Modulation of virulence gene expression constitutes an ideal mechanism to adjust virulence-associated processes of pathogens to different hosts ( e . g . with varying body temperature ) as it allows the bacteria to readjust expression of certain gene subsets of regulatory networks controlling virulence , stress and metabolic adaptation to their demands in individual hosts . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"medical",
"microbiology",
"biology",
"microbiology"
] | 2011 | Unique Cell Adhesion and Invasion Properties of Yersinia enterocolitica O:3, the Most Frequent Cause of Human Yersiniosis |
RAVEN is a commonly used MATLAB toolbox for genome-scale metabolic model ( GEM ) reconstruction , curation and constraint-based modelling and simulation . Here we present RAVEN Toolbox 2 . 0 with major enhancements , including: ( i ) de novo reconstruction of GEMs based on the MetaCyc pathway database; ( ii ) a redesigned KEGG-based reconstruction pipeline; ( iii ) convergence of reconstructions from various sources; ( iv ) improved performance , usability , and compatibility with the COBRA Toolbox . Capabilities of RAVEN 2 . 0 are here illustrated through de novo reconstruction of GEMs for the antibiotic-producing bacterium Streptomyces coelicolor . Comparison of the automated de novo reconstructions with the iMK1208 model , a previously published high-quality S . coelicolor GEM , exemplifies that RAVEN 2 . 0 can capture most of the manually curated model . The generated de novo reconstruction is subsequently used to curate iMK1208 resulting in Sco4 , the most comprehensive GEM of S . coelicolor , with increased coverage of both primary and secondary metabolism . This increased coverage allows the use of Sco4 to predict novel genome editing targets for optimized secondary metabolites production . As such , we demonstrate that RAVEN 2 . 0 can be used not only for de novo GEM reconstruction , but also for curating existing models based on up-to-date databases . Both RAVEN 2 . 0 and Sco4 are distributed through GitHub to facilitate usage and further development by the community ( https://github . com/SysBioChalmers/RAVEN and https://github . com/SysBioChalmers/Streptomyces_coelicolor-GEM ) .
Genome-scale metabolic models ( GEMs ) are comprehensive in silico representations of the complete set of metabolic reactions that take place in a cell [1] . GEMs can be used to understand and predict how organisms react to variations on genetic and environmental parameters [2] . Recent studies demonstrated the extensive applications of GEMs in discovering novel metabolic engineering strategies [3]; studying microbial communities [4]; finding biomarkers for human diseases and personalized and precision medicines [5 , 6]; and improving antibiotic production [7] . With the increasing ease of obtaining whole-genome sequences , significant challenges remain to translate this knowledge to high-quality GEMs [8] . To meet the increasing demand of metabolic network modelling , the original RAVEN ( Reconstruction , Analysis and Visualization of Metabolic Networks ) toolbox was developed to facilitate GEM reconstruction , curation , and simulation [9] . In addition to facilitating the analysis and visualization of existing GEMs , RAVEN particularly aimed to assist semi-automated draft model reconstruction , utilizing existing template GEMs and the KEGG database [10] . Since publication , RAVEN has been used in GEMs reconstruction for a wide variety of organisms , ranging from bacteria [11] , archaea [12] to human gut microbiome [13] , eukaryotic microalgae [14] , parasites [15–17] , and fungi [18] , as well as various human tissues [19 , 20] and generic mammalian models with complex metabolism [21 , 22] . As such , the RAVEN toolbox has functioned as one of the two major MATLAB-based packages for constraint-based metabolic modelling , together with the COBRA Toolbox [23–25] . Here , we present RAVEN 2 . 0 with greatly enhanced reconstruction capabilities , together with additional new features ( Fig 1 , Table 1 ) . A prominent enhancement of RAVEN 2 . 0 is the use of the MetaCyc database in assisting draft model reconstruction . MetaCyc is a pathway database that collects only experimentally verified pathways with curated reversibility information and mass-balanced reactions [26] . RAVEN 2 . 0 can leverage this high-quality database to enhance the GEM reconstruction process . While the functionality of the original RAVEN toolbox was illustrated by reconstructing a GEM of Penicillium chrysogenum [9] , we here demonstrate the new and improved capabilities and wide applicability of RAVEN 2 . 0 through reconstruction of a GEM for Streptomyces coelicolor . S . coelicolor is a representative species of soil-dwelling , filamentous and Gram-positive actinobacterium harbouring enriched secondary metabolite biosynthesis gene clusters [27 , 28] . As a well-known pharmaceutical and bioactive compound producer , S . coelicolor has been exploited for antibiotic and secondary metabolite production [29] . The first published GEM for S . coelicolor , iIB711 [30] , was improved through an iterative process resulting in the GEMs iMA789 [31] and iMK1208 [32] . The most recent GEM , iMK1208 , is a high-quality model that includes 1208 genes and 1643 reactions and was successfully used to predict metabolic engineering targets for increased production of actinorhodin [32] . Here , we demonstrate how the new functions of RAVEN can be used for de novo reconstruction of a S . coelicolor GEM , using comparison to the existing high-quality model iMK1208 as benchmark . The use of three distinct de novo reconstruction approaches enabled capturing most of the existing model , while complementary reactions found through the de novo reconstructions gave the opportunity to improve the existing model . After manual curation , we included 402 new reactions into the GEM , with 320 newly associated enzyme-coding genes , including a variety of biosynthetic pathways for known secondary metabolites ( e . g . 2-methylisoborneol , albaflavenone , desferrioxamine , geosmin , hopanoid and flaviolin dimer ) . The updated S . coelicolor GEM is released as Sco4 , which can be used as an upgraded platform for future systems biology research on S . coelicolor and related species .
RAVEN 2 . 0 aims to provide a versatile and efficient toolbox for metabolic network reconstruction and curation ( Fig 1 ) . In comparison to other solutions for GEM reconstruction ( Table 1 ) , the strength of RAVEN is its ability of semi-automated reconstruction based on published models , KEGG and MetaCyc databases , integrating knowledge from diverse sources . A brief overview of RAVEN capabilities is given here , while more technical details are stated in Material & Methods , and detailed documentation is provided for individual functions in the RAVEN package . RAVEN supports two distinct approaches to initiate GEM reconstruction for an organism of interest: ( i ) based on protein homology to an existing template model , or ( ii ) de novo using reaction databases . The first approach requires a high-quality GEM of a phylogenetically closely related organism , and the functions getBlast and getModelFromHomology are used to infer homology using bidirectional BLASTP and build a subsequent draft model . Alternatively , de novo reconstruction can be based on two databases: KEGG and MetaCyc . For KEGG-based reconstruction , the user can deploy getKEGGModelForOrganism to either rely on KEGG-supplied annotations—KEGG currently includes over 5000 genomes—or query its protein sequences for similarity to HMMs that are trained on genes annotated in KEGG . MetaCyc-based reconstruction can be initiated with getMetaCycModelForOrganism that queries protein sequences with BLASTP for homology to enzymes curated in MetaCyc , while addSpontaneous retrieves relevant non-enzyme associated reactions from MetaCyc . Regardless of which ( combination of ) approach ( es ) is followed , a draft model is obtained that requires further curation to result in a high-quality reconstruction suitable for simulating flux distributions . Various RAVEN functions aid in this process , including gapReport that runs a gap analysis and reports e . g . dead-end reactions and unconnected subnetworks that indicate missing reactions and gaps in the model , in addition to reporting metabolites that can be produced or consumed without in- or output from the model , which is indicative of unbalanced reactions . RAVEN is distributed with a gap-filling algorithm gapFill , however , results from external gap-filling approaches can also be readily incorporated . This and further manual curation is facilitated through functions such as addRxnsGenesMets that moves reactions from a template to a draft model , changeGeneAssoc and standardizeGrRules that curate gene associations and combineMetaCycKEGGModels that can semi-automatically unify draft models reconstructed from different databases . In addition to model generation , RAVEN includes basic simulation capabilities including flux balance analysis ( FBA ) , random sampling of the solution space [33] and flux scanning with enforced objective function ( FSEOF ) [34] . Models can be handled in various file-formats , including the community standard SBML L3V1 FBCv2 that is compatible with many other constraint-based modelling tools , including the COBRA Toolbox [23] , as well as non-MATLAB tools as COBRApy [35] and SBML-R [36] . As the SBML file format is unsuitable for tracking changes between model versions support for flat-text and YAML formats are provided . In addition , models can be represented in a user-friendly Excel format . As a MATLAB package , RAVEN gives users flexibility to build their own reconstruction and analysis pipelines according to their needs . The enriched capabilities of RAVEN 2 . 0 were evaluated by de novo generation of GEMs for S . coelicolor using three distinct approaches , as described in Material & Methods ( Fig 2 ) . Cross-comparison of genes from de novo reconstructions and the published S . coelicolor GEM iMK1208 indicated that the three de novo approaches are complementary and comprehensive , combined covering 88% of the genes included in iMK1208 ( Fig 3 ) . The existing model contained 146 genes that were not annotated by any of the automated approaches , signifying the valuable manual curation that has gone into previous GEMs of S . coelicolor . Nonetheless , matching of metabolites across models through their KEGG identifiers further supported that most of the previous GEM is captured by the three de novo reconstructions , while each approach has their unique contribution ( Fig 3 ) . The three draft reconstructions were consecutively merged to result in a combined draft reconstruction ( S1 Data ) , containing 2605 reactions , of which 958 and 1104 reactions were uniquely from MetaCyc- and KEGG-based reconstructions , respectively ( Fig 2 ) . While MetaCyc-based reconstruction annotated more genes than KEGG-based reconstructions ( Fig 3 ) , the number of unique reactions by MetaCyc is slightly lower than by KEGG , indicating that KEGG based reconstruction is more likely to assign genes to multiple reactions . Of the 789 reactions from the existing high-quality model that could be mapped to either MetaCyc or KEGG reactions , 733 ( 92 . 9% ) were included in the combined draft model ( S1 Table ) . The combined de novo reconstruction has a larger number of reactions , metabolite and genes than the previous S . coelicolor GEM ( Fig 2 ) . While a larger metabolic network does not necessarily imply a better network , we took advantage of the increased coverage of the de novo reconstruction by using it to curate iMK1208 , while retaining the valuable contributions from earlier GEMs . The culminating model is called Sco4 , the fourth major release of S . coelicolor GEM . Through manual curation , a total of 398 metabolic reactions were selected from the combined model to expand the stoichiometric network of the previous GEM ( S3 Table ) . These new reactions cover diverse subsystems including both primary and secondary metabolism ( Fig 4A ) and displayed close association with existing metabolites in the previous GEM ( Fig 4B ) . Despite both MetaCyc- and KEGG-based reconstructions contributing roughly equally , MetaCyc-unique reactions are more involved in energy and secondary metabolism , while KEGG-unique reactions are more related to amino acid metabolism and degradation pathways ( Fig 4C ) . The de novo reconstruction annotated genes to 11 reactions that had no gene association in the previous GEM ( S4 Table ) . Together with 34 spontaneous reactions and 10 transport reactions identified by the MetaCyc reconstruction functions ( S5 and S6 Tables ) , the resulting Sco4 model contains 2304 reactions , 1927 metabolites and 1522 genes ( Fig 2 ) . The process of model curation using de novo reconstructions furthermore identified erroneous annotations in the previous GEM . Seventeen metabolites were annotated with invalid KEGG identifiers ( S7 Table ) , impeding matching with the KEGG-based reconstructions . However , by annotating the reactions and metabolites to MetaCyc , we were still able to annotate all 17 metabolites with a valid KEGG identifier , using MetaCyc-provided KEGG annotations . While the KEGG identifiers used in iMK1208 were valid previously , they have since been removed from the KEGG database . Unfortunately , no changelogs are available to trace such revisions . The quality of Sco4 was evaluated through various simulations . It displayed the same performance as iMK1208 in growth prediction on 64 different nutrient sources , with a consistent sensitivity of 90 . 6% ( S8 Table ) . Experimentally measured growth rates in batch and chemostat cultivations were in good correlation with the growth rates predicted by Sco4 ( Fig 5A ) . A recent large-scale mutagenesis study produced and analyzed 51 , 443 S . coelicolor mutants , where each mutant carried a single Tn5 transposition randomly inserted in the genome [37] . No transposition insertions were detected in 79 so-called cold regions of the genome , harboring 132 genes of which 65 are annotated to reactions in Sco4 ( S9 Table ) . The 132 genes are potentially essential , as insertions into these loci would have resulted in a lethal phenotype . However , as it is unclear whether gene essentiality is truly the cause behind the cold-regions , we therefore take the more conservative assumption that genes located outside cold regions are not essential and compared the non-essential gene sets . Simulation with Sco4 indicates a specificity ( or true negative rate ) of 0 . 901 , which is an increase over the 0 . 876 of the previous model ( Fig 5B ) . The S . coelicolor genome project revealed a dense array of secondary metabolite gene clusters both in the core and arms of the linear chromosome ( Bentley et al . 2002 ) , and extensive efforts have been made to elucidate these biosynthetic pathways ( Van Keulen and Dyson , 2014 ) . The previous GEM of S . coelicolor included only three of these pathways ( i . e . actinorhodin , calcium-dependent antibiotic and undecylprodigiosin ) . Through our de novo reconstruction , we captured the advances that have since been made in elucidating additional pathways: Sco4 describes the biosynthetic pathways of 6 more secondary metabolites ( e . g . geosmin ) . These additional pathways were mainly obtained from the MetaCyc-based reconstruction ( Fig 4C ) . The expanded description of secondary metabolism was used to predict potential metabolic engineering targets for efficient antibiotic production in S . coelicolor . Flux scanning with enforced objective function ( FSEOF ) [34] was applied to all secondary metabolic pathways in Sco4 and suggested overexpression targets were compared , with significant overlap between different classes of secondary metabolites ( Fig 6 , S10 Table ) . In addition , several targets were predicted to increase production of all modelled secondary metabolites . Three reactions , constituting the pathway from histidine to N-formimidoyl-L-glutamate , and catalyzed by SCO3070 , SCO3073 and SCO4932 , were commonly identified as potential targets ( S10 Table ) .
The RAVEN toolbox aims to assist constraint-based modeling with a focus on network reconstruction and curation . A growing number of biological databases have been incorporated for automated GEM reconstruction ( Fig 1 ) . The generation of tissue/cell type-specific models through task-driven model reconstruction ( tINIT ) has been incorporated to RAVEN 2 . 0 as built-in resource for human metabolic modeling [19 , 39] . RAVEN 2 . 0 was further expanded in this study by integrating the MetaCyc database , including experimentally elucidated pathways , chemically-balanced reactions , as well as associated enzyme sequences ( 21 ) . This key enhancement brings new features toward high-quality reconstruction , such as inclusion of transport and spontaneous reactions ( Table 1 ) . The performance of RAVEN 2 . 0 in de novo reconstruction was demonstrated by the large overlap of reactions between the automatically obtained draft model of S . coelicolor and the manually curated iMK1208 model [32] . This indicates that de novo reconstruction with RAVEN is an excellent starting point towards developing a high-quality model , while a combined de novo reconstruction can be produced within hours on a personal computer . We used the de novo reconstructions to curate the existing iMK1208 model , and the resulting Sco4 model was expanded with numerous reactions , metabolites and genes , in part representing recent progress in studies on metabolism of S . coelicolor and related species ( Fig 5 ) . We have exploited this new information from biological databases to predict novel targets for metabolic engineering toward establishing S . coelicolor as a potent host for a wide range of secondary metabolites ( Fig 7 ) . Therefore , RAVEN 2 . 0 can be used not only for de novo reconstruction but also model curation and continuous update , which would be necessary for a published GEM to synchronize with the incremental knowledge . We thus deposited the Sco4 as open GitHub repositories for collaborative development with version control . While RAVEN 2 . 0 addresses several obstacles and significantly improves GEM reconstruction and curation , a number of challenges remain to be resolved . One major obstacle encountered is matching of metabolites , whether by name or identifier ( e . g . KEGG , MetaCyc , ChEBI ) . Incompatible metabolite nomenclature , incomplete and incorrect annotations all impede fully automatic matching and rather requires intensive manual curation , especially when comparing and combining GEMs from different sources . Efforts have been made to address these issues , e . g . by simplifying manual curation using modelBorgifier [40] . Particularly worth noting is MetaNetX [41] , where the MNXref namespace aims to provide a comprehensive cross reference between metabolite and reactions from a wide range of databases , assisting model comparison and integration . Future developments in this direction ultimately leverage this information to automatically reconcile metabolites and reactions across GEMs . Another major challenge is evaluation and tracking of GEM quality . Here we evaluated Sco4 with growth and gene essentiality simulations ( Fig 5 , S8 Table , S9 Table ) , however , the GEM modelling community would benefit from such and additional quality tests according to community standards . Exciting ongoing progress here is memote: an open-source software that is under development that contains a community-maintained , standardized set of metabolic model tests [42] . Given the YAML export functionality in RAVEN already supports convenient tracking of model changes in a GitHub repository , this should ideally be combined with tracking model quality with memote , rendering RAVEN suitable for future GEM reconstruction and curation needs .
The RAVEN Toolbox 1 . 0 was released as an open-source MATLAB-package [9] , that has since seen minor updates and bugfixes . Since 2016 , the development of RAVEN has been organized and tracked at a public GitHub repository ( https://github . com/SysBioChalmers/RAVEN ) . This repository provides a platform for the GEM reconstruction community , with users encouraged to report bugs , request new features and contribute to the development . The RAVEN Toolbox is based on a defined model structure ( S11 Table ) . Design choices dictate minor differences between COBRA and RAVEN structures , however , bi-directional model conversion is supported through ravenCobraWrapper . Through resolving previously conflicting function names , RAVEN 2 . 0 is now fully compatible with the COBRA Toolbox . Detailed documentation on the purpose , inputs and outputs for each function are provided in the doc folder . Novel algorithms were developed to facilitate de novo GEM reconstruction by utilizing the MetaCyc database [26] . In this module , corresponding MATLAB structures were generated from MetaCyc data files ( version 21 . 0 ) that contained 3118 manually curated pathways with 13 , 689 metabolites and 15 , 309 reactions ( Fig 7 ) . A total of 17 , 394 enzymes are associated to these pathways and their protein sequences are included ( protseq . fsa ) . Information from these structures is parsed by getModelFromMetaCyc to generate a model structure containing all metabolites , reactions and enzymes . This MetaCyc model can subsequently be used for de novo GEM reconstruction through the getMetaCycModelForOrganism function ( Fig 7 ) . A draft model is generated from MetaCyc enzymes ( and associated reactions and metabolites ) that show homology to the query protein sequences . Beneficial is that MetaCyc reactions are mass- and charge-balanced , while curated transport enzymes in MetaCyc allow inclusion of transport reactions into the draft model . In addition , MetaCyc provides 515 reactions that may occur spontaneously . As such reactions have no enzyme association , they are excluded from sequence-based reconstruction and can turn into gaps in the generated models . By cataloguing spontaneous reactions in MetaCyc , the addSpontaneousRxns function can retrieve spontaneous reactions depending the presence of the relevant reactants in the draft model . In addition to MetaCyc-based GEM reconstruction , RAVEN 2 . 0 can utilize the KEGG database for de novo GEM reconstruction . The reconstruction algorithms were significantly enhanced in multiple aspects: the reformatted KEGG database in MATLAB format is updated to version 82 . 0; and the pipeline to train KEGG Orthology ( KO ) -specific hidden Markov Models is expanded . Orthologous protein sequences , associated to particular KEGG Orthology ( KO ) , are organised into non-redundant clusters with CD-HIT [43] . These clusters are used as input in multiple-sequence alignment with MAFFT [44] , for increased accuracy and speed . The hidden Markov models ( HMMs ) are then trained for prokaryotic and eukaryotic species with various protein redundancy cut-offs ( 100% , 90% or 50% ) using HMMER3 [45] and can now be automatically downloaded when running getKEGGModelForOrganism . To capitalize on the complementary information from MetaCyc- and KEGG-based reconstructions , RAVEN 2 . 0 facilitates combining draft models from both approaches into one unified draft reconstruction ( Fig 2 ) . Prior to combining , reactions shared by MetaCyc- and KEGG-based reconstructions are mapped using MetaCyc-provided cross-references to their respective KEGG counterparts ( S12 Table ) . Additional reactions are associated by linkMetaCycKEGGRxns through matching the metabolites , aided by cross-references between MetaCyc and KEGG identifiers ( S13 Table ) . Subsequently , the combineMetaCycKEGGModels function thoroughly queries the two models for identical reactions , discarding the KEGG versions while keeping the corresponding MetaCyc reactions . In the combined model , MetaCyc naming convention is preferentially used such that unique metabolites and reactions from KEGG-based draft model are replaced with their MetaCyc equivalents whenever possible . The combined draft model works as a starting point for additional manual curation , to result in a high-quality reconstruction . RAVEN 2 . 0 contains a range of additional enhancements . Linear problems can be solved through either the Gurobi ( Gurobi Optimization Inc . , Houston , Texas ) or MOSEK ( MOSEK ApS , Copenhagen , Denmark ) solvers . Various file formats are supported for import and export of models , including Microsoft Excel through Apache POI ( The Apache Software Foundation , Wakefield , Massachusetts ) , the community standard SBML Level 3 Version 1 FBC Package Version 2 through libSBML [46] and YAML for easy tracking of differences between model files . Meanwhile , backwards compatibility ensures that Excel and SBML files generated by earlier RAVEN versions can still be imported . An improved GEM of S . coelicolor , called Sco4 for the fourth major published model , was generated through RAVEN 2 . 0 following the pipeline illustrated in Fig 3 . The model is based on the complete genome sequences of S . coelicolor A3 ( 2 ) , including chromosome and two plasmids ( GenBank accession: GCA_000203835 . 1 ) [27] . MetaCyc-based draft model was generated with getMetaCycModelForOrganism using default cut-offs ( bit-score ≥ 100 , positives ≥ 45% ) . Two KEGG-based draft models were generated with getKEGGModelForOrganism by ( i ) using 'sco' as KEGG organism identifier , and ( ii ) querying the S . coelicolor proteome against HMMs trained on prokaryotic sequences with 90% sequence identity . These two models were merged with mergeModels , subsequently combined with the MetaCyc-based draft using combineMetaCycKEGGModels , followed by manual curation . Reactions were mapped from iMK1208 to MetaCyc and KEGG identifiers in a semi-automated manner ( S1 Table ) . Metabolites in iMK1208 were associated to MetaCyc and KEGG identifiers through examining the mapped reactions ( S2 Table ) . Pathway gaps and invalid metabolite identifiers were thus detected and revised accordingly . Manual curation of the combined draft and iMK1208 culminated in the Sco4 model . Curation entailed identifying reactions from the combined draft , considering the absence of gene-associations in iMK1208; explicit subsystem and/or pathway information; support from both MetaCyc and KEGG reconstructions; additional literature information , as well as potential taxonomic conflicts . Manual curation was particularly required for secondary metabolite biosynthetic pathways , due to high levels of sequence similarity among the synthetic domains of polyketide synthase and nonribosomal peptide synthetase [47] . The identified new reactions were added to Sco4 , while retaining the previous manual curation underlying iMK1208 . Spontaneous reactions were added through addSpontaneousRxns , while transport reactions annotated in the MetaCyc-based reconstruction were manually curated . Gene essentiality was simulated on iMK1208 and Sco4 by the COBRA function singleGeneDeletion , with a more than 75% reduction in growth rate identifying essential reactions . Potential targets for metabolic engineering were predicted using the flux scanning with enforced objective function FSEOF [34] . The reconstruction and curation of Sco4 is provided as a MATLAB script in the ComplementaryScripts folder of the Sco4 GitHub repository . The updated Sco4 model is deposited to a GitHub repository in MATLAB . mat , SBML L3V1 FBCv2 . xml , Excel . xlsx , YAML . yml and flat-text . txt formats ( https://github . com/SysBioChalmers/Streptomyces_coelicolor-GEM ) . Users can not only download the most recent version of the model , but also report issues and suggest changes . Updates in the metabolic network or gene associations can readily be tracked by querying the difference in the flat-text model and YAML representations . As such , Sco4 aims to be a community model , where improved knowledge and annotation will incrementally and constantly refine the model of S . coelicolor . RAVEN is an open source software package available in the GitHub repository ( https://github . com/SysBioChalmers/RAVEN ) . The updated S . coelicolor genome-scale metabolic model Sco4 is available as a public GitHub repository at ( https://github . com/SysBioChalmers/Streptomyces_coelicolor-GEM ) . | Cellular metabolism is a large and complex network . Hence , investigations of metabolic networks are aided by in silico modelling and simulations . Metabolic networks can be derived from whole-genome sequences , through identifying what enzymes are present and connecting these to formalized chemical reactions . To facilitate the reconstruction of genome-scale models of metabolism ( GEMs ) , we have developed RAVEN 2 . 0 . This versatile toolbox can reconstruct GEMs fast , through either metabolic pathway databases KEGG and MetaCyc , or from homology with an existing GEM . We demonstrate RAVEN's functionality through generation of a metabolic model of Streptomyces coelicolor , an antibiotic-producing bacterium . Comparison of this de novo generated GEM with a previously manually curated model demonstrates that RAVEN captures most of the previous model , and we subsequently reconstructed an updated model of S . coelicolor: Sco4 . Following , we used Sco4 to predict promising targets for genetic engineering , which can be used to increase antibiotic production . | [
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] | 2018 | RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor |
Fine-tuning the plasma-membrane permeability to essential nutrients is fundamental to cell growth optimization . Nutritional signals including nitrogen availability are integrated by the TORC1 complex which notably regulates arrestin-mediated endocytosis of amino-acid transporters . Ammonium is a ubiquitous compound playing key physiological roles in many , if not all , organisms . In yeast , it is a preferred nitrogen source transported by three Mep proteins which are orthologues of the mammalian Rhesus factors . By combining genetic , kinetic , biochemical and cell microscopy analyses , the current study reveals a novel mechanism enabling TORC1 to regulate the inherent activity of ammonium transport proteins , independently of arrestin-mediated endocytosis , identifying the still functional orphan Amu1/Par32 as a selective regulator intermediate . We show that , under poor nitrogen supply , the TORC1 effector kinase' Npr1' promotes phosphorylation of Amu1/Par32 which appears mainly cytosolic while ammonium transport proteins are active . Upon preferred nitrogen supplementation , like glutamine or ammonium addition , TORC1 upregulation enables Npr1 inhibition and Amu1/Par32 dephosphorylation . In these conditions , as in Npr1-lacking cells , hypophosphorylated Amu1/Par32 accumulates at the cell surface and mediates the inhibition of specific ammonium transport proteins . We show that the integrity of a conserved repeated motif of Amu1/Par32 is required for the interaction with these transport proteins . This study underscores the diversity of strategies enabling TORC1-Npr1 to selectively monitor cell permeability to nutrients by discriminating between transporters to be degraded or transiently inactivated and kept stable at the plasma membrane . This study further identifies the function of Amu1/Par32 in acute control of ammonium transport in response to variations in nitrogen availability .
Proteins of the Mep-Amt-Rh superfamily including the human Rhesus factors mediate the transmembrane transport of ammonium from bacteria to mammals [1–4] . Ammonium , hereafter referring to the sum of NH4+ and NH3 , is a key nitrogen source for microorganisms and plants whereas it is mainly documented for its role as a blood pH regulator and for the deleterious consequences it has on the central nervous system upon cytotoxic accumulation in mammals for instance [5–7] . Mep-Amt-Rh proteins adopt a trimeric fold , with a proposed conducting pore crossing each of the three monomers [8–13] . The latter are composed of 11 or 12 helices and are prolonged by a cytosolic C-terminal extension showing conserved peculiarities specific to each of the Mep-Amt and Rh subfamilies [14] . In Escherichia coli , the cytosolic extension of each subunit of the AmtB trimers participates to the interaction with a trimeric association of the PII-type protein GlnK , a negative regulator of the ammonium transport activity [15 , 16] . Yet , PII-type proteins , key transducers of the nitrogen signal , are only found in bacteria , Archaea and a few plant species [17] . Unravelling the mechanisms and the signalling pathways involved in the activity regulation of eukaryotic Mep-Amt-Rh members remains an open field . We recently showed that the activity of Mep2 , one of the three Mep-Amt-Rh proteins enabling ammonium transport in the yeast Saccharomyces cerevisiae , is dynamically controlled by the conserved TORC1 ( Target Of Rapamycin Complex ) pathway [18 , 19] . Under poor nitrogen supply , TORC1 downregulation relieves inhibition of the Npr1 kinase which enables phosphorylation of an autoinhibitory domain in the C-terminus of Mep2 , thereby favouring ammonium transport . In contrast , preferred nitrogen supplementation activates TORC1 and thus inhibits Npr1 . In this case , Mep2 is no longer phosphorylated and plasma-membrane phosphatases Psr1 and Psr2 additionally mediate desphosphorylation of preaccumulated phosphorylated Mep2 , enabling autoinhibition of ammonium transport activity [18] . The latter mechanism notably contrasted with the known role of TORC1 and of its effector kinase Npr1 in regulating arrestin–mediated endocytosis of transporters but supported previous studies indicating a multiplicity in the mechanisms of Npr1-mediated regulation of Saccharomyces cerevisiae and Candida albicans Mep proteins [20–25] . Seminal works by Grenson and collaborators led to the isolation of mutations suppressing specific defects of Npr1-lacking cells in either amino-acid uptake , including the mut-2 , mut-4 and mut-5 mutations , or in ammonium uptake , like the amu1 mutation [25 , 26] . Of note the mut loci , also known as npi1 , npi2 and npi3 , were shown to respectively encode variants of the Rsp5 ubiquitin-ligase , the orthologue of mammalian Nedd4 , of the Doa4 ubiquitin-hydrolase , and of Bro1 , the orthologue of mammalian Alix/Aip-1 [27–31] . While the characterization of the mut suppressor mutations shed light on the mechanism of ubiquitin-mediated endocytosis of permeases and the role of the multivesicular-body pathway in their delivery to the lysosome/vacuole [27–29 , 32 , 33] , the nature of Amu1 and of the underlying mechanism of ammonium transport control remain unsolved . Here , we cloned AMU1 by functional complementation identifying YDL173w/PAR32 , a gene of unknown function . We show that the phosphorylation status of Amu1/Par32 is dynamically controlled by TORC1-Npr1 in response to the quality of the nitrogen supply . When the function of Npr1 is inhibited , desphosphorylated Amu1/Par32 accumulates at the cell surface and mediates inhibition of specific ammonium transport proteins . This study unravels a novel mode of plasma-membrane permeability tuning , governed by TORC1 and reminiscent of the GlnK-mediated regulation of prokaryotic ammonium transport proteins .
All three Mep ammonium transport proteins are most produced and active when wild-type cells are grown in the presence of a non-preferred nitrogen source , the MEP2 gene being strongly expressed compared to MEP1 and MEP3 [19] . In these conditions , all three Mep transport activities largely depend on the integrity of the Npr1 kinase [22] . Npr1 is so far reported to protect amino-acid permeases from arrestin-mediated endocytosis and subsequent degradation , while we recently showed that the kinase also regulates the inherent activity of the Mep2 ammonium transport protein by controlling its phosphorylation state [18 , 20 , 21 , 34] . Upon addressing the influence of Npr1 on the protein levels of Mep1 and Mep3 , we found that both proteins are not destabilized in the absence of the kinase ( Fig 1a and 1b ) . Mep1 and Mep3 are respectively detected as at least 3 and 2 main forms , both in wild-type and Npr1-lacking cells . In the latter , the relative abundance of the 3 main Mep1 forms is slightly modified , the faster-running one being more predominant in the absence of the kinase . An essential requirement of Npr1 for the presence of one of these immunodetectable Mep1 and Mep3 forms can however not be deduced from these observations . We nevertheless tested whether the different detected Mep1 and Mep3 forms correspond to differentially phosphorylated states of the proteins . Treating protein extracts from wild-type and Npr1-lacking cells with alkaline phosphatase ( ALP ) led to a removal of the Mep1 and Mep3 slower-running forms , leaving one main intense state with a mobility similar to the faster-running form observed in the absence of ALP ( Fig 1b ) . Hence , Mep1 and Mep3 exist under different phosphorylated states . Fluorescence microscopy revealed that Npr1 is dispensable for proper cell-surface localization of Mep1-GFP and Mep3-GFP as both proteins appeared evenly localized in the presence as in the absence of the kinase ( Fig 1c ) . Hence , Npr1 is required for Mep1 and Mep3 inherent transport activity but , in contrast to what has been previously shown for Mep2 , the requirement of the kinase does not appear to be simply correlated to the detection of a particular phosphorylated status of the transport proteins . We have previously shown that Npr1 integrity is notably required for the transport activity of Mep1 and Mep3 [22] . We used cells expressing a thermosensitive Npr1 variant [35] to test the consequence of immediate Npr1 inactivation on the Mep-dependent transport activity , focusing on Mep1 . In contrast to the low affinity protein Mep3 , the Mep1 transport activity can be easily monitored by following accumulation of [14C]-methylammonium ( mea ) , a convenient tracer analogue of ammonium [19 , 22] . MEP1 was expressed under the control of its own promoter from a low-copy-number centromeric plasmid ( YCpMep1 ) in cells deprived of the three endogenous MEP genes ( triple-mepΔ ) , bearing or not the thermosensitive Npr1 mutation ( npr1ts ) . Inactivation of the Npr1 kinase by shifting npr1ts cells at 37°C clearly reduced the Mep1-dependent accumulation of mea ( Fig 1d ) . Moreover , the initial rate of mea uptake measured just after the shift showed an immediate effect of Npr1 inactivation on the Mep1 activity , revealing a rapid inactivation of Mep1 upon Npr1 inactivation ( Triple-mepΔ + YCpMep1 at 29°C: 8 . 6 nmol min-1 per mg prot; triple-mepΔ + YCpMep1 at 37°C: 6 . 7 nmol min-1 per mg prot; triple-mepΔ npr1ts + YCpMep1 at 29°C: 8 . 4 nmol min-1 per mg prot; triple-mepΔ npr1ts +YCpMep1 at 37°C: 1 . 9 nmol min-1 per mg prot ) . Immunodetection of Mep1 did not reveal a major impact of Npr1 inactivation on the Mep1 protein level or bands distribution ( Fig 1e ) . These observations are consistent with Mep1 inherent activity being largely dependent on the maintenance of the Npr1 integrity , and indicate that the activity of plasma-membrane Mep1 is rapidly downregulated upon loss of Npr1 activity . We next evaluated whether overproduction of each of the three Mep proteins could bypass the requirement of Npr1 for their transport function . The Mep functionality was assessed by performing growth tests in the presence of a low ammonium concentration as sole nitrogen source ( Fig 2a ) . Triple-mepΔ cells are unable to grow in the presence of low ammonium concentrations while expression of only one of the three MEP genes enables growth in these conditions [19] . As expected , Mep1 and Mep3 proteins produced from the unique chromosomal MEP1 or MEP3 gene locus were fully dependent on Npr1 for function ( Fig 2a ) [22] . Expressing the MEP1 and MEP3 genes under their own promoter from a high-copy-number episomal plasmid led to an effective overproduction of the corresponding proteins ( Fig 2b ) . In these conditions , growth on ammonium was observed despite the kinase absence ( Fig 2a ) . MEP2 expression from the episomal plasmid did however not allow Mep2 overproduction ( Fig 2b ) , most likely reflecting the natural high strength of the MEP2 promoter [19] . As expected in this case , the Mep2 function remained totally dependent on Npr1 ( Fig 2a ) . These data reveal that overexpression of the MEP1 and MEP3 genes relieves the Npr1 requirement for the corresponding Mep protein function . The above findings could be consistent with the existence of a limiting negative factor involved in the Npr1-mediated regulation of Mep1 and Mep3 . In 1979 , Dubois and Grenson characterized a strain bearing a suppressor mutation in a locus called amu1 ( ammonium uptake ) enabling yeast growth on low ammonium concentrations despite the lack of a functional Npr1 [25] . Amu1 was proposed to act as a negative regulator of the low-affinity and high-capacity component of the ammonium transport activity of wild-type cells . These data could be consistent with Amu1 regulating Mep1 and/or Mep3 , as both proteins possess a lower affinity for their substrate and a higher Vmax compared to Mep2 [19] . Accordingly , while Npr1-lacking cells resist to toxic concentrations of methylammonium , a non-metabolizable ammonium analogue transported via Mep1 and Mep3 , cells further bearing a mutated amu1 locus do not grow in these conditions ( Fig 3 ) . We used the latter phenotype to clone the AMU1 gene by functional complementation of amu1-1 npr1-1 ura3 cells using a genomic library of the Σ1278b strain and selecting clones able to grow in the presence of a toxic concentration of methylammonium . The selected clones were next controlled for loss of growth on ammonium as sole nitrogen source ( Fig 3 ) . Analysis of the plasmidic content of these clones revealed that they all were transformed by a plasmid bearing one common gene , namely the YDL173w ORF . Single expression of YDL173w from a centromeric plasmid complemented the amu1-1 mutation in amu1-1 npr1-1 ura3 cells , conferring resistance to methylammonium and loss of growth on low ammonium ( Fig 3 ) . Full deletion of YDL173w in Npr1-lacking cells was sufficient to restore growth on low ammonium and to confer sensitivity to methylammonium . These findings are consistent with the AMU1 gene corresponding to YDL173w , a gene coding for a protein of unknown function and previously named PAR32 standing for ‘Phosphorylated After Rapamycin , 32kDa’ [36] . The biological function of Amu1/Par32 is unknown . A recent proteomic study identified the cleavage of the N-terminal methionine of Amu1/Par32 and the N-acetylation of the subsequent alanine [37] , giving a predicted 294-residue long protein with a calculated molecular weight of 31 . 75 kDa . The Amu1/Par32 sequence exhibits a biased amino-acid composition with several low-complexity regions . In particular , poly-Asn and poly-Lys stretches are located in the N- and C-terminal region , respectively ( Fig 4 ) . The presence of such low-complexity regions often characterizes intrinsically disordered or natively unfolded proteins . Accordingly , disorder prediction algorithms predict an intrinsically unstructured protein based solely on the amino-acid sequence of Amu1/Par32 . Of note , the Amu1/Par32 sequence contains an internal repeat ‘GRGGAGN’ present in four copies ( Fig 4 ) . No biological function is so far reported to be associated to this particular motif . Sequence similarities are difficult to reveal by simple blast analysis when considering proteins containing large low complexity regions . While one motif was not sufficient in itself , a multi-copy simultaneous search allowed the identification of orthologues , underlying the repetition of the motif as a common feature in the Amu1/Par32 protein family ( Fig 4 ) . All identified sequences were found in fungi , with a number of motif repetitions varying between 3 and 6 according to the considered protein . In order to determine which of the three Mep proteins recovers activity in a double npr1 amu1 context , we constructed strains bearing the AMU1 deletion , the npr1 mutation and the deletions of two of the three MEP genes , in all the combinations . Deletion of AMU1 improved growth on low ammonium of npr1 cells expressing specifically MEP1 or MEP3 , but not those expressing the MEP2 gene ( Fig 5 ) . The simple AMU1 excision had no major impact on growth of cells producing one of the three Mep in the presence of a functional Npr1 kinase . Measurements of initial uptake rates of [14C]-methylammonium were consistent with the growth tests ( Table 1 ) . An increase in Mep1 activity was observed in Npr1-lacking cells further deleted of AMU1 , while Mep2 activity remained low in these conditions , as in npr1 cells . Altogether , these observations reveal that loss of AMU1 specifically restores the transport function of Mep1 and Mep3 in Npr1-lacking cells . We next tested whether the Npr1 kinase affects the phosphorylation state of the Amu1 protein . In proline-grown Npr1-containing cells , the Amu1-3HA protein produced from the chromosomal tagged-gene was detected as a principal signal of about 63 kDa ( Fig 6a ) . In the latter experiment , overexposure of the autoradiogram also enabled to reveal a signal of about 25 kDa which was however not readily detectable in all the immunoblot experiments . In Npr1-lacking cells , these signals shifted respectively to about 59 and 23 kDa , the faster-running one being hardly detectable . The slower-running Amu1 form could correspond to a multimeric state of the protein or to a complex , both being resistant to denaturing conditions of the SDS-PAGE . Hereafter , when an immunoblot of Amu1-3HA will be discussed , we will mainly focus on the slower-running form . ALP treatment of extracts from Npr1-containing cells was accompanied by a down-shift of the main Amu1-3HA signal from 63 to 59 kDa , thus at the same running-rate observed for the Amu1-3HA signal in Npr1-lacking cells extracts , treated or not with ALP ( Fig 6b ) . Hence , Amu1-3HA appears phosphorylated in an Npr1-dependent manner . The Npr1 phosphorylation state and function is regulated by the TORC1 pathway according to the quality of the nitrogen supply [18 , 43–45] . Immunodetection of Amu1-3HA in Npr1-containing cells grown with nitrogen sources of different quality showed variations in the phosphorylation status of the protein ( Fig 6c ) . The protein was the most phosphorylated during growth on poor nitrogen sources like proline and urea , or intermediate quality nitrogen source like glutamate , namely under conditions where Npr1 is hypophosphorylated and presumed active [44 , 45] . In contrast , Amu1-3HA appeared to be less phosphorylated during growth with raising concentrations of ammonium or with glutamine , conditions where Npr1 is hyperphosphorylated and inhibited in a TORC1-dependent manner . In Npr1-lacking cells , Amu1-3HA was immunodetected as a fast-running form whatever the nitrogen supply , indicating that the variation in phosphorylation state of Amu1-3HA is triggered by Npr1 . Rapamycin addition , to hinder TORC1 activity in cells growing on high ammonium concentration , was accompanied by a rapid up-shift of the Amu1-3HA signal , not observed in Npr1-lacking cells ( Fig 6d ) . This is consistent with previous findings reporting that Amu1/Par32 is hyperphosphorylated after rapamycin treatment [46] . A similar rapid up-shift was also visible when ammonium-grown cells were transferred to a proline-medium , in keeping with a fast response of the Amu1 phosphorylation status to the quality of the nitrogen source ( Fig 6e ) . Inversely , supplementation of a high ammonium concentration to proline-grown cells was correlated with a rapid down-shift of the Amu1-3HA signal consistent with instant dephosphorylation of Amu1 upon shift from non-preferred to preferred nitrogen supply ( Fig 6f ) . We recently showed that the regulation of the inherent activity of Mep2 involves a dynamic control of the phosphorylation status of S457 in the C-terminal extension of the transport protein [18] . This control is mediated by a balance between Npr1-dependent phosphorylation and Psr1/Psr2-dependent dephosphorylation of Mep2 . As the Mep1 and Mep3 negative regulation involves an intermediate protein which is phosphorylated in an Npr1-dependent manner , we tested whether Amu1 could be dephosphorylated via the Psr1 and Psr2 plasma-membrane phosphatases . Our data show that the Amu1-3HA ammonium-induced dephosphorylation was also observed in cells lacking one or both of the Psr phosphatases ( Fig 6g ) . These findings further support a new distinction in the TORC1-Npr1 dependent mechanism of Mep2 regulation compared to Mep1/Mep3 . Altogether , these observations are consistent with TORC1 down-regulation triggering Npr1-dependent phosphorylation of Amu1 and with Amu1 phosphorylation state being tightly and rapidly regulated according to variation of the quality of the nitrogen supply . It has been reported that an arrestin-target of Npr1 is specifically hypophosphorylated in Npr1-lacking cells where it accumulates at the plasma membrane [20] . We checked whether Amu1 could respond to the Npr1 regulation through a modified subcellular localization by analyzing the impact of the nitrogen supply and of Npr1 integrity on the localization of Amu1-GFP . In proline-grown cells , Amu1-GFP was most exclusively cytoplasmic in the presence of Npr1 , whereas it was detected at the cell surface in Npr1-lacking cells ( Fig 7a ) . Addition of either glutamine or high ammonium concentration to proline-grown Npr1-containing cells triggered an increase of Amu1-GFP at the plasma membrane and a decrease of cytosolic Amu1-GFP revealing a recruitment of the protein at the cell surface ( Fig 7b ) . In all these conditions , Mep1-mCherry expressed from the tagged chromosomal MEP1 locus was principally detected at the plasma membrane . Both Mep1-mCherry and Amu1-GFP labeled the cell surface with discontinuous fluorescence intensity , intense foci of Mep1-mCherry co-localizing with intense Amu1-GFP foci ( Fig 7a and 7b ) . Addition of rapamycin to proline-grown cells prior ammonium supply at least partially prevented the recruitment of Amu1-GFP at the cell surface ( Fig 7b ) , indicating that Amu1-GFP localization can be controlled by TORC1 . Accordingly , the Amu1-GFP dephosphorylation induced by ammonium addition was inhibited in cells pretreated with rapamycin ( Fig 7c ) . Our data indicate that the kinase prevents plasma-membrane accumulation of Amu1 , likely protecting Mep1 and Mep3 from the TORC1-dependent inactivation occurring upon preferred-nitrogen supplementation . We next wished to address whether Amu1 dephosphorylation could constitute a signal for its cell-surface localization . The Amu1 295-residue-long protein contains no less than 29 serine , 15 threonine and 3 tyrosine residues and , at least 18 putative phosphorylation sites are predicted using the NetPhosYeast 1 . 0 server ( http://www . cbs . dtu . dk/services/NetPhosYeast/ ) . In addition , several independent large-scale phosphoproteomic analyses performed in response to different stimuli , such as rapamycin treatment , cell cycle regulation or general osmotic stress , have revealed numerous phosphorylated sites in Amu1 , and also distinct combinations between these phosphorylated sites [36 , 46–51] . The Amu1 hyperphosphorylation observed upon rapamycin treatment or during growth on proline likely results from the simultaneous phosphorylation of several sites . Taking all these data into consideration , we decided to substitute by alanine 9 serine or threonine residues ( S34 , S36 , S39 , S49 , S206 , S246 , S249 , S250 and T253 ) including residues of sites reported to respond to rapamycin treatment [47] . The resulting Amu1-3HA variant , Amu1phos-3HA , was detected as a principal signal of about 59 kDa , showing a down-shift in the migration profile compared to the native Amu1-3HA protein ( Fig 8a ) . The signal was composed of at least two major bands , the faster-running form being detected at a size similar to the Amu1-3HA signal observed in cells lacking the Npr1 kinase . These data indicate that the Npr1-dependent phosphorylation of Amu1phos-3HA is largely reduced . While Amu1-GFP was mainly cytosolic in proline-grown cells , the Amu1-GFP variant mutated in the 9 potential phosphorylation sites , Amu1phos-GFP , was at least partially directed to the cell surface , despite the presence of the Npr1 kinase ( Fig 8b ) , indicating that the reduction in Amu1 phosphorylation could be linked to its cell-surface localization . We next addressed the functionality of the Amu1phos-3HA variant by performing growth tests on low ammonium medium as sole nitrogen source and on glutamate medium with a toxic methylammonium concentration ( Fig 8c ) . Double amu1Δ npr1Δ cells expressing a functional Amu1 protein should behave as npr1Δ cells , thus showing no growth on ammonium and resistance to methylammonium , while expression of a non-functional Amu1 protein should not alter the growth of amu1Δ npr1Δ cells on ammonium and the sensitivity to methylammonium . The AMU1-3HA variants were expressed from centromeric ( low-copy ) and episomal ( high-copy ) plasmids . Expressing AMU1-3HA from a centromeric plasmid in amu1Δ npr1Δ cells partially inhibited growth on ammonium while it clearly conferred resistance to methylammonium , indicating that the Amu1-tagged protein is partially functional ( Fig 8c ) . Overexpressing AMU1-3HA from an episomal plasmid in amu1Δ npr1Δ cells however fully complemented the AMU1 deletion , suggesting that the partial function alteration of tagged Amu1-3HA can be compensated by overproduction of the protein . As expected , expression of AMU1phos-3HA in amu1Δ npr1Δ cells also complemented the AMU1 deletion , indicating that the mutated protein has conserved its ability to inhibit ammonium transport ( Fig 8c ) . amu1Δ cells producing or overproducing Amu1phos-3HA were able to grow on ammonium as the cells producing the non-mutated Amu1-3HA protein , showing that Amu1phos-3HA was still sensitive to Npr1-mediated inhibition . These data suggest that partial localization of Amu1phos-3HA at the cell surface in cells containing Npr1 is not sufficient to observe a constitutive inhibition of Mep1 and Mep3 . However , amu1Δ cells overproducing Amu1phos-3HA appeared more resistant to methylammonium compared to those producing Amu1-3HA , suggesting that the hypophosphorylated variant may have gained a partial ability to inhibit Mep1 and/or Mep3 despite the presence of the Npr1 kinase . Expressing AMU1phos-3HA from a centromeric plasmid in amu1Δ npr1Δ cells appeared to induce a slightly stronger inhibition of growth on ammonium compared to AMU1-3HA , suggesting that the Amu1phos-3HA variant might have an enhanced inhibitory capacity on Mep1 and Mep3 even in the absence of the kinase . Together , these results highlight the importance of Amu1 phosphorylation for the control of its localization , the hypophosphorylated Amu1phos-3HA variant being at least partially directed to the plasma membrane even if the Npr1 kinase is active . In these conditions , Amu1phos-3HA appears however unable to completely inhibit Mep1 and Mep3 , indicating that it is still sensitive to Npr1-mediated inhibition , likely containing additional Npr1-dependent phosphorylation sites . Our data indicate that upon preferred nitrogen supply , Mep1 and Mep3 are inactivated in a TORC1- and Npr1-dependent manner via the Amu1 factor . As Amu1 is targeted to the plasma membrane in this condition , the protein could mediate inactivation of Mep1 and Mep3 via physical interactions . We performed co-immunoprecipitation assays focusing on potential Amu1-Mep interactions . As Mep1 and Mep3 are poorly expressed proteins , we used an experimental setup enabling to produce Mep-GFP under the control of the strong GAL1 promoter . We show that upon immunoprecipitation of Amu1-3HA , Mep1-GFP and Mep3-GFP were co-immunoprecipitated while Mep2-GFP was not ( Fig 9a ) . It is to note that the co-immunoprecipitation of Mep1-GFP and Mep3-GFP with Amu1-3HA was observed when using proline-grown cells expressing Npr1 and that the addition of glutamine to the proline-grown cells had no significant impact on the efficiency of the co-immunoprecipitation , in the tested experimental conditions . These results reveal that Mep1-GFP and Mep3-GFP are able to interact in vitro with Amu1-3HA . We finally assessed the potential functional importance of the conserved repeated ‘GRGGAGN’ motif present in Amu1 . We generated a plasmid allowing the expression of tagged Amu1-3HA where the arginine residue of all four motifs was mutated into alanine ( Amu14R-A-3HA ) . Amu14R-A-3HA showed a migration profile similar to native Amu1 , with no major alteration in the protein level of the major 63 kDa signal ( Fig 8a ) . It also responded to Npr1 presence or absence similarly to non-mutated Amu1-3HA in terms of apparent phosphorylated and dephosphorylated states . However , Amu14R-A-GFP was cytosolic both in the presence as in the absence of Npr1 , revealing a key role of the motif in the cell-surface localization of Amu1 ( Fig 8b ) . The functionality of the Amu14R-A-3HA variant in the process of Mep1 and Mep3 inhibition was assessed by performing growth tests on low ammonium medium or on glutamate medium with a toxic methylammonium concentration ( Fig 8c ) . Consistent with the mislocalization of Amu14R-A-3HA , amu1Δ npr1Δ cells producing or overproducing Amu14R-A-3HA remained able to grow on ammonium and sensitive to methylammonium , showing that this version of Amu1 was unable to inhibit Mep1 and Mep3 . In addition , co-immunoprecipitation experiments further revealed that the in vitro interaction between Mep1 and Amu1 was compromised by the mutation of the four repeated motifs of Amu1 ( Fig 9b ) . These results show a crucial role for the arginine residue of the four repeated motifs in the cell surface localization of Amu1 and in the intrinsic ability of Amu1 to interact and to inhibit the Mep ammonium transport proteins . Together , our findings are consistent with a direct negative role of Amu1 in the TORC1-Npr1 control of the inherent activity of Mep1 and Mep3 .
This study reveals a novel mechanism enabling TORC1 and the effector kinase Npr1 to regulate nutrient permeability according to environmental variations . The TORC1-Npr1 pathway is thus able to regulate plasma-membrane transport proteins via three different ways ( Fig 10 ) . For instance , the TORC1-Npr1 pathway is so far mainly described for its control of the stability of amino-acid permeases at the plasma membrane [20 , 21] . Npr1 exerts a phospho-inhibitory control on arrestin-like adaptors thereby preventing recruitment of the Rsp5 ubiquitin-ligase to its permease targets , and consequently protecting them from endocytosis and vacuolar degradation . Seminal studies supported the existence of a different mechanism of Npr1-mediated regulation of yeast Mep ammonium transport proteins and also suggested the existence of a diversity among Npr1-dependent regulatory processes controlling Mep paralogues [22–25] . Consistently , we recently unraveled the molecular mechanism enabling TORC1-Npr1 to fine-tune the inherent activity of the Mep2 ammonium transport protein by dynamically regulating the phosphorylation status of an auto-inhibitory C-terminal domain of the transport protein [18] . Although Npr1 is also required for the activity of the two other Mep1 and Mep3 ammonium transport systems , our data reveal that their regulation indeed involves a different process implicating an inhibitory partner , Amu1/Par32 , an ever still functional orphan . On the basis of our findings , we propose a model of Mep1 and Mep3 regulation by TORC1-Npr1 and the nitrogen supply ( Fig 10 ) . In the presence of a non-preferred nitrogen source , TORC1 is poorly active and Npr1 is hypophosphorylated and presumably active . In these conditions , Amu1 is phosphorylated in an Npr1-dependent manner and is mainly cytosolic while Mep1 and Mep3 are kept active . The Npr1 kinase might directly phosphorylate Amu1 . For instance , a physical interaction between both proteins has been reported by two independent large-scale studies [52 , 53] . In the presence of a preferred nitrogen source , such as glutamine or a high ammonium concentration , TORC1 is upregulated , Npr1 is hyperphosphorylated and inhibited . In these conditions , Amu1 is dephosphorylated and accumulates at the cell surface . It forms a complex with Mep1 and with Mep3 , and mediates inhibition of ammonium transport . Mep1 and Mep3 transport activity could be inhibited upon interaction with Amu1 by physical hindrance of the conducting pore crossing the hydrophobic core of the proteins . Alternatively , physical interaction with Amu1 might prevent C-terminal-dependent activation of transport . The C-terminal extension of several Mep-Amt proteins is indeed reported to regulate transport activation by controlling an allosteric switch [18 , 54 , 55] . It is also possible that Amu1 serves as a scaffold for yet to define regulatory protein ( s ) , controlling the activity of Mep1 and Mep3 . A regulation by an inhibitory partner is highly reminiscent to the GlnK-mediated control of prokaryotic Mep-Amt proteins . GlnK belongs to the PII protein family of signal transduction proteins widely distributed in bacteria and Archaea [17] . PII proteins play a pivotal role in the control of nitrogen metabolism by regulating the activities of diverse enzymes , transcription factors and membrane transport proteins . Phylogenetic analyses indicate that PII proteins evolved to regulate bacterial AmtB ammonium transport proteins , as evidenced by the early linkage of GLNK with AMTB in operon [56 , 57] . In E . coli cells , under nitrogen limitation , GlnK is uridylylated and essentially cytoplasmic , while supplementation of high ammonium concentrations is accompanied by deuridylylation of GlnK and interaction with AmtB at the plasma membrane [58] . Crystallisation of the AmtB-GlnK complex reveals that trimeric GlnK regulates trimeric AmtB by insertion of the regulatory deuridylylated T-loop of one GlnK monomers into the pore of the neighboring AmtB monomer in the trimer , and thus by physically blocking the substrate transport [15 , 16] . GlnK also binds α-ketoglutarate and ATP/ADP and , was recently shown to display an ATPase activity inhibited by α-ketoglutarate [15 , 16 , 59 , 60] . In conditions of nitrogen sufficiency , a drop in cellular α-ketoglutarate leads to a depletion of α-ketoglutarate bound to GlnK , accompanied by a hydrolysis of ATP into ADP . ATP hydrolysis would drive a change in the conformation of the T-loop allowing it to protrude deep into the cytoplasmic exit of the AmtB pore . Amu1/Par32 is of unknown biochemical function . It is characterized by a four-fold repetition of a new motif ‘GRGGAGN’ . The repetition of this motif enables to identify Amu1 orthologues , defining a new family of fungal proteins . Based on prediction algorithms , Amu1 would be classified as an intrinsically disordered protein . These algorithms do however not take into account possible post-translational modifications such as phosphorylation and the impact these could have on folding and function , as recently nicely demonstrated for another intrinsically disordered protein [61] . Although Amu1 is not related in sequence to PII proteins , it is tempting to propose that it could acquire a particular folding/function upon binding to partners , such as the Npr1 kinase or the Mep proteins , and act as a functional analogue of the PII proteins . For instance , we show that the hypophosphorylated Amu1phos variant is at least partially directed to the plasma membrane even in the presence of Npr1 . In contrast , the substitution by alanine of the conserved arginine residue in the four motifs in Amu14R-A prevents the cell-surface localization , normally occurring in the absence of Npr1 , and this , despite Amu14R-A being dephosphorylated in these conditions . These data suggest that the integrity of the motifs plays a dominant role for the cell-surface localization of dephosphorylated Amu1 . Moreover , if Amu14R-A has lost its ability to inhibit Mep1 and Mep3 in vivo , as expected given its mislocalization , Amu14R-A has also lost its proper capacity of interaction with Mep1 in vitro , indicating a key role of the conserved arginine residues . The motifs integrity could thus be required for Amu1 to adopt a particular folding enabling interaction with the Mep proteins . In this model , nutrient-induced dephosphorylation of Amu1 would favor an Amu1 folding process involving the repeated motifs . The dephosphorylation of Amu1 could also be required for the interaction with proteins involved in its cell-surface targeting . We show that yeast cells have evolved different mechanisms to regulate transport proteins of the same family . While Mep2 shares about 40% of identity with Mep1 and Mep3 , the two latter proteins share about 79% identity [19] and likely emerged from the whole-genome duplication event that occurred in the hemiascomycete branch [62] . We previously showed the existence of two functional Mep-Amt subfamilies in fungi distinguishable according to whether the first of two conserved histidines in the conducting pore is preserved , as in yeast Mep2 , or replaced by glutamate , as in Mep1 and Mep3 [63] . In fungi , there is usually coexistence of at least one Mep2-type protein with a Mep1/3-type protein . In baker yeast , these two subfamilies notably differ in their kinetic properties and particularly in their optimal pH of transport . We previously proposed that Mep2 and Mep1/Mep3 could transport ammonium via different molecular mechanisms , involving or not a deprotonation step of the recognized NH4+ substrate , leading to opposite direct effects on intracellular pH and to different impacts on physiology . Of note , Mep2-type proteins have a unique status in that they are proposed to play a signalling role in filamentation induction , a dimorphic transition often associated to the virulence of pathogenic fungi [64] . These observations indicate a separation in the evolution history and a functional specialization of proteins of both subfamilies . Although both Mep2 and Mep1/3 regulations are mediated by TORC1-Npr1 , evolution of different molecular mechanisms of activity control could enable to discriminate between both subfamily members and to fine-tune each regulatory process in response to specific physiological parameters . Interestingly , in Candida albicans , the CaMep2 activity is abolished in cells lacking CaNpr1 while the CaMep1 activity is only partially compromised , and CaMEP3 appears to be a non-functional gene [24] . Though the potential role of the CaAmu1 protein ( Fig 4 ) in CaMeps regulation is unknown , these data could point to variations to Npr1-dependency of Mep proteins among yeast species . However , it is also conceivable that the distinct functions carried out by Npr1 in Saccharomyces cerevisiae could be supported by distinct Npr1-like , or even distinct kinases , in other species . For instance , in collaboration with the team of Bettina Tudzynski , we recently showed that the expression of at least one of the Fusarium fujikuroi Npr1-like proteins confers growth on ammonium to the Saccharomyces cerevisiae npr1 mutant while being unable to mediate Mep2 phosphorylation [65] . These data suggest that the Fusarium kinase is able to protect yeast Mep1 and/or Mep3 against Amu1-mediated inactivation while being unable to control Mep2 activity . The TORC1-Npr1 control passing via the Amu1 intermediate affects at least two yeast transport proteins . The latter are dedicated to the transport of a preferred nitrogen source further underlying that TORC1-Npr1 discriminates between transporters to be degraded , transiently inactivated or kept active at the cell surface by controlling at least three different regulatory mechanisms . It will be informative to determine the specter of action of Amu1 . Available data already indicate that Amu1 does not control amino-acid permeases like Gap1 and Put4 [25] . Could an Amu1-like regulatory mechanism also apply to mammalian ammonium transport proteins of the Mep/Amt/Rh family ? To date the mechanisms and the pathways involved in the activity regulation of Rhesus factors , mammalian counterparts of yeast Mep proteins , are largely unknown . The human RhCG protein shares a similar structure with Mep/Amt and Rh proteins from bacteria and Archaea [8–13] . Recent characterization of a nsSNP variant of human RhCG indicated that the activity regulation of this Rhesus factor could implicate molecular mechanisms similar to those controlling their Mep-Amt homologues [14] . PII proteins are absent from eukaryotes except their presence in plastids of a few plants , and obvious Amu1 homologues are limited to fungi . However , our findings suggest that the molecular mechanism of prokaryotic and fungal Mep-Amt proteins regulation is conserved although the regulatory partners are structurally different . It is tempting to propose that a similar mechanism has evolved to enable the regulation of mammalian Rhesus factors . Determining whether functional analogues of Amu1 and/or PII exist in mammals constitute a challenge for further investigation .
The S . cerevisiae strains used in this study are listed in Table 2 . All strains are isogenic with the wild type Σ1278b [66] . Cell transformation and gene deletions were performed as described previously [67 , 68] . mCherry-tagging of MEP1 at the chromosomal locus was performed by homologous recombination using a PCR fragment amplified from the pFA6a-link-yomCherry-Kan plasmid , a gift from Wendell Lim and Kurt Thorn ( Addgene plasmid 44903 ) [69] . HA-tagging of AMU1 at the chromosomal locus was similarly performed using a PCR fragment amplified from pFA6a-3HA-kanMX6 [70] . Cells were grown in a minimal buffered ( pH 6 . 1 ) medium with 3% glucose as the carbon source [71] . In experiments in which genes were expressed under the GAL1 promoter , 3% galactose + 0 . 3% glucose were used for transcriptional induction , and 3% glucose for repression . To this medium , nitrogen sources were added as required by the experiment and as specified in the text . The nitrogen sources used were 0 . 1% proline , 0 . 1% urea , 0 . 1% glutamine , 0 . 1% glutamate , or ( NH4 ) 2SO4 at the specified concentration . When required , the medium was supplemented with 0 . 0025% uracil to complement the auxotrophy . Rapamycin ( LC Laboratories ) was used at a final concentration of 2 μg/ml from a stock solution prepared in 90% ethanol/10% Tween-20 . The S . cerevisiae AMU1 gene was cloned by screening a low copy number library [1] , representing the genome of Σ1278b strain , for plasmids complementing the amu1-1 mutation in the 31034c recipient strain ( npr1-1 amu1-1 ura3 ) . Cells transformed with the plasmid library were plated on a selection minimal medium containing glutamate 0 . 1% as nitrogen source and 50 mM methylammonium . Among about 125 . 000 transformants , 10 tested candidates had simultaneously recovered methylammonium resistance and loss of growth on low ammonium ( 1mM ) . DNA isolated from these transformants was transformed in E . coli JM109 for purification and amplification . The phenotypes were verified after reintroducing the 10 purified plasmids into 31034c cells . Sequencing of the 10 genomic inserts enabled to identify one single common gene , YDL173w . A HincII-HindIII DNA fragment , containing the single YDL173w ORF with 311 pb upstream and 121 pb downstream sequences , was subcloned into pFL38 [74] to generate YCpAmu1 . The latter plasmid was sufficient to complement the amu1-1 mutation of 31034c cells . Plasmids used in this study are listed in Table 3 . Primers used in this study are available upon request . pGAL1Mep1-GFP: the MEP1 gene was amplified by PCR using the YCpMep1 vector [1] as template and then cloned by in vivo recombination in the pGAL1Gap1-GFP vector [34] by replacement of the GAP1 gene . pGAL1Mep3-GFP: the MEP3 gene was amplified by PCR using YCpMep3 vector [19] as template and then similarly used to replace the GAP1 gene in the pGAL1Gap1-GFP vector [34] . YEpMep1 , YEpMep2 and YEpMep3 were constructed by transferring the complete insert of YCpMep1 [1] , YCpMep2 [19] and YCpMep3 vectors [19] into the pFL44 vector [74] by restriction-ligation . YCpAmu1-GFP: a fragment containing the AMU1 gene and promoter was amplified by PCR using S . cerevisiae ( 23344c ) genomic DNA and then cloned by in vivo recombination in the YCpMep2-GFP vector [18] by replacement of the MEP2 gene and promoter . YCp and YEpAmu1-3HA: a fragment containing a part of AMU1-3HA gene and terminator was amplified by PCR using MB142 ( AMU1-3HA ) genomic DNA and then cloned by in vivo recombination in the YCp or YEpAmu1 vector . Mutated AMU14R-A and AMU1phos genes were synthesized and cloned in pUC57 vector by GeneCust ( Dudelange , Luxembourg ) . YCp/YEpAmu14R-A-3HA and YCp/YEpAmu1phos-3HA were constructed by transferring the complete insert of the corresponding pUC57-Amu1 into the YCp/YEpAmu1-3HA vector by restriction-ligation . YCpAmu14R-A-GFP and YCpAmu1phos-GFP: a fragment containing a last part of AMU1 gene fused to GFP was amplified by PCR using YCpAmu1-GFP and then cloned by in vivo recombination in the corresponding YCpAmu1-3HA vector by replacement of the 3HA-tag . pGAL1Mep1-GFP ( LEU2 ) : the LEU2 gene was amplified by PCR using pFL46 [74] as template and then cloned by in vivo recombination in the pGAL1Mep1-GFP ( URA3 ) vector by replacement of the URA3 gene . Total protein extracts were performed as described previously [75] . Membrane-enriched cell extracts were prepared as described previously [22] . For blot analysis , equal protein amounts ( ~20 μg ) were loaded onto an 6% to 8% SDS-polyacrylamide gel in a Tricine system [76] . After transfer to a nitrocellulose membrane ( Protran , VWR ) , proteins were probed with a mouse or rabbit antiserum raised against the C-terminal region of Mep1 ( 1:1000 ) [77] , Mep2 ( 1:2000 ) [77] , Mep3 ( 1:1000 ) [77] , HA ( 1:10000 ) ( Roche ) , GFP ( 1:10000 ) ( Roche ) and Pma1 ( 1:10000 ) [34] . Primary antibodies were detected with horseradish-peroxidase-conjugated anti-rabbit- or anti-mouse-IgG secondary antibodies ( GE Healthcare ) followed by measurement of chemoluminescence ( Lumi-LightPLUS , Roche ) . For alkaline phosphatase treatment on total cell extracts , the protein pellet collected after TCA precipitation was resuspended in a solution ( 0 . 1 M de Tris-HCl pH 6 . 8 , 20% glycérol , 4% SDS , 2% β-mercaptoethanol and 2 mM PMSF ) containing proteases inhibitors ( Complete Mini , Roche ) . This extract is then diluted 5 X in a dephosphorylation buffer [CIP 1X ( Roche ) , 50 mM Tris-HCl 1M pH 6 . 8 , 2 mM PMSF] containing proteases inhibitors ( Complete Mini , Roche ) . pH could eventually be adjusted to 7 . 6 and the extracts were then incubated 2h at 37°C in the presence ( or not ) of 20 units of calf alkaline phosphatase ( Roche ) . Proteins were precipitated with 10% TCA . For alkaline phosphatase treatment on membrane-enriched cell extracts , the collected membrane pellet was suspended in phosphatase buffer CIP 1X added of 0 . 1% SDS , 2 mM PMSF and proteinase inhibitors ( Complete Mini , Roche ) . The extracts were then incubated 1h at 37°C in the presence ( or not ) of 10 units of calf alkaline phosphatase ( Roche ) . Proteins were precipitated with 10% TCA . For N-glycosidase F treatment on membrane-enriched cell extracts , the collected membrane pellet was suspended in buffer ( 1x PBS , 10mM EDTA pH8 , 0 . 5% octyl-glucopyranoside , 0 . 2% 2-mercaptoethanol , 3mM PMSF and proteinase inhibitors ) and incubated 1 h at 37°C in the presence of 1 . 5 unit of peptide-N-glycosidase F ( PNGase F , Roche ) . Co-immunoprecipitation protocol in the presence of a cross-linker was modified from [78] . About 5 . 108 cells were washed with H2O , and incubated 10 min in prespheroplasting buffer ( 100 mM Tris pH 9 . 4 , 40 mM β-mercaptoethanol ) . Spheroplasts were prepared by 30-min incubation in spheroplasting buffer ( 20 mM HEPES pH 7 . 4 , 0 . 8 M sorbitol , 0 . 5X 868 medium , 40 mM β-mercaptoethanol ) in the presence of 800 U of lyticase at 20°C . Spheroplasts were washed once in cross-linking buffer ( 20 mM HEPES pH 7 . 4 , 0 . 8 M sorbitol , 100 mM potassium acetate ) and resuspended in 600 μl of cross-linking buffer added with proteinase inhibitors ( Complete Mini , Roche ) . Cross-linking was conducted with 4 mM dithiobis[succinimidylpropionate] ( DSP ) ( ThermoScientific , 22585 ) for 30 min at 4°C , and the reaction was quenched by addition of 100 mM Tris pH 7 . 4 for 15 min at 4°C . Spheroplasts were then lysed in 200 μl of lysis buffer ( 50 mM Tris pH 7 . 4 , 150 mM NaCl , 1% Nonidet P-40 ) added with proteinase inhibitors ( Complete Mini , Roche ) , 2 mM phenylmethylsulfonyl fluoride ( PMSF ) , 2 μg/ml leupeptin , 1 μg/ml pepstatin A and 0 . 5 μg/ml chymostatin; and broken with a glass rod and then by vortex-mixing for 5 min in the presence of glass beads . 700 μl of lysis buffer containing the different proteinase inhibitors were added and the lysates were incubated on a wheel for 30 min to extract membrane proteins . The extracts were centrifuged at 14000 rpm for 10 min . An aliquot of the lysates was collected and proteins were precipitated with 10% TCA . The remaining lysates were incubated for 30 min on a wheel with 25 μl pre-washed Pierce anti-HA magnetic beads ( ThermoScientific , 88836 ) . Beads were washed two times with 300 μl lysis buffer and proteins were eluted by incubation for 10 min at 60°C with 50 μl sample buffer ( 100 mM Tris pH 6 . 8 , 4% SDS , 20% glycerol , 0 . 02% bromophenol blue ) . 50 μl of Tris 1M and 2% β-mercaptoethanol were added to the samples . Samples were analyzed by SDS-PAGE , followed by immunoblotting overnight with antibodies against HA ( 1:1000 ) ( Roche ) and GFP ( 1:1000 ) ( Roche ) . Initial rates of [14C]-methylammonium ( BioActif ) uptake were measured as described for amino acids with cells grown in minimal medium containing proline as nitrogen source . Briefly , 5-ml samples of an exponentially growing culture corresponding to about 0 . 25 mg protein per ml were put , without any change of the medium , into vessels containing the labelled methylammonium and preheated to 29°C or 37°C in a rotary water bath . One-millilitre samples were then removed at time intervals and poured onto filters ( 0 . 45 μM , Millipore ) which were immediately washed 5 times with 2 ml iced water before counting . Cells were observed on a Zeiss Axio Observer Z1 microscope , driven by MetaMorph ( MDS Analytical Technologies ) . High-resolution images were captured in the confocal mode using a Yokogawa spindisk head and the HQ2 camera with a laser illuminator from Roper ( 405 nm 100 mW Vortran , 491 nm 50 mW Cobolt Calypso , and 561 nm 50 mW Cobolt Jive ) . Images were processed with Adobe Photoshop 8 . 0 ( Adobe Systems , Mountain View , CA ) and ImageJ ( http://rsb . info . nih . gov/ij ) . | Cells have evolved a variety of mechanisms to control the permeability of the plasma membrane to face environmental perturbations . Transcriptional regulation , endocytosis , gating and activity control of channels and transporters enable global or specific responses to stressful conditions and focused variations in nutrient availability . Emerging data from the yeast model reveal that the conserved TORC1 pathway regulates arrestin-mediated endocytosis of amino-acid transporters . We provide genetic and biochemical evidence for a novel mechanism enabling TORC1 to regulate the inherent activity of transport proteins via the Amu1/Par32 regulator intermediate . This low complexity protein mediates inhibition of specific proteins dedicated to the transport of ammonium , a favored nitrogen source , underscoring that TORC1 selects transporters to be degraded or transiently inactivated and preserved at the cell surface according to the environmental situation . The here-revealed mechanism of transport inhibition by Amu/Par32 is reminiscent to the inhibition of prokaryotic ammonium transport proteins mediated by PII-type proteins , key nitrogen signal transducers widespread in bacteria and Archaea . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
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"and",
"Methods"
] | [] | 2015 | Identification of a Novel Regulatory Mechanism of Nutrient Transport Controlled by TORC1-Npr1-Amu1/Par32 |
We designed a straightforward method for discriminating circulating Leishmania populations in the Indian subcontinent ( ISC ) . Research on transmission dynamics of visceral leishmaniasis ( VL , or Kala-azar ) was recently identified as one of the key research priorities for elimination of the disease in the ISC . VL in Bangladesh , India , and Nepal is caused by genetically homogeneous populations of Leishmania donovani parasites , transmitted by female sandflies . Classical methods to study diversity of these protozoa in other regions of the world , such as microsatellite typing , have proven of little use in the area , as they are not able to discriminate most genotypes . Recently , whole genome sequencing ( WGS ) so far identified 10 different populations termed ISC001-ISC010 . As an alternative to WGS for epidemiological or clinical studies , we designed assays based on PCR amplification followed by dideoxynucleotide sequencing for identification of the non-recombinant genotypes ISC001 up to ISC007 . These assays were applied on 106 parasite isolates collected in Nepal between 2011 and 2014 . Combined with data from WGS on strains collected in the period 2002–2011 , we provide a proof-of-principle for the application of genotyping to study treatment outcome , and differential geographic distribution . Our method can aid in epidemiological follow-up of visceral leishmaniasis in the Indian subcontinent , a necessity in the frame of the Kala-azar elimination initiative in the region .
Visceral Leishmaniasis ( VL ) is a neglected tropical disease caused by parasites of the Leishmania donovani species complex , which are transmitted by the bite of phlebotomine sand flies . WHO estimates that annually , 300 million people worldwide are at risk of VL [1] . In the Indian subcontinent ( ISC ) , including Bangladesh , India , and Nepal , each year an estimated 237 , 500 new cases occurred , of which 4 , 450 in Nepal [2] . Together this accounts for 80% of all new VL cases worldwide . However , recently VL incidence is declining in the Indian subcontinent , and the numbers of new reported cases have dropped to 735 , 9241 , and 335 respectively in the aforementioned countries in 2014 [3] . Monitoring/tracking the genetic diversity of the parasites in these endemic regions over time is essential to understand transmission dynamics . This can help to evaluate the effect of both preventive and curative intervention programs , to monitor progress towards elimination , and to study the dynamics of variants associated with specific phenotypes . Several molecular assays for identifying populations of L . donovani have been developed . Among these are sequencing of ribosomal loci [4] , multi-locus microsatellite typing [5] , multilocus sequence typing [6] , amplified fragment length polymorphism analysis [7] , and kinetoplast minicircle DNA RFLP ( restriction fragment length polymorphism ) analysis [8 , 9] . These methods are capable of discriminating a number of genotypes , but are less effective in recently evolving epidemic parasite populations which are relatively homogeneous , such as L . donovani in the ISC . A phylogenomic study , based on whole genome sequences of over 200 clinical ISC parasite isolates , allowed documenting genetic diversity on a much finer scale [10] . Based on single point mutations ( SNPs ) , ten major ISC populations ( named ISC001-ISC010 ) could be defined . Seven of them ( ISC001-ISC007 ) represented congruent monophyletic groups , while the remaining three ( ISC008-ISC010 ) contained mixed signatures of these . Because whole genome sequencing ( WGS ) cannot currently be applied in all laboratories , our goal was to develop simpler molecular assays for discriminating ISC001-ISC007 in individual isolates , based on PCR amplification followed by amplicon sequencing , further called ISC single locus genotyping ( ISC-SLG ) . This will allow application in epidemiological surveys and transmission studies . In case of genotype ISC005 , such assay could also have a clinical relevance , as this genotype was shown to correlate with antimonial drug resistance and treatment failure [10] . After development of the assay and evaluation of its analytical performance , we applied it to Nepalese isolates that were collected in the years following the WGS survey , and analyzed the spread of genotypes over time and space .
Ethical clearance was obtained from the institutional review boards of the Nepal Health Research Council , Kathmandu , Nepal and the corresponding body of the Institute of Tropical Medicine , Antwerp , Belgium . The sample collection consisted of a total of 204 Leishmania isolates from 195 confirmed VL patients who presented between 2002 and July 2014 at the B . P . Koirala Institute of Health Sciences ( BPKIHS ) , a tertiary care medical center in Dharan , Nepal . The clinical criteria were fever for more than 2 weeks , combined with hepatomegaly and/or splenomegaly . The laboratory criteria were a positive rK39 rapid diagnostic test ( InBiOS , Cat . nr . INS015 ) [11 , 12] , and bone marrow smear positivity . Written informed consent was obtained from patients , or from parents or guardians in case of children . Detailed geographical and clinical information of each patient is provided in S1 Database . Among the 195 patients , 9 were treated twice because they either did not respond to the first treatment , or relapsed . The period during which the second treatment was administered is referred to as second episode , hence our study included 204 disease episodes . Of these , treatment history of 26 was not traceable . The remaining episodes were treated with antimonials ( Sodium stibogluconate , SSG ) , Miltefosine ( MIL ) , or Amphotericin B ( AmB ) in 33 , 85 , and 57 cases , respectively , while in 3 cases treatment was not completed . Treatment failure was recorded for 42 episodes , meaning that patients either did not respond to treatment ( persisting clinical signs and symptoms of VL , positive bone marrow smear after treatment ) , or they relapsed after initial cure ( reappearance of disease symptoms and/or positive bone marrow smear during 12 months follow-up ) . Of these 42 episodes , SSG was used in 10 , MIL in 29 , and AmB in 3 cases . Parasite promastigotes were derived from bone marrow aspirates of VL patients by culturing in Tobie’s blood agar medium with Locke’s overlay [13] , with 200 IU/ml penicillin and 200 μg/ml streptomycin . Once the parasites were fully grown from the clinical material , they were transferred to M199 ( Sigma-Aldrich , cat . nr . 2520 ) with 20% fetal calf serum ( Invitrogen , cat . nr . 10270 ) . The parasite cultures were grown to late logarithmic growth phase and cryopreserved at -80˚C with 10% sterile glycerol . A total of 204 parasite cultures were isolated at BPKIHS , one for each disease episode . Out of these , 98 had been previously analyzed by WGS [10] , while 106 were genotyped in this study with ISC-SLG . DNA was extracted from parasite cultures using the QiaAmp DNA mini kit ( Qiagen , www . qiagen . com ) . Parasites in late logarithmic growth phase were washed thrice with sterile PBS solution and DNA was eluted in 200 μL AE buffer . DNA concentration and purity was verified by spectrophotometric measurement with the NanoDrop 2000 ( Thermo Scientific , Waltham , MA , USA ) . The species of L . donovani was confirmed using PCR-RFLP analysis of the heat-shock protein 70 gene ( hsp70 ) . The fragments referred to as HSP70-N [14] were digested with restriction enzymes HincII ( the isoschizomer of HindII ) [15] , and MluI . Previous WGS analysis of L . donovani from ISC identified 10 populations [10] , seven of which ( ISC001-ISC007 ) being characterized by a unique combination of apomorphic homozygous SNPs or INDELs ( insertions/deletions ) . The remaining three ( ISC008-ISC010 ) represented composite genotypes . For each of the genotypes ISC001-ISC007 , a unique apomorphic homozygous SNP or INDEL was selected for designing a specific assay . PCR primers were chosen to amplify about 500 nucleotides flanking each SNP/insertion at both sides . The same primers were used for the amplicon sequencing . PCR assays were done in 50 μl final reaction volume which contained 1x PCR buffer with a total of 2 mM MgCl2 , 200 μM of each dNTP , 1 μM of each primer , and 1 . 5 units of HotStarTaq Plus DNA polymerase ( Qiagen , Cat . nr . 203605 ) . Finally , 0 . 1 to 1 ng of L . donovani DNA was added . Since SNPs of ISC001 and ISC002 were located in a high GC% locus , 1x Q-solution was used in both these PCRs to decrease secondary structures . The thermo-cycling program was ( i ) initial denaturation at 95°C for 5 minutes; ( ii ) 36 cycles of denaturation at 94 °C for 1 minute , annealing at 60°C for 30 seconds and extension at 72°C for 45 seconds; and ( iii ) final extension at 72°C for 10 minutes . In addition , two positive controls ( 1 ng and 0 . 1 pg parasite DNA of MHOM/NP/2003/BPK282/0cl4 ) and two no-template controls were included in each experiment . The amplified PCR-products were verified on a 2% agarose gel prior to sequencing . The analytical sensitivity was determined for each PCR using reference strain MHOM/NP/2003/BPK282/0cl4 . Ten-fold DNA dilution series in water were examined , ranging from 20 ng to 0 . 2 pg added as template . The concentration of the reference DNA was determined using spectrophotometric measurements with the Nanodrop machine ( www . nanodrop . com ) . PCR amplicons were shipped to MACROGEN ( www . macrogen . com , Seoul , South Korea ) for capillary sequencing ( ABI3730XL DNA Analyzer , Applied Biosystems ) with either the forward or reverse PCR primer . Chromatogram trace files were aligned with the corresponding reference sequences from WGS data in order to identify the SNPs or insertion in the amplicon . Because we sequenced only one strand , we ensured having an excellent quality read at the nucleotide position in question , and no insertions or deletions outside the query area when aligning to the reference sequence . GPS coordinates of the villages where patients were living were taken from Google maps ( www . google . com . np/maps ) [16] and elevations were extracted from the R3 . 0 . 3 software ( www . R-project . org ) [17] using the “rgbif” package . Bubble plots were made with R3 . 0 . 3 using the “ggplot2” package . GPS plots were generated with QGIS version 2 . 8 . 7-Wien ( www . qgis . org ) [18] and Google earth ( www . google . com/earth ) [19] .
For each of the WGS-defined populations ISC001-ISC004 and ISC006-ISC007 , a unique homozygous SNP was selected: each SNP was thus an apomorphic character for a given population , also not found in ISC005 or in any of the composite genotypes ISC008-ISC010 . In the case of ISC005 , an apomorphic two-nucleotide insertion ( GA ) in the Aquaglyceroporin-1 gene was selected . Table 1 lists all selected SNPs and INDELs , with their characteristics and chromosome location . The PCR primers that were designed to amplify the specific SNP/INDEL positions with their flanking regions are given in Table 2 . Also indicated are the PCR primer that was used for sequencing , and the analytical sensitivity as determined on dilution series of parasite DNA . The analytical sensitivity is illustrated in Fig 1 and ranges between 2 pg and 0 . 2 pg . A total of 204 clinical parasite isolates of L . donovani obtained in Nepal were included in this study ( detailed information in S1 Database ) , 98 of which were collected between 2002 and 2011 and were previously analyzed with WGS [10] . For the present study , we used ISC-SLG to classify the remaining 106 isolates collected between mid-2011 and 2014 in genotypes ISC001 ( n = 21 ) , ISC003 ( n = 9 ) , ISC004 ( n = 8 ) , ISC005 ( n = 8 ) , ISC006 ( n = 16 ) , and ISC007 ( n = 0 ) , while 44 could not be classified . This was done in a sequential manner , whereby the assays for the most common Nepalese genotypes were performed first . Isolates that could not be assigned to a genotype at this stage were further analyzed for less common genotypes , and so on , till all six assays were used . If an isolate could not be categorized after running the six assays , it was listed as “unclassified genotype” . Even though we also developed ISC-SLG for ISC002 , we did not test for this genotype as it was so far only reported from Bangladesh [10] , and migration between both countries is restricted by travel visa requirements . Detailed results of the WGS and ISC-SLG analyses are provided in S1 Database . Of the 204 isolates , 7 originated from patients who were treated a second time , and that showed the same genotype as found in the first disease episode . When these 7 are not taken into account , as they do not represent independent data points , we found 33 ISC001 , 16 ISC003 , 33 ISC004 , 15 ISC005 , 43 ISC006 , and 8 ISC009 isolates , while 49 could not be classified ( 6/93 analyzed with WGS , 43/104 analyzed with ISC-SLG ) . Fig 2 illustrates the distribution of genotypes over the period of sampling . Genotypes ISC001 and ISC003-ISC006 were present in most sampled years , with some exceptions . But even when they were not found in a particular year , they reappeared later on , proving that all of them circulated continuously in the region . For a given year , the most abundant classified genotype varied: ISC004 in 2002–2003 , ISC006 from 2004 to 2012 , and ISC001 in 2013–2014 . ISC009 was the rarest genotype and was not identified after 2011 because no ISC-SLG test is available . ISC007 was not found in any sample . The distribution of genotypes according to the treatment outcome of patients with three different drugs ( SSG , MIL and AmB ) is shown in Fig 3 , whereby only episodes where treatment was completed are included . With respect to SSG , treatment failure was observed only in ISC004-ISC006 , but most patients infected with ISC004 and ISC006 were cured . In contrast , none of the patients infected with ISC005 cured after SSG treatment . For MIL , relapse was observed for the 6 identified genotypes but never for the unclassified ones . Half of four MIL treated relapsing patients for which genotyping was done at relapse stage , showed the same genotype before and after relapse . Two of them however did not: BPK519 and BPK676 were initially infected with ISC003 , but at the time of relapse respectively ISC001 and ISC006 were isolated . The three cases of AmB relapse were associated with ISC004 , ISC006 , and an unclassified genotype . VL patients included in this study were from 15 administrative districts . Fig 4 shows the presumed geographical origin of typed parasites over time , with the assumption that patients got infected in their home village . An overview of the numbers per year and per district is given in S1 Table . Seven patients for which identical genotypes were recovered before and after relapse were included only once in this analysis . Genotype ISC001 was mostly present in hill districts such as Bhojpur , Dhankuta , Khotang , Okhaldhunga , Sankhuwasabha , and Udayapur . Other genotypes were unevenly distributed in the lowland area ( Terai ) . The highest number of different genotypes was found in the three districts Morang , Sunsari and Saptari .
Several Leishmania populations have been documented to circulate in the Indian Subcontinent [10] . Keeping track of their distribution over time is of particular importance for parasite elimination by control and treatment measures . Indeed , tracking the spread of populations allows tracing parasite movements from one area to another , assisting in monitoring control efforts . In addition , parasites from different populations could react differently to treatment , be carried by different vectors , or differ in response to vaccines should they become available . Identifying L . donovani populations in the ISC is however challenged by the fact that they are genetically highly homogeneous: WGS revealed no more than 2418 SNPs in 191 isolates of the core population [10] . Previously used methods such as microsatellites , which are effective in other areas in the world , have shown limited value in this region [5] . Data from WGS offered the additional resolution needed for distinguishing different populations based on single nucleotide polymorphisms [10] . Although WGS could be used for large-scale epidemiological surveys or clinical studies , it remains currently too expensive , has limited availability , and requires too much bio-informatics analysis time . The ISC-SLG method presented in this paper partly solves these limitations , as it requires only PCR and classic Sanger sequencing methods , which are far easier to perform and interpret than WGS , at a significantly smaller cost . As a proof-of-principle , we investigated the geographic spread of different parasite genotypes over a period of more than 10 years ( 2002–2014 ) , combining data from WGS and ISC-SLG of L . donovani in Nepal . Based on these data we could show that particularly ISC001 has a different geographic distribution as compared to the other genotypes , and is present predominantly in hilly areas . This could be related to a local epidemic , which is corroborated by a recent outbreak investigation showing that transmission does take place at higher altitudes [20] . ISC001 is genetically very different from parasites belonging to the main population endemic in the Terai lowland , and shows different phenotypic features , hence its epidemiological follow-up is highly relevant . No obvious pattern could be seen for the other genotypes , which are found in the Terai ( lowland ) . As this analysis was merely a proof-of-concept , no firm conclusions should be drawn . The data collection was not set up for such precise monitoring , and only confirmed VL cases visiting the BPKIHS medical services were included . In addition , the sampling should be extended to other countries of the ISC . An assessment was presented on differential treatment response from the different genotypes . Apart from ISC005 , which systematically did not react to SSG , no obvious patterns were seen . The treatment failure of ISC005 infected patients does not come as a surprise , because all parasites of this population have a defective aquaglyceroporin transporter [21] . This transporter is needed for uptake of trivalent antimonials , which are the active derivatives of pentavalent antimonial drugs such as SSG . It is exactly the underlying 2-nucleotide insertion responsible for the inactivating frameshift that was used for identification of ISC005 . As for the other treatments , AmB was effective in all genotypes , and MIL frequently resulted in relapse , also across genotypes . Regarding the latter , no relapse was seen in unclassified genotypes , which remains to be elucidated: identification of these samples is needed , as well as a sufficiently powered study . In two patients , different genotypes were detected at the onset of disease and at relapse stage after MIL treatment . Several scenarios could explain this . First , the patients might have been simultaneously infected with 2 different genotypes initially , of which one outgrew the other during culturing . After treatment , the first detected parasite could have been eliminated , allowing the other to be isolated at the time of relapse . Alternatively , the patients might have been re-infected with a different genotype , causing the relapse . As WGS-based methods can be considered the gold standard for identifying parasite populations because they use nearly all nuclear sequence information , our study can assess the power of alternative methods based on single or few genes . A previous report , including 31 strains from our analysis , classified Nepalese genotypes with kinetoplast DNA mini-circles , microsatellites , cysteine proteinase B , glycoprotein 63 , and the hydrophilic surface protein B [9] . This analysis identified 14 kDNA and 8 nuclear genotypes , which in general correlated well with WGS-defined genotypes ( data provided in S1 Database ) , even though there was no perfect one-to-one relationship . This could be explained by the fact that microsatellites tend to suffer from homoplasy [22] , mini-circles are highly variable and difficult to analyze in a reproducible manner , and genetic homogeneity calls for analysis of many loci in parallel . We applied ISC-SLG on parasite cultures , but so far not on clinical samples . Nevertheless , the analytical sensitivity of the assays was between 0 . 2 and 2 pg , or roughly 1 to 10 parasite genomes , which makes the assay at least theoretically usable on VL samples with sufficient parasite load , such as bone marrow aspirates , spleen/liver biopsies , and even blood [23] . In addition , also tissue from Post-Kala-azar dermal leishmaniasis ( PKDL ) patients was shown to surpass this threshold [24] . Also , currently efforts are ongoing to specifically select or amplify low abundant parasite DNA from clinical samples , which may provide new opportunities to extract useful genetic information from these [25] . Improvement of ISC-SLG could involve the use of multiplex and real-time PCR . Currently , each genotype requires a different PCR , and these could be combined in a single tube by multiplexing to increase speed and reduce cost . Moreover , as illustrated in this paper , analysis can be done in a sequential manner , whereby samples are first tested for the most abundant genotype ( s ) instead of running all assays simultaneously . Further , to enhance throughput and compatibility with existing infrastructure in low-resource settings , sequencing could be avoided by using fluorescent real-time PCR probes as shown by Feehery et al . and Tyagi et al . [26 , 27] . It should be noted that ISC-SLG can detect documented genotypes/populations , but does not allow identification of new ones or alternative genotypes showing the same polymorphism as used in the assay . Indeed , 42% of tested parasite isolates could not be classified . These could either represent hitherto undetected genotypes , or populations for which no ISC-SLG test was developed or used . Nevertheless , highly useful information can be obtained even by tracking half of the circulating genotypes , as it can provide insight into the way of spreading , and hint to invasion of new genotypes in a particular area . Hence , WGS remains complementary to our method , allowing to investigate new genotypes and serving as a basis for developing additional ISC-SLG assays . In conclusion , ISC-SLG was successfully applied to cultured isolated parasites from various locations in Nepal . The method needs further improvement , but is already in its current version a practical tool for use in clinical studies and epidemiological surveys . As such it contributes to “research on epidemiology and transmission dynamics of VL” , one of the key research priorities for visceral leishmaniasis elimination recently suggested by Singh et al . [28] . Applying our technique in country-wide systematic epidemiological surveys would help to better understand and control leishmaniasis in Nepal . The method could easily be extended to additional genotypes circulating in other regions of the ISC , in support of the Kala-azar elimination program . | Visceral Leishmaniasis ( VL ) or Kala-azar is a life-threatening neglected tropical disease that annually affects half a million people worldwide . In the Indian subcontinent ( India , Nepal , Bangladesh ) , the disease is caused by infection with the protozoan parasite Leishmania donovani , which is transmitted by female sand flies . Currently , the Kala-azar elimination program aims at reducing the number of VL cases in the region to less than 1 in 10 . 000 at upazila , sub-district and district level in Bangladesh , India , and Nepal respectively . In support of this program , tools for tracking L . donovani populations are essential , because these allow monitoring geographic spread over time . However , the parasite populations in the region are highly homogeneous , requiring sequencing of the entire genome to gather sufficient information for discriminating them . Because whole genome sequencing ( WGS ) is impractical for large-scale use , we designed a simple alternative to identify the WGS-genotypes . Our method is based on PCR amplification followed by sequencing of one particular locus , diagnostic of each population . We provide proof-of-principle that our method can be used to track parasite populations over time , and to correlate them with clinical parameters . We believe that our assay can support the Kala-azar control efforts in the Indian subcontinent . | [
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] | 2017 | Single locus genotyping to track Leishmania donovani in the Indian subcontinent: Application in Nepal |
Podoconiosis is a neglected tropical disease ( NTD ) that is prevalent in red clay soil-covered highlands of tropical Africa , Central and South America , and northern India . It is estimated that up to one million cases exist in Ethiopia . This study aimed to estimate the prevalence of podoconiosis in East and West Gojam Zones of Amhara Region in northern Ethiopia . A cross-sectional household survey was conducted in Debre Eliyas and Dembecha woredas ( districts ) in East and West Gojam Zones , respectively . The survey covered all 17 , 553 households in 20 kebeles ( administrative subunits ) randomly selected from the two woredas . A detailed structured interview was conducted on 1 , 704 cases of podoconiosis identified in the survey . The prevalence of podoconiosis in the population aged 15 years and above was found to be 3 . 3% ( 95% CI , 3 . 2% to 3 . 6% ) . 87% of cases were in the economically active age group ( 15–64 years ) . On average , patients sought treatment five years after the start of the leg swelling . Most subjects had second ( 42 . 7% ) or third ( 36 . 1% ) clinical stage disease , 97 . 9% had mossy lesions , and 53% had open wounds . On average , patients had five episodes of acute adenolymphangitis ( ALA ) per year and spent a total of 90 days per year with ALA . The median age of first use of shoes and socks were 22 and 23 years , respectively . More men than women owned more than one pair of shoes ( 61 . 1% vs . 50 . 5%; χ2 = 11 . 6 p = 0 . 001 ) . At the time of interview , 23 . 6% of the respondents were barefoot , of whom about two-thirds were women . This study showed high prevalence of podoconiosis and associated morbidities such as ALA , mossy lesions and open wounds in northern Ethiopia . Predominance of cases at early clinical stage of podoconiosis indicates the potential for reversing the swelling and calls for disease prevention interventions .
Podoconiosis is a non- infectious elephantiasis distinct from lymphatic filariasis that affects barefoot individuals exposed to red clay soil of volcanic origin . In particular , podoconiosis is prevalent among barefoot subsistence farmers that live and work in these areas [1] . Even though the pathogenesis of the diseases has not yet been investigated in depth , it is believed to be caused by fine particles in the soil that penetrate the skin and induce an inflammatory reaction in the lymphatic system [2] . The disease results in bilateral progressive swelling of the lower legs , usually limited below the level of the knees . Based on the disease progression , podoconiosis is classified into five stages where the first and second stages have swelling limited below ankle which is either reversible over night ( stage one ) or not ( stage two ) . The third stage of the disease has water bag like or nodular swelling above the level of the ankle . The fourth stage entails above knee swelling whereas the fifth stage involves joint fixation as a result of surrounding soft tissue overgrowth [3] . Podoconiosis can be identified clinically in endemic areas ( above 1200 m ) without the need to do laboratory tests because it usually presents with bilateral and asymmetric swelling on the lower limbs with rare groin involvement unlike the lymphatic form of elephantiasis [4] . Similarly , the nervous system is intact in podoconiosis and there is neither loss of sensation nor thickened nerves or trophic ulcers unlike leprosy [5] , [6] . Podoconiosis can be prevented , early forms of the disease can be treated , disease progression can be curbed and the disease can potentially be eliminated as a public health burden with low technology but effective measures such as washing feet with soap and water on a regular basis and wearing protective shoes consistently [7] , [8] , [9] . High prevalence of podoconiosis has been reported in many parts of highland Africa: Ethiopia [10] , Cameroon [11] , Rwanda [12] , Burundi , Sudan [13] , Uganda [14] , Tanzania [15] , Kenya [16] , the islands of Bioko , Sao Tome and Principe [17] , and Equatorial Guinea [18] . Up to one million cases are estimated to exist in Ethiopia , of whom one-third belong in the economically productive age group [10] . Recent studies in southern and western Ethiopia estimated the prevalence of podoconiosis to be 5 . 5% [10] and 2 . 8% [19] , respectively . Although the Amhara Region in northern Ethiopia is one of the regions burdened by podoconiosis in specific highland districts , there have been no recent studies to assess the prevalence , clinical features , and socio-economic burden of the disease . To our knowledge , the only two studies that provided data on the prevalence of the disease in Amhara region date back more than 40 years [20] , [21] . In June 2010 , International Orthodox Christian Charities ( IOCC ) , a non-government organization , started the first podoconiosis program in East Gojam Zone , Amhara Region . The program aims to address podoconiosis prevention , awareness , and care and support activities . To strengthen the services provided in East Gojam Zone and scale up to West Gojam Zone , there was an evident need for baseline data to direct the public health interventions . Therefore , the aim of this study was to assess the burden of podoconiosis in East and West Gojam Zones of Amhara Regional State , northern Ethiopia . Specifically , the study aimed to answer questions including , but not limited to , overall , gender- and age-specific prevalence; manifestations of acute attack episodes ( acute adenolymphangitis or ALA: painful inflammation of the foot and leg with swollen lymph nodes and fever ) ; clinical disease stage; treatment seeking behavior; and foot washing and shoe wearing practices of patients .
Ethical clearance was obtained from the Amhara Regional Health Bureau . Support letters were obtained from East and West Gojam Zonal Health Departments and Woreda Health Offices . Oral informed consent was obtained from each study participant after reading the written consent form to them , since most of the respondents were not able to read and write . The interviewers confirmed the participant's oral consent by signing on the respective consent form for each interview as per the guideline of the ethical review Board of the Amhara Regional Health Bureau . When children aged under 18 years ( the legal age for giving consent for research in Ethiopia ) were encountered , consent was obtained from their parents or guardians . The use of verbal consent was approved by the ethical review committee because the majority of the study participants cannot read and write . This study was a cross-sectional community-based house-to-house survey . The study was conducted in East and West Gojam Zones of Amhara Regional State . All villages ( Ketena ) in known podoconiosis-endemic kebeles ( the lowest level government administrative structure in Ethiopia ) were included in the house to house case enumeration . Identification of the study area was based on a report by IOCC's podoconiosis treatment center , written in 2010 summarizing information from key local informants . The study participants were residents of the selected kebeles and podoconiosis cases in all households with podoconiosis . The Ethiopian administrative structure is organized hierarchically , with multiple Zones in each Region . Each Zone contains multiple Woredas ( equivalent to districts ) . Each Woreda contains Kebeles and there are villages with multiple households in each Kebele . A convenience non-random sampling method was used to select two Zones . A list of woredas ( government administrative units equivalent to districts ) in East and West Gojam Zones , known for the presence of podoconiosis based on expert opinion and key informants , was prepared . Second , a random sampling technique was applied to select two woredas , one from each Zone . Third , kebeles from each of these two woredas were sampled randomly proportional to their population size in each woreda . A total of 20 kebeles from the two woredas in East Gojam and West Gojam Zones ( 7 kebeles from East Gojam and 13 kebeles from West Gojam ) were selected . All households in the selected kebeles were assessed for the presence of podoconiosis cases through interviews with the household head followed by clinical examination of cases by community health extension workers ( HEW ) . Households with podoconiosis cases were included for individual podoconiosis case interviews by clinical nurses . In households where there was more than one podoconiosis patient , all patients were interviewed , and physical examination and measurement of leg circumference were done . Data collection was done house-to-house by trained HEWs supervised by nurses that work in the respective woredas . The HEWs were responsible for house-to-house enumeration of podoconiosis cases and the nurses were responsible for supervising the activities of the HEWs and the detailed assessment of podoconiosis cases ( i . e . , interviewing and physical examination of patients ) . All HEWs and nurses received training from the team of researchers before performing data collection . The training consisted of techniques and approaches for obtaining informed consent from prospective participants , interviewing techniques , podoconiosis diagnostic features , clinical staging according to a standard method [3] , assessment of ALA , measurement of leg circumference ( the largest circumference between the levels of the ankle and knee measured using a tape , to a precision level of the nearest centimeter [3] ) , assessment of presence of open wounds , and features that differentiate lymphoedema and leg swelling resulting from podoconiosis from other diseases such as leprosy and filarial elephantiasis . Furthermore , these data collectors were trained on how to advise patients to wear shoes and wash their feet to control disease progression at the end of every interview . A pre-test of the actual data collection process and the data collection tools was conducted immediately after the training of the data collectors . The pretest was done in two kebeles ( one in West Gojam Woreda and the other in East Gojam Woreda ) which were not included in the main survey . The pretests were evaluated in terms of ( i ) organization of the fieldwork and coordination between the team of investigators , supervisor nurses and HEWs; ( ii ) ability of the HEWs to effectively conduct the census and complete the questionnaires; ( iii ) ability of the supervisor nurses to correctly diagnose and stage podoconiosis , and identify ALA symptoms; ( iv ) completeness , skip patterns , flow and clarity of the questionnaire . At the end of the pre-test , the trainees brought back the data they collected to the training centre . The completed questionnaires were checked by the trainers . Discussion on the challenges the trainees faced during data collection and on the data collection tools was held and the questionnaires were revised accordingly . The data collection tool was a structured questionnaire . The questionnaire was developed in English , translated into Amharic and back translated into English to check consistency . The questionnaire was sub-sectioned thematically into socio-demographic characteristics , podoconiosis history , clinical features , treatment-seeking behavior , sources of water , walking practices , foot hygiene and shoe wearing practices . Data were entered and analysed using the Statistical Package for Social Sciences ( SPSS ) software v . 17 . 0 . The overall prevalence of podoconiosis was calculated as the ratio of the number of patients with podoconiosis to the total population surveyed aged 15 years and over . Statistical significance was tested using the Chi-squared test or t-test as appropriate . The level of significance was set at α of 0 . 05 .
A total of 17 , 553 households with 51 , 017 members aged 15 years and above were included in the present survey . Of the surveyed households , 9 . 7% had one or more podoconiosis patients . A total of 1 , 319 podoconiosis patients that provided consent and were available during the interview participated in the detailed patient interview . Characteristics of these patients are presented in Table 1 . Almost all patients were in the age group 15–64 ( the age group that includes economically active individuals in Ethiopia ) , did not read and write , and were farmers . More women than men patients were divorced ( 22 . 5% vs . 3 . 6% , χ2 = 102 . 3 , p<0 . 0001 ) . The prevalence of podoconiosis was found to be 3 . 3% ( 95% CI = 3 . 2% to 3 . 6% ) in people aged 15 years and above . The prevalence was 3 . 3% ( 95% CI = 3 . 1% to 3 . 6% ) in Debre Eliyas and 3 . 4% ( 95% CI = 3 . 2% to 3 . 6% ) in Dembecha Woredas . The male to female ratio was 0 . 98∶1 . More than 87% of the patients fell within the 15 to 64 year age group , and less than 2% were under the age of 15 years ( Table 2 ) . The median age of onset of leg swelling was 22 years ( range: 10 to 77 years ) . On average , patients sought treatment 5 years ( SD = 6 . 9 ) after the start of the leg swelling , predominantly at health centers ( 39 . 8% ) and from traditional healers ( 39 . 1% ) . More study subjects had symmetric bilateral swelling than unilateral or asymmetric bilateral swelling . Most subjects had second or third clinical stage disease ( Table 3 and Figure 1 ) . Nearly all ( 97 . 9% ) patients had mossy lesions and 53% had open wounds on at least one of their legs . On average , patients had five episodes of ALA per year and had 90 ALA morbidity days per year . Among patients who had ALA episodes more frequently than once per month ( n = 323 ) , 73 . 1% had ALA during the two weeks prior to the date of interview . Similarly , 94 . 4% of the ALA episodes reported in the year prior to the interview happened in the most recent six months . Nearly half of the participants ( 49 . 8% ) had ALA during the interview . Physical examination of the interviewees that had ALA showed that hot ( 49 . 8% ) and tender ( 60 . 2% ) swelling , and inguinal lymphadenopathy ( 62 . 1% ) were common features ( Table 4 ) . Half of the study subjects ( 49% ) that had ALA in the past one year ( n = 1 , 299 ) sought treatment for the pain . The commonest treatment facilities visited were health centers ( 28 . 7% ) and traditional healers ( 29 . 4% ) . Among patients that went to other places for the treatment of ALA ( n = 196 ) , most ( 80 . 6% ) went to Tsebel ( holy water ) places . Patients stated that on average they spent five days in bed during episodes of ALA . Over half of the study participants ( 54 . 5% ) said ALA commonly occurred during the hot and dry seasons , whereas 20% said the episodes were not season specific . The most common ALA precipitating factors mentioned by patients were long walks ( 72 . 2% ) , ‘mitch’ ( effect of the sun inducing inflammation , 52 . 1% ) , laborious work ( 28 . 9% ) , and dust ( 13 . 2% ) . The most common coping measures employed by patients to reduce morbidity during episodes of ALA were staying in bed ( 55 . 6% ) , resorting to less laborious work ( 44 . 2% ) , use of antibiotics ( 25 . 8% ) and Hareg Resa ( a local herb that is boiled generating steam that is inhaled by patients believed to have mitch , 20 . 5% ) . The median ages of first use of shoes and socks in the area were 22 and 23 years , respectively . About 40% of the patients said that they had one pair of shoes . More men than women owned more than one pair of shoes ( 61 . 1% vs . 50 . 5%; χ2 = 11 . 6 p = 0 . 001 ) . Most study participants suggested that they need three pairs of shoes per year . The types of shoes worn by the study participants at the time of interview were covered hard plastic ( 33 . 3% ) followed by canvas ( 20 . 9% ) and berebaso/gilet ( open sandals locally made from tires ) ( 13 . 2% ) . During the interview , 23 . 6% of the respondents were observed to be barefoot of whom most ( 65 . 3% ) were women . Men were more likely to wear open , non-protective shoes . There was no statistically significant association between gender and use of protective shoes ( p = 0 . 92 ) . Based on patients' estimates , the average one-way walking time to the nearest water source for washing feet was 19 minutes ( SD = 15 . 7 ) . The average one-way walking time to the nearest field and nearest market were 20 minutes ( SD = 14 . 9 ) and 54 . 5 minutes ( SD = 50 . 1 ) , respectively . On average , the respondents travelled to their nearest field and to market nine ( SD = 10 . 9 ) and four ( SD = 3 . 9 ) times per month , respectively . On observation , 46 . 8% of patients had clean feet , 25 . 1% had dirty feet , 13 . 9% had cracked feet and 13 . 9% had both dirty and cracked feet . The reported average frequency of foot washing was seven times a week . There was no statistically significant difference between men and women in the frequency of foot washing ( p = 0 . 12 ) and foot washing with soap ( p = 0 . 33 ) ( Table 5 ) .
This study presents the largest of all household surveys of podoconiosis in Ethiopia conducted over the past ten years . It is the first community-based study of podoconiosis in the Amhara region , the second largest region in Ethiopia . Men and women were equally affected by podoconiosis , as found in the Wolaita study ( 1∶0 . 98 ) [10] but in contrast to the Gulliso ( 1∶2 . 6 ) [19] and Ocholo ( 1∶4 . 2 ) [22] studies . The prevalence of podoconiosis in the present study area ( 3 . 3% ) was higher than the recent reports for Gulliso woreda in western Ethiopia ( 2 . 8% ) [19] but lower than that reported among long-term residents in Ocholo village in southern Ethiopia ( 5 . 1% ) [22] , among resettlement scheme residents in Illubabor , western Ethiopia ( 9 . 1% ) , among residents in Gera and Didessa towns in southern Ethiopia ( 8–10% ) [23] , among residents in Midakegn district , central Ethiopia [24] , and in Wolaita , southern Ethiopia ( 5 . 5% ) [10] . The prevalence falls within the earliest national estimate of 0 . 4% to 3 . 7% across fifty-six markets [20] . The prevalence of podoconiosis found in the present study was greater than the previous estimates in Gojam of 2 . 4% based on market counts by Oomen [20] and 2 . 3% based on school enquiry by Price [21] nearly four decades ago in Debre Markos , the capital of East Gojam Zone . These studies had limitations since they were based on market counts of cases and school enquiry of students from villages and were therefore likely to underestimate the overall prevalence . Nevertheless , the absence of decline in prevalence of podoconiosis after four decades clearly reflects that podoconiosis has remained neglected in the Amhara region . Based on our findings , we reviewed the potential opportunities and challenges for primary and secondary prevention of podoconiosis in Gojam . Primary prevention consists of avoiding prolonged skin to soil contact by wearing protective shoes and socks . Secondary prevention requires regular foot hygiene , and the use of antiseptic soaks and emollients . Early evidence of effectiveness of this treatment in reducing leg circumference and disease stage and in improving quality of life has recently emerged from a small , uncontrolled follow-up study by Sikorski et . al [9] . Since most cases of podoconiosis in the present study were in the early stages of 2 and 3 , secondary prevention is potentially possible in this area . The study also revealed several challenges to primary and secondary prevention . First , there were serious deficiencies in protection against the soil with footwear . Suboptimal shoe-wearing behavior was reported even among those owning shoes , and observation at the time of interviews confirmed a substantial proportion of barefoot respondents . The types of shoes worn by most patients were not considered protective . Although men owned more pairs of shoes than women , there were similar low levels of shoe wearing and foot washing practice among men and women resulting in almost equal prevalence of disease . However , more advanced stages were seen among women . The similar average age of onset of leg swelling and age of first shoe wearing indicate prolonged contact with the soil and delay in protection . Secondly , there was substantial continuous contact with irritant soil . In addition to daily work as subsistence farmers , the frequency of travel and walking distances to and from water sources , markets and fields considerably increased the duration of contact with the soil . Limited access to water ( average round trip of 40 minutes ) may explain poor foot hygiene as patients prioritize water for drinking and cooking before washing their feet . The average time spent travelling to get water in Gojam was greater than in Gulliso , western Ethiopia ( average round trip of 20 minutes ) and also greater than the WHO recommended maximum ( 30 minutes round trip ) [25] . This will constitute a considerable challenge for primary and secondary prevention of podoconiosis in Gojam . Thirdly , the long interval between onset of swelling and seeking treatment indicate an important delay in accessing secondary prevention to control disease progression . Most of the podoconiosis cases in our study were found in the highland areas away from the towns where most health centers are based . There was no podoconiosis treatment in Amhara Region before the establishment of the IOCC podoconiosis prevention and treatment center in June 2010 . The patients who visited health centers for treatment may not have received appropriate treatment , forcing them to try other forms of support including traditional medicine . Previous studies have demonstrated health professionals' misconceptions surrounding podoconiosis and stigmatizing attitudes towards patients , so patients who attended formal health facilities may not have received treatment [26] . Fourthly , limited knowledge and misconceptions about the disease by the patients themselves may also act as a barrier against primary and secondary prevention by delaying treatment seeking behavior [27] . In Wolaita , adopting avoidant coping strategies led to patient isolation and reduced access to health care [28] . Similarly , linking ALA to a range of experiences including mitch resulted in poor treatment seeking and resorting to traditional medicine for a significant proportion of the patients . This study reinforces recent evidence from Gulliso indicating the enormous burden imposed by ALA among podoconiosis patients [19] . The frequency of attacks , duration of pain and number of bed days due to ALA were all considerable . Physical examination of the interviewees reporting ALA at the time of interview confirmed the widespread frequency of the problem . Although our study did not compare the financial status of patients with unaffected people in the area , previous studies have shown the large economic burden imposed by podoconiosis [25] . This burden arises because of the concentration of the disease in the productive age group as seen in this study and the effect of ALA hampering productivity [10] , [29] . In conclusion , the prevalence of podoconiosis in Gojam is almost identical to that described in the 1970s by Price and Ooman [20] , [21] indicating that the disease has been almost entirely neglected since that time . Significant challenges remain in increasing protective shoe-wearing practices , improving access to water for washing , and encouraging earlier treatment seeking . However , given that early stages of disease were predominantly observed , if treatment is offered , it is likely to be effective . | Podoconiosis is non-infectious elephantiasis that affects barefoot people that have prolonged exposure to red clay soil . It is common in tropical Africa , central America and northern India . Podoconiosis presents as bilateral below knee swelling . Podoconiosis can be both prevented and controlled by consistently washing feet , wearing shoes , and using antiseptics and emollients . This survey is the biggest conducted to date in Ethiopia: 17 , 553 households in East and West Gojam Zones of northern Ethiopia were included , and 1 , 704 patients were identified . We interviewed patients in detail about manifestations of acute attacks ( painful inflammation of the foot and leg with swollen lymph nodes and fever ) , clinical disease stage , treatment seeking , foot washing and shoe wearing practices . We found the prevalence of podoconiosis to be 3 . 3% . Most patients were farmers , uneducated and within the economically active age group . There was no gender difference in occurrence of podoconiosis and in foot washing practices . The onset of leg swelling and the age of first shoe wearing were similar . We also found delayed treatment seeking and many days confined to bed during acute inflammatory episodes . We conclude that podoconiosis imposes a huge burden in northern Ethiopia . | [
"Abstract",
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"Methods",
"Results",
"Discussion"
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] | 2012 | Podoconiosis in East and West Gojam Zones, Northern Ethiopia |
Assembly of the essential , tubulin-like FtsZ protein into a ring-shaped structure at the nascent division site determines the timing and position of cytokinesis in most bacteria and serves as a scaffold for recruitment of the cell division machinery . Here we report that expression of bacteriophage λ kil , either from a resident phage or from a plasmid , induces filamentation of Escherichia coli cells by rapid inhibition of FtsZ ring formation . Mutant alleles of ftsZ resistant to the Kil protein map to the FtsZ polymer subunit interface , stabilize FtsZ ring assembly , and confer increased resistance to endogenous FtsZ inhibitors , consistent with Kil inhibiting FtsZ assembly . Cells with the normally essential cell division gene zipA deleted ( in a modified background ) display normal FtsZ rings after kil expression , suggesting that ZipA is required for Kil-mediated inhibition of FtsZ rings in vivo . In support of this model , point mutations in the C-terminal FtsZ-interaction domain of ZipA abrogate Kil activity without discernibly altering FtsZ-ZipA interactions . An affinity-tagged-Kil derivative interacts with both FtsZ and ZipA , and inhibits sedimentation of FtsZ filament bundles in vitro . Together , these data inspire a model in which Kil interacts with FtsZ and ZipA in the cell to prevent FtsZ assembly into a coherent , division-competent ring structure . Phage growth assays show that kil+ phage lyse ∼30% later than kil mutant phage , suggesting that Kil delays lysis , perhaps via its interaction with FtsZ and ZipA .
The replication and lytic functions of bacteriophage λ rapidly diminish Escherichia coli viability and lead to ultimate host death by lysis [1] . Decades-old research uncovered a secondary mode of λ-induced host cell death using a defective prophage containing only the immunity region and the PL operon . Under derepressed conditions , E . coli cells containing this defective prophage filament and eventually die . The PL operon ( Figure 1A , top ) contains no genes essential for lytic growth except N , but consists of accessory genes that may be essential in certain circumstances , such as the red recombination genes ( exo , bet , and gam ) [2] . A series of nested deletions beginning at attL and int , and removing successive prophage genes toward PL , initially defined the region of this secondary , lysis-independent killing function [3] . These deletions identified a putative gene located in this region named kil ( host killing by an induced λ prophage ) responsible for host cell filamentation , loss of viability , and ultimate death . However , because kil overlaps the gam and cIII genes [4] , some questions remained concerning the exact identity of kil and the possible influence of gam and cIII on host killing [2] , [5] . Later experiments further mapped Kil activity to the annotated kil open reading frame [6] . Additionally , separate experiments inducing expression of the annotated kil open reading frame from a plasmid verified that this region was responsible for causing cell filamentation and a loss of viability [7] . Although assumed to encode a protein , the product of the annotated kil gene has not been identified . Likewise , the host cell target of the kil gene product ( Kil ) is unknown . Given the strong cell filamentation and loss-of-viability phenotypes associated with kil expression , we reasoned that Kil likely targets a component of the E . coli cell division apparatus . Cytokinesis in most bacteria studied to date involves assembly of the highly conserved prokaryotic tubulin-homolog FtsZ into a ring-shaped structure at the nascent site of divison [8] . FtsZ undergoes GTP-dependent polymerization into single stranded polymers in vitro , which in turn are able to bundle together through lateral interactions that are enhanced by certain buffer conditions or bundling agents [9] . In E . coli , the assembly of the FtsZ ring at mid-cell prior to division is stabilized and linked to the membrane through the formation of a ‘proto-ring’ that includes the essential transmembrane-anchored ZipA and membrane-associated FtsA proteins [10] . Once the proto-ring is formed , a coterie of both essential and non-essential proteins is recruited in a partially step-wise fashion to form a mature complex termed the divisome . The divisome contains all the components necessary to divide the cell through a combination of constriction , a switch from lateral cell wall growth to septum ( crosswall ) formation , and cell separation [11] . Cell survival requires proper coordination of division with other cell cycle events , such as growth , DNA replication , and chromosome segregation . This coordination is largely controlled by precisely regulating the timing and position of FtsZ ring formation by altering FtsZ assembly dynamics [12] . In E . coli , this regulation is chiefly controlled through the combined activities of the Min system ( MinCDE ) and the nucleoid-occlusion factor SlmA [8] , [13] . SlmA is a protein that binds specific regions of the chromosome and prevents FtsZ from assembling over unsegregated nucleoids [14] , [15] , [16] , [17] , [18] . The Min system functions to prevent FtsZ from assembling in DNA-free regions of cell poles through the inhibitory activity of MinC , whose localization is controlled by MinD and MinE [13] , [19] , [20] , [21] . Another well-described inhibitor of FtsZ assembly is SulA , which is activated following DNA damage as part of the SOS response to inhibit cell division until genetic errors are corrected [22] , [23] , [24] . Whereas numerous additional host factors that regulate cell division have been described in several species [11] , [25] , little work has been done characterizing potential regulation by phage factors . Rac prophage and bacteriophage Mu each contain a gene also named kil [26] , [27] . Despite their identical names , however , these kil genes and their predicted peptide products have no significant similarity to one another or to λ kil . Rac kil expression prevents FtsZ ring formation , which blocks cell division resulting in filamentation; no details on the direct target or the mechanism of its activity have been reported [26] . In contrast , expression of the Mu kil gene results in spherical E . coli cells [27] , indicative of inhibiting cell elongation by this temperate member of the Myoviridae . The cryptic lambdoid prophage Qin ( Kim ) and its widespread relatives also contain two factors known to affect cell division [28]: DicB , which acts in place of MinD to bring MinC into position to inhibit FtsZ ring formation [29] , [30] , and dicF , which encodes an antisense RNA that inhibits ftsZ translation [31] . Finally , the cryptic e14 phage-like element of E . coli contains the sfiC gene , which inhibits FtsZ assembly following SOS induction similarly to SulA ( SfiA ) [32] , [33] , [34] . Here , we report that λ kil expression from a defective prophage , from a plasmid , or during induction of a complete , lytic-competent λ lysogen inhibits cell division due to a block in FtsZ ring formation . We verify that Kil encodes a peptide , and show that it acts independently of well-characterized host systems of FtsZ assembly regulation . We further identify and characterize Kil-resistant ftsZ and zipA mutant alleles , demonstrate inhibition of FtsZ assembly in vitro by an affinity-tagged Kil derivative , and discuss potential models for Kil activity on FtsZ assembly . Finally we address the relevance of kil to λ biology , demonstrating that Kil acts during normal lytic growth of λ phage and suggesting that this activity can delay cell lysis .
To investigate the role of kil expression on E . coli cell division , we first used a bacterial strain ( CC4506 ) harboring a defective λ prophage in which a modified operon is under control of a temperature-sensitive ( ts ) allele ( cI857 ) of the phage CI repressor . In this kil+ strain , a point mutation destroys the start codon of cIII , a cat cassette replaces sieB to ea10 , and a tet cassette replaces gam through int ( Figure 1A ) . Consistent with previous findings [6] , CC4506 cells formed long , non-dividing filaments after derepression of the PL operon by thermo-inactivation of the CI857 repressor at 42°C ( Figure 1B ) , and lost viability ( Figure 1C ) . In contrast , an isogenic strain with the start codon of kil destroyed by a point mutation ( CC4512 ) , continued to divide normally following induction of the prophage and retained viability , similar to the W3110 background strain ( Figure 1B & C ) . The loss of cell viability , presumably caused by the division blockage elicited by kil expression , could be rescued in the short term by returning E . coli filaments to low temperature conditions that restored CI857 repressor activity ( Figure 1C , bottom left ) . However , prolonged kil expression at 42°C ( ∼6 hours ) prevented restoration of growth even after returning cells to conditions that repress kil expression ( Figure 1D ) . To identify the potential target of kil expression , we screened a pBR322 library of E . coli chromosomal fragments for multi-copy suppression of kil-induced toxicity at 42°C . Consistent with kil expression targeting cell division , multi-copy expression of an ∼5 . 4-kb fragment including the ftsQAZ operon completely suppressed toxicity . Similarly , low-copy ( pSC101 ) expression of the ftsQAZ operon alone suppressed kil-induced toxicity , but less efficiently ( Figure 1E ) . Analysis of the kil-expressing strain containing pSC101 with ftsQZ , ftsQA , or ftsZ alone confirmed that this suppression derives specifically from ftsZ ( but not ftsQA ) over-expression . Further supporting the link between the toxicity of kil expression and cell division , an independent multi-copy suppressor screen identified sdiA ( Figure 1E ) , whose product increases ftsQAZ operon transcription [35] . Filamentation of E . coli cells could arise either from a failure to form FtsZ rings at the nascent division site , or from a defect in divisome maturation and septal synthesis after FtsZ ring assembly . Over-expression of ftsZ could conceivably help suppress either of these mechanisms to permit Kil-resistance . We therefore determined by immunofluorescence microscopy whether FtsZ rings continued to form in E . coli cells following derepression of kil under PL control . At 30°C , when PL is repressed , both CC4506 ( kil+ ) and CC4512 ( kil− ) cells were normal-sized on average ( 3 . 1±0 . 1 and 3 . 1±0 . 2 µm , respectively ) compared to W3110 wild-type control cells ( 3 . 1±0 . 2 µm ) ( Figure 2A , top ) . Immunofluorescence microscopy ( IFM ) with antibody against E . coli FtsZ demonstrated that cells of each strain contained a single band of FtsZ signal localized at midcell in the majority ( 92 . 4±1 . 3% to 94 . 0±1 . 5% ) of the populations , on average ( Figure 2B , top ) . However , upon a shift to growth at 42°C and the resulting kil expression , CC4506 cells continued to grow at a normal rate into nondividing filaments ( >10 µm ) , before reaching stationary phase ( Figure 2A , bottom ) . In contrast , W3110 and CC4512 control strains still displayed normal average cell lengths at 42°C ( 3 . 3±0 . 55 and 3 . 2±0 . 48 µm , respectively ) . Kil induction also led to a rapid ( <5 minutes ) loss in FtsZ rings observable by IFM , leaving only a few cells with normal FtsZ localization on average ( 8 . 3±2 . 2% ) . FtsZ localization in W3110 cells was unaffected on average ( 92 . 1±1 . 7% ) until 90 minutes post-temperature-shift when cells entered stationary phase and FtsZ ring frequency decreased sharply ( Figure 2B , bottom ) . Notably , although CC4512 ( kil− ) cells displayed normal cell lengths during growth at 42°C ( Figure 2A , bottom ) , this strain background still showed a small , but significant , effect on FtsZ ring formation in the first minutes following temperature shift , with ring frequency dropping to an average of 73 . 0±4 . 6% . However , by 20 minutes , these cells had recovered normal FtsZ ring frequencies ( 92 . 7±0 . 07% ) , unlike the CC4506 kil+ counterpart strain where FtsZ ring frequency remained below 10% ( Figure 2B , bottom ) . This suggests that some other factor in CC4512 has a minor and transient effect on FtsZ assembly upon shift to high temperature . IFM micrographs corresponding to the data in Figure 2A & B showed normal medial FtsZ localization in both W3110 and CC4512 kil− strains after five minutes post temperature shift to 42°C ( Figure 2C ) and all time points observed thereafter ( data not shown ) . CC4506 kil+ cells showed normal FtsZ localization at 30°C , but FtsZ immunostaining became patchy and diffuse after only five minutes of kil induction at 42°C . This mislocalization continued throughout growth at 42°C , sometimes forming into broad , unproductive FtsZ foci ( possibly helices ) along the cell filament ( Figure 2C ) . This pattern , typical upon FtsZ ring formation inhibition in vivo , suggests that FtsZ is unable to form a coherent ring-shaped structure in the presence of Kil , thus preventing septum formation and cell division . Due to the observed kil-independent , transient effect on FtsZ ring formation ( Figure 2B , bottom ) , we chose to study the effects of kil outside of any phage context by expressing the gene from a plasmid . This enabled us to be certain that any observed effects were caused by Kil alone , and eliminated the need to expose E . coli cells to temperature shock . We cloned the kil gene downstream of the arabinose-inducible promoter in pBAD33 and transformed the resulting plasmid ( pDH104 ) into W3110 . W3110 pDH104 cells grown in non-inducing conditions divided normally , comparable to the W3110 background containing empty vector , indicating that uninduced levels of Kil are low . Consistent with the prophage results , expression of kil from the plasmid proved sufficient to induce cell filamentation through a rapid loss of FtsZ ring formation ( Figure 2D ) . Similar results were also obtained by cloning kil under Plac ( IPTG-inducible ) control in pRR48 ( data not shown ) . Proper FtsZ assembly and subsequent cell division in E . coli is dependent on levels of FtsZ relative to other division components [36] . Though alterations in FtsZ levels are not a normal part of division regulation in E . coli [37] , conditions that artificially elevate or reduce available FtsZ result in FtsZ mislocalization and cell filamentation [38] . A trivial explanation for the loss of FtsZ ring formation upon the induction of λ kil is that its product , the presumed Kil peptide ( see below ) , somehow alters FtsZ protein levels . A known example of this occurs with the cryptic prophage-derived dicF , which encodes a small RNA that blocks ftsZ mRNA translation by an antisense mechanism [31] . However , quantitative immunoblotting of FtsZ in CC4506 cells induced for kil expression showed levels of FtsZ approximately equivalent to those in uninduced CC4506 counterparts or in W3110 and CC4512 controls ( Figure 3A ) . Furthermore , induction of kil from pBAD33 or pRR48 in W3110 similarly had no effect on FtsZ compared to levels seen in uninduced cells or cells with empty plasmid ( data not shown ) . These results suggest that the kil product does not act by altering FtsZ levels . Another possibility is that Kil acts indirectly through an endogenous system of FtsZ assembly inhibition , such as the SOS-response activated SulA [22] , [23] , [39] , [40] , MinC [41] , [42] , [43] , [44] , or the nucleoid-occlusion factor SlmA [14] , [15] , [16] , [17] . This was important to rule out because another phage-derived dic gene , dicB , encodes a small protein that inhibits FtsZ ring assembly by mimicking MinD to recruit MinC to midcell [29] , [30] . To investigate a possible contribution of the SOS-inducible protein , SulA , in Kil activity , we examined the effects of kil induction from pBAD33 in a WM1074 ΔsulA::kan background . WM1074 is a wild-type derivative of MG1655 , whereas the characterizations of Kil presented above utilized the K12 derivative W3110 . Expression of kil from pBAD33 in WM1074 caused filamentation and inhibition of FtsZ ring formation ( Figure 3B ) comparable to that seen in W3110 ( Figure 2D ) . Addition of 0 . 2% arabinose to sulA− cells resulted in cell filamentation ( Figure 3C ) indistinguishable from that seen for the sulA+ background , verifying that Kil does not act through SulA and that it confers a similar phenotype in a different strain background . As with the ΔsulA::kan background , induction of kil from pBAD33 in ΔminCDE::kan or ΔslmA::kan backgrounds also increased cell filamentation ( Figure 3C ) , arguing that neither MinC nor SlmA are involved in Kil activity . As shown previously , minCDE mutant cells already have division defects due to the presence of extra FtsZ rings , and are elongated . Upon kil induction all FtsZ rings disappear into irregular patchy localization , and the already-long minCDE mutant cells grow into even longer filaments . Together these data demonstrate that unlike dicF or DicB , the kil product does not act through any of the well-characterized endogenous host systems that regulate FtsZ assembly . The preceding results suggest that Kil inhibits FtsZ ring formation , potentially through direct interaction with FtsZ . To further investigate this interaction , we generated ftsZ mutant alleles by recombineering with randomly mutagenized ftsZ PCR fragments , selecting for those that allowed survival at 42°C in a thermo-inducible kil+ and thermo-sensitive ftsZ ( ftsZ84 ) strain ( see Materials and Methods ) . This strategy identified two mutant alleles of ftsZ with increased resistance to kil expression , ftsZV208A and ftsZL169R ( Figure 4A ) . According to a recently reported Mycobacterium tuberculosis FtsZ crystal structure [45] , both of these residues are located in the subunit interface of FtsZ protofilaments . Specifically , FtsZV208 lies in the conserved T7-loop region , which during polymerization inserts into the nucleotide-binding region near the FtsZL169 residue in the N-terminal domain of an adjacent subunit ( Figure 4B ) . To verify that these alleles confer Kil resistance , we replaced the wild-type ftsZ gene of a fresh kil+ strain with each mutant allele . Spot dilutions of the resulting strains verified that the ftsZV208A or ftsZL169R alleles conferred resistance to Kil compared to the wild-type ftsZ allele control , although the appearance of the spots suggests that the strains acquired suppressors fairly readily at 42°C ( Figure 4C ) . IFM on the kil+ strains harboring ftsZV208A or ftsZL169R in place of the native wild type allele showed normal-sized cells with FtsZ rings present at 30°C when kil expression is repressed ( Figure 4D ) . However , in addition to normal medial ring localization , FtsZV208A appeared to also form frequent rings or puncta at cell poles ( marked by arrowheads ) and occasional ring doublets ( marked by an asterisk ) . Similarly , FtsZL169R sometimes formed aberrant FtsZ structures ( marked by asterisks ) , along the long axis of the cell . These observations suggest that although these FtsZ mutants are competent for assembly and cell division , they seem to be overly stable and insensitive to endogenous regulators of FtsZ assembly . Unlike in the wild-type ftsZ allele background , short-term exposure to kil expression at 42°C did not cause cell filamentation in ftsZV208A or ftsZL169R backgrounds ( Figure 4D ) , consistent with their partial resistance to Kil as seen in spot dilutions ( Figure 4C ) . The apparent insensitivity of the mutant FtsZV208A and FtsZL169R proteins to endogenous regulation seen at 30°C is even more obvious at 42°C upon PL operon derepression . For example , FtsZV208A localizes predominantly to one cell pole at higher temperature ( only ∼14% midcell localization after 40 min of kil induction ) . FtsZL169R , in contrast , forms multiple rings throughout the length of cells at higher temperatures , likely contributing to their slightly longer cell lengths . These cells also contain apparent inclusions visible by DIC microscopy ( Figure 4D ) , which may be from high levels of non-interactive Kil . Importantly , the inclusion bodies and mutant FtsZ localization abnormalities did not arise from inappropriate FtsZ levels in the cell , as both mutant FtsZs were present at levels comparable to the wild-type control ( Figure 4E ) . The above spot dilution and IFM data demonstrate that the isolated ftsZV208A and ftsZL169R mutant alleles confer partial resistance to kil as expressed from PL upon de-repression at 42°C , permitting FtsZ assembly , albeit aberrant , and preventing cell filamentation . To further address the Kil-resistance of these mutant ftsZ alleles and avoid the mutant FtsZ mislocalization seen at higher temperatures , the above strains were transformed with pRR48-kil and investigated by expressing kil by IPTG induction at 30°C . In contrast to the resistance of the ftsZ mutant alleles to kil expressed at 42°C from PL , they were unable to confer resistance to short-term induction of kil from plasmid pRR48 ( 1 mM IPTG ) . Rings formed by FtsZWT , FtsZV208A , or FtsZL169R were all rapidly lost upon pRR48-kil induction ( Figure 4F , top and center panels ) , leading to cell filamentation ( Figure 4F , bottom panels ) . It is possible that the levels of Kil obtained from plasmid expression were higher than those obtained from its native PL context , but we noticed that longer inductions of kil from PL also ultimately overcame the initial resistance of FtsZV208A or FtsZL169R ( data not shown ) . These results suggest that although these ftsZ alleles confer partial resistance to Kil from their abnormal assembly characteristics , Kil is still able to overcome these mutant FtsZ proteins under some conditions . The abnormal localization of FtsZV208 and FtsZL169R , such as to cell poles , suggested that these mutants may have increased filament stability and a certain general resistance to endogenous FtsZ assembly inhibitors , not just the action of λ Kil . Additionally , WM1074 cells transduced from ftsZWT to ftsZV208A or ftsZL169R had a minicell-producing phenotype ( data not shown ) , further implicating resistance to FtsZ assembly inhibition by MinC . To determine whether the ftsZV208A and ftsZL169R alleles make the strains generally resistant to FtsZ assembly inhibitors , we monitored resistance to over-expression of sulA or to a his-minCD translational fusion ( minCD ) . We transformed the kil+ ( under chromosomal PL control ) strains harboring ftsZV208A or ftsZL169R with either pDSW210-his-minCD or pBAD33-sulA and grew them at 30°C , where kil is not expressed whether or not the plasmids are induced . Induction of either minCD or sulA caused FtsZWT cell filamentation and a loss of FtsZ ring formation after 40 min . However , in the presence of FtsZV208 or FtsZL169R , high levels of SulA or MinCD had no apparent effect on cell length in the same time frame ( Figure 5A & B ) . Consistent with prior results , FtsZV208 and FtsZL169R localized normally at 30°C in non-inducing conditions for either plasmid . Similar to observations for the FtsZ mutants upon kil expression at 42°C ( Figure 4C ) , induction of sulA , and particularly minCD , at 30°C caused both FtsZV208 and FtsZL169R to mislocalize , often at cell poles ( Figure 5A & B ) . This suggests that , in contrast to FtsZWT , both FtsZ mutants are able to assemble in the presence of high SulA or MinCD levels , but that this assembly is abnormal and persists at new cell poles following division , similar to what was seen for these FtsZ mutant proteins in the presence of Kil . The continued growth and division of ftsZV208A or ftsZL169R mutant cells upon short-term induction of either minCD or sulA suggests that these cells remain more viable than wild-type cells , despite many mislocalized FtsZ rings . Spot dilutions of ftsZWT , ftsZV208A , or ftsZL169R cells carrying pDSW210-his-minCD or pBAD33-sulA onto plates with relevant inducers at 30°C ( to ensure no kil expression ) verified that both ftsZV208A and ftsZL169R increased cell viability upon sulA over-expression ( Figure 5C ) . Although minCD over-expression blocked wild-type FtsZ ring formation and led to cell filamentation ( Figure 5A ) , these cells remained partially viable in spot dilutions upon full induction with IPTG ( 1 mM ) . However , ftsZV208A and ftsZL169R conferred an approximately 10-fold improvement in that viability ( Figure 5C ) . As expected , cell growth was normal in the absence of inducer ( data not shown ) . As with kil resistance ( Figure 4D ) , the ftsZV208A allele showed somewhat stronger resistance to minCD and sulA over-expression compared to the ftsZL169R allele ( Figure 5C ) . Previously characterized ftsZ mutant alleles , ftsZ9 ( ftsZ18ΩV-G – a two residue insertion ) and ftsZ114 ( ftsZF268C ) , show general resistance to both MinC and SulA [46] , [47] , [48] . We therefore tested whether these alleles were also resistant to λ kil expression . For these experiments we utilized the original PB143 ftsZ− background strains that contain ftsZWT , ftsZ9 , or ftsZ114 on a low-copy number plasmid under constitutive expression ( pBEF0 , pBEF9 , and pBEF114 ) and transformed each with pBAD33-kil . FtsZWT and FtsZ114 , which displays ∼50% GTPase activity of the wild-type FtsZ , were unable to resist inhibition by Kil and failed to form detectable FtsZ rings in the presence of Kil . However , FtsZ9 , which is nearly devoid of GTPase activity ( 10% of normal ) more strongly resisted Kil inhibition and was able to form some detectable FtsZ rings ( Figure 5D ) . This result in the presence of Kil is comparable to the partial , weak resistance of FtsZ114 ( and the relatively strong resistance of FtsZ9 ) to inhibition by SulA or MinC [46] , [47] , [48] . The ability of these strains to form colonies with or without kil induction correlates well with their Kil resistance by IFM ( Figure 5E ) . The ftsAR286W ( ftsA* ) gain of function mutation can bypass the loss of several normally essential cell division proteins , including ZipA or FtsK , as well as partially suppress an ftsQ ts mutant [49] , [50] , [51] , [52] . This ability to stabilize the divisome prompted us to ask whether ftsAR286W cells might be more resistant to Kil . However , we found that ftsAR286W conferred no resistance to Kil produced from pRR48 , as cells formed extensive filaments ( data not shown ) . As a control , we also tested a ftsAR286W ΔzipA::aph double mutant for resistance to Kil , expecting similar results . Strikingly , these double mutant cells were entirely resistant to kil expression from pRR48 , manifesting neither filamentation nor a loss of FtsZ ring localization following induction ( Figure 6A ) . This strain background was also resistant to induction of kil from pBAD33 ( data not shown ) . These results suggested that the absence of zipA , not the presence of ftsAR286W , imparts resistance to Kil . Note that zipA+ ftsAR286W cells are slightly shorter , while ΔzipA ftsAR286W cells are slightly longer than their wild-type counterparts [49] . To verify that the observed kil-resistance is specifically caused by an absence of zipA , we added the gene back in trans by introducing the compatible plasmid pKG110-zipA into the ΔzipA ftsAR286W strain containing pRR48-kil . Uninduced levels of zipA expressed from pKG110 in these cells did not perturb cell division on their own but were sufficient to restore kil-sensitivity ( Figure 6B ) . Cells with the empty vector or expressing another early division protein , zapA [53] , [54] , [55] , did not restore Kil-sensitivity in this ΔzipA ftsAR286W strain ( Figure 6B ) . Unlike the isolated Kil-resistant ftsZ alleles , ΔzipA ftsAR286W cells remained sensitive to both SulA and MinC inhibition ( Figure 6C ) , arguing that the Kil resistance of the ΔzipA ftsAR286W strain is not a general effect on FtsZ . Taken together , these results strongly suggest that ZipA is specifically required for the effect of Kil on FtsZ assembly and subsequently cell division . If ZipA were required for Kil-mediated inhibition of FtsZ as inferred from the above genetic experiments , we reasoned that it should be possible to isolate mutations in the essential zipA gene that confer Kil-resistance in a wild-type ftsA background without abrogating ZipA's normal function in the divisome . The powerful phenotype of Kil-induced cell filamentation and death allowed us to isolate spontaneous Kil-resistant mutants . To discourage the isolation of mutations that simply reduce kil expression or inactivate the kil product itself , we constructed a ‘double kil’ strain harboring both pBAD33-kil and pRR48-kil in WM1074 . We isolated spontaneous Kil-resistant colonies by plating cultures of this strain on LB agar with both IPTG and arabinose ( Figure 7A ) . Several independent isolates were saved and their zipA loci amplified for DNA sequencing . All isolated kil resistant strains contained one of two mutations in zipA , encoding ZipAL286Q and ZipAL286R , respectively . The C-terminal domain of ZipA containing this residue ( ZipAC ) directly interacts with the C terminus of FtsZ [56] , [57] , [58] ( Figure 7B ) . As both alleles seemed to have similar properties , we chose ZipAL286Q for further investigation . To assess the general activity of ZipAL286Q in cell division , we first cloned it into pKG110 and transformed the resulting plasmid into a WM1074 wild-type background . We then introduced the ΔzipA::aph allele by P1 transduction . The transduction efficiencies into cells harboring pKG110-zipAL286Q or pKG110-zipAWT were similar , verifying that ZipAL286Q functions normally in cell division in place of the essential ZipAWT . Low-level induction of either zipAWT or zipAL286Q from pKG110 ( with 0 . 5 µM sodium salicylate ) in the WM1074 ΔzipA::aph background resulted in cellular levels of ZipA comparable to those in wild-type cells ( Figure 7C ) and caused no discernable differences in growth or division phenotypes . Additionally , overproduction of ZipAWT [59] or ZipAL286Q caused cell filamentation with multiple FtsZ rings present ( data not shown ) . To verify the Kil-resistance of zipAL286Q , we replaced the zipAWT gene of the W3110 strain harboring kil under PL control with zipAL286Q ( or zipAL286R ) by recombineering . The resulting strains displayed normal cell division phenotypes and resistance to kil upon derepression of promoter at 42°C ( Figure 7D and data not shown ) . Finally , a fresh WM1074 wild-type background transduced with zipAL286Q linked to a ptsH<>tet marker was resistant to kil expression from pRR48 , but remained sensitive to both SulA and MinCD inhibition ( Figure 7E ) , demonstrating that this zipA allele is specific for resistance to Kil . Finally , random mutagenesis of zipA by PCR generated a mutation in a nearby residue , Q290R , ( Figure 7B ) which conferred the same level of Kil resistance to cells as the L286 mutations ( data not shown ) , further arguing for the importance of this region of ZipA for Kil activity in vivo . Early research on the kil gene identified a putative and abundantly produced protein product [60] . However , subsequent research established that this protein was actually λ Ea10 , and that kil is likely expressed at only low levels from the PL promoter of λ phage ( [2] and see below ) . Initial attempts to identify , purify , or chemically synthesize the protein product of the kil gene failed , prompting us to investigate whether the kil gene truly encodes a protein . Previous work established that insertion of a stop codon within the 5′ portion of kil or disruption of its stop codon abolishes Kil activity ( [6] and Figure 1 ) , but did not definitely show whether the loss of activity was caused by changes at the protein level or the nucleotide alterations themselves . To test this definitively , we inserted an amber stop mutation into the thirty-first codon ( normally encoding tyrosine ) of kil ( kiltyr31UAG ) to terminate translation prematurely . Cells harboring the kiltyr31UAG allele under PL control survived at 42°C . To determine if cell survival was due to interrupted translation or due to a mutation in the RNA , we introduced the supF gene , which encodes a suppressor tRNA that would supply the originally encoded tyrosine amino acid at the amber mutation . The presence of supF restored Kil activity , confirming the product of kil functions as a protein ( Figure 8A ) . To obtain purified Kil protein , we cloned the kil gene into a pET vector , adding an N-terminally encoded FLAG-tag to create a his6-flag-kil fusion for expression and protein purification by cobalt-affinity chromatography . Purification of His6-FLAG-Kil yielded a single prominent band on Coomassie-stained SDS polyacrylamide gels that migrates near its predicted ∼10 . 5 kDa molecular weight with an estimated purity of >95% ( Figure 8B ) . Induction of his6-flag-kil in BL21 ( DE3 ) cells inhibited cell division , indicating that the tagged fusion is active ( data not shown ) . We found that optimal induction occurred in the absence of zipA and in the presence of extra FtsZ; we therefore preferentially expressed his6-flag-kil in a BL21 ( DE3 ) ftsAR286W ΔzipA::aph pBS58 background . Surprisingly , his6-flag-kil expression seemed to augment Kil activity in vivo , blocking cell division even in the absence of zipA ( data not shown ) . Notably , this phenotype occurs with all tested Kil fusion derivatives , and no instances of complete suppression of any fusions have been isolated to date . With no antibody against Kil , we cannot know if this effect is merely because Kil fusions permit higher protein levels compared to wild-type untagged Kil , or if this effect arises from the increased length/size of a tagged Kil fusion . Nonetheless , because ZipA is required for the activity of normal , untagged Kil on FtsZ assembly in vivo , we investigated whether Kil interacts directly with ZipA or FtsZ . We incubated purified , renatured His6-FLAG-Kil ( see Materials and Methods ) in the presence of α-FLAG M2 affinity resin with or without purified FtsZ and/or purified , His-tagged ZipA C-terminal domains ( denoted ZipAC for wild type zipA and ZipA*C for zipAL286Q ) . Following binding of the resin by His6-FLAG-Kil , samples were washed extensively and retained proteins bound to the resin and/or His6-FLAG-Kil were visualized on Coomassie-stained SDS-polyacrylamide gels ( Figure 8C ) . As expected , His6-FLAG-Kil remained bound to the resin following the washes , whereas FtsZ , ZipAC , or ZipA*C were not resin-associated when incubated on their own without any His6-FLAG-Kil . However , FtsZ and each ZipAC remained in samples following washes in the presence of His6-FLAG-Kil , arguing in favor of direct specific interactions between His6-FLAG-Kil and FtsZ , and between His6-FLAG-Kil and either ZipAC . In support of this , bovine serum albumin added to all the input mixtures at concentrations similar to those of FtsZ and ZipAc showed no specificity for the resin . Notably , His6-FLAG-Kil – ZipAC interacts similarly with wild-type ZipAC and the mutant ZipA*C , and the His6-FLAG-Kil – FtsZ interaction does not seem to be significantly augmented by either ZipAC under the conditions of this experiment . Together these data suggest that Kil is capable of interacting independently with either FtsZ or the C-terminal domain of ZipA , and the L286Q mutation in ZipA does not prevent it from interacting with His6-FLAG-Kil . Our in vivo evidence suggests that Kil inhibits FtsZ assembly , and that this activity normally requires the presence of ZipA . To test whether Kil could directly act to inhibit FtsZ assembly , we used sedimentation assays with purified FtsZ and His6-FLAG-Kil purified from the BL21 ( DE3 ) ftsAR286W ΔzipA::aph pBS58 background to ensure that little ZipA would be present in reactions . Not surprisingly , purified FtsZ does contain a small amount of copurified ZipA ( data not shown ) , barely detectable by immunoblotting and not visible at the FtsZ concentrations used for sedimentation reactions . We initiated FtsZ assembly with the addition of 1 mM GTP and then sedimented polymer bundles of FtsZ by centrifugation . Sedimentation primarily detects polymer bundles of FtsZ , and in our buffer conditions; little FtsZ sedimented in the presence of GTP alone , consistent with the relatively poor bundling capability of E . coli FtsZ [61] . Addition of calcium increased FtsZ polymer bundling and thus sedimentation , as previously reported [62] , [63] . Strikingly , addition of His6-FLAG-Kil to FtsZ assembly reactions greatly reduced the amount of polymer sedimentation in the presence of calcium ( Figure 8D ) , suggesting that the purified tagged Kil can directly inhibit FtsZ assembly in vitro . To address the potential contribution of ZipA to Kil activity on FtsZ , we added purified ZipAC or ZipA*C to additional sedimentation reactions . As previously reported [56] , ZipAC increased polymer bundling , measured as sedimentation , similar to the effect of calcium . ZipA*C also enhanced FtsZ sedimentation to similar levels . As with calcium , addition of His6-FLAG-Kil to the assembly reactions greatly reduced polymer sedimentation in the presence of either ZipAC or ZipA*C ( Figure 8E ) . His6-FLAG-Kil co-sedimented with the small fraction of FtsZ polymer bundles that assembled in its presence , either with calcium ( Figure 8D ) or the ZipAC domains , but did not sediment on its own ( Figure 8E ) . This suggests that Kil may multimerize in the presence of FtsZ and/or form stable Kil-FtsZ complexes . Together , these data demonstrate that His6-FLAG-Kil interacts with FtsZ and inhibits its assembly in vitro , and suggest that the normal importance of ZipA in vivo for this activity is bypassed by the in vitro conditions . To test the effect of Kil on FtsZ GTP hydrolysis rates , we performed GTPase activity assays under conditions identical to the sedimentation assays . GTP hydrolysis by FtsZ is induced by monomer-monomer interactions within a newly formed protofilament . If Kil inhibits FtsZ assembly by sequestering monomers , similar to SulA , it should strongly inhibit FtsZ GTP hydrolysis activity . If instead Kil severs FtsZ protofilaments or decreases FtsZ polymer bundling , this would increase the pools of monomers available to make new protofilaments , which should increase GTP hydrolysis . The background GTPase activity signal from His6-FLAG-Kil , ZipAC , or ZipA*C was negligible ( ∼0 . 5 GTP/min/FtsZ ) , and FtsZ displayed a rate of ∼3 . 2–4 . 1 GTP/min/FtsZ independent of bundling agent ( Figure 8F ) . The presence of Kil in assembly reactions caused a small but significant increase in FtsZ GTP hydrolysis to 4 . 3–5 . 3 GTP/min/FtsZ . The effect of Kil was most pronounced in the presence of calcium ( a 1 . 4-fold increase ) and least pronounced in the presence of ZipA*C ( Figure 8F ) . Though modest , the across-the-board increase in GTP hydrolysis in the presence of Kil is consistent with either inhibition of FtsZ protofilament extension , severing protofilaments , or inhibition of FtsZ protofilament bundling . Our data inspire a model in which Kil interacts with FtsZ in a ZipA-dependent manner in vivo to inhibit FtsZ ring assembly and cause cell filamentation . The location of kil in the λ genome ( Figure 1A ) suggests that it would be expressed transiently during initial establishment of lysogeny and then upon exit of lysogeny when entering the lytic cycle . Normally , induction of a λ lysogen leads to rapid host cell lysis , but the potential role and importance of kil in this process is unknown . We therefore chose to investigate kil in its native context in intact E . coli λ lysogens , with the cI857 allele to facilitate universal λ lysogen activation . Induction of a λ lysogen by a shift to 42°C led to an increase in cell length up to 40 minutes post-induction ( Figure 9A ) , at which time cells began to lyse . This increase in cell length is similar to that observed upon similar PL derepression in a defective prophage ( Figure 2A ) , but does not proceed as rapidly or reach the point of extreme filamentation seen during kil expression . Induction of the λ lysogen also led to a rapid loss of FtsZ rings ( Figure 9B ) . The observed increase in cell length and rapid , complete loss of FtsZ ring assembly following induction of the λ lysogen did not occur in an isogenic kil− mutant . Although kil− cells still entered the lytic cycle with no observable delay , cell length did not increase significantly in the absence of kil ( Figure 9A ) . Although FtsZ ring formation was partially inhibited under these conditions , perhaps by other λ components or through indirect effects on host cell physiology , the majority of kil− cells still contained FtsZ rings sufficient to maintain division ( Figure 9B ) . These data indicate that kil expression has a dramatic effect on FtsZ ring formation , and subsequently on cell length , during the induction of a λ lysogen into the lytic cycle . Finally , to ask whether kil− phage are compromised for reproduction , we monitored a single cycle of phage growth of cI857 and a nonpolar deletion of kil , cI857kilΔ7 , in MG1655 at 39°C ( Figure 9C ) . Overall phage yields were not significantly affected by the absence of kil , although we observed a reproducibly shorter lysis time for the cI857 kilΔ7 phage relative to kil . Kil effects on host cell lysis have been previously reported [7] , [64] .
The normal involvement of ZipA in vivo suggests that Kil may interact with both FtsZ and ZipA in the cell , a possibility supported by our in vitro interaction data . One explanation for the in vivo ZipA requirement is that ZipA may act specifically to recruit Kil to FtsZ protofilaments ( Fig . 9D ) . The location of the mutations in ZipA that confer resistance to Kil is consistent with this idea . Although these mutations are in the FtsZ-binding domain of ZipA , the mutated L286 residue is not predicted to interact directly with the C-terminus of FtsZ , facing away from it in the co-crystal structure [58] . The L286 mutations could have an allosteric effect on ZipA-FtsZ interactions , but cells carrying zipAL286Q divide normally , so these interactions cannot be grossly altered . Moreover , over-expression of zipAL286Q causes cell division defects similar to that seen with zipAWT ( data not shown ) , further arguing that the mutant is not dysfunctional in its effects on FtsZ assembly . According to this model , ZipAL286Q would be less able to recruit Kil to midcell than ZipAWT , presumably because of decreased ZipA-Kil interactions . However , our in vitro interaction data suggest no difference between His6-FLAG-Kil interaction with ZipAC or ZipA*C . This disparity could stem from the additional length/size of the His6-FLAG-Kil fusion ( that seems to act independently of ZipA in vivo unlike untagged Kil ) , or from the absence of full-length ZipA in the in vitro experiments . Additionally , results from the sedimentation experiment suggest that the high concentrations of Kil present in reactions might cause it to multimerize in the presence of FtsZ . Further work is required to clarify the precise mechanism of Kil activity and the role of ZipA in this activity . The proposed ZipA-mediated recruitment of Kil to FtsZ in vivo is reminiscent of mechanisms proposed for other FtsZ inhibitors . For example , the cryptic prophage-derived DicB protein uses ZipA to recruit the DicB/MinC complex to the membrane-associated FtsZ ring [65] . However , unlike DicB , Kil inhibits FtsZ directly and does not require MinC for its inhibitory activity ( Figure 3 ) . The B . subtilis EzrA protein is related to ZipA in that it binds FtsZ and shares ZipA's unusual topology of N-terminal integral membrane domain and C-terminal cytoplasmic domain . A mutant of EzrA lacking this N-terminal transmembrane domain is able to inhibit FtsZ assembly directly in vitro , but in vivo this mutant does not localize to the membrane , thus lowering the local concentration of EzrA to a point where its interaction with FtsZ is no longer inhibitory [66] . By analogy , ZipA might serve to concentrate Kil near the membrane where FtsZ is located , enhancing its inhibition of FtsZ assembly ( a function no longer needed in vitro ) . Kil is predominantly hydrophobic , and although it is not predicted to contain any transmembrane segment , it is predicted to have peripheral membrane association [67] . If this is the case , interactions with ZipA could still enhance localization of Kil specifically to midcell and/or position Kil optimally to interfere with FtsZ assembly within the in vivo environment that is absent in our in vitro FtsZ assembly assays . Normal FtsZ assembly dynamics ensure that FtsZ rings properly form both temporally and spatially to link cell division with other cell cycle events [12] . Kil acts independently of the well-characterized host-derived systems of regulation , but may act on FtsZ assembly in a generally similar fashion . In support of this notion , our two Kil-resistant ftsZ alleles , ftsZV208A and ftsZL169R , display a general resistance to multiple forms of FtsZ assembly inhibition , and ftsZ alleles previously reported for SulA and MinC-resistance [46] , [47] , [48] also show similar degrees of resistance to Kil . Despite having lesions in the conserved T7-loop and near the nucleotide-binding region , these two mutant FtsZs are capable of FtsZ ring assembly in vivo , although many rings form at potential division sites other than midcell , including cell poles . This is consistent with a bias away from disassembly and towards stabilization . Such a bias would lead to resistance to disassembly factors such as MinC , even if Kil inhibits by a different mechanism . This resistance is incomplete , because Kil produced from a plasmid rapidly ablates FtsZV208A and FtsZL169R rings , and even Kil produced from the PL operon eventually overwhelms their ability to form rings and encourages acquisition of suppressors . Recent publication of a crystal structure for a GDP-bound protofilament of FtsZ from Mycobacterium tuberculosis implicates residues adjacent to those corresponding to V208 and L169 of E . coli FtsZ as being involved in conformational changes at the subunit interface between straight , GTP-bound filament and curved , GDP-bound filament forms [45] . The general resistance of the FtsZV208A and FtsZL169R mutants to disassembly factors suggests that they may favor the GTP-bound form and have reduced GTP hydrolysis . The properties of other inhibitor-resistant FtsZ mutants fit this idea . The FtsZ9 mutant has extremely low GTPase activity and is highly resistant to SulA , MinC or Kil . In contrast , the FtsZ114 mutant , which has ∼50% of normal GTPase activity , confers only partial resistance to Kil or MinC [48] . The inhibitory activity of His6-FLAG-Kil on FtsZ filament bundling would be predicted to induce greater FtsZ subunit turnover and thus increase GTP hydrolysis , which is what we observe , and is similar to the effects of some other factors that inhibit FtsZ bundling such as EzrA [66] , [68] . Consistent with Kil blocking FtsZ bundling , FtsZ localization in the presence of Kil becomes patchy and diffuse , possibly into broad helices , suggesting that FtsZ filaments still assemble , but fail to condense into a mature , bundled ring . An alternative explanation for the increased GTPase activity is that Kil may also prevent FtsZ protofilament elongation , which would increase the pool of free FtsZ monomers available to form dimers and oligomeric filaments capable of hydrolyzing GTP . A handful of other phage-encoded factors have been identified that block bacterial cell division , including a newly-described T7 gene product that also acts on FtsZ [69] . Other factors act through host-cell regulation of FtsZ assembly ( DicB and dicF [28] , [29] ) or through an unknown mechanism ( Kil of prophage Rac [26] ) . The lytic SPO1 phage of Bacillus subtilis encodes a peptide that inhibits host division prior to lysis [70] , but acts at a stage following FtsZ ring formation ( Haeusser and Margolin , unpublished data ) . Therefore , it seems that a variety of phage are able to target host cell division through unique peptides that act by diverse mechanisms . Suppression of host cell division by cryptic prophage-encoded factors has previously been implicated in increasing host adaptation to stress and resistance to antibiotics [71] , and it is possible that kil benefits the host in some way during the lysogenic state . In contrast to inhibiting FtsZ ring formation , a recent report described the role of B . subtilis Φ29 p1 in promoting phage replication through association with assembled FtsZ [72] . This strategy allows Φ29 to utilize an existing host cell scaffold to organize and optimize viral DNA production , but how a phage would benefit from perturbing FtsZ ring formation and inhibiting cell division is less clear . The original studies on kil− λ phage suggested that they still replicate , assemble , and lyse the host comparably to kil+ counterparts , with similar burst sizes [3] , [6] , [73] . However , these studies used cIII67 mutant phage , which may be more prone to lysogeny and mask a kil− growth phenotype . Here , we show that Kil activity is evident upon lytic induction of λ , and demonstrate that , in a single cycle of growth , the kil− mutant phage has a shorter latent period and causes earlier cell lysis . Although we did not observe a decrease in yield for the kil mutant phage , in some circumstances a shorter latent period may result in lower phage yieldl . The larger average volume of kil+ cells relative to kil− cells might translate into a longer time to induce lysis . Cell size changes may also affect the lysis-lysogeny decision [74] . ln addition to affecting the timing of lysis , kil could benefit phage by creating a non-compartmentalized host that permits easier and more accurate phage reproduction . In this scenario , activation of cell division and construction of a septum could interfere with excision of the λ lysogen , its replication , or its packaging . Previous studies with kil from the lambdoid P22 phage of Salmonella found that kil expression was required for efficient lytic growth of abc− mutants lacking anti-RecBCD activity , increasing burst size by eight fold [75] . This suggests Kil activity becomes important during conditions of high recombination frequency . By analogy , B . subtilis Maf induces a temporary block in cell division during natural competence development that permits efficient , uninterrupted DNA recombination [76] . The lack of an obvious kil− phenotype for λ phage in original studies [3] and the subtle defects reported here could arise from biased , unnatural laboratory growth conditions , or an overlapping function with other phage components , such as gam . The abrupt but temporary loss of FtsZ rings upon PL derepression in the absence of kil and the relatively large percentage of cells that lose FtsZ ring formation even in an otherwise complete kil− λ lysogen suggest that Kil may not act completely independently . Future experiments will focus on clarifying the molecular mechanism of Kil-mediated FtsZ ring disruption and uncovering its role in λ phage biology .
All E . coli strains used are listed in Table 1 . Standard genetic methods including transformation and P1 vir transduction were used for strain construction . Recombineering methods for strain construction [77] , [78] are described in a section below . Cells were grown in Luria-Bertani ( LB ) medium at 30°C or 32°C , as indicated , for temperature-sensitive ( ts ) strains under permissive conditions and 42°C under non-permissive conditions , or at 37°C for all non-ts strains . Optical density readings at 600 nm ( OD600 ) were measured using a UV-1601 or UV-1800 spectrophotometer ( Shimadzu ) . LB medium was supplemented with ampicillin ( 50 µg/ml; Fisher Scientific ) , kanamycin ( 50 µg/ml; Sigma-Aldrich ) , chloramphenicol ( 20 µg/ml; Acros Organics ) , tetracycline ( 10 µg/ml; Sigma-Aldrich ) , and spectinomycin ( 100 µg/ml; Sigma-Aldrich ) , as needed . Gene expression from vectors derived from pET28- , pET15- ( Novagen – EMD Millipore ) , and pRR48 [79] was induced with 1 mM isopropyl-β-D-galactopyranoside ( IPTG ) ( Fisher Scientific ) . Gene expression from pBAD33-derived vectors [80] was induced at a final concentration of 0 . 2% L- ( + ) -arabinose ( Ara ) ( Sigma-Aldrich ) . Gene expression from pKG110-derived vectors ( J . S . Parkinson , University of Utah ) was either uninduced or induced with 0 . 5 µM sodium salicylate ( Mallinkrodt ) , as indicated . A PCR test [81] confirmed that LT447 and LT1566 were monolysogens . Standard protocols or manufacturers' instructions were used to isolate plasmid DNA , as well as for restriction endonuclease , DNA ligase , PCR , and other enzymatic treatments of plasmids and DNA fragments . Enzymes were purchased from New England BioLabs , Inc . ( NEB ) or Invitrogen . Plasmid DNA was prepared using the Wizard Plus SV Minipreps DNA Purification Kit , PCR and digest reactions were cleaned up using the Wizard SV Gel and PCR Clean-up System , and chromosomal DNA was prepared using the Wizard Genomic DNA Purification Kit ( Promega ) . KAPA HiFi HotStart DNA polymerase ( Kapa Biosystems ) or Phusion High-Fidelity DNA polymerase ( Thermo Scientific – NEB ) or Platinum Taq ( Invitrogen ) were used for PCR reactions in a MyCycler Thermal Cycler ( Bio-Rad ) . Oligonucleotides were purchased from Sigma-Aldrich or IDT and their sequences are listed in Table S1 . The final versions of all cloning products were sequenced to verify their construction . DNA sequencing was performed by GeneWiz ( South Plainfield , NJ ) , SeqWright ( Houston , TX ) or SAIC-Frederick , Inc . ( Frederick , MD ) . DNA bands were visualized using an AlphaImager Mini System ( ProteinSimple ) and DNA concentrations were estimated with a NanoDrop ND-1000 Spectrophotometer ( Thermo Scientific ) . Protein concentrations were determined using the Coomassie Plus Assay ( Themo Scientific – Pierce ) . Molecular graphics and analyses were performed with the UCSF Chimera package ( http://www . cgl . ucsf . edu/chimera ) . Chimera is developed by the Resource for Biocomputing , Visualization , and Informatics at the University of California , San Francisco ( supported by NIGMS P41-GM103311 ) . All plasmids are listed in Table 2 . Kil expression plasmids: For pRR48-kil , the kil coding sequence was amplified from CC4506 chromosomal DNA with primers DPH199 and 200; the PCR product was digested with PstI and SpeI , then ligated into a pRR48-derivative where the original multiple cloning site had been replaced ( NdeI to SalI ) with that of pKG110 . For pDH104 ( pBAD33-kil ) , the kil coding sequence with its native ribosome-binding site was amplified from CC4506 chromosomal DNA with primers DPH217 and 202; the PCR product was digested with XmaI and PstI , then ligated into pBAD33 . Toxic overexpression of minCD: For pWM2737 ( pDSW210-his-minCD ) the minD coding sequence was amplified with primers WM960 & 356 , the PCR product was digested with SalI and HindIII , then ligated into pWM2735 ( pDSW210-his6-minC ) [44] to create sequence encoding an uninterrupted His-tagged , MinCD translational fusion ( minCDtf ) . Complementation of ΔzipA cells with the zipAL286Q allele: pDH145 ( pKG110-zipAL286Q ) was constructed as previously published for pKG110-zipA [82] , but using DPH615 ( zipAL286Q ) chromosomal DNA as template . Plasmid pKG110-zapA was constructed by Daisuke Shiomi in the same manner as pKG116-zapA [82] . Plasmids for protein purifications: For pET28-zipAC the C-terminal ZipA domain coding sequence was amplified by Tushar Beuria with primers WM269 & 268; the PCR product was digested with BamHI and XhoI , then ligated into pET28a . As primer WM268 did not include a stop codon , this construct produces His6-ZipAC-His6 . Construction of pDH146 ( pET28-zipA*C ) was therefore performed identically , but with DPH615 chromosomal DNA as template , to produce a double His-tagged version of ZipAC that harbors the L286Q mutation . For pDH139 ( pET28-flag-kil ) the kil coding sequence with its stop codon was amplified from CC4506 chromosomal DNA in two steps ( primers DPH309 & 170 , followed by DPH310 & 170 ) to add sequence encoding a FLAG-tag to the 5′ end of kil , in-frame with the His-tag-encoding codons of the plasmid . The resulting product was digested with BamHI and HindIII , then ligated into pET28a . Plasmid pDH149 ( pET15-flag-kil ) was constructed by digesting pDH139 with NcoI and XhoI , then ligating the his6-flag-kil insert into identically-digested pET15b . Recombineering was done using published methods [77] , [78] . Briefly , the Red functions were expressed either from the defective prophage or from a recombineering plasmid such as pSIM18 , a hygromycin resistant plasmid encoding the temperature-sensitive CI857 repressor and a portion of the PL operon containing gam , exo , and bet . Log phase cells propagated at 32°C were subjected to a 15 minute heat pulse in a 42°C shaking water bath to induce the Red functions , quickly chilled in an ice-water slurry , and prepared for electroporation by washing . DNA , either double- or single-stranded , was introduced into the cells by electroporation . When a drug marker was selected , the cells were allowed to recover for several hours in 1 mL broth before plating . When point mutations were introduced with ∼70 base oligonucleotides , the cells were plated non-selectively on LB agar plates after a 30 minute recovery time , either at 42°C for direct selection of Kil-resistant alleles or at 32°C for screening by PCR , as described below . In some cases oligonucleotides with additional sequence changes in third positions ( wobble positions ) were used to create mutations . As described [83] , these additional wobble changes were placed near the change of interest , creating a configuration of mispairs that is not recognized by the E . coli mismatch repair system , without changing the amino acid sequence . This allows both high-efficiency recombineering and detection of recombinant chromosomes with PCR . When wobble changes were introduced , between 12–20 colonies were analyzed , using one oligonucleotide that hybridized specifically to the recombinant sequence , paired with a second nearby oligonucleotide; this primer pair should not yield product with the parental sequence . Positive candidates were purified to single colonies and about a dozen of these single colonies were again subjected to the same PCR analysis . The region of interest from positive candidates identified in the second round of PCR screening was sequenced . Sequences for oligonucleotides used are listed in Table S1 . A seven-codon in-frame deletion within kil , removing codons 20–26 , was initially constructed in XTL241 ( HME6 gam<>cat-sacB ) and then moved to a phage . The deletion was built into a hybrid oligonucleotide , LT793 , which along with an oligonucleotide to the downstream gam gene , LT795 , were used to amplify a PCR product containing the deletion and spanning the region containing the counter-selectable marker . Recombineering was used to replace the cat-sacB . After introduction of the PCR product into electrocompetent XTL241 induced for the Red functions , cultures were grown overnight and recombinants were selected on sucrose plates at 32°C . Candidate colonies were purified on sucrose and confirmed to be chloramphenicol-sensitive . Primers AW24 and LT795 were used to amplify the region containing the deletion , which was confirmed by sequencing . In contrast to the kil+ control , cells containing the deletion did not filament after several hours of growth at 42°C , and formed colonies after overnight growth at 42°C . A lysate of λ cI857red3 was grown on cells containing the seven-codon deletion to allow marker rescue from the defective prophage onto the phage . The lysate was plated on LT352 . Plaques were picked into 0 . 5 mL TMG ( 10 mM Tris base , 10 mM MgS04 0 . 01% gelatin ) and 2 µl of the pickate was used for PCR with oligonucleotides AW24 and LT795: the difference in size between the deletion and the wild-type alleles was resolvable on a 1 . 2% agarose gel . The deletion phage was purified by another round of plating on LT352 and a high titer plate lysate was grown from a purified plaque on C600 . CC4506 was transformed with a pBR322-based library containing 1 . 5–5 kb Sau3A fragments of LE392 genomic DNA cloned into pHDB3 [84] and transformants were selected on LB ampicillin agar at 42°C . Ampicillin-resistant colonies that survived Kil induction were pooled , plasmid DNA was isolated and CC4506 was transformed with this enriched plasmid population to confirm suppression . The Sau3A library was kindly provided by Nadim Magdalani ( NIH ) . Plasmid pJP10 was isolated by this procedure . Plasmid pNB15 was isolated by a similar procedure except the pBR322-based library was constructed by cloning 2–4 Kb Sau3A fragments of JS549 genomic DNA into pBR322 cut with BamHI . The ftsZ gene was amplified from W3110 with oligonucleotides XMZ325 and XMZ326 , using standard PCR conditions . This ftsZ PCR product was used as a template for mutagenic PCR [85] with the same oligonucleotides . This randomly mutagenized pool of ftsZ PCR fragments was used for recombineering into strain AW34 , which carries the thermo-sensitive ftsZ84 allele ( G105S ) linked to leuD::Tn10 , a defective λ prophage with thermo-inducible kil expression , and a mutS<>amp allele to prevent host mismatch repair during recombination . After a 30 minute recovery in broth at 30°C , aliquots were plated on nitrocellulose filters on LB plates and incubated at 32°C for 3 hours . Filters were then transferred to 42°C pre-warmed LB plates and these plates were subsequently incubated overnight at 42°C to select for growth . This procedure simultaneously selects for recombinants that replace ftsZ84 with the wild type allele and for resistance to λ Kil expression . A lysate of P1 vir was grown on a pool of the temperature-resistant isolates . This lysate was used to transduce the Kil-expressing strain AW41 , selecting tetracycline resistance at 42°C . Thermo-resistant colonies were purified and their ftsZ gene was amplified with colony PCR; the resulting PCR products were sequenced . Several isolates of the ftsZV208A mutation were obtained , and only one isolate of ftsZL169R . One isolate of each of the mutant types was chosen for further characterization . The mutations were introduced into a fresh background by P1 transduction at 32°C , selecting for the linked leuD<>Tn10 and screening for temperature resistance . Competent WM1074 cells were sequentially transformed with pBAD33-kil and pRR48-kil and the resulting strain was verified to have a kil+ phenotype upon induction of kil from either plasmid . A culture of this ‘double kil’ strain was grown to mid-logarithmic phase and induced with IPTG and arabinose simultaneously . 100 µL of stationary phase culture was plated on LB agar supplemented with appropriate antibiotics , IPTG , and arabinose and grown overnight at 37°C . All resulting colonies were purified , then grown in liquid media to freeze samples . Chromosome purification and PCR amplification of the zipA locus in the saved isolates showed that all contained a zipAL286Q mutation , while the original WM1074 pBAD33-kil pRR48-kil strain contained zipAWT sequence . A second isolation of spontaneous Kil-resistant mutants was carried out using a similar protocol , with the only difference being that cells were grown in liquid culture under non-inducing conditions into stationary phase , then plated on medium containing IPTG and arabinose . All isolated colonies from this second experiment contained a zipAL286R mutation . Recombineering using ssDNA can be very efficient with up to 75% of the cells being recombinants [83] . Therefore , recombineering with ssDNA can be used to isolate and map mutations , and these techniques were used throughout this work . For example , when mutagenic PCR was used to isolate zipA mutations , in one case sequencing revealed a double mutation , zipAA245T , Q290R . We designed and ordered oligonucleotides to make each mutation separately via recombineering . Recombineering-proficient cells prepared on CC4506 were transformed with each oligonucleotide separately or both together , outgrown for 30 minutes , then diluted and spot-titered on LB plates at 30°C and 42°C . We found that only one of the oligonucleotides , MH82 , was necessary and sufficient to create a mutation that suppressed Kil-dependent killing . Cells used for spot titers were taken from the same cultures used for fixation unless as noted below . A ten-fold dilution of these cultures was taken approximately forty minutes after induction ( or control conditions ) , unless otherwise noted , and then serially diluted into fresh LB media in a 96-well plate using a multichannel pipette . A flame-sterilized and cooled , metal-pronged tool was then used to replica-plate spots of serially diluted culture onto LB plates with added components and incubation conditions as indicated in the text and figures . Photos of plates were taken in a FluoroChem 8800 system with its accompanying camera and software ( Alpha Innotech ) . Spot titers in Figures 4C and 7D were done as follows: An overnight culture was diluted 100-fold and cells were grown at 30° for 2 hours in LB . Ten-fold serial dilutions of these cultures were made in TMG ( see above ) and 10 µl was spotted on pre-warmed LB plates and incubated at the indicated temperatures . To generate the data in Figure 1D , an overnight culture of CC4506 was diluted 70-fold into 15 mL of LB broth and grown to an OD600∼0 . 25 at 32° . The culture was diluted in 10-fold increments from 100 to 10−5 . At time “0” , 0 . 1 mL samples of appropriate dilutions were spread on prewarmed 42° LB plates on which we had placed a sterile 82 mm ( diameter ) nitrocellulose filter . After the indicated time , sterile forceps were used to move the filter to a 32° plate . These LB plates were incubated overnight at 32° and colonies counted . Overnight cultures were started from −80°C strain stocks and grown under appropriate antibiotic selection and permissive conditions . Overnight cultures were diluted into fresh medium , grown to mid-logarithmic phase , then the OD600 of individual cultures was adjusted to a uniform OD600 = 0 . 025 with fresh medium . Cultures were grown for approximately 2 doublings at permissive conditions and then shifted to non-permissive conditions ( or kept as permissive controls ) at time point zero . Unless otherwise indicated , samples of culture for microscopy were taken approximately 40 minutes after shifting to non-permissive conditions . Cells were fixed with methanol and processed for immunofluorescence microscopy ( IFM ) as previously published [86] using lysozyme ( Sigma ) treatment for 5 minutes and antibodies diluted in bovine serum albumin ( Fisher Scientific ) . Primary polyclonal rabbit α-FtsZ [87] was used at 1/2500 , secondary goat α-rabbit-AlexaFluor 488 ( Molecular Probes ) and wheat germ agglutinin conjugated to rhodamine ( Molecular Probes ) , to visualize cell wall , were used at 1/200 . For DNA staining , 4′ , 6-diamidino-2-phenylindole ( DAPI ) ( Molecular Probes ) was used at 0 . 5 µg/mL . Micrograph images were captured on an Olympus BX60 microsope with a Hamamatsu C8484 camera using HC Image software ( Hamamatsu ) . Cell length and ring frequency measurements were taken with the ObjectJ extension [88] ( http://simon . bio . uva . nl/objectj/ ) of ImageJ [89] ( National Institutes of Health ) using a minimum number of 100 cells and images were minimally adjusted for brightness/contrast using Adobe Photoshop CS4 . Microsoft Excel 2008 for Mac ( v . 12 . 3 . 6 ) was used for data tabulation and calculatio Samples were prepared , subjected to SDS-PAGE on 20% acrylamide gels , and transferred as published [90] . Transfer of His6-FLAG-Kil samples was done in 10 mM CAPS pH 10 . 0 , 10% methanol transfer buffer with a two-hour transfer time . Mouse monoclonal α-His primary antibody ( Sigma-Aldrich ) and affinity-purified rabbit polyclonal α-FtsZ [87] were used at 1/5000 . Affinity-purified rabbit polyclonal α-ZipA [49] was used at 1/1000 . Goat α-mouse and α-rabbit secondary antibodies conjugated to horseradish peroxidase ( HRP ) ( Sigma-Aldrich ) were used at 1/10 , 000 . A SuperSignal West Pico Chemiluminescent Substrate Kit ( Thermo Scientific – Pierce ) was used for HRP detection; blots were exposed to film and developed using a Konica SRX101A Film Processor ( Konica Minolta ) . Proteins were induced for purification from pET vectors ( Novagen – EMD Millipore ) in BL21 ( DE3 ) [91] backgrounds as 2 L cultures that were grown to OD600∼0 . 7 at 30°C , at which point 1 mM IPTG was added . ( Volumes in this and subsequent steps were scaled down by a factor of 10 for copurification assays ) . Cultures were left overnight at 30°C to induce protein and were harvested in the morning by spinning in a Beckman J2-21 centrifuge with a JA-17 rotor at 7 , 000 rpm . Cell pellets were then washed in buffer ( 50 mM sodium phosphate pH 8 . 0; 300 mM NaCl ) , re-centrifuged , and stored as cell pellets at −80°C . For purifications , cell pellets were thawed on ice , resuspended in 30 mL of the sodium phosphate wash buffer ( except for His-tagged Kil , see below ) with 1 mg/mL lysozyme and an EDTA-Free c0mplete Protease Inhibitor Cocktail Tablet ( Roche ) , and incubated on ice for 30 minutes . Cells were disrupted by sonication on ice ( Branson Sonifier 250; 50% level , output 4 ) in a series of six alternating 30-second periods of sonication and 30-second rest periods . Cell lysates were clarified of debris by spinning at 40 , 000 rpm at 4°C for 45 minutes in an 80 Ti rotor with an Optima XL-100K Ultracentrifuge ( Beckman ) . E . coli FtsZ was purified from WM971 cell lysates by successive 20% and 30% ammonium sulfate cuts . Following the second cut , protein was resuspended in polymerization buffer ( 50 mM MES pH 6 . 5; 50 mM KCl; 2 . 5 mM MgCl2; 1 mM EGTA; 10% sucrose ) , flash-frozen in liquid nitrogen and stored at −80°C . His-tagged ZipAC proteins were purified by gravity flow over water-washed and buffer-equilibrated cobalt-conjugated resin with a 5 mL bed volume at 4°C . Imidazole at pH 8 . 0 was added to 10 mM in cell lysates for loading onto the column . Following loading , columns were washed successively in ten-column volumes of purification buffer ( 50 mM HEPES pH 7 . 5; 300 mM NaCl ) with 10 mM , 25 mM , and 50 mM imidazole . His-tagged ZipACs were eluted in 10 mL purification buffer+250 mM imidazole . Eluted proteins were concentrated and subjected to buffer exchange into polymerization buffer using Amicon Ultra-10K Centrifugal Filter Devices ( Millipore ) , flash-frozen in liquid nitrogen , and stored at −80°C . His6-FLAG-Kil was primarily induced in , and purified from , BL21 ( DE3 ) ftsAR286W ΔzipA::aph pBS58 cells . The exception was for copurification experiments , where the fusion was also prepared from zipAWT+ or zipAL286Q+ backgrounds , as noted . Following induction , His6-FLAG-Kil was found to be predominantly associated in insoluble inclusion bodies , leading to very low yields under native conditions , even in an ftsAR286W ΔzipA::aph background . We therefore purified His6-FLAG-Kil under denaturing conditions according to the QIAexpressionist Handbook ( QIAGEN , 2003 ) protocol , followed by renaturation by dialysis . Purity was estimated at >95% by Coomassie staining . Lysates from His6-FLAG-Kil-expressing cells were prepared similarly as described above , except cell pellets were resuspended in denaturing lysis buffer ( 100 mM sodium phosphate , pH 8 . 0 , 10 mM Tris-Cl , 6M guanidine hydrochloride ) with an EDTA-Free c0mplete Protease Inhibitor Cocktail Tablet ( Roche ) , but without lysozyme . After incubation for 30 minutes at room temperature , cells were sonicated as described above . These His6-FLAG-Kil-containing lysates were then loaded by gravity flow onto water-washed and denaturation lysis buffer-equilibrated cobalt-conjugated resin with a 5 mL bed volume at room temperature . Columns were washed in ten-column volumes of freshly prepared denaturing wash buffer ( 100 mM sodium phosphate , pH 6 . 3 , 10 mM Tris-Cl , 8 M urea ) . Denatured His6-FLAG-Kil was eluted in 10 mL freshly prepared denaturing elution buffer ( 100 mM sodium phosphate , pH 4 . 5 , 10 mM Tris-Cl , 8 M urea ) . The eluted protein was then renatured by dialysis into polymerization buffer overnight and through the following day ( three 2 L changes of buffer in total ) . Renatured His6-FLAG-Kil was concentrated using Amicon Ultra-3K Centrifugal Filter Devices ( Millipore ) , flash-frozen in liquid nitrogen , and stored at −80°C . To assay interaction between purified proteins , 200 mL samples were prepared in polymerization buffer containing 6 µM bovine serum albumin . FtsZ at 5 µM , His6-FLAG-Kil at 10 µM , and/or His6-tagged ZipAC domains ( WT and L286Q ) at 5 µM were included as indicated . 50 µL of 50% buffer-equilibrated α-FLAG M2 affinity resin ( Sigma-Aldrich ) were added and samples were incubated at room temperature , mixing , for one to three hours for binding . Samples were then loaded onto gravity flow columns and the resin was washed with 25 mL polymerization buffer . Following washes , resin was recovered in 250 µL buffer , SDS-PAGE sample buffer was added and samples were boiled and separated by 20% SDS-PAGE followed by Coomassie blue staining . Sedimentation assays were performed essentially as previously described [66] in a Beckman TL-100 Ultracentrifuge , but using a TLA 100 . 3 rotor at 70 , 000 rpm with appropriate adaptors and speed-resistant tubes ( Beckman ) . 100 µL samples were prepared in polymerization buffer with FtsZ at 5 µM , His6-FLAG-Kil at 10 µM , His6-tagged ZipAC domains ( WT and L286Q ) at 5 µM , and GTP at 1 mM . Components were added in the following order: polymerization buffer , Kil buffer or Kil , FtsZ , ZipAC , and GTP . For reactions with calcium-induced bundling , CaCl2 was added to 1 mM after GTP addition . GTPase activities were determined using the EnzChek Phosphate Assay Kit ( Molecular Probes ) in reactions set up with the same concentrations and buffers as for sedimentation assays , but in a 96 well plate and with the required purine nucleoside phosphorylase enzyme and 7-Methyl-6-thio-D-guanosine ( MESG ) substrate components . Reactions were initiated by adding one half the reaction volume as buffer with FtsZ alone , simultaneously via multi-channel pipette , into the other half of the reaction volume that contained all other components . ( For reactions without FtsZ , buffer with GTP alone was used to simultaneously initate reactions ) . OD360 readings were taken every 30 seconds using a Synergy Mx Microplate Reader ( BioTek ) . GTP hydrolysis rates were calculated based on a phosphate standard curve . One-step growth was done according to Frank Stahl ( unpublished ) . Briefly , 10 mL MG1655 was growth at 39°C in tryptone broth to OD600 = 0 . 4 ( ∼1 . 5×108 per mL ) . The cells were pelleted and suspended in TMG ( see above ) and incubated at 37°C for 30 minutes to starve the cells . NaCN was added at 2×10−3 M and 1 . 8 mL was dispensed to two small glass-plating tubes . To initiate the growth curve , 0 . 2 mL phage stock at 1 . 5×108 per mL was added to the cell suspension . Phage adsorption was monitored over a 30 minute period by mixing 0 . 1 mL infected cells into 4 . 9 mL tryptone broth containing 0 . 25 mL chloroform and plating appropriate dilutions on C600 host cells . After a 30 minute adsorption the infected cells were diluted 100-fold into tryptone broth and two further dilutions were made into 39°C tryptone broth , one 100-fold and one 5×103-fold . At various times , 0 . 1 mL samples were taken from these dilutions and plated immediately on C600 . | Bacterial antibiotic resistance is a serious concern , particularly its role in hospital-acquired infection . Viruses that infect bacteria ( bacteriophage ) can kill their host , and some prevent the bacterial cell from reproducing during that process . Since their discovery , phage have been considered a potential tool against bacterial infection , but little is known regarding how phage-encoded factors may inhibit bacterial cell division . Understanding the interaction between phage factors and the targeted host systems is therefore a critical research goal . Our report focuses on E . coli and λ , a well-studied phage that infects it . λ contains a gene , kil , whose expression prevents E . coli from dividing , causing cells to grow into long filaments that die . Here we report that Kil protein prevents an essential bacterial protein , FtsZ , from properly assembling into the structure needed for cell division . Our data show that Kil can inhibit FtsZ assembly directly in vitro , but that ZipA , another essential cell division protein , enhances its activity on FtsZ in vivo . The results of our study elucidate one way that a phage naturally inhibits bacterial reproduction , which could serve as a target for rational antibiotic design . | [
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] | 2014 | The Kil Peptide of Bacteriophage λ Blocks Escherichia coli Cytokinesis via ZipA-Dependent Inhibition of FtsZ Assembly |
Blood flukes of the genus Schistosoma cause schistosomiasis , a parasitic disease that infects over 240 million people worldwide , and for which there is a need to identify new targets for chemotherapeutic interventions . Our research is focused on Schistosoma mansoni prolyl oligopeptidase ( SmPOP ) from the serine peptidase family S9 , which has not been investigated in detail in trematodes . We demonstrate that SmPOP is expressed in adult worms and schistosomula in an enzymatically active form . By immunofluorescence microscopy , SmPOP is localized in the tegument and parenchyma of both developmental stages . Recombinant SmPOP was produced in Escherichia coli and its active site specificity investigated using synthetic substrate and inhibitor libraries , and by homology modeling . SmPOP is a true oligopeptidase that hydrolyzes peptide ( but not protein ) substrates with a strict specificity for Pro at P1 . The inhibition profile is analogous to those for mammalian POPs . Both the recombinant enzyme and live worms cleave host vasoregulatory , proline-containing hormones such as angiotensin I and bradykinin . Finally , we designed nanomolar inhibitors of SmPOP that induce deleterious phenotypes in cultured schistosomes . We provide the first localization and functional analysis of SmPOP together with chemical tools for measuring its activity . We briefly discuss the notion that SmPOP , operating at the host-parasite interface to cleave host bioactive peptides , may contribute to the survival of the parasite . If substantiated , SmPOP could be a new target for the development of anti-schistosomal drugs .
Schistosomiasis , also known as bilharzia , is caused by blood flukes of the genus Schistosoma with approximately 240 million people infected [1] . Three species of schistosome principally infect humans: Schistosoma haematobium , which causes urinary schistosomiasis , and S . japonicum and S . mansoni , which cause intestinal schistosomiasis [2] . Adult schistosomes can reside for decades as pairs in the veins surrounding the bladder or in mesenteric and the portal veins , and produce hundreds of eggs per day [3] . Morbidity arises from immuno-pathological reactions to and entrapment of schistosome eggs in various tissues [4] . Disease symptoms include spleno- and hepatomegaly , periportal fibrosis and hypertension , and urinary obstruction . Bladder carcinoma , sterility , malnutrition , and developmental retardation are common [3] . Infections can last a lifetime [5] . In the absence of a vaccine [6] , control and treatment of schistosomiasis rely on a single drug , praziquantel , and the possibility of emergent drug resistance is a constant concern [7 , 8] . Accordingly , there is a continued impetus to identify new schistosome drug targets and chemotherapeutically active anti-schistosomals [8 , 9] . Proteolytic enzymes ( peptidases ) of schistosomes are attractive drug targets as they operate at the host–parasite interface , where they may facilitate parasite invasion , migration , nutrition and immune evasion [10–12] . Most studies concerning schistosome peptidases have focused on either the serine peptidase called cercarial elastase that facilitates penetration of the human host by some schistosome species [13] or on those cysteine and aspartic peptidases that contribute to the digestion of the blood meal [14 , 15] . Among the latter , the digestive cathepsin B of S . mansoni , known as SmCB1 , has been validated in a murine model of S . mansoni infection as a molecular target for therapy [9 , 16] and small molecule inhibitors of SmCB1 are under consideration as potential drug leads [16–19] . Other peptidase groups of schistosomes are less studied [12] , including post-proline cleaving peptidases . This work focused on a S . mansoni prolyl oligopeptidase . Prolyl oligopeptidases ( POPs , also called prolyl endopeptidases ) are approximately 70–80 kDa and belong to the S9 family of serine peptidases [20] . POPs cleave internal peptide bonds on the C-terminal side of proline residues and are found in plants , bacteria , fungi , protozoa , invertebrates and vertebrates [21] . For parasites , the best characterized POP is Tc80 in the infective trypomastigote stage of Trypanosoma cruzi , the causative agent of Chagas disease [22] . Tc80 seems to be involved in the parasite invasion as inhibition of Tc80 prevents parasite entry into host cells [23] . Accordingly , Tc80 is under investigation as a potential drug target [23 , 24] . In this report , we identified and functionally characterized the prolyl oligopeptidase from S . mansoni ( SmPOP ) . We demonstrate that enzymatically active SmPOP is produced in several developmental stages and localized to the tegument and parenchyma of the parasite . We characterized in detail the biochemical activity of recombinant and native SmPOP , and designed nanomolar inhibitors of SmPOP that derange schistosomes maintained in culture . The data suggest that SmPOP is important to parasite survival and is , thus , a potential target for the development of anti-schistosomal therapeutics .
All animal procedures were performed at the UCSF , USA , in accordance with protocol ( AN107779–01 ) approved by the UCSF Institutional Animal Care and Use Committee ( IACUC ) as required by the Federal Animal Welfare Act and the National Institutes of Health Public Health Service Policy on Humane Care and Use of Laboratory Animals ( http://grants . nih . gov/grants/olaw/references/phspol . htm ) . S . mansoni ( a Puerto Rican isolate ) was kept in the University of California San Francisco ( UCSF ) laboratory by cycling between the intermediate snail host , Biomphalaria glabrata , and female golden Syrian hamsters ( infected at 3–5 weeks old ) , as the definitive host . Hamsters are infected by subcutaneous injection of 800 cercariae and sacrificed 6–7 weeks post-infection by intra-peritoneal injection of pentobarbital ( 50 mg/kg ) . Adults , eggs and miracidia were then isolated as described previously [25 , 26] . Free-swimming cercariae were obtained from water containing infection-patent Biomphalaria to ‘shed’ under a bright light . Cercariae were chilled over ice . Newly transformed schistosomula ( NTS ) were prepared by mechanically transforming cercariae [26 , 27] and cultivated in a Basch Medium 169 [28] containing 5% fetal calf serum , 100 units/mL penicillin and 100 μg/mL streptomycin for 5 days at 37°C under a 5% CO2 atmosphere . Daughter sporocysts were isolated by excision of hepato-pancreases from infected B . glabrata snails . Adult worms , eggs , miracidia , daughter sporocysts , cercariae and NTS were collected , washed three times in 1 . 5 mL PBS , re-suspended in 500 μL Trizol reagent ( Invitrogen ) and processed as described previously [26] . Single-stranded cDNA was synthesized from total RNA by SuperScript III reverse transcriptase ( Life Technologies ) and an oligo dT18 primer . The final cDNA product was purified and stored at -20°C . The gene expression profile of the SmPOP was assessed using reverse transcription- quantitative PCR ( RT-qPCR ) . The following primers were used: forward 5'-CATTCGTGGTGGAGGAGAAT-3' and reverse 5'- CGCATACTGGAACTTGAGCA -3' . The primers were designed using the Primer 3 software ( http://frodo . wi . mit . edu/ ) and their efficiency was evaluated as described previously [25 , 26] . The reactions , containing SYBR Green I Mastermix ( Eurogentech ) , were prepared in a final volume of 25 μL in 96-well plates ( Roche ) . The amplification profile consisted of an initial hot start ( 95°C for 10 min ) followed by 40 cycles comprising 95°C for 30 s , 55°C for 60 s and 72°C for 60 s , and ending with a single cycle of 95°C for 60 s , 55°C for 30 s and 95°C for 30 s . The PCR reactions were performed in duplicate for each cDNA sample . At least one biological replicate , i . e . , samples from a different RNA isolation , was performed . The analysis of the cycle threshold for each target was carried out as described [25 , 26] employing S . mansoni cytochrome c oxidase I ( SmCOX I , GenBank AF216698 ) [29] as the sample-normalizing gene transcript . Transcript levels were expressed as log functions and as a percentage relative to that of SmCOX I in order to compare expression patterns . The single gene encoding SmPOP ( SchistoDB code: Smp_213240 ) was identified in the S . mansoni genome database [12] ( S . mansoni GeneDB available at http://www . genedb . org/Homepage/Smansoni ) via a protein BLAST search with the amino acid sequences of human and porcine prolyl oligopeptidases ( GenBank accession numbers P48147 and P23687 , respectively ) as queries . The same search in the S . japonicum and S . haematobium genome databases [30 , 31] identified SmPOP orthologs with 88% and 95% identity , respectively ( S . japonicum: GeneDB Sjp_0080730 . 1 , GenBank AAX26405; S . haematobium: HelmDB Shae8836338 , GenBank KGB33720 ) . The Champion pET directional expression kit ( Life Technologies ) was selected for expression of the SmPOP gene . The 2139 bp ORF was amplified using Phusion High-Fidelity DNA Polymerase ( New England Biolabs ) from adult schistosome cDNA using specific forward ( 5´-caccATGGAGCATACCAGTATCAACTATCC-3´ ) and reverse ( 5´-TTCTTTCCATGTGAGTGACATT-3´ ) primers . The PCR product was cloned into the expression vector pET101/D-TOPO ( Invitrogen ) and verified by DNA sequencing . Recombinant SmPOP ( rSmPOP ) with a C-terminal His6-tag was produced in E . coli BL21 ( DE3 ) by induction in LB broth medium containing 0 . 5 mM IPTG for 16 h at 16°C . Soluble rSmPOP was purified from the bacterial lysate using Ni2+ chelating chromatography ( Hi-Trap IMAC FF column , GE Healthcare Life Sciences ) under native conditions . The bound rSmPOP was eluted using a linear gradient of 0 . 01–0 . 5 M imidazole . The preparation was buffer-exchanged into 20 mM Tris-HCl , pH 8 . 0 , using an Amicon Ultracel-30k ultrafiltration device ( Millipore ) . rSmPOP was subsequently purified by FPLC over a Mono Q HR 5/5 column ( GE Healthcare Life Sciences ) equilibrated in 20 mM Tris-HCl , pH 8 . 0 , and eluted using a linear gradient of 0–1 M NaCl in the same buffer . The purification process was monitored by a kinetic assay incorporating the peptidyl fluorogenic substrate , benzyloxycarbonyl ( Z ) -Gly-Pro-7-amino-4-methylcoumarin ( AMC ) , and by SDS-PAGE . The preparation was concentrated and desalted into 20 mM Tris-HCl , pH 8 . 0 , using an Amicon Ultracel-30k . The typical yield was approximately 3 mg of rSmPOP from 1 L of culture medium . Soluble protein extracts ( 0 . 2–3 mg protein/mL ) from S . mansoni adults , miracidia , cercariae , eggs and NTS were prepared by homogenization in 50 mM Tris-HCl , pH 8 . 0 , containing 1% CHAPS , 1 mM EDTA , 1 μM pepstatin and 10 μM E-64 in an ice bath . The extracts were cleared by centrifugation ( 16000 g at 4°C for 10 min , ) , ultra-filtered using a 0 . 22 μm Ultrafree-MC device ( Millipore ) and stored at -80°C . Specific polyclonal antibodies ( Moravian Biotechnology ) were generated in rabbits against the purified rSmPOP antigen using 50 μg of rSmPOP in Freund’s incomplete adjuvant and applied three times three weeks apart . IgG was isolated from the serum by affinity chromatography with a HiTrap Protein A column ( GE Healthcare Life Sciences ) according to the manufacturer’s protocol . For immunoblotting , adult schistosome homogenate ( 30 μg protein ) and rSmPOP ( 1 μg ) were resolved by SDS-PAGE ( 15% polyacrylamide gel ) under reducing conditions and transferred onto a PVDF membrane . The membrane was blocked 16 h in 10% non-fat milk in 50 mM Tris-HCl , pH 7 . 5 , containing 150 mM NaCl and 0 . 1% Tween ( TTBS ) . The membrane was then washed three times in TTBS and incubated for 1 h with anti-SmPOP polyclonal IgG diluted 1:1000 in TTBS . After washing in TTBS , the membrane was incubated for 1 h with goat horseradish peroxidase-conjugated anti-rabbit IgG ( Sigma-Aldrich , catalog number A6154 ) at a dilution of 1:20000 . After washing in TTBS , the membrane was developed with SuperSignal West Femto Chemiluminescent Substrate ( Pierce ) and imaged using an ImageQuant LAS 4000 biomolecular imager ( GE Healthcare Life Sciences ) . For sample preparation , adult S . mansoni worms were washed three times in PBS and fixed either in acetone ( 75% acetone in ethanol ) at -20°C for 10 min or 4% formaldehyde in PBS at 25°C for 45 min . The samples were then rinsed with PBS and incubated in a 30% sucrose solution at 4°C for 16 h . The worms were placed in cryofixation molds and the sucrose solution was replaced with Optimal Cutting Temperature ( OCT ) medium ( CellPath Ltd ) . The molds were placed over dry ice to freeze and the frozen blocks then stored at -80°C . The OCT-embedded worm samples were sectioned with a cryotome ( Cryostat 2800 Frigocout , Cambridge Instruments ) . Sections of ~7 μm were air-dried and further processed for immunostaining . Sections were rehydrated in PBS and fixed again either with formaldehyde or cold acetone as described above . The formaldehyde-fixed samples were further blocked in 100 mM glycine at 22°C for 20 min , followed by 2% BSA in PBS at 4°C for 16 h . Working solutions of primary and secondary antibodies were prepared in PBS containing 2% BSA; rabbit polyclonal anti-SmPOP IgG was diluted 1:900 and anti-rabbit IgG Alexa 594-conjugated secondary antibody ( Molecular Probes ) was diluted 1:200 . The antibodies were incubated at 25°C on the sections for 45 min with three washes between the primary and secondary antibody incubations , and four washes after the secondary-antibody incubation ( the fourth wash contained DAPI at 1 μg/mL for nuclear staining ) . NTS samples were fixed in 4% formaldehyde in PBS at 4°C for 16 h . After fixation , they were washed 3 times in PBS at 25°C for 10 min and subsequently blocked with 100 mM glycine at 25°C for 20 min . Samples were permeabilized with 0 . 2% Triton X-100 in PBS for 40 min at 25°C and blocked with 2% BSA in PBS for 16 h at 4°C . The antibody diluent contained 0 . 1% Triton X-100 , 0 . 1% BSA and 0 . 2% NaN3 . Primary and secondary antibody solutions were incubated for 24 h with four washes of diluent over a 10 h period ( the fourth wash contained DAPI at 1 μg/mL for nuclear staining ) . Sections of adults and whole-worm preparations of NTS were embedded in Mowiol ( Sigma-Aldrich ) and visualized using a Leica SP2 AOBS confocal laser scanning microscope ( Leica Microsystems ) and a 20x oil immersion objective . Appropriate lighting settings were determined using control slides probed with preimmune serum to define the background signal threshold . Image stacks of optical sections were further processed using the Huygens deconvolution software package version 2 . 7 ( Scientific Volume Imaging ) . Fluorescence resonance energy transfer ( FRET ) substrates containing o-aminobenzoic acid ( Abz ) as the fluorescent group and p-nitro-phenylalanine ( NPh ) as the quencher acceptor were synthesized as peptidyl amides by Fmoc solid phase chemistry in an ABI 433A peptide synthesizer ( Applied Biosystems ) as described previously[16 , 32] . Substrates containing the fluorogenic group , 7-amino-4-carbamoylmethylcoumarin ( ACC ) , were synthesized in the format Z-Xaa-Pro-ACC , with proteinogenic amino acids ( except for cysteine ) at the Xaa position , as described previously [33] . The inhibitors Z-Ala-Pro-chloromethyl ketone ( CMK ) and Z-Arg-Pro-CMK were prepared from the peptides Z-Ala-Pro-OH and Z-Arg ( Pbf ) -Pro-OH , respectively , according to the described procedure [34] . Z-Ala-Pro-OH and Z-Arg ( Pbf ) -Pro-OH were synthesized on solid phase using 2-chlorotritylchloride resin ( Iris Biotech ) . Z-Xaa-Pro-CHO ( CHO , aldehyde ) inhibitors , where Xaa is Gly , Ala , Tyr , Arg or Lys , were synthesized on solid phase using H-Thr-Gly-NovaSyn TG resin ( Merck ) as described [35] . All of the substrates and inhibitors were purified by reverse-phase ( RP ) -HPLC over a C18 column using a TFA/acetonitrile system and characterized by electrospray ionization mass spectrometry on an LCQ Classic Finnigan Mat device ( Thermo Finnigan ) . The substrates Z-Gly-Pro-AMC , Succinyl ( Suc ) -Gly-Pro-Leu-Gly-Pro-AMC , Lys-Pro-AMC , Gly-Pro-AMC and Pro-AMC were purchased from Bachem . The POP inhibitors Y-29794 oxalate and Z-Pro-Pro-CHO were purchased from Santa Cruz Biotechnology , and SUAM 14746 from PeptaNova . Assays were performed in triplicate in black , flat-bottomed , 96-well microplates ( Nunc ) in a total volume of 100 μL at 37°C . Z-Gly-Pro-AMC was used as substrate at a 50 μM final concentration . rSmPOP ( 50–100 ng ) , human POP ( 25–50 ng; Sigma-Aldrich , catalog number O9515 ) or schistosome homogenates ( 1–5 μg of protein ) were pre-incubated for 10 min at 37°C in 80 μL of 0 . 1 M sodium phosphate , pH 8 . 0 , containing 0 . 1% PEG 6000 . Substrate ( 20 μL in the same buffer ) was added to a final concentration of 50 μM . Hydrolytic activity was measured continuously in an Infinite M1000 microplate reader ( Tecan ) at the excitation and emission wavelengths of 360 and 465 nm , respectively . The pH profile of the activity was determined in 100 mM citrate phosphate ( pH range 5 . 5–8 . 0 ) , 100 mM Tris-HCl ( pH range 8 . 0–9 . 0 ) and 100 mM sodium borate ( pH range 9 . 0–10 . 0 ) . For inhibition measurements , inhibitors were added to the 80 μL pre-incubation solution at a final concentrations of 0 to125 μM for 10 min and the reaction was initiated by the addition of the substrate . IC50 values were determined by nonlinear regression using the GraFit software ( Erithacus Software ) . SmPOP activity in homogenates was measured in the presence of 10 μM E-64 to prevent undesired proteolysis by cysteine peptidases that contribute significant proteolytic activity in worm extracts [36] . POP activity was also measured with ACC and FRET substrates at excitation/emission wavelengths of 380/460 nm and 320/420 nm , respectively . Stock solutions of substrates and inhibitors ( 10 mM ) were prepared in DMSO and the final assays concentration of DMSO was 1 . 5% . rSmPOP ( 0 . 7 μg ) was incubated at 37°C for 16 h with 100 μg of human hemoglobin , human serum albumin , human collagens type I and IV ( Sigma-Aldrich , catalog numbers H7379 , A3782 , C7774 and C7521 respectively ) in 100 mM Tris-HCl , pH 8 . 0 , in a final volume of 50 μL . After incubation , a 10 μL sample was resolved by 15% SDS-PAGE or Tricine-SDS-PAGE and stained with Coomassie Brilliant Blue G250 . The following synthetic analogues of human bioactive peptides were analyzed: angiotensin II ( Sigma , catalog number A9525 ) , angiotensin I , bradykinin , luteinizing-hormone-releasing hormone ( LHRH ) , α-melanocyte-stimulating hormone ( α-MSH ) , neurotensin , oxytocin , substance P , and vassopresin ( all Bachem , catalog numbers H-1680 , H-1970 , H-6728 , H-1075 , H-4435 , H-2510 , H-1890 and H-1780 , respectively ) . Stock solutions of peptides ( 10 mM ) were prepared in water . rSmPOP ( 0 . 7 μg ) was incubated at 37°C for 16 h with 25 nmol of peptide in 0 . 1 M Tris-HCl , pH 8 . 0 , in a total volume of 50 μL . The reaction was stopped by adding TFA to a final concentration of 1% . The resulting fragments were purified by RP-HPLC over a C18 column ( Vydac , 25 x 0 . 46 cm ) using a TFA/acetonitrile system and characterized by electrospray ionization mass spectrometry on an LCQ Classic Finnigan Mat device ( Thermo Finnigan ) . Five adult schistosome pairs were placed into clear , 24-well , flat-bottom plates ( Costar ) containing 500 μL Basch Medium 199 [28] , supplemented with 2 . 5% FBS , 100 units/mL penicillin and 100 μg/mL streptomycin . Human angiotensin I or bradykinin in 5 μL water was added to a final concentration of 100 μM and the incubation continued for 16 h at 37°C under a 5% CO2 atmosphere . In control experiments , the peptides were cultivated in the same system in the absence of schistosomes . After incubation , the samples were ZipTiped and the resulting fragments were analyzed using MALDI-TOF performed on an UltrafleXtreme ( Bruker Daltonik ) operated in reflectron mode with an acceleration voltage of 25 kV and a pulsed ion extraction of 120 ns . Desorption and ionization were achieved using a Smartbeam II laser . α-Cyano-4-hydroxycinnamic acid was used as a matrix . The data were acquired from m/z 220 to 3700 and analyzed with the FlexAnalysis 3 . 3 software ( Bruker Daltonik ) . The mass spectra were externally calibrated using a Peptide Calibration Standard I ( Bruker Daltonik ) and averaged from 3000 laser shots . Adult worms ( 3 pairs ) or approximately 150 NTS were incubated at 37°C and 5% CO2 for 2 days in 200 μL of Basch Medium 169 containing 5% FBS , 100 units/mL of penicillin and 100 μg/mL using black clear bottomed 96-well microplates ( Costar ) . After incubation , half of the medium ( 100 μl ) was transferred to an empty well leaving the parasites in the remaining half . Then SmPOP activity was measured in both wells upon the addition of 20 μL of Z-Gly-Pro-AMC ( prepared as a 250 μM stock in Basch Medium 169 ) and in the presence or absence of 1 μM of the POP inhibitor , Z-Ala-Pro-CMK . Controls contained medium alone . A spatial model of SmPOP was constructed by homology modeling as described previously [17] . Briefly , the X-ray structure of porcine POP in complex with the inhibitor Z-Pro-Pro-CHO ( PDB entry: 1QFS ) was used as a template . The homology module of the MOE program ( Chemical Computing Group ) was used for the modeling of the SmPOP structure . The inhibitor conformation was refined by applying the LigX module of the MOE for the optimization procedure and its final binding mode was selected by the best-fit model based on the London dG scoring function and the generalized Born method [37] . Molecular images were generated with UCSF Chimera ( http://www . cgl . ucsf . edu/chimera/ ) . NTS ( 200–300 parasites ) were incubated in 200 μL of Basch Medium 169 and supplements , as described above . Inhibitors were added at final concentrations of 1 or 10 μM ( 0 . 5% DMSO final ) and the incubations continued for 4 days . Grading of phenotypic responses arising as a function of time and concentration was modified after Jilkova et al . [16]: Grade I , dead NTS by 2 days of culture at 10 μM and dying/dead NTS by 3 days at 1 μM . Grade II , dead NTS by 3 days at 10 μM and round/dark/dying by 3 days at 1 μM; Grade III , round/dark by 3 days at 1 and 10 μM concentrations ( S1 Fig ) . ‘Dead’ was adjudicated as the loss of normal shape and the lack of movement often accompanied by obvious internal disruptions . ‘Dying’ was similar to death except that movement was detectable . Otherwise , the terms ‘round/dark’ were used to indicate less severe but obvious changes in the parasites relative to DMSO controls .
A protein BLAST analysis of the S . mansoni genome database [12 , 38] using mammalian prolyl oligopeptidases as queries identified a gene ortholog ( SmPOP ) , Smp_213240 , located on the sex-determining Z/W chromosomal pair . SmPOP cDNA was cloned , sequenced , and the sequence was deposited into the GenBank as KF956809 . The blast analysis did not identify other gene isoforms . The SmPOP open reading frame consists of 2 , 139 bp that encodes a protein of 712 amino acid residues with a calculated molecular mass of 82 kDa . No signal/leader peptide was predicted for the sequence . SmPOP has about 50% identity with human and porcine POPs ( S1 Table ) and belongs to the S9 family of serine peptidases ( S2 Fig ) . SmPOP has the characteristic domain composition of mammalian POPs , consisting of N-terminal , β-propeller and peptidase domains . The peptidase domain of SmPOP has a catalytic triad in the order of Ser556 , Asp643 and His682 , which is typical of POPs and other S9 family peptidases [39] . In addition , the regions surrounding the catalytic-triad residues have the most notable sequence identity . A phylogenetic tree constructed for prolyl oligopeptidases of animal , plant , protozoan and bacterial origin ( S3 Fig ) demonstrates that SmPOP clusters with other trematode and nematode POPs . This monophyletic group is well separated from other clades . Messenger RNA transcript levels for SmPOP were evaluated in eggs , miracidia , daughter sporocysts , cercariae , NTS and adults using qRT-PCR ( Fig 1A ) . The expression of SmPOP was recorded in eggs , daughter sporocysts , NTS and adult schistosomes ( in the range of 4–12% of the expression of the validated reference gene , SmCOX I [26] ) . In miracidia and cercariae , expression was below 1% of the SmCOX I level ( Fig 1A ) . At the protein level , SmPOP enzymatic activity in soluble extracts of various developmental stages was determined in a kinetic assay using the fluorogenic substrate , Z-Gly-Pro-AMC , which is specific for prolyl oligopeptidases . The measured activities were further authenticated as being due to a prolyl oligopeptidase by their sensitivity to Z-Pro-Pro-CHO , a selective small-molecule inhibitor of prolyl oligopeptidases [40] . Prominent SmPOP activity was measured in the homogenates of eggs , NTS and adults , whereas weak activity was measured in miracidial homogenates; no activity was detected in cercariae ( Fig 1B ) . Overall , active SmPOP is expressed in the S . mansoni developmental stages that live in the human host and the activity profile is consistent with that for mRNA expression . In addition , the presence of SmPOP was confirmed in the protein homogenate of adult S . mansoni by mass spectrometry proteomics ( S2 Table ) . Recombinant SmPOP ( rSmPOP ) was expressed in E . coli as a soluble and catalytically active enzyme . rSmPOP was purified to homogeneity by a combination of metal-affinity chromatography and ion-exchange chromatography , and subsequently migrated on SDS-PAGE as a single band of approximately 80 kDa ( Fig 2A ) . Rabbit polyclonal antibodies raised against rSmPOP reacted with the original rSmPOP antigen by immunoblotting and recognized a single band in the homogenates from schistosome adults ( Fig 2A ) . The molecular mass of both the native SmPOP and rSmPOP is in good agreement with the theoretical mass of SmPOP predicted from the amino-acid sequence ( 82 kDa ) . The pH activity profile of rSmPOP was determined using the fluorogenic substrate Z-Gly-Pro-AMC and compared with that of the native SmPOP in schistosome adult homogenates ( Fig 2B ) . For both protein sources , the substrate was cleaved between pH 6 . 0 and 10 . 0 with optimal activity around pH 8 . 0 . No POP activity was detected below pH 5 . 0 . Prolyl oligopeptidases perform specific post-proline cleavages of various peptides [39 , 41] . Accordingly , using a broad panel of proline-containing bioactive peptides , we asked whether SmPOP cleaves human peptide hormones and neuropeptides ( Fig 3 ) . After incubation of the tested peptides with SmPOP , the resulting fragments were separated by HPLC and the cleavage positions identified by mass spectrometry . All substrates were cleaved specifically at the carboxyl terminus of proline residues with the exception of the Pro-Lys bond in Substance P and the Pro-Pro bond in bradykinin ( Fig 3 ) . The substrate specificity resembles that of mammalian prolyl oligopeptidases , which cleave a Pro-Xaa bond in peptides , where Xaa is not a Pro residue . Also , like mammalian prolyl oligopeptidases , SmPOP does not cleave after a penultimate N-terminal Pro residue [42] . The activity of rSmPOP towards host-derived macromolecular substrates was tested with several human proteins , including hemoglobin , serum albumin and collagens I and IV . No hydrolysis was observed even after prolonged incubation ( S4 Fig ) , indicating that SmPOP is a true oligopeptidase with an action restricted to oligopeptide substrates . A fluorogenic substrate library was used to determine the SmPOP cleavage specificity at the substrate P2 position ( Fig 4A ) . The greatest preference was recorded for basic residues ( Arg and Lys ) , but a variety of other amino acid residues was also acceptable at this position , including hydrophobic , aliphatic and polar residues . Substrates with acidic residues and Pro at P2 were least preferred . The substrate specificity of rSmPOP was further investigated using FRET synthetic substrates which had been designed based on the aminobenzoyl ( Abz ) -nitrophenylalanine ( NPh ) donor–acceptor pair and contained a Pro residue at P1 ( Fig 4B ) . We prepared a set of substrates with variations in the P2 position ( Abz-Ala-Pro-NPh , Abz-Gly-Pro-NPh , Abz-Lys-Pro-NPh , and Abz-Pro-Pro-NPh ) and which were lengthened to include the P3 ( Abz-Ala-Ala-Pro-NPh and Abz-Gly-Gly-Pro-NPh ) or P1’ positions ( Abz-Ala-Pro-Ala-NPh and Abz-Ala-Pro-Gly-NPh ) . The greatest rSmPOP activity was measured with the substrates Abz-Ala-Pro-NPh and Abz-Lys-Pro-NPh , whereas the substrate Abz-Pro-Pro-NPh was not digested; increasing the substrate length to P3 and P1’ positions did not increase its affinity ( Fig 4B ) . Finally , rSmPOP was tested for its ability to hydrolyze substrates with Pro in the P1 position that allows for cleavage by other post-proline cleaving enzymes , including collagenase-like peptidases ( Suc-Gly-Pro-Leu-Gly-Pro-AMC ) , dipeptidyl aminopeptidase II ( Lys-Pro-AMC ) , dipeptidyl aminopeptidase IV ( Gly-Pro-AMC ) and prolyl aminopeptidase ( Pro-AMC; Fig 4C ) . Only Suc-Gly-Pro-Leu-Gly-Pro-AMC , suitable for the endopeptidase mode of cleavage , was digested by rSmPOP with the same efficiency as found for the classical and minimal POP substrate , Z-Gly-Pro-AMC . The cleavage of exopeptidase substrates with free N-termini occurs only very slowly ( Lys-Pro-AMC ) or not at all ( Gly-Pro-AMC and Pro-AMC ) . To summarize , SmPOP is a true oligopeptidase that hydrolyzes peptide but not protein substrates in the endopeptidase mode with a strict specificity for Pro at P1 . The general inhibition specificity of rSmPOP was analyzed using a panel of peptidase class/type-selective small-molecule inhibitors as listed in Table 1 . rSmPOP activity was completely inhibited by selective prolyl-oligopeptidase inhibitors with chloromethyl ( CMK ) and aldehyde ( CHO ) warheads ( Z-Ala-Pro-CMK and Z-Pro-CHO ) , and by the general serine peptidase inhibitor , diisopropyl fluorophosphate . Partial inhibition was observed with Pefabloc SC , PMSF ( phenylmethylsulfonyl fluoride ) , TLCK ( Nα-tosyl-L-lysine chloromethyl ketone ) , TPCK ( N-p-tosyl-L-phenylalanine chloromethyl ketone ) and 3 , 4-dichloroisocoumarin , all of which target the serine peptidases of the chymotrypsin S1 family . SmPOP activity was neither affected by protein inhibitors of serine peptidases ( soybean trypsin inhibitor ( STI ) and bovine pancreatic trypsin inhibitor ( BPTI ) ) nor by the inhibitors of cysteine , aspartic and metallo-peptidases . This overall inhibition profile shows that SmPOP has the ligand-binding characteristics analogous to those of mammalian POPs [41 , 42] . A more detailed inhibitor specificity profile for rSmPOP was investigated using a panel of synthetic peptidic inhibitors with the structure Z-Xaa-Pro-CHO/CMK , which included aldehyde ( CHO ) or chloromethylketone ( CMK ) reactive warheads ( Table 2 ) . The amino-acid residues for the Xaa position were selected based on the S2 substrate specificity of rSmPOP ( Fig 4A ) . Table 2 shows that the synthesized aldehyde derivatives inhibit SmPOP with IC50 values in the low micromolar concentration range ( 1 . 3 to 6 . 1 μM ) ; the inhibitory specificity at the binding subsite S2 corresponds to the substrate specificity profile ( Fig 4A ) and shows that inhibitors with the basic amino acids in the P2 have position have the lowest IC50 values . The introduction of an irreversible covalent CMK warhead to the inhibitor scaffold improved the IC50 value by three orders of magnitude ( IC50 from 2 . 9 to 3 . 2 nM ) in comparison with inhibitors containing reversible covalent CHO warhead ( Table 2 ) . Furthermore , we tested the sensitivity of rSmPOP to three commercially available inhibitors developed for human POP , namely Y-29794 oxalate [43] , SUAM 14746 [44] , and Z-Pro-Pro-CHO [40] . Whereas the inhibition by SUAM 14746 was similar for both the human and schistosomal enzymes ( IC50 values of 83 nM and 92 nM , respectively ) , Y-29794 oxalate and Z-Pro-Pro-CHO inhibited SmPOP with IC50 values that were about one order of magnitude greater than those for human POP ( IC50 values of 8 . 6 μM and 0 . 49 μM , respectively , for Y-29794 oxalate , and 0 . 16 μM and 0 . 01 μM , respectively , for Z-Pro-Pro-CHO ) . A spatial model of SmPOP was constructed by homology modeling to study the structure-activity/inhibition relationship . The X-ray structure of porcine POP ( PDB code 1QFS ) was used as a template . Fig 5 shows that SmPOP has the conserved architecture of the mammalian POP comprising both the β-propeller and peptidase domains [45] . The peptidase domain ( residues 430–712 ) has a characteristic α/β-hydrolase fold [46 , 47] which consists of a central eight-stranded β-sheet flanked on both sides by eight α helices . The catalytic amino-acid residues Ser556 , Asp643 and His682 are located in a large cavity at the interface between the domains . The disk-shaped β-propeller domain ( residues 76–429 ) is composed of seven repeats of four-stranded antiparallel β-sheets which are arranged around a central tunnel . The binding mode of SmPOP was analyzed using the transition-state analog POP inhibitor Z-Pro-Pro-CHO ( benzyloxycarbonyl-L-prolyl-L-prolinal ) which was docked into the SmPOP active site based on the crystallographic complex of this inhibitor with porcine POP ( PDB code 1QFS ) . The docking model ( Fig 5 ) shows that the prolinal residue of the inhibitor forms a covalent hemi-acetal linkage with the catalytic Ser556 . The P1 Pro ring binds to the hydrophobic S1 binding pocket ( defined by Phe478 , Trp597 , Tyr601 and Val646 residues ) and is stacked against a Trp597 side chain . The backbone of both the P1 and P2 proline residues forms three hydrogen bonds to the SmPOP active site . Additionally , the P3 benzyloxycarbonyl group binds to the hydrophobic S3 binding site ( residues Phe175 , Cys257 , Asn273 , Ile593 and Ala596 ) . Indirect immunofluorescence microscopy on semi-thin sections using affinity-purified antibodies against rSmPOP demonstrate that SmPOP is expressed in the parenchyma and tegument of adult schistosomes ( Fig 6; for a high-resolution micrograph , see Fig 7 ) . The intensity of the signal was greater in the tegument of the male compared to the female ( Fig 6C and 6D ) . Labeling was not observed in the gastrodermis , gut lumen and muscular tissues ( Fig 7 ) . Intense staining was seen in the male tegumental tubercles ( Fig 6C and 6D ) . Pre-immune serum was applied as a negative control and only faint background fluorescence was detected ( Fig 6G and 6H ) . Similar results were obtained in immuno-histochemical studies with NTS ( S5 Fig ) . With this developmental stage , SmPOP was localized at or close to the surface; a low diffuse signal was also seen in the parenchyma whereas the gut exhibited no specific fluorescence . No reaction was observed with pre-immune serum ( S5 Fig ) . We investigated whether SmPOP can interact with peptidic substrates in the environment surrounding the schistosome . NTS or adult schistosomes were incubated in the presence of the fluorogenic peptide substrate Z-Gly-Pro-AMC . Cleavage of the substrate was measured in a microplate reader and was abolished in the presence of the specific POP inhibitor Z-Ala-Pro-CMK ( Fig 8A ) . We also tested whether SmPOP activity is measurable in the excretory/secretory ( E/S ) products of NTS and adults . For this purpose , E/S products were collected after a two-day cultivation of parasites and SmPOP activity was measured using the same fluorogenic substrate . No significant POP activity was detected in E/S products , demonstrating that SmPOP is not secreted into the cultivation media . In the next step , we used the above culture assay to measure cleavage by adult parasites of two vasoregulatory proline-containing hormones from the human host , namely angiotensin I and bradykinin . Both hormones were cleaved when added to the cultivation medium and the cleavage occurred specifically after Pro residues as demonstrated by mass spectrometry ( Fig 8B ) . Again , the fragmentation was abolished in the presence of a POP-specific inhibitor Z-Ala-Pro-CMK ( but not in the presence of the cysteine peptidase inhibitor E-64; S3 Table ) . The identified cleavage positions in the hormone sequences were identical with those obtained by in vitro fragmentation using rSmPOP . To conclude , SmPOP , although not secreted from the parasite , can nonetheless interact with physiologically relevant host peptides in the environment . A panel of SmPOP inhibitors was tested at 1 and 10 μM against NTS and the phenotypic responses graded I through III from the most to the least severe ( Table 2 ) . The CHO inhibitor , Z-Lys-Pro-CHO , induced a grade I response . Grade II phenotypes were induced by Z-Gly-Pro-CHO , Z-Tyr-Pro-CHO , Z-Arg-Pro-CHO and the CMK inhibitor , Z-Arg-Pro-CMK . The inhibitors Z-Ala-Pro-CHO and Z-Ala-Pro-CMK induced the least severe grade III phenotype . The commercial inhibitors of human POP , Y-29794 and SUAM 14746 , induced a grade II response or had no effect , respectively ( Table 2 ) .
We identified and functionally characterized a S9-family serine peptidase from the human blood fluke , S . mansoni . It was denoted SmPOP , S . mansoni prolyl oligopeptidase , based on its 51% primary sequence identity to human and porcine prolyl oligopeptidases . Also , homology modeling of SmPOP using porcine POP as a structural template revealed that both enzymes share the same spatial architecture and domain structure; specifically , a catalytic peptidase domain with an α/β hydrolase fold and a catalytic triad , and a cylindrical β-propeller domain that covers the active site and defines prolyl oligopeptidase as an oligopeptidase [48] . SmPOP was heterologously expressed in E . coli , purified as an active peptidase and subjected to a series of biochemical analyses to determine its substrate and inhibitory specificity . Consistent with its classification as a S9-family prolyl oligopeptidase , the enzyme cleaves various oligopeptide substrates in an endopeptidolytic mode at the carboxyl terminus of Pro residues [45] . Cleavage specificity analysis with the positional-scanning substrate library revealed a preference for basic amino acids over hydrophobic or aliphatic amino acids at P2; a Pro residue at P2 was unfavorable . A similar S2 subsite specificity profile was obtained for human POP ( Fig 4 ) . rSmPOP was effectively inhibited by the general serine peptidase inhibitor , diisopropylfluorophosphate [49] , but only weakly by inhibitors targeting the S1 family of serine peptidases such as Pefabloc , benzamidine , and BPTI . These data are consistent with the inhibitory specificities of mammalian and trypanosomal POPs [50 , 51] . The inhibitor specificity of rSmPOP was investigated further using a panel of synthetic prolinal inhibitors that vary at the P2 amino-acid residue ( Z-Xaa-Pro-CHO , Table 2 ) . The inhibitor specificity profile mirrored that determined with the positional- scanning substrate library , with the exception of the Pro residue in the P2 position , which generates a good inhibitor but a poor substrate ( Z-Pro-Pro-CHO vs . Z-Pro-Pro-ACC , respectively , Table 2 and Fig 4A ) . Note that Z-Pro-Pro-ACC substrate does not bind effectively in the active site neither as the uncleaved form nor as the hypothetical cleavage product Z-Pro-Pro-OH ( as they do not compete with Z-Gly-Pro- substrate ) . A similar discrepancy was observed for human POP ( Table 2 and Fig 4A ) . Based on the assembled biochemical and structural data , therefore , it is clear that SmPOP and its mammalian orthologs are almost identical in their catalytic specificity profiles suggesting a strong evolutionary conservation of function and structure . The panel of SmPOP inhibitors was further evaluated for their anti-schistosomal effects against NTS in culture . These tests demonstrated that some of the investigated inhibitors induced deleterious phenotypes or death . Although , interactions other than with the specific target protein cannot be excluded , the data encourage the search for small molecule inhibitors of SmPOP . Inhibitors of human POP are currently being examined as drug leads in several neurological disorders such as depression , Alzheimer’s disease and amnesia , and a number are in preclinical and clinical trials as nootropics ( for review see [44] ) . POP is also of interest for the treatment of celiac sprue , an inflammatory disease of the small intestine caused by ingesting proline-rich gluten [39] . The prolyl oligopeptidases Tc80 and Tb80 from the protozoan parasites Trypanosoma cruzi and T . brucei , respectively , are secreted and can degrade host extracellular-matrix ( ECM ) proteins such as proline-rich collagens I and IV [23 , 51] . Tc80’s ability to ability to degrade of ECM components contributes directly to the invasion of mammalian cells by T . cruzi trypomastigotes [22] . In contrast , SmPOP cannot degrade protein substrates , including collagens , even though it has about 40% identity with trypanosomal POPs ( S1 Table ) . Further , SmPOP is not found in S . mansoni E/S products suggesting that it is not secreted by schistosomes , a finding consistent with the absence of the signal peptide in the SmPOP sequence . The data would therefore indicate that the trypanosomal POPs possess different physiological functions from those postulated below for the schistosomal enzyme . By RT-qPCR and substrate analysis , SmPOP is expressed in those developmental stages parasitizing the definitive mammalian host ( adults , NTS and eggs ) . By immunolocalization with a monospecific rabbit antibody SmPOP is distributed in the tegument ( males ) and parenchyma of NTS and adult schistosomes . The enzyme is absent from the gastrodermis and gut lumen suggesting that the enzyme does not contribute to the digestion of ingested blood proteins . The antibody signal was significantly greater in male worms in accordance with the activity profiling of worm extracts , whereby male worm extracts displayed 5–6 times greater SmPOP specific enzymatic activity than females ( S6 Fig ) . Intriguingly , SmPOP is found in the male tegument , not least in the tubercles , but is apparently absent from the female tegument . This suggests that SmPOP may have male-specific peptidolytic functions at the host–parasite interface and/or at the male-female interface . As noted above , the enzyme seems not to be secreted by the parasite yet , via contact with the endothelium of the host vasculature , may exert localized effects on vascular physiology , including the degradation of vasoactive peptides ( see below ) . A similar localization in the tegument and parenchyma was previously noted for the S . mansoni cysteine peptidase cathepsin B2 for which physiological function ( s ) are not yet known [52] . We demonstrate that the schistosome parasite can cleave the vasoregulatory peptides , angiotensin I and bradykinin , when co-incubated in vitro and that the activity is due to SmPOP as indicated by mass spectrometry and specific inhibition by a POP inhibitor . Angiotensin I is produced by the renin-angiotensin system which is the primary physiological regulator of blood pressure , sodium balance and fluid volume [53] . SmPOP converts angiotensin I ( precursor of the main vasoconstrictor angiotensin II ) to the vasodilatory angiotensin- ( 1–7 ) . Angiotensin- ( 1–7 ) also inhibits cell proliferation , angiogenesis , fibrosis , and inflammation [54 , 55] . Bradykinin is generated by the kallikrein-kinin system which also participates in the regulation of blood pressure [53] . Bradykinin is a potent vasodilator , promotes natriuresis , diuresis and inflammation . Proteolytic cleavage by SmPOP inactivates this hormone . The possible contribution , therefore , by a tegument-localized SmPOP to the modulation or dysregulation of both these , and possibly , other , homeostatic systems is conceivable whereby cleavage of the pro-inflammatory and vasoconstrictory angiotensin I and pro-inflammatory bradykinin may provide a survival benefit to the schistosome during its residence in and movement through the venous blood system . Follow-up in vivo studies will examine these possibilities in more detail . | Schistosomiasis ( bilharzia ) is a major global health problem caused by the schistosome flatworm which lives in the bloodstream . Treatment and control of the disease relies on a single drug , and should resistance emerge , there would be increased pressure to discover new drug targets . Proteolytic enzymes are fundamental to the survival of parasites , and , hence , are attractive targets for drug intervention . Oligopeptidases from the S9 family are known virulence factors for protozoan trypanosomatids but have yet to be studied in parasitic flukes . We , therefore , investigated prolyl oligopeptidase in Schistosoma mansoni ( SmPOP ) and found that it is expressed in those developmental stages that infect humans . We provide a comprehensive analysis of the peptidase’s expression , localization and functional biochemical properties . Interestingly , SmPOP , which is found in the tegument and parenchyma of the parasite , can cleave blood peptides involved in vasoregulation and we discuss how this ability may aid the parasite’s survival . Finally , we designed potent inhibitors of SmPOP that cause deleterious changes in cultured parasites . We conclude that SmPOP is important for parasite survival and may be a potential target for the development of anti-schistosomal drugs . | [
"Abstract",
"Introduction",
"Materials",
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"Results",
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] | [] | 2015 | Prolyl Oligopeptidase from the Blood Fluke Schistosoma mansoni: From Functional Analysis to Anti-schistosomal Inhibitors |
During meiotic prophase in male mammals , the heterologous X and Y chromosomes remain largely unsynapsed , and meiotic sex chromosome inactivation ( MSCI ) leads to formation of the transcriptionally silenced XY body . In birds , the heterogametic sex is female , carrying Z and W chromosomes ( ZW ) , whereas males have the homogametic ZZ constitution . During chicken oogenesis , the heterologous ZW pair reaches a state of complete heterologous synapsis , and this might enable maintenance of transcription of Z- and W chromosomal genes during meiotic prophase . Herein , we show that the ZW pair is transiently silenced , from early pachytene to early diplotene using immunocytochemistry and gene expression analyses . We propose that ZW inactivation is most likely achieved via spreading of heterochromatin from the W on the Z chromosome . Also , persistent meiotic DNA double-strand breaks ( DSBs ) may contribute to silencing of Z . Surprisingly , γH2AX , a marker of DSBs , and also the earliest histone modification that is associated with XY body formation in mammalian and marsupial spermatocytes , does not cover the ZW during the synapsed stage . However , when the ZW pair starts to desynapse , a second wave of γH2AX accumulates on the unsynapsed regions of Z , which also show a reappearance of the DSB repair protein RAD51 . This indicates that repair of meiotic DSBs on the heterologous part of Z is postponed until late pachytene/diplotene , possibly to avoid recombination with regions on the heterologously synapsed W chromosome . Two days after entering diplotene , the Z looses γH2AX and shows reactivation . This is the first report of meiotic sex chromosome inactivation in a species with female heterogamety , providing evidence that this mechanism is not specific to spermatogenesis . It also indicates the presence of an evolutionary force that drives meiotic sex chromosome inactivation independent of the final achievement of synapsis .
During meiotic prophase , homologous chromosomes pair and are held together by the synaptonemal complex ( reviewed in [1] ) . In spermatocytes of male mammals , the heterologous X and Y chromosomes pair and synapse only in small pseudoautosomal regions ( PARs ) . The presence of the largely unsynapsed X and Y chromosomal axes is associated with meiotic sex chromosome inactivation ( MSCI ) [2] , [3] . The two X chromosomes in meiotic prophase in oocytes show complete synapsis and are transcriptionally active . In birds , females are heterogametic , carrying Z and W chromosomes ( ZW ) , whereas males have the homogametic ZZ constitution . The chicken Z chromosome is the larger of the two chromosomes ( http://www . ensembl . org/Gallus_gallus/index . html ) . Similar to the mammalian X and Y sex chromosomes , the Z and W chromosomes share only a small pseudoautosomal region [4] . However , the behaviour of the ZW pair during female oogenesis in the chicken differs from that of the XY pair in mammalian spermatocytes , in that the ZW chromosomes appear to reach a stage of complete synapsis . Based on electron micrographs , Solari [5] analysed the pairing between Z and W throughout the pachytene stage and found that the chromosomal axes of the Z chromosome thickens and shortens ( most likely by folding back on itself ) , and wraps itself around the W chromosome to achieve complete synapsis during the brief so-called equalized stage . Subsequently , the Z and W chromosomes desynapse but remain attached at their tips when the oocytes enter diplotene . The morphological changes of the Z and W axes have been explained by a mechanism called synaptic adjustment [5] . This mechanism describes the process of resolving an axial length difference between aligned chromosomes to achieve complete synapsis [6] , [7] . During mitotic prophase in female chicken cells , the small W chromosome appears to be heterochromatic [8] indicating that the W chromosome is mostly inactive in somatic cells . During early meiotic prophase in leptotene and zygotene oocytes , such a heteropycnotic area appears to be absent [9]–[11] . Subsequently , Z and W pair completely . Although the pairing is mainly heterologous , Jablonka and Lamb [12] have suggested that pairing , synapsis and subsequent retention of an active state is preferred above meiotic inactivation of Z and W , because of a requirement for Z- and/or W-linked genes for maintenance and growth of the large and long-living oocytes . However , Solari [10] describes the appearance of a more dense chromatin structure surrounding the ZW pair in late pachytene and early diplotene oocytes , and the appearance of a heteropycnotic body in some late pachytene and diplotene nuclei of chicken oocytes . This observation suggests that some form of Z and/or W inactivation may occur during late meiotic prophase . MSCI in mammals is thought to be a specialization of a more general process that silences unsynapsed chromatin during meiotic prophase , named MSUC ( meiotic silencing of unsynapsed chromatin ) [13]–[15] . Similar , but mechanistically distinct mechanisms ( meiotic silencing by unpaired DNA; MSUD ) are operative in a variety of distant species such as Caenorhabditis elegans and Neurospora crassa ( reviewed in [16] ) . In mammalian meiosis , chromosomal alignment and pairing is preceded by induction of DNA double strand breaks ( DSBs ) by the topoisomerase-like protein SPO11 , and these DSBs are thought to participate in homology recognition [17] , [18] . After formation of DSBs , the homologous recombination repair protein RAD51 rapidly forms filaments on the 3′ end single-strand DNA overhangs of meiotic DSBs [19] . The presence of persistent RAD51 foci on the unpaired X chromosome of mouse and man indicates that DSBs in heterologous regions show delayed repair [19]–[21] . This is most likely due to the fact that a non-sister chromatid from a homologous chromosome is not available for strand invasion and recombination repair . Ashley et al . [20] reported a high concentration of RAD51 foci on the unsynapsed axis of the Z chromosome in chicken oocytes during early pachytene , which disappear as the oocytes progress through pachytene . Unsynapsed sex chromatin , persistent DSBs , and meiotic silencing are always associated in mice [13] , [15] , [22] . In chicken oocytes , however , the ZW pair reaches a state of complete synapsis , but possibly with persistent DSBs . In the present paper , we have investigated whether meiotic DSBs in chicken oocytes persist on the Z chromosome , analogous to persistence of X-chromosomal meiotic DSBs in mouse spermatocytes , and whether or not this would be associated with MSCI .
Oocytes were isolated from embryonic day 20 ( E20 ) , day 4 ( P4 ) and 7 ( P7 ) post hatching female chickens . Ovaries were collected and incubated for 30 min in 20 ml Dulbecco's-PBS medium containing 1 mg/ml collagenase , 1 mg/ml trypsin and 0 , 5 mg/ml hyaluronidase ( Worthington , Lakewood , USA ) in a shaking waterbath with an amplitude of 1 cm at 37°C ( 60 cpm/min ) . A single cell suspension was obtained by repeated pipetting of the suspension . After filtration through 70 µm gauze , the cell suspension was centrifuged for 3 min at 800 g . 1 ml of cell suspension in DMEMF12 was loaded on 9 ml of a 3-step gradient of 1 . 012 , 1 . 037 and 1 . 071 mg/ml Nycodenz ( Nycoprep™ Universal , Axis Shield PoC AS , Oslo , Norway ) and centrifuged at 2400 g for 20 min at 20°C . The oocyte fraction was collected from the 1 , 037 mg/ml layer , centrifuged for 3 min at 800 g and the pellet was snap-frozen in liquid nitrogen and stored at −80°C . Based on SYCP3 staining of spread nuclei preparations from the purified fractions we calculated a purity of 70% , 40% and 50% oocytes in fractions isolated from E20 , P4 and P7 , respectively . Chicken ( Gallus gallus domesticus ) eggs were incubated at 37°C and a humidity of 70–80% until hatching . Chickens were killed by CO2 intoxication . The functional left ovary or left and right testes were dissected and placed in Hanks' solution . Spread nuclei preparations of chicken oocytes and spermatocytes were prepared using a modification of the drying-down technique described by Peters et al . [23] . Briefly , ovaries and testes were minced in pieces with forceps and cells were suspended in 500 µl of 100 mM sucrose , containing EDTA-free complete protease inhibitor cocktail ( Roche Diagnostics , Almere , The Netherlands ) . Oocytes and spermatocytes were dispersed on a glass slide dipped in 1% paraformaldehyde fixative with 0 . 1% Triton X100 . After two hours in a humid chamber at room temperature , the slides were allowed to dry for 30 minutes at room temperature , followed by a single wash in 0 . 08% Photoflo ( Kodak , Paris , France ) and air-dried . The slides were stored at −80°C . For immunocytochemistry , frozen slides were defrosted at room temperature and washed with PBS . The slides were blocked with PBS containing 0 . 5% w/v BSA and 0 . 5% w/v milk powder , and double stained with different combinations of the following antibodies: rabbit polyclonal anti-SYCP3 ( 1∶1000 ) , rabbit polyclonal anti-SYCP1 ( 1∶200 ) ( gifts from C . Heyting , Wageningen ) , mouse polyclonal anti-γH2AX ( 1∶1000 ) ( Upstate , Walthum , MA , USA ) , rabbit polyclonal anti-γH2AX ( 1∶1000 ) ( Upstate ) , mouse monoclonal IgM anti-H2AK119ub1 ( 1∶1000 ) ( Upstate ) , mouse monoclonal anti-RNA polymerase II , ( 8WG16 ) directed against the RNA polymerase II CTD repeat YSPTSPS ( 1∶600 ) ( Abcam , Cambridge , United Kingdom ) , mouse monoclonal anti-H4K16ac ( 1∶200 ) ( Upstate ) , mouse monoclonal anti-H3K27me3 ( 1∶100 ) ( Abcam ) , rabbit polyclonal anti-H3K9me3 ( 1∶500 ) ( Upstate ) , and rabbit anti-human RAD51 ( 1∶500 ) [24] . For mouse monoclonal primary antibodies , the secondary antibodies were fluorescein isothiocyanate ( FITC ) -labeled goat anti-mouse IgG antibodies ( 1∶128 ) ( Sigma , St Louis , USA ) for anti-RNA polymerase II , anti-γH2AX , and anti-H3K27me3 , FITC-labeled goat anti-mouse IgM ( 1∶128 ) ( Sigma ) for anti-H2AK119ub1 and tetramethylrhodamine isothiocyanate ( TRITC ) -labeled goat anti-mouse IgG antibodies ( 1∶128 ) ( Sigma ) for anti-γH2AX . The secondary antibody for polyclonal rabbit primary antibodies was tetramethylrhodamine isothiocyanate ( TRITC ) -labeled goat anti-rabbit IgG antibodies ( 1∶200 ) ( Sigma ) for anti-SYCP3 and fluorescein isothiocyanate ( FITC ) -labeled goat anti-rabbit IgG antibodies ( 1∶80 ) ( Sigma ) for anti-Rad51 , anti-SYCP1 , and anti-γH2AX . Primary antibodies were diluted in 10% w/v BSA in PBS and incubated overnight in a humid chamber . Thereafter , slides were washed in PBS , blocked in 10% v/v normal goat serum ( Sigma ) in blocking buffer ( 5% milk powder ( w/v ) in PBS , centrifuged at 13 . 200 rpm for 10 min ) , and incubated with secondary antibodies in 10% v/v normal goat serum in blocking buffer at room temperature for 2 hours . Next , the slides were washed in PBS and embedded in Vectashield containing DAPI ( 4′ , 6′-diamindino-2-phenylindole ) ( Vector Laboratories , Burlingame CA , USA ) . Double stainings of SYCP1 with SYCP3 , of RAD51 with SYCP3 , and of SYCP3 with H3K9me3 ( all rabbit polyclonal antibodies ) were obtained by sequential immunostainings with the single antibodies . Images of SYCP1 , RAD51 and SYCP3 stainings respectively , were obtained prior to immunostaining with anti-SYCP3 or H3K9me3 of the same nuclei . For real-time RT-PCR , RNA was prepared from embryonic female liver , embryonic day ( E20 ) , post hatching day 4 ( P4 ) and day 7 ( P7 ) ovaries and oocyte fractions by Trizol ( Invitrogen , Breda , The Netherlands ) , DNase-treated and reverse transcribed using random hexamer primers and Superscript II reverse transcriptase ( Invitrogen ) . PCR was carried out with the Fast SYBR green PCR mastermix ( Applied Biosystems , Foster City , USA ) in the DNA engine Opticon 2 real-time PCR detection system ( Bio-Rad , Hercules , USA ) . For ACTB , SYCP3 , SPO11 , W genes: NIBPL , SPIN , SMAD2 , HINTW and Z genes: NIBPL , SPIN1 , SMAD2 , HINT1 , DMRT1 , TXNL1 , TXN , ILR7 , PARP8 , SLCA1A3 we used the following conditions: 3 minutes 95°C , then 10 seconds 95°C , 30 seconds 58°C , 30 seconds 72°C for 40 cycles , experiments were performed in triplicate . For data analysis , the average threshold cycle ( Ct ) was converted to absolute amount of transcript ( E−Ct ) ( E = efficiency determined via a standard curve ) and presented as E Ct Actin -Ct gene of interest . To estimate the expression of Z and W encoded genes in oocytes and to correct for differences in purity , we used the following formulas: Expo = measured expression level in the purified oocyte sample , P = purity of the oocytes ( 0 . 7 , 0 . 4 and 0 . 5 for E20 , P4 and P7 respectively ) , Exoc = expression level in oocytes , Exr = expression level in the rest of the ovarian cells , Exov = measured expression level in the ovary , F = oocyte fraction in the ovary . We equalized the Exr for SYCP3 to the expression measured in embryonic liver . This allowed us to calculate the value of F in the different ovary samples . The median value of F was found to be 0 . 06 , and this number was used to calculate Exoc . All –RT reactions were negative . Forward and reverse primers ( 5′ to 3′ ) : See Table 1 . First , immunocytochemistry was performed as described above , and images were made of selected nuclei . Probe mixture of digoxigenin-labelled GGA ( Gallus GAllus ) W and biotin-labelled GGA Z chromosome ( heterochromatic part ) painting probes ( Farmachrom , Kent , UK ) , salmon sperm DNA and hybridisation buffer were mixed and denatured at 75°C . Slides were treated with 0 . 005% pepsine solution for 5 minutes at 37°C , washed in 2×SSC at room temperature for 5 minutes , rinsed in distilled water and then air dried . Next , they were dehydrated , air-dried and incubated for 1 hour at 75°C . Again , slides were dehydrated and air dried . Subsequently , RNAse mix ( 100 µg/ml in PBS ) was placed on each slide , and slides were incubated in a humid chamber at 37°C . After 1 hour , slides were again air dried . Slides were denatured in 70% formamide with 30% 2×SSC for 160 seconds at 75°C . This was followed by quenching the slides in ice-cold 70% ethanol , then at room temperature in 80% ethanol and finally in 100% ethanol . Probe mixture was placed on the slide , covered with a coverslip and sealed . The slides were placed in a pre-heated humid chamber and incubated overnight at 37°C . After incubation , the slides with coverslip were placed in 2×SSC at room temperature for 5 minutes . After removal of the coverslip , slides were then rinsed twice in 50% formamide and 50% 2×SSC for 10 minutes at 37°C , followed by rinsing in 2×SSC with 0 . 1% Triton X-100 at room temperature for 1 minute . Subsequently , the slides where placed 1 hour in 4×SSC with 0 , 05% Triton X-100 . Finally , the slides were placed in 4×SCC , 0 . 05% Triton X-100 , 3% BSA for 25 minutes at room temperature . Slides were incubated with anti-biotin-labelled Cy3 and anti-digoxigenin Avidine Alexa Fluor 488-labelled antibodies ( Invitrogen ) in a dark humid chamber for 35 minutes at room temperature . After removing the coverslips , slides were washed 3 times for 3 minutes in 4×SSC with 0 . 05% Triton X-100 , rinsed in distilled water and air dried before a droplet of Vectashield mounting medium with DAPI ( 4′ , 6′-diamidino-2-phenylindole ) ( Vector Laboratories ) was placed on the slide and covered with a coverslip . Analysis of the chicken oocyte nuclei was performed using a Carl Zeiss Axioplan 2 imaging microscope ( Jena , Germany ) with a plan-neofluar objective 100×/1 . 3 oil immersion . Images were taken with a Coolsnap-pro digital camera ( Photometrics , Waterloo , Canada ) . The acquired digital images were processed with Photoshop software ( Adobe Systems ) .
We analysed the progression of meiotic prophase in chicken oocytes by immunostaining for SYCP3 , which visualizes the lateral axial elements of the synaptonemal complex ( SC ) . At leptotene , small SYCP3 fragments started to appear throughout the nucleus ( Figure 1A ) . In addition to Z and W , the chicken genome is distributed over 38 autosomal chromosome pairs , including 10 pairs of microchromosomes . During zygotene , most microchromosomes are found at the periphery of one part of the nucleus , where they are aligned and have initiated pairing , whereas macrochromosomes are more confined to the center and opposite site of the nucleus , and appear entangled and disorganized ( Figure 1A ) . At early pachytene , when all autosomes have completed synapsis , the ZW pair starts to synapse ( Figure 1A , B ) . Around mid-pachytene , the ZW pair reaches the complete synapsed or so-called equalized stage ( Figure 1B ) , and frequently localizes to the periphery of the nucleus ( Figure 2A ) . These findings are consistent with the configurations of the Z and W chromosomes described by Solari [5] ( Figure 1B ) , and we used the consecutive configurations of the ZW pair to subdivide the pachytene stage . During early pachytene , the Z and W chromosomes appear to be separate ( ‘early type’ ) . This is followed by ZW pairing and synapsing in the short pseudo-autosomal regions . Subsequently the long asynaptic segment ( LAS ) of Z , starts to condense and shorten ( most likely by folding back on itself ) , becoming the medium asynaptic segment ( MAS ) . At mid-pachytene , the Z chromosome starts to wind itself around the relatively straight W axis , resulting in a fully equalized ZW pair ( Figure 1B ) . Next , the Z and W start to desynapse and rapidly separate again ( ‘late separate’ ) . At early diplotene , Z and W display end-to-end attachment ( Figure 1B ) . Subsequently , all bivalents desynapse , elongate and become intertwined , making it almost impossible to distinguish and follow the individual Z and W chromosomes . However , in some diplotene nuclei , the Z and W chromosomes were found to display an end-to-end pairing in a typical ζ ( zeta ) -like configuration ( Figure 1B and 2B ) . Next , we investigated if the Z and W chromosomes actually reach a state of full synapsis during the equalized stage . For this purpose , we stained for SYCP1 . In contrast to SYCP3 , which localizes to the chromosomal axes of meiotic chromosomes , SYCP1 is a component of the central element of the SC , which is only assembled on completely synapsed chromosomes ( reviewed in [25] ) . During the LAS and MAS stages , SYCP1 stains only the synapsed regions of the ZW pair . As soon as the Z chromosome starts to wrap itself around the W chromosome , we observed that the SYCP1 signal followed the twists of the Z chromosome ( Figure 1C ) . At the equalized stage , the SYCP3 and SYCP1 staining fully overlapped , except for the occasionally free tip of the Z chromosome . As pachytene progresses further , Z and W begin to desynapse , and this was accompanied by disappearance of SYCP1 from these regions ( Figure 1C ) . At the ‘late separate’ stage , SYCP1 was no longer present on Z and W . Based on these observations , we conclude that the equalized stage indeed represents a completely synapsed configuration of Z and W . To analyse the transcriptional activity of the Z and W chromosomes during the different stages of meiotic prophase , we immunostained oocytes for RNA polymerase II ( RNA pol II ) and SYCP3 . During leptotene and zygotene , we found positive staining for RNA pol II throughout the nucleus , but from early pachytene onwards , there is a depletion of RNA pol II surrounding the ZW pair ( Figure 2A ) . The absence of RNA pol II was most prominent during the equalized stage . As pachytene progresses into diplotene , the exclusion of RNA pol II around the ZW pair persists , and a reduction of RNA pol II surrounding the SC was also observed for other macrobivalents ( Figure 2A ) . In mid diplotene , the overall signal of RNA pol II increased , but the level in the area around ZW remained relatively low . These data indicate that the Z and W chromosomes are subjected to meiotic silencing . In late diplotene , RNA pol II staining is no longer reduced on Z and W ( not shown ) . To obtain further evidence for transcriptional silencing of Z and W during chicken oogenesis , we analysed the localization of the known heterochromatin marker H3K9me3 [26] , in combination with a FISH specific for the W chromosome and the heterochromatic part of the Z chromosome . In oogonia , and in leptotene and zygotene oocytes , we observed several regions enriched for H3K9me3 , but the region with the highest signal always colocalized with the FISH signal for W ( Figure 2B ) . The Z painting probe colocalized with a region of Z that was also enriched for H3K9me3 , but to a lesser extent compared to the enrichment of H3K9me3 on the W chromosome . During the equalized stage , the chromatin surrounding the ZW pair could easily be recognized as the region that displayed the strongest H3K9me3 staining in the nucleus ( Figure 2B ) . As the ZW pair desynapses , H3K9me3 is lost from the Z chromosome , with the exception of the heterochromatic region that is recognised by the painting probe ( Figure 2B ) . These findings indicate that the W chromosome is already inactive before entry into meiotic prophase , while the inactivation of the whole Z seems to be a transient process from early pachytene until diplotene . Based on our observations and earlier reports , we estimate that the duration from pachytene till early diplotene takes approximately 3–4 days [27] . Next , we analysed the behaviour of histone H2AX phosphorylated at serine 139 , ( γH2AX ) , a well-known marker of DNA double strand breaks ( DSBs ) [17] , [28] . This is also the earliest histone modification that appears on the silenced XY body in mouse ( reviewed in [29] ) . In chicken oocytes , γH2AX was found to be present throughout the nucleus with areas showing more intense staining in leptotene and zygotene ( Figure 3A ) . These areas most likely correspond to sites of meiotic DSBs , similar to what has been observed for mouse oocytes and spermatocytes [17] . At the end of zygotene , remaining γH2AX foci localize to sites associated with synaptonemal complexes ( SCs ) . Persistent γH2AX foci were observed along the unsynapsed arm of the Z chromosome ( Figure 3BC ) , as confirmed by subsequent FISH with specific probes against the heterochromatic part of Z and the whole W chromosome . During mid pachytene , when the ZW pair is fully synapsed , γH2AX foci along the length of the SCs have disappeared , but all telomeres showed a bright focus ( Figure 3D ) . During mid-late pachytene , when the Z and W start to desynapse , a second wave of γH2AX starts to accumulate in a distal to proximal fashion on all the desynapting regions of Z ( Figure 3EF ) . In diplotene , γH2AX covers the whole Z chromosome , with the exception of the heterochromatic part , which looses γH2AX during the late separate stage ( compare diplotene in Figure 3E with Figure 3F ) . In addition , all other chromosomes maintain γH2AX at the telomeres . Approximately two days after entering diplotene , as seen in part of the diplotene oocytes isolated from 7-day-old chickens , γH2AX is lost from the Z chromosome ( Figure 3A ) . Together with the RNA polymerase II and H3K9me3 staining patterns , these data show that the second wave of γH2AX accumulation starts after silencing of the ZW pair has been established . Moreover , the second wave of γH2AX labelling appears to be restricted to the Z chromosome . These findings contrast with observations during mouse meiosis , where γH2AX accumulation is essential for , and occurs concomitant with , silencing of the sex chromosomes [30] . To obtain more insight in the trigger for γH2AX accumulation on the Z chromosome during late pachytene in chicken oocytes , we analysed the immunolocalization of the DSB-repair protein RAD51 . We found RAD51 foci on the synapsed autosomes and the unsynapsed axis of the Z chromosome during early pachytene . However , we never observed RAD51 foci on the W chromosome during pachytene ( Figure 4A–F ) . During progression of pachytene , RAD51 foci gradually disappeared from the autosomes . As synapsis between Z and W progresses , RAD51 foci start to disappear from the synapsed part , but remain present on the part of Z that is still unsynapsed ( Figure 4B–D ) . During the equalized stage , only a diffuse RAD51 signal persists at the distal tip of Z ( Figure 4E ) . When the Z and W start to desynapse , we noticed a reappearance of RAD51 foci along the desynapsing Z chromosomal axis ( Figure 4F ) . When Z and W were almost completely separated ( ‘late separate’ subtype ) , RAD51 foci covered the complete Z chromosome ( Figure 4G ) , whereas the W chromosome remained devoid of these foci . Upon entering diplotene , all SC-associated RAD51 foci gradually disappear ( Figure 4A ) . The observed temporal disappearance of RAD51 foci ( and γH2AX ) during progression of synapsis between Z and W in pachytene could indicate that the repair proteins are transiently lost , while the breaks are not repaired . However , the lack of detectable RAD51 foci could also be due to the tight winding and twisting of Z around W , which may render the RAD51 proteins inaccessible to the antibody . Still , the absence of γH2AX from the synapsed ZW indicates that the DSBs may also be temporarily undetectable for the machinery that couples processing of these breaks to γH2AX formation . Final repair of these breaks may therefore be suppressed until Z and W desynapse . Next , we investigated the localization of several known other mammalian and marsupial XY body markers in chicken oocyte nuclei . First , we evaluated H2Ak119ub1 , a histone modification which is generally associated with gene silencing , in combination with FISH for Z and W . It marks the inactive X chromosome in female somatic cells [13] , [31] , [32] , and the mammalian XY body from mid-pachytene to early diplotene [33] . In chicken zygotene oocytes , this histone modification marks the W chromosome ( Figure 5B ) and from late zygotene onwards also accumulates on centromeric chromatin . In early pachytene , H2Ak119ub1 starts to spread from the centromeres on a few microbivalents . It also begins to accumulate on the already synapsed part of the ZW pair , and part of the distal unsynapsed arm of the Z chromosome ( Figure 5C ) . Around mid-pachytene , when the ZW pair is fully synapsed , the H2Ak119ub1 signal increases and intensifies specifically on the ZW pair ( Figure 5D ) . When the Z and W start to desynapse , H2Ak119ub1 remains present on the desynapting Z chromosomal axis , but is eventually lost from the W ( Figure 5E ) . At the late separate stage and during early diplotene , H2Ak119ub1 covers the Z chromosome ( Figure 5FG ) , with exception of the heterochromatic part recognized by the FISH probe . A few days after entering diplotene , H2AK119ub1 is lost from the Z chromosome , and appears in an evenly distributed manner throughout the whole nucleus ( Figure 5H ) . H3K27me3 , an early marker of X chromosome inactivation in the female mouse embryo [34] , is reduced on the XY body in mammals [35] and marsupials [36] . In chicken leptotene oocyte nuclei , this modification is virtually absent , whereupon the signal in zygotene nuclei increases on W and some microbivalents ( Figure 6A ) . During pachytene , H3K27me3 is enriched on three microbivalents , but this modification most prominently marks a subregion of the W chromosome ( Figure 6A ) . This enrichment of H3K27me3 on the W chromosome was found to remain prominent only on the W chromosome , even in late diplotene ( Figure 6A ) . Acetylation of H4K16 is associated with active transcription , and in nuclei of female chicken somatic cells , a subregion of the Z chromosome is specifically enriched for this histone modification [37] . We performed double-immunostainings of oocytes for H4K16ac and SYCP3 , followed by a FISH for Z and W . During zygotene , H4K16ac stained the nucleus more prominent then during leptotene and pachytene , which could indicate a transient global upregulation of transcription ( not shown ) . Similar to what was observed for RNA polymerase II , reduced H4K16ac staining is observed on the completely synapsed ZW pair ( Figure 6B ) . As pachytene progresses , H4K16ac is also reduced around long autosomal SCs . The low level of H4K16ac on ZW appears to persist until mid diplotene . We also performed double-stainings for γH2AX and H4K16ac and observed that when γH2AX accumulates on the desynapting Z , H4K16ac is reduced , and this persists up to diplotene ( Figure 6C ) . Concomitantly , H4K16ac signal increases on the rest of the genome . Together , these observations show that the Z and W chromosome lose H4K16ac around the midpachytene stage , indicating transcriptional silencing , in accordance with our other observations . If the Z and W chromosome are silenced during pachytene and early diplotene , mRNAs for Z and W-encoded genes should be decreased in these cells , compared to earlier and/or later stages of oocyte development . To analyse this , we performed real-time RT-PCR experiments using total RNA isolated from purified oocyte fractions and total ovaries isolated on 3 different time points ( embryonic day 20 , post hatching day 4 and day 7 ) . Real time RT-PCR was performed for 10 Z-encoded genes , 4 W-encoded genes ( Figure 7A ) and 2 autosomal meiosis-specific genes , namely the synaptonemal complex component SYCP3 and meiotic-DNA double strand break-inducing enzyme SPO11 . The expression profiles of SYCP3 and SPO11 followed the expected pattern ( Figure 7B , Figure S1 ) . The Z genes , HINT1 , TXN , NIPBL and SMAD2 all show a relative decrease in expression in oocytes of post hatching day 4 , followed by an increase in expression at day 7 ( Figure 7B ) ; Expression of the Z gene SLCA1A3 is measured in oocytes for the first time at day 7 . The W gene HINTW also shows a decrease on post hatching day 4 , and subsequently increased expression at day 7 . The other analysed Z- en W-encoded genes showed no expression in oocytes at any timepoint , indicating that they are inactive during meiotic prophase . Based upon earlier descriptions of ovary development [5] , [10] , [38] and our own observations , most oocytes are still in zygotene during embryonic day 20 , whereas the vast majority of the oocytes is in late pachytene on post hatching day 4 , and in late diplotene on day 7 . The observed decrease in mRNA levels of Z- and W-encoded genes supports our immunocytochemical findings and confirms that Z and W are transiently silenced during oocyte development . To establish that the ZW pair in oocytes behaves different from the ZZ pair in spermatocytes , we also performed immunocytochemical analyses on chicken spermatocytes isolated from adult testes . Similar to what we observed in oocytes , , γH2AX was present throughout the nucleus with areas showing more intense staining in leptotene and zygotene spermatocytes ( Figure S2A ) . At the end of zygotene , remaining γH2AX foci localize to sites associated with synaptonemal complexes , also resembling the pattern observed in chicken oocytes . However , during pachytene , all chromosomes were fully synapsed and γH2AX was present only on telomeres , and this pattern persisted up to late diplotene ( Figure S2A ) . Next , we analyzed the presence of H3K9me3 in combination with a FISH specific for the heterochromatic regions of the Z chromosomes ( Figure S2B ) . Several regions in leptotene and zygotene spermatocytes were enriched for H3K9me3 , but they never colocalized with the FISH signal ( s ) of Z ( Figure S2B ) . In pachytene , the heterochromatic region of Z showed some enrichment for H3K9me3 , and this signal decreased again during diplotene ( Figure S2B ) . H3K27me3 was present on a few microchromosome throughout meiotic prophase , but not on Z ( not shown ) .
Meiotic sex chromosome inactivation ( MSCI ) in male mammals is thought to be triggered by the presence of unsynapsed axes of the X and Y chromosome ( reviewed in [29] ) . Recently , it was discovered that in marsupial spermatocytes the unsynapsed X and Y chromosomes are also inactivated in a manner similar to what has been observed in mouse [36] , [39] . Herein , we show inactivation of sex chromosomes during meiosis in the female Gallus gallus domesticus , a species with female heterogamety and a ZW sex chromosome system that evolved independent of XY . Female oocytes undergo a much longer developmental process between the initiation of meiotic prophase and ovulation , compared to the time course that is involved during development of spermatocytes to mature sperm . Therefore , it was suggested that meiotic inactivation of Z ( and W ) would not occur because it would be incompatible with the lengthy oocyte developmental process [12] . Herein , we have shown to the contrary that MSCI does occur , but is transient in chicken oocytes; in diplotene , the Z chromosome loses its specific “silencing” histone modifications ( γH2AX and H2Ak119ub1 ) . In addition , the mRNA of several Z-encoded genes is higher in oocytes isolated at posthatching day 7 compared to day 4 . Reactivation of Z may allow Z-encoded genes to assist in further oocyte development . HINTW is a W chromosomal multicopy gene [40] , [41] that also shows increased expression in day 7 oocytes . It localizes to the non-heterochromatic tip of W [42] . Based on its female specificity and expression in differentiating ovaries of early embryos , HINTW has been implicated in female sex differentiation , but its exact function is unclear [42] . The W chromosome is gene poor , and to date , only a few genes have been described to be W-specific ( ICBN Mapviewer , [41] , [43] ) . In addition , the actual size of the pseudo-autosomal region between Z and W has not been established . Based on the persistent presence of H3K9me3 on W in diplotene oocytes , it could be suggested that the W remains inactive throughout oocyte development , perhaps with the exception of the non-heterochromatic tip that contains the multicopy gene HINTW . This nicely parallels the recent findings by Mueller et al [44] , who describe that X- linked multicopy genes that are subjected to MSCI are specifically re-expressed in postmeiotic spermatids in mouse , whereas the vast majority of single-copy genes remain inactive . In early mouse pachytene spermatocytes , the X and Y chromosome show more extensive synapsis compared to the later pachytene stages , when desynapsis progresses until the X and Y show only an end to end association in some diplotene nuclei [45] . This resembles the dynamics of ZW association during chicken oogenesis , with exception of the fact that complete synapsis is never achieved in mouse , and always in chicken . Our data now show that despite the complete ( heterologous ) synapsis , sex chromosome inactivation is not prevented , and repair of meiotic DSBs is delayed ( see below ) . During mammalian MSCI , silencing of some essential X chromosomal genes is compensated by expression from retroposed copies on autosomal chromosomes . The expression of these copies is male-specific and initiates concomitant with MSCI [46] . However , in the chicken genome , very few functional retroposed genes appear to be present [47] . For the 15 identified functional retroposed genes in chicken , no bias for genes from specific chromosomes was detected . Due to the transient nature of the ZW inactivation , Z-encoded mRNAs and proteins may be in large enough supply to allow maintenance of function of essential Z-linked genes during this short period . Genomic analyses and analyses of EST databases have revealed that ovary-specific genes are underrepresented on the chicken Z chromosome . In addition , microarray analyses of gene expression in different chicken tissues have shown that the average expression of Z-linked genes versus autosomal genes is lowest in the embryonic ovary [48] . This phenomenon could have different causes . In principle , so-called sexually antagonistic genes ( genes beneficial to one sex , detrimental to the other ) , are expected to accumulate on the sex chromosomes . In species with male heterogamety , recessive male beneficial genes would be expected to accumulate on the X . In accordance with this notion , the mouse and human X chromosome are enriched for spermatogenesis-genes expressed prior to meiotic prophase . Due to MSCI and PMSC ( post meiotic sex chromatin ) , the X is depleted for spermatogenesis-genes expressed during later stages , with the exception of some single-copy and multicopy genes , that show postmeiotic reactivation [44] , [49] , [50] . Since retroposition of Z genes to autosomes does not seem to occur in chicken [47] , it might be suggested that the evolutionary force to drive oocyte-specific genes off the Z during evolution is relatively weak , perhaps due to the transient nature of MSCI in chicken . Still , the relative lack of ovary-specific genes , and the generally low level of Z-encoded gene expression in embryonic ovary may indicate that MSCI in chicken reduces the likelihood of oocyte-specific genes that function during meiotic prophase to evolve on the Z . However , the properties of the chicken Z chromosome can also be explained by a dominant model of sexual antagonistic genes , whereby dominant genes encoding proteins that are beneficial to males would be downregulated in females to minimize antagonism [51] . More detailed analyses of ovary-specific genes is required , including separate analyses of genes expressed in somatic and germ line cells of the ovary , to determine whether MSCI in chicken affects gene content on Z . The inactivation of Z and W during chicken oogenesis shows marked differences and similarities to MSCI in marsupial and mouse ( summarized in Figure 8 ) . The timing of Z inactivation ( early pachytene ) is similar to what has been observed in the other vertebrates . However , the W chromosome appears to enter the zygotene stage already in a ( partially ) inactivated configuration . γH2AX appears as foci on the Z chromosome during zygotene , and these foci appear to persist longer on the Z compared to the autosomes , similar to what has been observed on the X chromosome during zygotene in mouse [17] , [52] . However , during the stage of complete synapsis , γH2AX is absent from the ZW pair . Then , a second wave of γH2AX formation appears around late pachytene on the desynapsed Z , and only after silencing has been established . This is in marked contrast with the second wave of γH2AX formation in mouse , which occurs on both X and Y , and immediately as spermatocyes enter pachytene . The appearance of γH2AX on the desynapting Z chromosome is accompanied by a reappearance of RAD51 . At this stage autosomal axes also begin to desynapse , but do not show a reappearance of RAD51 foci , and do not accumulate γH2AX . Thus , repair of meiotic DSBs on the Z chromosome may be inhibited to avoid recombination with the synapsed W chromosome , and postponed until desynapsis . This provides a clear link between the second wave of γH2AX formation and DSB-repair rather than with an unsynapsed axis per se . At this late pachytene/early diplotene stage , H2Ak119ub1 formation is also specifically enhanced on the Z chromosome . This modification is known to be associated with inactive chromatin , but has also been implicated in DSB-repair [53] . Perhaps silencing is induced at sites containing persistent DSBs to prevent aberrant ( truncated ) transcription through the damaged region in somatic as well as germ-line cells . In somatic cells , DSB repair can also be associated with the recruitment of silencing factors [54] . We reported a link between the presence of persistent DSBs and the frequency of meiotic silencing of unsynaped chromatin ( MSUC ) in mouse [22] . With the identification of meiotic sex chromosome inactivation in a species that shows female heterogamety as well as complete nonhomologous synapsis during pachytene , we provide indications for the presence of an evolutionary force that drives meiotic sex chromosome inactivation independent of the final achievement of synapsis . The absence of homologous chromatin ( as a template for the repair of DNA double-strand breaks ) could be instrumental in initiating this silencing , since synapsis is only achieved after silencing has been established . Based on the observations described herein , we propose the following model for the inactivation of the sex chromosome in the heterogametic female oocyte during meiotic prophase ( Figure 9 ) : The W chromosome enters meiosis in an inactive configuration , which includes hypermethylation of H3K9 and ubiquitylation of H2AK119 . H3K27me3 is also present on the W chromosome from zygotene onwards . H3K27me3 may recruit the polycomb protein complex PRC1 , which could then help to enhance ubiquitylation of H2AK119 , as has been observed during X inactivation in somatic cells of female mammals [32] . In pachytene , H3K27me3 remains enriched on a subregion of the synapsed ZW pair . Concomitantly , the synapsis with Z allows spreading in trans of heterochromatic marks such as H2Ak119ub1 and H3K9me3 from the inactive W chromosome on the Z chromosome . Also , additional spreading in cis of H3K9me3 and H2Ak119ub1 from the heterochromatic region of Z may contribute to inactivation of Z , triggered by the transient persistence of the meiotic DSB-associated γH2AX-signal . The accumulated silencing histone modifications result in inhibition of Z and W gene transcription , as visualized by reduced RNA polymerase II staining around ZW , and reduced mRNA expression of selected Z and W genes . During the compact arrangement of the Z-chromosomal axis around the W axis , DSB-repair is inhibited , and γH2AX and possibly also RAD51 are lost from the DSB-repair sites . Subsequent desynapsis is accompanied by reappearance of RAD51 , a second wave of γH2AX formation and enhanced H2Ak119ub1 formation on Z . The latter modification may maintain silencing ( despite the absence of H3K9me3 on the desynapsed Z ) until the breaks are repaired . The W chromosome remains inactive due to the high levels of H3K9me3 and H3K27me3 . Transcriptional inactivation of the ZW pair was first observed in oocytes when Z and W show the LAS to MAS configuration , at day 1 after hatching . Disappearance of γH2AX and H2Ak119ub1 from Z in diplotene was observed in oocytes isolated at the 7th day after hatching . This indicates that the period of Z inactivation lasts approximately 5 . 5–6 days . A wide variety of mechanisms exist that compensate for unequal gene dosage in species with chromosomal sex determination . Female marsupials show inactivation of the paternal X chromosome in somatic cells , to equalize the expression level of X-encoded genes with that of males . The recent discovery of MSCI and maintenance of X inactivation in postmeiotic cells of male marsupials supports the hypothesis that inheritance of a “pre-inactivated” X chromosome could contribute to the establishment of paternal X-inactivation in female embryos [36] . Our findings on transient ZW inactivation argue against the existence of such a mechanism in birds . This is in accordance with data from the literature that show that male birds do not show inactivation of one of the two Z chromosomes [48] , [55] , [56] . In fact , dosage compensation in birds appears to be far less complete than in mammals , and it is not yet known whether dosage compensation , if it occurs , is achieved via upregulation of Z-genes in females , or downregulation in males . It cannot be excluded however , that the transient inactivation of Z leads to epigenetic modifications that persist and may influence gene expression in male ( ZZ ) offspring . During male meiosis in mice , a general mechanism named meiotic silencing of unsynapsed chromatin ( MSUC ) silences all unsynapsed chromosomes [13] , [15] . This mechanism could be evolutionary related to meiotic silencing by unpaired DNA ( MSUD ) which operates in Neurospora crassa [57] . However , MSUD is a posttranscriptional silencing mechanism that acts at the single gene level . It is not clear whether components of MSUD are conserved and used in MSUC , which acts at a much larger scale and is far less efficient . Meiotic silencing of sex chromosomes ( MSCI ) in mammals is most likely a specialized form of MSUC . The driving force behind MSUD and MSUC may be that it is beneficial for the species to silence foreign DNA . Although sex chromosomes are no foreign DNA , recognition as such may also be beneficial , because it will help to suppress recombination between the heterologous regions of the sex chromosomes . This suppression of sex chromosome recombination could also be a strong driving force to silence single or heterologous sex chromosomes . Spreading of heterochromatin from W on Z in female chicken oocytes to achieve meiotic sex chromosome inactivation may be mechanism that evolved independent from MSCI in mammals . In XO male grasshoppers , the single X chromosome also enters spermatogenesis in an already inactive configuration [58] . In chicken , the heterologous synapsis between Z and W may be required to escape from a synapsis checkpoint , and not to avoid meiotic silencing . | Meiosis is a sequence of two specialized cell divisions during which haploid gametes are generated . During meiotic prophase , homologous chromosomes pair and recombine to allow proper separation of chromosomes during the first meiotic division . The pairing mechanism is challenged by the presence of the largely nonhomologous sex chromosomes in spermatocytes of male mammals , since X and Y pair only in the short regions of homology . The unpaired nonhomologous regions are recognized and transcriptionally silenced , which leads to the formation of the so-called XY body . In mammalian females , which carry two homologous X chromosomes , no such structure is formed and the sex chromosomes are both active in oocytes . We asked whether meiotic silencing of sex chromosomes also occurs during gametogenesis in chickens . In this species , males carry two Z chromosomes , and females are ZW . We show that Z and W fully pair in oocytes , despite the overall lack of sequence homology . Surprisingly , the ZW pair is transcriptionally silenced during meiotic prophase and remains inactive until the two chromosomes have largely separated . Reactivation of Z at this stage may be necessary to allow expression of genes that are required for further oocyte development . These data show that meiotic sex chromosome silencing occurs also in species with female heterogamety . | [
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] | 2009 | Female Meiotic Sex Chromosome Inactivation in Chicken |
Recent advances in structural bioinformatics have enabled the prediction of protein-drug off-targets based on their ligand binding sites . Concurrent developments in systems biology allow for prediction of the functional effects of system perturbations using large-scale network models . Integration of these two capabilities provides a framework for evaluating metabolic drug response phenotypes in silico . This combined approach was applied to investigate the hypertensive side effect of the cholesteryl ester transfer protein inhibitor torcetrapib in the context of human renal function . A metabolic kidney model was generated in which to simulate drug treatment . Causal drug off-targets were predicted that have previously been observed to impact renal function in gene-deficient patients and may play a role in the adverse side effects observed in clinical trials . Genetic risk factors for drug treatment were also predicted that correspond to both characterized and unknown renal metabolic disorders as well as cryptic genetic deficiencies that are not expected to exhibit a renal disorder phenotype except under drug treatment . This study represents a novel integration of structural and systems biology and a first step towards computational systems medicine . The methodology introduced herein has important implications for drug development and personalized medicine .
Despite the advantages gained from drug therapy in medicine , drug development has historically presented an expensive and frequently perplexing challenge for researchers . Identifying useful drug targets for treating disease and matching them to chemical compounds that can elicit the desired effect through drug-target interaction has been the paradigm for the drug development process in the era of molecular medicine . However , this approach has yielded many failed drug treatments and an incomplete understanding of the consequences of treatments for human health , even with drugs that have made it to market and been prescribed for decades . Two major contributing factors that confound individual molecular target-based drug discovery are drug off-target binding and the lack of systems-level understanding of drug response [1] . Adopting a new , systems-based approach to drug development is therefore a desirable goal in the era of systems medicine . The growing wealth of omics data offers a valuable opportunity for novel approaches in systems medicine but also presents significant challenges for data integration [2] . Increasingly sophisticated computational approaches are being developed to analyze and manipulate omics data in order to gain a greater understanding of complex biological systems . An algorithm for identifying and comparing ligand binding sites on protein structures [3] was recently employed to predict drug off-target binding sites across the proteome [4] . Such a tool offers unique capabilities for drug development by providing a comprehensive survey of uncharacterized drug targets that may participate directly in drug response , which is likely to be important as polypharmacology interactions suggest that drug promiscuity is a predominant property of existing drugs [5] . Biological systems exhibit redundant pathways and synergistic effects conferring a robustness of phenotype when confronted with external stimuli . As a result , multi-target drugs are generally more clinically efficacious than single-target drugs . These facts highlight the critical importance of studying polypharmacology in a systems level context [6] . The increasing use of genome-scale metabolic network models for a variety of applications [7] , [8] has established this research platform as a promising means for studying the emergent properties of complex systems . The published applications of metabolic models for drug development have thus far focused on identifying drug targets for antibacterial treatment in such pathogens as M . tuberculosis [9] , [10] , S . aureus [11] , [10] , H . pylori , and E . coli [10] . However , the human metabolic network reconstruction ( Recon 1 ) [12] and developed context-specific metabolic modeling algorithms [13] , [14] permit human-centered in silico drug studies . Integrating these structural bioinformatics and human system modeling techniques for application in drug development represents a first computational step into the era of systems medicine . As an example of this integrative approach , the results of protein off-target prediction for the drug torcetrapib [4] , a cholesteryl ester transfer protein ( CETP ) inhibitor , were evaluated in the context of a model of renal metabolism . CETP inhibitors are intended to treat patients at risk for atherosclerosis and other cardiovascular diseases by raising high-density lipoprotein cholesterol ( HDL-C ) and lowering low-density lipoprotein cholesterol ( LDL-C ) [15] . Torcetrapib was withdrawn from phase III clinical trials after a substantial investment of labor and capital due to its observed side effect of fatal hypertension in some patients [16] . It has since been of great interest to elucidate the cause of this side effect in order to avert such failures in the future and to better define the potential of CETP inhibitors for treatment [17] . Subsequent studies have provided evidence in favor of the hypothesis that the cause of this side effect was not due directly to the mechanism of HDL-C and LDL-C regulation via CETP inhibition [18] . Instead , it has been suggested that the hypertensive side effect may result from uncharacterized drug off-target effects [17] . Two other CETP inhibitors are now under clinical trial , anacetrapib [18] and JTT-705 [19] . Thus far , studies have not indicated the same risk of hypertension associated with the latter two drugs; however , these studies have been limited to relatively small patient groups lacking in diversity and over relatively short-term treatment . Even if these alternative CETP inhibitors do not carry the same adverse side effects , it is still of value to future drug development to determine the exact mechanism of torcetrapib's adverse action . It has been suggested that off-target effects of torcetrapib lead to increased activity of the renin-angiotensin-aldosterone-system ( RAAS ) and thereby hypertension [4] , [20] , but a recent review of the published CETP inhibitor clinical studies [21] concludes that the effect on blood pressure is most likely independent of the increase in aldosterone . Currently the exact cause of the hypertensive side effect of torcetrapib remains to be unambiguously identified . The predicted torcetrapib off-targets include many metabolic enzymes and metabolite transport proteins . Although there are several mechanisms involved in regulating blood pressure that may be responsible for the hypertensive side effect , one possible mode is the renal regulation of blood pressure via metabolite reabsorption and secretion . The kidneys are the primary organs that filter the blood and therefore are strong contributors to maintaining a normotensive state even independent of RAAS function . Thus a model of renal metabolism was developed as the system context in which to analyze torcetrapib off-targets and predict drug response phenotypes . The two best-supported causal off-targets predicted in this study are prostaglandin I2 synthase ( PTGIS ) , due to decreased capacity for renal prostaglandin I2 ( PGI2 ) secretion , and acyl-CoA oxidase 1 ( ACOX1 ) , due to decreased capacity for renal citrate and amino acid reabsorption . Four other predicted off-targets are also predicted to impact amino acid , glucose , citrate , or bicarbonate reabsorption . As well , the model predicts no effect on renal reabsorption or secretion for a number of other predicted off-target metabolic proteins . The goal of this study is not only to provide new insight into the torcetrapib problem but also to reveal the theoretical implications that this computational systems medicine platform has for drug development and personalized medicine . Characterizing the influence that genetic variation has in determining drug response phenotypes has been recognized as a crucial goal for the future of drug development [22] . To this end , the renal model was also used to analyze metabolic disorders resulting from genetic deficiencies and to identify those deficiencies that may pose additional risks for drug treatment in select individuals . Although many of the predictions generated by this approach are supported by clinical and other experimental evidence that describe the impact of loss of function for predicted causal off-targets and genetic deficiencies , the full set of exact metabolic mechanisms of drug action predicted by our model remain to be completely validated . While this is seen as a limitation of this study , it also offers a number of opportunities to experimentally evaluate promising hypotheses that , if validated , will lead to significant advancements in developing CETP inhibitors for treatment and novel insight into certain renal disorders .
The approach for context-specific organ modeling proposed in this study ( see Materials and Methods and Figure 1 ) yielded a renal metabolic model capturing functions of the kidney for reabsorption and secretion ( Table 1 ) . Many components of the renal objective function are factors known to be relevant determinants of blood pressure . However , there is currently incomplete knowledge about the exact role that some of these components play in blood pressure regulation . Calcium reabsorption , for example , leads to vasoconstriction in kidney glomeruli through the action of L-type and N-type calcium ion channels [23] suggesting a resulting increase in blood pressure if this mechanism applies across all vascular tissues . Calcium reabsorption also leads to an inhibition of renal sodium reabsorption in the proximal tubule [24] suggesting a blood pressure lowering effect consistent with the observation that increased dietary calcium also lowers blood pressure [25] . This highlights the complexity of the effect certain renal reasborptions have on blood pressure . Nevertheless , the many components accounted for in the renal objective function enabled explicit predictions about how system perturbations such as drug treatment and genetic deficiencies affect the kidney's ability to regulate the small molecule content of the blood . The kidney model included 336 explicitly predicted active metabolic genes ( Table S1 ) that met criteria for activity as summarized in Figure 2 . The majority , 243 genes , satisfied the gene expression significance threshold ( see Materials and Methods ) , although the activity of 58 genes was predicted despite expression values below the threshold . These genes were activated by the GIMME algorithm [13] to optimally achieve the renal objectives while remaining minimally inconsistent with gene expression data and may represent post-transcriptionally upregulated genes . The other 35 genes were predicted to be active without penalty since no corresponding probesets existed on the microarray upon which the transcriptomic data was obtained . Since many of these genes participated in optimal pathways for achieving renal objectives , it is projected that experimental measurement would confirm their expression if performed . The active reactions in the model reflect both the possible pathways by which the kidney can achieve the specified renal objectives as well as other functions supported by the gene expression data . The model included 1587 active reactions ( Table S2 ) , excluding model-based reactions such as objective functions , exchanges , and demands . Of these active reactions , 333 comprised a single connected sub-model accounting for all pathways which could possibly support the specified renal objectives . We refer to this sub-model as the reduced kidney model ( see Table S1 and Table S2 for the contents of the reduced model and Dataset S1 for the actual model in SBML format ) . It should be noted that because the reduced model included all reactions that can carry flux in support of the renal objectives , it had the exact same effective flux state solution space as the full renal model . The reduced kidney model reactions spanned a broad range of metabolic subsystems ( Figure 3 ) . The largest subsystem consisted of plasma membrane-spanning transport reactions , which is expected given that this model captured renal filtration and secretion functions . The second largest subsystem represented intracellular transport , signifying the importance of interaction among sub-cellular compartments in renal function including the cytosol , endoplasimic reticulum , Golgi apparatus , and mitochondria . A significant proportion of the other active subsystems in the reduced kidney model were involved directly in the metabolism of components of the renal objective function including carbohydrate , amino acid , vitamin , lipid , carboxylate , and glutathione metabolism as well as the urea cycle . These permitted the indirect reabsorption of metabolites as well as the required synthetic pathways for renal secretions . The integrative framework adopted for predicting causal drug targets associated with response phenotypes employed both structural bioinformatics tools as well as modeling techniques of systems biology ( see Materials and Methods and Figure 4 ) . The workflow begins with screening of the entire human structural proteome , with each subsequent step in the process narrowing the list of proteins ultimately into a set of targets for which a response phenotype was predicted upon functional inhibition . The first step of this process identified putative off-target drug binding sites using a ligand-binding site structural alignment algorithm ( see Materials and Methods ) . The 41 predicted metabolic protein off-targets were the focus of this study ( see Table S3 ) , 28 of which had predicted drug binding sites overlapping with their functional sites . Simulated inhibition of these targets in the reduced kidney model ( see Materials and Methods ) predicted response phenotypes for 6 of the off-target proteins with respect to renal function ( Figure 5 ) . The results of all analysis steps for these 6 off-targets are summarized in Table 2 . The expression of all of these targets was determined to be the most limiting for their associated metabolic reactions included in the reduced kidney model ( see Materials and Methods ) , providing additional evidence supporting that inhibition of these targets would be expected to have at least some deleterious impact on those reactions . The renal response phenotypes for inhibition of two of the predicted drug off-targets were supported by existing scientific literature . Simulated PTGIS inhibition completely precluded PGI2 secretion . Based on the relation of renal PGI2 secretion to blood pressure ( see Table 1 ) , this inhibition would be expected to have a hypertensive effect . Experimental studies confirmed that PTGIS is associated with essential hypertension in humans [26] and that transgenic rats highly expressing human PTGIS exhibited decreased mean pulmonary arterial pressure despite treatment with monocrotaline to induce hypertension [27] . Inhibition of hydroxyacid oxidase 2 ( HAO2 ) in the reduced kidney model led to reduced glutamate , glycine , and serine reabsorption suggesting a possible role for HAO2 in the hypertensive side effect following CETP inhibitor treatment based on the association of amino acid reabsorption with vasodilation and hypertension ( see Table 1 ) . HAO2 is highly expressed in human kidney [28] and was identified as a candidate quantitative trait locus for blood pressure in rat kidney in a study comparing normal to hypertensive rats [29] . Two predicted causal CETP inhibitor off-targets , PTGIS and ACOX1 , exhibited notable binding affinity differences when comparing docking results for their endogenous substrates to those for the three CETP inhibitors ( Figure 6 ) . The mean predicted binding affinity of PTGIS for its endogenous substrate prostaglandin H2 was weaker than for all three CETP inhibitors ( Figure 6A ) . Anacetrapib was predicted to have the strongest mean binding affinity of all four tested molecules for PTGIS and JTT-705 the weakest of the three drugs . The predicted mean binding affinity of ACOX1 for its endogenous substrate palmitoyl-CoA was weaker than for torcetrapib and anacetrapib but stronger than the affinity of the protein for JTT-705 ( Figure 6B ) . These results supported potential competitive inhibition of PTGIS and ACOX1 by torcetrapib and anacetrapib , but the predictions suggested a lesser effect of JTT-705 on ACOX1 . Similar to the use of the model to test inhibitory effects on drug targets , the model was also used to predict genetic deficiencies that lead to renal disorders and drug off-targets that act synergistically with genetic deficiencies . Simulated gene knockouts predicted to impact renal objective functions are displayed in Figure S1 , Figure S2 and Table S4 . The 118 deficient genes predicted to cause disorders impacted a variety of renal secretions and absorptions to varying degrees . Thirteen of these deficiencies predicted total loss of at least one renal function ( see Figure S2 ) . Some renal disorders were only predicted in the gene-deficient models in combination with drug treatment , not in the untreated gene-deficient models or in the normal drug-treated model , and are referred to in this study as cryptic genetic risk factors . Five such gene deficiencies were predicted ( see Table S4 ) . A deficiency in CYP27B1 , which impacted vitamin D secretion alone , also exhibited defects in proline reabsorption when combined with drug treatment in simulation . Defects in three amino acid transport proteins ( SLC7A10 , SLC3A1 , and SLC7A9 ) were predicted to decrease renal glycine reabsorption in combination with drug treatment along with the disorders predicted in the absence of drug treatment . The model deficient in the ATP-binding cassette sub-family C member 1 gene ( ABCC1 ) was predicted to exhibit a cryptic deficiency in renal phosphate reabsorption under drug treatment . These predictions are of special importance because they suggest that these renal phenotypes would only surface in gene-deficient individuals under certain conditions , such as when treated with CETP inhibitors . Multiple evaluations were performed to analyze and validate the content of the reduced kidney model . The reduced kidney model effectively predicted activity of significantly expressed metabolic genes . The ability of our modeling approach to correctly and robustly predict activity of highly expressing genes was evaluated by a five-fold cross validation ( see Materials and Methods ) . Our approach showed significant recall of the 20% most highly expressed metabolic genes , p-value = 4 . 57×10−22 . This observation is especially notable since the reduced kidney model was not a global model of kidney metabolism , and the result suggests the relative importance of the renal functions captured by our model within the context of total kidney gene activity . We compared the metabolic gene activity predictions from the reduced kidney model to the set of significantly expressed genes as well as to a proteomic dataset derived from normal , healthy human kidney glomerulus tissue [30] ( Figure 7A ) . A total of 164 genes active in the reduced kidney model , 72% of the predicted activities , were supported by either significantly expressed mRNA levels , high-confidence protein detection , or both ( see Table S1 for a detailed list ) . The remaining 64 gene activities accounted for in the model include 23 genes with no corresponding microarray probesets , and therefore not experimentally measured mRNA , and 41 genes that were determined to express more marginally below the established significance threshold . Despite a strong overlap between the transcriptomic and proteomic datasets , there were also large proportions of both which are unique . This disagreement may be due to tissue samples being taken from different kidney sub-tissues in each experiment , absent probesets on the microarray , or the propensity of mass spectrometry proteomic experiments to produce false negatives . All of the counted activities in Figure 7A were included in the full human metabolic network , signifying that the reduced kidney model was not a global kidney model and that there is potential for expansion to account for more metabolic functions than those of concern in this study . The literature-curated renal functions achievable by the kidney model were also compared to those achievable by a model derived from the predictions of Shlomi et al ( Figure 7B ) . While the kidney model developed in this study was compatible with all 41 curated renal functions , the predictions of Shlomi et al were only compatible with 25 functions . This difference in functionality was due to false negative inactivity predictions made by Shlomi et al such as inactive urea transport , prostaglandin synthesis , and ATP synthesis . These results underscore the need to manually curate automatically generated metabolic network reconstructions and the advantage of integrating objective functions with context-specific modeling . Next , the model was functionally validated by comparing the gene deficiencies predicted to cause renal disorder to disease phenotypes in the OMIM database collected from clinical studies . Twenty known gene deficiencies leading to specific disease phenotypes were accurately predicted using the model ( see Table S4 ) . Loss of function mutations in the gene encoding 25-hydroxyvitamin D3-1-alpha hydroxylase ( CYP27B1 ) have been linked to vitamin D-dependent rickets type I in both human patients [31] and pigs [32] consistent with the predicted inability of the gene-deficient model to secrete calcitriol . Hypouricosuria , low urinary excretion of urate , is a symptom of xanthinuria that is caused by xanthine dehydrogenase ( XDH ) deficiency [33] , which is consistent with the deficient model's inability to excrete urate . Similarly , hypouricemia , low blood serum urate , is a consequence of nucleoside phosphorylase ( NP ) deficiency [34] also predicted in the model . Deficiency of aromatic L-amino acid decarboxylase ( DDC ) leads to increased urinary excretion of 5-hydroxytryptophan [35] , which is consistent with the decreased ability to reabsorb tryptophan and secrete tryptamine predicted through simulation . Mutations in the mitochondrial cytochrome c oxidase gene ( COX6B1 ) lead to de Toni-Fanconi-Debre renal syndrome , whose symptoms include a deficiency in the renal reabsorption of glucose , amino acids , and bicarbonate [36] , [37] , all of which were predicted in the model . Deficiencies in seven NADH dehydrogenase genes all lead to hypoglycemia , confirmed in simulation , and a decreased ability to oxidize citrate and glutamate [38] , reactions important for indirect renal reabsorption of citrate and glutamate in the model . Proline dehydrogenase ( PRODH ) deficiency causes an inability to oxidize proline in kidney and other tissues leading to hyperprolinemia that includes increased urinary excretion of proline as a symptom [39]–[41] , which is also consistent with the predicted decrease in renal proline reabsorption . Deficiencies in two genes that take part in the ubiquinol-cytochrome c reductase complex III ( UQCRQ and UQCRB ) lead to proximal tubulopathy , including an inability to reabsorb amino acids [42]; the gene-deficient model exhibited reduced renal reabsorption of alanine , glutamate , and proline . Fumarate hydratase ( FH ) deficiency leads to defects in glutamate oxidation in kidney and other tissues [43] , [44] , which is also consistent with the decreased indirect renal reabsorption of glutamate predicted by the model . Renal glucosuria , recapitulated in the model , results from deficiency in a sodium-glucose transporter ( SLC5A2 ) [45] . Dicarboxylicamino aciduria [46] exhibits impaired renal glutamate and aspartate reabsorption and hypoglycemia resulting from a deficient glutamate transporter ( SLC1A1 ) , all symptoms predicted by the model . Severe dehydration is one symptom resulting from another deficient transporter ( SLC5A1 ) [47] , confirmed through decreased reabsorption of water in the model . These results qualitatively describe the ability of our modeling approach to predict perturbed phenotypic states . To more rigorously quantify the predictive ability of our model simulation approach , we performed area under receiver operating characteristic ( AROC ) analysis based on not only the abovementioned clinical validations of our gene-deficient phenotype predictions but based on the entire set of such known clinical phenotypes that could potentially have been investigated using our model ( see Figure S3 and Materials and Methods ) . The sharp declines in rates with increasingly stringent classifier ratio thresholds ( see Figure S3 ) reflect the likely low coverage of actual disorder phenotypes by existing clinical studies . Nevertheless , our approach performed very well based on this analysis , with an AROC of 0 . 7565 . Permutation trials resulted in a mean AROC of 0 . 5112 , in close agreement with the expected theoretical randomly achievable AROC of 0 . 5 . Our approach achieved a significantly greater AROC than could be expected by chance , p-value = 8 . 71×10−70 . Given the relatively low number of actual clinical negatives available ( see Table S5 ) , we also assessed the significance of our prediction results based purely on the true positive rates determined through the AROC analysis . The mean true positive rate of our results in this analysis was 0 . 2859 , significantly greater than the 0 . 0215 mean true positive rate obtained randomly , p-value = 3 . 29×10−127 . These analysis results illustrate that our approach for predicting perturbation phenotypes exhibits both favorable sensitivity and specificity based on actual clinical data and should hold not only for predicting genetic deficiency phenotypes but also enzyme inhibition by drugs , which exhibits a similarly deleterious phenotypic effect . In order to assess the effects of some of the critical assumptions made in the model development and simulation procedures , we performed sensitivity analysis with respect to the predicted renal disorder phenotypes . First , we compared the predictive capability of our reduced kidney model to that of the original , unconstrained human Recon1 metabolic network . The same approach to simulating renal disorder states was employed using both models ( see Materials and Methods ) . We simulated all single gene knock outs in both models and assessed the renal disorder phenotypes with respect to each individual component of the renal objective function based on the ratio of maximum objective flux in the perturbed state to maximum objective flux in the unperturbed state . Comparing the results achieved by each model ( Figure 8 ) , it is apparent that although there are a few cases where both models predict an equal degree of renal disorder given the same genetic perturbation , the vast majority of disorder phenotypes are more apparent in the reduced kidney model than in Recon1 alone . In fact , 427 out of the 608 ( 71% ) disorder phenotypes predicted by the reduced kidney model showed no degree of disorder relative to the unperturbed state in Recon1 , including 36 of the most severe phenotypes for which a total loss of renal function was predicted by the reduced kidney model . These observations display the predictive ability gained through integration of the gene expression data via the GIMME algorithm , incorporating metabolomics data to set exchange constraints , and the addition of six key membrane transport reactions during the limited function-enabling manual curation of the model . These reactions involve the transport of prostaglandins I2 and H2 , calcitriol , and carnosine . It should be noted that the 7 disorders for which Recon1 predicted a more severe phenotype than the kidney model result directly from the addition of these transporters in that these transporters have enabled additional pathways in the kidney model that are absent in Recon1 . All but one of the predictions concerning CETP inhibitors showed a clearer phenotype in the kidney model as well; this off-target is PTGIS for which both models predict a complete loss of function when fully inhibited . Finally , 28 out of the 33 clinically validated phenotypes are predicted more noticeably by the kidney model , 17 of these showing no disorder phenotype in Recon1 . Overall , this comparison establishes the relative contribution of context-specific modeling in studying disorder and drug response phenotypes . Second , we investigated the sensitivity of our drug off-target response phenotype predictions to the variability of two important parameters used in our simulations , the system boundary flux constraint , set as equal fractions of the upper bound on renal objective fluxes ( see Materials and Methods ) , and the degree of enzymatic activity inhibition assumed to result from drug treatment . The system boundary flux constraint was imposed upon demand and exchange reactions other than those optimized during a given simulation . By default we set this constraint assuming that all allowed boundary fluxes can carry an equal fraction of the potential maximum renal objective flux . This assumption was made to allow all pathways that could possibly contribute to the objective to be used simultaneously in the optimal flux state , providing the most flexible state while maintaining maximum sensitivity of our model to additional system perturbations such as gene deficiencies or drug effects . This approach was unbiased in that it did not favor any possible pathway over another in achieving a set objective without imposing additional constraints , which may not always reflect biological reality but was the most conservative assumption in the absence of additional experimental data required to more precisely set these flux constraints . In our sensitivity analysis , we varied this parameter between 0 and 1000 flux units , the absolute lower and upper magnitudes possible in our model , and repeated the simulations of drug off-target effects . The result of this analysis ( Figure S4 ) was captured in the normalized sensitivity coefficient computed for each simulation ( see Materials and Methods ) . The coefficient can vary between negative and positive unity and displays the deviation from a base result , the primary predictions we have presented in this study . The base result is indicated by a black star in Figure S4 , and the parameter value in this case equals 13 . 5 flux units . It is clear from Figure S4 that PTGIS inhibition resulted in the same renal disorder phenotype regardless of the value of the system boundary flux constraint parameter . This was because there was only one pathway in the model by which prostaglandin I2 could be secreted . Most other disorder phenotype predictions begin to diverge from the base result around a parameter value of 200 flux units , a fairly permissive value , which shows that the predictions were fairly robust to variability of this parameter . The closer to 1000 flux units this parameter was set , the more completely alternative pathways could compensate for a loss of function in the simulations . If alternative pathways existed to achieve a renal function , it was guaranteed that the ability to predict a disorder phenotype with respect to that function would be completely lost at the maximum possible parameter value of 1000 . We similarly analyzed the sensitivity of our predictions to changes in the degree of enzyme inhibition assumed to follow from drug treatment ( Figure S5 ) . For the primary results presented in this study , we assumed complete inhibition of activity by the drug , corresponding to a fraction of maximum enzymatic reaction flux equal to 0 in Figure S5 . Similar to the default setting of our system boundary flux constraint , this default of complete inhibition was chosen in order to maximize the sensitivity of our model in detecting disorder phenotypes . Most of the phenotypes were still detectable to varying degrees with as much as 25% of the maximum activity of drug targets . The predicted phenotypes associated with PTGIS , ACOX1 , and AK3L1 were especially robust to variation in degree of inhibition , still exhibiting a phenotype near 50% of maximum activity . Decreased glucose and bicarbonate reabsorption under drug-induced MT-COI and UQCRC1 inhibition exhibited the most sensitivity to variability in this parameter , although none of the predicted phenotypes required complete inhibition of the drug target in order to be detected .
A novel approach for making functional predictions of drug response phenotypes has been introduced that integrates techniques of both structural bioinformatics and systems biology . Although the current study focused on a specific metabolic system , the general methodology excluding techniques particular to metabolic modeling are extensible to other systems such as signaling or transcriptional regulation . Non-metabolic protein drug off-targets are predictable using the same structural analysis tools , and many such off-targets have indeed been predicted as well for CETP inhibitors [4] . The context-specific organ metabolic modeling strategy employed in this study represents an improvement upon previous efforts in this realm . Model development algorithms such as GIMME [13] or that developed by Shlomi et al , when integrated with multiple omics datasets , can lead to more biologically realistic models . It is also of critical importance to include context-specific metabolic objective functions in the model development process in order to yield a fully functional and predictive model , as is evident from the functional comparisons of models performed in this study . As an early effort at modeling such a context-specific metabolic system it is important to discuss the limitations of our model . Although the functional validations presented here are compelling , currently available clinical data only permits the assessment of a subset of the predictions possible in the model . Also , the functional portion of the model , the reduced kidney model , does not and is not intended to represent a global model of kidney metabolism but only the specific renal functions studied in this work . As such , our model does not fully resolve of complexity of the human kidney . The human kidney fulfills a number of functions not studied here and is a spatially distributed system across multiple distinct tissue types . Here we have summarily replaced the various kidney sub-tissues with a single , net system model . Because we integrated expression data with curated renal functions that operate across multiple kidney tissues , it is likely that our model approximates a superset of the metabolic pathways supporting these functions . Although we have made several simplifying assumptions in the model development process , even the current level of model validation suggests that the gene and reaction content of the model is fairly accurate and that simulations in this model indeed hold predictive capability . The simulation approach taken , optimization of a linear objective function , does not fully capture the full physiological role of the kidney . The goal of these simulations was to determine drug-target effects that may limit the capacity of the kidney to move towards a homeostatic nominal state from a state of high blood pressure , thereby decreasing the capacity of the kidney to lower blood pressure . This strategy is appropriate for the goals of the current study but would not be appropriate to simulate all physiological states of interest in the kidney . On a related note , the choice to define a disorder state based on the ratio of perturbed to unperturbed maximum achievable renal objective flux demonstrates a difference in the capacity of the renal function and not necessarily a precise flux state . Therefore this strategy too is not appropriate for modeling all physiological states . The predictions made for CETP inhibitors in this study serve as illustrative examples of many important implications that this approach has for drug development and personalized medicine . Predicted causal off-targets for renal metabolic disorders related to blood pressure may be responsible in part or full for the clinically observed hypertensive side effect of torcetrapib . The evidence resulting from this study suggests that PTGIS and ACOX1 are both potential causal torcetrapib off-targets , the inhibition of which may explain the side effect of hypertension . In addition , AK3L1 , HAO2 , MT-COI , and UQCRC1 may also play a role in this side effect as we have predicted , although our docking trials did not suggest that they are bound as strongly by torcetrapib . The specific predicted deficiencies in renal function associated with the drug off-targets can serve as biomarkers to be measured in patients participating in clinical trials . A positive correlation of these biomarkers with side effects would lend support to the predictions of this study and confirm these biomarkers as risk indicators in future patient treatment . It is important to note that although these predictions comprise the basis for a renal filtration and secretion-based hypothesis explaining the hypertensive side effect of torcetrapib , these results do not refute the hypothesis based on a RAAS-mediated mechanism . These two hypotheses are not mutually exclusive and could potentially contribute alternatively or synergistically to the clinically observed side effects . This possibility illustrates the major tenet for systems biology: studying a single protein or even a single pathway is not necessarily sufficient to explain complex biological phenomena . Aside from the confirmation that some of our predicted off-targets are known to be involved in renal disorders , we do not currently present direct experimental verification that torcetrapib binds and inhibits the predicted targets and that this inhibition leads to the predicted response phenotypes . Although this would be the obvious next step , a retrospective validation is currently hampered by the availability of the drug and the nature of the phenotypes both predicted and known . Ideally , relevant physiological studies would be carried out during actual clinical trials , when a method such as ours would be most useful , in preclinical and clinical phases of drug development . The extended structural analysis of causal drug off-targets to identify differential binding affinities for endogenous substrates and drug molecules suggests possible differences in drug response phenotypes across the CETP inhibitors tested . The results suggest that anacetrapib may potentially lead to a similar response phenotype to that of torcetrapib , while JTT-705 may not carry the same adverse effect , at least with respect to the off-targets detailed in this study . This particular type of analysis may aid in differentiating between likely response phenotypes expected for chemically and functionally similar drugs . Results of the computational pipeline for interaction prediction between proteins and CETP inhibitors employed in this study , SMAP and docking , have yet to be confirmed experimentally . Although we are currently unable to provide direct experimental evidence for the off-target interaction predictions for this class of drugs , multiple recent studies have shown experimental support for the general efficacy of this approach for interaction prediction [48] , [49] . The predicted renal metabolic disorders with a genetic basis suggest classes of individuals in which treatment with CETP inhibitors may pose a higher risk for adverse side effects . These predictions suggest a likely relationship between participants in torcetrapib clinical trials exhibiting symptoms of these disorders and the observed adverse side effects . The concept of cryptic genetic risk factors for drug treatment introduced in this study suggests a novel approach to personalized medicine . Should polymorphisms within these genes be clinically linked to side effects of drug treatment , the result would comprise a basis for genetic screening to assess the risk of drug treatment for future patients . Given that these cryptic risk factors are not expected to elicit the predicted abnormal phenotypes in the absence of drug treatment , identification of causal polymorphisms through association studies could only occur during clinical phase when a sufficient number of patients could be observed to gain the statistical power needed to draw significant correlations . As illustrated above , this approach for in silico drug testing could become an indispensible tool during the pre-clinical and clinical phases of new drug development for studying the nature of adverse side effects . In addition , this platform holds obvious potential for analyzing drug efficacy in general and identification of potential beneficent drug side effects that may be useful for drug repositioning and could also be easily adapted for studying combinatorial drug treatment . For a failed drug like torcetrapib , results from this approach could reinitiate the drug development process , providing new insight to help target patients who could benefit from the treatment without the risk of serious adverse side effects .
The binding site for CETP inhibitors on the CETP structure and the predicted off-target binding sites for this class of drug across the proteome were assumed to be as previously predicted using the SMAP program [4] , which implements the Sequence Order Independent Profile-Profile Alignment ( SOIPPA ) algorithm to identify significant structural similarity to a given ligand-binding site [3] . The results contained proteins from all organisms represented in the PDB , not just human structures . In order to integrate the result of drug off-target predictions with the metabolic network , it was necessary to first map all PDB structures ( http://www . pdb . org ) corresponding to human metabolic proteins included in Recon1 , downloaded from the BiGG database , to their respective gene identifiers as represented in Recon1 . The BiGG database requires registration and a password , which can be requested by visiting ( http://bigg . ucsd . edu/bigg/home . pl ) . The UniProt ID mapping tool ( http://www . uniprot . org/ ) was used to map PDB structures corresponding to human proteins to gene identifiers linked to metabolic reactions in Recon1 accounting for all predicted human metabolic protein drug off-targets . All non-human predicted metabolic protein drug off-targets were mapped to their human orthologs using the Basic Local Alignment Search Tool ( BLAST ) [50] to perform a bi-directional BLAST with a mutual best hit criterion . BLAST was also used to resolve inconsistencies in functional annotation between Recon1 gene-protein-reaction associations ( GPRs ) and gene annotations from the Entrez Gene database ( http://www . ncbi . nlm . nih . gov/sites/entrez ? db=gene ) with respect to predicted drug targets , leading to the reannotation of three Recon 1 GPRs . The overall result of this mapping was that 97 metabolic reactions in Recon1 were linked to 41 predicted CETP inhibitor off-targets . The metabolic enzymes predicted as CETP inhibitor off-targets using SMAP were evaluated to determine potential enzymatic inhibition by the drug . The predicted drug-binding sites of the putative off-targets were compared to endogenous ligand-binding sites from existing PDB protein-ligand complex structures ( http://www . pdb . org ) and catalytic sites from the Catalytic Site Atlas ( http://www . ebi . ac . uk/thornton-srv/databases/CSA/ ) . Ligand-binding sites were defined as amino acid residues lying within 4 . 5 Å from atoms of the ligand . Drug-binding sites were defined as residues aligned with the cholesteryl ester binding sites on the CETP structure using SMAP . Overlap between endogenous ligand-binding sites and drug-binding sites was defined by a sharing of any amino acid residues between the sites . The function of predicted drug targets present in Recon1 with at least a partial such overlap was considered to be competitively inhibitable by the drug . Enzyme substrates were identified from Recon1 reaction formulas . Certain molecules ( H+ , H2O , O2 , phosphate , ferricytochrome C , and ferrocytochrome C ) were excluded from docking trials due to size or structural challenges prohibiting a useful docking result for the purposes of binding affinity predictions . All protein structures used in this study were downloaded from the PDB ( http://www . pdb . org ) . Three-dimensional structures for endogenous enzyme substrates were downloaded directly from the PDB if available . If the PDB ligand structure did not exist or was non-functional for docking , the structure was searched for in PubChem ( http://pubchem . ncbi . nlm . nih . gov/ ) . The subsequently downloaded SDF file was converted to PDB format using the ChemAxon web applet available at the PDB website ( http://www . rcsb . org/pdb/ligand/chemAdvSearch . do ) . If the three-dimensional ligand structure could not be found in PubChem , the two-dimensional structure was derived from the canonical SMILES [51] representation of the compound available in PubChem and then converted to a three-dimensional structure in PDB format using the Clean3D Fine Build tool available through the Marvin web applet ( http://www . chemaxon . com/marvin/sketch/index . jsp ) . The three-dimensional structures for glycolipids were derived from their KEGG glycan structures ( http://www . genome . jp/kegg/glycan/ ) using SWEET-II ( http://www . glycosciences . de/spec/sweet2/doc/index . php ) . Protein structures were pre-processed for docking using AutoDockTools ( ADT ) version 1 . 5 . 2 [52] by adding polar hydrogen atoms , removing all non-protein molecules from the PDB structure including water , detergents , and ligands , adding Kollman charges to the protein and converting it to PDBQT format . Ligand structures were also prepared using ADT , using the default method for preparing ligands for docking that adds hydrogens and charges . The default rotatable bonds were accepted as well , and the structure was converted to PDBQT format . The search space for docking was determined visually by centering the Grid Box in ADT central to the experimentally determined binding site of the ligand and expanding the dimensions of the cubic search space to just completely encompass the site . Docking was performed using AutoDock Vina [53] with default parameter settings other than the search space specification described above , and the mean predicted binding affinity from the set of predicted binding poses was accepted as the true binding affinity for each docking run . The predicted binding affinities for endogenous substrates were compared to the affinity of the same site for the CETP inhibitor drugs in order to make predictions about differential responses with respect to each of the drugs . As the preliminary step in modeling human renal function , the scientific literature was reviewed to compile a list of specific metabolic functions of the kidney , with a focus on functions implicated as determinants of blood pressure . This list includes a number of renal reabsorptions and secretions . Each function in this list was tested for compatibility with Recon1 , downloaded from the BiGG database ( http://bigg . ucsd . edu/bigg/home . pl ) , by performing flux balance analysis ( FBA ) on the fully unconstrained network optimizing for the given function . Those functions compatible with Recon1 were those that could achieve a positive flux and are summarized in Table 1 . These metabolic functions were combined with a basic ATP maintenance function to form a single model reaction that represents the kidney's ability to filter the metabolic content of blood with preference for lowering blood pressure . This model reaction was used as the objective function in developing the metabolic kidney model and is referred to as the renal objective function in this study . All stoichiometric coefficients in this reaction were set equal to one , which is a safe assumption for the model development step as this only significantly impacts the magnitude of fluxes through pathways that support each individual renal objective and not generally whether or not certain fluxes will be active in the resulting model . For the full renal objective function reaction to be seen as useful in performing simulations , more careful balancing of these coefficients based on experimental evidence would be required . As such , the full renal objective function was not used in any subsequent simulations with the model , instead being substituted as an objective by the reactions representing individual reabsorptions or secretions . Metabolite exchange and transport reactions needed to achieve some of the renal functions were also added to the network . It was observed that Recon1 as a base model could not achieve flux through certain key renal metabolite reabsorptions: sodium , calcium , chloride , potassium , and oxalate . These deficiencies were corrected for by simply adding demand fluxes for these metabolites in the cytosol model compartment . Demand fluxes were also added for the remaining kidney reabsorptions and secretions as well to enable an array of simulations involving individual components of the renal objective function to be tested . In the case of reabsorption , this allows for direct reabsorption of metabolites in addition to indirect reabsorption in which the absorbed metabolite is first metabolized into other compounds and then reabsorbed into the blood , as is the primary mechanism of reabsorption for some metabolites , such as reduced glutathione ( GSH ) [54] . A preliminary model was created by imposing kidney-specific exchange flux constraints representing the metabolic exchanges the kidney carries out with the blood and urine . The preliminary model was initialized by loading Recon1 into the COBRA Toolbox [55] and , by default , unbounding all reaction fluxes by setting them to the default maximum magnitude of 1000 flux units . Next , the renal objective function was added to the network as a single reaction . Exchange fluxes for kidney secretion objectives were constrained to preclude uptake of those metabolites to achieve the renal objective , forcing the model to synthesize those metabolites in order to secrete them . The resulting preliminary model included 407 exchange fluxes , only 49 of which were explicitly unconstrained based on literature-curated kidney functions and the most basic of metabolic precursor requirements . The basic metabolic exchanges assumed to take place include ions and other inorganic compounds . The Human Metabolomics Database ( HMDB ) ( http://www . hmdb . ca/ ) was queried to derive further evidence in support of allowable exchange fluxes for the kidney . All 407 exchange metabolites in the preliminary model were searched in HMDB for experimental detection in specific biofluids and tissues . Those metabolites detected both in the blood and kidney tissue were assumed to be freely exchangeable in the kidney model , leading to 78 more explicitly unconstrained exchanges beyond what was derived from basic and curated kidney-specific metabolic functions . This assumption is based on the kidney's physiological role of filtering the blood and the observation that if both the blood and kidney contain a metabolite , it must either be exchanged between the two or synthesized separately in both . In the former case , this data provides evidence of that exchange . In the later case , although the model might allow a biologically unrealistic exchange , because the metabolite exists in both blood and kidney , the impact on simulations using the resulting model should be merely quantitative in terms of the maximum renal objective fluxes achievable by the unperturbed model . The integration of gene expression data in the model development process described below should reduce the propensity for biologically unsound metabolic pathway activation that could follow from precursors introduced by any biologically unsound exchanges . Those metabolites detected both in the urine and kidney were assumed to be possible excretions , and exchange constraints were set accordingly . Excretions determined utilizing the urine metabolomics data mostly showed redundancy in determining exchange constraints with exchanges determined using blood data or literature curation with the exception of 4 additional metabolites . The remaining 276 exchange fluxes for which no evidence was found to support were tentatively constrained to 0 flux units . The resulting preliminary model was again tested for the ability to achieve all kidney-specific metabolic functions . It was found that this model could not absorb and metabolize GSH , without also absorbing oxidized glutathione , the exchange of which was subsequently unconstrained . Also , L-threonine and L-methionine could not be absorbed and metabolized in this model without exchange of 2-hydroxybutyrate and 2-methylcitrate , the exchanges of which were similarly unconstrained as a corrective measure . The resulting preliminary model could still achieve all the same renal objectives as the fully unconstrained model . As a final preliminary constraining measure , all system effluxes were bound to equal fractions of the default upper bound on influxes of 1000 flux units; we term this parameter the system boundary flux constraint . This was done so that any available direct or indirect reabsorption pathways could possibly be used to achieve metabolite reabsorption without biasing the model towards use of any particular pathways without further evidence . This represents the state of the model just prior to final processing using the GIMME algorithm . The fitting of the allowable fluxes to the gene expression data by GIMME ultimately determined the usable reabsorption and secretion pathways in accordance with gene expression . Two gene expression microarray dataset for normal , healthy kidney tissue [56] were obtained from the GEO database ( http://www . ncbi . nlm . nih . gov/geo/ ) , accession GSE803 . The two background-subtracted datasets were first normalized using a global normalization factor equal to the sum of probe intensities from the first dataset divided by the sum of probe intensities from the second dataset to account for any systematic differences in procedure between the two experiments . The resulting data were then normalized using the Lowess method [57] to reduce random noise . The resulting normalized datasets were then weighted equally as replicates in determining the final data for integration with the human metabolic network by taking the mean of the two normalized datasets . The gene-protein-reaction associations ( GPRs ) in Recon1 use Entrez Gene IDs to annotate reactions in the network . To map the data from the AffyHG-U95 chips to Recon1 , all genes included in Recon1 were mapped to corresponding AffyHG-U95 probesets using Bioconductor [58] and the most recent chip annotations [59] . A single expression value was then assigned to each gene in Recon1 based on the maximum normalized data value associated with any of the probesets mapped to a given gene . Next , a single expression value was assigned to each reaction in Recon1 by evaluating the Boolean rules in the GPRs with respect to the normalized expression data . The minimum data point was chosen for genes linked by an AND operator in a GPR , and the maximum data point was chosen for genes linked by an OR operator in a GPR . Finally , a significant expression threshold was established for subsequent use in the GIMME algorithm . This was done by fitting the normalized gene expression data to a Gaussian distribution , estimating the mean and standard deviation of this distribution , and calculating p-values associated with each data point by subtracting the cumulative distribution function from one . The normalized data value corresponding to the p-value closest to but not exceeding 0 . 05 was chosen as the significance threshold; this resulted in a threshold of 991 . 3698 for the normalized expression data . To integrate the renal objective function and kidney gene expression data with the preliminary model to derive a functional kidney model , the GIMME algorithm [13] was implemented . The GIMME algorithm takes a metabolic network model , a gene expression dataset , and specified required metabolic functions as input and solves a linear programming optimization to yield the network flux activity state that maximizes the specified functions while remaining as consistent as possible with the gene expression data . The complete renal objective function , the combination of all functions presented in Table 1 , was set as the metabolic objective with a minimum requirement of 90% of the maximum possible flux set as a parameter for GIMME in determining the final kidney model . The reaction expression threshold parameter was set as described above . GIMME was run with these parameters and the normalized expression data and preliminary model as inputs . The resulting reaction activity predictions were used to constrain metabolic reactions yielding the full kidney model . Subsequently , the connected sub-graph of this full kidney model , which includes all functioning reactions possible for achieving the renal objectives , was isolated and is this portion of the model we focused on for validation and simulation . We refer to this sub-model as the reduced kidney model ( available in SBML format as Dataset S1 ) . Gene activity predictions made when deriving the metabolic kidney model were compared to the set of expressed genes with normalized expression values above the significance threshold described above . Activity predictions were also validated against a comprehensive proteomics dataset from normal human kidney glomerulus tissue [30] for overlap with network-associated proteins detected with high confidence , that is , identified through detection of two or more peptides . To evaluate the modeling approach used in this study , a five-fold cross validation was performed in which the data corresponding to the most highly expressed 20% of network-associated genes were excluded before deriving the kidney model . The ability of each approach to correctly predict the activity of these most highly expressed 20% of genes was measured from the overlap of predictions with the highly expressed gene set assuming a hypergeometric distribution , and the resulting probability was Bonferroni-adjusted . All predicted metabolic protein drug off-targets were tested in the kidney model to assess the drug response phenotype caused by inhibitory effects in this system . Inhibition of metabolic proteins by the drug was modeled by constraining corresponding reactions catalyzed by drug targets to 0 flux units . Simulations of the consequences of these drug effects were performed using FBA as implemented in the COBRA Toolbox [55] in the MATLAB programming environment . Each drug target was evaluated with respect to its impact on each individual renal function to determine if target inhibition by the drug leads to a renal deficiency relative to the untreated normal kidney model . This was done by optimizing single exchange or demand fluxes at a time , representing reabsorptions and secretions respectively , out of the full set listed in Table 1 . The cumulative effect of all predicted drug targets being simultaneously inhibited was also tested against each individual renal function . Renal secretion fluxes were maximized in simulation . Renal reabsorption fluxes were set as unbounded and then maximized while the remainder of allowable uptakes were constrained to equal fractions of the default maximum magnitude of 1000 flux units . The additional constraints were imposed for reabsorption simulations in order to allow the resulting network flux state to include concurrently active alternative optimal direct and indirect reabsorption pathways rather than having to identify alternative optimal pathways by performing multiple simulations . Single gene deficiencies were also simulated in the kidney model to assess their effects on renal function and their potential as risk factors for treatment with CETP inhibitors . Each of the genes annotated to reactions in Recon1 was knocked-out of the kidney model and simulations were run using the gene-deficient kidney model both with and without drug treatment to assess effects on each individual renal reabsorption and secretion . Drug response and metabolic disorder phenotypes were assessed by taking the ratio of maximum gene-deficient , untreated renal function flux to maximum normal , untreated renal function flux . A ratio of less than unity indicates a deleterious phenotype . Predicted metabolic disorder phenotypes were validated against previous clinical studies as represented in the Online Mendelian Inheritance in Man ( OMIM ) database ( http://www . ncbi . nlm . nih . gov/omim/ ) . Cryptic genetic risk factors for drug treatment were also predicted for which the maximum gene-deficient , untreated renal objective flux equals the maximum normal , untreated renal objective flux but the ratio of maximum gene-deficient , drug-treated renal objective flux to maximum normal , drug-treated renal objective flux is less than unity . Sensitivity of our prediction approach to variability in parameters was performed through repeated simulation in which we varied the parameter value across the full range of possible values . We investigated sensitivity with respect to each parameter independently . A normalized sensitivity coefficient was calculated as the result of each of these simulations . This coefficient was calculated by first taking the percent difference in the predicted outcome relative to a base case , our primary results , and then dividing it by the maximum possible percent difference . Benchmark data was collected from the OMIM database ( http://www . ncbi . nlm . nih . gov/omim/ ) by searching for all metabolic disorders related to renal reabsorptions or secretions that are associated with deficiencies in genes included in the reduced kidney model . The resulting list of disorders was manually curated using literature references to identify precisely which metabolic renal reabsorptions and secretions were impacted . These included not only those renal functions captured in Table 1 , but also other renal exchanges . All resulting reabsorptions and secretions that can have corresponding non-zero fluxes under unperturbed conditions in the reduced kidney model were included in our benchmark data set ( see Table S5 ) . Every phenotype in the benchmark data was investigated through our model as described for simulating drug target effects and renal metabolic disorders , taking the ratio of perturbed to unperturbed flux capacities as a measure of phenotype , where a ratio of one signifies no disorder phenotype and a ratio of less than one signifies some degree of disorder . Next , the ratio threshold for classifying normal versus disorder phenotype was iteratively set to assess the sensitivity and specificity of our approach for predicting true and false positives across the full range from zero to one . Note that a threshold of one was used by default for the main results presented in this study . The true positive rate was plotted against the false positive rate ( see Figure S3 ) , the ROC curve , and the AROC was computed using the trapezoidal rule for approximating definite integrals . The statistical significance of our result was determined by comparison to 100 permutation trials in which all reaction flux ratios , perturbed to unperturbed , were randomly shuffled for each simulated gene deficiency and AROC-analyzed . The permutation trials exhibited true positive and false negative rates expected for random disorder phenotype classification ( see Figure S3 ) , and thus comprised an appropriate assessment of the predictive ability of our model simulation approach relative to chance . One-sample left-tailed student t-tests were performed using an alpha value of 0 . 05 to assess the statistical significance of the AROC and mean true positive rate achieved by our model simulation approach relative to the permutation results . | Pharmaceutical science is only beginning to scratch the surface on the exact mechanisms of drug action that lead to a drug's breadth of patient responses , both intended and side effects . Decades of clinical trials , molecular studies , and more recent computational analysis have sought to characterize the interactions between a drug and the cell's molecular machinery . We have devised an integrated computational approach to assess how a drug may affect a particular system , in our study the metabolism of the human kidney , and its capacity for filtration of the contents of the blood . We applied this approach to retrospectively investigate potential causal drug targets leading to increased blood pressure in participants of clinical trials for the drug torcetrapib in an effort to display how our approach could be directly useful in the drug development process . Our results suggest specific metabolic enzymes that may be directly responsible for the side effect . The drug screening framework we have developed could be used to link adverse side effects to particular drug targets , discover new uses for old drugs , identify biomarkers for metabolic disease and drug response , and suggest genetic or dietary risk factors to help guide personalized patient care . | [
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] | 2010 | Drug Off-Target Effects Predicted Using Structural Analysis in the Context of a Metabolic Network Model |
An important goal in molecular biology is to understand functional changes upon single-point mutations in proteins . Doing so through a detailed characterization of structure spaces and underlying energy landscapes is desirable but continues to challenge methods based on Molecular Dynamics . In this paper we propose a novel algorithm , SIfTER , which is based instead on stochastic optimization to circumvent the computational challenge of exploring the breadth of a protein’s structure space . SIfTER is a data-driven evolutionary algorithm , leveraging experimentally-available structures of wildtype and variant sequences of a protein to define a reduced search space from where to efficiently draw samples corresponding to novel structures not directly observed in the wet laboratory . The main advantage of SIfTER is its ability to rapidly generate conformational ensembles , thus allowing mapping and juxtaposing landscapes of variant sequences and relating observed differences to functional changes . We apply SIfTER to variant sequences of the H-Ras catalytic domain , due to the prominent role of the Ras protein in signaling pathways that control cell proliferation , its well-studied conformational switching , and abundance of documented mutations in several human tumors . Many Ras mutations are oncogenic , but detailed energy landscapes have not been reported until now . Analysis of SIfTER-computed energy landscapes for the wildtype and two oncogenic variants , G12V and Q61L , suggests that these mutations cause constitutive activation through two different mechanisms . G12V directly affects binding specificity while leaving the energy landscape largely unchanged , whereas Q61L has pronounced , starker effects on the landscape . An implementation of SIfTER is made available at http://www . cs . gmu . edu/~ashehu/ ? q=OurTools . We believe SIfTER is useful to the community to answer the question of how sequence mutations affect the function of a protein , when there is an abundance of experimental structures that can be exploited to reconstruct an energy landscape that would be computationally impractical to do via Molecular Dynamics .
Mutations in protein sequences that lead to altered functions have been found to drive or participate in many human diseases [1 , 2] . An important goal of molecular biology is to understand functional changes upon single-point mutations in proteins . This is a challenging task for both wet and dry laboratories . Investigations in the dry laboratory promise in principle to unravel the sequence-function relationship in proteins through a holistic , detailed characterization of a protein’s structure space and underlying energy landscape [3] . However , exploring the breadth of a protein’s structure space via MD-based conformational search algorithms remains computationally challenging [4] . In this paper we propose a novel conformational search algorithm , which is based on stochastic optimization rather than MD to circumvent the computational challenge of exploring the breadth of a protein’s structure space . We refer to this algorithm as SIfTER for Structure Initiated Search for Transient Energy Regions . SIfTER exploits structural characterizations of a protein in the wet-laboratory to rapidly map the structure space and underlying energy landscape of a given protein sequence . By doing so , the algorithm allows mapping and juxtaposing landscapes of variant sequences of a protein and then relating observed differences to functional changes . Before relating further details on the novel algorithmic components that make this possible , we justify SIfTER in a gradual and systematic way on a hallmark case study in molecular biology , the family of Ras proteins . Ras proteins mediate signaling pathways that control cell proliferation , growth , and development via guanine nucleotide-dependent conformational switching between an active and inactive structural state [5] . Ras is in its active ( on ) state when bound to GTP , and in the inactive ( off ) state when bound to GDP [5] . The rate of exchange between the GTP- and GDP-bound states is enhanced by two types of regulatory proteins , GTPase activating proteins ( GAPs ) , which promote GTP hydrolysis , and guanine nucleotide exchange factors ( GEFs ) , which promote GDP release , allowing for GTP to bind . Ras isoforms ( H- , N- , and K-Ras are the most prevalent ) exist , and they have unique physiological functions and roles in different human cancers and developmental diseases . Many structures have been reported and can be found in the Protein Data Bank ( PDB ) [6] for the wildtype ( WT ) ordered catalytic ( G ) -domain of H-Ras and several of its oncogenic variants . The active ( GTP-bound ) and inactive ( GDP-bound ) states of the Ras catalytic domain differ structurally by 1 . 5Å . This change is concentrated near the nucleotide-binding site , which includes the switch regions SI ( residues 25–40 ) and SII ( residues 57–75 ) [7–15] . The structural change is driven by the formation of hydrogen bonds from the conserved residues T35 and G60 to the gamma-phosphate of GTP , which effectively closes the binding pocket [7] . When bound to GDP , and the gamma-phosphate is missing , the switch regions have fewer structural contacts to the ligand , and this allows the Ras catalytic domain to populate a more open structure [7 , 9] . Mutations that deregulate Ras activity are found in over 25% of all human tumors [16] . In particular , two such mutations , G12V and Q61L , are shown to be oncogenic . The G12V mutation in H-Ras is implicated in bladder carcinoma [17 , 18] . The Q61L mutation is implicated in melanoma due to its strongly reduced GTP hydrolysis in the presence of RAF-1 [19 , 20] . NMR studies point to correlated conformational dynamics in Ras [21] , which motivates further investigation of allosteric effects in the WT and variants . At present , our understanding of the impact of sequence variations on the ability of variants to populate functional conformations is limited to those structures documented in the PDB . Seminal work by Grant and McCammon in 2009 projected the experimentally-probed conformation space of H-Ras onto two reaction coordinates extracted through a linear dimensionality reduction technique such as Principal Component Analysis ( PCA ) [7] . The two principal components ( PCs ) obtained from the PCA that captured most of the variance of the original structure data were used as reaction coordinates . The two-dimensional map of the conformation space of H-Ras exposed vast unpopulated regions by the WT and variants . Simple interpolation over existing structures in the two-dimensional embedding would not be accurate in delineating features of the energy landscape over the unpopulated regions of the conformation space ( analysis in S8 Fig in the Supporting Information shows many regions of the energy landscape that are currently not covered by any known experimental structures of H-Ras ) . Moreover , many structural details would be sacrificed , as more coordinates or dimensions are needed to preserve the structural variance observed in the experimentally-probed conformation space . More sophisticated conformational search algorithms , systematic or stochastic , are needed to handle more coordinates and explore the breadth of the conformation space . One could in principle devise a systematic search algorithm that imposes a grid over the specified coordinate axes . However , even at a small number of dimensions and a coarse resolution to define cells of the resulting grid , the number of structures needed to populated the grid would be prohibitive for any further energetic evaluation and improvement . Even at few cells per dimension and a modest number of dimensions , the number of structures easily reaches in the millions . As such , systematic grid-based searches have too high computational costs to be useful at all . Instead , either algorithms based on Molecular Dynamics ( MD ) or stochastic optimization remain viable . Indeed , MD-based conformational search algorithms have been employed to study Ras structure and dynamics . MD-based simulations of Ras in uncomplexed and complexed forms were used in [22] to study subtle conformational and dynamics changes of Ras upon effector binding . A structural alphabet ensured removal of trivial roto-translations . Comparison of MD trajectories revealed changes due to downstream effector binding of Ras to Byr2 , PI3Kγ , PLCɛ , and RalGDS [22] . The majority of MD-based approaches focus on mapping the conformation space of the uncomplexed form of Ras isoforms . The earliest such studies simulated local structural fluctuations around individual nucleotide states of uncomplexed Ras [23 , 24] . Unbiased MD simulations in [25] captured spontaneous nucleotide-dependent transitions of the oncogenic H-Ras G12V variant [25] . Analysis of the uncovered regions of the energy landscape demonstrated that the energy barrier between the inactive and active states was lower in the H-Ras G12V variant than in the WT . Due to the computational cost of unbiased MD simulations and demonstrated limitations in sampling , biased and accelerated MD simulations have been attempted , as well . Biased MD simulations resulted in unrealistic high-energy structures [26 , 27] . On the other hand , accelerated MD , an approach originally proposed in [28] , was shown to populate many regions of the H-Ras conformation space not observed in the wet laboratory [7] . Several known stable conformations of H-Ras variants were also found to be accessible to the WT . Multiple barrier-crossing trajectories were observed for the WT with 60ns-long accelerated MD simulations; as the authors noted , such trajectories would have been practically impossible to obtain with classical , unbiased MD simulations of the same length due to the high free energy barrier separating the active and inactive states in the H-Ras WT [7] . The sampling capability of accelerated MD was shown to greatly depend on the structure used to initiate a trajectory [7] . In several cases , accelerated MD simulations initiated from a WT inactive structure did not reach the crystallographic active structure , pointing to persistent limitations in sampling . Nonetheless , accelerated MD remains a viable option over classical MD and has been applied to characterize the dynamics of other Ras isoforms , several H-Ras variants [29] , and has even been integrated in computational pipelines for identification of leads in drug design [30] . Non MD-based approaches devised to improve sampling over MD-based approaches [31] have been applied to study Ras , as well . For instance , work in [32] computed minimum-energy paths bridging between the active and inactive states through a modification of the conjugate peak refinement algorithm [33] . Other non MD-based approaches , such as CONCOORD [34] , FIRST/FRODA [35 , 36] , and PEM [37–39] are designed to rapidly populate the conformation space in a neighborhood around a given structure . Though not directly applied to populate the conformation space of Ras , such methods could , in principle , if initiated from each existing crystallographic structure , provide a map of the conformation space of H-Ras . The foreseen difficulty would be on populating regions of the space with no experimentally-available structures in the vicinity . Documented difficulties of MD-based methods and foreseen challenges with adapting existing non MD-based approaches motivate our proposal of SIfTER , a novel non MD-based conformational search algorithm capable of exploring the breadth of the structure space and mapping the underlying energy landscape of a protein . Since MD simulations remain computationally demanding and are challenged by complex high-dimensional search spaces [4] , SIfTER implements stochastic optimization and yields a sample-based representation of the conformation space and energy landscape of a protein under investigation . We apply SIfTER to map and juxtapose energy landscapes of H-Ras WT and selected oncogenic variants to provide the energy landscape as the intermediate explanatory link between sequence mutations and functional changes . SIfTER is a data-driven evolutionary algorithm . While in this paper we focus on the uncomplexed form of the catalytic domain of H-Ras in the WT form and two oncogenic variants , the algorithm is general . No system-specific information is exploited beyond experimentally-available structures of a protein . Unlike MD- and other non-MD based approaches that are limited to being initiated from a specific structure , SIfTER leverages information available in a collection of experimentally-determined structures documented for a protein . Inspired by the seminal work of Grant and McCammon in [7] , SIfTER also employs PCA over experimentally-determined structures to define collective variables/parameters of the search space as well as effective ranges of these parameters . The algorithm efficiently draws samples from the resulting low-dimensional search space , and then maps samples through a novel multiscale procedure to all-atom conformations that are local minima in the all-atom energy landscape ( the all-atom energy function used here is Rosetta score12 ) . In this way , local minima in the energy landscape can be computed efficiently while still allowing for a wide search range within the space defined by the experimental structures . As we demonstrate here , SIfTER reconstructs , for the first time , the all-atom energy landscapes of various sequences of the catalytic domain of H-Ras . The algorithm is able to efficiently do so by exploiting the existence of close to a hundred crystallographic structures of H-Ras WT and variants in the PDB . The guiding hypothesis for SIfTER is that documented structures of H-Ras WT and variants are also available and populated by a specific H-Ras sequence under investigation , though possibly with different population probabilities than in the native sequence probed in the wet laboratory . This is in essence the principle of conformational selection [40–43] . Grant and colleagues provided the first evidence of this by observing stable structures of variants populated by WT H-Ras [7] . This guiding principle allows treating the structures documented for WT and variants as possibly important locations in the energy landscape for a specific protein sequence under investigation . Taken together , SIfTER produces an ensemble of all-atom conformations residing at local minima , effectively and efficiently providing a representation of the energy landscape relevant for understanding function . We juxtapose and analyze here in detail the landscapes obtained by SIfTER for WT H-Ras and two important oncogenic variants , G12V and Q61L . Our comparative analysis suggests that G12V and Q61L cause constitutive activation through two different mechanisms . G12V directly affects binding specificity while leaving the energy landscape unchanged , whereas Q61L has pronounced effects on the underlying landscape . In addition to validating existing biological knowledge , SIfTER provides for the first time a detailed view of the energy landscapes of H-Ras WT and variants and proposes novel structural states not observed in the wet laboratory . These structures provide the foundation for further structure-guided studies of function , molecular interactions , and therapeutics for oncogenic H-Ras variants . An implementation of SIfTER is made available to the community at http://www . cs . gmu . edu/~ashehu/ ? q=OurTools to encourage studies on the impact of sequence mutations on biological activity in other protein molecules .
One can analyze in further detail the molecular motions associated with the top three PCs . Each PC is a vector containing 166 × 3 displacements for each of the x , y , z cartesian coordinates of the 166 CA atoms in the catalytic domain of H-Ras . These displacements are visualized in the right panel of Fig 2 by plotting the coordinates of each PC . The SI and SII regions are annotated . The displacements along each PC are additionally visually illustrated on an H-Ras structure in the left panel of Fig 2 . The right panel of Fig 2 shows that the region whose motions are captured consistently and are dominant along each of the top three PCs is the SII region ( ( amino acids at positions 57–75 ) . The dominance of motions of the SII region has also been observed by Grant and McCammon in [7] . In particular , in [7] , the helix α2 region ( amino acids at positions 66 to 74 ) contained in SII is noted to be the major dynamic element of the Ras structure , in agreement with our observations here . As Fig 2 shows , CA displacements in each of the top three PCs additionally capture the correlated motions between the SI ( amino acids at positions 25–40 ) and SII regions . The regions that undergo the largest displacements are those of amino acids at positions 26 to 37 , referred to as loop2 in the SI region , and those of amino acids at positions 66 to 74 , the α2 helix in the SII region . The switch regions undergo the main structural changes in the GTP- to GDP- transition . Since PCA is capturing such deviations , this analysis lends further credibility to employing the reduced space of PCs as the search space for SIfTER to rapidly find more functional conformations of H-Ras . Moreover , since the top two PCs also account for over 55% of the variance ( essentially allowing to capture 55% of the dynamics ) and capture the structural changes between the GTP- and GDP-bound states , they are both effective to be employed in the structurization/grid by the local selection operator ( detailed below ) and to project the energy surface for the purpose of visualizing the energy landscape on 2 dimensions ( projecting all SIfTER-obtained conformations on PC1 and PC2 ) . In addition , CA displacements in PC2 and PC3 show correlated motions that include amino acids at positions 93 to 110 . This region is referred to as α3-loop7 in [7] . Taken together , the motions along PC1 , PC2 , and PC3 capture the dynamic linkage between three regions , SI ( specifically , loop2 in SI ) , SII ( specifically , α2 in SII ) , and α3-loop7 . Such linkage has been observed previously in MD simulation studies [7] . In particular , the correlated motions between α2 and α3-loop7 have been previously noted to show a novel GTP-dependent correlated motion in Ras with functional implications [7] . These motions serve as a non-covalent communication route in Ras , and Grant and McCammon speculate that amino acids in these regions may be important for nucleotide-dependent modulation of membrane attachment and lateral segregation by linking the switching apparatus to the membrane interaction apparatus [7] . As noted by Grant and McCammon , while the loop3 region has been studied via mutations in the wet laboratory , the other regions , including the dynamic α3-loop7 region , though shown to undergo correlated motions in simulation , have received little attention in the wet laboratory . Our analysis seems to additionally emphasize the need for better understanding of the role of these regions in the function of Ras . Using the top ten PCs as axes of the reduced search space , SIfTER is then applied to the WT , G12V , and Q61L sequences of H-Ras . It is worth noting that while the axes of the search space are the same for each application of SIfTER on each of the three sequences , the multiscale procedure that maps points sampled in the reduced search space to the space of all-atom conformations employs sequence information . Hence , the ensembles obtained by SIfTER on each application are different . On each application , the entire ensemble of all-atom conformations is stored . A conservative energy threshold of −100 Rosetta score12 units is then applied in order to retain for further analysis only functional conformations ( and essentially filter out false positives expected from any semi-empirical protein energy function ) . The determination of this threshold is not system-specific but is made based on the range of score12 energy values obtained for crystallographic structures when their CA traces are threaded onto the WT sequence and then subjected to the multiscale procedure used by SIfTER . The range of resulting score12 energies is observed to be from around −300 to around −100 units . Hence , only SIfTER-obtained conformations with energies no higher than −100 units are retained for further analysis . The rest of our analysis below focuses first on the ability of SIfTER to recover functional conformations corresponding to crystallographic structures withheld from the PCA and then on visualization and comparison of energy landscapes constructed for each H-Ras sequence . We validate first the capability of SIfTER to discover known functional conformations of H-Ras . We show data for the WT . For each of the 86 crystallographic structures , we find the closest conformation to that structure among the functional conformations obtained by SIfTER for WT H-Ras ( all-atom conformations whose energies meet the energetic threshold described above ) . The distance between two conformations is measured through the well-known root-mean-squared-deviation ( RMSD ) after an optimal superimposition has been found that removes structural differences due to rigid-body motions [45] . In particular , Fig 3 shows CA RMSDs ( the distribution of backbone RMSDs is very similar ) . It is not possible to report all-atom RMSDs , because many of these crystallographic structures may be on different sequences or have missing side-chain atoms even if reported for the WT sequence . As can be seen in Fig 3 , RMSDs for the structures withheld from PCA ( in blue ) are low , with the majority less than 1Å . As described in the Materials and Methods section on the presence of about 5 outlier structures with loop motions outside the SI regions , CA RMSDs higher than 1Å are only observed for a few outlier structures ( details on these outlier structures are provided in S2 Table and S1 Fig in the Supporting Information ) . In comparison , the CA RMSDs for the 46 structures used by SIfTER to define the reduced space ( in green and blue in Fig 3 to indicate structural state ) are no higher than 0 . 7Å . Taken together , these results suggest that SIfTER is able to recover known functional conformations of H-Ras even though they are not directly incorporated in the algorithm . In addition to being able to recover known functional conformations , SIfTER also provides the ability to map the location of these conformations on the energy landscape . Fig 4 shows the energy landscape associated with functional conformations generated by SIfTER for WT H-Ras . The landscape is a projection of the energy surface over the top two PCs for the purpose of visualization . This two-dimensional projection of the space of functional conformations is color-coded as follows . A grid is laid over the embedding , with cells of size 1 . Each cell is then colored by the median energy score of the conformations with projections in that cell . The bilinear interpolation in the imshow python utility is employed for this purpose . For ease , the color bar shows not the range of absolute score12 energy values but instead the difference from the lowest-energy value . Fig 4 additionally shows the locations of all collected 86 crystallographic structures on the SIfTER-obtained energy landscape for WT H-Ras . A crystallographic structure can be easily projected onto given PCs , as described in detail in the Materials and Methods section . Projections of the 46 structures used by SIfTER to define the reduced search space are annotated differently from projections of the unused set of 40 structures . Moreover , crystallographic structures reported for the WT are specially annotated . Fig 4 allows visualizing the location of experimentally-obtained structures onto the energy landscape . Several observations can be made . The majority of crystallographic structures reported for the WT are all on regions of the landscape that correspond to the deepest basins ( darker blue regions ) . This applies to both structures employed by SIfTER to define the search space and those withheld for the purpose of validation . Structures reported for variant sequences also map to low-energy regions , which supports the hypothesis that these structures , though not reported for the WT , can be used as representatives of meta-stable states to guide a data-driven algorithm like SIfTER . In addition , no crystallographic structures , whether reported for the WT or variant sequences , are found to lie on energy barriers . This further lends credibility to SIfTER’s ability to find novel features of the energy landscape that a simple interpolation of energies in the PC1-PC2 embedding or limited exploration around a structure cannot produce . The energy landscape elucidated by SIfTER allows better understanding the menu of functional conformations used by H-Ras WT , beyond the space probed directly in the wet laboratory . The rest of our analysis focuses on novel knowledge that SIfTER confers about the three sequences of H-Ras studied in this paper by comparing energy landscapes generated by SIfTER for each sequence . We recall that the landscapes are projections of functional conformations generated by SIfTER on each sequence onto the top two PCs . Color-coding of the two-dimensional embeddings is as described above . In addition , the analysis below provides not only Rosetta score12 landscapes , but also Amber ff12SB landscapes . The latter are obtained by subjecting functional conformations to a short energy minimization protocol in AMBER , described in detail in the Materials and Methods section . The Rosetta and Amber landscapes for each H-Ras sequence studied here are shown in Fig 5 . The left column shows the Rosetta score12 landscapes , and the right column shows the AMBER ff12SB landscapes . The top row shows the landscapes obtained for the WT , the middle row shows the landscapes obtained for the G12V variant , and the bottom row shows the landscapes obtained for the Q61L variant . We note that the color bars do not show absolute energy values , but differences from the lowest-energy value obtained for each sequence . This allows focusing on relative scales rather than absolute energy values , which can be different among energy functions . The Rosetta and AMBER SIfTER-obtained energy landscapes agree very well for the WT sequence ( see top row in Fig 5 ) . Four basins are observed , annotated On , Conf1 , Conf2 , and Off . The On basin is designated as such based on the location of projections of GTP-bound structures on the PC1-PC2 map ( shown in Fig 1 ) . Similarly , the Off basin is designated as such based on the location of projections of GDP-bound structures on the PC1-PC2 map . It is reassuring to note that the On and Off structural states both correspond to deep basins ( blue regions ) in the Rosetta and AMBER energy landscapes generated by SIfTER for the WT and G12V H-Ras . However , for both sequences , the GTP-bound/active structural state resides in a deeper basin than the GDP-bound/inactive structural state . This difference is starker on the Rosetta landscapes for each of the sequences . Two novel higher-energy basins , annotated Conf1 and Conf2 , are additionally observed . Comparison with the projections of crystallographic structures in Fig 1 reveals that the Conf2 basin corresponds to the same location as structures with PDB ids 2q21 and 1q21 . These structures are described in a study on the G12V mutation [46] but have not been reported as possibly functional conformations of the WT H-Ras . The energy landscape analysis here suggests that these structures may be functional , from a thermodynamic availability point of view , but perhaps difficult to access for the WT . The reason for this is that the Conf2 basin is surrounded by high-energy barriers that may prevent the WT sequence from readily adopting this alternative functional state . The other , novel Conf1 basin corresponds to an unanticipated structural state . The crystallographic structures whose locations in the PC1-PC2 map correspond to this basin are those with PDB ids 1lf0 and 6q21 ( D ) . The structure with PDB id 1lf0 is the crystallographic structure of H-Ras A59G variant in the GTP-bound state [47] . This variant adopts a conformation that is an intermediate between the GTP- and GDP-bound states of WT H-Ras . Prior work has noted the intermediate nature of A59G conformations , as removing the gamma-phosphate of the bound GTP from the structure of A59G led to a spontaneous GTP-to-GDP conformational transition in a 20-ns unbiased MD simulation [29] . The location of the Conf1 basin found by SIfTER confirms this and sheds additional novel insight . The experimentally-probed structure for A59G H-Ras ( PDB id 1lf0 ) can indeed be populated by WT H-Ras as a semi-stable structural state . The corresponding Conf1 basin may indeed mediate the transition between the On and Off basins . This may be a general mechanism for the WT and the two oncogenic variants studied here . No high-energy barriers are noted for this possible transition in the landscapes obtained for the WT and G12V sequences ( and to some extent , the Q61L sequence , as well , though there are starker differences between the Rosetta and AMBER landscapes for the Q61L variant ) . The observations made above for the alignment of known and novel structural states with basins in the landscapes obtained for WT H-Ras largely transfer to observations for the G12V variant ( see middle row in Fig 5 ) . The AMBER landscape depicts basins Conf1 and Conf2 as being deeper than in the Rosetta landscape . Comparing the Rosetta landscape for the G12V sequence to the WT landscape shows that the Off basin has also become less defined in the G12V variant . In particular , in the AMBER landscape for G12V , the barrier between the On and Off basins has been significantly reduced . This is the main change between the WT and G12V H-Ras landscapes . The reduced stability of the GDP-bound state for the G12V variant suggest that it may be this change that contributes to the oncogenic activity associated with the G12V mutation . However , the change in the G12V energy landscape is small , which may further suggest that a change in binding specificity due to the proximity of G12V to the binding site may also contribute to the oncogenic activity . These findings agree with published computational and experimental studies on the G12V variant . In particular , previous MD simulation studies have shown that both GTP-bound and nucleotide-free G12V H-Ras sample a wide region of conformation space , indicating the absence of significant changes in the conformation space due to the G12V mutation [25] . Experimentally , it has been shown that the G12V variant has similar binding affinity of ATP as the WT , though the V12 side chain in the G12V variant hinders correct orientation of water molecule needed for ATP hydrolysis [48] . The bulky V12 side chain in the G12V variant is thought to lower the GTPase activity through a steric interference over this catalytic process [49] . The Rosetta and AMBER SIfTER-obtained energy landscapes for the Q61L variant agree on the main features ( see bottom row in Fig 5 ) . In both landscapes , the Conf2 and Off basins have all but disappeared . While the Conf1 basin is retained in the Rosetta landscape , and the On basin extends towards the Conf1 basin , the Conf1 basin disappears in the AMBER landscape . Both the Rosetta and AMBER landscapes agree that mainly the On basin is retained , which corresponds to the GTP-bound state . This suggests that the oncogenic mutation Q61L causes significant changes to protein stability by causing the protein to become much more rigid , thereby destabilizing all structural states except the GTP-bound state associated with the On basin . By essentially only allowing Q61L to adopt the GTP-bound state , this mutation causes H-Ras to be constitutively activated , which may initiate the cascade of cellular processes resulting in unregulated cell growth and cancer . We point out that early studies through classical MD simulations succeeded in capturing the active to inactive transition in Q61L largely because of an observed lower free-energy barrier compared to the WT [7] . This is in agreement with our observations , and the detailed energy landscapes obtained here for the Q61L variant provide an easy visualization of why this is the case for the first time . In addition , our findings on the rigidification of the GTP-bound state in the Q61L variant have been corroborated in the wet laboratory [19 , 20] . In particular , work in [50] shows that Q61L is not able to hydrolyze GTP in the presence of Raf and thus is a constitutive activator of this mitogenic pathway . In addition , the study shows that the newly-resolved crystal structures of the Ras-GppNHp/Raf-RBD and RasQ61L-GppNHp/Raf-RBD complexes , in combination with MD simulations , exhibit a rigid SII relative to the WT . Finally , it is worth noting that one of reasons the AMBER landscapes are morphologically very similar to the Rosetta landscapes is that the AMBER minimization of each structure obtained by SIfTER does not introduce significant structural changes , particularly to the positions of the CA atoms . This is shown in the Supporting Information in S5 Fig . Since the PCs are over CA traces , no significant morphological changes are expected . However , as the analysis above has demonstrated , changes in the relative depths of various regions on the landscape are expected , due to the employment of a different energy function . For completion , projections of the landscape along PC3 are also provided and can be found in S9 Fig in the Supporting Information document . Projections along PC3 fail to provide any more separation of the basins identified above , as expected , given that variance along PC3 is minimal compared to PC1 and PC2; in other words , the dynamics of H-Ras can largely be accounted for by PC1 and PC2 . In addition , while the above analysis color codes the cells of the PC1-PC2 maps by the median energy of structures mapping to a cell , S10 Fig in the Supporting Information document color codes by variance . S10 Fig shows lower variance for the four identified structural states/basins; this is expected , as SIfTER is a stochastic optimization algorithm that explores lower-energy regions in greater structural detail . The structural states corresponding to each of the 4 basins recovered by SIfTER for WT H-Ras are shown in Fig 6 ( top panel ) . 4 conformations representing each of these 4 basins are superimposed over one another . Superimposition of these conformations allows visualizing the slight structural changes associated with the four different structural states found by SIfTER . Another visualization of each of the four structural states corresponding to the four basins is provided in Fig 6 ( bottom panel ) , which now shows these states not only for WT H-Ras but the other two variants , as well . Crystallographic structures mapping to the four basins are also shown for reference . Fig 6 demonstrates that conformations taken from the same region in the landscape , regardless of which sequence , have the same conformational topology . In addition , crystallographic structures mapping to the same region ( shown in red ) also have very similar topology . In addition , Fig 6 shows that the G12V mutation is very close to the binding site for the ligand . This supports the conclusion that the G12V mutation derives some of its oncogenic properties due to the mutation interacting with the ligand . On the other hand , the Q61L mutation is located much further away from the binding site , but position 61 is part of the SII region . As we have shown previously , this is the region of H-Ras that undergoes the largest conformational change between the GTP- and GDP-bound states . Taken together , these observations support the argument that the Q61L mutation has major effects on the stability of H-Ras by effectively rendering the GDP-bound state inaccessible .
The energy landscapes obtained by SIfTER offer the most comprehensive energetic analysis of H-Ras thus far available . For the first time , energy landscapes have now been reported for the WT and two oncogenic variants of H-Ras . The energy landscapes connect individual experimentally-known conformations to their relative energies in the global scale . Most importantly , some of these conformations are located on the energy barrier connecting active and inactive conformations , thus providing important insight into Ras function and dynamics . In addition , semi-stable structural states ( corresponding to the Conf1 and Conf2 basins ) are revealed for WT H-Ras . Mechanistic insight is obtained for a possible Conf1-mediated transition between the On and Off states . Juxtaposition of the energy landscapes reveals a thermodynamic argument for changes to function in the two oncogenic variants G12V and Q61L . Computed energy landscapes are potential energy landscapes without entropic effects . However , entropic effects are implied visible in the width of the discovered basins . Regarding entropic effects , flexible structures in shallow basins should have higher entropy and so can be further stabilized . Deep basins separated by high energy barriers may have unfavorable entropic effects . For instance , the Q61L mutation causes a higher-energy barrier between different conformational states and rigidifies H-Ras , which also has entropic implications . It is also worth noting that what we have studied here is the “intrinsic” energy landscape without the effects of the GTP/GDP nucleotides . When GTP/GDP bind to Ras , the relative energies in the energy landscape change; the gamma phosphate of GTP can further stabilize the closed GTP conformation . The essence of the conformation selection and population theory is that these conformations pre-exist prior to the ligand ( GTP/GDP ) binding , which is what we reveal in this paper . Application of SIfTER to the G12V H-Ras variant reveals that the G12V mutation has a small effect on the energy landscape . Analysis of the landscape and location of the mutation relative to the GTP/GDP binding site suggest that the oncogenic properties of this mutation may result from a combination of altered protein stability and changed binding specificity . The Q61L mutation has a more profound effect , essentially rigidifying H-Ras to the GTP-bound state . Mutation-induced structural changes , such as the rigidification of the Q61L variant , affect the intrinsic GTP hydrolysis activity in H-Ras and gives rise to aberrant function in this oncogenic variant , which may be sufficient to interfere with the intrinsic regulation of downstream signaling . The identification of specific conformations associated with distinct stable and semi-stable structural states in WT H-Ras and variants supports wet-laboratory efforts on selectively interfering with misfunctions in oncogenic variants [51] . Findings on the two variants studied here are important in understanding how mutations in Ras affect function and can be further applied to predict the effect of mutations that remain unclassified . Ras mutations vary in their oncogenicity , and the reason is not understood . Sampling variant-preferred conformational states may help in elucidating this challenging goal and is the subject of future studies in our labs . There are differences among Ras isoforms , as well , and future studies can focus on isoforms other than H-Ras . We believe that the results presented in this paper have both confirmed experimental and computational knowledge on H-Ras , as well as advanced knowledge through novel findings . For the first time , energy landscapes have now been reported for the WT and two oncogenic variants of H-Ras . In addition , novel functional conformations have been reported . These novel findings are crucial to advance our understanding of H-Ras and facilitate other structure-driven studies in the wet or dry laboratories . For this reason , in addition to the implementation of SIfTER , which is available at http://www . cs . gmu . edu/~ashehu/ ? q=OurTools , all the data obtained and reported in this paper are available to researchers upon demand . From a methodological point of view , the use of PCA in SIfTER is an effective means to reduce the search space and focus computational resources on structural fluctuations that have been captured in the wet laboratory . However , it also presents challenges that may limit its application . Sufficient experimental structures need to be deposited so dimensionality reduction techniques can be employed . It is also hard to draw general rules of thumb on how many structures and other considerations for application of PCA and credibility of the motions captured by its PCs . Investigation of these needs to be conducted on a case by case basis . For instance , an analysis along the lines of what we detail in the Supporting Information can be conducted to identify and exclude outlier structures whose inclusion would bias the PCA-revealed modes of motion away from those demonstrated to have functional implications in the wet laboratory . In addition , other techniques can be employed to extract concerted motions from one structure at a time . It is worth noting that non-linear dimensionality techniques may possibly reveal even lower-dimensional search spaces than PCA , which is a linear dimensionality reduction technique , but they must allow conformational search algorithms direct sampling in the reduced space , which PCA directly provides . However , the reduced search space obtained via PCA here is sequence-independent and therefore can be explored to search for stable and semi-stable structural states of a given protein , which makes SIfTER a general algorithm . Direct integration of more physics-based energy functions may provide more accurate representations of the energy landscapes computed by SIfTER . However , at this moment , physics-based engines largely limit interactions via scripts; in particular , there is no side-chain packing functionality in AMBER as opposed to a simple-to-use interface in Rosetta that can be integrated in external codes . For these reasons , the analysis in this paper on AMBER landscapes is based on short post-processing of SIfTER-obtained functional conformations .
On the specific application of SIfTER on H-Ras , the PDB is queried for any structures of H-Ras . Only crystallographic structures are considered in order to reduce biasing the dimensionality reduction technique with small structural fluctuations present in NMR ensembles . The WT sequence of 166 amino acids of the H-Ras catalytic domain is obtained from the UniProt [17] . This sequence is used as reference to define the maximum sequence length . Out of all collected structures , only those corresponding to variant sequences with no more than 3 mutations over the WT are retained . Any structures with missing internal fragments are excluded . Specifically , 86 structures fitting these criteria are identified and collected ( PDB ids are listed in S1 Table in the Supporting Information ) . 46 of these structures , which represent the state of the PDB for H-Ras by 2009 , have been used previously by McCammon and colleagues to analyze the essential modes of motion in H-Ras [25] . We decide to only allow SIfTER to exploit these same 46 structures , leaving the other 40 added to the PDB after 2009 to validate several results obtained by SIfTER ( PDB ids are listed in S1 Table in the Supporting Information ) . Our premise is to treat these 46 structures as known representatives of stable or semi-stable structural states in any sequence of H-Ras , whether WT or variant . SIfTER does so by threading CA traces of these structures onto a sequence of interest . The traces are subjected to the dimensionality reduction technique described next to define the reduced search space . They are also employed to seed the initial population . Like McCammon and colleagues [25] , we also employ PCA [52] as our dimensionality reduction technique . However , while McCammon and colleagues employed PCA mainly to visualize a collection of H-Ras structures on a two-dimensional map , SIfTER makes use of PCA to define its reduced search space for sampling novel conformations . PCA finds orthogonal axes ( Principal Components—PCs ) in order of preserving variance . We subject PCA to the 46 CA traces in order to define the reduced search space . To ensure that the PCA results are not capturing rotational or translational differences but instead internal structural fluctuations , the CA traces are aligned to some reference trace ( we use arbitrarily the first one ) using the optimal superimposition process typically employed when identifying least root-mean-squared-deviation ( lRMSD ) between two structures [45] . Subsequent to the alignment , an average trace AT is computed and subtracted from all the traces . The resulting centered matrix X is subjected to the dgesvd routine in LAPACK [53] in order to obtain a singular value decomposition X = U ⋅ Σ ⋅ VT . The new axes or PCs are the rows of the U matrix , and the singular values , which are the square roots of the eigenvalues corresponding to the PCs , are the diagonal entries of the Σ matrix . The PCs are ordered from largest to smallest corresponding eigenvalue; an eigenvalue measures the variance captured by the corresponding PC if the data ( traces aligned and centered ) are projected onto it . An aligned CA trace ( CT ) , even if not included in the PCA , can be readily projected onto the space of extracted PCs . Its projection RS can be obtained using the equation RS = ( CT − AT ) ⋅ U . Conversely , an aligned CA trace CT can be recovered from a projection RS by the following equation CT = RS ⋅ UT + AT . These two equations are important for SIfTER to have the sample drawing and the multiscale procedure interface with each-other seamlessly . When a sample/offspring is generated , its CA trace can be recovered via the second equation . When the multiscale procedure is applied on a CA trace and an all-atom conformation is obtained , its projection back onto the reduced search space can be obtained via the first equation . Projecting all-atom conformations back onto the reduced space is necessary , as the multiscale procedure may slightly modify the CA trace in order to accommodate side chains for an overall lower all-atom energy . Analysis of eigenvalues allows determining whether PCA is effective , which is not guaranteed if the data lie on a non-linear space . As originally demonstrated by McCammon and colleagues [25] and also by us here , more than 90% of the variance can be captured with no more than 10 PCs; that is , if the traces are instead represented by their projections on 10 axes . The top two PCs capture more than 50% of the cumulative variance ( as related in Fig 1 in the Results section ) . The detailed analysis of the motions captured by the PCs in the Results section allows concluding that PCA is effective for H-Ras , and that the PCs can be employed as axes of a reduced search space to search for novel functional conformations of a given sequence of H-Ras . The fact that PCA is effective means that SIfTER can operate not in the full space of 166 × 3 dimensions but instead on a lower-dimensional space of d PCs of corresponding highest eigenvalues . This effectively allows SIfTER to represent an individual in its search by only d collective coordinates , but determining an effective value for d is critical . In S1 Text in the Supporting Information we outline a procedure for doing so by employing the additional 40 structures/traces not subjected to the PCA . Analysis of data obtained from the procedure ( shown in S2 Fig in the Supporting Information ) suggests d = 10 for the dimensionality of the search space . SIfTER directly generates 10-dimensional samples in the space of the top ten PCs revealed by the PCA; that is , each individual is represented by only 10 variables that are projections on the top 10 PCs . The reproductive operator perturbs each parent , one at a time , in a randomly-drawn vector in the d-dimensional search space to obtain an offspring for each parent . A maximum step size smax ( set to 1 here ) is first defined . For each of the d PC coordinates of the parent , a step size si is sampled uniformly in [−smax , +smax] and then scaled according to the ratio of variance captured by the corresponding PCi such that s i , s c a l e d = s i ⋅ V a r ( P C i ) V a r ( P C 1 ) . Since the PC dimensions are ordered according to the variance they capture ( highest to lowest ) , scaling the step size in each dimension in this way ensures that larger perturbations will be carried out along the PCs/dimensions that capture more of the variance . This essentially preserves the shape of the search space as suggested by the crystallographic structures . After the step size for each dimension is determined in this way , the corresponding coordinate PCi , offspring for the offspring is obtained by PCi , offspring = PCi , parent+si , scaled . Each offspring obtained by the reproductive operator is subjected to a local improvement operator . The process begins with recovering the CA trace corresponding to the d-dimensional representation of an offspring , as detailed above . A backbone is then reconstructed from the CA trace using BBQ [54] , which is one of the top backbone reconstruction protocols . Our decision to employ BBQ over other similar protocols is due to the reported ability of BBQ to faithfully restore backbones [54] . Once the backbone is built from a CA trace , side chains are then packed onto the reconstructed backbone via the Rosetta relax protocol [55] . The protocol is employed to obtain an all-atom conformation corresponding to the offspring drawn by the reproductive operator in the reduced search space . In addition to adding side chains , the relax protocol conducts a Monte-Carlo based energetic minimization of the all-atom conformation to obtain an all-atom conformation representing a local minimum in the all-atom energy landscape . While there are currently many side-chain packing protocols , the one in the Rosetta software package employs a sophisticated all-atom energy function as opposed to simple functions focusing mainly on Lennard-Jones and electrostatic interactions . In addition , the protocol is efficient and implemented in an object-oriented programming language , which allows efficient interfacing with our implementation of SIfTER and maintaining the computational demands of the algorithm low . Analysis on the effectiveness of the local improvement operator is provided in Supporting Information in S3 and S4 Figs . The ability to integrate Rosetta functionality in SIfTER is one of the main reasons for choosing Rosetta as opposed to physics-based simulation platforms to evaluate and energetically-refine conformations . The latter require scripting , which results in computationally impractical time demands for an algorithm that essentially generates N × P all-atom conformations . It is also important to note that there is currently no side-chain packing functionality in AMBER; that is , to pack side chains onto backbone structures , one needs to rely on other packages . This is a central reason why we use Rosetta in this paper . However , we do address the generality of the obtained Rosetta score12 landscapes by further subjecting all generated conformations to short energetic minimizations in AMBER . The minimization protocol uses the Amber ff12SB force field and sander to conduct 500 steps of steepest descent followed by 500 steps of conjugate gradient descent ( maxcyc = 1000 , ncyc = 500 ) . Nonbonded interactions beyond 10Å are cutoff ( cutoff = 10 ) . The generalized Born solvation model is used ( igb = 1 ) . All our conclusions regarding changes that mutations introduce to the H-Ras WT energy landscape are made by studying common features between the Rosetta score12 and the AMBER ff12SB landscapes . Due to the employment of the Rosetta relax protocol in the local improvement operator , the fitness value that the selection operator in SIfTER uses to evaluate and compare individuals is the all-atom Rosetta score12 energy . Given two individuals under comparison , the one with the highest fitness ( lowest score12 value ) survives . Instead of a global or central selection operator , SIfTER employs a local or decentralized one . A global selection operator combines all N offspring and N parents in a generation prior to determining which N should survive based on fitness . The danger with such an operator is that offspring have a hard time competing with parents . Therefore , the entire algorithm risks being taken over very quickly by a few currently fittest individuals , essentially prematurely converging to a few local minima . Since the goal in SIfTER is high sampling capability so as not to miss important functional conformations ) , a local selection operator is employed to improve the likelihood that offspring survive . This is accomplished through what is known as a crowding model [56] , where essentially offspring compete with a limited subset of parents . The idea is to have an offspring compete mainly with structurally-similar parents . Structural similarity is determined quickly and coarsely over a 2-dimensional representation of individuals; essentially , only the first two coordinates ( top two PCs ) are used , so that a simple 2-dimensional grid can be imposed over parents and offspring . Individuals in the same or nearby cells are considered structurally-similar . If there are no parents nearby , an offspring competes with all parents . The concept of a neighborhood is illustrated in the Supporting Information in the top panel of S6 Fig . A detailed analysis is conducted to determine an effective neighborhood size C , also detailed in the Supporting Information . The analysis suggests employing a value of 25 , which is what is used to obtain the data reported and analyzed in this paper ( the analysis provided in the Supporting Information in the bottom panel of S6 Fig also shows that convergence is reached by generation 50 , suggesting that any number of generations no smaller than this value is sufficient to allow SIfTER to explore the breadth of the conformation space . ) The 46 crystallographic structures used to define its d-dimensional search space seed the initial population . Their projections are the first set of individuals added to the initial population . To associate fitness values with these individuals , each of them is subjected to the local improvement operator . Moreover , SIfTER uses a much larger population size P = 500 . The size of the population is an important decision , as a small population risks premature convergence , whereas a larger one increases the computational demands of an EA . Typically , population sizes in the hundreds are currently advised for application of EAs on medium-size proteins ( cf . to Review in Ref . [31] ) . Analysis of applications of SIfTER with smaller population sizes ( data not shown ) have led us to P = 500 as a compromise between obtaining a broad view of the conformation space while controlling the computational demands of the algorithm to a few days on one CPU . To increase the size of the initial population from 46 employed crystallographic structures to 500 , more individuals need to be generated . P is continually doubled by subjecting all current individuals to the reproductive and local improvement operator before being added back into the population . This continues until doubling again would cause the population to exceed P = 500 . The population is then filled to the desire size by continuing to randomly select an individual to generate another offspring , which is added to the population . The algorithm is implemented in C/C++ and run on a 16 core red hat linux box with 3 . 2GhZ HT Xeon CPU and 8GB RAM . Population size P is set to 500 , and SIfTER is run for N = 100 generations . The analysis summarized in the Supporting Information ( bottom panel of S6 Fig ) indicates that this number of generations is sufficient to allow SIfTER to converge; indeed , convergence is observed around generation 50 . The reproductive operator uses a maximum step size of 1 . The local selection operator uses neighborhood C25 , and cell widths of 1 . Total run time for application of SIfTER on a given Ras sequence is approximately 72 hours on 16 CPUs ( 16 processes are used to alleviate the computation burden of the Rosetta relax protocol employed when improving offspring ) . Finally , it is worth noting that the results shown in this paper are not exploiting particular runs of SIfTER . Instead , the algorithm is run many times , and comparison of energy landscapes and convergence across the different runs ( data shown in Supporting Information in S7 Fig ) allow us to conclude that the results presented here are representative of the capabilities of the algorithm and reproducible . | Important human diseases are linked to mutations in proteins . One such protein , Ras , undergoes mutations in over 25% of human cancers . Its biological activity involves switching between two distinct states , and several oncogenic mutations affect this switching . Despite significant investigation in silico via methods based on Molecular Dynamics , details are missing on how mutations affect the ability of Ras to access the states it needs to perform its biological activity . In this paper we present an algorithm that is capable of providing such details by exploring the breadth of the structure space of a given protein . The algorithm leverages information gathered in the wet laboratory on long-lived structures of the healthy/wildtype and mutated versions of a protein to effectively explore its structure space and reconstruct the underlying energy landscape . We apply this algorithm to the wildtype H-Ras and two known oncogenic variants , G12V and Q61L . Comparison of the energy landscapes elucidates the detailed mechanism by which the oncogenic mutations affect biological activity . We provide the algorithm for the research community to allow further investigation of the open question on how mutations to the sequence of a protein affect biological activity . | [
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] | [] | 2015 | Mapping the Conformation Space of Wildtype and Mutant H-Ras with a Memetic, Cellular, and Multiscale Evolutionary Algorithm |
Following recent advances in high-throughput mass spectrometry ( MS ) –based proteomics , the numbers of identified phosphoproteins and their phosphosites have greatly increased in a wide variety of organisms . Although a critical role of phosphorylation is control of protein signaling , our understanding of the phosphoproteome remains limited . Here , we report unexpected , large-scale connections revealed between the phosphoproteome and protein interactome by integrative data-mining of yeast multi-omics data . First , new phosphoproteome data on yeast cells were obtained by MS-based proteomics and unified with publicly available yeast phosphoproteome data . This revealed that nearly 60% of ∼6 , 000 yeast genes encode phosphoproteins . We mapped these unified phosphoproteome data on a yeast protein–protein interaction ( PPI ) network with other yeast multi-omics datasets containing information about proteome abundance , proteome disorders , literature-derived signaling reactomes , and in vitro substratomes of kinases . In the phospho-PPI , phosphoproteins had more interacting partners than nonphosphoproteins , implying that a large fraction of intracellular protein interaction patterns ( including those of protein complex formation ) is affected by reversible and alternative phosphorylation reactions . Although highly abundant or unstructured proteins have a high chance of both interacting with other proteins and being phosphorylated within cells , the difference between the number counts of interacting partners of phosphoproteins and nonphosphoproteins was significant independently of protein abundance and disorder level . Moreover , analysis of the phospho-PPI and yeast signaling reactome data suggested that co-phosphorylation of interacting proteins by single kinases is common within cells . These multi-omics analyses illuminate how wide-ranging intracellular phosphorylation events and the diversity of physical protein interactions are largely affected by each other .
Protein phosphorylation is a reversible , ubiquitous , and fundamentally post-translational modification ( PTM ) that regulates a variety of biological processes; one of its critical roles is the control of protein signaling [1]–[3] . Recent advances in mass-spectrometry ( MS ) –based technologies and phosphopeptide enrichment methods have enabled the use of high-throughput in vivo phosphosite mapping [4]–[7] to identify thousands of phosphoproteins . To date , around 10 , 000 phosphosites of serine , threonine , or tyrosine residues have been identified in each of many organisms , including human [8]–[12] , mouse [13] and yeast [14]–[16] . Many public databases , such as PHOSIDA [17] , Phospho . ELM [18] , and UniProt [19] , have been developed or expanded to catalog such phosphoproteome data . Accordingly , the numbers of phosphoproteins that have been identified in various organisms now greatly exceed the numbers known to have roles in protein signaling . This has raised the question of whether this intracellular phosphorylation , which occurs on such a large scale , has other major roles . In modern biology , the use of high-throughput screening methods has enabled rapid progress in the disclosure of protein–protein interaction ( PPI ) networks in many organisms [20]–[27] . Topological features common to PPI networks ( e . g . , scale-free and small-world properties ) are of prime importance in interpreting intracellular protein behavior and the evolutionary aspects of PPIs [28]–[31] . PTM changes the physical characteristics of proteins . It is therefore probable that reversible PTM has large effects on the dynamic states of intracellular protein-binding patterns and complex formation , and that it controls not only signal transduction but also many other cellular pathways . However , the impact of PTM on the whole picture of the PPI network has not yet been described . Here , we describe the intracellular global relationships between protein phosphorylation and physical PPI , as derived from the results of integrative and systematic data-mining of Saccharomyces cerevisiae multi-omics data ( Fig . 1 ) . New phosphoproteome data on S . cerevisiae were initially obtained by MS–based analysis and unified with data on previously identified phosphoproteomes . We superimposed the unified phosphoproteome data onto a S . cerevisiae PPI network with other multi-omics data on S . cerevisiae . From the results , we infer that the tremendous numbers of phosphorylations within a cell have a large impact on PPI diversity , and that intracellular phosphorylation patterns are affected partly by simultaneous phosphorylation of physically bound proteins that is triggered by the action of single kinases .
On the basis of liquid chromatography ( LC ) -MS analysis , we initially identified 1 , 993 S . cerevisiae phosphoproteins containing 6 , 510 phosphosites . Information on the identified phosphopeptides has been stored in PepBase ( http://pepbase . iab . keio . ac . jp ) . We unified these new phosphoproteome data with the publicly available phosphoproteome datasets of Holt et al . [16] and UniProt [19] and obtained a total of 3 , 477 phosphoproteins containing 25 , 997 phosphosites ( Fig . 2; Supplementary Table S1 ) . The pS/pT/pY ratios of this study , the study of Holt et al . , and UniProt were 72%/23%/5% , 72%/23%/5% , and 80%/18%/2% , respectively . Among the unified phosphoproteome data , 343 phosphoproteins and 2 , 778 phosphosites were not found in the data of Holt et al . or UniProt . Comparison with S . cerevisiae genomic information [32] revealed that 58 . 5% of the 5 , 815 known and predicted genes were phosphoprotein-encoding genes ( Supplementary Table S2 ) . Although the use of current high-throughput technologies cannot disclose the entire phosphoproteome picture of a cell , these results imply that most intracellular proteins can be phosphorylated under the appropriate environmental conditions . The unified phosphoproteome data were superimposed onto the PPI network to generate a “phospho-PPI” network . PPI data were obtained via DIP ( Database of Interacting Proteins ) [33] and grouped into four categories according to the experimental method used for the PPI assay: all kinds of experimental methods ( “ALL” ) , yeast two-hybrid ( “Y2H” ) , co-immunoprecipitation ( “IMM” ) , and tandem affinity purification ( “TAP” ) . Among all the protein nodes involved in every category of the phospho-PPI network , the proportion of phosphoproteins was also nearly 60% ( Supplementary Fig . S1 ) . For example , the phospho-PPI network of the “ALL” category was composed of 4 , 945 proteins , including 2 , 934 phosphoproteins ( 59 . 3% ) and 17 , 215 physical interactions . To explore specific characteristics of the phospho-PPI network , the number counts of interacting partners of phosphoproteins and nonphosphoproteins were analyzed ( note that throughout this study , the word “nonphosphoprotein” means a protein with no phosphosite identified to date ) . We found that , in general , phosphoproteins had more interacting partners than nonphosphoproteins . In each phospho-PPI network of the “ALL” and “Y2H” categories with enough protein nodes for the subsequent statistical analysis , the cumulative percentage distributions of node degrees ( or the number count of interacting partners ) of phosphoproteins and nonphosphoproteins were markedly different ( Fig . 3A and D ) . For example , in the dataset of “ALL” , 47 . 6% of nonphosphoproteins had three or more interacting partners , but this was true for 67 . 9% of phosphoproteins . Moreover , in both datasets , about twice as many phosphoproteins as nonphosphoproteins had 10 interacting partners ( Fig . 3B and E ) . To analyze the statistical significance of this difference in the context of phosphorylation , we prepared randomly generated phospho-PPI networks by “node label shuffling” ( NLS ) , in which the node positions of phosphoproteins and nonphosphoproteins were randomly moved within the phospho-PPI networks ( for details , see Materials and Methods ) . This demonstrated that the node degree of phosphoproteins was significantly higher than expected from a random distribution ( Fig . 3C and F ) . Node degree in PPI networks has an exponential relationship with protein expression level [34]–[36] , perhaps because cellular proteins with more copies have a greater possibility of interacting with others by chance [36] . Therefore , if the phosphoproteome data are biased by protein abundance and highly abundant proteins tend to be identified as phosphoproteins , there is a strong possibility that the relationship between phosphorylation and node degree is spurious , with no direct causal connection . In fact , proteome abundance data obtained through a single-cell proteomic analysis combining high-throughput flow cytometry and a library of GFP-tagged yeast strains [37] showed that the number of phosphoproteins in the “ALL” phospho-PPI was skewed , especially among highly abundant proteins ( Fig . 4A and D ) . However , we demonstrated that in the “ALL” phospho-PPI network there were still significant differences in the node degree levels of phosphoproteins and nonphosphoproteins of similar abundance , and that the differences could be explained independently of protein copy number ( Fig . 4B , C , E and F ) . Similar results were derived from the phospho-PPI network generated only from the “Y2H” category ( Supplementary Fig . S2 ) . We further compared the abilities to predict phosphoproteins by using node degree and protein abundance levels above given thresholds . The predictive power of node degree was markedly higher than that of protein abundance , except in the case of proteins that were extremely abundant ( Supplementary Fig . S3 ) . If this higher predictive ability were attributable to a spurious relationship associated with the actual intracellular proteome abundance , then the node degree of a protein given by PPI assays would appear to provide a better approximation of the intracellular protein copy number than would single-cell proteomic analysis , which is unlikely . Protein disorder is also a typical feature of “hub” proteins in PPI networks [38]–[40] . Parts of unstructured proteins lack fixed structure , and such disordered regions may have the ability to bind multiple proteins and to diversify PPI networks [38]–[40] . Additionally , at the proteome level , phosphorylation occurs at high rates in the disordered regions of proteins [16] , [17] , [41]–[44] . Therefore , it is highly likely that protein disorder affects the node degree difference between phosphoproteins and nonphosphoproteins . For every S . cerevisiae protein registered in UniProt , we calculated the probability of harboring intrinsic disordered regions ( see Materials and Methods ) . In the “ALL” phospho-PPI network , the ratio of phosphoproteins to nonphosphoproteins increased smoothly with increasing disorder probability level ( Fig . 4G ) . However , in the same network , the node degree levels of phosphoproteins and nonphosphoproteins of the same disorder probability level were significantly different ( Fig . 4H and I ) . Even between phosphoproteins that had a low disorder probability of <0 . 1 and nonphosphoproteins that had an extremely high disorder probability of >0 . 9 , the node degree level of the phosphoproteins was significantly higher than that of the nonphosphoproteins ( P = 0 . 0043 ) . Similar results were observed in the “Y2H” dataset ( Supplementary Fig . S2 ) . These results imply that the higher node degree of phosphoproteins than of nonphosphoproteins is at least partly independent of the PPI network diversity produced by unstructured proteins . Other factors that could influence the relationship between protein phosphorylation and interaction are protein size and protein groups with identical cellular function . Larger proteins may have a greater chance of being phosphorylated and may provide more binding domains for interactions with other proteins . However , similar to the results for protein abundance and disorder , statistical significance of the higher node degree of phosphoproteins was observed independently of protein length ( Supplementary Fig . S4 ) . ( Phosphorylation probability was highly correlated with protein length; Supplementary Fig . S4 . ) In the event that both protein phosphorylation and interaction events occurring in a fraction of proteins confer a particular , identical cellular function , then the global difference in node degree levels of phosphoproteins and nonphosphoproteins would appear to be caused only by differences in function . However , we found that , for most functional annotations of S . cerevisiae in GO Slim ( a higher level view of Gene Ontology ) , there was a higher node degree level for phosphoproteins than for nonphosphoproteins ( Supplementary Fig . S5 ) . The average node degree of phosphoproteins is higher than that of nonphosphoproteins [45] , but it was unclear 1 ) whether this characteristic was observable only in hub proteins or whether it existed broadly at the proteome level; and 2 ) whether this was a spurious correlation that had emerged because of the presence of some third factor hidden in the complex and intertwining proteomes . Our results show that , in many cases , this characteristic is present not only in hub proteins but also in proteins that have few interacting partners . They also imply that these protein interactions or binding patterns are not the result of influence by a third factor but are caused by phosphorylation-dependent cellular activities . The additive effect of kinase–substrate and phosphatase–substrate reactions is one possible model for interpreting this phenomenon in the phospho-PPI network . If PPIs include many transient signaling reactions between kinases , phosphatases , and their substrates ( most of which are phosphorylated under certain conditions ) , then the signaling proteins may have interactions additional to the cohesive protein binding interactions in the PPI data . Indeed , some enzyme–protein substrate interactions are surprisingly stable and can be captured in protein interaction assays [46] . However , of the 795 yeast phosphorylation and dephosphorylation reactions for which information has previously been published [47] , only 3 . 9% , 1 . 6% , 2 . 4% , and 0 . 8% overlapped with those in our “ALL , ” “Y2H , ” “IMM , ” and “TAP” PPI datasets , respectively ( Supplementary Fig . S6 ) . [Note , however , that these values were significantly higher than those expected from negative controls of the corresponding PPI networks generated by “random edge rewiring” ( RER ) , and similar , significant overlaps between physical PPI and signaling network were obtained by another group [48]; for details of RER , see Materials and Methods . ] On the other hand , the node degree levels of at least 600 proteins ( >20% of phosphoproteomes in the “ALL” phospho-PPI network ) might have been related to , and affected by , phosphorylation , as evidenced by the cumulative percentage of phosphoproteins , which was more than 20% higher than that of nonphosphoproteins ( Fig . 3A ) . In addition to this , many unidentified phosphoproteins are certain to be present in the nonphosphoprotein dataset . Therefore , it is difficult to interpret such a large difference in the node degree of phosphoproteins and nonphosphoproteins only in terms of the additive effect of signaling reactions , which had such a small overlap with the PPI data . Furthermore , among the GO Slim ontology groups within the “signal transduction” and “cell cycle” categories , which especially include many signaling proteins , there were no great distinctions between the node degree levels of phosphoproteins and nonphosphoproteins ( although the node degree levels for “cytokinesis” and “response to stress , ” like those for most of the other ontology groups , showed marked differences between phosphoproteins and nonphosphoproteins ) ( Supplementary Fig . S5 ) . In the phospho-PPI network , phosphoproteins had a greater tendency than nonphosphoproteins to interact with proteins harboring phosphoprotein binding domains ( PPBDs ) . Out of 10 known PPBDs—14-3-3 , BRCT , C2 , FHA , MH2 , PBD , PTB , SH2 , WD-40 , and WW [49]—six ( BRCT , C2 , FHA , SH2 , WD-40 , and WW ) were present in the member proteins of the “ALL” phospho-PPI network , and the average probabilities that phosphoproteins would interact with proteins that had all PPBDs or each type of PPBD were higher than those for nonphosphoproteins ( Fig . 5 ) . ( The gap between node degree levels of phosphoproteins and nonphosphoproteins was normalized; see Materials and Methods . ) Considering all of these results and perspectives , a reasonable and generalized model that can be used to interpret the higher node degree of phosphoproteins is that reversible and alternative phosphorylation reactions alter the physical characteristics of proteins under various environmental conditions; the interacting or binding partners of phosphoproteins are thereby more diversified than those of nonphosphorylated proteins . Consistent with this interpretation , phosphoproteins harboring at least two phosphosites had more interacting partners than those with a single phosphosite in the phospho-PPI network ( Supplementary Fig . S7 ) , even though phosphoproteins follow a power-law distribution with regard to phosphosite number counts and only a small fraction of phosphoproteins have multiple phosphosites [50] . Protein phosphorylation reactions therefore seem to make a large contribution to intracellular PPI diversity . We further analyzed the phosphorylation patterns of protein pairs forming pair-wise interactions in the phospho-PPI network , and we found that both interacting proteins in each pair tended to be phosphorylated . For every category of phospho-PPI network , three types of pair-wise interactions were counted , whereby “Both , ” “Either , ” or “Neither” of two interacting proteins were phosphorylated . The “Both” and “Neither” types of protein interactions were significantly more common in the real phospho-PPI network than was expected from negative controls produced by RER , whereas the “Either” types of protein interactions were significantly less common than expected ( Fig . 6; Supplementary Fig . S8 ) . Notably , this outcome was independent of whether the node degrees of the phosphoproteins were higher or lower than those of the nonphosphoproteins , because RER does not change the node degree of each protein in a given network [51] . PPI data contain homodimer and heterodimer information that can be captured by experimental assays such as two-hybrid assays [52] . Therefore , to check the possibility that the tendency of interacting proteins to have similar phosphorylation patterns was caused by protein interactions between structurally and sequentially homologous proteins with similar phosphosites , we conducted the same analysis as above but using “filtered” phospho-PPI networks , in which interactions between two homologous proteins were eliminated by E-value cut-offs of 1e–10 in the BLASTP program , but no marked change was observed ( Fig . 6; Supplementary Fig . S8 ) . Proteins involved in signal transduction pathways tend to be phosphorylated , and this is reflected in the PPI data , although the overlaps between such signaling reactions and PPIs are limited ( see above and Supplementary Fig . S6 ) . Another possible interpretation for the multitude of physical interactions between phosphoproteins is that physically binding proteins that are members of the same protein complex tend to be phosphorylated simultaneously by a single enzyme . To search for the protein kinases potentially responsible for the co-phosphorylation of proteins forming the same complex , we analyzed a dataset of kinase–substrate relationships with PPI data of the “ALL” category . In the following analysis , we used 85 and 65 kinases , respectively , from the experimental results of an in vitro kinase–substrate assay [53] and a literature-derived collection of yeast signaling reactions [47] , each having multiple substrates ( Supplementary Table S3 ) . For each kinase , its multiple substrates were superimposed on the PPI network and the number of “interacting kinate modules” ( IKMs , triangle motifs composed of a kinase and its two physically interacting substrates ) ( Fig . 7A ) [53] was counted and compared with those estimated in negative controls of the PPI network produced by NLS and RER . This analysis revealed that three kinases from the in vitro assay and 12 from the literature-based collection had significantly higher IKM formability than those expected from both NLS and RER ( P<0 . 05 ) ( Fig . 7B and C; Supplementary Table S3 ) . Similar results were obtained by using the “filtered” phospho-PPI network ( Supplementary Fig . S9; Supplementary Table S3 ) . Accordingly , we suggest that , when a protein complex and kinase are in close proximity within the intracellular environment , there is a high chance of simultaneous phosphorylation of member proteins participating in the complex . This is consistent with the subcellular co-localization of signaling networks recently revealed through the systematic prediction of signaling networks by using phosphoproteome data with an integrated protein network information derived from curated pathway databases , co-occurring terms in abstracts , physical protein interaction assays , mRNA expression profiles , and the genomic context [48] , and by data analysis of time-course phosphoproteome data [54] . IKMs may enhance the subcellular co-localization of signaling reactions , and/or vice versa . The literature-derived signaling collection is presumably more enriched with well-investigated reactions and thus may more accurately reflect in vivo signaling . This may explain why the collection harbored more kinases with high IKM formabilities ( 12 out of 65 ) than the in vitro kinase–substrate relationship data ( three out of 85 ) . It is plausible that , in living cells , the diversity of protein interactomes ( not only of protein signaling but also of protein complex formation ) is essentially influenced by the large number of phosphorylation events; many reversible phosphorylations might control condition-specific protein binding interactions related to different subcellular processes and molecular machines . On the other hand , protein phosphorylation patterns also seem to depend largely on intracellular protein interaction diversity . It is possible that many of the proteins defined as nonphosphoproteins in this study can actually be phosphorylated under appropriate cellular conditions . Even where this is true , however , the set we defined here as phosphoproteins should be enriched with proteins that are frequently phosphorylated under normal or many different cellular conditions , because the frequently phosphorylated proteins have a higher chance of being identified as phosphoproteins than do the rarely phosphorylated proteins . Accordingly , the features and models discussed in this study should reflect the overall characteristics of phosphoproteins and nonphosphoproteins among a number of different cellular conditions . This is supported by the finding that proteins that had two or more phosphosites physically interacted with more proteins than did those with only a single phosphosite ( Supplementary Fig . S7 ) . Although the quality of current yeast PPI data is also not perfect and the data may include false positives , the observed features with statistical significance should be consequences of the actual behaviors of intracellular proteins , because the effects of such false positives on the statistical tests are supposedly random . The integrative data-mining of yeast multi-omics data has now shed light on the macroscopic and large-scale relationships between phosphoproteomes and protein interactomes . Future comprehensive analyses of the in vivo link between protein phosphorylation and physical interaction will yield more insights into the complex and intertwined molecular systems of living cells .
Saccharomyces cerevisiae strain IFO 0233 cells grown continuously on glucose medium [55] were used . Pelleted cells were vacuum dried and frozen until further analysis . A Bioruptor UCW-310 ( Cosmo Bio , Tokyo Japan ) was used to disrupt the pellets in 0 . 1 M Tris-HCl ( pH 8 . 0 ) containing 8 M urea , protein phosphatase inhibitor cocktails 1 and 2 ( Sigma ) , and protease inhibitors ( Sigma ) . The homogenate was centrifuged at 1 , 500g for 10 min and the supernatant was reduced with dithiothreitol , alkylated with iodoacetamide , and digested with Lys-C; this was followed by dilution and trypsin digestion as described [56] . Digested samples were desalted by using C-18 StageTips [57] . Phosphopeptide enrichment by hydroxy acid–modified metal oxide chromatography ( HAMMOC ) was performed as reported previously [11] , [58] . Briefly , digested lysates ( 100 µg each ) were loaded onto a self-packed titania-C8 StageTip in the presence of lactic acid . After the samples had been washed with 80% acetonitrile containing 0 . 1% TFA , phosphopeptides were eluted by a modified approach using 5% ammonium hydroxide , 5% piperidine , and 5% pyrrolidine in series [59] . An LTQ-Orbitrap XL ( Thermo Fisher Scientific , Bremen , Germany ) coupled with a Dionex Ultimate 3000 ( Germering , Germany ) and an HTC-PAL autosampler ( CTC Analytics AG , Zwingen , Switzerland ) was used for nanoLC-MS/MS analyses . An analytical column needle with a “stone-arch” frit [60] was prepared with ReproSil C18 materials ( 3 µm , Dr . Maisch , Ammerbuch , Germany ) . The injection volume was 5 µL and the flow rate was 500 nL/min . The mobile phases consisted of ( A ) 0 . 5% acetic acid and ( B ) 0 . 5% acetic acid and 80% acetonitrile . A three-step linear gradient of 5% to 10% B in 5 min , 10% to 40% B in 60 min , 40% to 100% B in 5 min , and 100% B for 10 min was employed throughout this study . The MS scan range was m/z 300 to 1500 , and the top 10 precursor ions were selected in MS scans by Orbitrap with R = 60 , 000 for subsequent MS/MS scans by ion trap in the automated gain control ( AGC ) mode; AGC values of 5 . 00e+05 and 1 . 00e+04 were set for full MS and MS/MS , respectively . The normalized collision energy was set at 35 . 0 . A lock mass function was used for the LTQ-Orbitrap to obtain constant mass accuracy during gradient analysis . Both Mass Navigator v1 . 2 ( Mitsui Knowledge Industry , Tokyo , Japan ) and Mascot Distiller v2 . 2 . 1 . 0 ( Matrix Science , London , UK ) were used to create peak lists based on the recorded fragmentation spectra . Peptides and proteins were identified by automated database searching using Mascot Server v2 . 2 ( Matrix Science ) against UniProt/SwissProt v56 . 0 with a precursor mass tolerance of 3 ppm , a fragment ion mass tolerance of 0 . 8 Da , and strict trypsin specificity , allowing for up to two missed cleavages . Carbamidomethylation of cysteine was set as a fixed modification , and oxidation of methionines and phosphorylation of serine , threonine , and tyrosine were allowed as variable modifications . Phosphopeptide identification and phosphorylated site determination were performed in accordance with a procedure reported previously [11] . The false discovery rate was estimated to be 1 . 07% using a randomized database . All annotated MS/MS spectra were stored in PepBase ( http://pepbase . iab . keio . ac . jp ) . Saccharomyces cerevisiae phosphoproteome data were obtained from Dataset S1 of Holt et al . [16] . Another collection of formerly identified phosphoproteins and their phosphosites was obtained from UniProt ( release 15 . 14; http://www . uniprot . org/ ) [19] . All UniProtKB/Swiss-Prot protein entries identified to have at least one phosphosite in high-throughput phosphoproteomics studies were downloaded via the Protein Knowledgebase ( UniProtKB ) in XML format by querying the term scope: “PHOSPHORYLATION [LARGE SCALE ANALYSIS] AT” . Some phosphoproteins registered in UniProt had multiple synonyms of UniProt accession . For integrative analyses and comparisons of yeast multi-omics data , all identities of proteins and genes obtained from different data sources were standardized to UniProt accessions . If objects ( e . g . gene names , ORF names , and/or locus names ) in a data source did not have UniProt accessions , the objects were standardized to their corresponding UniProt accessions according to the cross-reference list prepared from UniProtKB/Swiss-Prot protein entries obtained from UniProt ( release 15 . 14 ) . In cases when an object corresponded to multiple synonyms of UniProt accessions , all accessions were used to identify its corresponding objects in other data sources . The phosphoproteome data newly identified in this study and the former phosphoproteome datasets obtained from Holt et al . and UniProt were unified according to their UniProt accessions . Positions of phosphosites and their amino acid residues in the unified phosphoproteome data were double-checked by using the proteome sequences obtained from UniProt ( release 15 . 14 ) . From SGD ( Saccharomyces Genome Database; http://yeastgenome . org ) [32] , annotations of 5 , 815 known and predicted genes were obtained . ORF names of genes were checked by using the unified phosphoproteome data to determine whether the encoded protein was identified as a phosphoprotein . The S . cerevisiae PPI network was obtained as XML files ( Scere20081014 ) from DIP ( Database of Interacting Proteins; http://dip . doe-mbi . ucla . edu ) [33] . We eliminated each interaction entry including three or more “interactors” ( e . g . , in which multiple prey proteins were detected for one bait protein in one experimental assay ) and used only those including two “interactors . ” Every node in the PPI network was labeled by its corresponding UniProt ID provided in the same XML file . For the PPI assay , PPI data were further grouped into four categories: all kinds of experimental methods ( “ALL” ) , yeast two-hybrid ( “Y2H” ) , co-immunoprecipitation ( “IMM” ) , and tandem affinity purification ( “TAP” ) . A “filtered” PPI network was also prepared for each category by eliminating interactions between two similar proteins by using the BLASTP program and an E-value cut-off of 1e–10 . Unified phosphoproteome data were mapped onto every category of PPI data prepared from DIP according to their UniProt accessions , and a phospho-PPI network was generated . Throughout this study , proteins that did not correspond to phosphoproteome data were termed “nonphosphoproteins . ” To prepare negative controls for PPI and phospho-PPI networks , two different processes ( as diagrammed in Fig . 1 ) were appropriately adopted on a case-by-case basis . “Node label shuffling” ( NLS ) swaps the labels of two randomly selected nodes in a given network; it repeats this operation a sufficient number of times until all pair-wise interactions in the queried network have disappeared or until the number of iterations reaches 1 , 000 times the number of interactions . “Random edge rewiring” ( RER ) randomly selects two edges in a given network and randomly rewires them . During this process , each rewiring operation is retried if a pair of nodes redundantly wired by two edges occurs in the network; the iteration termination condition is the same as that of NLS . Proteome abundance data for S . cerevisiae that were previously acquired through a single-cell proteomics analysis combining high-throughput flow cytometry and a library of GFP-tagged strains [37] were used to analyze the characteristics of protein expression in the phospho-PPI network . These data were composed of proteome abundance data measured for cells grown in rich ( YEPD ) and synthetic complete ( SD ) medium . For each cell growth condition , protein names were standardized to UniProt accessions , and protein abundance levels were log-transformed ( base 10 ) and superimposed on each of the phospho-PPI networks of “ALL” and “Y2H . ” In this case , protein nodes for which the abundance levels were not provided in the abundance data were deleted from the phospho-PPI network . The protein disorder level of every S . cerevisiae protein registered in UniProt ( release 15 . 14 ) was predicted by the POODLE-W program , which uses the support vector machine–based learning of amino acid sequences of structurally confirmed disordered proteins [61] . For the analysis , we used the “disorder probability” ( i . e . the probability that a given protein is unstructured ) output by this program . Saccharomyces cerevisiae gene annotations belonging to “molecular function , ” “biological process , ” or “cellular component” of GO Slim , a higher level view of S . cerevisiae Gene Ontology ( GO ) , were downloaded via the SGD ftp site . Information on S . cerevisiae proteins , each of which has at least one of 10 known phosphoprotein binding domains ( PPBDs ) , namely 14-3-3 , BRCT , C2 , FHA , MH2 , PBD , PTB , SH2 , WD-40 , and WW [49] , was obtained according to the protein domain annotations of UniProt ( release 15 . 14 ) , which were provided by other protein databases . To evaluate the tendencies of phosphoproteins and nonphosphoproteins to interact with proteins that had PPBDs , the normalized probabilities of such interactions were defined . For each protein , the number of interacting protein partners that had PPBDs was divided by the number of all interacting partners . To find possible IKMs , kinases previously reported to phosphorylate multiple substrates were obtained from data on in vitro substrates recognized by most yeast protein kinases that were measured with the use of proteome chip technology [Supplementary Data 2 of Ptacek et al . [53]] , as well as from a literature-derived collection of documented yeast signaling reactions [Table S3 of Fiedler et al . [47]] . All gene names of substrates in the in vitro kinase–substrate relationship data and ORF names of substrates in the literature-derived collection were standardized into UniProt accessions and linked to proteins in the “whole” and “filtered” PPI networks of the “ALL” category . The statistical significance of differences in a single real value from a group of repeatedly generated random values was estimated by calculating the proportion of random values equal to the real value or more ( or less , in certain instances ) . The Wilcoxon–Mann-Whitney rank sum was used to assess statistical significance between groups . | To date , high-throughput proteome technologies have revealed that hundreds to thousands of proteins in each of many organisms are phosphorylated under the appropriate environmental conditions . A critical role of phosphorylation is control of protein signaling . However , only a fraction of the identified phosphoproteins participate in currently known protein signaling pathways , and the biological relevance of the remainder is unclear . This has raised the question of whether phosphorylation has other major roles . In this study , we identified new phosphoproteins in budding yeast by mass spectrometry and unified these new data with publicly available phosphoprotein data . We then performed an integrative data-mining of large-scale yeast phosphoproteins and protein–protein interactions ( complex formation ) by an exhaustive analysis that incorporated yeast protein information from several other sources . The phosphoproteome data integration surprisingly showed that nearly 60% of yeast genes encode phosphoproteins , and the subsequent data-mining analysis derived two models interpreting the mutual intracellular effects of large-scale protein phosphorylation and binding interaction . Biological interpretations of both large-scale intracellular phosphorylation and the topology of protein interaction networks are highly relevant to modern biology . This study sheds light on how in vivo protein pathways are supported by a combination of protein modification and molecular dynamics . | [
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"computational",
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] | 2011 | Integrative Features of the Yeast Phosphoproteome and Protein–Protein Interaction Map |
Gametophytic development in Arabidopsis depends on nutrients and cell wall materials from sporophytic cells . However , it is not clear whether hormones and signaling molecules from sporophytic tissues are also required for gametophytic development . Herein , we show that auxin produced by the flavin monooxygenases YUC2 and YUC6 in the sporophytic microsporocytes is essential for early stages of pollen development . The first asymmetric mitotic division ( PMI ) of haploid microspores is the earliest event in male gametophyte development . Microspore development in yuc2yuc6 double mutants arrests before PMI and consequently yuc2yuc6 fail to produce viable pollens . Our genetic analyses reveal that YUC2 and YUC6 act as sporophytic genes for pollen formation . We further show that ectopic production of auxin in tapetum , which provides nutrients for pollen development , fails to rescue the sterile phenotypes of yuc2yuc6 . In contrast , production of auxin in either microsporocytes or microspores rescued the defects of pollen development in yuc2yuc6 double mutants . Our results demonstrate that local auxin biosynthesis in sporophytic microsporocytic cells and microspore controls male gametophyte development during the generation transition from sporophyte to male gametophyte .
Life cycle of eukaryotes alternates between haploid and diploid generations . The alternation of generations is initiated by meiosis ( 2n to 1n ) and gamete fusion ( 1n to 2n ) [1] . In land plants , the multicellular diploid generation is called sporophyte , whereas the multicellular haploid organism is named gametophyte . In bryophytes ( mosses and liverworts ) , haploid gametophyte is the dominant generation and represents the main plant . In vascular plants , including ferns , gymnosperms , and angiosperms , the diploid sporophyte generation is dominant , whereas the gametophyte generation is much reduced [1] . For example , in seed plants , both the female and male gametophytes develop within the sporophyte . Understanding the molecular mechanisms governing the generation alternation will impact fundamental plant biology and plant breeding . Pollen grains , which are the male gametophyte in seed plants , are developed in locules encircled by four sporophytic cell layers: tapetum , middle layer , endothecium , and epidermis . Inside a locule , a diploid male meiocyte divides into a tetrad of four haploid microspores after meiosis [2 , 3] . Each microspore then undergoes an asymmetric cell division ( pollen mitosis I ( PMI ) ) , resulting in two structurally and functionally different daughter cells: the small generative cell and the large vegetative cell . The generative cell divides one more time ( PMII ) to produce two sperm cells whereas the vegetative cell no longer divides . The mature pollen grain contains two haploid sperm cells and one haploid vegetative cell [3 , 4] . Genetic analyses have identified a number of genes that play important roles in pollen development [5] . These genes can be classified into two categories: gametophytic or sporophytic genes . Pollen development depends on coordinated expression of both sporophytic genes and gametophytic genes [3] . Most of the identified gametophytic genes are related to cell division and differentiation . For example , MOR1 , a member of the microtubule-associated protein 215 ( MAP215 ) , is involved in the PMI asymmetric cell division [6 , 7] . In the mor1/gem1 mutants , defects in microspore nucleus migration lead to altered division plane , and the formation of two equal- or similar sized cells [6 , 7] . Genes including Two-in-one ( TIO ) , GAMMA-TUBULIN 1 ( TUBG1 ) and 2 essential for phragmoplast formation , localization and/or expansion , also affect male gametophyte development . Mutations in these genes cause incomplete cytokinesis in PMI and result in failure to produce the generative cell [8–13] . Several cell cycle factors have also been reported to be important for pollen mitosis . ICK4/KRP6 ( Interactors of Cdc2 kinase 4/kip-related protein 6 ) is a cyclin-dependent kinase inhibitor . Timely degradation of ICK6/KRP6 by RHF1a/2a and SCFFBL17 E3 ligase is essential for the progression of pollen mitosis [14–16] . Cyclin-dependent kinase D ( CDKD ) was recently found to be essential for pollen mitosis . In the cdkd;1–1 cdkd;3–1 double mutants , microspore is defective in both PMI and PMII [17] . A main feature of the male gametophytic genes is that no viable mutant pollens can be generated and that no homozygous diploid mutants are available . Sporophytic genes for pollen formation represent the contribution of sporophytic tissues including tapetum and microsporocyte for male gametophyte development . Tapetum directly provides pollen wall materials and nutrients including Magnesium for pollen development [18–22] . A series of transcription factors including DYT1 , TDF1 , AMS , MYB33/65 , MS188/MYB80/MYB103 , and MS1 have been shown to play essential roles in normal development of tapetum [23–32] . The defective tapetum caused by mutations in these genes results in pollen wall defects and leads to complete pollen abortion [23–32] . Enzymes involved in outer pollen wall formation are also expressed in tapetum and are essential for pollen development [33–41] . The pollen wall pattern is determined inside a tetrad that depends on the sporophytic genes expressed in microsporocytes , such as RPG1 , NPU , NEF and DEX1 [42–45] . The sporophytic cells including tapetum and microsporocyte supply material and nutrients for pollen development and determine the pollen wall pattern . Unlike gametophytic genes , viable mutant pollen can be produced from heterozygous mutant plants , and homozygous mutant plants can be obtained . However , homozygous diploid mutants cannot produce viable pollens . Plant hormones are essential for normal plant development . However , it is not clear whether plant hormones or other signaling molecules produced in sporophytic tissues are required for the development of male gametophyte . The plant hormone auxin plays critical roles in nearly all aspects of plant development including embryogenesis , organogenesis , gametophyte development , and various tropisms [46] . It is known that disruption of either auxin biosynthesis , or polar transport , or signaling causes defects in male gametophyte development and pollen formation . Indole-3-acetic acid ( IAA ) , the primary natural auxin in plants , is mainly synthesized through a TAA/YUC two-step tryptophan-dependent pathway [47–51] . Simultaneously disruption of both YUC2 and YUC6 completely eliminates the production of viable pollen grains [49] . It was reported that the two atypical members of the PIN auxin efflux carriers , PIN5 and PIN8 , which are believed to regulate intracellular auxin homeostasis and metabolism in pollen , also participate in the development of normal pollen morphology [52 , 53] . Other auxin transporters including ATP-BINDING CASSETTE B19 ( ABCB19 ) /MULTIDRUG RESISTANCE PROTEIN 1 ( MDR1 ) / P-GLYCOPROTEIN 19 ( PGP19 ) and ABCB1/ PGP1 also play important roles in pollen development [54 , 55] . The abcb1 abcb19 double mutants show precocious pollen maturation [54 , 55] . Similar precocious pollen maturation takes place in tir1 afb2 afb3 triple and tir1 afb1 afb2 afb3 quadruple mutants , which are defective in auxin perception [54] . It is known that auxin biosynthetic , transport , and signaling genes are expressed during pollen development [49 , 54] . Previous studies have clearly demonstrated that auxin is required for anther development and pollen formation [49 , 52–55] , but it was not understood the role of auxin for pollen development and in the transition from sporophytic generation to gametophyte generation . It was previously proposed that auxin produced in tapetum is required for pollen development [56] . Here we report that pollen development in the auxin biosynthetic mutants yuc2yuc6 failed to progress past the PMI , which is an early step in male gametophyte growth . Our genetic analyses demonstrated that both YUC2 and YUC6 function as sporophytic genes . We further show that auxin produced in sporophytic microsporocytes rather than tapetum is required for the early stages of pollen development , demonstrating that auxin produced in the diploid sporophytic cells plays a critical role in the haploid male gametophyte development .
We previously showed that yuc2yuc6 double mutants were male sterile , and the expression of the bacterial auxin biosynthetic gene iaaM under the control of the YUC6 promoter fully restored the fertility of yuc2yuc6 , indicating that the fertility defects of yuc2yuc6 were caused by partial auxin deficiency during anther development [49] . The auxin reporter DR5-GFP/GUS has been previously detected in anther from flower stages 10 to 12 [54 , 57 , 58] . It has also been reported that the DR5 activity is decreased in the yuc6 single mutant , although yuc6 did not display obvious reproductive defect [58] . To better understand the distribution patterns of DR5 in anthers of yuc2yuc6 , we introduced the auxin reporter DR5-GFP into yuc2yuc6 plants and compared the GFP signals in yuc2yuc6 with those in WT plants . Consistent with previous findings [54 , 57 , 58] , GFP signals in WT plants were detected in anthers from anther stages 9 to 12 ( all the stages refer to anther stages in our results ) ( Fig 1A ) . The expression pattern of DR5-GFP in yuc2 and yuc6 anthers was similar to that in WT ( S1 Fig ) . However , no substantial signals were detected in yuc2yuc6 anthers at the same developmental stages ( Fig 1B ) . We also introduced the DR5-GUS into the yuc2yuc6 background . Similar to the DR5-GFP patterns , GUS signals were not detected in the yuc2yuc6 anthers ( S1 Fig ) . Therefore , it appears that YUC2 and YUC6 are the main auxin biosynthetic genes responsible for auxin production during anther development . Because we hardly observed any DR5-GFP signal in pollen , we used DII and mDII auxin reporter lines as a proxy to determine the pattern of auxin-induced degradation of Aux/IAA repressors during pollen development [59] . We replaced the 35S promoter with the microspore-specific promoter proMSP1 to drive the DII-VENUS and mDII-VENUS expression units [60] . Our results showed that fluorescence signals in microspores/pollens of proMSP1:DII-VENUS transgenic plants were weaker than that in proMSP1:mDII-VENUS transgenic plants at stage 10 ( proMSP1:DII-VENUS/proMSP1:mDII-VENUS = 0 . 45 ) and at stage 11 ( proMSP1:DII-VENUS/proMSP1:mDII-VENUS = 0 . 54 ) ) ( Fig 2A and 2B ) . The results of the auxin response reporters are indicative that auxin accumulated significantly in unicellular microspores and bicellular pollens . To investigate whether signals of the auxin response reporters are correlated with the expression patterns of YUC2 and YUC6 , we generated proYUC2-GFP and proYUC6-GFP transgenic plants . We found that both YUC2 and YUC6 were weakly expressed in microsporocytes , tetrad and microspores at stage 9 ( S2A , S2B , S2C , S2I , S2J and S2O Fig ) and strongly expressed in microspores from stages 10 to 13 ( S2D–S2G and S2K–S2N Fig ) . We also found that YUC2 and YUC6 were strongly expressed in somatic cell layers including tapetum cells in anther ( S2H , S2I and S2O Fig ) . The yuc2yuc6 double mutants showed markedly reduced fertility with few viable pollen inside the locule [49 , 54] . Pollination of the yuc2yuc6 pistil with WT pollen resulted in F1 plants with normal fertility ( ~50 seeds produced in each silique , n = 4 ) , indicating that the female fertility of yuc2yuc6 was unaffected . Alexander staining was performed to understand the defects of pollen development in yuc2yuc6 . Similar to those in wild type ( WT ) , the anthers of yuc2 and yuc6 single mutants contained purple-stained viable pollen grains ( Fig 3A–3C ) . Consistent with previous reports [49] , Fig 3D showed that the yuc2yuc6 anthers did not produce viable pollens ( Fig 3D ) . We then generated anther cross sections and used transmission electron microscopy to determine in which stage ( s ) the anther and pollen developmental defects took place in yuc2yuc6 . We noticed that a normal tetrad was produced in yuc2yuc6 ( Fig 3E and 3K ) , suggesting that the meiotic division progressed normally . After release from the tetrad , microspore development in yuc2yuc6 appeared similar to that of WT from stages 8 to 9 ( Fig 3F , 3G , 3L , 3M , 3Q , 3R , 3V and 3W ) . However , at stage 10 , WT microspores became vacuolated and contained a polarized nucleus ( Fig 3H and 3S ) , whereas yuc2yuc6 microspores had an irregular shape and started to degenerate ( Fig 3N and 3X ) . From stages 11 to 12 , WT microspores underwent the first mitotic division and gradually developed into mature pollen ( Fig 3I , 3J and 3T ) . In yuc2yuc6 , microspores were severely degenerated and failed to form normal pollen ( Fig 3O , 3P and 3Y ) . The pollen wall of yuc2yuc6 appeared normal as compared with that of WT ( Fig 3U and 3Z ) . To obtain further insight into the microgametogenesis defects of yuc2yuc6 , we stained nuclei with 4’ , 6-diamidino-2-phenylindole ( DAPI ) in developing pollen . The microspores of yuc2yuc6 were similar to WT microspores at stages 8 to 9 ( Fig 4A , 4B , 4F and 4G ) . However , at stage 10 , some of the yuc2yuc6 microspores were degenerated , with little DAPI staining signal ( Fig 4H right ) . At this stage , some normal yuc2yuc6 microspores with a nucleus located at one side of the microspore were still visible ( Fig 4C and 4H left ) . Overall during the unicellular stage ( from stages 8 to 10 ) , most of the single haploid cells in both the WT ( 92 . 7% ) and yuc2yuc6 ( 67 . 9% ) showed a bright nucleus ( Fig 4A–4C , 4F–4H and 4K ) , and about 30% of the microspores in yuc2yuc6 were degenerated ( Fig 4H right , 4K ) . After PMI , 91 . 1% of the WT microspores divided asymmetrically , producing a large vegetative cell and a small generative cell engulfed in the cytoplasm of the vegetative cell ( Fig 4D and 4K ) , which is called the bicellular stage . In contrast , only about 2 . 2% of the yuc2yuc6 microspores progressed past PMI to reach the bicellular stage ( Fig 4K ) . Approximately 44 . 8% of the microspores in yuc2yuc6 remain arrested at the unicellular stage ( Fig 4I left , 4K ) , and the rest ( 53% ) became degenerated ( Fig 4I right , 4K ) . At the tricellular stage , WT microspores fully developed into tricellular pollen , whereas yuc2yuc6 microspores ( 96% ) became completely degenerated or still contained a very loosely packed DNA mass ( Fig 4E , 4J and 4K ) . Therefore , we conclude that mutations in YUC2 and YUC6 lead to the defects in early stages including PMI of pollen development . We performed genetic complementation to determine whether mutations in the YUC genes are responsible for the sterile phenotype of yuc2yuc6 . The DNA fragment including about 2 kb upstream sequence of YUC2 and the YUC2 open reading frame ( ORF ) was fused with GFP ( named proYUC2:YUC2-GFP ) and the construct was introduced into yuc2-/- yuc6+/- plants ( S3 Fig ) . Two independent lines of yuc2yuc6 that contained the proYUC2:YUC2-GFP transgene were identified in T1 generation . Both lines of proYUC2:YUC2-GFP in the yuc2yuc6 background had normal fertility ( S3B Fig ) . Alexander staining and DAPI staining results indicated that YUC2 could rescue the pollen development defects of yuc2yuc6 ( S3C and S3D Fig and S5 Fig ) . The results also demonstrated that the YUC2-GFP fusion is functional . From our phenotypic analysis , it was clear that the yuc2yuc6 double mutants were defective in gametophyte development . Gametophyte development depends on the expression of both sporophytic and gametophytic genes . To determine whether YUC2 and YUC6 function as sporophytic or gametophytic genes , we analyzed the male transmission efficiency of yuc2yuc6 . We used yuc2-/-yuc6+/- and yuc2+/-yuc6-/- plants as pollen donors to cross with WT plants . PCR genotyping revealed that approximately 50% of F1 progeny contained the yuc2yuc6 mutations ( Table 1 ) , suggesting that yuc2yuc6 microspores were transmitted normally . We next analyzed the segregation ratio of self-fertilized yuc2-/-yuc6+/-and yuc2+/-yuc6-/- plants . Consistent with the normal transmission efficiency , the segregation displayed a typical Mendelian ratio ( 3:1 ) in both cases ( n>290 for each case ) . These results showed that YUC2 and YUC6 are sporophytic genes for pollen development , indicating that auxin produced in the sporophytic tissues by the YUCs is required for normal male gametophyte development . It is known that YUC2/6 mRNA is expressed in meiocytes , microspores , tapetum , middle layer , and endothecium in anthers [54] . To investigate the source of auxin for pollen development , we used various promoters to drive the expression of YUC2-GFP fusion , which we have shown functional ( S3 Fig ) . The DR5 auxin reporter line showed an extremely active auxin response in the tapetum cells during late developmental stages in Arabidopsis [54 , 56 , 58] . It was proposed that auxin is transported from tapetum cells into developing pollens [56] . To investigate whether the YUC genes expressed in tapetum are responsible for regulating microspore development and pollen formation , we generated transgenic lines that express YUC2-GFP in tapetum cells using specific tapetum promoters ( proA9 and proATA7 ( ARABIDOPSIS THALIANA ANTHER7 ) ) in the yuc2yuc6 background [32 , 61 , 62] ( Fig 5 and S4 Fig ) . We found that both proA9: YUC2-GFP ( yuc2yuc6 ) ( n = 6 ) and proATA7:YUC2-GFP ( yuc2yuc6 ) ( n = 7 ) T1 transgenic plants were still sterile ( Fig 5B and S4 Fig ) . The pollen defects in yuc2yuc6 were not rescued by the YUC2-GFP transgene ( Fig 5C , S4 and S5 Figs ) . We investigated whether the tapetum-specific promoters behaved as designed . RNA in situ hybridization data showed that YUC2-GFP was significantly transcribed in tapetum cells from microsporocytes stage to early microspore stage in proA9:YUC2-GFP ( yuc2yuc6 ) plants ( Fig 5D ) . The GFP signal in proA9:YUC2-GFP ( yuc2yuc6 ) plants appeared in the tapetum layer at stages 8 and 9 ( Fig 5E showed stage 9 ) . Although the GFP fluorescence of proATA7:YUC2-GFP ( yuc2yuc6 ) plants could not be detected ( S4 Fig ) , the YUC2-GFP transcripts were detected in tapetum layer at stage 8 ( S4 Fig ) . To rule out the possibility that the ATA7 promoter was too weak to drive adequate expression of YUC2-GFP in anther , we used real-time quantitative RT-PCR to analyze the transcript levels of YUC2 in WT and YUC2-GFP in the transgenic plants . The expression levels of YUC2-GFP in all of the analyzed transgenic plants were similar to or higher than YUC2 expression in WT ( S5 Fig ) . These results suggest that the ATA7 and A9 promoters were able to drive YUC2-GFP expression in tapetum , but auxin production in tapetum is not sufficient to overcome the auxin deficiency in yuc2yuc6 microspores . We next used promoters specific for microsporocytes and microspores ( proARF17 ) [63] to drive the expression of YUC2-GFP in yuc2yuc6 plants ( Fig 6 ) . All of the 5 independent T1 proARF17:YUC2-GFP ( yuc2yuc6 ) lines showed almost complete rescue of the sterile phenotypes of yuc2yuc6 ( Fig 6A ) . In addition , the pollen defects were fully rescued in the transgenic plants ( Fig 6A and S5 Fig ) . In the transgenic plants , YUC2-GFP expression was observed in microsporocytes and was significant in early stages of microspores ( Fig 6A ) . Fig 6A also showed that the YUC2-GFP protein accumulated in early stages of microspores . Because ARF17 promoter drives gene expression in both microsporocytes and microspores , we further tested whether localized auxin biosynthesis in microspores is sufficient to rescue yuc2yuc6 . We used the promoter proLAT52 , which is specifically activated in male gametophyte [14 , 64] , to drive the expression of YUC2-GFP in yuc2yuc6 plants ( Fig 6B ) . All of the 6 independent T1 proLat52:YUC2-GFP ( yuc2yuc6 ) lines showed partial rescue of the fertility defects of yuc2yuc6 ( Fig 6B ) . The proLat52:YUC2-GFP ( yuc2yuc6 ) plants were fertile at a late reproductive development stage ( Fig 6B ) . During late reproduction development , 30% to 70% of the pollen in the transgenic lines appeared normal in the anthers ( Fig 6B and S5 Fig ) . At bicellular stage , 70 . 7% of the unicellular pollen can develop into bicellular pollen , and 18% of the microspores are arrested at unicellular stage . At tricellular stage , proLat52:YUC2-GFP ( yuc2yuc6 ) produced 56 . 9% tricellular pollens , and 31 . 8% pollens were aborted ( Fig 6B and S5 Fig ) . These results indicated that proLat52:YUC2-GFP could partially support the microspores development past PMI and PMII . In the proLat52:YUC2-GFP ( yuc2yuc6 ) transgenic plants , YUC2-GFP was transcribed from late stages of microspores ( Fig 6B ) . Meanwhile , YUC2-GFP protein was detected in pollen at stage 13 ( Fig 6B ) . The observation that auxin produced in microspores partially rescued the sterile phenotype of yuc2yuc6 suggested that early stages of pollen development including PMI of unicellular microspores require auxin . The sterility rescue efficiencies of proARF17:YUC2-GFP ( yuc2yuc6 ) and proYUC2:YUC2-GFP ( yuc2yuc6 ) ( S3 Fig ) were significantly higher than that in proLat52:YUC2-GFP ( yuc2yuc6 ) transgenic plants . We noticed that the expression of YUC2-GFP or GFP was at earlier stage of microspores in proARF17:YUC2-GFP ( yuc2yuc6 ) and in proYUC2:GFP ( S2 Fig ) than that in proLat52:YUC2-GFP ( yuc2yuc6 ) transgenic plants ( Fig 6 ) . Therefore , it is likely that auxin may be required at early phase of microspore development . Combined with the genetic data that YUC2 and YUC6 act as sporophytic genes , we conclude that the auxin synthesized in the sporophytic microsporocytes is essential for early stages of pollen development in plants . Therefore , auxin produced in sporophyte contributes to male gametophyte during the generation alternation in plant .
Both YUC2 and YUC6 are known required for pollen development and the yuc2yuc6 double mutants are male sterile . Here we further defined that the male sterility of yuc2yuc6 is caused by defects in early stages of pollen development including the first mitotic cell division ( PMI ) of microspores . Moreover , we show that early stages of microspore development and PMI require auxin produced in the diploid sporophytic microsporocytes , indicating that sporophytic cells not only provide nutrients and cell wall materials for pollen development , but also supply hormone and signaling molecules to haploid cells . Our results also demonstrate that different sporophytic cells play different roles in male gametophytic development . Tapetum cells provide nutrients , but auxin produced in tapetum cells is not sufficient to support early stages of pollen development . In contrast , auxin synthesized in sporophytic microsporocytes is necessary and sufficient for male gametophytic development . Because yuc2yuc6 double mutants could undergo meiosis successfully and our results showed that supply of auxin after meiosis could partially rescue the pollen defects of yuc2yuc6 ( Fig 6 , ProLat52:YUC2-GFP ( yuc2yuc6 ) ) , we conclude that auxin produced by YUC2 and YUC6 may not be required for male meiosis . Following meiosis , the microspore undergoes two rounds of mitosis to form mature pollen during anther development . PMI is the first round of mitosis for pollen formation . Several lines of evidence show that auxin produced by YUCs is essential for PMI . We showed that YUC2 and YUC6 are the main enzymes responsible for auxin synthesis in anther based on the expression of the auxin reporter DR5:GFP/GUS ( Fig 1 and S1 Fig ) . Our results are consistent with previous studies showing DR5 activity in anthers possibly resulting from auxin synthesis [54] . Secondly , we found that the microspores of yuc2yuc6 were aborted and degenerated before PMI and failed to form mature pollen ( Fig 3 and Fig 4 ) . Consistent with this phenotype , we found significant AUX/IAA degradation , which is presumably induced by auxin , in unicellular microspores judging from the expression of the modified DII-Venus reporter ( Fig 2 ) . Lastly , we revealed that YUC2-GFP expressed in microspores at early gametophyte stages could partially rescue the yuc2yuc6 pollen defect ( Fig 6 , ProLat52:YUC2-GFP ( yuc2yuc6 ) ) . These results demonstrated that auxin is required for early stages of pollen development . Because most of the microspores in yuc2yuc6 were arrested prior to PMI , we could not exclude the possibility that auxin is also required in subsequent steps such as PMII . Auxin regulates plant development mainly through auxin response factors ( ARFs ) . Among the ARF genes , ARF6 , ARF8 , ARF10 , ARF16 , and ARF17 are expressed in unicellular microspores [65] . The arf17 mutant shows defective pollen formation [63] , suggesting that auxin synthesized by YUCs may control male gametophyte development through ARF17 . However , we noticed that pollen development defects in arf17 and yuc2yuc6 were not the same . The arf17 mutants displayed defective pollen coat formation whereas it was not the case for yuc2yuc6 . Therefore , we believe that ARF17 may have unique functions in the earlier stages of pollen development that do not overlap with those of YUC2 and YUC6 , such as controlling of the morphogenesis of pollen wall . It was reported that pollen development in tir1 afb1 afb2 afb3 quadruple mutants was not significantly compromised , an observation that was quite different from the severe pollen defects found in yuc2yuc6 . It is puzzling that disruption of auxin signaling and auxin biosynthesis resulted in different phenotypes . It was known that some of the tir1 afb1 afb2 afb3 plants can survive and produce seeds , but auxin transport mutants such as pin1 and auxin biosynthesis mutants including yuc1yuc4 were completely sterile [49 , 66] . It is likely that other AFB proteins such as AFB4 and AFB5 may compensate the loss of tir1 afb1 afb2 afb3 . In addition , we noticed that afb1 and afb3 in the quadruple mutants still produced truncated transcripts and might have produced residual protein activities [67] . The fact that tir1 afb1 afb2 afb3 were not a complete null in auxin receptor may account for the observed paradoxical results . AFB5 is expressed in bicellular pollens ( S1 Table ) . Analysis of higher order tir1 afb mutants may clarify why auxin signaling mutants behaved differently from auxin biosynthesis and transport mutants . Most of the known functions of auxin in flowering plants are related to sporophyte generation , which is the dominant generation . The auxin pathways are evolutionary conserved in the plant kingdom . The homologs of auxin biosynthetic genes such as TAAs and YUCs are also used for auxin biosynthesis in moss Physcomitrella patens and Liverwort Marchantia polymorpha [68 , 69] , whose haploid gametophyte is the dominant generation . In liverwort , auxin synthesized by YUCs is essential for normal gametophyte development and dormancy [69] , implying that auxin may also play essential roles in gametophyte generation in flowering plants . However , it is difficult to study the roles of auxin in male gametophyte development because male gametophyte has been reduced to several cells within the diploid sporophyte . Our detailed analysis of the auxin biosynthetic mutants yuc2yuc6 revealed that auxin is required for male gametophyte development . More importantly , we show that auxin produced in microsporocytes , which are sporophytic cells , is necessary for normal progression of the haploid microspores . Our genetic data suggest that YUC2 and YUC6 affect early stages of pollen development mainly via a sporophytic effect , implying that auxin required for pollen development may be synthesized by YUC2 and YUC6 in sporophytic anther tissues . These data are consistent with the transcription patterns of YUC2 and YUC6 in microsporocytes , microspores and anther somatic cell layers at premeiotic and meiotic stages [54] . In anther , tapetum cells and microsporocytes are closely related sporophyte cells involved in microspore/male gametophyte development . It was proposed that auxin could be transported to developing pollen from tapetum cells [56] . However , the expression of YUC2 in the tapetum cell of yuc2yuc6 could not lead to viable pollen ( Fig 5 and S4 Fig ) , suggesting that the auxin from tapetum is not sufficient to support pollen development . On the other hand , the expression of YUC2-GFP in microsporocytes completely rescued the sterility phenotypes of yuc2yuc6 ( Fig 6 ) , demonstrating that auxin synthesized in microsporocytes is sufficient for pollen development . We propose that auxin production in diploid microsporocytes is necessary and sufficient for the early stages of the development of the haploid cells during pollen development . Our conclusion is mainly based on two observations: 1 ) YUC2 and YUC6 are sporophytic genes and the yuc2yuc6 fail to produce viable pollen; 2 ) expression of YUC2 driven by specific promoters rescued yuc2yuc6 ( Fig 6 ) . The ARF17 promoter is active in both microsporocytes ( sporophytic ) and microspores ( gametophytic ) ( Fig 6 ) . Therefore , it is conceivable that the rescued yuc2yuc6 phenotypes by YUC2-GFP driven by ARF17 promoter were caused by ectopic auxin production in the haploid microspores . However , from our genetic analysis , it is clear that viable and fully functional pollen that lacks YUC2 and YUC6 can be produced from yuc2-/-yuc6+/- or yuc2+/-yuc6-/- , demonstrating that auxin does not have to be produced in microspores for the development of viable pollen . Rather auxin produced by YUCs in sporophytic cells ( microsporocytes to be exact ) is sufficient to guide the progressive development of microspores . Microsporocytes developing into mature pollen through PMI and PMII is a continuing process . Production of auxin in microsporocytes is an efficient way to regulate newly formed microspores to undergo PMI and other processes of early male gametophyte development . Using two different diploid cell types ( tapetum and microsporocytes ) to provide nutrients and hormonal signals for male gametophyte development may also be advantageous in terms of efficiency and specificity .
All plants used in this study were in the Columbia-0 genetic background . The yuc2yuc6 mutants have been described previously [49] . All relevant primer sequences were listed in S2 Table . The DII-VENUS ( N799173 ) and mDII-VENUS ( N799174 ) seeds were ordered from the European Arabidopsis Stock Centre ( NASC ) . Plants were grown under long-day conditions ( 16 hr light/8 hr dark ) in a ~22°C growth room . The DR5:GFP and DR5:GUS reporter lines were introduced into yuc2yuc6 by genetic cross . Plants were photographed using a Nikon digital camera ( D-7000 ) . Alexander solution was prepared as previously described [70] . Anthers were dissected and immersed in Alexander solution for 0 . 5 hr , and images were obtained under a microscope with an Olympus BX51 digital camera ( Olympus , Japan ) . Plant materials for the semi-thin sections were prepared and embedded in Spurr resin as described in [25] and cut into 1-μm thick sections , stained with toluidine blue , then photographed with an Olympus BX51 digital camera . For transmission electron microscopic analysis , the same-stage anthers of wild type ( WT ) and yuc2yuc6 were fixed and embedded as previously described [25] . Green fluorescent protein ( GFP ) fluorescence in ProARF17:YUC2-GFP ( yuc2yuc6 ) , ProLAT52:YUC2-GFP ( yuc2yuc6 ) , ProMSP1:DII , and ProMSP1:mDII transgenic plants was detected under a fluorescence microscope ( Olympus BX51 ) . GFP fluorescence in ProA9:YUC2-GFP ( yuc2yuc6 ) transgenic plants and WT or yuc2yuc6 expressing DR5:GFP was detected by confocal laser scanning microscopy ( Carl Zeiss , LSM 5 PASCAL ) . To generate YUC2-GFP , we amplified YUC2 cDNA without the stop codon from inflorescence mRNA by standard RT-PCR ( see S2 Table for primers ) for cloning into the modified pCAMBIA1300 binary vector ( CAMBIA , Australia ) , pCAMBIA1300-GFP . The resulting construct was named pCAMBIA1300-YUC2-GFP . The promoter sequences of YUC2 , YUC6 , ARF17 , ATA7 and A9 were PCR-amplified from genomic DNA of WT Col-0 . The promoter sequence of LAT52 was PCR-amplified from genomic DNA of tomato . The primers for amplification were listed in S2 Table . The amplified sequences were first inserted into pMD19-T ( Takara ) for sequence verification , then subcloned into the vector pCAMBIA1300-YUC2-GFP for plant transformation . The promoter sequences for YUC2 and YUC6 were subcloned into pCAMBIA1300-GFP for plant transformation . The promoter sequence for MSP1 was PCR-amplified from genomic DNA of WT Col-0 , then subcloned into the vector pCAMBIA1300 to obtain pCAMBIA1300-proMSP1 . The DII-VENUS and mDII-VENUS sequences were amplified from genomic DNA from DII-VENUS and mDII-VENUS plants . The amplified sequences were inserted into pMD19-T ( Takara ) for verification , then subcloned into the vector pCAMBIA1300-proMSP1 for plant transformation . For plant transformation , all plasmids were introduced into the Agrobacterium strain GV3101 and transformed into plants by the floral dip method[71] . For tissue specific rescue experiments , all of the constructs were transformed into the offspring of yuc2-/-yuc6+/- . After collected the T1 seeds , we first selected transgenic plants by growing on MS media containing hygromycin . We then genotyped the transgenic plants for yuc2yuc6 double mutants[49] . The probe fragments were amplified from plasmid containing GFP ( pCAMBIA1300-GFP ) with primers GFP-F and GFP-R . The PCR products were cloned into the pBluescriptSK vector and confirmed by sequencing . Plasmid DNA was digested with HindIII or BamHI . The digestion products were used as templates for transcription into sense and antisense probes by T3 and T7 RNA polymerases , respectively ( Roche ) . Oligonucleotide sequences of GFP-F and GFP-R are provided in S2 Table . Images were taken using the Olympus BX-51 microscope . Total RNA was extracted from the inflorescences of T1 transgenic plants by the Trizol method ( Invitrogen , USA ) following the manufacturer’s instructions . Quantitative real-time PCR involved an ABI PRISM 7300 detection system ( Applied Biosystems , USA ) with SYBR Green I master mix ( Toyobo , Japan ) . Relevant primer sequences are in S2 Table . β-Tubulin was as a constitutive expression control . Three biological repeats were used for gene expression analysis . | Plant life cycle alternates between the diploid sporophyte generation and the haploid gametophyte generation . Understanding the molecular mechanisms governing the generation alternation impacts fundamental plant biology and plant breeding . It is known that the development of haploid generation in vascular plants requires the diploid tapetum cells to supply nutrients . Here we show that the male gametophyte ( haploid ) development in Arabidopsis requires auxin produced in the diploid microsporocytic cells . Moreover , we show that auxin produced in microsporocytic cells and microspore is also sufficient to support normal development of the haploid microspores . This work demonstrates that Arabidopsis uses two different diploid cell types to supply growth hormone and nutrients for the growth of the haploid generation . | [
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"organisms"
] | 2018 | Auxin production in diploid microsporocytes is necessary and sufficient for early stages of pollen development |
Autophagy helps deliver sequestered intracellular cargo to lysosomes for proteolytic degradation and thereby maintains cellular homeostasis by preventing accumulation of toxic substances in cells . In a forward mosaic screen in Drosophila designed to identify genes required for neuronal function and maintenance , we identified multiple cacophony ( cac ) mutant alleles . They exhibit an age-dependent accumulation of autophagic vacuoles ( AVs ) in photoreceptor terminals and eventually a degeneration of the terminals and surrounding glia . cac encodes an α1 subunit of a Drosophila voltage-gated calcium channel ( VGCC ) that is required for synaptic vesicle fusion with the plasma membrane and neurotransmitter release . Here , we show that cac mutant photoreceptor terminals accumulate AV-lysosomal fusion intermediates , suggesting that Cac is necessary for the fusion of AVs with lysosomes , a poorly defined process . Loss of another subunit of the VGCC , α2δ or straightjacket ( stj ) , causes phenotypes very similar to those caused by the loss of cac , indicating that the VGCC is required for AV-lysosomal fusion . The role of VGCC in AV-lysosomal fusion is evolutionarily conserved , as the loss of the mouse homologues , Cacna1a and Cacna2d2 , also leads to autophagic defects in mice . Moreover , we find that CACNA1A is localized to the lysosomes and that loss of lysosomal Cacna1a in cerebellar cultured neurons leads to a failure of lysosomes to fuse with endosomes and autophagosomes . Finally , we show that the lysosomal CACNA1A but not the plasma-membrane resident CACNA1A is required for lysosomal fusion . In summary , we present a model in which the VGCC plays a role in autophagy by regulating the fusion of AVs with lysosomes through its calcium channel activity and hence functions in maintaining neuronal homeostasis .
Autophagy is an evolutionarily conserved , lysosome-mediated degradation process required to maintain cellular homeostasis [1 , 2] . In eukaryotic cells , autophagy is a ubiquitous process that is important for several physiological processes . It occurs at a basal level in most cells to remove damaged organelles and is required for the turnover of long-lived proteins and other cellular macromolecules . Cellular quality control through autophagy is particularly relevant in long-lived neurons , as evidenced by autophagic malfunction in many human neurological disorders , including Alzheimer’s disease , Parkinson’s disease , Huntington’s disease , and amyotrophic lateral sclerosis ( ALS ) [3] . In both flies and mice , loss of autophagy-related genes leads to progressive neurodegeneration . It is still an open question whether neurons have their own tailored mechanism to regulate autophagy . Autophagy is characterized by the formation of an isolation membrane that further elongates to form the double membrane autophagosome , which then fuses with the late endosomes and lysosomes [2] . Soluble N-ethylmaleimide-sensitive factor activating protein receptor ( SNARE ) proteins have been shown to be required for the fusion of autophagosomes with lysosomes . In yeast , the fusion of autophagosomes with vacuoles , the counterparts of lysosomes , involves the SNARE proteins Vti1 ( Q04338 . 3 ) , Ykt6 ( CAA82040 . 1 ) , Vam3 ( CAA99304 . 1 ) , and Vam7 ( CAA96928 . 1 ) [4–7] , but the latter two have no obvious homologues in metazoan cells . In Drosophila , the SNARE complex required for the fusion of autophagosomes with late endosomes and lysosomes consists of Syntaxin 17 ( Syx17 ) ( AGB94109 . 1 ) , ubiSNAP ( SNAP-29 ) ( AAF47071 . 1 ) , and Vamp7 ( AHN56053 . 1 ) [8] . The requirement of these SNARE proteins for this fusion step is evolutionarily conserved as Vamp7 , and Syntaxin 17 also play similar roles in mammalian cells [9] . Recent studies have shown that two pore channel ( TPC ) , a lysosomal sodium channel , depolarizes lysosome membranes and promotes lysosome fusion upon PI ( 3 , 5 ) P2 stimulation or translocation of mammalian target of rapamycin ( mTOR ) away from the lysosome [10 , 11] . It is not established how the change in lysosome membrane potential coordinates the SNARE mediated fusion events . In an unbiased genetic screen designed to isolate mutations that cause neurodegenerative phenotypes , we isolated many mutant alleles of cacophony ( cac ) ( ID: 32158 ) that encode an α1 subunit of a Drosophila voltage-gated calcium channel ( VGCC ) . VGCCs consist of multiple subunits , including the conducting pore forming subunit α1 , and the accessory subunits α2δ , β , and γ [12] . The α1 subunit contains four internal repeats , each consisting of six transmembrane segments ( S1–S6 ) . The loop between transmembrane segments S5 and S6 of each repeat contains conserved domains for short segments 1 and 2 ( ss1 and ss2 ) . The calcium ion selectivity of the conducting pore is conferred by a conserved glutamate residue in the ss2 loop of each of the four internal repeats in the α1 subunits [13] . The α2δ subunit of VGCC consists of two disulfide-linked subunits , α2 and δ , derived from posttranslational cleavage of a single gene product [14 , 15] . In flies , a gene named straitjacket ( stj ) ( ID: 36526 ) encodes the α2δ subunit which mediates the proper localization of Cac ( P91645 . 3 ) at synapses [16] . Loss of cac is embryonic lethal in Drosophila and causes an almost complete loss of synaptic transmission [17 , 18] . stj mutants also exhibit a severe reduction in neurotransmitter release [16] . Mutations in human Cacna1a ( ID: 773 ) and Cacna2d2 ( ID: 9254 ) , the orthologs of cac and stj respectively , lead to severe neurological diseases , including episodic ataxia 2 , familial hemiplegic migraine 1 ( FHM1 ) , absence epilepsy , progressive ataxia , and the polyglutamine disorder spinocerebellar ataxia 6 ( SCA6 ) [19 , 20] . Mutations in two subunits of Cav2 . 1 in mice , CACNA1A ( AAW56205 . 1 ) and CACNA2D2 ( Q6PHS9 . 1 ) , also exhibit ataxia , epilepsy and neurodegeneration [21] . Aside from these spontaneous mutations , knock-in models of FHM1 and SCA6 have also been generated in mice . However , impairments in synaptic transmission do not underlie the mutant phenotypes observed in CACNA1A null mutant mice , and the molecular mechanisms underlying these diseases are still unclear [22] . Indeed , Jun et al . showed that in CACNA1A null mutant mice , excitatory synaptic transmission is largely unaffected because the N- and R-type VGCCs provide the calcium influx needed for synaptic vesicle ( SV ) fusion . However , these mice exhibit severe neurological deficits , implying that the P/Q-type VGCC plays other important roles than in synaptic transmission [22] . Here we show that , mutant alleles of cac and stj exhibit age-dependent autophagic defects in photoreceptor cells . We find that the role of the VGCC complex in neuronal autophagy is evolutionarily conserved as the loss of the mouse homologues , Cacna1a ( ID: 12286 ) and Cacna2d2 ( ID: 56808 ) , also result in autophagic defects in mice cerebella . We provide compelling evidence that the VGCC functions at the lysosomal fusion steps and that its role in autophagy is independent of its role in synaptic transmission . We further demonstrate that the α1 VGCC subunit CACNA1A is present on lysosomes , where it serves as a calcium channel required for lysosomal fusion with endosomes and autophagosomes . We propose that the VGCC in neurons regulates lysosomal fusion through its calcium channel activity on lysosomes .
In order to identify essential genes on the X chromosome that are involved in neuronal homeostasis , we performed a forward genetic screen using ethyl methanesulfonate ( EMS ) . We used the FLP/FRT system to induce homozygous mutant clones in the photoreceptor neurons of the otherwise heterozygous flies and performed electroretinograms ( ERGs ) on 3- and 33-days-old flies . Flies were exposed to a 1 s light pulse , and the electrophysiological responses were recorded . The amplitude of depolarization reflects photoreceptor activity and the on-off transients reflect pre- and post-synaptic connections . One of the complementation groups corresponds to XE06 . The ERGs of these mutants exhibited a reduction of “on” transients in young and old animals ( Fig . 1A and B ) , indicating a loss of synaptic transmission [23] . We mapped the mutations to cac using deficiency and duplication mapping ( Fig . 1C ) . We then performed Sanger sequencing and identified seven different alleles ( Fig . 1D ) : two early nonsense mutations , four missense mutations , and one splicing donor mutant . We selected two alleles for further characterization: cacJ has an early nonsense mutation which is embryonic lethal and cacF has a missense mutation that destroys a key glutamate residue in the calcium ion selectivity loop and is third instar larval lethal ( Fig . 1D and E ) . The lethality associated with both alleles is rescued with a transgene ( Fig . 1E ) . To examine whether the cac mutants have degenerative phenotypes in the eyes , we performed Transmission Electron Microscopy ( TEM ) on the mosaic eyes with most photoreceptor cells homozygous for cac mutant . As shown in Fig . 2A and S1 Fig , TEM of cacJ and cacF photoreceptor terminals at day 3 show aberrantly expanded terminals that are more densely filled with SVs when compared to controls ( CTL ) . As the flies age ( day 27 ) , the terminals expand further , and the cartridge structure in the lamina is lost ( Fig . 2A and S1 Fig ) . In addition , the number of capitate projections ( CPs ) ( Fig . 2C ) and active zones ( AZs ) ( Fig . 2D ) decrease dramatically , whereas the number of mitochondria per terminal is increased ( Fig . 2E ) . We also observed a significant accumulation of AVs in aged photoreceptor terminals , showing a progressive worsening of the phenotype ( Fig . 2A , B and S1 Fig ) . The intermediate AVs , especially fusion-primed AVs ( blue arrow in Fig . 2B ) are greatly increased in aged mutants ( Fig . 2F ) . This suggests that although cac mutant photoreceptor terminals form autophagosomes , there is a defect in autophagosomal maturation and fusion . The genomic fragment containing cac rescues both the morphology defects of photoreceptor terminals in the lamina and the accumulation of AVs in the photoreceptor terminals ( S1 Fig ) . Poly-ubiquitinated proteins are delivered to autophagosomes and degraded by lysosomes through AV-lysosomal fusion [24] . Therefore , they could serve as a marker to examine the autophagy flux . Indeed , impairment of autophagy has been shown to cause an increase in poly-ubiquitinated proteins in aged Atg7 ( ID: 37141 ) mutant flies [25] . To distinguish whether the accumulation of AVs in cac mutant flies is due to the blockage of autophagy at the late steps or the enhancement of autophagy induction , we measured the autophagic flux by monitoring poly-ubiquitinated proteins in cac mutant flies . We made mosaic flies with cac depleted in the eye , stained the eye-brain complexes of the aged cac flies with an anti-poly-Ubiquitin antibody , and compared the phenotype to the aged Atg7 flies . As shown in Fig . 2G , cac mutant brains accumulate poly-ubiquitinated proteins similar to Atg7 flies , supporting a defect in autophagy . To confirm that autophagic flux is reduced , we also examined protein levels of p62 , one of the selective substrates for autophagy , using western blotting ( Fig . 2H ) , in aged fly brains . We find an almost 2-fold increase in p62 in aged mutants , suggesting a reduction in autophagic flux ( Fig . 2H and I ) . All these results , together with the TEM data , indicate that cac is required for autophagy . Cac regulates autophagy either through its VGCC channel activity or other activities independent of the calcium channel functions . To distinguish between these possibilities , we tested whether loss of other VGCC subunits leads to similar autophagy defects in flies . We examined the flies with a mutation for the α2δ subunit of VGCC encoded by the stj gene [16] . Loss of stj or cac causes very similar autophagic defects , a great accumulation of AVs , suggesting that the VGCC complex , not just Cac , is required for proper autophagy ( Fig . 3A–C ) . We then examined several other mutants involved in lysosomal fusion and function . Loss of the Vacuolar H+ ATPase 100 kD subunit 1 ( Vha100-1 ) ( Q8IML5 . 1 ) , a protein required for endosomal acidification [26] , also results in accumulation of AVs in the photoreceptor terminals ( Fig . 3D–F ) . Since cac , stj , and Vha100–1 ( ID: 43442 ) are all required for neurotransmitter release , and mutations in these genes result in SV accumulation in the photoreceptor terminals , it is possible that the autophagy defects we observed in these mutant terminals were a secondary effect of SV accumulation . However , loss of neuronal synaptobrevin ( n-Syb ) ( ID: 38196 ) , encoding a key regulator for neurotransmitter release , results in accumulation of SVs in the terminals [27] but does not lead to the autophagy phenotype ( Fig . 3G–I ) . It indicates that loss of neurotransmitter release in cac and stj mutants is not causing autophagy defects per se . Moreover , loss of Vamp7 [28] , a SNARE required for autophagosomal maturation and lysosomal fusion and Fab1 ( O96838 . 2 ) , a kinase required for autophagosomal-lysosomal fusion [29] cause similar AV accumulation phenotypes as cac and stj flies ( Fig . 3J–O ) . These data confirm that Cac and Stj play a role in the AV-lysosomal fusion step of autophagy . To determine if the role of Cac and Stj in autophagy is conserved in vertebrates , we obtained leaner ( Cacna1atg-la ) [30 , 31] and ducky ( Cacna2d2du-2J ) mice [32 , 33] that carry mutations in orthologs of cac and stj respectively . Leaner mice have a splicing mutation in the Cacna1a locus [31] , whereas ducky mice have a 2 bp deletion within the exon 9 of Cacna2d2 [32] . These mice are deficient in neuronal autophagy and show striking similarities to the mice in which Atg5 ( ID: 11793 ) or Atg7 ( ID: 74244 ) is lost in neurons . The four mouse models exhibit motor defects , ataxia , reduced body size and weight , and smaller cerebella than the wild type ( WT ) littermates ( S1 Table ) [34–37] . In addition , these defects occur at similar ages in all these four mutant mice . Cacna1atg-la mice have gradually narrowed granule cell layer and display a purkinje cell ( PC ) loss starting at day 30 that worsens gradually until there are almost no PCs visible in the anterior lobe at 3 months of age ( Fig . 4A and S2 Fig ) . The degeneration of the Cacna1atg-la mice cerebella resembles that of the Atg5 and Atg7 neuron specific knockout mice which show extensive PC loss by 2 months of age [34–37] . Moreover , all four mouse models exhibit swollen PC axons in the granule cell layers of the cerebella ( S1 Table , Fig . 4B–E and S3 Fig ) . To examine whether Cacna1atg-la and Cacna2d2du-2J mice indeed suffer from autophagy defects , we performed ultrastructural studies on their cerebella using TEM . We observed many similarities between cerebella from these mutant mice and mice with neuronal autophagy defects . The swollen axons of both Cacna1atg-la and Cacna2d2du-2J mice contain numerous abnormal-looking mitochondria , expanded membranes and endoplasmic reticulum ( ER ) , expanded Golgi cisternal stacks and increased number of autophagosomes , multivesicular bodies ( MVBs ) , and various cytoplasmic vesicles , a hallmark of lysosomal malfunction ( S1 Table , Fig . 4C , E and S3 Fig ) . All of these phenotypes except for autophagosome accumulation have also been documented in mice with neuronal knockouts of Atg7 [37] , suggesting that Cacna1atg-la and Cacna2d2du-2J mutant mice are also defective in autophagy . The difference of the autophagosome accumulation between the Atg7 mice and the VGCC mutant mice probably is due to the fact that Atg7 is required for autophagosome formation [38] whereas VGCC functions at the later fusion steps . We then probed the cerebellar lysates of both mutant mice with antibodies against autophagosomal protein LC3 and autophagy substrate p62 ( Q64337 . 1 ) and observed a small but significant increase in the levels of both the LC3-II form of LC3 and p62 proteins , indicating that the autophagic flux is reduced in these mutant mice ( Fig . 4F and G ) . Immunohistochemistry of Cacna1atg-la Cerebella section also displayed increased levels of LC3 and p62 in the PC soma ( S4 Fig ) , supporting a reduction in autophagic flux . The reduction in autophagy flux and the accumulation of MVBs and autophagosomes in mutant mice suggest that lysosomal fusion or degradation is compromised . It has been reported that CACNA1A not only localizes to the plasma membrane , but is also present in the neuronal cytosol [39] . To assess if CACNA1A affects lysosomal function by residing on lysosomes , we stained primary cultured cerebellar neurons with two different commercially available CACNA1A antibodies ( Millipore and Abcam ) and confirmed the specificity of the CACNA1A antibodies using peptide competition assays ( S5 Fig ) . We observe a co-localization of CACNA1A with the lysosomal marker LAMP1 ( P11438 . 2 ) both in WT and Cacna1atg-la cerebellar neurons , showing that CACNA1A localizes to lysosomes ( Fig . 5A , C and S6 Fig ) . We also stained the neurons with an early endosome marker ( EEA1 , Q8BL66 . 2 ) or ER marker ( Calreticulin , P14211 . 1 ) in combination with the CACNA1A antibody and detect no obvious colocalization of CACNA1A with these two markers ( S7 Fig and S8 Fig ) . To confirm lysosomal distribution of CACNA1A , we enlarged the lysosomes by pre-treating the primary neurons with Vacuolin-1 [40] and examined the distribution of CACNA1A with LAMP1 and CACNA1A antibodies . In both WT and Cacna1atg-la primary cultured neurons , CACNA1A staining is present as punctae on the membrane of the enlarged lysosomes ( Fig . 5B ) . To provide independent biochemical evidence , we dissected cerebella from WT mice , and purified and separated lysosomes by iodixanol gradient and observe that full length CACNA1A is enriched in the lysosomal fractions ( Fig . 5D ) . To exclude the possibility of plasma membrane contamination , we also probed the fractions with Annexin V antibody , and no signal was detected in the lysosomal fractions ( Fig . 5D ) . In addition , we also extracted lysosomes from whole brains of WT mice using a subcellular fractionation protocol [41] and find that CACNA1A protein is present in the lysosomal fraction , which was verified with LAMP1 antibody ( S9 Fig ) . The fainter CACNA1A band in the lysosomal lysate as compared to total brain lysate may be due to a much higher level of the protein on plasma membranes than lysosomes . To assess whether lysosomal function is affected in the Cacna1a mutant cells , we isolated primary neurons from WT and Cacna1a mutant mice cerebella and stained the cells with LysoTracker Red DND-99 . WT neurons show big and bright LysoTracker positive vesicles , and LysoTracker staining is almost completely abolished when the neurons are pre-treated with a lysosomal acidification inhibitor bafilomycin A1 . As shown in Fig . 6A–D , Cacna1a mutant cells also display severely reduced LysoTracker staining , suggesting that lysosomes are impaired in Cacna1a mutant neurons . In order to determine if Cacna1a deficient neurons exhibit defects in autophagosomal-lysosomal fusion , we co-stained primary cultured WT and Cacna1a mutant neurons with antibodies against a lysosomal marker ( LAMP1 ) and an autophagosomal marker ( LC3 ) . In WT neurons , LC3 and LAMP1 co-localize , whereas little co-localization is observed in Cacna1a mutant cells ( Fig . 6E and F ) , indicating that the fusion between AVs and lysosomes is affected in Cacna1a mutant neurons . Lysosomes not only fuse with autophagosomes to degrade and recycle intracellular materials but also fuse with late endosomes to degrade and recycle membrane proteins and extracellular material [42] . To determine if lysosomal fusion with other organelles is compromised in Cacna1a mutant neurons , we labeled late endosomes and lysosomes with DQ-BSA . This fluorogenic proteolysis probe permits tracking of endocytic compartments after fluid-phase endocytosis [43] . As shown in Fig . 7A and C , LAMP1 co-localizes extensively with DQ-BSA in WT neurons , but not in Cacna1a mutant neurons . Indeed , numerous green and red punctae are observed in the mutant neurons , whereas most punctae are labeled yellow in WT neurons . These data show that lysosomes fail to fuse with late endosomes in Cacna1a cells . Given that the primary role of a VGCC is its calcium channel activity and that a mis-sense mutation in the calcium ion selectivity pore in the fly homolog of Cacna1a causes lysosomal fusion defects similar to the loss of the gene , CACNA1A likely regulates lysosomal fusion through its calcium channel activity . Even though CACNA1A is present on lysosomes , the CACNA1A localized at the plasma membrane of synaptic terminals may be required for the calcium influx needed for lysosomal fusion in the cytosol . To rule out that CACNA1A activity on the plasma membrane is required for lysosomal fusion , we applied a P/Q-type calcium channel blocker ω-agatoxin TK at a saturating concentration ( 1 μM ) [44 , 45] to primary cultured neurons and analyzed endosomal-lysosomal fusion with DQ-BSA . To first test whether ω-agatoxin TK could efficiently block the P/Q-type VGCC on the cell surface , we depolarized the neurons with high potassium chloride solution ( 90 mM ) to activate VGCC , and recorded the calcium influx using a calcium indicator , Fluo 4-AM in the presence or absence of ω-agatoxin TK . ω-agatoxin TK greatly reduces calcium influx induced by the depolarization , indicating that the toxin is blocking depolarization-induced calcium entry via VGCCs ( S10 Fig ) . However , we detected no obvious endo-lysosomal fusion defects in the WT neurons treated with the toxin ( Fig . 7C and D ) . Since ω-agatoxin TK is not cell permeable , our data imply that the cell surface CACNA1A is not essential for lysosomal fusion . We then applied a cell-permeable calcium channel blocker Bepridil ( 10 µM ) to the primary cultured neurons and analyzed endo-lysosomal fusion with DQ-BSA . We detected a significant reduction in colocalization between DQ-BSA and LAMP1 ( Fig . 7C and D ) . A partial block of lysosomal fusion observed here may be due to insufficient block of the intracellular VGCC under current conditions . Taken together , our data suggested that the intracellular CACNA1A but not the cell surface CACNA1A is required for lysosomal fusion .
Here , we show that CACNA1A is present on lysosomes and that it is required for endo-lysosomal fusion and autophagy ( Fig . 8 ) . Our work suggests that the VGCC regulates fusion of lysosomes with endosomes and AVs through its calcium channel activity on lysosomes . In the absence of VGCC subunits , as the neurons age and undergo basal autophagy , they accumulate AVs that are unable to fuse with lysosomes . Neurons then accumulate other damaged cellular organelles and misfolded proteins . Eventually this initiates a process of degeneration that mostly affects synapses and synaptic glial cells in fly eyes ( Fig . 2A and S1 Fig ) . The latter phenotype is unlike most other neurodegenerative mutations , which cause a degeneration of rhabdomeres and cell body of the photoreceptors [46 , 47] . VGCCs have so far been implicated in the fusion of synaptic vesicles and dense core secretory vesicles with the plasma membrane as resident proteins of the plasma membrane [48] . In synapses , a sodium channel gates sodium upon an action potential that depolarizes the plasma membrane and promotes the activation of VGCC . The opening of the VGCC allows influx of extracellular calcium into the cytosol , which stimulates the assembly of the SNARE complex at the fusion site and subsequently promotes the fusion between neurotransmitter loaded vesicles and plasma membrane [49] . Although calcium and SNAREs have also been shown to be required for different steps of autophagy , a VGCC has not been implicated in autophagy previously . Our work suggests that the fusion events required in autophagy are not fundamentally different from those observed at presynaptic terminals for neurotransmitter release . We show that CACNA1A is present on the lysosomal membrane in neurons . The cytosolic C terminal region of this protein contains a conserved YxxΦ motif across the different orthologs that is known to be required for lysosome targeting of some other lysosomal proteins ( S1 Text ) [50 , 51] . All these conserved motifs are remained in Cacna1atg-la . In addition , the CACNA2D2 protein is heavily glycosylated , similar to other lysosomal membrane proteins [15 , 52] , which is known to protect lysosomal membrane proteins from proteolysis [53] . Thus it is likely that these characteristics might be responsible for the lysosomal localization of VGCC subunits , although this idea needs to be further investigated . It is not clear whether the delivery of VGCCs to lysosomes occurs by an indirect route via the plasma membrane or by a direct intracellular trafficking pathway . However , the route must ensure the correct topology of the channel on the lysosomal membrane so as to allow calcium to flow from the lysosome to the cytosol . The lysosomal ionic compositions are similar to the extracellular environment [10] and lysosomes are known to have high calcium content [54] . Studies have shown that the resting calcium concentration inside the lysosomal lumen of human macrophages is between 0 . 4–0 . 6 mM [55] , a range that is much higher than the approximately 100 nM calcium concentration in the cytosol [56] . The 0 . 5 mM range of extracellular calcium concentration is sufficient to promote a robust calcium influx during synaptic transmission [57] . Hence , the luminal lysosomal calcium concentration is sufficient to induce calcium efflux from lysosomes through the VGCC to facilitate SNARE-mediated fusion of lysosomes with late endosomes and autophagosomes . In addition to the requirement of high levels of resting luminal calcium concentration in the lysosomes , there should be a need for a depolarization of the lysosomal membrane to activate the VGCC . Recently , Cang et al . demonstrated that lysosomes are electrically excitable and contain a voltage-activated sodium channel NaV ( formed by TPC1 , Q9EQJ0 . 1 ) [58] . However , the role of this voltage depolarization in lysomes is unknown . Our findings imply that such a NaV-mediated depolarization may be able to activate the VGCCs to trigger Ca2+ efflux from lysosomes in neurons [10 , 11] . The activity of the sodium channels on the lysosome is triggered by PI ( 3 , 5 ) P2 stimulation or loss of lysosomal mTOR activity , and both are closely associated with autophagy and lysosomal fusion events [10 , 11 , 58] . Thus , the TPC proteins are well poised to act as the trigger to activate lysosomal VGCC and facilitate lysosomal fusion with autophagic or late endosomal organelles . Another interesting question to consider is how the calcium efflux from the lysosomes through the VGCC triggers lysosomal fusion events . At the presynaptic plasma membrane , calcium regulates the fusion machinery through its binding to the C2 domains of synaptotagmin . As a calcium sensor , synaptotagmin interacts with SNAREs and phospholipids to facilitate fusion pore formation upon calcium entry [59] . Synaptotagmin VII ( Syt7 , Q9R0N7 . 1 ) is a calcium sensor that is present on lysosomes and has been shown to be required for lysosomal exocytosis during membrane repair [60] . It would therefore be interesting to test whether Syt7 or other calcium sensors participate in lysosomal fusion events . In flies , cac is required in neurons because the neuronal specific expression of a transgene of cac can rescue the lethality and phenotypes associated with cac null mutant flies [18] . Mammalian P/Q-type VGCC subunits CACNA1A and CACNA2D2 are also expressed in neuronal tissues [31 , 32] , and mutations in subunits in humans and mice mostly affect neurons . Hence , the requirement of the P/Q-type VGCC for lysosomal fusion might be specific to the neuronal system . Autophagy is a rather ubiquitous process that exists in all tissues . It is still an open question how lysosomal fusion is regulated in cells without P/Q-type VGCCs . Other calcium channels , such as transient receptor potential channels ( TRPCs ) , may play a similar role in non-neuronal cells . Indeed , the TRPC homolog in yeast Yvc1 resides in the vacuole , a lysosome like organelle that can release Ca2+ in response to voltage changes . By contrast , the sole VGCC homolog in yeast localizes on the plasma membrane and is regulated by the stimuli that typically activate TRPC in animal cells [61] . The interchangeable regulation modes of TRPC and VGCC during evolution suggest they may play similar roles in certain conditions . Our data also suggest a mechanism underlying the role of lysosomal dysfunction in the mouse model of human SCA6 [62 , 63] . SCA6 is a late-onset neurodegenerative disease caused by a polyglutamine tract expansion at the C terminal of CACNA1A . Unno et al . observed lysosomal involvement based on the accelerated neurodegeneration in SCA6 mice that were also lacking a key lysosomal cysteine protease in the cerebellum , Cathepsin B ( P10605 . 2 ) [62] . However , they failed to detect autophagic defects in the SCA6 mouse model . This could be due to the low basal autophagy level in cerebella as evidenced by the low levels of LC3II in the cerebellar lysates ( Fig . 4F and G ) [64] . This may also explain why the AV accumulation in Cacna1atg-la and Cacna2d2du-2J cerebella is not as dramatic as that in fly synapses ( Fig . 4C , E and S3 Fig ) . In summary , our work has uncovered an unexpected role of VGCC in AV- lysosomal fusion in neurons in helping to maintain cellular homeostasis and provides a new angle to our understanding of the pathology of Cacna1a- and Cacna2d2-related diseases in humans .
The experimental procedures using animals were in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and approved by Zhejiang University Institutional Animal Care and Use Committee . cac mutants were isolated from an ey-FLP EMS screen as described previously [46] . The duplication and deficiency mapping were performed as described [65] . The genotypes of the fly strains generated in the paper are as following: Figs 1 , 2 and S1 Fig CTL: y w , iso FRT19A / P{w+} cl ( 1 ) FRT19A; eyFLP . cacJ: y w , cacJ FRT19A/ P{w+} cl ( 1 ) FRT19A; eyFLP . and cacF: y w , cacF FRT19A/ P{w+} cl ( 1 ) FRT19A; eyFLP . S2 Fig rescue: y w , cacJ FRT19A/Y; Dp ( 1;3 ) DC131 . Fig . 2G: Atg7 d4 . Fig . 3A and B: y w , eyFLP; stj1 FRT42D/ P{w+} cl ( 1 ) FRT42D [16] . Fig . 3D and E: y w , eyFLP; V100–12 FRT82B/ P{w+} cl ( 1 ) FRT82B [66] . Fig . 3G and H: y w , eyFLP; FRT sybΔF33B FRT42D/ P{w+} cl ( 1 ) FRT42D [67] . Fig . 3J and K: y w , eyFLP; P ( EP ) VAMP7G7738 FRT42D/ P{w+} cl ( 1 ) FRT42D . Fig . 3M and N: y w , eyFLP; fab121 FRT42D/ P{w+} cl ( 1 ) FRT42D [29] . For ERG recording , y w *cac ( lethal ) FRT19A/FM7c , Kr-Gal4 , UAS-GFP flies were crossed to y w P{w+} cl ( 1 ) FRT19A/Dp ( 1;Y ) y+; eyFLP to generate flies with mutant clones in the eyes , and ERGs were performed as previously described [16] . At least five flies of each genotype were used for quantification . Dissected fly adult brains were fixed in PBS with 3 . 7% formaldehyde for 20 min , followed by washing with PBX ( PBS + 0 . 4% Triton X-100 ) three times . The tissues were incubated with primary antibody overnight in 4°C followed by extensive washing and incubated with secondary antibody overnight at 4°C . After extensive washing , the samples were mounted in Vectashield ( Vector Labs ) followed by microscopy . Polyubiquitinylated conjugates antibody ( FK1 ) was obtained from Enzo Life Sciences , 1:200 dilution was used . Elav antibody was obtained from Developmental Studies Hybridoma Bank and 1:100 dilution was used . TEM was performed as described previously [68] . Heterozygous leaner mice with the control genotype , C57BL/6J: tgla/+ were originally obtained from The Jackson Laboratory in Bar Harbor , MA , United States . Male and female heterozygous leaner were mated to produce tgla/+ and homozygous tgla/tgla offspring . Male and female heterozygous ducky mice ( du2J/+ ) were originally obtained from The Jackson Laboratory and mated to each other to produce control ( +/+ ) wild-type and homozygous mutant ducky ( du2J/du2J ) mice . Rabbit polyclonal to LC3 antibody ( Novus Biologicals , 1:200 dilution ) and Mouse polyclonal to LC3 antibody ( MBL , 1:50 dilution ) were used for immunofluorescence studies and Rabbit pAb to LC3 ( Novus Biologicals , 1:1 , 000 dilution ) was used for immunoblotting . Two rabbit polyclonal to CACNA1A antibodies were purchased from Abcam ( 1:100 dilution ) and Millipore ( 1:60 dilution ) for immunofluorescence studies . Anti-CACNA1A antibody ( Millipore , 1:1000 dilution ) was used for immunoblotting . Anti-murine LAMP-1 ( 1D4B ) mAb ( 1:1000 dilution for immunoblotting and 1:500 dilution for immunofluorescence studies ) was purchased from Developmental Studies Hybridoma Bank . The mouse monoclonal antibody anti-p62 ( 1:500 dilution for immunohistochemistry and 1:1 , 000 dilution for immunoblotting ) was from Abcam . Rabbit polyclonal antibody anti-Hsp60 ( 1:5 , 000 dilution ) was from Epitomics . Rabbit mAb to tubulin ( 1:2 , 000 dilution ) was from Cell Signaling , and rabbit pAb anti-Calbindin D-28K ( 1:500 dilution ) was purchased from Millipore . Mouse anti-EEA1 mAb ( 1:1 , 000 dilution ) was from MBL . Chicken pAb anti-Calreticulin ( 1:200 dilution ) was from Abcam . DQ-BSA green and LysoTracker Red DND-99 were from Molecular Probes . Cytosine-β-D-arabinofuranoside were from Sigma . Bafilomycin A1 was from Tebu-Bio . ω-Agatonxin TK and Bepridil hydrochloride were purchased from Tocris Bioscience . Fluo 4-AM and Pluronic F-127 were from Dojindo Laboratories . Four percent paraformaldehyde-fixed , paraffin-embedded sections in 5 μm thickness were deparaffinized with xylene and washed with distilled water . Tissue sections were boiled for 20 min in 10 mM citrate buffer ( pH 7 . 4 ) . After antigen retrievals , all sections were washed in distilled water , treated with 0 . 3% ( vol/vol ) hydrogen peroxide to quench endogenous peroxide , and then incubated with normal goat serum for 30 min . Sections were incubated for 2 h at room temperature with primary antibodies . The primary antibodies were serially detected with the appropriate biotinylated anti-rabbit IgG ( Vector ) , avidin-biotinylated-peroxidase complex ( Vector ) , and , finally , developed with diaminobenzidine ( Vector ) . The sections were washed , counterstained with hematoxylin , dehydrated , and mounted . Mice cerebella were homogenized in lysis buffer containing protease and phosphatase inhibitors . Protein concentration was determined using Bio-Rad protein assay reagent . Proteins were separated by SDS–PAGE , and transfer the protein onto a PVDF membrane . The membrane was blocked with 5% non-fat milk in TBST buffer and incubated with primary antibodies in 5% non-fat milk in TBST at room temperature for 1 h . Blots were incubated in goat anti-rabbit/mouse-HRP secondary antibody and diluted 1:2 , 500 in 5% non-fat milk/TBST for 1 h at room temperature . Blots were washed in TBST and then incubated with ECL reagent and exposed . Quantification of protein bands was done using the Image J software . WT and Cacna1atg-la/ Cacna1atg-la primary cerebella neurons were derived from P0-P2 pups . Cerebella were dissected from pups and individually digested with trypsin . Single cell suspensions obtained were plated on a poly-D-lysine-coated surface in Dulbecco's Modified Eagle's Medium ( DMEM ) supplemented with 10% ( vol/vol ) Fetal bovine serum ( FBS ) and 10% F12 Nutrient Mixture . 12 h after plating , culture medium was half replaced by serum-free neurobasal medium supplemented with B27 ( Gibco ) and L-Glutamine ( Gibco ) . Mixed cultures were maintained at 37°C and 5% CO2 . After 3 days in vitro ( div ) , 5µM cytosine-β-D-arabinofuranoside was added to restrict glial cell growth . The cultures were used for experiments at 7 div–14 div . The mice were anesthetized with 10% chloral hydrate ( 0 . 12 ml/10 g ) and perfused with 0 . 9% NaCl , followed by a 100 ml mix of 1% paraformaldehyde and 1% glutaraldehyde , made in PBS ( pH 7 . 4 ) . After perfusion , cerebella were dissected and stored in fresh fixative overnight at 4°C . 0 . 5 to 1 mm sagittal sections of each cerebellum were postfixed with 2% osmium tetroxide for 2–3 h , dehydrated through an ascending series of ethanol and embedded in epon812 . Ultrathin sections were cut , mounted on uncoated copper grids , stained with 2% uranyl acetate and 1% lead citrate for 12 min each . All the samples were observed using a Hitachi HT7700 electron microscope . Primary cultured cells were loaded with 2 µM Fluo-4 AM premixed with Pluronic F-127 in regular media for 30 min at 37ºC . Cells were washed in indicator-free media for three times and incubated for another 30 min to allow complete de-esterification of intracellular AM esters . Measurements were done at 37°C in Tyrode’s solution ( NaCl 129 mM , KCl 5 mM , CaCl2 2 mM , MgCl2 1 mM , Glucose 35 mM , and HEPES 20 mM ) , and we added high potassium Tyrode’s solution ( NaCl 5 mM , KCl 129 mM , CaCl2 2 mM , MgCl2 1 mM , Glucose 35 mM , and HEPES 20 mM ) to a final concentration of 90 mM KCl for depolarization . Cell imaging was taken by high resolution living Cell system DeltaVision Elite . Fresh cerebella were dissected from mice that were starved overnight and killed the next morning . Then lysosome isolation by subcellular fractionation from the mice cerebella was performed with a lysosome isolation kit ( Sigma-Aldrich ) according to the manufacturer's manual . After a discontinuous iodixanol gradient centrifugation using Optima MAX-XP Benchtop Ultracentrifuge ( Beckman Coulter ) with MLS-50 rotor at 150 , 000 × g and 4°C for 4 h , the sample was divided into ten fractions ( 0 . 5 ml each ) for further biochemical analyses . Lysosomes were enriched by centrifugation from a pool of three independent mouse brains in a discontinuous Nycodenz density gradient , as described in [41] , with modifications . Briefly , homogenate was prepared in assay buffer ( 0 . 25 M sucrose , pH 7 . 2 ) and centrifuged in succession at 4 , 800 × g , 5 min , and 17 , 000 × g , 10 min . The sediment of the second centrifugation was washed at 17 , 000 × g , 10 min , resuspended 1:1 vol/vol in 84 . 5% nycodenz , and placed on the bottom of an Ultraclear ( Beckman ) tube . On top , a discontinuous gradient of Nycodenz was constructed ( layers from bottom to top were: 32 . 8% , 26 . 3% , and 19 . 8% Nycodenz ) . Centrifugation was for 1 h in an SW 40 Ti rotor ( Beckman ) at 141 , 000 × g . Lysosomes were collected from the 26 . 3/19 . 8 interface , diluted in 5–10 volumes of assay buffer and centrifuged at 37 , 000 × g , 15 min . Pellet was resuspended in 500 μl of assay buffer . Data were analyzed by two-tailed unpaired Student’s t test . A p-value of <0 . 05 was considered statistically significant . | Autophagy is a cellular process used by cells to prevent the accumulation of toxic substances . It delivers misfolded proteins and damaged organelles by fusing autophagosomes—organelles formed by a double membrane that surrounds the “debris” to be eliminated—with lysosomes . How this fusion process is regulated during autophagy , however , remains to be established . Here , we analyze this process in flies and mice , and find that loss of different subunits of a specific type of Voltage Gated Calcium Channel ( VGCC ) leads to defects in lysosomal fusion with autophagosomes in neurons . It was already known that VGCCs control calcium entry at synaptic terminals to promote the fusion of synaptic vesicles with the plasma membrane , and that mutations in the subunits of VGCCs in humans cause neurological diseases . Our data indicate that defects in autophagy and lysosomal fusion are independent of defects in synaptic vesicle fusion and neurotransmitter release , and we show that a specific VGCC is present on lysosomal membranes where it is required for lysosomal fusion with endosomes and autophagosomes . These observations suggest that the fusion events required in autophagy rely on mechanisms similar to those that trigger the fusion of synaptic vesicles with the presynaptic membrane . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | A Voltage-Gated Calcium Channel Regulates Lysosomal Fusion with Endosomes and Autophagosomes and Is Required for Neuronal Homeostasis |
Human respiratory syncytial virus ( RSV ) is the leading viral cause of acute pediatric lower respiratory tract infections worldwide , with no available vaccine or effective antiviral drug . To gain insight into virus-host interactions , we performed a genome-wide siRNA screen . The expression of over 20 , 000 cellular genes was individually knocked down in human airway epithelial A549 cells , followed by infection with RSV expressing green fluorescent protein ( GFP ) . Knockdown of expression of the cellular ATP1A1 protein , which is the major subunit of the Na+ , K+-ATPase of the plasma membrane , had one of the strongest inhibitory effects on GFP expression and viral titer . Inhibition was not observed for vesicular stomatitis virus , indicating that it was RSV-specific rather than a general effect . ATP1A1 formed clusters in the plasma membrane very early following RSV infection , which was independent of replication but dependent on the attachment glycoprotein G . RSV also triggered activation of ATP1A1 , resulting in signaling by c-Src-kinase activity that transactivated epidermal growth factor receptor ( EGFR ) by Tyr845 phosphorylation . ATP1A1 signaling and activation of both c-Src and EGFR were found to be required for efficient RSV uptake . Signaling events downstream of EGFR culminated in the formation of macropinosomes . There was extensive uptake of RSV virions into macropinosomes at the beginning of infection , suggesting that this is a major route of RSV uptake , with fusion presumably occurring in the macropinosomes rather than at the plasma membrane . Important findings were validated in primary human small airway epithelial cells ( HSAEC ) . In A549 cells and HSAEC , RSV uptake could be inhibited by the cardiotonic steroid ouabain and the digitoxigenin derivative PST2238 ( rostafuroxin ) that bind specifically to the ATP1A1 extracellular domain and block RSV-triggered EGFR Tyr845 phosphorylation . In conclusion , we identified ATP1A1 as a host protein essential for macropinocytic entry of RSV into respiratory epithelial cells , and identified PST2238 as a potential anti-RSV drug .
Human respiratory syncytial virus ( RSV ) is the leading viral cause of severe lower respiratory tract infections in infants and young children worldwide [1] . RSV-associated acute lower respiratory infection of children younger than 5 years of age causes ~118 , 000 deaths worldwide annually [2] . So far , no licensed RSV vaccine or effective antiviral drug is available , although a number of vaccine and drug candidates are under development . Understanding the fundamental mechanisms of virus-host interactions and identifying factors critical for RSV infection might lead to the development of new antiviral drugs . RSV has a single stranded , non-segmented , negative sense RNA genome and belongs to the genus Orthopneumovirus of the family Pneumoviridae within the order Mononegavirales [3] . The genome is approximately 15 . 2 kb long and contains 10 genes that encode 11 proteins , namely ( in 3’ to 5’ genomic order ) the nonstructural proteins NS1 and NS2; nucleocapsid ( N ) ; phosphoprotein ( P ) ; matrix protein ( M ) ; small hydrophobic ( SH ) , attachment ( G ) , and fusion ( F ) glycoproteins; M2-1 and M2-2 proteins that are encoded by the two overlapping open reading frames in the M2 gene; and large polymerase protein ( L ) [4] . The envelope glycoproteins G and F mediate viral attachment and fusion , for entry into the host cell , while SH forms ion channels whose role in infection remains unclear . SH and G are not essential for virus replication in immortalized cell lines [5–7] , but G is important for efficient replication in vivo [8] . A number of host proteins and pathways have been suggested to play roles in RSV attachment and entry , but a detailed understanding remained elusive . For instance , it was shown that RSV utilizes lipid rafts in cholesterol-rich microdomains on the cell surface known as caveolae as a docking platform for entry [9] . Cell surface glycosaminoglycans ( GAGs ) appear to be important in RSV attachment to immortalized cell lines [10] , but GAGs do not appear to be present on the apical surfaces of primary epithelial cells and so may not play an important role in vivo . The G protein contains a CX3C motif reported to mediate cell attachment by binding to the chemokine receptor CX3CR1 [11 , 12] . Nucleolin also has been reported as a cellular receptor for RSV that is bound by the F protein [13] . Epidermal growth factor receptor ( EGFR ) signaling has been postulated to play a role in triggering macropinocytic uptake of RSV [14] , but how this occurs was unknown . It remained unknown if EGFR alone is sufficient or requires other factors to initiate signaling , or if EGFR and its associated signaling are somehow physically linked with caveolae . While RSV entry generally has been thought to involve fusion between the viral envelope and the plasma membrane , new evidence suggested either of two additional , different uptake pathways , namely EGFR-triggered macropinocytosis [14] and clathrin-mediated endocytosis [15] . It is unclear if one or both are involved . We describe an in vitro genome-wide siRNA screen that was performed to identify cellular proteins with presumptive roles in RSV infection . One of the proteins identified by this screen was described previously [16] . Another protein that was identified is ATP1A1 ( GenBank ID: 476 ) , the α-subunit of the Na+ , K+-ATPase complex located in the plasma membrane . This complex contains in addition a β-subunit , and usually also a γ-subunit ( also known as the FXYD subunit ) [17 , 18] . ATP1A1 is the major subunit and contains ten transmembrane helices that embed the protein complex in the plasma membrane and form the ion channel . The β and FXYD subunits are important for the ion transport properties of the Na+ , K+-ATPase and also stabilize the complex [19] . Humans express three additional α-isoforms beside ATP1A1 ( ATP1A2 , ATP1A3 , and ATP1A4 ) . The expression profile of the four isoforms is cell type-dependent , with ATP1A1 being expressed ubiquitously and being the predominant isoform in A549 cells [20] ( minor amounts of ATP1A3 have been found in A549 cells , but are 50-fold reduced compared to ATP1A1 [20] ) . In the ciliated epithelial cells lining the nasopharynx and the bronchi of both mice and humans , Na+ , K+-ATPase bearing ATP1A1 is present in greater abundance on the basolateral surfaces and in lower abundance on the apical surface; it also is readily detected in human alveolar cells including on the luminal surface [21–23] . Na+ , K+-ATPase plays a major role in ion transport , maintaining electrolyte and fluid balance . In addition , a subpopulation of Na+ , K+-ATPase that is localized in caveolae [24 , 25] uniquely can engage in signal transduction , via the ATP1A1 subunit [17 , 26–28] . Na+ , K+-ATPase , bearing the ATP1A1 subunit , has been well-characterized as the sole receptor for cardiotonic steroids ( CTS ) such as ouabain , which are its sole known agonists initiating signaling . Ouabain has been reported in humans as an endogenous hormone-like agent that contributes to the regulation of blood pressure , among other things , via ATP1A1 signaling [29] . ATP1A1 does not possess a known cytoplasmic signaling domain , but it interacts through its cytoplasmic tail with the cellular kinase c-Src [30] . ATP1A1 initiates signaling by conferring a conformational change to c-Src that exposes its kinase domain , leading to activation through autophosphorylation of c-Src at tyrosine 418 [30] . This can trigger several different signaling pathways , which can lead to the induction of endocytosis by more than one mechanism . For example , activated c-Src can mediate phosphorylation and activation of EGFR in an EGF-independent manner [31 , 32] , which can induce macropinocytosis [31] , similar to the well-characterized EGF-induced macropinocytosis [33 , 34] . Activated c-Src also can trigger signaling through the PI3K pathway to induce clathrin-mediated endocytosis [17 , 26] . Incidentally , this results in removal of Na+ , K+-ATPase from the plasma membrane for degradation in the lysosome [35 , 36] , resulting in decreased ion channel activity and increased blood pressure . This can be reversed by a synthetic digitoxigenin derivative called PST2238 ( or rostafuroxin ) , which competitively inhibits ouabain binding and signaling [37] and is being evaluated as a therapeutic to lower this kind of hypertension [38] . Here , we report a novel role for ATP1A1 signaling in enabling RSV entry into human airway epithelial cells . We demonstrate that RSV induces the signaling function of ATP1A1 to enable cell entry by a mechanism that is dependent on the activation of c-Src and EGFR . We also show that this signaling results in the induction of macropinocytosis , which appears to be a major route for uptake of RSV into the cell , with membrane fusion presumably occurring in the macropinosomes . We also provide evidence that RSV-induced ATP1A1 activation and signaling occur in the caveolae and can be inhibited by cholesterol depletion . The cardiotonic steroid ouabain or the digitoxigenin derivative PST2238 inhibit RSV-triggered ATP1A1 activation , prevent RSV entry , and thus could serve as a target for antiviral drug development .
We performed a genome-wide high-throughput siRNA screen in which the expression of ~ 21 , 500 cellular genes was individually knocked down in human airway epithelial A549 cells by three individual siRNAs per gene , followed by infection with recombinant RSV expressing enhanced green fluorescent protein ( RSV-GFP ) . Knockdowns that reduced GFP expression at 48 h post-infection ( p . i . ) with minimal effect on cell viability indicated a presumptive role for that protein in RSV replication . ATP1A1 was among the genes with the strongest effect on RSV-GFP ( S1 Table ) which was confirmed with additional , different siRNAs . Three siRNAs with the greatest effect on ATP1A1 expression and RSV infection were used for further experiments , and in addition two different scrambled siRNAs ( Neg . siRNA 1 and 2 ) were included as negative controls . To confirm the efficiency of knockdown of ATP1A1 mRNA , A549 cells were transfected with this set of five siRNAs . ATP1A1 mRNA level and the expression of ATP1A1 protein was quantified at different time points post transfection by TaqMan assay and Western blotting , respectively , and reported relative to Neg . siRNA1 at 48 h p . t . ( Fig 1 ) ; and time course over 72 h ( S1 Fig ) . At 48 h post transfection ( p . t . ) , the level of ATP1A1 mRNA was reduced to below 5% compared to Neg . siRNA 1 ( Fig 1A ) that resulted in a reduction of the ATP1A1 protein expression at 48 h p . t . to 39% ( siRNA1 and 3 ) and 35% ( siRNA2 ) ( Fig 1C ) and did not show any further reduction at 72 h p . t . ( S1 Fig ) . The transfected cells showed no visible cytotoxicity or morphological changes over the period of 72 h . For more sensitive evaluation , cellular ATP , which reflects cell viability , was measured in cell lysates at 72 h p . t . The ATP1A1 siRNA knockdown showed only minimal reductions in cell viability ( S1D Fig ) . A549 cells were transfected with the panel of siRNAs targeting ATP1A1 , and 48 h later the cells were infected with RSV-GFP at an MOI of 1 plaque forming unit ( PFU ) /cell . The efficiency of virus infection and replication were evaluated by GFP expression quantified by ELISA reader ( Fig 2A ) and flow cytometry ( Fig 2C and 2D ) . By ELISA reader , all three ATP1A1-specific siRNAs reduced the amount of GFP expression by about 50 to 75% compared to Neg . siRNA 1 ( Fig 2A ) . This level of reduction was substantial given that the residual level of ATP1A1 expression remained 35% or greater , as was shown in Fig 1C . We also investigated effects on infection with vesicular stomatitis virus expressing GFP ( VSV-GFP ) . ATP1A1 knockdown had no effect on GFP expression by VSV-GFP ( Fig 2B ) . This indicated that the reduction in GFP expression observed with RSV-GFP was specific to RSV , did not affect VSV , and was not due to some general effect on cellular functions . Analysis of cells infected with RSV-GFP ( MOI = 1 . 0 PFU/cell ) by flow cytometry 24 h p . i . showed that knockdown of ATP1A1 resulted in a broad reduction in GFP expression in the infected-cell population rather than a reduction in the number of GFP-expressing cells ( Fig 2C and 2D ) . The effect of transfection with the panel of siRNAs on the production of progeny RSV-GFP were assessed 24 h p . i . The infected cells were collected by scraping , vortexed to release cell-associated virus , and pelleted by centrifugation . Virus titers in the clarified supernatants were quantified by plaque titration on Vero cells ( Fig 2E ) . This showed that , with ATP1A1 knockdown , RSV titers were reduced between 5- ( siRNA3 ) and 42-fold ( siRNA2 ) compared to Neg . siRNA 1 , an effect that was even more dramatic than the reduction in GFP expression described above ( Fig 2E versus 2A and 2D ) . ATP1A1 siRNA 2 showed the strongest effect against both GFP expression and virus production . A549 cells were infected with wt RSV ( MOI = 5 PFU/cell ) , fixed at various times p . i . , and subjected to immunofluorescence staining for ATP1A1 and RSV F protein . In mock-treated cells , ATP1A1 was homogeneously distributed on the plasma membrane ( Fig 3A , top panel ) . Following infection with wt RSV , clusters of ATP1A1 were observed as early as 15 min p . i . ( Fig 3A , second panel ) , whereas these clusters were not evident in uninfected cells ( Fig 3A , top panel ) . With time , the ATP1A1 clusters became more prominent and numerous , as shown for 30 min and 5 h p . i . ( Fig 3A , third and fourth panel ) . All shown timepoints are very early in the RSV replication cycle . Some ATP1A1 clusters , but not all , partially co-localized with RSV F protein ( Fig 3A , indicated by arrows ) . The localization of clustered ATP1A1 in close proximity to RSV F became more noticeable at later time points such as 5 h p . i . ( Fig 3A , bottom panel ) . Localization of ATP1A1 clusters close to RSV N protein also could be observed ( Fig 4 and S2 Fig ) : co-localization with both F and N suggested that the RSV-specific staining most likely reflects enveloped virions ( which had not yet fused ) . Similar clustering of ATP1A1 and RSV N protein also was observed for UV-inactivated RSV ( S2 Fig ) , indicating that the staining largely involved pre-formed proteins from the incoming virus , and that clustering does not require transcription of the complete viral genome , viral RNA replication , or virus replication . Cross-sections ( Fig 3B ) and a ZY-view movie ( S1 Movie ) of images of RSV-infected A549 cells 5 h p . i . indicate that the ATP1A1 clustering occurred at the cell surface and was localized close to the RSV virions . Given the very early appearance of ATP1A1 clusters , independent of viral transcription or replication , we hypothesized that ATP1A1 might be involved in an early step of infection such as viral entry . As another means of exploring early events in RSV infection , we investigated whether RSV mutants bearing the deletion of the SH protein ( dSH ) or the combined deletion of SH and the attachment G glycoprotein ( dSH/dG ) retained the ability to trigger the clustering of ATP1A1 ( deletion of RSV F could not be investigated because it abrogates infectivity ) . A549 cells were infected with wt RSV , RSV dSH , or RSV dSH/dG ( MOI = 10 PFU/cell ) and incubated for 5 h . Cells were fixed , permeabilized and immunostained with antibodies specific to ATP1A1 ( green ) and RSV N ( red ) ( Fig 4 ) . Wt RSV was included as a reference and showed increased cluster formation compared to Fig 3 , which may have been due to the increased MOI of 10 PFU/cell compared to 5 PFU/cell . The RSV dSH virus induced clustering that was very similar to that with wt RSV , indicating that deletion of the SH protein seemed to have no effect on ATP1A1 clustering . On the other hand , the dSH/dG virus did not induce any ATP1A1 clustering , and the viral particles , stained for RSV N in red , were reduced in amount and were much more dispersed as compared to wt RSV and the dSH virus . The lack of ATP1A1 cluster formation with the dSH/dG virus suggested that RSV G protein is involved in triggering ATP1A1 clustering . The clustering of ATP1A1 in response to RSV exposure suggested that its signaling function might play a role in RSV infection . For example , ATP1A1 signaling cascades can result in the induction of endocytosis including clathrin-mediated or caveolin-mediated endocytosis , or macropinocytosis , which could be involved in RSV entry . The only known agonists for ATP1A1 signaling are CTS such as ouabain , which activate non-receptor tyrosine kinase Src-mediated signaling pathways [29] . The synthetic digitoxigenin derivative PST2238 is a competitive inhibitor of ouabain that inhibits ouabain binding and signaling [37] . Therefore , we tested ouabain and PST2238 for their effects on RSV infection . Serial dilutions of ouabain and PST2238 were evaluated for cytotoxicity on A549 cells ( S3C and S3D Fig ) , and we selected concentrations for ouabain ( 25 nM ) and PST2238 ( 20 μM ) that had less than 20% reduction in cell viability 24 h post treatment , which was the longest treatment period for these studies . The effects of ouabain and PST2238 on ATP1A1 and EGFR expression were analyzed by immunofluorescence microscopy ( Fig 5A ) using antibodies specific for ATP1A1 and EGFR . EGFR was evaluated in addition to ATP1A1 because it previously was shown to be important for RSV entry [14] and is closely associated with the ATP1A1 signalosome [31 , 32] . In mock-treated cells , ATP1A1 and EGFR had homogeneous membrane distributions ( Fig 5A , left column ) . After 24 h treatment with ouabain , the ATP1A1 level was greatly reduced ( Fig 5A , middle column , top panel ) –presumably due to the removal of cell-surface Na+ , K+-ATPase by clathrin-mediated endocytosis induced by ATP1A1 signaling [35 , 36]—while EGFR expression and localization appeared unchanged ( Fig 5A , middle column , bottom panel ) . On the other hand , PST2238 ( Fig 5A , right panel ) had no discernible effect on the expression and localization of ATP1A1 or EGFR: this drug does not cause removal of ATP1A1 because it does not induce ATP1A1 signaling and endocytosis . To evaluate possible effects on RSV infection , A549 cells were pre-treated for 16 h with ouabain or PST2238 , inoculated with RSV-GFP ( MOI = 1 PFU/cell ) and incubated with the compounds present throughout . RSV infection was evaluated by ( i ) GFP expression 17 h p . i . ( Fig 5B ) , and ( ii ) the yield of progeny RSV harvested 24 h p . i . , quantified by plaque assay on Vero cells ( Fig 5C ) . Both methods correlated well , and demonstrated a reduction in RSV replication for both compounds that was greater than that achieved with the ATP1A1-specific siRNAs ( Fig 2 ) . Ouabain had the strongest effect: it reduced viral GFP expression by 96% and virus yield by almost 3 . 0 log10 compared to infected cells that did not receive the drug , and the corresponding reductions observed with PST2238 were 89% ( GFP reduction ) and 2 . 0 log10 ( reduction in viral yield ) . To investigate the stage of RSV infection that is inhibited by the compounds , a “time of addition” experiment was performed . A549 cells were infected with RSV-GFP ( MOI = 3 PFU/cell ) , and at different times p . i . ouabain ( Fig 5D and 5E ) or PST2238 ( Fig 5F and 5G ) was added . Cells were incubated for a total of 24 h p . i . and the viral GFP expression intensity of single , live cells was analyzed by flow cytometry . For both compounds , the strongest inhibitory effect was observed when the inhibitor was added simultaneously with RSV-GFP at 0 h , resulting in 85% and 66% reduction of GFP expression by ouabain and PST2238 , respectively ( Fig 5D–5G ) . The inhibition of infection continued to diminish and was almost completely lost when the drugs were added at 10 h p . i . These results suggest a role for ATP1A1 early in infection , such as uptake and entry . We also investigated whether PST2238 treatment had any effect on the clustering of ATP1A1 that was noted above in response to RSV . A549 cells were pretreated with PST2238 as described above and visualized by confocal microscopy . PST2238 treatment had no apparent effect on ATP1A1 clustering . This indicates that clustering of ATP1A1 did not depend on signaling from ATP1A1 and occurs prior to the step blocked by PST2238 . We next investigated the downstream signaling pathways of ATP1A1 that might be involved in ATP1A1-dependent RSV entry . Binding of ouabain to ATP1A1 activates the c-Src-kinase that transactivates EGFR signaling [17] . Therefore , we investigated whether c-Src activity is needed for RSV infection , which was done using two Src-kinase inhibitors PP2 and Src-Inhibitior I ( SrcI-I ) . A549 cells were pre-treated with these inhibitors separately or together for 5 h , using concentrations that preliminary studies showed were non-cytotoxic ( S4 Fig ) , followed by infection with RSV-GFP ( MOI = 1 PFU/cell ) in the continued presence of inhibitors . The efficiency of RSV infection was evaluated by ( i ) GFP expression at 17 h p . i . for all treatments ( Fig 6A ) , and ( ii ) RSV titration at 24 h p . i . for cells that had been treated with both inhibitors ( SrcI-I+PP2 ) ( Fig 6B ) . Each Src-inhibitor showed a modest but significant ( p < 0 . 0001 ) reduction in GFP intensity of 23% ( SrcI-I ) and 33% ( PP2 ) relative to mock-treated infected cells . When added together , the inhibitory effect increased to 45% reduction compared to mock-treated infected cells . The RSV titer ( PFU ) for the combined Src-inhibitor treatment showed a 2-fold , significant ( two-tailed , unpaired t-test , p = 0 . 0014 ) reduction compared to mock-treated infected cells . These data confirmed that Src-kinase activity contributes to RSV infection . Next , we investigated whether EGFR , a downstream signaling partner of Src-kinase , made a contribution to RSV infection . We identified an EGFR-specific siRNA that reduced EGFR expression in A549 cells to 15% at the protein level compared to Neg . siRNA1 48 h p . t . ( S5 Fig ) , with minimal effect on cell viability . A549 cells were transfected with EGFR-specific , ATP1A1-specific , or control siRNA for 48 h and evaluated by immunofluorescence staining for EGFR and ATP1A1 . This showed that the ATP1A1 and EGFR siRNAs greatly reduced the expression of their corresponding target proteins ( Fig 7A , ATP1A1 top panel; EGFR: bottom panel ) without affecting EGFR and ATP1A1 , respectively , whose expression remained similar to that of Neg siRNA 1 . EGFR knockdown cells were infected with RSV-GFP and infection was evaluated by viral GFP intensity quantified by ELISA reader 17 h p . i . ( Fig 7B ) and by plaque titration 24 h p . i . on Vero cells ( Fig 7C ) . EGFR knockdown resulted in a nearly 50% reduction in viral GFP expression ( Fig 7B ) as compared to Neg . siRNA 1 ( p = 0 . 0001 ) . There also was a 38% reduction in RSV titer compared to Neg . siRNA 2 ( p = 0 . 0015 ) or mock-transfected cells ( p = 0 . 0001 ) ( Fig 7C ) . There was a modest but consistent reduction in PFU titer for Neg . siRNA1 for unknown reason and hence the reduction in titer for EGFR siRNA treated cells was not significantly lower compared to this particular control siRNA ( ns , p = 0 . 9891 ) , but as noted above the reduction in GFP expression was highly significant . None of the siRNAs had an effect on cell viability ( Fig 7D ) . Taken together , these data confirm that EGFR plays a role in RSV infection . We next investigated EGFR phosphorylation during RSV infection . As described in Fig 8 , A549 cells were pretreated by transfection with ATP1A1 siRNA 1–3 , or Neg . siRNAs 1 and 2 , or were pretreated with ouabain , PST2238 , or the Src-inhibitors SrcI-1+PP2 . The cells were then infected with RSV ( MOI = 5 PFU/cell ) and lysates were prepared following 5 h of incubation . The lysates were analyzed using an EGFR phosphorylation array to identify the EGFR sites that were phosphorylated during infection . EGFR in RSV-infected A549 cells was phosphorylated at Tyr845 , which was not detected for uninfected cells ( Fig 8 and S6A Fig ) , whereas both samples showed nearly equivalent phosphorylation of ErbB2 ( another member of the human EGFR family ) at Thr686 and Ser1113 ( S6 Fig ) . The level of pTyr845 in RSV-infected cells was significantly ( p < 0 . 0001 ) reduced in the ATP1A1 siRNA knockdown cells , to an average of 35% ( siRNA1 ) , 22% ( siRNA2 ) , and 33% ( siRNA3 ) relative to Neg . siRNA1 ( Fig 8B ) . The phosphorylation of Tyr845 in RSV-infected cells was similar to Neg . siRNA1 . While it was slightly reduced for Neg . siRNA2 , the difference was not significant ( p = 0 . 3651 ) compared to Neg . siRNA1 . Consistent with the ATP1A1 knockdown , a significant reduction in Tyr845 phosphorylation also was observed when the cells were pre-treated with ouabain , PST2238 , or Src-kinase inhibitors ( SrcI-I +PP2 ) prior to infection with RSV ( Fig 8C ) . For ouabain- and PST2238-treated cells , the level of pTyr845 was reduced to 27% and 26% , respectively , compared to mock-treated RSV-infected cells; the reduction was similar to that observed for ATP1A1 knockdown . To confirm a lack of a direct inhibitory effect of Ouabain or PST2238 on EGFR , A549 cells were pre-treated with PST2238 or Ouabain and stimulated with EGF for 45 min . The EGF-induced phosphorylation of pTyr845 indeed was not affected by the compounds as compared to mock-treated cells ( Fig 8D ) . The Src-kinase inhibitors ( SrcI-I+PP2 ) reduced phosphorylation at Tyr845 to 12% compared to mock-treated infected cells ( Fig 8C ) . Thus , phosphorylation at EGFR Tyr845 could be reduced either by decreasing ATP1A1 expression or by ATP1A1- or Src-specific inhibitors . This suggested that EGFR pTyr845 is ATP1A1-dependent and that Src-kinase serves as a signaling effector to transactivate EGFR by Tyr845 phosphorylation . EGFR signaling is known to cause actin rearrangement , membrane ruffling , and activation of endocytosis and macropinocytosis [31 , 33 , 34] . Macropinocytosis is a nonspecific , fluidic uptake at the cell surface that initiates through actin rearrangement and membrane ruffling that give rise to large vesicles called macropinosomes . Limited prior evidence suggested macropinocytosis as a route of RSV uptake [14 , 16] . In the present study , A549 cells were infected with wt RSV ( MOI = 5 PFU/cell ) in the presence of dextran ( 10 , 000 MW ) conjugated to fluorescent dye ( Alexa Fluor [AF] 568 ) as a fluidic uptake marker . At different time points p . i . , cells were washed and fixed , nuclei were counterstained with DAPI , and the uptake of dextran was analyzed by fluorescence confocal microscopy . Cells that had been mock-infected were found to contain dextran-positive vesicles that were small , round , and homogeneous in size with an average volume of ~ 0 . 5 μm3 ( Fig 9A , top panel ) , reflecting the basal level of dextran uptake . This phenotype changed dramatically by 5 h after infection with wt RSV ( Fig 9A , bottom panel ) . The dextran-positive vesicles were much bigger ( average volume of ~5 . 7 μm3 ) and irregular in shape , as is typical of macropinosomes . The induction of large dextran-positive vesicles also was visible at earlier time points and could be detected as early as 30 min p . i . and became more prominent at 1 h p . i . ( S7 Fig ) . This showed that RSV infection induces macropinocytosis . Next , A549 cells were infected with RSV in the presence of dextran-AF568 ( cyan ) , and at 5 h p . i . were co-stained for ATP1A1 ( AF488; green ) and RSV N ( marker of RSV virions; AF647; red ) and visualized by fluorescence confocal microscopy . As previously noted , 5 h p . i . is very early in RSV infection , and the N protein that is detected would be mainly from the input virus particles , as was shown earlier with UV-inactivated virus . Clusters of ATP1A1 were observed co-localized with RSV N protein in the dextran-positive macropinosomes ( Fig 9B , indicated by arrows ) , indicating that RSV was indeed taken up by macropinocytosis . Co-staining for RSV F and N was also performed and showed that both proteins were co-localized in the dextran-positive macropinosomes ( Fig 9C ) . The presence of RSV F suggests that the RSV detected in the macropinosomes was enveloped , indicating that fusion and release of nucleocapsid presumably occurs subsequently in the internal vesicles rather than at the plasma membrane . To examine the role of ATP1A1 in this putative uptake mechanism , ATP1A1 expression was knocked down with siRNA , or the cells were treated with ouabain or PST2238 as previously described . Next , these cells were infected with RSV ( MOI = 5 PFU/cell ) in the presence of dextran-AF568 , followed by fluorescence confocal microscopy . Multiple random Z-stack images were acquired by confocal microscopy , and dextran-positive vesicles were analyzed by Imaris imaging software to determine the total fluorescence intensity per vesicle . Vesicles smaller than 1 . 0 μm3 were excluded to omit the basal level of dextran uptake and to focus on the large vesicles that are typical for macropinosomes . The total intensity of dextran vesicles larger than 1 . 0 μm3 was determined per field , normalized to the number of nuclei and expressed relative to Neg . siRNA1-transfected cells ( Fig 9D ) . This showed that dextran uptake was increased 4-fold in RSV-infected as compared to uninfected-cells , which had both been transfected with Neg . siRNA1 ( Fig 9D ) , confirming the visual observation of increased dextran-AF568 uptake ( Fig 9A ) . On the other hand , knockdown of ATP1A1 caused a significant ( p = 0 . 0003 ) reduction of 33% compared to Neg . siRNA1 ( Fig 9D ) . Ouabain and PST2238 caused an even-greater reduction in RSV-induced macropinosomes , to less than 50% compared to mock-treated , RSV-infected cells ( Fig 9E ) . Since RSV G was suggested to be important for triggering ATP1A1 activation , based on the loss of clustering observed with the dSH/dG mutant as described previously in Fig 4 , we also quantified macropinosomes in cells infected with wt RSV or the dSH/dG RSV mutant . This showed that macropinosome formation indeed was significantly ( p = 0 . 0039 ) reduced for the dSH/dG virus as compared to wt RSV ( Fig 9F ) , consistent with a role for the G protein in activating the pathway leading to macropinosome formation . Signaling from ATP1A1 also can induce clathrin-mediated endocytosis [17 , 26] , and this endocytic pathway has been controversially suggested to be involved in RSV uptake [15] . However , preliminary studies in our hands using an inhibitor of clathrin-mediated endocytosis ( e . g . , chlorpromazine ) did not detect effects on RSV infection at non-cytotoxic concentrations ( S8 Fig ) , and this was not pursued further . ATP1A1-Src-EGFR signaling characteristically is associated with caveolae [17 , 26–28] . The structural integrity of caveolae depends on the presence of cholesterol , and cholesterol-depletion disrupts caveolae from the plasma membrane [39 , 40] . We therefore evaluated the impact of depleting cholesterol in A549 cells prior to RSV infection , which was done using methyl-beta-cyclodextrin ( MBCD ) and Mevinolin , individually or in combination at non-cytotoxic concentrations ( S4 Fig ) . MBCD removes cholesterol from the plasma membrane whereas Mevinolin inhibits its biosynthesis . First , we infected cholesterol-depleted A549 cells with RSV-GFP and found that GFP expression at 17 h p . i . was reduced to approximately 50% with each of the depletions , compared to control infected cells ( Fig 10A ) . Next , we quantified the level of RSV-induced macropinocytosis in cholesterol-depleted cells by dextran-AF568 uptake into large vesicles . In RSV-infected cells , dextran uptake was reduced by each of the cholesterol-depletion treatments , with the most significant ( p < 0 . 0001 ) reduction of 59% observed for the combined MBCD-Mevinolin treatment ( Fig 10B ) . The phosphorylation of EGFR Tyr845 also was determined in RSV-infected cells pretreated with MBCD + Mevinolin . A modest but significant ( two tailed t-test , p = 0 . 0163 ) reduction in pTyr845 was observed ( Fig 10C ) . These results show that cholesterol depletion results in reduced EGFR transactivation , reduced macropinocytosis , and reduced RSV infection , consistent with caveolae as the site of ATP1A1 signaling . All experiments described above were performed with the human airway epithelial A549 cell line . We sought to confirm some of the major findings using primary human small airway epithelial cells ( HSAEC ) from a 16-year old healthy male donor . SiRNA transfection knocked down the expression of ATP1A1 protein to 25–30% compared to Neg . siRNA 1 ( Fig 11A ) , which was somewhat more than the reduction to 35–39% observed for A549 cells . Following the same protocols as for A549 cells , we found that ( i ) knockdown of ATP1A1 reduced the expression of RSV-GFP to 29–42% of the negative control ( Fig 11B ) , similar to what was observed with A549 cells ( Fig 2A ) . ( ii ) Phosphorylation of EGFR Tyr845 was also significantly ( p = 0 . 0038 ) reduced in ATP1A1-knockdown ( siRNA2 ) HSAEC ( Fig 11C ) , similar to what was seen in A549 cells ( Fig 8 ) . ( iii ) The inhibitory effects of ouabain and PST2238 on the expression of RSV-GFP were even stronger in HSAEC than in A549 cells ( Fig 11D ) . IC50 titrations of the compounds on HSAEC for RSV-GFP expression showed that the values were lower ( i . e . , more effective inhibition ) in HSAEC than A549 cells by 4 . 9-fold for ouabain ( S3A Fig ) and 8 . 2-fold for PST2238 ( S3B Fig ) . ( iv ) RSV-induced ATP1A1 clustering and colocalization of ATP1A1 and RSV N also was observed in HSAEC ( Fig 11E ) , similar to A549 cells ( Fig 3 ) . In addition , we used HAE-ALI cultures , a model of primary , differentiated , polarized mucociliary airway epithelium , to investigate the localization of ATP1A1 and to confirm the phenomenon of RSV-induced ATP1A1 clustering . Cells were infected with wt RSV ( 106 PFU/transwell ) , incubated for 1h or 5 h , fixed with PFA , permeabilized with TritonX-100 , and immunostained for RSV F ( red ) and ATP1A1 ( green ) , as described for A549 cells in Fig 3 . The apical surface was demarcated by staining for F-actin ( cyan ) since it is abundant beneath the apical membrane and provides a close estimation of the apical surface location . To visualize ATP1A1 location , three-dimensional sections are shown without ( Fig 12A ) and with ( Fig 12B ) F-actin staining . In mock treated cells , ATP1A1 was predominantly present in the basolateral surfaces of cells with relatively smaller amounts present on the apical surface in a spotted distribution , ( Fig 12 , left panel ) . Upon infection with RSV , ATP1A1 clusters were visible as early as 1 h p . i . ( Fig 12A and 12B , middle panel ) , which became more noticeable and larger at 5 h p . i . ( Fig 12A and 12B right panel ) . The apical ATP1A1 seemed to increase in amount over time following infection , suggesting its recruitment to the apical surface . The ATP1A1 clusters were mostly visible in close proximity to RSV F . These observations were similar to those in A549 cells ( Fig 3 ) , confirming that RSV-induced ATP1A1 clustering could be reproducibly demonstrated in two different primary cell systems .
In the present study , we investigated the host proteins involved in RSV infection using a genome-wide high-throughput siRNA screen in human airway A549 cells infected with a recombinant RSV that expresses GFP . Knockdown of the cellular ATP1A1 protein provided one of the greatest reductions in GFP expression with minimal effects on cell viability . ATP1A1 is the major subunit of Na+ , K+-ATPase , a transmembrane complex that is an ATPase , an ion channel , and also is involved in signal transduction [17] . In this study , we provided evidence that ATP1A1—in particular its signal transduction function—is needed for efficient RSV infection . We attempted to evaluate the effect of reduced ATP1A1 expression on RSV infection in vivo using a heterozygous ATP1A1 knockdown mouse strain ( B6;129S5-Atp1a1Gt ( neo ) 311Lex/Mmucd; from the Mutant Mouse Resource & Research Centers ( MMRRC ) , University of California , Davis , RRID: MMRRC_011687-UCD ) . It was necessary to use the heterozygous ATP1A1+/- genotype because the homozygous ATP1A1-/- knock-out is lethal at the preweaning stage . No significant difference in the virus load was observed between ATP1A1+/- mice and their wild-type litter mates . This was not surprising , given the modest reduction in ATP1A1 expression ( reduced only by 30–35% compared to wt litter mates ) , which presumably was not sufficient to reduce the efficiency of RSV infection . Two ATP1A1-binding drugs , ouabain and PST2238 , were found to inhibit RSV infection . Inhibition of RSV infection with ouabain was achieved at sub-nanomolar concentrations that initiate ATP1A1 signaling cascades [17 , 26] but are not inhibitory for its ATPase and ion channel functions and do not alter the cytosolic Na+ and K+ levels [41] . While incubation with ouabain depletes Na+ , K+-ATPase over time from the plasma membrane , it is unlikely that this depletion was the sole mechanism for the inhibition of RSV infection , because the antiviral effect of ouabain was evident even when added simultaneously with the virus inoculum . We speculate that the mechanism of inhibition by shorter-term treatment with ouabain involves competition with RSV for ATP1A1 signaling , as is discussed later . Treatment with PST2238 also reduced the efficiency of RSV infection . PST2238 is a competitive inhibitor of ouabain that shares a common binding site on the extracellular domain of ATP1A1 . PST2238 does not induce signaling and indeed blocks ATP1A1 signaling in response to ouabain or RSV . Both of these ATP1A1-binding drugs implicated ATP1A1—and in particular ATP1A1 signaling—as being important for efficient RSV infection . Time-of-addition experiments indicated that the inhibitory effects of ouabain and PST2238 occurred very early during infection . We observed a striking phenomenon in which ATP1A1 formed clusters in the plasma membrane within 15 minutes following infection with RSV . This clustering was not affected by treatment with PST2238 , indicating that clustering does not depend on ATP1A1 signaling . Clustering of ATP1A1 occurred with equal efficiency with UV-inactivated RSV , and thus was independent of transcription of the complete genome , viral RNA replication , and virus replication . This clustering was reminiscent of the behavior of signaling receptors following ligand binding , and suggested there might be a physical interaction between the virions and the cell surface that triggers ATP1A1 clustering . Interaction of this sort could be imagined as part of viral attachment or part of a cellular response to RSV virions . However , we were unable to detect binding between ATP1A1 and any of the RSV surface glycoproteins ( G , F or SH ) by various co-immunoprecipitation techniques . For example , we investigated possible binding using the human lung epithelial cell line H1299 ATP1A1-YFP ( kindly provided by Uri Alon , Weizmann Institute of Science , Rehovot , Israel [42 , 43] ) that chromosomally expressed ATP1A1 genetically fused to yellow fluorescent protein ( YFP ) tag . These cells were infected with RSV , incubated for 1h and lysed , and co-immunoprecipitation was performed with YFP-specific antibodies followed by Western blotting with antibodies to RSV proteins . However , there was no evidence of pull-down of RSV proteins . We also performed comparable co-precipitation experiments in which , prior to lysis , cells were treated with the permeable , reversible cross-linker dithiobis ( succinimidyl propionate ) [44] . We also incubated RSV virions with ATP1A1 immobilized on beads . However , there was no evidence of binding between ATP1A1 and RSV proteins in these experiments . We also performed a cell-based binding assay [45] , using A549 cells that had been siRNA-transfected to knock down ATP1A1 . Specifically , the cells were transfected with ATP1A1 siRNA , incubated for 48 h , detached , and incubated on ice with RSV for 30 min , after which the cells were extensively washed and incubated with a pool of RSV F-specific monoclonal antibodies to detect possible bound virus . ATP1A1 knockdown did not result in an appreciable reduction in RSV binding , and thus we did not detect any contribution of ATP1A1 to RSV attachment . Treatment of the cells with heparinase I prior to RSV exposure to remove cell surface GAGs , which was done to eliminate GAG-mediated RSV attachment , also did not reveal any contribution of ATP1A1 to RSV attachment . Therefore , there was no evidence of stable binding of any RSV surface protein to ATP1A1 . It may be that an interaction between ATP1A1 and one or more RSV proteins occurs but is insufficiently stable to be detected by these methods . Using RSV deletion mutants , we did demonstrate that the RSV G protein is required to trigger ATP1A1 clustering . This implies that an initial virus attachment event involving G is needed to initiate ATP1A1 clustering . That initial attachment event might involve a direct interaction between RSV G and ATP1A1 , although there is as yet no evidence of this , as already noted . It perhaps is more likely that RSV attachment is an earlier event involving other cellular structures , and that attachment induces ATP1A1 signaling through some as-yet unknown intermediate step . Clustering of signaling receptors in general can increase ligand binding and signal transduction [46] by reducing the effective dissociation rate through enhancing rebinding within the receptor cluster [47] . Therefore , clustering of ATP1A1 may be beneficial for RSV infection by enhancing the ATP1A1-mediated signaling that is required for viral uptake . We hypothesized that RSV utilizes ATP1A1 signaling for uptake into the cell by endocytosis . This potentially could involve any of the various pathways including clathrin- or caveolin-mediated endocytosis or macropinocytosis . We showed that RSV infection indeed induces and requires ATP1A1 signaling , and confirmed that Src-kinase activity was required for efficient RSV infection . We also confirmed that EGFR is essential for efficient RSV infection , as previously shown [14] , but is not sufficient alone and requires the upstream activation of ATP1A1 and c-Src for efficient RSV infection . ATP1A1 signaling in response to ouabain results in clathrin-mediated endocytosis and the uptake and destruction of Na+ , K+-ATPase [35 , 36] . Clathrin-mediated endocytosis also has been controversially suggested to be involved in the uptake of RSV [15] . In preliminary experiments , inhibitors of clathrin-mediated endocytosis did not affect RSV infection . However , we found that RSV infection induced a high level of macropinocytosis , and that these macropinosomes contained a high content of RSV virions . Previous studies also have suggested a role for macropinocytosis in RSV uptake [14 , 16] . Macropinocytosis also can be induced through components of the ATP1A1 signaling pathway . For example , it has been described that phosphorylation of EGFR Tyr845 by c-Src , in an EGF-independent manner , can lead to the induction of macropinocytosis [31 , 32] , Src-kinase activity plays an important role during macropinosome formation and trafficking [48] , and can synergistically enhance macropinocytic induction [49] . Typical macropinosomes are formed as a result of extensive , nonspecific fluidic uptake at the plasma membrane ( reviewed in [25 , 33 , 49] ) that engulf fluid and solid cargo from outside of the cell into cytoplasmic vesicles . They are heterogeneous in size and are larger than other endocytic vesicles , with diameters of 0 . 5–5 μm . In RSV-infected cells , extensive macropinocytosis began very early in infection . Macropinosome formation under these conditions was confirmed to be dependent upon ATP1A1 , and was significantly reduced if ATP1A1 expression was decreased or if the cells were treated with ouabain or PST2238 . Depletion of cholesterol resulted in a decrease in the formation of macropinosomes , consistent with the involvement of signaling complexes in the caveolae . In addition , immunostaining revealed the co-localization of ATP1A1 , RSV F protein ( marker of viral envelope ) and RSV N protein ( marker of viral nucleocapsid ) , and dextran in macropinosomes . This supports a model in which RSV virions are taken up by the macropinosome , and membrane fusion and release of the nucleocapsid presumably taking place at a later step after the macropinocytic uptake . Although the data provide evidence on the role of ATP1A1 in macropinocytic uptake , they do not exclude the possibility of clathrin-mediated endocytosis as an additional mode of RSV entry . It was somewhat surprising that both ouabain and PST2238 inhibited RSV infection in short-term treatments , since they have opposite effects on ATP1A1 signaling , namely that ouabain induces and PST2238 inhibits signaling . The mechanism by which PST2238 inhibits RSV infection seems straight-forward: specifically , blockade of RSV-induced ATP1A1 signaling . The mechanism by which ouabain inhibits RSV infection is less clear , since both ouabain and RSV individually induce ATP1A1 signaling . We hypothesize that , while the signaling cascades induced by ouabain versus RSV employ some of the same signaling intermediates , their outcomes are not exactly the same . Ouabain-induced signaling results in clathrin-mediated endocytosis , whereas RSV-induced signaling results in macropinocytosis . Also , we could readily detect phosphorylation of EGFR Tyr845 following infection with RSV , but not following treatment with ouabain , suggestive of a quantitative or qualitative difference in EGFR phosphorylation . Thus , while signaling through ATP1A1 by ouabain versus RSV may involve a number of steps in a common signal transduction pathway , we suggest that the ouabain-induced signaling cascade from ATP1A1 not only is different from that of RSV , but also competes with and thereby inhibits ATP1A1 signaling induced by RSV . ATP1A1-mediated signaling cascades have been reported to take place in the cholesterol-rich microdomains called caveolae [27 , 28] , which are thought to serve as a region to integrate multiple signaling pathways by concentrating signaling proteins and creating temporal and spatial patterns of cell regulation [24] . Many proteins associated with signaling functions are present in the caveolae , including ATP1A1 , EGFR and c-Src [17 , 50 , 51] . It has also been described that cholesterol is needed for the ouabain-induced ATP1A1-Src-EGFR signaling cascade , and that depletion of cholesterol reduced the recruitment of c-Src and therefore reduced ATP1A1 signaling [27] . Interestingly , it has been reported that the cholesterol-rich lipid rafts are required as a docking platform for RSV entry [9] . In the present study , depletion of cholesterol with MBCD and Mevinolin indeed reduced the efficiency of RSV infection , consistent with the signaling by ATP1A1 , c-Src , and EGFR taking place in caveolae . We speculate that the inhibitory effects of depleting cholesterol could be due to disintegration of the caveolar ATP1A1-Src-EGFR signaling complexes . A number of key observations made using the A549 cell line were reproduced using primary human small airway epithelial HSAEC cultures , including inhibition of RSV-GFP by siRNA as well as by PST2238 and Ouabain , clustering of ATP1A1 on RSV exposure , and phosphorylation of EGFR . We also used differentiated HAE-ALI cultures to confirm clustering of ATP1A1 on RSV infection , and to evaluate the distribution of ATP1A1 in a polarized epithelial cell . This showed a strong basolateral presence of ATP1A1 and much reduced speckled expression on the apical surface . However , upon RSV infection , ATP1A1 cluster formation was observed on the apical surface , associated with an increase in the apical amount of ATP1A1 that might be due to increased trafficking to the apical surface . This also showed that the small amounts of apical ATP1A1 present in the uninfected cells is likely sufficient for initiating the signaling cascade . ATP1A1 also has been implicated as a pro-viral factor in the infection cycles of Ebola virus [52] , coronavirus [53] , hepatitis C virus [54] , and mammarenaviruses [55] , but the nature and mechanism of its involvement for those viruses remains largely unknown . In the present study , we showed that VSV infection was not inhibited by ATP1A1 knockdown , indicating that the effect is specific to particular viruses and does not involve a general inhibitory cellular effect . Ouabain has been described to have anti-viral properties for several viruses , namely herpes simplex virus [56 , 57] , chikungunya virus [58] , human immunodeficiency virus [59] , adenovirus [60] and porcine reproductive and respiratory syndrome virus [61] , but the mechanism of inhibition was not conclusively identified . It may be that ouabain inhibits these other viruses in the same way that we propose for RSV , namely that it competes with the virus for signaling through ATP1A1 . To our knowledge , PST2238 has not previously been investigated for anti-viral activity against any virus , including RSV . We speculate that PST2238 might also inhibit the replication of other viruses that are ouabain-sensitive by directly blocking ATP1A1 signaling . PST2238 is being evaluated as an anti-hypertensive drug in phase II clinical trials for ouabain- and adducin-induced hypertension patients [38] . PST2238 does not have any known adverse effects , does not lower the blood pressure of healthy humans [62] , and therefore might be well-tolerated as an anti-viral drug . The prevailing paradigm of virus spread involves packaging , release , and infection of the neighboring cells . However , an emerging model suggests direct cell-to-cell spread of partially assembled virions , nucleocapsids , and inclusion bodies via intercellular channels [63] . Given the very different nature of this exit/entry , likely requiring a different set of proteins and mechanisms , we speculate that ATP1A1 may not have a role in this and would be primarily engaged in mediating uptake of the extracellular packaged virions . The proposed direct intercellular spread presumably occurs only between adjoining cells , while ATP1A1 would be important for spread/uptake into non-contiguous cells . Note that most studies have described the direct intercellular transmission using cell lines ( reviewed in [63] ) . Specifically , among respiratory viruses , intercellular transmission in primary HAE cells has been shown only for measles virus [64] and this manner of spread for other respiratory viruses including RSV remains to be determined in a primary differentiated HAE-ALI system . In summary , we propose a model for RSV entry into human airway epithelial cells that is illustrated in Fig 13 . RSV infection activates ATP1A1 signaling by an unknown mechanism that involves the RSV G protein and does not rely on viral transcription and genome or virus replication . Activation of ATP1A1 leads to transactivation of EGFR that requires c-Src kinase activity . Signaling events downstream of EGFR cause actin rearrangement and ruffling at the plasma membrane , where membrane extensions engulf fluid and RSV into large vesicles—the macropinosomes . RSV is taken up in its enveloped form into the macropinosome , presumably followed by fusion and entry into the host cell . We also provided evidence suggesting that the ATP1A1-Src-EGFR signaling occurs predominantly in the cholesterol-rich domains of the caveolae which are thus important for efficient infection . This study identified ATP1A1 signaling as a new target for the development of anti-RSV drugs . PST2238 in particular is a drug that already has been shown to be well-tolerated in humans , specifically acts on ATP1A1 , decreases the efficiency of infection by reducing the RSV-ATP1A1 signaling needed for entry , and could be further developed as an antiviral drug for RSV .
A549 cells ( ATCC CCL-185 ) were maintained in F12-K media ( ATCC , Manassas , VA ) supplemented with 10% fetal bovine serum ( FBS , Thermo Scientific , Atlanta , GA ) and 1x L-Glutamine ( Life Technologies , Grand Island , NY ) , Vero cells ( ATCC CCL-81 ) were maintained in Opti-MEM I medium with GlutaMax-I ( Life Technologies ) supplemented with 5% FBS . Normal primary human small airway epithelial cells ( HSAEC ) ( ATCC PCS-301-010 ) were derived from a 16 year old male Hispanic/Latino donor ( Lot: 64079184 ) and were maintained in airway cell basal medium ( ATCC PCS-300-030 ) , supplemented with bronchial epithelial cell growth kit ( ATCC PCS-300-040 ) , and detached for passage using trypsin and trypsin-neutralizing solution formulated specifically for primary cells ( ATCC PCS-999-003 and ATCC PCS-999-004 . The primary cells were passaged a maximum of two times . HAE-ALI cultures ( EpiAirway , AIR-100 ) were obtained from MatTek Corporation ( Ashland , MA ) and were cultured at the air-liquid interface as described in the manufacturer’s protocol with the provided maintenance medium , with daily medium changes . The recombinant viruses RSV-GFP [65] , VSV-GFP [66] , wt RSV A2 ( Genbank accession # KT992094 ) , rgRSV-dSH and rgRSV-dSH/dG [7] have been previously described . For all experiments , virus stocks were purified on a discontinuous ( 60% and 30% w/v ) sucrose gradient as described previously [65] . Cell cultures were maintained at 37ºC and 5% CO2 , and any cells used in experiments were incubated under these conditions . The chemical compounds and inhibitors ouabain ( PubChem CID: 439501 ) , PST2238 ( rostafuroxin , PubChem CID: 153976 ) , Src-Inhibitor-I ( PubChem CID: 1474853 ) , PP2 ( PubChem CID: 4878 ) , methyl-beta-cyclodextrin ( MBCD , PubChem CID: 51051622 ) and Mevinolin ( Lovastatin , PubChem CID: 53232 ) were obtained from Sigma-Aldrich , St . Louis , MO . 50 μM ouabain stock solution was prepared in sterile ultrapure water . 10 mM stock solutions of PST2238 , Src-Inhibitor-I and PP2 were prepared in DMSO . 76 . 3 mM MBCD stock solution was prepared in F12 media . 1 mg/ml Mevinolin stock solution was prepared in 200 proof ethanol . Working stock solutions , at concentrations as indicated , were prepared in the appropriate cell culture media . Non-cytotoxic concentrations for all chemical compounds were determined by serial dilution on A549 cells ( see S3 Fig ) and the cytotoxicity was quantified by the ATP-based viability assay , as described below . The final DMSO concentration was below 0 . 2% and was considered not to have any effect on the cells as determined by DMSO control treated cells ( S3 Fig ) . The high-throughput screen was performed and the data were analyzed as described previously [67] . In brief , the siRNAs were from the Ambion Silencer Select Human Genome siRNA library version 4 ( Fischer Scientific ) , targeting ~21 , 500 human genes with 3 siRNAs per gene , evaluated individually . High throughput screening was performed in 384-well plates ( total of 186 plates ) using a Bravo VPrep liquid handler within a BioCel automation platform ( Agilent ) . Single siRNAs ( 0 . 8 pmol ) were added to wells followed by 20 μl of serum-free medium containing 0 . 12 μl Lipofectamine RNAiMax . The mixtures were incubated for 45 min at room temperature , followed by the addition of A549 cells that we had engineered to constitutively express DsRed as a viability marker . The final transfection mixtures contained 1000 A549 cells and 20 nM siRNA in F12 medium and 10% FBS . The cells were incubated for 48 h , RSV-GFP was added at a multiplicity of infection ( MOI ) of 1 PFU/cell , and cells were incubated for an additional 48 h . The cells were fixed with paraformaldehyde and stained with Hoechst 33342 . Images were acquired on an ImageXpress Micro XL ( Molecular Devices ) automated microscope and analyzed with associated MetaXpress software using the “Multi Wavelength Cell Scoring” analysis module . Ambion Silencer Select Negative Control #2 was present in all screening plates ( 16 wells ) and the median negative control value on each plate was used for normalization . An siRNA targeting GFP was used as a positive control ( 16 well per plate ) and yielded near-complete elimination of cells scoring positive for GFP . The median absolute deviation ( MAD ) based z-score was calculated for each siRNA [68] . Scores were adjusted for seed-based off-target effects to help deprioritize likely false positives [69] . The median seed-adjusted Z-scores are provided in the S1 Table . A549 and HSAEC cells were transfected with siRNA by reverse transfection with siLentFect transfection reagent ( Bio-Rad , Hercules , CA ) in 12-well plates . For the ATP1A1 and EGFR knock down the following siRNAs ( obtained from Qiagen , Germantown , MD ) were used: Hs_ATP1A1_5 ( named siRNA1 , CCC GGA AAG ACT GAA AGA ATA ) , Hs_ATP1A1_6 ( named siRNA2 , CTT GAT GAA CTT CAT CGT AAA ) , Hs_ATP1A1_7 ( named siRNA3 , ATC CAT GAA GCT GAT ACG ACA ) , Hs_EGFR_3 ( named EGFR siRNA , CAG AGG AAA TAT GTA CTA CGA ) . These were different from those used in the high throughput screen . The two negative control siRNAs were Neg . siRNA 1 ( AllStars Neg . Conrol siRNA [Qiagen 1027281 , sequence proprietary] ) and Neg . siRNA 2 ( Negative Control siRNA ( Qiagen 1027310 , AAT TCT CCG AAC GTG TCA CGT ) . Transfection methods were optimized with the cell death positive control siRNA ( AllStars Hs Cell Death siRNA control [Qiagen 1027299] ) . Cell viability was measured by an ATP-based assay CellTiter-Glo ( Promega , Madison , WI ) performed as described by the manufacturer . Cells in white 96-well plates were lysed and the ATP concentration was determined by luciferase activation . Luciferase light emission was analyzed using a Synergy 2 ELISA reader ( BioTek , Winooski , VT ) . Reduction in ATP relative to control cells was indicative of reduced viability . A549 or HSAEC cells in 12-well plates were lysed with 75 μl 1x LDS sample buffer ( Life Technologies ) . 22 . 5 μL aliquots of lysate were reduced , denatured , and electrophoresed on 4–12% Bis-Tris SDS gels ( Life Technologies ) . Proteins were transferred onto PVDF membranes using the iBlot2 transfer system ( Life Technologies ) and analyzed by Western blotting . ATP1A1 was detected with an anti-ATP1A1 rabbit MAb ( Abcam , Cambridge , MA; ab76020 ) and the corresponding infrared dye-conjugated goat anti-rabbit immunoglobulin 680RD ( Li-Cor , Lincoln , NE ) . Tubulin was used as a loading control and was detected with an anti-tubulin mouse MAb and an infrared dye-conjugated goat anti-mouse immunoglobulin 800CW ( Li-Cor ) . Western blot images were acquired on the Odyssey infrared scanner ( Li-Cor ) and analyzed with Image Studio Software ( Version 5 . 2 . 5 , Li-Cor ) . ATP1A1 band intensity values were normalized to tubulin and reported relative to Neg . siRNA1 transfected cells . Cells were harvested and total RNA was isolated with RNeasy Mini Kit ( Qiagen ) as described by the manufacturer’s protocol , including on-column DNase digestion . 1 μg total RNA was used for reverse transcription with oligo ( dT ) 12–18 primers and the SuperScript TM First-Strand Synthesis System for RT-PCR ( Life Technologies ) . The synthesized cDNA was pre-diluted 1:10 and used for the TaqMan gene expression analysis of ATP1A1 ( Hs00167556_m1 ) and 18S rRNA ( Hs99999901_s1 ) as a normalization control . The TaqMan assay reactions were analyzed on the 7900HT Fast Real-Time PCR system ( Applied Biosystems , Foster City , CA ) . The threshold cycle ( Ct ) for each reaction was determined by the SDS RQ Manager program ( Applied Biosystems ) . The relative changes in ATP1A1 transcript level were calculated by the 2-ΔΔCt method [70] and reported relative to cells transfected with Neg . siRNA 1 . RSV gene expression was measured using RSV-GFP , a recombinantly derived virus that expresses enhanced green fluorescent protein ( eGFP ) from an additional gene inserted between the P and M genes . SiRNA transfected or pre-treated A549 cells in 12-well plates were inoculated with an MOI of 1 PFU/cell . Inoculum was adsorbed for 2 h on a rocking platform at 37°C and then washed off and replaced with fresh media . The infected cells were incubated for 17 h , and GFP expression was quantified either by ELISA reader or flow cytometry . For the ELISA reader quantification , the GFP intensity of the infected monolayer was quantified by an area scan ( average GFP intensity of 29 individual measurements per well ) on a Synergy 2 ELISA reader ( BioTek ) . The intensity values were adjusted by subtracting the average intensity of mock-infected cells as background and reported relative to Neg . siRNA 1 transfected or mock-treated cells that had been infected with RSV-GFP . For the flow cytometry-based GFP quantification , the cells were detached with 1 mM EDTA , stained with LIVE/DEAD fixable dead cell staining kit ( Life Technologies ) , and fixed with 4% paraformaldehyde ( PFA , Electron Microscopy Science , PA ) . The GFP intensities of single , live cells were analyzed on a Canto II flow cytometer ( BD Biosciences , Franklin Lakes , NJ ) . The median fluorescence intensity ( MFI ) of GFP-positive cells was determined and reported as change relative to Neg . siRNA 1 transfected or mock-treated cells that had been infected with RSV-GFP . Infected cell monolayers were scraped into the media supernatant , vortexed for 30 s , clarified by centrifugation at 478 x g , snap frozen on dry-ice , and stored at -80°C . Samples were 10-fold serially diluted and Vero cells were inoculated with each dilution in duplicate and incubated for 2 h on a rocking platform at 37°C . Cells were overlaid with OptiMEM I ( Life Technologies ) containing 0 . 8% methylcellulose ( Sigma-Aldrich ) , 1x L-Glutamine , 2% FBS and 50 μg/ml Gentamicin and incubated for 6 days at 37°C . For RSV that expressed GFP , the plaques were visualized directly by GFP expression with a Typhoon imaging system ( GE Healthcare , Chicago , IL ) . Wt RSV plaques were fixed with ice-cold 80% methanol and immunostained with a mix of three RSV F-specific mouse MAbs [71] followed by a 680RD infrared dye-conjugated goat anti-mouse secondary immunoglobulin ( Li-Cor ) . The plaques were imaged on the Odyssey infrared scanner ( Li-Cor ) and were counted using the ImageJ software ( Version 1 . 46r; NIH , Bethesda , MD ) . A549 cells were seeded on glass cover slips in 24-well plates and used when still sub-confluent . For the immunofluorescence microscopy based assays , cells were fixed with 4% paraformaldehyde for 16 h at 4°C , permeabilized with 0 . 1% TritonX-100 ( Sigma Aldrich ) for 15 min and blocked with PBS containing 5% bovine serum albumin ( BSA ) ( Sigma Aldrich ) for 1 h at room temperature . All antibody dilutions were prepared in PBS , containing 5% BSA and 0 . 1% TritonX-100 . The primary antibody incubation was performed in a humidified chamber for 2 h with the following antibodies: rabbit anti-ATP1A1 ( Abcam; ab76020 , 1:100 ) , rat anti-EGFR ( Abcam; ab231 , 1:100 ) , mouse anti-RSV-N ( Abcam; ab94806 , 1:1 , 500 ) and anti-RSV-F ( mouse MAb #1129 [72] , 1:200 ) . After washing with PBS , the secondary antibody staining was performed with the respective Alexa Fluor ( AF ) conjugated secondary antibodies: donkey anti-rabbit AF488 , goat anti-rabbit AF700 , donkey anti-mouse AF647 , goat anti-rat AF647 . Simultaneous staining of RSV-F and RSV-N was performed with conjugated primary antibodies: specifically , anti-RSV-F mouse MAb #1129 [72] that we conjugated with AF488 [Antibody Labeling Kit ( Thermo Fisher Scientific , Waltham , MA ) ]; and a commercially-available anti-RSV N mouse MAb conjugated with allophycocyanin ( APC ) ( NB100-64752APC , Novus Biologicals , Littleton , CO ) . Nuclei were counterstained with 300 nM DAPI ( Life Technologies ) in PBS for 5 min and mounted on glass-slides with ProLong Diamond Antifade mountant ( Life Technologies ) . Immunostainings of HAE-ALI cells were performed as described above for A549 cells , except the incubation times of the primary and secondary antibodies were extended to 16 h at 4°C . In addition , the cultures were stained for F-Actin with the SiR-actin kit ( CY-SC001; Cytoskeleton; Inc , Denver , CO ) . Images were acquired on a Leica TCS-SP8 confocal microscope ( Leica Microsystems , Mannheim , Germany ) using a 63x oil immersion objective ( NA 1 . 4 ) , a zoom between 1 . 0 to 4 . 0x , laser emission at 488nm for AF488 , 561 nm for AF568 and 633 nm for AF647 . DAPI was excited using a 450 nm diode laser . Detector slits were configured to minimize any crosstalk between the channels and , if necessary , the channels were collected sequentially and merged afterwards . Images were processed using Leica Application Suite X ( LAS-X ) software , Imaris ( Version 9 . 0 . 0 , Bitplane AG , Zurich , Switzerland ) and ImageJ . Images of the HAE-ALI cells were deconvolved with Huygens Essential deconvolution software ( Scientific Volume Imaging B . V , Hilversum , The Netherlands ) . An EGFR phosphorylation array ( Ray Biotech , Norcross , GA ) was used to analyze phosphorylation of the EGFR receptor family . The array consisted of nitrocellulose membrane that was spotted in duplicate with phospho-specific antibodies against 17 different phosphorylation sites of the human EGFR family , plus a positive control antibody that binds EGFR irrespective of phosphorylation . Cells were treated as indicated , either transfected with siRNA 48 h prior or pre-treated with the indicated chemical compound for 16 h . Coincident with transfection or treatment , the cells were serum-starved for 16 h and then infected with wt RSV ( MOI = 5 PFU/cell ) for 5 h at 37°C . Cells treated with Ouabain or PST2238 for 16 h were incubated in F12 medium containing EGF ( Sigma-Aldrich , 100 ng/ml ) for 45 min as controls for PST2238 and Ouabain specificity . Cells were washed twice with cold PBS and lysed in the provided lysis buffer , containing protease and phosphatase inhibitor cocktails . The protein concentration of the lysate was quantified by bicinchoninic acid ( BCA ) assay ( Thermo Fisher Scientific ) and lysate containing 150 μg total protein was used for each array . The array was processed as described by the manufacturer , in brief: the array was incubated with the diluted lysate for 16 h at 4°C on a rocking platform , washed , and incubated with a biotinylated pan EGFR antibody followed by horseradish peroxidase-conjugated streptavidin , and luminescence was detected with X-ray film . The films were scanned and spot intensity was quantified by ImageQuant TL ( Array Version 8 . 1 . , GE Healthcare ) . Three independent experiments with two technical replicates each were normalized to the internal array controls and pan EGFR . Values are reported relative to the average signal of Neg . siRNA 1 ( for siRNA-transfected ) or to mock-treated ( for inhibitor-treated ) , RSV-infected samples . Following a published procedure [73] , A549 cells on cover slips were transfected with siRNA for 48 h or were treated with indicated chemical compound . Coincident with transfection or treatment , the cells were serum-starved for 16 h . The cells were infected with wt RSV ( MOI = 5 PFU/cell ) in media containing AF568-conjugated dextran ( Dextran-AF568; 10 , 000 MW; Life Technologies ) , incubated for 5 h at 37°C , and washed and fixed for 16 h with 4% PFA at 4°C . For co-localization experiments , the cells also were stained for ATP1A1 , RSV F , and RSV N using specific antibodies as described above . Nuclei were counterstained with DAPI ( 300 nM in PBS for 5 min ) and mounted on glass slides with ProLong Diamond Antifade mountant . For each treatment , at least ten random images were acquired , using the mark and find function of the Leica LAS-X image acquisition software , as Z-stacks on a Leica TCS-SP8 confocal microscope ( Leica ) with a 63x Objective ( NA 1 . 4 ) and a zoom of 1 . 0x . The images were analyzed by batch process with the software Imaris ( Version 9 . 0 . 0 , Bitplane AG ) . The DAPI-stained nuclei were detected as spots to count the number of cells per field . The uptake of dextran was quantified by using the surface function of Imaris to recognize distinct dextran-positive vesicles . The total intensity of dextran-AF568 within the created surfaces , which had a volume larger than 1 . 0 μm3 , of one field was normalized to the number of nuclei per field . The values were reported relative to Neg . siRNA 1-transfected or mock treated cells that had been infected with RSV . For each experiment a total of at least 600 cells per condition were analyzed . All animal studies were approved by the NIH Institutional Animal Care and Use Committee ( IACUC ) under the animal study protocol number LID 34E . The National Research Council’s Guide for the care and use of laboratory animals and the Public Health Service Policy on humane care and use of laboratory animals served as the guidelines for the care and use of mice in this study . The primary HSAEC and HAE-ALI cells were obtained from the American Type Culture Collection ( ATCC ) and MatTek Corporation , respectively . The cells were isolated under informed consent and conform to HIPAA standards to protect the privacy of the donor’s personal health information . The research with these human cells is not considered human subjects research because the cells are publicly available and therefore was exempt from 45 CFR Part 46 and no Institutional Review Board ( IRB ) approval was required . | RSV continues to be the most important viral cause of severe bronchiolitis and pneumonia in infants and young children , and also has a substantial impact in the elderly . It is estimated to claim the lives of ~118 , 000 children under five years of age annually . No vaccine or antiviral drug suitable for general use is available . The involvement of host factors in RSV infection and replication is not well understood , but this knowledge might lead to intervention strategies to prevent infection . Using a genome-wide siRNA screen to knock down the expression of over 20 , 000 individual cellular genes , we identified ATP1A1 , the major subunit of the Na+ , K+-ATPase , as an important host protein for RSV entry . We showed that ATP1A1 activation by RSV resulted in transactivation of EGFR by Src-kinase activity , resulting in the uptake of RSV particles into the host cell through macropinocytosis . We also showed that the cardiotonic steroid ouabain and the synthetic digitoxigenin derivative PST2238 , which bind specifically to the extracellular domain of ATP1A1 , significantly reduced RSV entry . Taken together , we describe a novel ATP1A1-enabled mechanism used by RSV to enter the host cell , and describe candidate antiviral drugs that block this entry . | [
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] | 2019 | The alpha-1 subunit of the Na+,K+-ATPase (ATP1A1) is required for macropinocytic entry of respiratory syncytial virus (RSV) in human respiratory epithelial cells |
In an effort to understand how a tick-borne pathogen adapts to the body louse , we sequenced and compared the genomes of the recurrent fever agents Borrelia recurrentis and B . duttonii . The 1 , 242 , 163–1 , 574 , 910-bp fragmented genomes of B . recurrentis and B . duttonii contain a unique 23-kb linear plasmid . This linear plasmid exhibits a large polyT track within the promoter region of an intact variable large protein gene and a telomere resolvase that is unique to Borrelia . The genome content is characterized by several repeat families , including antigenic lipoproteins . B . recurrentis exhibited a 20 . 4% genome size reduction and appeared to be a strain of B . duttonii , with a decaying genome , possibly due to the accumulation of genomic errors induced by the loss of recA and mutS . Accompanying this were increases in the number of impaired genes and a reduction in coding capacity , including surface-exposed lipoproteins and putative virulence factors . Analysis of the reconstructed ancestral sequence compared to B . duttonii and B . recurrentis was consistent with the accelerated evolution observed in B . recurrentis . Vector specialization of louse-borne pathogens responsible for major epidemics was associated with rapid genome reduction . The correlation between gene loss and increased virulence of B . recurrentis parallels that of Rickettsia prowazekii , with both species being genomic subsets of less-virulent strains .
Spirochetes of the genus Borrelia are bacterial pathogens responsible for relapsing fever and Lyme borreliosis . Whereas the Lyme disease agents Borrelia burgdorferi [1] , [2] , Borrelia garinii [3] , and Borrelia afzelii [4] are transmitted by hard ticks , the numerous relapsing fever borreliae are typically transmitted by soft ticks . Interestingly , tick-borne relapsing fever borreliae , including Borrelia duttonii , have shown extended vectorial capacity , whereas transmission of Borrelia recurrentis , which causes louse-borne relapsing fever , is restricted to Pediculus humanus [5] , [6] . Besides their mode of transmission , these two highly related species of Borrelia exhibit very different epidemiological and clinical features . B . duttonii is endemic in Western Africa , where it demonstrates the highest incidence among all bacterial infections and causes up to six relapses , no mortality , and adverse perinatal outcomes [7] . In contrast , B . recurrentis , once responsible for worldwide outbreaks , is currently limited to Ethiopia and its surrounding countries [8] . It causes fewer relapses , but spontaneous mortality remains as high as 2–4% despite antibiotics , with patients suffering from distinctive hemorrhagic syndrome [9] . In addition , women who develop relapsing fever during pregnancy have a high incidence of spontaneous abortion [10] . Indeed , B . recurrentis and other louse-borne pathogens , including the typhus agent Rickettsia prowazekii [11] and the trench fever agent Bartonella quintana [12] , exhibit higher virulence than their respective tick-borne relatives B . duttonii , Rickettsia conorii [13] , and Bartonella henselae [12] . Borreliae are unique among bacteria in that their genome is comprised of a linear chromosome and both linear and circular plasmids [14] . We sequenced the genomes of B . duttonii and B . recurrentis to gain new insights into the structure and evolution of the borreliae .
While the 1 , 242 , 163 bp B . recurrentis A1 strain genome contains only 8 linear fragments of 930 , 981-6 , 131 bp , the 1 , 575 , 296 bp B . duttonii Ly strain genome contains 17 linear fragments of 931 , 674-11 , 226 bp and one 27 , 476 bp circular fragment ( Table 1 , Figures S1 and S2 , Genbank accession numbers CP000976-CP000992 for B . duttonii and CP000993-CP001000 for B . recurrentis ) . For each species , we designated the largest fragment as the chromosome and the smaller ones as the plasmids . The organization of the chromosome was conserved among borreliae , with spoOJ , gyrA , gyrB , dnaA , and dnaN ( BDU_431-435 , BRE_434-438 ) being clustered around the putative origin of replication near the GC/AT skew cross point ( Figure 1 and Figure S3 ) . In both species , the sole rrs operon ( BDU_415-416 , BDU_424 , BRE_419-420 , BRE_428 ) , which is close to the putative origin of replication , was split by hpt , purA , and purB ( BDU_418-420 , BRE_422-424 ) , as reported for B . hermsii and other relapsing fever borreliae [15] , [16] ( Figure 1 ) . We also found similarity between the B . duttonii-circular plasmid ( cp ) 27 , B . duttonii-linear plasmid ( lp ) 26 , and B . duttonii-lp28 . In addition , colinearity was observed between B . duttonii-lp23/B . recurrentis-lp23 , B . duttonii-lp11/B . recurrentis-lp37 , B . duttonii-lp32/B . recurrentis-lp33 , B . duttonii-lp ( 26 , 28 , 31 , 40–42 , 70 ) /B . recurrentis-lp ( 35 , 53 ) , and B . duttonii-lp165/B . recurrentis-lp124 ( Figure 2 ) . The latter plasmid has no counterpart among Lyme group borreliae . In both species , the linear plasmid lp23 , which is syntenic to the circular plasmids B . burgdorferi/B . garinii-cp26 and B . afzelii-cp27 , was particularly interesting . This plasmid exhibited a large polyT track ( 174 nucleotides in B . duttonii and 46 in B . recurrentis ) of a length not previously reported in other bacteria , although T-rich regions containing Ts in 16 of 20 positions and Ts in 18 of 20 positions have been reported in the ospAB and vmp promoters of B . burgdorferi and B . hermsii , respectively [17] . This polyT track is located in the promoter of an intact variable large protein ( vlp , BDU_13021 , BRE_6020 ) gene situated at the telomere ( Figure 3 ) . This locus has been shown to be the site of vlp expression in B . recurrentis [18] . Strikingly , this plasmid encodes the unique telomere resolvase ( resT , BDU_13014 , BRE_6013 ) , a protein specific to Borrelia species ( Figure 3 ) [19] , [20] . In B . duttonii and B . recurrentis , lp23 lacks the celABC genes involved in the PTS cellobiose system as well as oppA compared to other Borrelia . Aside from the variable number of copies of repeated genes ( see below ) , a few genomic differences were found between B . duttonii and B . recurrentis . There was a difference in the number of the protein genes encoded by the chromosome ( 820 genes in B . duttonii and 800 in B . recurrentis ) . Five genes ( recJ , putative membrane protein , rpsU , ftsK , bacA , BDU_257-262 , BRE_256-260 , BRE_261-265 ) were duplicated in B . recurrentis , with one copy of recJ ( BRE_261 ) presenting a frameshift and one copy of bacA ( BRE_260 ) containing a frameshift and partial deletion . Four genes , pantothenate permease ( panF , BDU_821/826 , BRE_824 ) , pseudouridylate synthase ( rluA , BDU_822/827 , BRE_825 ) , an uncharacterized conserved protein ( BDU_823/828 , BRE_826 ) , and UDP-N-acetylmuramate-alanine ligase ( murC , BDU_824/829 , BRE_827 ) , were duplicated in B . duttonii . An ATPase involved in chromosome partitioning ( homolog to Soj , BDU_429 ) , close to the replication origin was lacking in B . recurrentis . An in-frame STOP codon ( tga , replacing tgg in B . duttonii ) was found in the B . recurrentis copy of recA ( BDU_135 , BRE_134 ) , involved in the RecBCD dsDNA end repair pathway and the RecFOR ssDNA gap repair pathways [21] ( Table S2A ) . We also found that mutS ( BDU_101 , BRE_100 ) and smf ( BDU_300 , BRE_304 ) , genes belonging to the DNA processing DpRA family that collaborates with recA for recombination and bacterial transformation , were both impaired in B . recurrentis [22] , with an in-frame STOP codon in smf ( taa replacing caa ) and a frameshift in mutS . Other impaired genes were found in B . recurrentis that are implicated in the following processes: maltose transport and metabolism ( malX , BDU_119 , BRE_118 and malQ , BDU_165 , BRE_164 , frameshifts ) , glycerol metabolism ( glpA , BDU_244 , BRE_243 and glpK , BDU_241 , BRE_240 , frameshifts ) , and adaptation to host environments ( oppA1 transporter , BDU_329 , BRE_333 , internal STOP codon taa replacing caa ) . Other disrupted genes in B . recurrentis were yplQ ( BDU_120 , BRE_119 , frameshift ) , encoding a hemolysin III , xylR2 ( BDU_843 , BRE_841 , frameshift ) of the xylose operon , the A subunit of an ATP-dependant Clp protease ( BDU_364 , BRE_368 , frameshift ) , and an uncharacterized conserved protein ( BDU_743 , BRE_746 , frameshift ) . Finally , a p35-like antigen ( BDU_1 ) , similar to the B . burgdorferi fibronectin-binding lipoprotein BBK32 , was absent in B . recurrentis . A significant number of Borrelia genes corresponded to repeat families , including variable major proteins ( Vmp ) and Borrelia direct repeats ( Bdr ) . Most of these were plasmid-borne paralogous families [2] . To further study this phenomenon and compare different Borrelia species , we grouped together all predicted protein coding genes of B . duttonii , B . recurrentis , B . burgdorferi , B . garinii , and B . afzelii ( see Materials and Methods ) . This analysis indicated that the most abundant families were those of the variable major proteins ( vmp , including 600-bp vsp and 1000-bp vlp ) [23] , Borrelia direct repeats ( Bdr ) , and plasmid partition proteins PF32 , PF49 , ppap1 , and ppap2 ( Table 2 ) . Most Vmps are encoded by linear plasmids , and only two and three copies were found at the beginning of the B . recurrentis and B . duttonii chromosome , respectively ( Table S3 ) . The vlp family genes , similar to VlsE in Lyme disease borreliae , encode lipoproteins that , as a result of antigenic variation , allow relapsing fever borreliae to escape the host immune response [24] . B . duttonii encodes 68 vlp copies ( 19 with the consensus GGAGG of Ribosomal Binding Site ) , while B . recurrentis encodes 17 vlp copies ( 6 with the consensus GGAGG of Ribosomal Binding Site ) ( Table S3 , Figure S4 ) . Phylogeny clearly indicated that vlps are grouped into 4 subfamilies designated α , β , γ , and δ ( Figure S4 ) , as previously found for B . hermsii [23] . The largest subfamily is γ , with 26 vlp copies in B . duttonii and 9 in B . recurrentis . While numerous vlp pseudogenes were found in both genomes , B . recurrentis showed a tendency to lose intact vlps , with one vlp every 18-kb ( on average , excluding the chromosome ) compared with one vlp every 9 . 5-kb for B . duttonii . We identified remnants of 46 vlp genes in B . duttonii and 29 in B . recurrentis . The vsp family genes are related to the lipoprotein ospC present in Lyme disease borreliae . We identified 14 vsp in B . duttonii and 10 in B . recurrentis . The ratio of intact vlp to vsp was 17/10 ( 1 . 7 ) in B . recurrentis and 68/14 ( 4 . 9 ) in B . duttonii . The Bdr family is common to relapsing fever and Lyme disease group borreliae [25] . In B . burgdorferi , Bdr are characterized by temperature-independent , low expression level , inner membrane-localized immunogenic proteins that are organized into 6 families ( A to F ) . Bdr genes are found on most plasmids , except for the large B . duttonii-lp165/B . recurrentis-lp124 plasmid , which was also devoid of vlp and vsp . In B . duttonii , putative replication and partition genes were identified on most plasmids , and were usually organized as a set of the four consecutive genes: PF32 , PF49 , ppap1 , ppap2 ( ORFe in B . burgdorferi ) [2] . In B . recurrentis , this organization was still apparent despite gene decay . The Bmp family contains basic membrane protein genes encoding lipoproteins . These proteins are expressed in infected patients , and result from different gene rearrangements in the five borreliae ( Figure S5 ) . For instance , the protein BmpB-1 is present only in Lyme group borreliae and could thus be used as a Lyme-specific diagnostic test . An abundant repeat family ( Family 44 , 14 members , Table 2 ) was found in B . duttonii , but not in B . recurrentis . Indeed , members of this family are located at the 5′-end of the B . duttonii-lp164 plasmid , a region that lacks a counterpart in B . recurrentis . It contains uncharacterized conserved lipoproteins that are predicted to represent 7 . 6% of the lipoproteins in B . duttonii . Genome sequencing of B . recurrentis and B . duttonii provides the opportunity to compare the gene content between relapsing fever and Lyme disease group borreliae . Whole chromosome comparison ( Figure S1 ) shows extensive conservation of gene content and gene order . In both groups , we found an intact RecBCD system , which is important for repairing double-stranded DNA ends , but a deficient RecFOR pathway . RecF and RecR proteins are associated with RecO in the reparation of single-stranded DNA; however , RecO is absent in all borreliae , potentially leading to deficient repair of single-stranded nicks . We observed only 13 genes specific to the Lyme disease group and 17 genes specific to the relapsing fever group ( excluding bmp genes , Table S2B ) in the chromosomes of borreliae . As previously observed in B . hermsii [15] , [16] , chromosome-encoded genes involved in purine metabolism and salvage were similarly found in these relapsing fever borreliae , including adenylosuccinate synthase ( purA , BDU_419 , BRE_423 ) , adenylosuccinate lyase ( purB , BDU_420 , BRE_424 ) , and hypoxanthine phosphoribosyltransferase ( hpt , BDU_422 , BRE_425 ) . They were located between the 16S and 23S ribosomal DNA . Other genes unique to the relapsing fever group borreliae included a putative adenine-specific DNA methyltransferase ( BDU_467 , BRE_470 ) , a copper homeostasis protein ( cutC , BDU_844 , BRE_842 ) , the sugar specific PTS family protein ( nagE , BDU_838 , BRE_836 ) , a trypsin-like serine protease ( BDU_797 , BRE_800 ) , an ATP-dependent helicase belonging to the DinG family ( BDU_740 , BRE_743 ) , a TPR domain containing protein ( BDU_737 , BRE_740 ) , a protein with similarity to a response regulator receiver ( CheY ) modulated serine phosphatase ( BDU_523 , BRE_526 ) , glpQ ( BDU_243 , BRE_242 ) , glpT ( BDU_241 , BRE_240 ) , maf protein ( BDU_127 , BRE_126 ) , hsp20 heat shock protein ( BDU_444 , BRE_447 ) , purine salvage pathway genes including peptidyl-prolyl cis-trans isomerase ( BDU_407 , BRE_411 ) , and the rec family members RecN ( BDU_313 , BRE_317 ) , RecF ( BDU_436 , BRE_439 ) , and RecR ( BDU_465 , BRE_468 ) . Likewise , arcC ( Carbamate kinase , BDU_857 , BRE_855 ) , which is involved in glutamate , arginine and proline biosynthesis are specific to relapsing fever borreliae , but was impaired in B . recurrentis . Among these genes , 16 exhibited best homologs with sequences outside of the spirochetes group . Interestingly , 5 demonstrated good homology with Fusobacterium nucleatum , as described for another spirochete , Treponema denticola [26] . Conversely , some genes were only found on the Lyme disease group ( Table S2B ) , including a putative L-sorbosone dehydrogenase , two antigens S2 , an oligopeptide ABC transporter ( oppA-3 ) , a methylglyoxal synthase , a lipoprotein LA7 , a basic membrane protein B ( bmpB-1 ) , an inositol monophosphatase , an aldose reductase , a MATE efflux family protein , a pfs protein ( pfs-2 ) , a rep helicase , a small primase-like protein , and an Na+/H+ antiporter ( nhaC-1 ) . In contrast to what was observed for the chromosome , the plasmid contents of the relapsing fever group were very different from that of the Lyme disease group . Only three B . duttonii plasmids ( lp165 , lp70 and lp23 ) exhibited significant synteny with B . burgdorferi plasmids ( Figure S6 ) . B . duttonii-lp165 and B . recurrentis-lp124 encoded nrdF ( ribonucleoside-diphosphate reductase beta subunit , BDU_1075 , BRE_1045 ) , nrdE ( ribonucleoside-diphosphate reductase alpha subunit , BDU_1076 , BRE_1046 ) , and nrdI ( auxiliary protein , BDU_1077 , BRE_1047 ) ( Table S2B ) , all of which were previously reported in B . hermsii [27] , but were absent in the Lyme disease group of Borrelia . Using the SpLip program [28] with the B . burgdorferi matrix supplied by the authors , we retrieved 171 probable and 13 possible lipoproteins in B . duttonii , 80 ( 11 ) in B . recurrentis , 111 ( 9 ) in B . burgdorferi , 45 ( 8 ) in B . garinii , and 84 ( 10 ) in B . afzelii . Relapsing fever borreliae proteomes contain a larger fraction of lipoprotein ( 13 . 63% in B . duttonii and 8 . 72% in B . recurrentis ) than Lyme disease group borreliae ( 7 . 74% in B . afzelii , 7 . 32% in B . burgdorferi and 5 . 9% in B . garinii ) . B . duttonii contained no impaired genes in its chromosome ( except for two vlp pseudogenes ) , whereas B . recurrentis exhibits 20 impaired genes ( Table S2A ) . This suggests that B . recurrentis evolved under more relaxed constraints ( e . g . accumulated more deleterious mutations ) than B . duttonii . This hypothesis was examined by analyzing the ratio of non-synonymous ( Ka ) to synonymous ( Ks ) substitution rates ( denoted ω = Ka/Ks ) among 773 conserved genes of the five borreliae . Based on the most suitable model of evolution ( See Materials and Methods ) , the estimated ω ratio was nearly twice as high for the B . recurrentis branch ( ωBre = 0 . 18 ) than for the B duttonii branch ( ωBdu = 0 . 10 ) . These results suggest that , on average , the genome of B . recurrentis tends to evolve under weaker coding sequence constraints than the genome of B . duttonii . In addition , the number of non-synonymous substitutions was higher in the B . recurrentis branch ( n = 695 ) than in the B . duttonii branch ( n = 366 ) . This indicates that B . recurrentis proteins tend to diverge faster . To find out whether this acceleration was restricted to a specific subset of genes , we further analyzed sub-alignments comprising , on average , 10 genes . This analysis showed that ωBre calculated for the sub-alignments were not systematically higher than ωBdu ( Figure 4A ) . This suggests that the selective constraints acting on coding sequences are , in general , not less effective in B . recurrentis than in B . duttonii . In contrast , the Ka and Ks values were almost systematically higher for B . recurrentis ( Figure 4B and C ) . These results indicate that B . recurrentis genome is globally evolving faster that the one of B . duttonii .
While circular chromosomes are most commonly seen in bacteria , linear chromosomes are encountered in some phylogenetically distinct species including Agrobacterium tumefaciens [29] , [30] , Streptomyces species [31] , [32] , and Borrelia species [1]–[4] . The latter are unique in that they harbor >3 linear genomic fragments , whereas the other sequenced spirochetes , Treponema [33] , [26] and Leptospira [34]–[36] , possess 1–2 circular chromosomes . This suggests that genome linearization is a recent evolutionary event in the spirochete lineage . Genome linearization of Borrelia is sustained by telomeres , terminal small inverted repeats with covalently closed hairpin ends [37] , [38] . Similar features have been described for Poxvirus , African swine fever virus , Chlorella viruses , the mtDNA of yeasts and protozoa , and the Escherichia coli phage N15 [37]–[39] . Replication of telomeres from a bidirectional origin [40] , [41] produces intermediates for which the replicated telomeres comprise dimer junctions between inverted repeats of the original plasmid [19] . Replicated telomeres are then processed by ResT , the essential B . burgdorferi cp26-encoded telomere resolvase responsible for a particular DNA breakage and reunion event that regenerates the hairpin telomeres [20] , [42] , [43] . When cp26 was deleted in B . burgdorferi cells , viability was lost [44] . ResT acts via a catalytic mechanism analogous to that of tyrosine recombinases and type IB topoisomerases [45] . We found ResT in relapsing fever Borrelia , in agreement with the concept of telomere-mediated genome linearization among these organisms . ResT was recently also shown to perform a reverse reaction that fuses telomeres from unrelated replicons . In the Lyme disease group , initiation of replication occurs in the central region of the linear chromosome that comprises a polar CG skew and proceeds bidirectionnaly [40] , [46] . The observed parallel genome architecture suggests an identical replication mechanism among the relapsing fever group . Previous limited phylogenetic data based on 16S rDNA [6] and 16S–23S intergenic spacer [5] raised the question of whether B . duttonii and B . recurrentis are different species [47] . Gene content analysis showed that the genome of B . recurrentis is a subset of that of B . duttonii . The chromosomes of both species were found to be almost entirely colinear , and all B . recurrentis plasmids have a counterpart in B . duttonii . Altogether , 30 genes or gene families of B . duttonii were either absent , split , or reduced in number in B . recurrentis . In particular , a set of four consecutive genes , PF32 , PF49 , ppap1 , and ppap2 , involved in plasmid replication and partitioning were well conserved in most B . duttonii plasmids , but were damaged considerably in B . recurrentis plasmids . This suggests ongoing plasmid loss in B . recurrentis . Likewise , B . recurrentis lacks a chromosomal Soj homologue , which is involved in chromosome partitioning . Such reductive evolution may be linked to defective DNA repair in B . recurrentis . Indeed , the B . recurrentis recA gene sequence presents an in-frame STOP codon . Although compensatory mechanisms that preserve the expression of recA could not be ruled out , this finding was surprising , as recA is a ubiquitous and highly conserved gene involved in DNA repair [21] . Impaired recA was previously reported in Spiroplasma melliferum [48] , whereas Buchnera and Blochmania floridanus lack this gene [49] , [50] . In Escherichia coli , 50% of recA mutants are viable and avoid chromosome lesions [51] , but recA dut* ( dUTPase ) mutants are lethal in the presence of nfi , which encodes endonuclease V ( deoxyinosine 3′ endonuclease ) [52] . Since Borrelia species lack dut , we hypothesize that the viability of B . recurrentis is maintained by the absence of nfi , as occurs in B . burgdorferi , B . garinii , and B . duttonii . We were unable to find either an ATP-dependant LigD or the DNA-end-binding-protein , Ku , involved in DNA repair by non-homologous end-joining [53] . The lack of an intact recA and smf in B . recurrentis may explain the observed accelerated evolution of its genome compared to B . duttonii . Taken together , the genomic data and phylogenetic data suggest that B . recurrentis is actually a strain of B . duttonii . Genome comparison of louse-borne bacteria with their tick-borne counterparts indicated an extensive genome size reduction of 20 . 4% for Borrelia spp . , 18% for Bartonella spp . , and 12 . 6% for Rickettsia spp . Among borreliae , genes that were lost included the antigenic lipoproteins vlp and vsp , genes involved in chromosome and plasmid partitioning , and genes involved in xylose and glycerate metabolism . Degradation of genes into pseudogenes within louse-borne species ( 128 B . henselae / 175 B . quintana; 2 B . duttonii / 20 B . recurrentis , Table S2A ) suggests a progression toward the complete loss of these genes . Indeed , louse-borne species contain 21%–39% less CDSs than their tick-borne counterpart . This phenomenon is illustrated by the decreased number of repeat families from 43 in B . henselae to 11 in B . quintana [12] , from 12 in R . conorii [13] to 3 in R . prowazekii [11] , and from 54 in B . duttonii to 17 in B . recurrentis . Loss of DNA repair genes such as mutM and mutT in the typhus group R . prowazekii [54] , and recA , mutS , and smf in B . recurrentis may contribute to a higher rate of replication error , leading to faster genome decay among these louse-borne pathogens . Genomic differences between louse-borne species and their tick-borne counterparts may correlate with their concomitant adaptation to a human host [12] . A 4-nucleotide difference ( 0 . 26% ) in the 16S rDNA sequence of B . duttonii and B . recurrentis estimates their divergence to have occurred between 6 . 5 and 13 million years ago [55] . This is roughly the same as the time of the divergence of the human specific louse vector of B . recurrentis and the common ancestral primate-associated ectoparasite [56] . We hypothesize that genome decay in louse-borne bacteria correlates with the host-specific bottleneck of the arthropod vector . Conversely , tick-transmitted organisms may adapt to diverse host populations , which is facilitated by tick feeding habits , unlike louse-borne pathogens . Such adaptation to body louse transmission is correlated with increased evolutionary rates illustrated in B . recurrentis analogous to those observed for R . prowazekii [54] . Genome size reduction and on-going gene and function decay in louse-borne pathogens illustrate the genomic fluidity associated with adaptation of bacteria from a large environmental niche to a more restricted one [57] , [58] . Variation in the expression of a dominant surface antigen allows borreliae to evade immune defences . This evasion increases the duration and number of recurrences of bacteremia , and thus , the likelihood of subsequent transmission [14] . In B . recurrentis strain A1 , Vlp has been shown to be the major pro-inflammatory molecule [59] . Furthermore , expression of certain lipoproteins , for instance in Borrelia turicatae , has been shown to modulate tissue tropism . Specifically , the Bt1 and Bt2 variants are predictive of either neurotropism or spirochetemia and arthritis , respectively [60] , [61] . Detailed molecular analyses revealed that the corresponding genes are arranged into silent and expressed copies on different plasmids [62] , [63] . Indeed , two copies of vlp1B . recurrentis A1 were found in B . recurrentis [59] . This gene was identified as a pseudogene in lp53 and as an active gene in lp23 ( lp23_20295_21386 , BRE_6020 ) . Antigenic variation occurs either by replacing the entire open reading frame of the expressed gene with a previously silent one , or by activating a previously silent downstream gene [64] . The likelihood of different antigenic variants being expressed appears not to be random , but is ordered in a semi-hierarchical fashion . This hierarchy depends on the sequence similarity between the upstream homology sequence located at the expression site of the variant gene and the distance separating the extragenic downstream homology sequence [65] . To date , the absence of suitable animal models has precluded antigenic variation studies among B . recurrentis and B . duttonii; however , the genome sequence data reported here could facilitate the molecular characterization of antigenic variants in clinical samples . In contrast to Lyme disease spirochetes ( <105/ml ) , relapsing-fever spirochetes achieve high cell densities ( >108/ml ) in patients' blood , suggesting differences in the ability of both groups to either exploit or survive in blood . It has been hypothesized that the purine salvage pathways are among these differences [16] . In particular , hypoxanthine , a primary product of purine catabolism , is exported to the outer surface of red blood cells . This could facilitate the direct uptake of hypoxanthine from red blood cells , providing a purine source for the synthesis of nucleotides by these borreliae [16] . In addition , some researchers have suggested that differences in glycerol-3-phosphate ( G3P ) , an important metabolic intermediate for phospholipid synthesis , acquisition pathways contribute to differences in the density of borreliae in blood [66] . B . recurrentis has apparently inactivated glpA and glpK , indicating that two of the three G3P acquisition pathways in Borrelia have been turned-off in B . recurrentis . B . recurrentis could acquire G3P only by the hydrolysis of deacylated phospholipids from the erythrocyte membrane , in agreement with the fact that its body louse vector takes daily bloody meal in order to survive . Therefore , such a restriction would not be deleterious to B . recurrentis , but indeed exemplifies adaptation to a specific ecological niche [67] . As GlpQ is an immunodominant antigen used to discriminate between Lyme disease and relapsing fever groups [68] , the present genomic data may help refine the serological diagnosis of relapsing fever group borrelioses . Genome analysis revealed that B . recurrentis encodes fewer putative virulence factors than B . duttonii , an unexpected finding given the high mortality in untreated louse-borne relapsing fever [69] . In particular , B . recurrentis encodes a reduced proportion of major antigenic Vlp compared to Vsp lipoproteins than B . duttonii . It also lacks a hemolysin , which is present but is obviously degradated , as well as a p35-like antigen similar to the BBK32 fibronectin-binding lipoprotein of B . burgdorferi . Loss of intact glpA and glpK in B . recurrentis may limit the acquisition of glycerol-3-phosphate . It is also possible that the loss of one intact copy of bacA in B . recurrentis may cause increased virulence , as observed for Brucella abortus , in which bacA is deleted [70] . Other genes that are critical for the environmental survival of B . recurrentis , including the broad-spectrum peptide permease OppA-1 gene [71] and the ClpA chaperone , were also degraded . The ClpA chaperone prepares protein substrates for degradation by ClpP [72] , a central complex that controls the stability and activity of transcriptional regulators during cell stress Impaired ClpA may deregulate transcription during B . recurrentis infection and lead to uncontrolled expression of virulence factors . Altogether , these defects may impair environmental sensing by B . recurrentis . These findings illustrate the lack of correlation between the observed virulence and the number of virulence factors possessed by an organism [73] . Finally , B . recurrentis illustrates the emerging concept that microbial virulence , for humans , may result from gene loss [58] .
B . recurrentis strain A1 isolated from an adult patient with louse-borne relapsing fever in Ethiopia [67] and B . duttonii strain Ly isolated from a 2-year-old girl with tick-borne relapsing fever in Tanzania [74] were grown on BSK-H complete medium batch number 057K4413 and 10K8402 ( Sigma ) at 37°C . Pulsed field gel electrophoresis ( PFGE ) was performed ( CHEF-DRIII apparatus , Biorad ) to determine the size of the genome and to analyze plasmid patterns under three different electrophoretic conditions . The samples were prepared as described previously [75] . Small plasmids could be visualized using a linear increase in pulse times between 1 to 3 sec . at 180 V over a 10 h period . Plasmids from 145 to 23 kb were detected using a linear increase in pulse time between 3 to 10 sec . at 180 V over a 15 h period , followed by an extensive migration using a linear increase in pulse time between 50 to 150 sec . at 180 V over a 30 h period ( Figure S7 ) . As attempts to isolate chromosome and plasmid DNA from PFEG after β-agarase treatment failed to produce sufficient DNA yield , genomic DNA was extracted from 25 ml of culture by incubation with 1% SDS-RNAseI ( 50 µg/ml ) for 3 hours at 37°C , followed by proteinase K digestion ( 250 µg/ml ) at 37°C overnight . After 3 phenol extractions , the DNA was precipitated with ethanol . The quality , yield , and DNA concentration were estimated by electrophoresis on agarose gels stained with ethidium bromide . Genomic DNA was sheared by mechanical fragmentation with a Hydroshear device ( GeneMachines , San Carlos , California , USA ) to construct plasmid libraries . After blunt end repair and BstXI adapter ligation , fragments of 2 kb , 5 kb , and 10 kb were cloned into the high copy number vector pCDNA2 . 1 ( Invitrogen , Life Technologies ) digested with BstXI . Transformations were performed using the electrocompetent E . coli strain DH10B ( Invitrogen , Life Technologies ) . Each library was validated using 96 clones from which the insert size was estimated by agarose gel electrophoresis . Sequencing using vector-based primers was carried out using the ABI 3730 Applera sequencer . For B . duttonii , only libraries of 2 kb and 10 kb were sequenced , producing 14 , 719 and 10 , 066 reads , respectively . For B . recurrentis , three shotgun libraries of 2 kb , 5 kb , and 10 kb generated 14 , 794 , 2 , 248 , and 2 , 042 reads , respectively . Reads were analyzed and assembled into contigs using the Phred , Phrap , and Consed software packages [76]–[78] . Finishing was performed to verify low quality regions , to fill-in sequences by DNA walking using subcloned DNA , and to close gaps . A total of 1 , 034 B . duttonii specific primers and 784 B . recurrentis primers were designed . All finishing sequencing reactions were carried out on an ABI 3130 Applera sequencer . An initial set of protein-coding genes was detected using self-training Markov models [79] and careful examination of intergenic regions to rescue additional genes . Putative protein coding genes were then validated and annotated by sequence similarity using BlastP [80] against the non-redundant protein database from the National Center for Biotechnology Information ( NCBI ) and the KEGG protein database [81] . Putative protein coding genes were also validated by profile detection using RPSblast [80] and the COG database [82] . Genes encoding tRNA were identified with tRNAscan-SE [83] , and other RNAs were located using BlastN [80] . Dot plots of plasmids from both species were computed using the NUCmer program from the MUMmer package [84] . To compare the distribution of genes in different Borrelia families , we grouped together all predicted protein coding genes for B . duttonii ( this work ) , B . recurrentis ( this work ) , B . burgdorferi ( GenBank: NC_000948-57 , NC_001318 , NC_001849-57 , NC_001903 , NC_001904 ) , B . garinii ( GenBank: NC_006128 , NC_006129 , NC_006156 ) , and B . afzelii ( GenBank: NC_008273 , NC_008274 , NC_008277 , NC_008564-69 ) , by performing a mutual BlastP comparison of this set of genes . The resulting comparison data were submitted to a Markov Chain Clustering algorithm to regroup the genes into families [85] . The resulting set of clustered sequences is available as Dataset S1 . The same analysis was performed on the individual proteome of B . henselae , B . quintana , R . prowazekii , R . conorii , B . duttonii , and B . recurrentis to count the number of repeat families containing at least 3 members in each of these genomes . Lipoprotein computational prediction has been the subject of a specific article [28] that describes the SpLip program used in the present work . The 856 proteins of the B . burgdorferi chromosome were aligned with the other Borrelia ( B . duttonii , B . recurrentis , B . garinii and B . afzelii ) proteomes using the BlastP program ( e-value<1e-10 ) [80] . We identified 773 genes that were conserved in all borreliae ( borreliae core genes ) using the reciprocal best Blast hit criterion . The 773 Borrelia core proteins were first aligned individually using MUSCLE [86] . Poorly aligned regions were discarded by GBLOCKS [87] . The resulting alignments were used as a guide to align the corresponding coding sequences on a codon basis . After cleaning up the nucleotide alignments for poorly aligned regions , the 773 multiple alignments were concatenated in a single alignment of 169 , 249 codons . Estimation of the ω = Ka/Ks ratio was performed using the maximum likelihood method implemented in the CODEML program [88] . The ω ratio measures the magnitude and direction of selective pressure on coding sequence , with ω = 1 , <1 , and >1 indicating neutral evolution , purifying selection , and positive diversifying selection , respectively . To examine whether the ω ratio varied between the B . recurrentis and B . duttonii branches , we fitted two different models: the first model considered a single ω ratio for the 2 branches of B . recurrentis and B . duttonii ( ωBre-Bdu ) and a background ω ratio ( ω0 ) averaged over the remaining branches of the borrelia phylogeny . In the second model , a specific ω ratio was considered for each of the B . recurrentis and B . duttonii branches ( ωBre and ωBdu , respectively ) as well as a background ω0 ratio common to the remaining branches . To determine which of the two nested models best fit the data , we compared their likelihoods using the Likelihood Ratio Test ( LRT ) ( Table S4 ) . The likelihood statistics – i . e . twice the log likelihood difference between the 2 models ( 2δlnL ) , can be compared to the chi square distribution with a degree of freedom equal to the difference of the number of free parameters in the two models ( ddf = 1 in our analysis ) . The LRT test ( 2δlnL = 6 . 0 ) indicated that model 2 better fits the data than model 1 . However , the likelihood difference between the two models is only borderline significant ( P = 0 . 014 ) . | Borreliae are vector-borne spirochetes that are responsible for Lyme disease and recurrent fevers . We completed the genome sequences of the tick-borne Borrelia duttonii and the louse-borne B . recurrentis . The former of these is responsible for emerging infections that mimic malaria in Africa and in travellers , and the latter is responsible for severe recurrent fever in poor African populations . Diagnostic tools for these pathogens remain poor with regard to sensitivity and specificity due , in part , to the lack of genomic sequences . In this study , we show that the genomic content of B . recurrentis is a subset of that of B . duttonii , the genes of which are undergoing a decay process . These phenomena are common to all louse-borne pathogens compared to their tick-borne counterparts . In B . recurrentis , this process may be due to the inactivation of genes encoding DNA repair mechanisms , implying the accumulation of errors in the genome . The increased virulence of B . recurrentis could not be traced back to specific virulence factors , illustrating the lack of correlation between the virulence of a pathogen and so-called virulence genes . Knowledge of these genomes will allow for the development of new molecular tools that provide a more-accurate , sensitive , and specific diagnosis of these emerging infections . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"genetics",
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"genomics/genomics",
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"diseases/tropical",
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] | 2008 | The Genome of Borrelia recurrentis, the Agent of Deadly Louse-Borne Relapsing Fever, Is a Degraded Subset of Tick-Borne Borrelia duttonii |
Ultrasonography allows for non-invasive examination of the liver and spleen and can further our understanding of schistosomiasis morbidity . We followed 578 people in Southwest China for up to five years . Participants were tested for Schistosoma japonicum infection in stool and seven standard measures of the liver and spleen were obtained using ultrasound to evaluate the relationship between schistosomiasis infection and ultrasound-detectable pathology , and the impact of targeted treatment on morbidity . Parenchymal fibrosis , a network pattern of the liver unique to S . japonicum , was associated with infection at the time of ultrasound ( OR 1 . 40 , 95% CI: 1 . 03–1 . 90 ) and infection intensity ( test for trend , p = 0 . 002 ) , adjusting for age , sex and year , and more strongly associated with prior infection status and intensity ( adjusted OR 1 . 84 , 95% CI: 1 . 30–2 . 60; test for trend: p<0 . 001 respectively ) , despite prompt treatment of infections . While declines in parenchymal fibrosis over time were statistically significant , only 28% of individuals with severe parenchymal fibrosis ( grades 2 or 3 ) at enrollment reversed to normal or grade 1 within five years . Other liver abnormalities were less consistently associated with S . japonicum infection . Parenchymal fibrosis is an appropriate measure of S . japonicum morbidity and can document reductions in disease following control efforts . Other ultrasound measures may have limited epidemiological value in regions with similar infection levels . Because severe fibrosis may not reverse quickly following treatment , efforts to reduce exposure to S . japonicum should be considered in combination with treatment to prevent schistosomiasis morbidity .
Schistosomiasis causes morbidity in the human host through the schistosome egg , which triggers inflammation and fibrosis that can lead to anemia , impaired growth and in severe cases , gastrointestinal bleeding and death [1]–[4] . The major intestinal schistosomes , Schistosoma japonicum , found in Asia , and S . mansoni , found in Africa , the Americas and the Middle East , mature , mate and lay eggs in the portal and mesenteric blood vessels . Eggs are transported to the liver where they are encapsulated and the granulomas that form induce an inflammatory cascade that includes the deposition of collagen and extracellular matrix proteins , a normal liver repair process that can lead to fibrosis when fibrogenesis exceeds the replacement of scar tissue with healthy cells [5] , [6] . The immune regulation of this process is currently being explored [7] . Approximately 700 , 000 people are infected with S . japonicum in China [8] . As in other parts of the world , schistosomiasis control efforts have focused primarily on the distribution of the antischistosomal drug , praziquantel [9] , [10] . However the success of such efforts hinges on the ability to reduce not only schistosomiasis infections , but also morbidity . A means of documenting S . japonicum morbidity is essential to the evaluation of disease control efforts [11] . Ultrasound is a non-invasive method that can be used to evaluate fibrosis resulting from schistosomiasis infection . Fibrosis along the portal vein and its branches produces a clay pipestem pattern , as the portal tracks are lined with fibrous tissue , and is observed following both S . mansoni and S . japonicum infection . This periportal fibrosis can be assessed qualitatively through image classification [12] or quantitatively by measuring the diameter of three secondary portal branches [13] . Unique to S . japonicum infection is parenchymal fibrosis , a network pattern that is often described as fish scale or tortoise shell-like . Parenchymal fibrosis is likely due to the smaller S . japonicum egg size which allows the parasite eggs to enter smaller portal veins and reach a greater portion of the liver [7] . S . japonicum adult females produce ten times more eggs per day than S . mansoni , and the eggs often are deposited in clusters , two additional factors that exacerbate the severity of S . japonicum morbidity relative to other schistosome species and may contribute to the unique fibrotic pattern [3] . Ultrasound can also be used to assess hepatomegaly , splenomegaly and dilation of the portal vein , all of which result from portal hypertension . Recognizing the potential of ultrasound to be used to evaluate the impact of disease control efforts , draft protocols for the use of ultrasound in assessing schistosomiasis morbidity were established for each of the three major schistosome species in 1990 [13] , [14] . Follow-up meetings to refine the protocols for S . haematobium and S . mansoni were held in 1996 and 1997 [15] . Ultrasound is considered the gold standard for schistosomiasis morbidity assessment for these species [11] . However , due to insufficient evidence the protocol for S . japonicum has not been revised . To date , a comprehensive evaluation of the S . japonicum ultrasound measures proposed in Cairo , including their relationship to S . japonicum infection and the way in which they change following treatment , is lacking . Li et al . [16] , [17] offer the most complete examination of the proposed ultrasound measures to date , tracking a highly exposed cohort over five years , but as standard organ sizes have only recently been published [18] , assessments of liver and spleen enlargement did not account for participant height as currently recommended [15] . Failure to account for height-specific variation in organ sizes can lead to underestimates of morbidity , particularly in pediatric populations [19] . Ideally , ultrasound measures are associated with S . japonicum infection and decline following treatment [13] . The available data is conflicting on both criteria . Treatment led to declines in parenchymal and periportal fibrosis in a highly exposed Chinese cohort; however 68% of participants experienced no change in parenchymal fibrosis over a five-year period [16] , [17] and other studies have not found significant declines in periportal fibrosis following S . japonicum treatment [20] , [21] . Further , a direct relationship between infection and fibrosis or measures of portal hypertension has not been demonstrated consistently [16] , [17] , [22] . We followed 578 individuals over five years in order to examine the relationship between S . japonicum infection and five liver ultrasound measurements recommended in the draft protocol as well as two spleen ultrasound measurements included in the standard Chinese examination . Specifically , we hypothesized that S . japonicum infection is associated with ultrasound-detectable measures of hepatic fibrosis and that treatment of infected individuals leads to declines in ultrasound-detected morbidity .
All participants provided oral informed consent and were provided treatment following S . japonicum positive stool examinations . As the survey procedures used in this study are the same as those used by the Institute of Parasitic Diseases , Sichuan Center for Disease Control and Prevention ( IPD ) for schistosomiasis surveillance and given the high rates of illiteracy in the population , oral informed consent was obtained and documented by IPD staff . The research protocol and consent procedures were approved by the Sichuan Institutional Review Board and the University of California , Berkeley Committee for the Protection of Human Subjects . Ultrasound examinations were conducted in fall 2000 , 2002 and 2005 . All examinations were conducted by one trained ultrasonographer ( YZ ) using a single portable ultrasound machine ( Hitachi EUB 405 , Hitachi Corporation , Tokyo , Japan ) and 3 . 5 MHz probe ( Hitachi EUP-C314T , Hitachi Corporation , Tokyo , Japan ) with participants in the supine position at a central location in each village . The ultrasonographer was blind to infection status . Liver ultrasonography was conducted according to the 1990 draft guidelines [13] , [14] . Liver parenchymal fibrosis was graded 1 through 3 based on observed lesions , or 0 if none were present . Periportal fibrosis was assessed by grading the average diameter , from outer wall to outer wall , of three peripheral branches of the portal vein between the first and third branching point ( grade 0: <3mm; grade 1: 3 to 5 mm; grade 2: >5 to 7 mm; grade 3: >7 mm ) . As done previously , grades 0 and 1 were combined for analysis [16] . The internal diameter of the portal vein was measured at the entry point of the portal vein into the liver . The length of the left liver lobe was measured in a longitudinal section along the left parasternal line , and the length of the right liver lobe was measured as the maximum oblique diameter using a right anterior axillary view according to the revised guidelines established for S . mansoni [15] . Two measurements of the spleen that are part of the standard Chinese examination were also included: spleen thickness , measured from the hilum to the opposite section , and the internal diameter of the spleen vein , measured at the entry point to the spleen [24] . Because organ and vein sizes vary with height , left and right liver lobe length , portal vein diameter and spleen thickness were evaluated using height-specific standard sizes drawn from a Chinese population where schistosomiasis is not endemic [18] . Measurements greater than two standard deviations above the mean size for height were classified as abnormal . Height was measured in 2002 in 440 of the 578 cohort members . The 343 adults ( ≥18 years old in 2000 ) with height measurements were assigned their 2002 height throughout the study . Children ( <18 years old in 2000 ) were measured again in 2007 as part of a study described elsewhere [19] . The height measurements from 2002 and 2007 from 119 children ( 60 with 1 height measurement , 59 with two height measurements ) were used to generate an age- and sex-dependent random intercept model in order to impute heights during the years children weren't measured . Height for child i at time j was calculated using the following equation:where Aij represents a child's age at time j , Si represents his or her sex ( S = 1 for males ) and represents his or her random intercept . The model was fit using xtmixed in Stata 10 . 1 ( StataCorp , College Station , TX , USA ) and was predicted using empirical Bayes [25] . As random intercept models assume parametric distribution of residuals , first and second order residuals were examined and were normally distributed . The selected model was superior to a model that did not include a random intercept ( likelihood ratio test , χ2 = 38 . 20 , 1 d . f . , p<0 . 001 ) . Organ and vessel measures could not be height adjusted for the 86 adults and 26 children without height measurements . Participants with any versus no height data did not differ significantly by any of the predictors examined in the analyses including sex , mean age or infection status . No height standardized values were available for spleen vein diameter , so it was evaluated by the standard threshold used in China: >8 mm [24] . Participants were tested for infection with S . japonicum in the fall of 2000 and 2002 using the miracidial hatch test [26] and the Kato-Katz thick smear procedure [27] . For each hatch test , a stool sample weighing at least 30 g was suspended in aqueous solution , filtered using copper mesh to remove large particles ( 40–60 mesh ) followed by nylon gauze ( 260 mesh ) to concentrate schistosome eggs . This sediment was re-suspended with distilled water in a 250 ml Erlenmeyer flask . Flasks were examined for miracidia 30–60 minutes , 4 hours and 8 hours after suspension if temperatures were above 30 degrees Celsius , or at 6 , 12 and 18 hours at lower ambient temperatures . In 2000 , three miracidial hatch tests were conducted per person using stool samples from three distinct days . In 2002 , due to logistical constraints , one miracidial hatch test was conducted per person; however the Kato-Katz protocol was identical both years . The Kato-Katz procedure involved the preparation of three 41 . 5 mg slides from one homogenized stool sample in 2000 and 2002 . Infection intensity , in eggs per gram of stool ( EPG ) , was calculated as the total number of S . japonicum eggs present on the slides divided by the total sample weight . Participants were classified as infected if at least one test was positive . Everyone testing positive for S . japonicum was provided praziquantel treatment by the county Anti-Schistosomiasis Control Station . In addition , praziquantel was administered to all residents in the study villages in 2003 , as part of a nation-wide effort to control infectious diseases following the outbreak of severe acute respiratory syndrome . Participant age , sex , occupation and highest level of schooling were obtained by interview in fall 2000 . In order to assess whether the participants in the ultrasound cohort were representative of the village populations from which they were selected , cohort participants were compared to individuals who participated only in the cross-sectional demographic and infection surveys in terms of age , sex , occupation , educational attainment and 2000 S . japonicum infection status . Similarly , cohort members with complete vs . incomplete follow-up were compared in terms of age , sex , baseline morbidity and infection in order to assess non-differential loss to follow-up . In both cases , comparisons were conducted using the χ2 and t-test . Analyses that included multiple observations from individuals accounted for within subject correlation of outcomes . Liver parenchymal fibrosis grade , an ordinal measure , was examined using ordinal logistic regression , a population averaged model using a sandwich type estimator for inference accounting for within-subject residual correlation [28] . Because ordinal logistic regression assumes the effect of a predictor on an outcome is constant for each stepwise increase in the outcome , the Brant test [29] was used to check that this parallel regression assumption was not violated . For all other liver and spleen measures and for predictors of S . japonicum infection status , generalized estimating equation ( GEE ) logistic regression with exchangeable correlation was conducted [30] . The Huber/White/sandwich estimator of variance was used which is robust to misspecification of the outcome distribution [31] , [32] . The relationship between S . japonicum infection and ultrasound-detected abnormalities was first assessed by examining the impact of current infection status and , separately , infection intensity , on current ultrasound measures . Because infection intensity was highly right skewed , it was categorized into approximate quartiles among those who were infected . In order to examine the role of past infection on current morbidity , we also examined the relationship between infection status and intensity two to three years prior to the ultrasound examination and ultrasound-detected abnormalities ( for example: 2000 infection status as a predictor of ultrasound-detected morbidity in 2002 , and 2002 infection status as a predictor of ultrasound-detected morbidity in 2005 ) . We hypothesized that age , sex and year of examination could modify the effect of infection on morbidity , so each model was run including all possible first-order interaction terms . The Wald test was used to test for significant interactions and if present , terms were removed from the model step-wise until only interaction terms significant at p-values <0 . 05 remained . In the absence of effect modification , these same variables could confound the relationship between infection and ultrasound-detected morbidity . While occupation , village and educational status were considered potential predictors of S . japonicum infection , they are unlikely to effect ultrasound morbidity independent of infection status . As they do not fit the definition of confounders [33] , they were not controlled for in models examining the relationship between infection and ultrasound-detected abnormalities . The change in ultrasound-detected abnormalities over time was examined adjusting for age and sex . We modeled age as a categorical variable when examining the relationship between age and ultrasound-detected morbidity to allow a non-linear relationship . Because liver abnormalities increase with age , age was treated as a continuous variable when included as a confounder in models testing the relationship between infection and morbidity , or changes in morbidity over time . Periportal fibrosis grade was modeled as a binary variable , as grades 0 and 1 were combined and no grade 3 fibrosis was detected . Tests for trend were calculated by treating categorical variables as ordinal . All results were assessed for statistical significance setting α = 0 . 05 . Statistical analyses were conducted using Stata 10 . 1 ( StataCorp , College Station , TX , USA ) .
In 2000 , 578 people from ten villages were examined using ultrasound . The mean age of participants was 29 . 8 years ( range 4–61 years ) . Half ( 51% ) were female ( Table 1 ) . Most adults ( ≥18 years ) were farmers ( 91% ) and had no formal schooling beyond elementary school ( 59% ) . Participants were similar in terms of occupation , educational attainment and 2000 infection status to the 1 , 333 residents in these villages who participated in infection and demographic surveys only , although cohort members were slightly older than the rest of the population ( mean age 29 . 8 vs . 28 . 2 , p = 0 . 037 ) . We conducted ultrasound examinations with 444 people in 2002 and 321 people in 2005 . The 320 people with complete ultrasound follow-up were no more likely to be infected with S . japonicum at enrollment than those who missed at least one follow-up examination , but they were older ( mean age 33 . 0 vs . 25 . 6 , p<0 . 001 ) and more likely to have at least one liver abnormality in 2000 ( 57% vs . 37% , p<0 . 001 ) . Nearly half ( 47% ) of participants tested positive for S . japonicum in 2000 . Mean infection intensity was 53 . 4 EPG . In 2002 , infection prevalence declined to 32% and intensity to 9 . 4 EPG . As shown in Table 2 , adults aged 50 and older were less likely to be infected than younger participants . Neither sex nor occupation was associated with infection prevalence , but among adults , higher educational attainment was protective . Infection prevalence in 2002 was significantly higher among those who were infected vs . uninfected in 2000 despite the distribution of treatment to everyone who tested positive ( 41% vs . 23% , p<0 . 001 ) . Infection prevalence varied significantly by village . Table 3 describes the prevalence of liver parenchymal fibrosis , periportal fibrosis and abnormal liver and spleen measurements from 2000 to 2005 . Following the initiation of schistosomiasis testing and treatment of all infections in 2000 , parenchymal fibrosis , periportal fibrosis and right liver lobe enlargement decreased significantly through 2005 , controlling for age and sex ( Table 4 ) . Decreases in spleen enlargement were also observed , although the trend was of marginal significance ( p = 0 . 091 ) . Liver abnormalities increased significantly with age , most notably for parenchymal fibrosis ( Table 4 ) . Spleen enlargement was not associated with age . Individuals aged 18 to 29 years had the highest odds of spleen vein dilation . The relationship between liver abnormalities and sex varied: men were more likely to have periportal fibrosis and enlarged right liver lobes; women were more likely to have enlarged left liver lobes . Schistosomiasis infection at the time of ultrasound was associated with an increase in liver parenchymal fibrosis grade ( OR 1 . 40 , 95% CI: 1 . 03–1 . 90 ) adjusting for age , sex and year of ultrasound ( Table 5 ) . Infection intensity at the time of ultrasound was also associated with an increase in liver parenchymal fibrosis grade ( test for trend: p = 0 . 002 ) . Individuals with greater than 50 EPG had 2 . 10 times greater odds of more advanced fibrosis than those not excreting eggs ( 95% CI: 1 . 33–3 . 32 ) . Schistosomiasis infection two to three years prior to ultrasound was associated with an increase in liver parenchymal fibrosis grade , and the association was stronger than that of current infection ( OR 1 . 84 , 95% CI: 1 . 30–2 . 60 ) . Prior infection intensity was also associated with liver parenchymal fibrosis ( test for trend , p<0 . 001 ) . Individuals with greater than 50 EPG two to three years prior to the ultrasound examination had 2 . 84 times greater odds of advanced fibrosis than those not excreting eggs two to three years prior to ultrasound ( 95% CI: 1 . 71–4 . 73 ) . The other hepatosplenic ultrasound measures were not associated with current infection status or intensity . Several measures were associated with prior infection , although the relationships were not as consistent as those observed for periportal fibrosis . Prior infection appeared to elevate the probability of left liver lobe enlargement ( OR 1 . 45 , 95% CI: 0 . 97–2 . 17 ) . Prior infection intensity but not prior infection status , was associated with increased odds of portal vein dilation ( test for trend , p = 0 . 051 ) . The impact of prior infection status on right liver lobe enlargement varied by the year of examination and the sex of the participant . Prior infection was associated with increased odds of right liver lobe enlargement among males examined in 2005 ( OR 3 . 95 , 95% CI: 1 . 82–8 . 57 ) and decreased odds of right liver lobe enlargement among females examined in 2002 ( OR 0 . 33 , 95% CI: 0 . 13–0 . 86 ) . Prior infection intensity was not associated with right or left liver lobe enlargement . Due to the limited number of individuals with periportal fibrosis , models were unable to yield stable estimates of the effect of prior infection on this measure Spleen enlargement and spleen vein dilation were not associated with current or prior infection . Most people with liver and spleen enlargement , portal vein dilation , periportal fibrosis or spleen vein dilation in 2000 had normal pathology by 2002 ( Table 6 ) . However , this was not the case for parenchymal fibrosis: 67% of people with grade 2 fibrosis and 100% with grade 3 fibrosis in 2000 remained at or above grade 2 throughout the five-year follow-up .
We found evidence of a direct , exposure-response relationship between S . japonicum infection and parenchymal fibrosis . While there has been suggestive evidence of an association between infection and parenchymal fibrosis , including an association between progression of parenchymal fibrosis and current infection [16] , this is the first study to show the risk of parenchymal fibrosis is higher in people who are infected vs . uninfected , and highest in individuals with the greatest infection intensities . Parenchymal fibrosis declined significantly following treatment however , improvements were limited among individuals with advanced fibrosis: 72% of people with severe fibrosis at enrollment ( grades 2 or 3 ) had not resolved below grade 2 by the end of the five-year study . This suggests parenchymal fibrosis is an appropriate measure of S . japonicum morbidity and can document improvements in morbidity following treatment , although little improvement may be observed among those with advanced fibrosis . In contrast , the remaining measures were less consistently associated with S . japonicum infection and are of questionable epidemiological use in regions with similar infection levels . Periportal fibrosis was rare in this population and could not be associated with S . japonicum infection , although it did decline significantly following the initiation of targeted treatment . Others have used image-based classification to assess periportal fibrosis [34] , [35] , which has been shown to have better reproducibility for S . mansoni-related fibrosis , perhaps because it does not require the ultrasonographer to measure narrow vessel widths [36] . Our measures of periportal fibrosis were not height adjusted , as Chinese standards for the diameter of portal vein branches as measured here have not been published . The lack of height adjustment may have led to underestimates of the prevalence of periportal fibrosis and may explain the higher prevalence of periportal fibrosis in men , however higher prevalence of fibrosis has also been observed in males using image-based classification [35] . The remaining three hepatic measures , left and right liver lobe enlargement and portal vein dilation , were associated with S . japonicum infection or declined following chemotherapy . However , the relationships between S . japonicum infection and these morbidity measures were less consistent than those observed with parenchymal fibrosis and several associations were of marginal statistical significance . The spleen measures were neither associated with infection nor did they decline with treatment . All five measures require the ultrasonographer to measure organ or vessel sizes and participant's height . Like the measures of periportal fibrosis used here , these methods present opportunities for measurement error which may bias estimates of exposure-disease relationships toward the null , producing attenuation and exacerbating non-linearity [37] . The reproducibility of some of these measures has been shown to be poor in a pediatric population , and further efforts to evaluate the accuracy of organ and vein size measurements are needed [19] . Overall , the prevalence of morbidity in this cohort was lower than has been observed elsewhere in China as was infection intensity [16] , [17] , [34] , [38] . Measures of liver and spleen enlargement , portal vein dilation and spleen vein dilation were less informative than measures of parenchymal fibrosis but may be appropriate in areas where infection intensity and associated morbidities are higher . Declines in hepatomegaly and splenomegaly have been demonstrated following treatment in regions with higher average worm burdens [16] , [17] . The strong associations between age and all liver measures highlight the importance of considering age as a potential confounder when examining the relationship between S . japonicum infection and morbidity and declines in morbidity over time . For example , the unadjusted prevalence of parenchymal fibrosis did not change over time , however as loss to follow-up was highest in younger populations which were least likely to have fibrosis , the age and sex adjusted prevalence did decline . Our findings shed light on the development of hepatic fibrosis following S . japonicum infection . The lack of reversal of grade 3 parenchymal fibrosis to grade 1 or normal and the association between past infection and current fibrosis suggest severe fibrosis may persist or even progress following treatment . Prior studies have also found minimal reversal of severe fibrosis following treatment [16] , [39] and hepatic fibrosis has been documented in people living in areas where the parasite , and therefore exposure , was eliminated 20 years previously [40] . While treatment with praziquantel can reduce infection prevalence , intensity and fibrosis , this analysis provides further evidence that severe hepatic fibrosis may be unlikely to reverse quickly . Minimal declines in severe hepatic fibrosis associated with S . mansoni infection have also been detected [41] but other studies have noted complete reversal of severe morbidity [42] . Further , parenchymal fibrosis was associated with current infection status and intensity but more strongly associated with infection status and intensity two to three years prior to ultrasound , despite timely treatment of infections . The surprising association between past infection and fibrosis raises questions about the progression of fibrosis following infection and treatment . Praziquantel kills the adult worm but schistosome eggs can remain trapped in host tissues decades after exposure [43] . While schistosome eggs are thought to disintegrate within weeks of granuloma formation [7] , it is possible , due to an inflammatory cascade , fibrogenesis continues over a longer time period . Collagen deposition has been shown to occur following treatment with praziquantel in S . japonicum infected mice , suggesting fibrosis may continue despite removal of adult worms [44] . In humans , progression of fibrosis has been observed following treatment and was not explained by reinfection [21] , [45] . Alternatively , it is possible that the relationship between past infection and fibrosis is due to reinfection . Past infection predicted subsequent infection . However , if reinfection rather than past infection determined fibrosis , one would expect stronger relationships between current infection and fibrosis than between past infection and fibrosis , which was not observed . It is also possible that some individuals who were treated were not cured . A single dose of praziquantel cures 90% of S . japonicum infections [46] , suggesting 10% of those treated may continue to harbor adult worms and face continued egg production . In our work in this region , we have also found individuals who decline to take praziquantel even after a positive infection test . Non-compliance and treatment failure are realities of any chemotherapy-based control program , however the marked declines in infection prevalence , intensity and morbidity suggest the number of individuals who were not cured was limited . This study examined one of the largest populations to be followed over five years in order to assess ultrasound-detectable morbidity and S . japonicum infection . Participants were randomly sampled from a comprehensive cross-sectional survey in order to minimize selection bias . Loss to follow-up was greater among those without ultrasound-detectable morbidity , which suggests the prevalence of morbidity in 2002 and 2005 may be overestimated , and therefore the true declines in morbidity over time may be greater than observed . Retention was independent of infection status , minimizing bias in estimates of the impact of infection on pathology . No information was available on alcohol consumption or infection with hepatitis B virus ( HBV ) , two factors that can induce liver pathology and may exacerbate schistosomiasis morbidity . The parenchymal network pattern due to S . japonicum is distinct from the lesions produced by HBV , as HBV produces a finer , meshwork texture [47] , suggesting the observed prevalence of parenchymal fibrosis is specific to schistosomiasis . While HBV has been shown to hinder regression of periportal fibrosis following treatment of S . mansoni infections [41] , the extent to which HBV exacerbates morbidity due to S . japonicum remains unclear and warrants further study . Reductions in parenchymal fibrosis may be impaired by alcohol consumption , which in our study areas is confined almost exclusively to males [17] . Unless alcohol consumption or HBV impacts a person's probability of infection , they are unlikely to confound the relationships between infection and ultrasound-detected morbidity . Community-wide testing and treatment of all infections with praziquantel yielded marked declines in infection prevalence and intensity . However , reinfection was high: 32% of people were infected two years after the first round of targeted treatment . High rates of infection following treatment are not uncommon and underscore the challenges of sustainably reducing human schistosomiasis [48] . Adults aged 50 and over were less likely to be infected than younger populations , possibly corresponding to a decline in water contact later in life or acquired immunity [49] . In summary , we present evidence that ultrasound-detectable liver fibrosis is associated with S . japonicum infection status and intensity , controlling for age , sex and year of ultrasound examination , and this measure can be used to monitor S . japonicum induced morbidity . Other ultrasound measures including hepatomegaly and splenomegaly were less clearly associated with infection . Our findings also suggest that some morbidity may not reverse within five years of treatment and may even progress despite treatment . Praziquantel has yielded remarkable declines in schistosomiasis morbidity in China and throughout the globe but reinfection following treatment is common as observed in this study population . S . japonicum infection , particularly high egg loads , may lead to fibrosis that is not rapidly reversed by treatment , underscoring the importance of measures to prevent new infections as well as treating current disease . | Schistosomiasis is a water-borne parasite that infects approximately 200 million people worldwide . Schistosoma japonicum , found in Asia , causes disease by releasing eggs in the liver , leading to fibrosis , anemia , and , in children , impaired growth . Ultrasound can assess liver pathology from schistosomiasis; however more information is needed to evaluate the relevance of standard ultrasound measures . We followed 578 people for up to five years , testing for schistosomiasis infection and conducting ultrasound examinations to assess the relationship between infection and seven ultrasound measures and to evaluate the impact of treatment with anti-schistosomiasis chemotherapy ( praziquantel ) on morbidity . All infections were promptly treated . Fibrosis of the liver parenchyma , pathology unique to S . japonicum , was associated with schistosomiasis infection , and was most advanced in people with high worm burdens . Liver fibrosis declined significantly following treatment , but reversal of severe liver fibrosis was rare . Other ultrasound measures were not consistently related to schistosomiasis infection or treatment . These findings suggest parenchymal fibrosis can be used to measure morbidity attributable to S . japonicum and evaluate the impact of disease control efforts . Because reversal of severe fibrosis was limited , disease control efforts will be most effective if they can not only treat existing infections but also prevent new infections . | [
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] | 2010 | The Impact of Schistosoma japonicum Infection and Treatment on Ultrasound-Detectable Morbidity: A Five-Year Cohort Study in Southwest China |
Intestinal parasitic infections ( IPIs ) have a worldwide distribution and have been identified as one of the most significant causes of illnesses and diseases among the disadvantaged population . In Malaysia , IPIs still persist in some rural areas , and this study was conducted to determine the current epidemiological status and to identify risk factors associated with IPIs among communities residing in rural and remote areas of West Malaysia . A total of 716 participants from 8 villages were involved , comprising those from 1 to 83 years old , 550 ( 76 . 8% ) participants aged ≤12 years and 166 ( 23 . 2% ) aged ≥13 years , and 304 ( 42 . 5% ) male and 412 ( 57 . 5% ) female . The overall prevalence of IPIs was high ( 73 . 2% ) . Soil-transmitted helminth ( STH ) infections ( 73 . 2% ) were significantly more common compared to protozoa infections ( 21 . 4% ) ( p<0 . 001 ) . The prevalence of IPIs showed an age dependency relationship , with significantly higher rates observed among those aged ≤12 years . Multivariate analysis demonstrated that participants aged ≤12 years ( OR = 2 . 23; 95% CI = 1 . 45–3 . 45 ) , low household income ( OR = 4 . 93; 95% CI = 3 . 15–7 . 73 ) , using untreated water supply ( OR = 2 . 08; 95% CI = 1 . 36–3 . 21 ) , and indiscriminate defecation ( OR = 5 . 01; 95% CI = 3 . 30–7 . 62 ) were identified as significant predictors of IPIs among these communities . Essentially , these findings highlighted that IPIs are highly prevalent among the poor rural communities in West Malaysia . Poverty and low socioeconomic with poor environmental sanitation were indicated as important predictors of IPIs . Effective poverty reduction programmes , promotion of deworming , and mass campaigns to heighten awareness on health and hygiene are urgently needed to reduce IPIs .
Globally , the neglected intestinal parasitic infections ( IPIs ) such as soil-transmitted helminth ( STH ) and protozoa infections have been recognized as one of the most significant causes of illnesses and diseases especially among disadvantaged communities . With an average prevalence rate of 50% in developed world , and almost 95% in developing countries , it is estimated that IPIs result in 450 million illnesses [1] , [2] , [3] . These infections are ubiquitous with high prevalence among the poor and socioeconomically deprived communities where overcrowding , poor environmental sanitation , low level of education and lack of access to safe water are prevalent [4] , trapping them in a perennial cycle of poverty and destitution [5] . These parasitic diseases contribute to economic instability and social marginalization; and the poor people of under developed nations experience a vicious cycle of under nutrition and repeated infections leading to excess morbidity with children being the worst affected [2] , [6] . Of these illnesses , infections by STH have been increasingly recognized as an important public health problem and most prevalent of IPIs [7] . STH infections caused by Ascaris lumbricoides , Trichuris trichiura and hookworm ( Necator americanus and Ancylostoma duodenale ) are most significant in the bottom billion of the world's poorest people ( i . e . , <US$1 . 25 per day ) [8] . To date , approximately one third of the world's population is infected with at least one species of STH , with A . lumbricoides infecting 800 million people , T . trichiura 600 million , hookworm 600 million and resulting in up to 135 , 000 deaths annually [5] . With regards to intestinal protozoan infections , giardiasis caused by Giardia duodenalis , is the most predominant protozoa infection with an estimated prevalence rates ranging from 2 . 0 to 7 . 0% in developed countries and 20 . 0 to 30 . 0% in most developing countries , affecting approximately 200 million people worldwide [9] . Amoebiasis caused by Entamoeba histolytica is another important pathogenic protozoa affecting approximately 180 million people , of whom 40 , 000 to 110 , 000 succumbed to death annually [10] . The opportunistic protozoa , Cryptosporidium sp . has also emerged as an important cause of diarrhoeal illnesses worldwide particularly in young children and immunocompromised patients with a prevalence of 4% in developed countries and three to four times more frequent in developing countries [11] . Since the colonial era ( i . e . , 1930s ) in Malaysia , many surveys and studies have been conducted on IPIs , in particular STH infections as they are deemed to be of great medical importance among Malaysian population . While vector-borne diseases such as malaria and filariasis have declined significantly over the years , IPIs which are closely associated with environmental and personal hygiene practices are still causing major health problems among the poor in rural and remote communities in Malaysia [12] . Within this context , we conducted this study to provide a comprehensive data of the current status of IPIs among rural communities residing in remote areas of West Malaysia . The establishment of such data will be beneficial for the public health service to justify and facilitate the reassessment of control strategies and policies .
A cross-sectional study was carried out from November 2007 to July 2009 among 8 villages from 5 different states in rural and remote areas of West Malaysia without being discriminatory towards age or gender . Villages include Betau ( 101 . 78°E longitude , 4 . 10°N latitude ) , Kuala Betis ( 101 . 79°E longitude , 4 . 90°N latitude ) , Sungai Bumbun ( 101 . 42°E longitude , 2 . 85°N latitude ) , Sungai Perah ( 100 . 92°E longitude , 4 . 48°N latitude ) , Gurney ( 101 . 44°E longitude , 3 . 43°N latitude ) , Pos Iskandar ( 102 . 65°E longitude , 3 . 06°N latitude ) , Bukit Serok ( 102 . 82°E longitude , 2 . 91°N latitude ) and finally Sungai Layau ( 104 . 10°E longitude , 1 . 53°N latitude ) ( Figure 1 ) . The villages were selected based on ( i ) village entry approval by the Ministry of Rural and Regional Development Malaysia and ( ii ) willingness to participate by the head and community members of the villages . All villages were located at lowland altitude at the jungle fringes surrounded by rubber and palm oil estates . In general , although these communities have the provision of basic infrastructure ( i . e . , treated water and electricity ) with concrete houses , these facilities are either not fully utilized or evenly distributed . Even if these provisions were given , most of them could not afford to pay their monthly utility bills due to extreme poverty leading to the termination of water and electricity supplies . Therefore , rivers located adjacent to the village remained their main source of water for domestic needs ( i . e . , drinking , cooking , bathing and washing clothes ) . Some households still lived in traditional structures of bamboo , wood , brick or a mixture of both with attap roof ( i . e . , thatched roof made from leaves of Nipah palm tree ) . In addition , although there are pour flush toilets , this facility is not consistently used as the villagers prefer to use nearby bushes and river for defecation . Rearing of animals such as pigs , chickens , ducks , dogs , cats and monkeys are common practices . Most of the residents were employed as unskilled laborers in construction sites , factories , vegetable farms , oil palm and rubber plantations . Before the commencement of the study , an oral briefing explaining the objectives of the study was given to the participants and a voluntary written informed consent was taken from each participant . The participant was then asked by a trained field assistant to answer a pre-tested questionnaire developed to elicit information on the demographic data ( i . e . , age , gender and education attainment ) , socioeconomic ( i . e . , occupation , household income ) , behavioral ( i . e . , personal hygiene such as wearing shoes and food consumption ) , medical treatment ( i . e . , whether the participant has taken anthelminthic drugs and iron supplement ) , environmental sanitation and living condition characteristics ( i . e . , type of water supply , latrine system , garbage disposal system and presence of domestic animals ) which will be used to assess the potential risk factors for IPIs . The questionnaire was designed in Bahasa Malaysia , which is the national language for Malaysia and well understood by the participants . For children and very old participants , the questionnaire was completed by interviewing their parents and guardians or the relevant adult ( normally head of the family ) who signed the informed consent . After consent was obtained and questionnaire answered , a wide mouth screw capped containers pre-labeled with their names and coded were distributed to each participant . Their ability to recognize their names was counter-checked . The participant was instructed to scoop a thumb size fecal sample using a provided scoop into the container , making sure that the sample was not contaminated with urine . Parents and guardians were instructed to monitor their children during the sample collection to ensure that they placed their fecal samples into the right container . Participants who turned up with their fecal samples the following day were honored with a small token of appreciation . The collected fecal samples were processed and examined for the presence of parasites by the formalin ether concentration technique [13] . Briefly , 1 to 2g of fecal sample was mixed with 7 ml of formalin and 3 ml ethyl acetate , centrifuged , stained with 0 . 85% iodine and examined under light microscope . For Cryptosporidium sp . , all fecal samples were examined using modified Ziehl Neelsen stain which includes usage of strong carbol fuchsin , 1% acid alcohol and 0 . 4% malachite green [14] . In addition , Kato-Katz technique was employed to determine the intensity of STH infections , as estimated by egg counts per gram of feces ( EPG ) as described by Martin and Beaver for A . lumbricoides , T . trichiura and hookworm [15] . The total number of eggs observed was multiplied with an appropriate exchange number ( i . e . , number of eggs X 22 . 2 ) to give the number of eggs per gram of feces . The worm burden was categorized as light , moderate or heavy intensity based on the threshold proposed by World Health Organization ( WHO ) Expert Committee in 1987 [16] . Dysenteric or inadequate samples , which were unsuitable for egg counts were used only for examination of intestinal parasites ova by formalin ether concentration technique . Statistical analysis was carried out using the SPSS software ( Statistical Package for the Social Sciences ) programme for windows version 13 ( SPSS , Chicago , IL , USA ) . Initial data entry was cross-checked by two independent individuals in order to be sure that data were entered correctly . Before each analysis , data were again checked for consistency . Prevalence of IPIs was determined on the basis of combined results from the different diagnostic methods . For descriptive data , rate ( percentage ) was used to describe the characteristics of the studied population , including the prevalence of IPIs according to villages , age and gender . The intensity of STH infections ( worm burden ) was quantitatively estimated as eggs per gram of feces ( EPG ) and was divided into three main categories: light , moderate or heavy infections and expressed as means . A Pearson's Chi-square ( X2 ) on proportion was used to test the associations between each variable . In univariate statistical model , the dependent variable was prevalence of IPIs , while the independent variables were sociodemographic , behavior , medical treatment , environmental sanitation and living condition characteristics . All variables that were significantly associated with prevalence of IPIs in univariate model were included in a logistic multivariate analysis using forward elimination model to identify the predictors of IPIs . The level of statistical significance was set as p<0 . 05 and for each statistically significant factor , an odd ratio ( OR ) and 95% confidence interval ( CI ) was computed by the univariate and multivariate logistic regression analysis . The study protocol ( Reference Number: 638 . 36 ) was approved by the Ethics Committee of the University Malaya Medical Centre ( UMMC ) , Malaysia before the commencement of the study . The participants were informed that the procedure used did not pose any potential risk and their identities and personal particulars will be kept strictly confidential . During the meetings , parents and their children were informed that their participation was voluntarily and they could withdraw from the study at any time without giving any reason . Consent of those who agreed to participate were taken either in written form ( signed ) or verbally followed by their thumb prints ( for those who are illiterate ) and from parents or guardians ( on behalf of their children ) .
A total of 716 villagers participated in this study . With regards to age groups , there were a total of 550 ( 76 . 8% ) participants aged ≤12 years and 166 ( 23 . 2% ) aged ≥13 years ranging from 1 to 83 years with a median age of 11 years and a proportion of 1 . 1% , 2 . 4% , 73 . 3% , 2 . 0% and 21 . 2% for the age groups 1 to 4 , 5 to 6 , 7 to 12 , 13 to 17 and above 18 years , respectively . These participants consisted of 304 ( 42 . 5% ) male and 412 ( 57 . 5% ) female . The overall prevalence of IPIs among 716 participants was 73 . 2% with STH infections ( 73 . 2%; 524 ) being significantly more common compared to protozoa infections ( 21 . 4%; 153 ) ( p<0 . 001 ) . In addition , there were also 2 ( 0 . 3% ) cases of Fasciolopsis/Fasciola sp . infection detected ( legend indication “other infection” ) ( Table 1 ) . Prevalence of IPIs were very high in most of the surveyed villages , ranging from 66 . 7% to 97 . 8% . Interestingly , infections were very low in Sungai Layau village ( 4 . 5% ) ( Table 1 ) . There was no significant difference of the IPIs between male and female , although female ( 73 . 3% ) had slightly higher overall prevalence rate compared to male ( 73 . 0% ) ( Table 2 ) . The prevalence of IPIs showed an age dependency relationship , with significantly higher prevalence seen among participants aged ≤12 years compared to those aged ≥13 years ( 76 . 7% versus 61 . 4% , p<0 . 001 ) . With regards to specific age groups , prevalence was highest in the 5 to 6 aged group ( 94 . 1% ) and lowest ( 59 . 2% ) among those aged 18 years and above ( Table 2 ) . The overall prevalence of STH infections was 73 . 2% with T . trichiura ( 66 . 8% ) being the most predominant , followed by A . lumbricoides ( 38 . 5% ) while only 12 . 8% had hookworm infections . In general , participants from Betau village had the highest prevalence of STH infections ( 97 . 8% ) whilst those from Sungai Layau village ( 4 . 5% ) had the least . Based on the total sample size ( n = 716 ) , double infections ( 35 . 6% ) were most common , followed by single infections ( 31 . 6% ) and triple infections ( 6 . 0% ) . T . trichiura ( 28 . 4% ) was the most dominant cause of single infections . The combination of T . trichiura and A . lumbricoides were the most predominant in the double infections , accounting for 30 . 6% of the infection rates . With regards to the intensity of infections , all three species of STH showed light to heavy infections . In general , both T . trichiura and A . lumbricoides infections had similar pattern of worm burden with moderate infection being the most common followed by light and heavy infections . In contrast , most of hookworm infections were light ( Table 3 ) . With regards to the protozoa infections , the overall prevalence was 21 . 4% . The highest prevalence rate was due to G . duodenalis ( 10 . 4% ) , followed by E . histolytica/dispar ( 10 . 2% ) and Cryptosporidium sp . ( 2 . 1% ) . For protozoa infections , participants from Kuala Betis village ( 39 . 0% ) had the highest prevalence , whilst those from Sungai Layau village had the least ( 4 . 5% ) ( Table 1 ) . Based on the total sample size ( n = 716 ) , single infections ( 21 . 4% ) were most predominant , followed by double infections ( 1% ) . There were no triple infections recorded . As for mix infections with both STH and protozoa , the most common combinations were T . trichiura , hookworm and G . duodenalis ( 17 . 4% ) followed by T . trichiura either with G . duodenalis or E . histolytica/dispar ( 12 . 4% ) and finally a combination of four species which included T . trichiura , A . lumbricoides , G . duodenalis and E . histolytica/dispar ( 1 . 4% ) infections . The risk factors associated with IPIs in relation to sociodemographic and lifestyles among rural communities were examined by univariate analysis . There were eight risk factors identified which included those less than 12 years old ( OR = 2 . 10; 95% CI = 1 . 43-2 . 98; p<0 . 001 ) , low household income ( OR = 7 . 60; 95% CI = 5 . 30–11 . 13; p<0 . 001 ) , using untreated water supply for daily chores ( OR = 2 . 84; 95% CI = 2 . 08–3 . 86; p<0 . 001 ) , the lack of proper latrine system ( OR = 2 . 19; 95% CI = 1 . 54–3 . 10; p<0 . 001 ) , non-existence of pour flush toilet ( OR = 3 . 29; 95% CI = 2 . 62–4 . 12; p<0 . 001 ) , indiscriminate defecation ( OR = 3 . 45; 95% CI = 2 . 76–4 . 32; p<0 . 001 ) and indiscriminate garbage disposal ( OR = 2 . 06; 95% CI = 1 . 45–2 . 94; p<0 . 001 ) , and finally not taking any anthelminthic drugs in the last 12 months ( OR = 1 . 29; 95% CI = 1 . 01–1 . 65; p = 0 . 038 ) . Although being a female ( 73 . 3%; p = 0 . 935 ) , jobless ( 74 . 1%; p = 0 . 088 ) , have had no close contact with animals ( 80%; p = 0 . 193 ) and not taking any iron supplement ( 73 . 5%; p = 0 . 801 ) were factors which had higher infection rates , nonetheless these variables were not statistically significant ( Table 4 ) . Multivariate analysis using forward logistic regression model further confirmed that participant less than 12 years old were 2 . 2 times ( 95% CI = 1 . 45–3 . 45; p<0 . 001 ) , low household income had 4 . 9 times ( 95% CI = 3 . 15–7 . 73; p<0 . 001 ) , using untreated water supply had 2 . 1 times ( 95% CI = 1 . 36–3 . 21; p<0 . 001 ) and indiscriminate defecation were 5 times ( 95% CI = 3 . 30–7 . 62; p<0 . 001 ) more likely to suffer from an IPIs , respectively .
Intestinal parasitic infections are highly prevalent and are major public health concerns among the poor and socioeconomically deprived rural and remote communities in West Malaysia . Given that IPIs are intimately associated with poverty , poor environmental sanitation and lack of clean water supply , it is crucial that these factors are addressed effectively . Improvement of socioeconomic status , sanitation , health education to promote awareness about health and hygiene together with periodic mass deworming are better strategies to control these infections . With effective control measures in place , these communities ( especially children ) will have a greater opportunity for a better future in terms of health and educational achievement . | Intestinal parasitic infections ( IPIs ) are among the most prevalent human afflictions; these infections still have major impact on the socioeconomic and public health of the bottom billion of the world's poorest people . Although Malaysia has a thriving economy , IPIs are still very much prevalent and causing major health problems among the poor and in deprived communities especially in rural and remote areas . A comprehensive study is paramount to determine the current prevalent and factors closely linked to IPIs so that effective control measures can be instituted . In view of this , we conducted this study to provide detailed data of the existing status of IPIs among 716 participants living in rural and remote areas in Peninsular Malaysia . The establishment of such data is beneficial for the public health service to justify and facilitate the reassessment of control strategies and policies in terms of reducing intestinal parasitism . With effective control measures in place , these communities ( especially children ) will have a greater opportunity for a better future in terms of health and educational achievement and eventually will be at par socially and economically with urban communities in Malaysia . | [
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] | 2011 | Prevalence and Risk Factors of Intestinal Parasitism in Rural and Remote West Malaysia |
To eliminate and eradicate gambiense human African trypanosomiasis ( HAT ) , maximizing the effectiveness of active case finding is of key importance . The progression of the epidemic is largely influenced by the planning of these operations . This paper introduces and analyzes five models for predicting HAT prevalence in a given village based on past observed prevalence levels and past screening activities in that village . Based on the quality of prevalence level predictions in 143 villages in Kwamouth ( DRC ) , and based on the theoretical foundation underlying the models , we consider variants of the Logistic Model—a model inspired by the SIS epidemic model—to be most suitable for predicting HAT prevalence levels . Furthermore , we demonstrate the applicability of this model to predict the effects of planning policies for screening operations . Our analysis yields an analytical expression for the screening frequency required to reach eradication ( zero prevalence ) and a simple approach for determining the frequency required to reach elimination within a given time frame ( one case per 10000 ) . Furthermore , the model predictions suggest that annual screening is only expected to lead to eradication if at least half of the cases are detected during the screening rounds . This paper extends knowledge on control strategies for HAT and serves as a basis for further modeling and optimization studies .
Human African trypanosomiasis ( HAT ) , also known as sleeping sickness , is a parasitic disease that is caused by two sub-species of the protozoa Trypanosoma brucei: Trypanosoma brucei gambiense ( gambiense HAT ) and Trypanosoma brucei rhodesiense ( rhodiense HAT ) . The infection causing the disease is transmitted from person to person through the tsetse fly . It is estimated that there were 20000 cases in the year 2012 [1] and that 70 million people from 36 Sub-Saharan countries are at risk of HAT infection [2 , 3] . Our work focuses on gambiense HAT , which represents 98% of all HAT cases [3] . Gambiense HAT , which we will refer to as “HAT” from now on , is a slowly progressing disease and is fatal if left untreated . In the first stage of the disease , symptoms are usually absent or non-specific [4] . The median duration of this stage is about 1 . 5 years [5] . By the time patients arrive at a healthcare provider , the disease has often progressed to the neurological phase , which causes severe health problems . In addition , this treatment delay increases the rate of transmission , since an infected patient is a potential source of infection for the tsetse fly [4 , 6] . Therefore , active case finding and early treatment are key to the success of gambiense HAT control [7 , 8] . The current case finding strategy uses mobile teams that travel from village to village to conduct exhaustive population screening [4 , 8 , 9] . For example , 35 mobile teams are active in the Democratic Republic of the Congo ( DRC ) . Because this strategy has considerably reduced disease prevalence in several African countries [6 , 10–12] , the disease is no longer perceived as a major threat . Consequently , donors are now scaling down their financial commitments [8] . This , however , poses a serious risk to the control of HAT . The disease tends to re-emerge when screening activities are scaled down , bringing about the risk of a serious outbreak , as shown by an epidemic in the 1990s [4 , 11 , 13] . For example , the number of cases in 1998 is estimated to have exceeded 300000 [3] . In order to minimize the risk of re-emergence when resources are scaled down , and in order to eliminate and eradicate the disease , maximizing the effectiveness of the control programs is crucial . Mpanya et al . [9] suggest that the effectiveness of population screening is determined by ( among others ) the management and planning of the mobile teams . Planning decisions—which determine which villages to screen , and at what time interval to screen them—have a direct impact on the risk and the magnitude of an outbreak . Existing literature does not address these issues , as highlighted by the WHO [1] , and a wide variety of screening intervals have been applied in different control programs [12 , 14 , 15] . To optimize the planning decisions , it is of key importance to be able to predict the evolution of the HAT prevalence level in the villages at risk . This allows decision makers to assess the relative effectiveness of a screening round in these villages and to prioritize the screening rounds to be performed . However , practical tools for predicting HAT prevalence appear to be lacking . Existing models for HAT are mostly based on differential equations , describing the rate of change for the HAT prevalence level among humans and flies as a function of the prevalence levels among humans and flies ( some models also include an animal reservoir ) [16–22] . As the information needed to use such models—e . g . , the number of tsetse flies in a village—is not available on the village level , using these models for prediction is impractical . This paper therefore sets out to develop practical models describing and predicting the expected evolution of the HAT prevalence level in a given village , based on historical information on HAT cases and screening rounds in that village . The main difference with the models mentioned in the previous paragraph is that our models make no assumptions about the causal factors underlying the observed prevalence levels: the “inflow” of newly infected persons and the “outflow” of infected persons by cure or death . Instead , we just consider data on the net effect of these two processes—the evolution of the prevalence level—and fit five different models to this . To analyze the predictive performance of these models , we make use of a dataset describing screening operations and HAT cases in the Kwamouth district in the DRC for the period 2004–2013 . Furthermore , we use one of the models to analyze the fixed frequency screening policy , which assigns to each village a fixed time interval for consecutive screening rounds . Specifically , we investigate screening frequency requirements for reaching elimination and eradication . Here , eradication is defined as “letting the expected prevalence level go to zero in the long term” , and elimination is defined as “reaching an expected prevalence level of one case per 10000” . Our paper thereby contributes to the branch of research on control strategies for HAT . Next , we list several other papers that are highly related to our work . The effectiveness of active case finding operations is analyzed by Robays et al . [23] , who define “effectiveness” as the expected fraction of cases in a village which will eventually get cured as a result of a screening round in that village . The papers by Stone & Chitnis [16] , Chalvet-Monfray et al . [20] , and Artzrouni & Gouteux [24] introduce differential equation models to gain structural insights on the effectiveness of combinations of active case finding and vector control efforts and on the requirements for eradicating HAT . The effect of active case finding activities is modeled through a continuous “flow” of infected individuals into the susceptible compartment . Since we explicitly model the timing and the effects of a screening round , this is one of the main differences with our paper . Finally , Rock et al . [10] study the effectiveness of screening and treatment programs and the time to elimination using a multi-host simulation model . Their paper , however , considers the screening frequency as a given , whereas we consider the effects of changing this frequency . Furthermore , we propose models for predicting prevalence on a village level , whereas their model implicitly assumes all villages to be homogeneous .
Our dataset consists of information on screening operations in the period 2004–2013 in the health zone Kwamouth in the province Bandundu . The raw data were cleaned up based on the rules described in S1 Text . The number of villages in the dataset equals 2324 , and 143 of these villages were included in the data analysis based on three criteria: ( 1 ) the number of screening rounds recorded was at least two , ( 2 ) at least one case has been detected over the time horizon , and ( 3 ) at least one record of the number of people screened during the operation was available . The first condition is necessary to enable modeling the prevalence level observed in a given screening round as a function of past observed prevalence levels , and the third condition is necessary for estimating prevalence itself . We estimate the prevalence level in a village at the time of a screening round as the number of cases detected in that round over the number of people participating in that round . Furthermore , lacking population size data , we estimate the population of a village as the maximum number of people participating in a screening round reported for that village . Though our dataset also contains cases identified by the regular health system in between successive screening rounds , these do not yield ( direct ) estimates of prevalence levels in the corresponding villages , as required by the models proposed in the next section . We therefore focus on the active case finding data only . The total number of screening rounds reported for the 143 villages included equals 766 ( on average 5 . 4 per village ) . Fig 1 shows cumulative distributions of the observed prevalence level in these screening rounds ( mean 0 . 0055 , median 0 . 0011 , standard deviation 0 . 0121 ) , the time interval between each pair of consecutive screening rounds ( mean 1 . 28 , median 1 . 00 , standard deviation 1 . 03 ) , the estimated population for each village ( mean 1073 , median 450 , standard deviation 2046 ) , and the participation level in the screening rounds ( mean 0 . 69 , median 0 . 72 , standard deviation 0 . 27 ) . Note that the relatively large number of observations with a participation level of 100% is due to the method used to estimate the population sizes . Before we propose our prediction methods , we introduce some notations . A table of the most important notations used in this article can be found in S1 Table . Let sv = {sv1 , sv2 , …} denote the vector of screening time intervals for village v , where sv1 denotes the time between the start of the time horizon and the first screening for this village , sv2 denotes the time between the first and the second screening , and so on . The time at which the nth screening is performed is given by Svn = ∑m≤n svm and the participation fraction in this screening round is denoted by pvn . Parameter Nv represents the population size of village v . Furthermore , let iv represent historical information on HAT cases in this village: the numbers of cases detected during past screening rounds . We model the expected prevalence level at time t in village v as a function fv ( ⋅ ) of sv , iv , and some parameters β: fv ( t , sv , iv , β ) . Note that the expected prevalence level is a latent , i . e . unobserved , variable , and that the observed prevalence level , xv ( t ) , generally deviates from the expected value . We measure prevalence levels fv ( ⋅ ) and xv ( ⋅ ) as fractions and represent the difference between the expected and observed prevalence level in village v by the random variable εv: x v ( t ) = f v ( t , s v , i v , β ) + ε v ( 1 ) Time series models such as discrete time ARMA , ARIMA or ARIMAX models seem to be the most popular methods for predicting prevalence ( or incidence ) ( see e . g . [25 , 26] ) . These models describe the prevalence level at time t as a linear function of the prevalence levels at time t − 1 , t − 2 , … and ( optionally ) some other variables . Their applicability in our context is however limited . Discrete time models require estimates of the prevalence level at each time unit ( e . g . , each month ) , whereas information to estimate the HAT prevalence level is available only at moments at which a screening round is performed . Namely , many HAT patients are not detected by the regular health system , particularly if they are in the first stage of the disease [8] . The class of continuous time models is much more suitable for analyzing data observed at irregularly spaced times . These models assume that the variable of interest , fv ( t , sv , iv , β ) , follows a continuous process , defining its value at each t > 0 . The next subsections propose five continuous time models for predicting HAT prevalence levels . We again note that models describing the causal processes determining the observed prevalence levels in detail ( e . g . , by explicitly modelling disease incidence , passive case finding , death and cure ) may be most intuitive , but require data that are not available on a village level . Therefore , to safeguard their relevance for practical application , the variables we include are only those that are available on a large scale . This does not imply that our models neglect the causal processes . Instead , they are to some extent accounted for in an implicit way by fitting the models to the observed prevalence levels . Data that are typically available at village level are numbers of HAT cases found during screening rounds and the times of these screening rounds . For a given village , the first yields estimates of past prevalence levels , and the latter yield the time intervals between past screening rounds . We hypothesize that the current expected prevalence level at time t is related to past prevalence levels , past screening intervals , and in particular the time since the last screening round , which we denote by δ v - ( t ) = min n { t - S v n | S v n ≤ t } . Hence , we include ( functions of ) these variables in our models . Linear regression models are very widely used in the world of forecasting ( see e . g . [27] ) . Major advantages of these models are that they are easy to understand , to implement , to fit , and to analyze . Therefore , the first model we introduce is a linear model ( model 1 ) , which also serves as a benchmark for our more advanced models . This model describes the expected HAT prevalence in a given village as a function of the time since the last screening and past prevalence levels . Such linear model is , however , very vulnerable to a typical structure present in active case finding datasets . High past prevalence levels tend to increase the priority of screening a village , causing the time intervals between screening rounds to decrease . As a result , δ v - ( t ) is a highly “endogenous” variable . More formally , external variables ( past prevalence levels ) are correlated with both the dependent variable ( fv ( t ) ) and the independent variable ( δ v - ( t ) ) , which makes it hard to quantify the ( causal ) relation between them . In response to this , we present four alternative models . Model 2 is a fixed effects model , which adds a dummy-variable for each village to the initial model . Model 3 is a ( non-linear ) exponential growth and decay model which is inspired by the SIS epidemic model . This model is being used extensively for modeling epidemics that are characterized by an initial phase in which the number of infected individuals grows exponentially , and a second phase in which this number levels off to a time-invariant carrying capacity . We refer to model 3 as the logistic model with a constant carrying capacity . Finally , model 4 is a less data dependent version of model 3 and model 5 is variant of model 3 in which the carrying capacity is allowed to vary over time . As HAT prevalence levels are very low , the variance of these levels is high , which enhances the chance that there are significant outliers among the observations . For example , no cases were detected in three out of four screening rounds performed in a village of 122 people , whereas five cases were detected in the 4th round . This implies two things . First , observed prevalence levels will generally deviate significantly from expected prevalence levels . Second , we need to choose a technique for estimating the model coefficients that is robust with respect to outliers . Instead of Least Squares ( LS ) regression , one of the most commonly applied model fitting methods , we therefore use Least Absolute Deviations ( LAD ) regression to fit the model parameters , which is known to be relatively insensitive to outlying observations [32] . An alternative technique would be to use a maximum likelihood estimation ( MLE ) approach based on a heavy-tailed probability distribution for the observed prevalence levels . In S2 Table , we show the results obtained when assuming a Poisson , Beta-Binomial , or Negative Binomial distribution . Each of the MLE approaches is , however , clearly outperformed by the LAD regression approach . The variance of the observed prevalence level strongly depends on the sample size . For example , under the assumption of an independent infection probability for each person , the variance is inversely proportional to the sample size . We therefore weight the fitting deviation evn = fv ( Svn ) − xv ( Svn ) for observation n for village v by weight w v n = N v · p v n , yielding the following weighted LAD regression problem: min β S a b s ( β ) = ∑ ( v , n ) w v n | e v n | ( 13 ) To deal with the risk of overfitting , we select the variables to be included in the models by means of a backward elimination method . This method initially includes all variables in the model and iteratively removes the least significant variable ( if its p-value > 0 . 10 ) and estimates the model with the remaining variables . The algorithm stops as soon as all remaining variables are significant or if only one variable is left . We enforce that αv and κ cannot be removed by the backward elimination method so as to preserve essential elements of the corresponding models . Hence , only parameters β1-β8 in models 1 and 2 , and parameters β1-β2 in models 3–5 could be removed . Finally , to test the predictive performance of the models , we split the data in an estimation sample ( which we use for fitting the model ) and a prediction sample . Specifically , for each of the 143 villages , we include the last screening round in the prediction sample , and include the others in the estimation sample . Next , we measure performance based on the mean of the prediction errors M E = ∑ v e v n ^ | V | , indicating whether the predictions obtained by the model are biased , and based on two indicators for the amount of explained variation in the prevalence levels: the mean absolute error , M A E = ∑ v | e v n ^ | | V | and the mean relative error , M R E = ∑ v | e v n ^ | ∑ v x v ( S v n ^ ) . Here , the index combination v n ^ indicates the last screening round for village v . The intuition behind the measures of explained variation is that they equal 0 if the predicted prevalence levels are exactly equal to the observed prevalence levels ( i . e . , the model perfectly explains the variation in the observed prevalence levels ) and that their value increases when the absolute difference between predicted and observed levels increases ( i . e . when the model explains less variation in observed prevalence levels ) . We use Matlab R2015b for the implementation of our methods .
Table 1 presents the coefficient estimates for the variables of the five presented models . The results for models 1 and 2 are very similar . Seven of the eight variables are identified as being non-significant by the backward elimination algorithm: the interaction terms , the long term prevalence level , the time since the last screening round , and the square root of the time since the last screening round . The resulting model provides a clear prediction method: the expected prevalence equals 24 . 5% of the prevalence level observed at the previous screening round ( note , if this level was 0 . 0% , the estimated expected prevalence remains 0 . 0% ) according to model 1 , and equals 14 . 7% of this prevalence level plus a constant fraction αv according to model 2 . Hence , this model predicts that , in the absence of screening activities , the expected prevalence remains the same over time . The fitted models 3 , 4 , and 5 reveal a clear and intuitive relationship between screening frequency , prevalence , and carrying capacity: a larger historical prevalence indicates a higher carrying capacity , and facing an equal historical prevalence for a higher historical screening frequency indicates a higher carrying capacity . The constant term has been identified as non-significant for models 3 and 4 and as significant for model 5 . To illustrate the typical output of models 3 and 4 , Fig 2 shows the development of the expected prevalence levels for two villages over time ( the lines ) , as well as the observed prevalence levels ( stars and circles ) . Furthermore , Fig 3 depicts the carrying capacities for the 143 villages in Kwamouth , as estimated by the LMCCC model . Though data to validate these estimates are lacking , we note that they are in the same order of magnitude as prevalence levels found during screening rounds . The latter are usually between 1% and 5% in high or very high transmission areas , and exceed 10% in some extreme cases [33 , 34] . As mentioned in Section Model Fitting , we measure the predictive performance of the different models in terms of the prediction bias and in terms of the amount of variation explained . Table 2 contains the values of the different indicators for each of the models , and Fig 4 and S1 Fig . compare the prediction errors produced by the different models . These prompt several interesting observations . First , the prediction bias ranges from 0 . 47/1000 ( rLMCCC model ) to -1 . 86/1000 ( LM model ) . Given that the average observed prevalence in the 766 screening rounds in our dataset equals 5 . 5/1000 , we consider the biases of the LM model and the LMVCC model as quite substantial . Yet , this may be very well explained by the highly variable character of the HAT epidemic . A small number of outbreaks may substantially shift the average observed prevalence level . For example , without the four most negative prediction errors , the prediction bias for the LM model would be only -0 . 69/1000 . Second , the LM model performs relatively well in terms of explained variation . Yet , we see two vulnerabilities of this model: ( 1 ) as discussed before , this model is likely to be hampered by endogeneity , inducing a potential bias in the coefficient estimates , and ( 2 ) the variation in the screening intervals is relatively small for the villages with the highest endemicity levels in our sample , as these villages are screened almost every year . When there is little variation in δ v - ( t ) , the true effects of variations might not become visible . These two fundamental vulnerabilities may very well explain why ( a function of ) δ v - ( t ) has not been identified as significant for the LM model . As a result , this model unrealistically predicts that the value of the expected prevalence level remains the same over time in the absence of screening activities , contrasting with vast historical evidence . The same vulnerabilities apply to the FEM model , which also provides a counter-intuitive relation between the expected prevalence and δ v - ( t ) . On top of that , its predictive power is relatively low , which could be explained by the fact that , for many villages , there is insufficient data to estimate the fixed effect accurately . As variants of the logistic model already fix the structure of the relationship between δ v - ( t ) and f v ( S v n + δ v - ( t ) ) based on epidemiological insights , these models do not suffer from the vulnerabilities mentioned above . We therefore consider these models to have most potential for accurately predicting HAT prevalence levels in general ( i . e . , in any region and for any time horizon ) . Among the three logistic model variants , model 3 ( LMCCC ) performs reasonably well in terms of both criteria . Model 5 ( LMVCC ) has a substantial prediction bias , but performs best in terms of explained variation , as can be seen in Fig 4 ( its performance is closest to the “perfect fit” ) . Though model 4 ( rLMCCC ) performs best in terms of prediction bias , it performs very weakly in terms of explained variation . Hence , among the logistic model variants , there is no clear winner when both criteria are assigned equal importance . For planning decisions , however , we consider model 5 to be most suitable , followed by model 3 . The reason is that , in contrast with prediction bias , explained variation indicates the ability to identify differences in expected prevalence levels between villages , as required for effective planning decisions . Hence , identifying an effective prioritization of the different villages will be more important than obtaining unbiased estimates of the resulting prevalence levels . The sensitivity level s is known to differ between regions [35] . Furthermore , the population size of a village had to be estimated , which induces a potential bias in the participation level estimates . These issues beg to question the robustness of our results on the logistic model variants ( note , models 1 and 2 are not affected by this as these do not use these parameters ) . S3 Table shows the results of a sensitivity analysis , which largely confirm our findings . In all scenario’s analyzed , model 5 remains best in terms of explained variation , followed by model 3 , and models 3 and 4 outperform model 5 in terms of prediction bias . Another assumption that questions the robustness of our results is the one about the expected prevalence level at the beginning of the time horizon ( i . e . , at 01-01-2004 ) . S4 Table provides the results of a sensitivity analysis on this assumption . Again our main findings remain the same . In the previous section we argue that , among the models analyzed in this paper , variants of the logistic model have most potential for accurately predicting HAT prevalence levels in general . In this section we demonstrate the applicability of one of these model variants to analyze the effectiveness of screening operations . In particular , since information on the development of the carrying capacities is lacking , as required by the LMVCC model , and since we consider the predictive performance of model 3 superior to that of model 4 , we choose to use the LMCCC model as a basis for this analysis . We do note that the theoretical results presented here also hold for model 4 and , if the carrying capacity remains constant , for model 5 also . Our analysis will concentrate on the fixed frequency screening policy . This policy assigns to each village a fixed time interval for consecutive screening rounds based on the village’s characteristics . As the policy is relatively easy to understand and implement , it has been the basis for guideline documents for HAT control . For example , the WHO recommends a screening interval of one year for villages reporting at least one case in the past three years , and an interval of 3 years for villages that did not report a case in the last three years , but did report at least one case during the past five years [1] . In the first part of this section , we mathematically analyze the impact of a fixed screening policy for a given village and investigate the screening frequency required to eradicate HAT in that village . As mentioned in the introduction , we define that HAT is eradicated in the long term if the expected prevalence level goes to zero in the long term . A shorter term objective is to eliminate HAT , where elimination is defined as having at most one new case per 10000 persons per year [1 , 7] . For example , the WHO’s roadmap towards elimination of HAT states the aim to eliminate ( gambiense ) HAT as a public health problem by 2020—which is defined as having less than one new case per 10000 inhabitants in at least 90% of the disease foci [1]—and to reach worldwide elimination by 2030 . The second part of this section presents analytical results about the time needed to reach elimination and about the screening frequency requirements for reaching elimination within a given time frame . As our models consider expected prevalence instead of incidence , we redefine elimination as “reaching an expected prevalence level of one case per 10000” . We argue that the times and efforts required to reach this elimination target are practically suitable lower bounds on the times and efforts needed to reach the WHO’s targets . First , incidence and prevalence levels are argued to be “comparable” for HAT if mobile units visit afflicted areas infrequently [16] . If mobile teams visit the areas more frequently , incidence will only become larger compared to prevalence and the prevalence level target will be easier to achieve than the incidence level target ( e . g . , under the assumption that the fraction of flies infected is proportional to the fraction of humans infected , this follows directly from the epidemic model presented by Rogers [22] ) . Second , even if the expected prevalence level is below the defined threshold level , the intrinsic variability of the HAT epidemic may induce an actual prevalence level that exceeds this threshold . Throughout this section , we consider an imaginary village with a constant carrying capacity K . ( For sake of conciseness we omit the subscript v in this section ) . Furthermore , we assume a constant participation level pvn = p , 0 < p < 1 , and a fixed screening interval τ . The expected prevalence level at the beginning of the time horizon is denoted by f ( 0 ) , f ( 0 ) > 0 . Finally , recall that s , 0 < s < 1 , denotes the sensitivity level .
This paper introduces and analyzes five models for predicting HAT prevalence in a given village based on past observed prevalence levels and past screening activities in that village . Based on the quality of prevalence level predictions in 143 villages in Kwamouth ( DRC ) , and based on the theoretical foundation underlying the models , we conclude that variants of the logistic model—a model inspired by the SIS model—are most practically suitable for predicting HAT prevalence levels . Sensitivity analyses show that this conclusion is very robust with respect to assumptions about participation levels , the sensitivity of the diagnostic test , or the initialization value of the prevalence curves are violated . Second , we demonstrate the applicability of one variant of the logistic model to analyze the effectiveness of the fixed frequency screening policy , which assigns to each village a fixed time interval for consecutive screening rounds . Due to the intrinsic variability of the HAT epidemic , observed prevalence levels will generally deviate significantly from predicted prevalence levels . We strongly believe , however , that this does not render predictions worthless in the context of planning decisions . In contrast , a major contribution of our models is that they indicate the expected disease burden in different villages and can hence be applied to develop planning policies that aim to minimize the total expected disease burden for the villages considered . Our analysis of the fixed frequency screening policy reveals that eradication of HAT is to be expected in the long term when the screening interval is smaller than a given threshold . This threshold strongly depends on the case detection fraction: the fraction of cases who participate in the screening rounds and are detected by the diagnostic tests . Under current conditions , we estimate the threshold to be approximately 15 months . This suggests that annual screening , as recommended by the WHO for endemic areas , will eventually lead to eradication . More specifically , our model predicts that annual screening will lead to eradication if the case detection fraction exceeds 55% . The logistic model also reveals expressions for the time needed to reach the more short term target of eliminating HAT and for the screening interval required to eliminate HAT within a given time frame . These suggest that it takes 10 years to eliminate HAT in a village or focus with a prevalence of 5/1000 ( under current conditions and annual screening ) . Furthermore , we estimate that it is only feasible to reach elimination within five years if the case detection fraction is very high—roughly above 75%—or if the current prevalence level is very low—roughly below 1/1000 . We argue that these figures are practically suitable lower bounds on the time or efforts needed to reach the WHO’s targets for elimination . Our results on requirements for eradication or elimination are based on a deterministic model , which begs to question their validity for reality , where events are stochastic . We note , however , that we model the expected behavior of a stochastic system , and hence that our results also hold in expectation for the stochastic system . On the other hand , we acknowledge that our models are not perfect . For example , we neglect interaction effects between neighboring villages . It would therefore be interesting and relevant to investigate whether our results can be reproduced by a validated simulation model . A necessary condition for the applicability of our prediction models is that data about possible past HAT cases are available . Obviously , they thereby fail to identify endemic villages that have never been visited by a screening team . Different types of models , making use of different types of data—such as vegetation data ( see e . g . [36] ) or data about cases in nearby areas—are needed for these villages . A second limitation of the models is that they have been tested on a set of villages for which the screening interval was relatively short . Consequently , it is hard to establish the behavior of the epidemic if much larger screening intervals are used or if screening operations would be abandoned . Since datasets that do reveal this behavior are lacking , fitting the models to an appropriate dataset obtained by a validated simulation model would be a promising direction for future research . We consider it likely that the speed of convergence to an epidemic equilibrium , as indicated by the parameter κ , differs per disease focus . This may be due to differences in epidemiological conditions , such as the presence of an animal reservoir and the specific tsetse subspecies living in a focus . These differences induce a need for developing and analyzing a cost-effective control strategy that takes differences between foci into account , as also recognized by Simarro et al . [37] . Repeating our analyses for different disease foci to investigate differences in requirements for elimination and eradication would therefore be highly relevant . Our analyses revealed that the effectiveness of screening operations strongly depends on the participation level in the screening activities and the sensitivity of the diagnostic tests . Using screening algorithms with a higher sensitivity or case finding procedures that increase participation levels therefore seems to be very effective . For example , Robays et al . [23] list several combinations of diagnostic tests with different sensitivity levels , and a more acceptable case finding procedure is currently being piloted in the DRC . Using our model to investigate the cost-effectiveness of different control strategies , defining the screening frequencies as well as the screening procedures and diagnostic tests used , would be a promising direction for future research . The results on the fixed frequency screening policy are all concerned with the screening frequency or the time needed to reach certain targets . While at a strategic level , these results might be interesting , at a tactical or operational level , screening frequency decisions are constrained by resource availability . Consequently , policies providing effective , acceptable , and practically suitable recommendations on how to allocate available screening capacity over the villages at risk are of much higher relevance at these levels . Literature about this allocation problem is however absent , as also observed by the WHO [1] , so that future research addressing this topic is much needed . | The primary strategy to fight gambiense human African trypanosomiasis ( HAT ) is to perform extensive population screening operations among endemic villages . Since the progression of the epidemic is largely influenced by the planning of these operations , it is crucial to develop adequate models on this relation and to employ these for the development of effective planning policies . We introduce and test five models that describe the expected development of the HAT prevalence in a given village based on historical information . Next , we demonstrate the applicability of one of these models to evaluate planning policies , presenting mathematical expressions for the relationship between participation in screening rounds , sensitivity of the diagnostic test , endemicity level in the village considered , and the screening frequency required to reach eradication ( zero prevalence ) or elimination ( one case per 10000 ) within a given time-frame . Applying these expressions to the Kwamouth health zone ( DRC ) yields estimates of the maximum screening interval that leads to eradication , the expected time to elimination , and the case detection fraction needed to reach elimination within five years . This paper serves as a basis for further modeling and optimization studies . | [
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] | 2016 | Forecasting Human African Trypanosomiasis Prevalences from Population Screening Data Using Continuous Time Models |
Microbes within polymicrobial infections often display synergistic interactions resulting in enhanced pathogenesis; however , the molecular mechanisms governing these interactions are not well understood . Development of model systems that allow detailed mechanistic studies of polymicrobial synergy is a critical step towards a comprehensive understanding of these infections in vivo . In this study , we used a model polymicrobial infection including the opportunistic pathogen Aggregatibacter actinomycetemcomitans and the commensal Streptococcus gordonii to examine the importance of metabolite cross-feeding for establishing co-culture infections . Our results reveal that co-culture with S . gordonii enhances the pathogenesis of A . actinomycetemcomitans in a murine abscess model of infection . Interestingly , the ability of A . actinomycetemcomitans to utilize L-lactate as an energy source is essential for these co-culture benefits . Surprisingly , inactivation of L-lactate catabolism had no impact on mono-culture growth in vitro and in vivo suggesting that A . actinomycetemcomitans L-lactate catabolism is only critical for establishing co-culture infections . These results demonstrate that metabolite cross-feeding is critical for A . actinomycetemcomitans to persist in a polymicrobial infection with S . gordonii supporting the idea that the metabolic properties of commensal bacteria alter the course of pathogenesis in polymicrobial communities .
The survival of pathogens in the human body has been rigorously studied for well over a century . The ability of bacteria to colonize , persist and thrive in vivo is due to an array of capabilities including the ability to attach to host tissues , produce extracellular virulence factors , and evade the immune system . Invading pathogens must also obtain carbon and energy from an infection site , and specific carbon sources are required for several pathogens to colonize and persist in the host [1] . Although mono-culture infections provide interesting insight into pathogenesis , many bacterial infections are not simply the result of colonization with a single species , but are instead a result of colonization with several [2] , [3] , [4] , [5] . The mammalian oral cavity is an excellent environment to study polymicrobial interactions as it is persistently colonized with diverse commensal bacteria as well as opportunistic pathogens . Our lab has utilized a two-species model system composed of the opportunistic pathogen Aggregatibacter actinomycetemcomitans and the common commensal Streptococcus gordonii to provide mechanistic insight into how specific carbon sources impact disease pathogenesis in polymicrobial infections [6] , [7] . A . actinomycetemcomitans is a Gram-negative facultative anaerobic bacterium that inhabits the human oral cavity and is a proposed causative agent of localized aggressive periodontitis [8] . A . actinomycetemcomitans is found between the gums and tooth surface in the subgingival crevice [9] , [10] , an area restricted for O2 depending on tissue depth [11] and irrigated by a serum exudate called gingival crevicular fluid ( GCF ) . GCF not only contains serum proteins such as complement and immunoglobulin [12] , but also glucose from 10 to 500 µM in healthy patients [13] and as high as 3 mM in patients with periodontal infections [14] . L-lactate is produced by host lactate dehydrogenase in GCF [15] , [16] and resident oral streptococci . Together glucose and L-lactate represent two of the small number of carbon sources that A . actinomycetemcomitans is able to catabolize [17] . A . actinomycetemcomitans has been proposed to primarily inhabit the aerobic [9] “moderate” pockets ( 4 to 6 mm in depth ) of the gingival crevice as opposed to deeper anaerobic subgingival pockets [18] . In addition to A . actinomycetemcomitans , the subgingival crevice is home to a diverse bacterial population , including numerous oral streptococci [19] , that reside in surface-associated biofilm communities [20] . Oral streptococci , aside from Streptococcus mutans , are typically non-pathogenic and depending upon the human subject and method of sampling , comprise approximately 5% [21] to over 60% [22] of the recoverable oral flora . Through fermentation of carbohydrates to L-lactate and sometimes H2O2 , acetate , and CO2 , oral streptococci such as S . gordonii have been shown to influence the composition of oral biofilms [19] , [20] , [23] , [24] . Additionally , S . gordonii-produced H2O2 influences interactions between A . actinomycetemcomitans and the host by inducing production of ApiA , a factor H binding protein that inhibits complement-mediated lysis [7] , [25] . Thus , streptococcal metabolites are important cues that influence the growth and population dynamics of oral biofilms and how oral bacteria interact with the host . A . actinomycetemcomitans preferentially catabolizes L-lactate over high energy carbon sources such as glucose and fructose in multiple strains , despite the fact that this bacterium grows more slowly with L-lactate [6] . Given this preference for a presumably inferior carbon source and the observation that A . actinomycetemcomitans resides in close association with oral streptococci [26] , [27] , we hypothesize an in vivo benefit exists for A . actinomycetemcomitans L-lactate preference . To test this hypothesis , we investigated the importance of A . actinomycetemcomitans L-lactate catabolism during mono-culture and co-culture with S . gordonii in vitro and in a murine abscess model of infection . Our results reveal that co-culture with S . gordonii enhances colonization and pathogenesis of A . actinomycetemcomitans , and the ability to utilize L-lactate as an energy source is essential for these co-culture benefits . Surprisingly , inactivation of L-lactate catabolism had no impact on mono-culture growth in vitro and in vivo suggesting that A . actinomycetemcomitans L-lactate catabolism is only critical for establishing co-culture infections . Taken together , these results provide compelling mechanistic evidence that the metabolic properties of human commensals such as S . gordonii can alter the course of pathogenesis in polymicrobial communities .
Within the gingival crevice , host-produced glucose and L-lactate are present [13] , [14] , [15] , [16] , [28] and likely serve as in vivo carbon sources for A . actinomycetemcomitans . However in contrast to glucose , L-lactate is also produced by the oral microbial flora , primarily oral streptococci [20] . Indeed , the ability of A . actinomycetemcomitans to catabolize streptococcal-produced L-lactate has been demonstrated previously [6] , and it was proposed that A . actinomycetemcomitans consumes streptococcal-produced L-lactate during co-culture . To assess the importance of A . actinomycetemcomitans L-lactate catabolism in polymicrobial communities in vitro , we examined the metabolic profile during catabolism of L-lactate and glucose under aerobic and anaerobic conditions . Aerobically , A . actinomycetemcomitans primarily produced lactate and acetate from glucose ( Fig . 1A ) while acetate was the sole metabolite produced by L-lactate-grown bacteria ( Fig . 1C ) . It was intriguing that lactate was produced , but not consumed , by A . actinomycetemcomitans during aerobic catabolism of glucose . We hypothesized that the lactate produced by A . actinomycetemcomitans was likely D-lactate , which is not catabolized by A . actinomycetemcomitans [29] . Using an enzymatic assay [30] , we were able to verify that >99% of the lactate produced by A . actinomycetemcomitans was indeed D-lactate . Anaerobically from glucose , A . actinomycetemcomitans primarily produced the mixed acid fermentation products formate and acetate along with lactate , succinate , and trace amounts of ethanol ( Fig . 1B ) . Surprisingly , A . actinomycetemcomitans was unable to catabolize L-lactate anaerobically ( Fig . 1C ) , even if the potential alternative electron acceptors nitrate or dimethyl sulfoxide were added , suggesting that L-lactate oxidation was O2 dependent . This is distinct from other oral bacteria including members of the genus Veillonella [24] , [31] , in which L-lactate is an important anaerobic carbon and energy source . If O2 respiration was indeed required for A . actinomycetemcomitans growth with L-lactate , we hypothesized that elimination of the terminal respiratory oxidase , which is required for aerobic respiration , would abolish L-lactate utilization by A . actinomycetemcomitans aerobically . To test this hypothesis , cydB , which encodes a component of the sole putative A . actinomycetemcomitans respiratory oxidase , was insertionally inactivated . The cydB mutant was unable to catabolize L-lactate aerobically supporting the hypothesis that L-lactate oxidation requires O2 respiration ( Fig . 1C ) . Interestingly when grown with glucose aerobically , the cydB mutant doubled much slower ( 6 . 6 hr ) than the wt ( 1 . 9 hr ) and cell suspensions produced a metabolite profile that differed from the wt ( Fig . 1A ) indicating that while not required for aerobic growth on glucose , O2 respiration is the primary means by which glucose is catabolized by wt A . actinomycetemcomitans . As expected , the cydB mutant exhibited identical growth rates anaerobically on glucose ( not shown ) and produced similar metabolites as the wt ( Fig . 1B ) . Collectively , these data indicate that O2 respiration is required for L-lactate oxidation in A . actinomycetemcomitans . As the ultimate goal of this study is to assess the importance of A . actinomycetemcomitans L-lactate catabolism for establishing co-culture with oral streptococci , it was important to assess whether eliminating the ability of A . actinomycetemcomitans to utilize L-lactate affected growth with glucose . To examine this , we examined growth and metabolite production in an A . actinomycetemcomitans strain in which the catabolic L-lactate dehydrogenase LctD , which is present in all strains sequenced to date [32] , [33] , was insertionally inactivated [29] . LctD oxidizes L-lactate to pyruvate and is required for A . actinomycetemcomitans growth with L-lactate as the sole energy source [29] . As expected , the lctD mutant was unable to catabolize L-lactate aerobically or anaerobically ( Fig . 1C ) ; however , metabolite production from glucose was not affected ( Fig . 1A&B ) nor was the growth rate with glucose ( not shown ) . These data indicate that L-lactate catabolism can be eliminated in A . actinomycetemcomitans without affecting growth and metabolite production with glucose . Because A . actinomycetemcomitans preferentially catabolizes L-lactate in lieu of hexose sugars [6] , we hypothesized that L-lactate cross-feeding was important for establishing co-culture with oral streptococci grown on glucose . To test this hypothesis , we examined growth of glucose-grown A . actinomycetemcomitans and S . gordonii during in vitro co-culture aerobically and anaerobically . Aerobically , wt A . actinomycetemcomitans co-culture cell numbers were similar to those observed in mono-culture while the A . actinomycetemcomitans lctD mutant exhibited an approximate 25-fold decrease in cell number during co-culture with S . gordonii ( Fig . 2 ) . Anaerobically , both wt A . actinomycetemcomitans and A . actinomycetemcomitans lctD- cell numbers diminished nearly 10-fold in co-culture compared to mono-culture ( Fig . 2 ) , likely due to the inability to catabolize S . gordonii-produced L-lactate . Examination of aerobic metabolic end products of the A . actinomycetemcomitans lctD-/S . gordonii co-culture revealed high levels of lactate , reminiscent of S . gordonii mono-cultures , indicating that as expected , the A . actinomycetemcomitans lctD mutant is unable to catabolize L-lactate in co-culture ( Fig . 3A ) . Additionally , metabolite concentrations in anaerobic co-cultures were similar to S . gordonii mono-culture ( Fig . 3B ) . It should be noted that these metabolites were measured from growing cells , not cell suspensions as in Fig . 1 . These data provide strong evidence that the inability to use L-lactate , even when glucose is present , significantly inhibits A . actinomycetemcomitans growth and survival in co-culture . Interestingly , an approximate 7-fold increase in S . gordonii cell numbers were observed in the presence of A . actinomycetemcomitans aerobically , indicating that A . actinomycetemcomitans enhances S . gordonii proliferation under these co-culture conditions even when A . actinomycetemcomitans is unable to utilize L-lactate ( Fig . S1 in Text S1 ) . Importantly , the pH of the medium used in these experiments remained at neutrality; thus changes in cell numbers were not due to alterations in pH . The observation that L-lactate catabolism is critical for A . actinomycetemcomitans to establish co-culture with S . gordonii in vitro provides new insight into this model polymicrobial community; however , whether the requirement for this catabolic pathway extended to in vivo co-culture was not known . To examine the role of A . actinomycetemcomitans L-lactate catabolism for in vivo growth in mono- and co-culture , we used a mouse thigh abscess model . This model has relevance as A . actinomycetemcomitans causes abscess infections outside of the oral cavity in close association with other bacteria [34] and has been used as a model system to examine pathogenesis of several oral bacteria [35] , [36] . Using this model , bacterial survival and abscess formation was assessed for wt A . actinomycetemcomitans and A . actinomycetemcomitans lctD- during mono- and co-culture with S . gordonii ( Fig . 4 ) . Unexpectedly , wt A . actinomycetemcomitans and the lctD mutant established similar infections in terms of cell number ( Fig . 4A ) and in abscess weight ( Fig . 4B ) indicating that host-derived L-lactate is not an important in vivo nutrient source during mono-culture infection . Interestingly , wt A . actinomycetemcomitans displayed a 10-fold increase in cell number when co-cultured with S . gordonii , while cell number of the lctD mutant declined >100-fold compared to the wild-type providing evidence that the ability to catabolize L-lactate is crucial for A . actinomycetemcomitans co-culture survival in vivo . These data also indicate that while not critical for mono-culture growth , L-lactate is an important energy source during co-culture infection . Unlike the in vitro experiments ( Fig . S1 in Text S1 ) , S . gordonii numbers were not statistically different in monoculture or in co-culture abscesses ( 2 . 7×107 and 1 . 3×107 CFU/ml respectively; p = 0 . 15 via Mann-Whitney test ) indicating that S . gordonii does not receive a benefit , at least in regard to cell number , from co-culture with A . actinomycetemcomitans . As a control , in vivo growth of the A . actinomycetemcomitans apiA mutant , which is hypersusceptible to killing by innate immunity , was examined . As expected , the apiA mutant exhibited a >250-fold decrease in mono-culture in vivo survival , which was unchanged in the presence of S . gordonii ( Fig . 4A ) .
Microbes within polymicrobial infections often display synergistic interactions that result in enhanced colonization and persistence in the infection site [5] , [34] , [36] , [37] , [38] , [39] , [40] . Such interactions have been particularly noted in oral polymicrobial infections , although the molecular processes controlling these synergistic interactions are not well defined . Detailed mechanistic studies of the interactions required for enhanced persistence in vivo is a critical step towards a more comprehensive understanding of natural polymicrobial infections . In this study , we used a model polymicrobial infection [6] , [7] to determine the importance of metabolic cross-feeding for establishing co-culture infections . Cross-feeding in polymicrobial populations has been reported in numerous studies [24] , [41] , [42] , but its importance for establishing co-culture infections has not been investigated in depth . The methodology used in this study began with detailed studies of the metabolic pathways required for growth with the in vivo carbon sources glucose and L-lactate , followed by examination of the importance of specific catabolic pathways for establishing co-culture infections . It is relevant to discuss the rationale for two in vivo experimental parameters: using a ‘smooth’ strain of A . actinomycetemcomitans in lieu of a ‘rough’ strain; and using a murine abscess model in lieu of a rat periodontal infection model [43] , [44] . A “smooth” strain of A . actinomycetemcomitans , which displays impaired surface attachment , was used in this study [45] , [46] . As we were not investigating attachment or biofilm development , we opted to utilize a smooth strain that had undergone robust metabolic characterization , and feel this decision is justified as this bacterium clearly causes abscess infections in this model ( Fig . 4 ) . The murine abscess model was used for several reasons . First , in addition to periodontal infections , A . actinomycetemcomitans causes abscess infections outside of the oral cavity that resemble , from a gross morphological standpoint , the abscess model infection [34]; thus the abscess model has clinical relevance . Second , the abscess model avoids complications arising from the normal flora , which are not completely eradicated in the periodontal rat infection models , and whose presence would make interpretation of metabolic interactions extraordinarily complex . Third , the abscess model allows direct , controlled inoculation with a finite number of cells that can be quantified throughout the infection by assessing colony forming units after removal of the entire abscess [37] , [47] , [48] . Finally , although the abscess model has primarily been used to study anaerobic pathogens [35] , [36] , it is also relevant for studying aerobic pathogens , demonstrated by the large abscesses [48] formed by the strict aerobe Acinetobacter baumanii [17] , [49] . The presence of aerobic microenvironments in the abscess is also supported by our observations that the S . gordonii spxB mutant is significantly impaired for abscess formation ( Fig . S2 in Text S1 ) . The spxB gene encodes pyruvate oxidase which utilizes O2 for biosynthesis of the virulence factor H2O2 [50]; thus its importance is limited to aerobic infections . The observation that A . actinomycetemcomitans requires O2 to catabolize L-lactate was surprising , as many oral bacteria grow on L-lactate anaerobically [24] , [31] . These results also solve an apparent contradiction in the literature . It was reported by multiple sources [17] , [51] that A . actinomycetemcomitans does not catabolize L-lactate , yet we recently provided evidence that several strains of A . actinomycetemcomitans grow aerobically with L-lactate as the sole energy source [6] , [29] . Interrogation of the previous growth environments revealed that A . actinomycetemcomitans was grown under very low or O2 free conditions; thus it is not surprising that significant growth was not observed in these studies . The O2 dependency of L-lactate oxidation also highlights another facet of our in vivo data . In the murine abscess model , the A . actinomycetemcomitans wt and lctD mutant grew equally well in mono-culture ( Fig 4 ) . However , in co-culture only the survival of the lctD mutant was impaired . This result is reminiscent of our in vitro data ( Fig . 2 ) suggesting that O2 dependent metabolism occurs in our model polymicrobial infection . The observation that the terminal oxidase CydB is required for aerobic growth with L-lactate allows development of a new model for L-lactate consumption in A . actinomycetemcomitans ( Fig . 5 ) . Since L-lactate dehydrogenase ( LctD ) is necessary for lactate oxidation and does not use NAD+ as an electron acceptor [29] , anaerobic fermentation pathways that regenerate NAD+ cannot act as electron acceptors for L-lactate oxidation . The model predicts that A . actinomycetemcomitans instead donates electrons directly to the quinone pool which in turn is re-oxidized by CydAB [52] . It should be noted that this does not rule out an unknown electron carrier between LctD and the membrane associated quinone . The most exciting observation from these studies is that L-lactate catabolism is likely an important factor for A . actinomycetemcomitans to establish a polymicrobial , but not mono-culture , infection in a murine abscess model ( Fig . 4 ) . These data indicate that host-produced L-lactate is not a vital energy source for A . actinomycetemcomitans in mono-culture abscesses , but when S . gordonii is present , L-lactate catabolism becomes critical . We speculate that in the absence of S . gordonii , carbohydrates such as glucose are present in the infection site for A . actinomycetemcomitans growth . When S . gordonii is introduced , competition for these carbohydrates increases , and A . actinomycetemcomitans is likely at a disadvantage due to its relatively slow growth and catabolic rates compared to S . gordonii [6] . Thus , the ability to preferentially utilize L-lactate , the primary metabolite produced by S . gordonii , allows A . actinomycetemcomitans to avoid competition with S . gordonii for carbohydrates and consequently enhance its survival in the abscess . This model ( Fig . 6 ) suggests that the importance of individual carbon catabolic pathways is dependent on the context of the infection , specifically if oral streptococci are present . Our work demonstrates that metabolic pathways required for A . actinomycetemcomitans proliferation during mono-culture infection are distinct from those required for co-culture infection with a common commensal . This study provides strong evidence that simply because elimination of a catabolic pathway does not elicit a virulence defect in mono-species infection does not preclude it from being important in polymicrobial infections . Since metabolic interactions can potentially occur in virtually any polymicrobial infection , our results suggest that in some cases , the ability to cause infection will be as dependent on metabolic interactions as it is on known immune defense mechanisms and classical virulence factors . Our observations also have therapeutic implications , as development of small molecule inhibitors of metabolic pathways , particularly pathways restricted to prokaryotic pathogens , have promise as new therapeutic targets . Based on this study , efforts to develop such therapeutics will require a detailed understanding of how polymicrobial cross-feeding affects colonization and persistence in an infection site .
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by the Institutional Animal Care and Use Committee of Texas Tech University Health Sciences Center ( Protocol Number: 09039 ) . A . actinomycetemcomitans strains VT1169 [53] , Streptococcus gordonii strain Challis DL1 . 1 ( ATCC 49818 ) , S . gordonii spxB- [50] , Escherichia coli DH5α-λpir , and E . coli SM10-λpir were used in this study . A . actinomycetemcomitans and S . gordonii were routinely cultured using Tryptic Soy Broth + 0 . 5% Yeast Extract ( TSBYE ) . For resting cell suspension A . actinomycetemcomitans metabolite analysis , a Chemically Defined Medium ( CDM ) [6] lacking nucleotides , amino acids , pimelate and thioctic acid ( to eliminate further cell growth ) containing either 20 mM glucose or 40 mM L-lactate was used . For co-culture experiments , complete CDM with 3 mM glucose was used . Aerobic culture conditions were 37°C in a 5% CO2 atmosphere shaking at 165 RPM , and anaerobic culture conditions were static growth at 37°C in an anaerobic chamber ( Coy , USA ) with a 5% H2 , 10% CO2 and 85% N2 atmosphere . E . coli strains were grown on Luria-Bertani ( LB ) medium at 37°C . Where applicable , antibiotics were used at the following concentrations: chloramphenicol , 2 µg/ml for A . actinomycetemcomitans and 20 µg/ml for E . coli; spectinomycin , 50 µg/ml for selection and 10 µg/ml for maintenance for A . actinomycetemcomitans and E . coli and 100 µg/ml for selection and maintenance for S . gordonii spxB-; kanamycin , 40 µg/ml for selection and 10 µg/ml for maintenance; naladixic acid , 25 µg/ml; streptomycin , 50 µg/ml for selection and 20 µg/ml for maintenance . For quantifying CFU/ml in co-culture assays , vancomycin ( 5 µg/ml ) was added to agar plates to enumerate A . actinomycetemcomitans and streptomycin ( 100 µg/ml ) was added to agar plates to enumerate S . gordonii . DNA and plasmid isolations were performed using standard methods [54] . Restriction endonucleases and DNA modification enzymes were purchased from New England Biolabs . Chromosomal DNA from A . actinomycetemcomitans was isolated using DNeasy tissue kits ( Qiagen ) , and plasmid isolations were performed using QIAprep spin miniprep kits ( Qiagen ) . DNA fragments were purified using QIAquick mini-elute PCR purification kits ( Qiagen ) , and PCR was performed using the Expand Long Template PCR system ( Roche ) . DNA sequencing was performed by automated sequencing technology using the University of Texas Institute for Cell and Molecular Biology sequencing core facility . Allelic replacement of apiA ( AA2485 ) was carried out by double homologous recombination . For construction of the knockout construct , 856 bp and 842 bp DNA fragments flanking apiA were amplified and combined with the aphA gene ( encoding kanamycin resistance ) from pBBR1-MCS2 [55] by overlap extension PCR [56] . The construct was prepared so that aphA was positioned between the upstream and downstream regions . Primers used were: Kan-5′ ( ATGTCAGCTACTGGGCTATCTG ) and Kan-3′ ( ATTTCGAACCCCAGAGTCCCGC ) for the 1074 bp aphA-containing fragment; ApiA-UF ( CCGATAACAGTAAGATCTTCTAC ) and ApiA-UR ( CAGATAGCCCAGTAGCTGACATCCTTTTCGGCTTGAATTTATACC ) for the upstream apiA fragment; and ApiA-DF ( GCGGGACTCTGGGGTTCGAAATGCGGTCAGAATTTTAGGTGTTTT ) and ApiA-DR ( CGAAACCAACGAACTCTTTATTC ) for the downstream apiA fragment . Underlined sequences indicate overlapping DNA sequences between the apiA fragments and aphA . The overlap extension product was TA-cloned into the pGEM-T Easy vector ( Promega , USA ) and excised by EcoRI digest . The EcoRI fragment containing the overlap extension product was ligated into the unique EcoRI site within the λpir-dependent suicide vector pVT1461 [57] . The cloned construct , pVT1461-apiA-KO , was first transformed into E . coli DH5α-λpir then into E . coli SM10-λpir for conjugation into A . actinomycetemcomitans . Conjugation was performed as described [53] and potential mutants were plated onto TSBYE agar plates containing kanamycin to select for recombinant A . actinomycetemcomitans and nalidixic acid to kill the E . coli donors . Kanamycin resistant , spectinomycin sensitive double recombinants were selected and verified by PCR . Enhanced susceptibility of the apiA mutant to serum was verified as described previously [7] . Insertional mutagenesis of the cydB gene was performed by single homologous recombination using a 543 bp internal piece of the cydB ( AA2840 ) gene amplified using the primers cydB-KO5′ ( GAAGATCTTTATGATTAATACTATCGCGCCG ) and cydB-KO3′ ( GAAGATCTCAAAACCATCTTTGAAAGATAACCA ) . Underlined sequences represent BglII restriction sites . The internal cydB fragment was digested with BglII and ligated into the A . actinomycetemcomitans suicide vector pMRKO-1 ( see below ) to generate pMRKO-cydB . pMRKO-cydB was transformed into E . coli SM10-λpir and conjugated into A . actinomycetemcomitans . A . actinomycetemcomitans recombinants were grown anaerobically on TSBYE agar containing spectinomycin and naladixic acid . Colonies were subcultured anaerobically on liquid medium at the same antibiotic concentrations and insertion into cydB was verified by PCR . The spectinomycin resistance gene from pDMG4 [58] was amplified by PCR using the primers: 5′Spec-cass-NotI ( ATAAGAATGCGGCCGCCGATTTTCGTTCGTGAATACATG ) and 3′ Spec-cass-EcoRI ( CGGAATTCCATATGCAAGGGTTTATTGTTT ) , digested with NotI-EcoRI and ligated into NotI-EcoRI digested pmCherry ( Clontech ) underlined sequences indicate NotI and EcoRI restriction sites . The 3105 bp region containing the pUC origin of replication , plac:mCherry and the spectinomycin resistance gene were PCR amplified using the primers: 5′pMcher-trunc ( GAAGATCTGACCAAGTTTACTCATATATACT ) and 3′ Spec-cass-EcoRI ( CGGAATTCCATATGCAAGGGTTTATTGTTT ) . Underlined sequences indicate BglII and EcoRI restriction sites . This fragment was digested with BglII and EcoRI and ligated into the 2780 bp fragment from BglII-EcoRI digested pVT1461 . The resulting plasmid ( pMRKO-1 , submitted to Genbank ) is a suicide vector for A . actinomycetemcomitans and contains oriT , mob , and tra genes from pVT1461 along with the pUC origin of replication , mCherry expressed from plac , and a spectinomycin resistance cassette . A . actinomycetemcomitans was grown in CDM overnight either aerobically or anaerobically in the presence of 20 mM glucose or 40 mM L-lactate . Bacteria were then subcultured in 30 ml of medium and exponential phase cells ( OD600 = 0 . 4 ) were collected by centrifugation ( 5 , 000 x g for 15 min ) at 25°C . Cell pellets were resuspended in an equal volume of CDM lacking nucleotides , amino acids and any carbon source . Cells were incubated at 37°C aerobically or anaerobically depending on the test conditions for 1 hr . Cells were collected again by centrifugation as described above and resuspended to an OD600 of 2 in 3 ml of CDM without nucleotides , amino acids , pimelate and thioctic acid containing either 20 mM glucose or 40 mM lactate . Cells were incubated for 4 h at 37°C either aerobically or anaerobically . After incubation samples were stored at −20°C for HPLC analysis . D-lactate assays were performed as described [30] with modifications . Glycylglycine buffer was replaced with an equal concentration of Bicine ( Fisher , USA ) buffer and enzymatic assays were monitored by spectrophotometry at 340 nm for 4 hours . A . actinomycetemcomitans and S . gordonii were grown overnight in CDM containing 3 mM glucose . 3 mM glucose was used to ensure that the medium was limited for catabolizable carbon . Cells were diluted 1∶50 in the same medium and allowed to grow to exponential phase ( OD600 of 0 . 2 ) . Cells were then diluted 1∶100 ( 2×106 S . gordonii/ml and 1×107 A . actinomycetemcomitans/ml ) as mono-cultures or co-cultures in 3 ml CDM containing 3 mM glucose . Cultures were allowed to grow for 10 h aerobically or 12 h anaerobically , after which cells were serially diluted , plated on either TSBYE agar + vancomycin for A . actinomycetemcomitans enumeration or TSBYE agar + streptomycin for S . gordonii enumeration . Colonies were counted after incubation at 37°C for 48 h . An aliquot of the culture was also stored at −20°C for HPLC metabolite analysis . Metabolite levels were quantified using a Varian HPLC with a Varian Metacarb 87H 300×6 . 5 mm column at 35°C . Samples were eluted using isocratic conditions with 0 . 025 N H2SO4 elution buffer and a flow rate of 0 . 5 ml/minute . A Varian refractive index ( RI ) detector at 35°C was used for metabolite enumeration by comparison with acetate , ethanol , formate , glucose , L-lactate , D-lactate , pyruvate and succinate standards . Murine abscesses were generated essentially as described previously [37] . Briefly , 6–8 week-old , female , Swiss Webster mice were anesthetized with an intraperitoneal injection of Nembutal ( 50 mg/kg ) . The hair on the left inner thigh of each mouse was shaved , and the skin was disinfected with 70% alcohol . Mice were injected subcutaneously in the inner thigh with 107 CFU A . actinomycetemcomitans , S . gordonii or both . At 6 days post- infection , mice were euthanized and intact abscesses were harvested , weighed and placed into 2 ml of sterile PBS ( or water for pH measurements ) . Tissues were homogenized , serially diluted and plated on Brain Heart Infusion ( BHI ) agar + 20 µg/ml Na2CO3 + vancomycin for A . actinomycetemcomitans enumeration or BHI agar + 20 µg/ml Na2CO3 + streptomycin for S . gordonii enumeration , to determine bacterial CFU/abscess . Experimental protocols involving mice were examined and approved by the Texas Tech University HSC Institutional Animal Care and Use Committee . | Many bacterial infections are not the result of colonization and persistence of a single pathogenic microbe in an infection site but instead the result of colonization by several . Although the importance of polymicrobial interactions and pathogenesis has been noted by many prominent microbiologists including Louis Pasteur , most studies of pathogenic microbes have focused on single organism infections . One of the primary reasons for this oversight is the lack of robust model systems for studying bacterial interactions in an infection site . Here , we use a model co-culture system composed of the opportunistic oral pathogen Aggregatibacter actinomycetemcomitans and the common oral commensal Streptococcus gordonii to assess the impact of polymicrobial growth on pathogenesis . We found that the abilities of A . actinomycetemcomitans to persist and cause disease are enhanced during co-culture with S . gordonii . Remarkably , this enhanced persistence requires A . actinomycetemcomitans catabolism of L-lactate , the primary metabolite produced by S . gordonii . These data demonstrate that during co-culture growth , S . gordonii provides a carbon source for A . actinomycetemcomitans that is necessary for establishing a robust polymicrobial infection . This study also demonstrates that virulence of an opportunistic pathogen is impacted by members of the commensal flora . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"microbial",
"metabolism",
"microbial",
"physiology",
"microbial",
"pathogens",
"biology",
"microbiology",
"host-pathogen",
"interaction",
"bacterial",
"pathogens",
"microbial",
"ecology"
] | 2011 | Metabolite Cross-Feeding Enhances Virulence in a Model Polymicrobial Infection |
Mycobacterium tuberculosis , the causative agent of tuberculosis ( TB ) , infects an estimated two billion people worldwide and is the leading cause of mortality due to infectious disease . The development of new anti-TB therapeutics is required , because of the emergence of multi-drug resistance strains as well as co-infection with other pathogens , especially HIV . Recently , the pharmaceutical company GlaxoSmithKline published the results of a high-throughput screen ( HTS ) of their two million compound library for anti-mycobacterial phenotypes . The screen revealed 776 compounds with significant activity against the M . tuberculosis H37Rv strain , including a subset of 177 prioritized compounds with high potency and low in vitro cytotoxicity . The next major challenge is the identification of the target proteins . Here , we use a computational approach that integrates historical bioassay data , chemical properties and structural comparisons of selected compounds to propose their potential targets in M . tuberculosis . We predicted 139 target - compound links , providing a necessary basis for further studies to characterize the mode of action of these compounds . The results from our analysis , including the predicted structural models , are available to the wider scientific community in the open source mode , to encourage further development of novel TB therapeutics .
One third of the world's population is infected with Mycobacterium tuberculosis ( MTB ) , the causative agent of tuberculosis [1] . Approximately 95% of infected individuals are thought to have persistent , latent MTB infections that remain dormant until activated by specific environmental and host response events . Approximately 10% of latent infections eventually progress to active disease , which , if left untreated , kills more than half of the infected patients [2] . Moreover , there is an increasing clinical occurrence of MTB strains with extensive multi-drug-resistance ( eg , MTB MDR and MTB XDR ) , where mortality rates can approach 100% [3] . In some countries , the MTB MDR and XDR strains may account for up to 22% of infections [1] . In addition , current TB therapeutic regimes involve a combination of antibiotics , administered at regular intervals over a 6-month period , which makes patient compliance an issue , especially in developing countries [1] , [2] . The discovery and development of new antibiotics is widely recognized as one of the major global health emergencies , yet it is also a major pharmaceutical challenge . Most currently used antibiotics were discovered during the golden era from the 1940s to 1960s through large scale screening of compound collections for anti-bacterial activity – the so-called whole cell or phenotypic screens [4] . The emergence of bacterial molecular genomics technologies and the availability of whole genome sequences in the 1990s led to dramatic changes in anti-bacterial drug discovery , where the emphasis was placed on screening essential targets for inhibitory compounds . However , despite intensive efforts , target-based screening has been largely unsuccessful in producing clinical candidate molecules [5] . As a result , a return to whole cell screening has been widely advocated , in combination with novel technologies and bioinformatics to rapid identify targets associated with a compound's mechanism of action ( MOA ) [4] , [6] . Recently , the pharmaceutical company GlaxoSmithKline ( GSK ) completed an anti-mycobacterial phenotypic screening campaign against M . bovis BCG , a non-virulent , vaccine Mycobacterium strain , with a subsequent secondary screening in M . tuberculosis H37Rv ( MTB H37Rv ) for hit confirmation [7] . A total of 776 potent compound hits ( including 177 MTB H37RV hits with limited human cell line toxicity ) were made openly available to the wider scientific community through the ChEMBL database ( http://dx . doi . org/10 . 6019/CHEMBL2095176 ) . The aim of this release was to stimulate mechanism of action analyses using chemical genetics/proteomics approaches , as well as to provide many potential new starting points for synthetic lead generation activities . To attain these goals , it is essential to identify the likely protein targets of these active compounds . Here , we introduce an integrative computational analysis towards the genome-wide characterization of targets for selected compounds against tuberculosis . Our approach is in contrast to the classical target-based experiments , widely used in drug discovery , that suffer from very high attrition rates in anti-infective molecules [8] . This study should also serve the wider anti-tuberculosis research community by providing a list of genes and pathways that are more likely to be validated as TB targets for drug discovery and development . We applied computational approaches using three domains of knowledge , namely the “assay space” , “chemogenomics space” and “structural space” , to identify new targets that are likely to interact with the active compounds from the GSK collection . We characterized the structural and chemical spaces of the recently released set of 776 compounds active against tuberculosis [7] and grouped the compounds into a total of 551 structural families . Subsequently , we predicted their likely targets using three orthogonal and complementary computational approaches . Jointly , we identified several amino-acid biosynthesis proteins as possible targets of several compounds in the dataset . A total of 207 unique pairs of compounds and potential MTB targets have been predicted . These compounds constitute a basis for further hypothesis-led exploration of their mode of action . We briefly outline the possible impact and contribution of our findings to Open Drug Discovery Initiatives [9] , [10] , [11] , in particular against tuberculosis .
GSK recently released the data from a phenotypic screen against tuberculosis ( available at ChEMBL http://dx . doi . org/10 . 6019/CHEMBL2095176 ) [7] . This open access dataset contains a total of 776 compounds active against M . bovis BCG , a non-virulent Mycobacterium species widely used in experimental studies as a vaccine component , and a subset of 177 confirmed compounds active against MTB strain H37Rv . The compound collection had been pre-filtered to remove known anti-bacterial compounds to maximize the discovery of novel compounds with anti-Mycobacterium activities . About 90% of the compounds have a quantitative estimate of drug-likeness ( QED ) value above 0 . 35 [12] , herein called optimal drug-like compounds ( Figure 1 ) . The remaining 10% of compounds , which are highlighted by red bars in Figure 1 , have higher molecular weights ( >400 KD ) and slightly higher hydrophobicity , expressed as the calculated logarithm of the 1-octanol/water partition coefficient ( ALogP ) [13] . For the subset of 177 compounds active against H37Rv , the average molecular weight is statistically smaller than for the entire dataset ( Figure 1 ) , consistent with known trends of lipophilicity and cytotoxicity/polypharmacology . The molecular PSA ( polar surface area ) , ALogP ( octanol–water partition coefficient ) and wQED ( weighted QED ) scores result in statistically indistinguishable average values and distributions for both datasets . To assess the diversity of the dataset , we applied our Random Forest Score ( RFS ) to identify pairs of similar compounds ( Methods ) . An all-against-all comparison was performed by nAnnolyze [14] and any pair of compounds with an RFS higher than 0 . 9 were considered similar . The resulting network of compound similarities was layered using Cytoscape [15] ( Figure 1E ) . The entire dataset of 776 compounds was clustered into a total of 551 compound families , primarily composed of two large compound families and 481 singleton families . The two large families of compounds ( GSKFAM_1 and GSKFAM_2 ) included 38 compounds each connected by 156 and 80 links , respectively ( Figure 1F ) . In summary , the active compound set released by GSK is composed of drug-like molecules with non-redundant and diverse scaffolds . The 776 compounds released by GSK were used as input to our integrative computational analysis approach that combines the results from a chemogenomics space search ( CHEM ) , a structural space search ( STR ) and a historical assay space search ( HIST ) . First , the exploration of the chemical space allowed us to identify likely targets for the input compounds based on their structural similarity to compounds with experimentally validated targets deposited in the ChEMBL database [16] . The approach employed a multi-category Naïve Bayesian classifier , which has been successfully used in ligand-based target prediction efforts [17] , [18] , [19] . Second , the exploration of the structural space allowed for the identification of likely targets based on the structural similarity of compounds and protein targets with known three-dimensional structures . The method was based on an improved version of the AnnoLyze program [14] . Finally , the exploration of the historical data on screening assays resulted in testable hypotheses for the anti-Mycobacterium mode of action of the selected compounds , based on the historical data from internal GSK screening experiments . This integrative approach allowed us to predict targets for the set of released compounds in the absence of known structural data ( CHEM and HIST ) or the absence of knowledge of the binding site ( STR ) . When the three-dimensional structure of the target and the localization of the binding site are known or predicted , it is often helpful to follow up with molecular docking ( see [20] and examples below ) . However , such an approach would be prohibitive for large numbers of compounds against a large number of targets , because molecular docking results still need to be interpreted manually for best impact . The three methods used in our integrative approach are further detailed in the Methods section of this manuscript . We applied a multi-category Naïve Bayesian classifier ( MCNBC ) that was built and trained using structural and bioactivity information from the ChEMBL database [16] . Given a new compound , the model calculates a likelihood score based on the molecule's individual sub-structural/fingerprint features and produces a ranked list of likely targets . In total , the 776 compounds in the M . bovis BCG dataset resulted in 2 , 179 statistically significant target associations ( at a Z-score >2 . 0 ) to proteins in the ChEMBL database from 62 different organisms ( 63% of hits are to human proteins ) . A simple orthology search against the MTB proteins from this set resulted in 1 , 401 compound-target relationships for 84 MTB proteins , with detectable orthology to 34 organisms . The specific predictions from the chemical space search are available at http://www . tropicaldisease . org/TCAMSTB ( CHEM type ) . We applied a Random Forest Score that identified structural similarities between any compound in the dataset and ligands from the Protein Data Bank ( PDB ) [14] . Each compound in the M . bovis BCG dataset is compared to ∼2 , 500 ligands for which there are known complex structures in the PDB , identifying structural similarities to be included in a pre-built network of structural relationships between ligands and targets . In total , the 776 compounds resulted in 207 significant target associations ( RFS score >0 . 4 ) to proteins in a set of modeled three-dimensional structures from the MTB proteome . The specific predictions from the structural space search are available at http://www . tropicaldisease . org/TCAMSTB ( STR type ) . We used the historical GSK bioassay data to develop hypotheses for the anti-Mycobacterium mode of action for the active compounds . Using conservative activity thresholds , we found among the compounds active against MTB H37Rv unambiguous annotations for 49 compounds and their previously measured activity in 120 biochemical assays against 63 human targets ( i . e . , sub-micromolar IC50 or EC50 ) . Overall , the M . bovis BCG screens resulted in a considerably larger number of active compounds and thus have a correspondingly greater amount of historical assay information . A total of 240 compounds were found to have activity recorded in 642 assays involving 209 human targets , with the largest human target classes being GPCRs and protein kinases , as expected . We then searched for orthologous sequences of the human assayed proteins in the MTB H37Rv and M . bovis BCG genomes using conservative criteria for assigning human-Mycobacterium homology ( BLAST E-value ≤1 . 0e−10 ) . Although there are significant evolutionary differences between bacterial and mammalian genomes , we still found 19 M . bovis BCG homologous genes ( Table S1 ) in different target classes ( Figure S1 ) , including kinases ( 8 genes ) , cytochrome P450s ( 2 genes ) and nine other enzymes such as a putative D-amino acid oxidase , an amidase , a putative flavin-containing monoamine oxidase , a NAD-dependent deacetylase , a putative catechol-O-methyltransferase , a protease , a putative epoxide hydrolase , a 3-ketoacyl- ( acyl-carrier-protein ) reductase , and a dihydroorotate dehydrogenase 2 . While these M . bovis BCG genes had orthologous sequences in MTB H37Rv , fewer compounds were associated with putative targets in the latter species . For example , two Mycobacterium kinases and five enzymes were exclusively associated with M . bovis BCG positive compounds . Two kinases ( pknA and pknB ) and one enzyme ( fabG ) were experimentally characterized as essential for the survival of MTB [21] , [22] . A total of 20 and 94 compounds were indirectly mapped by human protein target homology to 12 MTB H37Rv and 19 M . bovis BCG genes , respectively . The specific predictions from the historical assay space search are detailed in Supporting Information and are available at http://www . tropicaldisease . org/TCAMSTB ( HIST type ) . Of the 776 compounds in the GSK dataset , only one compound ( GSK445886A ) was predicted to hit diverse targets from different pathways by the three independent methods ( Figure 2A ) . A total of 25 and 9 compounds were jointly predicted to hit a target by CHEM/STR and CHEM/HIST searches , respectively . The majority of predictions were obtained by the CHEM approach ( 404 compounds with predicted targets ) , followed by the STR approach ( 38 compounds with a predicted target ) and the HIST approach ( 20 compounds with predicted targets ) . Such results were expected because the available information on biological activity shrinks as we move from the general “chemical” to the more specific “structural” and “historical” spaces . Interestingly , as an indication of the orthogonality of the three approaches , most of the redundancy of compounds with a predicted target was specific to each approach . In other words , each of the three approaches covered different parts of the space of compound-target predictions . For example , the CHEM approach predicted a target for 300 compound families ( compared to a total of 404 unique compounds ) , of which it still shared 34 with either the STR or the HIST approaches ( Figure 1B ) . A similar trend was observed for the other two approaches , indicating that the common compounds mostly occurred in small compound families or even singletons . Indeed , the GSK445886A compound , which was predicted to have a target by all three approaches , corresponded to a singleton compound family ( GSKFAM_293 ) . To identify whether the three different approaches predicted targets for specific families in the dataset , we calculated the log odds probability ( LogOdd ) of a given compound family to appear in the list of selected compounds , given their different distributions in the original dataset ( Figure 2C ) . This analysis aimed at identifying possible biases or artifacts specific to each of the three independent methods used in our integrative approach . Eleven compound families were under-represented in the selected dataset and 18 families were over-represented ( with LogOdd values smaller than −0 . 5 and greater than 0 . 5 , respectively ) . Interestingly , GSKFAM_551 , which is a singleton with the SKF-67461 compound , was over-represented in the subset of selected compounds . Such predictions were based mostly on the STR and CHEM searches and may correspond to the chemical properties of the compound , resulting in a high false-positive rate for those two approaches . Conversely , the GSKFAM_4 , which contains 15 compounds , is under-represented in the final subset of selected compounds , with only 1 hit identified by the CHEM approach . There are a total of 1 , 044 unique MTB targets associated with a total of 112 pathways annotated in the KEGG database [23] ( the mtu identifiers below refer to the relevant KEGG pathway id ) . Of those , the three orthogonal approaches identified targets for the selected set of compounds in a total of 84 pathways ( Figure 3A ) . The STR search resulted in hits to 71 unique pathways , while the CHEM and the HIST searches resulted in hits to 35 and 16 pathways , respectively . These results were expected , because the target information is reduced from the STR space to the HIST space . A total of 11 unique pathways were predicted by the three approaches ( Figure 3A and Table 1 ) ; these include many pathways associated with amino acid and nucleotide metabolism , such as arginine and proline metabolism ( mtu00330 ) , tryptophan metabolism ( mtu00380 ) , phenylalanine metabolism ( mtu00360 ) , tyrosine metabolism ( mtu00350 ) , histidine metabolism ( mtu00340 ) , glycine/serine/threonine metabolism ( mtu00260 ) and pyrimidine metabolism ( mtu00240 ) . The results indicate that the GSK compounds potentially target proteins associated with primary metabolism . Interestingly , another seven pathways , not identified by the HIST approach , were found over-represented in the final set of predicted targets ( Figure 3B ) . Those include some further primary and secondary metabolism systems , including streptomycin biosynthesis ( mtu00521 ) , folate biosynthesis ( mtu00790 ) , nitrogen metabolism ( mtu00910 ) , aminoacyl-tRNA biosynthesis ( mtu00970 ) , purine metabolism ( mtu00230 ) , penicillin and cephalosporin biosynthesis ( mtu00311 ) , D-arginine and D-ornithine metabolism ( mtu00472 ) , and one carbon pool by folate ( mtu00670 ) . To assess the significance of our predictions using the three different approaches , we calculated a t-statistics p-value of any compound family - KEGG pathway pair ( Methods ) . The search identified 8 different compound families with significant links ( p-value <1×10−5 ) to 14 different KEGG pathways ( Table 2 ) . The GSK compound family 1 , through its compounds GSK975784A , GSK975810A , GSK975839A , GSK975840A and GSK975842A , was predicted to target the glycerolipid ( mtu00561 ) and glycerophospholipid metabolisms ( mtu00564 ) , with significant over-representation through 6 different targets including Rv2182c and Rv2483c , both acyltransferases essential for the survival of the bacteria [21] . The GSK compound family 3 was predicted to target the ABC transporters ( mtu02010 ) through its compounds GSK547481A , GSK547490A , GSK547491A , GSK547499A , GSK547500A , GSK547511A , GSK547512A , GSK547527A , GSK547528A and GSK547543A . Similarly , it was also predicted to target the aminoacyl-tRNA biosynthesis ( mtu00970 ) pathways , through 3 different targets including Rv1640c , a lysyl-tRNA synthetase essential for the survival of the bacteria [21] . The GSK compound family 7 , was predicted to target several pathways through 2 different targets Rv0053 ( 30S ribosomal protein S6 ) and Rv0650 ( a glucokinase ) , none considered essential for the survival of the bacteria [21] . The GSK compound family 9 through its compounds GSK1188379A and GSK1188380A , was predicted to target the ABC transporters ( mtu02010 ) pathway through the Rv0194 target ( ATP-binding cassette , subfamily C ) considered non-essential for the survival of the bacteria [21] . Identical results were obtained with the GSK compound family 16 through its compounds GSK1825940A and GSK1825944A . The GSK compound family 35 through its compounds BRL-10143SA and BRL-51093AA was predicted to target the one carbon pool by folate ( mtu00670 ) pathway through the Rv2763c and Rv2764c targets ( a dihydrofolate reductase and a thymidylate synthase , respectively ) considered non-essential for the survival of the bacteria [21] . The GSK compound family 173 through its compound GSK14022909A was predicted to target the aminoacyl-tRNA biosynthesis ( mtu00970 ) pathway through three essential targets [21] , Rv1640c , Rv3598c and Rv3834c ( a lysyl-tRNA synthetase , a lysyl-tRNA ligase , and a seryl-tRNA ligase , respectively ) , which are essential for the survival of the organism [21] . Interestingly , this family is also predicted to target Rv3105c and Rv3135 genes ( a peptide chain release factor 2 and a PPE family protein ) , which are also essential for the survival of the organism [21] . Finally , the GSK compound family 334 through compound GSK270671A was predicted to target the nitrogen metabolism ( mtu00910 ) pathway through the Rv1284 and Rv3588 targets ( carbonic anhydrases ) considered essential for the survival of the bacteria [21] . Even though target Rv0014c , a serine/threonine-protein kinase , was not identified as belonging to an enriched pathway ( it is not annotated in the KEGG database ) , it was predicted by the HIST approach to be a target for the GSK1365028A , GSK1598164A , GSK275628A and GW664700A ( all singleton families in our compound clustering ) . Kinases are the most prominent human target class having identifiable orthologs in both M . tuberculosis H37Rv and M . bovis BCG genomes ( Figure 4A ) . The human genome encodes over 450 kinases , while Mycobacterium contains between 4 and 24 serine/threonine kinases , depending on the exact species ( M . tuberculosis and M . bovis have 11 conserved kinases each ) . At least two of these kinases , pknA and pknB , have been determined to be essential for in vitro viability of M . tuberculosis [21] . To further evaluate potential MoA of kinase inhibitors , we computationally docked several compounds into the adenine-binding portion of the ATP binding pockets of the two available experimental structures for the essential kinase pknB . The criteria for choosing the compounds were whole cell screening activity of MIC90 less than 10 µM and IC50 less than 8 µM . Two structures ( PDB IDs: 2PZI and 3F69 ) were selected because both were co-crystallized with an inhibitor , clearly detailing their ATP binding pockets . An empirical docking score threshold of −8 . 5 kJ/mol was chosen to identify putative positive bindings of the active compounds across the two pknB PDB models ( Table S2 ) . GSK1598164A , an inhibitor of several human serine/threonine protein kinases , was positive in both H37RV and BCG whole cell screens , based on favorable docking scores ( −9 . 19 and −8 . 96 kJ/mol against 2PZI and 3F69 , respectively ) . Both GSK1598164A and the enzymatic product ADP in the crystal structure were found to interact with the Glu93 of pknB , where the nitrogen atoms on the ‘head’ unit form the hydrogen bond with Glu93 ( Figure 4B ) . Glu93 is conserved across both human and TB kinases ( Figure 4A ) . Several residues in the putative hydrophobic binding pocket ( Leu17 , Gly18 , Phe19 , Val25 , Ala38 , Val72 , Met92 , Glu93 and Val95 ) were also found to be within 4 Å of both GSK1598164A and ADP . In conclusion , our analysis suggests that several bactericidal compounds in the published phenotypic screen act by inhibiting essential M . tuberculosis kinases . The CHEM and STR methods identified Rv3598c ( lysS1 lysine-tRNA ligase 1 ) and Rv3834c ( serS serine-tRNA ligase ) as possible targets for the GSK1402290A compound , respectively . Both enzymes are part of the aminoacyl-tRNA biosynthesis pathway ( mtu00970 ) and are essential in in vitro experiments [21] . Moreover , the mtu00970 pathway was selected in our analysis as being significantly associated with GSKFAM_173 ( GSK1402290A compound ) . The CHEM approach predicted that the human lysyl-tRNA synthetase ( UniProt ID Q15046 ) was a likely target of GSK1402290A , with a likelihood score of 11 . 3 and a Z-score of 2 . 4 . Furthermore , the model indicated that the individual fragments contributing to this prediction were derived by its fused triazole ring ( e . g . , pyrazole and imidazole features ) , as well as by its aniline group . In fact , the model for this target was trained using 47 active compounds from ChEMBL and almost all of them contained the aforementioned fragments ( Figure 5A ) . Moreover , the predicted human target shared in OrthoMCL [24] the ortholog group ( OG5_126972 ) with MTB's lysine-tRNA ligase 1 ( UniProt ID P67607 ) . The STR method predicted a link between the compound and the target through a 3D model of the Rv3834c protein built based on the known structure of a seryl-tRNA synthetase from Aquifex aeolicus . The Rv3834c target and the seryl-tRNA synthetase template aligned with 43% sequence identity and resulted in good quality models ( MPQS>1 . 5 ) [25] . To further evaluate potential MoA of the GSK1402290A compound , we computationally docked it into the nAnnoLyze predicted binding site for Rv3834c ( Figure 5 ) . The AutoDock run resulted in a best pose with −8 , 4 kJ/mol , indicating interactions between the GSK1402290A compound and the Rv3834c target ( Figure 5B ) . In support of this model , the interactions occur with conserved protein residues , given the curated multiple sequence alignment for PFAM family PF00587 ( tRNA synthetase class II core domain ) . In summary , our CHEM and STR predictions suggest that GSK1402290A could act as an inhibitor of the aminoacyl-tRNA biosynthesis pathway and provide the basis for further chemical optimization of this compound . The recent publication of a large-scale screening effort for identifying drug-like small molecule compounds active against tuberculosis has been used as starting point for our research . Here , we predicted the likely mode of action of a selected set of compounds active against tuberculosis , based on a computational approach that integrates data from historical assay results , chemical features and their relationship to activity , and structural comparisons . Our integrated approach resulted in prediction of several compound-target pairs , which can be further tested using genomics , genetics and biochemical assays . More broadly , our approach can be applied to whole cell screens for any pathogen , provided sufficient datasets are available . We have predicted a wide range of MTB specific as well as more evolutionary conserved targets . While compounds with known activity against a human protein could be compromised by toxicity , and therefore should be eliminated from further study , empirical evidence suggests that existence of a human orthologous sequences is not a strong filter for selecting pathogen targets . Many clinically used antibiotics have targets with human orthologs , such quinolones ( DNA gyrase and topoisomerases ) , rifampicin ( RNA polymerase ) , mupirocin ( isoleucyl-tRNA synthetase ) and the latest anti-TB drug now in Phase II testing , bedaquiline ( F1F0 ATPase ) [4] , [6] . The associated side effects of antibiotics are mostly due to high doses treatments affecting off-target proteins ( including human ortologs ) and not specifically to on-target effects . The billion plus years of evolutionary distance between prokaryotes and mammals has lead to significant divergence between orthologous proteins such that there is sufficient structure activity relationship or SAR bandwidth to develop specific inhibitors of the pathogen target , in our case MTB . It is important to note that we also had a subset of compounds with historical data indicating activity against human protein targets with no known homologs in MTB , such as the GPCRs . Thus , their mechanism of action against MTB must be due to non-human target related interactions . These compounds must be pursued with caution as drug candidates given their known in vitro interaction with a human protein . Nevertheless , such compounds could be valuable tools for understanding MTB viability . In general , knowledge of potential human protein interactions adds to the design of effective counter-screens to drive compound SAR specificity and potency towards the pathogen . The public availability of the data and compounds [7] as well as our predictions ( http://www . tropicaldisaes . org/TCAMSTB/ or ftp://ftp . ebi . ac . uk/pub/databases/chembl/tb ) will facilitate further research on drug discovery against tuberculosis . A major goal of our work is to encourage other researchers to experimentally validate the described targets and make their findings publicly available as soon as possible , thus optimizing the process of developing a safe and well tolerated novel therapy for tuberculosis .
All compound datasets used in this study ( that is , BCG dataset of 776 GSK compounds including the H37Rv sub-dataset of 177 compounds ) were obtained directly from the ChEMBL database ( as deposition set http://dx . doi . org/10 . 6019/CHEMBL2095176 ) . Chemical properties of the compounds ( Figure 1 ) were calculated as previously described [12] . A multi-category Naïve Bayesian classifier ( MCNBC ) was built using structural and bioactivity information from the ChEMBL database ( version 14 ) [16] . In brief , the classifier learns the various classes ( in this case protein targets ) by considering the frequency of occurrence of certain sub-structural features for the different chemical compounds . Given a new , unseen compound , the model calculates a Bayesian probability score based on the molecule's individual features and produces a ranked list of likely targets . The model was built in Accelrys Pipeline Pilot ( version 8 . 5 ) . The structure and bioactivity data were extracted from the ChEMBL database and conformed the following filters: ( i ) the activity value was better than 10 uM ( pIC50>5 ) , ( ii ) the target type was a protein , ( iii ) the activity type was IC50 , Ki or EC50 , and ( iv ) the target confidence score was above 7 . 0 . The last filter ensured that there was a reported direct interaction between the ligand and the protein target . The script resulted in 489 , 056 distinct compound-target pairs . To increase the robustness of the model , only targets with 40 or more active compounds were considered further , thus reducing the number of unique compound-target pairs to 466 , 686 , spanning 1 , 258 distinct targets and 271 , 918 distinct compounds . Two multiple-category models were subsequently built . Firstly , a model was created by choosing at random 85% of the compound records as the training set , so that the remaining 15% could be used as a test set for model validation , ensuring no overlapping structures in the 85-15 partition [17] . The MCNBC trained on 85% of the 271 , 918 ChEMBL compounds and associated targets was then used to predict the targets for the remaining 15% of the ChEMBL subset , containing 40 , 788 distinct compounds , unseen by the model . Standard ECFP_6 fingerprints were employed as molecular descriptors for the classifier [26] . These fingerprints encode a molecular structure as a series of overlapping features/fragments of a diameter of up to three bond lengths . For each compound in the test set , the Pipeline Pilot model generated a likelihood score Ptotal for all possible targets . This is derived by the Laplacian-corrected Bayes rule of conditional probability P ( A|Fi ) for each fingerprint feature i of the compound . where Fi is the ith fingerprint feature; A is the number of active molecules for a target; T is the total number of molecules; AFi is the number of active molecules containing feature i; and TFi is the number of all molecules containing feature i . For the purposes of this validation , only the top five target predictions were considered ( i . e . , the ones with the highest positive likelihood score ) . This reflects a real-life situation where only a small number of target predictions can be practically and economically tested experimentally . To test the accuracy of the method , the five target predictions were then compared to the actual target reported for that particular compound . The model derived by the training set ranked the correct target highest among all 1 , 258 possible targets for 82% of the compounds in the test set ( Figure 6A ) . The target is correctly predicted on the second guess for 6% of the compounds and correctly predicted on the third guess for 2% of the compounds . In total , 92% of the compounds in the test set are correctly assigned to their known targets within the top five predicted targets . The ChEMBL database groups most of the individual protein targets into a hierarchical classification of target family names . Given this information , further analysis was done to examine the accuracy of the target classification predictions . Individual targets were replaced by their respective protein classification annotation using a lookup dictionary . In total , 568 unique protein classification labels were considered . The model's predictive power improves , returning the correct protein family as the top ranked prediction in 88% of the compounds and within the top five predictions in 94% of the compounds ( Figure 6A ) . After the successful validation of the method , a second model was created utilizing 100% of the data and keeping the rest of the parameters intact . The derived model was then used for predicting the targets of all GSK compounds . A network of structural similarities between compounds and targets was built to identify the most likely target of a given compounds in our GSK dataset . To explore the structural space we used an improved version of our previously published AnnoLyze algorithm [14] , which was based on homology detection through structural superimposition of targets and their interaction networks to small compounds similarly to previously published approaches [27] , [28] . Briefly , the new nAnnoLyze algorithm relies in four pre-built layers of interconnected networks , First , the “GSK Ligand” network where nodes are GSK compounds and edges correspond to their similarity as measured by a Random Forest classifier score ( RFS ) ( see below ) . Second , the “PDB Ligand” network where nodes are ligands in the Protein Data Bank ( PDB ) [29] and edges correspond to their similarity also measured by the RFS . The “GSK Ligand” network is linked to the “PDB ligand” network by edges corresponding to the compound similarity measure by the RFS . Third , the “PDB Protein” network where nodes are proteins in PDB and edges corresponds to their structural similarity as measured with the MAMMOTH structural superimposition [30] . Fourth , the “MTB Models” network where nodes are structure models of MTB targets and edges corresponds to their structural similarity after superimposition by the MAMMOTH program . The two central networks ( that is , “PDB Ligand” and “PDB Protein” networks ) are connected by co-appearance in any solved structure in the PDB and the “PDB Protein” and the “MTB Models” networks are also linked by the structural comparison between any protein in the PDB and all models from MTB . Finally , once all the networks are constructed , we identified the closest path between any GSK compounds and a MTB target and scored their relationship as the sum of all similarities scores in the network . Such score was then normalized between 0 ( non-similar ) and 1 ( similar ) and only pairs of GSK compounds and their MTB targets with scores higher than 0 . 4 were kept . To identify whether two compounds could be considered similar , we developed a new Random Forest classifier ( RFS ) , which was trained with a dataset of “similar” and “non-similar” ligands . Two ligands were similar if they bind the same binding site as defined by the LigASite database , a gold-standard dataset of biologically relevant binding sites in protein structures [31] . To avoid overestimation in the validation of our approach , all ligands in the database that were included in a testing set of 2 , 380 ligands from the PDB were removed . Our training set of similar ligands included 197 pairwise comparisons considered as “true similar” and a set of randomly paired ligands as “true non-similar” comparisons . The SMSD program [32] was then used to compare all pair of selected ligands to obtain their Tanimoto score , bond breaking energy , Euclidian distance for equivalent atoms , stereochemical match , substructure fragment size , and finally the molecular weight difference . Such scores were then normalized and constituted a vector defining the similarity between any two compared ligands , which was then used as input for the Random Forest classifier . The aim of the classifier was thus to identify hidden relationships between the six scores to maximize its capacity to identify true pairs of similar ligands and discern them from non-similar ligands . The classifier was then tested with a 10-fold cross validation procedure and resulted in an area under the ROC curve of 0 . 97 and a very small false positive rate of 1 . 6% ( Figure 6B ) . To populate the “MTB Model” network with structures of MTB targets , we built all possible comparative structure models for any protein in the M . tuberculosis H37Rv , M . bovis BCG , and M . smegmatis genomes using the ModPipe program [25] . All sequences were obtained from the Genomes Web site of the NCBI database . Such modeling resulted in a total of 34 , 894 comparative models for which 5 , 008 were predicted to be reliable models ( that is , 1 . 1 or higher ModPipe quality score and ga341 higher than 0 . 7 ) . Next , we structurally compared this set of selected models to any non-redundant ( 90% sequence identity ) structure in the PDB that contained at least one known ligand . Structural comparisons between two proteins were performed using the MAMMOTH algorithm [30] . Four different scores were stored for each structural superimposition: percentage of sequence and structure identity for the entire protein and percentage of sequence and structure identity for the residues involved in the binding site defined as any residue in the PDB template structure within 6 Ångstroms of any atom in the ligand . A binding site in a model was considered then similar to a binding site in a known PDB structure if at least the binding site sequence and structure similarity were higher than 40% . This similarity cut-off was previously validated in a large-scale comparison of known ligand-protein pairs [14] . The final entire network of comparisons included the 776 compounds from the GSK dataset , ∼2 . 500 unique ligands from the PDB , ∼16 , 000 unique protein structures from the PDB and a total of ∼5 , 000 structure models from MTB . Such network resulted in 207 pairs of GSK compound to MTB target short paths ( i . e . , score >0 . 4 ) . GSK proprietary compound screening databases were queried for any historical assay data associated with both Mycobacterium species active compounds . The majority of these screens were against human protein targets . The threshold above which compound efficacy against specific human targets was considered significant was defined as pIC50≥5 . 0 for inhibition or antagonist assays , and pEC50≥5 . 0 for agonist , activation or modulator assays . Activities at more than 600 target-result type combinations ( some targets are assayed in both an antagonist and agonist mode ) were analyzed amongst the BCG and H37Rv active compounds , representing potential modes of action . The target activities for the screened compounds were analyzed to identify targets over-represented amongst the anti-malarial actives vs . inactives . Using BLASTP [33] we queried the protein complement of published MTB H37Rv and M . bovis BCG genomes with RefSeq proteins [34] for all human targets accepting a homology cut-off of an E-value ≤1 . 0e-10 and visual inspection of the alignments . Putative homologous relationships were confirmed by reciprocal BLASTP searches of identified Mycobacterium homologues against the human RefSeq protein databases . Initial multiple sequence alignments were performed using the program CLUSTALW v1 . 8 [35] with default settings and subsequently refined manually using the program SEQLAB of the GCG Wisconsin Package v11 . 0 software package ( Accelrys , San Diego , CA , USA ) . We measured two different statistics to assess the significance of a particular link between a chemical compound and a target pathway . Firstly , we calculated the LogOdds ( that is , the odds of an observation given its probability ) . A feature i ( in our case , a compound in Figure 2C or a pathway in Figure 3B ) has a probability ( pi , c ) in the entire dataset and a probability ( pi , r ) of being at the subset of selected compounds/pathways . Their LogOdds are defined as the logarithm of its Odds ( Oi ) :Therefore , Odds higher than 1 ( or positive LogOdds ) indicate over-occurrence of the compound/pathway in the selected subset . Odds smaller than 1 ( or negative LogOdds ) indicate under-representation of the compound/pathway in the selected subset . Secondly , a p-value score was calculated for each predicted link between a compound and a target pathway using a Fisher's exact test for 2×2 contingency tables comparing two groups of annotations ( i . e . , the group of compounds in a given pathway and the group of compounds in the entire dataset ) [36] . Autodock 4 . 2 was used for docking studies [37] . The ga_num_evals were set at 250 , 000 to balance docking performance and CPU consumption . Thirty replicates were run for each chemical-protein pair and the binding conformation with the lowest docking score was chosen for visualization using PyMOL . | Mycobacterium tuberculosis is a major worldwide pathogen infecting millions individuals every year . Additionally , the number of antibiotic resistant strains has dramatically increased over the last decades . Trying to address this challenge , the pharmaceutical company GlaxoSmithKline has recently published the results of a large-scale high-throughput screen ( HTS ) that resulted in the release of 776 chemical compound structures active against tuberculosis . We have used this dataset of compounds as input to our computational approach that integrates historical bioassay data , chemical properties and structural comparisons . We propose 139 targets alongside their respective hit compounds and made them open to the wider scientific community . Our hope is that the availability of the experimental data from GSK and our computational analysis will encourage further research providing validated therapeutically targets against this devastating disease . | [
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] | [] | 2013 | Target Prediction for an Open Access Set of Compounds Active against Mycobacterium tuberculosis |
RNA decay and maturation have in recent years been recognised as major regulatory mechanisms in bacteria . In contrast to Escherichia coli , the Firmicute ( Gram-positive ) bacteria often do not encode the well-studied endonuclease RNase E , but instead rely on the endonucleases RNase Y , RNase J1 and RNase J2 , of which the latter two have additionally been shown to have 5′ to 3′ exonucleolytic activity . We have previously demonstrated that these RNases could be deleted individually in the pathogenic Firmicute Staphylococcus aureus; however , we here present that , outside a narrow permissive window of growth conditions , deleting one or both of the RNase J genes presents serious difficulties for the cell . Moreover , an active site mutant of RNase J1 behaved like a deletion , whereas no phenotypes were detected for the RNase J2 active site mutant . Furthermore , in order to study the in vivo enzymatic activity of RNase J1 and J2 , a method was developed to map the exact 5′-ends of mature and processed RNA , on a global scale . An enrichment of 5′ RNA ends could be seen in the RNase J mutants , suggesting that their exonucleolytic activity is crucial for normal degradation of bulk RNA . Using the data to examine specific RNAs , we demonstrated that RNase J activity is needed for correct 5′ maturation of both the 16S rRNA and the RNase P ribozyme , and can also inactivate the latter , possibly as quality control . Additional examples show that RNase J perform initial cleavages , apparently competing with ribosomes for access to mRNAs . The novel 5′ mapping assay offers an exceptionally detailed view of RNase activity , and reveals that the roles of RNase J proteins are diverse , ranging from maturation and post-transcriptional regulation to degradation .
RNA decay is an important regulatory process in bacteria and is thought to be a major factor in post-transcriptional control [1] . Some bacterial mRNAs have halflives of only seconds , most mRNAs have halflives of minutes , and a few especially stable RNAs can last for hours [2] , however the signals that distinguish a short-lived from a long-lived RNA are only poorly understood . The standard RNA decay paradigm , based on the model organism Escherichia coli , describes an initial endonucleolytic cut made by RNase E and regulated by largely unknown mechanism ( s ) . Then 3′ to 5′ exonucleolytic degradation follows , carried out by polynucleotide phosphorylase ( PNPase ) , which is normally inhibited by hairpin structures at the 3′-end of the RNA [3]–[5] . However , this model can rarely be applied to bacteria outside the beta and gamma-proteobacteria , since large families such as the Firmicutes often do not encode RNase E homologs , but instead encode RNase Y [6] and one or more RNase J paralog ( s ) [7] . A role for RNase J1 in general RNA decay was shown by depleting it in Bacillus subtilis and Streptococcus pyogenes , which greatly increases the half-lives of many mRNAs [8]–[10] . Moreover , B . subtilis and S . aureus RNase Y , RNase J1 , and RNase J2 have been proposed to be a part of a larger degradosome-complex , identified via bacterial two-hybrid interactions [11] , [12] , which might coordinate and/or regulate the RNA decay . The characterisation of the in vivo enzyme activity of B . subtilis RNase J1 revealed a 5′ to 3′ exoribonucleolytic activity , previously unheard of in bacteria [13] , and structural studies have provided important clues to the molecular basis for this activity [14]–[16] . Removal of the final 38 nucleotides from the 5′-end of pre-16S rRNA in B . subtilis is dependent on this exonucleolytic activity , underlining its importance [13] , [17] . In contrast , RNase J2 exhibits little to no exonucleolytic activity [18] , which is accompanied by a virtual lack of phenotypes in a B . subtilis RNase J2 mutant [7] , [8] . A hint to the role of RNase J2 may be found in bacterial two-hybrid experiments , where RNase J1 and J2 interact strongly with each other [11] , [12] , and several lines of evidence from both B . subtilis and S . aureus suggest that RNase J1 and J2 can form both homo- and hetero-dimers as well as hetero-tetramers , although reports do not agree on which form is predominant [12] , [16] , [18] . Moreover , individually both B . subtilis RNase J1 and J2 have been shown in vitro to endonucleolytically cut a number of RNAs , and that the interplay between the two proteins changes the specificity of this activity [7] , [18] . However , the physiological role of this , and to what extent it complements the endonucleolytic activity of RNase Y , is not clear [9] . RNase J1 was originally identified as an essential gene in B . subtilis [19] , and both RNase J1 and J2 were reported to be essential in S . pyogenes [10] . In S . aureus , a saturated transposon insertion screen of the genome failed to find insertions in either RNase J1 or RNase J2 , suggesting that both were essential in this organism [20] . In contrast , using our recently developed system for generating allelic replacements in S . aureus , we were able to isolate deletion mutants of both RNase J1 and J2 [21] . In this work we examine the range of severe phenotypes caused by the loss of RNase J1 and RNase J2 , however at the same time we show that a deletion of both is viable in S . aureus . This is in concert with results published during the preparation of this manuscript by Figaro and coworkers [22] , where , in contrast to previous data , the two RNase J genes were shown to be non-essential in B . subtilis . In addition , we show that mutations in the RNase J1 active site are virtually equivalent to a complete deletion of the RNase J1 gene , whereas the RNase J2 active site appears to have no function under the tested conditions , even though a complete deletion of RNase J2 results in growth defects that approach the RNase J1 deletion . To study the details of RNase J1 and J2 mutations , we furthermore developed a new method for examining the 5′-ends of the entire mono-phosphorylated transcriptome . Using this assay , we show that the major role of RNase J ( RNase J will be used as generic term , where we discuss J1 and J2 , and not a specific one of them ) in RNA decay is the 5′ to 3′ exonucleolytic activity , but examples are also given where the RNase J endonucleolytic activity might play an important role . Finally , we show that RNase J activity is responsible for the normal pathway of RNase P RNA and 16S rRNA 5′-maturation .
In order to consolidate the apparent contradiction between the findings of Chaudhuri and coworkers ( 2009 ) , which indicated essentiality of RNase J1 and J2 , and our own previous findings , in which the two genes are non-essential [21] , we used total genome sequencing to confirm the deletions of the two RNase J genes ( S0940 and SA1118 , using the S . aureus N315 nomenclature , which will be used throughout this manuscript ) . Out of more than three million 100 bp reads from the Illumina machine , none mapped to the deleted regions , in contrast to the sequence of unrelated strains , where at least 1100 reads would map to each of the two RNase J genes ( Table 1 ) . This confirmed that RNase J1 and RNase J2 regions had indeed been deleted in our mutants , and additionally ruled out that the rnase genes had been moved to an alternative genomic location by an unfortunate recombination event . The sequencing data was also used to perform a search for single nucleotide polymorphisms ( SNPs ) and small inserts and deletions ( indels ) in our mutant strains , localising any potential second-site mutations which might aid the cell in surviving the loss of the RNase J genes . However , the only secondary mutation identified in the RNase J1 deletion strain ( strain ΔJ1 ) was a silent valine to valine in the gluconate operon repressor ( C to A at position 2578631 in SA2295 ) , and no secondary mutations were detected in the RNase J2 deletion strain ( strain ΔJ2 ) . Furthermore , to ensure that the viability of the RNase J1 deletion mutants was not a peculiarity of the SA564-strain used [21] , the RNase J1 deletion was generated twice , independently , in an RN4220 background ( strains PR02-03 and 06 , Table 2 ) . The main difference between our method for generating mutants and that of Chaudhuri and coworkers , was the passages at 44°C used by the latter to eliminate their thermosensitive transposon-carrying plasmid . Indeed , the authors warn that their list of essential genes reflect conditions at 44°C in the specific medium used , and state: “Consequently , genes required for high temperature survival will be scored as putatively essential” [20] . Therefore , we tested whether high temperature was limiting growth of the RNase J mutants , by spotting a dilution series of RNase J1 and J2 mutants on Mueller-Hinton ( MH ) plates , incubated at a range of temperatures . Corresponding with the warning from Chaudhuri and coworkers , the RNase J deletion mutants did indeed grow extremely poorly at 42°C , but , surprisingly , also at 30°C and below , and it is therefore only at 37°C that the mutants will grow relatively unaffected ( Figure 1 ) . The requirements for the medium were examined by using a defined medium ( RH-medium , containing only glucose , amino acids , vitamins , buffer , and salts ) , along with LB-medium and MH-medium . The spot-tests revealed that RNase J deletion mutants require a complex medium for growth , and will not grow on RH-medium . Furthermore , even though LB medium contains a complex range of various salts and nutrients , it has a low Magnesium concentration ( 30 to 50 µM; [23] ) , and this deficiency apparently also inhibits growth of the RNase J mutants , unless additional MgCl2 is added , in which case the ΔJ2 mutant will grow ( Figure 1A ) . Thus , RNase J mutants are only viable at a very restrictive temperature range and are highly susceptible to medium changes . In the single RNase J1 and J2 mutants , it is still a possibility that the activity of the remaining RNase J partially compensates for the loss of the other RNase J . To examine the consequences of a complete absence of RNase J activity , a double mutant ( ΔJ1ΔJ2 ) was generated , where the RNase J2 mutant was used as parent for a second round of mutagenesis , to substitute the RNase J1 gene with an erythromycin resistance cassette . The full genome of the double mutant was also sequenced , to confirm the deletions ( Table 1 ) . The double mutant does grow at 37°C , but even slower than the single mutants ( Figure 1B ) . Both strains ΔJ1 and ΔJ1ΔJ2 generate visible aggregates when grown in liquid culture , making it difficult to obtain reproducible growth data by measuring OD600 or CFU-counts . We therefore used a semi-quantitative spot-assay to evaluate the growth of the various mutant strains , by comparing the size of individual colonies on the same petri-dish . RNase J2 is not essential in B . subtilis , and a deletion mutant exhibits only very mild phenotypes [8] . In S . aureus the RNase J2 deletion does result in strong growth defects , however these defects are less severe than those observed for the ΔJ1 strain ( Figure 1 ) . This raised the possibility that the effects observed from deleting RNase J2 were in fact due to a partially malfunctioning RNase J1 , in the absence of RNase J2 . Alternatively , since the interaction of RNase J2 with the degradosome appears to go through RNase J1 [11] , [12] it is possible that the stronger phenotypes observed for the ΔJ1 strain are due to removing RNase J2 from the degradosome in absence of RNase J1 . Active-site mutants were therefore generated , in order to maintain the possibility of correctly forming a J1+J2 complex , but eliminating the enzymatic activity of either one or the other of the ribonucleases . The active site of S . aureus RNase J1 has a 74-HGHEDH-motif , which matches the signature motif ( HxHxDH ) of the metallo-β-lactamase family [18] , while the S . aureus RNase J2 active site sequence 76-HGHEHA exhibits several differences from the motif ( Figure S1 ) . A H76A mutation disrupts the unique active site of B . subtilis RNase J1 [13] , [16] , [17] , and since both RNase J1 and J2 of S . aureus have the first two Zinc-coordinating histidines of the HxHxDH motif , these were chosen for substitution with alanines , generating the active site mutants RNase J1 H74A-G-H76A ( J1AGA ) and RNase J2 H76A-G-H78A ( J2AGA ) in place of the wild-type genes on the chromosome ( Table 2; Figure S1 ) . The growth of J1AGA and J2AGA mutants were then examined , under the conditions where ΔJ1 and ΔJ2 are inhibited . The J2AGA mutant grew like wild-type under all tested conditions consistent with a proposed structural role of RNase J2 , whereas the J1AGA strain exhibited defects that were very similar to the ΔJ1 mutant ( Figure 1B ) , and it is therefore not dissociation of the degradosome that produces the phenotypes . RNase J1 , and to a lesser degree RNase J2 , from B . subtilis were shown in several studies to have 5′ to 3′ exoribonucleolytic activity , and that mono-phosphorylated 5′ ends were strongly preferred over tri-phosphorylated ends . To examine the effects of RNase J1 and J2 on 5′-ends of RNAs in S . aureus , the Exact Mapping Of Transcriptome Ends ( EMOTE ) assay was developed to map the exact 5′ base of a large number of mono-phophorylated RNAs in the cell ( see flowchart in Figure 3 ) . Briefly , large excess of a custom-designed 18 nt RNA oligo ( Rp5 ) was ligated to total RNA preparations from WT , ΔJ1 , ΔJ2 , ΔJ1ΔJ2 , J1AGA , ΔY , and ΔcshA strains ( Table 2 ) . The enzyme used , T4 RNA ligase 1 , will not ligate tri-phosphorylated ends to Rp5 , and the assay is therefore specific for the 5′ mono-phosphorylated ends that are preferred and generated by RNase J . The cDNA was generated using a semi-random primer ( DROAA ) , which also adds one of the two linkers needed for sequencing with Illumina HiSeq technology . In order to avoid cDNA generated from the excess of Rp5 , the DROAA primer terminated in two deoxyadenosines , a combination which is extremely common in the S . aureus genome , but is unable to basepair with the uridine-lacking Rp5 oligo . Second strand synthesis and PCR amplification was carried out using a primer specific for the Illumina linker in DROAA , paired with a Rp5-specific primer which also added the second Illumina linker sequence to the DNA . 50 bp Illumina sequencing was then performed from the Rp5-end of the DNA , revealing the 24 first bases of each RNA , more than enough to map the reads precisely in a bacterial genome ( Figure 3 ) . The first of these 24 bases thus represents the 5′-end of an RNA molecule in the original sample , and the number of Illumina reads that correspond to each original 5′ position , are then added up and tabularised ( see Tables S1 , S2 and S3 for examples ) . In the tables , the position given is the number of the first ( 5′ ) base in the detected RNA , and a cleavage at position X is therefore defined as a cleavage between base X-1 and base X . Each column shows the number of reads that detect a specific 5′-end from a given strain . Table 4 gives a general overview of the output from the EMOTE assay . The first step was to remove reads that do not have the Rp5 sequence ( about 6% ) , and therefore cannot be used to determine 5′-ends . Next the barcodes were identified to assign each read to a specific bacterial strain . These pools of reads were then examined for the presence of the CC motif , which ensures that the read reflects a genuine RNA 5′-end . Aligning the 24 bases after the CC motif to the S . aureus N315 genome sequence resulted in either uniquely mapping reads , or reads that mapped to multiple locations on the genome ( such as rRNA genes , IS elements , etc . ) . Uniquely mapping and multiply mapping reads were organised in separate tables for further analyses , as shown in Table S1 and S2 . The EMOTE method was evaluated by comparing our data to the results from the recent landmark paper on RNase III function in S . aureus [25] . The described RNase III cleavage of the 16 rRNA processing stem , the cut inside the rnc gene , and the double-stranded cut of a hairpin in the cspA gene were all detected by our method ( Tables S3 , S4 and S5 ) . The cleavage of the 16S rRNA processing stem by RNase III was detected at the exact previously published site , and served as a basis for further analyses of the 16S rRNA gene ( see below ) . In the rnc gene we detect a large number of RNA with a 5′ base at position 1216563 and a smaller sub-population at the adjacent base 1216564 , and in addition , a weaker signal is seen for 5′-bases 10–16 bases downstream , corresponding to the cleavage detected in vivo by primer extension . In the cspA gene , we could detect a high number of 5′-ends at positions 1409120 and 1409083 , which not only confirm the previously published results , but additionally our exact method serves to refine the positions of the RNase III cleavages to one base further towards the base of the cspA hairpin [25] . RNase J1 has been proposed to be a major player in bulk RNA decay [7] , by processively digesting the RNAs from the 5′-end once they become mono-phosphorylated , either by an endonucleolytic cut , or by the action of a pyrophosphohydrolase . This hypothesis has been supported by the observed stabilisation of individual RNAs during depletion of RNase J1 in B . subtilis and S . pyogenes [8] , [10] . However , until now it has been unclear to what extent it is a general mechanism that affects a majority of the transcriptome , or whether only a small subset of RNAs are dependent on RNase J1 for correct degradation . To resolve this , the number of reads for a given position in the WT data-set was compared to the number of reads in the RNase J mutants . Only positions where at least two reads mapped in both the WT and mutant data-sets were included , reducing background noise , and potential bias caused by lack of sequencing depth . Table 5 shows the number of positions that fulfilled the criteria , and the percentage of these that are either 4-fold more abundant or 4-fold less abundant in the mutants . The ΔY and ΔcshA data are included as controls , and show neither strong enrichment nor strong reduction in the 5′-ends . The strong enrichment of 5′-ends in the RNase J mutants , signifies that under wild-type conditions , the bulk of the RNA is indeed degraded by the 5′ exonucleolytic activity of the RNase J complex . The assay does not reveal what happens to the 3′-ends of the RNA , however , the strains are viable , and it must therefore be presumed that the RNA is degraded via the 3′-ends in the RNase J mutants . When an RNase is analysed in an isolated in vitro system , the interpretation is often straight-forward since the presence/absence of the RNase will generate certain specific patterns of RNA products . In vivo however , many RNases function together , often with overlapping functions , to degrade or mature RNA , and it is therefore important to take this into account when interpreting the data . Several scenarios can be imagined when the RNase J genes are deleted , due to the potential combination of exo- and endo-nucleolytic activities . Below , we present four examples where RNase J activity impacts on RNAs ( Figures 4 , 5 , 6 and 7 ) and although they are certainly not exhaustive for all situations , they illustrate different outcomes of the absence of RNase J activity .
RNase J1 and RNase J2 active-site mutants were examined , and surprisingly , the J2AGA mutant exhibited no growth defects , whereas the J1AGA mutant behaved almost exactly like the full RNase J1 deletion mutant , both in the 5′-mapping experiments and in terms of growth , with the only major difference being an ability to grow on magnesium complemented LB-medium ( Figure 1 ) . This seems to indicate that the only active RNase J in S . aureus is RNase J1 , but that the RNase J2 protein is needed for RNase J1 to function correctly . Taking into account data mainly from B . subtilis [11] , , but also from S . aureus [12] , RNase J1 and RNase J2 strongly interact , and will generate a population of hetero-dimers or tetramers . We therefore propose a model where RNase J1 provides the active site of the complex , accounting for the strong phenotype of the J1AGA mutant , and the lack of phenotypes for the J2AGA mutant . In contrast , RNase J2 serves mainly as a structural protein , ensuring the proper function of the RNase J1+J2 complex . The phenotypes seen for the RNase J2 deletion mutants are therefore caused by a disruption of the RNase J1+J2 complex , which can be partially overcome by over-expressing RNase J1 from a plasmid , however , the over-expressed RNase J1 does not need to be enzymatically active ( Figure 2 ) . This hypothesis is strengthened by the almost identical molecular data from ΔJ1 and J1AGA , and ΔJ2 , found throughout our EMOTE and Northern blot data ( Figures 4 , 5 , 6 and 7; Table S1 and S2 ) . Nevertheless , the model does not completely exclude a minor enzymatic activity of RNase J2 , perhaps when it is not complexed to RNase J1 , an activity that would account for the +45 cut of SA1075 in ΔJ1 ( Figure 7 and see below ) . Moreover , the interplay between RNase J1 and J2 may be different in organisms where RNase J2 was shown to be either essential or virtually dispensable , such as S . pyogenes and B . subtilis , respectively [10] , [7] . RNase J enzymes were reported to have endonucleolytic and 5′ to 3′ exonucleolytic activities . To obtain a better picture of these enzymatic activities within the cell , it was necessary to develop an assay that allowed us to examine the 5′-ends of all cellular RNA in the mutants , and compare it to the wild-type ( Figure 3 ) . Two additional mutants of the RNA decay machinery ( ΔY and ΔcshA ) were included as controls , to ensure that observed effects were RNase J specific . Processed RNA and degradation intermediates possess a mono-phosphate 5′-end , and are readily detected in our assay , whereas primary 5′-ends are generally protected by their triphosphate ends , and are only detected due to the pyrophosphohydrolase activity of enzymes such as RppH [24] . The assay is therefore useful for studying enzymes like RNase J , that endo- or exonucleolytically cleave RNA and produce molecules with monophosphorylated 5′-ends . The EMOTE analysis shows a clear enrichment in the RNase J1 mutants at all positions upstream of the 4+M position ( defined here as the mature rRNA with additional 4 nucleotides at the 5′-end ) , whereupon the abundance rapidly decreases to an extreme under-representation at position M1 ( the first nucleotide of the mature rRNA ) . The proportion between the RNase J1 mutants and the WT stays at the same high plateau from position 13+M to 4+M ( Figure 4 ) , and our data indicate that this plateau extends all the way to the RNase III cleavage site ( 93+M ) ( Table S3 ) . Downstream of position 5+M , in the wild-type , 5′ ends are strongly enriched , presumably due to rapid exonucleolytic activity of RNase J trimming the 16S rRNA down to position 4+M , and then a somewhat slower final trimming to obtain the fully mature 16S rRNA at position M1 . It is furthermore possible that the difference between the severity of phenotypes seen for ΔJ2 and ΔJ1 ( Figure 1 ) can be explained by the higher proportion of mature 16S rRNA observed in ΔJ2 ( Figure 4 ) . Our interpretation is that an unidentified endonuclease cleaves semi-randomly between 93+M and 5+M , whereupon the RNase J1+J2 complex exonucleolytically degrades the resulting 5′-end until it reaches the M1 position . The endonuclease responsible for the random cuts in S . aureus is not likely to be RNase Y , since the ΔY data follow the WT data closely ( Figure 4 ) . Even in the total absence of RNase J , there is however still a small but significant amount of 16S rRNA with a correctly matured 5′-end , but it is unclear whether this is caused by occasional cleavage at the M1 position by the above mentioned unidentified endonuclease , or by a backup-system for RNase J ( Figure 4 ) . In B . subtilis , the 16S rRNA is specifically cut by the unidentified endonuclease at position 38+M , whereupon it is trimmed to maturity by RNase J1 [13] , [17] . In S . aureus , a peak in the reads at positions 27+M and 28+M in both WT and all mutant strains ( Figure 4 , Table S3 ) suggests that these two positions are equivalent to 38+M in B . subtilis , but that the S . aureus enzyme is less specific . Since RNase J is responsible for maturing the 5′ end of 16S rRNA , they must somehow limit their processive exonuclease activity , in order to avoid degrading the entire rRNA . Mathy and coworkers [13] observed that in vitro , the B . subtilis RNase J1 will digest the entire 16S rRNA molecule , but this is obviously not the case in vivo , where RNase J processivity is arrested at the M1 site , presumably by ribosomal proteins . We have shown that the +1 transcript of SA1279 continues into rnpB ( Figure 5 ) and that this long RNA is processed to obtain a mature RNase P RNA ( Table 7 , Figure S2 ) . We propose that the accumulation of RNA species with 5′-ends in the region downstream of the SA1279 ORF ( +452 to +477 ) , detected in the RNase J mutants , represent cleavage products by an unidentified endonuclease , which in the WT strain are trimmed by RNase J to form the mature RNase P RNA at position +485 ( Figure 5C ) . This model thus explains the reduction in observed +485 RNA in the RNase J mutant strains , and the remaining , lower , level of mono-phosphorylated mature RNase P RNA is generated directly by transcription initiation and pyrophosphohydrolysis at this site ( Figure 5B ) , despite the poor −35 motif . It is possible that it is RNase Y that performs the endonucleolytic cleavage of the +452 to +477 region . However , our data can neither confirm nor reject this , since the resulting 5′-ends are removed so quickly by RNase J in the WT strain that they do not appear in our data , and thus the absence of these species in the ΔY mutant is not conclusive ( Figure 5 ) . The formation of +499 RNA population is less obvious , however our data clearly show that it is caused by RNase J . The evolutionary conserved P1 Helix , which presumably protects the 5′-end of the RnpB RNA from 5′ degradation cannot form during transcription , but only once the entire RNA has been made . One possibility is therefore that a 5′ exonucleolytic attack is made by RNase J on nascent RNA , which has not yet formed the P1 Helix ( Figure 5D ) . This exonucleolytic digestion would then continue until blocked by one of the many secondary structures in RNase P RNA , or by the protein component ( RnpA ) of the ribozyme . The +499 end would in this model represent a degradation intermediate , where RNase J either is blocked or pauses long enough to accumulate a detectable population of +499 RNA . The EMOTE data , due to potential ligation and PCR biases , cannot be used quantitatively to compare the relative abundance of two different 5′-ends such as +485 and +499 , and the same is the case for the circularised and cloned junctions shown in Table 6 , which seem to indicate that the +499 5′-end is more abundant in the WT strain than the +485 end . Instead , Table 6 confirms qualitatively that the 5′-end of the RNA can be both +485 and +499 in WT . Adding further complexity to the maturation of RNase P is the existence of a small anti-sense RNA , which can base-pair to the 3′-end of RnpB [2] , [28] . One could imagine that this anti-sense RNA is in competition with the 5′-end of the RnpB to hybridise to the 3′-end , and if the competition is successful , then the P1 Helix will fail to form , and the 5′-end is free to be degraded by RNase J ( Figure 5D ) . Our data cannot directly determine whether the +52 cut of SA2322 is due exonucleolytic digestion of the primary transcript , or an endonucleolytic cut directly at +52 . In either scenario , 5′ to 3′ exonucleolytic digestion beyond +52 is very likely inhibited by ribosomes binding the RBS , as seen for the hbs gene in B . subtilis [29] . Importantly , if Helix I , helped by Helix II , forms in vivo in full-length mRNA , the +52 cut may serve a regulatory function , since Helix I partially sequesters the RBS of SA2322 . It is also worth noting that the transcription start site of SA2322 appears to be less precise in all the RNase J mutants ( Figure 6A ) . This might be due to lessened fidelity of the transcription initiation complex , altered activity of pyrophosphohydrolases , which would reveal new products to our assay , or perhaps that RNAs starting at position +3 or +4 are so rapidly degraded by RNases J in the WT strain , that these RNA species simply are not observed . The essential [20] SA1075 gene , where a cut at position +16 liberates the RBS , serves as a second example of an RNase-mediated regulatory mechanism . This cleavage however , is not mediated by RNase J . Instead , a second cleavage at position +45 , inside the SA1075 ORF , is performed by either RNase J1 or J2 individually , and reveals an intriguing difference in activity between the RNase J1+J2 complex , and RNase J1 or J2 alone . It appears that three scenarios are possible for a newly transcribed SA1075 mRNA: i ) Translation is initiated before Hairpin I can form , and successively loading ribosomes prevent the formation of Hairpin I . If ever a pause in translation initiation occurs , then Hairpin I will form , blocking further initiation , unless ii ) an RNase cleaves at position +16 , to destroy Hairpin I and allow translation initiation . However , if an SA1075 mRNA molecule is not shielded by ribosomes , then it is a potential target for iii ) an RNase J cleavage at position +45 , which removes the RBS and start codon , and initiates degradation of the mRNA ( Figures 7C and E ) . While our data cannot identify the enzyme that cleaves SA1075 mRNA at position +16 , it is possible that it is RNase III , because the 5′ fragment of the SA1075 mRNA was recovered in a pull-down experiment , using an inactive RNase III mutant as bait , whereas a fragment starting at +16 was obtained when wild-type RNase III was used ( [25]; P . Romby , personal communication ) . If so , then the fate of an SA1075 mRNA is decided by a competition between RNase J , RNase III and the ribosome ( which itself is matured by RNase J and RNase III ) . Several hypotheses can explain difference at position +45 , between the ΔJ1 , ΔJ2 and J1AGA mutants and ΔJ1ΔJ2 , observed in both the Northern blot and EMOTE data ( Figure 7 ) . It is possible that the +45 cleavage is caused by an unrelated RNase , which is over-expressed in the ΔJ1 , ΔJ2 and J1AGA mutants , but not in the ΔJ1ΔJ2 strain . It is also possible that RNase J1 or J2 individually still retain a small amount of exonucleolytic activity , even though no such activity has been shown for RNase J2 [18] , and that this activity is able to digest until position +45 , where it is blocked by an unknown mechanism . What this mechanism might be is uncertain , since the +45 RNA does not contain a ribosomal binding site , nor is any secondary structure predicted which could block RNase J exonucleolysis . Our preferred hypothesis , is that the +45 is an endonucleolytic cleavage which can be performed by either of the two RNase J proteins individually , but that any subsequent 5′ to 3′ exonucleolytic degradation can only be carried out by a functional RNase J1+J2 complex . This would explain why 5′-ends at position +45 are not seen in the WT strain , since the RNAs are rapidly 5′ to 3′ digested , neither seen in the ΔJ1ΔJ2 strain , because the +45 cleavage is never made . In contrast , the +45 RNA is highly enriched in the ΔJ1 , ΔJ2 and J1AGA mutants , because they are able to perform the +45 cut , but unable to exonucleolytically degrade the resulting product . This hypothesis would also correspond with the observation by Mäder and coworkers [8] that several genes had significantly altered abundance in their B . subtilis RNase J1 and/or RNase J2 mutants , but did not exhibit any change in the double mutant . Supporting this hypothesis are the data presented in Table 5 , where the severely inhibited or lacking in vivo exonuclease activity in strains ΔJ1 , ΔJ2 and J1AGA results in a similar accumulation of 5′-ends to that found in strain ΔJ1ΔJ2 . As seen in Figure 1 , the RNase J mutants exhibit severe growth defects when taken outside the narrow ‘comfort zone’ of 37°C and Mueller-Hinton medium . The exact cause ( s ) of these problems have not been identified , but since our 5′ data shows that RNase J exerts a global influence on mRNAs ( as well as on maturation of stable RNAs ) , the growth defects are most likely due to mis-regulation of a number of genes , each of which probably not causing major phenotypes , but generating severe effects when combined . Possible candidate genes could be SA1075 ( hmrB ) and RNase P , which are both essential [20] . In all mutant studies , especially those where the growth of the cell is severely affected , there is always a risk of detecting secondary effects of the mutation . This is important to keep in mind when interpreting the RNase J mutant data , even though we have attempted to strengthen the observations by using a range of different RNase J mutants and including the ΔY and ΔcshA strains as controls . It appears that the 5′ to 3′ exonucleolytic activity is crucial for normal growth , whereas the endonucleolytic activity only serves a secondary function . The normal growth of strain J2AGA supports this , if the S . aureus RNase J2 is similar to its B . subtilis counterpart , which almost exclusively exhibits endonucleolytic activity in vitro [18] . While we do not assume that our four presented examples are exhaustive for all the functions of RNase J , they reveal how RNase J activity remodels sub-populations of RNA ( Figures 4 , 5 , 6 and 7 ) , and show that the roles of RNase J are diverse , ranging from maturation and post-transcriptional regulation to degradation . Furthermore , our data clearly show that RNase J1 is the work-horse , while RNase J2 plays a supporting role , with no detected phenotypes of the J2AGA mutant . However , we also detect that an important RNase J-mediated cleavage takes place in the SA1075 gene in ΔJ1 , which demonstrates that RNase J2 is capable of performing some tasks by itself . The implied interplay between RNase J1 , RNase J2 and the RNase J1+J2 complex in vivo , which might correlate with switching between endo- and exo-nucleolytic activity , is likely to have fine-tuned regulatory functions , arising from the evolutionary event that duplicated the RNase J gene in an early Firmicute ancestor .
Mueller-Hinton ( Beckton-Dickinson , Sparks , MD , USA ) and LB-plates ( Merck , Darmstadt , Germany ) were prepared with 13 g/l agar ( Merck ) , and RH-plates were made by autoclaving 100 ml milliQ water with 7 . 5 g agar , cooling it to 55°C and mixing with 500 ml modified RPMI-medium ( Sigma , R7388 ) prewarmed to 55°C . +U , +C , and +Mg , indicates addition of 20 mg/l uracil , 10 mg/l chloramphenicol , and 5 mM MgCl2 , respectively . Mutants were generated using the pRLY-vector series ( Table 3 ) , and following the protocol described in Redder and Linder , 2012 . However , since the RNase J mutants are sensitive to both heat and cold , strains PR01-20 , PR01-25 , PR02-03 , and PR02-06 were kept between 32°C and 39°C throughout their construction , and strain PR01-27 and PR01-37 were grown at 37°C at all times , since the lack of origin of replication in the pRLY-vectors used for these strains precluded the need for plasmid establishment and plasmid elimination phases ( see also Redder and Linder , 2012 ) . Strains were cultured overnight in liquid MH+U with agitation . Dilution series were then made in MH medium , to obtain 10−5 and 10−6 dilutions , 5 µl of which were then spotted on MH and RH plates with added uracil ( 10 mg/l ) . The plates were then incubated at the indicated temperature ( s ) until the WT colonies reached appropriate size , typically 18 hours for 42°C and 37°C , 24 hours for 30°C and 48 hours for 25° . All strains compared in Figure 1 were spotted on the same plate , to eliminate variations between batches . The same was the case for the strains in Figure 2 . 2 ml of mid-exponential phase cultures ( OD600 between 0 . 40 and 0 . 45 ) were harvested by centrifugation , the supernatant removed , and 1 ml cold 1∶1 ethanol/acetone was immediately added to protect the RNA . After washing the bacterials pellets in 1×TE buffer ( 10 mM Tris , 1 mM EDTA , pH 8 ) , the cells were lysed with 100 µg lysostaphin ( AMBI Products LLC , Lawrence , NY , USA ) in 200 µl TE with 1 U/µl Murine RNase Inhibitor ( M0314S , New England Biolabs , Ipswich , MA , USA ) , and homogenised using RNeasy Shredder columns ( Qiagen , Hombrechtikon , Switzerland ) , whereupon total RNA was prepared using the RNeasy mini kit ( Qiagen ) with an on-column DNase I treatment ( Cat: 79254; Qiagen ) . For each strain , 0 . 5 nmol of Rp5 oligo ( Table 8 ) , 5 µg of total RNA , and TE buffer to a total volume of 55 µl was heated for 120 seconds at 95°C and then flash-cooled in ice/water . A premix of 10 µl 10× T4 RNA ligase buffer , 10 µl 10 mM ATP , 30 U T4 RNA ligase 1 , 1 µl Murine RNase inhibitor ( all from New England Biolabs ) , and 21 µl water was added to each tube of denatured RNA , and incubated for 3 hours at 37°C . After ethanol precipitation and re-suspension in 20 µl TE , the protocol for the MicrobeExpress kit ( Ambion , Life Technologies , Zug , Switzerland ) was followed to deplete the ribosomal RNA , followed by re-suspension in 25 µl water . cDNA with one Illumina-sequencing adaptor was generated from 4 . 5 µl Rp5-ligated and rRNA-depleted total RNA , with 100 pmol DROAA oligo , 6 µl water , 4 µl 5× Reverse Transcriptase buffer , 2 µl 100 mM DTT , 1 µl 10 mM dNTP , 0 . 5 µl Murine RNase inhibitor , and 1 µl M-MLV ( -H ) Reverse Transcriptase ( New England Biolabs ) , which was incubated for 10 minutes at room temperature , 50 minutes at 42°C , and 30 minutes at 65°C to inactivate the enzymes . 180 µl water with 1 mg RNase I was added and the cDNA was purified using the Promega SV PCR-purification kit ( Promega , Madison , WI , USA ) . The second Illumina sequencing adaptor , together with barcodes for identifying from which strain the sequence originated , was added in a second-strand PCR: 32 µl H2O , 1 . 5 µl 10 µM oligo D5La ( D5Lb , D5Lc , etc . ) , 1 . 5 µl 10 µM B-oligo ( Table 8 ) , 10 µl 5× Phusion HF buffer , 1 . 5 µl 10 mM dNTP , 0 . 5 µl Phusion enzyme , 3 µl cDNA . Program: 2 min @ 98°C , 20 sec @ 98°C , 15 sec @ 55°C , 30 sec @ 72°C ( 30 cycles ) , 3 min @ 72°C . 6 µl of each PCR product was loaded on an agarose gel , to verify that the yields were similar . 40 µl of the WT PCR product was mixed with 20 µl from each of the other strains , and the mixture was purified using the Promega SV PCR-purification kit , and eluted twice with 50 µl water . The purified mixture was loaded on an agarose gel , and the smear between 300 bp and 1400 bp was extracted using the Promega SV Gel extraction kit ( Promega ) , according to protocol ( Figure 3 ) , and the DNA was sent for 50 bp Illumina sequencing ( Fasteris , Plan-des-Ouates , Switzerland ) . Two biological replicates were carried out for strains WT , ΔJ1 , ΔJ2 , ΔJ1ΔJ2 , ΔY and ΔcshA , but only one for strain J1AGA . Data presented for J1AGA and in Figure 4 are from the second biological replicate , and the latter exhibit the same patterns as the first biological replicate . Before mapping on the reference genome , reads were split into groups looking for the exact match with the corresponding barcode sequence . After sorting , only reads having the control sequence ( CC ) at the proper position were selected . Then , reads were trimmed in order to only keep the sequence corresponding to the RNA . Reads were mapped on the reference genome ( Staphylococcus aureus N315 , accession number: NC_002745 . 2 ) using Bowtie 0 . 12 . 7 with the standard parameters . A first mapping was performed , keeping reads that mapped to unique positions on the chromosome ( Table S1 ) . Reads mapping at multiple positions on the chromosome were used on a second step ( Table S2 ) . Both mappings were analysed separately . Analysing the 5′-ends of rRNAs used data from the group of reads that mapped to multiple locations ( the five rRNA operons for example ) . The percentage of detected RNAs with 5′-ends at a given position was determined by dividing the number of reads mapping to that position by the total number of reads with a 5′-end within the region from the 16S rRNA processing stem cleavage by RNase III ( 93+M ) to the 3′-end of the mature 16S rRNA . The proportion of 5′-ends compared to the WT strain ( shown in Figure 4 ) was then obtained by dividing the percentage from the mutant strain with the percentage from the WT strain . The full data-set for 16S rRNA is shown in Table S3 . 5′-ends of mRNAs and RNase P RNA used data from the group of reads that mapped to unique positions on the chromosome . The percentages for a given position was calculated as described above , however , the proportion between mutant and WT percentages was not calculated , since several positions had a WT percentage of zero , which would lead to division by zero . The full data-sets for the examples given in the text are shown in Tables S6 , S7 , and S8 . Total RNA was prepared in the same way as for the EMOTE assay , but with an additional step of ethanol precipitation to concentrate the RNA . 4 µg total RNA from each strain was loaded on a 5% polyacryl amide gel with 8M urea , and afterwards transferred to a Hybond-N nitrocellulose membrane ( Amersham ) using a Biorad Protean Tetra-cell blotting system . The RNA was crosslinked to the membrane with a UV Stratalinker 2400 ( Stratagene ) , and the marker was revealed using Methylene blue . Probes were hybridised over night at 37°C in ExpressHyb hybridization solution ( Clontech , Mountain View , CA , USA ) , excess probe was washed away , and the signal was detected using a Typhoon FLA 7000 phosphorimager ( General Electric ) . The membrane was stripped for 2 hours at 75°C with 0 . 2% SDS and 10 mM Tris pH 7 . 5 , whereupon a new probe was hybridised . Loading control was done with a 5S rRNA probe , used last to ensure that the strong 5S signal did not interfere with the other experiments . Probes used for Northern blotting ( Table S9 ) were 5′ labelled using 32P γ-ATP and T4 polynucleotide kinase ( New England Biolabs ) . | The long RNA ( ribonucleic acid ) chains are key intermediates in the transfer of information from the genes on chromosomes to the production of protein . An RNA copy ( mRNA ) is transcribed from the gene , and this copy is then translated into protein by a complex molecular machine called the ribosome . The amount of mRNA copies of a given gene is therefore important for how much of the corresponding protein can be generated . This “pool” of mRNA depends on how many copies are made per second , but also on how many copies disappear due to degradation . In this study , we examine mutants of the bacterial pathogen Staphylococcus aureus , which have lost one or both of their RNase J genes ( ribonuclease J ) . These mutants grow relatively fine under standard laboratory conditions , but will stop growing if they are stressed by alternative food sources or temperatures equivalent to a high fever ( 42°C ) . We show that the RNase J enzymes are major players in the degradation of RNA by removing one link at a time in the RNA-chains , thus influencing the pool of mRNAs in the cell . Furthermore , certain RNAs are processed to stable and active forms by RNase J , instead of being degraded . | [
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] | 2014 | Transcriptome-Wide Analyses of 5′-Ends in RNase J Mutants of a Gram-Positive Pathogen Reveal a Role in RNA Maturation, Regulation and Degradation |
Recent advances in DNA sequencing have enabled mapping of genes for monogenic traits in families with small pedigrees and even in unrelated cases . We report the identification of disease-causing mutations in a rare , severe , skeletal dysplasia , studying a family of two healthy unrelated parents and two affected children using whole-exome sequencing . The two affected daughters have clinical and radiographic features suggestive of anauxetic dysplasia ( OMIM 607095 ) , a rare form of dwarfism caused by mutations of RMRP . However , mutations of RMRP were excluded in this family by direct sequencing . Our studies identified two novel compound heterozygous loss-of-function mutations in POP1 , which encodes a core component of the RNase mitochondrial RNA processing ( RNase MRP ) complex that directly interacts with the RMRP RNA domains that are affected in anauxetic dysplasia . We demonstrate that these mutations impair the integrity and activity of this complex and that they impair cell proliferation , providing likely molecular and cellular mechanisms by which POP1 mutations cause this severe skeletal dysplasia .
Skeletal dysplasias ( SD ) are a group of genetic disorders affecting skeletal development that cause deficiencies and deformities of the limbs and spine , dwarfism , or abnormal bone strength . SDs are usually inherited as dominant or recessive monogenic Mendelian traits or occur as a result of de novo mutations . Recent advanced in targeted whole-exome DNA re-sequencing have enabled several groups to identify of causative mutations underlying various Mendelian diseases , in which traditional linkage approaches were not feasible because of the paucity of familial cases in which to perform the mapping [1]–[7] . In this study we report the mapping of mutations causing a severe bone dysplasia in a family of unrelated unaffected parents with two affected siblings . The clinical and radiographic features of the affected siblings showed similarities to anauxetic dysplasia , an autosomal recessive spondylo-epi-metaphyseal dysplasia characterized by extremely short stature [8] , [9] . Both siblings had severe growth retardation of prenatal onset , a bone dysplasia affecting the epiphyses and metaphyses of the long bones particularly in the lower limbs , and abnormalities of the spine including irregularly shaped vertebral bodies and marked cervical spine instability ( Figure 1 ) . Anauxetic dysplasia is caused by mutations in RMRP , an untranslated intronless gene , mutations of which also cause cartilage-hair hypoplasia ( CHH , OMIM 250250 ) , another severe form of dwarfism [10] . As RMRP mutations had been excluded in this family , we sought to identify the disease-causing variants by whole-exome sequencing .
We sequenced exomes of both parents and the affected siblings using the Nimblegen SeqCap Ez exome capture protocol and the Illumina Genome Analyser II paired-end sequencing method . High quality sequence reads were aligned to the human reference genome ( UCSC assembly hg19 ) ; 90% of targeted bases had coverage of fourfold or higher; and 79% of targeted bases had coverage greater than tenfold . We then used SAMtools [11] , Genome Analysis Toolkit ( GATK ) [12] and custom scripts to detect polymorphic sites in the four individual exome sequence data sets . Following quality filtering , we retained approximately 15 , 000 SNPs per sequenced exome ( Table 1 ) . The vast majority of these SNPs ( >96% ) were reported in the recent NCBI dbSNP 131 release , and were therefore excluded from further analysis as unlikely to cause this severe , rare , phenotype . Following the functional annotation of the remaining novel SNPs , we focused our analyses on a set of 483 unique novel coding non-synonymous SNPs that were detected in at least one sample . Given the affected status of both siblings and unaffected status of the parents we considered autosomal recessive homozygous and autosomal recessive compound heterozygous as the two most likely inheritance models; as the parents are unrelated , a compound heterozygous model was considered most likely . All novel non-synonymous SNPs were analyzed assuming either a homozygous or a compound heterozygous model . We did not find any novel non-synonymous mutations that satisfied a recessive homozygous inheritance model . To be accepted as candidate mutations for a compound heterozygous inheritance model , we sought genes with at least two novel non-synonymous SNPs within the protein coding sequence in both siblings; additionally , the same alleles had to be present in the parents in a mutually exclusive manner . We identified four candidate genes ( POP1 , PKD1 , MICALL2 , and COL5A1 ) that fitted this model ( Table S1 ) . To determine the gene likely to be causing the disease we analyzed the effects of the detected missense mutations on protein function using the SIFT algorithm [13] . In all but one gene the detected missense mutations were predicted to be tolerated in terms of effect upon protein function . The single remaining candidate gene carried two novel alleles – one creating a premature stop codon , and the other causing a missense mutation with predicted damaging effect on protein function , thus representing a strong candidate for the disease-causing gene in this family ( Figure 2 ) . Remarkably , we found that this gene encodes the human homolog of the yeast POP1 ( processing of precursor RNA ) protein , one of the core components of the RNase P and RNase MRP complexes [14] , [15] . RNase P and RNase MRP are essential ribonucleoprotein complexes present in all eukaryotes [16] . Both enzymatic complexes have an evolutionarily conserved RNA component as a catalytic moiety . Several proteins essential for enzymatic activity form a constitutive part of RNAse P and RNase MRP complexes . POP1 is the largest constitutive component of both complexes ( Figure S1 ) [15] , [16] . Importantly , mutations in RMRP , which encodes the RNA moiety of the RNase MRP complex , cause anauxetic dysplasia and cartilage-hair hypoplasia [10] . To validate the identified POP1 mutations we re-sequenced genomic DNA fragments encompassing mutated alleles of the POP1 gene using Sanger sequencing , confirming that the two affected siblings carry both mutated alleles , while each parent carries only one allele ( Figure 2A , 2B ) . While neither of these mutations is located within known protein domains ( as determined by PFAM annotation ) , both amino acids affected by the mutations show high levels of evolutionary conservation , suggesting their importance for the functional integrity of POP1 and/or RNase P/RNase MRP complexes ( Figure 2C; Figure S1 ) . The p . Arg513Ter mutation is likely to be particularly damaging; the premature stop codon located in the exon 10 would trigger mRNA degradation via nonsense mediated decay mechanism . Alternatively ( though less likely ) , p . Arg513Ter mutation would result in translation of a truncated protein lacking the evolutionarily conserved POPLD domain ( Figure 2C ) . These results are consistent with findings in yeast . Xiao et al . [16] identified several point mutations in the yeast POP1 protein that affect either the stability or activity of RNase P and RNase MRP complexes . Importantly , some of the yeast mutations were found close to the mutations identified in our study , supporting our conclusion that these are likely to cause significant detrimental effect on RNase P and RNase RMP function . The very low population frequency of the described skeletal dysplasia , and the essential roles of RNase P/RNase MRP enzymatic complexes in cellular functions , suggest that there is strong negative selection pressure on homozygous and compound heterozygous mutations with detrimental effects on the activity of these complexes . Indeed , analysis of mutations that ablate POP1 function in model organisms demonstrate that POP1 is essential for viability in yeast and Drosophila [14] , [17] . In this context , it is likely that one or both detected POP1 mutations have only a partial effect on function of either RNAse P or RNase MRP complexes . This conclusion is consistent with the broad spectrum of mutations observed in RMRP in cases of anauxetic dysplasia and cartilage-hair hypoplasia and their correlation with the severity of the disease phenotype [18] . RMRP mutations implicated in anauxetic dysplasia and cartilage-hair hypoplasia have distinct clustering within the RMRP RNA molecule [18] . Importantly , POP1 directly interacts with the same RMRP RNA domains that are affected in anauxetic dysplasia ( Figure S1 ) [18] , [19] . This further strengthens the link between our findings and the molecular mechanisms underlying the clinical phenotype in anauxetic dysplasia and our patients . To assess population frequency of the POP1 alleles we screened 186 DNA samples from healthy control subjects . For the NM_001145860 . 1:c . 1573C>T ( p . Arg513Ter ) allele we used direct Sanger sequencing of PCR-amplified DNA fragments . To estimate the frequency of the second POP1 allele , NM_001145860 . 1:c . 1748G>A ( p . Gly583Glu ) , we used a restriction fragment length polymorphism ( RFLP ) assay designed to detect the loss of the BsaJ1 restriction site ( CCNNGG ) created by c . 1748G>A ( p . Gly583Glu ) mutation . None of the 186 control samples contained either mutation . Further , these variants are not reported in public SNP databases including dbSNP 131 . Therefore we conclude that both mutations represent novel rare alleles . One of the cellular functions of the RNase RMP complex is processing of precursor 5 . 8S ribosomal RNA into the mature form [15] . To determine the impact of the mutated alleles on functional integrity and activity of the RNase P/MRP complexes , we measured relative abundance of the RMRP RNA and unprocessed pre-5 . 8S rRNA in the affected siblings , non-affected parents , and unrelated controls . We found that the relative abundance of RMRP RNA was markedly reduced in the affected individuals compared with non-affected parents and controls ( Figure 3 ) , indicating that the mutated alleles are likely to cause mis-assembly and destabilization of the RNase MRP complex . These results are consistent with the previous study in yeast demonstrating that mutations in POP1 affect integrity of the RNase MRP complex , resulting in destabilization of the complex and reduction of the abundance of NME1 RNA ( the yeast homolog of human RMRP ) [16] . We also found that affected individuals have higher abundance of the unprocessed pre-5 . 8S rRNA compared to non-affected parents and controls ( Figure 3 ) , consistent with the established role of RNase P in processing of rRNA [15] and demonstrating that activity of the RNAse MRP complex is impaired in the affected individuals . To assess the cellular impact of this molecular defect , we measured cell proliferation in stimulated peripheral blood mononuclear cells ( Figure 4 ) . These studies showed that , in comparison with healthy controls , the two affected cases had markedly diminished cell proliferation in response to proliferation stimulus , as evidenced by the reduced rate of dilution of CFSE fluorescence intensities ( Figure 4A ) . Additionally , individual SKDP-6 . 1 , carrying the c . 1573C>T ( p . Arg513Ter ) allele , had noticeable reduction in cell proliferation rate , consistent with the predicted more damaging effect of this mutation ( Figure 4 ) . These findings also explain similarities with the anauxetic dysplasia phenotype , as individuals with this disease also have impaired RNase P/RNase MRP activity , and diminished cell turnover [10] , [18] . In conclusion , we have identified mutations in POP1 underlying the skeletal dysplasia presented in this study . Involvement of POP1 in the skeletal dysplasia highlighted the existence of a shared molecular pathway in the etiology of skeletal dysplasias involving the RNAse P and RNase MRP complexes [10] , [18] and raises the possibility of the involvement of other components of the pathway , or allelic variants of RMRP or POP1 , in other as yet unmapped severe short-stature syndromes . Screening of RMRP-negative cases of anauxetic dysplasia or CHH , or patients with similar phenotypic features , may yield additional mutated alleles within POP1 , and possibly in other components of the RNase MRP complex . We further hypothesize that the distinct skeletal phenotype associated with POP1 mutations may indicate that RNAse P and RNase MRP complexes may process other yet unidentified target RNAs with regulatory roles in specific developmental pathways such as osteogenesis . This study also provides an example of the feasibility of whole-exome re-sequencing approach in rare familiar monogenic diseases with small pedigrees .
This study was approved by the University of Queensland ethics committee ( Approval #2007001196 ) . Written , informed , consent was obtained from all subjects or their respective guardians . 5 µg of human genomic DNA extracted from peripheral venous blood samples was used for preparation of each DNA sequencing library . The DNA libraries were prepared using Illumina's paired-end sequencing DNA sample preparation kit according to the manufacturer's protocol . Whole-exome sequence capture was performed using “SeqCap EZ Exome Library v1 . 0” liquid phase sequence capture kit ( Roche/Nimblegen ) according to the manufacturer's recommendations . Sequence capture efficiency was assessed by quantitative real-time PCR using a standard set of control primers recommended in the sequence capture protocol . Individual DNA libraries were quality-checked and quantified on Agilent 2100 Bioanalyzer using DNA1000 kit , and DNA concentration adjusted to 10 nM . Sequencing was performed on the Illumina Genome Analyzer II using a standard 56 cycle paired-end read sequencing protocol and Illumina's sequencing reagents according to the manufacturer's recommendations . Each library was sequenced individually on a single flow cell lane . Base calling and sequence reads quality assessment was performed using Illumina's Data Analysis Pipeline software v . 1 . 6 . Alignment of sequence reads to the reference human genome ( hg19 , UCSC assembly , February 2009 ) was performed using the Burrows-Wheeler alignment ( BWA ) tool [20] . Sequence alignment files conversions were performed using SAMtools [11] . Only high quality sequence reads with unique mapping positions to the reference human genome were used for calling SNPs and Indels . Identification of SNPs and Indels in the alignment files was performed using Genome Analysis Toolkit ( GATK ) [12] . Raw SNP calls were filtered using empirically derived cut-offs for the following GATK filter expressions: –filterExpression “QUAL <50 . 0 || AB>0 . 75 && DP>40 || QD<5 . 0 || HRun>5 || SB>−0 . 10” –filterName “StandardFilters” –filterExpression “DP<6” –filterName “LOW_DEPTH” , where QUAL – combined recalibrated quality score at the SNP position; AB – allele balance at the SNP position; DP – sequencing depth at the SNP position; QD – QUAL/DP ratio at the SNP position; HRun – maximal length of the homopolymer run; SB- strand bias at the SNP position . Known SNPs were obtained from the NCBI dbSNP build 131 ( http://www . ncbi . nlm . nih . gov/SNP/ ) . Prediction of the effect of non-synonymous amino acid substitutions on protein function was done using SIFT algorithm [13] . Sanger sequencing of the exons 10 and 12 of POP1 was performed on Genetic Analyzer 3130 ( Applied Biosystems ) using standard sequencing protocol for PCR-amplified DNA . Primers used for PCR amplification of POP1 DNA fragments and Sanger sequencing were as follows: POP1 . 10F 5′-CAATGGGAAGAGAGGGAATACATGTTT-3′; POP1 . 10R 5′-CTGGAGAGGTGTCAGAGAAAGAACTCTT-3′; POP1 . 12F 5′-CATCCTTGAGAAGGTGTCACTTAATTGTT-3′; POP1 . 12R 5′-CACCACTCAATTCCTCCTAAGTTGTACAT-3 . 186 DNA samples from healthy white European controls were studied to determine the population frequency of the variants identified . The c . 1573C>T ( p . Arg513Ter ) allele located within exon 10 of POP1 was tested by Sanger sequencing using POP1 . 10F and POP1 . 10R primers listed above . The c . 1748G>A ( p . Gly583Glu ) allele located within exon 12 of POP1 was tested by a restriction fragment length polymorphism ( RFLP ) assay designed to screen for the loss of the BsaJ1 restriction site ( CCNNGG ) created by the mutation . Following PCR amplification of exon 12 DNA fragments with POP1 . 12F and POP1 . 12R primers , DNA fragments were digested with BsaJ1 , separated by agarose gel electrophoresis , and visualised by ethidium bromide staining and UV transillumination . Total RNA was extracted from peripheral blood mononuclear cell samples using TRIZOL reagent ( Invitrogen ) following the manufacturer's protocol . The RNA concentrations and purity were determined using the RNA 6000 Bioanalyzer kit ( Agilent ) . For cDNA synthesis , 500 ng of total RNA was treated with DNase I ( Invitrogen ) and then utilized as a template for randomly primed reverse transcription using SuperScript III reverse transcriptase ( Invitrogen ) , according to the manufacturer's instructions . The resulting cDNA was diluted 1∶25 ( v/v ) with nuclease-free water . A total of 5 µL of the cDNA was used as a template for quantitative real-time PCR . Relative abundance of unprocessed 5 . 8S rRNA and RMRP transcripts in affected in non-affected individuals was determined by real-time PCR using SYBR Green RCR Master Mix ( Applied Biosystems ) according to manufacturer's protocol . The PCR amplification was performed on the ABI Prism 7900HT sequence-detection system ( Applied Biosystems ) in a final volume of 12 µL using standard cycling parameters ( 10 min , 95°C; 30 sec , 95°C; 30 sec 65°C; 30 sec 72°C , with the latter three steps repeated for 45 times ) . Primers for the real-time PCR reaction were designed using Vector NTI 11 . 0 software package ( Invitrogen ) , following primer design guidelines given in the SYBR green PCR Master Mix and RT-PCR protocol ( Applied Biosystems ) . The melting temperatures of all primers were between 65 and 71°C . All primers were purchased from the ITD ( Glycon Australia Pty Ltd ) . The primers used for detection of pre-5 . 8S rRNA were as follows: pre5 . 8S_F 5′-TGTGAAACCTTCCGACCCCTCT-3′; pre5 . 8S_R 5′-CGAGTGATCCACCGCTAAGAGTCGTA-3′ . The primers used for detection of the RMRP RNA ( GenBank NR_003051 ) were as follows: RMRP_F 5′-AGGACTCTGTTCCTCCCCTTTCCGCCTA-3′ , RMRP_R 5′-TGGAGTGGGAAGCGGGGAATGTCTA-3′ . The primers used for detection of human beta actin mRNA ( ACTB , GenBank NM_001101 ) used as an internal normalization standard were as follows: ActF 5′-TCACCATTGGCAATGAGCGGTT-3′; ActR 5′-AGTTTCGTGGATGCCACAGGACT-3′ . The final optimized concentration of primers was 250 nM for all DNA amplicons . The absence of inter- and/or intramolecular duplex formation between primers was confirmed in a control real-time PCR reaction lacking template . Relative quantification was performed as described in ABI Prism 7900HT Sequence Detection System User Bulletin #2 ( Applied Biosystems ) according to Comparative CT Method . In brief , threshold cycle ( CT ) values of experimental samples were normalized to corresponding CT values of the ACTB mRNA control , and then quantified relative to the sample with the maximal CT value ( calibrator ) . All real-time PCR reactions were done in five technical replicates , and results were confirmed in two independent experiments . Progressive dilution of the fluorescent dye CFSE during cell division was used as a proxy to assess cell division rates using flow cytometry [21] . PBMC from the affected children ( SKDP 6 . 3 and 6 . 4 ) , their parents ( SKDP 6 . 1 and 6 . 2 ) and healthy controls were labelled with 2 . 5 µM CFSE and plated in triplicate at 5×105 cells/well in 48-well plates . PBMC were stimulated with PMA and Ionomycin or left unstimulated for seven days . Proliferation of PBMC in response to stimulation was assessed by examining CFSE dilution on a FACSCanto flow cytometer ( BD ) . Comparative cell division rates were determined by calculating proliferation indices of cells undergoing 2 or more cell divisions using ModFit software ( Verity Software House ) . POP1 amino acid substitutions are given using human POP1 mRNA sequence and annotations with GenBank accession NM_001145860 . Human beta actin mRNA , RMRP RNA , and rRNA polycistron sequences have GenBank accession numbers NM_001101 , NR_003051 , and U13369 respectively . NCBI and FlyBase accession numbers for Drosophila POP1 homolog are NP_572236 and FBgn0026702 respectively . UCSC genome browser http://genome . ucsc . edu/; NCBI dbSNP http://www . ncbi . nlm . nih . gov/SNP/; Protein families database ( PFAM ) http://pfam . sanger . ac . uk/; SIFT website http://sift . jcvi . org/; GATK website http://www . broadinstitute . org/gsa/wiki/index . php/The_Genome_Analysis_Toolkit; Online Mendelian Inheritance in Man ( OMIM ) , http://www . ncbi . nlm . nih . gov/Omim/ . | Skeletal dysplasias are a group of genetic disorders affecting skeletal development that cause deficiencies and deformities of the limbs and spine , dwarfism , or abnormal bone strength . Skeletal dysplasias are usually inherited as monogenic Mendelian traits or occur as a result of de novo mutations . We report identification of mutations in human POP1 gene as the cause of a severe novel skeletal dysplasia . Molecular analyses presented in our work provide an important link between the pathogenesis of the disease and basic cellular processes including RNA processing and the cell cycle . We posit that our work will also have an immediate impact on assessment and counselling of novel cases of severe short stature . | [
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] | 2011 | Whole-Exome Re-Sequencing in a Family Quartet Identifies POP1 Mutations As the Cause of a Novel Skeletal Dysplasia |
The ability of the Lentivirus HIV-1 to inhibit T-cell activation by its gp41 fusion protein is well documented , yet limited data exists regarding other viral fusion proteins . HIV-1 utilizes membrane binding region of gp41 to inhibit T-cell receptor ( TCR ) complex activation . Here we examined whether this T-cell suppression strategy is unique to the HIV-1 gp41 . We focused on T-cell modulation by the gp21 fusion peptide ( FP ) of the Human T-lymphotropic Virus 1 ( HTLV-1 ) , a Deltaretrovirus that like HIV infects CD4+ T-cells . Using mouse and human in-vitro T-cell models together with in-vivo T-cell hyper activation mouse model , we reveal that HTLV-1’s FP inhibits T-cell activation and unlike the HIV FP , bypasses the TCR complex . HTLV FP inhibition induces a decrease in Th1 and an elevation in Th2 responses observed in mRNA , cytokine and transcription factor profiles . Administration of the HTLV FP in a T-cell hyper activation mouse model of multiple sclerosis alleviated symptoms and delayed disease onset . We further pinpointed the modulatory region within HTLV-1’s FP to the same region previously identified as the HIV-1 FP active region , suggesting that through convergent evolution both viruses have obtained the ability to modulate T-cells using the same region of their fusion protein . Overall , our findings suggest that fusion protein based T-cell modulation may be a common viral trait .
The mutual evolutionary pressure between viruses and their hosts has driven viruses to adopt various immune evasion mechanisms [1–4] . Many evasion strategies of enveloped viruses , such as antigen presentation antagonism and glycan shielding , can be mediated by their fusion glycoproteins ( reviewed in [5] ) . One of the most studied glycoproteins in this aspect is HIV’s gp41 , which aside from its crucial role in virus-cell membrane fusion [6 , 7] , was shown to inhibit T-cell activity . This was proposed to occur during the fusion process using several membrane interacting segments [8–10] , including the fusion peptide ( FP ) [11 , 12] ( reviewed in [9] ) . This strategy of modulating the immune response during membrane fusion has only been reported for HIV , although other enveloped viruses infect T-cells through membrane fusion as well [13–16] . We hypothesized that other human enveloped viruses might share HIV’s strategy of immune suppression . To this aim we examined the immune modulatory ability of the human T-lymphotropic virus-1 ( HTLV-1 ) , which exploits CD4+ T-cells as its primary target cell population [17] . As both HTLV-1 and HIV-1 are members of the retroviridae family they share a common ancestor and similar genomic architecture [18 , 19] . Their envelope proteins are similarly structured and are composed of two non-covalently bound subunits , gp46/gp21 in HTLV and gp120/gp41 in HIV , which bind cellular receptors and initiate fusion , respectively [20 , 21] . Both viruses utilize several proteins to interfere with T-cell activity and manipulate the anti-viral immune response ( 23–25 ) . HTLV’s p12 and p8 promote the proteosomal degradation of MHC-I and downregulate TCR complex signaling , respectively [22] while HIV’s Nef and Vpu downregulate MHC-I from the cell surface and promote internalization and degradation of CD4 in infected cells [23 , 24] . Additionally , HTLV-1 has been previously reported to harbor an immunosuppressive domain ( ISD ) within its envelope transmembrane subunit gp21 that is conserved between different retroviral envelope proteins [25] . The ISD that is concealed by the envelope’s surface subunit [26 , 27] , has been reported to inhibit T-cell proliferation [25] , to be crucial for viral infection in vivo [27] and to support tumor cells immune escape [26 , 28 , 29] . Suppression of TCR induced activation by HIV is well characterized and was shown to occur by targeting several TCR complex components via gp41 in the membrane [8 , 9 , 11 , 30] . A membranotropic region of HTLV-1 gp21 is the FP that is concealed within the envelope complex . Following binding of the surface subunit to the cellular receptor , a conformational change exposes the FP leading to its insertion into the plasma membrane and to fusion with the host cell [31 , 32] . Therefore , we decided to focus on the FP region as a possible immune suppressor of TCR activation in the membrane . In this study we utilized in-vitro and in-vivo assays including T-cell proliferation and an experimental autoimmune encephalomyelitis ( EAE ) mouse model to investigate the ability of the HTLV-1 gp21 FP to interfere with T-cell activity . We reveal that the HTLV FP inhibits T-cell activation downstream of the TCR complex in contrast to the HIV FP that specifically targets the TCRα subunit . Moreover , the HTLV FP markedly reduced manifestation of an in-vivo EAE mouse model . Downregulation of T-cell activity was associated with reduced expression and secretion of Th1-specific cytokines and an elevated expression and secretion of Th2-specific cytokines . This transition in cytokine pattern was correlated to a decreased expression of T-bet and an elevated expression of Gata3 , Th1- and Th2- specific transcription factors respectively . Interestingly , the HIV FP had no effect on both T-bet and Gata3 expression levels . This study suggests that in addition to its role in fusion , the HTLV FP interferes with T-cell activation by downregulating the type 1 anti-viral immune response , consequently leading to an elevated type 2 response . Overall , these findings reveal that like HIV , HTLV-1 adopted a similar strategy of immune suppression by it fusion protein , pointing to a possible prevailing trait of human T-cell viruses .
To examine whether other viruses can utilize their FPs to interfere with T-cell activity we initially investigated the immunosuppressive ability of the HTLV FP on primary C57BL/6J mMOG ( 35–55 ) -specific T-cells upon activation by antigen presenting cells ( APCs ) . We compared this activity to the well characterized HIV FP and to the bovine leukemia virus ( BLV ) and Jembrana disease virus ( JDV ) FPs . BLV and JDV are HTLV and HIV equivalents in cattle , respectively ( Table 1 ) . The HTLV FP was found to inhibit T-cell proliferation with equal potency to that of HIV’s FP and significantly stronger than the BLV FP . The JDV FP showed no inhibitory activity ( Fig 1A ) . The HTLV FP was not toxic up to 4-fold higher than the concentrations used in this study ( S1A Fig ) , even when viability was measured following 72 hours incubation of cells with the peptide ( S1B Fig ) . T-cells can be activated in-vitro either directly through TCRα and β by antigen presentation , downstream to TCRα and β using antibodies against CD3 and CD28 or downstream to the entire TCR complex using the PKC activator PMA together with the Ca+2 ionophore Ionomycin [8 , 9] . To examine where in the TCR signaling cascade the HTLV FP exerts its inhibitory activity , we activated T-cells using either APCs , CD3 and CD28 antibodies or PMA and Ionomycin . The HTLV FP inhibited T-cell proliferation induced at all three levels of activation with equal potency , while inhibition by the HIV FP that specifically targets the TCRα subunit , decreased significantly when activation was downstream of TCRα and β ( Fig 1B ) , as previously reported [11] . This indicates that in contrast to HIV-1’s FP , the HTLV FP does not inhibit T-cell activation by targeting the TCR complex . Following the previous results we tested HTLV FP specificity by assessing its inhibitory activity on activated macrophages . Primary mouse bone marrow derived macrophages ( BMDM ) were isolated , grown and stimulated using LTA , LPS , or PAM3CSK4 , toll like receptor ( TLR ) 2/6 , 4/4 , and 2/1 ligands , respectively . The effect of HTLV FP treatment on TNFα and IL6 secretion was measured by ELISA . The HTLV FP had no effect on cytokine secretion from primary mouse BMDM ( S2 Fig ) , demonstrating that the peptide selectively inhibits T-cell activation . To further characterize the inhibitory mechanism of the HTLV FP , we examined its effect on the expression level of several Th1 and Th2 specific genes that are transcribed upon T-cell activation [33 , 34] . C57BL/6J mMOG ( 35–55 ) -specific primary T-cells were activated using APCs . RNA was extracted 24hr following activation and mRNA levels were determined using RT-qPCR . The HTLV FP reduced the mRNA levels of the Th1-specific genes IFNG , LTA and the Th1 key mediator STAT4 [35 , 36] ( Fig 2A ) . On the other hand , the HTLV FP elevated the mRNA levels of the Th2-specific genes IL4 and IL10 ( Fig 2A ) . Yet , Tumor necrosis factor α ( TNF-α ) , that is expressed by both subsets [37] , was not affected ( Fig 2A ) . To determine whether the observed changes in gene expression can be observed at the protein level , we performed ELISA for selected cytokines . C57BL/6J mMOG ( 35–55 ) -specific primary T-cells were activated using APC and supernatants were collected 24hr following activation . The HTLV FP inhibited IFN-γ secretion , elevated IL4 secretion and had no effect on TNF-α secretion from activated T-cells ( Fig 2B ) , further corroborating our RT-qPCR results . These findings suggest that HTLV-1 might utilize its FP to restrict the T-cell antiviral immune response by downregulation of the Th1 and upregulation of the Th2 responses . As the HTLV FP was shown to inhibit mMOG ( 35–55 ) -specific primary T-cell activation in-vitro ( Fig 1A and 1B ) by downregulating their Th1 response ( Fig 2 ) , we examined inhibition of pathogenic MOG ( 35–55 ) -specific T-cells in-vivo by the HTLV FP . We tested this in an EAE model , which is a widely used mouse model that mimics chronic MS in humans [38 , 39] and is considered a CD4+ Th1-mediated autoimmune disease [40 , 41] . We performed an initial experiment in which C57BL/6J mice were immunized with MOG35-55/CFA for EAE induction and were either treated with a single dose of HTLV FP ( 1mg/kg ) or vehicle . Clinical manifestation of EAE for vehicle-treated mice was first observed at 8 days post immunization ( DPI ) , reaching a severe disease at 10 DPI , and was accompanied with a substantial loss of weight ( S3A and S3B Fig ) . Moreover , clinical severity was correlated to reduced locomotion as a result of hind limb ataxia or paralysis ( S1 and S2 Movies ) . In contrast , HTLV FP treated mice showed only mild clinical symptoms that were first observed at 11 DPI and were followed only by minor weight fluctuations ( S3A and S3B Fig ) . Additionally , most of the HTLV FP treated mice exhibited normal locomotory behavior throughout the experiment ( S3 and S4 Movies ) . As disease manifestation in vehicle treated mice was relatively severe , experiment was terminated at 14 DPI due to institutional animal care and use committee ( IACUC ) limitations and requirements . In order to examine whether the HTLV FP sequence is crucial for its inhibitory activity we synthesized a scrambled HTLV FP peptide ( HTLV Scr ) , consisting of the same amino acid composition and length as the HTLV FP ( Table 1 ) . The effect of both peptides on mMOG ( 35–55 ) -specific primary T-cell activation was compared . The HTLV FP inhibited both T-cell proliferation and IFN-γ secretion with higher potency than the HTLV Scr ( Fig 3A and 3B ) , demonstrating that the HTLV FP sequence is critical for its inhibitory activity . We then performed an additional EAE experiment in which mice were treated with a single dose of HTLV FP ( 1mg/kg ) , HTLV Scr ( 1mg/kg ) or vehicle . EAE clinical signs of vehicle and HTLV Scr treated groups ascent between 11 to 16 DPI , a period during which the HTLV FP treated mice showed only mild clinical symptoms and weight loss ( Fig 3C and 3D ) . Moreover , most of the HTLV FP treated mice exhibited better locomotory behavior than the HTLV Scr treated mice throughout the experiment ( S5 and S6 Movies ) . As disease manifestation was milder compared to the previous experiment , we were able to monitor animals for a longer period of time . In order to determine whether the reduction in EAE severity upon HTLV FP treatment actually results from downregulation of pathogenic MOG35-55-reactive T-cells , spleens were harvested at 26 DPI , cultured ex-vivo , and stimulated using MOG35-55 . Stimulation with MOG35-55 resulted in a T-cell proliferative response that was significantly lower in HTLV FP treated spleenocytes compared to HTLV Scr treated spleenocytes ( Fig 3E ) . In addition , HTLV FP treatment resulted in significantly lower IFN-γ secretion and significantly higher IL4 secretion compared to both vehicle and HTLV Scr treated groups ( Fig 3F and 3G ) . These results demonstrate that the HTLV FP modulates antigen-specific T-cell activation in-vivo leading to a downregulation of Th1 and upregulation of Th2 responses . As HTLV-1 is a T-cell infecting human pathogen [17] and since in this study we show that the HTLV FP inhibits T-cell activation in mice both in vitro and in vivo , we aimed to determine whether this inhibition would apply to human T-cells as well . Hence , human peripheral T lymphocytes were isolated from Peripheral blood mononuclear cells ( PBMCs ) , cultured ex-vivo and activated using CD3 and CD28 antibodies . The effect of HTLV FP treatment on secretion of the T-cell activation marker IL2 was measured by ELISA , as well as the Th1- and Th2-specific cytokines IFN-γ and IL10 , respectively . HTLV FP treatment resulted in a significant reduction in IFN-γ and IL2 secretion and an elevation in IL10 secretion , while treatment with HTLV Scr had no effect on T-cell activation ( Fig 4 ) . These results demonstrate that the modulatory activity of the HTLV FP is not limited to mouse cells or to cells that recognize a certain antigen and further emphasize its sequence specificity . To determine whether the transition in cytokine pattern driven by the HTLV FP is indicative of a Th1 to Th2 transition we examined the expression of Th1 and Th2 specific transcription factors , T-bet and Gata3 respectively . C57BL/6J mMOG ( 35–55 ) -specific primary T-cells were activated using APCs following HTLV FP treatment . RNA was extracted 24hr following activation and mRNA levels were determined using RT-qPCR . HTLV FP treatment resulted in a reduced TBX21 ( T-bet ) expression and elevated Gata3 expression ( Fig 5A and 5B ) . We next examined the expression of these genes at the protein level via FACS analysis . C57BL/6J mMOG ( 35–55 ) -specific primary T-cells were activated using APCs following either HTLV FP or HIV FP treatment , collected 0 , 24 , 48 and 72 hours following activation and stained for T-bet and Gata3 . Initially , we gated on T-bet expressing lymphocytes ( S5A Fig ) . Since our mMOG ( 35–55 ) -specific primary T-cells express basal level of T-bet that is elevated upon activation , we focused on the activated subset of lymphocytes ( S5B Fig ) . The HTLV FP reduced T-bet expression 24 and 48 hours following activation , while the HIV FP had no effect on T-bet expression ( Fig 5C and 5D ) . However , after 72 hours no difference was observed ( Fig 5E ) , though T-bet expression of activated cells diminished in comparison to 24h and 48h ( S6 Fig ) . When gating on Gata3 expressing cells ( S7 Fig ) , we found that the HTLV FP elevated Gata3 expression 24 , 48 and 72 hours following activation while the HIV FP had no effect on Gata3 expression ( Fig 5F–5H ) . Taken together , these results suggest that HTLV FP administration downregulates the Th1 response leading to a more Th2-like response . In order to detect the active segment within the HTLV FP , three peptides , designated HTLV FP5-13 , HTLV FP9-22 and HTLV FP14-22 ( Table 1 ) , were synthesized based on the network protein sequence ( NPS ) secondary consensus prediction method [42] ( Fig 6A ) . The HTLV FP5-13 peptide encompasses the helical predicted section of the HTLV-1 FP ( S8 Fig ) and is located at the same region previously found to be active segment of the HIV FP , both at the 5–13 amino acid section [12] . The HTLV FP9-22 peptide consists of two consecutive repeats of the known GxxxG-like dimerization motif [43 , 44] , while the HTLV FP14-22 peptide contains only one . These HTLV FP derived peptides were then examined for their ability to inhibit T-cell proliferation . This analysis revealed that both HTLV FP1-33 and FP5-13 are significantly more active compared to the FP9-22 and FP14-22 ( Fig 6B ) . In order to compare the ability of the HIV FP5-13 and HTLV FP5-13 to suppress the induction of T-cell activation at different steps of the TCR signaling cascade , C57BL/6J mMOG ( 35–55 ) -specific primary T-cells were activated using either APC , CD3 and CD28 antibodies or PMA and Ionomycin . Similar to the HTLV FP , the HTLV FP5-13 inhibited all three levels of activation ( Fig 6C ) . Peptides were not toxic to T-cells at concentrations used in this study ( S1A Fig ) . In contrast , the activity of the HIV FP5-13 significantly diminished when T-cells were activated using CD3 and CD28 antibodies or PMA and Ionomycin ( Fig 6C ) . The secondary structures of the peptides were then determined in a membrane mimetic environment using circular dichroism ( CD ) ( Fig 6D ) and analyzed for structure proportions using CDNN . Both the HTLV FP and HTLV FP5-13 exhibited an α-helical structure while the HTLV FP9-22 and HTLV FP14-22 were found to be random coils ( Table 2 ) . This result suggests that the loss of inhibitory activity by the HTLV FP9-22 and FP14-22 might be due to loss of secondary structure . Next we aimed to determine whether T-cell inhibition by the HTLV FP5-13 occurs within the membrane . For that purpose we utilized a D-enantiomer form of the HTLV FP5-13 ( designated HTLV FP5-13D ) as interactions of peptides and proteins in the membrane have been shown to be chirality independent [45–47] . We activated our C57BL/6J mMOG ( 35–55 ) -specific primary T-cells with APCs and examined their proliferative response following treatment with HTLV FP5-13 and HTLV FP5-13D . Both peptides inhibited T-cell proliferation with the same potency ( Fig 6E ) , suggesting that their active site is within the membrane . Overall , these results indicate that the HTLV FP5-13 is the immune modulatory segment of the HTLV FP and that it acts as an α-helix in the membrane .
HIV-1 utilizes the FP of its gp41 fusion protein to downregulate T-cell activation [11] . Yet , it is unknown whether this ability is shared by other viruses . We utilized the FP of the CD4+ T-cell infecting retrovirus HTLV-1 to explore whether other viral FPs might exhibit immune modulating properties . We reveal that the HTLV-1 gp21 FP is a potent suppressor of T-cell activation , demonstrated by its ability to reduce the onset of the EAE multiple sclerosis ( MS ) model in mice . Comparing both HIV-1 and HTLV FPs reveals that in contrast to HIV-1 , the HTLV FP’s inhibitory effect occurs downstream of the TCR complex and is associated with a decrease in Th1 responses and an elevation in Th2 responses . Activation of T-cells can be induced in-vitro by antigen presentation either through the TCR itself , downstream of the TCR using CD3 and CD28 antibodies or downstream from the entire TCR complex via PMA and Ionomycin [8 , 9] . Here we found that in contrast to the HIV FP , the HTLV FP does not exert its inhibitory effect by targeting the TCR complex . This raises a question regarding the specificity of HTLV-1’s FP inhibitory activity to T-cells , yet , the peptide had no effect on the activation level of mouse primary bone marrow derived macrophages , supporting its specificity T-cells . In order to elucidate HTLV FP’s mechanism of action , we examined its effect on mRNA expression and cytokine secretion levels of several Th1 and Th2 specific genes that are transcribed upon T-cell activation [33 , 34] . The HTLV FP inhibited expression and secretion of Th1-specific cytokines that are crucial for the T-cell antiviral response [48 , 49] , yet , elevated Th2-specific cytokines [50 , 51] . These findings suggest a shift in the Th1/Th2 balance promoted by the HTLV FP . A Th1 response evokes cell-mediated immunity , therefore crucial for the eradication of intracellular pathogens such as viruses . On the other hand a Th2 response controls humoral immunity and evokes antibody responses , which govern the elimination of extracellular pathogens [52] . Skewing the Th1/Th2 balance towards a Th2 response is beneficial for viral persistence within its host and several viruses have been shown to utilize this immune modulation strategy [53 , 54] . This is also evident by the findings that some antiviral compounds exert their activity by increasing the Th1 response [55] . Studies indicate that HTLV-1 infection induces IFN-γ production that is aimed to eradicate the virus [56 , 57] . As the HTLV FP is exposed during membrane fusion [32] , our data suggests that the virus might have the ability to utilize this gp21 region to antagonize this initial anti-viral immune response , thus to better persist within its host . This is in line with evidence showing that HTLV-1 harbors Th1 suppressing factors [58] . Additionally , the ISD that was previously identified within retroviral envelope proteins [25] , including the HTLV-1 gp21 , has been reported to decrease Th1 and increase Th2 cytokine production [59] . As in the case of the ISD , HTLV FP treatment inhibited IL2 secretion [60] . The ISD is proposed to induce this immune modulation by elevation of cAMP concentration and by inhibition of protein kinase C ( PKC ) [59 , 61] . In this study we show that the HTLV FP significantly inhibits T-cell activation through PMA ( PKC activator ) and Ionomycin [11] , indicating some similarities between the HTLV FP and the ISD derived peptide mechanisms of action . Yet , additional work is required in order to elucidate the exact mechanism of HTLV FP immune suppression . Th1- and Th2-responses are orchestrated by the specific transcription factors T-bet and Gata3 , respectively [62–64] . Therefore , changes in the expression level of these proteins seen in this study further suggest a shift in the Th1/Th2 balance . Yet , though significantly elevated , the fold change of Gata3 expression levels in activated versus non-activated cells was low compared to T-bet as seen by FACS analysis . This suggests that the HTLV FP is not directly elevating Gata3 expression but rather inhibiting T-bet . Since Gata3 expression is negatively regulated by T-bet expression and vice versa [63 , 64] , it is plausible that the remarkably sharp decrease in T-bet expression is sufficient to cause a prolonged elevation in Gata3 expression . This experimental evidence suggests that by downregulating T-bet expression the HTLV FP disrupts the Th1/Th2 balance , thus elevating Gata3 expression . Yet , other T-cell subsets such as T regulatory cells ( Treg ) are infected by HTLV-1 [56 , 65] . Interestingly , although the development and function of Treg is governed by the master regulator FoxP3 [66] , this T-cell subset has been shown to express Gata3 as well [67] . Yet , in contrast to its inhibitory effect on T-bet , Gata3 has been shown to be crucial for Treg function and homeostasis by enhancing FoxP3 expression [68–70] as reviewed in [71] . Interestingly , an HTLV-1 derived factor has been shown to induce CCR4 expression through induction of Gata3 in Treg , promoting T-cell migration and proliferation [72] . Since cell-free HTLV-1 virions are poorly infectious [73 , 74] the virus mainly spreads from cell to cell through virological synapses [75] . Thus , promoting T-cell migration is of crucial importance for viral transmission and propagation as it allows infected cells to infiltrate healthy tissues eventually supporting transmission from infected to non-infected cells . Overall , HTLV-1 might utilize its FP to modulate the activity of different T-cell subsets through elevation of Gata3 expression in order to support its persistence within hosts . As the HTLV FP was shown to downregulate Th1-responses in-vitro , we examine its effect on the induction of a Th1-mediated autoimmune disease in-vivo . EAE is induced by immunization with myelin peptides , such as MOG ( 35–55 ) , emulsified in CFA , yet , it can be induced by adoptive transfer of myelin-specific CD4+ Th1 cells into naïve recipient mice as well [76–82] . In addition , Stat4 and T-bet , transcription factors in the Th1 differentiation pathway , have been shown to be essential for EAE induction [81 , 83–85] . In this study , we demonstrate that the HTLV FP downregulates the transcription of Stat4 and T-bet mRNA , as well as inhibiting mMOG ( 35–55 ) -specific primary T-cell activation in-vitro , making EAE an ideal in-vivo model . Here we demonstrate that inhibition of EAE clinical signs by the HTLV FP specifically results from downregulation of pathogenic MOG35-55-reactive T-cells . Interestingly , in humans a small percentage of HTLV-1 infected individuals develop a chronic neuroinflammatory disease termed HTLV-1-associated myelopathy/tropical spastic paraparesis ( HAM/TSP ) [86] that has some pathological similarities to MS . In both cases , lymphocytes that infiltrate the CNS secrete pro-inflammatory cytokines such as IFN-γ and TNF-α [87–89] that can induce neurotoxicity at high concentrations [90 , 91] . This results in spinal lesions that initially lead to muscular weakness in the lower limbs [87] . Additionally , soluble TNF-α receptor has been suggested as a common marker for monitoring the progression of these diseases [88] that are both characterized by Th1 predominance [41 , 87] . In light of our results , the fact that only a small percentage of HTLV-1 infected individuals eventually develop HAM/TSP might be partially attributed to the neuro-protective nature of the HTLV FP , demonstrated here by its ability to specifically downregulate IFN-γ secretion from pathogenic T-cells in EAE and to alleviate and delay disease onset . Next , we aimed to identify the immune modulatory region within the HTLV FP . NPS secondary structure prediction analysis [42] predicted the HTLV FP5-13 to be alpha helical . This region was found to be alpha helical in CD analysis and inhibited T-cell activation in contrast to the non-alpha helical regions of the HTLV FP . As we assume that the HTLV FP functions in the membrane , it is likely that an alpha helical structure would support its activity as interactions within the membrane are typically mediated by helix-helix interactions [92–94] through dimerization motifs [95–97] , such as GxxxG [30 , 98–102] . Hence , we concluded that the 5–13 region is the active segment within the HTLV FP . Interestingly , this is the same region previously identified as HIV-1’s FP active segment [12] . Since HIV-1 and HTLV-1 FPs completely differ in sequence , it seems that possibly through convergent evolution both viruses have obtained the ability to downregulate T-cell activation using the same region of their fusion protein . The membrane environment holds unique characteristics that allow protein-protein interactions that would not be energetically favored in soluble environment [45] , such as interactions between L- and D-enantiomer proteins [47] . Such chirality-independence has been utilized for inhibition of HIV cell-cell fusion by the HIV FP D-enantiomer [46] , inhibition of T-cell activation by gp41’s loop derived peptides [103] and for inhibition of Tar receptor mediated chemotaxis in E . coli [47] . In these cases , the L- and D-enantiomers had the same potency . Since FPs are membranotropic regions of viral fusion proteins [104] , and as HIV’s FP was specifically shown to target the transmembrane domain of the TCR within the membrane [11] , we utilized a D-enantiomer form of the HTLV FP5-13 . As both L- and D- peptides were found to inhibit T-cell proliferation with the same potency , we concluded that their active site is situated within the membrane . This is in line with evidence showing that upon binding of the envelope’s surface subunit gp46 to its cellular receptors , the HTLV-1 gp21 FP is exposed and then binds and perturbs the membrane eventually leading to fusion [32 , 105] . In summary , our findings indicate that FP mediated T-cell immunosuppression is not unique to HIV , and suggest that it might be a more widespread immune evasion strategy utilized by viruses . Yet , it seems that the HTLV-1 and HIV-1 FPs exert their inhibitory activity on T-cells through different mechanisms thus demonstrating that there are distinct manners by which T-cell activation can be overcome . Our findings demonstrate that the HTLV FP has the capacity to downregulate Th1-mediated antiviral immune response , suggesting that the virus might utilize it for T-cell modulation during fusion . Yet , additional studies using HTLV-1 particles or HTLV-infected cells are required in order to be more conclusive . As the HTLV-1 gp21 FP is known to mediate membrane fusion [106] , its ability to modulate T-cell activity highlights how viruses have evolved to alter different cellular processes with limited repertoire of proteins .
C57Bl/6J mice were purchased from Jackson Laboratories ( Bar Harbor , ME , USA ) . All mice were 2–3 month-old when used in the experiments . Antigen-specific T-cells were selected in-vitro [107] from primed lymph node cells derived from C57Bl/6J mice that had been immunized 9 days before with antigen ( 100μg myelin peptide , MOG35-55 ) emulsified in complete Freund’s adjuvant ( CFA ) containing 150μg Mycobacterium tuberculosis ( Mt ) H37Ra ( Difco Laboratories , Detroit , MI ) . T-cells were maintained in-vitro in medium containing 500 ml RPMI Ca/Mg + heat inactivated FCS ( 10% final ) + 5 ml 200 mM L-Glu ( 2 mM final ) +5 ml 100 M Na pyruvate ( 1 mM final ) + 5 ml Pen Strep antibiotics + 5 ml Eagle-MEM ( Biological Industries , Ref 01-340-1B ) + interleukin-2 ( IL-2 ) , with alternate stimulation with the antigen every 14 days . Mouse Femora and tibiae BM cells were isolated from C57Bl/6J mice and cultured in RPMI medium containing FBS ( 10% ) , L-glutamine ( 1% ) , sodium pyruvate ( 1% ) , Pen-strep ( 1% ) , and 10 ng/ml recombinant CSF-1 ( Peprotech ) . At day 3 , half the medium was replaced , and on day 7 , cells were used for in vitro assay , in which 2*105 cells were plated per well in a 24-well plate . Human peripheral T lymphocytes were isolated from whole blood of healthy adult donors by dextran sedimentation and Ficoll ( Sigma ) gradient separation followed by depletion of B cells using nylon wool column ( Unisorb ) , to which B cells were adsorbed . Cells were incubated in a complete RPMI growth medium ( 500 ml RPMI Ca/Mg + heat inactivated FCS ( 10% final ) + 5 ml 200 mM L-Glu ( 2 mM final ) +5 ml 100 M Na pyruvate ( 1 mM final ) + 5 ml Pen Strep antibiotics ) for more than 2 h , and then non-adherent cells were harvested and transferred to a new plate , resulting in ~90% CD3+ T lymphocytes . Cells were then used for in vitro assay , in which 105 cells were plated per well in a 96-well plate and activated using CD3 and CD28 antibodies . Peptides were synthesized using the F-moc solid phase method on Rink amide resin ( 0 . 65mmol/gr ) , as previously described [108] . The peptides were purified by reverse phase HPLC ( RP-HPLC ) to >95% homogeneity on a C4 or C2 column using a linear gradient of 20–70% acetonitrile in 0 . 1% trifluoroacetic acid ( TFA ) for 45 minutes . The peptides were subjected to ESI–MS ( electrospray ionization mass spectrometry ) analysis to confirm their composition . Antigen-specific T-cells were plated onto round 96-well plates in medium containing RPMI-1640 supplemented with 2 . 5% fetal calf serum ( FCS ) , 100 U/ml penicillin , 100 μg/ml streptomycin , 50μM β-mercaptoethanol , and 2mM L-glutamine . Each of the 96 wells contained 104 T-cells , 5x105 irradiated ( 25 gray ) antigen presenting cells ( APC ) , and 5μg/ml of MOG p35-55 . In addition , the relevant peptide was added . In order to exclude interaction between the examined peptides and the MOG p35-55 antigen , we added the MOG p35-55 antigen to the APC in a test tube , and in a second test tube we added the examined peptides to the T-cells . After 1 hour , we mixed the APC with the T-cells and incubated them for 48h in a 96 well round bottom plate . Then T-cells were pulsed with 1μCi ( H3 ) thymidine , with a specific activity of 5 . 0 Ci/mmol , for 24 hours , and ( H3 ) thymidine incorporation was measured using a 96-well plate beta-counter . The mean cpm ± SD was calculated for each quadruplicate . In several experiments , cells were activated with pre-coated CD3 and CD28 antibodies ( LEAFTM purified anti mouse clones 145-2-C11 and 37 . 51 , respectively from Biolegend ) at final concentration of 2μg/ml , or 50ng/mL of PMA ( phorbol 12-myristate 13-acetate ) together with 1μM of ionomycin ( Sigma Chemical Co , Israel ) . Antigen-specific T-cells were plated onto round 96-well plates in medium containing RPMI-1640 supplemented with 2 . 5% fetal calf serum ( FCS ) , 100 U/ml penicillin , 100 μg/ml streptomycin , 50μM β-mercaptoethanol , and 2mM L-glutamine . Each of the 96 wells had a final volume of 200μl and contained 104 T-cells , 5x105 irradiated ( 25 gray ) spleen cells , as APC , and 5μg/ml of MOG p35-55 . In addition , the relevant peptide was added . Each treatment was made with quadruplicate . Analysis of IFN-γ , IL-4 and TNFα secretion was performed by ELISA 24 hours after cell activation according to standard protocols from R&D systems . Mouse Femora and tibiae BM cells were collected and cultured in RPMI medium containing FBS ( 10% ) , L-glutamine ( 1% ) , sodium pyruvate ( 1% ) , Pen-strep ( 1% ) , and 10 ng/ml recombinant CSF-1 ( Peprotech ) . On day 7 , cells were stimulated by either ( i ) LTA , ( ii ) LPS , or ( iii ) PAM3CSK4 ( 1 μg/ml ) , in the presence of the HTLV FP at 10μM . Media was collected either 5 hours following activation ( for TNF-α detection ) or 22 hour following activation ( for IL-6 detection ) and secretion levels were determined according to standard protocols from R&D systems . Human peripheral T lymphocytes were isolated from whole blood of healthy donors and were incubated in a complete RPMI growth medium ( 500 ml RPMI Ca/Mg + heat inactivated FCS ( 10% final ) + 5 ml 200 mM L-Glu ( 2 mM final ) +5 ml 100 M Na pyruvate ( 1 mM final ) + 5 ml Pen Strep antibiotics ) . Cells were activated using CD3 and CD28 antibodies , in the presence of relevant peptides at 10μM . Media was collected 48 hours following activation and secretion of IL2 and IFN-γ was determined according to standard protocols from R&D systems . Antigen-specific T-cells were plated onto round 12-well plates ( 106 cells/ well ) and activated with 5x105 irradiated ( 25 gray ) APC and 5μg/ml of MOG p35-55 in the presence or absence of relevant peptides . Cells were washed with PBS , blocked ( 5% Donkey serum , 2% BSA and 0 . 1% Triton in PBS ) and fixed with 4% Paraformaldehyde ( PFA ) 24 hour following activation . Cells were then stained with Gata3-FITC and T-bet-APC fluorochrome-labeled monoclonal mouse antibodies ( purchased from Miltenyi Biotec ) according to Miltenyi Biotec protocols . Samples were then collected using LSR-II flow cytometer and analyzed with FlowJo cell analysis software . EAE was induced in 9-week-old wild type and homozygous C57BL/6 female mice ( Harlan Laboratories Israel/ Weizmann Institute animal facilities ) by injecting a peptide comprising residues 35–55 of mouse myelin oligodendrocyte glycoprotein ( MOG35–55; PolyPeptide Laboratories , Strasbourg , France ) . Mice were injected subcutaneously above the lumbar spinal cord with 100 μl of emulsion containing 200 μg/mouse of the encephalitogenic peptide in complete Freund’s adjuvant ( BD-Difco ) enriched with 250 μg/mouse of heat-inactivated Mycobacterium tuberculosis ( BD-Difco ) at 0 days post-induction ( DPI ) . The HTLV FP was dissolved in PBS and added to the emulsion ( 1mg/kg ) . Pertussis toxin ( Enzo Life Sciences ) at a dose of 300 ng per mouse was injected intraperitoneally immediately after the encephalitogenic injection , as well as at 0 DPI . EAE disease was scored using a five-point grading with 0 for no clinical disease; 1 , tail weakness; 2 , paraparesis ( incomplete paralysis of one or two hindlimbs ) ; 3 , paraplegia ( complete paralysis of one or two hindlimbs ) ; 4 , paraplegia with forelimb weakness or paralysis; 5 , moribund or dead animals . The mice were examined daily . Aliquots of 104 cells were distributed onto a 96-well plate in the presence of 1 . 25–40μM of the relevant peptides for 16 or 72 hours . Following incubation , XTT reaction solution ( benzene sulfonic acid hydrate and N-methyl dibenzopyrazine methyl sulfate , mixed in a proportion of 50:1 ) , was added for 2 hours . Optical density was read at 450-nm wavelength . The percentage of toxicity was calculated relative to the control , 104 cells in medium with no peptide added . Samples sizes were chosen with adequate statistical power on the basis of past experience and literature . Differences between group means were tested using student’s t-test when the experiment contained two groups , or one-way ANOVA ( followed by a Tukey post hoc test ) when the experiment contained more than two groups . P< 0 . 05 was considered significant . Analyses were done using GraphPad Prism ( data analysis software ) version 6 . 05 . ( *P≤0 . 05 , **P≤0 . 01 , ***P≤0 . 001 ) . Results are displayed as mean ±SEM . All experiments involving animals were conducted under the approval of the IACUC of the Weizmann Institute , permit numbers: 26980516–3 ( in-vitro T-cell activation assays ) and 29650816–3 ( Experimental Autoimmune Encephalomyelitis ) , which were performed in accordance to their relevant guidelines and regulations . The facility where this research was conducted is accredited by AAALAC and has an approved Office of Laboratory Animal Welfare ( OLAW ) Assurance ( #A5005-01 ) . The facility operates according to the guide for the care and use of laboratory animals 8th edition by the national research council . All procedures were conducted by trained personnel under the supervision of veterinarians and all invasive clinical procedures were performed while animals were anesthetized . Human peripheral T lymphocytes were isolated from whole blood of healthy adult donors that provided written informed consent under the regulations and authorization of the Weizmann Institutional Review Board , Project 247–2 . | In order to successfully infect and persist in their hosts , viruses utilize multiple strategies to evade the immune system . HIV utilizes membrane interacting regions of its envelope protein , primarily used to fuse with its target cells , to inhibit T-cell activation . Yet , it is unknown whether this ability is shared with other viruses . In this study we examined the T-cell inhibitory activity of the envelope protein of the Human T-lymphotropic virus 1 ( HTLV-1 ) , which infects T-cells . We focused on a functionally conserved region of HTLV’s and HIV’s fusion proteins , the fusion peptide ( FP ) . Here , we reveal that HTLV’s FP inhibits the activity of T-cells in-vitro and in a T-cell hyper activation model in mice . This inhibition is characterized by downregulation of the T-cell Th1/type 1 response , leading to an elevated T-cell Th2/type 2 response observed by transition in the profiles of mRNA , cytokines and regulatory proteins . Furthermore , we demonstrate that the HTLV and HIV FPs inhibit T-cell activation at different levels of the signaling cascade . Although the HTLV FP’s mechanism of T-cell inhibition differs from the HIV’s FP , our findings suggest that FP mediated immune evasion might be a trait shared between different viruses . | [
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] | 2018 | The HTLV-1 gp21 fusion peptide inhibits antigen specific T-cell activation in-vitro and in mice |
Immunity to a sand fly salivary protein protects against visceral leishmaniasis ( VL ) in hamsters . This protection was associated with the development of cellular immunity in the form of a delayed-type hypersensitivity response and the presence of IFN-γ at the site of sand fly bites . To date , there are no data available regarding the cellular immune response to sand fly saliva in dogs , the main reservoirs of VL in Latin America , and its role in protection from this fatal disease . Two of 35 salivary proteins from the vector sand fly Lutzomyia longipalpis , identified using a novel approach termed reverse antigen screening , elicited strong cellular immunity in dogs . Immunization with either molecule induced high IgG2 antibody levels and significant IFN-γ production following in vitro stimulation of PBMC with salivary gland homogenate ( SGH ) . Upon challenge with uninfected or infected flies , immunized dogs developed a cellular response at the bite site characterized by lymphocytic infiltration and IFN-γ and IL-12 expression . Additionally , SGH-stimulated lymphocytes from immunized dogs efficiently killed Leishmania infantum chagasi within autologous macrophages . Certain sand fly salivary proteins are potent immunogens obligatorily co-deposited with Leishmania parasites during transmission . Their inclusion in an anti-Leishmania vaccine would exploit anti-saliva immunity following an infective sand fly bite and set the stage for a protective anti-Leishmania immune response .
Leishmaniasis is a vector-borne neglected disease transmitted exclusively by the bite of infected phlebotomine sand flies . An estimated 350 million people are at risk for leishmaniasis with an annual incidence of 2 million cases and a loss of 2 , 357 , 000 disability-adjusted life years [1] , [2] , [3] . Leishmaniasis presents with multiple clinical manifestations including cutaneous , mucocutaneous , diffuse and visceral ( VL ) infections . The latter is responsible for 59 , 000 deaths a year , a parasitic disease statistic surpassed only by malaria [4] . There are two types of VL , anthroponotic and zoonotic . Zoonotic VL ( ZVL ) is wide spread and occurs in Latin America , Northern Africa , Southern Europe and areas of the Middle East and Asia [5] , [6] , [7] . The dog is considered the main reservoir of ZVL [5] , [8] . Indeed , there is a clear association between a high rate of infection in dogs and an increased risk of human disease [3] . An anti-Leishmania canine vaccine would not only protect dogs from a fatal disease but could have a considerable effect on reducing human infections . Understandably , the search for vaccine candidates for leishmaniasis has focused on Leishmania antigens [9] . Several promising first , second and third generation vaccine candidates produced variable levels of protection in animal models [9] . Still there are no available human vaccines for any form of leishmaniasis and LEISHMUNE , a canine vaccine based on a Leishmania infantum chagasi fucose-mannose-ligand glycoprotein fraction [10] , is only licensed in Brazil [11] . Although LEISHMUNE has demonstrated some efficacy against canine visceral leishmaniasis ( CVL ) it has limitations that include safety issues and the difficulty to serologically distinguish asymptomatic from vaccinated dogs [11] , [12] . Sand fly salivary proteins are inoculated at the site of parasite deposition during transmission by infective sand fly bites . Thus , immunogenic salivary proteins that influence the immune status of the host can potentially have consequences on the outcome of leishmaniasis . This hypothesis has been corroborated in rodent models where immunization with sand fly saliva or a distinct salivary protein conferred protection against both cutaneous and visceral leishmaniases [13] , [14] , [15] , [16] , [17] . This protection has been correlated with a Th1 response against salivary antigens characterized by the presence of IFN-γ at the bite site [14] , [17] . The above puts forward a solid argument for the use of salivary gland proteins of appropriate vector sand fly species to improve the efficacy and immunogenicity of Leishmania-based vaccine candidates . In this study , immunization of dogs with two novel salivary proteins from Lutzomyia longipalpis , the only established vector of L . i . chagasi in Latin America , resulted in a strong systemic and local Th1 cell-mediated immunity that was efficiently recalled by sand fly bites and adversely affected parasite survival in vitro . To our knowledge , this is the first demonstration that specific immunity to a salivary protein can be elicited in a natural host of the Leishmania parasite and an endorsement for the use of salivary proteins , neglected thus far , as novel antigens in anti-Leishmania vaccines .
In rodent models , cellular immunity characterized by a Th1 delayed type hypersensitivity ( DTH ) response to sand fly salivary proteins protected animals from cutaneous and visceral leishmaniases [16] , [17] . Up to date , there is no information pertaining to the presence and nature of cellular immunity to sand fly saliva in dogs , the main reservoirs of ZVL [5] . Here , we explored the early kinetics of anti-saliva immunity in dogs following exposure to bites of Lu . longipalpis , the vector of L . i . chagasi in Latin America . Seven of nine beagles showed specific anti-saliva antibodies one week after the third exposure to sand fly bites ( Figure 1A ) . Apart from a single dog with a mixed IgG2/IgG1 antibody response , these animals showed a strong IgG2 response and no IgG1 ( Figure 1A ) . To investigate whether dogs exposed to sand fly bites develop a DTH response , we measured the skin induration at the bite site following each sand fly exposure . Following the second exposure , a small induration was observed in the 7 dogs that produced significant levels of antibodies ( Figure 1B ) . This was characterized by a localized erythema , swelling and thickening of the skin . The intensity and duration of the observed induration was significantly increased following the third sand fly exposure lasting up to 96 h following sand fly bites ( Figure 1B ) . No reaction was observed in naive animals after the first exposure . Histological analysis of the induration site 48 h following the first and second exposure shows minimal inflammation characterized by scattered perivascular lymphocytes and rare neutrophils within the superficial dermis ( Figure 1C ) . A dramatic increase in the cellular infiltrate was noted 48 h following the third exposure , characterized by a prominent thickening of the epidermis and multifocal infiltrates of lymphocytes , macrophages and eosinophils ( Figure 1D ) . The timing of the reaction as well as the nature of the infiltrate established that sand fly saliva induces a DTH reaction in the skin of dogs after repeated exposures . Immunization with a single DTH inducing salivary molecule conferred protection from cutaneous and visceral leishmaniases in rodent models [16] , [17] . To identify the salivary molecules responsible for the generation of a DTH response in dogs , we screened 35 DNA plasmids encoding secreted salivary proteins of Lu . longipalpis [18] using a novel approach we termed reverse antigen screening ( RAS ) . Five dogs were exposed to sand fly bites then injected individually with up to 38 samples including three controls ( Figure 2A ) . Out of the 35 salivary DNA plasmids only four ( LJL143 , LJM17 , LJM11 and LJL138 ) induced a macroscopic DTH response 48 h after challenge defined by a strong erythema with or without palpable induration in at least three of five dogs ( Figure 2B ) . This DTH response was highly specific as shown in Figure 2C . Since induration is an important indicator of cellular recruitment , we focused on LJL143 and LJM17 that produced the strongest combined responses in at least 3 dogs ( Figure 2B , D ) . Histological analysis of injection sites 48 h post-challenge showed that LJL143 and LJM17 induce a typical DTH response characterized by considerable lymphocytic infiltration with few macrophages ( Figure 2E ) . This recruitment was comparable to that of SGH ( positive control ) and was absent for LJM111 ( negative control ) as well as the vector control and PBS ( data not shown ) . Analysis of the DTH site for expression of selected cytokines associated with Th1 or Th2 responses showed an appreciable induction of IL-12 , a moderate expression of IFN-γ and low expression of TGFβ for LJM17 ( Figure 2F ) . LJL143 showed a mixed response with IL-12 and IL-4 expression ( Figure 2F ) . In comparison , SGH showed considerable expression levels of the four investigated cytokines ( Figure 2F ) . There was minimal to no expression of any of the cytokines tested in negative controls ( Figure 2F ) . To validate the specificity of the observed antigenic properties of LJL143 and LJM17 plasmids , 300 ng of purified recombinant proteins ( Figure 3A ) were injected in the five dogs previously exposed to DNA plasmids and in two more dogs pre-exposed to sand fly bites alone . In addition , 300 ng of rLJM111 , a non-reactive sand fly salivary molecule , 300 ng of rTB179 , a non-related tick salivary protein ( negative controls ) and a pair of SGH ( positive control ) were simultaneously injected . A clear DTH response was observed 48 h following the injection of rLJL143 and rLJM17 . The DTH response was characterized by erythema with or without palpable induration ( Figure 3B ) and cellular infiltration ( Figure 3C ) comparable to those observed following the injection of DNA plasmids ( Figure 2C , E ) . As predicted , rLJM111 , rTB179 and PBS showed no erythema or induration ( Figure 3B ) . The absence of cellular infiltration was confirmed by histology for rLJM111 ( Figure 3C ) . It is worth noting that LJM111 remained non-reactive following the injection of the recombinant protein despite the fact that five dogs were pre-challenged with the DNA plasmid encoding that protein . It is well established that a Th1 cell-mediated immunity ( CMI ) , characterized by the production of IFN-γ , is critical for protection from Leishmania infection [19] . Using RAS , LJL143 and LJM17 were identified as vaccine candidates following the induction of a DTH response in dogs previously exposed to Lu . longipalpis bites ( Figures 2 and 3 ) . Subsequently , naïve dogs were immunized with LJL143 and LJM17 using DNA plasmids followed by a recombinant protein boost . Both LJL143 and LJM17 induced a strong humoral response ( Figure 4A ) that was efficiently recalled by a viral vector boost ( Figure 4A , B ) . Furthermore , IgG2 was the predominant IgG subclass in immunized dogs ( Figure 4B ) . Following the viral vector boost , PBMC from control or LJL143- and LJM17-immunized dogs were isolated and stimulated with recombinant proteins or SGH . PBMC from LJL143-immunized dogs produced over 3600 pg/ml and 1200 pg/ml of IFN-γ following stimulation with rLJL143 and SGH , respectively ( Figure 4C ) . In LJM17-immunized dogs , IFN-γ production was also high at 1813 pg/ml and 446 pg/ml after stimulation with rLJM17 and SGH , respectively ( Figure 4C ) , Moreover , IFN-γ production was specific to the recombinant proteins since stimulation of PBMC from LJL143-immunized dogs with rLJM17 produced background levels of IFN-γ and vice versa ( Figure 4C ) . LJL143- and LJM17-immunized dogs produced a strong Th1 systemic humoral and cellular response to the corresponding salivary proteins ( Figure 4 ) . To determine whether this immunity is maintained under natural conditions , these dogs were exposed to sand fly bites , the natural route of transmission . A distinct focal cellular infiltration of CD3+ cells and a few scattered macrophages was observed 48 h following the bites from 20 or five uninfected flies in dogs immunized with LJM17 or LJL143 ( Figure 5A , Figure S1 ) . RNA from biopsies taken at the bite site was used to determine the expression of key cytokines 48 h after sand fly bites . Following bites by 20 uninfected flies , LJM17-immunized dogs showed a polarized Th1 immune response characterized by a significant induction of IFN-γ and IL-12 ( P<0 . 03 ) with low levels of IL-4 and the regulatory cytokine TGF-β ( Figure 5B ) . This expression profile was also observed in response to 5 uninfected sand fly bites . Interestingly , LJL143-immunized dogs induced a different profile when challenged with 20 compared to 5 sand flies . TGF-β was the dominant cytokine induced following 20 bites ( P<0 . 03 ) with low expression levels for IFN-γ , IL-12 and IL-4 ( Figure 5B ) . In contrast , LJL143-immunized dogs challenged with 5 sand flies produced five times the expression levels of IFN-γ compared to those observed in controls and low levels of IL-4 expression ( Figure 5B ) . To assess whether altered feeding behavior of infected sand flies ( caused by parasite blockage of the stomodeal valve ) influences the nature of the recall response , LJL143- and LJM17-immunized dogs were simultaneously exposed to the bites of 10 sand flies infected with L . i . chagasi . Forty-eight h following challenge with infected sand flies , both groups of dogs produced a strong focal cellular infiltration ( Figure S2 ) and a cytokine profile similar to that of uninfected sand flies ( Figure 5C ) . Analysis of PBMC one week after sand fly challenge showed that the frequency of CD3+ cells producing IFN-γ following stimulation with the appropriate recombinant proteins was considerably larger in LJL143- and LJM17-immunized dogs and showed a significantly higher mean fluorescence intensity ( MFI ) ( P<0 . 05 ) compared to cells from control dogs ( Figure 5D ) . Further analysis showed that CD3+ CD4+ T cells were the source of IFN-γ in immunized dogs ( Figure 5E ) . Immunization of dogs with the salivary proteins LJL143 and LJM17 resulted in a strong focal and systemic CMI against sand fly bites , the natural route of Leishmania transmission . To test whether this immunity has an adverse effect on Leishmania parasites , macrophages from PBMC of LJL143- and LJM17-immunized or control dogs were infected with L . i . chagasi in vitro . The addition of SGH-stimulated autologous lymphocytes from LJL143- and LJM17-immunized dogs resulted in a 74% and 82% ( P<0 . 0001 ) reduction of infection in macrophages , respectively ( Figure 6 ) . In contrast , the percent of infected macrophages was not altered by the addition of SGH-stimulated autologous lymphocytes from PBMC of control dogs .
We propose the inclusion of salivary antigens of the sand fly Lu . longipalpis , the only established vector of L . i . chagasi in Latin America , as a component of anti-Leishmania vaccines against CVL . This is based on the 1 ) induction of a strong Th1 cellular immune response , the hallmark of protection against leishmaniasis , in dogs immunized with two novel salivary proteins from the vector Lu . longipalpis; 2 ) efficient recall of this Th1 immunity in the skin at the bite site of infected sand flies , important when considering that Leishmania are co-deposited with salivary proteins during probing and feeding; 3 ) evidence that immunity to these salivary proteins has an adverse effect on L . i . chagasi . From a repertoire of 35 salivary molecules from Lu . longipalpis , RAS correctly identified two salivary proteins , LJL143 and LJM17 , as inducers of CMI in dogs . It is important to note that the antigens identified in this study differ from those eliciting immune responses in rodent models [15] , [16] , [17] . LJM19 , a salivary molecule from Lu . longipalpis , conferred protection from visceral leishmaniasis through induction of a strong DTH response in hamsters [16] but induced a weak response in dogs ( Figure 2 ) . This may be due to the restriction imposed by the repertoire of the major histocompatibility complex class II molecules present in different animals . Therefore , one can expect that immunogenic antigens will vary in different animals . This demonstrates the power of RAS in large laboratory animals such as dogs for the rapid screening of antigens inducing CMI . For this reason , the RAS technique represents a significant improvement in the selection of appropriate vaccine candidates whereby it permits screening of populations targeted by a vaccine , including dogs and humans , for antigens inducing a cellular response . In dogs pre-exposed to sand fly bites , LJL143 and LJM17 induced a distinct cellular infiltration characterized by CD3+ lymphocytes , macrophages and notably , the absence of eosinophils . This differs from the response to natural bites that produced a mixed response including a substantial number of eosinophils and suggests that LJL143 and LJM17 are not likely to induce an allergic response typically associated with exposure to insect saliva . This was further supported by the lack of an allergic response in immunized dogs following challenge by up to 35 sand fly bites , an important consideration in the selection of salivary vaccine candidates . Dogs immunized with LJL143 or LJM17 showed a consistent systemic adaptive immune response indicative of a Th1 profile . This was demonstrated by the dominance of IgG2 antibodies throughout the study period and the substantial production of IFN-γ by CD3+CD4+ T cells stimulated with SGH or recombinant proteins . Considering that beagles are out bred , this consistency is encouraging and bodes well for the use of these antigens in the field . A Leishmania vaccine has a better chance of success under field conditions if it generates a rapid immune response in the skin following the deposition of a relatively low dose of parasites [20] by an infective sand fly . This immune response should be specific to an antigen delivered during the bite , be it Leishmania antigens or salivary proteins that are co-injected into the bite site . Sand fly bites , uninfected and infected , elicited a distinct and comparable cellular recruitment mediated by lymphocytes at the bite site in dogs immunized with either LJL143 or LJM17 . The cytokine profile , assessed 48 h post bites , was characterized by the presence of IFN-γ and IL-12 and the absence of IL-4 in LJM17-immunized dogs challenged with 5 , 10 or 20 sand fly bites . This profile was similar in LJL143-immunized dogs challenged with 5 sand flies . However , the response in these dogs to 10 and 20 bites was low with the exception of TGFβ . The presence of high levels of TGFβ , a regulatory cytokine , suggests that this may be a regulatory mechanism to dampen an earlier burst of IFN-γ production . Thus , the differences observed in cytokine levels may be explained by different kinetics of the immune response to the two molecules combined with the different number of bites received . Indeed , PBMC of LJL143-immunized dogs produced high levels of IFN-γ following stimulation with SGH . We hypothesized that anti-saliva immunity if generated against a Th1 polarizing antigen can potentially have an adverse effect on the parasites deposited together with saliva . In vitro , macrophages infected with L . i . chagasi efficiently killed the parasites following the addition of autologous T cells from LJL143- and LJM17-immunized dogs stimulated by SGH showing a 74% and 82% reduction of infection in macrophages respectively . This demonstrates a clear effect of anti-saliva immunity on Leishmania parasites . How this anti-saliva immunity plays out in vivo remains to be fully elucidated . It could act through an initial indirect killing of Leishmania in situ , acceleration of specific anti-Leishmania immunity or a combination of both [14] , [15] , [16] , [17] . Acceleration of anti-Leishmania immunity can occur as a result of a more rapid processing of killed parasites or through the effect of an altered cytokine milieu on the nature and commitment of cells recruited to the site by anti-saliva immunity . In conclusion , induction of immune correlates of protection in dogs immunized with salivary proteins from Lu . longipalpis is a strong predictor that these molecules will be an advantageous addition to an anti-Leishmania canine vaccine . Sand fly salivary molecules have been neglected as a component of anti-Leishmania vaccines despite their reported immunogenicity in rodent models and humans [16] , [17] , [21] , [22] , and their unique advantage as a permanent feature of natural transmission . Salivary proteins can provide a novel source of antigens that may complement or synergize promising Leishmania-based vaccines providing an independent arm of the immune response that could be of value in the control of leishmaniasis .
One to two year old female beagles ( Marshall Farms ) were housed at the NIH animal facility following the Animal Care and User Committee guidelines . Four to seven day old Lutzomyia longipalpis female sand flies ( Jacobina colony ) were used in experiments . Salivary glands were sonicated , centrifuged at 10 , 000 g for 3 min and used immediately . L . i . chagasi ( BA262 strain ) promastigotes were cultured as previously described [16] . DNA plasmids were constructed and purified as previously described [16] , filter sterilized and stored at −70°C . Specific Lu . longipalpis salivary cDNA containing a histidine tag at the 3′ end were cloned into the VR2001-TOPO expression vector [23] . HEK-293F cells were transfected and supernatants collected at 72 h . Expressed proteins were purified by HPLC ( DIONEX ) using a HITRAP Chelating HP column ( GE HealthCare ) charged with Ni2SO4 0 . 1M . Proteins were eluted using an imidazole gradient , dialyzed against PBS and stored at −70°C . Canarypoxviruses from ALVAC vectors expressing the LJL143 ( vCP2389 ) or LJM17 ( vCP2390 ) were generated as previously described [24] . PUREVAX ferret distemper vaccine ( Merial ) was used as control . Sand flies were fed through a chick skin membrane on a suspension of 3×106 L . i . chagasi procyclic promastigotes/ml of heparinized blood containing penicillin and streptomycin . Flies with mature infections were used for transmission . Dogs were sensitized three times weekly with 20 sand flies placed in custom made chambers and secured to the shaved side of the neck with a Velcro collar for 10 min . For assessing the skin immune response , five and 20 uninfected and 10 infected sand flies were placed in small vials and hand-held to marked sites on the shaved belly of dogs for 10 min . Dogs were handled without any chemical restraint . The diameter of erythema and the induration ( elevation over 1 mm ) on the skin of dogs were measured 48 h post-injection . 6mm skin punch biopsies ( Acuderm ) were cut in two . One half was fixed in neutral-buffered formaldehyde ( 10% formalin ) for histology and the other was stored in RNALATER ( Sigma-Aldrich ) for RNA extraction . Formalin fixed skin biopsies were embedded in paraffin . Four µm sections were processed for staining with hematoxylin and eosin ( H & E ) and Luna's stain . Additional sections were labeled with anti-CD3 and Mac387 . Sections were incubated with primary rabbit anti-human CD3 ( Dako , Glostrup , Denmark ) and mouse anti-human Mac387 ( Serotec , Raleigh , NC ) at 1∶300 and 1∶400 respectively for 1 h . For CD3 , a secondary biotinylated goat anti-rabbit antibody was used at 1∶500 for 15 min ( Vector Laboratories , Burlingame , CA ) and detected by R . T . U . VECTASTIN Elite ABC reagent ( Vector ) and DAB chromagen . For Mac387 , a secondary antibody labeled with Mach 4 HRP Polymer ( Biocare Medical , Concord , CA ) was used following the manufacturer's recommendation and detected by DAB chromagen . Dogs pre-exposed to sand fly bites were anesthetized and randomly injected intradermally with 40 µL of 35 salivary DNA plasmids ( 20 ug each ) or recombinant proteins ( 300 ng ) diluted in PBS and separated from each other by ∼15mm . Controls included PBS , a pair of Lu . longipalpis SGH ( 1 µg ) , 20 µg of control vector or 300 ng of rTB179 , a tick recombinant salivary protein . At day 0 , five dogs per group were immunized intradermally ( ID ) in the ear pinna with 500 µg of LJL143 DNA plasmid ( group one ) , LJM17 DNA plasmid ( group two ) and VR2001 control vector ( group three ) . The dogs were given a second and third immunization at days 14 and 28 with 500 µg of the appropriate DNA plasmids injected in both thighs intramuscularly ( IM ) coupled to electroporation ( Sphergen ) . At day 42 , the dogs were immunized ID with 100 µg of rLJL143 for group 1 , rLJM17 for group 2 or BSA for group 3 together with 300 µg CpG ODN in 20% EMULSIGEN ( MVP laboratories ) . At day 210 , the dogs received a vaccine booster ( IM ) in the left quadriceps using 108 pfu of recombinant canarypoxvirus expressing LJL143 or LJM17 for group two , and PUREVAX control canarypoxvirus for group three . Microtiter plates ( MAXSORP , Nunc ) were coated with 100 µl of 2 µg/ml rLJM17 or rLJL143 or Lu . longipalpis SGH ( five salivary gland pairs/ml ) overnight at 4°C . Plates were blocked with 4% fetal bovine serum ( FBS ) in PBS-TWEEN 0 . 05% at RT for 2 h . A100 µl of dog sera ( 1∶50 ) was incubated for 1 h at 37°C . After three washes with PBS-T , sheep anti-dog IgG ( 1∶5000 ) , goat anti-dog IgG1 ( 1∶500 ) or sheep anti-dog IgG2 ( 1∶500 ) phosphatase alkaline-conjugated antibodies ( Bethyl Laboratories Inc . ) were incubated for 1 h at 37°C . Plates were developed with p-nitrophenylphosphate ( Sigma-Aldrich ) and absorbance was read at 405nm using a SPECTRAMAX Plus ( Molecular Devices ) . PBMC were isolated as previously described [25] . A million cells per well of a 96 well-plate ( Research & Diagnostic systems ) were cultured for 72 h in 500 µl of RPMI supplemented with 20% heat-inactivated FBS , 2mM L-glutamine , 100 units/ml penicillin and 100 µl/ml streptomycin ( cRPMI ) with either two pairs of SGH , ConA ( 4 µg ) , rLJM17 ( 4 µg ) or rLJL143 ( 4 µg ) . IFN-γ production was measured from supernatants using QUANTIKINE ELISA ( Research & Diagnostic Systems ) . Absorbance ( 405 nm ) was measured using SPECTRAMAX Plus ( Molecular Devices ) . Isolation of RNA from skin and first strand cDNA synthesis was performed as previously described [16] . DNA was amplified with specific dog primers ( Operon Biotechnologies , Inc . ) and probes ( Roche Diagnostics ) for IFN-γ , IL-12 , IL-4 and TGF-β as previously described [16] . The expression level of genes of interest was normalized to GAPDH levels . Two million PBMC were cultured in a ml of cRPMI for 18 h in the presence of either ConA ( 4 µg ) , rLJM17 ( 20 µg ) or rLJL143 ( 20 µg ) at 37°C in 5% CO2 . Cells were incubated with 2 µM final concentration of GolgiStop ( BD Pharmingen ) for 4 h , washed with PBS-5% FBS , and blocked with PBS-10% FBS for 30 min at 4°C . Cells were stained with FITC-labeled anti-CD3 ( CA17 . 2A12 , BD Pharmingen ) and ALEXA FLUOR 647-labeled anti-CD8 ( YCATE55 . 9 , BD Pharmingen ) for 30 min at 4°C , washed twice , fixed and permeabilized with CYTOFIX/CYTOPERM Plus ( BD Pharmingen ) and stained with PE-labeled anti-IFN-γ ( CC302 , BD Pharmingen ) . A minimum of 200 , 000 cells were acquired using a FACSCalibur flow cytometer ( BD Biosciences ) and analyzed with CELLQUEST Pro software . Canine monocyte-derived macrophages were prepared as previously described [26] . PBMC collected from immunized dogs were plated in 8 well chamber slides ( BD FALCON ) at 5×106 cells per ml and incubated for 30 min at 37°C with 5% CO2 . Non-adherent cells ( autologous T cells ) were removed and cultured separately . After 5 d of culture , macrophages were infected with stationary phase L . i . chagasi at a 5∶1 parasites to macrophage ratio for 2 h at 37°C- 5% CO2 . Non-internalized parasites were removed by gentle washing . Infected macrophages were cultured for 72 h in the presence of autologous lymphocytes at a 2∶1 lymphocyte to macrophage ratio and stimulated with Lu . longipalpis SGH ( 2 pairs ) or ConA ( 4 µg ) . The percentage of infected macrophages was assessed by microscopic examination of Giemsa-stained preparations . Statistical significance was tested with the two-tailed student's t-test using Graph Pad 4 . 0 Prism Software . | Leishmaniasis is a neglected infectious disease with a global distribution encompassing 88 countries , 350 million people at risk , and an annual incidence of 2 million cases . Leishmaniasis is a vector-borne disease transmitted by sand fly bites where parasites are co-deposited with saliva into the wound . Our group has demonstrated that distinct molecules in the saliva of various sand fly species drive an immune response that protects experimental rodent models from self-healing cutaneous and fatal visceral leishmaniasis . Here we show for the first time that dogs , natural reservoirs of visceral leishmaniasis , develop a strong immune response to two salivary proteins from the natural vector sand fly . Blood from immunized dogs contained immune cells that produced molecules ( IFN-γ ) typically associated with protection from Leishmania parasites . This response efficiently recruited appropriate immune cells to the site of sand fly bites in the skin and had an adverse effect on Leishmania parasites in an experimental assay . These findings suggest that inclusion of these salivary molecules in anti-Leishmania canine vaccines would enhance their efficiency in protecting dogs from visceral leishmaniasis . A successful anti-Leishmania canine vaccine would not only protect dogs from a fatal disease but could have a considerable effect on reducing human infections . | [
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] | 2009 | Sand Fly Salivary Proteins Induce Strong Cellular Immunity in a Natural Reservoir of Visceral Leishmaniasis with Adverse Consequences for Leishmania |
Male Drosophila flies secrete seminal-fluid proteins that mediate proper sperm storage and fertilization , and that induce changes in female behavior . Females also produce reproductive-tract secretions , yet their contributions to postmating physiology are poorly understood . Large secretory cells line the female's spermathecae , a pair of sperm-storage organs . We identified the regulatory regions controlling transcription of two genes exclusively expressed in these spermathecal secretory cells ( SSC ) : Spermathecal endopeptidase 1 ( Send1 ) , which is expressed in both unmated and mated females , and Spermathecal endopeptidase 2 ( Send2 ) , which is induced by mating . We used these regulatory sequences to perform precise genetic ablations of the SSC at distinct time points relative to mating . We show that the SSC are required for recruiting sperm to the spermathecae , but not for retaining sperm there . The SSC also act at a distance in the reproductive tract , in that their ablation: ( 1 ) reduces sperm motility in the female's other sperm-storage organ , the seminal receptacle; and ( 2 ) causes ovoviviparity—the retention and internal development of fertilized eggs . These results establish the reproductive functions of the SSC , shed light on the evolution of live birth , and open new avenues for studying and manipulating female fertility in insects .
Females of many animal species store sperm after mating , in specialized organs of the reproductive tract [1] , [2] . In addition to sperm , seminal proteins are transferred to females during mating . In Drosophila , seminal proteins perform multiple functions that advance the male's reproductive interests . These functions include promoting sperm storage , decreasing the female's receptivity to subsequent courters , and stimulating egg production and ovulation [3] , [4] . Female reproductive interests do not necessarily coincide with those of their mates . A coevolutionary arms race can therefore ensue [5] . In Drosophila , the coevolutionary pressure on female reproductive functions is apparently quite strong: seminal fluid decreases female lifespan [6] and does so to a greater extent when females are experimentally prevented from coevolving with males [7] . Of course , males and females do share some reproductive interests , such as successful production of offspring , and therefore evolutionary pressure also exists to coordinate their reproductive functions [8] . Although it has been appreciated that molecular interactions—both antagonistic and cooperative—between male and female products are key to understanding insect fertility and its evolution , much more progress has been made in characterizing the composition and functions of seminal fluid [3] than in characterizing female reproductive secretions . A potentially major role of female secretions is in sperm storage . Insect females typically have multiple specialized sperm storage organs , to which sperm are recruited after copulation and in which sperm can be maintained for weeks or , in the case of queens of social insect species , years [9] . Female Drosophila melanogaster have three such organs located at the anterior of the uterus: a long tubular seminal receptacle and a pair of spermathecae . Each spermatheca is mushroom shaped , with a duct that extends from the uterus to a cuticular cap . The seminal receptacle houses up to 80% of stored sperm , whereas the spermathecal caps house the remainder [1] , [10] . Each spermathecal cap is lined with large glandular cells containing prominent secretory organelles that open into the lumen where sperm are stored [11] , [12] . Despite considerable divergence in sperm-storage organ anatomy , such cells are found lining or adjacent to the spermathecae of a wide range of insects [9] . The position of these spermathecal secretory cells ( SSC ) suggested they might have a role in sperm storage , yet direct in vivo evidence has been lacking [9] , [12] , [13] . Indeed , the most direct evidence for a role in sperm storage comes from a 1975 study of boll weevils with surgically removed spermathecal glands: sperm did not enter the spermatheca in such females , although because sperm motility was greatly diminished it cannot be concluded whether the glands are necessary just for sperm viability or also for recruitment into storage [14] . The SSC might also contribute to sustained levels of egg production and fertilization , by secreting proteins that alter female reproductive physiology or by modulating the activities of male seminal proteins . Sex peptide , a seminal protein , binds to sperm tails and during storage is gradually cleaved to an active form that stimulates egg production [15] . Sex peptide is also required for release of sperm from storage [16] . In the female , the sex peptide receptor is expressed in neurons that mediate a decrease in courtship receptivity and an increase in egg laying after mating , and it is required for these changes [17] . The sex peptide receptor is also expressed in the SSC [17] , suggesting that sex peptide acts directly on these cells . Other genes expressed specifically in the SSC have not been comprehensively identified , although some such genes have emerged from transcriptional profiling studies of: ( 1 ) somatic tissues of males versus females [18] , ( 2 ) dissected whole spermathecae [11] , [19] , [20] , and ( 3 ) virgin versus mated females [21]–[23] . One notable class of genes revealed by these studies is those encoding proteases . Protease-encoding genes are over-represented among those induced in females by mating [21]–[23] , and among those highly expressed in the spermathecae [11] , [19] , [20] . Proteases are especially interesting due to their potential for interactions with seminal proteins . Such interactions could be antagonistic , for example by degradation of seminal proteins , or cooperative , for example by regulated cleavage of seminal proteins to their active forms [8] . Male-female coevolution would be expected to lead to rapid divergence of female-expressed protease-encoding genes , and indeed such genes show elevated rates of coding-sequence evolution in several species [19] , [24]–[30] . To address how the SSC contribute to female postmating physiology , we have developed tools that allow us to manipulate these cells in a precise spatiotemporal manner . To develop these tools , we first identified the regulatory regions controlling transcription of two protease-encoding genes that are expressed exclusively in the SSC . The gene CG17012 , which encodes a serine-type endopeptidase , is expressed exclusively in the SSC , in both unmated and mated females [18] . We hereafter refer to CG17012 as Spermathecal endopeptidase 1 ( Send1 ) . CG18125 , which also encodes a serine-type endopeptidase , is expressed exclusively in the SSC and its transcription is upregulated 76-fold 3–6 h after mating [27] . We hereafter refer to CG18125 as Spermathecal endopeptidase 2 ( Send2 ) . Identifying these genes' regulatory regions allowed us to create drivers and reporters for manipulating and monitoring the SSC . We show that the SSC are required to recruit sperm to the spermathecae , but not for maintaining them there . Moreover , we show that the SSC act at a distance in the reproductive tract , in that they are required for maintaining sperm motility in the seminal receptacle . We also show action at a distance with respect to egg laying , in that females lacking SSC are ovoviviparous . Fertilized eggs develop , and indeed sometimes hatch into larvae , inside the uterus . This phenotype is reminiscent of two species of Drosophila that retain developing eggs , D . sechellia and D . yakuba [31] . Our results therefore not only reveal the functions of a poorly understood reproductive tissue , but also shed light on the evolution of live birth .
For each of the SSC-expressed genes , Send1 and Send2 , we created a driver carrying ∼4 kb of upstream sequence and ∼4 kb of downstream sequence , flanking the coding sequence of the yeast transcriptional activator GAL4 , which can activate transgene expression in Drosophila through its cognate UAS sequence [32] . We also created GAL4-independent reporters by cloning a subfragment of the Send1 or Send2 upstream sequence in front of the coding sequence of a fast-maturing , nuclear-localized , red-fluorescent protein ( DsRed . T4 . NLS , hereafter called nRFP ) [33] . Send1-GAL4 drives expression of a membrane-bound green fluorescent protein ( GFP ) ( UAS-mCD8-GFP ) specifically in the SSC of virgin and mated females ( Figure 1A–1D ) . GFP expression driven by Send1-GAL4 is visible by 20 h posteclosion and increases in intensity by day 4 . Send2-GAL4 drives GFP expression in the SSC of mated females only , as early as 3 h postmating ( Figure 1E–1H ) . Send1-nRFP and Send2-nRFP recapitulate expression of the respective endogenous genes as well ( Figure 1I–1K ) . The potential for redundancy among spermathecae-expressed serine proteases is high . Protease-encoding genes are over-represented among those induced in females by mating [21]–[23] , and among those highly expressed in the spermathecae [11] , [19] , [20] . Moreover , some spermathecae-expressed serine proteases are recently duplicated paralogs with high levels of amino acid identity . Consistent with redundancy , we did not observe any effects on female fecundity or fertility when we used Send1-GAL4 to drive RNAi efficiently targeting Send1 or Send2 transcripts ( see Materials and Methods ) . To fully understand how SSC-expressed proteases contribute to female reproductive function might require the simultaneous knockdown or knockout of many genes . As an alternative approach , we used the Send1-GAL4 and Send2-GAL4 drivers to ablate the SSC at different times , thereafter eliminating their ability to secrete any products into the spermathecal lumen . As the SSC are terminally differentiated adult cells , we used the drivers to express a modified form of the apoptosis-promoting protein Hid ( HidAla5 ) that is effective in postmitotic cells [34] . We assayed the timing and effectiveness of cell-death induction using the nRFP reporters , as well as direct visualization of apoptotic cells by TUNEL ( Materials and Methods ) . For all assays with Send1-GAL4 , we mated females on day 4 posteclosion , to ensure that the majority of their SSC had been ablated . Note that occasionally a few SSC remain at day 4 . We use this lack of complete penetrance to our advantage because it creates some mosaic females who have one of the two spermathecae lacking SSC whereas the other still has SSC . With Send2-GAL4 , the SSC are clearly apoptotic as early as 31 h postmating . By 43 h postmating , the majority of SSC are dead ( Figure S1 ) . We examined sperm storage in SSC-ablated and control females by individually mating them with males expressing protamine-GFP , which renders sperm heads fluorescent green [35] . Males transfer between 3 , 000 and 4 , 000 sperm during mating , of which only ∼25% are stored . Of the stored sperm , approximately 65% to 80% reside in the seminal receptacle and the rest reside in the spermathecae [1] , [10] . Mortality of stored sperm remains quite low for about 2 wk [36] . In control +/UAS-hidAla5; Sp/+; Send1-nRFP/+ females , sperm are stored in the spermathecae and seminal receptacle within 1 h of mating , although sperm are also found in the uterus and occasionally the oviduct ( Figure 2A–2D ) . In their +/UAS-hidAla5; CyO , Send1-GAL4/+; Send1-nRFP/+ sisters , whose SSC were ablated prior to mating , sperm are also found in the seminal receptacle and uterus , and occasionally in the oviduct , but often are not present in the spermathecae ( Figure 2E–2H ) . Indeed , out of 17 SSC-ablated females , 16 had at least one empty spermatheca , and eight of these had both spermathecae empty . By contrast , no control female had even one empty spermatheca , and in only one case did one of the spermathecae contain fewer than ten sperm ( Table S1 ) . In cases of SSC-ablated females in which sperm were found in one of the spermathecae but not the other , the presence or absence of sperm correlated with the presence or absence of SSC in a mosaic female ( e . g . , Figure 2E ) . These results imply that the SSC are required to recruit sperm to the spermathecae . It was previously shown that glucose dehydrogenase , which is secreted from the proximal and distal ends of the spermathecal duct , promotes recruitment of sperm into the spermathecae [37] . We observed some cases in which sperm were present in the spermathecal duct leading to a spermathecal cap with no sperm ( e . g . , Figure 2H ) , but in most cases the ducts were empty of sperm as well . This result suggests that recruitment of sperm by the duct cells is largely dependent on SSC function . By 7 h postmating , nearly all remaining sperm in control females are in the seminal receptacle or spermathecae ( Figure 2I ) , as expected . By contrast , SSC-ablated females have sperm in their seminal receptacles , yet tend to lack sperm in the spermathecae ( Figure 2J; Table S1 ) . The lack of sperm in the spermathecae at 7 h suggests that sperm recruitment to the spermathecae is indeed impaired and not merely delayed . At 24 h postmating , sperm storage in control females appears very similar to that observed at 7 h postmating . In SSC-ablated females , however , sperm dynamics in the seminal receptacle are aberrant . Whereas in control females , sperm are found throughout the tubular receptacle ( Figure 2K ) , in many SSC-ablated females , sperm have lost motility and clumped together in one part of the receptacle , leaving the rest of it largely empty ( Figure 2L; Table S1; Videos S1 and S2 ) . This result suggests that the products of the SSC travel to , and act in , the seminal receptacle . Consistent with this inference , Anderson [38] found that females lacking entirely the spermathecae and female accessory glands lose fertility within a few days after mating . The loss of fertility is apparently caused by loss of motility of sperm stored in the females' seminal receptacles [38] . A similar conclusion was reached by Allen and Spradling [11] , who used a different mutation that causes loss of the spermathecae and accessory glands . Our results localize the source of at least one motility-maintaining factor to the SSC . At 6 to 9 d postmating , sperm storage in control females still appears very similar to that observed at 7 h or 24 h postmating ( Figure 2M–2P; Table S1 ) . Likewise , sperm storage at 6 to 9 d postmating in SSC-ablated females appears very similar to that observed in SSC-ablated females at 24 h postmating ( Figure 2Q–2T ) . Although rare females contain a few sperm in their spermathecae ( e . g . , Figure 2Q ) , most do not ( e . g . , Figure 2R–2T ) . As at 24 h postmating , clumps of sperm in the seminal receptacle are also seen in some females ( e . g . , Figure 2Q–2R; Table S1 ) . The existence of a few sperm in the spermathecae of some SSC-ablated females approximately 1 wk postmating suggests that the SSC are not required to retain sperm in the spermathecae once they have been stored there . However , as described above , there is a correlation between sperm recruitment to the spermathecae and the existence of residual , nonablated SSC . It could be that the same residual SSC function that recruited the sperm to the spermathecae is sufficient to retain them there . To test definitively whether the SSC are required to retain sperm in the spermathecae , we eliminated the SSC after sperm were stored in the spermathecae . We did so by ablating the SSC after mating using Send2-GAL4 in combination with UAS-hidAla5 . At 7 h postmating , sperm storage in control +/UAS-hidAla5; Send1-nRFP/+; MKRS/+ females does not appear different to that of their +/UAS-hidAla5; Send1-nRFP/+; Send2-GAL4/+ sisters ( Figure 3A–3B ) . As noted above , SSC ablation is complete in the latter females within one more day . If the SSC are required for long-term sperm retention in the spermathecae , then SSC-ablated females should lose the sperm they had stored in the spermathecae . However , this is not the case . At 6–8 d postmating , SSC-ablated females retain as many sperm in their spermathecae as do their control sisters ( Figure 3C–3D ) . Moreover , sperm clumping in the seminal receptacle is not observed in these SSC-ablated females , implying that whatever SSC products are required to maintain sperm motility need only be supplied up to or around the time of mating , not continually . Because females whose SSC are ablated prior to mating do not store sperm in their spermathecae and lose sperm motility in their seminal receptacles , we next asked whether this impaired sperm storage affects fecundity or fertility . Females with SSC ablated prior to mating lay as many eggs on days 1 to 3 postmating as their control sisters ( Figure 4A ) . However , after day 3 , their egg laying is significantly reduced ( Figure 4A ) . Notably , after day 3 an individual SSC-ablated female tends to lay vastly different numbers of eggs on successive days . Indeed , 10 out of 18 SSC-ablated females had one day in which 0 or 1 egg was laid , followed immediately by a day with greater than ten eggs laid . By contrast , only one out of 15 control females had any day in which 0 or 1 was laid . The alternation of low and normal levels of egg laying in SSC-ablated females suggests that the SSC play some role in either ovulation or oviposition . To determine which is the case , we dissected SSC-ablated females that had not laid an egg in the previous 24 h . Strikingly , SSC-ablated females are ovoviviparous: a large proportion of such females ( eight out of 16 ) had a late-stage embryo or live first-instar larva stuck in the uterus ( Figure 4B; Video S3 ) . This result implies a defect in ejecting eggs from the uterus ( oviposition ) rather than egg production and release ( ovulation ) . However , those females with stuck eggs did not appear to have a “log jam” of eggs in the oviduct , suggesting either: ( 1 ) that inability to eject a fertilized egg signals back to the ovary to halt or slow ovulation [39] , [40]; or ( 2 ) that ovulation is independently slowed by SSC loss . A simple , mechanical explanation for the stuck-egg phenotype is that the SSC produce a lubricant that coats the uterus , allowing eggs to pass easily . An alternative explanation is that products of the SSC are required before or around the time of mating to trigger cellular and physiological changes in the reproductive tract that are required for full reproductive maturity . Consistent with the latter explanation , females whose SSC have been ablated postmating , using Send2-Gal4 , do not show any difference from control sisters in the number of eggs laid on each of days 1 to 8 postmating ( Figure 4C ) . This result implies that proper egg laying after day 3 postmating requires SSC function earlier in adulthood . The earlier function could be the production of a secretion , such as a lubricant , that is long-lived . However , multiple lines of evidence support the existence of posteclosion and postmating developmental programs by which the female reproductive tract achieves full maturity [41] , [42] . The triggering of such a program by one or more SSC gene products could explain not only the egg-laying defect but also the loss of sperm motility in the seminal receptacle in females with Send1-driven , but not Send2-driven , ablation of the SSC . Work prior to ours had suggested several possible functions for the secretory cells of the spermathecae , including recruitment and maintenance of sperm , yet direct in vivo evidence was lacking because of the absence of tools for precisely manipulating these cells . In D . melanogaster , it had been observed that females lacking the spermathecae and accessory glands lose fertility , despite having normal seminal receptacles , but this effect could not be ascribed to any particular cell population within the missing organs [11] , [38] . Our cell-specific drivers enabled us to determine that the SSC contribute to reproductive function in multiple ways , some expected and some not . The SSC do indeed produce one or more products required for recruiting sperm into storage , although they are not required to maintain sperm in the spermathecae once recruited . In contrast , the SSC are not required for sperm to reach the seminal receptacle , but they are required to maintain sperm motility there , consistent with the lost fertility of females lacking spermathecae and accessory glands [11] , [38] . In addition to their action at a distance in the seminal receptacle , the SSC also act at a distance in sustaining egg laying . The impairment of egg laying in SSC-ablated females manifests as an unanticipated phenotype: ovoviviparity . SSC-ablated females retain fertilized eggs , which develop inside the uterus and , in some cases , hatch as larvae inside the mother . Our findings have relevance to two evolutionary patterns observed in the genus Drosophila . First , all Drosophila species that have been examined have a pair of spermathecae and a single seminal receptacle , yet there are at least 13 independent Drosophila lineages in which females use only the seminal receptacle to store sperm [43] . In species that do not store sperm in the spermathecae , the spermathecal caps are small and weakly sclerotized , but are surrounded by large cells that are presumably their SSC [43] . Our finding that the SSC act at a distance in the female reproductive tract might explain why these species retain their spermathecae , despite not using them to store sperm . Second , the ovoviviparity observed in SSC-ablated females suggests that transitions to live birth might require fewer evolutionary steps than once thought . In a surprising recent discovery it was found that two species of Drosophila are ovoviviparous: even when exposed to ample substrate for oviposition , females of D . sechellia and D . yakuba retain fertilized eggs , which develop internally , in contrast to those of all other examined Drosophila species , which are laid immediately after fertilization [31] . Our SSC-ablation results suggest that the Drosophila uterus is “preadapted” to support internal embryo development , in that eggs stuck there are capable of hatching into perfectly viable larvae . The genetic tools we have developed will be useful for further dissection of the molecular and evolutionary mechanisms underlying female reproductive function . Insect reproductive secretions are of particular interest because of their relevance to the fertility of agricultural pests and human disease vectors . To date , attention has focused on male secretions [44]–[47] , because of the far greater knowledge of male seminal proteins than of products of the female reproductive tract , but recent studies in malaria-vector mosquitoes have begun to counter this bias [48] . Reproductive secretions are also highly relevant to the study of beneficial insects , as evidenced by recent work characterizing the seminal-fluid and spermathecal-fluid proteomes of honey bees [49]–[51] . Increased knowledge of the regulation and functions of spermathecal secretions will add a new dimension both to insect-control efforts and to the maintenance of healthy breeding populations of agriculturally important insects .
P{w+mc = UAS-mCD8::GFP . L}LL5 ( referred to as UAS-mCD8-GFP in the text ) and w; P{w+mC = Cha-GAL4 . 7 . 4}19B P{w+mC = UAS-GFP . S65T}T2 ( referred to as Cha-GAL4 , UAS-GFP in the text ) fly lines were obtained from the Bloomington Drosophila Stock Center . The Canton-S fly line was obtained from Michelle Arbeitman [52] . The protamine-GFP fly line was obtained from John Belote and Scott Pitnick . The UAS-hidAla5 fly line was obtained from Hermann Steller . Virgin flies were collected within 6 h of eclosion and maintained in single-sex groups for 4 to 5 d before mating . All virgin female flies were mated with Canton-S , protamine-GFP or Cha-GAL4 , UAS-GFP males , in single pairs . Mated females were used only if copulation lasted at least 15 min . All flies were maintained on standard yeast-cornmeal-molasses medium at 25°C . The Send1-GAL4 construct contains ∼8 kb of genomic sequence surrounding Send1 ( coordinates 2 , 249 , 863–2 , 258 , 703 on Chromosome 2L ) , with the Send1 coding sequence precisely replaced with the coding sequence of GAL4 . Send2-GAL4 was similarly constructed and contains ∼8 kb of genomic sequence surrounding Send2 ( coordinates 14 , 341 , 694–14 , 350 , 575 on Chromosome 2L ) . Each Send-GAL4 cassette was inserted separately into the P-element transformation vector pP{whiteOut2} , which was provided by Jeff Sekelsky . Reporter constructs were made by PCR-amplifying genomic fragments from Send1 ( coordinates 2 , 255 , 054–2 , 255 , 684 ) and Send2 ( coordinates 14 , 346 , 671–14 , 347 , 347 ) and cloning each separately into pRed H-Stinger , which places the cloned fragment upstream of a minimal promoter and the coding sequence for DsRed . T4 . NLS [33] . Germline transformation of w1118 embryos was carried out by Rainbow Transgenics . RNAi-producing UAS-hairpin constructs were made for Send1 and Send2 by inserting inverted repeats into the P-element transformation vector pWIZ , a derivative of pUAST that separates the repeats by a small intron to facilitate cloning and enhance silencing [53] . For Send1 , a 518-bp fragment starting at position 291 of the coding sequence was amplified by PCR , using primers with added SpeI restriction sites at their 5′ ends . The SpeI-digested PCR product was cloned into the NheI site of pWIZ and then again in inverted ( head-to-head ) orientation into the AvrII site of the resulting plasmid . For Send2 , the cloning steps were identical to those for Send1 , except the amplified fragment comprised the 514 bp starting at position 1 of the coding sequence . P elements were transformed into flies by standard methods [54] , [55] . To test if loss of either the Send1 or Send2 transcript has an effect on female fecundity or fertility , we used the Send1-GAL4 driver in combination with the UAS-RNAi construct as well as a UAS-Dicer-2 transgene , which increases RNAi pathway activity [56] , and a UAS-GAL4 transgene , which sets up a positive-feedback loop of GAL4 expression [57] . UAS-Dicer-2; CyO , Send1-GAL4/Sp; Send1-nRFP males were mated to +; UAS-Send1RNAi; UAS-GAL4 or +; UAS-Send2RNAi; UAS-GAL4 females . Female progeny that did not inherit the GAL4 driver ( i . e . , inherit the Sp chromosome ) served as controls . 4-d-old virgin experimental and control females were mated individually to Canton-S males and incubated for 3 h at 29°C . Females were then shifted to 25°C in groups of five and transferred to fresh food vials every 24 h . The number of eggs laid was counted each day for 10 d postmating , as was the number of adult progeny produced from these eggs . The knockdown of each gene had no impact on fecundity relative to controls , as determined by Kolmogorov-Smirnov tests on the egg-count data ( p = 0 . 313 for Send1RNAi , p = 0 . 675 for Send2RNAi ) . Likewise , the knockdown of each gene had no impact on fertility , as all eggs produced viable adults . We did confirm , however , that RNAi effectively targeted each gene's transcript . As assayed by quantitative RT-PCR with a Gadph2 internal standard , Send1 transcript levels in virgin and mated females were reduced to 10 . 2% and 9 . 4% of wild-type levels , respectively; Send2 transcript levels in mated females were reduced to 1 . 5% of wild-type levels . The mutant HidAla5 cannot be phosphorylated by MAP kinase , which promotes survival of differentiated cells [34] . To test the efficacy of Send1-driven HidAla5 to trigger cell death , we mated +/UAS-hidAla5; CyO , Send1-GAL4/+; Send2-nRFP/+ females to males at day 2 , 3 , or 4 posteclosion . As assayed by activation of the Send2-nRFP reporter , the majority of SSC respond to mating when it occurs on day 2 posteclosion , but fail to respond to mating on or after day 3 posteclosion . To examine Send2-driven cell death , we used the TUNEL assay . Experimental +/UAS-hidAla5; +/Send1-nRFP; +/Send2-GAL4 females were aged for 4 d prior to mating with Canton-S males . Females were incubated at 29°C for 3 h postmating and transferred to 25°C for 21 , 28 , or 40 h . Lower reproductive tracts , including the spermathecae , were dissected in cold PBS with 0 . 05% Tween-20 and fixed in 2% paraformaldehyde , PBS , 0 . 05% Tween-20 for 1 h at 25°C . Tissues were then permeabilized for 5 min in a 1% Triton-X , 0 . 1% sodium citrate buffer at room temperature . Reproductive tracts were incubated with the TUNEL reagent ( Roche ) for 2 h at 37°C then washed in PBS , fixed for 30 min in 4% paraformaldehyde , mounted in Vectashield ( Vector Labs ) and maintained at 4°C . After mating to protamine-GFP males , experimental and control females were incubated at 29°C for 3 h then shifted to 25°C . Ovaries and reproductive tracts of females were dissected at room temperature in Grace's medium ( Fisher Scientific ) . Reproductive tracts were quickly removed and observed for 5 min to monitor sperm motility and score sperm clumping , using a Leica MZ16FA stereomicroscope with Plan Apo 2 . 0X objective . Female reproductive tracts were dissected in room-temperature Grace's medium and mounted in 35-mm glass-bottomed dishes ( MatTek ) . Videos were collected at ten frames per second by spinning-disk confocal imaging on a Leica DM IRE2 inverted microscope with HC PL Apo 10×/0 . 40 CS objective . A single confocal plane was imaged for the duration of the video . The microscope was interfaced with a computer running Velocity v5 . 0 . 2 imaging software and a Hamamatsu EM-CCD digital camera . To stage embryos , we mated +/UAS-hidAla5; CyO , Send1-GAL4/+; Send1-nRFP/+ females to homozygous Cha-GAL4 , UAS-GFP males . Cha-GAL4 contains 7 . 4 kb of 5′-flanking sequence of the Choline acetyltransferase ( Cha ) gene and is expressed in the brain , ventral nerve cord , and peripheral nervous system , starting at embryonic stage 16 [58] . Females that had not laid an egg for 24 h were gently anesthetized by cooling to allow for reflex oviposition and mounted in 100% silicone to stabilize the abdomen . Videos and still images of embryos were collected using a Leica MZ16FA stereomicroscope with Plan Apo 2 . 0× objective . All internal reproductive tract images were collected on a Nikon TE2000e microscope with Plan Apo 10× ( 0 . 45 numerical aperture ) air objective . For the sperm visualization experiments , multiple planes of focus were imaged so as to capture all sperm . The images in Figures 2 and 3 are overlays of one , two , or three focal planes of the fluorescent channels , with the number chosen in each case to best display all the sperm . In each panel a low-contrast brightfield image , to show outline of tissue , is overlaid with green-channel image to show protamine-GFP sperm and red-channel image ( magenta ) to show SSC ( Send1-nRFP ) . | Females of many animal species store sperm after mating , but the molecular and cellular mechanisms of sperm storage and maintenance are largely unknown . D . melanogaster females store sperm in the seminal receptacle and the paired spermathecae . Each spermathecal cap is lined with large secretory cells . There has been little direct evidence about the functions of these cells because we have not had the tools to manipulate the cells in otherwise wild-type females . Here , by creating transgenic tools to ablate the spermathecal secretory cells ( SSCs ) at different times relative to mating , without affecting any other cells , we show that SSCs are required to recruit sperm to the spermathecae but not to retain them there . We further show that SSC products act elsewhere in the reproductive tract in at least two ways . First , the SSCs are required to maintain sperm stored in the other storage organ , the seminal receptacle . Second , the SSCs are required to sustain normal egg laying . In the absence of SSCs , fertilized eggs develop and occasionally hatch as larvae inside the female . These results could have implications for understanding the evolution of sperm storage and live birth , as well as for studying and manipulating insect fertility . | [
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] | 2011 | Sperm-Storage Defects and Live Birth in Drosophila Females Lacking Spermathecal Secretory Cells |
Binding of small molecules to proteins often involves large conformational changes in the latter , which open up pathways to the binding site . Observing and pinpointing these rare events in large scale , all-atom , computations of specific protein-ligand complexes , is expensive and to a great extent serendipitous . Further , relevant collective variables which characterise specific binding or un-binding scenarios are still difficult to identify despite the large body of work on the subject . Here , we show that possible primary and secondary binding pathways can be discovered from short simulations of the apo-protein without waiting for an actual binding event to occur . We use a projection formalism , introduced earlier to study deformation in solids , to analyse local atomic displacements into two mutually orthogonal subspaces—those which are “affine” i . e . expressible as a homogeneous deformation of the native structure , and those which are not . The susceptibility to non-affine displacements among the various residues in the apo- protein is then shown to correlate with typical binding pathways and sites crucial for allosteric modifications . We validate our observation with all-atom computations of three proteins , T4-Lysozyme , Src kinase and Cytochrome P450 .
Modern drug discovery operates around the principle of molecular recognition in the context of protein-ligand binding . In the preliminary stages , drug discovery programs often invest in quantifying the binding affinity of suitable drug candidates towards a well-established protein target . However , such efforts often encounter scenarios where identification of the ligand-binding cavity on the protein target becomes challenging . In addition , screening across a large pool of protein receptor candidates as potential drug targets for a specific drug proves tedious and time consuming . A popular and inexpensive approach for zeroing on a suitable combination of protein receptor and ligand has been drug design based on in silico techniques . Towards this end , macromolecular docking [1–5] based techniques are routinely employed for screening protein-ligand recognition partners . One of the major drawbacks of docking based approach has been the heuristic choice of the scoring function implemented in the docking programs to quantify and rank-order the protein-ligand affinity . Further , the other major criticism has been that in most of the cases the receptor cavity’s inherent flexibility is not taken into account for docking purposes . Rather , docking softwares [6–17] consider the protein cavity to be rigid and perform the search for a ligand’s ability to dock only in a limited area of protein , often pre-determined by the user’s intuition-based inputs . As a result , docking based drug discovery protocols are fraught often with failures in identifying the correct set of protein ligand combinations . Molecular Dynamics simulations , with the recent emergence of Graphics-Processing-Unit ( GPU ) based computation and special purpose machine like Anton , has slowly emerged as an accurate approach to simulate the complete process of protein ligand binding in its atomistic details . The approach , majorly pioneered by Shaw and coworkers [18–21] has been able to decipher the kinetic pathways leading to spontaneous recognition of the ligand by the receptor . This process is frequently being supplemented by judicious application of Markov State Model [22–24] based techniques to infer long time recognition processes by shorter time simulations . These techniques being unbiased and devoid of user intervention , currently remain one of the best approaches to explore the protein ligand recognition at their highest resolution . But the process comes at the expense of high computational cost and extended wall clock time . As a result , a plan for practical usage of the Molecular dynamics simulation for the purpose of serious drug discovery is still in its infancy . The current work offers a practical middle ground between expensive Molecular Dynamics simulation of protein-ligand recognition processes and inaccurate docking based approach by employing an idea from materials physics , which correctly accounts for deformations in protein structure relevant for binding . We use a formalism , introduced earlier to analyse atomic displacements in solids [25–27] , to predict the protein locations which are potentially susceptible towards ligand recognition . We build on our work under the basic premises that all external and internal stresses result in two types of mutually orthogonal deformations namely those which are “affine” i . e . expressible as a homogeneous deformation of the native structure , and those which are not i . e . “non-affine” . Further details are provided in figure A and section 1 of S1 text . As further elaborated in a later section , the current study characterizes the local arrangements of atoms inside protein by probing an important metric termed as “Non Affine parameter” ( NAP ) [25] . The approach is first convincingly validated by reproducing key conformational changes en route to ligand entry to a mutant T4 Lysozyme . This formalism is then used to propose potential regions which are implicated in “gate-opening” and capture the conformational dynamics during the binding process in the protein receptor Src kinase and Cytochrome P450 . Finally , we show how spatial correlations of NAP can elucidate sites for allosteric control in these proteins . For discussion on the effect of different coarse-graining volume on the eigen-spectrum refer section 6 of SI—Notes on the effect of choice of neighbourhood on NAP eigen-spectrum . c . Local structure of the T4Lys protein showing the neighbourhood analysed in b . The helices and β−sheets are in purple while the rest of the protein is in cyan . The dominant eigenvector is also shown in transparent purple ( see also SI movies S1 & S2 , description provided in section 4 of SI—Description of Videos ) .
Atoms of an isolated protein molecule in aqueous solution and at non-zero temperatures undergo continuous random motion . For most proteins , these atomic motions may be analysed in terms of displacement fluctuations about some fixed native structure . Some of these fluctuations represent local affine distortions of the native state while others correspond to non-trivial conformation changes . It is the latter which are associated with functional aspects of the protein . Determining functionally relevant conformational changes is a challenge , especially if such distortions are subtle and have to be extracted from the random background noise . We show now how a collective variable may be defined , which does exactly that . This collective variable , which we call the non-affine parameter , was first defined for crystalline solids . In solids , non-affine displacements are obtained by systematically projecting out [25] trivial homogeneous deformations of atoms , capturing only those displacements responsible for irreversible plastic events [26 , 27] . The NAP is the squared sum of the mean amplitudes of these displacements . In proteins NAP behaves as a collective coordinate responsible for revealing binding pathways and also for determining possible allosteric couplings between spatially distant residues . Consider for example ( see Fig 1a ) an atom i and its neighbourhood Ωi which contains j = 1 , nΩ neighbours . The size of Ωi is fixed . Too small a Ωi results in large fluctuations while making Ωi too large may average out the relevant signal and make it disappear . Typically , we use a neighbourhood which contains 50–100 atoms excluding H-atoms . The instantaneous positions of the atoms ri at any particular time step of MD simulation are compared with a set of fixed reference positions Ri taken , for example , from the ( ligand-free ) native state of the protein . NAP is then defined as the value of the quantity χ i > 0 = min D ∑ j = 1 n Ω [ r j - r i - D ( R j - R i ) ] 2 where the minimisation is over choices of the deformation matrix D . NAP is therefore the least square error incurred in trying to represent an arbitrary displacement as an affine or homogeneous deformation of the reference configuration . The minimisation process is actually equivalent [25] to a projection . The instantaneous displacement of atom i is ui = ri − Ri . Within the region Ωi , displacements of neighbouring particles relative to that of i are given by Δij = uj − ui . Next we define a projection of Δij onto the non-affine subspace using a projection operator P where P = I − R ( RTR ) −1RT , and the nΩ d × d2 elements of Rjα , γγ′ = δαγRjγ′ , taking i to be at the origin . Finally , one may show χ ( Ri ) = ΔT P Δ where we have used the definition Δ , as an nΩ d dimensional column vector constructed by rearranging Δij . This projection formalism can be carried out for any given set of {Ri} . This identification also allows us to compute statistical averages , probability distributions and spatio-temporal correlation functions using standard methods of statistical mechanics . For example , one derives [25] the equilibrium ensemble average 〈χ〉 = ∑μ λμ where λμ are the eigenvalues of the matrix PCP with C = 〈ΔT Δ〉 the local displacement correlator , and we have suppressed the particle index i for simplicity . Associated with NAP , we can also define the local NAP susceptibility 〈 ( χi − 〈χi〉 ) 2〉 and the spatial correlation function 〈 ( χi − 〈χi〉 ) ( χj − 〈χj〉 ) 〉 , in the same way as it is done for a crystalline solid [26] . Section 1 of SI , along with figure A , provides a summary of useful terms related to our analysis for the readers . One of our important results concerns the distribution of the eigenvalues λμ . For crystalline solids we had observed [26] that ( 1 ) this distribution is non uniform and the largest eigenvalue is separated from the rest by a large gap and ( 2 ) the eigenvector corresponding to the largest eigenvalue represented the dominant plastic mode eg . the creation of a defect dipole . Quite interestingly , the situation is similar here . For details of NAP formalism refer section 1 of SI . In Fig 1b we have plotted the relative magnitudes of the eigenvalues of the local PCP matrix for three different locations on the protein T4Lys . The first one ( I ) corresponds to a Carbon atom on a Carboxyl group on residue 132 ( amino acid Asn ) in a region of helix 7 , the second one ( II ) on an Oxygen atom of a Carboxyl group on helix 5 corresponding to residue 105 ( amino acid Gln ) , and the third one ( III ) for an α− Carbon atom within β sheet 1 , belonging to residue 13 , ( amino acid Leu ) . We shall see later that regions I and II are both quite active during binding events while region III is relatively inert . The eigenvalue spectrum surprisingly bears an imprint of this behaviour . The active regions appear to be dominated by a single non-affine mode which is particularly soft . The eigenvalue for this mode is larger than the rest by a substantial amount producing a gap Γi in the non-affine spectrum . The inert regions of the proteins have more uniformly distributed eigenvalues . By looking at the structure alone , ( see Fig 1C ) it would have been impossible to guess this fact . In Fig 2a & 2b we show that the distribution of the eigenvalues of the PCP matrix are not random . The soft modes that prove out to be useful in our study correspond to a set of eigenvalues which are quite well separated from the spectrum of the rest of the eigenvalues . In order to demonstrate this , in Fig 2a , we plot the distribution of the various eigenvalues of the PCP matrix for region ( I ) of T4Lys ( Fig 1c ) , which is involved in the gate opening resulting from the movements of helices 7 and 9 . This is fitted to the Marchenko Pastur ( MP ) distribution from the prediction from Random Matrix Theory [38–40] . It is clear that the fit is not perfect and there are several eigenvalues which are separated from the rest by gaps . On the other hand , if the matrix PCP was constructed out of Δ which were completely random then we should have obtained the distribution enclosed under the red curve representing the MP distribution for our data . This is shown explicitly for a random correlation matrix in Fig 2b . The fact that we have a sparsely distributed tail of few relatively very large eigenvalues widely separated from the rest of the spectrum and these large eigenmodes contribute most towards the major conformational changes , clearly demonstrates that our analysis is not a straightforward strain-analysis [41] . Instead , indeed , there is an underlying physics that can be revealed by focusing on the non-affine subspace PΔ of the total displacement Δ . Non-affinity may play an important role in guiding a majority of the routine functions performed by the proteins . The relation between activity i . e . a large NAP susceptibility and gaps , Γi , appears to be an universal feature of all the three proteins , with very diverse structures and functions , studied by us . In Fig 2c we have plotted the NAP susceptibility Γi and NAP for several regions within three proteins T4Lys , P450 and Src kinase . In all of these proteins the three quantities are positively correlated with each other and the nature of the correlation ( the slope of the curves ) appears to be the same within the error bars for all the proteins . We demonstrate next that regions of the protein which are involved in a binding event and show large NAP values during the process of ligand binding also have large NAP susceptibility in the apo form of the proteins without the ligand . The motions of the protein during binding events are also captured by the dominant non-affine eigenmode . Finally we show that large NAP correlations between spatially distant parts of the proteins point out domains of possible allosteric control . We first validate the ability of NAP to successfully trace the ligand binding pathway for a recently studied protein-ligand system by Mondal et al . [28] , namely benzene binding to T4Lys . Briefly , Mondal et al . has recently captured the full details of the benzene binding pathways to the buried cavity of T4Lys using multi-microsecond long atomistic MD simulations . The resulting binding trajectories had identified more than one binding pathways . A key observation from those simulated trajectories was that the benzene binding to the solvent-inaccessible cavity of T4Lys did not require large-scale protein conformational change . Rather , the simulations discovered that it is the subtle displacement of helices of the protein which opens up productive pathways leading to ligand binding in the buried cavity . Specifically , as plotted in the right hand axis of Fig 3a , a subset of the trajectories pinpointed that prior to benzene binding , the distance between helix-4 and helix-6 increases transiently by around 2–3 Å from its equilibrium value , facilitating benzene-gating in the cavity , before it reverts back to its original equilibrium distance after the binding event is complete . On the other hand , another subset of trajectories , spawned from same starting configuration , revealed an alternate pathway of ligand binding , where the transient increase in the distance between a different pair of helices namely , helix-7 and helix-9 triggers the ligand entry to the cavity , as depicted in Fig 3b ( right hand axis ) . The snapshots shown at the bottom panel of the Fig 3a and 3b captures the location of the benzene relative to the helix gateway during the period of binding event . The three different snapshots labelled as 1 , 2 and 3 respectively represent the helix conformations before , during and after the ligand binding event . The creation of a helix gateway prior to ligand binding ( snapshot 2 in each case ) is very evident from the increased inter-helix distance . We calculate the time profile of NAP , averaged over all heavy atoms involving these helices and compare its correspondence with corresponding inter-helix distance . As presented in Fig 3a , we plot the profile of average NAP involving helix-4 and helix-6 on the left hand axis and that of average distance between these two helices on the right hand axis , for the part of time period spanning the benzene entry to the cavity . We find that , both NAP profile and distance profile involving helix-4 and helix-6 follow almost identical trend during the course of ligand entry . Similarly , as shown in Fig 3b , for the other trajectory where ligand binding occurred via helix-7 and helix-9 gateway , time profile of NAP involving helix-7 and helix-9 reproduces the trend of distance fluctuation involving helix-7 and helix-9 quite accurately . The remarkable consistency between the NAP profile and displacement profile of key-profiles responsible for ligand binding suggests that these subtle helix fluctuations are results of non-affine displacements of local environment for each particle . Overall , these results validate the potential of NAP as a suitable collective variable or descriptor for tracking ligand binding kinetics . The results discussed in previous section have validated the role of NAP as a good descriptor of a ligand binding event and its ability to track the ligand binding pathways . But the validation needed the extensive simulation of actual ligand binding events . As an important finding of the current work , in this section we show that by analysing the NAP susceptibility on a ligand-free ( apo ) protein itself , one can predict potential protein sites for facile ligand approach , otherwise known as “ligand hotspots” . Since MD simulations of the apo protein do not need to track rare binding events , these cost a small fraction of the time needed for simulating the full protein-ligand systems . Fig 4a and 4c illustrate the spatial distribution of computed NAP susceptibility of two protein systems in their ligand-free ( apo ) form , namely , T4Lys and Src kinase . For the purpose of comparison , we have also plotted the locations on protein surface which ligand frequently visits in previously carried out multi-microsecond long unbiased ligand-binding simulations ( Fig 4b and 4d ) . Fig 4a represents the three-dimensional map of NAP susceptibility of T4Lys . Location 2 of T4Lys includes residues with very high NAP susceptibility ( shown in red spheres ) . A comparison with corresponding location 2 of the time-trace of the ligand in Fig 4b , as obtained from unbiased ligand-binding trajectories , identifies this location as the native ligand binding site at the buried cavity near the 102nd residue ( a part of helix 5 ) . Further , apart from the final ligand binding location at the 102nd residue , the computed NAP susceptibilities around ligand-free T4Lys were also found to be quite high near locations 1 and 3 , which are respectively the 105th ( a part of helix 5 ) and 137th residues ( gateway between helix-7 and helix-9 ) . The residues 102 and 105 ( which are parts of helix-5 ) act as hinge-centers or pivots about which the neighboring residues undergo relative re-arrangement opening up the gateway between helices 4 and 6 . Similarly , the residue 137 ( which is a part of helix-8 ) acts as a pivot for the gateway between helix 7 and 9 . The residue 164 corresponds to location 4 in T4Lys which also has a very high NAP-susceptibility value as it is a terminal residue-part of random coil , mildly contributing towards re-arrangement in helix-9 . Interestingly , as shown in Fig 4b , previously simulated independent binding trajectories have also revealed that the pathways leading to ligand entry to the buried cavity of T4Lys involve the helices near locations 1 , 2 and 3 . More over , the NAP susceptibility analysis recognises multiple locations with moderate NAP susceptibility ( shown by green sphered residues ) , which are also regularly visited by ligands . Although away from major binding sites , these sites serve as possible precursors to intermediates leading to final molecular recognition . Taken together , the ability to correctly predict eventual ligand binding site and other accessory potential ligand hotspots at T4Lys in its apo form by measuring NAP susceptibility , without the need for prior knowledge of protein-ligand binding interactions , rates NAP susceptibility as a very promising metric . The display of the hinge action which opens the gateway to the hydrophobic binding cavity is demonstrated by the supporting movie S1 ( opening-up of helix-7 and helix-9 ) and S2 ( opening-up of helix-4 and helix-6 ) , see ( S1 Text for further details ) . Note that these are not MD simulation snapshots but represent the dominant eigen-displacements arising from a single non-affine mode with the largest eigenvalue . The collective motion involves a “twisting” of the helices and is a very special linear combination of hundreds of local normal modes from which all affine ( strain-like ) distortions have been systematically projected out . We return to this issue later in the paper . The ability of NAP susceptibility to predict the potential ligand hotspots on a protein surface is also validated in another popular receptor protein , namely the Src kinase . Fig 4c shows the NAP susceptibility map around Src kinase in its ligand-free form while the corresponding simulated ligand binding trajectories , as previously simulated by Shaw and coworkers , is shown in Fig 4d . In this case as well , the ATP-binding site ( location 2 ) is correctly predicted to have one of the highest NAP susceptibilities in the apo-form and independent simulated ligand-binding trajectories also confirm this . Moreover , other locations of kinase rated as high to intermediate NAP susceptibility for ligand approach are also independently found to be locations regularly traced by ligand in the unbiased ligand binding trajectories by Shaw and coworkers [18] . Specifically , so-called PIF site , MYR site and G-loop site of kinase ( PIF-site:region1 , MYR-site:region4 , ) , which were found to attract regular ligand visit in actual ligand binding trajectories , are also predicted to have high to moderate NAP susceptibility for the ligand in apo form of the kinase itself . However , interestingly , our NAP susceptibility analysis also predicts a new location 5 deemed highly susceptible to ligand , which is otherwise not known as a ligand hotspot . The discovery of this new site prompted further analysis to justify the observed high susceptibility for the ligand . We have also checked the effect of simulation lengths on the NAP susceptibility . Figure B plots the NAP susceptibility of all particles of src kinase computed over two different simulation lengths . We find that the results remain invariant over simulation time . We also note that these simulations on ligand-free protein , which are used for NAP analysis , are orders of magnitude shorter than the simulation time required for seeing the direct ligand binding events . In the next section , we show that the newly obtained regions of Src kinase which have high NAP-susceptibility also play an important role in establishing an allosteric communication across the protein structure . All the important sites with moderate and high NAP susceptibility values are reported in section 3 of SI . In the previous section , we have explored the NAP susceptibilities for different locations of the protein and using this as a metric we were able to extract the important ligand hotspots , in accordance with the simulated ligand binding trajectories . Similarly spatial NAP correlation function or covariance , calculated at the same time , as defined previously , measures the correlation between non-affine displacement fluctuations at two different , possibly distant , locations . We link this quantity to a measure of allostery in the protein systems i . e . the ability of spatially distal sites in proteins to influence catalytic or binding activity . In Fig 5 , we plot residue-residue NAP covariance matrix representing spatial correlation functions for our two protein systems , namely T4Lys ( Fig 5a ) and Src kinase ( Fig 5b ) respectively . On the two axes we have the residue ids and the value of the spatial correlation function between two residues is given by the colour of the point . High values above a suitable cut-off are in yellow and the rest are in black . We are interested in those off-diagonal residues that are spatially far away from each other , since spatially adjacent residues will be trivially correlated due to direct interactions . As shown in Fig 5a , we could get five prominent locations in the matrix for T4Lys which have high NAP correlation at a spatially far-off distance ( see S1 Text for further details of these regions ) . For example , we found that a very high NAP correlation exists between residue 137 in region 3 and residue 18 in region 5 ( labelled ( 3 , 5 ) ) of T4Lys . This allosteric connection can be seen to be contributing towards regulation of the hydrogen bond between the residue 22 Glu and residue 137 Arg . Using a newly introduced method ExProSE , It was confirmed by Greener et al . [42] that , the breaking of a hydrogen bond between Arg137 and Glu22 causes the opening motion taking the protein from a closed active site cleft conformation to an open active site cleft conformation . Also , earlier , Mchaourab et al . [43] have confirmed that in solution there is a conformeric equilibrium between substrate-bound and substrate-unbound T4 Lysozyme which is in accord with the active site cleft opening upon substrate removal due to Hinge-Bending motion . Mchaourab et al . used the site-directed Spin Labeling to detect these motions . From our NAP formalisms too , [26] we can see that the softest non-affine modes corresponding to the residues 18 and 137 act as the nucleating-precursors to the opening of the active site cleft . These modes contribute by initially breaking the hydrogen bond between residues 22 and 137 and therefore we can directly see the increasing distance between residue 22 and 137 in S3 Video ( description provided in section 4 of SI—Description of Videos ) in the supplementary info . For Src kinase too , as shown in Fig 5b , we could identify five regions of high NAP correlations at distant locations . For example , residue 416 ( Tyr ) of region 5 of src kinase has a very high NAP correlation with residue 328 ( Val ) ( an element of Helix-αc ) of region 1 ( labelled ( 1 , 5 ) . This is supported by a previous report [44] of coupling between the activation loop and Helix-αc . A hallmark of active conformation of kinase [45] is the autophosphorylation of the activation loop ( 404–432 ) at the residue 416 ( Tyr ) and “αC-in” conformation of Helix-αc . Analysis of non-affinity shows that the softest non-affine modes ( S4 Video in supporting info , description provided in section 4 of SI—Description of Videos ) at residue 416 and residue 328 in our simulations act as incipients for residue 416 ( Tyr ) protruding outward from the activation loop region , thereby becoming more exposed for the phosphorylation at this site ( this site being tyrosine which is favourable for phosphorylation ) , and at the same time inward rotation of Helix-αc . In summary , our analysis based upon NAP-susceptibility and NAP spatial correlation function points towards allosteric contact between Helix-αc ( helix undergoing inward rotation ) and activation loop of kinase ( phosphorylation site Tyr416 getting exposed ) . Apart from this , we also note that there is a slight distortion of the salt-bridge between 295LYS and 310GLU . The two residues 295LYS and 310GLU are shown in silver small spheres and stick form . This is also supported by the previous works [45–47] . The details of regions 1-5 are mentioned in section 3 of SI . The family of Cytochrome P450 proteins are quite versatile and are present in many different human tissues performing many tasks such as oxygen metabolism by binding to Heme , breakdown of toxins and hormones , synthesis of cholesterol [48] etc . They are often associated with intracellular membranes such as in mitochondria and the endoplasmic reticulum . Extensive studies using sequence-based co-evolutionary analysis and anisotropic thermal diffusion MD simulations have identified four principal active regions in P450 related to membrane association , catalytic activity , Heme binding and dimerization [49] . Our results for the NAP susceptibility are shown in Fig 6 . Remarkably , we can also identify the same regions as obtained in the earlier study [49] , although the variant of P450 used by us is somewhat different . A complete analysis of all the different binding and allosteric processes of P450 analysed using the NAP values , eigenvectors and correlation functions is much beyond the scope of the present work and will be published elsewhere .
Pinpointing sites of catalytic activity , binding of ligands or other functionally important conformational changes in proteins is a challenge when such displacements in protein residues are subtle and easily masked by background noise . Accurate “order parameters” or collective variables need to be designed to study such activity . It is often unclear how such collective variable may be defined . Drawing from ideas which were first demonstrated in crystalline solids [25–27] we have defined a new collective variable , NAP , which quantifies non-affine thermally excited displacements of proteins . Firstly , we show that the susceptibility of different locations of a protein to non-affine displacements can be used as an indicator to determine regions which are important for binding events . Secondly , from the analysis of the NAP susceptibility values we conclude that the regions with higher values of NAP susceptibilities are also those which contain a dominant non-affine mode whose eigenvalue is separated from those of the the rest of the modes by a large gap . The eigenvalue spectrum of the non-affine modes is also highly non-random . The eigenvector corresponding to this dominant mode involves atomic displacements that are the ones prone to act as binding gate-ways and the time spent by a ligand during a binding event at a particular residue is determined by the NAP susceptibility of this region . We also show that a positive correlation exists between the NAP value , its susceptibility and the magnitude of the gap in all the proteins studied by us . Recent times have seen the emergence of many novel techniques to tackle the challenging issue of coming up with optimum sets of collective variable . Tiwary and Berne’s techniques of spectral gap optimisation of order parameters ( SGOOP ) , [50] Time-structure based independent component analysis ( TICA ) -based approach for optimising collective variable [51–53] for protein conformational analysis and molecular recognitions certainly have contributed significantly in this line . The approach described in this work is quite relevant , in light of these recent efforts in optimising collective variable for describing a biological processes . It is quite remarkable that our projection formalism yields useful data even from short simulation runs and results are robust over different simulation lengths ( refer section 2 of SI and figure B ) . Our analysis is fundamentally different from principal component analysis ( PCA ) [54–56] or other PCA based methods [57] which are used extensively for analysing protein configurations obtained from simulations . The restriction to the coarse graining volumes Ωi makes the analysis local and the projection to the non-affine sub space guarantees that all trivial motions are filtered out . Nonetheless , we have analysed the sensitivity of our results over choice of coarse-graining volumes in Section 5 of SI and figure C provides justification of our choice of Ωi . The NAP eigen spectrums are also analysed over varying coarse-grains radius in figure D and section 6 of SI . Our NAP analysis are also robust against choice of main-chain or side-chain atoms of protein for the computation ( see section 7 of SI and figure E . ) Finally , the large gap in the non-affine excitation spectrum between the dominant eigenmode and the rest ensures that there is very little mixing of the modes . As an example , recall the ( un- ) twisting motion of the helices observed in T4Lys as shown in the supplementary S1 Video ( see S1 Text ) . Such a motion requires a special linear superposition of a large number of normal modes . The dominant PCA mode on the other hand cannot capture these motions ( refer to figure F and section 8 of SI for detailed discussion on comparison with PCA ) in detail although atomic displacements in the relevant regions are large . Unfortunately , these displacements are also contaminated by unimportant , affine motons which mask the gate opening feature . The ability to compute NAP susceptibility by our approach helps us to unify two different proposed hypotheses of protein-ligand recognition , namely “conformational selection” [58–63] ( in which protein’s intrinsic ability to shift to a ligand-preferred conformation guides the molecular recognition ) and “induced fit” ( in which ligand induces the protein to change its conformation ) . Our calculations show that these ideas are not in conflict but follows from standard fluctuation-response behaviour connecting local fluctuations of non-affine part of atomic displacements to the response of the protein to the conjugate local non-affine field [26] . This is a simple consequence of a fluctuation response relation viz . 〈χ〉 = 〈χ〉0 + hχ〈 ( χ − 〈χ〉 ) 2〉0 if we identify ligands with local fields hχ which generate NAP in proportion to their susceptibilities at hχ = 0 . The ligand , in this case acts as such an “external” field and the response of the protein to the field is proportional to the fluctuations of local NAP in its apo state without the field ( ligand ) . Additionally , we see that the spatial correlation of NAP among various residues can be used to discover sites of possible allosteric control . NAP susceptibilities and correlations may be obtained readily from simulations of the apo protein without the ligand and come at a fraction of the cost needed for detailed simulations of ligand binding events . This implies that our proposed method is extremely well suited to be adapted for high throughput searches of possible protein ligand pairs and allosteric control . It is to be noted that in our work we have focussed on the projection of the displacements to the non-affine subspace which is orthogonal to local strain [41] . Since binding hotspots feature large displacements , both strain and strain fluctuations may be large together with large NAP values . NAP however , quantifies the error made in trying to fit the local displacements to an affine model and therefore large NAP values also signify that a description in terms of strain becomes invalid in those regions .
We have worked on three systems including binding of benzene to the solvent-inaccessible cavity of the L99A mutant of T4 Lysozyme ( T4Lys ) . Also we had previously performed multi-microsecond molecular dynamics simulation where we have simulated the complete kinetic process of ligand recognition [28] . The details of atomistic simulation process and models for this system have been discussed therein . The apo or ligand-unbound form of T4Lys ( PDB id: 3DMV ) and and Src kinase ( pdb id: 1Y57 ) have also been explored in our work along with with some data for Cytochrome P450 ( pdb id: 2CPP ) . All the apo forms have been modelled using same simulation protocols . We have used the CHARMM36 force field [64] . The protein is solvated by 11613 TIP3P water molecules in a cubical box of dimension 7 . 18 nm . Sufficient number of ions were added to maintain 150 mM salt concentration . All MD simulations were performed with the Gromacs 5 . 0 . 6 simulation package [65] . During the simulation , the average temperature was maintained at 303K using the Nose-Hoover thermostat [66 , 67] with a relaxation time of 1 . 0 ps and an average isotropic pressure of 1 bar was maintained with the Parrinello-Rahman barostat [68] . The Verlet cutoff scheme was employed throughout the simulation with the truncated and shifted Lenard Jones interaction extending to 1 . 2 nm and long-range electrostatic interactions [69] treated by Particle Mesh Ewald ( PME ) summation [70] . All bond lengths involving hydrogen atoms of the protein and the ligand benzene were constrained using the LINCS algorithm [71] and water hydrogen bonds were fixed using the SETTLE [72] approach . Simulations were performed using the leapfrog integrator with a time step of 2 fs and initiated by randomly assigning the velocities of all particles . The total time for our simulations of the apo-proteins amounted to ( T4Lys = 493 . 54ns , Src kinase = 460 . 00ns , P450 = 500ns ) 1453 . 54 ns which was sufficient to obtain equilibrated data . | Designing drugs which target specific proteins involved in diseases consumes a lot of time and effort in the pharmaceutical industry . In recent times , in silico design of drugs using all-atom molecular modelling has started to provide crucial inputs . Even so , discovery of binding pathways of small molecules both at the primary binding site , as well as sites for allosteric control , is time consuming and often fortuitous . We provide here a framework within which critical conformational changes likely to occur during binding are quantified from statistical analysis of configurations of proteins in their apo , or inactive form , greatly simplifying identification of target residues . We illustrate this idea by analysing ligand binding pathways for three proteins T4- Lysozyme , P450 and Src kinase , which are active respectively in the immune system , metabolism and cancer . | [
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] | 2019 | On identifying collective displacements in apo-proteins that reveal eventual binding pathways |
In many biological systems , the network of interactions between the elements can only be inferred from experimental measurements . In neuroscience , non-invasive imaging tools are extensively used to derive either structural or functional brain networks in-vivo . As a result of the inference process , we obtain a matrix of values corresponding to a fully connected and weighted network . To turn this into a useful sparse network , thresholding is typically adopted to cancel a percentage of the weakest connections . The structural properties of the resulting network depend on how much of the inferred connectivity is eventually retained . However , how to objectively fix this threshold is still an open issue . We introduce a criterion , the efficiency cost optimization ( ECO ) , to select a threshold based on the optimization of the trade-off between the efficiency of a network and its wiring cost . We prove analytically and we confirm through numerical simulations that the connection density maximizing this trade-off emphasizes the intrinsic properties of a given network , while preserving its sparsity . Moreover , this density threshold can be determined a-priori , since the number of connections to filter only depends on the network size according to a power-law . We validate this result on several brain networks , from micro- to macro-scales , obtained with different imaging modalities . Finally , we test the potential of ECO in discriminating brain states with respect to alternative filtering methods . ECO advances our ability to analyze and compare biological networks , inferred from experimental data , in a fast and principled way .
Network science has provided a breakthrough in the analysis and modeling of biological systems with the aim to unlock molecular mechanisms behind human disease [1–3] and quantify brain ( re ) organization underlying behavior , cognition and mental disorders [4–6] . In part , this has been made possible by the increasing availability of tools that indirectly infer the structure of those networks from empirical measurements , thus bypassing the current lack of accurate and complete interaction maps [3 , 7] . In system biology , functional links are estimated from transcriptional or phenotypic profiling , and genetic interactions by using measures such as Pearson correlation [8] or Granger causality [9] . In neuroscience , imaging tools such as magnetic resonance imaging ( MRI ) and electro/magnetoencephalography ( E/MEG ) , are extensively used to map connections and/or interactions between different brain sites , i . e . , the connectome [7 , 10] . Brain connectivity methods are typically used to estimate the links between the nodes . While structural connectivity ( SC ) measures the probability to find axonal pathways between brain areas , typically from diffusion MRI , functional connectivity ( FC ) rather calculates the temporal dependence between remote neural processes as recorded , for instance , by functional MRI , EEG or MEG [4 , 7] . At this stage , the resulting networks correspond to maximally dense graphs whose weighted links code for the strength of the connections between different nodes . Common courses in brain network analysis use thresholding procedures to filter information in these raw networks by retaining and binarizing a certain percentage of the strongest links ( S1 Fig ) . Despite the consequent information loss , these procedures are often adopted to mitigate the incertainty of the weakest links , reduce the false positives , and facilitate the interpretation of the inferred network topology [3 , 11] . At present , there’s no objective way to fix the value of such threshold . Because network properties significantly depend on the number of remaining links , scientists are obliged to explore brain network properties across a wide range of different candidate thresholds and eventually select one representative a-posteriori [12] . Concurrently , alternative approaches can be adopted to cancel spurious links emerging from third-party interactions [13–15] , or statistically validate the estimated connections [7 , 16 , 17] . However , these procedures lack of precise rationale , are subject to arbitrariness ( e . g . , the choice of the statistical significance ) and make difficult the comparison of network properties between many individuals or samples [11 , 18] . Furthermore , these become extremely time-consuming when considering several large connectomes due to the computational complexity of graph quantities based on paths between nodes or on communities detection [19] . To circumvent these issues , we propose a topological criterion for selecting a threshold which captures the essential structure of a network while preserving its sparsity . Based on the optimal trade-off between two desirable but incompatible features—namely high global and local integration between nodes , and low connection density—this method is inherently motivated by the principle of efficiency and economy observed in many complex systems [20] , including the brain [21] .
Global- and local-efficiency have revealed to be important graph quantities to characterize the structure of complex systems in terms of integration and segregation of information [22 , 23] . Both structural and functional brain networks tend to exhibit relatively high values of global- and local-efficiency . At the same time they also tend to minimize , for economical reasons , the number of their links leading to sparse networks [21] . Thus , we propose to determine a density threshold that filters out the weakest links and maximizes the ratio between the overall efficiency of a network and its wiring cost . Notice that the definition of cost can have different connotations , e . g . , the spatial distance between connected nodes [21] . Here , the cost in terms of number of links is a more general definition which also applies to non-spatially embedded networks ( e . g . , molecular interaction networks ) . We formally introduce a criterion to filter information in a given network by finding the connection density ρ that maximizes the quality function: J = E g + E l ρ ( 1 ) where Eg and El represent respectively the global- and local-efficiency of a network . By definition , the three quantities Eg , El and ρ are normalized in the range [0 , 1] , and both Eg and El are non-decreasing functions of ρ . More details about the formulation of J can be found in the Material and Methods . For both regular lattices and random networks , we proved analytically that the optimal density that maximizes J follows a power-law ρ = c/ ( n − 1 ) , where c is a constant and n is the network size , i . e . , the number of nodes in the network . More specifically , c = 3 . 414 for lattices and c = e = 2 . 718 for random networks , so that we have approximately ρ ≃ 3/ ( n − 1 ) . Hence , to maximize J , these networks have to be sparse with an average node degree k ≃ 3 or , equivalently , with a total number of links m that scales as m ≃ 3 2 n ( S1 Appendix ) . We confirmed this result ( S2a and S2b Fig ) through extensive numerical simulations ( Materials and Methods ) , showing that it held true also in more realistic network models , such as in small-world networks [24] ( Fig 1a ) and in scale-free networks [25] ( Fig 1b ) . For these simulated networks the fitted values varied progressively from c = 3 . 265 , in lattices , to c = 2 . 966 , in random networks , thus falling within the theoretical range found analytically ( S1 Table ) . Notably , the optimal density values maximizing J emphasized the intrinsic properties ( random or regular ) of all the implemented synthetic networks in terms of global- and local-efficiency ( Fig 1d and 1e and S2d and S2e Fig ) . We computed the quality function J in both micro- and macro-scale brain networks and we evaluated how the density maximizing J scaled as a function of the network size . We considered connectomes used in previously published studies that were obtained with different imaging modalities , from calcium imaging to EEG , and constructed with disparate brain connectivity methods ( Table 1 ) . For each connectome we applied a standard density-based thresholding . We started with the empty network by removing all the links ( ρ = 0 ) . Then , we reinserted and binarized one link at time , from the strongest to the weakest , until we obtained the maximally dense network ( ρ = 1 ) . At each step we computed J and we recorded its profile as a function of ρ . The pooled density values , as returned by the maximization of the healthy group-averaged J profile in each modality ( see Fig 1f for one representative ) , followed a power law comparable to the one that we reported for synthetic networks ( Fig 1c ) . In particular , the fit ρ = c/ ( n − 1 ) to the data gave c = 3 . 06 with an adjusted r-square R2 = 0 . 994 . Notably , we obtained a similar scaling ( c = 2 . 87 adjusted R2 = 0 . 946 , S2c Fig ) when considering individual J profiles ( S2f Fig ) . These results confirm that also for brain networks we can assume that the optimal density threshold maximizing J only depends on the network size according to the same rule ρ ≃ 3/ ( n − 1 ) . In conclusion , we introduced a criterion , named efficiency cost optimization ( ECO ) , to select a threshold leading to sparse , yet informative brain networks . Such a threshold is relatively independent of the connectome’s construction and invariant to the underlying network topology so that it can be selected a-priori once the number of nodes is known . To illustrate the methodology , we considered connectomes from four different imaging modalities , namely EEG , MEG , fMRI , and DTI ( Table 1 ) . Because we do not know the true structure for these connectomes , we evaluated the ability of ECO to discriminate network properties of different brain states , i . e . , healthy versus diseased , at individual level . We characterized brain networks by calculating graph quantities at different topological scales , i . e . , large ( global- and local-efficiency , Eg and El ) , intermediate ( community partition , P; and modularity , Q ) , and small ( node degree , ki; and betwenness , bi ) ( Materials and Methods ) . To assess network differences between brain states , we measured distances between the values of the graph quantities obtained in the healthy group and those in the diseased group . We adopted the Mirkin index ( MI ) to measure distances between community partitions , and the divergent coefficient ( D ) for other graph quantities ( Materials and Methods ) . We explored a wide range of density thresholds and , as expected , the value of the threshold affected the ability to separate network properties of different brain states ( Kruskalwallis tests P < 0 . 01 , S2 Table ) . Notably , the choice ρ = 3/ ( n − 1 ) resulted among the best candidates in producing larger distances regardless of the graph quantity ( Tukey-Kramer post hoc tests P < 0 . 05 , Fig 2 and S3 Fig ) . This outcome was not associated to the possible presence of disconnected components . In all the filtered brain networks the size of the largest component ( > 50% of the nodes ) did not differ between groups for any threshold value ( Wilcoxon rank-sum tests P ≥ 0 . 01 , Fig 3 ) . Furthermore , ECO overall outperformed alternative methods , such as the minimum spanning tree ( MST ) and the planar maximally filtered graph ( PMFG ) [26] , in giving larger distances ( Tukey-Kramer post hoc tests P < 0 . 05 , Fig 4 , S4b Fig , S2 and S3 Tables ) . Notably , we reported good performance with respect to a hybrid method , named MST+ECO , where we added the remaining strongest links to the backbone obtained with MST , in order to reach the same average node degree as ECO , i . e . k = 3 ( Tukey-Kramer post hoc tests P < 0 . 05 , S3 Table ) . Finally , brain networks filtered with ECO were more efficient ( Fig 5a ) and exhibited J values that better separated different brain states ( Fig 5b ) as compared to the other filtering methods ( Tukey-Kramer post hoc tests P < 0 . 05 , S3 Table ) .
ECO is based on a graph theoretic approach and cannot filter out possible false positives ( i . e . , spurious links ) resulting from biased brain connectivity estimates [7 , 11] . Our criterion admits that the weighted links of the raw networks had been previously validated , either maintained or canceled . Some inference methods [32 , 33] and group-based approaches [34] naturally produce sparse brain networks . In these cases , ECO would still apply as long as there is enough information to filter , i . e . , a number of links m ≥ 3 2 n . By construction , brain networks filtered with ECO ( k ≃ 3 ) are less sparse than networks filtered with MST ( k ≤ 2 ) . However , differently from MST and PMFG , ECO does not guarantee the connectedness of the pruned networks , which can be indeed fragmented ( S5 Fig ) . Whether this condition leads to a more realistic representation of connectomes , especially for large n , we cannot say . Current literature tends to focus on thresholded brain networks which are slightly denser than ECO , with 0 . 05 ≤ ρ ≤ 0 . 3 [35] . However , little is known on how this range depends on the number of brain nodes and future studies will have to ascertain if and how the choice of a specific threshold can give more accurate results . Here , we showed that the size of the largest components contained in average more than the 50% of the nodes ( Fig 3 ) . Therefore , caution should be used in the evaluation of the resulting network properties and , whenever possible , using graph quantities that can handle networks with disconnected nodes ( e . g . , the harmonic mean of the shortest path lengths [36] ) appears more appropriate . Finally , other combinations could have been considered when conceiving the quality function J . For example , in [37] authors introduced the cost-efficiency Eg − ρ , which , however , did not include the clustering counterpart . This quality function , as well as other ones that we investigated , did not exhibit meaningful analytic solutions and was therefore excluded as a possible alternative ( S2 Appendix ) . A more general formulation would include a scaling factor in the numerator , like for example 2[αEg + ( 1 − α ) El] where α is a control parameter ranging from 0 to 1 . We proved analytically that , for both regular lattices and random graphs , the optimal density that maximizes the corresponding quality function remained ρ ≃ 3 n - 1 regardless of the α value ( S3 Appendix ) . We confirmed this result through numerical simulations also in small-world and scale-free networks ( S4 Fig ) where the optimal density maximizing J corresponded to an average node degree k ≃ 3 , except when α → 1 in lattices and α → 0 in random networks . Taken together , these findings indicate that the density threshold given by ECO is relatively invariant to the specific value we assigned to the parameter α . The advantage of considering our quality function is that i ) it did not depend on external parameters , ii ) we could derive analytically the optimal ρ values for lattices and random networks , and iii ) the density values obtained by maximizing J in real brain networks fitted the power-law that we found analytically and were able to separate different brain states . Despite these advantages , we notice that ECO could not be the definitive solution to the problem of thresholding in imaging connectomics . Other methods , possibly inspired by biology , are likely to be developed in the future and validation benchmarks will be crucial to evaluate their potential . ECO is founded on asymptotic results in unweighted network models . Its natural application implies binarization after thresholding , a procedure widely adopted to mitigate the uncertainty carried by the weights estimated from neuroimaging data [4 , 11] . Further work is needed to clarify how ECO can be extended to weighted networks , where the asymptotic expression of topological properties is less straightforward . Interactions between biological components are not constant and need to dynamically vary to accomplish internal regulation and external function [38–40] . In neuroscience , functional brain connectivity exhibits rich temporal dynamics that are fundamental for human cognition and complex behavior [41–44] . Further studies should aim to elucidate if and how brain network differences highlighted by ECO change over time . We introduced ECO as a possible method for filtering information in imaging connectomes . Concrete applications range from cognitive to clinical and computational neuroscience . Given its generality , we anticipate that ECO can also serve to facilitate the analysis of interconnected systems where the need of sparsity is plausible and the links are weighted estimates of connectivity . This is , for example , the case of functional networks in system biology , where links are typically derived from transcriptional or phenotypic profiling , and genetic interactions [3] .
The expression of J can be seen as a particular case of a general family of functions of the form f ( Eg , El , ρ ) . Here , we defined J as a ratio to measure the incidence of the density on the network efficiency both at global and local scale . Indeed , we were interested in a relative measure that could tell the network efficiency changes per unit of density . In addition , we did not weight the global- and local-efficiency in the numerator . While , in general , a scaling factor might be necessary to normalize changes between different graph quantities [45] , here both Eg and El range between 0 and 1 and are formulated in terms of the same concept , namely the efficiency ( at global and local scale ) between nodes [22] . We remind to S3 Appendix and S4 Fig for more details on the introduction of a scaling parameter . By looking at Eq ( 1 ) , we have that when ρ = 0 , then both global- Eg and local-efficiency El are null leading to an indefinite form . As density slightly increases ( 0 < ρ < ϵ , with ϵ sufficiently small ) it can be demonstrated that J tends to 1 . Indeed , in this range , the probability to find at least three nodes connected together ( a triangle ) is extremely low . By definition , El = 0 in absence of at least one triangle [22] and therefore J ≃ Eg/ρ . By considering the definitions of Eg and ρ , this quantity can be rewritten as E g / ρ = 1 / m ∑ i ≠ j n 1 / d i , j , where m is the number of existing links and di , j is the distance between the nodes i and j . In a generic network with m links there are at least m pairs of nodes directly connected ( i . e . , di , j = 1 ) . This means that the sum in the latter equation is bounded from below by m in the case of isolated pairs of connected nodes ( m = n/2 ) or in the trivial case of m = 1 . It follows that J → 1 when there are relatively few links in a network . When ρ tends to 1 , it is trivial to see from Eq ( 1 ) that J → 2 , as both Eg and El tend to one . For intermediate density ranges ( ϵ < ρ ≪ 1 − ϵ ) the analytic estimate of J is not trivial since Eg and El depend on the network topology which is , in general , unknown . Small-world networks were generated according to the Watts-Strogatz ( WS ) model [24] with a rewiring probability pws = 0 . 1 . Scale-free networks were generated according to the Barabasi-Albert ( BA ) model [25] . In the first simulation , we considered undirected networks . We varied both the network size and the average node degree , i . e . , n = 16 , 128 , 1024 , 16384 and k = 1 , 2 , 3 , 4 , 5 . In the WS models , k is even accounting for the number of both left and right neighbors of the nodes in the initial lattice . To obtain small-world networks with k odd , we first generated lattices with k even and then , for each odd node ( e . g . , 1 , 3 , … ) , we removed the link with its left farthest neighbor . This procedure removes in total n/2 links leading to a new average node degree k′ = k − 1 , while keeping a regular structure . As for BA models , we set the number of links in the preferential attachment mba = 3 and the initial seed was a fully connected network of n0 = mba nodes . This setting generated scale-free networks with k = 6 − 12/n , that is k ≥ 5 regardless of the selected network size . We then removed at random the exceeding number of links until we reached the desired k value . This procedure had the advantage to preserve the original scale-free structure . In the second simulation , we considered directed networks to confirm and extend the results we obtained for undirected WS and BA networks . We selected eight representative network sizes , i . e . , n = 8 , 16 , 32 , 64 , 128 , 256 , 512 , 1024 covering the typical size of most current imaging connectomes , and we varied the connection density . Specifically , we performed a two-step procedure: For WS models , initial lattices had k equal to the nearest even integer equal or higher than ρ ( n − 1 ) , with ρ ∈ ( 0 , 1 ) . For BA models , the number of attaching links was mba = log2 n to ensure an initial relatively high density; the seed was a fully connected network of n0 = mba nodes . By construction ρ ∈ ( 0 , 2 m b a n + m 0 n ( n - 1 ) ) , where m0 = n0 ( n0 − 1 ) /2 is total number of links in the initial seed . For both models , we then removed at random the exceeding links until we reached the desired density value . For both simulation we generated one-hundred sample networks . Complex networks can be analyzed by a plethora of graph quantities characterizing different topological properties [46] . Here , we considered a subset of representative ones which have been shown to be relevant for brain network analysis [47] . To characterize the entire brain network ( i . e . , large-scale topology ) , we used global- and local-efficiency , which respectively read: E g = 2 n ( n - 1 ) ∑ i ≠ j n 1 d i j E l = 1 n ∑ i = 1 n E g ( i ) ( 2 ) where dij is the length of the shortest path between nodes i and j , and Eg ( i ) is the global-efficiency of the ith subgraph of the network [22] . To characterize modules , or clusters , of brain regions with dense connections internally and sparser connections between groups ( i . e . , mid-scale topology ) , we evaluated the community structure of the brain network [4] . We extracted the partition P of the network into modules by means of the Newman’s spectral algorithm maximizing the modularity: Q = 1 2 m T r ( G T M G ) ( 3 ) where G is the ( non-square ) matrix having elements Gig = 1 if node i belongs to cluster g and zero otherwise , and M is the so-called modularity matrix [48] . To characterize individual brain areas ( i . e . , small-scale topology ) , we measured the centrality of the nodes in the brain network by means of the node degree and of the node betwenness , which respectively read: k i = ∑ j ≠ i n A i j b i = ∑ j ≠ i ≠ h σ j h ( i ) σ j h ( 4 ) where the element of the adjacency matrix Aij = 1 if there is a link between node i and j , zero otherwise; and where σjh is the total number of shortest paths between nodes j and h , while σjh ( i ) is the number of those paths that pass through i . These quantities represent a small subset of all the possible metrics available in the market . Nevertheless , these are among the most adopted in network neuroscience thanks to their interpretability in terms of connectivity at different topological levels ( e . g . , network , modules , nodes ) [4 , 11 , 27 , 49–51] . To assess brain network differences between individuals ( or samples ) in the two groups , we measured the distance between the respective values obtained for each graph quantity . We used the Mirkin index to compute distances between two network partitions Pu and Pv: M I ( P u , P v ) = 2 ( n 01 + n 10 ) ( 5 ) where n01 is the number of pairs of nodes in the same cluster under Pv but not under Pu; and n10 is the number of pairs in the same cluster under Pu but not under Pv [52] . The Mirkin index is an adjusted form of the well-known Rand index and it assumes null value for identical clusterings and 1 for totally different clusterings [52] . It corresponds to the Hamming distance between the binary vector representation of each partition . Although this measure can be sensitive to the cluster sizes , it has the advantage of being a metric on the space of the clustering partitions [53] . For all other graph quantities , we used the divergent coefficient [54]: D ( X u , X v ) = 1 M ∑ m = 1 M x u , m - x v , m x u , m + x v , m 2 ( 6 ) where Xu = [xu , 1 , xu , 2 , … , xu , M] and Xv = [xv , 1 , xv , 2 , … , xv , M] , contain the value ( s ) of the graph quantity for the uth and vth sample . Notably , M = 1 for global- , local-efficiency and modularity ( i . e . , Eg , El , Q ) . M = n for the node degree vector K = [k1 , k2 , … , kn] and the node betweenness vector B = [b1 , b2 , … , bn] . The divergent coefficient is a L2-norm distance similar to Euclidean distance but with a normalizing factor which is used for multidimensional scaling [55] . It ranges between 0 ( equal multidimensional distribution of the features ) and 1 ( totally heterogeneous multidimensional distribution ) . This coefficient is a metric in the Euclidean space when all the values of the features are positive , as for our graph quantities [56] . Both Mirkin index and divergent coefficient are therefore metrics normalized between 0 and 1 , allowing for a coherent analysis across different imaging modalities and threshold values . We used Kruskal–Wallis one-way analysis of variance , with a 0 . 01 statistical threshold , to evaluate the overall effect of different thresholds , or filtering methods ( i . e . , MST , PMFG ) on distances between individuals . A Tukey-Kramer multiple comparison post hoc test was then used to determine specific differences between pairs of thresholds or methods [57] . Here the statistical threshold was fixed to 0 . 05 . | Complex brain networks are mainly estimated from empirical measurements . As a result , we obtain networks where everything is connected to everything else through different strengths of interaction . Filtering procedures are typically adopted to prune weakest connections . However , network properties strongly depend on the number of remaining links and how to objectively fix such threshold is still an open issue . Here , we propose a criterion ( ECO ) to filter connectivity based on the optimization of fundamental properties of complex systems , i . e . , efficiency and economy . Using ECO , investigators can analyze and compare connectomes in a fast and principled way , capturing network properties of different brain states to eventually quantify ( re ) organizational mechanisms underlying cognition and disease . Given its generality , we anticipate that ECO can also facilitate the study of networks in other fields , such as system biology . | [
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] | 2017 | A Topological Criterion for Filtering Information in Complex Brain Networks |
Salmonella enterica species are enteric pathogens that cause severe diseases ranging from self-limiting gastroenteritis to enteric fever and sepsis in humans . These infectious diseases are still the major cause of morbidity and mortality in low-income countries , especially in children younger than 5 years and immunocompromised adults . Vaccines targeting typhoidal diseases are already marketed , but none protect against non-typhoidal Salmonella . The existence of multiple non-typhoidal Salmonella serotypes as well as emerging antibiotic resistance highlight the need for development of a broad-spectrum protective vaccine . All Salmonella spp . utilize two type III Secretion Systems ( T3SS 1 and 2 ) to initiate infection , allow replication in phagocytic cells and induce systemic disease . T3SS-1 , which is essential to invade epithelial cells and cross the barrier , forms an extracellular needle and syringe necessary to inject effector proteins into the host cell . PrgI and SipD form , respectively , the T3SS-1 needle and the tip complex at the top of the needle . Because they are common and highly conserved in all virulent Salmonella spp . , they might be ideal candidate antigens for a subunit-based , broad-spectrum vaccine . We investigated the immunogenicity and protective efficacy of PrgI and SipD administered by subcutaneous , intranasal and oral routes , alone or combined , in a mouse model of Salmonella intestinal challenge . Robust IgG ( in all immunization routes ) and IgA ( in intranasal and oral immunization routes ) antibody responses were induced against both proteins , particularly SipD . Mice orally immunized with SipD alone or SipD combined with PrgI were protected against lethal intestinal challenge with Salmonella Typhimurium ( 100 Lethal Dose 50% ) depending on antigen , route and adjuvant . Salmonella T3SS SipD is a promising antigen for the development of a protective Salmonella vaccine , and could be developed for vaccination in tropical endemic areas to control infant mortality .
Salmonellae are members of the Enterobacteriaceae family , a large group of Gram-negative bacteria [1] . While consisting of only two species ( enterica and bongori ) , there are a multiplicity of subspecies among which enterica spp . represent 99% of Salmonella infections in warm-blooded animals and humans [2–3] . The Salmonella that induce human diseases are divided into typhoidal serotypes ( S . Typhi and S . Paratyphi A and B ) and thousands of non-typhoidal serotypes [4] . While Salmonella infections are usually responsible for a self-limiting gastroenteritis or a relatively well controlled typhoid fever in healthy humans of high-income countries [5] , they remain a serious health hazard in Asian and African countries , where they manifest as invasive illnesses associated with high morbidity and mortality rates [6]: enteric fever caused by Typhoidal Salmonella and mainly found in South and South-East Asia and invasive Non-Typhoidal Salmonella ( iNTS ) characterized by severe extra-intestinal invasive bacteremia in sub-Saharan Africa [7–8] . Currently , three types of Salmonella vaccines are licensed: the oral live attenuated Salmonella Typhi Ty21a vaccine and the parenteral Vi capsular polysaccharide antigen , either unconjugated or conjugated to tetanus toxin [9–12] . However , all of them target S . Typhi and are not cross-protective against other Salmonella serovars , except for slight protection afforded by the Ty21a vaccine against S . Paratyphi B ( which represents a minority of cases among all paratyphoid cases ) [13] . None of them are protective against non-typhoidal Salmonella . The multiplicity of Salmonella serovars [14] , the high global burden of the disease as well as the emergence of strains resistant to anti-microbial drugs [15–18] make the development of an effective broad-spectrum Salmonella vaccine even more urgent . Thus , efforts to develop a multivalent vaccine that targets the different serovars ( S . Typhi , S . Paratyphi , S . Typhimurium , S . Enteritidis and S . Choleraesuis ) are needed to control invasive Salmonella infections worldwide [19] . Salmonella , as facultative intracellular bacteria , are found within a variety of phagocytic and non-phagocytic cells in vivo [20] . Following intestinal adherence , invasive Salmonella bacteria preferentially enter microfold ( M ) cells and transport them to lymphoid cells in the underlying Peyer’s Patches ( PPs ) [21] . Salmonella can also induce its internalization in non-phagocytic enterocytes and actively invade them through its virulence-associated type 3 secretion system encoded by Salmonella Pathogenicity Island 1 ( SPI-1 ) [22] . After crossing the intestinal barrier at the site of PPs , the bacteria are taken up by phagocytic immune cells like macrophages and dendritic cells . Once phagocytosed , Salmonella replicate within a modified phagosome known as the Salmonella-containing vacuole ( SCV ) in the cytoplasm [23–24] . A second type 3 secretion system encoded by Salmonella Pathogenicity Island 2 ( SPI-2 ) seems to play a crucial role in this replication process and in survival within macrophages and consequently in systemic virulence [25] . However , there is increasing evidence that the so-called chronological and localized partitions of SPI-1 and SPI-2 T3SS roles become less and less clear and that both T3SS-1 and T3SS-2 contribute to multiple stages of pathogenesis [26–27] . Type 3 secretion systems ( T3SSs ) or injectisomes are bacterial macromolecular organelles that are involved in the pathogenesis of many important human , animal and plant diseases [28] . T3SSs are widely distributed in gram-negative pathogens and are structurally conserved across species . These injectisomes are composed of a basal body that traverses the inner and outer bacterial membrane and a needle-like complex that emerges at its apical end , through which effectors are secreted [29] . The T3SS-1 needle of S . Typhimurium is built by the helical polymerization of several hundred subunits of a single small protein ( PrgI , 8 . 9 kDa ) , while the needle-tip is formed by a pentameric hydrophilic protein complex ( SipD , 35 . 1 kDa ) connecting the distal end of the needle to the membrane-spanning translocon ( SipB , SipC ) [30] . Therefore , during infection , the bacteria receive an external signal from the host environment and begin to assemble coordinately the constituents of the secretion system [31] . Because T3SS-1 is essential for virulence and is conserved among all pathogenic Salmonella strains , T3SS-1 proteins appear as ideal candidates for vaccine development . A subunit-based vaccine would provide broader coverage across multiple serotypes and would also simplify vaccine production and formulation . With this aim , we examined the immunogenicity of the Salmonella PrgI and SipD proteins , administered alone or together , by comparing subcutaneous , intranasal and orogastric immunization routes in a mouse model . Protective efficacy was determined against lethal oral intestinal infection with Salmonella Typhimurium . We provide the first demonstration that SipD might be a promising target antigen for a Salmonella vaccine .
All experiments were performed in compliance with the French and European regulations on care and protection of laboratory animals ( European Community [EC] Directive 86/609 , French Law 2001–486 , 6 June 2001 ) and with agreement of the ethical committee ( CETEA ) no . 12–026 and 15–055 delivered to S . Simon and agreement D-91-272-106 from the Veterinary Inspection Department of Essonne ( France ) . Biotin N-hydroxysuccinimide ester and streptavidin were from Sigma-Aldrich . Goat anti-mouse IgG and IgM polyclonal antibodies were from Jackson ImmunoResearch . Rat anti-mouse IgG1 , IgG2a and IgG2b antibodies were from AbD Serotec . Goat anti-mouse IgA antibodies were from CliniSciences . Sandwich ELISAs were performed with MaxiSorp 96-well microtiter plates ( Nunc , Thermoscientific ) , and all reagents were diluted in Enzyme ImmunoAssay ( EIA ) buffer ( 0 . 1 M phosphate buffer [pH 7 . 4] containing 0 . 15 M NaCl , 0 . 1% bovine serum albumin [BSA] , and 0 . 01% sodium azide ) . AEBSF ( serine protease inhibitor ) was from Interchim . Dialysis membranes were from Spectra/Por . Cholera Toxin and Luria Broth were from Sigma . PBS was from Gibco by Life Technologies . The prgi and sipd genes of Salmonella Typhimurium were synthesized ( Genecust ) based on the published sequence of strain CIP 104474 ( Pasteur Institute Collection ) , and cloned into NdeI/XhoI restriction sites of the IPTG inducible pET22b vector ( Novagen ) , allowing insertion of a poly-histidine tag sequence at the 3′ end of the genes . The pET22b recombinant plasmids were used to transform competent E . coli BL21 ( DE3 ) cells . For each gene , one transformant was grown overnight in Luria Broth ( LB ) with 100 μg/mL ampicillin at 37°C . 5 mL of this preculture was added to 400 mL of LB + ampicillin for 2 h at 37°C until the mid-log phase was reached ( OD600 nm = 0 . 7 ) and induced for 3 hours at 37°C by isopropyl-β-D-thiogalactopyranoside ( 1 mM IPTG ) Cells were harvested by centrifugation at 4 , 000 x g for 15 min at 4°C and resuspended on ice in 5 mL of sonication buffer ( 0 . 05 M Tris-HCl pH 8 , 0 . 1 M NaCl , 1 mM AEBSF ) . The bacterial suspensions were then sonicated 3 times at 10–15 Watts for 15 seconds and centrifuged at 14 , 000 x g for 15 min at 4°C . The pellets containing the inclusion bodies were dissolved overnight at 4°C in 5 mL of solubilization buffer ( 0 . 05 M Tris-HCl pH 8 , 0 . 2 M NaCl , 8 M urea ) . After centrifugation at 20 , 000 x g for 10 min at 4°C , the clarified supernatants were diluted with 20 mL of binding buffer supplemented with 10 mM imidazole before application to pre-equilibrated 2 mL of Ni-NTA affinity resin ( Chelating Sepharose Fast Flow , GE Healthcare ) for 1 h at room temperature . After washing with 20 mL of binding buffer , elution of proteins was performed with elution buffer ( 0 . 05 M Tris-HCl pH 8 , 0 . 2 M NaCl , 8 M urea and 0 . 5 M imidazole ) . The eluted fractions were pooled and dialyzed in 2 L of 50 mM phosphate buffer , pH 7 . 4 , 150 mM NaCl in a molecular membrane porosity of 3 . 5 kD . Protein concentrations were measured by absorbance at 280 nm ( A280 ) using the NanoDrop Spectrophotometer and the purity was assessed by SDS PAGE ( 10–15% gradient Phast Gel , Phast system , GE Healthcare ) . Purified recombinant proteins were stored at -20°C until use . Far-UV CD spectra were collected for SipD and PrgI . Briefly , a Jasco J-815 spectrometer fitted with a Peltier temperature controller ( Jasco ) was used to collect spectra from 190 nm to 250 nm through a 0 . 1-cm-length quartz cuvette . Samples were kept at 20°C and scanned at 100 nm/min with a 1-nm spectral resolution and a 1-s data integration time . All spectra are an average of three measurements . All protein solutions were made to 0 . 1 mg/mL in potassium phosphate buffer , pH 7 . 4 . Far-UV CD signals were converted to mean residue molar ellipticity . Six- to 8-week-old female BALB/c mice ( Janvier Labs , France ) were used for all experiments , by groups of 14–16 mice . For subcutaneous ( SC ) and intranasal ( IN ) immunizations , mice were anesthetized with isoflurane delivered through a vaporizer . Mice were immunized subcutaneously or intranasally on days 0 , 21 and 42 with 20 μg of proteins in 100 μL of PBS ( SC ) or 10 μg in 20 μL of PBS ( IN ) , administered separately or in 1:1 mixture . The proteins admixed with alum hydroxide ( 1:1 ) ( SC ) or with 1 . 5 μg cholera toxin ( IN ) adjuvant , were incubated for 1 h in a shaker at room temperature before immunization . For orogastric ( OG ) immunizations , 300 μg of each protein or of combined proteins ( in 200 μL of PBS admixed with 10 μg of cholera toxin ) was administered to mice on days 0 , 21 and 42 ( for the three immunizations ( 3I ) protocol ) and on days 0 , 21 , 42 and 63 ( for the four immunizations ( 4I ) protocol ) . Mice that received only adjuvant and PBS were included as controls . Animals were monitored daily after immunizations . All graphics and statistical analysis were generated using GraphPad Prism 5 . Statistical significance was assessed using the non-parametric Mann-Whitney test to compare antibody concentrations and titers . Survival curves were compared using a two-tailed Fisher’s exact test . A P value <0 . 05 was considered significant in all determinations .
To produce the large amounts of purified PrgI and SipD proteins necessary to immunize mice , the corresponding genes were cloned into the IPTG inducible pET22b plasmid , generating genes carrying a poly-histidine tag sequence at their 3’ ends . The resulting recombinant vectors were then introduced into E . coli BL21 and expression of the proteins led to the production of 2 . 3 mg/L and 1 . 4 mg/L of SipD and PrgI , respectively , in inclusion bodies . Purity of the proteins was assessed by SDS PAGE electrophoresis and Coomassie blue staining ( Fig 1A ) . Far-UV CD spectroscopy was employed to assess the secondary structure of the purified recombinant proteins . The CD measurements of PrgI and SipD showed spectra exhibiting dominant minima at 208 and 222 nm , characteristic of proteins with α-helical secondary structures ( Fig 1B ) thus assessing their correct refolding . The kinetics of serum Ig ( G+M ) responses against Salmonella PrgI and SipD are shown in S1 Fig . Mice immunized subcutaneously ( SC ) , intranasally ( IN ) and orally ( OG ) with PrgI and SipD proteins separately ( Fig 2A ) or combined ( Fig 2B ) in the presence of alum ( SC ) or cholera toxin ( CT , for IN and OG immunizations ) developed antigen-specific antibody responses . Except for IN immunization , whatever the other routes of immunization , the specific antibody titers against each protein were equivalent in terms of concentrations and kinetics when proteins were administered alone ( PrgI or SipD ) or together ( PrgI/SipD ) ( compare panels A and B for each route of immunization ) , meaning that none of the proteins in the mixed administration was dominant over the other and used the immune response to its advantage . Except for the IN route , the antibody titers with SipD were greater than with PrgI ( Table 1 ) . For all immunization routes , serum Ig ( G+M ) antibodies to SipD and PrgI were detected rapidly ( 2 weeks ) after the first immunization and reached a plateau after the second ( SipD , SC route ) , the third ( IN routes for PrgI and SipD , SC for PrgI ) or the fourth immunization ( OG routes , PrgI and SipD ) . PrgI-specific Ig ( G+M ) concentrations reached the highest values by the IN route ( 14 μg/mL measured at day 84 , one month after the third immunization , see Table 1 ) up to 2 logs better than OG or SC routes . Comparatively , SipD-specific Ig ( G+M ) production after IN immunization was delayed , and the peak concentration was ten-fold reduced compared with PrgI-specific Ig ( G+M ) ( 1 . 7 . 103 ng/mL at day 84 ) . In contrast , titers obtained for SipD immunizations were one log better by the SC route than the others . Because entry of pathogenic Salmonella occurs via the oral route , oral immunization would induce a first line of defense at the mucosal epithelial surface , through inhibition of bacterial penetration into the PPs . With this goal in mind , we examined the immunogenicity of PrgI and SipD when administered to mice orally in the presence of CT as adjuvant . Two studies were performed in which we compared the effect of 3 or 4 injections of the proteins . The groups immunized with SipD , in both cases , exhibited the highest levels of serum Ig ( G+M ) with no significant difference between the 2 protocols ( 1 . 3 vs 1 . 8 μg/mL , 4 weeks after the last immunization ) . In contrast , the mice immunized with PrgI , responded poorly in both cases ( 290 ng/mL , after the last immunization ) , confirming that PrgI was less immunogenic than SipD . To evaluate the induction of IgA antibodies in the mucosa , which represent the first line of adaptive immune defense against enteric pathogens , the PrgI- and SipD-specific IgA titers in serum from immunized and control mice were measured , 2 weeks after the last immunization ( Fig 3 and Table 1 ) . As expected , and like controls , mice immunized subcutaneously did not produce any IgA antibodies . For each protein , the specific IgA titers were equivalent for mice immunized intranasally or orogastrically 3I or 4I ( Table 1 ) . The titers of PrgI-specific IgA in mice immunized by the IN route were slightly higher than those of mice immunized IN with SipD , as observed for IgG titers . Comparatively , the IgA titers obtained for mice immunized with both proteins were lower than those obtained for mice immunized by each protein separately ( Tables 1 and 2 ) . To investigate further the immune response elicited by the different routes of immunization , the PrgI- and SipD-specific IgG1 , IgG2a and IgG2b subclasses were measured in serum from immunized and control mice at day 56 ( after the third immunization ) for the SC , IN , OG ( 3I ) routes and at day 77 ( after the fourth immunization ) for the OG ( 4I ) route ( S2 Fig ) and Table 1 ) . Measurement of the IgG isotype concentrations in sera of immunized mice revealed that all main subclasses contributed to the humoral response whatever the route . It should be noted that for the majority of Ig ( G+M ) measurements ( Table 1 ) , the concentrations were below the sum of the concentrations obtained for the different IgG isotypes . This could be due to the antibodies used for the standard curve in the sandwich ELISA: a mixture of specific PrgI or SipD IgG1:IgG2a:IgG2b ( 1:1:1 ) was used as a standard of Ig ( G+M ) polyclonal antibodies , which does not exactly reflect the diversity of a polyclonal response ( and particularly the IgM production ) , by comparison with the other tests where each specific isotype was used . Overall , IgG1 were found in higher concentration after SC route immunization compared with the other routes , for PrgI or SipD . While SipD elicited a strong IgG1 response whatever the route , PrgI IgG1 quantities were much lower ( 10- to 100-fold ) by the IN and OG routes compared with the SC route ( upper panels A and B , S2 Fig and Table 1 ) . The same profile was obtained for specific PrgI IgG1 and IgG ( 2a+2b ) antibodies , with the highest concentration ( 14 μg/mL ) obtained for the SC route and the lowest ( 100 ng/mL ) for the OG ( 3I ) route . IgG1 and IgG ( 2a+2b ) are respectively indicators of the T helper type 2 ( humoral ) and type 1 ( cellular ) immune responses . IgG ( 2a+2b ) :IgG1 ratios were taken as indicators of the T helper type 1 ( Th1 ) / Th2 balance , in order to evaluate the contribution of each pathway to the immune response . As Salmonella are facultative intracellular pathogens and multiply in macrophages , the ratio of IgG ( 2a+2b ) to IgG1 titers was determined ( Fig 4 ) . For PrgI immunizations , the Th1/Th2 balance was clearly in favor of the cellular ( Th1 ) immune response ( 100-fold more IgG ( 2a+2b ) than IgG1 ) for the IN and OG routes , and close to 1 for the SC route ( Fig 4 ) . Interestingly , the profile of SipD-specific antibodies was the opposite of the PrgI antibody profile: a 10-fold higher IgG1 response was obtained for the OG route ( 5 to 7 μg/mL ) than IgG ( 2a+2b ) antibody response ( S2 Fig and Table 1 ) . Thus , the Th1/Th2 balance appears in favor of humoral immunity for the SipD immunogen ( Fig 4 ) . Similar results were obtained when both proteins were administered together , with a Th1/PrgI and a Th2/SipD response ( compare left panels A and B for PrgI and right panels A and B for SipD , S2 Fig and Fig 4 ) . The oral lethal dose 50% ( LD50 ) of the S . Typhimurium strain used in the experiments ( see experimental procedures ) was determined at 104 CFU/mL . To assess the protective efficacy induced by PrgI or SipD , immunized and control mice were subjected to oral challenge , six weeks after the last immunization , with ~100 LD50 ( 106 CFU/mL ) of S . Typhimurium ( Fig 5A–5D ) . In all challenges , the mortality rate of control animals ( PBS/adjuvant immunized mice ) was 100% with death occurring at 15–18 days after challenge . The protective efficacy of the PrgI and SipD proteins by SC immunization was 19% and 25% , respectively ( Table 3 ) . Two-fold higher protection was observed for mice vaccinated by the IN route ( 44% and 50% for PrgI and SipD , respectively ) . Mice immunized thrice orally with PrgI and SipD did not exhibit better protection ( 21 . 5% and 43% , respectively ) . The highest level of protection ( 71 . 5% ) was obtained for mice immunized four times by the oral route with SipD , while those immunized with PrgI exhibited only 29% protection . In all cases , the admixed proteins provide less or equivalent protection than SipD alone , showing that there was no synergistic protection effect of proteins administered together .
The ID numbers of proteins mentioned in the text are AAB60189 . 1 for PrgI and AAA86617 . 1 for SipD ( from NCBI ) . | Salmonella are bacteria responsible for a high global burden of invasive diseases , especially in South and South-East Asia ( mainly enteric fever due to Salmonella Typhi ) and sub-Saharan Africa ( mainly invasive Non-Typhoidal Salmonella , iNTS ) . This iNTS disease has emerged as a prominent cause of systemic infection in children and immunocompromised African adults , with an associated case fatality of 20–25% . Because licensed vaccines only protect against enteric fever , there is a crucial need to develop a new broad-spectrum vaccine effective against enteric fever and iNTS that can be administered safely to children under 2 years old . The virulence of Salmonella depends on two type III secretion systems ( T3SS-1 and T3SS-2 ) necessary for invasion , replication , intracellular survival and dissemination of the bacteria . Two structural proteins of T3SS-1 ( essential for crossing the epithelial barrier ) are highly conserved among Salmonella spp . and might be good candidates for a broad-spectrum vaccine . The current study describes the protective effect elicited by these proteins in a murine model . A specific immune response was generated against our antigens and provided protection against Salmonella Typhimurium oral infection . Such a candidate vaccine offers promising perspectives to control Salmonella diseases . | [
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] | 2016 | Role of T3SS-1 SipD Protein in Protecting Mice against Non-typhoidal Salmonella Typhimurium |
The Community Dialogue Approach is a promising social and behaviour change intervention , which has shown potential for improving health seeking behaviour . To test if this approach can strengthen prevention and control of schistosomiasis at community level , Malaria Consortium implemented a Community Dialogue intervention in four districts of Nampula province , Mozambique , between August 2014 and September 2015 . Cross-sectional household surveys were conducted before ( N = 791 ) and after ( N = 792 ) implementation of the intervention to assess its impact on knowledge , attitudes and practices at population level . At both baseline and endline , awareness of schistosomiasis was high at over 90% . After the intervention , respondents were almost twice as likely to correctly name a risk behaviour associated with schistosomiasis ( baseline: 18 . 02%; endline: 30 . 11%; adjusted odds ratio: 1 . 91; 95% confidence interval: 1 . 14–2 . 58 ) . Increases were also seen in the proportion of people who knew that schistosomiasis can be spread by infected persons and who could name at least one correct transmission route ( baseline: 25 . 74%; endline: 32 . 20%; adjusted odds ratio: 1 . 36; 95% confidence interval: 1 . 01–1 . 84 ) , those who knew that there is a drug that treats the disease ( baseline: 29 . 20% , endline: 47 . 55%; adjusted odds ratio: 2 . 19; 95% confidence interval: 1 . 67–2 . 87 ) and those who stated that they actively protect themselves from the disease and cited an effective behaviour ( baseline: 40 . 09% , endline: 59 . 30%; adjusted odds ratio: 2 . 14; 95% confidence interval: 1 . 40–3 . 28 ) . The intervention did not appear to lead to a reduction in misconceptions . In particular , the belief that the disease is sexually transmitted continued to be widespread . Given its overall positive impact on knowledge and behaviour at population level , Community Dialogue can play an important role in schistosomiasis prevention and control . The intervention could be further strengthened by better enabling communities to take suitable action and linking more closely with community governance structures and health system programmes .
Schistosomiasis is one of the most common parasitic diseases , with approximately 190 million people infected worldwide [1] , causing over 100 , 000 deaths [2] and the loss of over 1 . 8 million disability-adjusted life years every year [3] . The disease is caused by worms of the Schistosoma ( S . ) genus , which use certain types of freshwater snails as intermediary hosts . The infected snails release cercariae , which infect humans by penetrating the skin when they come into contact with freshwater that contains the parasite . Inside the human body , the cercariae go through several stages and eventually grow into adult worms , which live in infected people’s blood vessels . Here they undergo sexual reproduction , producing and releasing eggs into the lumen of the gut , bladder or urinary tract . The parasite’s life cycle is completed when infected people excrete its eggs while urinating or defecating near freshwater , where the eggs hatch and the resultant miracidia infect the snails [4 , 5] . One of the countries most affected by schistosomiasis is Mozambique , where the main parasite species present is S . haematobium . Countrywide , the prevalence of S . haematobium infection among school-age children is 47% [6] and 18 million of the total population of 23 . 5 million require preventive chemotherapy [7] . S . haematobium causes urogenital schistosomiasis , of which the defining symptom is blood in the urine . Pathology can also include scarring , calcification , bladder cancer , and occasional ectopic egg granulomas in brain or spinal cord [4 , 5] . In areas with moderate to high transmission of schistosomiasis , a key disease control strategy is preventive chemotherapy using praziquantel , typically delivered to at-risk populations in the form of periodic , large-scale mass drug administration ( MDA ) [8] . Other prevention and control strategies recommended by the World Health Organization include increasing access to and use of safe water , improving sanitation and hygiene , and implementing snail control [9] . Individual and community perceptions of schistosomiasis are likely to have a significant impact on schistosomiasis transmission and uptake of disease prevention and control interventions . For example , preventive chemotherapy programmes are more likely to be successful if they are adapted to local circumstances to build trust , address fear of side effects and correct misconceptions about the treatment among target populations [10] . Social and behaviour change and community engagement are therefore crucial elements of successful MDA campaigns [11] and will also have an important role to play in improving adoption of positive health seeking behaviours more generally [12] . The Community Dialogue Approach [13] is a promising social and behaviour change and community engagement intervention , which has shown potential for improving uptake of health services and promoting recommended behaviours in the context of Integrated Community Case Management of childhood illness [14] . In this approach , volunteers from within the community receive a brief training on a health issue and group facilitation skills . Equipped with a set of visual tools , the volunteers then host regular community meetings to discuss the health issue . Each meeting comprises three stages: The Community Dialogue Approach targets both individual and social behaviour determinants [15]: It seeks to increase individuals’ knowledge and awareness of a health issue by sharing key messages through the volunteers and visual tools ( during the “explore” and “identify” stages ) , but it also aims to influence social norms through public dialogue and collective decision making ( during the “identify” and “decide” stages ) . Although only a small proportion of the population will actively participate in community meetings , knowledge is expected to spread through word of mouth , while changing social norms are expected to affect the wider community to which the norms apply . To assess if the Community Dialogue Approach can strengthen prevention and control of schistosomiasis at community level , Malaria Consortium conducted an implementation research study in partnership with the Republic of Mozambique’s Ministério de Saúde ( Ministry of Health ) and the Direcção Provincial de Saúde ( Provincial Health Authority ) in Nampula province . Between August 2014 and September 2015 , 157 volunteers facilitated regular community dialogue meetings in four districts of Nampula province , discussing the causes and symptoms of schistosomiasis and how the disease can be prevented and controlled , including MDA and adoption of improved water , hygiene and sanitation practices . The main tool developed for this intervention was a flipchart containing images illustrating key intervention messages . Approximately 1 , 500 community meetings were conducted , each typically comprising between 25 and 45 participants . To evaluate the intervention under programmatic conditions , the implementation research study drew on a range of sources , including qualitative and process evaluation data , mainly focussing on the feasibility and acceptability of the Community Dialogue Approach . Another component of the study explored the intervention’s impact on knowledge , attitudes and practices ( KAP ) at population level , testing the assumption that the intervention will have impact beyond those who actively participate in community meetings . To this end , two cross-sectional household surveys were conducted in the four study districts , immediately before ( baseline ) and after ( endline ) implementation of the Community Dialogue intervention . Baseline survey results have been published [16] and showed that while awareness of the disease was high , correct knowledge of how it is acquired , transmitted and prevented was low . Few respondents reported that their children had received MDA and the misconception that schistosomiasis is sexually transmitted was widespread . Only a minority of respondents reported practicing protective behaviours . This paper presents unpublished endline survey data , demonstrating changes in population-level KAP over the course of the Community Dialogue intervention . A paper describing the intervention in more detail , as well as presenting qualitative and process evaluation data exploring its feasibility and acceptability will be published elsewhere .
The study was conducted in Nampula province ( Fig 1A ) , which records the highest provincial schistosomiasis prevalence figures in Mozambique , with around 78% of school-age children infected with S . haematobium [6] . The four study districts of Eráti , Mecubúri , Mogovolas and Murrupula ( Fig 1B ) were selected purposively in consultation with the Direcção Provincial de Saúde . Prevalence of schistosomiasis in the districts was known to be high and they were considered to be comparable with regard to the population’s exposure to common risk factors . Specifically , large proportions of the population depend on subsistence agriculture in or near freshwater sources , and there is poor access to clean water for bathing and washing . According to the 2007 Mozambique census , the total population in the four study districts is approximately 839 , 000 [17] . An integrated neglected tropical disease ( NTD ) control programme is implemented in all study districts and regular MDA has been conducted since 2009 . According to an independent MDA coverage survey carried out in 2015 , coverage was comparatively high across northern Mozambique , but lower in Nampula than in any of the other provinces [18] . Only two of the four districts ( Mecubúri and Murrupula ) received MDA for schistosomiasis while the community dialogue intervention was implemented . These campaigns targeted the entire population over five years of age , whereas MDA conducted before the start of the intervention had targeted school-age children between five and 14 years . Reported programme coverage was 64% and 81% respectively . According to the Direcção Provincial de Saúde , no other programmes targeting schistosomiasis prevention and control were implemented in the study area during the study period . Baseline and endline KAP surveys were designed as cross-sectional household surveys , with the four study districts considered as one sampling domain . All households were eligible for selection . It was calculated that , when comparing proportions between baseline and endline , a sample size of 389 households was needed to give 80% power to detect a change of at least 10% , conservatively assuming a percentage of 50% at baseline . In order to adjust for confounders , non-response and design effect , the sample size was more than doubled to an intended sample size of 800 households for each survey . Using proportional-to-size methods , 40 out of the 68 enumeration areas in the four study districts used in the 2007 census were randomly selected . Enumeration areas are based on localidades , the lowest level of the central state administration . Some larger localidades are further subdivided into bairros , which loosely correspond to villages and communities . In a second step , 20 households were selected in each of the 40 enumeration areas , using a random sampling approach adapted from the one recommended for malaria indicator surveys [19] . Household sampling was based on lists of households obtained from community leaders . Taking into account available time and budget , it was not possible to perform household mappings , but field teams were instructed to discuss the reliability of the household lists with community leaders and correct inaccuracies before commencing the sampling process . In each selected household , the household member best placed to answer questions about the household’s health as nominated by the acting household head was interviewed . Only household members over 18 years were eligible . Participation in a Community Dialogue meeting was not a selection criterion . If selected households could not be located , no eligible respondent was available despite at least three repeated visits to the household or respondents declined to be interviewed , the household was dropped from the sample without replacement . To avoid bias and for operational reasons , different samples were selected for the two surveys . It is therefore unlikely that the households sampled or individuals interviewed at baseline and endline were identical . Baseline data were collected in July 2014 , just before the start of the Community Dialogue intervention . The endline survey was conducted in December 2015 , shortly after completion of the intervention . On both occasions , data were collected by five field teams , each comprising four researchers and one supervisor . Researchers were typically educated to college level , while supervisors were required to have completed a university degree . All field team members were native speakers of Macua , the language commonly spoken in the study districts . Before the surveys , they were trained on the survey procedures , data collection tools and interview techniques . Consent procedures and issues relating to ethical data collection were also discussed . Researchers were trained for three days and supervisors for four days , including one day in the field to conduct a mock survey . A structured face-to-face questionnaire ( S2 Appendix ) was developed in English and subsequently translated into Portuguese . Survey questions were further translated into Macua . Accuracy of the Macua translation was checked with researchers and supervisors during the baseline training . The mock survey conducted as part of the baseline training was used to pre-test the questionnaire . Field teams were instructed to establish the most appropriate local term for schistosomiasis in each community where the survey was conducted in consultation with district health staff and community leaders and to use this term throughout the interview . Otherwise , researchers read out questions exactly as provided . Responses were recorded on paper , assigning them to pre-defined answer categories , which were provided in Portuguese at the request of the field researchers as there is no tradition of reading and writing in Macua . After asking questions about the drug that treats schistosomiasis , field researchers informed all respondents that the name of the drug is praziquantel and showed sample tablets before proceeding to ask whether any of the children living in the household had ever received the drug . Only respondents with children living in their households were asked this question , as prior to the baseline survey , MDA had exclusively targeted school-age children . Table 1 illustrates how the topics covered by the questionnaire relate to the three stages of each Community Dialogue meeting . Data were independently double-entered into EpiData 3 . 1 ( EpiData Association ) by data entry officers who had attended a one-day training . Where differences between first and second entry were detected , records were verified against the paper questionnaire . Data were further checked for consistency and prepared for analysis using STATA Version 12 ( StataCorp LP ) . Responses recorded under ‘other’ were reviewed by senior members of the study team and either re-assigned to a pre-defined answer category , assigned to a newly created category or left in the ‘other’ category . The survey procedures in STATA were used to account for the study design . All percentages reported are population average estimates . Only results considered programmatically relevant are reported in this paper , but more detailed survey responses , including 95% confidence intervals ( CI ) , at baseline and endline can be found in S3 Appendix . To examine the association between baseline and endline KAP results , a multivariate logistic regression analysis was conducted for eleven key indicators . See S4 Appendix for an overview of how the key indicators were operationalised . Odds ratios ( ORs ) were calculated to provide a quantifiable measure of the increased likelihood of respondents having correct KAP after , compared with before the intervention . ORs were adjusted for sex , education and district , the three socio-demographic characteristics consistently associated with significant KAP differences at baseline [16] . Unadjusted ORs for key indicators are reported in S5 Appendix . Statistical significance of unadjusted and adjusted ORs was determined by a Wald p-value of <0 . 05 . Ethical approval for the study , including the consent procedures used for the two KAP surveys , was granted by the University of Leeds School of Medicine Research Ethics Committee ( SoMREC/13/071 ) and the Comité Nacional de Bioética para Saúde in Mozambique ( 42/CNBS/2014 ) . Participation in the surveys was voluntary and informed written consent was taken from all respondents . All data were kept confidential and have been anonymised .
At baseline , five of the 800 randomly selected households could not be located or a suitable respondent was not available despite repeated visits to the household . A further four households were retrospectively excluded from the analysis because respondents’ ages were recorded as under 18 . A total of 791 respondents were therefore included in the analysis . At endline , three of the 800 selected households could not be located or a suitable respondent was not available . A further five households were excluded because respondents’ ages were recorded as under 18 , resulting in a total of 792 respondents included in the analysis . None of the selected households declined to be interviewed . Table 2 shows survey respondents’ socio-demographic characteristics at baseline and endline . Adjusted ( aOR ) and unadjusted ORs for all key indicators were generally found to be similar . There was therefore no confounding by sex , education or district and , with the exception of children who have taken praziquantel , results by socio-demographic respondent characteristics will not be reported in this paper . However , key indicators analysed by sex , education and district can be found in S6 Appendix .
The KAP surveys aimed to detect changes in knowledge , attitudes and practices with regard to schistosomiasis prevention and control at population level over the course of a Community Dialogue intervention . They were not designed to: Another limitation relates to the languages used to develop survey tools and to conduct the survey . While the quality of translations of data collection tools and researcher training materials was checked repeatedly , it is possible that subtleties got lost in the translation chain from English to Portuguese to Macua . Similarly , though care was taken to use appropriate local terminology and formative research carried out before the baseline survey concluded that local terms for schistosomiasis broadly concur with the biomedical definition of the disease , it cannot be ruled out that some respondents may have referred to disparate disease concepts . Finally , responses regarding adoption of practices need to be interpreted bearing in mind that the survey relied on self-reporting . It was not possible to objectively verify survey participants’ responses . In general , social desirability bias may have led respondents to give answers they considered more socially acceptable . While this would have applied at both baseline and endline , the pressure to give socially desirable responses may have been stronger following an intervention designed to shape social norms . The survey results are thought to be representative of the population in the four study districts . As the study area shares many characteristics of predominantly rural , resource-poor areas in sub-Saharan Africa and our findings reflect those of other studies in similar settings , the results reported in this paper are thought to have wider applicability . We therefore believe that , given its overall positive impact on knowledge , attitudes and practices , the Community Dialogue Approach can play an important role in affecting positive social and behaviour change , a key requirement for improved disease prevention and control identified by a recent systematic review [27] . The approach goes beyond more established community engagement approaches for NTD control , such as community-directed delivery of MDA [35] or involving community health workers in the detection of suspected NTD cases [36] . Rather than being community-directed or community-based , it is community-owned and has the potential to serve as a platform for community participation , conceived as a process rather than an outcome [37] , beyond a single disease or control intervention . More research is needed , however , to investigate the intervention’s mechanisms of impact , trace the spread of information , as well as uncover the conditions under which Community Dialogue can correct misconceptions and trigger sustainable behaviour change . Further research should also include testing of the required intervention dose and reach to determine the number of facilitators required per population unit , the percentage of the population that needs to actively participate in community meetings , or the required number and frequency of community meetings . | Schistosomiasis is a parasitic neglected tropical disease that affects around 190 million people worldwide , causing chronic ill health and disability . Central to its prevention and control are the acceptance of health interventions such as the distribution of drugs on a mass scale and the adoption of good hygiene and sanitation practices in communities where the disease thrives . One promising method for promoting such behaviours is the Community Dialogue Approach , which involves training volunteers to host regular community meetings , where local health concerns are discussed and culturally appropriate solutions are agreed upon . In 2014/15 , Malaria Consortium implemented a Community Dialogue intervention in four districts of Nampula province , Mozambique , to improve knowledge , attitudes and practices with regard to schistosomiasis prevention and control . To assess the effectiveness of the approach , two household surveys were conducted . Results show that before the intervention , knowledge of how schistosomiasis is acquired , transmitted , prevented and treated was low . After the intervention , knowledge and self-reported adoption of positive behaviours had improved substantially , demonstrating that Community Dialogue can play a central role in strengthening disease prevention and control . The approach could be strengthened by further empowering communities to take action and reducing deeply-held misconceptions . | [
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] | 2019 | Knowledge, attitudes and practices with regard to schistosomiasis prevention and control: Two cross-sectional household surveys before and after a Community Dialogue intervention in Nampula province, Mozambique |
As the world’s fastest spreading vector-borne disease , dengue was estimated to infect more than 390 million people in 2010 , a 30-fold increase in the past half century . Although considered to be a non-endemic country , mainland China had 55 , 114 reported dengue cases from 2005 to 2014 , of which 47 , 056 occurred in 2014 . Furthermore , 94% of the indigenous cases in this time period were reported in Guangdong Province , 83% of which were in Guangzhou City . In order to determine the possible determinants of the unprecedented outbreak in 2014 , a population-based deterministic model was developed to describe dengue transmission dynamics in Guangzhou . Regional sensitivity analysis ( RSA ) was adopted to calibrate the model and entomological surveillance data was used to validate the mosquito submodel . Different scenarios were created to investigate the roles of the timing of an imported case , climate , vertical transmission from mosquitoes to their offspring , and intervention . The results suggested that an early imported case was the most important factor in determining the 2014 outbreak characteristics . Precipitation and temperature can also change the transmission dynamics . Extraordinary high precipitation in May and August , 2014 appears to have increased vector abundance . Considering the relatively small number of cases in 2013 , the effect of vertical transmission was less important . The earlier and more frequent intervention in 2014 also appeared to be effective . If the intervention in 2014 was the same as that in 2013 , the outbreak size may have been over an order of magnitude higher than the observed number of new cases in 2014 . The early date of the first imported and locally transmitted case was largely responsible for the outbreak in 2014 , but it was influenced by intervention , climate and vertical transmission . Early detection and response to imported cases in the spring and early summer is crucial to avoid large outbreaks in the future .
Dengue is a febrile illness caused by the dengue virus which is further classified into 4 serotypes ( DENV 1–4 ) , and transmitted by Aedes aegypti and Aedes albopictus mosquitoes . Classically , dengue virus infection produces mild flu-like fevers but can also result in lethal dengue hemorrhagic fever ( DHF ) and dengue shock syndrome ( DSS ) when infected a second time with a different serotype [1] . According to the World Health Organization ( WHO ) , dengue is the fastest growing vector-borne disease in the world with only one thousand cases reported in the 1950s to more than 90 million cases in the 2000s [2] . Estimated from a systematic literature search , there were 96 million apparent dengue infections globally in 2010; however , an additional estimated 294 million infections were asymptomatic [3] . Dengue is believed to be an imported disease in mainland China , and 55 , 114 cases were reported from 2005 to 2014 . Approximately 94 percent of the indigenous cases that occurred in this period were reported in Guangdong Province , and 83 percent of these Guangdong cases were in Guangzhou City [4] . In 2014 , an unprecedented dengue outbreak hit Guangzhou , with 37 , 341 new cases contributing to 94 percent of the new cases from 2005 to 2014 in Guangzhou . The annual new cases in Guangzhou were normally lower than 150 except for the 765 in 2006 , 1 , 249 in 2013 and 37 , 341 in the 2014 outbreak . Guangzhou differs significantly from other dengue transmission areas with Ae . albopictus as the sole vector rather than Ae . aegypti [5] . Unlike Ae . aegypti , Ae . albopictus adapts to the cold winter in temperate and subtropical areas by diapausing , which gives it the ability to expand to higher latitudes . Normally , the adults cannot survive the low temperature in winter , but they can produce diapause eggs when the temperature becomes lower and the day becomes shorter [6 , 7] . These diapause eggs will not hatch until the next spring , when the temperature and water condition become favorable again . Moreover , the vertical transmission of dengue virus in Ae . albopictus is more efficient [8] , with approximately 0 . 5 to 2 . 9 percent of the eggs laid by infected mosquitoes being infected [8–10] . When the vertical infected diapause eggs develop to adults in the next spring , they have the ability to infect humans immediately without biting infected humans , even causing a significant outbreak if there were sufficient infected eggs in the past year . This pathway might allow dengue to become endemic in Guangzhou . The other possibility for dengue to be endemic is through overwintering infected adults , especially when global warming increases the temperature in the winter . However , the daily mean temperature from December to February of the 30-yr average ( the coldest three months ) was 14 . 8°C , and that of 2013 was 14 . 4°C . Thus the possibility for infected adults to live through the winter of 2013 is relatively low , considering that the temperature in the winter of 2013 was not abnormally high . Mathematical models suggest that vertical transmission can increase the endemic level of the vector population and human population significantly [11] . However , Ae . albopictus is less efficient in transmitting dengue virus . Typical explosive DHF epidemics have not been found in the places where Ae . albopicus predominates over Ae . aegypti , such as parts of China , the Seychelles Islands , La Reunion Island , the Maldive Islands , historically in Japan and most recently in Hawaii [12 , 13] . Another possible causal factor for the 2014 outbreak in Guangzhou was the abnormally high precipitation in May and August which provided more breeding sites and increased the environmental carrying capacity for Ae . albopictus [14] . A third possibility was the early starting date of the outbreak , with the earlier imported cases occurring in the late spring and early summer leading to the greater final size of the epidemic as a result of the lengthened infection season before the decrease of Ae . albopictus abundance in the winter [15] . A multivariate Poisson regression analysis of the Guangzhou outbreak data was recently published that showed the number of imported cases , minimum temperature with a one-month lag and cumulative precipitation with a three month lag predicted the outbreak in 2013 and 2014 [16] . Here we use a mathematical model rather than statistical model to further explore the factors underlying these outbreaks since the structure of our model is based on mechanistic factors controlling both mosquito population dynamics and the dynamics of viral transmission explicitly and , therefore , should allow greater confidence in making predictions in the presence of environmental change [17] . There were 99 dengue transmission models cited in literature from 1970 to July 2012 , most based mainly on the Ross-Macdonald model of malaria transmission , the classical theoretical framework for modelling mosquito-borne diseases [18] . However , the core assumptions of some of these models differs from Ross-Macdonald model in various ways . Examples include those explicitly modelling the mosquito immature stage population dynamics [19 , 20] , the temperature-dependent extrinsic incubation period ( EIP ) [21] , vertical and mechanical transmission [11 , 22] , spatial heterogeneity [15 , 23] , control strategies [24 , 25] , or multiple dengue virus serotypes [26] . Stochastic models [15] or agent-based models [27] have also been developed to simulate the transmission dynamics of dengue virus . To emphasize local characteristics , we included only immature stage population dynamics , vertical transmission , control strategies , and temperature-dependent adult mosquito mortality rate , biting rate and the EIP . Coinfection , multiple pathogen types , and temporary immunity were not considered here since dengue virus 1 ( DENV-1 ) has been the only predominant serotype found in Guangzhou since the 1990s [4] . Though the test results for 2014 are not ready , in the 1 , 249 cases of 2013 , 1 , 243 are DENV-1 cases and only 6 are dengue virus 2 ( DENV-2 ) cases . Spatial distributions of the mosquitoes , and heterogeneous biting were not considered here mainly because of limited data availability . In this paper , a population level deterministic mathematical model including explicitly modelled water level and mosquito population in different life stages was developed . Then the parameters in the model were estimated via successive cycles of fitting . Observed monthly mosquito index was used to validate the mosquito submodel . Finally , different scenarios were created to investigate the important mechanisms responsible for the unprecedented outbreak of dengue in 2014 in Guangzhou City .
The study was reviewed and approved by the Ethics Committee of the Guangzhou Center for Disease Control and Prevention . All the patient data were de-identified and the data were analyzed anonymously . Guangzhou is the capital and largest city of Guangdong Province , with a total area of 7 , 434 square kilometers [28] and a population of 13 million at the end of 2013 [29] . ( Fig 1 ) . It is one of the most urbanized areas and the center of China's economic growth . With the Tropic of Cancer crossing just north of the city , Guangzhou has a humid subtropical climate with hot and wet summers and mild and dry winters . The annual average temperature is approximately 21 . 5°C . January is the coldest month with an average temperature of 13 . 0°C while the hottest is July at 28 . 5°C . Annual rainfall varies from 1 , 612 to 1 , 909 mm , with more than 80 percent occurring between April and September [30] . The wet and warm climate is favorable for the growth of Ae . albopictus , which is the secondary vector for dengue virus in the world but the sole vector in Guangzhou [31 , 32] . Though dengue is not endemic in Guangzhou , more than 0 . 30 million travelers from dengue endemic countries such as Malaysia , Singapore , Indonesia , Thailand and India visit Guangzhou each year . These countries are also the top choices for outbound travelers from Guangzhou [33] . Since the natural and socio-economic conditions in Guangzhou are conducive to mosquito growth and reproduction , high densities of Ae . Albopictus together with dengue-infected travelers present a high potential for initiating local spread of the disease [31] . Dengue is a notifiable disease in China which means that , once diagnosed , cases must be reported to the web-based National Notifiable Infectious Disease Reporting Information System ( NIDRIS ) within 24 hours . All case reports used in this analysis were diagnosed according to the National Diagnostic Criteria for Dengue Fever ( WS216-2008 ) published by the Chinese Ministry of Health [34] . In addition , active case detections was carried out through field investigations in the communities with confirmed dengue cases [14] . Cases were then divided into indigenous and imported cases based on whether the patient traveled to a dengue endemic area and was bitten by mosquitoes there within 15 days of the onset of illness [14] . A list of daily reported new cases for 2013 and 2014 , obtained from Guangzhou Center for Disease Control and Prevention ( Guangzhou CDC ) , was used to calibrate the model . This dataset was published online in the transmission season on the website of the Health Department of Guangdong Province ( http://www . gdwst . gov . cn/ ) . There were a total of 1 , 249 and 37 , 341 reported cases for 2013 and 2014 , respectively . Monthly mosquito surveillance reports consisting of the Breteau Index ( BI ) and the Mosquito Ovitrap Index ( MOI ) in 2013 and 2014 were also obtained from Guangzhou CDC and used to validate the mosquito submodel ( S1 Table ) . BI is the number of positive containers with Ae . albopictus larva per 100 houses inspected , and is considered to be the best single index for Aedes density surveillance [14] . MOI is the percentage of Ae . albopictus positive ovitraps in all ovitraps collected from a specified area , and reflects the abundance of the adults [35] . Daily temperature , rainfall and evaporation data for Guangzhou from 2012 to 2014 , which were used as inputs to the model , were downloaded from the China Meteorological Data Sharing Service System ( CMDSSS ) ( http://cdc . nmic . cn/ ) . In addition , climate data from 1985 to 2014 were also retrieved from CMDSSS to calculate 30-year daily average values . Population data for the human submodel was obtained from the Guangdong Statistical Yearbook on China Infobank ( http://www . bjinfobank . com/ ) . This data was also used to estimate human birth rate and death rates in Guangzhou [36–38] . A deterministic mathematical model was developed to interpret the transmission of dengue in Guangzhou city based on the Ross-Macdonald model [39 , 40] , which is a basic framework widely used to study the dynamic transmission of mosquito-borne diseases . Fig 2 presents the structure of our model with Table 1 showing the definition for each symbol in this figure . Temperature can influence the development rate , death rate of immature mosquitoes , average duration of and number of eggs laid each gonotrophic cycle , biting rate and the EIP of dengue virus [41–43] . The form of temperature-dependent functions were based on [20 , 41] , and the coefficients were estimated from experiments on Ae . albopictus strains from Guangzhou and adjacent areas [42 , 44] . Density of the larvae also plays an important role in the development rate of eggs and larvae , and the death rate of larvae . The form of density forcing rates were taken from [27] . More detailed information about the parameters , temperature or density forcing functions for Ae . albopictus development and death rates , and the differential equations for the model can be found in the S1 File . The model includes several modifications to the Ross-Macdonald framework to incorporate the influence of climate factors , vertical transmission and local interventions . First , the immature aquatic phases of Ae . albopictus were modeled explicitly since the development rate of eggs , larva , and pupa , as well as the mortality of larva and pupa can be influenced by temperature and density . Second , a SEI ( Susceptible , Exposed , and Infected ) model was used for mosquito submodel instead of a SI ( Susceptible and Infected ) model to capture the temperature-dependent pathogen latency in Ae . albopictus . Thirdly , an element to reflect mosquitoes infected by vertical transmission was added , because Ae . albopictus has the ability to transmit dengue virus vertically through eggs , with a filial infection rates ranging from 0 . 5 to 2 . 9% for Dengue-1 virus [8] . Fourthly , we explicitly modeled the water availability by including evaporation , rainfall , and maximum and minimum water level ( See details in S1 File ) . The environmental carrying capacity for mosquitoes will increase when the water level rises , and the density-dependent death rate will decrease in a short period . Furthermore , a spillover effect is triggered when there is an extreme rainfall event and the water level is close to the maximum water level , resulting in a loss of immature mosquitoes . The ideal death rate of larva and the development rate of eggs and larva depend only on temperature . However , the real death rate also depend on the water-level or density of the larva ( See S1 File for more information ) . Similarly , the control intervention to empty water containers can also remove a fraction 1-μi of water and immature mosquitoes , while ultra-low-volume ( ULV ) aerosol applications of insecticides can kill a fraction 1-μa of adult mosquitoes . In addition , temperature-dependent biting rate and the number of eggs per gonotrophic cycle were incorporated to better represent the effects of climate on mosquito population dynamics . Since dengue is still considered as a non-endemic disease in China , which means new autochthonous cases occur only after imported cases , an imported case input was added to the system at day β2013 and β2014 ( January 1st , 2012 as day 1 ) to initiate the outbreak in 2013 and 2014 , respectively . Instead of using the date of the first reported imported case , we treated the timing of the first imported case as a parameter , since the outbreak may be started by an unreported or asymptomatic case . We only added the first imported case to the system and left out all the other subsequent imported cases , because it was a small number when compared with the number of infectious people after the rapid local transmission began , and was reasonable to be ignored . And because Ae . albopictus will survive adverse winter temperatures as diapausing eggs , the development rate from eggs to larva is assumed to be zero from late October to early March [53] . The reporting rate φ was also included to account for the asymptomatic and unreported dengue infections . In summary , a SEI model was used for the vector submodel and SEIR ( Susceptible , Exposed , Infected and Recovered ) model for the human submodel ( Fig 2 ) . Five different life stages for mosquitoes were considered: three aquatic stages ( E , eggs; L , larva; P , pupa ) , one emerging adult stage ( Ae ) , and one biting and reproductive adult stage ( A ) . Subscripts u and i were used to represent uninfected and vertical infected aquatic phases and emerging adults; while s , e , and i were used to denote the populations of susceptible , exposed , and infected adults . Analogously , the human population was divided into four subclasses: Hs , He , Hi , and Hr , which stands for susceptible , exposed , infected and recovered humans , respectively . All the analyses were conducted in R 3 . 2 . 0 [54] , and the differential equations in the model were solved by R package deSolve [55] . The model was run over the period 2012 to 2014 , though the focus is on simulating the dengue outbreak in 2013 and 2014 . The mosquito abundance for only the first simulated year is affected by the initial value for eggs , and the following years showed no memories from previous years [56] , so an extra year was needed to achieve a stable mosquito population for 2013 and 2014 . However , for simplicity , we assumed that there was no imported cases in 2012 . The only possibility for dengue cases in 2012 to affect the next two years was through vertical transmission . Taking into account the low vertical transmission rate and the small number of dengue cases in 2012 ( 139 cases ) , we assumed that the influence of 2012 on the next two years was negligible . Typical of the class of mechanistic disease transmission models used here , there are a large number of parameters with substantial uncertainty in their values . In addition , in this analysis we place considerably more confidence in the timing and pattern of the field data describing human cases and mosquito infection and abundance in Guangzhou in 2013 and 2014 than in the precise numbers reported on any day . As a result , we chose to address the issue of parameter estimation using a strategy that has been called regional sensitivity analysis or RSA [57] . This approach begins with the specification of a region of parameter space thought to include the range of feasible values of each parameter with high probability ( As the typical value for each parameter in Table 1 ) . Monte Carlo simulation runs are then conducted to assess the performance of the model over this parameter space . Here we define this space by specifying the univariate marginal distributions of the model parameters need to be estimated , as given in Table 1 , each of which we assume to be independent . Classification criteria are then defined and applied to the output of the model to determine if a particular realization captures the essential features of the pattern of daily case reports . Fig 3 shows the specific criteria for the 2013 and 2014 Guangzhou dengue case reports ( See the detailed criteria in S1 File ) . If a particular model run results in a case report trajectory passing through all six of the shaded windows , the model is classified as a “pass” , that is as having adequately mimicked the pattern of the field data used for calibration . Passing and failing parameter vectors are then collected for subsequent analysis . Usually the first simulation experiments using the RSA approach result in a very small fraction of passes and these vectors extend over almost the entire range of any of the univariate prior distributions . This is a result of the fact that there are many parameter combinations that can produce the same patterns of model response and their correlation structure is usually very complex in the high dimensional parameter space being sampled . Non-uniqueness of model parameterization of this sort is an issue about which there is a substantial literature particularly in the field of hydrology [57] . In the present case , 74 passing parameter vectors were obtained in 410 , 594 initial simulation runs which we term Cycle 1 . In the S2 File the sample cumulative distribution functions are shown for each parameter for passes and fails . As shown there , some parameter distributions that differ little between passes and fails which gives little clue as to parts of the range of that parameter where passes are more likely . The value of dm , n , the Kolomogorov statistic , is a measure of the maximum difference between the two distributions and can be used as a rough index of sensitivity . Very large differences can be seen for some parameters in Cycle 1 , for example β2013 , μi , μem and ωmax . In view of the very low pass rate of the first set of simulations , we chose to use the outcome of the Cycle 1 experiments to seek a subspace in which passing parameters were more likely to be found . This was done by trimming the ranges of parameters with large values of dm , n . Trimming was an ad hoc procedure based on trimming the range of parameters with few passes at either the high or low end of the sample distribution function of passes . A total of 4 trimming cycles were conducted resulting in a pass rate of 3 . 19% in the final subspace , Space 5 , an increase of about 175 times over the initial space , Space 1 . The marginal distributions of the parameters in Space 5 now show much reduced differences between passing and failing distributions as discussed below . We regard a highly trimmed parameter range and a large decrease in dm , n between spaces 1 and 5 as evidence of the importance of a parameter in producing simulations meeting the pass criteria . However , we note that a parameter may be very important , but if initial uncertainty in its value is small , that is the prior range is narrow , there may be little difference in the marginal distributions under passes versus fails . A second situation in which a parameter can show little difference in its pass/fail marginal distributions yet be important can occur if there are interactions with other parameters not reflected in the marginal distributions . The pairwise correlation matrix can give some clues to such situations and will be discussed below for Space 1 and Space 5 . ( See S2 Table for the pairwise correlation matrices for parameter values Cycle 1 and Cycle5 ) Fig 4 summarizes the case report data for 2013 and 2014 and shows the envelope of 637 passing simulation trajectories from the Space 5 parameter distributions . The daily number of new cases output by the model was calculated as the number of individuals entering the compartment Hi times the reporting rate φ . The median final epidemic size for 2013 and 2014 was 1 , 044 and 30 , 863 , respectively , for the 637 passing parameter sets of Cycle 5 . Although the envelope of passing simulations contains the observed peak values in both years , the median passing peaks were 16% and 17% lower than the observed peaks respectively . Fig 5 shows the Cycle 5 simulation results and field data for larvae and adult mosquitoes . We aggregated the monthly average amount of larva and adults from daily model output of the 637 passing simulations , then normalized them to 0 to 1 and plotted them against the normalized BI and MOI data from Guangzhou CDC . Mosquito surveillance data in 2012 was not used in the validation , because the mosquito abundance in the first simulated year can be affected by the initial value for eggs . Entomological surveillance data recorded only the absence/presence not the number of Ae . albopictus in each container , so it is only a proxy of the abundance . The minimum , maximum , mean and standard deviation for Pearson’s correlation between scaled model output larva amount and BI were 0 . 76 , 0 . 86 , 0 . 82 , and 0 . 02 , respectively . And the correlation for scaled model output adult amount and MOI ranged from 0 . 65 to 0 . 80 , with a mean of 0 . 74 and standard deviation of 0 . 03 . The BI and MOI data were not used in calibration but the patterns produced by the model , as shown in Fig 5 , confirm that the model is producing realistic patterns of mosquito abundance over time . Table 2 shows the Space 1 versus Space 5 marginal distribution comparisons with RR ( range reduction ) denoting the fractional reduction of the range in each parameter . The ranges of six parameters were unaltered and nine were reduced by 50% or more of their initial range . The nine fall into three types of parameters , those associated with vector population dynamics and infection ( μE , λ , σ , and αhv ) , those related to the timing and reporting of imported cases ( β2013 , β2014 , and φ ) , and those associated with the effectiveness of mosquito control interventions ( μa and μi ) . The pairwise correlation matrices for the passing parameter distributions in Space 1 and Space 5 are shown in S2 Table . For Space 1 , the same 9 parameters with large range reductions show high correlations with one or more of others in that group . There is also a very high correlation between ωmin and ωmax , an artifact that is imposed by the model structure . In the Space 5 correlations , all of the high values from Space 1 are lower , and most very much lower , as might be expected . However , some new correlations emerge , notably with πmax , the maximum carrying capacity for immature stages of the mosquito . These correlations are with μem , mortality during adult emergence , and the human to vector , αhv , and vector to human , αvh , transmission probabilities . We do not believe we have access to additional field data or other information which will allow significant further reduction in Space 5 or point to other areas in the parameter space that might suggest alternative underlying processes to be driving the observed patterns of behavior of the system . Hence , parameter vectors meeting the passing criteria sampled from Space 5 will be used in the subsequent explorations of the key processes underlying the 2014 epidemic . The year 2013 differed from 2014 in several aspects , notably the date of imported cases ( β2013 and β2014 ) , climate , the time and frequency of the interventions , and the number of eggs infected by vertical transmission from the previous year . We first explore the timing of imported cases , which is not the real timing of the first imported case reported to the NIDRIS , but a parameter we need to estimate , denoting the first imported case that starts the local transmission . The outbreak in 2014 started at June 11th , and peaked around October 1st , with a time interval of 112 days , while the smaller outbreak in 2013 began at July 14th , and peaked around October 19th , with an interval of 97 days . If the force of infection was the same for these two years , the final size of epidemic in 2014 would be significantly higher than that in 2013 on this basis alone . Without interventions , the peak occurs when the temperature drops to cause a sufficient combination of a decrease in biting rate and an increase in the mosquito death rate . Appropriately timed interventions reduce the abundance of mosquitoes , thus reducing the force of infection which results in an earlier peak . To make the two years comparable , we changed the date of the first imported case in 2014 , β2014 , in the 637 passing parameter sets to β2014 + ( Peak time 2013—β2013 ) ( Scenario Postpone 2014 ) . By doing this , we made the time interval between the imported case and the peak in 2014 equal to that in 2013 . The case report trajectory for each run was recorded ( Fig 6A ) . Then in another scenario ( Scenario Advance 2013 ) , we changed the β2013 to β2013 – ( Peak time 2014—β2014 ) , to attempt to produce an outbreak in 2013 with a size similar to the observed number in 2014 ( Fig 6B ) . Furthermore , to investigate the relationship between the date of imported cases and the final epidemic size further , we kept all the other parameters the same as in the 637 passing sets , and only changed β2014 in each set to integers between Day 791 and 1066 , that is from March 1st , 2014 to November 30th , 2014 ( Scenario Change importing dates ) , and recorded the final epidemic size for each run ( Fig 6F ) . The results of these experiments are shown in Fig 6 . When the time interval between the imported case and the peak in 2014 was changed to match that in 2013 , only 30 parameter sets ( 4 . 7% of the original 637 ) mimicked the pattern of the outbreak in both years . The median final epidemic size of 2014 dropped to 1 , 474 , similar to that of 2013 ( Fig 6A ) . And when the time interval between the imported case and the peak in 2013 was increased to the same as that in 2014 , none of the 637 parameter sets produced passing behaviors . As shown in Fig 6B , after the change , the peak number of cases was significantly higher in both years , with new median final outbreak sizes of 158 , 889 , and 137 , 003 for 2013 and 2014 , respectively . In summary , postponing the date of the import case in 2014 produces an outbreak whose scale is similar to that of 2013 , and advancing the date of the import case in 2013 produces an outbreak even worse than observed in 2014 . In addition , since all other parameters were unchanged except for β2013 , the larger than observed outbreak in 2014 is attributable to vertical transmission , that being the only way that the situation in 2013 can influence that in 2014 . A separate scenario was created , still by advancing β2013 , but removing all infected eggs in the system at the beginning of 2014 , as discussed below . The final experiment on the timing of imported cases involved holding all parameters the same as in the 637 passes , except that of the date of imported case which was varied from March 1st to November 30th . The final epidemic size for each run is plotted in Fig 6F and shows that when the first imported case occurs on April 18th , the median final epidemic size was the highest at 60 , 158 . The final epidemic size became stable after July 1st at approximately 1 , 350 , similar to the observed size in 2013 . These experiments clearly suggest that the date of the first imported cases was a crucial determinant of the severity of the 2014 epidemic . However , the force of infection was not the same in 2013 and 2014 . It is affected by mosquito abundance , biting rate , transmission probability from vector to human and transmission probability from human to vector . Though we assumed the transmission probabilities were the same for 2013 and 2014 ( αhv and αvh ) , the biting rate depends on temperature and the mosquito abundance depends on both temperature and precipitation . Hence , different scenarios were created to study the role of climate of the variations in climate depicted in Fig 7 . Experiments were conducted in which the precipitation , temperature , and evaporation data of 2014 were replaced by data of 2012 , 2013 or of the 30-yr average . Since the temperature in 2014 did not differ significantly from that in other years , while the precipitation in May and August 2014 were much higher , we also ran simulations with actual temperature and evaporation in 2014 , but scaled the precipitation to 30 year average . The new case trajectory for the real climate data was treated as baseline here , so the passing rate was 100 percent for the 637 parameter sets . Table 3 shows the results of the various experiments . As can be seen , the passing rate was relatively low , at only about 28 percent , when 30 year average precipitation was used to replace the real 2014 data ( Scenario 2 , 5 , 6 , 7 , 8 , and 13 ) . Furthermore , the median peak size and final epidemic size were significantly lower than baseline . When the 2014 precipitation was used ( Scenario 3 , 9 , 10 , 11 and 12 ) , the passing rate was around 65 percent but it was more than 80 percent when the 2013 or 2014 temperature was used . The median peak outbreak size was higher than baseline when 2014’s precipitation and average temperature were combined together ( Scenario 3 and 11 ) . The maximum difference between precipitation in 2014 and the 30-year average occurred in May and August , so we scaled the precipitation in these two months to their 30-year average . The passing rates were 65 . 0 , 61 . 2 and 35 . 8 percent when we scaled only May , only August and both , respectively ( Scenario 16 , 17 , and 18 ) . When comparing Scenario 19 , 20 , 21 with 13 , higher passing rate and average outbreak size are observed as a result of increasing the rainfall in May and August above the 30-year average . Rainfall in August seems to be slightly more important . All the results suggest that the precipitation in 2014 played an important role in forming the outbreak , especially rainfall in May and August . However , the temperature in 2014 was lower than average in the spring and winter months , thus acting as a protective factor . That is , if the temperature in 2014 had been higher , the average outbreak size would have been higher as well . The peak time of daily new cases is clearly sensitive to the date of interventions and the simulation results suggests that the interventions are very effective . The most common interventions in Guangzhou were emptying water containers and ULV spraying of adulticide , both conducted at neighborhood level and organized by neighborhood committee . Emptying water containers reduces the abundance of the immature stage , water level and environmental carrying capacity , thereby reducing adult abundance . ULV spraying of insecticide decreases the abundance of adults almost instantly . With a reduced vector to human ratio , the force of infection decreases while the recovery rate remains the same resulting in an earlier peak . The interventions in 2013 took place every Friday from October 9th to November 10th , while in 2014 on every Friday from September 24th to November 30th , as well as on July 25th , August 15th , September 4th and 28th , and October 8th . To determine the effectiveness of these interventions , we set interventions in 2014 the same as those in 2013 and recorded the trajectories ( Scenario Change intervention dates ) . The intervention in 2013 took place later and has a much lower repetition frequency . No passes occurred after the changes , because the median peak size and overall outbreak size increased drastically to 21 , 808 and 843 , 430 respectively ( Fig 6C ) , approximately 27 times the baseline value and 23 times the actual reported cases in 2014 . The new peak time was October 12th , almost 15 days later than the observed peak , which again shows the importance of the time interval between the imported case and the peak . In addition , the filial infection rate can also change the characteristic of an outbreak . To investigate the importance of vertical transmission , the number of infected eggs ( Evi ) was set to zero at the beginning of 2014 ( Scenario Remove Evi ) , because this is the only way that the epidemic in 2013 can influence that in 2014 . This change resulted in 490 passing simulations out of 637 runs . The median of peak size and outbreak size were 778 and 2 , 792 , respectively , only slightly lower than the baseline ( Fig 6D ) . In addition , when we investigated the role of timing of the imported case and changed β2013 to make the time interval between the import case and peak in 2013 the same as that in 2014 , we found that the peak size and outbreak size in 2014 also increased and attributed this to vertical transmission . A scenario was also run with both an advanced import case date in 2013 and no infected eggs carried over from 2013 to 2014 ( Scenario Advance 2013 and remove Evi ) . The peak and outbreak size dropped to 539 and 15 , 526 , respectively , which suggested that the effect of vertical transmission should not be neglected when the outbreak size in the previous year was large ( Fig 6E ) .
From our analyses , four factors appear to have been principally responsible for the pattern of the moderate outbreak in 2013 and the much larger one in 2014 , namely the date of the first imported case , unusually high precipitation in 2014 , interventions , and vertical transmission . We found the timing of first imported and transmitting case was the dominant feature responsible for this pattern . Furthermore , once the timing of imported case is fixed , climate significantly affects the dengue transmission dynamics . For example , precipitation in May and August , 2014 were found to have a moderate effect on the size of the outbreak , while temperature in 2014 was less favorable for the outbreak and suggests that if the temperature had been higher in the spring and winter months in 2014 , the final outbreak size would have been even greater . Vertical transmission played a minor role in forming the pattern , but it is likely to be significant only when the outbreak size in the previous year is large . In addition , we found that the earlier and more frequent interventions in 2014 proved to be effective , otherwise the outbreak size might have been over an order of magnitude higher than the observed value . The date of imported case was crucial in producing the outbreak pattern in 2013 and 2014 . The date of the first imported case in our analysis is not the exact date of the first imported case , but a dummy variable indicating the time of the imported cases which starts the local outbreak . Since we have no information about which imported case will cause local transmission , the time of imported cases was set to be a parameter to be fitted in the model . Though imported cases occurred in almost every month , indigenous cases were mainly reported from July to November when the mosquito abundance and biting rate are higher , and the EIP is shorter . [4] Temperature and arrival date of the first infectious human also interact since early arrival will occur at lower temperature , but there is a longer time for transmission to increase before the beginning of winter season and thereby produce a larger outbreak [15] . That is , low temperature can increase the EIP as well as reduce the biting and the mortality rate resulting in fewer mosquitoes surviving to be infectious as was also shown in Fig 6F . Considering the tradeoff between higher biting rate and longer transmission season , a case imported around mid-April appears to have triggered the biggest outbreak in 2014 . ( Fig 6F ) In addition , the number of imported cases also matters to the outbreak size [16] . However , we did not take this into account , since in our deterministic model one imported case is sufficient to initiate internal transmission . Precipitation too can have both beneficial and detrimental effects on the abundance of Ae . albopictus and dengue transmission . Ae . albopictus mainly breed in flower pot trays , bamboo tubes , used tyres , disposable containers and surface accumulated water . Precipitation can change the water level in these containers and thereby affect the density-dependent development and death rate [27] . When the water level is higher , the environmental carrying capacity also increases; hence , the maximum number of mosquitoes the environment can support will also increase . Higher water level will also bring down the death rate and increase the development rate , so the survival rate of mosquitoes increases during such periods , and development from larvae to adult will be faster . On the other hand , heavy rainfall also can destroy breeding sites . When a heavy rain occurs at the time the water level is close to the maximum , some of the immature stage mosquitoes will be washed out of their containers ( Spillover effect in Fig 2 ) making container habitats significantly less attractive to ovipositing females . Both mechanisms can cause population loss of Ae . albopictus [58] . In contrast , a study in France suggested that the heavy rainfall events can increase the risk of chikungunya [59] . In fact , the relationship between precipitation and mosquito abundance is complicated . We increased or decreased different amounts of rainfall in 10-day time windows , and ran the model with these new precipitation profiles . The result showed that the relationship between the amount of precipitation and mosquito abundance or the number of dengue cases was nonlinear , and there was no simple rule to predict the effects of rainfall or heavy rainfall . According to Table 3 , the temperature in 2014 was not as important as precipitation in causing the outbreak pattern because the inter-annual change of temperature is much smaller than that of precipitation . However , temperature plays an important role in controlling various aspects of the seasonal population dynamics of Ae . Albopictus as discussed above . The vertical transmission rate was less important in determining the outbreak pattern in 2013 and 2014 , though experiments have confirmed that adults hatched from infected diapause eggs can transmit dengue virus [60] . Our analysis suggested that with the small number of cases in 2013 , it is impossible that the big outbreak size in 2014 was caused by only by vertical transmission , therefore dengue was still imported , not endemic , for the 2014 outbreak , which was also recognized by analyzing seasonality and virus source of dengue cases [4] . The probable sources of dengue virus detected in Guangzhou were mainly Thailand , Philippines , Indonesia , Vietnam , Cambodia , and Malaysia [14 , 61] , all of which are also popular tourist destinations for residents in Guangzhou [33] . However , the influence of vertical transmission should not be neglected if a big outbreak occurred in the previous year . Considering the large amount of infected eggs left over from 2014 to 2015 , the effect of vertical transmission in 2015 should be large , even can start a local outbreak without any imported case . However , there is no big outbreak in 2015 , with 44 imported cases but only 57 indigenous cases , though the precipitation in May was higher and there are more imported cases than 2014 . This is likely to be attributable to the extensive interventions in 2015 . After the unprecedented outbreak in 2014 , the government paid more attention to early detection of imported cases , early mosquito control ( started in April compare with in the end of July , 2014 ) , and the quarantine of every suspicious case . Moreover , residents in Guangzhou have more knowledge about the difference between dengue and influenza after 2014 , so they are more likely to go to the hospital when symptoms occur and will be put quarantined immediately after confirmed , which can also reduce local transmission . However , due to the deterministic nature of this model , its use is only appropriate when the scale of the outbreak was big enough to ignore the stochastic effects , but the outbreak size in 2015 was relatively small , therefore we did not simulate the situation in 2015 here . Currently , there is no effective commercial dengue virus vaccine available . Thus , the prevention of a dengue outbreak relies heavily on vector control . Container emptying and ULV spraying are the most common control strategies in China . Other approaches such as releasing Wolbachia infected male Ae . albopicus and introducing mosquito larvae-eating fish have also been adopted , though to a much smaller extent . Although the efficiency of ULV spray in controlling adult Ae . albopictus has been questioned over the years [24 , 62] , larval source reduction has proven to be successful [62] . Since Guangzhou applied both strategies at the same time , we could not separate them . In addition , though it was argued that mosquito control strategies were often implemented after the peak of transmission and had little or no impact on dengue transmission [62] , the first intervention in Guangzhou was timely , two months earlier than the peak , and does appear to have reduced the final epidemic size significantly . Some studies have suggested positive associations between dengue incidence and the Aedes household index and the BI , [63 , 64] while others have concluded that there was no significant correlation [65 , 66] . In our study , we found that the abundance of Ae . albopictus was almost the same for 2013 and 2014 ( Fig 5 ) , and there is no relationship between dengue incidence and the mosquito index for Guangzhou in this specific outbreak . However , on the other hand , according to our results when manipulating the climate files , the abundance of mosquitoes can affect the transmission dynamics , though does not appear to be the most important reason for the large 2014 outbreak . There are , of course , various limitations to our analysis particularly for use in the future . For example , the whole population was considered to be susceptible in 2012 since dengue is not a common disease in Guangzhou . There were 12 . 70 million people at the beginning of 2012 and only 2 , 381 cases were reported between 2002 and 2011 . In addition , there may be transmission of other serotypes in the future , only one serotype was included in the model because most of the cases have been DENV-1 in recent years . Another limitation of the study may be that the temperature dependent functions employed in the model were based on experiments which were conducted under constant temperature conditions [42 , 44 , 67] . Temperature changes from day to day as well as the diurnal temperature range can also change the transmission dynamics [68 , 69] . The most significant limitation , however , may be that our model does not take spatial effects into account . Further steps should be taken to develop a spatially-explicit individual based model , and to include the spatial heterogeneity and stochasticity of transmission of dengue in Guangzhou . With a stochastic model , we can learn more about the probability of local transmission , which can be combined with the outbreak scale to give us a more practical estimation of the dengue outbreak risk . With the spread of Ae . albopictus under global warming and increasing numbers of international travelers , dengue poses additional challenges to policymakers , especially when taking into account the antibody-dependent enhancement , which can lead to increased viral replication and higher viral loads [70] when infected by another heterologous strain . A second wave outbreak with a different serotype could bring more serious manifestations of dengue fever like DHF or DSS [71] . Sustained efforts should be taken to control mosquito abundance and to prevent or limit the extent of further outbreaks . | Dengue has not been considered to be a major problem in China since it is recognized as an imported disease and only 8 , 058 cases were reported from 2005 to 2013 . However , in 2014 alone , 47 , 056 new cases were reported . In this study , a mathematical model was developed to determine the possible cause of this outbreak . The most important parameters found to underlie the pattern of a small outbreak in 2013 and a much larger one in 2014 was the timing of the first imported and locally transmitted case . The importance of precipitation and temperature was also confirmed by the simulation results under different climate scenarios . The model also suggests that the earlier and more frequent control interventions in 2014 targeting immature mosquitoes , such as emptying water containers , and adult control , were effective in preventing larger outbreaks . Furthermore , more attention should be paid to imported cases occurring between March 1st and July 1st to prevent early and prolonged transmission . Without early detection and response , the final outbreak size might otherwise be an order of magnitude or more the size when the imported case occurred outside this time period . | [
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] | 2016 | Climate and the Timing of Imported Cases as Determinants of the Dengue Outbreak in Guangzhou, 2014: Evidence from a Mathematical Model |
Post-translational modifications ( PTMs ) of histones exert fundamental roles in regulating gene expression . During development , groups of PTMs are constrained by unknown mechanisms into combinatorial patterns , which facilitate transitions from uncommitted embryonic cells into differentiated somatic cell lineages . Repressive histone modifications such as H3K9me3 or H3K27me3 have been investigated in detail , but the role of H4K20me3 in development is currently unknown . Here we show that Xenopus laevis Suv4-20h1 and h2 histone methyltransferases ( HMTases ) are essential for induction and differentiation of the neuroectoderm . Morpholino-mediated knockdown of the two HMTases leads to a selective and specific downregulation of genes controlling neural induction , thereby effectively blocking differentiation of the neuroectoderm . Global transcriptome analysis supports the notion that these effects arise from the transcriptional deregulation of specific genes rather than widespread , pleiotropic effects . Interestingly , morphant embryos fail to repress the Oct4-related Xenopus gene Oct-25 . We validate Oct-25 as a direct target of xSu4-20h enzyme mediated gene repression , showing by chromatin immunoprecipitaton that it is decorated with the H4K20me3 mark downstream of the promoter in normal , but not in double-morphant , embryos . Since knockdown of Oct-25 protein significantly rescues the neural differentiation defect in xSuv4-20h double-morphant embryos , we conclude that the epistatic relationship between Suv4-20h enzymes and Oct-25 controls the transit from pluripotent to differentiation-competent neural cells . Consistent with these results in Xenopus , murine Suv4-20h1/h2 double-knockout embryonic stem ( DKO ES ) cells exhibit increased Oct4 protein levels before and during EB formation , and reveal a compromised and biased capacity for in vitro differentiation , when compared to normal ES cells . Together , these results suggest a regulatory mechanism , conserved between amphibians and mammals , in which H4K20me3-dependent restriction of specific POU-V genes directs cell fate decisions , when embryonic cells exit the pluripotent state .
Embryonic development is controlled by fine-tuned differential gene expression . A succession of regulatory protein networks unfolds the zygotic gene expression program along a hierarchy of decisions , leading from the embryonic ground state to the epiblast and then to germ layers , which become patterned into cell type and organ precursor territories . The pluripotent trait , key feature of embryonic stem ( ES ) cells [1] , is progressively restricted and finally lost as soon as embryonic cells become specified to germ layer fates . Recent studies have revealed that alterations in chromatin structure , dynamics and composition represent fundamental processes , which define the epigenetic landscape that directs cell type specification along this hierarchy [2] , [3] . Besides important contributions from ATP dependent chromatin remodelling factors [4] , [5] and histone variants [6] in modulating nucleosome dynamics , histone post-translational modifications ( PTMs ) have been linked to gene expression [3] , [7] . The transition from pluripotent to differentiated cells is characterized by a progressive increase in heterochromatin formation , in a process that changes the hyperdynamic open chromatin structure into a less accessible architecture [1] , [8] . At the same time transcriptional silencing of non-lineage specific genes is achieved via acquisition of repressive histone marks . In vivo studies have shown that dynamic alterations in the levels of histone modifications characterize early stages of development both in mammals [9]–[11] and other vertebrates [12]–[14] . Lysine methylation of histones is catalyzed by SET domain-containing histone methyltransferases ( HMTases ) , and can be linked both to transcriptional activation and repression [15] , [16] . In particular , repressive histone methyl marks are found on lysine residues at position 9 and 27 on histone H3 and in position 20 on histone H4 . H3K27 trimethylation is catalyzed by polycomb repression complex ( PRC ) 2 , which predominantly represses developmental regulatory genes [17]–[19] . Trimethylation of H3K9 and H4K20 relies on Suv39h and Suv4-20h enzyme activities , respectively [20] , [21] , and predominantly marks repetitive genomic DNA at pericentromeric and telomeric heterochromatin [16] , [21] . While H3K9-specific HMTases have been characterized in significant depth [20] , [22] , [23] , we know little about the functions of Suv4-20h1 and Suv4-20h2 enzymes with regard to gene regulation . In vivo analysis of H4K20 methylation states in mouse embryos reveals specific patterns both in cellular or subnuclear abundance [9] , [24] . Suv4-20h DKO pups die perinatally , indicating an essential function of the two enzymes during embryogenesis [24] . Moreover , quantitative analysis of histone PTMs in X . laevis revealed a progressive and significant accumulation of H4K20me3 levels during embryogenesis , suggesting developmental functions for these enzymes [13] . To characterize the functional role of H4K20me2/3 during vertebrate development we have investigated the consequences of both morpholino-mediated protein knockdown and mRNA-born overexpression of the Xenopus Suv4-20h1 and h2 homologs in frog embryos . Our data reveal a specific and selective requirement for Suv4-20h enzyme acitivities in neuroectodermal differentiation , in a process which involves transcriptional repression of pluripotency associated POU-V genes , both in Xenopus embryos and in murine ES cells .
We initially identified X . laevis Suv4-20h1 and h2 ESTs via database mining . Mouse and frog Suv4-20h1 and h2 protein sequences are well conserved , particularly within the SET domains ( ≥88% identity ) , even though the xSuv4-20h2 open reading frame is longer than its mouse homolog due to C-terminal insertions ( supplementary data , Figure S1 ) . XSuv4-20h1/h2 genes are both maternally and zygotically expressed in a ubiquitous manner , as shown by RNA in situ hybridisation and RT-PCR analysis ( Figure S2A–S2D ) . XSuv4-20h1 mRNA abundance decreases during the initial stages of development and subsequently rises from mid-gastrula on , reflecting the switch from maternal-to-zygotic transcription at midblastula . In contrast , the initially high xSuv4-20h2 mRNA level falls and stays low at late stages ( Figure S2D ) . To test the acivities of these Xenopus HMTases , we first analyzed their ability to rescue H4K20me3 levels in Suv4-20h1/h2 DKO mouse embryonic fibroblasts ( MEF Suv4-20h DKO; [24] ) , which lack this modification . Both frog cDNAs re-established a proper H4K20me3 pattern , which was strongly enriched at heterochromatic regions that were identified as DAPI-dense chromocenters within nuclei ( Figure 1A ) . Thus , Xenopus laevis Suv4-20h homologs are biologically active and can direct H4K20 trimethylation . To test , whether they generate this histone mark in frog embryos , we designed antisense Morpholino oligonucleotides ( MO ) to reduce synthesis of xSuv4-20h1 and h2 proteins from endogenous mRNAs ( Figure S3A , S3B ) . These MOs specifically inhibited translation of their cognate templates in vitro ( Figure S3C ) . To avoid possible functional complementation between the xSuv4-20h enzymes in vivo , we decided to inject the two MOs simultaneously into both blastomeres of 2-cell stage embryos and performed western blots with nuclear protein extracts from these double-morphant embryos at the tadpole stage ( NF30-33 ) . Compared to uninjected controls or embryos injected with an unrelated control MO ( control-morphants ) , the double morphants contained significantly less H4K20me2 ( p = 0 . 0011 ) and H4K20me3 ( p = 0 . 0164 ) , which was coupled to an increase in H4K20me1 ( p = 0 . 0034 ) ( Figure 1B and 1C ) . This result was confirmed by MALDI-TOF mass spectrometry ( Figure S4A ) . As described in Schneider et al . [13] , the relative abundance of histone modifications was calculated by quantifying the amount of a specific modification relative to the amount of all modification states determined for the same histone peptide . As reported before [13] , the H4K20me3 mark could not be quantitated reproducibly for technical reasons . Compared to control embryos , however , xSuv4-20h double morphants contained approximately 2 . 5-fold less of H4K20me2 ( p = 0 . 0153 ) and three-fold more H4K20me1 ( p = 0 . 0185 ) , while the abundance of the unmodified peptide state remained unaffected . Importantly , the levels of histone H3 methylation on two tryptic peptides , covering the K9 , K27 and K36 positions , were indistinguishable between control and double-morphant embryos ( Figure S4B and S4C ) . Western blot analysis with antibodies against trimethylated H3K9 or H3K27 also showed no difference in the abundance of these two marks between control embryos and xSuv4-20h double morphants ( Figure S4D ) . To further characterize the effects of xSuv4-20h enzyme depletion on the cellular level , we performed immunohistochemistry on sections from tailbud stage embryos ( NF30 ) , which were injected with the xSuv4-20h MO-mix into one of two blastomeres at 2-cell stage together with fluorescently labelled dextranes as lineage tracer . While H3 staining was comparable between injected and uninjected sides under all conditions ( Figure S5A ) , staining for H4K20me2 and –me3 was clearly reduced on the double-morphant side of the neural tube ( Figure 1D ) . In agreement with our western blot and mass spec results , the reduction in the di- and tri-methyl mark was coupled to an increase in H4K20me1 staining . Altogether these results indicate that xSuv4-20h1 and h2 downregulation leads to a quantitative reduction of H4K20 di- and trimethyl marks in the frog embryo , without affecting the bulk abundance of other repressive histone marks such as H3 K9/K27 methylation . RNA-based overexpression of Suv4-20h HMTases had the opposite effect . When injected singly , xSuv4-20h1 or h2 mRNAs increased both di- and trimethylated H4K20 in a dose-dependent manner ( Figure S8A ) . A comparable result was achieved by injection of either mouse Suv4-20h1 or h2 mRNAs ( Figure S9A ) . Together , these results identify the frog cDNAs as orthologs of mammalian Suv4-20h enzymes . Loss and gain of function experiments also indicate that the bulk abundance of di- and trimethylated H4K20 can be manipulated over a wide range without compromising embryonic viability . We next tested , whether depletion of xSuv4-20h HMTases affects embryonic development . We injected xSuv4-20h1/h2 MO-mix into one blastomere of two-cell stage embryos and scored phenotypic alterations by comparing injected with uninjected sides . No obvious differences were observed during early development , including gastrulation , axial extension and dorsoventral patterning . From tailbud stages on , two main phenotypes became manifest . First , in the injected side of xSuv4-20h double morphants the eye formation was strongly compromised . The eye rudiments contained no or barely visible retinal pigment and typically had no lens ( Figure 2A ) . Secondly , melanophores that are found on the dorsal part of the head and the lateral portion of the trunk , were severely reduced in numbers or completely lost from the double-morphant side ( Figure 2A ) . Both phenotypes had a penetrance between 80–90% in xSuv4–20h double morphants ( p<0 . 0001 , Fisher's exact test ) in several independent experiments ( Figure 2B ) . Control-morphant embryos had normal eyes and melanocytes ( Figure 2A ) and were indistinguishable from uninjected siblings in most cases ( Figure 2B ) . The distinct eye phenotype prompted us to investigate the underlying molecular changes . RNA in situ hybridization experiments revealed a clearly reduced expression of the homeobox transcription factor Rx-1 ( Figure 2C ) and the paired box transcription factor Pax-6 ( Figure S5D ) in xSuv4-20h double morphants . The reduction of these two master regulators of eye differentiation explains the morphological eye phenotype , but we noticed that embryonic transcription was already misregulated upstream of these factors . The pan-neural markers Nrp1 ( Figure 2C ) and N-CAM ( Figure S5E ) , which are induced during gastrula stages , were also strongly reduced in double morphants . However , several key markers of embryonic patterning were not perturbed , such as the organizer genes Chordin , Goosecoid and Xnr-3 at gastrula stages ( Figure S5B ) . The anteroposterior patterning of the central nervous system ( CNS ) appeared also to be normal given the wild-type-like expression patterns of Otx2 and Krox20 in fore- and hindbrain territories , respectively ( Figure S5C ) . These results provide first evidence that H4K20 di- and trimethylation serves to regulate distinct developmental genes in a selective manner . The specificity of the developmental phenotypes arising from xSuv4-20h enzyme depletion was validated by rescue experiments , in which we coinjected increasing doses of murine Suv4-20h1/h2 mRNAs together with the xSuv4-20h MO-mix . Due to sequence divergence , transcripts of the murine orthologs escape inhibition by the MOs targeting the frog mRNAs . Already 2 ng of murine Suv4-20h transcripts were sufficient to rescue the eye defect in two thirds of the double morphant embryos ( p<0 . 0001 , Fisher's exact test ) . In most cases , the retinal neuroepithelium regained its circular structure and near normal size , as well as a central lens ( Figure 2A ) . The rescue efficiency did not increase with higher concentrations of mouse transcripts ( Figure 2B , columns 4–6 ) . The number of melanophores was also increased at their proper sites under rescue conditions ( Figure 2A ) . Furthermore , the expression domains of Rx-1 and Nrp1 ( Figure 2C ) , as well as Pax-6 and N-CAM ( Figure S5D and S5E ) were efficiently restored . To test , whether this phenotypic rescue requires Suv4-20h proteins or their enzymatic activity , we generated catalytically inactive murine Suv4-20h protein variants ( Figure S6A ) , based on structural predictions [25] , [26] . Unlike the wild-type proteins , neither variant restored the H4K20me3 mark at heterochromatic foci in Suv4-20h DKO MEFs ( Figure S6B ) . When tested side by side with the wild-type enzymes , the mutants did neither increase the abundance of the H4K20me2 and -me3 marks in wild-type frog embryos ( Figure S6C , compare lanes 1 , 3 and 5 ) , nor rescue H4K20 methylation levels in xSuv4-20h double morphants ( Figure S6C compare lanes 1 , 4 and 6 ) , although being expressed at similar levels ( Figure S6D ) . Consequently , the inactive variants also failed to rescue the eye and melanophore phenotype ( Figure S7A–S7C and S7D , compare columns 2–4 ) . In the course of these experiments we noticed that overexpression of either frog or mouse Suv4-20h1 and h2 proteins never caused any obvious morphological or molecular changes in the embryos ( Figures S8B , S8C and S9B , S9C ) , despite strongly enhanced H4K20me3 levels in bulk chromatin ( Figures S8A and S9A ) . In particular , morphological landmarks such as eyes and melanophores formed normal in size , number and location under overexpression conditions . Expression domains of marker genes such as Rx-1 and Pax-6 were unaffected ( Figures S8D and S9D ) . Thus , H4K20 di- and trimethylation is required for normal development , but excess deposition of these marks has no apparent phenotypic consequences . The apparent functional selectivity of the ubiquitously expressed enzymes encouraged us to test , whether xSuv4-20h HMTases control additional aspects of germ layer formation and patterning . Therefore , we compared the expression of key developmental regulatory genes in uni-laterally injected control-morphants versus xSuv4-20h double morphants by RNA in situ hybridisation ( listed in Figure 3A ) . Based on our previous results , we continued with genes involved in neurogenesis ( Figure 3B ) . At the open plate stage , primary neurons are specified in three stripes next to the dorsal midline on each side . At this time , each stripe expresses the neural specific regulatory genes Neurogenin-related 1a ( Ngnr-1a ) and Delta-like 1 , as well as the differentiation marker N-tubulin . The expression of these three genes was extinguished in almost all of the xSuv4-20h MO-injected sides , while being unaffected by control-MO ( Figure 3B ) . In addition to these stripes , Delta-like 1 mRNA delineates the anterior border of the neural plate , and this domain was also extinguished ( Figure 3B ) . In contrast , mesodermal expression of Delta-like 1 around the blastoporus remained unaffected in morphant condition ( Figure 3B , arrow ) . Delta-like 1 and N-tubulin stripes were effectively rescued by coinjection of wild-type mSuv4-20h1/h2 mRNAs , while Ngnr-1a was restored in a broad , diffuse manner ( Figure 3B , right column ) . Notably , inactive mouse Suv4-20h HMTases could not rescue N-tubulin expression ( Figure S7E , middle column ) . At the same time , mesodermal control genes like MyoD were unaffected ( Figure S7E , right column ) Together , these results implicate xSuv4-20h enzymes in neuronal fate selection . Next , we extented our analysis to marker genes expressed in other germlayers and territories ( Figure 3C and Figure S5 ) . The epidermal keratin gene XK81 demarcates non-neural ectoderm and was expressed normally on the surface of morphant epidermis; however , due to a slight retardation in neural tube closure on the injected side , its expression appears asymmetric in anterior views . This may indicate an involvement of xSuv4-20h enzymes in morphogenetic processes during neurulation and/or neural crest specification . This phenotype led to a mild broadening of the neural plate markers Sox2 ( Figure 3C ) , Sox3 and Sox11 ( Figure S5F ) at apparently normal mRNA levels . Prior to these neural plate markers , a group of genes including FoxD5 , Geminin , Zic1 , Zic2 , Zic3 and members of the Iroquois family are induced in the prospective neuroectoderm and stabilize the neural fate by their regulatory interactions ( reviewed in ref [27] ) . At midgastrula ( NF11 ) , FoxD5 and Geminin did not respond to xSuv4-20h enzyme depletion ( Figure S5F ) , but Xiro1 , Zic1 ( Figure 3C ) , Zic2 and Zic3 ( Figure S5F ) mRNAs were strongly reduced . In contrast , key mesodermal factors such as Xbra , MyoD ( Figure 3C ) and VegT ( Figure S5F ) , as well as regulators of endodermal differentiation like Sox17 α and Endodermin ( Figure 3C ) were expressed normally in both morphants and in embryos overexpressing frog xSuv4-20h proteins ( Figure S8E ) . Taken together these results demonstrate that xSuv4-20h HMTases are critical for neural development , but apparently dispensable for mesoderm and endoderm formation in X . laevis . To further verify the specific role of Xenopus Suv4-20h enzymes in neural development , we considered two different approaches; in a first series of experiments we performed injections at 8-cell stage in the animal or vegetal pole blastomeres , selectively labelling cells predominantly belonging either to mesendoderm ( vegetal injections , Figure 4A ) or ectoderm ( animal injections , Figure 4D ) . Vegetal pole blastomere injections led to no evident morphological and molecular phenotypes ( Figure 4B and 4C ) . Conversely , animal injections reproduced the eye and melanophore phenotypes from half-injected embryos , while mesodermal and endodermal structures developed normally ( Figure 4E ) . Consistent with the morphological defects , Delta-like 1 expression in the neural plate was suppressed , while MyoD and Sox17 α genes were unaffected ( Figure 4F ) . These results provide strong evidence that the neural and melanocyte phenotypes originate in the ectoderm . As second approach we took advantage of animal cap ( AC ) explants , which form epidermis in isolation but can be neuralized by the BMP-inhibitor Noggin . Specifically , we tested whether the downregulation of xSuv4-20h HMTases prevented neural induction by Noggin . Without Noggin , wt and double morphant explants were positive for XK81 and negative for Nrp1 ( Figure 5A ) . They were also negative for Xbra , indicating absence of contaminating mesoderm . Noggin-mediated Nrp1 expression was clearly visible in wt caps , but strongly reduced upon co-injection of xSuv4-20h morpholinos , while XK81 expression was downregulated in both the samples ( Figure 5A ) . Thus , double morphant caps are both refractory to neural induction and restrained in epidermal differentiation . However , they differentiate into mesoderm upon stimulation with Activin A just like control explants , as shown by immunostaining for muscle myosin heavy chain ( Figure 5B ) . These results confirm the crucial role of xSuv4-20h enzymes in coordinating the formation of ectodermal tissues , and show that in the absence of the two enzymes neural induction is impaired . Loss of H4K20 di- and trimethylation is known to compromise DNA damage repair in mice and to partially block G1/S transition [24] . This prompted us to test , whether xSuv4-20h depletion affects apoptosis and cell proliferation in frog embryos . Immunostaining for activated Caspase3 revealed an increase in apoptotic cells on the injected side of double morphant embryos ( Figure S10A ) . Coinjection of xBcl-2 mRNA , an anti-apoptotic factor , reduced the Caspase3 positive cells to levels of the uninjected control side , however , without re-establishing a proper Delta-like 1 and N-tubulin pattern in the double-morphant side . Overexpression of xBcl-2 mRNA alone had no effect on the expression of the tested markers ( Figure S10A ) . Thus , although embryonic frog cells depleted for the H4K20me2/me3 marks become apoptotic at higher rate than wt cells , the absence of neurons in the double-morphant neural plate cannot be explained by selective cell death . Double morphant embryos stained for the mitotic marker H3S10P , showed a two-fold reduction ( p = 0 . 0058 ) in the number of proliferating cells at midneurula stage , compared to control morphant embryos ( Figure S10B ) . This mild phenotype might be correlated with the observed increase in apoptosis . Since neural induction continues in frogs , even when cell proliferation is blocked from gastrulation onwards [28] , it is unlikely that the nearly complete loss of N-tubulin positive neurons is brought about by this mild reduction in cell proliferation . Taken together , the main xSuv4-20h morphant phenotype represents not a selective loss of neuroblasts , but a block in neural differentiation . So far , our analysis in xSuv4-20h morphant embryos has indicated a specific and selective loss of gene expression in ectodermally derived tissues . The earliest affected markers - Zic and Xiro genes - become induced at early gastrula stage and help establish the neural plate state [27] . At this time in frog development , embryonic cells in the animal hemisphere are still plastic and express members of the POU-V gene family – i . e . Oct-25 , Oct-60 and Oct-91 - that encode paralogs of the mammalian pluripotency regulator Oct4 [29] , [30] . Because Oct-25 and Oct-91 regulate germ layer differentiation in Xenopus [31]–[34] , we investigated their expression ( Figure 6A ) . Oct-25 is initially expressed throughout the animal hemisphere at early gastrula , but gets restricted to the presumptive floor plate ( notoplate ) by midneurula [31] . On the injected side of the vast majority of double morphants , however , Oct-25 expression was expanded from the notoplate down to the ventral midline . Interestingly , ectopic Oct-25 expression was restricted to the sensorial cell layer of the ectoderm , which contains neural and epidermal precursor cells , respectively ( Figure 6A , sections ) . The Oct-60 gene , which is expressed during oogenesis , was not activated under these conditions . Oct-91 staining appeared normal in the majority of the embryos , although some showed a mild upregulation in double morphants as well ( data not shown ) . The ectopic expression of Oct-25 is a specific consequence of xSuv4-20h enzyme depletion , because its normal pattern was re-established in morphants upon coinjection of mRNAs encoding wild-type , but not inactive , mouse Suv4-20h proteins ( Figure S7E , left column ) . Notably , the selective derepression of the Oct-25 gene was also observed in double-morphant AC explants ( Figure 6B ) , excluding indirect effects from non-ectodermal tissues . We then performed qRT-PCR analysis to quantitate the relative changes in gene expression . It is frequently observed that embryo cohorts develop in slight asynchrony as a non-specific consequence of Morpholino injection , possibly obscuring transcriptional responses . To minimize this potential artifact , we analysed the RNAs of matching pairs of wt and xSuv4-20h depleted samples by dissecting embryos at early neurula stage ( NF14 ) into uninjected and injected halves , based on the coinjected fluorescent lineage tracer ( Figure S11A ) . As shown in Figure 6C , the Oct-25 mRNA is about three-fold higher in xSuv4-20h double-morphant halves ( p = 0 . 0123 ) , while being similar between control-morphant and uninjected halves . In the same sample , Oct-91 expression was unaffected ( Figure 6C ) . We used this assay also to confirm the diminished expression of neural plate marker genes detected earlier by RNA in situ hybridisation . With the exception of Ngnr 1a , Nrp1 and N-tubulin , mRNA levels were clearly reduced in the morphant halves ( p = 0 . 0122 and 0 . 0163 , respectively; Figure S11B ) . To gain further information about the complexity of the underlying transcriptional misregulation , we performed transcriptome analysis in wild-type and double-morphant embryos , again dissecting embryos in corresponding pairs of injected and uninjected halves ( Figure S12A ) . Six percent of the 11639 annotated probe sets present on the microarray were significantly altered in their expression as a consequence of xSuv4-20h enzyme depletion , about equally split into upregulated ( n = 319 ) and downregulated ( n = 404 ) probes ( Figure S12B and S12C; for a complete list of the responding probesets see NCBI's GEO Series accession number GSE41256 ) . This result suggests that the observed phenotypes in the double morphants originate from transcriptional misregulation of distinct genes , rather than from global , pleiotropic effects . Indeed , Oct-25 mRNA is also specifically upregulated in the microarray data set , where it is among the ten most upregulated mRNAs in the double-morphant condition ( Figure S12D ) . The sustained expression of Oct-25 in xSuv4-20h morphant embryos fits the prediction of Oct-25 being a direct target of H4K20me3 mediated transcriptional silencing . To test this assumption directly , we carried out chromatin-immunoprecipitation ( ChIP ) experiments with H4K20me3-specific antibodies at the neurula stage ( NF15-16 ) . For ChIP experiments we used X . tropicalis embryos , since the available genome sequence of this closely related frog species [35] allowed us to design primer amplicons for non-exon derived DNA sequences . RNA in situ hybridization performed on neurula stage X . tropicalis embryos , confirmed that the expression patterns of Oct-25 and N-tubulin were up- and down-regulated , respectively , to the same extend as observed for X . laevis ( Figure S13 ) . We retrived the pericentromeric major satellite repeat sequence ( MSAT3 ) as positive control amplicon for the experiment . Genic regions , which are H4K20me3-free and , thus , could be used as negative controls , are difficult to predict , since genome-wide analysis in mammalian cells reported only enrichment of this modification on pericentromeric and subtelomeric heterochromatin [36] , [37] . As negative controls we considered: GAPDH , a constitutively expressed housekeeping gene; thyroid hormone receptor α ( thra ) , a gene whose expression can be detected at neurula; and thra-induced bzip protein ( thibz ) that is expressed from metamorphosis on ( Figure S14A ) . Statistical analysis of qRT/PCR data indicates that expression of GAPDH and thra was not significantly altered under the double-morphant condition ( ) . Therefore , the relative H4K20me3 levels at these genes were defined as background , and compared to the levels on other loci ( Figure S14A ) . The modification strongly decorated the pericentromeric MSAT3 repeat region ( Figure 6D ) , as expected from the analysis in murine cells [21] . At the 5′UTR amplicon of the Oct-25 gene , H4K20me3 was significantly enriched compared to the control genes GAPDH ( p = 0 . 0155 ) , thra ( p = 0 . 0103 ) and thibz ( p = 0 . 0128 ) ( Figure S14A and Figure 6D ) . In a second set of experiments , we compared the abundance of H4K20me3 between wild-type and xSuv4-20h double-morphant embryos ( Figure 6E ) . In morphants , the modification was selectively reduced at the 5′UTR amplicon of Oct-25 ( p = 0 . 004 ) . Together , these ChIP experiments validate the 5′ end of the Oct-25 gene as direct target of xSuv4-20h mediated transcriptional silencing . Xenopus Oct-25 has been implicated in germ layer formation [32] , [34] . We wanted to know , whether the sustained expression of Oct-25 in xSuv4-20h morphants could cause the observed downregulation of early neural plate and neural differentiation markers . This question is difficult to address , since the role of Oct-25 in neural induction is ambiguous - both overexpression and morpholino knockdown inhibit neural differentiation [32] , [34] . Thus , Oct-25 acts in pleiotropic fashion , perhaps switching target genes or protein interaction partners . In a previous report [38] , human Oct4 protein was shown by ChIP analysis to bind to promoters of early neural markers , including Zic and Sox genes . In order to link Xenopus Oct-25 mechanistically to these genes , we have misexpressed constitutively activating and repressing Oct-25 fusion proteins in animal caps ( Figure S15A ) . Zic1 , Zic3 and Sox2 responded to the Oct-25 variants in a manner consistent with direct regulator/target gene interaction , i . e . they were hyperactivated by Oct-25-VP16 ( p = 0 . 0143; 0 . 0456; 0 . 01622 , respectively ) and suppressed by Oct-25-EnR ( p = 0 . 0236; 0 . 0167; 0 . 0231 , respectively ) compared to the uninjected sample . In line with this assumption , inspection of the X . tropicalis gene sequences detailed the presence of multiple Oct-25 DNA binding motifs within 2 . 0 Kb distance from the transcriptional start site for each of these genes ( Figure S16 ) . For the two Zic genes , which are misregulated in the forming neural plate of morphant embryos ( Figure 3C and Figure S5F ) , we confirmed the misregulation by Oct-25 variants via RNA in situ hybridisation ( Figure S15B ) . Interestingly , Sox2 expression was affected only in AC explants , but not in the double morphant embryos . This can be explained by considering two points: First , in animal caps levels and activities of the injected Oct-25 protein variants most likely exceed endogenous Oct-25 protein activity and regulate Sox2 expression in a dominant fashion . Secondly , formation of neural tissue in the embryo requires inductive influences including FGF signalling [39] , and Sox2 transcription is stimulated by FGF8 [27] , which is normally expressed in the mesoderm . Thus , the stimulating influence of FGF signalling on Sox2 transcription in the embryo may neutralize the repressive influence from deregulated Oct-25 expression , while the repressive activity of the deregulated Oct-25 levels prevails in animal caps in the absence of FGF signalling . The remaining genes either failed to respond to one of the two Oct-25 protein variants ( Zic2 , Xiro1 ) , or did not respond ( Ngnr 1a , N-tubulin ) . These observations suggest an indirect effect . While it is possible that additional factors that are misregulated in xSuv4-20h morphants contribute to the neural phenotype , the combined results from ChIP experiments and Oct-25 variants define a pathway , in which xSuv4-20h enzyme dependent repression of Oct-25 is needed during gastrulation for proper neuroectoderm differentiation . To further analyse the mechanistic interaction between xSuv4-20h enzymes and Oct-25 , we performed rescue experiments with triple-morphant embryos , in which synthesis of Oct-25 and xSuv4-20h proteins was simultanously blocked ( Figure 7 ) . The Oct-25 morpholino that we used has been shown before to inhibit efficiently Oct-25 translation from both non-allelic gene copies [40] . Because global Oct-25 depletion inhibits the formation of anterior neural structures [40] , we employed two different strategies for the triple-knockdown to circumvent this problem . In a first series of analysis we injected a single A1 blastomere of 32-cell stage embryos to target cells that predominantly contribute to the retina and brain . Also in this experimental series , the morphology of double morphant eyes was strongly affected ( Figure 7A ) . 71% of the injected embryos showed a clear reduction of retinal pigment , the remainders often restricted to the dorsal-most portion of the eyecup . The majority of the eyes contained no lens ( Figure 7C ) . When the downregulation of xSuv4-20h enzymes was coupled to a concomitant knockdown of Oct-25 ( triple morphants ) , the percentage of embryos showing this defect was reduced to 49% ( p = 0 . 0188 , Fisher's exact test ) . The retinal pigment was rescued in the triple morphants , whose eyes also regained a properly structured lens ( Figure 7C ) . To confirm the morphological phenotypes , we investigated the basal neural gene expression in AC explants . The expression of a subset of genes involved in the establishment of the neural plate state ( Zic1 , Zic2 , Xiro1 , Sox2 and Sox3 ) was strongly reduced upon downregulation of xSuv4-20h enzymes at early neurula ( NF14-15 ) , compared to uninjected animal caps ( p = 0 . 0068; p = 0 . 0127; p = 0 . 0113; p = 0 . 0321; p = 0 . 0037 , respectively ) . With the exception of Sox2 , the simultaneous downregulation of xSuv4-20h enzymes and Oct-25 , rescued neural gene expression . In fact , under the triple morphant condition most of these genes were expressed at higher levels than normal , suggesting that they are partly repressed by Oct-25 in unmanipulated explants ( Figure 7D ) . Most importantly , the combined results of the two triple-knockdown experiments indicate that both morphological and molecular features of the xSuv4-20h double morphant phenotype can be rescued to a significant extent by reducing Oct-25 protein levels . This result firmly establishes that the sustained and elevated expression of Oct-25 protein is responsible for the neural differentiation defect of xSuv4-20h double-morphant embryos . Oct-25 plays multiple roles during early frog development , including interference with Activin/BMP-dependent mesendoderm formation before gastrulation , and with neural induction during gastrulation [32] , [34] . A similar role is considered for its mammalian paralog Oct4 , which is required for the pluripotent state of ES cells , but antagonizes ectodermal differentiation as soon as these cells exit pluripotency [30] , [41] , [42] . Although previous genome-wide studies of histone modifications in mammalian cells have not detected H4K20me3 on the Oct4 gene [36] , [37] , this apparent similarity made us investigate Oct4 protein expression in wild-type and Suv4-20h1/h2 DKO murine ES cells . We tested two independently derived DKO cell lines ( B4-2 and B7-1 ) , and compared them with two wild-type controls , i . e . wt26 , an isogenic ES cell line , and the well-characterized GSES-1 cell line [43] . All four cell lines formed comparable ES cell colonies in LIF-containing medium ( Figure 8A and Figure S17B ) , although the two DKO lines grew slightly slower . Upon aggregation they formed embryoid bodies , which were clearly smaller than those of the wild-type lines , both at day 2 and day 6 of differentiation ( Figure 8A and Figure S17 ) . After replating the differentiated cells for one day , the two DKO lines frequently formed again colonies resembling undifferentiated ES-cells ( day 7 in Figure 8A and Figure S17B ) . To obtain a quantitative measure of Oct4 gene expression , we fixed and stained the four cell lines before ( day 0 ) and during ( day 6 ) differentiation for Oct4 protein and subjected equal cell numbers to FACS-analysis . The Oct4 signals were quite similar between wt26 and GSES-1 cells , as they were between the two DKO lines . In contrast to the wild-type cell lines , however , the signals of the DKO lines were reproducibly shifted to the right ( Figure 8B and Figure S17C ) . Based on normalized median fluorescence intensity , the two DKO lines contained approximately three-fold higher Oct4 protein amounts than the wild-type lines at day 0 ( p = 0 . 00604 ) , and still two-fold more at day 6 ( p = 0 . 01266 ) ( n = 3; Figure 8C and Figure S17B ) . We conclude that Oct4 expression is being reduced during differentiation in Suv4-20h1/h2 DKO cells . However , these cells have higher Oct4 levels in the undifferentiated state , and maintain higher levels during differentiation in comparison to wild-type cells . Oct4 protein levels are known to be tightly regulated [1] and to influence lineage decisions during ES cell differentiation [41] , [42] . We therefore investigated the biological significance of the elevated Oct4 protein levels in Suv4-20h DKO ES cell lines . Unfortunately , the applied EB differentiation protocol promotes predominantly mesendodermal differentiation , which prevented the analysis of neural markers . Nevertheless , we performed FACS analysis on wt and Suv4-20h DKO cell lines stained for the chemokine receptor 4 ( CXCR4 ) protein , whose expression indicates mesendoderm induction in embryoid bodies . At day 6 of differentiation , wt cell lines showed a robust increase in CXCR4 positive cells compared to day 0 ( Figure 8D and data not shown ) . In contrast , both Suv4-20h DKO cell lines contained a significantly lower percentage of CXCR4 positive cells at day 6 when compared to the wild type cell lines ( p = 0 . 03255; Figure 8 ) . We also noted that replated wt cells frequently formed autonomously beating areas at differentiation day 14 ( see Video S1 ) , indicating functional cardiomyocyte formation , while contracting areas were never observed in the Suv4-20h DKO cells ( Video S2; n = 4 experiments ) . Finally , qRT-PCR analysis indicated a reproducible and statistically significant shift in mesendoderm gene expression in the DKO ES cells , which show enhanced induction of FoxA2 ( p = 0 . 00706 ) and reduced levels of Gata4 ( p = 0 . 00037 ) , compared to the wt ES cell lines ( Figure S17D ) . Together , these results reveal a compromised and biased differentiation capacity for Suv4-20h DKO ES cell lines , and provide an entrypoint for further experimentation in the murine system .
In this study , we have investigated the developmental functions of the histone- methyltransferases Suv4-20h1 and h2 during frog embryogenesis , which are responsible for the establishment of the H4K20 di- and trimethylated states . These modifications have been implicated in heterochromatin formation , DNA damage repair and G1/S-transition [21] , [24] and are also involved in transcriptional regulation [44] , [45] . Our experiments identify a specific and selective role of xSuv4-20h HMTases in the formation of the ectodermal germlayer through control of mRNA expression of key regulators of the neural plate state and neuronal differentiation circuits . Indeed , our results indicate for the first time that H4K20me3 controls transcription in a rather gene-specific manner . The mRNA profile of double morphant embryos shows appr . 6% of the annotated probesets to be misregulated , when H4K20me3 levels have been reduced to appr . 25% . About half of the responding mRNAs are transcriptionally upregulated and , thus , their genes may qualify as being directly controlled by H4K20me3 deposition . Surprisingly , our molecular analysis revealed that xSuv4-20h enzymes are required to restrict the expression of the pluripotency-associated Oct-25 gene during gastrula and neurula stages . In the absence of proper H4K20me3 deposition , the Oct-25 gene becomes transcriptionally derepressed and interferes with neural differentiation . The successful rescue of key morphological and molecular aspects of the neural defect in double-morphant embryos by the simultanous inhibition of Oct-25 translation establishes this pathway formally . At least in Xenopus , the regulatory interaction between xSuv4-20h enzymes and Oct-25 is needed for embryonic cells to exit the pluripotent state and differentiate as neuroectoderm . The genetic interaction between Suv4-20h enzymes and POU-V genes appears also to be conserved in mouse ES cells , although the H4K20me3 mark has not yet been detected on the Oct4 gene locus . To this point , we have shown that Suv4-20h DKO ES cells contain significantly elevated Oct4 protein levels , compared to wt ES cells . During ES cell differentiation the mammalian Oct4 gene is known to become repressed by a battery of epigenetic mechanisms including DNA methylation , incorporation of somatic linker histones and repressive histone modifications ( H3K9me3/H3K27me3 ) , which cooperate to achieve chromatin compaction of the Oct4 gene locus [46] . Our finding that Oct4 protein levels are increased in the DKO ES cells both before and during differentiation actually suggests that Suv4-20h enzymes regulate mammalian Oct4 transcription in a way that is at least partly independent from the other repressive mechanisms targetting this locus . Our results in Xenopus rest predominantly on loss of function analysis , achieved by morpholino-mediated knockdown of endogenous xSuv4-20h protein translation . Specifically , we have shown that our antisense oligonucleotides block translation of xSuv4-20h1 and h2 isoforms in vitro , and significantly decrease H4K20me2 and –me3 levels in vivo , without altering the bulk abundance of other repressive histone marks such as H3K9me3 and H3K27me3 . The morpholinos produced specific phenotypes , which were rescued on the morphological and molecular level by RNA-born co-expression of heterologous xSuv4-20h enzymes and , thus , originate from deficient H4K20me2/me3 states . While xSuv4-20h double morphant embryos showed consistent phenotypes at high penetrance , we were surprised to see that H4K20me2 and –me3 states could be quantitatively increased in frog embryos without any obvious morphological or molecular consequences ( Figures S8 and S9 ) . This result can be explained considering first of all the higher stability of the knockdown by non-degradable morpholinos compared to the transient protein upregulation by RNA injection; secondly , demethylation of higher-methylated states may occur rather rapidly through H4K20me2 and me3 demethylases at specific sites , where H4K20me1 is required , e . g . Wnt/β-Catenin inducible genes [47] . However , we did not observe evidence for compromised transcription of Wnt target genes under overexpression ( Figures S8 and S9 ) or morphant condition ( Figure S5 ) . Since mono- and dimethylated H4K20 states are quite abundant modifications in Xenopus embryos ( 30–40% each; see ref . [13] ) , it is most likely the loss of H4K20 trimethylation , which interferes with normal development . XSuv4-20h double-morphant embryos were frequently defective for eye and melanocyte differentiation , indicating a prominent impairment of neuroectodermal differentiation . This selectivity is surprising , given that the two HMTases are expressed throughout the entire embryo ( Figure S2 ) . As a matter of fact , the phenotypes originate in the neuroectoderm , as shown by targeted injection into animal or vegetal blastomeres of 8-cell stage embryos ( Figure 4 ) . A large panel of marker genes that were investigated by RNA in situ hybridisation indicates that mesodermal and endodermal gene expression patterns are not perturbed by xSuv4-20h enzyme depletion ( Figure 3A ) . This includes markers , which are required for specification of embryonic axes and formation and patterning of the mesendodermal germlayers ( Figure S5 ) . We also note that morphant animal cap explants were refractory to Noggin-dependent neural induction , but could be induced to differentiated skeletal muscle by a mesoderm inducing signal ( Figure 5 ) . We therefore assume that a major function of xSuv4-20h enzymes lies in the transcriptional control of genes that coordinate and execute neuroectodermal differentiation . Consistent with this hypothesis , many of the genes that we found downregulated in xSuv4-20h morphants , are key regulators of eye development ( Rx-1 , Pax-6 ) , neuronal differentiation ( Ngnr 1a , Delta-like 1 ) or regulators of neural competence and neural plate state ( Zic-1 , -2 , -3 , Xiro-1 , Nrp1 , N-CAM; [27] ) . While these molecular results explain the overt morphological phenotypes in a consistent manner , it should be noted that these HMTases are clearly involved in additional cellular aspects . The mild reduction in mitotic cells and the increased apoptotic rate of morphant embryos ( Figure S10 ) is reminiscent of findings in Suv4-20h1/h2 DKO MEFs , which are less resistant to DNA damage and compromised at the G1/S checkpoint [24] . The data reported here indicates a need for deeper analysis of the regulatory impact of Suv4-20h enzymes on transcription in both mammals and non-mammalian vertebrates . According to current models , xSuv4-20h enzymes mediate transcriptional repression , based on the enrichment of the H4K20me3 mark on heterochromatic foci . Genes that are regulated by these enzymes should therefore become derepressed under loss of function condition . Following this logic , many of the genes , which are misregulated in morphant frog embryos , would be classified as indirect targets , since they were downregulated . One very notable exception , which we have validated as direct target , is Oct-25 ( Figure 6 ) . Oct-25 is induced broadly in the animal hemisphere at the blastula/gastrula transition , before it becomes restricted to the notoplate at neurula stages [31] . Oct-25 plays multiple roles during early frog development , including interference with Activin/BMP-dependent mesendoderm formation before gastrulation , and with neural induction during gastrulation [31] , [32] , [34] . Our study reveals now a new function for Oct-25 , namely to control the transit from a pluripotent cell to a neural cell that differentiates , when Oct-25 expression has faded . As depicted in our model ( Figure 7E ) , this function depends on the precise dose and duration of Oct-25 transcription , which is controlled by the level of H4K20me3 deposition on the first exon of the Oct-25 gene through xSuv4-20h enzymes . As we have shown here , deregulated transcription of Oct-25 in double-morphant embryos elicits massive consequences on the differentiation of neuroectodermal organs and cell types . We have traced back the origin of the malformations to the gastrula stage , when a gene network , defining the neural state , become perturbed by Oct-25 . Some members of this network are good candidates for direct regulation through Oct-25 ( e . g . Zic and Sox genes ) . However , since Oct-25 transcription persists ectopically at least until the mid-neural fold stage in the ectoderm , subsequent gene cascades involved in regional differentiation of the neuroectoderm could also be directly misregulated by Oct-25 . The specific and selective deregulation of Oct-25 transcription in a precise spatial domain , i . e . the sensorial cell layer of the ectoderm , implies a very intriguing role for xSuv4-20h enzymes . This domain contains not only the uncommitted precursors of neuronal and epidermal cell types , but – with regard to the involuting marginal zone – includes also mesodermal and endodermal precursor cells . The observed derepression of Oct-25 in this domain may thus reflect a conserved mechanism , by which Suv4-20h enzymes control pluripotency in the embryo . As discussed above , we have found Oct4 protein to be increased in two independent Suv4-20h double knockout ES cell lines under LIF-maintained self-renewal conditions , when compared to wt ES cells ( Figure 8 and Figure S17 ) . The DKO cell lines also maintain higher Oct4 levels during differentiation than wt ES cells , although their Oct4 levels get diminished in the course of 6 days . Recent data from several labs suggest that the pluripotency regulators Sox2 and Oct4 guide ES cells towards specific germ layer differentiation programs , when they exit the pluripotent state [41] , [42] . Indeed , our findings are in agreement with Thomson and colleagues , who describe Oct4 to antagonize ectodermal specification and to direct mesendodermal cell fate decisions . The conserved Suv4-20h-dependent restriction of Oct4 expression may thus contribute to the germ-layer specification of embryonic cells , when they exit the pluripotent state .
Animal work has been conducted in accordance with Deutsches Tierschutzgesetz; experimental use of Xenopus embryos has been licensed by the Government of Oberbayern ( Projekt/AK ROB: 55 . 2 . 1 . 54-2532 . 6-3-11 ) . Full length X . laevis Suv4-20h1a ( NM_001092308 ) and Suv4-20h2a ( NM_001097050 ) cDNAs in pCMV-SPORT6 were provided by ImaGenes . Capped mRNAs were synthesized in vitro with SP6 RNA-Polymerase after HpaI linearization . Both cDNAs were subcloned via XhoI/EcoRI sites into pBluescript II KS to generate digoxygenin-labelled antisense probes with T3 RNA-Polymerase . Xenopus Bcl-2 , Oct-25-VP16 and –EnR constructs were transcribed with SP6 RNA-Polymerase from NotI- ( Bcl-2 and Oct-25-VP16 ) and SacII- ( Oct-25-EnR ) linearized pCS2+ plasmids , respectively . Mouse Suv4-20h1 and h2 enzymes were transcribed with SP6 from PvuI-linearized pCMVmyc-constructs [24] . Enzymatically inactive mouse Suv4-20h HMTases were generated via PCR-mutagenesis ( see Text S1 , Table S1 for primers ) . Synthetic mRNAs were injected in the animal pole of two-cell stage embryos at 2 , 3 or 4ng per embryo . Rescue experiments with wt and mutated mRNAs were performed with 3ng of a 1∶1 mix of wt or mutated Suv4-20h1 and h2 mRNAs , injected into the animal pole of a single blastomere at two-cell stage . Xenopus Bcl-2 mRNA was injected unilaterally in the animal pole of two-cell stage embryos at 800 pg per embryo . Xenopus Oct-25-VP16 , -EnR mRNAs were injected in the animal pole of two-cell stage embryos at 100 pg per embryo . Mouse embryonic fibroblasts ( MEF ) wild type and Suv4-20h DKO cells [24] were cultivated in High Glucose DMEM with L-Glutamine and sodium pyruvate , complemented with 10% FCS , β-mercaptoethanol , non essential amino acids and penicillin/streptomycin in a 37°C incubator at 5% CO2 . Lipofectamine 2000 ( Invitrogen ) was used for the transfection of plasmid DNAs . Immunofluorescence analysis was performed as described in the Text S1 . Mouse ES cells were cultivated on gelatinized plates in High Glucose DMEM with L-Glutamine and sodium pyruvate , complemented with 15% FCS , 0 . 1 mM ß-mercaptoethanol , non essential amino acids , penicillin/streptomycin and LIF . Cells were maintained at 37°C in a humidified atmosphere of 5% CO2 . ES in vitro differentiation and FACS analysis were carried out as described [43] The incubation steps with the primary Oct4 ( 1∶250 , Abcam ) or CxCR4 ( 1∶50 , BD Pharmingen ) antibody and subsequently a FITC-conjugated secondary antibody ( 1∶250 , Invitrogen ) were performed at RT for 45 min with two washing steps after each antibody incubation . For the isotype controls purified , IgG was used instead of the Oct4-antibody . All FACS analyses were performed with an Epics XL ( Beckman-Coulter ) using the analysis software FlowJo . Translation-blocking Morpholino oligonucleotides targeting Xenopus Suv4-20h1 ( X . laevis and X . tropicalis: 5′-GGATTCGCCCAACCACTTCATGCCA-3′ ) , Xenopus Suv4-20h2 ( X . laevis: 5′-TTGCCGTCAACCGATTTGAACCCAT-3′: X . tropicalis: 5′-CCGTCAAGCGATTTGAACCCATAGT-3′ ) and Xenopus Oct-25 ( X . laevis: 5′-TTGGGAAGGGCTGTTGGCTGTACAT-3′ ) mRNAs were supplied by Gene Tools LLC . Each Morpholinos recognizes the two non-allelic isoforms of each gene in X . laevis ( see Figure S3A , S3B ) . GeneTools' standard control Morpholino was used to monitor non-specific effects . Morpholino activity was tested by in vitro translation ( SP6-TNT Kit , Promega ) , adding 2 pg of control Morpholino or 1 pg of Suv4-20h1 and/or h2 Morpholinos per TNT reaction . Unless stated otherwise , embryos were injected at a dose of 60–80 ng per embryo ( 30–40 ng each of Suv4-20h1 and h2 Morpholinos , or 60–80 ng control Morpholino per embryo ) . For 8-cell stage experiments , morpholinos were injected in two neighbouring , animal or vegetal blastomeres on one side of the embryos , at half the dose ( i . e . 40 ng total ) . For morphogical epistasis experiments , Xenopus Suv4-20h1 and h2 Morpholinos ( 5 ng each per embryo ) and Oct-25 Morpholino ( 1 ng per embryo ) were injected into A1 blastomere at 32-cell stage . Xenopus laevis eggs were collected , fertilized in vitro , and handled following standard procedures; embryos were staged according to Nieuwkoop and Faber ( 1967 ) . The embryos were injected with maximally 10 nl volume . When required , they were sorted into left side or right side injected cohorts before fixation , based on the coinjected lineage tracer Alexa Fluor-488 Dextran ( Invitrogen ) . Alkaline-phosphatase stained and refixed embryos were either sectioned after embedding in paraffin ( 10 µm ) , or in gelatine/albumin mixture supplemented with 25% glutaraldehyde before sectioning ( 30–50 µm ) with a Vibratome 1000 ( Technical Products International , INC . ) as described [48] . Animal caps were manually dissected at NF9 and transferred singly into wells of a 96-well plate , coated with 1% agarose and filled with 1X Steinberg's solution , 0 . 1% BSA with or without Activin A ( 1∶10 diluted conditioned cell culture supernatant ) . For neural induction , embryos were injected into the animal pole with Noggin mRNA ( 60 pg per embryo ) alone or together with xSuv4-20h1 and h2 morpholinos ( 40 ng each per embryo ) at two- to four-cell stage . For mesoderm induction , embryos were injected animally 4 times with 2 . 5 nl of control morpholino ( 80 ng per embryo ) or a mix of xSuv4-20h1 and h2 morpholinos ( 40 ng each ) at two or four cell stage . For Oct-25-VP16 and –EnR overexpression experiments , embryos were injected animally 4 times with 2 . 5 nl of each mRNAs ( 100 pg per embryo ) . For epistasis experiments on animal caps , embryos were injected 4 times with 2 . 5 nl of xSuv4-20h1 and h2 Morpholinos ( 40 ng each per embryo ) and Oct-25 Morpholino ( 30 ng per embryo ) at two or four cell stage . Nuclei extraction from Xenopus embryos and mass spectrometry analysis of histone modifications were performed as described [13] . Histone marks were quantitated as relative abundances of a specific modification state as a fraction of the amount of all modifications found for this peptide ( for details see ref 13 ) . Whole-mount RNA in situ hybridizations were performed as described ( Sive et al . 2000 ) . Embryos were photographed under bright light with a Leica M205FA stereomicroscope . The following antibodies were used for immunocytochemistry: H3S10P antibody ( 1∶300 , Upstate Biotechnology ) , active Caspase3 antibody ( 1∶500 , Promega ) , and myosin heavy chain antibody MF20 ( 1∶100 hybridoma cell culture supernatant ) , anti-mouse or anti-rabbit alkaline phosphatase-conjugated secondary antibodies ( 1∶1000 , Chemicon ) . Embryonic histones were purified via acidic extraction of nuclei as described [13] , size-separated by SDS-PAGE and blotted onto PVDF membranes ( Roth ) . Membranes were blocked with 3% BSA ( Roth ) in PBS and subsequently incubated o/n at 4°C with polyclonal rabbit antibodies against H4K20me1 ( 1∶6000 ) , H4K20me2 ( 1∶1000 ) , H4K20me3 ( 1∶500 ) [21] , [24] and pan H3 ( 1∶25000 , Abcam ) . Infrared ( IR ) 680 or 800 conjugated Goat anti Rabbit IgG ( 1∶5000 , Li-Cor ) were used as secondary antibodies ( incubation o/n at 4°C ) . Signals were detected with an ODYSSEY Infrared Imaging System . To extract exogenous myc-tagged fusion proteins embryos were treated as described in the Text S1 . Proteins were separated by SDS-PAGE , BSA-blocked PVDF membranes were incubated o/n at 4°C with anti-myc 9E10 antibody ( 1∶50 ) , followed by anti-mouse HRP- conjugated antibody ( 1∶3000 , Jackson Immunoresearch ) . Proteins were detected with ECL plus western blotting detection reagents ( GE Healthcare ) . Histological sections were stained with pan H3 ( 1∶2000 , Abcam ) , H4K20me1 ( 1∶5000 ) , H4K20me2 ( 1∶2000 ) , H4K20me3 ( 1∶5000 ) antibodies [24] . Total cellular RNA was isolated with TRizol ( Qiagen ) and phenol/chloroform extraction . On-column RNA clean-up , including a DNAse digestion step , was performed using RNeasy-Mini-Kit ( Qiagen ) . Samples for qRT-PCR and microarray profiling were collected as described in the Text S1 . Microarray data were processed using R/Bioconductor ( www . bioconductor . org ) . If not indicated otherwise , we used standard parameters in all functions calls . Expression values were calculated using ‘gcrma’ . Probe sets were kept for differential expression analysis if there were more ‘present’ calls ( calculated using ‘mas5calls’ ) in one of the treatment groups than non-‘present’ calls , if their expression level variance was higher than 0 across all arrays and if the probe set had an Entrez identifier annotation according to the Entrez database with a date stamp of 2011- Mar16 . One gene to many probe set relationships were resolved by retaining only the probe set with the highest variance across all arrays . Differential expression statistics were obtained using a linear model ( library ‘limma’ ) . A significant response was defined if the local false discovery ( ‘locfdr’ package ) rate calculated on the moderated t statistic was smaller than 0 . 2 . The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE41256 ( http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE41256 ) . ChIP experiments were performed using Xenopus tropicalis as described [49] , with minor changes ( see Text S1 for details ) . A published weight matrix ( PMID:17567999 ) was used to scan 2 kb upstream regions of selected X . tropicalis genes ( Xenbase version 7 . 1 ) for binding site occurrence . Scanning was performed using RSA matrix-scan ( PMID:18802439 ) with default parameters . | The quest of modern developmental biology is a detailed molecular description of the process that leads from the fertilized egg to the complex and highly differentiated adult organism . This process is controlled largely on the level of gene expression . While early embryonic cells are pluripotent and capable of transcribing most of their genome , older cells have become committed to the germ layer and differentiation programs during gastrulation . They express then a subset of genes compatible with their future physiological function . Young , pluripotent cells and post-gastrula , committed cells express different networks of transcription factors and contain chromatin of different structure and composition . How these two regulatory layers are interconnected during development is incompletely understood . We describe a novel and unexpected link between the pluripotency-associated POU-V gene Oct-25 and xSuv4-20h histone methyltransferases . XSuv4-20h enzymes are required to repress the Oct-25 gene , a homolog of mammalian Oct4 , in the neuroectoderm of frog embryos as a prerequisite for neural differentiation . Consistently , murine Suv4-20h double-null ES cells show increased Oct4 protein levels before and during in vitro differentiation and display compromised differentiation in comparison to wild-type ES cells . Thus , Suv4-20h enzymes control specific POU-V genes and are involved in germ-layer specific differentiation . | [
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"differentiation"
] | 2013 | Suv4-20h Histone Methyltransferases Promote Neuroectodermal Differentiation by Silencing the Pluripotency-Associated Oct-25 Gene |
Stringent steric exclusion mechanisms limit the misincorporation of ribonucleotides by high-fidelity DNA polymerases into genomic DNA . In contrast , low-fidelity Escherichia coli DNA polymerase V ( pol V ) has relatively poor sugar discrimination and frequently misincorporates ribonucleotides . Substitution of a steric gate tyrosine residue with alanine ( umuC_Y11A ) reduces sugar selectivity further and allows pol V to readily misincorporate ribonucleotides as easily as deoxynucleotides , whilst leaving its poor base-substitution fidelity essentially unchanged . However , the mutability of cells expressing the steric gate pol V mutant is very low due to efficient repair mechanisms that are triggered by the misincorporated rNMPs . Comparison of the mutation frequency between strains expressing wild-type and mutant pol V therefore allows us to identify pathways specifically directed at ribonucleotide excision repair ( RER ) . We previously demonstrated that rNMPs incorporated by umuC_Y11A are efficiently removed from DNA in a repair pathway initiated by RNase HII . Using the same approach , we show here that mismatch repair and base excision repair play minimal back-up roles in RER in vivo . In contrast , in the absence of functional RNase HII , umuC_Y11A-dependent mutagenesis increases significantly in ΔuvrA , uvrB5 and ΔuvrC strains , suggesting that rNMPs misincorporated into DNA are actively repaired by nucleotide excision repair ( NER ) in vivo . Participation of NER in RER was confirmed by reconstituting ribonucleotide-dependent NER in vitro . We show that UvrABC nuclease-catalyzed incisions are readily made on DNA templates containing one , two , or five rNMPs and that the reactions are stimulated by the presence of mispaired bases . Similar to NER of DNA lesions , excision of rNMPs proceeds through dual incisions made at the 8th phosphodiester bond 5′ and 4th–5th phosphodiester bonds 3′ of the ribonucleotide . Ribonucleotides misinserted into DNA can therefore be added to the broad list of helix-distorting modifications that are substrates for NER .
In order to preserve the properties and functions of a living organism , the genetic information encoded in its DNA should be kept essentially unchanged . In reality , DNA is constantly subjected to numerous attacks from endogenous and exogenous sources changing its chemical composition and structure . If left unrepaired , these changes could have potentially serious cytotoxic and/or mutagenic consequences for the cell . Among all abnormalities in DNA , the presence of ribonucleotides in the DNA backbone appears to be one of the most common threats to genomic stability . Because of the reactive 2′-hydroxyl group on the sugar moiety , rNMPs embedded in the chromosome make the DNA strand susceptible to spontaneous and enzymatically-catalyzed hydrolytic cleavage [1] . They can also cause B- to A-form helical transition in DNA that would interfere with normal binding of various DNA-interacting proteins and disrupt a range of DNA transactions [2] , [3] . Moreover , unrepaired ribonucleotides can lead to replication stress and genome instability [4]–[7] . RNA primers synthesized during the initiation of lagging-strand replication are a major source of rNMPs in DNA . These primers must be excised from DNA prior to joining of Okazaki fragments into an intact lagging strand . Several nucleases have been implicated in this process [8] . Among these are enzymes specifically hydrolyzing the phosphodiester bond between ribo- and deoxyribonucleotides , i . e . ribonucleotide-specific endonucleases , ribonucleases HI and HII ( RNase H ) , which appeared to be ideally suited to play a primary role in RNA primer removal . However , subsequent studies revealed that the RNase H-initiated pathway is not the major mechanism leading to the removal of RNA primers ( reviewed in [8] ) , although the enzymes are nevertheless essential for many key cellular processes requiring degradation of RNA from RNA/DNA hybrids . In particular , it has been shown that the RNase H pathway is indispensable for the removal of errant ribonucleotides randomly misinserted by DNA polymerases during replication and repair synthesis [9]–[11] . The role of Saccharomyces cerevisiae ( S . cerevisiae ) and Escherichia coli ( E . coli ) ribonucleases in ribonucleotide excision repair ( RER ) has been described in several recent publications [10]–[13] . In both organisms rNMP removal is primarily initiated by an RNase H type 2 enzyme; RNase H2 encoded by rnh2 in eukaryotes and RNase HII encoded by rnhB in prokaryotes . Ribonucleases of this type possess a broad cleavage specificity effectively hydrolyzing phosphodiester bonds at the RNA-DNA junction on the templates containing RNA fragments , as well as isolated rNMPs embedded into double-stranded ( ds ) DNA . In contrast , type 1 ribonucleases , such as RNase H1 encoded by rnh1 in eukaryotes and RNase HI encoded by rnhA in prokaryotes , require a tract of at least four consecutive ribonucleotides within the DNA strand for the efficient cleavage . Biochemical analysis using yeast purified recombinant proteins revealed that RNase H1 cannot substitute for RNase H2 in the RER pathway [10] . On the other hand , using an in vivo approach , we have recently shown that RNase HI substitutes for RNase HII in ΔrnhB cells thus limiting the mutagenic consequences of excessive ribonucleotide accumulation in E . coli genome [11] . The apparent discrepancy between these two studies is most likely explained by differences in sugar selectivity of the polymerases responsible for rNMPs insertion , rather than by differences in substrate specificities , or other biochemical properties of yeast and bacterial type 1 ribonucleases that govern the participation of the enzymes in the RER pathway . Indeed , both yeast replicative polymerases , pol δ and pol ε effectively discriminate between rNTPs and dNTPs and incorporate ribonucleotides into DNA at low frequencies ( 1 per ∼600–900 nt; [10] ) . It is therefore highly unlikely that either pol δ or pol ε would catalyze synthesis of DNA containing several consecutive ribonucleotides , which would be a potential substrate for RNase HI . In contrast , E . coli pol V ( UmuD′2C heterotrimer ) appears to be one of the most indiscriminate polymerases for sugar selection [14] . In the presence of rNTPs , it is able to synthesize remarkably long RNA products [14] . A Y11A substitution in the steric gate of UmuC not only further reduces the selectivity against single rNTP incorporation , but also essentially converts the resulting mutant into a bona fide primer-dependent RNA polymerase that synthesizes RNA products at a 3-fold faster rate relative to the wild-type enzyme [14] . It is not surprising , therefore , that the mutant pol V catalyzes synthesis of DNA strands containing not only scattered single rNMPs , but also continuous RNA fragments that could be cleaved by both RNase HI and RNase HII [14] . Thus , while RNase HII plays a major role in keeping the E . coli chromosome free from errant ribonucleotides , in its absence RNase HI functions as an effective substitute to reduce genomic instability promoted through frequent ribonucleotide misincorporation . In contrast , in the absence of a proper substitute for yeast RNase H2 , replicative stress occurs and leads to genome instability [12] . This instability depends on the activity of topoisomerase 1 ( Top1 ) , whose primary function in the cell is to regulate DNA supercoiling by creating transient single-strand ( ss ) breaks . When Top1 cleaves the phosphodiester bond at the sites of incorporated rNMP , the ss break that is created is irreversible because of the presence of a 2′-OH group of the ribose ring . This leads to the formation of a 2′–3′-cyclic phosphate that is refractory to re-ligation [12] . Indeed , substitution of RNase H2 by Top1 in the processing of rNMPs has distinct mutagenic consequences , i . e . accumulation of 2- to 5-bp deletions within tandem repeat sequences [12] . There is no doubt that RER initiated by type 2 RNase H is the major pathway removing errant rNMPs from ds DNA . However , as with other cellular processes , it is anticipated that alternative mechanisms limiting the impact of ribonucleotides in the genome have evolved . Indeed , as noted above , that is the case when rnhB is inactivated and rnhA helps sanitize the E . coli genome of errantly incorporated ribonucleotides [11] . However , whilst umuC_Y11A-dependent mutagenesis relative to wild-type pol V increased from ∼7% in rnh+ strains to ∼39% in ΔrnhB strains and further increased to ∼74% in the ΔrnhB ΔrnhA strain , it was still significantly lower than that promoted by wild-type pol V , despite the fact the enzyme exhibits the same low-base selectivity in vitro [14] . These data suggest that additional mechanisms exist which target the ribonucleotides incorporated by umuC_Y11A for repair and in the process misincorporated deoxyribonucleotides are also removed from the E . coli genome . We have taken advantage of the pol V phenotype to investigate the contribution of mismatch repair ( MMR ) , base excision repair ( BER ) and nucleotide excision repair ( NER ) to ribonucleotide excision repair ( RER ) in E . coli . We find no evidence for a significant role of either MMR or BER in back-up RER pathways . Somewhat surprisingly , we discovered that there was a major contribution to RER by NER in vivo . By using in vitro assays , we confirm that NER is able to recognize and excise an isolated ribonucleotide , as well as multiple rNMPs within a short RNA fragment in dsDNA in vitro . Efficient ribonucleotide repair in E . coli and most likely other prokaryotes is , therefore , achieved though the concerted actions of rnhB , rnhA and NER .
E . coli pol V is a highly error-prone Y-family DNA polymerase best characterized for its capacity to replicate damaged DNA [15] , [16] . However , in certain genetic backgrounds , such as in recA730 strains in which the RecA protein is in a so-called constitutively “activated state” ( RecA* ) that both favors the formation of pol V ( UmuD′2C ) [17] , [18] , and also increases its stability [19] , [20] , pol V can compete with the cell's replicase ( pol III ) for access to undamaged genomic DNA . Since pol V has much lower fidelity than pol III , this is manifested as a dramatic increase in spontaneous mutagenesis [21] , [22] . We have previously taken advantage of this phenotype to elucidate pathways of ribonucleotide repair in E . coli . To do so , we generated a steric-gate Y11A mutant in the catalytic UmuC subunit of pol V , which has significantly reduced sugar discrimination . As a result , the mutant pol V enzyme incorporates ribonucleotides into DNA nearly as efficiently as deoxyribonucleotides [14] . In contrast , the base-selection fidelity of the Y11A mutant was largely unchanged and like wild-type pol V , umuC_Y11A frequently misincorporated the wrong base into nascent DNA in vitro [14] . However , to our surprise , the spontaneous mutation frequency in a recA730 lexA ( Def ) ΔdinB ΔumuDC strain expressing umuC_Y11A was an order of magnitude lower than that of the isogenic strain expressing wild-type pol V [23] . The apparent discrepancy was explained by the umuC_Y11A-dependent incorporation of rNMPs into the E . coli genome that triggered efficient ribonucleotide excision repair ( RER ) pathways and concomitantly removed misincorporated deoxyribonucleotides . umuC_Y11A-dependent spontaneous mutagenesis increased significantly in a ΔrnhB background and to a much larger extent when both rnhB and rnhA were inactivated [11] ( Fig . 1 ) . However , mutagenesis was still lower than that of wild-type pol V suggesting that other back-up RER pathways exist in E . coli that operate to remove errantly incorporated ribonucleotides . We hypothesized that similar to our earlier observation , where the extent of umuC_Y11A-dependent mutagenesis relative to wild-type pol V increased when rnhA was inactivated in an ΔrnhB strain , we would also observe an increase in umuC_Y11A-dependent mutagenesis in other genetic backgrounds that are compromised for RER . We therefore constructed a series of isogenic recA730 lexA ( Def ) ΔdinB ΔumuDC rnhB+/ΔrnhB strains in which mismatch repair ( MMR; ΔmutL , ΔmutH , ΔmutS , ΔuvrD ) , base excision repair ( BER; Δung , Δxth , Δnfo ) , or nucleotide excision repair ( NER; ΔuvrA , uvrB5 , ΔuvrC , Δcho , ΔuvrD ) were inactivated and assayed for pol V-dependent spontaneous mutagenesis ( Fig . 1 ) . As noted previously , despite being isogenic , the strains expressing wild-type pol V exhibit quite different levels of spontaneous mutagenesis . We believe that this phenotype is due to effects on the constitutive activation of the RecA protein , which is an absolute requirement for high levels of pol V-dependent spontaneous mutagenesis [21] . As a consequence , we report the extent of umuC_Y11A-dependent mutagenesis relative to wild-type pol V , since any indirect effect on RecA activation would be the same for both mutant and wild-type pol V , with the only difference being their respective ability to efficiently incorporate ribonucleotides into genomic DNA . As a control , we monitored spontaneous mutagenesis in the isogenic strains lacking pol V ( containing the plasmid vector , pGB2 ) . Since the number of His+ revertants in these cells is pol V-independent , it should remain constantly low in all genetic backgrounds with the exception of the MMR deficient strains , where a ∼10-fold increase in mutation frequency is anticipated . Inactivation of MMR ( via ΔmutL , ΔmutH , or ΔmutS alleles ) results in an ∼3 . 5-fold increase in the relative amount of spontaneous His+ mutagenesis promoted by plasmid encoded umuC_Y11A compared to wild-type pol V ( Fig . 1 ) . These data appear to implicate MMR in the repair of at least a subset of ribonucleotides ( mis ) incorporated by umuC_Y11A and such observations are consistent with an earlier study reporting an effect of MMR on ribonucleotide repair [13] . However , there was no additional increase in the relative amount of umuC_Y11A mutagenesis in ΔrnhB ΔmutL , ΔrnhB ΔmutH , or ΔrnhB ΔmutS strains ( Fig . 1 ) , which would be expected if MMR participates in repair pathways that substitute for the RNase HII-dependent RER of ribonucleotides misincorporated by umuC_Y11A . We hypothesize that the increase in relative mutagenesis in the rnhB+ MMR-deficient strains expressing umuC_Y11A is not caused by a reduction of rNMP repair , but rather reflects misincorporations made by a different DNA polymerase participating in the re-synthesis step of ribonucleotide repair . To examine this possibility , we determined the spectra of mutations generated in rnhB+/ΔrnhB strains expressing umuC_Y11A ( Fig . 2 ) . As expected , the ΔmutL rnhB+ spectrum ( Fig . 2A ) was dominated by transition events . In contrast , the ΔmutL ΔrnhB strain exhibited a different mutagenic spectrum that included many more transversions ( Table S1 ) , which are “signatures” of error-prone pol V [24] , [25] . To further extend our hypothesis that the mutations in the rnhB+ and ΔrnhB strains are generated by two different polymerases operating in two different pathways , we assayed the spectrum of rpoB mutations in mismatch repair proficient rnhB+ and ΔrnhB strains expressing umuC_Y11A ( Fig . 2B ) . In contrast to the MMR− strains , where the spectrum was dominated by transitions , the majority of base substitutions in the MMR+ strains were transversion events , which is consistent with the efficient repair of transition mutations by the mismatch repair machinery ( Table S1 ) . In agreement with our hypothesis , not only was the mutation rate of the rnhB+ strain 6-fold lower compared to the ΔrnhB strain , the mutagenic hot-spots varied considerably , suggesting that the mutations were generated by different DNA polymerases . In particular , in the ΔrnhB strain where umuC_Y11A misincorporations are likely to persist , the spectrum was dominated by AT→TA transversions ( at positions 1547 , 1577 and 1714 ) that are characteristic of pol V [24] . Together , our data indicate that the prokaryotic MMR pathway , while possessing the capacity to recognize mispaired bases , does not selectively recognize ribonucleotide mispairs over deoxyribonucleotides mispairs and therefore does not contribute significantly to RER . To continue our search of a RER backup pathway , we turned to base excision repair ( BER ) , which targets a variety of base lesions . Of particular relevance , are dUMPs frequently misincorporated by DNA polymerases [26] , or formed through the spontaneous hydrolytic deamination of cytosines and which are released through BER initiated by uracil DNA glycosylase ( encoded by the ung gene ) . Ung recognizes the lesion and hydrolyzes the N-glycosylic bond between the uracil base and sugar ring converting uracil into an abasic site . The next major step of BER is cleavage of the abasic site by one of the class II apurinic/apyrimidinic ( AP ) endonucleases , such as exonuclease III ( encoded by the xthA gene ) , or endonuclease IV ( encoded by nfo ) , which together account for the vast majority of AP endonuclease activity in E . coli [27] , [28] . Similar to the proposed RNase HII-dependent RER pathway , processing of the BER intermediates involves strand-displacement DNA synthesis with replication products ranging from just one base-pair to several hundred nucleotides [29]–[31] . We therefore considered the possibility that BER might operate to remove misincorporated rUMPs , which would provide a mechanism to reduce the mutagenic potential of umuC_Y11A-dependent spontaneous mutagenesis . However , inactivation of ung , xth , or nfo had no discernible effect on the relative extent of umuC_Y11A mutagenesis in either rnhB+ or ΔrnhB strains ( Fig . 1 ) . Based upon these observations , we conclude that BER is unlikely to participate in any RER back-up pathway in E . coli . We recently reported that ΔuvrA and ΔuvrC strains expressing umuC_Y11A are as UV-resistant as those expressing wild-type pol V . This is in dramatic contrast to uvr+ strains in which umuC_Y11A confers minimal UV-resistance [23] despite being as proficient as wild-type pol V in its ability to traverse a UV-induced cyclobutane pyrimidine dimer ( CPD ) [23] . Such phenotypes were attributed to the dual actions of RNase HII nicking the nascent TLS strand and the concomitant actions of the NER proteins on the opposite CPD-containing strand to generate lethal double-strand breaks [11] . In the present study , we analyzed the effect of NER on RER of undamaged DNA . To do so , we determined spontaneous mutagenesis in strains carrying mutations in genes encoding key proteins that mediate damage recognition and excision steps of the E . coli NER pathway ( uvrA , uvrB , uvrC , cho and uvrD ) . It should be noted that the uvrA , uvrB , cho and uvrD genes are normally regulated at the transcriptional level by the LexA repressor [32] . However , since the strains used for the mutagenesis assays carry the recA730 lexA ( Def ) alleles which lead to derepression of all genes in the LexA-regulon , the UvrA , UvrB , Cho and UvrD proteins are all expected to be expressed at fully derepressed levels and as a consequence , NER is active in the absence of exogenous DNA damage . Despite this fact , inactivation of uvrA , uvrB , cho or uvrC ( which is not under lexA control ) , in the rnhB+ background had little effect on the overall low level of mutagenesis promoted by umuC_Y11A relative to wild-type pol V ( Fig . 1 ) . The ΔuvrD strain exhibited somewhat higher levels of spontaneous mutagenesis . However , this phenotype is probably unrelated to NER , but is instead more in line with its dual functions in MMR [33] , [34] . Interestingly , there was a significant increase in the extent of umuC_Y11A-dependent spontaneous mutagenesis in the ΔuvrA ΔrnhB , uvrB5 ΔrnhB and ΔuvrC ΔrnhB strains ( Fig . 1 ) . In contrast , the relative extent of spontaneous mutagenesis remained essentially unchanged in the Δcho ΔrnhB , or ΔuvrD ΔrnhB strains . Together , these observations imply that NER is able to remove ribonucleotides from DNA , and this process occurs via the “classical” NER pathway mediated by the UvrABC proteins and not through an alternate UvrAB/Cho-dependent pathway [35] . In addition , the lack of an apparent uvrD phenotype in RER is consistent with a previous study showing that UvrD is not necessary for the lesion removal under SOS conditions [36] . Furthermore , inactivation of NER ( by ΔuvrA ) in the ΔrnhB ΔrnhA strain resulted in a dramatic increase in umuC_Y11A-dependent mutagenesis , such that it actually became greater than that produced by wild-type pol V ( Fig . 3 ) , indicating that RER is completely inactivated in this genetic background . These findings confirm that UvrABC-dependent NER serves as a bona fide back-up to RNase HII-mediated RER . In summary , our in vivo studies do not indicate a significant role for MMR or BER in ribonucleotide repair in E . coli . In contrast , inactivation of RER via mutations in rnhB resulted in an increase in umuC_Y11A-dependent mutagenesis in ΔrnhA and NER-deficient ( ΔuvrA , uvrB5 and ΔuvrC ) strains , suggesting that RNase HI and the UvrABC proteins function in alternative ribonucleotide repair pathways in E . coli ( Fig . 1 ) . To our knowledge , our data present the first biological evidence for the participation of prokaryotic NER proteins in ribonucleotide repair . We therefore wanted to test the ability of the UvrABC complex to remove rNMPs from DNA directly . To do so , we performed an in vitro incision assay to determine whether the reconstituted NER complex has the capacity to remove ribonucleotides from double-stranded ( ds ) DNA . For these experiments , we chose to utilize highly purified Bacillus caldotenax UvrA and UvrB and Thermatoga maritima UvrC proteins . The UvrABC proteins from the thermophilic bacteria while having extremely high level of sequence similarity with the E . coli proteins are remarkably more stable [37]–[41] . Furthermore , previous studies have demonstrated that individual subunits of the NER complex from Gram-positive bacteria are able to efficiently substitute for the components of the E . coli nuclease in various in vitro excision reactions [37]–[39] , [42]–[46] . We have shown earlier that the UmuC_Y11A polymerase readily extends primers by very efficient ( mis ) incorporation of ATP opposite a variety of different template bases [14] . Therefore , the double-stranded DNA oligonucleotide used as a substrate in the in vitro assays contained either a single , or two consecutive rAMPs . In addition , since UmuC_Y11A is also known to replicate DNA with very low base-substitution fidelity producing both transitions and transversions , in some of the substrates either one ( 3′ ) , or both rAMPs , were mispaired with either cytosine or adenine on the complementary DNA strand . The UmuC_Y11A enzyme is also characterized by an extraordinary ability to synthesize long RNA strands within minutes of engaging the primer-terminus [14] . As a consequence , we also wanted to examine whether the UvrABC proteins are able to initiate repair of DNA containing multiple ribonucleotides and for this purpose , we utilized oligonucleotides with five sequential rNMPs . In the current study , we used double-stranded 50-mer oligonucleotides with rNMPs embedded into a 5′ or 3′ end-labeled DNA strand , which allows us to monitor incisions at both sides of the modified base ( s ) ( Fig . 4 ) . Furthermore , the duplex oligonucleotides were modeled upon a nearly identical fluorescein adducted substrate , which has previously been shown to be a good substrate for the UvrABC endonuclease in vitro [39] ( Fig . 4A , lanes 2 , 3 ) thereby allowing us to directly compare the efficiency of lesion-mediated incision to ribonucleotide-mediated incision . As expected , the undistorted templates remained intact ( Fig . 4B , lane 2 ) , while reactions with duplexes containing A:C and AA:CC mispairs yielded barely detectible bands corresponding to the incisions made at the 8th bond 5′ to the mispair ( Fig . 4B , lanes 3 , 4 ) . In contrast , A:A and AA:AA mismatches did not attract UvrABC mediated incisions ( Fig . 4B , lanes 5 , 6 ) . Our finding is in good agreement with previously published reports of low levels ( 0 . 03–0 . 5% ) of mismatch repair by the bacterial and human NER proteins [47] , [48] . Consistent with our in vivo observations for a role of NER in RER , incubation of the 5′-labeled rAMP-containing DNA with UvrA , UvrB , and UvrC proteins resulted in the robust oligonucleotide cleavage ( Fig . 4C , lane 2 ) , which was only minimally less efficient than cleavage of the DNA with a single fluorescein-adducted thymine ( c . f . Fig . 4A vs . 4C , lane 2 ) . As with the lesions-containing substrate , incision of the ribonucleotide-containing substrate was made at the 8th phosphodiester bond 5′ to the RNA–DNA junction producing an 18 bp product . Reactions with oligonucleotides having two sequential AMPs used as substrates for the UvrABC endonuclease yielded two bands , 18- and 19-mers ( Fig . 4D , lane 2 ) that correspond to incisions made at the 8th bond on the 5′ side of each ribonucleotide . Incision of the substrates with five rNMPs in a row mainly generated an 18 nucleotide fragment ( corresponding to an incision 7 bases 5′ to the first rAMP ) , although a small amount of 17-mer , which is produced by the incisions of the 8th bond 5′ to the RNA/DNA junction , was also observed ( Fig . 4E , lane 2 ) . In contrast and as expected , no cleavage was observed when the complementary DNA strand lacking rNMPs was labeled ( Fig . S1 ) . It has been reported that NER prefers compound lesions consisting of a base damage placed opposite one or more mispaired bases , over the correctly paired lesions ( Fig . 4A , lane 3 ) [49]–[51] . Similarly , the efficiency with which the rNMP-containing template was incised by the UvrABC endonuclease , was also determined by the type of the mispaired base ( Fig . 4 , B–E ) . Mispairing of rA with dC potentiated incision of the substrates containing one , two , or five ribonucleotides ( lane 3 on the Fig . 4C , D , and E ) . In contrast , formation of a dA:rA mispair inhibited removal of the nucleotide with an incorrect sugar ( lane 5 on the Fig . 3B , C , and D ) . The number of mismatches did not affect the incision efficiency for the substrates with one or two rAMPs ( lanes 4 and 6 in Fig . 4C and D ) , but in case of the longer ribonucleotide fragment , the presence of an additional mispair ( Fig . 4E , lane 4 ) counteracted the stimulatory effect of a single mismatch ( lane 3 ) . Among all DNA/RNA hybrids tested , the greatest incision by UvrABC was observed on the substrate with a tract of five rNMPs and one C:rA mispair ( Fig . 4E , lane 3 ) . In contrast to the UvrABC reactions , RNase HII-catalyzed cleavage 5′ to the rAMP was not stimulated by a mispaired base , but was identical for all the substrates with one or two ribonucleotides embedded into ds DNA ( Fig . 5 ) . Analysis of the NER reactions using templates with 3′-labeled rNMP-containing strands indicated that the incision was made at the 5th phosphodiester bond 3′ to the RNA–DNA junction producing a 20 bp ( Fig . 6A ) , or a 19 bp ( Fig . 6B ) product . In contrast to the 5′ incision activity , the efficiency of the cleavage 3′ to the rNMP ( s ) was mainly independent of the presence of base mismatches and type and number of mispaired bases , although templates with the rAs were cleaved somewhat more efficiently than templates containing a single rAMP ( Fig . 6 ) .
E . coli pol V belongs to the Y-family of DNA polymerases [52] , most of which are involved in replication of damaged or distorted DNA [53] . In order to accommodate abnormal nucleotides , the active site of these polymerases is spacious and solvent-exposed [54] . As a consequence , the polymerases exhibit low-fidelity when replicating undamaged DNA and their up-regulation in cells often confers a mutator phenotype [21] , [55] , [56] . Pol V differs from other Y-family members in that along with low base-substitution fidelity , it is also characterized by exceptionally low sugar selectivity [14] . Even though the majority of DNA polymerases discriminate against nucleotides with a ribose moiety quite efficiently , rNMPs appear to be among the most abundant abnormalities in chromosomal DNA [5] , [57] . Nevertheless , investigation of the cellular mechanisms directed at removal of ribonucleotides from DNA has only recently attracted considerable attention . The first line of defense comes from the innate structural features of DNA polymerases themselves . Active sites of most DNA polymerases contain a so-called “steric gate” residue that plays a major role in rNMP exclusion by colliding with the 2′-hydroxyl of an incoming ribonucleotide [58] . The steric gate residue of pol V is Y11 in the UmuC subunit of the polymerase and is among the least efficient barriers against ribonucleotide incorporation since wild-type pol V readily incorporates ribonucleotides into DNA [14] . Substitution of Y11 with a much smaller alanine residue takes sugar indiscretion of the variant polymerase to extremes , since when presented with both types of deoxy- and ribonucleotides , UmuC_Y11A often selects rNTPs during primer extension [14] . Biochemical characterization of UmuC_Y11A and wild-type pol V revealed that besides the differences in sugar selectivity , other properties of the polymerases are similar [14] , [23] . Despite a virtually identical base-substitution fidelity in vitro , the mutability of the strains expressing umuC_Y11A is quite low compared to wild-type pol V [23] . The difference in spontaneous mutagenesis is explained by the extent of the accumulation of errant rNMPs into genomic DNA , and the subsequent actions of repair pathways directed at rNMP removal [11] . Although triggered by the presence of nucleotides with the wrong sugar , activation of these pathways also results in the removal of the deoxyribonucleotides base mispairs which happen to lie inside the rNMP repair “patch” [11] . The connection between rNMP repair and levels of spontaneous mutagenesis therefore provides a unique opportunity to elucidate various repair mechanisms aimed at sanitization of errantly incorporated NTPs from the E . coli genome . Thus , changes in the extent of umuC_Y11A-dependent spontaneous mutagenesis compared to wild-type pol V mutagenesis should identify pathways for rNMP removal . Indeed , using such an approach , we have recently demonstrated that the main pathway directed at rNMP excision involves the nicking action of RNase HII [11] and subsequent strand-displacement DNA synthesis by pol I ( unpublished observations ) . In the present study , we have analyzed the contribution of mismatch repair ( MMR ) , base-excision repair ( BER ) and nucleotide excision repair ( NER ) to ribonucleotide repair in E . coli . Although umuC_Y11A is expected to frequently incorporate ribo-UMP into DNA , we found no evidence that deletion of ung , xth or nfo , all of which lead to defects in the uracil glycosylase-mediated BER pathway , has any effect on ribonucleotide repair in E . coli ( Fig . 1 ) . Such observations are , therefore , consistent with the limited ability of the uracil glycosylase to remove rU compared to dU in vitro [59]–[61] . Furthermore , given the fact that the level of umuC_Y11A-dependent mutagenesis observed when rnhA , rnhB and NER are all inactivated was even higher than with wild-type pol V ( Fig . 3 ) , it seems unlikely that another , as yet unidentified , BER enzyme ( s ) might contribute to RER , but it cannot be formally excluded . When compared to the level of mutagenesis exhibited by wild type pol V , mismatch repair-deficient ΔmutL , ΔmutH and ΔmutS cells all exhibited higher levels of umuC_Y11A-dependent mutagenesis ( Fig . 1 ) . This was initially assumed to reflect the participation of MMR in the removal of ribonucleotides incorporated by umuC_Y11A , especially if the base was also mispaired [13] . However , there was no further increase in umuC_Y11A mutagenesis in the MMR− strains upon deletion of RNase HII ( Fig . 2 ) . Based on our recent finding revealing that the extent of mutagenesis in rnhB+ MMR-deficient strains is dependent upon pol I ( unpublished observations ) , we hypothesize that the increase in mutagenesis observed in the rnhB+ umuC_Y11A MMR− strains actually reflects persisting transition errors which are made by pol I during RNase HII-initiated ribonucleotide repair and which otherwise would be subjected to repair in MMR+ cells ( Fig . 2 ) . Overall , our data suggest that even though MMR is able to remove mispaired ribonucleotides from DNA , it has a limited ( if any ) , role in prokaryotic RER in vivo . Conversely , it has recently been shown that RNase HII-dependent RER plays a significant role in MMR in eukaryotes by providing the strand-discrimination signal that identifies the newly synthesized DNA [62] , [63] . In contrast to MMR and BER , our present study strongly implicates NER as a backup mechanism for ribonucleotide repair in prokaryotes ( Fig . 1 ) . The in vivo data suggest that similar to the RNase HI-dependent pathway , NER is not a primary mechanism of rNMP repair in cells with a functional RNase HII-initiated RER pathway , but plays an important role in the absence of RNase HII . Furthermore , it appears that in ΔrnhB cells both the NER proteins and RNase HI are required for efficient ribonucleotide repair ( Fig . 3 ) . While RNase HI specializes in removal of longer RNA fragments , the UvrABC endonuclease is able to eliminate isolated rNMPs , as well as to compete with RNase HI for removal of several sequential ribonucleotides . In general , it is assumed that NER is the major defense mechanism against bulky DNA adducts , although it is also known to repair relatively minor DNA modifications , such as apurinic sites ( reviewed in [40] , [41] ) and we report here that even misincorporated ribonucleotides that only differ by a single 2′-OH from their deoxyribose counterparts , are also substrates for NER . UvrB/C dependent incisions are made 8 bp 5′ and 4–5 bp 3′ to the ribonucleotide generating a ribonucleotide containing fragment of ∼12–13 bases ( Fig . 4 & 6 ) , which is identical to that obtained with DNA damage-mediated NER in E . coli [40] . So how is the ribose moiety recognized as a “lesion” ? Based on the analysis of the structure and conformation of the diverse set of DNA lesions that are repaired by the NER machinery , it has been suggested that UvrA2B complex is not targeted by nucleotide damage per se , but rather by damaged-induced conformational changes in DNA; the more the DNA helix deviates from the canonical B-form conformation , the more efficient the NER [40] , [41] . This is supported by the fact that NER is much more efficient within the context of distorting base mispairs ( e . g . , Fig . 3A ) . Similarly , we show that the ribonucleotide excision activity of UvrABC endonuclease varies depending on the number of ribonucleotides incorporated into DNA , the presence of base mismatches , and the type and number of mispaired bases , suggesting that it the distortion of the DNA around the ribonucleotide that helps target it for NER ( Fig . 4 ) . However , we also observed significant incision of a single correctly-paired rNMP embedded in DNA , which is unlikely to cause a major conformational change in the local sequence surrounding the ribonucleotide [3] . Since the ribonucleotide moiety provides a negative electrostatic potential and offers new hydrogen bonding opportunities compared to the deoxynucleotide , it is possible that the local differences between an embedded ribo- vs . deoxynucleotide might lead to NER recognition . Clearly , the mechanisms underlying ribonucleotide recognition by the NER complex is a topic that should be investigated further . In summary , we show here that a complex network of DNA repair mechanisms is involved in cleansing chromosomal DNA of misincorporated ribonucleotides ( Fig . 7 ) . RER initiated by RNase HII plays the leading role in removing isolated rNMPs . When this pathway is overloaded , or inactivated , prominent backup roles are assumed by RNase HI and NER proteins . In general , RNase HI facilitates the removal of stretches of ribonucleotides 4 bp or more in length , while NER can excise single and poly-ribonucleotides embedded in DNA . As a consequence , both RNase HI and NER proteins help to reduce genomic instability generated though errant ribonucleotide misincorporation .
Most of the E . coli K-12 strains used in this study are derivatives of RW698 ( full genotype: recA730 lexA51 ( Def ) ΔdinB61::ble ΔumuDC596::ermGT thr-1 araD139 Δ ( gpt-proA ) 62 lacY1 tsx-33 glnV44 galK2 hisG4 rpsL31 xyl-5 mtl-1 argE3 thi-1 sulA211 ) [11] . Repair-deficient “KEIO” strains were obtained from the E . coli Genetic Stock Center and isogenic derivatives of RW698 were generated via generalized transduction using P1vir [64] ( Table 1 ) . Where noted , KanS strains were obtained by transforming cells with the temperature sensitive ampicillin and chloramphenicol resistant plasmid , pCP20 , which expresses the FLP recombinase [65] . Transformants were selected on LB plates containing the appropriate antibiotics at 25°C and subsequently re-streaked on LB plates lacking ampicillin , chloramphenicol and kanamycin and incubated overnight at 43°C . Colonies from these plates were subsequently confirmed to be ampicillin , chloramphenicol and kanamycin sensitive at 37°C . The following antibiotics were used for selection; Zeocin ( 25 µg/ml ) , Kanamycin ( 50 µg/ml ) , Tetracycline ( 15 µg/ml ) , Chloramphenicol ( 20 µg/ml ) , and Ampicillin ( 100 µg/ml ) , Spectinomycin ( 50 µg/ml ) . The low-copy-number spectinomycin resistant plasmids pRW134 and pJM963 which encode E . coli wild-type UmuC and the umuC_Y11A variant , respectively , along with UmuD′ [23] are derived from pGB2 [66] and express the UmuD′C proteins at close to physiological levels from their native promoter [23] . Bacteria harboring plasmids were grown in LB media containing appropriate 50 µg/ml spectinomycin . Cells transformed with the vector plasmid , pGB2 , or the low-copy number plasmid pRW134 expressing wild-type pol V , or pJM963 expressing the umuC_Y11A variant [23] were grown overnight at 37°C in LB media plus appropriate antibiotics . The next day , cultures were centrifuged and resuspended in an equal volume of SM buffer [64] . To determine the number of spontaneously arising histidine mutants on the plate , the cell cultures were seeded on the Davis and Mingioli minimal agar plates [67] plus glucose ( 0 . 4% wt/vol ) ; agar ( 1 . 0% wt/vol ) ; proline , threonine , valine , leucine , and isoleucine ( all at 100 µg/ml ) ; thiamine ( 0 . 25 µg/ml ) ; and either no histidine , or histidine ( 1 µg/ml ) . On the plates containing no histidine , only pre-existing His+ mutants grew to form colonies . When ∼4×107 bacteria were seeded on the 1 µg/ml histidine , they grew to form a lawn , concomitantly exhausting the low level of histidine . Spontaneously arising His+ mutants grew up through the lawn and were counted after 4 days incubation at 37°C . Spontaneous mutagenesis is expressed as a frequency ( mutants per plate ) , because the number of mutants arising on the plate is independent of the number of cells plated , but is , instead , dependent upon the limiting amount of nutrient ( histidine ) in the plate [68] . The relative extent of umuC_Y11A mutagenesis was calculated by first subtracting the number of pre-existing His+ mutants ( mutants arising on the plates lacking histidine ) and subsequently dividing the number of spontaneously arising mutants on the umuC_Y11A ( pJM963 ) plates by the number of spontaneously arising mutants on the wild-type pol V ( pRW134 ) plates . The data reported in Figs . 1 and 3 represent the average number of His+ mutants from at least 3 separate experiments ( ± standard error of the mean [SEM] ) . The mutation spectra were generated using the rpoB/RifR mutagenesis assay [69] , [70] . A single pair of oligonucleotide primers can be used for PCR amplification and a single primer for DNA sequencing because 88% of all rpoB mutations are localized in the central 202 bp region of the gene [69] . E . coli strains RW710 [relevant genotype: lexA ( Def ) recA730 ΔdinB ΔumuDC ΔmutL] , RW942 [relevant genotype: lexA ( Def ) recA730 ΔdinB ΔumuDC ΔmutL ΔrnhB ] , RW698 [relevant genotype: lexA ( Def ) recA730 ΔdinB ΔumuDC] , and RW838 [relevant genotype: lexA ( Def ) recA730 ΔdinB ΔumuDC ΔrnhB ] , harboring the umuC_Y11A plasmid , pJM963 were diluted from a frozen stock cultures such that the initial inoculum contained <1000 viable cells . Cultures were grown in LB for 24 h at 37°C and appropriate dilutions spread on an LB agar plate containing 100 µg/ml rifampicin . Individual independent RifR colonies were picked from the plate using a pipette tip and subjected to PCR in a 96-well micro-titer plate . An <1 kb central region of the rpoB gene was amplified using the PCR primers RpoB1: 5′-CAC ACG GCA TCT GGT TGA TAC AG-3′ and RpoF1: 5′-TGG CGA AAT GGC GGA AAA C-3 by denaturation at 95°C for 3 min , followed by 30 cycles of 94°C for 30 s , 1 min at 59°C , 2 min at 72°C , followed by a final extension step at 72°C for 7 min . The nucleotide sequence of the ∼200 bp target region of rpoB in each PCR amplicon was determined by Beckman Coulter Genomics ( Danvers , MA ) using WOG923AP01 primer ( 5′-CAG TTC CGC GTT GGC CTG-3′ ) . Only base-pair substitutions occurring between positions 1516 and 1717 of the rpoB gene were considered during data analysis . Nucleotide sequences obtained were aligned and analyzed using the ClustalW multiple sequence alignment program ( Hinxton , UK ) . Rates for forward mutations to rifampicin resistance ( mutations in rpoB ) were determined as previously described [25] . The Bacillus caldotenax UvrA and UvrB proteins and the Thermatoga maritima UvrC protein were purified as previously described [39] , [71] . E . coli RNase HII was purchased from New England Biolabs ( Ipswich , MA , USA ) . All oligonucleotides were synthesized by Lofstrand Laboratories ( Gaithersburg , MD ) and gel purified prior to use . The basic sequence of the 50-mer template is: 5′-GAC TAC GTA CTG TTA CGG CTC CAT caa taC CGC AAT CAG GCC AGA TCT GC-3′ . The lowercase letters indicate sites at which substrate dNMPs were replaced by rNMPs . Substrates with a single rAMP ( first underlined a on the 5′ side ) , two consecutive rAMPs ( shown in bold ) , or five rNMPs were tested . A substrate with the site-specifically placed fluorescein adduct ( fT ) [39] was used as a control for the activity of NER proteins and has the same sequence except that the aa bases ( shown in bold ) were replaced with the [fT]C sites . The fT-containing oligonucleotide and the DNA-RNA-DNA hybrids were 5′- or 3′-32P end-labeled and annealed with either completely complementary DNA strands , or with the DNA strands containing one or two mispaired bases . In the case of the fluorescein-adducted template , the damaged T was either correctly paired with A , or mispaired with C . In the case of the DNA-RNA-DNA hybrids , either the 5′A , or both As shown in bold were correctly paired with Ts or mispaired with one , or two , Cs or As . Hybridization was performed at a 1 . 5 molar excess of the unlabeled strand by heating in an annealing buffer ( 50 mM Tris-HCl ( pH 8 ) , 5 mM MgCl2 , 50 µg/ml BSA , 1 . 42 mM 2-mercaptoethanol ) for 10 min at 100°C followed by slow cooling to room temperature . Prior to initiation of the incision assay , the UvrABC proteins were diluted from stock solutions and preheated for 10 min at 55°C . The 10 nM DNA substrates were incubated with UvrA ( 40 nM ) , UvrB ( 200 nM ) , and UvrC ( 100 nM ) proteins for 1 hour at 55°C in the presence of 1 mM ATP in a 1× reaction buffer ( 10 mM Tris , pH 7 . 5 , 10 mM KCl , 2 mM MgCl2 , 1 mM DTT , 0 . 2 mM ATP ) . Cleavage of the 10 nM DNA substrates by RNase HII was performed according to the manufacturer's instructions . Reactions were terminated by the addition of 2× loading buffer ( 97% formamide , 10 mM EDTA , 0 . 1% xylene cyanol , 0 . 1% bromophenol blue ) and the incision products were analyzed on a 15% denaturing polyacrylamide gel . The extent of incision was determined for each substrate and expressed as a percentage of radioactivity in the cleaved products relative to the total signal . Data shown below the gels are the mean values calculated from at least two independent experiments . | Most DNA polymerases differentiate between ribo- and deoxyribonucleotides quite effectively , thereby deterring insertion of nucleotides with the “wrong” sugar into chromosomes . Nevertheless , a significant number of ribonucleotides still get stably incorporated into genomic DNA . E . coli pol V is among the most inaccurate DNA polymerases in terms of both sugar selectivity and base substitution fidelity . The umuC_Y11A steric gate variant of pol V is even less discriminating when selecting sugar of the incoming nucleotide while keeping a similar capacity to form non-Watson-Crick base pairs . In the present study , we describe mechanisms employed by E . coli to excise rNMPs from DNA and to concomitantly reduce the extent of spontaneous mutagenesis induced by umuC_Y11A . The first line of defense comes from Ribonuclease HII , which initiates the ribonucleotide excision repair pathway . In the absence of RNase HII , alternate repair pathways help remove the misincorporated ribonucleotides . Here , we present the first direct evidence that nucleotide excision repair ( NER ) has the capacity to recognize both correctly and incorrectly paired rNMPs embedded in DNA . The combined actions of RNase HII and NER thereby reduce the mutagenic potential of ribonucleotides errantly incorporated into prokaryotic genomes . | [
"Abstract",
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"Results",
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"Methods"
] | [] | 2013 | Removal of Misincorporated Ribonucleotides from Prokaryotic Genomes: An Unexpected Role for Nucleotide Excision Repair |
Crimean-Congo hemorrhagic fever virus ( CCHFV ) is a tick-borne virus capable of causing a severe hemorrhagic fever disease in humans . There are currently no licensed vaccines to prevent CCHFV-associated disease . We developed a DNA vaccine expressing the M-segment glycoprotein precursor gene of CCHFV and assessed its immunogenicity and protective efficacy in two lethal mouse models of disease: type I interferon receptor knockout ( IFNAR-/- ) mice; and a novel transiently immune suppressed ( IS ) mouse model . Vaccination of mice by muscle electroporation of the M-segment DNA vaccine elicited strong antigen-specific humoral immune responses with neutralizing titers after three vaccinations in both IFNAR-/- and IS mouse models . To compare the protective efficacy of the vaccine in the two models , groups of vaccinated mice ( 7–10 per group ) were intraperitoneally ( IP ) challenged with a lethal dose of CCHFV strain IbAr 10200 . Weight loss was markedly reduced in CCHFV DNA-vaccinated mice as compared to controls . Furthermore , whereas all vector-control vaccinated mice succumbed to disease by day 5 , the DNA vaccine protected >60% of the animals from lethal disease . Mice from both models developed comparable levels of antibodies , but the IS mice had a more balanced Th1/Th2 response to vaccination . There were no statistical differences in the protective efficacies of the vaccine in the two models . Our results provide the first comparison of these two mouse models for assessing a vaccine against CCHFV and offer supportive data indicating that a DNA vaccine expressing the glycoprotein genes of CCHFV elicits protective immunity against CCHFV .
Crimean-Congo hemorrhagic fever virus ( CCHFV ) is a tick-borne virus with a wide geographical distribution , including Africa , the Balkans , the Middle East , Russia and western Asia [1] . CCHFV , a member of the Nairoviridae family in the Bunyavirales order , has a tripartite , negative-sense RNA genome comprising small ( S ) , medium ( M ) and large ( L ) segments . The S segment encodes the nucleocapsid protein ( N ) , the M segment encodes the glycoprotein open reading frame ( ORF ) that is cleaved into two structural glycoproteins ( GN and GC ) and non-structural proteins , and the L segment encodes the RNA-dependent RNA polymerase ( reviewed in [2] ) . CCHFV infection can cause Crimean-Congo hemorrhagic fever ( CCHF ) , a severe , often fatal , human disease characterized by hemorrhage . Humans appear to be uniquely affected by CCHFV as infection in other animals , including agricultural animals , does not cause significant disease and the virus is generally cleared after a brief period of viremia [3] , ( reviewed in [4] ) . Human infection can result from the bite of infected ticks , as well as from exposure to infected agricultural animals during butchering [5] . Nosocomial CCHFV infections primarily impacting medical staff have also been reported [6 , 7] . Between 1953 and 2010 , the prevalence and geographical distribution of CCHFV has been increasing with mortality rates ranging from 5–67% , and from 2002 to 2016 more than 9700 CCHF patients were reported in Turkey alone [5 , 8–10] . There is also some evidence that the range of CCHFV is expanding , as CCHFV infected ticks were found in Spain in 2010 and the first reported human infections in Southwestern Europe occurred in Spain in 2016 [11 , 12] . As of 2017 , CCHFV has been designated as one of ten priority emerging infectious diseases by the World Health Organization . This has led to an increased awareness of the need for medical countermeasures aimed at preventing this disease . To date , the only CCHFV vaccine tested in humans is a formalin inactivated , suckling mouse brain-derived , virus preparation formulated with an aluminum hydroxide adjuvant , which was developed in Bulgaria [13] . Evaluation of this vaccine in healthy human volunteers showed that four vaccinations elicited high levels of total IgG but only low levels of neutralizing antibodies [14] . Individuals vaccinated four times were also found to have T-cell responses to N that were approximately ten-fold higher than those individuals receiving a single vaccination . The historical absence of a lethal animal model of CCHF has precluded laboratory evaluation of the efficacy of this vaccine , and controlled human studies have not been reported . Although CCHFV is apathogenic in wild-type mice , two lethal mouse models , a STAT-1 knockout mouse model ( C57BL/6 background ) and interferon α/β ( IFN-α/β ) receptor 1 knockout ( IFNAR-/- ) mouse models ( C57BL/6 or A129 background ) , have been developed , which recapitulate some of the clinical features of CCHF in humans , including severe hepatic injury [15–17] . Both of these mouse systems have been used to evaluate CCHFV vaccines . A study in the STAT-1 mouse model showed that a CCHFV subunit vaccine could elicit strong neutralizing antibodies; however , the mice were not protected from lethal disease , indicating that the STAT-1 model , which has defects in both type I and II interferon signaling systems , is perhaps too sensitive to CCHFV for vaccine evaluation [18 , 19] . In contrast , experimental CCHFV vaccines have recently been reported to show protective efficacy in the IFNAR-/- ( A129 ) model [20 , 21] . This includes a formalin-inactivated CCHFV ( cell culture-derived Turkey-Kelkit06 strain ) vaccine that demonstrated protective efficacy in IFNAR-/- ( A129 ) against a lethal infection with the homologous strain of CCHFV . Additionally , a modified vaccinia Ankara ( MVA ) -vectored vaccine expressing the CCHFV M-segment ORF ( MVA-GP ) , from the IbAr 10200 strain , provided complete protection from lethal infection with the homologous strain of CCHFV [20 , 22] . Investigation of vaccine-induced immune responses with the MVA-GP vaccine suggested that both the cellular and humoral arms were critical for protective efficacy . A CCHFV DNA vaccine comprised of three separate plasmids encoding GN , GC , and N , each tethered to a ubiquitin coding sequence , was also shown to elicit protective immunity in IFNAR-/- A129 mice [23] . We previously developed a CCHFV DNA vaccine encoding the CCHFV M-segment ORF that induced neutralizing antibodies in mice when delivered by gene gun , albeit inconsistently [24] . Efficacy testing was not possible at the time due to the lack of a lethal animal model for CCHFV . Here , we report the improvement of this DNA vaccine by gene optimization of the full length M segment . We evaluated the immunogenicity and protective efficacy of this optimized vaccine when delivered by intramuscular electroporation ( IM-EP ) in two lethal CCHFV models , IFNAR-/- ( C57BL/6 ) mice and a novel transiently immune-suppressed ( IS ) C57BL/6 mouse CCHFV model . The IS mouse model exploits a monoclonal antibody ( MAb-5A3 ) that blocks signaling via the IFNAR-1 subunit of the murine IFN α/β receptor . This transient IFN blockade has been used in several other viral studies to examine the role of type I IFN in disease [25–27] . The advantage of the transient IFN-α/β blockade model is that vaccines can be evaluated in mice with intact IFN-α/β signaling , and then during challenge IFN- α/β can be blocked to test protective efficacy . To our knowledge , this is the first direct comparison of the IFNAR-/- and IS mouse model for assessing the immunogenicity and efficacy of a CCHFV vaccine .
This work was supported by an approved USAMRIID IACUC animal research protocol . Research was conducted under a USAMRIID IACUC supported and approved protocol in compliance with the Animal Welfare Act , PHS Policy , and other Federal statutes and regulations relating to animals and experiments involving animals . The facility where this research was conducted is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care , International and adheres to principles stated in the Guide for the Care and Use of Laboratory Animals , National Research Council , 2011 [28] . This research was conducted at a facility that is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International ( AAALAC ) . Humane endpoints were used during these studies , and mice that were moribund , according to an endpoint score sheet , were humanely euthanized . Mice were euthanized by CO2 exposure using compressed CO2 gas followed by cervical dislocation . However , even with multiple observations per day , some animals died as a direct result of the infection . Hep G2 cells were propagated in Modified Eagle’s Medium with Earle’s Salts ( MEM ) ( Corning ) supplemented with 10% fetal bovine serum ( FBS ) ( Gibco ) , and 1X Glutamax ( Gibco ) . BHK-21 cells were cultured in Dulbecco’s Modified Eagle’s Medium ( DMEM ) ( Corning ) supplemented with: 10% heat-inactivated FBS , 1% penicillin/streptomycin ( Gibco ) , 1% sodium pyruvate ( Sigma ) , and 1% L-glutamine ( HyClone ) . SW-13 cells were cultured in DMEM supplemented with 10% FBS , 1% penicillin/streptomycin , 1% HEPES ( Sigma ) , 1% non-essential amino acids ( Gibco ) , and 1% L-glutamine . COS-7 cells were propagated in MEM supplemented with 10% heat-inactivated FBS , 1% penicillin/streptomycin , and 1% L-glutamine . All cells were maintained at 37°C/5% CO2 . CCHFV strain IbAr 10200 ( USAMRIID collection ) was used for all experiments . This virus was previously passaged nine times in suckling mouse brain and then propagated three times in Hep G2 cells . The virus was collected from clarified cell culture supernatants and stored at -80°C . All CCHFV work was performed in BSL-4 containment . The M-segment ORF of strain IbAr 10200 ( Accession # AAA86616 ) was optimized by GeneArt for human codon usage and deletion of known motifs that are detrimental to mRNA stability or expression . The optimized gene was de novo synthesized and cloned into pCAGGS ( a generous gift from Robert Doms , University of Pennsylvania ) . The codon-optimized M-segment ORF was subcloned into the mammalian expression vector pWRG7077 at the NotI sites to create the optimized CCHFV-M DNA vaccine [24] . Nucleotide sequences were confirmed prior to vaccination . COS-7 cells were propagated in 12-well tissue culture plates ( Corning ) to 70–90% confluency in MEM . The medium in these plates was replaced with an Opti-MEM ( Gibco ) solution containing 2% FBS and 0 . 1% Gentamicin ( Sigma ) ( cOpti-MEM ) . The DNA plasmids were transfected into COS-7 cells in a dilution series of 250 , 100 , 50 , or 0 ng in duplicate using FuGENE 6 ( Promega ) according to manufacturer’s directions . Transfected cells were incubated for 44 h , washed once with PBS and then detached by adding 100 μL of trypsin-EDTA ( Gibco ) per well and incubating at ambient temperature . The cells were washed three times in FACS buffer solution , PBS with 2% heat-inactivated FBS and 0 . 1% sodium azide ( Sigma ) , fixed in Cytofix buffer ( BD Biosciences ) for 30 minutes at 4°C , and then washed once with FACS buffer as above . To detect the intracellular CCHFV glycoprotein , cells were permeabilized with Perm/Wash buffer ( BD Biosciences ) at ambient temperature for 15 minutes , and then centrifuged for five minutes at 980 x g , at 4°C . The permeabilized and non-permeabilized cells were incubated with 20 μg/ml of anti-CCHFV GC mouse monoclonal antibody 11E7 ( USAMRIID ) in Perm/Wash buffer or PBS with 2% FBS respectively , and incubated for 30 minutes at 4°C . Cells were washed three times in Perm/Wash buffer and centrifuged for five minutes at 980 x g , at 4°C between each wash . Alexa Fluor 488-conjugated goat anti-rabbit IgG ( Life Technologies ) was diluted 1:200 and incubated with the cells for 20 minutes at 4°C , and then washed three times with FACS buffer . Cell pellets were re-suspended in 500 μl FACS buffer and analyzed on a FACSCalibur flow cytometer ( BD Biosciences ) . Cells staining positive for intracellular glycoprotein were shown as a percentage of total cells per 10 , 000 events . Histograms and dot plots were generated using FlowJo flow cytometry analysis software ( Tree Star Inc ) . Following the aforementioned 44 h incubation post-transfection , COS-7 cells were lysed with 1X Protein Loading Buffer ( LI-COR ) . The cell lysates were probe sonicated for 15–20 seconds each , mixed 9:1 with 2-mercaptoethanol ( Sigma ) , and heated at 70°C for 10 min . Proteins were separated by SDS-PAGE in 10% Bis-Tris gels ( NuPAGE ) and transferred to polyvinylidene difluoride membranes ( Invitrogen ) . The membranes were blocked with Odyssey Blocking Buffer in Tris–buffered Saline ( TBS , LI-COR ) and probed for either GC with 4 . 1 μg/ml of monoclonal antibody 11E7 ( USAMRIID ) or GN with 1:500 rabbit polyclonal anti-CCHFV GN sera ( a generous gift from Robert Doms , University of Pennsylvania ) [29] prepared in TBS ( Sigma ) supplemented with 0 . 2% Tween-20 ( TBST , Sigma ) and incubated at 4°C overnight . The membranes were washed 3 times with TBST and incubated with IR680-conjugated anti-rabbit or IR800-conjugated anti-mouse secondary antibodies ( LI-COR ) diluted in TBST at ambient temperature for 1 hour . The membranes were washed an additional 3 times with TBST and imaged using an Odyssey CLx imaging system ( LI-COR ) . Groups of 10 IFNAR-/- or C57BL/6 mice were vaccinated in the anterior tibialis muscle with 25 μg of either the optimized CCHFV-M DNA vaccine ( IbAr 10200 ) or the pWRG7077 empty vector using the Ichor TriGrid IM-EP system [30] , under isoflurane anesthesia . All mice were vaccinated three times at three weeks intervals . Blood was obtained via submandibular bleeds prior to each vaccination . Production of IbAr 10200 strain of CCHF VLPs ( CCHFVLP ) was performed with slight modification of methods reported previously [31] . Briefly , BHK-21 cells were propagated to 70–80% confluency in 10 cm2 round tissue culture plates and then transfected with 10 μg pC-M Opt ( IbAr 10200 ) , 4 μg pC-N , 2 μg L-Opt , 4 μg T7-Opt , and 1 μg Nano-luciferase encoding mini-genome plasmid using the Transit LT-1 ( Mirus Bio ) transfection reagent according to manufacturer’s instructions . Three days post-transfection , supernatants were harvested , cleared of debris , and VLPs were pelleted through a cushion of 20% sucrose in virus resuspension buffer ( VRB; 130 mM NaCl , 20 mM HEPES , pH 7 . 4 ) by centrifugation for 2 h at 106 , 750 x g in an SW32 rotor at 4°C . VLPs were resuspended overnight in 1/200 volume VRB at 4°C , and then frozen at -80°C in single-use aliquots . Individual lots of CCHFVLP were standardized by Western Blot analysis based on incorporation of N relative to a parallel gradient of recombinant N loaded on the same SDS-PAGE reducing gel . CCHFVLP were also quantified using a TCID50 assay on SW-13 cells in 96-well , black-walled , clear-bottom plates ( Corning ) . Plates were incubated with ten-fold dilutions of the CCHFVLP overnight and were then processed for Nano Luciferase ( Promega ) expression . Wells that displayed a Nano Luciferase signal 3 standard deviations or greater above background levels were considered positive for VLP signal . VLP stock concentrations ( TCID50 per mL ) were calculated using the Reed and Muench formula [32] . One day prior to the assay , 50 , 000 SW-13 cells were seeded into a 96-well black-walled , clear bottom tissue culture plate . All serum samples were heat inactivated at 56°C for 30 m . Half-log serial dilutions were made in duplicate from 1:25 to 1:25 , 368 and then an equal volume of medium with IbAr 10200 VLPs containing 237 TCID50 units was added and incubated at 37°C/5% CO2 for 1 h . Final effective dilutions of analyte sera ranged from 1:50 to 1:50 , 736 . Half of this reaction mixture ( 50 μl ) was then added to the previously aspirated target cell plate . Cells were incubated for 24 h before being lysed using NanoGlo Lysis buffer mixed with 1/50 dilution of NanoGlo substrate ( Promega ) . Samples were mixed and incubated for 5 m at ambient temperature prior to the luminescent signal being measured on a Modulus Microplate Reader ( Turner Biosystems ) with an integration time of 5 s per well . To measure the effect of complement on neutralization , Low-Tox Guinea Pig Complement ( Cederlane Labs ) was reconstituted in DMEM , filtered , and added to the VLP/sera mixture at a final concentration of 5% and the assay was carried out as above . Data were analyzed as previously reported using GraphPad Prism software ( GraphPad Software ) [33] . High Bind ELISA plates ( Corning ) were coated overnight at 4°C with approximately 1 ng N equivalent of CCHFVLP diluted in PBS per 96-well plate . The following day , plates were washed and then blocked with 3% goat serum/3% skim milk for 1 h at 37°C . All washes were done with PBS containing 0 . 2% Tween-20 ( PBST , Sigma ) . Plates were washed again , prior to being loaded with two-fold serial dilutions of mouse sera in duplicate ( dilution range 1:200 to 1:25 , 600 ) . Serum dilutions were carried out in blocking buffer . Plates were incubated at ambient temperature for 1 h prior to being washed , and then incubated with a 1:1000 dilution of horse radish peroxidase ( HRP ) conjugated goat anti-mouse ( SeraCare Inc . ) in PBST for 1 h at ambient temperature . Plates were washed again and then developed with TMB substrate ( SeraCare Inc . ) . Absorbance at the 450 nm wavelength was detected with a Tecan M1000 microplate reader . Pooled naïve sera collected prior to vaccination was used as an internal control on each assay group . A plate cutoff value was determined based on the average absorbance of the naïve control starting dilution plus 3 standard deviations . Only sample dilutions whose average was above this cut-off were registered as positive signal . Additional analysis was carried out using GraphPad Prism 6 . Plates were coated with CCHFVLP as previously described . The following day , plates were washed and blocked , and two-fold serial dilutions of mouse sera starting at 1:100 were added to the wells of replicate plates . After 1 h incubation at ambient temperature , the plates were washed , and then incubated for 1 h with a 1:10 , 000 dilution of either anti-mouse IgG1 HRP conjugated antibody ( Bethyl ) or anti-mouse IgG2c HRP conjugated antibody ( Bethyl ) . Plates were then washed , and TMB substrate was added and absorbance at 450 nm was recorded . Plates were coated with CCHFVLP . The following day , plates were washed , blocked and loaded with 1:200 dilutions of experimental sera for 1 h at ambient temperature . Plates were then washed before being exposed to concentrations of Sodium Thiocyanate ( Sigma-Aldrich ) ranging from 0–5 . 0 M . Samples were incubated for 15 m at ambient temperature before being washed . Secondary antibody incubation and development with TMB substrate was then performed as previously stated . C57BL/6 mice were treated by the intraperitoneal ( IP ) route with MAb-5A3 ( Leinco Technologies Inc ) 24 h prior to ( 2 . 0 mg ) and 24 h after ( 0 . 5mg ) CCHFV challenge . IFNAR-/- and IS C57BL/6 mice were challenged with 100 plaque forming units ( PFU ) of CCHFV strain IbAr 10200 by the IP route four weeks following the final vaccination . The mice were monitored daily for group weight changes , clinical score , and survival . Twenty-eight days following challenge the surviving mice were euthanized by exsanguination under deep anesthesia , and sera were collected for post-challenge analysis . N-reactive antibodies in challenged mice were detected by ELISA . Recombinant N was produced as previously reported [34] with minor modifications . Briefly , CCHFV N ( strain IbAr 10200 ) was amplified and cloned into the vector pQE-30 ( Qiagen ) to have an N-terminal histidine tag . This insert was transferred into the plasmid pFastbac-1 ( Invitrogen ) in order to generate recombinant baculovirus according to manufacturer’s instructions using the Bac-to-Bac Baculovirus Expression System ( Invitrogen ) . The recombinant CCHFV N protein was produced and purified by AI BioTech . Briefly , Spodoptera frugiperda ( Sf9 ) insect cells were infected with the recombinant baculovirus and incubated at 28°C for 72 hours and then harvested at 2600 x g for 5 minutes . The pellet was washed with PBS without Ca or Mg and centrifuged at 1200 x g for 10 minutes . The cells were lysed by sonication in PBS containing a cocktail of protease inhibitors . The solubilized protein preparation was purified by metal chelate chromatography according the AI BioTech’s standard operating procedures . The purity of the recombinant proteins , as determined by HPLC , was 92 . 5% and the concentration was determined by BCA protein assay . For the ELISA , clear 96-well EIA ( Corning ) plates were coated overnight at 4°C with 34 . 5 ng of the purified N per well . The plates were then blocked in PBST with 3% nonfat dry milk ( BD Biosciences ) and 3% goat serum ( Corning ) for 2 h at 37°C , and washed with PBST . Twenty-eight days post-challenge , the sera were heat treated for 30 m at 56°C to inactive virus . Sera were diluted in half-log dilutions in blocking buffer , starting at 1:50 . The diluted sera were added to the wells and the plates were incubated at 37°C for 1 h . The plates were then washed with PBST , and probed for 1 h at 37°C with a 1:1000 dilution HRP-conjugated goat anti-mouse antibody ( Abcam ) , and then washed in PBST . The HRP was detected with TMB ( SeraCare Inc . ) and the plates were read at 450 nm absorbance . Weight loss significance was determined using two-way ANOVA with the Bonferroni’s post hoc correction . Survival statistics utilized the log-rank test . Statistical significance of CCHFVLP total IgG/avidity ELISA and neutralization data were assessed using one way ( Tukey’s post hoc correction ) and two way ( Sidak’s post hoc correction ) ANOVA respectively . Isotype ELISA data analysis was also performed using a two way ANOVA with Sidak’s post hoc correction . Isotype ratio analysis was performed using a Student’s t-test . Significance levels were set at a p value less than 0 . 05 . All analyses were performed using GraphPad Prism v . 6 .
In earlier studies we found that a DNA vaccine expressing the M-segment ORF of CCHFV did not consistently elicit neutralizing antibodies in vaccinated mice [24] . In studies with a DNA vaccine for Venezuelan equine encephalitis virus , we found that gene optimization could lead to a dramatic improvement in expression and immunogenicity [30] . Consequently , we generated a new construct in which the CCHFV M-segment gene was optimized to reflect the codon bias of humans and to remove known elements that impact mRNA stability and expression . Using flow cytometry , we showed that a monoclonal antibody to CCHFV GC detected viral protein both on the surface of transfected non-permeabilized COS-7 cells and within permeabilized cells ( Fig 1A ) . Expression levels were observed to be dose dependent ( S1 Fig ) ; there were 7-fold and 2 . 5-fold increases of cell surface GC and total GC , respectively , between the optimized CCHFV-M vaccine relative to the original wild-type CCHFV-M vaccine . Furthermore , we confirmed expression of both CCHFV glycoprotein genes by Western blot using a rabbit polyclonal antibody to detect GN and a mouse monoclonal antibody to detect GC ( Fig 1B ) . To compare the protective efficacy of the optimized CCHFV-M DNA vaccine in two lethal mouse models , we vaccinated groups of 10 IFNAR-/- ( C57BL/6 background ) mice or immunocompetent C57BL/6 mice three times at 3-week intervals by IM-EP with 25 μg of either the CCHFV-M vaccine or empty pWRG7077 DNA plasmid vector . Blood collection was performed prior to each vaccination to measure antibody responses . Four weeks after the third vaccination , mice were challenged by IP injection with 100 PFU of CCHFV . We previously performed a 99% lethal dose study in IFNAR-/- mice ( C57BL/6 background ) challenging IP with 10 PFU , 100 PFU , 1000 PFU , and 10 , 000 PFU ( S2 Fig ) . All challenge doses resulted in 100% lethality between 4 and 5 days and the survival curves of mice in all dosage groups higher than 10 PFU did not differ significantly . These results are similar to those reported previously [16] . We chose the IP route for challenge as IP is a surrogate for intravenous infection , and IP challenge of IFNAR-/- mice was previously found to result in a more rapid onset of disease than challenge by subcutaneous , intranasal , or intramuscular routes in both low dose and high dose challenges [16]; thus , the IP route should provide a stringent test of the vaccine’s efficacy . For the IS model , the vaccinated C57BL/6 mice were immunosuppressed by treatment with an antibody to the IFN-α/β receptor ( MAb-5A3 ) 1 day before and 1 day after challenge by the IP route as described in Methods . The dose and frequency of the MAb-5A3 was empirically determined to ensure >90% lethality . Following challenge , group weights ( Fig 2A ) were obtained daily . All of the mice in both empty vector control groups displayed dramatic weight loss and died or were euthanized between days 3 and 5 post-infection ( Fig 2A and 2B ) . Both the CCHFV-M-vaccinated IFNAR-/- and IS mice lost between 5–10% of their group weights by day 6 , but survivors returned to their starting weights by day 7 ( Fig 2B ) and had no visible signs of illness ( lethargy , ruffling ) . The CCHFV-M mice that succumbed to the virus had similar clinical signs as the control animals . Three mice in the CCHFV-M DNA vaccinated IFNAR-/- group died during manipulations three weeks following the final vaccination and prior to challenge . Two out of seven ( 29% ) CCHFV-M DNA-vaccinated IFNAR-/- mice died between days 4 and 5 post-infection , and four out of 10 ( 40% ) CCHFV-M vaccinated C57BL/6 mice died or were euthanized on day 5 post-infection . There was no significant difference between the survival rates of CCHFV-M-vaccinated mice in the two mouse models , although there was a significant difference in both models as compared to mice that were vaccinated with empty vector ( Fig 2B ) . Total CCHFV glycoprotein-specific antibodies were measured after each vaccination by ELISA using a CCHFVLP antigen . All of the CCHFV-M-vaccinated mice developed CCHFV-specific antibody responses following three vaccinations . The kinetics of the antibody responses were the same for the immune competent C57BL/6 mice and the IFNAR-/- mice; i . e . , both mouse strains displayed detectable antibody responses after the first vaccination , large increases after the second vaccination , and a smaller increase after the third vaccination ( Fig 3A ) . Although significantly higher total antibody titers were measured for individual IFNAR-/- mice vaccinated with CCHFV-M as compared to C57BL/6 CCHFV-M vaccinated mice , there was no correlation with ELISA titer and survival after challenge for either mouse strain ( Fig 3B ) . As an indirect measure of the Th1 vs Th2 response to the CCHFV-M DNA vaccine , we performed IgG2c vs IgG1-specific ELISAs on samples collected 2 weeks after the final vaccination . Both strains of mice had higher IgG2c then IgG1 responses ( Fig 4A ) indicating a predominant Th1 response , which is consistent with previous trends seen in mice vaccinated by IM-EP or needle delivery [30] . All of the CCHFV-M vaccinated mice developed measureable IgG2c responses and there was no significant difference between titers observed in the two mouse strains . There was a significant difference in the IgG1 response between the IFNAR-/- group and the C57BL/6 group , with 42 . 8% ( 3 out of 7 ) of the IFNAR-/- mice having detectable IgG1 , and 80% ( 8 out of 10 ) of the WT C57BL/6 mice having detectable IgG1 . The ratio of IgG2c to IgG1 was significantly greater in the IFNAR-/- mice than in the WT C57BL/6 , with a ratio of 1 . 85 and 1 . 39 respectively ( p = 0 . 0422 ) , indicating that overall the immunocompetent mice may have a more balanced response than the IFNAR-/- mice . We also confirmed the ability of our CCHFV-M DNA vaccine to induce affinity maturated B cell responses by avidity ELISA ( Fig 4C ) . Estimated avidity of the CCHFV-specific antibodies in the CCHFV-M vaccinated IFNAR-/- group was significantly higher than the WT C57BL/6 group , however , this did not correlate to a higher survival in the IFNAR-/- mice . To assess the neutralizing antibody responses to the CCHFV-M DNA vaccine we used a CCHFVLP neutralization assay similar to that used in earlier studies comparing neutralizing and non-neutralizing monoclonal antibodies [31] . We found that this assay provided similar results as live virus neutralization when tested with a panel of CCHFV-specific monoclonal antibodies ( S3 Fig ) . All of the CCHFV-M DNA-vaccinated IFNAR-/- mice and 90% of the C57BL/6 mice developed neutralizing antibodies to CCHFV . Although there was no significant difference in the group titers of the two mouse strains , the IFNAR-/- mice all had consistent antibody responses as compared to one another whereas there was a wide range of responses among the C57BL/6 mice . There was no significant difference in the CCHFV-specific neutralizing response between the survivors and the non-survivors in either mouse model . For both mouse strains , the addition of complement significantly increased the neutralizing antibody titers ( Fig 5 ) . Our CCHFV-M DNA vaccine was immunogenic in both mouse models , as all of the vaccinated mice developed antibody responses to CCHFV . There was no clear correlation between the humoral response to the vaccine and survival after CCHFV challenge in either IFNAR-/- or WT C57BL/6 mice . Mice that developed a higher CCHFV-specific antibody response , a higher IgG1 response , higher neutralizing antibody titers , or higher antibody avidity did not have a corresponding increase in survival . To determine if mice that survived CCHFV challenge had been infected we measured antibodies to CCHFV N in sera collected from mice four weeks after challenge . CCHFV N was not encoded in our vaccine construct , so the presence of anti-N antibodies would suggest viral replication . All of the IFNAR-/- mice and all but one mouse of the IS C57BL/6 group had detectable antibodies to CCHFV N , indicating that the vaccine did not provide sterile immunity ( Fig 6 ) . There was no difference in the CCHFV-N antibody response between the IFNAR-/- and the IS mice , and the one IS C57BL/6 mouse that did not have detectable anti-N antibodies did not have a higher antibody response to the CCHFV-M vaccine than mice that succumbed to the infection .
We generated a DNA vaccine construct encoding the M-segment ORF of CCHFV , which was optimized for expression in mammalian cells . We compared and quantified both the humoral response and protective efficacy of our optimized DNA vaccine in two murine challenge models ( IFNAR -/- and IS ) with the same genetic background ( C57BL/6 ) . We found that the optimized CCHFV-M DNA vaccine delivered by IM-EP was highly immunogenic , with 100% of IFNAR-/- vaccinated mice and 90% of C57BL/6 mice developing CCHFV-specific immune responses , including neutralizing antibodies . The single mouse in the IS model that failed to produce neutralizing antibodies did develop GN/GC-specific antibodies , albeit at low levels . The immunocompetent C57BL/6 mice developed a more balanced IgG2c/IgG1 response than the IFNAR-/- mice , which may be due to cytokine signaling differences in the immunocompetent mice . In both mouse models , the CCHFV-specific IgG ELISA titers of vaccinated mice significantly increased between the second and third boosting vaccinations . Because we did not test additional vaccinations , we do not know if we reached the maximum response possible . As we were preparing this manuscript , another study reported DNA vaccination of IFNAR-/- mice with an A129 background using separate plasmids expressing CCHFV GN , GC , or N genes , each tethered to a ubiquitin coding sequence [23] . In general , our findings of the humoral immune response to DNA vaccination are in agreement with those in the other DNA vaccine report; however , numerous differences between the two studies make it difficult to directly compare results . For example , our vaccine expresses the complete M-segment ORF of CCHFV , whereas in the other study a mixture of plasmids was used , which included an N construct along with two constructs encoding the individual glycoprotein genes , from which the mucin-like domain and GP38 coding regions were deleted . Also , our vaccine does not express either the N gene or the ubiquitin sequence . The ubiquitin was intended to broaden the cell-mediated immune response , but it is difficult to determine if it did due to the small number of mice used and the limited sample volumes that precluded a comprehensive assessment of cell mediated immunity . In addition to differences in the DNA vaccine constructs and the differing genetic backgrounds of the IFNAR-/- mice , the studies differed in that we used a lower dose of DNA and a different delivery method ( IM-EP vs intradermal EP ) and compared the IFNAR-/- mouse model responses to antibody responses of immunocompetent mice . In our studies , we could not identify a correlate of protective immunity in either mouse model . While we were able to elicit specific anti-CCHFV antibody responses in all vaccinated mice , post-challenge seroconversion ELISA results revealed that the vaccine was not able to prevent viral replication in the majority of the CCHFV-M DNA-vaccinated mice . These results are similar to those reported previously with a MVA-GP vaccine , and in the recent CCHFV DNA vaccine study [20] . A comparative study between vaccinated and control mice to determine if vaccination reduces viral burden during the acute stage of disease will be included in future studies . In addition , it is possible that we did not achieve sufficient expression levels of the proteins to elicit full protective immunity in mice; therefore , we will examine whether a higher vaccine dose and/or improved expression will increase the immunogenicity and durability of the DNA vaccine in vivo . Also consistent with the MVA-GP and the DNA vaccine studies , we found no direct correlation between the humoral response ( s ) and survival in CCHFV-M DNA-vaccinated mice [20] suggesting that anti-CCHFV glycoprotein antibodies alone elicited by these vaccines are not sufficient for protection against viral challenge . This is in agreement with results of an earlier study demonstrating that the passive transfer of serum antibodies from MVA-GP vaccinated mice into a naïve host did not confer protection to CCHFV challenge [22] . MVA-GP vaccine studies further suggested , through adoptive transfer of T-cells and passive sera transfer studies , that both the cellular and humoral responses to the MVA-based CCHFV vaccine were necessary to provide protection , as determined by a statistically significant delay in time to death . Contrary to this , earlier passive transfer studies with monoclonal antibodies directed against CCHFV GN/GC show that individual neutralizing and non-neutralizing antibodies alone can provide 100% protection both before and after challenge in suckling mice [35] . However , monoclonal antibody studies have not been reported to confirm that this protection holds true in an adult mouse model . As we have not yet assessed cell-mediated immune responses to our DNA vaccine , we cannot eliminate the necessity for inclusion of additional immunogens , such as N , to elicit T cell responses , although the immune response elicited by the MVA-GP vaccine was fully protective , whereas MVA-N vaccine was unable to protect . We show in this study that immune competent mice can be used to evaluate CCHFV vaccines and protective efficacy can be examined by transient inhibition of IFN-I using MAb-5A3 proximal to the time of challenge . IFN-α/β signaling is critical for the generation of potent adaptive immune responses , for example by promoting antigen-presenting cell maturation , driving the T cell , and subsequent B cell , response [36 , 37] . IFN-α/β also amplifies B cell receptor sensitivity , boosting the ability of naïve B cells to produce antibodies upon antigen recognition [38] . Furthermore , IFN-α/β signaling promotes the generation of memory T and B cell pools . Although we did not observe significant differences either in antibody responses or protective immunity in the IFNAR-/- vs the IS models with our CCHFV M DNA vaccine , the ability to vaccinate immune intact mice might be advantageous for other DNA vaccine approaches or for other types of CCHFV vaccines . For example , in the same study where the mixed CCHFV DNA vaccine plasmids were tested , a transcriptionally-competent CCHF VLP ( tcVLP ) vaccine was given alone or in a prime-boost regimen with the DNA . The IFNAR-/- mice vaccinated with the tcVLP or the prime-boost were less protected than the DNA vaccine alone [23] . The authors concluded that a type I IFN responses may be required for the development of a protective immune response against the tcVLP vaccine . Therefore , the ability to study CCHFV vaccines in immune intact mice and then testing protective efficacy by disrupting IFN signaling only at the time of challenge might have important advantages over the IFNAR-/- CCHFV vaccination model , particularly when T cell responses are critical for protection [39 , 40] . In summary , here we show that a novel CCHFV M-segment DNA vaccine can elicit protective immune responses to CCHFV challenge in two lethal mouse models of CCHF . The exact mechanism of protection remains unclear , but it is evident that a DNA vaccine encoding the CCHFV M-segment ORF can generate protective immunity . It remains to be seen if this vaccine can provide cross-protective immunity to more genetically distant CCHFV strains . Overall , our results provide further insight into the protective capabilities of a CCHFV DNA vaccine and will help in the development of a more rationally tailored CCHFV vaccine . | Crimean-Congo hemorrhagic Fever Virus ( CCHFV ) is a tick-borne virus capable of causing lethal human disease against which there are currently no approved vaccines . In this study , we compared the immunogenicity and protective efficacy of a candidate DNA vaccine expressing the glycoprotein precursor gene of CCHFV in two mouse models . In addition to the recently established IFNAR-/- mouse pathogenesis model , we also tested the vaccine in a novel murine system in which the interferon ( IFN ) α/β signaling response of immunocompetent mice is transiently suppressed . We found that the DNA vaccine elicited high humoral immune responses and provided significant protection against challenge with CCHFV in both mouse models . These findings further our understanding of the requirements for a CCHFV vaccine and provide a new mouse model for the development of CCHFV countermeasures . | [
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] | 2017 | A DNA vaccine for Crimean-Congo hemorrhagic fever protects against disease and death in two lethal mouse models |
Pheromones are secreted molecules that mediate animal communications . These olfactory signals can have substantial effects on physiology and likely play important roles in organismal survival in natural habitats . Here we show that a blend of two ascaroside pheromones produced by C . elegans males primes the female reproductive system in part by improving sperm guidance toward oocytes . Worms have different physiological responses to different ratios of the same two molecules , revealing an efficient mechanism for increasing coding potential of a limited repertoire of molecular signals . The endogenous function of the male sex pheromones has an important side benefit . It substantially ameliorates the detrimental effects of prolonged heat stress on hermaphrodite reproduction because it increases the effectiveness with which surviving gametes are used following stress . Hermaphroditic species are expected to lose female-specific traits in the course of evolution . Our results suggest that some of these traits could have serendipitous utility due to their ability to counter the effects of stress . We propose that this is a general mechanism by which some mating-related functions could be retained in hermaphroditic species , despite their expected decay .
Comprehensive understanding of any organism requires bridging the knowledge of laboratory biology and natural history [1] . These two approaches to the study of life are complementary and mutually reinforcing , since one offers a powerful methodology for detailed mechanistic investigation , while the other illuminates problems relevant in native evolutionary and ecological contexts . The two aspects of natural history that are often underemphasized in laboratory studies are variation in the environment and interactions among organisms . A paradigmatic example of a mechanistic study informed by the considerations of natural history is the analysis of dauer formation in C . elegans [2] . In response to high population density , paucity of food , and other noxious stimuli , L1-stage larvae can enter a morphologically distinct quiescent state that is alternative to reproductive development and is protective against harsh environments . Dozens of genes that control dauer decision have been identified; they connect several signaling pathways and other conserved molecular processes with a flexible reaction to changing environmental conditions . Pheromones , secreted substances that potentiate behavioral or physiological responses , play prominent roles in dauer decision as they communicate information about the number and possibly the status of other worms in the population [3 , 4] . We believe that detailed analyses of the physiological and molecular mechanisms that allow worms to cope with other stresses could similarly uncover important biological phenomena . In their native habitats , C . elegans likely experience frequent and substantial temperature fluctuations [5 , 6] . We have studied the mechanisms used by worms to thrive under these conditions [7 , 8] . Here we specifically focus on the role of pheromone-mediated communication among animals exposed to prolonged heat stress .
C . elegans hermaphrodites can recover reproductive ability following even a prolonged exposure to temperatures at which egg laying stops and none of the offspring survive [8] . Importantly , because C . elegans hermaphrodites are self-fertile , recovery of a single individual could be sufficient to re-establish a population . To explore this process further and to avoid the potentially confounding effects of population density [9–11] we tested the ability of singled hermaphrodites to recover ( Fig 1A ) . Only a small fraction of individuals recovered when kept alone ( Fig 1B ) . In contrast , when one hermaphrodite and one male experienced stress together , the probability of recovery increased more than two-fold . We have previously demonstrated that because the primary cause of fecundity loss post heat stress is sperm death , hermaphrodites recovered much better after mating with unstressed males [8] . In the experiments reported here , matings did indeed occur when males and hermaphrodites were stressed together or when unstressed males were added ( S1 Fig ) . Yet , broods of many of the recovered hermaphrodites lacked males , which are expected if male-supplied sperm yielded extra progeny . This suggested to us that in addition to male sperm , other causes contributed to the better reproductive recovery of hermaphrodites in the presence of males . Importantly , the physical presence of a male was not required to increase the probability of recovery–scent left on a plate was sufficient , that is , hermaphrodites recovered approximately twice as frequently when they experienced stress and recovery on male-scented plates . Hermaphrodite scent may also improve recovery , but only marginally ( Fig 1B ) . These results suggest that a secreted substance produced primarily by adult ( S2 Fig ) males conveys a signal that improves reproductive recovery from prolonged heat stress . We tested whether exposure to male scent only during stress or recovery had the same effect as continuous incubation on scented plates . Intermediate recovery levels under each of these treatments suggested that their effects were somewhat cumulative ( S3 Fig ) Ascaroside pheromones [3 , 4 , 12 , 13] are likely candidates to mediate this scent-improved recovery . No pheromones produced exclusively by individuals of either sex have been reported in C . elegans so far . However , two ascarosides , ascr#3 ( asc-ΔC9 ) and ascr#10 , are produced in different ratios by the two sexes– 4:15 in males and 7:2 in hermaphrodites , respectively [14 , 15] . Thus , sex-specific pheromone cocktails , rather than particular molecules , likely constitute the male and hermaphrodite scents in C . elegans . Genetic evidence suggests that sex-specific ascaroside signals are involved in reproductive recovery from heat stress . Loss-of-function of daf-22 , a gene encoding a β-ketoacyl-CoA thiolase [16] , abrogates excretion of shorter chain ascarosides , such as ascr#3 and ascr#10 [14 , 15 , 17] . The scent of daf-22 ( m130 ) mutant males was unable to improve recovery as much as the scent of wild type males ( Fig 1B ) . In contrast , loss of an acyl-CoA oxidase ACOX-1 inverts the ratio of ascr#10 to ascr#3 production in hermaphrodites to make ascr#10 even more prevalent than in males [14 , 15 , 18] . As expected , the scent of acox-1 ( ok2257 ) hermaphrodites was as potent as that of the wild type males in improving recovery ( Fig 1B ) . Because male scent improved recovery and ascr#10 is predominantly found in males , we expected that exposure of hermaphrodites to this molecule would increase the probability of fecundity recovery following heat stress . Surprisingly , hermaphrodites on plates scented with purified ascr#10 recovered no better than on control plates ( Fig 2 ) . In contrast , ascr#3 , the hermaphrodite-enriched pheromone , improved recovery significantly better , to a level comparable to that induced by the complete hermaphrodite scent . Because both males and hermaphrodites produce ascr#3 and ascr#10 , albeit in different quantities , we conducted recovery experiments using cocktails of these molecules . These were concocted to have ascaroside concentrations that matched those produced by a single live animal ( male or hermaphrodite ) in 24 hours , as reported by Izrayelit et al . [14] , because in our experiments single live animals were used to scent plates for 24 hours . Remarkably , simple mixtures of two ascarosides recapitulated the salutary activity of the complete male and hermaphrodite scents , respectively ( Figs 1B and 2 ) . The significant difference between the effects of “male” and “hermaphrodite” cocktails suggests that worms can discriminate ratios of ascr#3 and ascr#10 . Reinforcing this conclusion , we found that an equal mixture of these two ascarosides , an intermediate between the “male” and “hermaphrodite” cocktails , was no more potent than the “hermaphrodite” cocktail ( S4 Fig ) . The male scent must be quite strong since a single male can produce enough of it in as little as 16 hours ( S5 Fig ) . Although the amounts of ascarosides produced by individual animals were reported previously [14] , we examined the effects of a range of concentrations of these molecules on reproductive recovery . ascr#10 had no detectable effect on recovery even at concentrations ~100 times higher than physiological ( S6 Fig ) . In contrast , activity of ascr#3 was dependent on the concentration ( S6 Fig ) . At 2 fmol , the amount produced by a single male in 24 hours [14] , it had no discernable effect in our assay , whereas the effect of 10 fmol of ascr#3 ( with no ascr#10 added ) was indistinguishable from that of the hermaphrodite cocktail . Remarkably , when 2 fmol of ascr#3 was mixed with 7 . 2 fmol of ascr#10 , which alone did not improve recovery ( Fig 2 ) , this cocktail was as potent as the complete male scent ( Fig 2 ) . Why do C . elegans males produce a signal that promotes self-reproduction ( evident as improved recovery from heat stress ) , which presents a direct competition to their own reproductive success ? Why does the efficient recovery of hermaphrodite reproduction from stress rely on a signal produced by males , which comprise only ~0 . 1–0 . 5% of C . elegans populations in the wild [6 , 19] , likely making encounters between the sexes infrequent ? We hypothesized that these apparent paradoxes may have an explanation in the evolutionary origin of the C . elegans mode of reproduction . The few extant hermaphroditic species in the genus Caenorhabditis arose from gonochoristic ( male-female ) ancestors relatively recently [5] . It is reasonable to assume that in a species in which mating is essential for reproduction , a male-produced signal that alerts the female reproductive system and increases mating efficiency would be advantageous . Recently arisen hermaphroditic species , such as C . elegans , may have retained elements of this mechanism . We therefore tested whether the male-produced pheromone signal is species-specific . Consistent with the previous finding that ascaroside signaling is broadly conserved in nematodes [20] , we found that the scent of males of three species from the genus Caenorhabditis ( two gonochoristic and one hermaphroditic ) could rescue the reproductive performance of heat-stressed selfing C . elegans hermaphrodites as well as the scent of the conspecific males ( Fig 3 ) . We concluded that despite changes in the reproductive mode , C . elegans retained the male-specific pheromone signaling system that arose in its gonochoristic ancestor–males still produce the pheromone , while hermaphrodites can respond to it . We thought that a likely ancestral function of male pheromones was to facilitate reproduction following mating . For this reason , we compared brood sizes produced by females of a gonochoristic species C . remanei that were either exposed to male scent or maintained on control plates . Reports of the time for sperm transfer during mating in C . elegans vary from 4 seconds [21] to 90 seconds [22] with the majority of sperm transferred at the beginning of ejaculation . In addition to measuring the time of sperm transfer during mating ( about 17 seconds ) , Lebouef et al . [23] studied the refractory period in C . elegans males . They found that males fell into two classes–those with a relatively short refractory period between matings ( less than 9 minutes ) and those with a longer refractory period between matings ( greater than 9 minutes ) . Males that exhibited a short refractory time were unlikely to produce many progeny from a second mating because they could not produce fresh sperm during the shorter refractory period . We considered these facts and decided that a ten-minute mating period made it most likely that only one successful mating could take place . Incidentally , this period is approximately 1% of the time that is required for male scent to have an effect on the probability of hermaphrodite’s recovery ( S5 Fig ) . At the end of the ten minutes , if the mating pair was still together , the female was gently touched with a platinum wire . If the mating pair did not separate–indicating that mating was ongoing , that female was excluded from the data . As expected , we found that brood sizes of C . remanei females that had been exposed to male scent prior to mating were significantly greater than the brood sizes of mated naïve females ( Fig 3B ) . This result strongly argues that the function of the male-specific pheromones in the gonochoristic ancestors of C . elegans was to alert the female reproductive system and induce appropriate physiological changes that resulted in substantially increased reproductive efficiency upon mating . We tested whether the male scent affects brood sizes of C . elegans hermaphrodites reproducing via self-fertilization at non-stressful conditions ( 20°C ) , but found no detectable differences between control and male-scented plates ( Fig 4A ) . Next we wondered whether the two-fold more likely recovery from heat stress in the presence of male scent ( Fig 1B ) was accompanied by an increase in brood sizes . It was not–brood sizes of C . elegans recovering via selfing on male-scented plates were not significantly different from those of animals recovering on control plates ( Fig 4B and S7 Fig ) . We considered several possible physiological mechanisms by which pheromone signaling could have improved reproductive recovery following heat stress . Because hermaphrodites were exposed to the 29°C stress after gamete production irreversibly shifted from spermatogenesis to oogenesis , improved recovery in the presence of male scent could in principle be due to a ) improved sperm survival/retention of function , b ) better preservation of the “female” aspects of the reproductive system including oocytes or gonads , or c ) higher post-zygotic survival . Although the catastrophic reduction of brood sizes in hermaphrodites recovering alone from heat stress is primarily due to sperm loss [8 , 24 , 25] , the similar brood sizes of worms recovering on scented and control plates suggested that the increase in the probability of recovery induced by the male scent was due to a more efficient gamete utilization , not their improved survival or post-zygotic mechanisms . In addition to the catastrophic sperm loss , other elements of the reproductive system also suffered considerable damage during stress . For example , large concretions consisting of oocytes and embryos formed in the uterus [8] . Recovery required purging of these obstacles to allow live fertilized oocytes to pass . This and possibly recovery of the gonad itself required time . Both self recovery and recovery following mating with unstressed males did not yield live L1-stage progeny until ~72 hours post-stress , suggesting that first productive fertilizations occurred ~48–60 hours after the return from 29°C to 20°C ( S8 Fig ) . We have previously shown that C . elegans hermaphrodites are able to suppress ovulation when the temperature reaches 31°C and that this improves recovery when the worms are shifted to a more permissive temperature [8] . Therefore , we tested whether male scent suppressed ovulation at 29°C . The numbers of oocytes in the gonad and embryos in the uterus were likewise not appreciably different between these treatments ( S9 Fig ) . We concluded that other mechanisms were likely responsible for the improved recovery . One phenomenon related to gamete utilization that is modulated by ascarosides has been recently described in C . elegans [26–28] . Oocytes were shown to secrete a prostaglandin signal that improves sperm targeting to the spermatheca , an organ where fertilization occurs ( Fig 5A and 5B ) . We therefore tested whether sperm guidance was improved on male-scented plates . Using a strain in which sperm were marked with an mCherry reporter gene [29] ( recovery of this strain does not appear to be different from that of N2; S10 Fig ) , we measured the distribution of this fluorescent label in the reproductive tracts of hermaphrodites following heat stress . In worms recovering on control plates most sperm were trapped in the uterus ( Fig 5C ) , likely because continued ovulation under these conditions ( [8] and S9 Fig ) displaced sperm from the proximal gonad ( all spermatids remained in the gonad in the absence of ovulation at 31°C; see S11 Fig ) . In contrast , we saw evidence of significantly higher localization of sperm in the spermatheca and the proximal gonad in worms recovering on male-scented plates ( Fig 5E and 5G ) . In unstressed animals male scent did not appear to have a detectable effect on sperm guidance ( Fig 5D , 5F and 5H ) . We inferred that under these conditions , guidance of self sperm toward oocytes is sufficiently high and cannot be substantially improved by the pheromone signal . To confirm that the improved sperm guidance caused by the male scent was mediated by ascarosides , we tested sperm guidance on plates containing ascr#10 , ascr#3 , and their mixtures . Sperm guidance was significantly improved on male- but not hermaphrodite-specific cocktail , an effect that appears to be mediated by ascr#10 alone ( Fig 6A ) . Because ascr#3 did not have any discernable effect on sperm guidance and yet somewhat improved recovery ( Fig 2 ) , we wondered about its possible mode of action that was distinct from ascr#10 . To explore whether it had an effect on the female aspects of the reproductive system , we examined the rates of ovulation and egg-laying , but did not observe any difference between control animals and those on plates containing either ascaroside . We did , however , find that in the presence of ascr#3 many fewer animals had large concretions in the uterus during recovery than did animals on ascr#10 ( Fig 6B ) . Clearing of the reproductive tract is important for the passage of fertilized oocytes , suggesting that ascr#3 contributes to an improved recovery of fecundity via a mechanism distinct from that of ascr#10 . The DAF-7 ( a TGF-β-like ligand ) function in ASI neurons mediates multiple aspects of C . elegans response to the environment , including pheromones [30 , 31] . In particular , it plays an important role in connecting sperm guidance to environmental conditions [27 , 28] . daf-7 loss-of-function or high concentrations of dauer pheromones ascr#2 and ascr#3 disrupt sperm guidance [28] . We therefore explored the role of DAF-7 signaling on reproductive recovery from heat stress . As expected , we found that daf-7 ( e1372 ) mutants recovered no better in the presence of male scent than they did on control plates at the frequency comparable to that of N2 on control plates ( Fig 7 ) . When the daf-7 mutation was rescued by constitutively expressing DAF-7 in ASI neurons , recovery was significantly improved , although it still was insensitive to male scent . We interpret these results to mean that DAF-7 signaling is both necessary and sufficient for improved recovery and , in particular , DAF-7 inducibility is required for the response to male scent . A peculiar feature of the set up of this experiment offered us an additional insight into the complex nature of environmental influences on the reproductive system . The daf-7 ( e1372 ) allele is temperature-sensitive and worms have to be reared at the permissive temperature of 16°C past the L2-larval stage to avoid the constitutive dauer phenotype [30] . We suspected that this treatment–16°C until late L2 and 20°C until young adulthood–improved the probability of recovery from the 29°C stress ( compare daf-7 ( e1372 ) in Fig 7 and N2 on control plates in Fig 1B ) . We confirmed that the temperature treatment and not the genotype of the animals was responsible for the observed differences . The N2 worms reared under this regime recovered better than the animals grown constantly at 20°C , whereas daf-7 ( e1372 ) ; gpa-4p::daf-7 grown at 20°C recovered less well than when grown at 16°C until late L2 and at 20°C thereafter ( S12 Fig ) . Cooler temperatures during the first two larval stages evidently make some aspect ( s ) of the reproductive system more apt to recover from heat stress .
Our results support six conclusions . First , secreted compounds produced primarily by males improve female reproductive performance in a variety of species [32–34] . We showed that this is the case in Caenorhabditis nematodes–male scent potently affected different aspects of female/hermaphrodite reproductive physiology . In a gonochoristic species C . remanei this resulted in larger brood sizes . In a hermaphroditic C . elegans it conferred salubrious effects after heat stress . Whereas animals of both sexes produce pheromone cocktails containing multiple distinct molecules [13 , 14] , we showed that ascr#3 and ascr#10 promote efficient uterine clearing and improve sperm guidance , respectively . Second , the study of McKnight et al . [28] , which demonstrated the effects of environmental cues on sperm guidance , reported that “pheromones” inhibited proper targeting . Here we report an ostensibly opposite result of “pheromones” promoting sperm guidance . We think that two factors could readily explain this apparent contradiction . The pheromones used by McKnight et al . [28] were ascr#2 and ascr#3 ( also known as asc-C6-MK and asc–ΔC9 , respectively ) , two main components of the “dauer pheromone” [4 , 12] . In contrast , we tested ascr#10 and ascr#3 . The amounts of applied pheromones were also different . Whereas we tested concentrations as low as ~2–10 fmol , roughly corresponding to daily production of single animals [14] , McKnight et al . [28] reported results using 10 μmol . Taken together , these results suggest a model in which low , male-specific concentrations of ascarosides manipulate the hermaphrodite reproductive system in a way that potentiates improved sperm guidance , whereas high concentrations of hermaphrodite pheromones ( reflecting overcrowding ) disrupt sperm guidance . Third , the importance of relative concentrations of ascarosides is highlighted by the curious mode of action of ascr#3 and ascr#10 . In previously described synergistic interactions between ascarosides , each molecule had some effect , while the combined effect was greater [12 , 35 , 36] . The male-enriched ascr#10 alone has no discernable effect on the reproductive recovery from stress , whereas the hermaphrodite-enriched ascr#3 has a modest effect . This is all the more remarkable considering that the two molecules are nearly identical , the only difference between them being one double bond [14] . The synergy between these two molecules depends on their relative concentrations–a “male-like” ratio of ~15:4 ( ascr#10:ascr#3 ) greatly potentiates recovery , whereas a “hermaphrodite-like” ratio of ~2:7 ( ascr#10:ascr#3 ) is indistinguishable from the effects of ascr#3 alone . This implies that worms could discriminate not only the presence of specific pheromone molecules , but their ratios as well . This synergy appears to be mediated by the complementary action of two distinct mechanisms–clearing of the reproductive tract ( by ascr#3 ) and sperm guidance ( by ascr#10 ) . The phenotypic effects of other pheromone mixtures may be similarly complex . The relationships between concentration and activity may also be different for different functions mediated by ascr#3 and ascr#10 [4 , 10 , 20] . Still , for example , ascr#10 was active at concentration ~10 fmol in both mate holding [14] and increasing sperm guidance ( Fig 6A ) . Our findings expand the universe of functions previously ascribed to ascr#3 –in dauer formation [4] , in attracting males and repelling hermaphrodites [12] and ascr#10 –in attracting hermaphrodites and holding them in place [14] . Fourth , the results of McKnight et al . [28] and our data ( Fig 7 ) suggest that the DAF-7 TGF-β-like ligand in ASI neurons plays a critical role in conveying the signal to the reproductive system of , respectively , the dauer ascarosides ( ascr#2 and ascr#3 ) and male-specific cocktail of ascr#10 and ascr#3 . Previous studies documented DAF-7 functions in mediating response to dauer pheromone [30 , 31] and male sexual attraction to hermaphrodite pheromones [37] . Together these studies implicate DAF-7 in ASI neurons in mediating multiple aspects of pheromone-influenced behaviors . Fifth , C . elegans researchers are well familiar with the fact that cultivation conditions could have profound effects on animal physiology . Dauer formation in response to high density or paucity of food [2] and more subtle consequences of being raised in isolation [9] are prime examples of this . Our finding that male pheromones , even at femtomole concentrations , can have substantial effects on hermaphrodite reproduction raises a note of practical caution–the presence of males could change multiple aspects of hermaphrodite behavior and should thus be considered in experimental design . Finally , our results suggest a simple scenario for the evolution of this pheromone signaling system . Its original function in the ancestral gonochoristic species was to communicate the proximity of males to females , which facilitated reproductive success following mating ( Fig 3 ) . Transition to a self-fertile hermaphroditic mode of reproduction is expected to have changed selection pressures on sex-specific traits [38] . In particular , hermaphrodites do not need to locate mates for reproduction . Whereas Caenorhabditis hermaphrodites lost several “female” functions [39–41] , why did they retain the ability to respond to male-specific pheromones , which do not increase brood sizes produced by selfing , a predominant mode of reproduction in the wild [6 , 19] ? Temperature fluctuations likely routinely expose C . elegans to chronic heat stress in its natural habitats [6] . This results in drastically reduced brood sizes , but also increased incidence of males among the recovered offspring [42–44] . Hermaphrodites that retained the ability to respond to male pheromones would therefore gain a substantial advantage because of a greatly increased probability of reproductive recovery . Other female-specific functions in recently evolved hermaphroditic species could also have been preserved by co-option due to their serendipitous ability to counteract the effects of stress .
N2 C . elegans WT , DR476 daf-22 ( m130 ) II , VC1785 acox-1 ( ok2257 ) I , EG4883 oxIs318[pCFJ167 ( Pspe-11::mCherry::histone–Cbr-unc-119 ( + ) ) ] II unc-119 ( ed3 ) II , CB1372 daf-7 ( e1372 ) III , DA2202 daf-7 ( e1372 ) III; adEx2202[gpa-4::daf-7 + rol-6p::GFP] , AF16 C . briggsae WT , EM464 C . remanei WT , PB2801 C . brenneri WT . All strains were maintained at 20°C under standard conditions [45] , except daf-7 ( e1372 ) and DA2202 , which were maintained at both 16°C and 20°C for different experiments . Synchronized cultures of L1 larvae were prepared by hypochlorite treatment of gravid hermaphrodites [46] . The liberated eggs were allowed to hatch in M9 Buffer overnight and the arrested L1 larvae were plated the next morning . The time that L1 worms were deposited on plates was noted as “0 hours post L1 arrest” . Between 30 and 50 L1 larvae were transferred to each lawn plate of E . coli OP50 and hermaphrodites were kept on these small population plates until just before young adulthood ( generally , 48 hours post L1 arrest at 20°C ) . In a typical experiment , to assess one condition , 25 or 50 hermaphrodites were singled onto plates just after the L4/adult molt ( around 46 hours post L1 arrest ) for each condition being assayed . Experiments contained multiple conditions ( including the control ) that were tested at the same time for a total of 100 to 125 plates–each containing a single hermaphrodite . These plates were banded together in stacks of five , placed in shoeboxes , and shifted at 48 hours post L1 arrest to 29°C for 24 hours . When the experiment called for male and hermaphrodite worms to be stressed together , age-matched pairs of males and hermaphrodites were used . After 24 hours of heat stress , the worms were returned to 20°C and allowed to recover . The numbers of eggs , both fertilized and unfertilized , and larvae produced by each worm were recorded daily . Worms were deemed to have recovered fecundity if they produced live progeny in the first 120 hours of recovery . See S1 Table for raw experimental data including numbers of independent trials and worms tested in each trial . C . remanei and C . brenneri produce large numbers of males . In other strains , males were generated by subjecting mid-L4 hermaphrodites to heat stress at 31°C for 3 hours and subsequently maintained by mating . To scent plates , males were segregated from hermaphrodites as L4 larvae and singled as one-day-old virgin adults . Unless otherwise noted , males were left on plates for 24 hours to deposit a scent and subsequently removed . Wild type and acox-1 hermaphrodites aged 24 hours post L1 arrest were used to condition plates until 52 hours post L1 arrest . This time span corresponds to the developmental stages from mid L3 larvae to young adult [47] . Purified ascr#3 and ascr#10 were a generous gift from Frank C . Schroeder ( Cornell University ) . For recovery of fecundity experiments , ascarosides were diluted in 10% ethanol and applied to Noble agar ( US Biological ) NGM plates in a total volume of 100 uL . The concentrations listed represent the total amount of ascaroside applied to each plate . A 10% solution of ethanol alone was used as the control . The diluted ascarosides were spread on the plate with a glass rod and allowed to absorb into the agar overnight at 20°C . The next day , these plates were seeded with a 1:100 dilution of an overnight culture of OP50 bacteria and incubated at 20°C . The plates were used the following morning in heat stress and recovery experiments as described above . CB1372 and DA2202 strains were treated in the same manner . A one-hour egg lay was used to produce synchronous populations that were maintained at 16°C for 54 hours–until the worms were in the mid L3 larval stage . They were next transferred to 20°C for 16 hours until the young adult stage equivalent to that of N2 worms ( raised at 20°C ) at 48 hours post L1 arrest . This was confirmed by counting oocytes in the gonad [8] . Supplemental experiments used only DA2202 raised until young adulthood at 20°C ( S12 Fig ) . For experiments using total male scent , a synchronized population of EG4883 hermaphrodites [29] was raised on small population plates at 20°C until they were 48 hours post L1 arrest . Worms were transferred to either control plates or plates conditioned with four young males . For heat stress experiments , small population plates were shifted to 29°C for 24 hours . For sperm guidance experiments with single ascarosides and cocktails of two ascarosides , the ascarosides were diluted in water and hermaphrodites were singled onto prepared plates in the same manner as heat stress and recovery experiments . These were single-blind experiments . In all sperm guidance experiments , worms were immobilized with sodium azide and mounted on 2% agarose pads . Images were taken with a Retiga 2000R camera mounted on a Leica DM5000B compound microscope and analyzed using ImageJ software . Individual images were stitched together using the MosaicJ plug-in [48] . Analyze Particles was used to count fluorescent sperm . An automatic thresholding program ( MaxEntropy ) [49] was used to determine image thresholds . L4 C . remanei males were isolated from a mixed population and allowed to develop at 20°C overnight , after which they were used to condition half of the prepared mating plates ( NGM plates with 5uL of a 1:100 dilution of an overnight culture of OP50 kept at 20°C overnight ) for 24 hours . From a synchronous population ( ~40 hours post L1 arrest ) , females were moved to separate plates in groups of 20–30 . At 48 hours post L1 arrest , they were singled onto either control or male-conditioned plates . Matings started 16 hours later , to ensure that both males and females were receptive . A single male was placed on top of an age-matched female in the shape of an X . Matings were short ( 10 minutes ) to make multiple matings unlikely [23] and to ensure that males did not have a chance to deposit much scent on plates ( S5 Fig ) . After 10 minutes , males were removed and the females were examined for the presence of a copulatory plug [50 , 51] . All females , whether or not a copulatory plug was detected , were kept at 20°C and transferred to fresh , seeded NGM plates daily; fertilized eggs and larvae were counted . | The Caenorhabditis elegans metabolome contains over a hundred ascaroside molecules . Most of them have no known function , or no function at all , but some act as pheromones . Two of these molecules , ascr#10 and ascr#3 , are produced in different proportions by males and hermaphrodites . We report that when a hermaphrodite senses a male-specific mixture of these molecules , it changes several aspects of its reproductive physiology , including signaling that guides sperm toward oocytes . During evolution from an ancestor that had both males and females , C . elegans hermaphrodites lost several female-specific traits , but their reproductive system retained the ability to respond to male pheromones . This greatly aids them during recovery from heat stress . We suggest that serendipitous side benefits of female-specific traits could be a general cause of their retention during evolution . | [
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] | [] | 2015 | Sex Pheromones of C. elegans Males Prime the Female Reproductive System and Ameliorate the Effects of Heat Stress |
The prevention and control of dengue rely mainly on vector control methods , including indoor residual spraying ( IRS ) and indoor space spraying ( ISS ) . This study aimed to systematically review the available evidence on community effectiveness of indoor spraying . A systematic review was conducted using seven databases ( PubMed , EMBASE , LILACS , Web of Science , WHOLIS , Cochrane , and Google Scholar ) and a manual search of the reference lists of the identified studies . Data from included studies were extracted , analysed and reported . The review generated seven studies only , three IRS and four ISS ( two/three controlled studies respectively ) . Two IRS studies measuring human transmission showed a decline . One IRS and all four ISS studies measuring adult mosquitoes showed a very good effect , up to 100% , but not sustained . Two IRS studies and one ISS measuring immature mosquitoes , showed mixed results . It is evident that IRS and also ISS are effective adulticidal interventions against Aedes mosquitoes . However , evidence to suggest effectiveness of IRS as a larvicidal intervention and to reduce human dengue cases is limited–and even more so for ISS . Overall , there is a paucity of studies available on these two interventions that may be promising for dengue vector control , particularly for IRS with its residual effect .
Dengue is the most prevalent arthropod-borne viral disease , infecting 300 to 500 million individuals each year . Approximately 100 million infections are symptomatic , which can range from mild to severe disease [1 , 2 , 3] . An estimated 500 000 people suffer from the severe forms , nearly 90% of whom are children , with a resulting 22 000 dengue-related deaths annually [4] . Global climate change , urbanisation , travel , poor sanitation , and inadequate public health services , all have the potential to increase the intensity of dengue transmission [5 , 6] . The four serotypes of the dengue virus ( DENV 1–4 ) are transmitted principally by female Aedes aegypti and to a lesser extent by Aedes albopictus mosquitos [7] . Aedes species are anthropophilic , feed in the dark , the early morning and twilight hours and show an indoor-resting behaviour preferentially in secluded stationary locations e . g . under furniture , lower walls , under sinks , in curtain folds , or in wardrobes [2 , 8 , 9] . Dzul-Manzanilla [10] determined that Aedes aegypti rested mostly below 1 . 5 meters of height , and mostly in bedrooms ( 44% ) , living rooms ( 25% ) and bathrooms ( 20% ) . At present , there is no effective vaccine available , for public health use , to prevent or treat dengue infections , efficacy of the existing vaccine is variable and not high [11 , 12] . Therefore , vector control is the primary method of dengue prevention and control . Since the turn of the 19th century , chemical insecticides applied to the environment in a variety of methods have served as one of the mainstays of dengue vector control programmes , basically outdoors against immature and indoors-outdoors against adult vectors . Indoor application of insecticides ( IAI ) includes indoor space spraying ( ISS ) or indoor residual spraying ( IRS ) . Both target the endophilic adult Aedes mosquitoes that bite and rest indoors [10 , 13] . IRS entails the coating of walls and surfaces of the entire house with a residual insecticide [14] . ISS is done to treat indoor spaces to control flying insects with less residual effect . IRS can potentially target Aedes aegypti as it was used for the first time in Malaysia in 1952 [15] . IRS , however , is not generally recommended for dengue vector control , as it is thought that adult Aedes aegypti often rest on non-sprayable surfaces in houses [16] . Despite this , reductions in Aedes aegypti populations have been observed in areas where IRS is utilised for malaria control . A recent meta-analysis [17] concluded that there is a need of more empirical evidence supporting the potential utility of IRS for dengue prevention , since it was based on only two studies . For a meta-analysis comparability of studies precludes inclusion of many articles , thus providing a justification with an update and further inclusion and analysis of studies using IRS/ISS with a further systematic review . This study systematically reviews the available evidence on community effectiveness of IRS and ISS for reducing Aedes populations and thereby for controlling dengue transmission .
This review follows the guidelines set forth in the PRISMA criteria for the reporting of systematic reviews and meta-analyses [18] . The literature search was conducted in parallel by two data extractors until 15 . 02 . 2017 , with an update until 28 . 02 . 17 . A wide range of search terms was used in combinations to identify all relevant studies . The search terms included ( a ) disease specific terms: Dengue , Dengue hemorrhagic fever , Dengue haemorrhagic fever , Dengue shock syndrome , DHF , and DF , ( b ) vector specific terms: Aedes , Aedes aegypti , Aedes albopictus , Ae . aeygpti , and Ae . albopictus , and ( c ) intervention specific terms: Indoor space spray , ISS , Indoor residual spray , IRS , Residual house spray , and Intra domiciliary residual spray . For the purposes of this review , IRS was defined as the application of chemical insecticides on walls and other surfaces with the aim to control Aedes mosquitoes inside houses , using substances which remain effective for 1 month or more . ISS was defined as any indoor spray using ultra-low volume spray ( ULV ) , low-volume spray ( LV ) , thermal fogging and other devices such as insecticide fumigant canisters . This review is limited to public health application of IRS/ISS , not commercial ( household ) use . Community effectiveness studies were defined as those studies conducted to evaluate the impact of IRS/ISS under normal field conditions , while efficacy studies were defined as those studies conducted under laboratory conditions . The above search strategy was applied to the following databases: PubMed , EMBASE , LILACS , Web of Science , WHO library database ( WHOLIS ) , Cochrane , and Google Scholar . Eligible studies met the following inclusion criteria: 1 ) peer-reviewed publications presenting original data evaluating the community effectiveness of IRS/ISS 2 ) studies with control group ( s ) during intervention , studies with pre- and post-intervention assessments , and cross-sectional studies , 3 ) no language restrictions were applied , and 4 ) the target was vector and human populations . The exclusion criteria were limited to the following: 1 ) abstracts , conference posters , short communications , and letters to the editor , 2 ) studies with not enough information on community effectiveness of IRS/ISS , 3 ) efficacy studies and 4 ) surveillance data or reviews . All identified studies were screened by title and abstract . Relevant studies were sent to EndNote X7 reference manager software . The numbers of relevant , irrelevant , and duplicated articles were identified and recorded for each database . Full texts of selected studies were retrieved either through online databases or through Heidelberg University libraries . All reference lists of retrieved studies were screened for additional relevant studies . The full eligibility criteria were applied to all retrieved articles to identify the final list of included studies . The systematic literature search and the review followed the assessment of multiple system reviews , AMSTAR , for assuring the methodological quality [19] . By using a pre-designed extraction sheet , the following data were extracted from each included study: author name , year of publication , source database , study title , geographical location , objective ( s ) of the study , study design , relevant outcomes , main results , and key conclusions of the authors ( Table 1 ) . To assess for quality , included studies were categorised into studies with and without a control arm . They were further classified by study design and number of interventions . Outcome measures were extracted , classified and summarised across studies . Different measures were used to record the frequency of observations and the way of presentation varied according to the type of the presented data . Different insecticides and methods of application , together with varying statistical methods and outcome measures across the studies precluded any attempt at meta-analysis . Articles included through an update of the initial searches , until 28 . 02 . 17 , are presented in the discussion section .
A comprehensive literature search of the seven databases identified 825 potentially relevant citations . After screening for title and abstract , 144 duplicates and 649 irrelevant articles were excluded . The reference lists of the 32 remaining articles added seven more studies . The 39 studies were retrieved for full text assessment . Upon meeting eligibility criteria , seven studies were included and 32 studies were excluded , most of the latter were efficacy studies only ( Fig 1 ) . Summaries of included studies were arranged chronologically in an evidence table ( Table 1 ) . Seven studies met the pre-specified eligibility criteria ( 1 ) Three IRS studies: Parades-Esquivel 2015 [20] , Vazquez-Prokopec 2010/1 [21] , Lien 1994 [22]; 2 ) Four ISS studies: Mani 2005 [23] , Perich 2003 [24] , Perich 2001 [25] and Koenraadt 2007 26] ) . Most dengue risk areas were represented except Africa , with three studies from Asia [22 , 23 , 26] , one study from Australia [21] and three from Latin America and the Caribbean [20 , 24 , 25] . All articles were reported in English . The time period of publication ranged from 1994 to 2015 . The seven studies were broadly classified into five controlled studies , two for IRS and three for ISS , and two non-controlled studies ( one each IRS/ISS ) ( Table 1 ) . Controlled studies were subsequently classified into four intervention control studies all testing IRS [20] and ISS [23 , 24 , 25]with multiple study arms . One cross-sectional time series compared data from sprayed and non-sprayed areas [21] . For the two non-controlled studies [22 , 26] , Lien [22] had one study arm only , Koenraadt [26] had multiple study arms . Reporting on sample size varied across included studies either for the diversity of methods or for the unavailability of data in some studies . For controlled studies , the smallest sample size for intervention was 36 houses [20] and the biggest three residential colonies with 216–260 houses each . The non-controlled studies covered 36977 houses [22] and four houses in two areas [26] . All included studies reported on geographical locations . Parades-Esquivel [20] , Vazquez-Prokopec [21] , Mani [23] reported on meteorological conditions . All studies reported on the season/time period of the study , in relation to dry and rainy seasons . All studies discussed factors that might influence dengue transmission , and mosquito abundance , such as ecology and housing structures . The latter is described in detail by Parades-Esquivel [20] , Vazquez-Prokopec [21] and Perich [24 , 25] . Parades-Esquivel [20] and Mani [23] present target populations and their socio-economic background . Pre-intervention dengue estimates were reported by Vazquez-Prokopec [21] and Lien [22] . Vazquez-Prokopec [21] reported on previous dengue outbreaks . Method ( s ) of intervention: All studies used IRS as a single intervention . Although Vazquez-Prokopec [21] compared data from areas sprayed and not sprayed with IRS , in addition to the ongoing local control programme , including control of breeding places . Mani [23] compared ISS and peridomestic spraying , Perich [24] compared ISS with ULV , LV and thermal fogging and Perich [25] compared ISS with ULV and thermal fogging . Koenraadt [26] compared ISS and peridomestic spraying , with different insecticide concentrations . Forms of application and formulations: Forms of application varied considerably , but including either ultra-low volume spray ( ULV ) , thermal fog spray , or low-volume spray ( LV ) . Formulations varied as well , including deltamethrin [20] , lambda-cyhalothrin [21 , 24 , 25] , alphacypermethrin [22] , pyrethrin [26] and deltacide , a mixture of Deltamethrin 0 . 5% , S-Bioallethrin 0 . 75% and Piperonyl Butoxide 10% [23] . Duration of residual effect: Paredes-Esquivel [20] estimates a good residual effect of IRS up to 16 weeks , for ISS Perich [24 , 25] demonstrated three weeks and four weeks’ residual effect , respectively . Mani [23] and Koenraadt [26] showed a residual effect of one week . Five of seven studies incorporated a control group into the study . They were assigned in different ways according to the methods used in each study . 1 ) IRS studies: Parades-Esquivel [20] used three single houses with similar structures to the 3 clusters of intervention houses ( 12 each ) . Vazquez-Prokopec [21] compared 97 sprayed houses to 151 non-sprayed houses , as the data were retrospectively available . 2 ) For ISS studies: Mani [23] used one cluster of houses ( 216–260 ) of three clusters for control . Perich [24] used two residential blocks with 12 untreated houses as control , Perich [25] used one residential bock with 6 untreated houses . A variety of entomological and disease specific outcome measures were used to assess the impact of IRS: 1 ) Measures for adult Aedes: Adult mosquito mortality and knock down ( KD ) rates[20 , 23 , 24 , 25]; Adult mosquito density [20 , 23 , 24 , 25 , 26] and spatial and temporal patterns [26]; 2 ) Measures for immature Aedes: Breteau Index ( BI ) [20 , 22 , 23]; House Index ( HI ) [20 , 22]; Percentages of breeding site [23]; Number of parous females [26]; 3 ) Disease specific measures: Age adjusted dengue incidence [21]; Odds of secondary dengue infection [21]; reported number of cases [22] . The effect of indoor spraying of insecticides on adult mosquitoes is strong immediately after application in all studies measuring these parameters . For IRS studies , in Peru [20] the Adult Index fell from 18 . 5 to 3 . 1 four weeks’ after intervention ( p < 0 . 05 ) . For ISS studies , adult mortality percentage reduction was 100% post indoor spraying , 77 . 8% on day 5 , 6 . 25 on day 7[23] . Similarly , adult density dropped to 0 after spraying with thermal fog and ULV , increasing after day 7 and continued to increase until 7 weeks post spraying , with similar results in Costa Rica [24] and Honduras [25] . In an uncontrolled setting in Thailand [26] , indoor spraying reduced the number of adult mosquitoes to around 10% , however gradually recovering after day 2 . The latter study measured also that there was a relationship between mosquito density and distance to the centre of application with an area of protection extending to 85 m . Parity rates also dropped after spraying . The effect on immature mosquitoes is less strong on all studies measuring larval indices . For IRS studies , deltamethrin in Peru reduced all immature indices in the first week and sustained throughout the period of studies [20] . Also , there was a noted reduction of BI from 35 to 5 in Taiwan [22] . However , for ISS , in India , with a BI of 50 at baseline , this reduced to 29 . 6 post 7 days , and recovered post 14 days to 37 . 5 . For human dengue infection parameters , there are only two IRS studies . Odds of dengue infection shown by Vazquez-Prokopec [21] , in Australia , were significantly higher at unsprayed than at sprayed premises ( OR = 2 . 8; 95%CI = 1 . 1–6 . 9; p = 0 . 03 ) . When 60% of the premises were sprayed around the index case house the odds reduced significantly to zero . Also the number of dengue cases was strongly and positively correlated to the number of IRS applications ( r >0 . 6 ) . Also , in Taiwan [22] , the number of cases reported over time , dropped with IRS applications from above 3000 to 1000 ( no control ) .
The evidence presented here suggests that IRS and ISS can be an effective dengue control intervention . The majority of included studies demonstrated a significant post-intervention reduction in adult and some effect on immature Aedes populations . Notably , of the studies that measured dengue incidence , both showed decreases in new dengue cases after the application of IRS . These findings support the use of IRS as a component of integrated vector management ( IVM ) [27] , and perhaps ISS as well . While the differing methodologies and interventions precluded meta-analysis , the included studies consistently show effective killing of adult Aedes mosquitos almost immediately after application of IRS and ISS . Estimates of the duration of effect are limited by the relative short time-frames studied , but multiple studies reported residual efficacy up to two months post-intervention . The impact of IRS on the incidence of dengue may be of even longer duration . The impact of ISS on dengue transmission was not measured . Further confirmations of the effect of IRS and ISS arise by two further studies [28 , 29]–the studies focused however on other elements and were excluded in the analysis . Ritchie [28] noticed an effect that started late but continued , using a combination of containers treated with S-methoprene or lambda-cyhalothrin and adult control with IRS using lambda-cyhalothrin , “human cases subsequently dropped from a high of seven cases per day in mid-March to only sporadic cases in late April , with the final reported onset of 7 May” . Stoddard [29] analysed surveillance data of dengue for explanatory models of transmission , ISS delivered in three cycles , using deltamethrin , cypermethrin , or alpha-cypermethrin , resulted in a good reduction of dengue transmission in trimester III . An update of the searches generated a further article , published shortly after the initial searches [30] . The authors conducted a study using space-time statistical data modelling from Cairns , Australia ( data from 2008 and 2009 ) . Targeted IRS “in potential exposure locations reduced the probability of future DENV transmission by 86 to 96% , compared to unsprayed premises” . This study strongly confirms the potential of IRS for reducing dengue transmission . While there is evidence for indoor spraying in the control of dengue , there are a number of challenges with scaling up such interventions . Since , indoor spraying can require high levels of coverage , which requires widespread community acceptance and participation . Few studies included in the review reported qualitative estimates of community acceptance , although IRS is often popular as it has the ancillary benefit of killing many nuisance insects [1 , 4] . However , Chang [31] emphasised how communities are still reluctant to take appropriate dengue control measures . Furthermore , Gürtler [32] suggested integrating sustained social participation into IVM activities like source reduction , biological control , and environmental management , in order to overcome such a challenge and to ensure long-term sustainability of dengue prevention and control . In addition , none of the included studies examined the associated costs of indoor spraying . In Australia however , where IRS is used for dengue control , a cost-analysis shows that the total costs of preparedness through surveillance are far lower than the ones needed to respond to the introduction of vector-borne pathogens [33] . Universal application and re-application is likely beyond the resources of many dengue-affected countries . Therefore , effective use of indoor spraying will require timely surveillance and response mechanisms . Combination of effective early warning systems with vector control measures could reduce densities of Aedes and subsequently dengue transmission [34] . Response systems could include mapping technologies like GIS [35] . Using space-temporal units besides such technologies is essential in delivering the resources and in measuring the coverage [36] . Analysis of one of the included studies showed similar evidence on how early detection of dengue outbreak helped to implement rapid and effective control actions , including early use of residual pesticides [22] . Experiments emphasised an association between type of insecticide used and its residual effect on Aedes and showed how the susceptibility of mosquitoes differs from one insecticide to another [37 , 38] . Perich [24 , 25] reported on another factor , which was the droplet size and linked it to post-spray residual effect . Sulaiman [39] pointed out how applying IRS on wooden surfaces is potentially controlling dengue . Another efficacy study in Malaysia linked house construction to the residual activity of IRS , since its wall bioassays indicated that both Ae . aegypti and Ae . albopictus were more susceptible to IRS on wooden surfaces than on brick surfaces [40] . Other challenges that are not well addressed in the included studies are optimal application and insecticide resistance , the latter is of a growing concern . Resistance particularly may affect severely the effectiveness of IRS/ISS . For residual treatment for example a study in Brazil showed a mortality of only 10% for Aedes in some communities for Deltamethrin [41] . A further challenge is the application of IRS , and where IRS is targeted . Whereas for Malaria and transmitting vectors IRS is defined as “the application of insecticide to the inside of dwellings , on walls and other surfaces that serve as a resting place for malaria-infected mosquitoes” and conditions for the use of IRS are set as “1 ) Majority of vectors ( i . e . , organisms that transmit malaria ) must feed and rest indoors 2 ) Vectors are susceptible to the insecticide in use , 3 ) Houses have “sprayable” surfaces and 4 ) A high proportion of the houses in target areas are sprayed ( more than 80 percent ) ” [42] , such conditions are not as clear set for dengue vectors . In addition to routine control measures , the use of indoor spraying as an emergency response is also feasible . Perich [24] pointed out how ISS successfully fulfils the criteria to be used as an emergency operation , which were: 1 ) providing an initial kill of adult Aedes , and 2 ) allowing a significant level of residual activity . Although residual activity with ISS may be mixed up with a time lag in recovery of mosquito populations . Evidence from that study and other efficacy studies in Malaysia and Taiwan plus ineffectiveness of outdoor spraying to control indoor Aedes populations make indoor spraying a true effective alternative for emergency suppression of Aedes mosquitoes [22 , 23 , 24 , 25 , 39 , 43] . This may also include the use of household ( commercial ) insecticides , another field that warrants analysis . The key limitation of this systematic review is the very limited number of studies that typically researched community effectiveness of IRS and ISS . This study reports therefore on the different forms of application in relation to the outcomes . Also , potential publication and selection bias are most concerning . It is well documented that studies with positive outcomes are more often reported in literature than negative outcomes . The diversified and extensive search strategy along with no restrictions in languages should minimise the publication and selection bias . The findings must also be interpreted with regard to the quality of the included studies: 1 ) Different methodologies , 2 ) Different study settings , 3 ) Limited use of statistical methods to assess for significance/control for confounding , 4 ) Relatively short study periods and 5 ) Lack of randomisation in most studies , influence the results . However , the review is the most comprehensive to date and highlights the need for future work in this area . Concluding , evidence obtained from this systematic review showed that the use of IRS and ISS can produce significant reductions of Aedes populations ( adult and immature forms ) . IRS can also produce significant reductions in human dengue cases , with very limited available evidence , but no data are available for ISS . However , evidence to suggest the effectiveness of IRS/ISS either on immature and adult stages of Aedes or on human dengue cases as a single intervention is limited . The community effectiveness of IRS is affected , directly and indirectly , by many factors . Examples for these factors are disease epidemiology , virus dynamics , human movements , effective surveillance systems , community participation in vector control , the insecticides used , particularly considering insecticide resistance , environmental factors , and house construction . When these factors work in harmony with IRS/ISS applications , they would maximise its community effectiveness . Moreover , they could maximise the applicability of IRS/ISS , also being used as an emergency control measure during epidemics instead of being just applied as a routine control measure . | The effectiveness of indoor residual spraying ( IRS ) and indoor space spraying ( ISS ) as dengue vector control methods depends on many factors . This study aims to systematically review the evidence on the community effectiveness of indoor spraying of insecticides to reduce Aedes mosquito populations and thereby to control dengue transmission . A systematic literature review was performed in PubMed , EMBASE , LILACS , Web of Science , WHO library database ( WHOLIS ) , Cochrane , and Google Scholar , including a manual search of the reference lists of the identified studies since its inceptions until 15 . 02 . 2017 . A total of 39 articles were retrieved for full assessment . Seven studies were included and analysed after final application of inclusion and exclusion criteria: two IRS studies with control , one without , three ISS studies and one , respectively . One IRS study and four ISS studies showed good evidence of effectiveness on adult Aedes mosquitoes . Evidence of effectiveness of IRS as a larvicidal intervention exists but is still inadequate , and is weak for ISS . Evidence of effectiveness of IRS on human dengue cases as a single intervention exists , but was limited and not available for ISS . It is recommended to scale up the research regarding the community effectiveness of IRS and ISS , including measuring dengue transmission , particularly , for IRS with its residual effect . It is also suggested to study in depth the factors that could affect the community effectiveness of IRS and ISS on Aedes populations and on human dengue cases . | [
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] | 2017 | Community effectiveness of indoor spraying as a dengue vector control method: A systematic review |
Lysine specific demethylase-1 ( LSD1/KDM1A ) in complex with its corepressor protein CoREST is a promising target for epigenetic drugs . No therapeutic that targets LSD1/CoREST , however , has been reported to date . Recently , extended molecular dynamics ( MD ) simulations indicated that LSD1/CoREST nanoscale clamp dynamics is regulated by substrate binding and highlighted key hinge points of this large-scale motion as well as the relevance of local residue dynamics . Prompted by the urgent need for new molecular probes and inhibitors to understand LSD1/CoREST interactions with small-molecules , peptides , protein partners , and chromatin , we undertake here a configurational ensemble approach to expand LSD1/CoREST druggability . The independent algorithms FTMap and SiteMap and our newly developed Druggable Site Visualizer ( DSV ) software tool were used to predict and inspect favorable binding sites . We find that the hinge points revealed by MD simulations at the SANT2/Tower interface , at the SWIRM/AOD interface , and at the AOD/Tower interface are new targets for the discovery of molecular probes to block association of LSD1/CoREST with chromatin or protein partners . A fourth region was also predicted from simulated configurational ensembles and was experimentally validated to have strong binding propensity . The observation that this prediction would be prevented when using only the X-ray structures available ( including the X-ray structure bound to the same peptide ) underscores the relevance of protein dynamics in protein interactions . A fifth region was highlighted corresponding to a small pocket on the AOD domain . This study sets the basis for future virtual screening campaigns targeting the five novel regions reported herein and for the design of LSD1/CoREST mutants to probe LSD1/CoREST binding with chromatin and various protein partners .
Lysine specific demethylase-1 with its corepressor protein CoREST ( LSD1/CoREST ) has emerged as one of the most promising epigenetic targets in drug discovery and design [1] . LSD1/CoREST is widely investigated for its expanding biological roles in cancer , neurodegeneration , and viral infection [2]–[7] . The precedence for drugging chromatin modifying epigenetic targets was established with FDA approval of vironostat and romidepsin , antineoplastic epigenetic drugs that target histone deacetylases [8]–[10] . However , no promising therapeutics that target LSD1/CoREST have emerged to date . A few LSD1 inhibitors have been reported [6] but they display modest activity , have non-ideal medicinal chemistry features due to their polycationic nature [11] , [12] or are poorly selective covalent inhibitors that bind to FAD in the H3-histone N-terminal tail-binding pocket ( Figure 1 ) [13]–[15] . Alternatively , short peptide sequences have been recently designed to bind with affinities comparable to those displayed by the natural H3-histone substrate [16] and are inspiring the development of lead compounds . Recently , our group proposed that druggable regions beyond the AOD active site ( Figure 1 ) might hold the key to developing pharmacologically relevant inhibitors by an allosteric mechanism revealed by extended molecular dynamics ( MD ) simulations [17] , [18] . Moreover , these new druggable regions could target protein-protein interactions necessary to the formation of multi-protein complexes [19]–[25] and/or prevent LSD1/CoREST from binding to the nucleosome [18] , [26] . Multiple solvent crystal structures ( MSCS ) is an experimental technique that can probe favorable binding regions for small molecular fragments on protein surfaces . Still , only a reduced number of protein crystals are suited for such experiments because the conditions for MSCS can interfere with crystallization . This limitation highlights the importance of developing reliable computational techniques that quickly and accurately identify potential binding hot spots on a protein receptor . FTMap [27] and SiteMap [28] , [29] are two algorithms that were successfully and independently developed to predict druggable hot spots . In order to investigate protein druggability while effectively including receptor dynamics , conformational clustering analysis has been shown to generate reduced receptor configurational ensembles with significant computational timesaving [30]–[33] . Thus far , ensemble-based approaches have often employed clustering algorithms to select only a handful of dominant receptor MD centroids , which are the most representative structures extracted from a conformational clustering analysis , but this poses the general question whether a few most dominant structures are sufficient to capture more ephemeral states of the receptor , which could contribute to important mechanistic steps such as the opening of transient cavities available for binding . Nichols et al . highlighted this problem in the context of blind virtual screening through ligand docking to MD generated receptor structures [34] , [35] . In this study , we took a complete-ensemble approach by effectively including all the most relevant MD centroids in addition to available X-ray structures to probe the druggable space of the dynamic LSD1/CoREST epigenetic target ( Figure 1 ) . A reduced number of tens of MD centroids allows effectively eliminating redundant information and efficient computational analysis . The entire LSD1/CoREST protein complex was investigated using the independent algorithms FTMap and SiteMap so that previously uncharacterized hot spots could be identified . The newly developed Druggable Site Visualizer ( DSV ) software tool was used to inspect favorable binding regions . The resultant computational predictions were compared with the available experimental data including X-ray crystallography experiments that used small peptides to investigate protein-protein interactions on the LSD1/CoREST surface . The co-crystallized Pro-Leu-Ser-Phe-Leu-Val peptide in a novel , predicted binding site on LSD1/CoREST shows the strength of the methods hereby presented .
The molecular systems and simulations used in this study were previously described [17] , [18] . The atomic coordinates from the structure by Yang et al . ( PDB ID: 2IW5; 2 . 6 Å resolution ) [26] were used to initialize a 500 ns run of LSD1/CoREST . A second 500 ns run of LSD1/CoREST bound to the H3-histone N-terminal tail ( 16 residues ) was initialized using the peptide substrate coordinates by Forneris et al . ( PDB ID: 2V1D; 3 . 1 Å resolution ) [36] . Standard preparation , minimization , heat-up , and equilibration procedures were performed using GROMACS ( version 4 . 5 . 4 ) compiled in double precision [37] , [38] , the GROMOS 53A6 force field parameter set [39] , the compatible SPC water model [40] , and compatible ion parameters [41] . 50 , 000 MD snapshots were extracted every 10 ps from each trajectory and used for analysis . An RMSD-based conformational clustering algorithm was used to extract reduced unbound and H3-bound configurational ensembles [42] as implemented in the GROMACS g_cluster program [37] , [38] . The snapshots from each trajectory were aligned to each other by least-square fitting [43] of the Cα atoms of key residues from the amine oxidase domain ( Pro171-Glue427 and Ser517-Lue836 ) . Conformational clustering was performed on all atoms of these residues by scanning a wide range of RMSD similarity thresholds , and the final choice was made by employing a similarity threshold of 2 Å . See the Results section for a detailed discussion of the conformational clustering analysis . Prior to the mapping calculations each structure was prepared using the Protein Preparation Wizard utility from Schrödinger [44] , [45] . Water molecules were removed when present and hydrogen atoms added to reproduce a neutral apparent pH . The position of all hydrogen atoms was energy minimized using the OPLS 2005 force field [46] . The FTMap and SiteMap alternative computational approaches were used to search for favorable binding regions on LSD1/CoREST structures . The FTMap algorithm samples an order of 109 docked poses for 16 small molecule probes using Fast Fourier Transforms . The docked probes are scored and reduced to sets containing the top 2 , 000 poses for each probe . After minimization the probes are rescored and clustered using a 3-Å cutoff . The SiteMap algorithm generates site points on a grid surrounding the receptor van der Waals surface ( 0 . 35 Å grid 3D resolution in our study ) . Site points sheltered in a pocket or cleft of the protein are retained while points left exposed to solvent are eliminated; the criteria for retaining a site point is determined by the ratio of the squares of the distance of site points to a protein receptor atom and the van der Waals radius of that receptor atom being less than the default value of 2 . 5 [29] . The remaining site points that have neighbors in close proximity are grouped into SiteMap sites . A probe simulating a water molecule explores each site and characterizes the sites based on van der Waals and electrostatic potentials . Contour maps of each site are generated that describe the binding characteristics of the site . Apart from grid resolution , the SiteMap default settings were employed in all cases and sites were merged with the receptor into a single PDB file for analysis . The Druggable Site Visualizer ( DSV ) software was developed for this work as a plugin for graphical modeling with Visual Molecular Dynamics ( VMD ) [47] . Figure 2 summarizes the DSV workflow and the underlying automated steps that remain blind to the user . The DSV function Visualize takes FTMap and SiteMap output in PDB file format and processes it for convenient and data-rich visualization . Visualize employs as arguments either a single receptor structure or an ensemble of structures; the latter scenario is subsequently described and used in this work for processing the reduced MD ensembles . The user loads a first PDB structure through DSV and a QuickSurf representation is created . Then the remaining structures with FTMap and SiteMap information are loaded as DSV performs their automated alignment to the first reference structure . DSV converts FTMap consensus sites ( CSs ) to spheres centered about the geometric midpoint of each CS and sized according to CS rank ( largest sphere corresponding to highest ranking CS ) . This graphical approach was inspired by previous work by Ivetac and McCammon [32] and automated in DSV . DSV colors such FTMap spheres corresponding with the rank of the MD centroid they correspond to ( color coding goes from red for highest-ranking MD centroids to blue for lowest ranking MD centroids where rank is determined by population of the MD cluster from which the centroid was extracted by conformational clustering ) . In parallel , DSV Visualize converts the SiteMap sites to isosurface representations colored according to their MD centroid rank . By default , all of the FTMap spheres and SiteMap surfaces are displayed on the first-loaded reference structure . For graphical purposes the user makes some system dependent , arbitrary decisions . Typical user-defined inputs are: In this work the number of CSs displayed for each system are specified in the text and figure captions , LSD1/CoREST structures were aligned based on the Cα atoms of all protein residues , the largest sphere radius was set equal to the number of spheres displayed ( in Å ) , and the iValue was set to the default value 0 . 5 . Another automated feature of DSV is the Select-residues function . This function may work with a single receptor structure or an ensemble of structures that contain FTMap and SiteMap output . The latter scenario is subsequently described and used in this work for identifying residues defining new druggable regions as described in the Discussion section . The first PDB reference structure file is loaded through DSV and a NewCartoon representation of the protein receptor is produced . Subsequent structures are loaded through DSV and aligned to the initial reference structure , following an identical procedure described above for the Visualize function . Select-residues then loops through all MD centroids and selects residues within 3 Å of FTMap CSs and produces licorice representations of the residues on the first structure while removing duplicate occurrences of residues across the ensemble of MD centroids . A licorice representation of residues is created for all residues within 3 Å of SiteMap sites while eliminating redundancy . At the last step , a third representation is created that shows residues in licorice representations for residues within 3 Å of both FTMap and SiteMap sites . For graphical purposes the user inputs some system-dependent decisions . Examples of user-defined inputs in the first release of DSV are: The first release of DSV ( version 1 . 0 ) can be freely downloaded at the software tools web page of the Baron lab , currently: http://barongroup . medchem . utah . edu/tools . The crystallographic data and three-dimensional structure of LSD1/CoREST bound to the peptide Pro-Leu-Ser-Phe-Leu-Val were described before [16] ( PDB ID: 3ZMV ) . Briefly , the peptide complex was obtained by crystal soaking in solutions consisting of 1 . 6 M sodium/potassium tartrate , 100 mM N- ( 2-acetamido ) -2-iminodiacetic acid pH 6 . 5 , 10% ( v/v ) glycerol , and 2–5 mM peptide for 3 h . X-ray diffraction data were collected at 100 K at the Swiss Light Source ( Villigen , Switzerland ) . Data processing and refinement were carried out using programs of the CCP4 package [48] .
The reduced ensembles obtained from conformational clustering contained 52 ( unbound ) and 45 ( H3-bound ) MD centroids . Figure 1 shows the MD centroids sorted according to their cluster rank as visualized by Druggable Site Visualizer ( DSV ) . The top-ranking clusters contained 11 , 643 ( unbound ) and 10 , 995 ( H3-bound ) MD snapshots whereas four ( unbound ) and three ( H3-bound ) MD clusters were singly populated . Overall , this result was consistent with the general observation of a moderate decrease in LSD1/CoREST flexibility upon H3-histone binding [17] , [18] ( Figure 1 ) . Note that this study employed all the MD centroids in each ( unbound or H3-bound ) reduced ensemble , to account as well for transient and more rare MD snapshots . It is therefore different from previous closely related approaches ( e . g . see Refs . [32] , [33] that focused the analysis on the most dominant MD centroids only ) . Druggability mapping was first explored using available X-ray structures of the LSD1/CoREST complex . Results based on X-ray structures of LSD1/CoREST bound to the H3 ( PDB code 2V1D [36] ) and SNAIL ( PDB code 2Y48 [49] ) N-terminal peptides were mapped with DSV for the five highest-ranking FTMap CSs ( Figure 3A , top row ) and the 10 highest-ranking FTMap CSs ( Figure 3A , bottom row ) . Druggability mappings of these structures were performed both in the absence ( first column ) and presence ( second and third columns ) of the peptide ligands . In all cases , the most likely druggable region picked by FTMap was clearly the well-known H3-pocket . The FAD cofactor pocket was also similarly favored ( Figure S1 ) . This result confirmed that new favorable regions were found independently of which X-ray structure was employed , and independently of which peptide substrates occupied the H3-binding site . The observed ability of FTMap to blindly predict favorable LSD1/CoREST sites for non-covalent binding of peptide ligands or of the FAD cofactor confirmed analogous successes recently reported for different protein receptors [27] , [50] , [51] . After achieving confidence in FTMap accuracy on the LSD1/CoREST complex , druggability mapping was investigated using complete reduced MD ensembles obtained through conformational clustering of each of our 500 ns MD simulations to evaluate the effects of LSD1/CoREST dynamics on the 3D druggable space . Figure 3B shows the five highest-ranking FTMap CSs ( top row ) and the 10 highest-ranking FTMap CSs ( bottom row ) on the MD reduced ensembles ( Figure 1 ) . The CSs from the unbound and bound reduced ensemble predicted that the H3-pocket and FAD cofactor sites were strongly favorable as observed for the X-ray structures ( Figure 3B ) . However and most important , inclusion of LSD1/CoREST dynamics resulted in remarkably broader predicted druggable regions due to the opening of transient niches and cavities on the protein surface and in the H3-pocket ( cf . Figure 3A vs . 3B ) . Most notably , new CSs were observed at the AOD/SWIRM ( solid arrows Figure 3B ) and AOD/Tower ( hollow arrows Figure 3B ) inter-domain interfaces , which widely expanded the druggable regions . In addition to performing FTMap calculations on LSD1/CoREST experimental structures and MD reduced ensembles , SiteMap calculations were also performed to explore the druggable space of LSD1/CoREST by means of an alternative , independent algorithm . Figure 4 shows the comparison of the top-five FTMap CSs and SiteMap sites obtained from DSV using the PDB ID 2V1D ( H3-histone tail present during FTMap and SiteMap calculations ) , the unbound MD reduced ensemble , and the H3-bound MD reduced ensemble ( H3-histone tail present during FTMap and SiteMap calculations ) . Consensus between FTMap and SiteMap was expected and largely found , as inferred by the observation that every FTMap sphere overlapped with a predicted SiteMap surface . In all cases , however , the SiteMap sites were also found in regions in which FTMap did not predict favorable sites . Most prominently , SiteMap predicted binding sites in the CoREST-SANT2/Tower region , while FTMap did not . In addition , SiteMap predicted more binding sites along the AOD/Tower inter-domain interface and on the SWIRM domain . Overall , the diverse unbound and H3-bound configurational ensembles led to distinguishable distributions of SiteMap sites on the LSD1/CoREST domains , in line with what was observed using FTMap on the same MD ensembles . Crystal contacts on protein surfaces and computational hot spot prediction have been used to predict protein-protein interactions in the past [52] , [53] . We thought to compare the LSD1/CoREST regions involved in crystal packing with the sites revealed by the computational analysis to determine whether predicted druggable sites corresponded to LSD1/CoREST crystal contacts . It was very satisfactory to see ( Figure 5 ) that the regions involved in inter-molecular crystal-packing interactions overlapped closely with both FTMap CSs and SiteMap sites . For instance , the Tower domain had minimal SiteMap and FTMap hot spots . Nevertheless , the crystal-contact inspection showed that the Tower of an LSD1/CoREST molecule interacted through crystal-contacts with a SiteMap-predicted hot spot on the amine oxidase domain ( AOD ) of a symmetry-related LSD1/CoREST molecule ( Panel B in Figure 5 ) . Likewise , the crystal-contact regions between the AOD and Tower/CoREST-SANT2 domain contained SiteMap-predicted hot spots on both partners ( Panel C in Figure 5 ) . These results further validated our approach and supported the observation that the identified sites represented promising small-molecule or protein-protein interaction sites . Additional support to the validity of our approach was given by the investigation of the crystal structure of LSD1/CoREST bound to Pro-Leu-Ser-Phe-Leu-Val . This peptide was investigated in the framework of a study aimed at identifying the sequence features that confer specificity to the interaction between the LSD1/CoREST active site and the N-terminal SNAG domain of SNAIL1 and related transcription factors [16] , [49] . Interestingly , the crystallographic analysis revealed that this peptide binds not only to the catalytic site but also in a distinct shallow cleft in the AOD domain ( Figure 6 ) . The electron density was poorly defined for Pro1 , but showed well-defined conformations for all other ligand residues bound to this newly discovered site . In particular , the peptide adopted an extended conformation that enabled its backbone to establish H-bond interactions with an adjacent β-strand ( residues 317–323 ) . Furthermore , Phe4 and Val5 were both engaged in van der Waals contacts with nearby residues ( Ala318 , Thr319 , Phe320 , Leu329 , and Val747 ) . It remains to be seen whether this region actually represents a potential site for interactions between LSD1 and other proteins; this will be the subject of future studies . In the context of this work , it was most significant that the peptide-binding site was correctly identified by our computational analysis and showed that including LSD1/CoREST dynamics was crucial . In more detail , neither FTMap nor SiteMap identified this region as a potential hotspot when the crystallographic coordinates were used . However , when the calculations were performed using the LSD1/CoREST configurational ensemble generated from MD snapshots the binding site was correctly located by FTMap on one centroid and by SiteMap on 71% of the centroids ( Figure 7A ) . Examination of the correlation between SiteMap hot spot prediction with specific protein conformational changes highlighted the importance of Arg312 and Phe320 ( Figures 6 and 7 ) . During the MD simulations , these residues sampled conformations that enabled SiteMap to identify the region as potential binding site ( Figure 7B , second column ) . Interestingly , Arg312 and Phe320 also sampled configurations that closed the binding pocket and led to negative SiteMap predictions ( Figure 7B , third column ) . These results underscored the importance of including ensembles of LSD1/CoREST structures for exploring the presence of new binding regions even if peptide binding does not cause per se any conformational change as gathered by the comparison of the bound and unbound crystal structures . Our findings were in line with a recent study by Johnson and Karanicolas indicating that druggable protein interaction sites are more predisposed to surface pocket formation compared with the rest of the protein surface [54] . On the other hand , it remains to be validated whether all new binding regions identified are favorable binding sites for small drug-like molecules; as suggested by Eyrisch and Helms transient pocket formation on protein surfaces may not be relevant in the context of protein-protein interactions [55] . Ongoing computational and experimental studies are being performed to target the newly predicted regions to discover new molecular probes .
An ensemble approach was designed to explore the druggability of dynamic protein receptors and applied to the LSD1/CoREST epigenetic target . Overall , five well-distinct , new binding regions were revealed and display hot spot properties comparable to the well-known H3-histone site ( Figure 8 ) . The regions at the SANT2/Tower interface ( region A ) and at the SWIRM/AOD interface ( region B ) overlap with the most prominent hinge points revealed by molecular dynamics simulations [17] , [18] . We suggest that they could be of primary relevance for LSD1/CoREST chromatin binding . A third interface region overlapping with a dynamic hinge point was discovered at the AOD/Tower interface ( region C ) . These first three regions are optimal targets for the discovery of molecular probes that might block LSD1/CoREST dynamics and prevent chromatin and/or protein association . Supporting experimental evidence of these computationally predicted properties can be obtained by examination of the LSD1/CoREST crystal contacts ( Figure 5 ) . A fourth region encompassing the back of the AOD domain was also predicted to have strong propensity for molecular binding ( region D ) . The computational prediction of this region was validated by X-ray crystallography experiments that used small peptides designed to investigate protein-protein interactions on the LSD1/CoREST surface . The co-crystallized Pro-Leu-Ser-Phe-Leu-Val peptide in a novel , blindly predicted binding site on LSD1/CoREST shows the strength of the approach presented . In addition , the observation that this true prediction would be prevented when using only the X-ray structures available ( including the structure bound to the same peptide ) underscores the relevance of including protein dynamics in the prediction of protein interactions . A fifth region was highlighted corresponding to a small pocket on the AOD domain ( region E ) . On the basis of our molecular dynamics simulations we propose that this predominantly hydrophobic pocket could be relevant as an allosteric site to hamper substrate binding . This study sets the basis for future virtual screening campaigns targeting the five novel regions reported and for the design of LSD1/CoREST mutants to probe LSD1/CoREST binding with chromatin and various protein partners . We developed and presented the Druggable Site Visualizer ( DSV ) that allows treatment of data of large-size protein configurational ensembles; it is freely distributed to the public , and readily transferable to other protein targets of pharmacological interest . | Protein dynamics plays a major role in determining the molecular interactions available to molecular binding partners , including druggable hot spots . The LSD1/CoREST complex is one of the most relevant epigenetic targets discovered and was shown to be a highly dynamic nanoscale clamp using molecular dynamics simulations . The general relationship between LSD1/CoREST dynamics and the molecular sites available for non-covalent interactions with an array of known binding partners ( from relatively small drug-like molecules and peptides , to larger proteins and chromatin ) remains relatively unexplored . We employed an integrated experimental and computational biology approach to effectively capture the nature of non-covalent binding interactions available to the LSD1/CoREST nanoscale complex . This ensemble approach relies on the newly developed graphical visualization by Druggable Site Visualizer ( DSV ) that allows treatment of large-size protein configurational ensembles data and is freely distributed to the public and readily transferable to other protein targets of pharmacological interest . | [
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] | 2013 | Expanding the Druggable Space of the LSD1/CoREST Epigenetic Target: New Potential Binding Regions for Drug-Like Molecules, Peptides, Protein Partners, and Chromatin |
Transcription factors are grouped into families based on sequence similarity within functional domains , particularly DNA-binding domains . The Specificity proteins Sp1 , Sp2 and Sp3 are paradigmatic of closely related transcription factors . They share amino-terminal glutamine-rich regions and a conserved carboxy-terminal zinc finger domain that can bind to GC rich motifs in vitro . All three Sp proteins are ubiquitously expressed; yet they carry out unique functions in vivo raising the question of how specificity is achieved . Crucially , it is unknown whether they bind to distinct genomic sites and , if so , how binding site selection is accomplished . In this study , we have examined the genomic binding patterns of Sp1 , Sp2 and Sp3 in mouse embryonic fibroblasts by ChIP-seq . Sp1 and Sp3 essentially occupy the same promoters and localize to GC boxes . The genomic binding pattern of Sp2 is different; Sp2 primarily localizes at CCAAT motifs . Consistently , re-expression of Sp2 and Sp3 mutants in corresponding knockout MEFs revealed strikingly different modes of genomic binding site selection . Most significantly , while the zinc fingers dictate genomic binding of Sp3 , they are completely dispensable for binding of Sp2 . Instead , the glutamine-rich amino-terminal region is sufficient for recruitment of Sp2 to its target promoters in vivo . We have identified the trimeric histone-fold CCAAT box binding transcription factor Nf-y as the major partner for Sp2-chromatin interaction . Nf-y is critical for recruitment of Sp2 to co-occupied regulatory elements . Equally , Sp2 potentiates binding of Nf-y to shared sites indicating the existence of an extensive Sp2-Nf-y interaction network . Our results unveil strikingly different recruitment mechanisms of Sp1/Sp2/Sp3 transcription factor members uncovering an unexpected layer of complexity in their binding to chromatin in vivo .
Eukaryotic transcription factors are grouped into families based on their common structural features . Prototypical zinc finger-containing transcription factors are the evolutionary conserved Specificity proteins/Krüppel-like factors ( Sps/Klfs ) ( reviewed in [1 , 2 , 3 , 4] ) that share three consecutive C2H2-type zinc fingers in their C-terminal moiety . Mammals have nine different Sp factors ( Sp1 to Sp9 ) , which can be grouped into two subclasses based on structural features outside of the zinc finger domain [5] . The Sp1 to Sp4 subclass is characterized by glutamine-rich domains that have been shown to act as transactivation domains in Sp1 , Sp3 and Sp4 . Sp1 , Sp2 and Sp3 are ubiquitously expressed whereas expression of Sp4 is largely restricted to neuronal cells [1 , 6] . Despite their structural similarities and broad co-expression there seems to be little functional overlap between Sp1 , Sp2 and Sp3 [7 , 8 , 9] . Briefly , Sp1null as well as Sp2null embryos are severely growth-retarded and die before embryonic day 10 [7 , 9] . Conditional inactivation of Sp2 in neuronal stem cells and neuronal progenitor cells resulted in impaired proliferation and disrupted neurogenesis in embryonic and postnatal brain [10] . In homozygous Sp2 transgenic mice terminally differentiated keratinocytes are depleted and the animals die within two weeks after birth again underlining the physiological importance of Sp2 [11] . Moreover , a genome-wide screen for cell division genes identified Sp2 as a gene essential for proper mitosis in HeLa cells [12] . Finally , Sp3null mice develop until birth but are not viable due to manifold defects including impaired lung , cardiac , bone and red blood cell development [8 , 13 , 14 , 15] . At the molecular level , the functional properties of Sp1 and Sp3 are well characterized . Particularly , numerous publications reported binding of Sp1 and Sp3 to the GC box ( GGGGCGGGG ) and related motifs in vitro . In contrast , Sp2 has largely escaped attention since its initial discovery [16] likely because no DNA-binding activity of full-length Sp2 is detectable by the electrophoretic mobility shift assay [17 , 18] , and because Sp2 has little activation capacity on promoters that are regulated by Sp1 or Sp3 in reporter gene assays [19] . We have recently determined the genome-wide occupancy of Sp2 in mouse embryonic fibroblasts ( MEFs ) and in HEK293 cells , and have found that Sp2 occupies numerous proximal promoters of essential genes [18] . Bioinformatics analysis of the Sp2 binding sites identified CCAAT- and GC boxes as prevalent motifs in these promoters . On this basis and taking into account the similarity of Sp2 with other Sp factors , we concluded that Sp2 is recruited to its sites in chromatin by binding to the GC box in vivo . However , in the global chromatin context , it remains a largely unanswered question whether the very similar transcription factors Sp1 , Sp2 and Sp3 are bound to the same promoters in vivo and whether regions outside the bona fide DNA-binding domain contribute to their binding site selection . To address this important question , we have compared the genome-wide chromatin occupancy of Sp1 , Sp2 and Sp3 with each other in mouse embryonic fibroblasts . We found that Sp1 and Sp3 essentially occupy the same promoters and localize to GC boxes . In marked contrast , Sp2 predominantly localizes at CCAAT motifs . By re-expression of various Sp2 and Sp3 mutants in corresponding Sp2 and Sp3 knockout ( Sp2ko and Sp3ko ) MEFs , we found that the zinc finger region mediates chromatin binding of Sp3 . Unexpectedly , the bona fide zinc finger DNA-binding domain is completely dispensable for binding of Sp2 . Rather , it is exclusively the glutamine-rich N-terminal domain , which mediates recruitment of Sp2 to its genomic sites . We further show that Sp2 colocalizes with the trimeric CCAAT-binding transcription factor Nf-y at a large fraction of Sp2 binding sites . We provide evidence that Nf-y is necessary for recruitment of Sp2 and suggest that , in turn , Sp2 potentiates Nf-y binding to shared sites , since binding of Nf-y to sites that are also bound by Sp2 is attenuated in Sp2ko MEFs . Therefore , we have discovered that the seemingly similar transcription factors Sp1/Sp3 and Sp2 utilize completely different modes of genomic binding site selection and shed light on the previously enigmatic properties of Sp2 .
Recently , we have identified genomic binding sites of the transcription factor Sp2 in MEFs [18] . To identify the binding sites for the related transcription factors Sp1 and Sp3 , and to elucidate the potential overlap with Sp2 , we performed ChIP-seq analysis with the same cells . Two different antibodies for each factor that do not cross-react with other Sp family members were used ( [8 , 18] and S1–S2 Figs ) . An Sp3 ChIP using Sp3ko MEFs served as a control for the selection of Sp3-specific peaks; and an IgG ChIP for the selection of Sp1-specific peaks , as Sp1ko MEFs are not viable . We identified 5589 Sp1 and 4041 Sp3 peaks as overlapping across two sets of samples using two different antibodies for each factor ( Fig . 1A ) . Comparing the Sp1 and Sp3 peaks of all four ChIP-seq data sets revealed 3597 high-confidence sites that are bound by Sp1 as well as by Sp3 ( Fig . 1B ) . The large majority of these sites ( ~93% ) are located close to the 5´-end ( +/- 500 bp ) of annotated transcripts ( Fig . 1C ) . The comparison of the Sp1- and Sp3 ChIP-seq data sets also revealed a fraction of ~700 Sp1-specific peaks and a few ( 81 ) Sp3-specific peaks ( Fig . 1B ) . The majority of these sites represent peaks with relatively low tag counts just above the threshold used for peak selection . Another fraction of the potential Sp1-specific peaks is also found in the Sp3 ChIP-seq data sets . However , these peaks were removed from the classified Sp3 list because a peak appeared also in Sp3ko MEFs . The latter observation highlights the great benefit of using knockout cells as ChIP controls . Taken together , we are not convinced about the reliability of the apparently specific Sp1- or Sp3 binding sites . Rather , our ChIP-seq results support the notion that Sp1 and Sp3 essentially occupy the same promoters in vivo . Combined binding of Sp1 and Sp3 to the same promoters is consistent with the phenotype of Sp1/Sp3 compound heterozygous mice . These mice are not viable suggesting that a critical threshold of Sp1 and Sp3 activity is required for normal embryonic development and for proper regulation of common target genes [20] . We next compared the Sp1/Sp3 binding sites with those of Sp2 [18] . Although there is a large overlap , we were able to distinguish , with high confidence , Sp1/Sp3-specific as well as Sp2-specific binding sites ( Fig . 1D ) . Genome browser snapshots of representative shared Sp1/Sp2/Sp3 , Sp1/Sp3-specific , and Sp2-specific binding sites are shown in Figs . 1E and S2 . We also probed a panel of selected target promoters by conventional ChIP-qPCR analysis , and confirmed binding of all three Sp-factors to common promoters such as the L3mbtl2 , Nxt1 , Bin3 and Dhfr promoter , Sp1/Sp3-specific binding to the Raf1 , Calcoco1 , Kdelr2 and the Grb2 upstream promoter , and Sp2-specific binding to the Oxr1 , Plcl1 , and the Nfyc and Grb2 downstream promoters ( Fig . 1F ) , the latter containing alternative promoters that are either occupied by Sp1/Sp3 or Sp2 . Of note , consistent with our previous observation [18] , Sp1 and Sp3 binding to several promoters is reduced in Sp2ko MEFs , which is likely due to their lower expression levels in these cells [18] . We performed an unsupervised de novo sequence motif analysis at Sp1/Sp3 and Sp2 binding sites . The top motif at the Sp1/Sp3 peaks matches well-known in vitro Sp1/Sp3 binding sites with the GGGCGGG core sequence ( GC box ) . The second enriched motif is “CCAAT” , which is a binding site for the transcription factor Nf-y . Essentially , the same two motifs are found at the Sp2 binding sites [18] . However , at the Sp2 binding sites , the CCAAT motif is much more prevalent than the GC box motif ( Fig . 2A ) . Moreover , only the GC box motif but not the CCAAT motif is enriched at sites that are bound by Sp1 and Sp3 but not by Sp2 . Conversely , only the CCAAT motif but not the GC box is enriched at sites that are bound by Sp2 but not by Sp1 and Sp3 ( Fig . 2A ) . To extract positional information for the GC and CCAAT motifs within Sp1/Sp3 and Sp2 peaks , we performed a central motif enrichment analysis ( CMEA ) [21] . This analysis revealed that the GC box motif is enriched at the peak centers of the Sp1/Sp3 binding sites , whereas the CCAAT box motif is found at flanking regions showing a multimodal shape ( Fig . 2B ) . A strikingly different picture emerges at the Sp2 binding sites . Most significantly , the GC box motif is barely enriched at the Sp2 peak centers , whereas the CCAAT box motif exhibits a centrally enriched , symmetrical bimodal distribution with a mean distance of ~35 bp ( Fig . 2B ) . Intrigued by the nicely shaped distribution of the CCAAT motifs at the Sp2 binding sites , we examined the distribution of the CCAAT motif in greater detail . We found that ~70% of the top Sp2 binding sites but only ~23% of the Sp1/Sp3 sites contain two , or more , perfect CCAAT motifs . Moreover , ~65% of the Sp2-specific sites but only ~8% of the Sp1/Sp3-specific sites contain more than one CCAAT motif ( Fig . 2C ) . Finally , many Sp2-specific promoters ( ~40% ) but only a few Sp1/3-specific promoters ( 2 . 3% ) contain two CCAAT/ATTGG motifs that are located within a distance of 30 to 50 nucleotides ( Fig . 2D ) . Thus it appears that a large fraction of the Sp2 binding sites is characterized by tandem CCAAT motifs . The CCAAT motif is a binding site for the transcription factor Nf-y . Since Nf-y is also found at promoters that contain imperfect CCAAT motifs [22] , the number of Sp2 binding sites with tandem arranged CCAAT motifs ( e . g . Nf-y binding sites , see below ) could be even higher . Finally , we also determined the binding sites of Sp1 in HEK293 cells and compared the motifs at the Sp1 binding sites with those at the Sp2 binding sites [18] . Similar to mouse cells , the GC box is the prevalent motif at the Sp1 binding sites , whereas the CCAAT box is the prevalent motif at the Sp2 binding sites ( S3 Fig ) . In summary , the comparison of the genomic Sp1/Sp3 and Sp2 binding sites revealed markedly different sequence motif distributions indicating that binding of Sp2 to chromatin is distinct from Sp1/Sp3 , and questions our previous conclusion that Sp2 is recruited to its target promoters in vivo via binding to the GC box [18] . Intrigued by the finding that Sp1 and Sp3 are present at GC boxes , whereas Sp2 is located primarily at CCAAT motifs , we sought to identify the protein domains that are responsible for the differences in binding site selection in vivo . We focused on Sp2 and Sp3 because corresponding knockout MEFs are available [7 , 23] that have been proven to be useful for rescue experiments [18 , 24 , 25] . We stably expressed Flag-tagged full-length Sp2 and Sp3 , and deletion mutants thereof in corresponding knockout MEFs . All proteins are expressed at levels similar to endogenous Sp2 and Sp3 with the exception of the zinc finger domains that are expressed at a higher level ( Fig . 3A-B ) . ChIP-qPCR analysis of selected target promoters including promoters that are bound by Sp2 as well as by Sp3 ( Nxt1 , Sp1 and Sp2 ) , and promoters that are preferentially bound by either Sp2 ( Gas2l3 and Osbp ) or Sp3 ( Calcoco1 and Raf1 ) revealed specific binding of re-expressed full-length Sp2 and the full-length Sp3 isoforms ( Sp3li and Sp3si ) ( Fig . 3C-D ) . The Sp3ZF fragment lacking the entire N-terminal part is also bound at the Sp3 target promoters showing that the Sp3 zinc finger domain is sufficient for binding . As expected , the Sp3NT mutant lacking the DNA-binding domain is not bound at any of these promoters ( Fig . 3D ) . The picture , which emerged from the analysis of the Sp2 mutants is completely different . The Sp2ZF fragment lacking the N-terminal part is not bound at any of the Sp2 target promoters ( Fig . 3C ) . Strikingly , the Sp2NT mutant expressing the entire N-terminal part but lacking all three zinc fingers is bound at the Nxt1 , Sp1 , Sp2 , Gas2l3 and Osbp promoters almost as strongly as full-length Sp2 ( Fig . 3C ) . Thus , the canonical DNA-binding domain of Sp2 is dispensable , and the N-terminal part sufficient for binding to these promoters in vivo . This result suggests that Sp2 is recruited to its target promoters indirectly , likely involving protein-protein interactions ( see Discussion chapter for further details ) . To further substantiate the conclusion that Sp2 is recruited to its genomic sites by the N-terminal region rather than by the C-terminal zinc finger domain , we performed ChIP-seq using Sp2ko MEFs re-expressing Flag-tagged versions of full-length Sp2 ( Sp2FL ) , the Sp2 N-terminal part ( Sp2NT ) or the Sp2 zinc finger domain ( Sp2ZF; see scheme in Fig . 3A ) . Although the Flag ChIP was less efficient in this particular experiment , we identified more than seven hundred highly reliable Sp2FL and Sp2NT binding sites but only ten potential Sp2ZF sites ( Fig . 4A ) . Comparison of these binding sites with those of endogenous Sp2 in wild type MEFs revealed that >99% of the Sp2FL and >95% of the Sp2NT sites , but remarkably none of the Sp2ZF sites correspond to native Sp2 binding sites ( Fig . 4A ) . The correlation of normalized tag counts at individual Flag-Sp2FL and Flag-Sp2NT peaks ( Fig . 4B ) shows that full-length Sp2 and the zinc finger-deficient Sp2NT mutant bind to chromatin with similar strength . Of note , the sites bound by the Sp2NT moiety correspond to the strongest native Sp2 peaks ( Fig . 4C ) . Representative genome browser snapshots of Sp2FL and Sp2NT peaks in comparison with native Sp2 peaks are shown in Fig . 4D . Taken together , these striking results show convincingly that the zinc finger domain is dispensable for genomic binding of Sp2 to its target promoters . Recruitment of Sp2 in vivo by its N-terminal region is not limited to just a few selected target sites , but is a general feature of Sp2-targeting to chromatin ( Fig . 4E ) . To map protein regions of Sp2 that are essential for chromatin binding in vivo , we stably re-expressed a series of N-terminal Sp2 deletion mutants ( Fig . 5A ) in Sp2ko MEFs and tested their binding to selected loci . Western blotting and immunohistochemistry control experiments showed that all mutants are expressed at similar levels and are present in the nucleus ( Fig . 5B-C ) . Deletion of 27 N-terminal amino acids does not affect binding of Sp2 , whereas deletion of 93 N-terminal amino acids completely abolishes binding ( Fig . 5D ) . The Sp2 mutant lacking 49 N-terminal amino acids shows some residual binding to the Sp2 and Osbp promoters . We conclude that the Sp2 sequence between amino acids 28 and 93 is essential for binding of Sp2 in vivo . This region contains the Sp-box ( 33-SPLALLAATCSKIG-46 ) , a hallmark of the Sp transcription factor family members [1] . Whether the Sp-box is directly involved in recruitment of Sp2 remains to be established . Finally , we also rescued Sp2ko MEFs with a C-terminal deletion mutant ( 1–506 mutant in Fig . 5A ) that lacks the zinc finger domain and , in addition , the buttonhead box . The buttonhead box is a cysteine-rich motif ( CxCPnC ) of unknown function , and it is also a hallmark of Sp factors . The Sp2 1–506 mutant binds to the Sp2 , Osbp and Amd1 promoters as efficiently as full-length Sp2 demonstrating that the buttonhead box is also dispensable for binding of Sp2 to its sites in vivo . We wanted to know whether binding of the Sp2NT fragment could affect expression of target genes . At first , we tested whether it has the capacity to activate transcription . We fused the Sp2NT fragment to the Gal4-DNA-binding domain and performed reporter gene assays . The Gal4-Sp2NT fusion protein activated a Gal4-responsive 5xUAS-luciferase reporter as efficiently as a corresponding Gal4-Sp1NT fusion protein ( Fig . 6A ) showing that the N-terminal part of Sp2 has an activation function . Next , we tested expression of a selection of Sp2 target genes in wild type , Sp2ko , and Sp2ko MEFs re-expressing Sp2 mutants . Compared to wild type MEFs , Nlk transcript levels are markedly lower in Sp2ko MEFs ( 20% of wt ) . Nearly wild type Nlk mRNA levels are restored in Sp2ko MEFs expressing either full-length Sp2 or the Sp2NT mutant , but not in cells expressing the Sp2ZF mutant ( Fig . 6B ) . This result indicates that the loss of Sp2 leads to downregulation of Nlk transcription , and that re-expression of the Sp2 N-terminal fragment is sufficient to rescue Nlk expression . Nevertheless , the expression levels of many other Sp2 target genes were not significantly affected in Sp2ko MEFs [18] . Inspection of annotated ensemble transcripts revealed that many Sp2 target genes ( 65% ) have alternative transcriptional start sites . Moreover , many of the Sp2 binding sites overlap with Sp1/Sp3 binding sites ( Fig . 1 ) . Therefore , we reasoned that alternative initiation sites might hide transcriptional initiation driven by Sp2 . We chose the Grb2 and the Oxr1 genes to test this possibility . Both genes contain an upstream promoter bound by Sp1 and Sp3 but not by Sp2 and a downstream promoter bound by Sp2 but not by Sp1 and Sp3 ( Fig . 6C ) . We analyzed levels of Grb2 and Oxr1 transcripts with primer pairs that detect all transcripts , and with primer pairs that detect specifically the transcripts initiated at the Sp2-specific downstream promoters . Compared to wild type MEFs , the total transcript levels of the Grb2 and Oxr1 genes are largely unaffected in Sp2ko MEFs . In contrast , the downstream promoter-specific transcript levels are significantly lower in Sp2ko MEFs; and they are at least partially restored in Sp2ko MEFs expressing full-length Sp2 or the Sp2NT mutant ( Fig . 6C ) . In summary , these results indicate that the N-terminal region of Sp2 is sufficient for activation of a subset of genes . However , they do not exclude that the zinc finger domain of Sp2 is essential for activation of other genes . The CCAAT box is the binding site of the ubiquitous transcription factor nuclear factor y ( Nf-y , previously also termed Cbf for CCAAT-binding factor; reviewed in [26] ) . Nf-y is a heterotrimeric protein composed of the three subunits Nf-ya , Nf-yb and Nf-yc . The Nf-ya subunit confers base-specific recognition of the CCAAT sequence , whereas the basic surface of the histone-fold Nf-yb/Nf-yc dimer makes strong contacts with the negatively charged DNA sugar-phosphate backbone [27] . All three Nf-y subunits are necessary for binding to the CCAAT box . Based on its histone-like properties , Nf-y is considered as an architectural promoter organizer that keeps a promoter free of nucleosomes [27] . The presence of Sp2 at CCAAT boxes rather than at the GC box prompted us to ask whether Nf-y is also present at these sites , and whether genomic binding of Nf-y and Sp2 impinge on each other . We performed ChIP-seq of Nf-ya , Nf-yb and Nf-yc with chromatin from wild type and Sp2ko MEFs ( Fig . 7A ) . We obtained a higher number of Nf-yb sites with respect to Nf-ya and Nf-yc sites , which very likely does not reflect the occurrence of Nf-yb-specific target loci , but a better ChIP efficiency of the Nf-yb antibody . This assumption is supported by the significantly higher average reads per peak obtained for Nf-yb as well as by the higher enrichment values obtained in ChIP-qPCR experiments ( see below ) . Comparison of the Sp2 and the Nf-y ChIP-seq data sets revealed that 84% of the Sp2 target sites are also bound by Nf-y ( Fig . 7B ) . Moreover , the strength of Nf-y- and Sp2 binding correlates with each other; in other words , sites with high Nf-y subunit tag counts have also high Sp2 tag counts ( Fig . 7C ) . Nevertheless , a subset of sites is clearly bound exclusively by Sp2 or exclusively by Nf-y . Examples of such sites are the Fanci and the Taf1c promoters that are bound by Sp2 but not by Nf-y , and the Atxn3 and the Wapal promoters that are bound by Nf-y but not by Sp2 ( Fig . 7D ) . We compared sites that are bound by Sp2 as well as by Nf-y with sites that are bound only by Sp2 or only by Nf-y . MEME reported the CCAAT and the GC motif as the top motifs at sites that are co-bound by Sp2 and Nf-y as well as at sites that are bound by Nf-y but not by Sp2 ( Fig . 7E ) . Consistent with the analysis of all Sp2 ChIP-seq peaks , the CCAAT motif shows a symmetric bimodal distribution at shared Sp2/Nf-y sites . The CCAAT motif at the Nf-y-specific sites does not show this pronounced bimodal distribution but is largely centrally enriched ( Fig . 7F ) . The prevalent motifs at sites bound by Sp2 but not by Nf-y are the GGAAG motif , a binding site for the Ets family members Gabp and Elk4 , and the GC box ( Fig . 7E ) . At these sites , the GC box appears to be centrally enriched and flanked by the GGAAG motif ( Fig . 7F ) . The occurrence of a centrally enriched GC box made it possible that the zinc finger domain of Sp2 could be essential for binding to these sites . Notably , these sites are weak binding sites ( S4 Fig ) that were not detected in our Flag-Sp2FL and Flag-Sp2NT ChIP-seq experiments shown in Fig . 4 . Therefore , we tested binding of Sp2 mutants to this class of promoters by conventional ChIP-qPCR . Full-length Sp2 as well as the Sp2NT fragment are bound to the Fanci and the Taf1c promoters ( S4 Fig ) . We conclude that the zinc finger region of Sp2 is also dispensable for binding to sites that are not bound by Nf-y . Finally , we determined the overlap of Sp1/Sp3 , Sp2 and Nf-y sites . Approximately 45% of the Sp1/Sp3 sites are also occupied by Nf-y ( Fig . 7G ) . Importantly , the vast majority of the Sp1/Sp3 binding sites that are not bound by Nf-y are also not bound by Sp2 ( 1825 of 1967; 93% ) ( Fig . 7G ) . These sites represent high tag count Sp1/Sp3 binding sites that are enriched of multiple GC boxes and , as expected , do not contain CCAAT motifs ( Fig . 7H ) . Thus , the occurrence of GC boxes and the presence of Sp1/Sp3 are not sufficient to recruit Sp2 . Of note , the prevalent , centrally enriched motif at the few Sp2 binding sites that are also bound by Sp1/3 but not by Nf-y ( 142 sites in Fig . 7G ) is the GGAAG motif and not the GC box ( Fig . 7H ) . These findings have also implications concerning the binding of Sp2 to promoters that contain both , GC and CCAAT boxes and are bound by Sp1/Sp3 and by Nf-y ( Figs . 2 , 7G ) . At these promoters , the resolution of the ChIP-seq peaks does in most cases not allow to distinguish whether Sp2 is located at a GC box or at a nearby CCAAT box . Given that Sp2 is bound to a large fraction of promoters that are bound by Nf-y lacking Sp1/Sp3 ( 1081 sites; 42% ) , it is tempting to conclude that the CCAAT box ( i . e . Nf-y ) and not the GC box ( i . e . Sp1/Sp3 ) is the decisive sequence for the recruitment of Sp2 to promoters bound by Nf-y and by Sp1/Sp3 . Having established the overlap of Sp2 and Nf-y target sites , we tested whether Sp2 and Nf-y simultaneously associate with chromatin , and performed sequential ChIP experiments ( re-ChIP ) . The eluate from Sp2 antibody chromatin precipitation was subjected to precipitation with Nf-yb antibodies , and vice versa . Re-ChIPs detected all selected promoters bound by Sp2 and Nf-y ( Sp1 , Sp2 , Osbp , Amd1 , Nxt1 and Nipal3 ) independently of the immunoprecipitation order ( Fig . 8A ) , but not the Sp2-specific Fanci , the Nf-y-specific Atxn3 or the Sp1/Sp3-specific Raf1 promoter . This result demonstrates that Sp2 and Nf-y co-occupy their shared binding sites in the context of chromatin . Co-occupancy of Sp2 and Nf-y at shared target promoters led us to ask whether Nf-y is necessary for recruitment of Sp2 to these sites . We knocked down all three Nf-y subunits individually by RNAi ( Fig . 8B ) , and subsequently analyzed binding of Nf-y and Sp2 to a panel of target promoters . These promoters include those that are co-bound by Nf-y and all three Sp factors ( Sp1 , Osbp , Amd1 and Dcnt4 ) , promoters that are co-bound by Nf-y and Sp2 but not by Sp1 and Sp3 ( Oxr1 and Plcl1 ) , and promoters that are bound by all three Sp factors but not by Nf-y ( Fanci and Taf1c ) ( Fig . 8C ) . Lower expression of any of the Nf-y subunits resulted in attenuated binding of Sp2 to all promoters that are co-bound by Nf-y and Sp2 . Importantly , the reduction of Sp2 binding is particularly strong at the Plcl1 and Oxr1 promoters , which are not bound by Sp1 and Sp3 . This result strongly suggests that reduced binding of Sp2 is not an indirect effect of reduced Sp1 levels in Nf-ya and Nf-yc depleted cells ( Fig . 8B , panel 4 , lanes 2 and 4 ) but directly caused by attenuated Nf-y binding . Binding of Sp2 to the Fanci and Taf1c promoters , which are not co-bound by Nf-y , was not affected upon depletion of Nf-yb and Nf-yc . Reduced binding of Sp2 to these two promoters upon Nf-ya knockdown is likely due to lower Sp2 levels in Nf-ya knockdown cells ( see Fig . 8B , panel 3 , lane 2 ) . Taken together , these results strongly suggest that the presence of Nf-y is necessary for recruitment of Sp2 to shared sites . Given the dependency of Sp2 on Nf-y , we wanted to know whether Sp2 does affect binding of Nf-y at these shared sites . We compared occupancy of Nf-y in wild type MEFs with occupancy in Sp2ko MEFs . Expression of Nf-y is similar in both cell types ( Fig . 9A ) . By calculating the ratio of normalized Nf-y ChIP-seq tag counts in wt and in Sp2ko MEFs ( wt/Sp2ko ) , we found attenuated Nf-y occupancy in Sp2ko MEFs at many promoters that are co-bound by Sp2 in wild type MEFs ( Fig . 9B , top panel ) . Attenuated Nf-y binding in Sp2ko cells is particularly strong at promoters that are bound in wild type MEFs by Sp2 but not by Sp1/3 such as the Nrxn2 , Grb2 , Nipal3 , Plcl1 or the Oxr1 promoters ( Figs . 9C-D , S5 ) . This demonstrates that binding of Nf-y to these promoters depends on the presence of Sp2 . Importantly , Nf-y binding remains largely unchanged or is even slightly potentiated at sites that are not co-bound by Sp2 ( Fig . 9B , bottom panel ) including promoters that are also bound by Sp1/Sp3 such as the Atxn3 , Mxi1 , and Pdcd4 promoters ( Figs . 9C-D , S6 ) . Given that genomic Nf-y binding is attenuated in Sp2ko MEFs at loci that are co-bound by Sp2 , it is to be expected that re-expression of Sp2 potentiates Nf-y binding at these sites . Indeed , we found stronger Nf-y binding in rescued MEFs , specifically at loci that are re-occupied by Sp2FL or by Sp2NT ( Sp2 , Osbp , Amd1 , Nipal3 and Nlk ) ( Fig . 9E ) . Binding of Nf-y at these promoters remained unchanged in cells expressing the Sp2ZF fragment . Finally , binding of Nf-y to the Atnx3 promoter , which is not an Sp2 target , is similar in Sp2FL , Sp2NT and Sp2ZF expressing cells ( Fig . 9E ) . Taken together , these results strongly support the conclusion that Sp2 potentiates binding of Nf-y at shared sites .
In this study , we have elucidated the mode of genomic binding site selection of the zinc finger transcription factors Sp1 , Sp2 and Sp3 . A key finding is that Sp1/3 and Sp2 bind to chromatin by distinct mechanisms . Consistent with numerous in vitro DNA-binding studies , Sp1 and Sp3 localize to GC boxes and essentially occupy the same promoters . Unexpectedly , Sp2 primarily localizes at CCAAT motifs , often arranged in tandem with a mean distance of 35 bp ( Fig . 2 ) . In line with their different binding site selection , re-expression of Sp2 and Sp3 mutants in corresponding Sp2ko and Sp3ko MEFs revealed that different protein domains mediate binding to their sites in chromatin . As expected , the C-terminal zinc finger domain is essential and largely sufficient for binding of Sp3 to its target promoters . Although not formally tested , we consider it as very likely that the zinc finger domain of Sp1 also mediates binding to chromatin . Intriguingly , the zinc finger domain of Sp2 is fully dispensable for binding in vivo . Instead , binding of Sp2 to its target promoters is mediated by the N-terminal glutamine-rich part , providing the essential clue for the different binding site selection of Sp2 , as compared to Sp1 and Sp3 . Interestingly , Sp2 targeted mice that do not express the zinc finger domain but aberrantly express an RNA encoding the N-terminal region display a markedly less severe phenotype than Sp2null mice [7] . Although expression remains to be established at the protein level , binding of the Sp2 N-terminal region to chromatin shown in this report provides a rational explanation for the different phenotypes of these mice . Sequence comparisons of the N-terminal region of Sp2 with the corresponding regions of Sp1 and Sp3 reveal major differences of their amino acid composition . Most significantly , in addition to the frequent occurrence of glutamine residues , the N-terminal domains of Sp1 and Sp3 are rich in acidic amino acids , whereas the N-terminal domain of Sp2 is very rich in basic amino acids ( S7 Fig ) . Thus , the general assignment of the N-terminal domains of Sp1 , Sp2 and Sp3 as glutamine-rich domains is misleading . Importantly , the presence of multiple positive charged lysines in the N-terminal region of Sp2 raises the possibility of non-specific interactions with the negatively charged sugar-phosphate backbone of the DNA . Binding sites of Sp1 and Sp2 have also been identified in K562 cells by the ENCODE consortium [28] . Since Sp1 and Sp2 binding sites largely overlap , it was concluded that Sp1 and Sp2 binding motifs ( i . e . GC boxes ) are indistinguishable [29] . We believe that this interpretation of the ChIP-seq data results from the structural similarity of Sp1 and Sp2 , and from Sp2´s capacity to bind GC rich oligonucleotides in vitro [18 , 19] . Admittedly , we also fell into this trap when we initially analyzed our Sp2 ChIP-seq data [18] . These misinterpretations emphasize the limitations of genomics data integration and highlight the importance of performing additional detailed experimental analysis . The data presented here revealed fundamental different modes of binding site selection of Sp1/Sp3 and of Sp2 , and also allow different interpretations of the Sp1-Nf-y and Sp2-Nf-y interactions . Sp1 and Sp3 ChIP-seq peaks locate to GC boxes that are often accompanied by Nf-y binding sites ( see Fig . 2 ) strongly suggesting that Sp1/Sp3 and Nf-y co-bind to neighboring sites in the genome . This is consistent with earlier reports showing synergistic activation by Sp1 and Nf-y and a direct interaction between Sp1 ( and Sp3 ) and Nf-ya [30 , 31 , 32] . In contrast , the majority of Sp2 locates at CCAAT boxes and binding is independent of the presence of a nearby GC box , and , most importantly , independent of the zinc finger domain . The localization of Sp2 at CCAAT motifs led us to detail the interaction network between Sp2 and Nf-y on a genome-wide scale . The arrangement of CCAAT motifs in regions that are bound by both factors differ from sites that are bound by Nf-y but not by Sp2 . Sp2-Nf-y interactions occur predominantly at tandem CCAAT boxes , whereas single CCCAT boxes are mostly bound by Nf-y but not by Sp2 . Utilizing Sp2ko cells lacking any Sp2 DNA-binding activity , and an RNAi approach to interfere with Nf-y binding , we have explored the interaction between Nf-y and Sp2 recruitment in an unbiased manner . Genomic binding analysis revealed a widespread attenuation of Nf-y loading in cells lacking Sp2 . Vice versa , reduced binding of Nf-y led to attenuation of Sp2 binding . Importantly , the reduction of Sp2 binding is specific to elements that are also bound by Nf-y , thereby providing support for a direct effect of Nf-y at shared sites . Given that multiple CCAAT boxes in a promoter region are simultaneously occupied by Nf-y , the particular placement of Nf-y complexes might be essential for direct or indirect interactions with Sp2 . In line with this , we observed a general agreement between the strength of the Sp2 ChIP-seq signals and the number of CCAAT motifs . Particularly , the strongest Sp2 peaks contain several pairs of CCAAT motifs . In a recent publication it was shown that Nf-y promotes binding of pluripotency transcription factors such as Oct4 or Sox2 at enhancers in murine ES cells by facilitating a permissive chromatin conformation [33] . Nf-y´s role in promoting the binding of Sp2 could be by a similar mechanism . However , unlike the pluripotency factors , Sp2 also potentiates binding of Nf-y at sites of co-localization . Whether Sp2 facilitates recruitment of Nf-y or whether it stabilizes binding of Nf-y at shared sites remains elusive at this stage . The mode of interaction between different transcription factors has been classically categorized into DNA-binding dependent ( co-binding ) and DNA-binding independent , whereby one transcription factor binds to another that , in turn , binds to DNA ( tethering ) . Tethering to chromatin has been reported for several transcription factors including recruitment of the glucocorticoid receptor by AP1 [34 , 35] or STAT3 [36] and the estrogen receptor alpha by Runx1 [37] . Likely , tethering mechanisms are also involved in the recruitment of SCL/TAL1 [38] and KLF3 [39] to a subset of their binding sites in vivo . The sequence adjacent to CCAAT boxes at which Sp2 is located is highly variable and does not contain a particular sequence motif . Consistently , the N-terminal region of Sp2 does not contain an obvious structural motif that might interact with a specific DNA sequence . It can be proposed that Nf-y binds to the CCAAT box through base-specific contacts . Sp2 would then be recruited by interaction with Nf-y or with additional factors . However , this simple tethering model does not explain the attenuated binding of Nf-y in Sp2ko cells at shared sites ( Fig . 9 ) , and the exceptionally large Sp2 ChIP-seq peaks and high ChIP-qPCR values ( more than 10% of input on highly occupied promoters; see Figs . 3 , 5 , 9 ) particularly as formaldehyde preferentially crosslinks proteins to DNA . Therefore , we envisage an alternative mechanism . Potentially , promoters bound by Nf-y , particularly those bound by two or more Nf-y complexes , adopt a particular conformation that allows the basic N-terminal region of Sp2 to interact , directly or indirectly , with two Nf-y complexes simultaneously , and additionally with the DNA backbone in a sequence-independent manner ( Fig . 10 ) . Such a scenario would explain the mutual dependency of Sp2 and Nf-y binding to common sites . Finally , a small fraction of the Sp2 binding sites does not contain CCAAT boxes and are not co-occupied by Nf-y . Nevertheless , binding of Sp2 to these sites is also mediated by the N-terminal region suggesting that binding of Sp2 to these sites is by a similar mechanism . De novo motif discovery at these sites revealed enrichment of the Ets transcription factor-binding motif GGAAG . Future work aims to identify the Ets factor that occupies these sites . A promising candidate is the widely expressed heterodimeric Ets transcription factor Gabp [40] that binds as a GABPalpha2beta2 heterotetramer complex to DNA containing two tandem GGAAG sites [41] . In conclusion , the data provided in this report challenge the prevailing view that the transcription factors Sp1/Sp3 and Sp2 regulate transcription by binding to similar promoter elements via their zinc finger domains . Instead , Sp1/Sp3 and Sp2 have distinctive binding landscapes , and their modes of genomic binding site selection are completely different . Collectively , our findings uncover strikingly different recruitment mechanisms of very similar transcription factors , and add another crucial level of detail to the current model of transcription factor binding to chromatin .
For Western blotting and ChIP of Sp1 , Sp2 and Sp3 in MEFs , we used homemade rabbit antibodies [7 , 42] affinity-purified against the respective recombinant Sp factor . Anti-Sp3 antibodies ( Santa Cruz , sc-644 ) were used for the Western blot shown in Fig . 3B , and anti-Sp2 antibodies ( Santa Cruz , sc-643 ) for ChIP-seq of Sp2 in HEK293 cells . Additional antibodies: Anti-Nf-ya ( Santa Cruz , sc-10779 ) , anti-Nf-yb ( Genespin , PAb001 ) , anti-Nf-yc ( Santa Cruz , sc-7715-R ) , anti-Flag M2 ( Sigma , F3165 ) , anti-Tubulin ( Millipore , MAB3408 ) . Retroviral expression plasmids for 3xFlag-Sp2 and 3xFlag-Sp3 mutants were generated by restriction cloning of PCR fragments into a pBABE3xFlag-puro plasmid . Primer sequences used for PCR can be found in S1 Table . The production of virus stocks , infection of MEFs and the selection of transduced Sp2ko and Sp3ko MEFs were as described [7] . MEFs were cultured in a 1:1 mixture of Dulbecco’s modified Eagle’s medium—high Glucose ( PAA ) and HAM’s F-10 ( PAA ) supplemented with 10% ( v/v ) fetal calf serum ( PAA ) and 1% Penicillin-Streptomycin . Wild type and Sp3ko MEFs , and MEFs with floxed Sp2 alleles ( Sp2fl/fl ) were isolated from E13 . 5 embryos using standard methods and subsequently immortalized by serial passages . Sp2ko MEFs were obtained by retroviral transduction of pBABE-Cre-neo as described [7] . Sp2ko MEFs have severely impaired proliferation rates [7] . Cells that escaped growth inhibition over time were used for rescue experiments . Immunofluorescence and microscopy was performed as described [43] . In brief , 5x104 MEF cells expressing 3xFlag-Sp2 mutants were grown on coverslips in 6-well plates overnight . Cells were fixed in 4% PFA/PBS for 25 min , permeabilized in 0 . 2% TritonX-100/PBS for 20 min , and blocked with 3% BSA/PBS for 1 hr . Incubation of the anti-Flag M2 antibody ( Sigma , F3165 , 1:800 dilution ) was for 1 hr at RT . Secondary antibody incubation ( anti-mouse AlexaFluor568 , Invitrogen , A10037 , 1:500 dilution ) was performed for 1 hr at RT in the dark . After a final washing step , coverslips were mounted onto glass slides using Vectashield mounting medium with DAPI ( Vector Laboratories , Inc . ) . For RNAi-mediated depletion of mouse Nf-ya , Nf-yb and Nf-yc , pools of four On-target plus siRNAs ( GE Dharmacon ) were used ( LU-065522 , LU-046072 , LU-060374 ) . The siGenome non-targeting siRNA #1 ( D-001210–01 ) was used as unspecific siRNA control . Wild type MEFs on 15 cm plates were transfected with 24 nM siRNA using Oligofectamine ( Invitrogen ) . Three days post-transfection 2x106 cells were replated , and transfected a second time . Additional three days later , cells were collected and cross-linked chromatin was prepared . To monitor knockdown efficiency at the protein level , a chromatin sample was incubated with an equal amount of 2xLaemmli buffer at 100°C for one hour and subsequently analyzed by western blotting . To monitor knockdown efficiency at the transcript level , RNA was isolated using the RNeasy Mini kit ( Qiagen ) and expression of Nf-ya , Nf-yb and Nf-yc was analyzed by RT-qPCR . Expression analysis by quantitative RT-qPCR was performed as described in [44] using gene-specific primers ( S1 Table ) . ChIP experiments were performed as described [18] using the One Day ChIP kit ( Diagenode ) . For a sequential ChIP of Sp2 and Nf-yb , the precipitated material of a standard ChIP was eluted twice from the beads with 100 mM NaHCO3 , 1% SDS , 10 mM DTT for 30 min at 37°C . Eluates were diluted 1:50 with ChIP buffer and subsequently subjected to a second ChIP in accordance with the One Day ChIP kit manual performing an overnight antibody incubation at 4°C . Enrichment was calculated relative to the input of the first ChIP . Primer sequences for ChIP-qPCRs are listed in S1 Table . For ChIP-seq experiments , four to six individual ChIPs were pooled , and precipitated DNA was purified on QIAquick columns ( Qiagen ) . Five nanograms of DNA were used for indexed next generation sequencing library preparation using the MicroPlex library preparation kit ( Diagenode ) in accordance with the manufacturer’s instructions . Library purification was performed with AMPure magnetic beads ( Beckman Coulter ) as described in the MicroPlex kit manual . Libraries were quantified on a Bioanalyzer ( Agilent Technologies ) and subsequently sequenced on an Illumina HiSeq1500 platform , rapid-run mode , single-read 50 bp ( TruSeq Rapid SR Cluster Kit—HS , TruSeq Rapid SBS Kit—HS—50 cycle ) according to manufacturer´s instructions . An overview of the various ChIP-seq results is shown in S2 Table . Raw ChIP-seq data were aligned to the mouse genome assembly mm10 or the human genome assembly hg19 using Subread 1 . 3 . 3-p3 [45] . Reads were filtered to have at most 5 mismatches to the reference , indels up to 5 bp and to occur at exactly one position in the genome . Peak calling was performed using MACS 1 . 4 [46] with default parameters . Raw and normalized ( to 1 million uniquely aligned reads ) read counts were annotated , and peaks were filtered to have at least 30 raw reads and a signal to background ( IgG , Sp2ko or Sp3ko ) normalized read ratio of at least 3 . Further analysis of peaks such as association with transcripts in the vicinity , classification of genomic position and Venn diagram generation was performed using a custom Python based pipeline . Genome annotation data from Ensembl revision 74 [47] was used . Position and characteristics of ChIP-seq peaks are listed in S3 Table . Venn diagrams were calculated by building the union of the datasets involved , and assigning each union-peak to a region by requiring at least a one-basepair overlap with the input regions . De novo motif search including central motif analysis [21] was performed with MEME-ChIP version 4 . 9 . 1 [48] using sequences surrounding peak summits ( +/- 150 bp ) . Elongating reads by 200 bp , and determining the position of highest overlap defined summits . Raw sequencing data were deposited at ArrayExpress under accession number E-MTAB-2970 . | A major question in eukaryotic gene regulation is how transcription factors with similar structural features elicit specific biological responses . We used the three transcription factors Sp1 , Sp2 and Sp3 as a paradigm for investigating this question . All three proteins are ubiquitously expressed , and they share glutamine-rich domains as well as a conserved bona fide zinc finger DNA binding domain . Yet , each of the three proteins carries out unique functions in vivo , and each is absolutely essential for mouse development . By genome-wide binding analysis , we found that Sp1 and Sp3 on the one hand , and Sp2 on the other hand engage completely different protein domains for their genomic binding site selection . Most strikingly , the zinc finger domain of Sp2 is dispensable for recruitment to its target sites in vivo . Moreover , we provide strong evidence that the histone-fold protein Nf-y is necessary for recruitment of Sp2 . Conversely , Sp2 potentiates Nf-y binding showing that binding of Sp2 and Nf-y to shared sites is mutually dependent . Our findings uncover an unexpected mechanistic diversity in promoter recognition by seemingly similar transcription factors . This work has broader implications for our understanding of how members of other multi-protein transcription factor families could achieve specificity . | [
"Abstract",
"Introduction",
"Results",
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"Materials",
"and",
"Methods"
] | [] | 2015 | Zinc Finger Independent Genome-Wide Binding of Sp2 Potentiates Recruitment of Histone-Fold Protein Nf-y Distinguishing It from Sp1 and Sp3 |
High-frequency oscillations ( above 30 Hz ) have been observed in sensory and higher-order brain areas , and are believed to constitute a general hallmark of functional neuronal activation . Fast inhibition in interneuronal networks has been suggested as a general mechanism for the generation of high-frequency oscillations . Certain classes of interneurons exhibit subthreshold oscillations , but the effect of this intrinsic neuronal property on the population rhythm is not completely understood . We study the influence of intrinsic damped subthreshold oscillations in the emergence of collective high-frequency oscillations , and elucidate the dynamical mechanisms that underlie this phenomenon . We simulate neuronal networks composed of either Integrate-and-Fire ( IF ) or Generalized Integrate-and-Fire ( GIF ) neurons . The IF model displays purely passive subthreshold dynamics , while the GIF model exhibits subthreshold damped oscillations . Individual neurons receive inhibitory synaptic currents mediated by spiking activity in their neighbors as well as noisy synaptic bombardment , and fire irregularly at a lower rate than population frequency . We identify three factors that affect the influence of single-neuron properties on synchronization mediated by inhibition: i ) the firing rate response to the noisy background input , ii ) the membrane potential distribution , and iii ) the shape of Inhibitory Post-Synaptic Potentials ( IPSPs ) . For hyperpolarizing inhibition , the GIF IPSP profile ( factor iii ) ) exhibits post-inhibitory rebound , which induces a coherent spike-mediated depolarization across cells that greatly facilitates synchronous oscillations . This effect dominates the network dynamics , hence GIF networks display stronger oscillations than IF networks . However , the restorative current in the GIF neuron lowers firing rates and narrows the membrane potential distribution ( factors i ) and ii ) , respectively ) , which tend to decrease synchrony . If inhibition is shunting instead of hyperpolarizing , post-inhibitory rebound is not elicited and factors i ) and ii ) dominate , yielding lower synchrony in GIF networks than in IF networks .
Fast oscillations ( 30–100 Hz and higher ) have been observed in several brain areas , and have been proposed as a general substrate of neural computation [1]–[4] . Several decades of intense investigations , using both experimental [5] , [6] and theoretical [7]–[13] approaches , have provided a detailed picture of how high-frequency oscillations are generated and modulated in the brain . Nevertheless , how intrinsic , single-cell dynamical properties affect high-frequency oscillations , and through which mechanisms , is only partially understood . In particular , most theoretical studies have focused on the mechanisms of collective synchronization in the regime where individual neurons fire regularly and can be considered as quasi-periodic oscillators [14]–[17] . However , cortical neurons in vivo generally exhibit highly variable spiking activity [18] . As we show in this study , the intrinsic neuronal properties that are more important for the generation of collective oscillations depend critically on the dynamical regime where individual neurons operate . Experimental and theoretical work demonstrated a key role for inhibitory interneurons in the generation of high-frequency oscillations [19] . In particular , application of metabotropic glutamate agonists in vitro in appropriate doses can elicit gamma oscillations which are robust to pharmacological suppression of fast glutamate-dependent excitation , but not of fast inhibition [6] ( note , however , that some level of phasic excitation is generally required for gamma rhythmicity elicited by cholinergic or kainate agonists; see for example [20] , [21] ) . Even more direct evidence comes from optogenetic experiments , where selective activation of fast-spiking interneurons has been shown to enhance gamma oscillations in vivo [22] , [23] . Interneurons in the cortex and hippocampus are present in several subtypes , characterized by specific molecular , electrophysiological and dynamical properties , as well as postsynaptic cellular and subcellular targets [24] , [25] . In particular , parvalbumin-positive fast-spiking basket cells have been shown to be causally related to the emergence of gamma oscillations [22] . These neurons are endowed with specific synaptic and intrinsic mechanisms that make them especially suitable for eliciting the temporally precise trains of Inhibitory Post-Synaptic Potentials ( IPSPs ) that are required for the generation of gamma oscillations [26] . Remarkably , they often exhibit intrinsic subthreshold oscillations or resonance in the gamma range , which have been attributed to the interplay between a persistent sodium conductance and a delayed-rectifier potassium conductance [27] . Intrinsic , single-cell oscillations have been observed in a variety of cell types [28] , [29] , including several types of inhibitory interneurons [27] , [30]–[34] . Subthreshold oscillations have been proposed as a dynamical substrate for several computations at the single neuron level , including band-pass filtering [35] , [36] , recognition of temporally precise sequences of inputs [37] , [38] and differential regulation of incoming connection strengths through spike timing-dependent plasticity rules [39] . Like pacemaker neurons in central pattern generators , it has been suggested that neurons with subthreshold oscillations play a key role in rhythmogenesis [40] . Being endowed with an intrinsic rhythm , just a few of these neurons can entrain a population of ( mostly ) passive cells to oscillate coherently through synaptic and/or ephaptic coupling . However , it has long been known that network oscillations can be produced even if individual neurons lack any oscillatory property , as a result of chemical and/or electrical synaptic interactions [41] , [42] . Previous work has assessed the influence of single-cell intrinsic dynamics on network activity in the regular firing regime , where each neuron fires repetitively with little variation across cycles [14]–[17] . In this regime , Phase Response Curve ( PRC ) theory provides a suitable framework for the prediction of network activity from the dynamical characteristics of constituent neurons [43] , [44] . The PRC of a regularly spiking neuron quantifies the phase shift that results from an infinitesimal perturbation as a function of the phase of the cycle at which the perturbation is applied . The shape of the PRC depends on the geometry of the limit cycle corresponding to tonic , regular spiking . However , cortical neurons in vivo generally exhibit highly variable spiking activity [18] . They dwell most of the time in the subthreshold regime and are driven beyond threshold by random fluctuations in their inputs . This variable activity at the single-cell level can nevertheless result in coherent , regular oscillations at the collective level [9] , [10] . Features of the collective oscillations can be quantitatively predicted from the phase response of the neuronal and synaptic dynamics in the case of sinusoidal oscillations [9] , [10] and also in the case of fully-developed , non-linear oscillations in networks of IF neurons driven by heterogeneous levels of DC currents [45] . The dynamical mechanisms by which intrinsic oscillations at the single-cell level affect global network oscillations are very different depending on the dynamical regime in which individual neurons operate . If individual neurons fire in each cycle of the collective oscillation ( i . e . , in the mean-driven regime ) , the geometry of the single-cell periodic attractor corresponding to the regular spiking regime enables one to predict and understand the population rhythm , as exemplified by the important insights provided by Phase Response Curve theory . However , if individual neurons fire irregularly ( i . e . , in the fluctuation-driven regime ) , and only take part in a subset of population cycles , the geometry of the regular spiking regime becomes less relevant , as neurons dwell most of the time in the subthreshold range . In this study , we show how intrinsic neuronal oscillations at the subthreshold level affect the generation and properties of collective high-frequency oscillations . We focus on a regime where individual neurons fire irregularly at a rate that is considerably lower than the frequency of network oscillations . For simplicity , and considering the key role of synaptic inhibition in gamma rhythmogenesis , we consider purely interneuronal networks . Individual units receive spatially independent and noisy background inputs , thus mimicking an activated state of neuronal processing [46] . This is a key difference with respect to previous theoretical investigations on this topic , which poised individual neurons in the regular firing regime and neglected the effects of the strong barrages of background synaptic activity , which are expected to be prominent in vivo . As we will soon make clear , the influence of single-cell dynamics on network activity in a realistic context can only be thoroughly understood if the interplay with extrinsic inputs from other brain regions is taken into account . Our network models can exhibit sinusoidal oscillations , as well as fully-blown , non-linear oscillations with highly synchronous firing . While we have studied a broad parameter space , our main focus is on the latter regime , as it more closely resembles the highly synchronous firing of basket interneurons during gamma-activated states in the cerebral cortex [19] . The presence of subthreshold oscillations affect several dimensions of single-cell dynamics . In response to a synaptic background bombardment , the restorative effect of a resonant current lowers firing rates and narrows the membrane potential distribution around the resting potential . Importantly , subthreshold oscillations change the functional coupling between neurons , i . e . the shape of post-synaptic potentials , and can result in post-inhibitory rebound depolarization . Some of these effects tend to enhance collective oscillations , while others tend to impair them . The adoption of neuron models with a fixed voltage threshold for spike generation enables us to disentangle these different effects . By independently varying the statistics of background inputs and the voltage threshold for spike generation , we can compare neuronal models that only differ along a single dimension of neuronal dynamics ( e . g . , in the presence of subthreshold damped oscillations , in conditions of equal firing rate response to the noisy background ) , hence elucidating the specific contribution of different features of single-cell dynamics that affect collective rhythmogenesis . In this work , we adopt neuron models that linearly describe the subthreshold dynamics , where action potential generation is implemented via a voltage threshold-crossing reset: the Integrate and Fire ( IF ) and the Generalized Integrate and Fire ( GIF ) . These neuron models only differ in their subthreshold dynamics , which is purely passive in the IF , while it exhibits subthreshold damped oscillations in the GIF . Importantly , they both exhibit type I PRC ( inhibitory perturbations always result in phase delay ) if made to fire regularly via the injection of a constant depolarizing curve ( see section “Phase Response Curves in the IF and GIF neuron” and Figure S1 in Text S1 ) . Correspondingly , when these neurons are coupled in a network by inhibition , the emerging collective dynamics only differ consistently when neurons are poised in the irregular , fluctuation-driven regime , but not when they are made to fire regularly in a mean-driven regime . While signalling is traditionally considered to be hyperpolarizing in the adult brain , it can be shunting or slightly depolarizing in some brain regions and neuron types [47] , [48] . Shunting inhibition precludes post-inhibitory rebound depolarization . In these conditions the effects of firing rate and depolarization responses dominate the dynamics , yielding stronger oscillations in networks of purely passive neurons . Synchrony and oscillations are dissociable concepts . Collective oscillations are possible in the absence of synchrony; for example , they can emerge as sinusoidal oscillations in the vicinity of a Hopf bifurcation [9] . In addition , synchronous firing can be observed in the absence of network oscillations , when neurons take part in population spikes that occur non-periodically [49] . In the networks considered in this study , synchronous collective oscillations are produced; hence , the two terminologies are used interchangeably .
We consider a network of inhibitory neurons with all-to-all connectivity and equal weights . Neurons are placed on the vertices of a 2D uniform grid of size 1 with periodic boundaries ( a torus ) . Hence , every neuron is associated with a pair of values , included in the unit square , denoting its relative spatial position . The distance between a pair of neurons located at and is calculated as ( 1 ) where and . As opposed to excitatory connections , which decay with distance in probability and strength , inhibitory connections have been shown to be independent of distance in a small cortical patch [50] . Hence , in our models , synaptic weights are equal for each pair of cells , and the topology is enforced by distance-dependent delays alone . Neuronal signals propagate with a conduction speed of 0 . 141 m/s , in accordance with experimental results in unmyelinated fibers supporting local , horizontal synaptic connections in cats and monkeys [51] , [52] . is taken to be equal to 400 , which constitutes approximately 10% of the number of basket cells ( an interneuronal type critically involved with high-frequency oscillations ) in the dorsal hippocampus of the rat [53] . The adoption of a toroidal topology with all-to-all connectivity and equal synaptic strengths enables us to exploit the symmetry of the network and average the bivariate measures we consider over pairs of neurons separated by the same distance ( see subsection “Measures” ) . This enables us to obtain precise estimates with reasonable computational cost . At the same time , both theoretical considerations as well as our own numerical simulations suggest that a network with sparse connectivity would yield the same qualitative results , because sparsity does not change the dynamic behavior of the network but just increases the level of finite-size effects ( see , for example , [42] ) . Individual neurons are described either as Integrate and Fire ( IF ) or Generalized Integrate and Fire ( GIF ) . Both models adopt a linear description of the subthreshold dynamics , which is one-dimensional for the IF and two-dimensional for the GIF , and a threshold-based spike generation mechanism . The subthreshold dynamics are based on analogies with linear electric circuits ( RC for the IF , RLC for the GIF ) , a formalism with a long and successful history in the phenomenological characterization of neuronal dynamics ( for some early examples , see [54]–[57]; for a recent review , see [58] , [59] ) . In the case of the IF , the voltage variable v , which measures the membrane potential deviation from the leak reversal potential , evolves according to the differential equation ( 2 ) where C is the membrane capacitance and g is the leak conductance . represents the inhibitory synaptic current resulting from action potential generation in other neurons of the network , and is a background term representing synaptic inputs from other brain areas not explicitly modelled . The subthreshold dynamics in the GIF includes an additional dynamical variable w , which represents the linearized effect of voltage-gated ion currents: ( 3 ) where and are the conductance and time constant associated with the w variable , respectively . The models are endowed with an after-spike reset mechanism , so that when v crosses a threshold from below a spike is emitted , the membrane potential is reset to a value , and kept there for a refractory time . We set below the leak reversal potential , in accordance with the observation of after-hyperpolarization in PV basket cells [27] . Our canonical parameter set corresponds to a membrane time constant of 10 ms in both models , and a period of intrinsic subthreshold oscillations of ∼31 ms ( ∼32 Hz ) in the GIF neuron , in accordance with the frequency of intrinsic subthreshold oscillations measured in fast-spiking inhibitory interneurons in the mammalian cortex and hippocampus ( 10–50 Hz [27] , [30] ) . In the absence of external inputs , the IF responds to an instantaneous perturbation with an exponential relaxation to rest with rate g . Hence , it provides a simple description of purely passive subthreshold dynamics . In a certain parameter subspace ( which includes the parameter set used here ) , the system ( 3 ) is characterized by a pair of complex conjugate eigenvalues ( see the Appendix in Text S1 ) . Therefore , the GIF neuron responds to perturbations with damped oscillations , and constitutes an analytically amenable model for the description of neuronal intrinsic oscillations , i . e . , oscillations generated by intrinsic ionic mechanisms as the activation of a resonant current or the inactivation of an amplifying current [29] . These phenomenological models can be considered as linear approximations ( one-dimensional in the case of the IF neuron , two-dimensional in the case of the GIF neuron ) of more general neuronal models ( see , for example , [35] ) . In fact , the only requirement that a detailed neuron model must satisfy for this approximation to be valid is the presence of a stable fixed point , where the Jacobian of the whole system is evaluated in order to obtain the coefficients of the corresponding IF or GIF description . This linear approximation is guaranteed to be valid in a small neighborhood of the stable fixed point . and represent the synaptic current from other interneurons in the network , and the background input from other brain regions and other interneuronal types that are not explicitly modelled ( e . g . , somatostatin-positive Martinotti cells ) and are described below . Parameter values and descriptions are provided in Table 1 . Synaptic coupling is described as ( 4 ) ( 5 ) where is the global inhibitory conductance impinging on the current neuron and is the sequence of spike times generated by neuron i . Synaptic transmission is delayed by distance-dependent and distance-independent components and , where is the distance between the current neuron and neuron i ( calculated according to ( 1 ) ) , s is the axonal propagation speed , and accounts for non-instantaneous processes at synaptic contacts . When a presynaptic pulse reaches the postsynaptic neuron , the synaptic conductance increases instantaneously by a value , and then decreases exponentially to zero with time constant . The corresponding synaptic current is then obtained by multiplication with the difference between the voltage variable and the reversal potential for inhibition . Unless stated otherwise , simulations are performed with the parameter values reported in Table 1 . Every neuron receives a spatially independent background term , which is composed of an excitatory and an inhibitory component with associated reversal potentials and : ( 6 ) The background time-varying conductances are described as rectified Ornstein-Uhlenbeck processes with mean , standard deviation ( SD ) , and autocorrelation time constant ( x = inh , exc ) : ( 7 ) ( 8 ) where is Gaussian white noise with zero mean and unit standard deviation . We maintain a fixed ratio between the background inhibitory and excitatory conductance , both in terms of mean values and variability ( unless stated otherwise ) . That is , and . We choose k = 5 and = 2 . 5 as canonical values , in accordance with in vivo estimates [60] . Isolated neurons respond to the synaptic bombardment with irregular firing at relatively high rates ( GIF: 74 Hz , Inter-Spike Interval coefficient of variation ( ISI CV ) = 0 . 78; IF: 90 Hz , ISI CV = 0 . 81 ) . Table 1 reports descriptions and canonical values for all parameters . Model equations ( 2 ) and ( 3 ) are integrated with a sixth-order , fixed step-size Runge-Kutta algorithm , with time step = 0 . 01 ms . The threshold-crossing and refractoriness conditions are evaluated only once per time step , as well as the calculation of synaptic currents according to equations ( 4 ) and ( 5 ) . The background conductances and are updated at each time step using the properties of Ornstein-Uhlenbeck processes . That is , is normally distributed with mean and standard deviation . We initialize the networks randomly and discard the initial transient . We focus on the steady-state dynamics , that is , on the regime in which the statistical properties of network dynamics are time-invariant . This regime is typically reached within a few tens of milliseconds . However , transients can be longer for certain parameter sets that are close to the onset of collective oscillations . Hence , we discard the first 2 s of simulation time to ensure that any initial transient is excluded from the analysis . Neuronal network activities are quantified using several measures at the individual , pairwise and collective levels .
Before we consider the dynamics of networks of neurons coupled by inhibitory conductances , it is instructive to characterize how individual neurons respond to the background noisy input alone , which represents input from other brain areas and is the main source of depolarization and variability in the model . Hence , we performed a linear analysis of the eigenvalues of the model neurons with fixed external conductances ( with ) . Figure 1 shows the effect of the background conductance on the resting potential , effective membrane time constant and effective intrinsic frequency for the canonical ratio between background inhibition and excitation ( k = 5 ) , and the effect of the background inhibition-to-excitation ratio k for the canonical value of the background excitatory conductance ( ) on these same quantities . The resting potential is defined as the voltage satisfying in equations ( 2 ) ( IF ) or ( 3 ) ( GIF ) , while the effective membrane time constant and the effective intrinsic frequency are defined from the eigenvalues of the systems ( 2 ) or ( 3 ) as and , respectively . Full expressions are reported in the Appendix , Text S1 . When background inhibition and excitation are balanced at the canonical ratio k = 5 , the resting potential is above zero but below threshold even for very large values of the background conductance ( Figure 1A ) . In this regime , spiking is irregular and is induced by random fluctuations in the background conductances . The injection of background noisy conductances mimics an activated state of the neuronal microcircuit , and decreases the effective membrane time constant , as previously reported [66] , [67] ( Figure 1B ) . In addition to this , we observe a decrease in the resonant frequency with increasing background drive in the GIF , which eventually results in a purely passive dynamics for ( Figure 1C ) as the canonical GIF eigenvalues coalesce onto the real axis . Varying the background inhibition-to-excitation ratio k shifts the resting potential and the membrane potential distribution ( Figure 1A , see also Figure 5A ) . The shift is greater in the IF neuron because the additional dynamical variable in the GIF counteracts voltage changes away from zero . If all the other parameters are held fixed , the depolarization of the membrane potential distribution induced by a decrease in k also translates to an increase in the mean firing rate . However , the adoption of neuron models with a fixed voltage threshold for spike generation enables one to adjust the threshold in order to maintain a desired rate of firing for each value of k and for both neuron models considered . As a consequence of the changes in membrane time constant and oscillation frequency , Inhibitory Post-Synaptic Potentials ( IPSPs ) in the presence of constant background conductances are smaller and narrower ( Figure 1D ) . In the case of the GIF , intrinsic oscillations are more strongly damped and exhibit a lower frequency . We consider the activity generated by a network of identical spiking neurons with all-to-all inhibitory connectivity . Coupling is delayed by a distance-dependent component , mimicking axonal propagation delays , and a distance-independent component that accounts for non-instantaneous dynamics at synaptic contacts . In addition to inhibitory conductances elicited by action potentials generated in their peers , individual neurons also receive random and spatially independent background synaptic conductances . In the absence of coupling , the background synaptic bombardment sets the neurons in an irregular firing regime . In a broad range of parameter space , network oscillations are produced at high frequency ( ∼100 Hz ) . As inhibitory coupling and background inhibition-to-excitation ratio are varied , oscillation strength and single-cell firing rates are modulated . However , the frequency of network oscillations is only slightly affected , with stronger coupling and lower depolarization resulting in slower collective oscillations , as previously reported in modelling and experimental studies [7] , [68] . While we have varied most parameters in ranges that are in accordance with physiological data , we choose a representative parameter set that corresponds to fully developed , yet unsaturated , oscillations in the GIF network . The results we report in this section refer to the canonical parameter set , while the effects of variations in the inhibitory coupling and/or in the background inhibition-to-excitation ratio k are reported in section “Effects of rate , membrane potential distribution and coupling on synchrony” . Figure 2 shows representative activities generated by a network composed of GIF neurons ( left panels ) , or IF neurons ( right panels ) . It is apparent from both the traces ( top rows ) and the raster plots ( middle row ) that the GIF network exhibits more prominent oscillations ( quantified in Table 2 ) . In this network , oscillations are fully developed and there are narrow temporal windows in between volleys of activity during which almost no spike is produced . The IF network also produces oscillations , but in this case , the firing probability in between peaks of activation does not completely vanish . Membrane potential trajectories of individual neurons are also more strongly correlated in the GIF network , with downward deflections corresponding to peaks of inhibitory drive showing greater correspondence across cells . Individual neurons fire irregularly at a rate that is much lower than the frequency of collective oscillations . As shown in Figure 2C and D , single-neuron ISI histograms are multipeaked . The first peak corresponds to the population period , and lumps the contribution of pairs of spikes emitted by the same cell in adjacent cycles . Subsequent peaks are gradually smaller and occur at integer multiples of the population period . The mean ISI is about 4 times greater than the population period . The envelope of the distribution resembles an exponential distribution , a signature of irregular , Poisson-like spiking . The periodic modulation of excitability is more prominent in the GIF network , where the ISI probability vanishes almost completely in between peaks . A small peak is discernible at very short ISIs , just longer than the refractory period . This peak lumps the contribution of spike doublets emitted by the same cell in the same cycle . These events are much more likely in the IF network , where oscillations are not fully developed and inhibitory volleys are not strong enough to completely preclude spiking during the inactive phase of the oscillation . The higher synchrony exhibited by the GIF network corresponds to higher firing rates: just before the onset of a population spike , inhibition vanishes almost completely , and this allows for a greater number of neurons to reach threshold and take part in the population spike . Conversely , in the IF network , there is a residual amount of inhibition that is present even at the trough of inhibitory volleys . This tonic component results in a smaller number of cells taking part in the population spike . The inclusion of an additional dynamical variable w in the GIF model , which implements a restorative force on the membrane potential dynamics , induces several changes in the neuronal response to background synaptic bombardment or isolated synaptic potentials . The dynamical variable w counteracts voltage changes , hence the GIF neuron exhibits a narrower membrane potential distribution , lower firing rates and lower firing variability . Firing rates have a strong influence on the level of synchronization that can be achieved in the coupled network , as higher firing rates induce inhibitory conductances of greater amplitude that more effectively drive the membrane potential near the reversal potential of inhibition at each inhibitory peak of the oscillation . In order to elucidate the influence of firing rate changes in the observed differences in synchronization between GIF and IF networks , we considered an additional pair of models: r-matched GIF and r-matched IF . The r-matched GIF ( r-matched IF ) neuron is equal to the GIF ( IF ) neuron , except for the voltage threshold for action potential generation , which has been adjusted in order to yield the same firing rate response as the IF ( GIF ) neuron to the synaptic background bombardment . As shown by a power spectrum analysis of population activity ( Figure 3 ) , GIF neurons synchronize more in spite of the lower firing rate response to the noisy background exhibited by this model . In fact , the r-matched GIF , which displays the same firing rate response to the background as the IF , exhibits even stronger oscillations . Likewise , the r-matched IF neuron , whose firing rate response has been decreased to match the GIF , synchronizes more weakly than the canonical IF . Oscillation frequency depends only weakly on the synchronization level , with higher synchrony corresponding with faster oscillations . Single-cell firing statistics and network oscillation measures for the four model networks considered are reported in Table 2 .
The adoption of a network model with spatial extension enables one to study the spatial modulation of synchrony in the network activity . From a theoretical perspective , we expect that spatial modulation will be affected by two opposing influences . Neurons that are located nearby will experience similar patterns of incoming PSPs , because the coupling delays from any other neuron in the network will be similar . This is expected to increase synchrony among local pairs of neurons . However , nearby neurons are connected by rapid inhibition with short propagation delays . Hence , if the propagation delays among adjacent neurons are shorter than the temporal width of a population spike , this will tend to decrease synchrony among local pairs of neurons . In order to quantify the spatial structure of correlations in the inputs that neurons receive , in their internal states , and in the outputs they emit , we calculate average Pearson correlations between synaptic inputs , membrane potential variables , and mean phase coherence among neuron pairs as a function of their distance in the cortical sheet . As shown in Figure 4A , the correlation between synaptic currents to neuron pairs decreases as a function of distance . This is a result that we expect from the topological structure of the network . However , at the level of the membrane potential , correlations between neuron pairs are independent of distance ( Figure 4B ) . This apparent incongruence is resolved if one takes into account the de-synchronizing effect of short-latency mutual inhibition between neurons . In fact , at the suprathreshold level , the synchronous firing of neuron pairs ( as measured by ) decreases at short distances ( Figure 4C ) . This phenomenon highlights a novel aspect of pattern decorrelation by inhibitory feedback [69] , namely that rhythmic mutual inhibition with topologically structured delays can offset the spatial bias of incoming synaptic inputs and yield a flat profile of membrane potential correlations . Strong interneuronal oscillations drive the membrane potential of all neurons to a narrow range near at the peak of the inhibitory drive in each cycle , so that the identity of the neurons that will be active in each cycle will faithfully represent the spatial pattern of inputs and will not be significantly biased by topological aspects . This property allows network activity to closely follow cycle-to-cycle variations in the spatial patterns of incoming stimuli [70] .
We have shown that neurons with subthreshold oscillations synchronize more strongly than passive neurons when coupled by inhibition . However , they also exhibit lower firing rates and less depolarization in response to the background input , and both effects weaken collective oscillations . Hence , the question arises as to what are the intrinsic dynamical mechanisms that enhance oscillations in GIF neurons , in spite of the relative disadvantage resulting from their lower rate and depolarization responses . In this section , we perform a detailed analysis of the intrinsic and synaptic currents flowing through the neuronal membrane at different phases of the oscillation cycle , and show that the synchronization advantage of GIF neurons can be understood as a result of the strong and coherent activation of inward intrinsic currents near the trough of membrane potential oscillations . Figure 6 shows the GIF population rate , along with the membrane potential v , the synaptic current , and the intrinsic current , averaged across neurons , for a few oscillation cycles . The intrinsic current is equal to for the GIF , and to for the IF ( see equations ( 3 ) and ( 2 ) ) . In each cycle , the average membrane potential reaches a peak near the end of the population spike . About a third of a cycle later , the average inhibitory synaptic current reaches a minimum , which then results in a minimum of the average membrane potential as neurons are driven to a small range near the reversal potential of inhibition . After a small lag corresponding to the time scale of subthreshold neuronal dynamics , intrinsic currents peak , facilitating the recovery from inhibition of the average membrane potential , which in turn leads to the next active phase of the oscillation . We reasoned that if inward currents are stronger in GIF neurons near the trough of the membrane potential oscillation , that would constitute a depolarizing force , coherent across neurons , that acts selectively in the later portion of the inactive phase of the oscillation , hence constituting a candidate for a synchronization mechanism . In order to assess the contribution of intrinsic currents to the generation of synchronized oscillations , we estimate the probability density of the intrinsic currents in the GIF and IF networks ( Figure 7 ) . We estimate by using either all available data points ( solid traces ) , or only those data points that fall around the peaks or troughs of the oscillation , as identified by sinusoidal fits to short traces of the average across neurons ( dashed and dotted lines , respectively ) . Figure 7 shows that the distribution of intrinsic currents is broader and more depolarized in the GIF network , and it is more strongly modulated by the population rhythm . Furthermore , the bivariate probability density for the GIF network shows a positive deviation from independence for 12 nA , which indicates that GIF neurons receive a strong depolarizing current which is coherent across pairs ( Figure 8A ) . The main contribution to this depolarizing current comes from the term . As inhibitory synaptic currents peak , individual neurons are brought to a narrow range close to the reversal potential , which activates the restorative variable w providing a post-inhibitory rebound . A positive deviation from independence is also observed in the IF network , albeit for lower ( less depolarizing ) values of the intrinsic currents . If probability densities are conditioned on the oscillation phase , no deviation from independence is observed , suggesting that there are no additional correlations in the intrinsic currents to cell pairs beyond those induced by the population rhythm ( Figure 8C–F ) . Intrinsic currents are more strongly activated in GIF neurons , and they provide a depolarizing force , coherent across neurons , that acts near the end of the inactive phase and greatly fosters oscillations . In addition to this , it is important to recognize that GIF neurons are endowed with an additional dynamical variable w , which actively opposes voltage changes and constitutes a single-cell memory trace of the inmediate past [38] . In IF networks , intrinsic currents only depend on the current value of the membrane potential . This results in a fixed phase relationship between the mean membrane potential and the mean intrinsic current , which are precisely in anti-phase . Conversely , the additional dynamical variable w in the GIF homeostatically adjusts intrinsic currents individually in each neuron on a cycle-by-cycle basis , compensating for transient variations in the input and resulting in more robust and stable oscillations . Figure 9A shows the relative phase of the mean synaptic current with respect to the mean voltage , computed in 20 ms time windows , as a function of the amplitude of the oscillation in the mean voltage in the same window ( see Methods for details ) . The amplitude of the oscillation in the mean voltage can be interpreted as a measure of oscillation strength , and it is strongly correlated to both the amplitude of the oscillation in the mean synaptic current and the amplitude of the oscillation in the mean intrinsic current . While GIF networks exhibit high oscillation strength and small variability in the phase of the mean synaptic current , IF networks exhibit lower oscillation strength and higher phase variability , which increases with poorer synchrony . Phase values for the synaptic current are much more variable in IF than in GIF networks , but their mean values are very similar ( 1 for the GIF , 1 . 02 for the IF ) . Circular-linear correlation analysis reveals that the phase of the mean synaptic current advances with higher synchrony for all networks ( p<0 . 01 ) , albeit less clearly in the case of the r-matched IF network ( p = 0 . 012 ) . Circular-linear correlation values for the four networks considered are reported in Table 3 , along with the corresponding p-values of the null hypothesis of no correlation . A more striking effect of the different intrinsic neuronal properties is observed in the distribution of the relative phase of the mean intrinsic current ( Figure 9B ) . In IF networks , intrinsic currents only depend on the current value of the membrane potential , hence their phase relationship is fixed and equal to . In GIF networks , conversely , intrinsic currents are adjusted on a cycle-by-cycle basis as a function of the recent input history , and peak later in the cycle , when inhibition has waned almost completely and neurons are driven by background inputs and intrinsic currents only . Depending on the background input that is received in the inactive phase of the oscillation , and in particular in its late portion , when the synaptic drive wanes , the intrinsic current will be differentially adjusted in each neuron . Since the intrinsic current in GIF neurons is restorative and tends to oppose voltage changes , its net effect will be a reduction of the variability across neurons in the membrane potential trajectories , which results in a narrower population spike , i . e . enhanced synchrony . The phase mismatch between synaptic and intrinsic currents is a significant indicator of oscillation strength , as shown in Figure 9C . In the IF networks , the mean intrinsic current depends on the mean voltage variable only; hence , the phase mismatch between synaptic and intrinsic currents exhibits the same level of correlation with oscillation strength as the phase of synaptic current . Conversely , in the GIF networks , the phase difference shows a stronger and more significant correlation with local synchronization ( as assessed by the amplitude of the sinusoidal fit to the mean membrane potential ) than , even though the phase of the mean intrinsic current is itself independent of synchrony ( Figure 9B and Table 3 , second row ) . As decreases , intrinsic currents peak later with respect to synaptic currents , and are more effective in bringing together the trajectories of individual neurons in the critical portion of the oscillation cycle that just precedes a population spike . Figure 10 shows the covariation of the mean membrane potential and the mean intrinsic current ( panel A ) , and the covariation of the mean membrane potential and its standard deviation ( panel B , GIF; panel C , IF ) . In the IF neuron ( red line in Figure 10A ) , the intrinsic current only depends on the current value of the membrane potential ( ) . In the GIF neuron ( blue line ) , the additional dynamical variable w implements a cellular memory of the inmediate past . The subthreshold dynamics of the GIF neuron is mathematically equivalent to a damped linear oscillator; hence , the trajectory in the phase plane has an elliptical shape , as expected from a linear oscillator driven by noisy inputs ( mediated by synaptic background inputs ) with an oscillatory component ( mediated by inhibitory currents originated within the network ) . Intrinsic currents are always greater in the GIF neuron , especially for hyperpolarized values of the membrane potential . As the inhibitory synaptic current peaks , the average membrane potential is driven close to , which strongly activates intrinsic inward currents . These act as a coherent depolarizing force across neurons , as the trajectory evolves clockwise in the plane and the network approaches a new active phase of the oscillation . The upward phase of the oscillation , between the trough of the membrane potential oscillation and the subsequent population spike , is a critical time window for the regulation of synchrony , as neurons are progressively released from inhibition and evolve on the basis of the background input and their intrinsic dynamics , with little influence from the local network . In this time frame , GIF neurons experience a particularly strong depolarizing drive from their intrinsic currents mediating post-inhibitory rebound , as the mean intrinsic current in the upper portion of the trajectory is greater than in the lower portion for equal values of the mean membrane potential . This , in turn , results in lower values for the standard deviation of the membrane potential across neurons ( Figure 10 , compare B and C ) , that is , the membrane potential trajectories of individual neurons are closer together; hence , they will cross the threshold for spike generation in a briefer time window , ultimately resulting in higher synchrony . It is worth noting that this synchronization mechanism is different from the resonant synchronization reported for networks of coupled oscillators , where individual neurons fire regularly in each cycle . In the low-noise , mean-driven regime , the amplitude and frequency of collective oscillations strongly depend on the intrinsic frequency of individual oscillators [15] . However , if neurons are poised in the noise-driven , irregular firing regime , the intrinsic frequency of subthreshold damped oscillations have very little effect on the amplitude and frequency of collective oscillations . Rather , it is the amount of damping that most strongly affects oscillation strength , with the more underdamped subthreshold dynamics resulting in stronger oscillations ( see section “Effects of variations in the intrinsic neuronal parameters and in the connection delays on synchrony” and Figure S2 in Text S1 ) . More underdamped subthreshold dynamics imply stronger rebound from inhibition . Hence , this result further highlights the key role played by post-inhibitory rebound as the main dynamical mechanism underlying enhanced synchrony in GIF networks . In some brain regions and neuron types , especially in early stages of development , signalling has been shown to be shunting or depolarizing , rather than hyperpolarizing . That is , GABA reversal potential can be above the leak reversal potential . In particular , mediated inhibition has been shown to be strongly depolarizing in the developing brain [71] , and remains shunting in some interneuron types of the amygdala , cerebellum , CA3 and dentate gyrus even in mature animals [47] , [48] , [72] , [73] . Intriguingly , the polarity of GABA effects could also differ among distinct subcellular compartments [74] , and be modulated on short time scales by activity-dependent mechanisms of chloride homeostasis [75] , [76] . Shunting inhibition has been shown to strengthen collective oscillations in the gamma range in the presence of heterogeneity in the level of excitability across neurons [48] . However , it has been reported that neurons near a Hopf bifurcation are poorly reset by shunting inhibitory pulses [77] . In this section , we investigate how the polarity of inhibitory synaptic potentials affect the mechanisms of gamma rhythmogenesis , and whether subthreshold intrinsic oscillations are expected to enhance collective oscillations if inhibition is shunting . Changes in the reversal potential of synaptic conductances do not affect neuronal eigenvalues , since the systems ( 2 ) and ( 3 ) are linear , but do affect the resting potential in response to constant background input ( see equation ( A-1 ) in the Appendix , Text S1 ) , and hence the distribution of the membrane potential in response to noisy synaptic bombardment . In particular , the resting potential in response to constant background conductances is considerably more depolarized in the IF neuron , as expected from the restorative character of the resonant variable in the GIF neuron ( Figure 11A , compare with the analogous results for hyperpolarizing inhibition shown in Figure 1A ) . As expected from the theoretical considerations and numerical simulations presented above , this difference in membrane potential distribution responses confers a synchronization advantage to the IF neuron , which indeed exhibits stronger synchronization in a broad range of parameter space if inhibition is shunting ( Figure 11B ) . In fact , for the canonical coupling value = 0 . 25 mV , only IF networks exhibit a noticeable level of synchronization ( brown solid curve ) , and only for low values of , which corresponds to greater depolarization and consequently higher firing rates . Stronger coupling results in higher synchrony in canonical IF networks , which saturates and eventually slightly decreases , as previously observed in the case of hyperpolarizing inhibition ( Figure 5B ) . Conversely , GIF networks exhibit appreciable oscillations only for medium to high values of the coupling strength , and only if the voltage threshold has been adjusted to increase their firing rate responses to background inputs to the IF level ( r-matched GIF , blue and light blue dashed lines ) . Even in these conditions , the level of synchrony observed in IF networks is only reached for high values of the coupling strength . This effect is reminiscent of the phenomenon reported by Börgers et al . [77] , who showed that neurons with subthreshold oscillations are poorly reset by shunting inhibitory pulses . The main difference between their approach and ours is that they considered a mean-driven , tonic spiking regime , while we considered a fluctuation-driven regime . In their model , as in ours , volleys of inhibition bring neurons close to the reversal potential of inhibition , which has a synchronizing effect . However , in their model , as inhibition wanes the fixed point ( which is a focus for a neuron with subthreshold damped oscillations ) becomes weakly repelling . As the focus undergoes a bifurcation from weakly attracting to weakly repelling , a “ghost” attractor dominates the dynamics in its vicinity . Hence , small differences in initial conditions between different neurons are amplified , as different neurons might make a different number of turns around the weakly repelling focus before leaving its vicinity and start a new spiking trajectory . This effect is more pronounced in the absence of external noisy inputs , since strong background conductances would move the state variables away from the bifurcating focus , into regions of phase-space with stronger and more directive field . In our model , a slightly depolarized reversal potential for inhibition abolishes post-inhibitory rebound excitation , and actually results in post-excitatory rebound inhibition for those cells with . This situation is observed even if the resting potential ( defined as in section “Single neuron dynamics” as the membrane potential that satisfies in systems ( 2 ) and ( 3 ) with constant background input ) is above , due to the fluctuating nature of background conductances . The hyperpolarizing current resulting from post-excitatory rebound inhibition pushes neurons away from the spiking threshold and enhances the desynchronizing effect of the noisy background input , by lengthening the time window during which cells evolve free from inhibition , driven solely by the incoherent background input . This phenomenon gives GIF networks a synchronization disadvantage with respect to IF networks , in addition to the synchronization disadvantage resulting from smaller firing rate and membrane potential distribution responses to the noisy background input , the latter effects being due to the presence of a restorative current .
Oscillations in the gamma range ( 30–100 Hz and higher ) have been the focus of intense experimental and theoretical work for more than two decades ( reviewed in [1]–[4] ) . Synchronization in that frequency range has been proposed as a physiological substrate of perceptual binding , whereby individual neurons selective to different features that coactivate in the same gamma cycle would signal the coherent perception of those features , i . e . , when those features belong to an object that is perceived as a single entity [78] . Gamma band oscillations are not exclusive to sensory cortices , but have also been observed in high-level decision areas such as the medial prefrontal cortex , in areas related to working memory maintainance such as the lateral intraparietal area , and in non-cortical regions such as the hippocampus , some subcortical nuclei , and the spinal cord . More recently , gamma-band synchronization has been recognized as a general process of neuronal processing , which might enable selective , dynamic and flexible routing of information across brain regions [79] , [80] . In accordance with its putative role in cognition , alterations of neuronal coherence in the gamma band have been associated with several psychiatric disorders , including autism and schizophrenia ( see [81] for a recent review ) . In spite of the recognized key role of high-frequency oscillations in neuronal processing , the biophysical mechanisms that underlie their generation are still incompletely understood . In particular , the role of intrinsic subthreshold oscillations , which have been observed in several interneuronal types critically involved in the emergence of gamma oscillations , is still unclear . Here , we show that intrinsic subthreshold oscillations enhance the synchrony induced by hyperpolarizing inhibitory coupling in networks of irregularly firing interneurons . As inhibitory synaptic currents peak , neurons are brought together to a narrow range close to the reversal potential . If neurons are endowed with damped subthreshold oscillations , hyperpolarization activates inward currents and results in post-inhibitory rebound , which in turn induces a depolarization of the membrane potential that is coherent across neurons due to common inhibitory input . This translates to a higher synchrony of spiking activity . Intrinsic subthreshold oscillations can result from delayed restorative currents , and are enhanced by the additional presence of amplifying currents [29] . Llinás et al . described a mechanism based on the interplay between a persistent sodium conductance and a delayed-rectifier potassium conductance [27] . Another current that often results in oscillatory properties is the h current , a hyperpolarization-activated inward current which has been proposed to control rythmogenesis in neurons and cardiac cells [82]–[85] , and is also expressed in fast-spiking interneurons of the hippocampus [86] . Activation of in response to IPSPs might induce the post-inhibitory rebound that is the key mechanism underlying enhanced synchrony in GIF networks . Deinactivation of the low-threshold inward calcium current might play a similar role . In fact , several biophysical mechanisms can yield equivalent neuronal dynamics [87] . The adoption of phenomenological models like the IF and GIF neurons enables us to assess the role of subthreshold damped oscillations in a general framework , abstracting from the specific biophysical mechanisms that are responsible for their generation . The heterogeneity of neuronal types is a phenomenon observed in many brain regions , and especially in those that are phylogenetically more recent and thus posited to be involved with higher brain functions , such as the hippocampus and the neocortex [24] , [25] . The functional significance of neuronal heterogeneity is an important , yet barely explored question that can greatly benefit from theoretical and computational approaches . As a step toward understanding the functional relevance of the complex distribution of intrinsic neuronal properties observed in the brain , we need to develop a better understanding of the effects of intrinsic neuronal properties in collective network dynamics in simplified settings . In general , the modification of a specific intrinsic neuronal property ( e . g . , modifying the subthreshold dynamics from purely passive to exhibiting damped oscillations ) results in changes in several other intrinsic properties ( e . g . , firing rate and depolarization responses to noisy synaptic bombardment ) . The latter changes can have substantial effects on the resultant network dynamics , which could be of the same or greater magnitude than the effects of the specific property under investigation . Hence , it is crucial to develop methods that enable a selective modification of a specific neuronal property , in the absence of changes in other neuronal properties that could also have a significant effect on the resultant network dynamics . This aim motivates our modelling choice of using IF and GIF neurons , because these models enable precise tuning of the firing rate response to noisy inputs by changes in the voltage threshold for spike generation , without affecting the subthreshold dynamics . In principle , the same aim could also be accomplished using more complex and realistic models , appropriately chosen from a large population generated with a database approach [88] . However , the highly non-linear dependency of neuronal activity on model parameters and initial conditions , which generally increases with model complexity , will have to be taken into account [89] . We identified three factors , conceptually independent but related through subthreshold intrinsic dynamics , that affect the influence of single-neuron properties on synchronization mediated by inhibition: i ) the firing rate response , ii ) the membrane potential distribution , in particular its relationship with the reversal potential of inhibition , and iii ) the shape of IPSPs , in particular the presence of a sign inversion ( post-inhibitory rebound depolarization or post-excitatory rebound inhibition ) . Importantly , the adoption of phenomenological models with a fixed voltage threshold for spike generation enabled us to disentangle the contribution to synchronization of these different factors . We presented some illustrative examples that expose each of these factors separately . By adjusting the firing threshold in order to keep the firing rate response equal for different values of the membrane potential distribution , we could isolate the influence of the membrane potential distribution on synchronization , and show that a more depolarized membrane potential distribution results in higher synchrony because of a stronger electrochemical driving force , independently of firing rate ( Figure 5B and C , compare curves corresponding to the same neuron type and different background inhibition-to-excitation ratio k ) . By comparing the synchronization properties of networks with different inhibition-to-excitation ratios k , with or without the additional calibration of the voltage threshold in order to match the firing rate response , we showed that higher firing rates increase synchronization regardless of the membrane potential distribution ( Figure 5B and C , compare solid and dash lines of the same color . Dash lines correspond to higher firing rate response to the noisy background for the GIF neuron , while the opposite holds for the IF neuron ) . Higher firing rates result in stronger inhibitory currents in each cycle of the oscillation which more effectively reset the membrane potential to a narrow range near the inhibitory reversal potential . By comparing the synchronization properties of networks of GIF and IF neurons , with or without the additional calibration of in order to match the firing rate response to the noisy background , we exposed the additional synchronizing effect due to the IPSP shape , in particular to the post-inhibitory rebound associated with hyperpolarizing IPSP in the GIF neuron ( Figure 5B and C , compare curves corresponding to the same firing rate response to the noisy background and inhibition-to-excitation ratio , and different subthreshold dynamics , such as the solid blue line for the GIF and the dash red line for the IF ) . If the reversal potential is slightly above the leak reversal potential ( shunting inhibition ) , IPSPs are slightly depolarizing . In this scenario , the presence of intrinsic subthreshold oscillations in the GIF neuron results in IPSP-mediated post-excitatory rebound inhibition , effectively diminishing the strength of oscillations in GIF networks ( Figure 11B ) . While subthreshold damped oscillations and post-inhibitory rebound always coexist in the GIF neuron , due to the linear description of the subthreshold dynamics , real neurons and non-linear neuron models can display post-inhibitory rebound while still responding passively to weak inputs . For example , a neuron can display real eigenvalues in the linearization of its subthreshold dynamics around its resting potential , while still being endowed with a hyperpolarization-activated inward current that only activates at membrane potentials considerably lower than its resting potential . In this case , weak hyperpolarizing inputs will elicit purely passive responses , while strong inputs will elicit post-inhibitory rebound and the neuron will return to baseline with a trajectory that overshoots its resting potential . Our results suggest that this class of neurons will also display enhanced propensity towards collective oscillations when coupled by hyperpolarizing inhibition . In this case , we would predict a non-linear increase in synchrony as a function of coupling strength , with a boost in synchrony as neurons switch from linear , passive responses to hyperpolarization to non-linear responses mediated by post-inhibitory rebound . The adoption of a network model with spatial extension enables one to assess the distance-dependent modulation of synchrony ( Figure 4 ) . Distance-dependent delays do not introduce a strong bias in the synchronization properties of cell pairs across short distances ( up to ∼1 mm ) , as higher input correlations to adjacent neuron pairs are counterbalanced by the desynchronizing effect of short-latency inhibition , resulting in a flat profile at the level of membrane potential correlation . As a result , firing synchrony only shows a modest decrease at short distances , but is otherwise distance-independent . Hence , the spatial profile of network synchronization does not exhibit a consistent topological structure , unless such a structure is present in the input . This is a desirable property , since spurious correlations would disrupt an efficient representation of information . The mechanism we describe is different from the recently proposed decorrelation by cofluctuations in excitation and inhibition [69] , [90] , and is crucially dependent on the spatial dimension of the network , in particular on distance-dependent propagation delays . As background input to individual neurons , we consider noisy conductances without any spatial correlation , and with only rapid temporal correlations consistent with filtering by fast AMPA and synapses . Spatio-temporal correlations in the input , either induced by the statistics of sensory stimuli or generated by neuronal dynamics in other brain areas , are expected to affect our results significantly . In fact , input temporal correlations affect neuronal processing in a cell-specific way [91] , [92] and spatial correlations shape the activity of recurrent networks [93] . Hence , we predict that the inclusion of more complex and realistic patterns of spatio-temporal correlations in the background input will enhance the cell-type dependent effects reported here . The study of how intrinsic neuronal properties affect the dynamics of networks receiving spatio-temporally structured inputs is an important topic for future research . In particular , some areas of the brain that are known to form allocentric maps of space , such as the hippocampus and entorhinal cortex , display a broad variety of interneuronal types . In some cases , intrinsic neuronal properties correlate with neurometric features of the maps , as in the case of the correlation between time constant , intrinsic oscillation frequency and grid field spacing in the dorsal region of the entorhinal cortex [94]–[96] . An extension of the current approach that includes spatio-temporally structured inputs and synaptic plasticity rules could be highly valuable to our understanding of how intrinsic properties and plasticity processes interact with the statistics of external inputs in the formation , access and manipulation of maps in the brain . In this work , we consider inhibitory networks with all-to-all connectivity and equal weights . This choice is convenient to assess the effects of propagation delays in the absence of additional spatial structure , which might dominate the dynamics in more realistic conditions . Our aim is to characterize the dynamical constraints enforced by delayed inhibitory coupling , while keeping all other parameters as unspecific as possible . Even if inhibitory connectivity in the neocortex might be very dense , almost approaching the all-to-all connectivity considered here ( see [97] , [98] and references therein ) , the heterogeneity of synaptic weights is expected to be significant . In our model , higher input correlations for nearby neurons interact with short latency inhibition , resulting in a flat spatial profile of output correlations . In a more realistic scenario , we expect that neurons that share a higher number of presynaptic partners will be more likely to synchronize [99] , especially if they are not connected or if they are located at a distance greater than required for short latency mutual inhibition . It should be noted that heterogeneous connectivity would break the toroidal symmetry of the network , and would greatly complicate an exhaustive characterization of the resultant dynamics . Likewise , interactions between excitatory and inhibitory neurons can also have a great impact on the population activity . If the connections from the excitatory to the inhibitory population are weak , or if excitatory neurons fire at low rates , the network would still operate in the ING ( Interneuron Network Gamma ) regime , and we would expect modest deviations from the results reported here . However , in the case of PING ( Pyramidal - Interneuron Network Gamma ) oscillations , excitatory neurons are active and they project to the inhibitory population . The dynamic interplay between excitatory and inhibitory populations could give rise to a qualitatively different collective dynamics , which could diverge substantially from the purely interneuronal network dynamics we described . The closed-loop interaction between excitatory and inhibitory populations greatly complicates the dynamics and the mechanistic analysis of the effects of subthreshold intrinsic oscillations in either , or both , neuronal populations , in the emergent collective rhythm . While the current study builds a useful foundation for pursing these investigations , the analysis of this case is beyond the scope of this manuscript and will be presented in a separate article . It is worth highlighting that the ING mechanism is not only of theoretical interest , but has also been supported by experimental data ( see , for example , [6] ) . In fact , the extent to which excitatory neurons contribute to the establishment and regulation of high-frequency oscillations is still a matter of debate [100] . Conversely , the necessary role of inhibition has long been established [6] , [7] , [68] . The role of inhibitory interneurons in the generation and modulation of high-frequency oscillations deserves special attention , since several neuropsychiatric disorders are associated with disruption of gamma band coherence and corresponding alterations in interneuron properties [101] . In fact , the key role played by interneuronal dysfunctions in the etiology of several neurological and psychiatric diseases has led to the introduction of the word “interneuronopathies” , which hints to underlying commonalities in genes and developmental mechanisms specific to GABA-ergic signalling ( in particular , those related to the fine tuning of excitatory/inhibitory balance along the course of development ) shared by several disorders with vastly different phenomenology , such as autism , epilepsy and schizophrenia [102]–[106] . In this work , we have focused on the influence of intrinsic subthreshold oscillations in the generation of high-frequency oscillations in interneuronal networks . In our approach , the desynchronizing effect is provided by the incoherent background input . Post-inhibitory rebound enhances synchrony by providing a depolarizing current which is coherent across cells due to common inhibitory input ( Figure 10A ) , and hence can counteract the desynchronizing effect of the incoherent background input . Other authors have identified several other factors that can either impair or promote high-frequency oscillations . Neuronal heterogeneity , either due to heterogeneity in the excitability of individual neurons , in their connections , or due to small network size or local coupling , is well known to have a desynchronizing effect [11]–[13] , [17] , [107] . Conversely , gap-junctional coupling among interneurons [108] and shunting inhibition [48] have been shown to increase synchrony by homogenizing firing rates across neurons with heterogeneous excitatory drive poised in the regular firing regime . In particular , gap-junctional coupling seems to bear a close resemblance to the synchronization mechanisms we described here , since both post-inhibitory rebound and gap-junctions can evoke depolarizing currents in the target cell , in the absence of excitatory chemical synaptic connections . However , the two mechanisms are markedly different . While gap-junctions tend to diminish the distance between the membrane potential trajectories of coupled neurons regardless of spiking activity , post-inhibitory rebound is spike-mediated . The investigation of how these different factors interact in realistic neuronal networks is an important topic for future research . Fast spiking basket interneurons exhibit several dynamical properties that have been suggested to facilitate gamma oscillations . For example , they can sustain high-frequency spiking with little or no adaptation [109] , display fast synaptic kinetics of both incoming and outgoing synapses [19] , [26] , [110] , and are endowed with specific intrinsic properties that boost the transmission of fast and synchronous EPSPs through their dendrites [111] . Fast spiking interneurons have also been shown to exhibit membrane resonance [30] , type II fI curves [34] , and type II Phase Response Curves [112] . Our modeling effort does not aim to reproduce all the dynamical features that have been reported in these cells . Rather , our aim is to elucidate the influence of a specific and commonly observed intrinsic neuronal characteristic , subthreshold damped oscillations , in the emergence and properties of high-frequency oscillations . In accordance with this intention , we adopted the simplest phenomenological model that can capture this dynamical property . Importantly , the IF and GIF models we considered in this study differ in their subthreshold dynamics ( passive in the IF , with subthreshold damped oscillations in the GIF ) , but they both exhibit type I Phase Response Curves . Recently , Moca et al . studied the effect of interneuronal membrane resonance in the gamma frequency synchronization of networks of excitatory and inhibitory neurons [16] , and reported more stable oscillations in networks with resonant interneurons , in general agreement with our results . However , our approach differs in two fundamental aspects . In our model , individual neurons are driven by strong barrages of background excitatory and inhibitory noisy conductances , mimicking neuronal activation in vivo; hence , neurons are poised in the irregular firing regime . As we have shown , the interaction between intrinsic neuronal properties and background synaptic conductances is a key factor in the resulting network activity . Conversely , Moca et al . included only a modest level of noise in their simulations , whose main effect is the generation of variability across trials . More importantly , their study considered collective oscillations generated in the regular firing regime , in which every neuron takes part in every cycle of the population rhythm ( see , for example , Figure 4B in [16] ) . If individual neurons are poised in the regular firing regime , the synchronization properties of the network will depend on the geometry of the limit cycle or chaotic attractor corresponding to tonic spiking , rather than on subthreshold dynamics themselves . Membrane resonance often results in a bifurcation to tonic spiking where firing period depends only weakly on input parameters , such as an Andronov-Hopf bifurcation . However , resonant subthreshold dynamics do not always correspond to a tonic spiking attractor with stable periodicity . For example , a neuron model characterized by a saddle node bifurcation off invariant circle will exhibit stable firing frequency in the tonic spiking regime , but passive subthreshold dynamics [87] . The correspondence between subthreshold dynamics and tonic spiking activity is expected to be even less accurate as more realistic neuronal models , and real living cells , are considered [112] . In particular , the neuron models we considered in this study behave similarly in the regular firing regime ( see section “Phase Response Curves in the IF and GIF neuron” and Figure S1 in Text S1 ) . Correspondingly , their synchronization properties do not differ consistently if neurons fire regularly in each cycle ( not shown ) . During network oscillations , pyramidal cells fire sparsely , while interneurons are thought to emit action potentials in every cycle . However , most experimental evidence on interneuron dense firing comes from in vitro studies where strong oscillations are induced by application of a glutamatergic agonist [6] or manipulation of the ionic environment [113] . Furthermore , most of these studies employed extracellular recordings , which are biased towards neurons with strong firing activity . In fact , an experimental study in rats engaged in running and exploration reported selective and sparse firing also in interneurons ( [114] , see in particular their Figure 1C ) . Other studies in rats reported sparse interneuronal firing during sensory-evoked gamma responses in the olfactory bulb in vitro [115] , and very sparse interneuronal firing during isoflurane anesthesia [116] . Intracellular recordings from interneurons in hippocampal slices activated by the cholinergic agonist carbachol also reported single-cell firing rates that are two or three times lower than collective gamma frequency [117] . We believe that this regime of partial synchronization might be , at least , as relevant to natural neuronal computation as the strongly synchronous bouts of gamma activity observed in response to the presentation of “favorite” stimuli in early sensory cortexes [5] . In fact , the level of synchrony can be modulated by physical properties of the stimulus , such as contrast [118] . Furthermore , weakly synchronous states are both information-rich ( in terms of the output they can convey to other brain regions ) as well as information-sensitive ( in terms of the representation capabilities they offer when stimulated by temporally structured inputs [119] ) . Hence , while the presentation of optimal stimuli in laboratory settings might induce strong gamma oscillations , neuronal information processing in naturalistic conditions might operate in an intermediate regime of information-rich weakly synchronized oscillations . Certain neuromodulators can affect the intrinsic properties of neurons . In particular , acetylcholine ( ACh ) changes the PRCs of cortical neurons by down-regulating the M-current , a slow potassium current which is also related to subthreshold oscillations [120] . Since subthreshold oscillations enhance oscillation strength in networks of interneurons coupled by hyperpolarizing , but not shunting , inhibition , our results suggest the intriguing possibility that ACh could differentially regulate the level of synchrony in different brain regions , depending on the nature of local coupling . For example , GABAergic input onto interneurons is shunting in the amygdala , CA3 and dentate gyrus [47] , [48] , [72] , but can be either shunting or hyperpolarizing in the cerebellum [73] , and is hyperpolarizing in the neocortex [97] . These region-specific effects could induce a bias in the synchronization properties of local networks and hence in the effective coupling between brain regions , under neuromodulatory control [80] . Experimental efforts in this direction would greatly benefit from theoretical investigations aiming to elucidate the properties and communication mechanisms of interacting networks [119] , [121] . Experimental data in the hippocampus and other areas revealed that distinct interneuronal populations are active at different phases of ongoing network oscillations , innervate specific postsynaptic types and subcellular domains , and might contribute to different aspects of information processing [24] , [116] , [122] . Reductionist modelling approaches combined with optogenetic experimental techniques will be needed in order to gain a mechanicistic understanding of the complex interaction between single-cell morphology , physiology and the emerging function of neuronal microcircuits . | Neurons in the brain engage in collective oscillations at different frequencies . Gamma and high-gamma oscillations ( 30–100 Hz and higher ) have been associated with cognitive functions , and are altered in psychiatric disorders such as schizophrenia and autism . Our understanding of how high-frequency oscillations are orchestrated in the brain is still limited , but it is necessary for the development of effective clinical approaches to the treatment of these disorders . Some neuron types exhibit dynamical properties that can favour synchronization . The theory of weakly coupled oscillators showed how the phase response of individual neurons can predict the patterns of phase relationships that are observed at the network level . However , neurons in vivo do not behave like regular oscillators , but fire irregularly in a regime dominated by fluctuations . Hence , which intrinsic dynamical properties matter for synchronization , and in which regime , is still an open question . Here , we show how single-cell damped subthreshold oscillations enhance synchrony in interneuronal networks by introducing a depolarizing component , mediated by post-inhibitory rebound , that is correlated among neurons due to common inhibitory input . | [
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] | 2014 | Interplay of Intrinsic and Synaptic Conductances in the Generation of High-Frequency Oscillations in Interneuronal Networks with Irregular Spiking |
Presynaptic , electron-dense , cytoplasmic protrusions such as the T-bar ( Drosophila ) or ribbon ( vertebrates ) are believed to facilitate vesicle movement to the active zone ( AZ ) of synapses throughout the nervous system . The molecular composition of these structures including the T-bar and ribbon are largely unknown , as are the mechanisms that specify their synapse-specific assembly and distribution . In a large-scale , forward genetic screen , we have identified a mutation termed air traffic controller ( atc ) that causes T-bar–like protein aggregates to form abnormally in motoneuron axons . This mutation disrupts a gene that encodes for a serine-arginine protein kinase ( SRPK79D ) . This mutant phenotype is specific to SRPK79D and is not secondary to impaired kinesin-dependent axonal transport . The srpk79D gene is neuronally expressed , and transgenic rescue experiments are consistent with SRPK79D kinase activity being necessary in neurons . The SRPK79D protein colocalizes with the T-bar-associated protein Bruchpilot ( Brp ) in both the axon and synapse . We propose that SRPK79D is a novel T-bar-associated protein kinase that represses T-bar assembly in peripheral axons , and that SRPK79D-dependent repression must be relieved to facilitate site-specific AZ assembly . Consistent with this model , overexpression of SRPK79D disrupts AZ-specific Brp organization and significantly impairs presynaptic neurotransmitter release . These data identify a novel AZ-associated protein kinase and reveal a new mechanism of negative regulation involved in AZ assembly . This mechanism could contribute to the speed and specificity with which AZs are assembled throughout the nervous system .
The majority of stimulus-dependent synaptic vesicle fusion occurs at presynaptic specializations called active zones ( AZs ) . Ultrastructurally , AZs consist of at least two components; 1 ) a presynaptic membrane of high electron density , reflecting the presence of proteins such as Ca2+ channels , t-SNAREs , and cell adhesion molecules and 2 ) a fibrillary cytomatrix ( CAZ ) that includes cytoskeletal elements , scaffolding proteins , and AZ-specific molecules such as Piccolo/Aczonin , Bassoon , Unc-13/Dunc-13/Munc-13 , RIM , and ELKS/Brp/ERC [1] . Many synapses that are characterized by a high release probability also include an electron-dense cytosolic projection that is believed to facilitate synaptic vesicle movement to the AZ . These projections are referred to as ribbons in the mammalian retina , dense bodies at the mammalian neuromuscular junction ( NMJ ) , and T-bars at the Drosophila NMJ [1]–[3] . To date , five proteins have been found within the presynaptic ribbon at synapses in the vertebrate retina , including Piccolo , Kif3A , RIM , CtBP1 , and RIBEYE/CtBP2 [1]–[3] . In Drosophila , there are no clear homologs of RIBEYE or Piccolo , and it remains unknown whether RIM or Kif3A associate with the Drosophila T-bar . The protein currently known to localize at the T-bar is the Drosophila homolog of ELKS/ERC , called Bruchpilot ( Brp ) [4] , [5] . Recently , it was demonstrated that mutations in the brp gene eliminate T-bars and severely impair synaptic vesicle release , consistent with the conclusion that T-bars and Brp are essential components of the presynaptic AZ [4] , [5] . T-bars and ribbons are large , macromolecular structures . In Drosophila , T-bars are first assembled at late embryonic stages as the nascent neuromuscular synapse begins to mature [6]–[8] . The appearance of T-bars and T-bar-associated antigens correlates with the ability of the neuromuscular junction to support larval movement . T-bars are formed only at the presynaptic face of the AZ and are not found at other sites , implying the existence of mechanisms that ensure site-specific assembly of these large , cytoplasmic structures . However , virtually nothing is known about how T-bar and ribbon structures are assembled and positioned at the AZ . One model for AZ formation that could be extended to ribbon/T-bar assembly is based upon the existence of transport vesicles that contain AZ components , including calcium channels as well as the Piccolo and Bassoon proteins . It has been suggested that these transport vesicles fuse at sites of nascent synapse formation to deliver protein constituents of the AZ in a site-specific manner [9]–[11] . Although transport vesicles have not been isolated in Drosophila motoneurons , it was recently demonstrated that mutation of a Kinesin 3 ( immaculate connections; imac ) prevents the transport of synaptic vesicle proteins to the developing synapse , and in this mutant background , both AZ and T-bar formation are significantly impaired [8] . These data suggest that a critical component of AZ and T-bar assembly is contributed by Imac-dependent axonal transport . Although transport vesicles could represent a mechanism to deliver transmembrane and membrane-associated proteins to the AZ , there presumably exist other mechanisms to control the site-specific assembly of cytoplasmic proteins into a T-bar . Here , we describe a previously uncharacterized gene in Drosophila that encodes a serine-threonine kinase that we have termed serine-arginine protein kinase at 79D ( srpk79D ) . The SRPK79D protein is a member of the serine-arginine protein kinase family previously shown to be involved in mRNA splicing and processing [12] . This gene was identified in a large-scale forward genetic screen for genes involved in the development , maturation , and stabilization of the Drosophila NMJ . In this study , we present evidence that SRPK79D is a T-bar-associated protein kinase that is necessary to prevent premature T-bar assembly in peripheral axons . We also present evidence that SRPK79D activity must be overcome within the NMJ for normal AZ assembly and neurotransmission . As such , our data identify a new T-bar-associated antigen and indicate that synapse-specific assembly of the presynaptic T-bar may be achieved , in part , through suppression of T-bar assembly at nonsynaptic sites including the axon .
In an ongoing screen to identify genes involved in the formation and stabilization of the Drosophila NMJ , we identified a P-element insertion ( P10036 ) in which the peripheral nerves contain numerous large accumulations of the AZ associated protein Brp ( Figure 1E–1G ) . These large , aberrant Brp accumulations ranged from roughly spherical to grossly elongated in appearance ( Figure 1E–1G ) . In wild-type animals , by contrast , axons within the peripheral nerves showed virtually no anti-Brp staining and the Brp puncta that did appear in these axons were small and spherical in appearance ( Figure 1B–1D ) . This phenotype is very unusual , based upon the results of our ongoing genetic screen . In this forward genetic screen , we have analyzed over 2 , 000 independent transposon insertion lines , including PiggyBac lines on chromosomes 2 and 3 from the Exelixis collection and an independent collection of P{GAL4} lines [13] . In each mutant background , we have stained three to five larvae with anti-Brp and anti-Discs Large ( Dlg ) antibodies and examined both the peripheral nerves and the neuromuscular synapse for defects . P10036 is the only mutation identified to date that causes the observed accumulation of anti-Brp staining in peripheral axons . The P10036 transposon resides within an intron of the previously uncharacterized gene CG11489 , which resides at chromosomal position 79D and is predicted to encode a member of the SRPK family ( Figure 1A and see below ) . Due to the dramatic effect on Bruchpilot ( German for crash pilot ) protein accumulation in peripheral axons , we named this mutant air traffic controller ( atc ) , and we refer to P10036 as srpk79Datc throughout this article . We next developed quantitative measures of the axonal Brp accumulations to further characterize and analyze the srpk79Datc mutant phenotype ( see Materials and Methods ) . In all cases , genetic controls were dissected , processed , stained , and imaged identically and in parallel with srpk79Datc mutants . We found a statistically significant increase in total nerve Brp fluorescence in srpk79Datc mutants compared to wild-type and heterozygous controls ( p<0 . 001 , Student t-test; Figure 1K ) . We also found a highly significant increase in the average puncta fluorescence intensity compared to wild-type and heterozygous controls . Indeed , the entire distribution of puncta intensities was shifted toward larger values ( p<0 . 001 , Mann-Whitney U Test; Figure 1L ) . Finally , we estimate that the frequency of these aberrant accumulations corresponds to 0 . 03 accumulations per micron of individual motor axon length . From these data , we conclude that Brp-positive puncta in srpk79Datc mutant axons represent larger , abnormal , protein aggregates compared to observations made in wild-type axons . Next , we assayed synaptic Brp staining intensity and NMJ morphology in the srpk79Datc mutant . We found that synaptic Brp staining intensity is significantly decreased compared to wild-type animals , assayed as both total Brp fluorescence ( p<0 . 001 , Student t-test; Figure 2A–2E ) and as the distribution of individual puncta intensities ( p<0 . 001 , Mann-Whitney U Test; Figure 2A–2D and 2F ) . This effect occurs at NMJ throughout the animal , and there is no evidence for a strong anterior–posterior gradient of this phenotype ( Figure S1 ) . Our data suggest that the accumulation of Brp aggregates in the axon of the srpk79Datc mutant depletes Brp protein from the presynaptic nerve terminal . Consistent with this conclusion , we found that total Brp protein levels , assayed by western blot , are unaltered in the srpk79Datc mutant background despite the dramatic increase in nerve Brp ( see below ) . We also determined whether the decrease in total Brp fluorescence causes a decrease in total Brp puncta number , which would be indicative of a change in AZ number . We found , however , that Brp puncta density within srpk79Datc mutant NMJs is identical to wild type and that total bouton numbers are wild type in the srpk79Datc mutant background ( Figure 2G and 2H ) . Moreover , anti-Dlg , anti-Synaptotagmin 1 ( Syt ) , and anti-Cysteine String Protein ( CSP ) staining at srpk79Datc mutant synapses are not different compared to wild type ( unpublished data ) . Thus , synapse growth , morphology , and AZ number appear normal in the srpk79Datc mutant . Consistent with the observed lack of morphological change , we found no change in neurotransmitter release in the srpk79Datc mutant background . We assayed neurotransmission by recording from the third-instar NMJ of homozygous sprk79Datc mutants , as well as homozygous srpk79Datc mutants lacking one copy of the brp gene ( brp69/+;srpk79Datc ) [5] . In all cases , evoked excitatory junctional potential ( EJP ) amplitude and spontaneous miniature EJP ( mEJP ) amplitudes were wild type ( wild-type average EJP = 34 . 28±1 . 59 mV compared to srpk79Datc = 34 . 27±1 . 28 mV; n = 10 , p>0 . 3; wild type average mEJP = 0 . 97±0 . 04 mV compared to srpk79Datc = 0 . 99±0 . 03 mV; n = 10 , p>0 . 3 ) . There was also no difference in the ability of the NMJ to sustain high-frequency ( 10 Hz ) stimulation in high extracellular calcium saline ( 2 mM ) ( unpublished data; see below for additional electrophysiological analyses ) . Thus , the srpk79Datc mutant causes inappropriate axonal accumulations of Brp protein , resulting in a depletion of this synaptic protein from the presynaptic AZ . However , the amount of depletion of Brp from the NMJ does not cause a defect in synaptic function over the time course of 4 d of larval development . We have used our quantitative assays to confirm that the phenotype of axonal Brp accumulation is caused by disruption of the srpk79D gene and to determine the nature of this genetic disruption . First , we demonstrated that the axonal Brp accumulation and synaptic Brp deficit phenotypes in the homozygous srpk79Datc mutant are statistically identical to those observed when the srpk79Datc mutation is placed in trans to a deficiency chromosome that uncovers the srpk79D gene locus , Df ( 3L ) Exel6138 ( Figures 1E–1L , 2E , and 2F ) . Furthermore , an independently identified molecular null allele of srpk79D ( srpk79DVN100; Eric Buchner , personal communication ) , has axonal and synaptic Brp phenotypes that are statistically identical to those observed in homozygous sprk79Datc ( Figure S2A–S2H ) . These data are consistent with the conclusion that the srpk79Datc transposon insertion is a strong loss-of-function or null mutation in the srpk79D gene . Interestingly , we found that the heterozygous srpk79Datc/+ mutant axons also have a slight , but statistically significant , increase in Brp fluorescence compared to wild type . These data indicate that srpk79D is partially haploinsufficient for the regulation of axonal Brp accumulation . Next , we determined the expression pattern of the srpk79D gene . In situ hybridizations performed on wild-type Drosophila embryos targeting an exon common to all known srpk79D transcripts ( see Materials and Methods ) detected high levels of srpk79D mRNA in the embryonic ventral nerve cord with lower expression present outside of the nervous system ( Figure 3A and 3B ) . This expression pattern is consistent with a function of srpk79D gene products in neurons , but does not rule out a possible function in other tissues including peripheral glia . To confirm that loss of srpk79D is responsible for the phenotype of axonal Brp accumulation , and to determine where srpk79D is required for normal Brp targeting , we employed a srpk79D RNA interference ( RNAi ) transgene ( UAS-srpk79DRNAi; Vienna Drosophila RNAi Collection ) . We found that expression of UAS-srpk79DRNAi in neurons phenocopies the srpk79Datc mutation ( Figure 3C–3F ) , whereas expression of UAS- srpk79DRNAi in glia ( also present in peripheral nerve ) does not cause formation of axonal Brp aggregates . These data indicate that srpk79D function is required in neurons , consistent with enriched expression in the central nervous system ( CNS ) . We also performed a genetic rescue experiment by expressing a Venus-tagged , full-length srpk79D transgene ( UAS-v-srpk79D-rd* ) in neurons in the homozygous srpk79Datc mutant background . In this experiment , neuronal expression of UAS-v- srpk79D-rd* significantly rescued the srpk79Datc mutant phenotype toward wild-type levels ( Figure 3G–3J ) . The presence of axonal Brp accumulations was reduced ( Figure 3G and 3H ) , and there was a correlated increase in synaptic Brp fluorescence in the rescue animals compared to the mutation ( unpublished data ) . Taken together , our data are consistent with the conclusion that loss of srpk79D , in neurons , is responsible for the abnormal accumulation of Brp in peripheral nerves . Finally , we noted that the srpk79D gene resides just downstream of the gene encoding CSP . In mammals , CSP was recently shown to suppress axonal protein aggregation [14] . Therefore , we pursued additional experiments to determine whether disruption of the Csp gene might participate in the phenotype of Brp axonal accumulation . In these experiments , we took advantage of a strong hypomorphic Csp allele in which the 5′ region of the Csp gene is deleted and the srpk79D locus is intact ( CspX1 , Figure 1A ) [15] . When srpk79Datc was placed in trans to the CspX1 mutation , we found a modest increase in Brp fluorescence and Brp puncta intensity compared to wild type , but not compared to the srpk79Datc/+ heterozygous mutant ( Figure 1K and 1L ) . On the basis of these data , we conclude that Csp is not directly involved in the phenotype of increased axonal Brp puncta staining observed in the srpk79D mutant . To date , the formation of axonal protein aggregates has been documented in mutations that disrupt both retrograde and anterograde axonal transport [16]–[19] . For example , mutations in kinesin heavy chain and disruption of the Dynein/Dynactin protein complex cause large axonal aggregates composed of diverse synaptic proteins and organelles including , but not limited to , Syt , CSP , Dap160/Intersectin ( Dap160 ) mitochondria , and Brp [16] , [17] , [19] . Thus , we considered the possibility that the srpk79Datc mutation disrupts axonal transport by asking whether additional synaptic proteins accumulate with Brp in the srpk79Datc mutant axons . We found , however , that the distribution of Syt , CSP , mitochondria , Dap160 , and Liprin-alpha were all unchanged relative to wild type in the srpk79Datc mutants ( Figure 4A–4L ) . We also find overexpressed EGFP-CaV2 . 1 is wild type in the srpk79Datc mutants ( unpublished data ) [20] . Thus , the srpk79Datc mutation seems to specifically disrupt the transport or aggregation of the Brp protein in peripheral axons without affecting the transport of synaptic vesicles or other AZ constituent proteins . We next explored the possibility that SRPK79D participates in the specific transport of Brp protein . In recent years , proteins have been identified that are specifically required for the anterograde transport of synaptic proteins or other cellular organelles such as mitochondria [8] , [17] , [21] . SRPK79D is not strictly required for axonal transport of Brp because Brp protein is present at the NMJ in the srpk79Datc mutant . However , it is possible that SRPK79D facilitates the anterograde transport of Brp/T-bars . Therefore , we pursued genetic interactions between srpk79D and either kinesin heavy chain ( Khc ) or kinesin 3 ( immaculate connections; imac ) [8] , [16] . Larval nerves that are heterozygous for the amorphic Khc8 allele contain rare “axonal swellings” that contain Syt , CSP , Brp , Dap160 , and KHC [16] ( E . L . Johnson and G . W . Davis , unpublished data ) . Importantly , these swellings can be clearly distinguished from the axonal Brp accumulations observed in srpk79D mutants because Brp accumulations in srpk79Datc do not contain any other known synaptic protein . Therefore , we are able to assess whether the presence of a heterozygous Khc or imac mutation would enhance the srpk79Datc mutant phenotype by increasing the abundance of Brp-specific protein aggregates in animals colabeled with anti-Brp and an additional synaptic protein . If SRPK79D facilitates axonal transport of Brp , then reducing KHC or Imac protein levels should enhance the srpk79Datc mutant phenotype ( Brp-specific protein aggregates ) . However , we found that placing a heterozygous Khc8/+ or imac170/+ mutation in an srpk79Datc homozygous mutant background ( Khc8/+; srpk79Datc or imac170/+; srpk79Datc ) affected neither the frequency nor the severity of the Brp-specific axon aggregates characteristic of the srpk79Datc mutant , nor was there any difference in the axonal swellings characteristic of the Khc mutant ( multiprotein aggregates ) ( Figure 4M and 4N ) . We then repeated this experiment using numerous additional mutations in the Khc gene as well as other genes implicated in axonal transport including: 1 ) the antimorphic Khc16 allele [16] , 2 ) Df ( 3L ) 34ex5 , which deletes the kinesin light chain locus [22] , and 3 ) the amorphic dynein heavy chain at 64C allele , Dhc64C4-19 [23] . We also analyzed double mutants for srpk79D and liprin-alpha ( lip-α ) , an AZ protein shown to play a role in axon transport [24] ( lip-αR60/lip-αF3ex5; srpk79Datc ) . None of these perturbations had any effect on Brp-specific protein accumulations in axons ( unpublished data ) . Finally , through direct observation , we find that small Brp puncta continue to be transported along axons in the srpk79Datc mutant larval nerves , whereas large aggregates appear to be stalled ( Figure S3 ) . Taken together , our genetic and live imaging data support the conclusion that Brp accumulations observed in srpk79D mutants are not due to a general defect in axonal transport . Finally , we asked whether T-bars might be preassembled structures that are trafficked to the NMJ and inserted at the AZ . In some mutant backgrounds , T-bars have been observed to dislodge from the synapse and reside in the cytoplasm [25] . However , we have never observed the appearance of T-bar–like structures in wild-type Drosophila axons at the ultrastructural level ( R . D . Fetter and G . W . Davis , unpublished data ) . This suggests that T-bars are normally assembled at the presynaptic AZ . To examine this question further , we analyzed the size and intensity of anti-Brp puncta in wild-type axons and synapses . At the light level , the vast majority of Brp puncta in wild-type axons are smaller and less intense than the puncta observed within the wild-type presynaptic nerve terminal , suggesting that synaptic T-bars are assembled at the synapse from constituent proteins , including Brp , that are transported down the axon to the synapse ( Figure 5 ) . By contrast , Brp puncta observed in srpk79D mutants stained more intensely and were much larger than Brp puncta found in wild-type axons . These Brp puncta were also often larger than the T-bar-associated Brp puncta observed at wild-type NMJ ( Figure 5 ) . Thus , the large Brp accumulations found in srpk79D mutant axons could represent superassemblies of T-bar-related proteins , including Brp . To address this possibility , we examined srpk79D mutant axons ultrastructurally . Mutations that cause focal accumulation of synaptic proteins in Drosophila nerves have been described previously and ultrastructural analyses have been carried out for three of these mutants . In Khc and Dhc64C mutants , axons become dramatically enlarged and are filled with an array of membrane-bound organelles , including multivesicular bodies , prelysosomal vacuoles , and mitochondria [16] , [17] . In contrast , lip-α mutant axons have normal diameters and contain organelle accumulations composed predominantly of clear-core vesicles [18] . In the srpk79D mutant , we found that axon diameters were not different from wild type ( Figure 6A and 6B ) . Remarkably , and in contrast to all three of the mutants described above , we found that srpk79D mutant motor axons contained highly organized , electron-dense structures that were not surrounded by a vesicular or intracellular membrane compartment ( Figure 6A–6C ) . Often , these electron-dense structures appeared strikingly similar to T-bars that had been joined at their “bases” into a large T-bar aggregate ( Figure 6C and 6D ) . We have never observed a similar structure in wild-type axons . In this study , we performed electron microscopy on five wild-type animals , analyzing 150 sections from the segmental nerves . None of these sections showed evidence of electron-dense aggregates . We performed electron microscopy on nine srpk79D mutant animals , analyzing 325 sections from segmental nerves . Sections from every mutant animal showed evidence of electron-dense plaques . Nearly every section from an individual mutant showed evidence of electron-dense plaques , consistent with the highly penetrant phenotype observed at the light level . The dimensions of these electron-dense structures , the prevalence of these structures in our electron microscopy sections and the similarity of their shape to T-bars present at the AZ strongly suggest that these structures represent the large Brp aggregates ( superassemblies ) that we observe at the light level in the srpk79D mutant background . Finally , similar to T-bars found at AZs , these electron-dense structures were surrounded by a filamentous matrix ( Figure 6A–6D ) . Although vesicles were also observed in these areas , we believe that they are molecularly distinct from synaptic vesicles because synaptic vesicle markers do not colocalize with Brp in the srpk79D mutant axons ( Figure 4A–4L ) . In contrast , synaptic ultrastructure in srpk79D mutants is identical to wild type ( unpublished data ) . Thus , loss of srpk79D leads to the formation of T-bar–like superassemblies in axons . Since we have never observed T-bar–like structures in wild-type axons , we propose that SRPK79D is required as part of a mechanism that normally suppresses premature T-bar assembly in the axon . To gain insight into the subcellular distribution of SRPK79D , we generated Venus-tagged srpk79D transgenes under UAS control ( UAS-v-srpk79D ) and expressed these transgenes in Drosophila neurons . We found that neuronally expressed Venus-SRPK79D-RD* , which rescues axonal Brp accumulations ( Figure 3G–3J ) , precisely colocalizes with Brp in both the nerve and at each presynaptic AZ ( see below ) . The voltage-gated calcium channel Cacophony is among very few other proteins that have been demonstrated to colocalize with Brp at the presynaptic AZ [20] . Furthermore , Venus-SRPK79D-RD* is highly unusual in that this protein has been shown to colocalize with Brp in a wild-type axon . These data suggest that SRPK79D closely associates with Brp during axonal transport of the Brp protein to the presynaptic nerve terminal . It is possible that the distribution of the tagged-SRPK79D protein does not reflect the wild-type SRPK79D protein distribution . However , the observation that Venus-SRPK79D-RD* shows a very restricted distribution , colocalizing with Brp in at least two cellular compartments , argues that this protein reflects , at least in part , the normal protein distribution . Given that SRPK79D colocalizes with Brp , we considered two hypotheses for SRPK79D function . First , we considered the hypothesis that SRPK79D somehow influences total Brp protein levels in the cell , perhaps by influencing Brp stability or turnover . However , when we assayed total Brp protein levels by western blot , we found no change in the srpk79D mutant compared to wild type and no evidence of altered protein degradation ( Figure S4B and S4C ) . Although western blots fail to measure Brp protein levels exclusively in motoneurons , this is consistent with our prior observation that axon Brp fluorescence increases while synaptic Brp decreases in the srpk79D mutant , leaving total Brp protein levels constant in the cell . To further examine this possibility , we overexpressed a GFP-tagged brp transgene in otherwise wild-type motoneurons using the GAL4-UAS expression system [4] . Although this resulted in the accumulation of Brp protein within axons , GFP-Brp overexpression did not precisely phenocopy the srpk79D mutant . GFP-Brp expression simultaneously increased synaptic and axonal fluorescence , whereas the srpk79D mutation causes increased axonal Brp and a correlated decrease in synaptic Brp ( Figures 1 , 2 , and 7A–7I ) . Thus , although Brp overexpression is sufficient to cause axonal aggregates , it seems unlikely that this is the cause of the defect in the srpk79D mutant . Consistent with this conclusion , co-overexpression of BRP and SRPK79D-RD* does not reduce the severity of the axonal accumulations caused by BRP overexpression alone . Similarly , axonal accumulations caused by BRP overexpression are not dramatically enhanced by mutating one copy of the srpk79D gene ( Figure 7J ) . To further address this issue , we asked whether Brp aggregates form in homozygous srpk79Datc mutants in which we decrease total Brp levels by removing one copy of the brp gene ( brp69/+;srpk79Datc ) [5] . We found that large axonal Brp aggregates persisted even when one copy of the brp gene is removed in the background of the srpk79Datc homozygous mutant ( Figure 7D , 7H , and 7I ) . Taken together , these experiments indicate that an SRPK79D-dependent elevation in Brp protein is not the direct cause of premature T-bar–like assembly formation in the axon . We therefore favor an alternative model based upon the observation that SRPK79D colocalizes with Brp and speculate that SRPK79D could sequester or inhibit the function of axonal T-bar proteins and thereby prevent the formation of axonal T-bar–like superassemblies . As mentioned above , sequence analysis of the predicted srpk79D gene products reveals similarity to a group of serine-threonine kinases called SRPKs ( Figure 8B ) . Members of this protein kinase family share a characteristic split serine-threonine kinase domain [26] . We therefore performed experiments to determine whether the kinase domain is required for SRPK79D activity . Transgenically expressed full-length SRPK79D ( SRPK79D-RD* ) colocalizes with Brp and rescues the srpk79D mutant phenotype ( Figure 8C–8K ) . In contrast , expression of an SRPK79D isoform with a truncated kinase domain ( SRPK79D-RD ) colocalized with Brp , but failed to rescue the srpk79D mutant phenotype ( Figure 8B and 8K ) . These data indicate that the SRPK79D kinase domain is involved in preventing axonal superassemblies of Brp but that it is not important for colocalization with Brp . To further test the importance of SRPK79D kinase activity , we generated a kinase dead srpk79D transgene by introducing a missense mutation into SRPK79D-RD* that is predicted to disrupt the ATP binding pocket of the kinase domain and thereby inhibit kinase activity ( SRPK79D-RD*KD , Figure 8B ) . A similar strategy has been used previously to eliminate kinase activity in other SRPKs ranging from yeast to human [27]–[29] . Like SRPK79D-RD* , SRPK79D-RD*KD colocalized with Brp . However , even when expressed at higher levels than SRPK79D-RD* , SRPK79D-RD*KD failed to rescue the srpk79D mutant phenotype ( Figure 8K and unpublished data ) . We next asked which domains might be required for SRPK79D protein trafficking and/or localization . We have found that an SRPK79D transgene that possesses an alternative SRPK79D N-terminal region but is otherwise identical to SRPK79D-RD* ( SRPK79D-RB ) failed to be efficiently trafficked out of the neuronal soma , was not found to colocalize with Brp , and failed to rescue the srpk79D mutant phenotype ( Figure 8B and 8K and unpublished data ) . This suggests that the common N-terminal domain of SRPK79D-RD , SRPK79D-RD* , and SRPK79D-RD*KD is required for the axonal transport of SRPK79D and its colocalization with Brp . Our data are consistent with a model in which SRPK79D prevents premature assembly of T-bars within axons . This model also suggests that SRPK79D activity must be inhibited locally , at the AZ , in order for synaptic T-bar assembly to proceed . We reasoned that overexpressing SRPK79D might overwhelm the synaptic machinery that disrupts SRPK79D activity and thereby reveal a role for SRPK79D during T-bar assembly or synaptic function . Here , we show that SRPK79D overexpression disrupts the punctate , highly organized appearance of synaptic Brp immunoreactivity ( Figures 9A–9D and S5A–S5D ) . For example , we observed regions where Brp was diffusely organized near the synaptic membrane . These regions encompass areas that would normally contain several individual Brp puncta . We hypothesize that these regions of diffuse Brp reflect either failed T-bar assembly or severely perturbed AZ organization . In addition , we found that SRPK79D overexpression also led to a decrease in total synaptic Brp fluorescence ( Figure 9E ) . This might be consistent with perturbed AZ formation but is also similar to that found in homozygous srpk79D mutants ( srpk79Datc ) , mutants heterozygous for a null mutation in brp ( brp69/+ ) , and mutants heterozygous for the brp null mutation and homozygous for the srpk79Datc allele ( brp69/+; srpk79Datc; Figures 2 and 7 , and unpublished data ) . It should be noted , however , that the diffuse synaptic Brp staining caused by SRPK79D overexpression is not observed in any of these srpk79D or brp loss-of-function paradigms . It should be further noted that SRPK79D levels in this overexpression experiment are higher than the SRPK79D levels that are sufficient to rescue the srpk79D mutation ( Figures 3G–3J , 9 , and S5 ) . SRPK localization was determined in rescue animals expressing relatively low levels of transgene-derived SRPK79D , and we believe that this is why we observe normal synaptic architecture and SRPK79D localization in those experiments ( Figure 8C–8F ) . Finally , overexpression of SRPK79D-RD*KD ( kinase dead ) or SRPK79D-RD ( truncated kinase domain ) did not cause diffuse Brp staining ( unpublished data ) , indicating that the kinase domain is required for this phenotype . If SRPK overexpression perturbs T-bar assembly or organization , then we might expect a disruption of presynaptic vesicle release . When we assayed synaptic function in larvae overexpressing SRPK79D , we found a dramatic ( ∼50% ) decrease in excitatory postsynaptic potential ( EPSP ) amplitude along with a trend toward an increase in the average amplitude of spontaneous miniature events ( minis , Figure 9F and 9G ) . Estimating the average number of vesicles released per action potential ( quantal content; calculated according to the average EPSP/average mEPSP per NMJ ) , we found that quantal content was severely perturbed . Since synapse function is intact in srpk79Datc homozygous animals , brp69/+ heterozygous animals , and brp69/+; srpk79Datc double-mutant larvae ( see above ) , the defects caused by SRPK79D overexpression are likely a consequence of excess SRPK79D activity at AZs . In addition , overexpression of SRPK79D-RD*KD ( kinase dead ) or SRPK79D-RD ( truncated kinase domain ) did not cause a defect in synaptic function ( unpublished data ) indicating that the kinase domain is required for this overexpression phenotype . Finally , it is worth noting that the defects in synaptic function caused by SRPK79D-RD* overexpression are similar to those found in brp null mutants , which lack T-bars [5] .
The best-characterized role for SRPKs is in controlling the subcellular localization of SR proteins , thereby regulating their nuclear pre-mRNA splicing activity [12] . More recently , SR protein involvement in several cytoplasmic mRNA regulatory roles has been reported [30] , [31] . In particular , a phosphorylation-dependent role for SR proteins has been reported in both Drosophila and mammalian cell culture [32] , [33] . It is interesting to speculate that the function of SRPK79D to prevent premature T-bar assembly might be related to the established function of SRPKs and SR-domain-containing proteins during RNA binding , processing , and translation [12] , [30] . One interesting possibility is that RNA species are resident at the T-bar . In such a scenario , SRPK79D-dependent repression of RNA translation could prevent T-bar assembly in the axon , and relief of this repression would enable T-bar assembly at the AZ . The continued association of SRPK79D with the AZ could allow regulated control of further T-bar assembly during development , aging , and possibly as a mechanism of long-term synaptic plasticity . Several results provide evidence in support of such a possibility . First , local translation has been proposed to control local protein concentration within a navigating growth cone [34] , [35] . There is also increasing evidence in support of local translation in dendrites and for the presence of Golgi outposts that could support local protein maturation [36] , [37] . A specific role for RNA binding proteins at the presynaptic AZ is supported by the prior identification of the RIBEYE protein , which is a constituent of the vertebrate ribbon structure . RIBEYE contains a CtBP domain previously shown to bind RNA [2] . The discovery of a different RNA binding protein ( CtBP1 ) at the ribbon and our description of a putative RNA regulatory protein at the Drosophila T-bar further suggest that RNA processing might be involved in the formation or function of these presynaptic electron dense structures [3] . In light of these data , we explored the possibility that SRPK79D might participate in translational control related to T-bar assembly . We , therefore , examined mutations in genes that could represent SRPK79D-dependent negative regulators of translation , such as aret ( bru ) , cup , pum , nos , and sqd [38]–[44] , reasoning that the loss of such a translational inhibitor might result in the ectopic synthesis of AZ proteins , ultimately leading to a phenotype similar to that observed in srpk79D mutants . We also generated genomic deletions for bru2 and bru3 . However , we did not find evidence of axonal Brp aggregation in any of these mutants . Next , we assayed mutations previously shown to be required for mRNA transport and local protein synthesis . If necessary for T-bar assembly , these mutations might disrupt synaptic Brp-dependent T-bar formation . These mutations , including orb , vas , and stau , have phenotypes at earlier stages of development , but show no defect in synaptic Brp staining [38] , [45]–[48] . Thus , although these experiments do not rule out a function for SRPK79D in local translation , we have examined mutations in several additional candidates and failed to uncover evidence in support of this model . Another possibility is that SRPK79D inhibits T-bar assembly through the constitutive phosphorylation-dependent control of a putative SR protein that colocalizes with SRPK79D and Brp within a nascent T-bar protein complex . Upon arrival of this nascent T-bar protein complex at the presynaptic nerve terminal , T-bar assembly could be initiated in a site-specific manner through the action of a phosphatase that is concentrated at a newly forming synapse . There are several examples of phosphatases that can be localized to sites of intercellular adhesion , some of which have been implicated in the mechanisms of synapse formation and remodeling [49] . This model , therefore , proposes that negative regulation of T-bar assembly , via SRPK79D , is a critical process required for the rapid and site-specific assembly of the presynaptic AZ-associated T-bar structure . Finally , we can not rule out the possibility that SRPK79D normally functions to prevent T-bar superassembly as opposed to T-bar assembly per se . Consistent with this idea is the observation of T-bar aggregates in axons and prior observation that detached ribbon structures coalesce into large assemblies in vertebrate neurons [50] . Synapse assembly is a remarkably rapid event . There is evidence that the initial stages of synapse assembly can occur in minutes to hours , followed by a more protracted period of synapse maturation [11] , [51]–[53] . Synapses are also assembled at specific sites . In motoneurons and some central neurons , synapses are assembled when the growth cone reaches its muscle or neuron target [53] , [54] . However , many central neurons form en passant synapses that are rapidly assembled at sites within the growing axon , behind the advancing growth cone [53] , [54] . Current evidence supports the conclusion that intercellular signaling events mediated by cell adhesion and transmembrane signaling specify the position of the nascent synapse [54]–[56] . The subsequent steps of presynaptic AZ assembly remain less clear . Calcium channels and other transmembrane and membrane-associated proteins appear to be delivered to the nascent synaptic site via transport vesicles that fuse at the site of synapse assembly [9]–[11] . It has been proposed that cytoplasmic scaffolding molecules then gradually assemble at the nascent synapse by linking to the proteins that have been deposited previously [11] . This model assumes , however , that the protein–protein interactions between the numerous scaffolding molecules that comprise the presynaptic particle web do not randomly or spontaneously occur in the cytoplasm prior to synapse assembly . What prevents these scaffolds from spontaneously assembling in the small volume of an axon , prior to synapse formation at the nerve terminal and between individual en passant synapses ? Currently , nothing is known about how premature scaffold assembly is prevented . We propose that our studies of srpk79D identify one such mechanism of negative regulation that prevents premature , inappropriate assembly of a presynaptic protein complex . We further propose that such a mechanism of negative regulation , when relieved at a site of synapse assembly , could contribute to the speed with which presynaptic specializations are observed to assemble .
The listed strains were obtained from the following sources: srpk79D[atc] ( c00270 ) , f00171 , d09582 , f05463 , and d09837 from the Exelixis collection at Harvard Medical School; v47544 ( UAS-srpk79DRNAi ) from the Vienna Drosophila RNAi Collection; P{GawB}elavC155 ( C155 ) , P{GawB}sca109-68 ( Sca ) , P{GawB}OK371 ( OK371 ) , P{GAL4}repo ( Repo ) , Khc8 , Khc16 , Df ( 3L ) 34ex5; dhc64C4-19 , Df ( 3L ) Exel6138 , UAS-mitoGFP , cup1 , sqdj4b4 , pum13 , nosL7 , vasRJ36 , orbdec , stau1 , and staury9 from the Bloomington Stock Center; CspX1 was a generous gift from Konrad Zinsmaier; srpk79DVN100 was a generous gift from Erich Buchner; imac170 was a generous gift from Thomas Schwarz; aretPA , aretPD , and aretQB were generous gifts from Paul MacDonald; and UAS-gfp-brp ( UAS-g-brp ) and brp69 were generous gifts from Stephan Sigrist . Wandering third-instar larvae were dissected in calcium-free saline and fixed with either 4% paraformaldehyde/PBS ( 15 min ) or 100% Bouin's Solution ( 2 min ) . Excess fixative was removed by extensive washing in PBS+0 . 1% Triton-X ( PBT ) . Dissected larvae were then incubated overnight at 4°C in PBT with one or more primary antibodies , washed in PBT , incubated either overnight ( 4°C ) or for 1 h ( 22°C ) in PBT with one or more fluorescent-conjugated secondary antibodies , and washed again before being mounted on a slide for imaging analysis . Primary antibodies: NC82 ( anti-Brp; Developmental Studies Hybridoma Bank ) 1∶100; 3H2 2D7 ( anti-Syt; Developmental Studies Hybridoma Bank ) 1∶25; anti-Liprin-alpha ( a generous gift from David Van Vactor ) 1∶1 , 000; 1G12 ( anti-DCSP-3; Developmental Studies Hybridoma Bank ) 1∶25; and anti-Dap160 ( Marie et al . , 2004 [57] ) 1∶100 . Fluorescent-conjugated secondary antibodies: goat-anti-mouse Alexa 488 ( Invitrogen ) 1∶500; goat-anti-mouse Alexa 555 ( Invitrogen ) 1∶500; and goat-anti-rabbit Alexa 488 ( Invitrogen ) 1∶500 . Where applicable , anti-HRP-Cy3 ( Jackson Immunoresearch ) 1∶200; anti-HRP-FITC 1∶100 or anti-HRP-Cy5 1∶50 were used at the same step as secondary antibody incubation . Genotypes being directly compared were grouped together during all of the above procedures . Images were digitally captured using a cooled CoolSnapHQ CCD camera mounted on a Zeiss Axiovert 200 M microscope . Images were acquired and analyzed using Slidebook software ( Intelligent Imaging Innovations ) . Individual nerves/synapses were optically sectioned at 0 . 5 µm ( 11–27 sections per nerve ) using a piezoelectric-driven z-drive controlling the position of a Zeiss 100× oil immersion objective ( numerical aperture [NA] = 1 . 4 ) . The intensity of anti-BRP immunostaining was quantified as follows: Each series of 0 . 5-µm optical nerve sections was deconvolved ( nearest-neighbors; Intelligent Imaging Innovations ) . Two-dimensional projections of the maximum pixel intensity were then generated , and the total Brp fluorescence and the maximum fluorescence intensity of each Brp punctum within the nerve/synapse area were determined for each resulting image using a semiautomated procedure as described previously [58] , [59] . For all quantifications , the nerve/synapse area was defined as that delimited by anti-HRP staining . Live imaging was carried out as previously described [60] . In brief , wandering third-instar larvae were dissected in HL3 saline ( 0 . 4 mM Ca2+ ) on a glass coverslip and held in place using pressure pins . Images were digitally captured using a Photometrics Cascade 512B camera mounted on an upright Zeiss Axioskop 2 microscope using a 100× water immersion ( NA = 1 . 0 ) objective and a GFP filter set ( Chroma ) . Time-lapse images were collected and analyzed using Slidebook software ( Intelligent Imaging Innovations ) . srpk79D mRNA was detected using a protocol based upon the “96-well plate RNA in situ protocol” available at the Berkeley Drosophila Genome Project ( BDGP ) Web site ( http://www . fruitfly . org ) . In short , mixed-stage embryos were collected , fixed in 3 . 7% formaldehyde/1×PBS , and prepared for incubation with SP6 or T7 polymerase generated digoxigenin ( DIG ) -labeled nucleotide probes . To generate probes , a 954-base pair ( bp ) fragment of the srpk79D gene was amplified by PCR from cDNA AT02150 , obtained from the Berkeley Drosophila Genome Project using primers with the sequence 5′-ttacccggattcgtccgac-3′ and 5′-gcagtgattttcttctccgttcgg-3′ . This fragment was TA cloned into the pGEM-T Easy vector ( Promega ) . The resulting product was used as a template for T7/SP6 DIG-labeled RNA probe synthesis ( Roche ) . After incubation and removal of excess probe , embryos were incubated with alkaline-phosphatase-conjugated anti-DIG Fab fragments ( Roche ) . Excess Fab fragments were removed by washing , and a NBT/BCIP developing reaction was performed ( Roche ) . Adult heads were removed by freezing at −70°C , followed by agitation . Heads were isolated using mesh filters . RNA was extracted using TRIzol reagent and standard molecular biology techniques . DIG-labeled RNA probes were generated by amplifying an 800-bp fragment of the brp gene from cDNA IP09541 obtained from the Berkeley Drosophila Genome Project using primers with the sequence 5′-gcaatgggcagtccatactacc-3′ and 5′-cccattcccttggcctgc-3′ and the 738-bp insert from rp49 cDNA RE59709 obtained from the Berkeley Drosophila Genome Project and 5′-cggcaaggtatgtgcg-3′ and 5′-actaaaagtccggtatattaacgtttac-3′ and TA cloning into pGEM-T Easy ( Promega ) . The resulting product was used as a template for T7/SP6 DIG-labeled RNA probe synthesis ( Roche ) . Northern blot analysis was carried out using Ambion NorthernMax-Gly protocols and reagents . Probe detection was carried out using alkaline phosphatase-conjugated anti-DIG Fab fragments ( Roche ) in conjunction with the DIG Wash and Block Kit and CSPD Ready-to-Use . Third-instar larval brains were pulverized in 2× Laemmli sample buffer . Proteins were separated by SDS-PAGE and transferred to PVDU membrane . The membrane was blocked in 2% milk powder in 1×TBS-Tween , and then incubated for 1 h at room temperature with an anti-Brp monoclonal antibody ( Developmental Studies Hybridoma Bank NC82 , 1∶100 ) or anti-GFP monoclonal antibody ( Invitrogen 3E6 , 1∶100 ) . As a protein loading control , the membrane was co-incubated with an anti-β-tubulin monoclonal antibody ( Developmental Studies Hybridoma Bank E7 , 1∶1 , 000 ) . After washing in 1×TBS-Tween , the membrane was incubated for 1 h at room temperature with horseradish peroxidase-conjugated anti-mouse secondary antibody ( 1∶20 , 000 ) , washed again and an electrogenerated chemiluminescence ( ECL ) detection reaction ( Amersham ) was performed . Mutant and wild-type third-instar larvae were prepared for electron microscopy as follows . Larvae were filleted in physiological saline and fixed with 2% glutaraldehyde in 0 . 12 M Na-cacodylate buffer ( pH 7 . 4 , 10 min ) . The fixed larvae were then transferred to vials containing fresh fixative and fixed for a total of 2 h with rotation . Larvae were rinsed with 0 . 12 M Na-cacodylate buffer and postfixed with 1% osmium tetroxide in 0 . 12 M Na-cacodylate buffer for 1 h . Specimens were then rinsed with 0 . 12 M Na-cacodylate buffer , followed by water , and then stained en bloc with 1% aqueous uranyl acetate for 1 h . After water rinse , dehydration , and embedding in Eponate 12 resin , sections were cut with a Leica Ultracut E microtome , collected on Pioloform-coated slot grids , and stained with uranyl acetate and Sato's lead . Sections were photographed with a Tecnai spirit operated at 120 kV equipped with a Gatan 4 k×4 k camera . Recordings were taken in HL3 saline ( Ca2+ 0 . 4 mM , Mg2+ 10 mM ) from muscle 6 in abdominal segments 2 and 3 of third-instar larvae as previously described [61] . Only recordings with resting membrane potentials more negative than −60 mV and input resistances greater then 7 MΩ were used for analysis . Measurements of EPSP and spontaneous miniature release event amplitudes were made using MiniAnalysis software ( Synapsoft ) . | Neurons communicate with each other through electrochemical impulses transmitted primarily at specialized intercellular junctions termed synapses . At each synapse , the primary site of synaptic vesicle fusion occurs at the active zone , an electron-dense presynaptic membrane with associated fibrillary matrix . Many active zones also possess one or more electron-dense cytosolic projections that are believed to facilitate vesicle mobilization to the active zone membrane and are required for normal synaptic transmission . These electron-dense projections are referred to as T-bars in Drosophila or ribbons in vertebrates . The molecular composition of these structures remains poorly characterized , and very little is known about how these structures are specifically assembled and stabilized at the presynaptic membrane . Here , we identify in Drosophila a neuronally expressed serine-arginine kinase called SRPK79D that localizes to the presynaptic active zone and that through its kinase activity appears to repress T-bar formation within peripheral axons . Our study thus provides evidence for kinase-dependent repression of active zone assembly , with implications for the development and growth of synaptic connections throughout the nervous system . | [
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] | 2009 | Negative Regulation of Active Zone Assembly by a Newly Identified SR Protein Kinase |
During infection with the intracellular parasite Toxoplasma gondii , the presentation of parasite-derived antigens to CD4+ and CD8+ T cells is essential for long-term resistance to this pathogen . Fundamental questions remain regarding the roles of phagocytosis and active invasion in the events that lead to the processing and presentation of parasite antigens . To understand the most proximal events in this process , an attenuated non-replicating strain of T . gondii ( the cpsII strain ) was combined with a cytometry-based approach to distinguish active invasion from phagocytic uptake . In vivo studies revealed that T . gondii disproportionately infected dendritic cells and macrophages , and that infected dendritic cells and macrophages displayed an activated phenotype characterized by enhanced levels of CD86 compared to cells that had phagocytosed the parasite , thus suggesting a role for these cells in priming naïve T cells . Indeed , dendritic cells were required for optimal CD4+ and CD8+ T cell responses , and the phagocytosis of heat-killed or invasion-blocked parasites was not sufficient to induce T cell responses . Rather , the selective transfer of cpsII-infected dendritic cells or macrophages ( but not those that had phagocytosed the parasite ) to naïve mice potently induced CD4+ and CD8+ T cell responses , and conferred protection against challenge with virulent T . gondii . Collectively , these results point toward a critical role for actively infected host cells in initiating T . gondii-specific CD4+ and CD8+ T cell responses .
Toxoplasma gondii is an intracellular protozoan parasite of medical and veterinary significance that can induce acute disease in its host and is an important opportunistic pathogen in immunocompromised individuals [1] , [2] . Successful control of this pathogen requires a rapid TH1 immune response , characterized by the production of the cytokine IL-12 , which promotes the ability of parasite-specific CD4+ and CD8+ T cells to produce the cytokine Interferon-γ ( IFN-γ ) [3] , [4] , [5] . The initiation of CD8+ T cell responses is a complex process which requires that professional antigen presenting cells acquire antigens and present them in the context of Major Histocompatibility Complex ( MHC ) I , and multiple models have been proposed to explain how this may occur during toxoplasmosis [6] , [7] . For example , in other systems , foreign antigens are acquired through the pinocytosis of soluble antigens , the phagocytosis of large particulate antigens , or the phagocytosis of host cells containing foreign antigens , and subsequently presented to CD8+ T cells through cross-presentation [8] , [9] . A role for cross presentation during toxoplasmosis is supported by in vivo imaging studies showing that uninfected dendritic cells interact extensively with parasite-specific CD8+ T cells [6] , [10] , [11] . Alternatively , since T . gondii is an intracellular parasite , actively infected dendritic cells may acquire parasite-derived antigens from their intracellular environment independently of phagocytosis and directly prime naïve CD8+ T cells . Indeed , the ability of cells actively infected by T . gondii to prime or present antigen to CD8+ T cells has been observed in vitro [12]–[14] and the critical role of perforin in immunity to T . gondii implicates the cytolysis of infected host cells as a mechanism of defense , thus arguing that infected cells can present antigen to effector CD8+ T cells in vivo [15] . However , several caveats must be acknowledged in interpreting these studies . Firstly , the ability of infected cells to present antigens to reporter cells lines or activated effector CD8+ T cells does not necessarily indicate that infected cells can prime naïve CD8+ T cells , and events that occur in vitro may not represent the in vivo situation . Additionally , it can be difficult to distinguish actively infected host cells from those that have phagocytosed the parasite by flow cytometry , thus confounding experimental interpretation . Furthermore , like many intracellular pathogens , T . gondii has been reported to inhibit the expression or upregulation of molecules involved in antigen presentation such as MHCI , CD40 , CD80 , and CD86 on infected cells , suggesting that the ability of infected cells to prime naïve CD8+ T cells may be compromised [16]–[18] . Antigens presented to CD4+ T cells in the context of MHCII may also be derived from the extracellular or intracellular environment of the host cell . Endocytosed antigens can be presented in the context of MHCII , and this pathway is considered to be the primary mechanism by which antigens are acquired for presentation to CD4+ T cells [19] . However , intracellular antigens can also be presented in the context of MHCII , as cytosolic peptides are presented in the context of MHCII by B cells and macrophages [20] . Similarly , in vitro studies have demonstrated that viral or model antigens expressed intracellularly can be presented to CD4+ T cells independently of phagocytosis [21]–[29] . Despite these findings , the role of infected cells in presenting antigen to CD4+ T cells in vivo during any infection remains unclear [30] . In the case of T . gondii , downregulated expression of MHCII and other molecules involved in antigen presentation has been observed on infected cells , and cells infected with T . gondii exhibit decreased ability to present antigen in vitro [16]–[18] . Furthermore , in vitro studies have observed that antigens from heat-killed or invasion-inhibited parasites incubated with dendritic cells can be presented in the context of MHCII , consistent with a role for phagocytosis-dependent antigen presentation to CD4+ T cells [12] . There are several difficulties involved with addressing the relative contributions of phagocytosis versus active invasion to antigen presentation in vivo during many infections . For example , interfering with these pathways can result in changes in pathogen burden and inflammation that confound experimental interpretation , and the parasite-mediated lysis of host cells and re-infection may obscure the analysis of the earliest cell populations that interact with the pathogen . In addition , there are limited tools to distinguish host cells that have phagocytosed pathogens from those that have been productively infected . In the present study , these issues are addressed using a non-replicating uracil auxotrophic vaccine strain of T . gondii ( the cpsII strain ) [31]–[33] and a novel assay that tracks the fate of parasites and distinguishes active invasion from phagocytosis in vivo . Using these approaches , cpsII parasites were found to infect large numbers of macrophages and dendritic cells , and dendritic cells were found to be necessary for optimal cpsII-induced CD4+ and CD8+ T cell responses . Infected dendritic cells displayed an activated phenotype , characterized by high levels of CD86 and MHCI expression , which was unique from the phenotype of dendritic cells that had phagocytosed T . gondii . Furthermore , the administration of heat-killed or invasion-blocked parasites did not induce CD4+ or CD8+ T cell responses , thus demonstrating that phagocytosis of parasites is insufficient to activate naïve T cells . Lastly , the selective transfer of infected dendritic cells or macrophages , but not those that had phagocytosed T . gondii , to naïve mice resulted in robust CD4+ and CD8+ T cell responses and protection from challenge with a virulent strain of T . gondii . These findings point toward a critical role for infected cells in initiating the adaptive immune response to T . gondii .
To distinguish between parasites that are phagocytosed by host cells and those that actively infect host cells , differences in sensitivity to pH between the fluorescent markers mCherry and CellTrace Violet were exploited . When mCherry-expressing parasites were labeled intracellularly with CellTrace Violet and incubated overnight in buffer solutions of varying pH , mCherry fluorescence was retained ( Figure 1a ) . In contrast , violet fluorescence intensity was maintained at pH 7 . 0 but was decreased at low pH ( Figure 1a ) . The ability of this system to distinguish active invasion from phagocytosis was demonstrated in vitro by incubating Violet-labeled , mCherry-expressing cpsII parasites with macrophages and examining fluorescence by flow cytometry 1 hour and 18 hours post-infection . At one hour after incubation with parasites , two distinct macrophage populations were present: One displayed mCherry and Violet fluorescence , while the other was negative for both markers ( Figure 1b ) . However , by 18 hours , two distinct mCherry+ve populations were apparent . One population displayed no loss of mCherry or Violet fluorescence ( mCherry+veViolet+ve ) , while the other population had decreased mCherry fluorescence associated with a complete loss of violet fluorescence ( mCherry+veViolet−ve ) . Utilizing ImageStream flow cytometry to generate images of individual cells from each of these populations revealed that the mCherry+veViolet+ve cells contained intact parasites , while the mCherry+veViolet−ve cells contained dimmer and more diffuse mCherry fluorescence ( Figure 1c , Figure S1 ) . Instances in which cells contained both diffuse fluorescence and intact parasites were rare ( <3% of infected cells ) . Furthermore , pre-treatment of parasites with the irreversible inhibitor of invasion 4-p-bromophenacyl bromide ( 4-p-bpb ) ( thus making parasites targets for phagocytosis ) [12] , [34]–[36] , resulted in the complete loss of the mCherry+veViolet+ve population at 18 hours post-infection ( Figure 1b , c , Figure S1 ) . Staining with LysoTracker , a fluorescent dye that specifically stains acidified compartments [37] , enabled parasites that localized to acidified compartments to be distinguished from those that persist in non-acidified compartments . Both of these populations of parasites ( LysoTracker+ve and LysoTracker−ve ) were apparent when untreated ( invasion competent ) parasites were incubated with bone marrow-derived macrophages one hour post-infection ( Figure S2 ) . In contrast , when invasion was pharmacologically inhibited parasites localized exclusively to the acidified compartments at these early time points , and at later time points the diffuse mCherry+ve fluorescence localized most commonly to a LysoTracker−ve compartment . Collectively , these results are consistent with a model in which phagocytosed parasites are degraded , and the acidic environment of the phagosome leads to a loss of Violet fluorescence , while mCherry fluorescence is retained . In contrast , when the parasite actively invades host cells and persists in the less acidic environment of the parasitophorous vacuole ( PV ) , both Violet and mCherry fluorescence are retained . The ability to distinguish active invasion from phagocytosis was then utilized to determine the fate of cpsII parasites in vivo . When C57BL/6 mice were vaccinated intraperitoneally with Violet-labeled , mCherry-expressing parasites , mCherry+veViolet+ve and mCherry+veViolet−ve populations were apparent in the Peritoneal Exudate Cells ( PECS ) 18 hours post-vaccination , and the presence of the mCherry+veViolet+ve population was abrogated by pre-treating the parasites with 4-p-bpb ( Figure 1d ) . Furthermore , when Violet+ve cells were sorted and cytospins were examined , they were found to contain intact parasites ( Figure 1e ) . ImageStream analysis also revealed that the mCherry+veViolet+ve population contained intact parasites whereas the mCherry+veViolet−ve population displayed diffuse mCherry fluorescence ( Figure 1f , Figure S3 ) . Collectively , these studies demonstrate that the use of fluorescent markers with differing pH sensitivities can be used to distinguish cells that have phagocytosed T . gondii from those that have been actively infected . To measure the persistence of cpsII parasites in vivo , bioassays were performed in which tissues from vaccinated mice were cultured in the presence of exogenous uracil and examined by microscopy for the presence of cpsII parasites . Using this method , cpsII parasites were detected in all mice examined at day 3 post-infection . However , by day 5 post-infection , 50% of mice had cleared the infection , and by day 10 post-infection , no parasites could be detected . These data suggest that cpsII parasites are ultimately cleared from the host , and are consistent with previous studies , in which parasite DNA could not be detected in the peritoneal cavities or spleens of cpsII-vaccinated mice when measured 3 weeks post-infection [38] . To determine the mechanisms by which cpsII parasites may ultimately be cleared from host cells , their fate within infected host cells was examined in vitro . Since IFN-γ ( in combination with LPS or TNF-α ) can induce the recruitment of immune enzymes such as the Immunity Related Guanosine Triphosphatases ( IRGs ) to the PV , and these enzymes have been implicated in the rupture of the PV which leads to the xenophagic elimination of the parasite [39] , the colocalization of the parasite with Irgb6 ( a member of the IRG family ) and LAMP-1 ( which is expressed on lysosomes ) in IFN-γ–activated cells and untreated cells was examined using immunofluorescence microscopy , to determine if IFN-γ induced the elimination of cpsII parasites within infected cells . When the subcellular localization of live cpsII parasites was examined , it was apparent that these parasites did not colocalize with either Irgb6 or LAMP-1 in IFN-γ-activated or untreated macrophages , at any time point examined ( ranging from 3 hours post-infection to 5 days post-infection ) ( Figure 2a–b ) . In contrast , LAMP-1 colocalized with heat-killed parasites , consistent with the idea that heat-killed parasites are phagocytosed . These data argue against the notion that cpsII parasites are eliminated by xenophagy , and demonstrate that these parasites can persist within infected cells for long periods of time . Electron microscopy was also utilized to examine the integrity of the PV , since IFN-γ can induce the blebbing and rupture of the PV during infection with replicating strains of T . gondii [40] , [41] . Using this approach , cpsII-infected macrophages were consistently observed to contain intact PVs and blebbing was not apparent ( Figure 2c ) . Additionally , some cpsII parasites showed atypical morphology , indicative of non-productive cell division ( Figure 2d ) . Collectively , these results confirm that cpsII parasites cannot replicate within host cells , and suggest that cpsII parasites can persist within infected cells , evading IFN-γ-mediated destruction , although they are eventually cleared from the host . To better understand the fate of cpsII parasites in vivo , mice were challenged intraperitoneally with Violet-labeled , mCherry-expressing cpsII parasites , and flow cytometry was performed on the PECS 18 hours later to characterize the cell populations that had phagocytosed T . gondii or were actively infected . The largest population of mCherry+veViolet+ve cells to be infected was CD11bHI macrophages , which comprised 44 . 0±16 . 7% of infected cells . Dendritic cells ( which have been previously implicated in the induction of T cell responses to cpsII [42] ) comprised 8 . 3±2 . 8% of infected cells ( Figure 3a , b ) . Of the infected dendritic cells the vast majority ( 97 . 8±2 . 0% ) belonged to the Gr-1−veCD11bHI subset ( data not shown ) . Although T . gondii is capable of infecting any nucleated cell , when the frequencies of CD11bHI macrophages and dendritic cells within the population of infected cells ( 44 . 0±16 . 7% and 8 . 3±2 . 8% , respectively ) were compared to their frequencies within the total population of peritoneal cells in vaccinated mice ( 11 . 3±7 . 9% and 1 . 3±0 . 4% , respectively ) , it was apparent that macrophages and dendritic cells are overrepresented among cells infected by the parasite ( Figure 3c ) . Analysis of the population that had phagocytosed T . gondii revealed 46 . 0±20 . 6% of these cells were CD11bHI macrophages , whereas dendritic cells represented 6 . 2±3 . 2% of this population ( Figure 3a , b ) . Additionally , 23 . 4±9 . 9% of the cells that had phagocytosed the parasite stained positive for markers for T , B or NK cells ( CD3 , CD19 and NK1 . 1 , respectively ) . Further sub-setting revealed these cells to be B cells , consistent with previous reports identifying a population of phagocytic B cells in the peritoneal cavity ( Figure 3b , data not shown ) [43] , [44] . Parasites were not detected in lymph nodes or spleens by flow cytometry , and parasites could not be cultured from these tissues at days 3 , 5 or 10 post-vaccination . The phenotype of infected cells and those that phagocytosed the parasite was compared by analyzing expression levels of MHCI and MHCII , as well as the costimulatory molecules CD86 and CD40 . Although vaccination with cpsII resulted in an overall increase in expression of MHCI on CD11bHI macrophages , macrophages that had phagocytosed the parasite and those that were infected displayed similar levels of MHCI to the total population present in the PECS of vaccinated mice . In contrast , dendritic cells that had phagocytosed cpsII and those that were infected by the parasite displayed higher levels of MHCI relative to the total dendritic cell population in the peritoneal cavity ( Figure 4a ) . Vaccination with cpsII induced no significant changes in MHCII expression on dendritic cells , although infected macrophages had lower levels of MHCII than the total population in the PECS ( Figure 4b ) . Expression of CD86 was markedly higher on macrophages and dendritic cell populations that were infected by the parasite , but not the populations that had phagocytosed the parasite ( Figure 4c ) . While vaccination induced increased CD40 expression on the total dendritic cell population , infected cells displayed similar expression levels to the total population , and those that phagocytosed the parasite exhibited the highest levels of expression ( Figure 4d ) . Collectively , these results reveal a complex pattern demonstrating that infected macrophages and dendritic cells display activated phenotypes , characterized by the upregulation of MHCI and CD86 , and constitutive expression of CD40 and MHCII , which is distinct from the phenotype of cells that phagocytosed T . gondii . Given the activated phenotype of dendritic cells infected with cpsII versus those that had phagocytosed the parasite , studies were performed to determine the role of dendritic cells in the development of CD4+ and CD8+ T cell responses to this strain . Mice that express the diphtheria toxin receptor under the control of the CD11c promoter ( CD11c-DTR mice ) were used to test the requirement for dendritic cells to prime T cells [45] . In these experiments , CD11c-DTR mice were treated with diphtheria toxin , which resulted in a 70–90% reduction in dendritic cells ( Figure 5a ) . One day following the administration of diphtheria toxin , mice were challenged with a strain of cpsII engineered to express Ovalbumin ( cpsII-OVA ) [38] . At eight days following vaccination , CD4+ and CD8+ T cell responses were measured using MHCII tetramers , which bind CD4+ T cells specific for the endogenous T . gondii epitope CD4Ag28m combined with magnetic enrichment for the tetramer+ve population [46] , [47] , and MHCI tetramers for OVA-specific CD8+ T cells . Additionally , the surface molecule CD11a , which is upregulated on antigen-experienced CD4+ and CD8+ T cells [48] , [49] , and the intracellular molecule Ki67 , which is indicative of cellular proliferation [50] , were used to estimate the total CD4+ and CD8+ T cell responses to T . gondii . Indeed , vaccination with cpsII induced a two-fold increase in the frequency of CD11aHIKi67HI cells and an expansion in the number of CD11aHI CD4+ T cells specific for the CD4Ag28m epitope , but depletion of dendritic cells inhibited these responses ( Figure 5b ) . Similarly , cpsII vaccination induced an increase in CD11aHIKi67HI and OVA-specific CD8+ T cells , however these responses were decreased in mice depleted of dendritic cells ( Figure 5c ) . Furthermore , when Flt3L−/− mice ( which have global defects in numbers of dendritic cells [51] ) or Batf3−/− mice ( which have a defect in numbers of CD8a+ dendritic cells [52] ) were challenged with cpsII-OVA , both mice displayed marked defects in tetramer-specific and total CD4+ and CD8+ T cell responses ( Figure S4 , S5 ) . Given the numbers of macrophages that were either infected or which had phagocytosed T . gondii , experiments were performed to assess their role in the cpsII-induced T cell responses . However , attempts to deplete macrophages using clodronate liposomes also resulted in significant depletion of dendritic cells , making it difficult to assess the specific contribution of macrophages ( data not shown ) . However , because monocytes were observed to interact with parasites ( Figure 3b ) , and these populations can develop into dendritic cells that express CD11c , experiments were performed to assess their role in generating CD4+ and CD8+ T cell responses following cpsII vaccination . Therefore , mice deficient in the chemokine receptor CCR2 , which promotes the recruitment of inflammatory monocytes to sites of inflammation during toxoplasmosis [53] , were immunized with cpsII-OVA parasites . Despite having a defect in monocyte recruitment to the peritoneum , CCR2−/− mice had similar cpsII-induced CD4+ and CD8+ T cell responses to WT control mice ( Figure S6 ) , thus arguing against a critical role for inflammatory monocytes in presenting antigen to CD4+ and CD8+ T cells following cpsII-vaccination . Collectively , these results establish a role for dendritic cells in the generation of CD4+ and CD8+ T cell responses following cpsII vaccination . To assess the contribution of phagocytosis to the generation of CD4+ and CD8+ T cell responses , mice were challenged with live cpsII-OVA parasites , heat-killed cpsII-OVA parasites , or parasites pre-treated with the irreversible inhibitor of invasion 4-p-bpb . As expected , vaccination with live parasites induced a robust CD4+ T cell response , however these responses were abrogated when parasites were killed or invasion was inhibited ( Figure 6a ) . Similarly , CD11aHIKi67HI and OVA-specific CD8+ T cells were detected when mice were administered live , but not heat-killed or invasion-inhibited parasites ( Figure 6b ) . Indeed , even when the dose of heat-killed parasites was increased to 107 parasites ( 100× the typical dose of live parasites used in these experiments ) , no CD4+ or CD8+ T cell responses could be detected ( Figure S7 ) . Additionally , gp91−/− mice , which have a defect in cross-presenting antigens to CD8+ T cells [54] , developed normal CD8+ T cell responses following cpsII-vaccination ( data not shown ) . Collectively , these data indicate that phagocytosis of parasites is insufficient to induce CD4+ and CD8+ T cell responses , and point toward a critical role for infected cells in these processes . To determine whether infected dendritic cells were sufficient to generate CD4+ and CD8+ T cell responses , bone marrow-derived dendritic cells cultured in GM-CSF ( which are CD11bHICD8α−ve ) were infected with violet-labeled , mCherry-expressing cpsII parasites in vitro overnight , and FACS sorting was used to purify the uninfected ( mCherry−veViolet−ve ) and infected cells ( mCherry+veViolet+ve ) from the same cultures , and each of these fractions was then administered to naïve mice . In addition , bone marrow-derived dendritic cells were cultured with invasion-blocked parasites , and the populations of DCs that had phagocytosed the parasite ( mCherry+veViolet−ve ) were also isolated by FACS sorting , and administered to mice . This experiment allowed a direct comparison of the ability of infected dendritic cells and dendritic cells that phagocytosed T . gondii to induce CD4+ and CD8+ T cell responses in vivo . In mice administered uninfected dendritic cells cultured with parasites , or dendritic cells that had phagocytosed parasites , there was no detectable increase in Ki67+veCD11aHI , antigen-experienced CD4+ or CD8+ T cells ( Figure 7a , b ) . In contrast , mice administered cpsII-infected dendritic cells developed CD4+ and CD8+ T cell responses as determined by tetramer-binding as well as expression of Ki67 and CD11a ( Figure 7a , b ) . Furthermore , when vaccinated mice were challenged 6 weeks later with a highly virulent strain of T . gondii , only those mice administered cpsII-infected dendritic cells displayed a ∼90% reduction in parasite burden ( Figure 7c ) . Similar results were obtained using splenic dendritic cells , which are composed of both CD8α+ and CD8α− dendritic cells ( data not shown ) . Moreover , the transfer of sort-purified infected bone marrow-derived macrophages to mice also induced CD4+ and CD8+ T cell responses and protected mice from challenge , whereas the transfer of macrophages that had phagocytosed parasites did not induce T cell responses or protection ( Figure S8 ) . Collectively , these results demonstrate a key role for infected cells in the induction of CD4+ and CD8+ T cell responses , and protective immunity upon re-challenge .
There are many fundamental questions about the mechanisms of antigen presentation that lead to the activation of CD4+ and CD8+ T cells during toxoplasmosis and multiple studies have addressed the ability of actively infected cells to present antigen [12]–[14] , [55] . The present work highlights that following challenge in vitro or in vivo with live parasites there are high rates of phagocytosis and the combination of flow cytometry and parasites that express a single fluorescent reporter protein are not sufficient to distinguish infected cells from those that phagocytose T . gondii . Rather , the ability to combine parasites that express a pH insensitive reporter such as mCherry protein with a pH sensitive dye and analysis by high throughput imaging and flow cytometry provide a unique opportunity to examine parasite fate and host cell phenotype . This approach should be broadly applicable to determining the fate of other intracellular fungal , bacterial and parasitic pathogens [56]–[62] . Regardless , the ability to distinguish active invasion from phagocytosis revealed that macrophages and dendritic cells infected by T . gondii have unique activation phenotypes when compared to those that have phagocytosed the parasite . Previous reports have indicated that infection with T . gondii inhibits the maturation of professional antigen presenting cells [6] , [16] , [18] , [63] , but the data presented here are more consistent with the idea that infection induces DC maturation [36] , [55] , [64]–[66] . The experiments in which dendritic cells were selectively depleted , or pre-infected dendritic cells were transferred to mice highlight the important role of these accessory cells in generating CD4+ and CD8+ T cell responses following cpsII-vaccination . However , these findings do not rule out the possibility that other cell types are also involved . Indeed , the transfer of infected bone marrow-derived macrophages could also induce CD4+ and CD8+ T cell responses , suggesting that resident macrophages may also contribute to the T cell responses that occur following cpsII vaccination . In current paradigms , the direct phagocytosis or endocytosis of soluble and particulate non-infectious antigens is the major pathway that allows antigens to be presented in the context of MHCII to CD4+ T cells [19] . Similarly , phagocytosed antigens are thought to be presented to CD8+ T cells through the process of cross-presentation [8] . However , the multiple approaches presented here indicate that phagocytosis of T . gondii is not sufficient to generate T cell responses . The finding that infected dendritic cells and macrophages display activated phenotypes and are able to promote CD4+ and CD8+ T cells responses in vivo distinguishes them from populations that phagocytose T . gondii . These observations suggest that live ( as opposed to phagocytosed ) parasites may uniquely activate innate sensing mechanisms that are linked to antigen presentation . This may relate to the persistence of parasites that occurs in infected cells , or to the engagement of mechanisms that allow the host to distinguish viable parasites from those that had been phagocytosed and would be killed [67] . The failure of cells that phagocytose the parasite to upregulate expression of CD86 is consistent with this idea . Another possibility is that dendritic cells actively infected with T . gondii display a hypermotile phenotype and enhanced migration to lymph nodes , a process that is considered essential for T cell priming [68]–[72] . Differences in cellular motility between infected cells and those that phagocytose parasites may account for the apparent discrepancy between the previous studies that showed that phagocytosis of parasites is sufficient to prime CD4+ T cells in vitro [12] and our finding that this process is not sufficient in vivo . Regardless of the reasons that cells that phagocytose T . gondii fail to prime T cells , the data presented here are consistent with models in which infected cells either directly prime CD4+ T and CD8+ T cells , or are taken up by efferocytosis ( i . e . the phagocytosis of apoptotic cells ) , leading to antigen presentation . Since T . gondii resides in a specialized non-fusogenic vacuole , it is unclear how parasite antigens may escape the PV for processing and presentation by infected cells . One possibility is that parasite antigens are acquired for presentation from the intracellular environment through the xenophagic elimination of cpsII parasites . Indeed , autophagic machinery has been implicated in the elimination of T . gondii [40] , [73] , [74] , and antigen acquired through autophagy can be subsequently presented [23] , [24] , [75] . However , the lack of recruitment of Irgb6 and LAMP-1 to the PVs containing cpsII parasites argues against this idea . Other possible mechanisms that would allow parasite material to enter antigen processing pathways include the fusion of the PV with the endoplasmic reticulum [12] , the secretion of antigen into the cytoplasm during invasion [76] , or leakage of antigen out of the PV [14] . More recent work has shown that T . gondii can secrete antigens into host cells without subsequently infecting these cells [77] . This population of injected-but-uninfected cells may also contribute to the host immune response , and the ability to track these abortive invasion events in vivo , as well as the ability to divorce injection from infection through modulation of the parasite , may provide further insight into the pathways involved in antigen processing during cpsII vaccination . Given the lack of overt inflammation observed during infection with cpsII parasites , the absence of parasite-driven cytolysis of host cells , and limited antigen load , it remains surprising that relatively low numbers of these parasites are able to generate strong protective CD4+ and CD8+ T cell responses , comparable to those seen during live infection [31]–[33] , [38] , [42] , [78] . Increased antigenic burden is generally associated with increased T cell responses , and inflammatory signals can promote pathways involved in antigen presentation , T cell proliferation , and T cell survival [79]–[81] . Caution is therefore required when extrapolating these findings to natural infection with replicating parasites . Regardless , the finding that phagocytosis is insufficient to induce antigen presentation in this system highlights the importance of alternative approaches to deliver antigens for vaccine design and immunotherapies , such as those that target antigens to the host cell cytosol [82] . Furthermore , while many studies have utilized models of murine infection to elucidate the factors involved in the generation of T cell responses and the formation of memory T cells , vaccination with cpsII parasites allows these processes to be studied in a setting in which overt inflammation is limited . Thus , this experimental system may prove valuable to dissect basic principles that lead to the generation of long-lived T cell responses that translate easily to vaccine design , where inflammation should also be limited .
All procedures involving mice were reviewed and approved by the Institutional Animal Care and Use Committee of the University of Pennsylvania ( Animal Welfare Assurance Reference Number #A3079-01 ) and were in accordance with the guidelines set forth in the Guide for the Care and Use of Laboratory Animals of the National Institute of Health . Flt3L−/− mice were obtained from Taconic Farms ( Germantown , NY ) . Batf3−/− mice , CCR2−/− and CD11c-DTR mice were obtained from Jackson Laboratories . C57BL/6 mice were obtained from Jackson Laboratories or Taconic Farms . All mice were kept in specific-pathogen-free conditions at the School of Veterinary Medicine at the University of Pennsylvania . For experiments in which dendritic cells were depleted , CD11c-DTR or WT control mice were administered 100 ng of Diphtheria Toxin ( Sigma-Aldrich ) diluted in 100 µL of PBS ( Invitrogen ) intraperitoneally ∼12 hours prior to vaccination . Depletion efficiency was typically 90% . All experiments were performed using cpsII parasites , cpsII-OVA parasites [38] , cpsII-OVA-mCherry parasites , or RH-OVA-Tomato parasites . RH-OVA-Tomato parasites [83] and cpsII-OVA parasites [38] , [84] have been previously described . CpsII-OVA parasites and were derived from the RHΔcpsII clone , which was provided as a generous gift by Dr . David Bzik [31] . CpsII-OVA-mCherry parasites were derived from the cpsII-OVA clone using the previously described methods [76] , [77] , with the exception that parasites were selected using zeomycin as previously described [85] . Parasites were cultured and maintained by serial passage on human foreskin fibroblast cells in the presence of parasite culture media [71 . 7% ( Corning ) , 17 . 9% Medium 199 ( Invitrogen ) , 9 . 9% Fetal Bovine Serum ( FBS ) ( Invitrogen ) , 0 . 45% Penicillin and Streptomycin ( Invitrogen ) ( final concentration of 0 . 05 units/ml Penicillin and 50 µg/ml Streptomycin ) , 0 . 04% Gentamycin ( Invitrogen ) ( final concentration of 0 . 02 mg/ml Gentamycin ) ] , which was supplemented with uracil ( Sigma-Aldrich ) ( final concentration of 0 . 2 mM uracil ) in the case of cpsII , cpsII-OVA and cpsII-OVA-mCherry parasites . For infections , parasites were harvested and serially passaged through 18 , 20 and 26 gauge needles ( BD ) before filtration with a 5 µM filter ( Sartorius Stedim ) . Parasites were washed extensively with PBS and mice were injected intraperitoneally with 105 or 106 parasites suspended in PBS . In vitro experiments were performed at an MOI of 0 . 5 or 1 . For experiments in which CellTrace Violet ( Invitrogen ) was utilized to track the fate of parasites , CellTrace Violet was diluted in 200 µL of DMSO to obtain a 0 . 5 mM stock solution . Parasites were washed once with PBS before incubation in 0 . 5 µM CellTrace Violet diluted in PBS for 10–25 minutes at 37°C . This reaction was quenched by the addition of ∼40 volumes of complete media [88 . 5% RPMI 1640 ( Corning ) , 8 . 8% FBS ( Invitrogen ) , 0 . 9% Sodium Pyruvate ( Gibco ) , 0 . 9% Penicillin and Streptomycin ( Invitrogen ) ( final concentration of 0 . 1 units/ml Penicillin and 100 µg/ml Streptomycin ) , 0 . 9% MEM Non-essential Amino Acids Solution ( Gibco ) and 0 . 18% beta-2-mercaptoethanol ( Gibco ) ] and parasites were washed extensively . In experiments in which 4-p-bromophenacyl bromide ( 4-p-bpb ) was utilized to inhibit parasite invasion , 4-p-bpb ( Sigma-Aldrich ) was prepared fresh for each experiment and dissolved in DMSO ( Sigma-Aldrich ) to make a 0 . 1 M stock solution . Parasites were incubated in a 100 µM solution of 4-p-bpb in Fetal Bovine Serum at a concentration of 107 parasites/ml for 10 minutes , and the reaction was quenched by the addition of ∼40 volumes of complete media , followed by extensive washing [12] . To heat-kill parasites , parasites were incubated at 60°C for 1 hour in PBS [86] . Death was confirmed using Trypan Blue staining ( Corning ) . Peritoneal exudate cells were obtained by peritoneal lavage with 5 ml of PBS . Splenocytes and lymphocytes were obtained by grinding spleens and lymph nodes over a 40 µM filter ( Biologix ) and washing them in complete media . Red blood cells were then lysed by incubating for 5 minutes at room temperature in 5 ml of lysis buffer [0 . 864% ammonium chloride ( Sigma-Aldrich ) diluted in sterile de-ionized H2O ) ] , followed by washing with complete media . Bone marrow-derived macrophages were obtained using previously described methods [83] , [87] . Immortalized macrophages from C57BL/6 mice were obtained by transforming bone marrow-derived macrophages with the J2 Virus and were cultured in macrophage media [88] . Tetramer-specific CD4+ T cells were measured using the protocol previously described [46] . MHCII Tetramer was obtained as generous gifts from Drs . Marc Jenkins and Marion Pepper , and subsequently from the NIH Tetramer Core Facility , and was used at a final concentration of 10 nM . APC-MHCI-SIINFEKL Tetramer was obtained from Beckman-Coulter . Cells were washed with FACS Buffer [1× PBS , 0 . 2% bovine serum antigen ( Sigma ) , 1 mM EDTA ( Invitrogen ) ] , stained with LIVE/DEAD Fixable Aqua Dead Cell marker ( Invitrogen ) and incubated in Fc block [99 . 5% FACS Buffer , 0 . 5% normal rat serum ( Invitrogen ) , 1 µg/ml 2 . 4G2 ( BD ) ] prior to staining . The following antibodies were used for staining: Ki67 Alexa Fluor 488 ( BD , B56 ) , CD3 APC-eFluor 780 ( eBioscience , 17A2 ) , CD8 eFluor 450 ( eBioscience , 53-6 . 7 ) , CD11a PerCP-Cy5 . 5 ( Biolegend , H155-78 ) , MHCII PE ( eBioscience , M5/114 . 15 . 2 ) , NK1 . 1 PE ( BD , PK136 ) , CD19 PE ( eBioscience , 1D3 ) , Foxp3 eFlour 450 ( eBioscience , FJK-16a ) , CD4 Pe-Cy7 ( eBioscience , GK1 . 5 ) , CD3 FITC ( BD , 145-2C11 ) , NK1 . 1 FITC ( eBioscience , PK136 ) , CD19 FITC ( eBioscience , 1D3 ) , Gr-1 PerCP-Cy5 . 5 ( eBioscience , RB6-8C5 ) , CD11c PE-Cy7 ( eBioscience , N418 ) , CD11b APC-eFluor 780 ( eBioscience , M1/70 ) , MHCII AF700 ( Biolegend , M5/114 . 15 . 2 ) , MHCI APC ( AlexaFlour647 AF6-88 . 5 ) , CD86 APC ( eBioscience , GL1 ) , CD40 APC ( eBioscience 1C10 ) , CD8 eFlour 650 NC ( eBioscience , 53-6 . 7 ) , CD45 . 2 APC-eFluor 780 ( eBioscience , 104 ) , polyclonal rabbit anti-T . gondii [a generous gift from Fausto G . Araujo ( Palo Alto Medical Foundation , Palo Alto , CA ) ] , and polyclonal Goat anti-Rabbit Alexa Fluor 680 ( Jackson ) . Intracellular staining was performed using the Foxp3/Transcription Factor Staining Buffer Set ( eBioscience ) following the manufacturer's instructions . Samples were run on a FACSCanto ( BD ) or LSR Fortessa ( BD ) and analyzed using FlowJo Software ( TreeStar ) . Images were obtained using the ImageStream and analysis was performed using IDEAS software ( Amnis ) . Splenic dendritic cells were obtained from mice injected subcutaneously with Flt3L-secreting b16 tumor cells [89] , [90] and magnetically enriched using CD11c microbeads ( Miltenyi Biotech ) and LD MACS separation columns ( Miltenyi Biotech ) , following the manufacturer's instructions . Bone marrow-derived dendritic cells were obtained by culturing bone marrow cells in the presence of 40 ng/ml of GM-CSF , which was added at days 0 , 3 , 6 and 9 post-seeding . Dendritic cells or bone marrow-derived macrophages were cultured overnight with parasites at 37°C and collected the following day . Dendritic cells were then stained for MHCII , CD11c , CD45 , and free parasites , and sorted for mCherry+veViolet+ve , mCherry+veViolet−ve or mCherry−veViolet−ve populations that were CD45+MHCIIHICD11cHI , and negative for free parasites using the FACSAria ( BD ) . Macrophages were stained for CD45 and free parasites and sorted into mCherry+veViolet+ve , mCherry+veViolet−ve or mCherry−veViolet−ve populations that were CD45+ and negative for free parasites . Bone marrow-derived macrophages from C57BL/6 mice were activated with IFN-γ and LPS for 18–24 hours or left untreated in macrophage media lacking uracil [DMEM ( Gibco ) supplemented with 4 mM L-glutamine ( Sigma ) and 10% dialyzed fetal bovine serum ( Hyclone ) ] . Where indicated , cells were infected with freshly egressed parasites , washed three times with PBS then fixed at 2 hours or 24 hours post-infection . For ultrastructural analysis , cells were fixed in 2% paraformaldehyde/2 . 5% glutaraldehyde ( Polysciences Inc . , Warrington , PA ) in 100 mM phosphate buffer , pH 7 . 2 for 1 hour at room temperature , processed and examined as described previously [91] . Immunofluorescence assays were performed in C57BL/6 bone marrow-derived macrophages . Bone marrow-derived macrophages for these experiments were derived as described previously [91] . Cells were activated with 100 U/ml IFN-γ and 0 . 1 ng/ml LPS in macrophage media lacking uracil . Macrophages were infected with freshly egressed parasites at an MOI of 1 , washed at 3 hours post-infection five times with PBS , and incubated in uracil-free media supplemented with IFN-γ and LPS for the indicated time . Heat-killed parasites were incubated at 65°C for 10 minutes and infected at an MOI of 5 . Cells for immunofluorescence were fixed in 4% formaldehyde , permeabilized with 0 . 05% saponin , and stained using primary antibodies as described . Parasite vacuoles were localized using mouse monoclonal Tg17-43 against GRA1 or rabbit polyclonal sera against GRA7 . Host LAMP-1 was localized with rat monoclonal antibody 1D4B and Irgb6 was localized using rabbit polyclonal sera raised against recombinant protein [92] . All secondary antibodies used in immunofluorescence were highly-cross adsorbed Alexa Fluor conjugated antibodies ( Invitrogen ) . Samples were visualized using a Zeiss Axioskop 2 MOT Plus microscope equipped for epifluorescence and using a 63× PlanApochromat lens , N . A . 1 . 40 ( Carl Zeiss , Inc . , Thornwood , NY ) . Images were acquired with an AxioCam MRm camera ( Carl Zeiss , Inc . ) using Axiovision v4 . 6 , and processed using similar linear adjustments for all samples in Photoshop CS4 v9 . Bone marrow-derived macrophages were cultured with invasion-blocked or untreated mCherry-expressing cpsII parasites ( MOI = 1 ) and LysoTracker Green DND-26 ( Life Technologies ) was added prior to imaging , following the manufacturer's instructions . Images were collected using a Leica DMI4000 microscope equipped with a Yokogawa CSU10 spinning disk confocal unit and a Hamamatsu ImagEM EMCCD camera . Images were analyzed using ImageJ software . Statistical analysis was performed using PRISM software ( Graphpad Software ) . Significance was calculated using an unpaired two-tailed student's t-test except when otherwise noted . | CD4+ and CD8+ T cells are critical for controlling many infections . To generate a T cell response during infection , T cells must encounter the microbial peptides that they recognize bound to MHC molecules on the surfaces of other cells , such as dendritic cells . It is currently unclear how dendritic cells acquire the antigens they present to T cells during infection with many intracellular pathogens . It is possible that these antigens are phagocytosed and processed by dendritic cells , or antigens may be presented by cells that are infected by pathogens such as Toxoplasma gondii , which invades host cells independently of phagocytosis . To differentiate these pathways , we developed a novel technique to track the fate of T . gondii in vivo that distinguishes actively infected cells from those that phagocytosed parasites . This technique was used to examine each of these cell populations . We also used pharmacological inhibitors of parasite invasion , and the transfer of sort-purified infected or uninfected dendritic cells and macrophages to determine what roles phagocytosis and active invasion have in the initiation of T cell responses . Our results demonstrate that phagocytosis of parasites is not sufficient to induce CD4+ or CD8+ T cell responses , whereas infected cells are critical for this process . | [
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] | 2014 | Parasite Fate and Involvement of Infected Cells in the Induction of CD4+ and CD8+ T Cell Responses to Toxoplasma gondii |
By modifying the nuclear genome of its host , the plant pathogen Agrobacterium tumefaciens induces the development of plant tumours in which it proliferates . The transformed plant tissues accumulate uncommon low molecular weight compounds called opines that are growth substrates for A . tumefaciens . In the pathogen-induced niche ( the plant tumour ) , a selective advantage conferred by opine assimilation has been hypothesized , but not experimentally demonstrated . Here , using genetics and structural biology , we deciphered how the pathogen is able to bind opines and use them to efficiently compete in the plant tumour . We report high resolution X-ray structures of the periplasmic binding protein ( PBP ) NocT unliganded and liganded with the opine nopaline ( a condensation product of arginine and α-ketoglurate ) and its lactam derivative pyronopaline . NocT exhibited an affinity for pyronopaline ( KD of 0 . 6 µM ) greater than that for nopaline ( KD of 3 . 7 µM ) . Although the binding-mode of the arginine part of nopaline/pyronopaline in NocT resembled that of arginine in other PBPs , affinity measurement by two different techniques showed that NocT did not bind arginine . In contrast , NocT presented specific residues such as M117 to stabilize the bound opines . NocT relatives that exhibit the nopaline/pyronopaline-binding mode were only found in genomes of the genus Agrobacterium . Transcriptomics and reverse genetics revealed that A . tumefaciens uses the same pathway for assimilating nopaline and pyronopaline . Fitness measurements showed that NocT is required for a competitive colonization of the plant tumour by A . tumefaciens . Moreover , even though the Ti-plasmid conjugal transfer was not regulated by nopaline , the competitive advantage gained by the nopaline-assimilating Ti-plasmid donors led to a preferential horizontal propagation of this Ti-plasmid amongst the agrobacteria colonizing the plant-tumour niche . This work provided structural and genetic evidences to support the niche construction paradigm in bacterial pathogens .
The widespread pathogen Agrobacterium tumefaciens evolved a unique process of niche construction inside the host plant: it transfers a portion ( T-DNA ) of its tumour-inducing ( Ti ) plasmid into the nuclear genome of the infected plant cells [1] , [2] . In the stably transformed host cells , the expression of the T-DNA genes drives synthesis of the plant growth factors auxin and cytokinins that enhance cell proliferation and vascular differentiation . In parallel , the surface and intercellular spaces of the neoplastic tissues of the tumour - that is a characteristic symptom of the crow-gall disease - are colonized by the bacterial pathogen . The carbon and nitrogen metabolisms of the transformed cells are also diverted . The T-DNA codes for the enzymatic synthesis of unusual metabolites . These diverse derivatives of sugars , phosphorylated or not , or amino , or organic acids are called opines [3]–[6] . As an example , the well-studied A . tumefaciens strain C58 induces accumulation of different opines such as nopaline that is formed from arginine and α-ketoglutarate ( α-KG ) and agrocinopines A and B that are non-nitrogenous phosphodiesters of sugars . Besides the opine synthesis genes carried on the T-DNA , the Ti-plasmid also harbours genes involved in the uptake and catabolism of the opines by A . tumefaciens . In other words , the bacteria carrying a Ti-plasmid can benefit from the opines produced by the cells of the plant tumours that express the appropriate T-DNA genes . Aside , some opines , the so-called conjugative opines such as agrocinopine , trigger the quorum-sensing pathway which in turns activates the horizontal transfer ( bacterial conjugation ) of the Ti-plasmid [7] . As a consequence , the tumour niche was called the opine niche , and the niche construction process was theorized as the opine concept [3] , [4] . This concept highlights the key-role of opines in the maintenance and dissemination of the Ti-plasmids among the agrobacteria colonizing the plant host . Experimental evaluation of the validity of the opine concept was performed by measuring the selective advantage conferred to opine-assimilating bacteria , including agrobacteria and other species , in opine-rich environments , such as a culture medium or the rhizosphere and phyllosphere of opine-producing plants [8]–[13] . However , to our knowledge , this hypothesis has not been tested in the natural opine niche , i . e . the plant tumour , making the opine concept in the Agrobacterium-plant host interaction formally still unproven . In A . tumefaciens , the recognition and import of opines is conferred by periplasmic binding proteins ( PBPs ) and their associated ATP-binding cassette ( ABC ) transporters [14] , [15]; but there is no known structure of the opine-PBP complex . In this work , we investigated the structural and biochemical properties of the PBP NocT of A . tumefaciens C58 which senses at least two opines: nopaline and pyronopaline , a lactam nopaline-derivative that can also be found in plant tumours [16] , [17] . In addition , the complete set of A . tumefaciens genes transcriptionally responsive to these opines was identified and the fitness advantage conferred by opine assimilation upon A . tumefaciens was measured directly in the plant tumours . This integrative work highlights the structural and functional characteristics of opine binding and assimilation in the niche construction process evolved by the plant pathogen . It also definitely provides evidence to support the opine concept that directs the A . tumefaciens plant-host interaction .
The X-ray structures of the mature free-liganded NocT and the two liganded NocT with pyronopaline and nopaline were obtained at 1 . 89 Å , 1 . 55 Å and 2 . 29 Å resolutions , respectively ( Table S1 ) . Each crystal contained two very similar molecules in the asymmetric unit as indicated by the overall root mean square deviations ( RMSD ) for all Cα atoms of 0 . 6 Å , 0 . 46 Å , and 0 . 28 Å respectively . The two liganded forms adopted a similar closed conformation ( RMSD of 0 . 3 Å for all Cα ) while the unliganded form showed an open conformation ( Figure 1 ) as commonly reported for the structures of PBPs solved with and without a ligand [18]–[20] . A 43° rotation around the hinge region of the C-terminal domain ( residues 117–231 ) was observed once the N-terminal domains ( residues 29–112 and 239–284 ) of the unliganded and liganded structures were superimposed leading to a movement of 16 Å for Thr168 . NocT possesses a typical fold of cluster F within the PBP structural classification [21] . Indeed , a structural comparison of its closed form to all entries in the PDB using SSM-EBI ( http://www . ebi . ac . uk/msd-srv/ssm [22] ) showed that the most similar overall structures were PBPs from the same cluster F , i . e . the liganded structure of the histidine binding protein HisJ ( PDB code 1HSL ) of Escherichia coli and that of the lysine-arginine-ornithine binding protein LAO ( PDB code 1LAF ) of Salmonella enterica [23] , [24] . RMSD values of NocT vs . HisJ and LAO ranged from 1 . 47 to 1 . 5 Å over 226/228 Cα atoms , corresponding to a sequence identity of 38 and 36% respectively . The nopaline and pyronopaline bound between the two closed lobes were very well defined in their respective electron density maps ( Figure 2 ) . The ligand-binding site of NocT was defined by the Glu36 , Tyr39 , Tyr42 , Trp77 , Ala94 , Ala95 , Gly97 , Arg102 , Thr115 , Met117 , Gln165 , Thr168 , Ser169 , His170 , Ser207 , Gly238 and Val239 residues . Overall both ligands shared the same protein binding mode for their arginine moiety . The side chain of this moiety was wedged between two aromatic residues ( Trp77 and Tyr39 ) and pointed toward the opening of the cleft by making seven hydrogen bonds with the side chains of Gln165 and Glu36 and the carbonyl of Ala94 ( Figure 2 ) . Its carboxyl group made a salt-bridge with the side chain of Arg102 and interacted with both NH of Gly97 and Ser169 while its NH group formed a hydrogen bond with the carbonyl of Ala95 . Remarkably this hydrogen bond cannot exist with pyronopaline due to the lactam structure of the molecule . Concerning the α-KG parts of both ligands , their first carboxyl group adopted a different position ( shift around 1 Å of the two oxygen atoms ) , but made similar hydrogen bonds with NocT involving the side chains of Tyr39 , His170 and Ser207 as well as the NH of Ser207 . An additional bond was observed between the Met117 side chain and the nopaline . In the pyronopaline , the hydroxyl of the terminal carbon covalently linked to the N atom interacted with the side chain of Ser169 whereas in the nopaline , each oxygen from the terminal carboxylate group of the α-KG moiety formed two water-mediated interactions with the main chains of Thr115 for one water and with the CO of Phe235 and the S169 side chain for the other water ( Figure S1 ) . An analogous water molecule interacting with the CO main chain of Phe235 in the pyronopaline-liganded structure was shifted by 1 . 4 Å and bound the Gln99 side chain which appeared well ordered in this structure . The large mobile residue Met117 was forced to accommodate its side chain position according to the type of bound ligand and made Van der Walls contacts with the pyronopaline ( Figure S1 ) . The rearrangement of the side chain ( shift of 1 . 9 Å ) in the pyronopaline structure compared with the nopaline structure led to a rearrangement of the carboxyl moiety of the α-KG and of the H170 side chain ( Figure S1 ) . By intrinsic protein fluorescence titration , the dissociation constant ( KD ) values between NocT and nopaline and pyronopaline were 3 . 7±0 . 6 and 0 . 57±0 . 07 µM respectively ( Figure S2 ) . These apparent KD values were in the low micromolar range usually observed for PBP ligands [21] . Using isothermal titration calorimetry ( ITC ) , the mean KD value between NocT and pyronopaline was determined as 0 . 58±0 . 05 µM ( Figure S2 ) , identical to that obtained by fluorescence measurement . The ITC data also confirmed the 1∶1 binding stoichiometry and demonstrated a positive enthalpy change upon pyronopaline binding . This binding reaction was entirely driven by a large favorable increase in entropy ( TΔS = 12 . 6 kcal/mol ) . With both fluorescence titration and ITC techniques , no interaction could be measured between NocT and arginine; ITC also revealed no interaction between NocT and histidine or ornithine ( Figure S2 ) . Around the arginine moiety of the nopaline/pyronopaline ligand , the ligand binding site of NocT resembled those of the PBPs HisJ and LAO which have been shown to bind arginine and other amino acids ( Figure 3 ) . Two residues were conserved in NocT , HisJ and LAO: Tyr39 ( Tyr14 in LAO ) which stacked the arginine side chain ligand and Arg102 ( Arg77 in LAO ) which bound the carboxyl group of the arginine ligand . Glu36 was replaced by an equivalent Asp residue that preserved the interaction with the guanidinium group of the ligand . The position of the side chain arginine ligand and that of its carboxyl group were similar in the three PBPs leading to similar polar interactions . The amino group of the arginine ligand was tightly bound in HisJ and LOA with the side chains of a serine at position 72 ( corresponding to Gly97 in NocT ) and an aspartate at position 161 ( Ser207 in NocT ) . Importantly , these two major interactions will be lost in NocT leading to a less efficient binding of an arginine ligand in line with the observed absence of detectable interaction between NocT and arginine by ITC and fluorescence titration . The presence of Gly97 in NocT seems especially essential for the spatial accommodation of the α-KG moiety of nopaline/pyronopaline whereas the equivalent residue ( Ser72 ) in HisJ and LAO seems incompatible with nopaline or pyronopaline binding due to steric clash . In A . tumefaciens strains harbouring an octopine-type Ti plasmid , the PBP OccJ allows the uptake of the opine octopine which is a condensate of arginine and pyruvate [25] . Interestingly , NocT seems involved in the importation of nopaline and octopine ( only in the presence of nopaline ) , whereas OccJ permits the importation of octopine but not that of nopaline ( [25] , [26] . The structure of OccJ is unknown . Sequence comparison between NocT and OccJ shows that among the 12 residues of NocT which directly interact with nopaline/pyronopaline , 4 are different in OccJ . These are G97 , M117 , H170 and S207 in NocT which correspond to serine , asparagine , alanine and asparagine residues in OccJ , respectively . As mentioned above in the NocT/LAO/HisJ comparison , the replacement of Gly97 in NocT by a serine at the equivalent position might be responsible for preventing OccJ from binding nopaline . Moreover M117 , H170 and S207 interact only with the α-KG moiety of nopaline/pyronopaline . We therefore define these 4 amino acids G97M117H170S207 as the nopaline-binding signature . To learn more on the role of Met117 residue in the interaction between NocT and its ligand , we constructed two NocT mutants with different short polar residues: NocT-M117N because an asparagine is found in the OccJ sequence and NocT-M117S because a serine is found in the LAO/HisJ sequences . Both mutants displayed a similar KD for pyronopaline that was 76-fold higher than that of the WT protein , proving that Met117 is a key component of the ligand affinity and belongs to the nopaline-binding signature . We also obtained the structure of NocT-M117N in complex with pyronopaline ( Table S1 ) . Prior to this , the stability of NocT-M117N was verified using differential scanning calorimetry ( DSC ) and , compared to the WT protein , the mutant presented similar Tm ( 60 . 12°C versus 60 . 25°C for the WT ) and ΔH ( 1 . 59 105 cal/mol/°C versus 1 . 4 105 cal/mol/°C for the WT ) ( Figure S3 ) , meaning that mutating M117 has no significant effect on protein stability . The structure of NocT-M117N in complex with pyronopaline confirmed that the replacement of Met117 with Asn led to a loss of hydrophobic interaction with the ligand and showed that His170 which is free to move towards Asn117 bound the carboxyl group of the α-KG of the pyronopaline in a position not observed in the WT complexes ( Figure S4 ) . A loss of the polar interaction between the side chain of Ser169 and the terminal OH of the pyronopaline ring was also observed due to steric hindrance . Five hundred bacterial NocT-homologous PBPs with a threshold set at at least 40% of identity were recovered using blastp at NCBI . To these were added 53 other homologous sequences found in the Agrobacterium genomes of the AgrobacterScope genome library ( Genoscope , France ) . The relation tree constructed from these 553 sequences revealed different subgroups . The closest NocT relatives were used to build a novel relation tree rooted with the HisJ and LAO sequences ( Figure 4 ) . Members of the NocT subgroup were highly similar PBPs which belong to the A . tumefaciens strains C58 , S56 , Zutra3-1 , Kerr14 ( biovar 1 ) , and A . radiobacter K84 ( biovar 2 ) . All of them are nopaline-assimilating agrobacteria . Their genomes exhibited a strong synteny with respect of the noc operon region of A . tumefaciens C58 . Moreover , all these NocT proteins retained the nopaline-binding signature G97M117H170S207 . Outside the NocT subgroup , the nopaline-binding signature was strongly degenerated , but the arginine-binding signature was conserved in some proteins , such as one PBP of the marine alpha-proteobacterium BAL199 ( NCBI BioProject PRJNA54661 ) . These features suggested that the ability to bind nopaline was highly specific to members of the NocT PBP-subgroup , and that NocT and some arginine-PBPs could have evolved from a common ancestor . The capability of NocT to bind pyronopaline suggested that A . tumefaciens C58 could use the same pathway for the assimilation of nopaline and pyronopaline . To test this hypothesis , we constructed two A . tumefaciens C58 KO-mutants that were affected in the binding and transport ( nocT ) and catabolism ( ocd ) of nopaline . When nopaline or pyronopaline were used as sole sources of carbon and nitrogen and when nopaline was used as a sole source of carbon in the presence of inorganic nitrogen , the nocT mutant could not grow while the growth of ocd mutant was strongly impaired ( Figure 5A ) . These features established that nopaline and pyronopaline were assimilated by the same catabolic pathway Noc , which had been previously characterized for nopaline [27] . In this pathway ( Figure 5B ) , the nopaline is cleaved into α-KG and arginine by the enzymatic complex NoxAB; then , the degradation of arginine into proline is completed by the enzymes Arc , ArcA and Ocd , and the conversion of proline into glutamate , a C and N-source , by the enzyme PutA ( = Atu4157 ) [27]–[30] . Furthermore , we delineated the nopaline and pyronopaline regulon by transcriptomics . In this experiment , an accR mutant of A . tumefaciens C58 was used because this mutant expresses the transcriptional regulator NocR at a higher level than does the wild type strain [31] . In presence of nopaline NocR induces the expression of the noc genes [32] . Consequently , an optimal expression of the nopaline regulon was expected in the accR genetic background . Noticeably , the accR mutant also mimics the condition of an exposure to the opine agrocinopine that accumulates in A . tumefaciens C58-induced plant tumours [33] . Comparative transcriptomics in cell culture of an accR mutant grown in the presence or absence of nopaline and pyronopaline should therefore reveal nopaline/pyronoplaine responsive genes in a context reminiscent of the plant tumour environment . With this approach , 32 differentially ( Fch>3; P<0 . 05 ) expressed genes of A . tumefaciens C58 were identified in the presence of nopaline/pyronopaline , 8 of them being downregulated and 24 upregulated ( Table S2 ) . Subsequent RT-qPCR experiments on a selection of genes ( cysJ , arcA , nocT , nocP and noxB ) confirmed the micro-array results ( Table S2 ) . The highest upregulated genes ( Fch>20 ) included the noc operons of the Ti-plasmid [14] and an arginase-encoding gene ( arcA = atu4007 ) located on the linear chromosome . As no other catabolic functions were affected , we suggest to refer to these highly-expressed genes as the nopaline/pyronopaline core-regulon ( Table S2 ) . In the tumours induced on tomato plants , we measured the level of nopaline and pyronopaline . Nopaline but not pyronopaline could be detected by mass spectrometry . Moreover , nopaline accumulated at significant and equivalent levels in tumour tissues induced by the C58-control and by the nocT strains ( Figure 6A ) . We therefore confirmed that the tumour niche is a natural nopaline-rich environment . However , as the quantification of nopaline was performed on whole plant tumour extracts , it remains possible that only a small fraction of this nopaline is available to the A . tumefaciens cells colonizing the exterior surface of the tumour . Thereafter , we investigated the selective advantage conferred upon A . tumefaciens C58 by the nopaline pathway in plant tumours . In addition to the nocT and ocd mutants that were impaired in the assimilation of nopaline , we constructed a nos mutant that was defective for the synthesis of the nopaline by the tumour cells ( see nopaline pathway in the Figure 5 ) . When these mutants were individually used to inoculate tomato plants , they colonized the tumour tissues at population sizes ( 105 CFU/mg FW ) similar to that reached by the C58-control strain ( Figure 6B ) . Hence , the tumour environment provides enough nutrients to support the growth of the pathogens whatever their capacities to produce , transport or catabolize the nopaline and pyronopaline . In a second experiment , the nos , nocT and ocd KO-mutants were co-inoculated with the C58-control strain in presence of the recipient strain C58 . 00 ( free of Ti and At plasmids ) . For each of these conditions the mixed populations colonized the plant tumours at levels ( total cell number at 105 CFU/mg FW ) that were similar to those reached in the single infections . The frequency of Ti-plasmid donors was determined at the infection time and in the plant tumours to allow the calculation of competitive indexes ( CI , see materials and methods ) . As expected , the CI value reached 1 . 0 in the competition between the nos mutant and C58-control . In this case , nopaline that is synthesized via the expression of the wild-type T-DNA gene , benefited equally to the two co-inoculated nopaline-utilizing populations ( nos mutant and C58-control ) . In contrast , CI values were only 0 . 35 and 0 . 07 in the competitions that involved nocT or ocd mutants and C58-control , respectively . These low CI values revealed that the C58-control population significantly outcompeted nocT and ocd populations which were unable to assimilate nopaline ( Figure 6C ) . Unlike agrocinopines A and B , nopaline is not a conjugative opine in A . tumefaciens C58 , hence the regulation of the plasmid Ti-transfer genes is independent of the presence and concentration of nopaline . In the above plant tumour assays , we were therefore also able to evaluate the capacity of each of the competitors to disseminate its Ti-plasmid into the recipient strain C58 . 00 . In plant tumours , Ti-plasmid transconjugants reached up to 102 CFU/mg FW . The proportion of transconjugants which acquired the Ti-plasmid from each of the two donors in competition was measured ( Figure 6C ) . We observed that , among transconjugants , the relative abundance of the Ti-plasmid that conferred nopaline-assimilation was higher than that of the Ti-plasmid that did not confer nopaline-assimilation . Preferential accumulation of the nopaline-using transconjugants we observed could simply mirror the relative abundance of Ti-plasmid donors in the tumour niche . The competitive advantage which is conferred by opine assimilation could therefore also contribute to dominance of opine-using transconjugants over non-users .
This work revealed the structural basis of the PBP NocT that is required for the binding and assimilation of the opines nopaline and pyronopaline in A . tumefaciens C58 . Structural and amino-acid sequence analyses showed that NocT was unique among more than 150 PBPs that are encoded by the A . tumefaciens C58 genome [34] . Genome data-base analysis also showed that close homologues of NocT can be only found in the nopaline-assimilating strains of the genus Agrobacterium: either in the pathogenic strains C58 , S56 , Zutra 3-1 , and Kerr 14 belonging to the A . tumefaciens species complex , or in non-pathogenic ones such as the biocontrol strain A . radiobacter K84 which carries the nopaline binding nocT gene on a 185-kbp plasmid [35] . In combination with toxin production [36] , [37] , nopaline assimilation might contribute to the capacity of A . radiobacter K84 to compete with A . tumefaciens pathogens in the plant environment . Based on our data we cannot rule out the possibility that other nopaline-assimilating isolates of different Agrobacterium species for whom genome sequence is still unknown could also possess a NocT PBP [38] , [39] . Previous reports established that the two PBPs LAO ( Salmonella ) and HisJ ( Escherichia ) , structurally close to NocT , can bind basic amino acids such as arginine [23] , [24] . The resemblance between NocT and LAO/HisJ structures and ligand binding sites is not surprising because nopaline and pyronopaline are L-arginine derivatives . However , we showed here that NocT cannot bind arginine ( nor histidine and ornithine ) probably due to the absence of two essential side chains ( Ser72 and Asp161 in LAO corresponding to Gly97 and Ser207 in NocT ) , both locking the α-amine . The absence of binding between arginine and NocT might confer two advantages . First it might prevent arginine from competing with nopaline for uptake by the Noc system and second it might prevent NocT from becoming saturated with arginine if it cannot pass on to the nopaline transporter . In parallel the presence of a Ser in LAO and HisJ at the equivalent position of Gly97 in NocT which creates a steric hindrance for the accommodation of nopaline and pyronopaline might prevent these molecules from competing with arginine , ornithine or histidine for being bound by their respective PBPs . The NocT structure is proposed as a reference for further structural comparisons with PBPs involved in the sensing and uptake of other opines , such as agrocinopine [15] and octopine [35] . The opine octopine is a condensate of arginine and pyruvate , therefore structurally close to nopaline . In A . tumefaciens strains harbouring an octopine-type Ti plasmid , octopine is recognized by the PBP OccJ and then transported into the cytoplasm where it acts both as a nutrient and a conjugative signal [25] . Interestingly , NocT is involved in the uptake of nopaline and that of octopine in the presence of nopaline; in contrast , OccJ is involved in the uptake of octopine but not nopaline [25] , [26] . Although OccJ and NocT share little homology ( 48% of identity ) 8 of the 12 residues interacting with nopaline in NocT are conserved in OccJ . Based on the 4 differences we defined a nopaline-binding signature and highlighted the importance of Gly97 in NocT for spatial accommodation of nopaline/pyronopaline . This signature notably explains why among LAO , HisJ , NocT and OccJ - which all share strong similarities for the arginine moiety of their ligand- NocT is unique in its ability to bind nopaline/pyronopaline . Further elucidation of the octopine-liganded structures of the PBPs OccJ and NocT would be informative in order to understand the binding properties of octopine and compare it with those of nopaline . Moreover , as enzymes encoded by the noc genes are able , once activated , to catabolize octopine [25] , [26] , it would be of great interest to investigate the mechanisms which drive the specific assimilation of nopaline and octopine in A . tumefaciens C58 , and notably the role of the transcriptional regulator NocR which controls the expression of the noc genes . The question about how co-existing A . tumefaciens populations evolved a specialized or generalist capacity in the synthesis and degradation pathways of opines remains to be explored . Some opines , i . e . nopaline , succinanopine and leucinopine can be spontaneously converted into cyclic derivatives under acidic conditions [4] , [16] , [17] . Pyronopaline was detected in tumours induced by A . tumefaciens C58 on the monocot Asparagus officinalis [17] , but its occurrence was not explored further in other plant hosts . In this work , pyronopaline was not detected in the tomato plant-tumours induced by the same pathogen ( i . e . A . tumefaciens strain C58 ) , suggesting that plant genotype and/or growth conditions may influence the nopaline/pyronopaline conversion in vivo . Even though the formation of the gamma-lactam ring strongly modifies the α-KG part of nopaline , we showed that NocT bound pyronopaline with an affinity higher than that it exhibited for nopaline . Interestingly , nopaline formed with NocT one more polar protein interactions than pyronopaline . However , these interactions were shorter for the pyronopaline . In terms of affinity , the present study highlighted the important contribution of hydrophobic contacts as the positive enthalpy of 2 . 1 kcal/mol indicated . The tight contacts of the Met117 side chain with the pyronopaline probably made this ligand conformation preferential for NocT . A combination of transcriptomics and genetics established that A . tumefaciens C58 assimilated nopaline and pyronopaline via the same Ti-plasmid encoded pathway . Hence , regardless of the nopaline/pyronopaline equilibrium in the plant tumours , A . tumefaciens appears to mobilize a unique binding , transport , and assimilation system to use them as nutrients . With respect to the T-DNA/opine-mediated niche construction process , this work experimentally evidenced the validity of the opine concept [3] , [4] within the natural agrobacterial environment that the plant tumour is . Indeed , we demonstrated that binding and assimilation of the opine nopaline contributed to the fitness of A . tumefaciens strain C58 in the plant tumour when nopaline assimilating and non-assimilating bacteria were co-infected . On the opposite , when both bacterial types were infected separately , they multiplied to reach a similar level in the plant tumour . The plant tumour is a nutrient-rich environment in which sugars , amino acids , phosphate and sulfate accumulate [40] . This observation supports the notion that the presence of nopaline , made available for bacteria in tumours , does not increase the carrying capacity of plant-tumour habitat for Agrobacterium pathogens , but selects those able to assimilate it . Using transgenic plants producing opines in all plant tissues but free of Agrobacterium-induced tumour , several studies investigated colonization and fitness of opine assimilating and non-assimilating Pseudomonas in rhizosphere and phyllosphere [10] , [12] , [13] . In all the opine-rich compartments , opine assimilating Pseudomonas outcompeted non-assimilating Pseudomonas . In the same reports , the carrying capacity of the plant tissues was only increased in the carbon-poor phyllosphere compartment , but was not affected in the carbon-rich rhizosphere compartment . The magnitude of the nutrient bias induced by opines seems therefore to directly influence the dynamics and fitness of the bacterial populations . However , it was previously reported that opine accumulation in plant tumour may favor its translocation to other parts of the host plant [41] . This suggests that opines which are stocked in plant tissues could benefit to the pathogen at different times of the infection cycle even after the death of the host plant , by allowing the maintenance of virulent populations ( carrying a Ti-plasmid ) in soil until the infection of a new host .
Using 5′-GGAATTCCATATGAAGGACTACAAAAGCATT and 5′-TTTGCGGCCGCTTAATGGTGATGGTGATGGTGCTGCTTGGGGGAGGCGTC primers , nocT gene of A . tumefaciens C58 was amplified and then cloned into pET-9aSN1 expression vector ( a gift from S . Chéruel , IBBMC , University Paris Sud , Orsay , France ) . The pET-9aSN1-nocT was used as template to generate directed mutations with QuikChange II XL directed mutagenesis kit ( Stratagene ) . For mutations Met117 to Ser ( M117S ) and Asn ( M117N ) , the synthetic forward primers 5′–TATCTCCTCAGCCCGAGTACGTTCTTG and 5′-TATCTCCTCACGCCGAATACGTTCTTG and their reverse complemented primers were designed . The nucleotide sequence of all alleles was confirmed by DNA-sequence analysis ( GATC , France ) . E . coli Rosetta pLysS ( Merck ) was transformed by the recombinant plasmid . Cells were grown at 37°C in tryptone-yeast extract ( TY ) broth supplemented with 0 . 5 mM IPTG to induce NocT production , then centrifuged , resuspended in a buffer that consisted in 50 mM Tris–HCl , pH 8 . 0 , 20 mM imidazole and 500 mM NaCl and disrupted by sonication . After centrifugation at 20 000 g for 30 min at 4°C , the supernatant was loaded onto a 5 mL Ni-NTA agarose column ( GE Healthcare ) . Elution of NocT was performed with the following buffer: 50 mM Tris-HCl pH 8 . 0 , 300 mM imidazole and 500 mM NaCl . NocT containing fractions were loaded onto a gel filtration column ( HiLoad 26/60 Superdex 200 prep grade , GE Healthcare ) equilibrated with 50 mM Tris-HCl pH 8 . 0 and 150 mM NaCl . NocT ( 29 221 . 6 Da including His tag without the signal peptide ) was concentrated to 80 mg/mL ( 2 . 73 mM ) . Nopaline was extracted from crushed tomato plant tumour tissues and purified according to the procedure described by Tempé [42] . Pyronopaline was obtained by synthesis using arginine and α-KG as precursors in the presence of sodium cyanoborohydride as described by Tempé [42] . This synthesis resulted in a mix of nopaline and pyronopaline . The complete conversion of this mix into pyronopaline was obtained as described previously [17] . The quantification of nopaline was performed as previously described [31] from macerates of whole tomato tumours . All solutions of nopaline , pyronopaline and nopaline/pyronopaline were checked by mass spectrometry . The mass spectrometry measurements were performed in negative mode with an electrospray Q/TOF mass spectrometer ( Q/TOF Premier , Waters ) equipped with the Nanomate device ( Advion ) with compounds diluted in 50% acetonitrile and 1% formic acid . The Mass Lynx 4 . 1 software was used for acquisition and data processing . The external calibration was performed with NaI clusters ( 2 µg/µL , isopropanol/H2O 50/50 , Waters ) in the acquisition m/z mass range and the estimated mass accuracy is ±0 . 01 Da ( at 300 Da ) . The spectra of nopaline and pyronopaline are shown in the figure S5 . Crystallization conditions for unliganded ( 40 mg/mL or 1 . 37 mM ) and liganded NocT ( solution of 2 . 73 mM protein and 8 mM ligand ) as well as for the M117N mutant were screened in sitting-drop vapour-diffusion experiments using the Classics and PEG II kits from Qiagen on a nanodrop robot ( Cartesian , Proteomic Solution ) . Condition 34 from Classics was manually optimized at 293 K with home made solution in hanging drops composed of a 1∶1 volume ratio of crystallization solution ( 2 M Ammonium Sulfate ( AS ) , 0 . 1 M Na Citrate pH 5 . 6 , 0 . 2 M K tartrate and 5% PEG 400 ) . Similar manually optimization of condition 31 from PEG II ( 30% PEG 4000 , 0 . 1 M Tris pH 8 and 0 . 1M LiSO4 ) for both WT and mutant liganded proteins led to plate-shaped crystals . Crystals were transferred to a cryo-protectant solution ( paraffin oil for AS precipitant or 20% ( w/v ) PEG 400 for PEG precipitant ) and flash-frozen in liquid nitrogen . Diffraction data were collected at 100 K on the PROXIMA I beamline at SOLEIL synchrotron ( Saint-Aubin , France ) . Data collection and processing statistics are given in Table S1 . Structure determination of all crystals were performed by molecular replacement with PHASER [43] using first the coordinates of the N-terminal ( residues 1–86 and 197–238 ) and the C-terminal ( residues 93–185 ) of the E . coli histidine binding protein HisJ ( 1HSL ) as two search models for the free-liganded structure and next our NocT model for the wild-type or mutant liganded-NocT complexes . Refinement was performed with BUSTER-2 . 10 [44] with NCS restraints as all asymmetric units contain two protein molecules . One TLS group was assigned for each structure . Electron density maps were evaluated using COOT [45] . Refinement details are shown in Table S1 . Molecular graphics images were generated using PYMOL ( http://www . pymol . org ) . Ligand-NocT interaction was monitored by autofluorescence by exciting the protein at a wavelength of 295 nm and monitoring the quenching of fluorescence emission of tryptophan residues at 340 nm . All experiments were performed at 25°C in 25 mM Tris-HCl pH 8 . 0 and 150 mM NaCl with a fixed amount of proteins ( 5 µM ) and increasing concentrations of ligand using a SpectraMax M5 microplate reader ( Molecular Devices ) . Each ligand exhibited no emission signal at 340 nm . Fluorescence measurements were done in triplicates . The data were analysed using Origin 7 software and fitted to the equation f = ΔFluorescencemax * abs ( x ) / ( KD+abs ( x ) ) . ITC experiments were performed with an ITC200 isothermal titration calorimeter from MicroCal Llc ( Northampton , MA ) . The experiments were carried out at 20°C . Protein concentration in the microcalorimeter cell ( 0 . 2 ml ) varied from 100 to 150 µM . Nineteen injections of 2 µl of the ligand solution concentration from 1 . 5 to 1 . 6 mM were performed at intervals of 180 s while stirring at 1000 rpm . The experimental data were fitted to theoretical titration curves with software supplied by MicroCal ( ORIGIN ) . This software uses the relationship between the heat generated by each injection and ΔH ( enthalpy change in Kcal . mol−1 ) , Ka ( the association binding constant in M−1 ) , n ( the number of binding sites ) , total protein concentration and free and total ligand concentrations . Thermal stability of wild type and M117N-NocT ( 20 . 5 µM ) was studied by differential scanning calorimetry ( DSC ) on a MicroCal model VP-DSC in a standard buffer . Each measurement was preceded by a baseline scan with the standard buffer . All solutions were degassed just before loading into the calorimeter . Scans were performed at 1K . min-1 between 20 and 90°C . The heat capacity of the buffer was subtracted from that of the protein sample before analysis . Thermodynamic parameters were determined by fitting the data to the following equation ΔCp ( T ) = ( Kd ( T ) ΔHcal ΔHvH ) / ( ( 1+Kd ( T ) ) 2 RT2 ) where Kd is the equilibrium constant for a two-state process , ΔHvH is the enthalpy calculated on the basis of a two-state process and ΔHcal is the measured enthalpy . The A . tumefaciens C58 derivatives carrying pTi-accR::Gm and pTi::Gm ( used as C58-control in plant assay ) in which the genes accR ( atu6138 ) and atu6147 were disrupted by inserting a gentamicin resistance cassette were already constructed [46] . The A . tumefaciens C58 derivatives harbouring the Ti-plasmid pTi-nos::Km , pTi-ocd::Gm , pTi-nocT::Gm were obtained by insertion of a gentamicin ( Gm ) or kanamycin ( Km ) resistance cassette into the genes nos ( = atu6015 ) , ocd ( = atu6016 ) , and nocT ( = atu6027 ) as described previously [46] . A . tumefaciens was cultivated at 30°C in Agrobacterium broth ( AB ) minimal medium supplemented with ammonium chloride ( 1 g/L ) and mannitol ( 2 g/L ) except when an alternative source of carbon and nitrogen is indicated , or in Luria-Bertani modified medium ( LBm; NaCl 5 g/L ) . In growth assay nopaline and pyronopaline were added as a sole carbon and nitrogen source at 3 mM ( ca 1 g/L ) . The antibiotics gentamycin and kanamycin were added at 25 µg/mL and 50 µg/mL , respectively . Overnight cultures of the A . tumefaciens accR mutant were sub-cultured at an initial OD600 of 0 . 05 in 50 ml of AB medium containing ammonium chloride ( 1 g/L ) and mannitol ( 2 g/L ) which was supplemented or not with the mix nopaline/pyronopaline at 1 mM . Cells were grown at 28°C for approximately 9 hours until early exponential phase ( OD600 = 0 . 4 ) . RNA extraction was performed using a phenol-based procedure , according to Planamente et al . [19] . Construction of cDNA libraries , hybridization and signal quantification were performed by the PartnerChip platform ( Génopole Evry , France ) . Experiments were performed in triplicates . Normalized data of samples were pairwise compared and P values corresponding to statistical t-test were attributed for each gene . Tomato plants ( F1 hybrid Dona , Vilmorin , France ) were grown in greenhouse under long day conditions and controlled temperature ( 24–26°C ) . One-month old plants were scalpel wounded between first and second stem nodes and inoculated with the agrobacteria as described previously [20] . For each independent experiment , five to seven plant tumours ( 32 dpi ) were crushed into NaCl 0 . 8% to recover the bacteria which were then spotted onto selective agar media to enumerate colony forming units ( CFU ) . In the case of mixed infections , the proportions of the genotypes ( C58-control and nos , nocT and ocd KO-mutants ) were measured in the inoculum ( Pi ) and the plant tumour ( Pt ) using antibiotic resistances and PCR with appropriate primers . This allowed calculation of the competitive index CI = ( Ptmutant/Ptcontrol ) / ( Pimutant/Picontrol ) as described by Macho et al . [47] . The A . tumefaciens derivative C58 . 00 that contains no plasmid but harbours a chromosomal resistance to rifampicin , was used as a recipient strain . The transconjugants that acquired a Ti-plasmid from the donor strains were enumerated using antibiotic resistances and PCR with appropriate primers . Sequences were analyzed using blastP from NCBI ( http://blast . ncbi . nlm . nih . gov/ ) and MicroScope ( https://www . genoscope . cns . fr/agc/microscope/about/collabprojects . php ) . Alignements of NocT and related sequences were conducted using the ClustalW software . Relationship tree was build using the MEGA software , Version 5 . The phylogeny was inferred using the neighbor-joining method . The bootstrap consensus tree inferred from 1000 replicates was taken to represent the evolutionary history of the taxa analyzed . The evolutionary distances are in units of the number of amino acid substitutions per site . The atomic coordinates and structure factors of the unliganded NocT and the complexes with nopaline and pyronopaline as well as the M117N-NocT in complex with pyronopaline have been deposited in the protein data bank ( http://www . rcsb . org ) under accession codes 4P0I , 4POX , 4POW and 4PP0 respectively . | An ecological niche is defined , in a given environment , by the availability of nutritive resources , which can be specifically assimilated by certain living organisms to promote their proliferation . The bacterial pathogen Agrobacterium tumefaciens is able to engineer an ecological niche in the infected host via the transformation of the plant genome and diversion of the plant metabolism towards production of the opine nutrients . In this work , we quantified the selective advantage conferred to a member of the phytopathogenic species A . tumefaciens which is able to assimilate the opine nopaline . This opine is a condensate of arginine and α-ketoglurate that is produced both under linear and cyclic forms in the plant tumour environment . We further determined at the molecular and atomistic levels how A . tumefaciens is able to sense the nopaline molecules , and which metabolic pathways are activated in response . Overall , this work deciphered some key molecular events in the niche construction of the pathogen A . tumefaciens that is unique among living organisms and used to develop bioengineering tools . | [
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] | 2014 | Agrobacterium Uses a Unique Ligand-Binding Mode for Trapping Opines and Acquiring A Competitive Advantage in the Niche Construction on Plant Host |
Like many intracellular microbes , the protozoan parasite Toxoplasma gondii injects effector proteins into cells it invades . One group of these effector proteins is injected from specialized organelles called the rhoptries , which have previously been described to discharge their contents only during successful invasion of a host cell . In this report , using several reporter systems , we show that in vitro the parasite injects rhoptry proteins into cells it does not productively invade and that the rhoptry effector proteins can manipulate the uninfected cell in a similar manner to infected cells . In addition , as one of the reporter systems uses a rhoptry:Cre recombinase fusion protein , we show that in Cre-reporter mice infected with an encysting Toxoplasma-Cre strain , uninfected-injected cells , which could be derived from aborted invasion or cell-intrinsic killing after invasion , are actually more common than infected-injected cells , especially in the mouse brain , where Toxoplasma encysts and persists . This phenomenon has important implications for how Toxoplasma globally affects its host and opens a new avenue for how other intracellular microbes may similarly manipulate the host environment at large .
Obligate intracellular organisms , from viruses to eukaryotic pathogens , modify the microenvironment of the infected host cell to avoid clearance by host-cell-intrinsic mechanisms ( e . g . , autophagy , phago-lysosomal fusion ) as well as to block the immune system from recognizing the host cell as infected . One commonly deployed method utilized by cellular pathogens is to secrete effector proteins which modify the cell or the cellular compartment in which the pathogen resides– such as LLO from Listeria monocytogenes , AvrA from Salmonella , or ROP16 from Toxoplasma [1]–[3] . Unlike extracellular gram-negative bacteria which can potentially target effector proteins to cells distant from their location [4] , obligate intracellular pathogens have previously only been known to secrete their effector proteins into the cell in which they reside [5] . The presumption has been that invasion or uptake is required in order to initiate injection or secretion of these effector proteins but two recent reports on Toxoplasma gondii , an obligate intracellular parasite related to Plasmodium , have challenged this notion [6] , [7] . Toxoplasma is a protozoan parasite that has a broad host range and is known to be capable of invading almost any nucleated cell [8] . The tachyzoite invasion process is associated with gross manipulation of host cell processes , including immune response genes , carbohydrate metabolism , and apoptosis [3] , [9] , [10] . Although all the details are not yet known , recent studies have shown that a significant portion of this manipulation is initiated less than one minute into the invasion process [11] , during which time Toxoplasma injects effector proteins into the host cell . Many of these effector proteins originate from specialized , apically-localized organelles called rhoptries [12] . Recent reports have provided evidence that some injected rhoptry proteins affect host transcription factors and block cell-intrinsic defense mechanisms [3] , [13] . The molecular details of how rhoptry proteins are injected are unknown; Toxoplasma has no homologs of any of the well-studied bacterial secretions systems nor has a candidate secretion apparatus been identified . And although , until recently , all the evidence suggested that rhoptry discharge only occurred in cells in which the parasite invaded , it should be noted that immediately after invasion , a few of the dozen or so rhoptries still appear “full” , suggesting that not all are discharged during the invasion process and that the parasite has enough loaded rhoptries for multiple invasion attempts [14] . In a productive invasion event , which includes establishment of a parasitophorous vacuole ( PV ) and subsequent replication within that PV , Toxoplasma tachyzoites must first strongly attach to the cell . Interestingly , in vitro , it has been described that only about a quarter of these strong attachments result in invasion [15] . It has been unclear whether this low rate of invasion simply reflects an inefficient process or whether this might even be a selected trait that serves some other purpose . Potentially , during these abortive events , Toxoplasma might be probing the cell to determine if it is optimal for invasion . Alternatively , it could be that the parasite has evolved to deliberately inject a bolus of effector proteins into cells it does not intend to invade . Consistent with this latter hypothesis , by infecting fibroblasts that only express eGFP after Cre-mediated recombination with parasites engineered to express Cre fused to the rhoptry protein “toxofilin” , we recently reported that eGFP expression could be observed in both infected cells as well as in a nearly equal number of cells that do not contain parasites [6] , [16] . Similar observations have recently been made using in vitro Toxoplasma infections of primary macrophages where SOCS3 up-regulation was seen in both infected and uninfected cells [7] . While the data from both studies are consistent with injection without invasion , they could also be explained by cell division after invasion with one daughter cell receiving the single PV and the other emerging “uninfected” . Alternatively , the SOCS3 upregulation could result from local paracrine effects of factors secreted by the infected cell or even cell-to-cell communication of inflammatory signals , which was recently described in HeLa cells infected with Salmonella [17] . To discriminate between these possibilities and to specifically assess whether Toxoplasma can inject rhoptry effector proteins into cells it does not invade , we sought to determine the origins of these uninfected-manipulated cells ( cells injected with Toxoplasma protein but not containing a parasite ) as well as to determine whether or not such cells could be found in vivo . Using a combination of reporter systems , we show that while some of the uninfected-manipulated cells do appear to result from division of the host cell after invasion , a significant fraction do not . In vivo , the effect is particularly striking in the brains of infected mice .
In our previous report , where we first observed uninfected-manipulated cells , we employed a commonly used laboratory strain of Toxoplasma ( RH ) . This highly virulent strain is unable to encyst and cause a latent infection in mice thereby severely complicating in vivo studies . To facilitate in vivo studies , therefore , we engineered a less virulent , encysting Toxoplasma strain ( Pru ) to express mCherry as well as the previously described rhoptry-targeted Cre fusion protein , toxofilin:Cre [6] . We then used the resulting Pru-mCherry-Cre strain to infect the previously described Cre-reporter fibroblasts at a multiplicity of infection ( MOI ) of 0 . 5 . Twenty four hours post-infection ( hpi ) , the cultures were examined by fluorescence microscopy to detect cells that had undergone Cre-mediated recombination and therefore expressed eGFP . In addition to the expected eGFP-positive , infected host cells ( Figure 1 a , b ) , we observed eGFP-positive , uninfected cells at a rate of about 40–50% of the frequency of the infected green cells . These uninfected green cells fell into two categories: ( 1 ) those in contact with or in very close proximity to an infected host cell ( Figure 1a ) or ( 2 ) those that were not in direct contact with and were distant from infected host cells ( Figure 1b ) . While the latter population is further from infected host cells , an infected cell was always seen within a radius of 5–10 cells from the green uninfected cell ( data not shown ) . A priori , these uninfected green cells observed during Toxoplasma-Cre infections could arise by several possible mechanisms: ( a ) the reporter cells exhibit a background leakiness ( i . e . , expression of eGFP occurs without undergoing Cre-mediated recombination ) , ( b ) the reporter cells take up either plasmid DNA or the Cre fusion protein from the extracellular environment; ( c ) after invasion , the host cells clear the parasites by cell-intrinsic mechanisms , ( d ) a host cell undergoes cell division after invasion and only one daughter acquires the PV , and/or ( e ) invasion is initiated , including injection of the rhoptry proteins , but the process is aborted . We previously showed that background leakiness can be excluded as an explanation for the uninfected green cells because no eGFP-expressing cells are found in Cre-reporter cultures in the absence of infection or upon infection with live parasites that do not inject Cre [6] . Similarly , we were able to exclude uptake of Cre fusion protein/DNA from the extracellular environment as an explanation because no eGFP-expressing cells were observed after incubation with heat-killed Toxoplasma-Cre parasites , freeze-thaw lysates of such parasites , or “conditioned” media from cultures heavily infected with these parasites [6] . We also examined reporter cells into which the toxofilin-Cre plasmid had been transfected ( without parasites ) and again saw no eGFP expression indicating that even if some amount of the parasite DNA is taken up , the toxofilin:Cre fusion protein will not be expressed [6] . Destruction of parasites after invasion is also unlikely to be the explanation for the uninfected eGFP-positive cells as we did not stimulate the cultures with cytokines and IFN-γ is a known requirement for non-immune cells to initiate cell-intrinsic defense mechanisms against Toxoplasma [18] , [19] . Also , in none of these experiments did we find mCherry debris or partially destroyed parasites in the Cre-reporter cells , which is consistent with these cells lacking the ability to destroy invaded parasites without cytokine stimulation . This left cell division after invasion and/or injection without invasion as possible explanations for the uninfected green cells . We know that host cell division can occur after Cre-mediated recombination secondary to parasite invasion as we see occasional green cells in the process of dividing ( Figure 1c ) . This , then , likely explains many of the uninfected green cells that lie in contact with infected cells . Cell division , however , does not explain the uninfected green cells that are separated from infected host cells by many uninfected cells as the reporter cells being used are non-motile fibroblasts and so , daughter cells should lie next to each other , not several cells apart . Taken in total , the results described above support but do not prove the hypothesis that a portion of the uninfected green cells are likely produced from Toxoplasma injecting its rhoptry proteins without proceeding to invade the cell . The Cre/loxP assay is extremely sensitive and binary; even one functional Cre tetramer has the potential to catalyze excision at the loxP sites and , once removed , expression of the reporter is not further influenced by more Cre being introduced . Hence , this assay provides little indication as to the amount of Cre introduced . To address this shortcoming and to confirm that the phenomenon of uninfected-injected cells is not dependent upon the immortalized nature of the Cre-reporter cells , we repeated our analysis using primary host cells ( human foreskin fibroblasts ) and a Toxoplasma strain expressing a toxofilin:β-lactamase fusion protein [20] . The β-lactamase assay uses a substrate that emits light at different wavelengths depending on whether it has been cleaved by β-lactamase , and the ratio of cleaved to uncleaved substrate determines the relative intensity of signal detected at each wavelength [21] . Furthermore , as β-lactamase will immediately cleave the substrate upon contact ( as opposed to the Cre-based assay which requires Cre-mediated recombination , transcription of the recombined DNA and translation of the resulting transcripts ) , the β-lactamase assay allows for the assessment of rhoptry protein injection much sooner after cells have been incubated with parasites . Hence , the β-lactamase-based assay greatly reduces the possibility of reporter-positive , uninfected host cells being due to host cell division or parasite destruction by the host cell following injection of the rhoptry fusion protein . In addition , the β-lactamase assay has a greater dynamic range than the Cre-based assay with the potential ability to detect varying amounts of injected enzyme . Using β-lactamase-injecting parasites , we infected near-confluent human foreskin fibroblast ( HFF ) cultures at an MOI of 0 . 5 for two hours and then added the detection substrate . As anticipated from the results described above and as seen in Figure 2 , we could detect the presence of the toxofilin:β-lactamase fusion protein in many cells that did not contain a parasite ( uninfected blue cells , arrows ) . Also consistent with our previous results , we observed two populations of uninfected blue cells: one population that was in contact with infected cells ( Figure 2a ) and one population that was more distant ( Figure 2b ) . Given the short time period between the incubation period and live cell imaging and the lack of mCherry debris in the uninfected blue cells , it is unlikely that many , if any , of these latter cells arose from parasite clearance by cell-intrinsic mechanisms . For similar reasons and because the host cells were HFFs , which are primary cells that have strong contact inhibition , it is likely that very few of the uninfected blue cells seen by this method were derived from division of infected cells , although this does appear to be the case for some; e . g . , the uninfected cell in Figure 2a appears to be connected directly to the infected cell next to it suggesting a recent division has occurred . On the other hand , the blue cell highlighted in Figure 2b , which is completely surrounded by cells that show no evidence of substrate cleavage , is very unlikely to have arisen from the division of an infected cell . Interestingly , many of these uninfected and infected blue cells show a range of blueness . By eye , the uninfected cells do not show a trend of being markedly less blue than the infected cells . To better quantify the color of the uninfected versus infected blue cells , confluent HFF cultures were treated in the same way as described above except that instead of being imaged by confocal microscopy , the cells were trypsinized and analyzed by flow cytometry . As seen in Figure 2c , the uninfected blue cells show a substantial but somewhat lower mean fluorescence intensity compared to the infected blue cells . These data suggest that compared to the infected blue cells , the uninfected blue cells receive less rhoptry protein , the rhoptry fusion protein is more rapidly degraded in such cells and/or the uninfected cells more efficiently export the cleaved substrate . Regardless , these results show that in primary cells and using a less sensitive assay for rhoptry injection , we can recapitulate the uninfected-injected cell phenomenon we found using the Cre/loxP system . In addition , the data provide strong evidence that these uninfected-injected cells receive a substantial amount of rhoptry proteins , although possibly less than the amount introduced into productively invaded cells . Having established by two systems that a portion of these cells most likely arises from aborted invasion , from here forward these cells will be referred to as uninfected-injected ( U-I ) cells . The previous experiments confirmed that U-I cells could be observed using 2 different reporter methods for detection of rhoptry injection; however , neither experiment enabled us to assess the functional consequence of such a phenomenon . In addition , both assays utilized ectopic expression of the same rhoptry protein ( toxofilin ) as the base for the fusion proteins . To address if other rhoptry proteins are being injected and , if so , whether they are introduced in physiologically relevant amounts , we took advantage of the fact that injection of the tyrosine kinase rhoptry protein , ROP16 , into HFFs invaded by Toxoplasma causes rapid phosphorylation and nuclear translocation of STAT6 . This phenotype is well documented , important for the host's immune response and is specifically dependent upon the injection of ROP16 into the host cell [3] , [11] . Thus , we infected confluent HFF cultures at a low MOI with a wild-type Toxoplasma strain that expresses only its native rhoptry proteins . Eighteen hours after infection , we assessed these cultures by immunofluorescence assay ( IFA ) for phosphorylation and nuclear translocation of STAT6 . As seen in Figure 3 , we again observed that a significant fraction of cells ( ∼6% ) that show STAT6 phosphorylation and nuclear translocation contain no parasites ( arrow ) . Given the distance between this particular U-I cell and the nearest infected cell ( empty arrowhead ) , it is highly improbable that the U-I cell arose secondary to cell division and then migrated several cells over to its current position . Mock-infected HFF cultures never showed phosphorylation and nuclear translocation of STAT6 ( data not shown ) . The percentage of U-I cells showing the pSTAT6 phenotype is significantly lower than the percentage of U-I cells found using the Cre-reporter system or the β-lactamase assay; this is not surprising and is likely due to several factors . First , the detection of pSTAT6 is likely to be much less sensitive than either the Cre or β-lactamase reporter assay . Consistent with this decreased sensitivity is the fact that pSTAT6 signal scales with the number of invasion events ( e . g . , the presence of two invaded parasites is associated with a stronger pSTAT6 signal compared with singly infected cells ) [3] while neither of the other reporter assays appeared to scale in this manner [6] , [20] . Additionally , as the IFA was done 18 hours after incubation with parasites , it is possible that the pSTAT6 signal may be more robustly maintained in completed invasion events compared to aborted ones ( e . g . , through the on-going interaction with other parasite effectors released after invasion ) . Nevertheless , these results with pSTAT6 activation confirm that , in vitro , Toxoplasma secretes multiple rhoptry proteins into cells it does not invade and that in at least some of these cells the amount of protein injected is sufficient to induce important changes in host cell physiology consistent with what is observed during productive invasion . All of the above studies were done in vitro and it could be that the U-I phenomenon is an artifact of suboptimal conditions in tissue culture . Therefore , to verify that U-I cells are also generated during in vivo infections , we returned to the Cre/loxP assay and utilized Cre-reporter mice that express ZsGreen only after Cre-mediated recombination [22] . We infected these mice with the encysting Pru-mCherry-Cre strain or a control strain , which expresses a non-functional toxofilin:Cre fusion protein as well as mCherry ( Pru-mCherry ) . We then examined the peritoneal exudate cells ( PECs ) at 4 days post infection ( dpi ) by fluorescence microscopy . Figure 4 shows that in mice infected with the control strain , no ZsGreen-expressing inflammatory cells are seen ( panel a ) , while in mice infected with the Cre-expressing strain , both infected ( panel b ) and uninfected ( panel c ) ZsGreen+ inflammatory cells are seen . To exclude the possibility these U-I PECs are secondary to an unknown ability of activated immune cells to take up Cre protein from the extracellular environment ( e . g . liberated from killed parasites ) , we infected a Cre reporter mouse with the control Pru-mCherry strain and 2 dpi injected the mouse intraperitoneally with recombinant Cre protein . The PECs were removed 3 days later ( 5 dpi ) and examined by fluorescence microscopy; no ZsGreen+ cells were observed ( data not shown . ) To better assess the ratio of ZsGreen+ U-I cells to ZsGreen+ infected cells in the Cre-reporter mice , we collected PECs at 5 dpi and analyzed them by flow cytometry for the fraction of live , Dump− ( CD3− , CD19− , NK1 . 1− ) ZsGreen+ cells that were either mCherry-positive ( infected ) or -negative ( uninfected ) . As expected , in mice infected with the control Pru-mCherry strain , no ZsGreen+ cells were observed ( Figure 5 , left plot ) . Remarkably , however , in mice infected with the Pru-mCherry-Cre strain we observed that of the ZsGreen+ PECs , ∼60–80% were U-I cells ( Figure 5 , right plot; U-I cells are ZsGreen+/mCherry− and are in the lower right quadrant; infected ZsGreen+ PECS are ZsGreen+/mCherry+ and are in the upper right quadrant ) . Given that these inflammatory cells come from an animal which has an intact immune system , the U-I PECs could be derived from one or more of three sources: ( 1 ) cell division in invaded cells that have undergone Cre-mediated recombination , ( 2 ) aborted invasion , or ( 3 ) successful invasion events but where Toxoplasma is cleared from the host cell by cell-intrinsic mechanisms [19] , [23] . Note that although we know from the results presented in Figure 1 that , in vitro , infected fibroblasts are able to divide post-invasion , we have no data to confirm or refute such a possibility in inflammatory cells in vivo . To address if in vivo the U-I cells were manipulated in a physiologically relevant manner , we infected Cre-reporter mice with RH-mCherry-Cre parasites , and harvested the PECs 18–20 hours later . The cells were fixed , permeabilized with methanol , stained with an anti-pSTAT6 antibody , and analyzed by flow cytometry ( Figure 6 ) . As seen in Figure 6a , U-I cells are readily detected based on having a Zs-Green+/mCherry− phenotype . Within such cells , there are two sub-populations , one in which no pSTAT6 signaling is seen , and a second , smaller population that clearly exhibits phosphorylation of STAT6 ( Figure 6b ) . To confirm that these pSTAT6+ U-I cells also show nuclear translocation of pSTAT6 , a number of cells were also examined by microscopy using the Amnis ImageStream X , which allows high throughput imaging of individual cells by brightfield and fluorescence microscopy . The pSTAT6 signal in the U-I cells was indeed found to be nuclear and indistinguishable from pSTAT6 signal in the infected ZsGreen+ cells ( Figure 6c and Figure S1 ) . Hence , U-I cells experience physiological changes comparable to infected cells , including in pathways with important implications for how the infection progresses . To examine the possibility that a portion of in vivo U-I cells were not derived from cell division , we needed to examine cells which were: 1 ) commonly infected by Toxoplasma; 2 ) long-lived; 3 ) not prone to cell division; and 4 ) expressed specific markers that reflected their division history . Fortunately , encysting strains of Toxoplasma commonly infect neurons in the brains of mice [24] and these cells meet the remaining criteria: most neurons live as long as the animal; new neurons in adult mice only occur in very specialized regions ( the dentate gyrus of the hippocampus and the subventricular zone of the lateral ventricles ) where they are derived from neural stem cell precursors [25]; and for the first two weeks after neurogenesis , the nascent neuron highly expresses a protein called doublecortin ( DCX ) which declines in expression in the subsequent week as NeuN-staining , a marker of a mature neuron , increases [26] . Hence , a newly generated neuron expresses DCX but not NeuN , while a mature or older neuron has the opposite phenotype . Thus , to determine if we could observe U-I cells that were mature neurons ( DCX− , NeuN+ ) , we infected Cre-reporter mice intraperitoneally with the encysting Pru-mCherry-Cre strain or the control Pru-mCherry strain . At 21 dpi , we sacrificed the mice , removed the brains , and , after fixation , sectioning and appropriate staining , examined brain slices by confocal microscopy . We specifically chose to inoculate with a relatively low dose of parasites and to sacrifice the mice at 21 dpi as previous studies suggested that parasites do not arrive in the brain from i . p . inoculation until ∼4–11 dpi [27] , [28] . Thus , when we examined the brain at 21 dpi , the parasite-neuron interaction at most would have occurred 17 days before our examination; this is well within the time period that a recently divided cell would still show DCX expression . Figure 7 shows a representative hippocampal brain section stained for DCX and NeuN . In Figure 7a , a ZsGreen+ cell that does not contain a detectable parasite stains for NeuN but not for DCX , confirming that this U-I cell has not recently undergone neurogenesis and therefore was not derived from cell division within the preceding 21 days . In Figure 7b , which is from the same hippocampal slice as that shown in Figure 7a , rare DCX-positive and NeuN-negative neurons are found , consistent with previous studies that have shown that in the adult mouse , neural stem cells in the dentate gyrus of the hippocampus continue to undergo neurogenesis at a basal rate [25] . Supplemental Figure S2 shows a montage of 16 consecutive slices from the full confocal scan of this 40 µm section in which no parasite or cyst is seen throughout the ZsGreen+ cell . Figure 7c shows another section stained for DCX and NeuN in which an infected ZsGreen+ cell that does not stain for either DCX or NeuN is seen; this serves as an example of how an infected cell appears under these staining conditions . No ZsGreen+ cells were seen in the brains of uninfected Cre-reporter mice or Cre-reporter mice infected with the control Pru-mCherry strain ( data not shown and Supplemental Figure S3 ) . To address the ratio of U-I cells to infected cells in the brain , we examined by fluorescence microscopy a total of 20 brain slices ( 8 from one infected reporter mouse and 12 from another ) and counted the number of ZsGreen+ cells seen compared to the number of cysts seen . Strikingly , we found between 30 and 50 times the number of U-I cells compared to the number of cysts/infected cells . Figure 8 is a representative , stitched grid of composite images of a single brain slice which shows both cysts ( arrowheads in Figure 8b , c ) and ZsGreen+ cells , many but not all of which are morphologically consistent with neurons . Not surprisingly , in the mouse that had far more cysts ( 11 cysts/slice vs . 2 cysts/slice in the less infected animal ) , far more ZsGreen+ cells were seen , as well ( ∼600/slice vs . ∼60/slice , respectively ) . It is unlikely that we are missing significant numbers of single parasites in distant projections of neurons because we have not found any single parasites even when the sections were stained with antibodies to Toxoplasma specific surface antigens and examined at high magnification ( data not shown . ) In addition , the lack of single parasites at 21 dpi is consistent with previously published electron micrographs [29] . It also seems unlikely that ZsGreen or Cre is passing from neuron to neuron as Cre-reporter mice such as these have been extensively used to examine neuronal lineage and specific neuronal subtypes ( e . g . , dopaminergic neurons ) with no apparent cell-to-cell transmission of the fluorescent reporter signal being noted [30] , [31] . Taken together with the PECs findings , these data confirm that U-I cells can be found frequently in vivo , a portion are manipulated in a physiologically relevant manner , and that , in the brain of a chronically infected animal , U-I cells can arise from mechanisms other than cell division .
The results presented here show that Toxoplasma gondii tachyzoites can inject effector proteins into cells that they do not productively invade . In vitro , we have established that these uninfected-injected cells ( U-I cells ) occur with both Type I ( RH ) and Type II ( Pru ) Toxoplasma strains and can be identified soon after the host cells are exposed to the parasites . We have also shown in vitro that while some U-I cells are derived from cell division , others appear to be the result of non-productive invasion . Although the results indicated that U-I cells may be injected with less rhoptry protein than productively invaded cells , the amounts introduced are nonetheless sufficient to produce physiologically relevant changes ( e . g . , phosphorylation of STAT6 ) in these cells . In vivo , we have shown that U-I cells are generated in several cell types ( PECs as well as in neurons ) , and that in the brain , at least some U-I cells have not divided within the time frame of the experiment . Given the in vitro data , these results are most easily explained by a similar non-productive invasion mechanism operating in vivo . We cannot exclude , however , the possibility that these U-I cells were infected but cleared the parasite without concomitant destruction of the infected cell . For example , autophagy has been implicated as part of the innate immune system in regards to controlling Toxoplasma infection [32] , and is hypothesized to specifically play a role in controlling toxoplasmic encephalitis [33] though no direct evidence has shown that neurons are able to clear Toxoplasma via autophagy , and there are mixed reports of autophagy helping or hindering neurotropic viruses [34] , [35] . Regardless of how they come to be , the results presented here show that U-I cells can exist at a surprisingly high frequency in infected animals and that a previously unknown mechanism is operating that results in rhoptry proteins being found within such cells . How long such proteins persist within these cells cannot yet be estimated and will likely vary depending on the identity of the protein . The Cre-reporter mice used here “lock in” a positive signal ( i . e . , once Cre has mediated the recombination , the cells will continue to express Zs-Green , even after no Cre remains ) so no conclusion can be reached about how long the Cre fusion protein persists in the U-I cells . Given the right evolutionary pressure , however , proteins could evolve within Toxoplasma that might persist for an extended period in U-I cells and/or that lock the cell into a given state by other ( e . g . , epigenetic ) means . One of the most striking observations reported here is the frequency of U-I cells in vivo . When paired with the STAT6 data showing that the U-I cells can be activated in a similar manner to infected cells , the results beg the question of what impact these U-I cells might have on the infected host . For example , U-I cells could also represent a way of systemically manipulating the host; e . g . , phosphorylation and nuclear translocation of STAT3/6 causes decreased IL-12 production from macrophages [3] and so the U-I macrophages that are pSTAT6+ could increase the number of immune cells with depressed IL-12 production . This manipulation of innate immune cells could alter the overall balance of cytokines within the host and thereby influence the delicate Th1/Th2 equilibrium of the immune response . In addition , since at least one Toxoplasma-specific T cell epitope is derived from a rhoptry protein [36] , if the injection without invasion provides enough parasite protein for loading onto host MHC molecules , these U-I cells might be targets for the host's immune response . In turn , these cells could represent a selective advantage to the parasite , e . g . , through providing antigenic decoys ( the immune response becomes directed at the U-I cells and not the productively invaded cells ) or they might favor the host through providing more antigenic priming to cells of the adaptive immune response . In either case , the targeting of U-I cells could contribute substantially to the pathogenesis of the disease The abundance of U-I cells in the brain was particularly remarkable . In part , this is likely because neurons which either cleared the parasite or were never invaded will potentially survive for the rest of the mouse's life , unlike many peripheral immune cells ( e . g . macrophages ) which have a finite life span . This accumulation of affected cells might help explain the notable and well-documented changes in behavior in rodents chronically infected with Toxoplasma [37] , [38] , a phenomenon that previously has been difficult to explain based on the very small numbers of parasites ( cysts ) actually present in the chronically infected brain [38] . The ability to inject cells that are not productively invaded may not be limited to Toxoplasma . Given the similarity in the invasion process between many members of the phylum Apicomplexa , it would not be surprising to find that other species also utilize this mechanism for manipulating the host environment . For the malaria parasite , Plasmodium spp . , for example , the ability to manipulate cells in which they cannot productively invade or grow ( e . g . leukocytes ) might represent a potent means of directly influencing the immune response . Ultimately , the finding that uninfected cells can be modulated by Toxoplasma will have a significant impact on how the global effects of infection with this parasite are analyzed , and if this ability occurs in other intracellular pathogens , it may lead to a shift in the overall paradigm of the host-pathogen interaction .
This study was carried out in strict accordance with the Public Health Service Policy on Humane Care and Use of Laboratory Animals and AAALAC accreditation guidelines . The protocol was approved by Stanford University's Administrative Panel on Laboratory Animal Care ( Animal Welfare Assurance # A3213-01 , protocol # 9478 ) UPenn: Multiple project assurance # A3079-01 . All efforts were made to minimize suffering . The parental strain used for encysting Toxoplasma was the type II PruΔhpt in which the endogenous gene for hypoxanthine xanthine guanine phosphoribosyl transferase ( HPT ) has been deleted . All strains were propagated in human foreskin fibroblasts ( HFFs ) . The vector expressing the selectable HPT marker and the epitope-tagged rhoptry protein fused to Cre recombinase ( pToxofilin-Cre ) has been previously described [6] . In addition to the pToxofilin-Cre plasmid , a second plasmid containing the coding sequence for mCherry , flanked by the GRA2 promoter and 5′-UTR and the GRA2 3′-UTR , was co-transfected into the parasites . The parental strain for all non-encysting parasites was the type I strain RHΔhpt [39] . The generation of RH-Cre and the vector expressing HPT and a toxofilin:β-lactamase fusion have been previously described [20] . In addition to the pToxofilin-β-lactamase plasmid , a second plasmid containing the coding sequence for mCherry flanked by the GRA1 promoter and 5′-UTR and GRA2 3′-UTR , was co-transfected into the parasites . To generate mCherry+ parasites expressing the respective toxofilin fusion protein , the parental parasites were electroporated with the appropriate plasmids , linearized upstream of the relevant expression cassettes prior to electroporation . As previously described , the parasites were then subjected to several rounds of selection for expression of HPT using medium containing 25 µg/ml mycophenolic acid and 50 µg/ml xanthine before being cloned by limiting dilution [40] . Single cell clones that were HPT+ and mCherry+ and confirmed to express the appropriate toxofilin fusion protein were then tested for efficacy in causing Cre-mediated recombination in a Cre-reporter cell line and Cre-reporter mice [6] , or for the ability to cleave the substrate CCF2-AM [20] to verify secretion of a functional toxofilin:Cre or toxofilin:β-lactamase fusion protein , respectively . For the encysting Pru-Cre strain , a control parasite strain was also selected that both expressed mCherry and had the selectable marker but , unlike the Pru-Cre strain , expressed a truncated form of the Cre fusion protein , as determined by western blot analyses ( data not shown ) . This truncated fusion protein was inactive as infection of either the Cre-reporter cells or mice with this control strain did not result in Cre-mediated recombination ( data not shown ) . For detection of Cre , specially engineered 10T ½ fibroblasts were used [6] . These have a cassette for eGFP downstream of a translational stop signal flanked by loxP sites so that upon Cre-mediated recombination , the eGFP is expressed . These Cre-reporter cells were plated on glass coverslips and infected 24 h later with syringed-released Toxoplasma-Cre parasites at an MOI of 0 . 5 , washed with 1× phosphate-buffered saline ( PBS ) 2 hours after incubation , and returned to the 37°C incubator until the following day when the infected monolayers were fixed with 3 . 5% formaldehyde . For the Toxoplasma-Cre strain that did not express mCherry , after fixation the cells were permeabilized and blocked for 2 hours in 1× PBS supplemented with 0 . 1% ( v/v ) Triton-X 100 ( TTX; Sigma ) and 3% ( w/v ) bovine serum albumin ( BSA ) . Cells were then stained with the mouse anti-SAG1 monoclonal antibody DG52 [41] ( dilution 1∶8 , 000 ) followed by the AlexaFluor647-goat-anti-mouse antibody ( Molecular Probes , 1∶2000 ) . After fixation and staining , if appropriate , coverslips were mounted on slides using Vectashield Mounting Media for Fluorescence with DAPI ( Vector laboratories ) . For Figure 1a and b , slides were viewed with a Leica TCS SPE confocal microscope . All digital images were obtained using Leica Application Suite , Advanced Fluorescence . For Figure 1c , slides were viewed on an Olympus BX60 upright fluorescence microscope , and images were obtained using Image-Pro Plus . All images shown in a given figure , using a given microscope and camera , and with a given color were obtained and processed using identical parameters . HFFs were plated on 24-well glass bottom plates ( MatTek Corporation , #P24G-1 . 5-13-F ) the day prior to incubation with Toxoplasma-β-lactamase parasites . The β-lactamase assay was carried out essentially as described previously [20] . In brief , prior to live imaging , Toxoplasma-β-lactamase parasites were syringed-released and incubated with HFFs at an MOI of 0 . 5 for 2 hours in a 37°C incubator . After incubation , the cells were washed once with PBS , then 300 µl of CDMEM was added after which 60 µl of 6× CCF2-AM ( Invitrogen K1085 ) was added to the wells and allowed to equilibrate as directed by the manufacturer's protocol . The live cells were then imaged with a LSM Meta Confocal Microscope ( Neuroscience Microscopy Service , Stanford University , Stanford , CA ) . To determine if the CCF2 had been cleaved , the cultures were excited with a blue diode 405 nm laser and the detectors set for 410–450 nm for coumarin ( cleaved ) and 493–550 nm for fluorescein ( uncleaved ) . To visualize parasites , the cultures were excited with a 561 nm laser with detectors set to pick up emissions greater than 600 nm . All images were obtained using Zen 2009 . For flow cytometry assay , cultures were prepared as detailed above except that tissue-culture-treated T25s were used . After 30 minutes of substrate loading , cells were washed with cold PBS , and then trypsinized at 25°C . Cells were then kept on ice until they were analyzed on a Becton-Dickinson LSR II that has been modified to include a UV laser and has both a 405 nm and 561 nm laser . MCherry expression was used to determine if cells were infected and detection in the cascade blue channel was used to determine whether or not the CCF2 had been cleaved . Analysis was done using FlowJo v . 9 . 4 . 9 software . Confluent HFF cultures plated on coverslips were infected with 104 non-encysting parasites ( RHΔhpt ) ( MOI ∼0 . 02 ) . At two hours post infection ( hpi ) , the cells were washed twice with 1× PBS and then left for 16 hours in CDMEM . At 18 hpi , infected monolayers were washed once with cold 1× PBS and then fixed with cold methanol for 10 minutes at −20°C . After washing the cells with 1× PBS supplemented with 0 . 2% ( v/v ) TTX , they were blocked for 2 hours with 1× PBS supplemented with 3% ( v/v ) goat serum and 0 . 2% ( v/v ) TTX . After washing cells with 1× PBS supplemented with 0 . 2% TTX , they were incubated overnight at 4°C with primary antibodies ( rabbit anti-pSTAT6 ( Cell Signaling Technologies #9361S ) at 1∶100 and mouse anti-SAG1 monoclonal antibody DG52 [41] at 1∶30 , 000 ) in 1× PBS supplemented with 3% ( v/v ) goat sera and 0 . 2% TTX . The cells were then washed with 1× PBS supplemented with 0 . 2% TTX and incubated with species-appropriate Alexa Fluor-conjugated secondary antibodies ( Molecular Probes , 1∶2000 ) at room temperature for 1 hour . Stained coverslips were then mounted onto slides as described above . Images were taken using QCapture v . 3 . 1 software and using an Olympus BX60 upright fluorescent microscope . Cre-reporter mice ( background C57B6 ) were purchased from Jackson Laboratories ( stock # 007906 ) and bred in a Specific Pathogen Free , AAALAC , Int . -approved , conventional facility . In the Rosa26 locus of these mice is a cassette for ZsGreen downstream of a transcriptional stop that is flanked by loxP sites so that only after Cre-mediated recombination will the mouse's cells express ZsGreen [22] . One to 5 days prior to infection the mice were transferred to the biohazard suites . For inoculation , Toxoplasma strains were grown in HFFs , and intracellular parasites were syringe-released , and counted on the day of infection . The parasites were diluted to appropriate inoculum sizes in sterile , serum-free 1× PBS . Mice were injected intraperitoneally ( i . p . ) with a total volume of 200 µl containing the appropriate number and type of parasites . For the Cre recombinase injection , 2 days post infection ( dpi ) with parasites , the infected mouse was injected with 20 units of Cre recombinase ( NEB , M0298L ) in a 200 µl solution of 1× serum-free PBS and Cre reaction buffer . At 4 or 5 dpi , infected mice were euthanized by CO2 , and PECs were collected by peritoneal lavage with 5–8 ml of cold 1× PBS . For the PECs that were to be examined by microscopy , all samples were treated with 1 ml of ACK lysis buffer ( Invitrogen ) for 3 minutes and then resuspended in 2 ml of CDMEM . About 600 µl of this suspension were then placed onto poly-L-lysine coated glass coverslips and placed in a 37°C incubator . The cells were allowed to settle for 30 minutes , after which the coverslips were washed with 1× PBS , then fixed with 2 . 5% formaldehyde for 15–20 minutes . After being mounted on slides with Vectashield Mounting Media for Fluorescence with DAPI ( Vector laboratories ) , slides were viewed with a 100× oil immersion lens on an Olympus BX60 upright fluorescence microscope . All digital images were obtained by using Image-Pro Plus and all images shown in a given figure and with a given color were obtained and processed using identical parameters . The PECs used for flow cytometry analysis came from mice different from those used for microscopy . These PECs were first incubated for 10 min in FcBlock containing Normal Rat Serum IgG and Live/Dead ( Invitrogen ) as a viability marker . Cells were then stained for surface markers for 20 minutes on ice . The following antibodies were used for staining: Pacific Blue-anti-mouse CD3 clone 17A2 ( Biolegend ) , eFluor 450-anti-mouse CD19 clone 1D3 ( eBioscience ) , and Pacific Blue-anti-mouse NK1 . 1 clone PK136 ( Biolegend ) . The PECs were kept on ice until analysis on an LSR Fortessa . The data were collected with FACSDiva software and analyzed with FlowJo software . Cre-reporter mice were infected i . p . with 2×106 parasites . At 20 hours post infection PECs were harvested using ice-cold Phospho-wash ( PBS containing Phosphatase Inhibitor Cocktail 2 ( Sigma , P5726 ) and Roche complete protease inhibitor ( Roche ) ) . Cells were immediately centrifuged , resuspended in 500 µL Phospho-wash containing Live/Dead aqua stain ( Invitrogen , L34957 ) , and incubated for 10 minutes on ice . Cells were rinsed with 500 µl Phospho-wash , and then fixed in 2% PFA containing Phosphatase Inhibitor Cocktail 2 for 20 minutes on ice . Cells were again rinsed with 500 µl Phospho-wash , resuspended in 400 µl 90% methanol in PBS , and incubated overnight at −20°C . After incubation , cells were rinsed with FACS buffer and blocked with FcBlock ( BD Pharmingen ) and normal rat serum for 10 minutes . Cells were then stained on ice for 4 hours using AlexaFluor647-anti-pSTAT6 pY641 ( clone: J71-773 . 58 . 11 , BD Pharmingen ) or a Rat IgG1k Alexa Fluor 647 isotype control ( BD Pharmingen ) . Cells were then washed and analyzed by flow cytometry . For analysis of pSTAT6 localization using the Amnis ImageStream X , cells were stained with DAPI for 10 minutes . At 21–29 dpi , mice were anesthetized with a ketamine/xylazine cocktail ( 24 mg/ml and 48 mg/ml , respectively ) and intracardially perfused with heparin ( 10 U/ml ) in a 0 . 9% saline solution followed by fresh 4% paraformaldehyde ( Sigma P6148 ) . Brains were then collected and drop-fixed in 4% paraformaldehyde for 24 hours , cryoprotected in 30% sucrose in 1× PBS , and stored in 30% sucrose at 4°C until sectioned . Free-floating coronal or sagittal sections ( 40 µm ) were cut on a sliding freezing microtome ( Microm HM 430 ) and stored at 4°C in cryoprotective medium ( 0 . 05 M sodium phosphate buffer containing 30% glycerol and 30% ethylene glycol ) . Sections were selected at random and immunostained with primary antibodies ( anti-NeuN clone A60 , biotin conjugated ( Millipore , 1∶200 ) and goat polyclonal anti-Doublecortin C-18 ( Santa Cruz , 1∶200 ) ) or not stained as appropriate . Species-appropriate or streptavidin Alexa Fluor-conjugated secondary antibodies were used ( Molecular Probes , 1∶200 ) . Brain sections were mounted on slides using Vectashield Hardmount with or without DAPI ( Vector laboratories ) and viewed with a 40× oil lens on a Leica TCS SPE confocal microscope , a 40× oil lens on a Zeiss LSM 510 meta scanning confocal , or a 10× lens on an upright widefield fluorescence microscope ( Zeiss AxioImager M1 with CCD camera ) . Confocal images were obtained using Leica Application Suite , Advanced Fluorescence or Zen 2009 ( Zeiss ) and upright fluorescent images were obtained using AxioVision software including Multichannel , MosaiX , Autofocus , and Mark and Find modules . All images shown in a given figure and with a given color were obtained using identical parameters . Images were analyzed and processed using ImageJ/FIJI . | Toxoplasma gondii is an intracellular parasite that infects warm blooded animals , including humans . In these hosts , Toxoplasma establishes a chronic infection in the brain , which the parasite accomplishes in part by injecting effector proteins , which manipulate many cellular processes , into cells it invades . Two recent reports suggested that Toxoplasma may also inject effector proteins into cells it does not invade . To look for these “uninfected-injected” cells , we utilized three different reporter systems that are tied to injection of effector proteins and not to invasion . With these systems , we determined that Toxoplasma injects proteins into cells it does not invade and enough protein is injected to manipulate the uninfected cells in a manner consistent with what occurs in infected cells . Furthermore , by using one of the reporter systems in mice , we verified that these uninfected-injected cells can include systemic immune cells and neurons in the brain . Remarkably , in the brain , the uninfected-injected cells out-number the infected cells by many fold . Together , these results strongly suggest that Toxoplasma manipulates far more cells than previously realized and , given their abundance , these uninfected-injected cells may play a central role in how Toxoplasma engages the host's immune response . | [
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] | 2012 | Toxoplasma Co-opts Host Cells It Does Not Invade |
Climate change has differentially affected the timing of seasonal events for interacting trophic levels , and this has often led to increased selection on seasonal timing . Yet , the environmental variables driving this selection have rarely been identified , limiting our ability to predict future ecological impacts of climate change . Using a dataset spanning 31 years from a natural population of pied flycatchers ( Ficedula hypoleuca ) , we show that directional selection on timing of reproduction intensified in the first two decades ( 1980–2000 ) but weakened during the last decade ( 2001–2010 ) . Against expectation , this pattern could not be explained by the temporal variation in the phenological mismatch with food abundance . We therefore explored an alternative hypothesis that selection on timing was affected by conditions individuals experience when arriving in spring at the breeding grounds: arriving early in cold conditions may reduce survival . First , we show that in female recruits , spring arrival date in the first breeding year correlates positively with hatch date; hence , early-hatched individuals experience colder conditions at arrival than late-hatched individuals . Second , we show that when temperatures at arrival in the recruitment year were high , early-hatched young had a higher recruitment probability than when temperatures were low . We interpret this as a potential cost of arriving early in colder years , and climate warming may have reduced this cost . We thus show that higher temperatures in the arrival year of recruits were associated with stronger selection for early reproduction in the years these birds were born . As arrival temperatures in the beginning of the study increased , but recently declined again , directional selection on timing of reproduction showed a nonlinear change . We demonstrate that environmental conditions with a lag of up to two years can alter selection on phenological traits in natural populations , something that has important implications for our understanding of how climate can alter patterns of selection in natural populations .
Global climate change has led to shifts in phenology , i . e . , the seasonal timing of life history events , such as budburst , flowering , hibernation , migration , or reproduction , in many species . Over the past three decades , plants and animals have shifted their timing , on average , three to four days per decade [1–8] . These shifts allowed them to at least partly adapt to the shifted optimal timing caused by the altered abiotic and biotic conditions . The observed shifts in seasonal timing have often not been as strong as the shift in the optimal timing , which could have negative consequences for fitness [9 , 10] . In seasonal habitats , reproductive success often increases with the temporal match at the peak of food availability [8 , 11–15] . Climate change can disrupt this phenological match between trophic levels because of differential phenological responses at different trophic levels [2 , 8 , 16] , but variation between specific systems is likely depending on the ecology of the interrelated trophic levels [17–21] . In migrant species , these differential responses could be caused by differences in the rates of temperature change in different geographical regions during the annual cycle [22] . Migratory species in particular must rely on environmental conditions experienced en route to predict the optimal time for stopover , arrival , or breeding at distant areas [23 , 24] . When in a population the timing of life cycle events shifts at a different rate than the optimal timing is shifting , directional selection on the timing will increase . Identifying the environmental variables that are the selective agents is important to predict future impacts of climate change and to be able to study the mechanisms underlying the ecological effects of climate change . However , these selective agents have rarely been identified , even outside the climate change setting , as pointed out earlier [25 , 26] . There are only a handful of studies that have identified such environmental variables [9 , 27–30] . One example is selection on timing of reproduction in great tits ( Parus major ) in the Netherlands , where increasing spring temperatures have advanced the peak date in the food for the nestlings ( i . e . , caterpillars ) more strongly than the egg-laying date of the birds [7] ( but see [28] for a United Kingdom great tit population where there has been no increase in phenological mismatch ) . As this mismatch between nestling food availability and demand affects the strength of selection on egg-laying date [9 , 12 , 27 , 28] , selection for earlier laying has increased [7] . As the timing of both the caterpillars and the birds depends on temperature , the strength of selection depended on spring temperature [9 , 27] . Here , we aim to identify the possible selective agents , including phenological mismatch , underlying the selection for egg-laying date in an insectivorous songbird , the pied flycatcher ( Ficedula hypoleuca ) . Pied flycatchers are long-distance migrant birds whose timing of reproduction is constrained by spring arrival time [31] . As for many long-distance migrants , spring arrival dates are advancing slowly , possibly because the environmental cues in the wintering grounds have limited reliability to forecast environmental conditions in the breeding areas [31] ( but see [23] ) . Pied flycatchers in our Dutch long-term study population have advanced their egg-laying date , but not sufficiently enough to keep track of the advancing caterpillar peak [32] , and selection for early breeding increased between 1980–1998 [31] . Pied flycatchers breeding in areas with early caterpillar phenology declined strongly , in contrast to areas with later phenology [33] , suggesting that the mismatch with caterpillar availability could be determining this change in selection patterns ( “phenological mismatch hypothesis” [7 , 34 , 35] ) . Despite these circumstantial data , the environmental variables causing the increased selection for earlier breeding have not been formally tested . We here aim to ( 1 ) describe ongoing changes in selection for timing of reproduction in our long-term pied flycatcher population , spanning more than three decades , using a novel statistical framework , and ( 2 ) identify the environmental variables that account for the temporal pattern of selection on timing of reproduction . To explore the environmental variables potentially underlying selection that could explain this temporal pattern , we analysed not only our primary fitness measure , the number of recruits produced , but also its two components: the number of fledglings produced and the probability that a fledgling recruits as a breeding bird . These two components could be affected by different environmental variables , and therefore analysing them separately may provide further insights in how environmental variables affect the number of recruits produced . As a way to identify the determinants of observed variation in ( directional ) selection , we assessed the effects of a number of environmental variables ( see below ) on the relationships between these fitness components and timing of reproduction . Three types of environmental variables were tested: climatic variables during the breeding season , food availability during the breeding season , and the conditions at the time the offspring returned to breed for the first time . As climatic variables , we considered seasonal patterns in temperature and the duration of rainfall ( which reduces the provisioning time for the parents ) , both during the chick feeding period and during the period just after fledging , i . e . , when offspring become independent , as these may affect fledgling survival from early and late broods differently ( e . g . , [36] ) . Next , we tested the hypothesis that the degree of temporal mismatch between caterpillar peak dates ( as one of the main food sources for offspring [37] ) and flycatcher egg-laying dates is important for explaining among-year variation in selection [35] . Finally , we tested an alternative mechanism to explain the observed variation in the annual strength of selection , based on previous observations that in years with low temperatures during spring arrival , early-arriving individuals are less likely to survive [38] . We investigate whether hatch date of an individual ( i . e . , the lay date of its mother ) is a predictor of spring arrival date when offspring return as a breeder and whether early- and late-hatched individuals’ survival upon arrival may thus be affected differentially by spring temperatures .
Pied flycatchers have advanced their annual mean egg-laying date between 1980 and 2010 by 12 d ( b = -0 . 38 ± 0 . 06 d/y , F1 , 29 = 40 . 2 , p < 0 . 001 ) . Over the same time period , directional selection in pied flycatchers for earlier egg-laying dates ( via numbers of local recruits produced ) initially increased in magnitude but waned again in the last ten years of our study period ( Fig . 1A; linear and quadratic trend of year in annual linear selection gradients: -0 . 05 ± 0 . 04 and 0 . 12 ± 0 . 06 , respectively , likelihood ratio test ( LRT ) of model with quadratic trend over model with only linear trend: Chi2 = 3 . 91 , df = 1 , p = 0 . 048 ) . Selection has therefore gone from stabilising in the first decade ( within-year analysis for the period 1980–1989: linear selection gradient = -0 . 09 ± 0 . 07 , p = 0 . 18 , quadratic selection gradient = -0 . 24 ± 0 . 08 , p = 0 . 012 ) to directional selection for earlier egg-laying dates in the second decade ( within-year analysis for the period 1990–1999: linear selection gradient = -0 . 50 ± 0 . 11 , p < 0 . 001; quadratic selection gradient = 0 . 43 ± 0 . 20 , p = 0 . 02 ) . However , in the last decade , directional selection on egg-laying date has weakened again but without a return to stabilising selection ( within-year analysis for the period 2000–2010: linear selection gradient = -0 . 24 ± 0 . 06 , p < 0 . 0001; quadratic selection gradient = 0 . 04 ± 0 . 09 , p = 0 . 70 ) . To explain this pattern in the annual strength of selection on egg-laying date ( Fig . 1A ) , we analysed how the relationships between egg-laying date and the number of recruits produced , and its two components , changed with environmental variables . Surprisingly , the strength of the seasonal decline in the number of recruits was not correlated with the mismatch between egg-laying date and the timing of the seasonal caterpillar peak ( interaction egg-laying date * mean population mismatch; Table 1 ) . In accordance with this result , we found no statistically significant relationship between mismatch and standardised linear selection gradients ( b = -0 . 02 ± 0 . 07 , Chi2 = 0 . 094 , df = 1 , p = 0 . 76 , LRT of model including mismatch as well as year and year2 versus a model including only year and year2 , see “Data analysis” in Materials and Methods for details ) ( Fig . 1B ) . Thus , the difference between the egg-laying date and the caterpillar peak ( the phenological mismatch ) does not appear to be a major driver of selection . Additionally , none of the meteorological variables during the breeding season , such as temperature or rainfall duration , explained variation in the strength of the seasonal decline in number of local recruits produced , the number of fledglings produced , or the recruitment probability of fledglings ( Table 1 ) . However , the seasonal decline in the number of fledglings produced was stronger when caterpillar peaks were lower , suggesting that the seasonal decline in reproductive output is related to the amount of caterpillars available ( interaction egg-laying date * height of the caterpillar peak; Table 1 ) . We found support for the alternative hypothesis that conditions upon spring arrival for recruiting offspring explain between-year variation in selection on egg-laying date . Thus , when arrival temperatures were warm in the year of recruitment , recruitment probability declined more steeply with the egg-laying date of the clutch the offspring hatched in than when the springs were cold ( interaction egg-laying date * arrival temperature; Table 1; Fig . 1C ) . As pied flycatcher fledglings mostly recruited in the first or second year after fledging ( see “Age at recruitment” in Materials and Methods ) , the arrival temperature was calculated as the mean minimum spring temperature averaged over the two years after hatching during the arrival period of females ( see Materials and Methods ) . In accordance with this , selection for earlier egg-laying date was stronger when arrival temperatures in the two years after fledging were higher ( b = -0 . 18 ± 0 . 08 , Chi2 = 4 . 76 , d f = 1 , p = 0 . 03; Fig . 1D , LRT of a model including arrival temperature as well as year and year2 versus a model including only year and year2 , see “Data analysis” in Materials and Methods for details ) , as in these years the early-hatched offspring have higher prospects to be recruited compared to cold years , while the recruitment probability of late-hatched offspring was not affected by arrival temperatures ( Fig . 1C ) . Note that when we fitted either of these year-specific temperatures alone or together ( rather than the temperature mean over the two years ) , we found similar effects ( Table 2 ) . To explain the initial increase and later relaxation of selection on egg-laying date ( Fig . 1A ) , arrival temperatures should have changed over time in a similar way , and , indeed , they have: arrival temperatures increased from 4°C to 8°C during the first 20 y of the study period , after which they decreased again over the last decade ( year2: b = -0 . 008 ± 0 . 003 , F1 , 28 = 9 . 23 , p = 0 . 03; Fig . 2; “broken stick” ( or segmented ) regression [39] testing for different ( linear ) trends in different periods: best fit for the two periods 1980–1996 and 1997–2010; in the first period , temperature increased ( b = 0 . 15 ± 0 . 06 , F1 , 15 = 5 . 44 , p = 0 . 03 ) , in the second period temperatures tended to decrease ( b = -0 . 15 ± 0 . 07 , F1 , 12 = 4 . 45 , p = 0 . 057 ) . This temporal pattern in arrival temperatures thus could explain the temporal change in the strength of selection on egg-laying dates ( Fig . 1A ) . We contend that spring arrival temperatures are important because these temperatures determine ecological conditions affecting survival and settlement just before or after arrival at the breeding grounds . The link with the egg-laying date of a bird’s mother is through a potential effect of hatch date on arrival date later in life . If early-hatched individuals themselves have an early arrival , they may benefit in warmer years but may pay a penalty in colder years ( c . f . , [38 , 40] ) . Indeed , the relative egg-laying date from the clutch in which an individual hatched was positively correlated with the first spring arrival date as adult breeder ( relative to the population mean ) , especially in females ( b = 0 . 22 ± 0 . 07 , F1 , 351 = 8 . 97 , p = 0 . 003 ) , but less so for males ( b = 0 . 11 ± 0 . 08 , F1 , 211 = 1 . 99 , p = 0 . 16 ) . Note that when we constrain the analysis for females to the same observation period as for males ( 2002–2012 ) , this effect remains statistically significant in females ( b = 0 . 28 ± 0 . 10 , F1 , 186 = 8 . 02 , p = 0 . 005 ) . A further indication that females hatched in early-laid clutches are themselves also arriving and laying eggs early is that egg-laying date is heritable: h2 = 0 . 33 ( 95% CI: 0 . 25–0 . 39 ) .
Between 1980 and 2010 , selection on egg-laying date changed from initially stabilising to directional selection for early laying , but this directional selection relaxed again during the last decade . We found no evidence indicating that this pattern was explained by environmental variables measured within the breeding season nor by the temporal mismatch with the food peak [35 , 41] . Instead , the annual variation in selection was correlated with spring temperatures up to two years after breeding , with stronger selection for earlier laying when spring temperatures in the arrival year for the cohort were high . In our study , the increase in spring temperatures initially led to stronger selection for early egg-laying , as offspring from early nests were more likely to recruit than offspring from late nests under warm conditions upon arrival ( Fig . 1C ) . Between 2000 and 2010 , however , arrival temperatures have decreased . This cooling has weakened the strength of directional selection on egg-laying date in this population . We thus show that changes in spring temperatures have a clear impact on selection on a key life history trait: timing of reproduction . We found no strong evidence for an effect of a phenological mismatch with the caterpillar peak on selection in this migratory species , as previously has been suggested [35 , 41] based on other systems [9–11 , 42] . This is unexpected , as synchrony between food peaks and avian timing of reproduction has often been suggested to be important [43 , 44] , and differential phenological responses across trophic levels to climate change have been a major hypothesis explaining increased selection , reduced reproduction , and population declines [45 , 46] . Also in our study population , caterpillars are an important component in the nestling diet of pied flycatchers , and in warm years , strong seasonal declines in the proportion of caterpillars in the diet were observed [37] . We did find that the height of the peak in caterpillar abundance , rather than the temporal synchrony with the caterpillar peak , affected the seasonal decline in number of fledglings ( Table 1 ) . In years with high caterpillar abundance , there was only a weak decline in the number of fledglings over the course of the season; whereas in low caterpillar peak years , this decline was much stronger . This suggests that caterpillars are indeed important as a food source affecting flycatcher fitness and that their availability per se influences selection on seasonal timing . The lack of an effect of synchrony could thus be partly obscured by variation in caterpillar peak height . Caterpillar availability strongly fluctuates between years , with a factor 20 or more between the lowest and highest caterpillar density years [47] and a cycle period of around 9–10 y [48] . Within our dataset , we had periods with peak abundances around 1996 and 2009 , and in these years , even birds that breed out of synchrony with the caterpillar peak do not have a strongly reduced offspring production , although very late birds always do poorly because of reduced food availability later in the season [49] . In line with this , the seasonal decline in clutch size is stronger in years when the birds breed late relative to the food peak [50] . Predictions of potential effects of climate change should thus not just consider temporal matching but also potential changes in food abundance [42] . Our fitness measure is the number of fledglings that locally recruit in our population , and therefore this fitness estimate does not include all offspring that survive and disperse out of the study population . Our best estimate is that about four times as many fledglings recruit elsewhere with dispersal distances up to 600 km [51] . This means that measuring fitness as the number of local recruits is potentially biased if differential dispersal exists with respect to laying date of the mother . If offspring that originate from early- or late-laid clutches differ in the likelihood that they recruit outside the study areas , this will lead to apparent selection for egg-laying date . However , correlative and experimental data in pied flycatchers do not support this idea; experimentally delayed hatching date ( during three consecutive breeding seasons ) did not affect natal dispersal in a metapopulation setup where dispersing offspring could be tracked up to 25 km [52] . Thus , we have no indication that differential dispersal with respect to timing exists in our study system . The idea of differential dispersal in response to climate change is that late-arriving individuals in warm years benefit by continuing their migration further north and thereby matching habitat phenology with their own timing [53] . Support for northwards dispersal has been found in black-winged stilts in dry springs [54] and in American redstarts that depart later from their wintering grounds [55] , but these studies could not unequivocally demonstrate that differential dispersal for a phenotypic trait was related to environmental variation . In our case , we predict that such a pattern would result in especially late-arriving individuals showing high survival in cold years , and low survival in warm years , whereas little effect is expected for early-arriving individuals . Our results , however , do not support these predictions for differential dispersal: late-born offspring recruited equally well when returning in colder or warmer springs ( Fig . 1C: comparing data points for laying dates >5 ) . Variation in selection between warm and cold years was thus not caused by differential survival of late-born offspring but rather for early-born offspring that return more in warmer than in colder years ( Fig . 1C ) . In almost any natural population , permanent dispersal is difficult to separate from mortality , especially when dispersal can occur over large distances . A key consideration in this respect is to assess whether this dispersal likelihood is correlated with the trait of interest , i . e . , egg-laying date . We cannot rule out the possibility that differential dispersal affects our fitness estimates , but available evidence suggests that differential dispersal is not a main factor explaining our results . Additionally , differential dispersal would only mediate the patterns observed in Fig . 1A if its relationship with laying date changed over time , which is unlikely . Consequently , in our opinion , the pattern depicted in Fig . 1A is most parsimoniously explained by temporal variation in the relationship between egg-laying date and fitness . As in many studies of natural populations , the correlation between trait ( here egg-laying date ) and fitness could potentially be caused by covariance with some environmental variable [56] . Further mechanistic experimental work could therefore be useful in determining whether variation in offspring phenology , and its consequences for offspring and parental fitness , is caused by parental egg-laying date and hence hatch date per se , or if it covaries with parental egg-laying date because of genetic or environmental correlations [57] . We also need more insights into why offspring from early-hatched clutches do so much better when the temperatures are high when they arrive ( Fig . 1C ) . Does an early arrival give them a competitive advantage which is offset against a higher mortality in colder years ? This could yield further insights into the evolutionary potential of these phenological traits through parameterisation of more formal models [58 , 59] of the relationships between parental and offspring phenotype and fitness . Studies have rarely demonstrated a relationship between selection on life history traits and climate change-altered environmental variables ( i . e . , selective agents [25] ) . Yet , all of these studies found immediate effects , i . e . , within the same season in which the life history trait is expressed [9 , 28 , 29] . Here , we have shown the apparent absence of such immediate effects but demonstrated an effect of conditions years after the life history trait is expressed . Such effects have been little studied in this context , but might be common . Studies of both delayed effects of environmental variables and the interaction between demographic and evolutionary processes on selection are urgently needed as selection is a key component for microevolution of life history traits , which is ultimately the only route for populations to adapt to novel environments [60] .
This study was carried out with the approval of the Animal Experimentation Committee of the Royal Dutch Academy of Sciences . We analysed data from 1980 until 2010 from the Hoge Veluwe study area ( 52°059 N , 05°509 E , the Netherlands ) , where about 400 nest boxes are supplied in a 171 ha study area of mixed deciduous and coniferous forest . We only analysed data until 2010 to get reliable estimates of the number of recruits produced since about half of the offspring is found to recruit only two years after fledging as a breeding individual ( see “Age at recruitment” in Materials and Methods ) . The broods of 1995 were excluded from all analyses since in this year almost all broods in the population were manipulated in a way that affected their breeding success [61] . Nest boxes were checked weekly during the egg-laying period , and first egg-dates ( henceforth called egg-laying dates ) were calculated on the assumption that one egg is laid per day . We included only clutches that we considered as first clutches of females: repeats of known females that failed were excluded , as were all clutches that started >30 d after the first egg-laying date in that year . During these regular checks , nest-building stages were reported . Adults were caught during chick feeding using nest box traps for identification based on their ring numbers . All nestlings were ringed with standard aluminium rings at an age of 7 to 12 d . The observed temporal pattern in the strength of selection ( Fig . 1A ) could be caused by a systematic change over the study period in how the adult recapture probabilities differed for birds hatched in late or in early-laid clutches . In order to test this possibility , we estimated survival and capture probabilities using a formal capture-mark-recapture analysis [62] using the software MARK [63] . We first fitted simple models , in which adult survival and recapture probability were constant over years and possibly only differed among the sexes . We then tested whether survival and recapture probabilities would differ among years and whether they depended on the egg-laying date of the clutch an individual was born in ( “birth clutch lay date” ) , and whether this relationship differed between years , by adding the interaction of “birth clutch lay date” with year to the model . If recapture probabilities would depend on “birth clutch lay date , ” and this relationship would differ among years , it could possibly bias our results . To test whether recapture probabilities could explain the observed selection and its temporal change , we fitted a range of capture-mark-recapture models in which recapture probability depended on sex , year ( linear and squared effect ) , and the egg-laying date of the clutch from which an individual hatched . While there was clear support for a linear temporal change in recapture probability ( Table 3 , model 1 ) , the support for a quadratic change of recapture probability over time was less clear ( Table 3 , model 2: Δ AICc = 2 . 0 and AICc weight = 0 . 27 ) . However , we found no evidence for capture probability being correlated with birth clutch lay date ( Table 3 , model 4: Δ AICc = 9 . 7 and AICc weight = 0 . 005 ) . Male arrival date was determined from 2002 to 2010 through daily observations covering the whole study area , from April to early May by one to three trained observers . In our pied flycatcher population , males greatly vary in their plumage characteristics ( i . e . , size and shape of forehead patch and darkness of dorsal feathers; see [64] ) , and about half of them had been marked in previous years with aluminium and colour rings . We made notes of these features during our daily observations to characterise males singing at each nest box , allowing ascribing arrival dates—based on the similarity of features—to individual males , which were captured during chick feeding in the nest boxes . Pied flycatcher males commonly breed in the immediate surroundings of the area where they are first observed singing [65] , and hence in most cases the description of the male repeatedly singing in a particular nest box matched the characteristics of the bird captured in it during breeding , which supports the validity of this approach to gather information on spring arrival phenology in this species ( see [65] for a similar approach ) . This procedure allowed us to assign the arrival date in 571 cases ( 397 different individuals ) in nine years , which is more than half of the males present in our study site . For female arrival date , we used the estimated start of nest building as proxy . Female flycatchers select a mate within hours upon their arrival [66 , 67] , and they start nest building immediately after . Over the entire study period , the stage of nest building was scored ( using a six-point scale , from little material to a complete nest ) during the weekly nest checks . We assumed that little material meant that nest building had started the day of the check , whereas a complete nest started six days ( i . e . , the day after the previous nest box check ) earlier ( and other stages in between ) . The validity of this proxy was tested using observational data on arrival dates of male and female pied flycatchers in a nearby population ( Dwingeloo , The Netherlands ) . The Dwingeloo study area has 100 nest boxes and approximately 50 pairs of pied flycatchers annually . The same observer ( CB ) checked arriving pied flycatcher on a mostly daily basis from April 10 to May 15 for 2007 , 2008 , 2009 , 2010 , and 2013 . Note that the years 2010 and 2013 were exceptionally cold springs , resembling what was normal during the early part of our time series ( 1980s ) , and therefore this allows us testing under the full range of environmental circumstances whether this proxy indeed can be used . Male flycatcher arrival was determined based on individual plumage characteristics ( see above ) . Female arrival date was determined as the pairing date , which was often clearly visible because males reduced or completely stopped singing after being paired , and these behavioural changes were mostly confirmed by the observation of a female with the focal male . Nest boxes were checked at least once every five days , but more often to confirm female arrival , and the contents of the box were noted on the same six-point scale as at the Hoge Veluwe . To test whether female arrival date correlated well with the start of nest building , we used 194 observations in which female arrival date and the start of nest building were known . The estimated slope was 1 . 05 ± 0 . 02 ( t1 = 66 . 84 , p < 0 . 001 ) . These data clearly show the validity of using the start of nest building as proxy for female arrival , as there is an almost 1:1 relationship . However , it must be noted that if females give up their nest and renest , their arrival dates cannot be estimated from the start of nest building . Especially late nests therefore should be treated with caution , adding noise to the data and , especially in cases where a large fraction of nests are abandoned , this proxy becomes inappropriate . In our Hoge Veluwe study population , however , this is rarely the case . We used the number of offspring produced that return as a breeding bird in the Hoge Veluwe population ( local recruit ) as a fitness measure . This number of recruits produced is the total number of recruits from first and replacement clutches ( after a failed first clutch ) within a single season . The number of recruits produced can be partitioned in two components , the number of fledglings produced and the probability for these fledglings to recruit . These two components can be affected by very different climatic variables , and hence we also analysed how these two components were affected by the selected climatic variables to gain more insight in how our overall fitness measure , the number of recruits , was related to climate variables . The number of fledglings was the number of chicks ringed minus the number of offspring found dead in the nest box after the offspring had fledged . The probability to recruit was calculated as the number of recruits per nest divided by the number of fledglings per nest ( thus excluding the nests without fledglings ) . As capture probability of a locally recruiting offspring was not correlated with the egg-laying date of the brood a recruit originated from ( see above and Discussion ) , we did not correct the number of recruiting offspring for capture probability . Note that an offspring is a recruit when it is caught at any age at the Hoge Veluwe , so even when birds are missed in their first breeding year , they are likely to be caught in their second year of breeding . Most locally-hatched pied flycatchers are caught as breeding adults for the first time either in their first or second year after fledging: 32% of all male recruits returned to breed for the first time at age one and 54% at age two; this pattern is almost exactly reversed in female recruits , of which 59% returned at age one and 32% at age two . Only 14% ( males ) and 9% ( females ) , respectively , returned at older ages to breed for the first time . Given our capture probabilities ( see above ) , the records of birds breeding for the first time two years after fledging is unlikely to be due to birds breeding but not being identified in their first year after fledging . Data on daily mean and minimum temperature ( °C ) and rain duration ( number of hours of rain in 24 hours ) from the weather station directly adjacent to the study area ( Deelen , 52°059 N , 05°509 E ) were obtained from the Royal Dutch Meteorological Institute ( KNMI; http://www . knmi . nl/klimatologie/uurgegevens/#no ) . We used daily mean temperature as the predictor variable for the nestling period ( defined per year as the period from the mean egg-laying date plus 18 d ( 6 d of egg laying plus 12 d of incubation ) to mean egg-laying date plus 30 d ( an additional 12 d of chick rearing ) and the fledging period ( defined per year as the period of the mean egg-laying date plus 31 d to mean egg-laying date plus 42 d ( 12 d of post-fledging care [64] ) . We used minimum temperature for the arrival period because we hypothesised that while nestling survival would be affected by a variety of factors better reflected by mean temperature , the survival of recruits upon arrival would depend on the severity of harsh conditions reflected by minimum temperatures . Temperatures at the time of arrival in spring were calculated during the period when 90% of all females arrived ( averaged over the 30 y ) . This “arrival period” was defined as the interval from the average annual 5% quantile ( between-year standard deviation 5 . 3 d ) until the average annual 95% quantile ( between-year standard deviation 6 . 7 d ) of female arrival dates ( using nest building as proxy ) : April 23 until May 12 . As most pied flycatchers were caught breeding for the first time either in their first or second year after fledging ( see “Age at recruitment” in Materials and Methods ) , we took the average daily minimum temperature during the arrival period one and two years after fledging as a measure of environmental conditions upon first arrival . We used temperatures averaged over a fixed period because using temperatures measured over the realised arrival period , i . e . , an annually variable period , would “reverse” causality: in that case , the behaviour of the birds would have determined the climatic variable rather than vice versa . Caterpillars form an important prey for the nestlings of many passerine bird species including pied flycatchers [37] , and caterpillar biomass has been monitored between 1985–2010 in the Hoge Veluwe-study area by collecting caterpillar droppings ( “frass” ) using special nets placed on the ground under oak trees ( Quercus robur ) . “Frass” was collected two to three times a week , dried , sorted , and weighed . Caterpillar biomass was then calculated from its weight using the formula given in [68] . See [11] for more details on study area and the described methods . We estimated annual standardised directional selection gradients following methods outlined in [69] . Briefly , we first characterised the relationship between egg-laying date and the number of local recruits produced , in each year using generalised linear models with a Poisson error structure . GLMs included linear and quadratic linear predictor scale regression terms ( to detect directional , stabilising or disruptive selection ) , except for 1981 , 1989 , 1990 , 1991 , and 2006 , where we fitted only linear regression terms because low numbers of recruits ( < 15 ) precluded fitting more complex models . Next , we used the R package gsg [69] to obtain yearly standardised directional selection gradients ( sensu [70] ) , and their standard errors and p-values using a parametric bootstrap algorithm . Because of the large statistical uncertainty associated with each annual selection gradient , we developed a method to robustly estimate the regression of selection gradients against predictors ( e . g . , year or environmental variables ) . We fitted the model βt ~ μ + b1t + b2t2 + mt + et , where βt are estimated selection gradients for year t , and mt are deviates of estimated selection gradients from their unknown true values and are assumed to be drawn from the distributions N ( 0 , SEt2 ) , where SEt are the standard errors associated with each estimated selection gradients . b1 and b2 are regression coefficients relating selection to year . When testing whether other environmental variables affected selection strength , coefficients relating selection to these environmental variables were included similarly in addition to linear and quadratic effects of year . et are residuals , and are assumed to be normally distributed with estimated variance . We fitted the model by maximum likelihood , tested regression terms with LRTs , and approximated the standard errors of regression coefficients from the information matrix . The maximum likelihood techniques provided nearly identical inferences to a complimentary Bayesian approach implemented by extending the meta-analytic approaches used in [71] . When formally analysing stabilising selection , we pooled data ( for reasons mentioned above ) , into the periods ( 1980–1989 , 1990–1999 , and 2000–2010 ) and regressed relative fitness against the linear and quadratic term of centred egg-laying date using the approach described above . The relationship of single fitness components ( number of recruits , number of fledglings and recruitment probability ) with egg-laying date and environmental variables was tested with GLMMs , with year as random effect , to account for nonindependence of data from the same year with respect to the environmental variables that were measured at an annual scale . Female identity was included as random effect to account for females breeding in more than one year . Number of fledglings and recruits were analysed using a log-link and a Poisson error-distribution . An observation-level random effect was included in the Poisson models , the commonly observed overdispersion in reproductive success [72] . The recruitment probability per brood was analysed using a logit-link and a Binomial error-distribution . The heritability of egg-laying date was calculated based on standard quantitative genetic approaches implemented in the so-called “animal model” ( [73] . To account for year-to-year variation and age effects , year and age were included as fixed factors . Female identity was included as “permanent environment” random effect to account for repeated breeding events of the same female . The additive genetic effect was included as random effect to estimate heritability as the ration of the variance explained by the additive genetic effect over the total phenotypic variance ( excluding year and age effects as these were fitted as fixed effects ) . All estimates are reported ± standard error . Data deposited in the Dryad repository: http://dx . doi . org/10 . 5061/dryad . cv24c [74] . | Pied flycatchers are long-distance migrant birds that have advanced their timing of reproduction over the past decades in response to climate change . We studied selection on egg-laying date using a 31-year-long population study and found that in the first 20 years , early-reproducing birds had increasingly higher fitness than late-reproducing birds , resulting in intensified selection on egg-laying date . However , during the last decade , selection on egg-laying date has weakened considerably , although the timing mismatch between breeding and food availability—supposedly the main determinant of selection on breeding phenology—did not change . Whereas conditions during breeding cannot explain the temporal pattern in the strength of selection , spring temperatures at the time the offspring’s first return to the breeding site , i . e . , one or two years later , do explain the annual variation in selection well . If spring temperature at arrival is high , early-hatched birds recruit to the breeding population better than late-hatched birds , while in cold years , early- and late-hatched birds recruit equally well . Because early-hatched daughters arrive early when they recruit into the population , females that lay eggs early ( and thus have early-hatched chicks ) have a strong selective advantage when the following years are warm . Arrival temperatures increased over the first two decades but then cooled again , leading to the observed pattern in selection . | [
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] | [] | 2015 | Effects of Spring Temperatures on the Strength of Selection on Timing of Reproduction in a Long-Distance Migratory Bird |
Medical devices , such as contact lenses , bring bacteria in direct contact with human cells . Consequences of these host-pathogen interactions include the alteration of mammalian cell surface architecture and induction of cellular death that renders tissues more susceptible to infection . Gram-negative bacteria known to induce cellular blebbing by mammalian cells , Pseudomonas and Vibrio species , do so through a type III secretion system-dependent mechanism . This study demonstrates that a subset of bacteria from the Enterobacteriaceae bacterial family induce cellular death and membrane blebs in a variety of cell types via a type V secretion-system dependent mechanism . Here , we report that ShlA-family cytolysins from Proteus mirabilis and Serratia marcescens were required to induce membrane blebbling and cell death . Blebbing and cellular death were blocked by an antioxidant and RIP-1 and MLKL inhibitors , implicating necroptosis in the observed phenotypes . Additional genetic studies determined that an IgaA family stress-response protein , GumB , was necessary to induce blebs . Data supported a model where GumB and shlBA are in a regulatory circuit through the Rcs stress response phosphorelay system required for bleb formation and pathogenesis in an invertebrate model of infection and proliferation in a phagocytic cell line . This study introduces GumB as a regulator of S . marcescens host-pathogen interactions and demonstrates a common type V secretion system-dependent mechanism by which bacteria elicit surface morphological changes on mammalian cells . This type V secretion-system mechanism likely contributes bacterial damage to the corneal epithelial layer , and enables access to deeper parts of the tissue that are more susceptible to infection .
Some bacteria induce changes in human cell architecture through expression of virulence factors , which aid in bacterial internalization into cells and provide a more favorable niche for microbial colonization . Cell alterations include the formation of pedestals on intestinal cells by enteropathogenic and enterohaemorrhagic Escherichia coli strains through expression of type III secretion system ( T3SS ) -associated effector proteins that alter the actin cytoskeleton [1 , 2] . Other bacteria create membrane ruffles , alterations that facilitate bacterial invasion into the mammalian cell [3] . Another type of mammalian cell surface alteration , known as bleb formation , appears following cellular injury [4 , 5] . The bacterium Pseudomonas aeruginosa can induce bleb formation in airway and ocular cells . These blebs are similar to , but are more stable than , necrotic blebs and require a T3SS encoded by P . aeruginosa , and the ExoS and ExoY T3SS effector proteins [6 , 7] . T3SS-dependent induction of membrane blebs on human cells was also reported for Vibrio parahemolyticus [8] . Large necrotic membrane blebs can also be induced by hydrogen peroxide and are thought to be a last-ditch effort by the cells to evade lysis . In this setting , they may serve as a storage unit to sequester damaged cellular components away from the cell or are simply a loss of cell homeostasis [5 , 9 , 10] . Blebs induced by membrane breach are hypothesized to be a result of the influx of calcium that activates hydrolytic enzymes capable of damaging the cellular cortex [11] . Gram-negative bacteria of the Enterobacteriaceae family , such as Proteus mirabilis and Serratia marcescens , cause nosocomial infections in neonates and immune compromised patients and contact lens associated complications in healthy individuals , including keratitis [12–17] . Microbial keratitis , or infection of the cornea , is a potentially blinding infection with a poor visual outcome , even when effective antibiotics are used to treat the infecting bacterium [14 , 18] . Bacteria must overcome the epithelial cell layer in order to cause keratitis , and the killing of ocular surface cells is one mechanism bacteria could use to access the stromal layer that resides under the epithelium [19] . Therefore , we set out to study mechanisms by which keratitis causing bacteria damage the epithelium , which are largely unknown for the Enterobacteriaceae family of bacteria . In this study , we observed that clinical keratitis isolates of S . marcescens cause bleb formation and cellular death in human ocular cells . However , S . marcescens bacterial genomes rarely encode genes for a T3SS , with strain FS14 [20] , isolated from a leaf-cutter ant fungus garden , being the only strain described in the literature with a T3SS . These results suggested that S . marcescens has another mechanism to elicit these structural changes from the human epithelial cell , and we therefore employed a genetic screen to identify bacterial genes required for eliciting bleb formation . The role of the identified genes in bleb formation , cytotoxicity , and virulence was characterized using strains with deletion mutations and their corresponding complements , and a potential regulatory pathway was determined . We demonstrated that the Rcs stress response system controls expression of pore forming toxins secreted by a type V secretion system ( T5SS ) mechanism . The role of the T5SS-dependent cytolysin in bleb formation was validated using keratitis isolates of P . mirabilis , which suggests a novel conserved mechanism by which bacteria can induce cellular blebs to facilitate pathogenesis at epithelial surfaces .
Dramatic bleb formation on the cellular surface of a human corneal epithelial cell line ( HCLE ) was observed by microscopic analysis when S . marcescens contact lens-associated keratitis isolate K904 was co-incubated with the human cells ( Fig 1A ) . Bleb formation was absent in HCLE cells exposed to bacterial growth medium ( Mock ) without bacteria ( 0% , n = 969 cells ) , whereas 69 . 5 ± 15 . 0% of HCLE cells challenged with S . marcescens K904 bacteria for 2 h ( MOI = 200 ) produced blebs ( n = 920 cells ) ( p<0 . 001 , Fisher Exact test ) . Bleb formation frequency remained high when the MOI was 50 ( 95 . 4 ± 8 . 2% , n = 571 ) , but reduced with an MOI = 10 , ( 4 . 6% , n = 22 ) . Confocal laser scanning microscopy and CellMask fluorescent membrane stain support that the bleb structures are extensions of HCLE plasma membranes and can become almost as large as the cells ( Fig 1B ) . Scanning electron microscopy revealed S . marcescens bacteria associated with the membrane blebs ( Fig 1C ) . Live microscopic imaging of HCLE cells exposed to S . marcescens K904 produced membrane blebs starting before 120 minutes of co-incubation ( compare S Movie 1 for Mock and S Movie 2 for S . marcescens K904 , Fig 1D ) . Blebs were observed to grow over time , and then retract into the cell body as the cells rounded up ( Fig 1D ) . We tested whether the observed phenomenon was an artifact of using a specific human cell type , bacterial strain , or bacterial species . Testing bacterial strain specificity , we observed that 34 out of 34 S . marcescens strains derived from a variety of sources including environmental and clinical isolates induced bleb formation; these include reference strain Db11 and laboratory strain PIC3611 ( S1A Fig ) . A variety of other species were tested for the ability to induce blebs in HCLE cells ( MOI = ~200 for 2 h exposure ) . We found that Proteus mirabilis and Edwardsiella tarda were able to induce blebs during the 2 h time frame ( S1B Fig ) , but no blebs were induced by tested strains of Acinetobacter baumannii , Citrobacter frundii , coagulase negative staphylococci , Enterobacter aerogenes , Enterococcus faecalis , Klebsiella pneumoniae , Morganella morganii , Staphylococcus aureus MRSA and MSSA , Staphylococcus epidermidis , Streptococcus pneumoniae [21] , and Stenotrophomonas maltophilia . With Pseudomonas aeruginosa , keratitis isolate K900 [22] did induce blebs ( S1B Fig ) but wound isolate PAO1 [23] did not under the tested conditions . Beyond the HCLE cell line , human primary corneal cells produced blebs in response to S . marcescens strain K904 ( Fig 1E ) . With an MOI of 50 , 34% of primary cells had a bleb ( n = 22 ) , as compared to 0% without bacterial challenge ( n = 48 ) . Calcein AM staining for intact , metabolically active cells suggested that the blebbing cells are no longer viable ( Fig 1E ) . Similarly , S . marcescens strain K904 induced membrane bleb formation in airway epithelial cell line A549 ( S2A Fig ) . S . marcescens causes contact lens associated keratitis , so we tested whether this effect could be seen on corneal tissue exposed to S . marcescens inoculated contact lenses . Strain K904 was introduced onto contact lenses and exposed to pig corneas ex vivo for 3 h . SEM analysis revealed extensive surface changes and membrane bleb formation on the porcine ocular surface on the S . marcescens exposed corneas , but not on control corneas bearing contact lenses without bacteria ( Fig 1F ) . The S . marcescens strain K904 genome was sequenced ( Genbank PRJNA243053 ) with no evidence for a type III secretion system ( T3SS ) . Because a T3SS-independent mechanism was therefore implicated , transposon mutagenesis was performed to elucidate the bacterial factors required for this phenotype . 6 , 920 mutants were screened for the inability to induce bleb formation in HCLE cells and kill the cells as judged by Calcein AM staining . Five mutants were reproducibly defective in bleb induction , which we confirmed with primary corneal epithelial cells . For K904 91 . 2±4 . 9% ( n = 334 ) of cells had blebs , compared to 0% for the mutants ( n≥160 ) ( Fig 2A ) . The mutations were mapped to two loci . Three were in the shlBA operon , with two in shlB at base pair 378 and 825 out of the 1680 base pair gene , and one in shlA at base pair 4063 out of the 4824 base pair gene ( Fig 2B ) . Two other mutations mapped to different locations in the gumB gene at base pairs 170 and 957 out of the 2136 base pair gene ( Fig 2B ) . The shlBA operon codes for a type Vb secretion system with ShlB being an outer membrane transporter and ShlA its cognate surface-associated and secreted cytolysin [24] . The gumB gene is a recently described member of the IgaA family involved in bacterial stress response that confers pleiotropic phenotypes when mutated [25] . IgaA is an inner membrane protein that influences Salmonella virulence in rodent infection models [26] and controls the Rcs stress response transcriptional system . Fifteen of the 34 bleb-inducing S . marcescens clinical isolates were selected arbitrarily among isolates that had caused different types of ocular infections . These were subject to PCR analysis for the shlA gene . Strain PIC3611 was used as a positive control and an shlBA deletion variant of PIC3611 was used as a negative control . DNA samples from all tested strains , except the deletion mutant , produced an amplicon consistent with the shlA gene ( S3 Fig ) . This result is consistent with shlA being a conserved gene in S . marcescens , and likely responsible for bleb induction by the tested strains . To further test the necessity of this this operon in bleb induction by S . marcescens , a deletion allele of the shlB gene was constructed in S . marcescens strain K904 . The ΔshlB mutant strain was completely defective in the ability to induce blebs and kill HCLE cells in our test conditions ( Fig 3A ) . Addition of the shlBA operon expressed from the nptII promoter on a plasmid ( pshlBA ) complemented the ΔshlB mutant phenotype supporting that the defect was due to mutation of shlB and not an unknown mutation elsewhere on the chromosome or a polar effect on adjacent genes ( Fig 3A ) . The pMQ591 plasmid ( pshlBA::tn ) , which has the shlBA operon with a transposon insertion in shlA at base pair 4063 , was able to restore bleb formation to the S . marcescens ΔshlB strain , providing genetic evidence that the ΔshlB mutation in strain CMS4236 was nonpolar , since the active ShlA protein must come from the chromosomal copy of shlA ( Fig 3A ) . A resazurin fluorescence-based assay was used as a second method to validate the cytotoxic phenotypes demonstrated in this study using calcein AM staining ( S4A and S4B Fig ) . We observed consistent results , including the lack of cytotoxicity caused by the ΔshlB mutant and the restoration of cytotoxicity using complementing plasmids ( MOI 10 and 200 ) ( S4A and S4B Fig ) . Thus , even though shlA may be expressed in the ΔshlB mutant , the ShlA protein is not secreted without the ShlB transporter , as was previously shown in other strains [24] . Importantly , shlBA expression was sufficient to confer bleb-induction ability to the E . coli laboratory strain S17-1 λ-pir that is normally unable to generate blebs ( Fig 3B and S2 Fig ) . This result suggested that ShlA may be sufficient to induce bleb formation . Further evidence supporting that ShlA is sufficient for bleb induction came from observations that partially purified ShlA expressed from E . coli could induce bleb formation; 31±3% of HCLE cells exposed to filtered supernatants ( n = 75 ) and 33±15% ( n = 208 ) of cells challenged with purified ShlA exhibited blebs ( Fig 3B ) . This is in sharp contrast to the absence of blebs in cells challenged with preparations made from E . coli harboring the control vector without shlBA ( n≥80 cells , Fig 3B ) . E . coli expressing pshlBA::tn with the transposon mutation in shlA , noted above to contain a null shlA allele , was unable to induce blebs or kill HCLE cells ( S2B Fig ) , which supports the conclusion that ShlA rather than ShlB is required for bleb induction . Combined , these data support a working model that the T5SS ShlB and cytolysin ShlA are the S . marcescens virulence factors responsible for induction of membrane blebs in mammalian cells and suggest that GumB is a regulator of shlBA expression . Since P . mirabilis is able to induce bleb formation in HCLE cells and its genome contains an shlBA-like virulence operon hpmBA [27] , we tested whether this operon could induce bleb formation . HpmA is 44% identical to ShlA at the amino acid level and HpmB/A constitute a Type Vb secretion pair analogous to ShlBA . Induced expression of the hpmBA operon from a plasmid was able to confer the bleb-formation phenotype to E . coli ( 82±9% blebs , n = 156 , Fig 4A ) . The hpmBA plasmid could complement the ΔshlB mutation in S . marcescens; there were fewer blebs than wild type treated cells ( 20±17% , n = 287 ) , but the cells appeared to be dead ( Fig 4A ) . To further verify the importance of HpmA in bleb formation , the chromosomal hpmA gene of P . mirabilis was mutated in two clinical keratitis isolates K2644 and K2675 , with 56±12% ( n = 122 ) and 39±7% ( n = 219 ) bleb formation , respectively , ( Fig 4A ) . Unlike the wild-type parental strains , isogenic hpmA mutant strains were defective in bleb formation and toxicity , and these phenotypes could be complemented by expression of the hpmA gene from a plasmid . Zero percent bleb formation was observed from corneal cells treated with the hpmA mutants with the vector alone ( n≥140 ) . For cells exposed to the hpmA mutants with the hmpA plasmid , ~40% had blebs ( 39±12% , n = 208 for strain K2644 and 40±10% , n = 187 for strain K2675 , Fig 4A and 4B ) . Together , these data indicate that T5SS secreted cytolysins of the ShlBA family represent a conserved mechanism by which bacteria elicit rapid cell death and dramatic morphological changes in human cells . Similar to the gumB transposon mutant ( Fig 2A ) , strain K904 with a deletion of the gumB gene was unable to induce blebs or kill primary corneal or HCLE cells ( 0% cells had blebs , n = 159 cells ) ( Fig 5A ) . The same trend was observed when the gumB gene was deleted from the S . marcescens reference and insect pathogen strain Db11 [28] ( S1A Fig ) . Plasmid-based expression ( lac promoter ) of gumB ( 85±12% , n = 280 ) or IgaA-family genes from Escherichia coli ( yrfF , 95±1% , n = 175 ) , Salmonella Typhimurium ( igaA , 95±5 , n = 175 ) , and Klebsiella pneumoniae ( kumO , n = 96±1 , n = 227 ) was able to restore bleb-induction ability to the ΔgumB mutant , which supports the notion that the function of IgaA-family proteins is highly conserved ( Fig 5B ) . The umoB gene from P . mirabilis was unable to complement the ΔgumB mutant , suggesting that it differs enough structurally from GumB as to not replace protein-protein interactions necessary for GumB function in S . marcescens ( Fig 5B and , 0% , n = 123 ) . Additionally , expression of gumB in E . coli did not enable E . coli to induce blebs ( Fig 5A ) ( 0% , n = 82 for vector and 225 for pgumB ) , suggesting that GumB is necessary , but insufficient for the bleb-induction phenomenon . We tested whether shlA expression was reduced in the gumB mutant using qRT-PCR , and observed a 100-fold reduction in transcript ( Fig 5C ) . This finding suggests that gumB mutant strains likely are defective in the ability to induce blebs because they do not produce adequate ShlA cytolysin . To test this model , the constitutive shlBA expression plasmid was introduced into the gumB mutant . The resulting strain induced blebs and was highly cytotoxic ( Fig 5A and S4 Fig ) , which indicates that artificial upregulation of shlBA bypasses the GumB-mediated regulation required for this virulence function . Reports indicate that IgaA-family proteins inhibit the Rcs phosphorelay system in other genera from the Enterobacteriaceae family [29 , 30] . The Rcs system is a multicomponent version of a two-component transcription factor system involved in responses to extracellular and envelope stress [31 , 32] ( Fig 6A ) . The core Rcs system is composed of sensor histidine kinase RcsC , an intermediate phosphoprotein RcsD , and the RcsB response regulator [32] . Therefore , one would predict that if the Rcs system is derepressed in an IgaA-family protein mutant strain ( ΔgumB ) , then elevated expression of Rcs system components in the wild-type strain could mimic the gumB mutant phenotypes ( Fig 6A ) . To test this prediction , the rcsC gene was placed under control of the E . coli lac promoter on a medium-copy plasmid in the wild-type strain , K904 . We observed gumB mutant strain-like phenotypes for the wild type with the rcsC multi-copy plasmid , such as reduction of pigmentation and mucoid colony morphology , which supports that multicopy expression of rcsC was activating the Rcs system akin to mutation of gumB that also prevents pigmentation ( S5 Fig ) . HCLE cells exposed to strain K904 with the rcsC expression plasmid , but not the vector control , were defective in inducing bleb formation and cytotoxicity ( Fig 6B ) . 93±6% bleb formation was observed in cells exposed to the K904 wild-type with vector control ( n = 208 ) , whereas those challenged with K904 with prcsC produced no blebs ( 0% , n = 454 ) . The proposed model ( Fig 6A ) also suggests that inactivation of the Rcs system in a gumB mutant strain should restore toxicity , bleb induction ability , and pigment production . The gene for the RcsB response regulator was mutated in the ΔgumB strain background . In order to interrogate the model and validate the strains , Rcs regulation of pigmentation was analyzed . The rcsB mutation reversed the gumB mutant pigment defect ( S5 Fig ) , which supports that RcsB acts downstream of GumB ( S6 Fig ) . We also observed that the gumB mutant strain pigment defect could be restored through complementation with wild-type rcsB expression from a plasmid ( S5 Fig ) , which further supports the validity of the mutation and plasmid . With regards to host-pathogen interactions , the ΔgumB rcsB double mutant strain was indistinguishable from the S . marcescens K904 parental strain for bleb induction and cytotoxicity to HCLE cells ( Fig 6B ) . Importantly , the ΔgumB rcsB double mutant strain toxicity and bleb inducing phenotypes could be complemented with rcsB on a plasmid ( Fig 6B ) . Zero blebbing cells were counted with the gumB mutant with the vector control ( n = 141 ) ; 94±6% of cells had blebs in the gumB rcsB with vector group ( n = 252 ) , and 0% of cells had blebs when exposed to the gumB rcsB mutant complemented with prcsB ( n = 338 ) . Together , these data indicate that bleb formation regulation by GumB requires a functional Rcs system , and that activation of the Rcs system prevents S . marcescens from inducing bleb formation and cytotoxicity to epithelial cells . Next , we investigated the mechanism of cellular death induced by ShlA-like cytolysins in corneal epithelium . Previous studies have shown that osmoprotectants can prevent bacterial T3SS-mediated bleb formation and necroptosis [33 , 34] . The osmoprotectant sorbitol ( 300 mM ) was able to reduce bleb formation from 89% ( n = 225 ) for HCLE cells exposed to S . marcescens ( strain K904 ) to 10% ( n = 409 ) for those exposed to S . marcescens and sorbitol ( p<0 . 001 ) . Dextran , a branched polysaccharide , is able to prevent cellular lysis induced by purified streptolysin O and other pore forming toxins , including ShlA , by occluding pores introduced by such toxins [35–38] . Here , dextran was found to reduce cells with blebs from 94 . 5% ( n = 383 ) with S . marcescens challenge MOI = 50 or 200 to 0 or 4 . 4% ( n = 397/544 ) with S . marcescens and dextran , a significant reduction ( p<0 . 0001 , Fisher’s Exact ) ( Fig 7A ) . These data suggest that the membrane pore introduced by ShlA’s pore forming domain is responsible for the bleb and cytotoxicity phenotypes . It has been demonstrated that intracellular S . marcescens can initiate the type of programmed cell death known as necroptosis in macrophages in a ShlA-dependent manner [39] . Oxidative stress plays a major role in necroptosis , so we tested whether the antioxidant coenzyme-Q10 ( 0 . 1 μM ) , had an impact on S . marcescens induced damage . CoQ10 prevented S . marcescens-induced cytotoxicity and bleb formation ( 0% blebs , n = 146 ) ( Fig 7B ) , whereas DMSO alone did not alter the ability of S . marcescens to induce blebs ( 89±6% , n = 121 ) ( Fig 7A ) . We tested whether blocking of necroptosis using the RIP-1 inhibitor necrostatin 5 could alleviate S . marcescens-induced phenotypes; a strong reduction in bleb formation ( 2±3% , n = 316 ) and cytotoxicity was observed ( Fig 7 ) . Necrostatin 5 itself did not produce a bleb or cytotoxicity phenotype ( 0% blebs , n = 97 ) , nor did the vehicle ( DMSO ) , 0% blebs , n = 115 ) . An inhibitor that targets the major regulator of necroptosis , the mixed lineage kinase domain-like protein ( MLKL ) , was tested [39 , 40] . The MLKL inhibitor GW806742X produced a dose-dependent reduction in bleb formation by HCLE cells challenged with wild-type S . marcescens ( S7 Fig ) . Together , these data suggest that S . marcescens-induced necroptosis in response to ShlA-mediated pore formation is responsible for bleb formation and cellular death . Whereas the ShlA cytolysin is a known S . marcescens virulence determinant in several pathogenesis models [41–43] , the role of GumB is unreported . A Galleria mellonella model of infection was used to test whether GumB is necessary for infection in vivo . When survival was analyzed over time ( Fig 8A ) , larvae that had been injected with S . marcescens strain K904 ( 200 CFU/larva ) started to die just after 20 h post injection . The larvae had a median survival of 23 h , and all larvae were dead by 44 h ( Fig 8A ) . Strikingly , the ΔgumB mutant strain-injected larvae ( 200 CFU/larva ) were fully viable at 44 h when the experiment reached its endpoint ( Fig 8A , p<0 . 001 Log-rank Test ) . In a separate experiment , different doses of S . marcescens ( strain K904 ) and the ΔgumB mutant strain were injected into G . mellonella larvae . A similar survival curve was observed between the two strains with 160 , 000 CFU of the ΔgumB strain ( n = 14 ) and 10 CFU of the wild-type K904 strain ( Fig 8B ) , which sharply delineates the >10 , 000-fold difference in the ability of the isogenic strains to kill a host organism . The ΔgumB strain with shlBA constitutively expressed on a plasmid was used to test whether reduced shlBA expression contributes to the lack of virulence exhibited by the ΔgumB mutant strain in the G . mellonella pathogenesis model . Plasmid-based expression of shlBA increased virulence of the ΔgumB mutant strain compared to the ΔgumB mutant strain carrying the vector negative control; however , it did not confer wild-type levels of virulence ( Fig 8C ) . The isogenic ΔshlB mutant was also defective in virulence compared to the wild type strain and was fully complemented with shlBA expressed from a plasmid . Together these results demonstrated that the gumB mutant is attenuated in virulence relative to the wild type , and suggest that the virulence defect is at least partially due to a loss of ShlA production . The mechanism for the loss of viability in the G . mellonella model was further analyzed . Bacteria were isolated from larvae before larval death ( 24 h post-injection ) , and the CFU were enumerated . There was a ~50-fold reduction in the median CFU of S . marcescens ΔgumB strain CFU isolated from the larvae compared to the K904 wild-type strain ( p = 0 . 029 , Mann Whitney test ) ( Fig 9A ) . To test whether the ΔgumB mutant strain was less capable of growth on the nutrients available in the larvae , we assessed bacterial growth in inactivated larval homogenates ( Fig 9B ) . The lysates were heat treated to prevent melanization and growth of endogenous bacteria and clarified by centrifugation . The growth rate as assessed by optical density measurement of the ΔgumB mutant and wild type strains were similar in clarified lysates ( Fig 9B ) , and the CFU achieved at 24 h were indistinguishable ( p = 0 . 565 , Mann Whitney test ) , ( Fig 9C ) . We also tested whether the ΔgumB mutant had reduced growth at limiting oxygen concentrations , which could explain its reduced ability to proliferate within the hemolymph of the larvae . The ΔgumB mutant and K904 wild-type strain exhibited qualitatively equivalent colony size on LB agar plates following growth in an anaerobic bag ( S5 Fig ) . Likewise , the ΔgumB mutant strain was similarly tolerant to hydrogen peroxide . Disk diffusion tests indicated that the gumB mutant was no more susceptible than the wild type strain ( 16 . 7±0 . 7 mm diameter of growth inhibition for the wild type strain and 17 . 4±1 . 7 for the ΔgumB strain , p = 0 . 203 Student’s T-test ) . This suggests that the ΔgumB mutant is more susceptible to immune components such as phagocytizing cells in the larval hemolymph rather than being unable to grow under nutrient- or oxygen-limiting conditions or exposure to reactive oxygen species in the larvae . To test whether there is a defect in the ability of the ΔgumB mutant strain to survive interaction with phagocytic immune cells , we tested the ability of the bacteria proliferate in a macrophage-like murine cell line , RAW264 . 7 cells . The ΔgumB mutant strain was taken up at a reduced rate ( ~6-fold lower , p<0 . 05 Student’s t-test ) compared to the wild-type K904 strain when CFU within RAW cells was assessed after 2 h of co-culture ( Fig 9D ) . Proliferation within the RAW cells measured at 24 h post-inoculation was also measured . Whereas the wild-type CFU increased almost 7-fold within the RAW cells , there was a ~50% reduction in ΔgumB strain CFU ( Fig 9D ) . Wild-type gumB expression from a plasmid was able to complement these defects in uptake and intracellular proliferation/survival of the gumB mutant , but had no effect on the wild-type K904 strain , as expected ( Fig 9D ) . We evaluated whether the gumB mutant defect in proliferation within RAW cells was due to reduced shlBA gene expression by expressing shlBA with the nptII promoter from a plasmid in the gumB mutant . We observed a significant , although partial , restoration in bacterial proliferation in RAW cells when shlBA was expressed in the gumB mutant ( S8 Fig ) . Together , these data indicate the GumB is required for virulence and indicate that gumB is required for resistance to phagocytic cell responses of the innate immune system .
We report a T5SS-dependent , T3SS-independent mechanism by which Gram-negative bacteria can induce massive morphological changes and cellular death in human cells . The purpose of this study was to characterize and gain mechanistic insight into how Enterobacteriaceae damage the corneal epithelium , a barrier that they must overcome to gain access to the corneal stroma , a niche where they can rapidly replicate . We observed that these bacteria induce formation of blebs in human corneal epithelial cells . S . marcescens-induced blebbing was evident in several types of mammalian epithelial cells and by >30 S . marcescens isolates ( 100% of isolates tested ) , which indicates that the effect is broadly conserved and not limited to only a few bacterial isolates or mammalian cell types . The induction of blebs on intact corneas following exposure to bacteria-coated contact lenses implies that contact lens delivery of bacteria or ShlA-like cytolysins may cause damage to the ocular epithelium , possibly whether the bacteria are alive or not . Consistently , approximately 10% of contact lens wearers have an adverse contact lens wear event every year , such as red eye and irritation , and bacteria such as S . marcescens are common contaminants of contact lens cases and lenses [44–46] . Even more important is that contact lenses are a major risk factor for the vision threatening infection , microbial keratitis , with a third to a half of keratitis patients being contact lens users [18 , 47] . Notably , the epithelial cell blebs reported here were similar in morphology to those P . aeruginosa-induced blebs described by Fleiszig and colleagues [6 , 7 , 33] . One difference between these studies and ours is that P . aeruginosa bacteria actively proliferate within the blebs [6 , 7 , 48] , whereas S . marcescens strain K904 was not observed within the epithelial cells . Additionally , the frequency of bleb formation was higher for S . marcescens-exposed cells , with 15–20% of corneal cells exhibiting blebs after treatment with P . aeruginosa at MOI = 100 , compared to up to 70% for S . marcescens-exposed cells at MOI = 200 , and 26% at MOI = 50 . A further difference between P . aeruginosa and S . marcescens is that bleb induction by P . aeruginosa requires a T3SS , a nanomachine largely absent in S . marcescens isolates . This study , rather , demonstrates that S . marcescens requires a T5SS to induce epithelial blebs and cytotoxicity . A subset of T3SS-lacking P . aeruginosa isolates have been described that express the T5SS secreted ExlA toxin [49 , 50] , and we speculate that these ExlA positive isolates may also induce blebbing and cellular death in a similar manner to P . mirabilis and S . marcescens . Genetic analysis implicated both the T5SS composed of ShlA and ShlB and the Rcs system regulator GumB in bleb induction , control of toxicity , and facilitation of virulence . Importantly , expression of shlBA in non-pathogenic E . coli strains conferred the ability to induce blebs and kill corneal cells in vitro . This result suggests that this single virulence determinant was sufficient for the observed host-pathogen interactions , a result that was corroborated using partially purified ShlA . Furthermore , the ability of HpmA from P . mirabilis to induce blebs and kill corneal cells supports the model that this widely conserved family of cytolysins are sufficient to cause bleb formation and cell death . Indeed , the other bacteria tested in this study able to cause blebs were from species known to harbor ShlBA-like cytolysins such as E . tarda [51] , although we did not prove that the strain we used has this gene . The P . aeruginosa isolate that induced blebbing has not been molecularly characterized , so it is not clear whether it induces blebbing through a T3SS or T5SS mechanism . Notably , ShlA-like proteins are found in a variety of organisms beyond those discussed above , including Chromobacterium violaceum , Haemophilus ducreyi , Photorhabdus luminescens , and Yersinia species [24 , 52] . Interestingly , bacteria known to make other types of cytolysins / hemolysins such as S . aureus and S . pneumoniae did not induce bleb formation under our tested conditions , even using strains known to express the respective hemolysins , e . g . S . aureus 8325–4 [53] . Bleb formation by Streptococcus species may be expected since purified streptolysin O has been a key tool in understanding the biology underlying bleb formation [11 , 54] . Our observations therefore suggest that many hemolytic bacteria do not generate sufficient pore forming toxins under the tested conditions to induce bleb formation in corneal cells or that the tested cells lack receptors required by the respective toxins . Furthermore , non-pore forming toxins can induce blebs . These include T5SS secreted serine proteases from E . coli , ExpC and Pet , which cause damage and induce bleb formation when added exogenously to epithelial cells [55–57] . This study implicates GumB as a S . marcescens virulence factor and mediator of host-pathogen interactions . GumB was found to be necessary for bleb induction and cytotoxicity by S . marcescens to corneal cells and virulence in G . mellonella . The bleb formation and cytotoxicity phenotypes were complemented by the wild-type gumB gene and several other IgaA-family genes on plasmids . This result implies that GumB is functionally conserved with other IgaA-family proteins , with the possible exception of UmoB from P . mirabilis . Several independent clones of umoB from different P . mirabilis genomes and different plasmid replicons were tested , suggesting that the lack of complementation was not due to a faulty complementation plasmid . The umoB gene codes for a protein that is more distantly related to GumB than the other tested proteins: 42% identity to GumB compared to ≥54% identity for the other tested proteins [25] . These structural differences may account for its inability to complement the ΔgumB mutation . Since expression of gumB in E . coli was insufficient to induce blebbing in mammalian cells , and it is unlikely that an IgaA-family protein could itself cause damage to mammalian cells , we tested the hypothesis that GumB is required for bleb formation and cytotoxicity through activation of shlBA expression . In support of this model , shlA expression was highly reduced in the ΔgumB mutant strain and ectopic expression of shlBA restored the ability of the ΔgumB mutant to induce blebs and kill cells . These data support the model that GumB is defective in bleb induction because it fails to produce sufficient levels of the ShlA cytolysin . Because IgaA-family proteins , similar to GumB , regulate the envelope stress response Rcs system [29 , 30] , we tested whether GumB functions through control of the Rcs system . Multicopy expression of rcsC in the wild type strain phenocopied gumB mutant strain phenotypes , conferring the loss of cytotoxicity and bleb induction . Additionally , mutation of rcsB in the gumB mutant strain restored bleb formation and cytotoxicity phenotypes . These were the expected outcomes if GumB functions to repress Rcs system function and RcsB inhibits shlBA transcription . Together these experiments support the model that GumB regulates shlBA expression indirectly through the Rcs system ( Figs 6 and S6 ) . Consistent with this model , the Vescovi group showed that shlBA transcription is directly inhibited by RcsB in S . marcescens strain RM66262 , and it was proposed that phosphorylated RcsB binds to the promoters of and directly represses both shlBA and flhDC transcription [58] . Since FlhDC is a positive and direct regulator of shlBA expression , and activated RcsB shuts down flhDC expression , it is clear that RcsB can shut down shlBA transcription both directly and indirectly [58] . It was reported that GumB is necessary for flhDC expression [25] and in this study , for shlBA . This is in agreement with a study by DeVenanzio [58] regarding RcsB control of shlBA , and further supports a role for GumB in Rcs system control . With respect to virulence , the ΔgumB mutant strain was highly attenuated , as injection of >10 , 000-fold more ΔgumB than wild-type K904 CFU into the larvae was required to produce similar survival profiles . The ΔgumB strain larvae killing defect was partially restored by multicopy expression of shlBA from a plasmid . Data here demonstrated that shlBA is essential for virulence in a G . mellonella model of infection , extending the host-range in which ShlA is a virulence factor . However , the ΔshlB mutant defect was not as severe as the ΔgumB defect , with 100-fold more CFU of the ΔgumB strain than ΔshlB strain required for complete killing of the larvae ( Fig 8C ) . Together , these data suggested that the lack of shlBA expression by the gumB mutant is partially , but not completely responsible for reduced virulence . In addition to ShlA , other factors regulated by GumB likely contribute to virulence . These could include as metalloproteases [59 , 60] , FlhDC controlled phospholipase A [61] , flagella [62] , the hemolytic surfactant serratamolide [63] , the biologically active pigment prodigiosin [64] , and Rcs system regulated outer membrane vesicle [65] and capsular polysaccharide production [66] . Regardless , GumB-mediated regulation of shlBA accounts for a large portion of S . marcescens virulence activity . Experiments demonstrated that GumB is necessary for replication within G . mellonella , but the ΔgumB mutant strain is perfectly able to use G . mellonella as a growth substrate . Experiments with the RAW macrophage-like cell line indicated that GumB is required for survival and proliferation after being phagocytized . This result suggests that GumB-regulated factors are required for the bacteria to survive within cells . In support of this notion , there is a growing body of evidence indicating a key role for ShlA in S . marcescens survival within and egress from intracellular vacuoles and regulation of autophagic processes [58 , 67–69] . This is somewhat antagonistic to data from E . coli and S . enterica , where partial function alleles of igaA and yrfF increased survival of phagocytized bacteria [70–72] . The different requirements for GumB may be due to fundamental differences in the role of IgaA-family proteins between species . Alternatively , because the yrfF and igaA genes are essential for growth , different results may have resulted from the partial function of the igaA and yrfF alleles used in the previous studies [70–72] . Cellular blebs are generally a sign of impending cellular death , and in this case Enterobacteriaceae that cause contact lens associated keratitis may use this mechanism to damage the corneal epithelium , a key barrier to ocular infections [73] . We speculate that contact lens wear can facilitate contact between bacteria with ShlA-like T5SS and the ocular surface , and that even if the bacteria are killed by cleaning solutions , their surface associated and extracellularly secreted pore-forming toxins of the ShlA family could damage the epithelium . Beyond the eye , S . marcescens causes many types of nosocomial infections [15] , and has been implicated in the dysbiosis associated with inflammatory diseases of the human gut [74] . In line with this observation , a recent study has shown that ShlA can cause severe damage to the digestive tract in a Drosophila melanogaster model [42] . ShlA also damages lung tissue and is required for hemorrhagic pneumonia , lung dysfunction , and necroptosis of epithelial cells in animal lung infection models [41 , 75] . An additional observation of note was that genetic data noted here suggest that the Rcs system is a regulator of the biologically active red prodigiosin pigment , characteristic to many biotypes of S . marcescens . This conclusion was based upon multicopy expression of rcsC conferring a loss of pigmentation , and mutation of rcsB suppressing the gumB mutant strain pigment defect . Further studies will be required to fully analyze the role of the Rcs system in pigment regulation; however , our current data suggests a model wherein the Rcs system inhibits pigmentation under stressful conditions . This is consistent with a previous study indicating that the alarmone cAMP is used to inhibit prodigiosin biosynthesis under metabolic stress [76] . In conclusion , this study identifies a novel mechanism by which bacteria cause dramatic and lethal morphological changes in host epithelial cells to potentiate pathogenesis on mucosal surfaces , as well as the regulatory pathways underlying this important virulence activity . This ShlB and ShlA-dependent mechanism is highly toxic and employed by a broad range of Gram-negative bacterial pathogens . In the context of bacterial keratitis , this T5SS may enable bacteria to rapidly kill surface epithelial cells , allowing them to penetrate into the corneal stroma , a tissue more permissive to bacterial growth . These findings therefore implicate novel strategies for therapeutic development to prevent this conserved system from causing tissue damage and augmenting disease .
De-identified corneas from organ donors were obtained from the Center for Organ Recovery and Education ( Pittsburgh , PA ) or the National Disease Research Interchange ( Philadelphia , PA ) . Research using de-identified tissue from non-living individuals is not considered human subject research under DHHS regulation 45CFR46 , and the use of decedent tissue for this project was approved by the University of Pittsburgh Committee for Oversight of Research and Clinical Training Involving Decedents . S . marcescens and P . mirabilis strains are listed in Table 1 . Bacteria were grown with on a TC-7 tissue culture roller ( New Brunswick ) in Lysogeny Broth ( LB ) medium [77] ( 0 . 5% yeast extract , 1% tryptone , 0 . 5% NaCl ) with or without 1 . 5% agar or in M9 minimal medium [78] supplemented with glucose ( 0 . 4% ) and casein amino acids ( 0 . 06% ) . Escherichia coli strains used were S17-1 λ-pir [79] , WM3064 [80] , Top10 ( Invitrogen ) , and EC100D pir-116 ( Epicentre ) . Saccharomyces cerevisiae strain InvSc1 ( Invitrogen ) was grown with either YPD or SC-uracil media [81] . Antibiotics used in this study include gentamicin ( 10 μg ml-1 ) , kanamycin ( 100 μg ml-1 ) , and tetracycline ( 10 μg ml-1 ) . For growth under oxygen limiting conditions , bacteria were grown on LB plates in a GAS PAK-EZ anaerobe pouch system with indicator ( Becton , Dickinson and Company ) , and incubated at 30°C for 20 h . HCLE cells ( originally from the Gipson laboratory , Harvard University ) [82] were grown in monolayers as previously described [83] in 12 well MatTek glass bottomed dishes ( product number P12G-1 . 5 . 14-F ) that were treated with poly-L-lysine or in tissue culture treated polystyrene 12 well dishes ( Costar catalog no . 3513 ) . Cells were grown to confluence in keratinocyte serum-free medium ( KSFM ) ( Gibco cataolog number 10724–011 ) supplemented with bovine pituitary extract ( 25 μg/ml ) and epidermal growth factor ( 0 . 2 ng/ml ) . Bacteria were grown overnight with aeration at 30°C , washed with phosphate buffered saline ( PBS ) , adjusted to the proper MOI in KSFM in a total volume of 1 . 5 ml and applied to the MatTek plate . After 2 h of incubation at 37°C with 5% CO2 , bacteria were removed by washing cells three times with 37°C PBS , and cells covered in KSFM with or without Calcein AM ( 0 . 5 μM , ThermoFisher ) for 15 minutes or CellMask plasma membrane stain ( 100 μM , ThermoFisher ) , then washed with KSFM and imaged . Cytotoxicity assays were performed as previously described using the Presto Blue viability assay ( ThermoFisher ) using bacteria at the described MOI [59] . Primary epithelial cells were obtained using reagents from Gibco and Sigma Aldrich and following the protocol of Chen and colleagues [84] with some modifications . Corneal tissue obtained as noted above from the Center for Organ Recovery and Education ( Pittsburgh , PA ) was washed three times with Hank’s balanced salt solution supplemented with gentamycin 50μg/ml and amphotericin B 1 . 25μg/ml . Corneal cells were removed and digested for ~16 h at 4°C using 10 mg/ml dispase II in MESCM ( a 1:1 ratio of Dulbecco’s modified Eagle medium and Ham’s F12 medium supplemented with insulin transferrin selenium solution , basic fibroblast growth factor 4 ng/ml , human leukemia inhibitory factor 10 ng/ml , gentamicin 50μg/ml and amphotericin B 1 . 25μg/ml ) . Epithelial sheets were removed and incubated with TrypLE protease mixture , neutralized with minimum essential medium supplemented with 20% FBS , and cells were plated into a 12 well plate ( ~8x105 cells/well ) . RAW 264 . 7 cells were grown and used as previously described [85] using kanamycin protection assays [86] to analyze bacterial proliferation . Porcine corneas were purchased from Sierra Medical ( Whittier , CA ) and processed as previously described [87] . Corneas and adjacent scleral tissues ( ~ 3 mm ) were excised from eyes ( n = 2 per treatment group ) , rinsed in PBS and placed on supports composed of minimal essential medium ( MEM , Gibco ) , rat tail collagen ( 1 mg/ml , Sigma ) , and agarose ( 1% w/v ) in 12 well dishes . MEM was added to cover the tissue up to the limbus . Contact lenses ( Air Optix Night and Day Aqua ) were incubated in PBS or PBS with S . marcescens strain K904 ( OD600 = 1 . 0; ~2x109 CFU/ml ) for 30 minutes and rinsed 2x in PBS to remove unattached bacteria , leaving ~ 1x108 CFU per lens . The control and bacteria-laden lenses were applied to the corneas and together were incubated at 37°C with 5% CO2 for 2 . 5 h . Lenses were removed and the corneas fixed with glutaraldehyde ( 2 . 5% ) for 20 h . Corneas were washed with PBS and post-fixed using aqueous osmium tetroxide ( 1% ) . The samples were dehydrated using increasing concentrations of ethanol ( 30%-100% ) , immersed in hexamethyldisilazane , air dried , and sputter coated with 6 nm of gold/palladium . Corneas were imaged using a JEOL JSM-6335F scanning electron microscope at 3 kV with the secondary electron imaging detector . Quantitative reverse transcriptase PCR ( qRT-PCR ) was used to assess gene expression as previously described [91] . To prepare bacteria for RNA extraction , single colonies were inoculated into 5 ml of LB broth , and the test tubes were incubated 30°C with aeration in 5 ml . After ~16 h , cultures were diluted to OD600 = 0 . 1 in fresh LB medium , grown to OD600 = 0 . 5 , subcultured to OD600 = 0 . 1 and then grown to OD600 = 3 . RNA and cDNA was prepared and validated to not have chromosomal DNA contamination as previously described [91] . Primers were 2638 and 2639 for the 16S rDNA gene and 4150 and 4151 for shlA sequences . Escherichia coli strain EC100D with pMQ492 ( shlB and shlA ) and with pMQ175 ( empty vector ) were grown overnight at 30°C with aeration for 16 h in LB medium supplemented with gentamicin ( 10μg/ml ) and L-arabinose to a final concentration of 0 . 2% ( v/v ) . Bacteria were removed by centrifugation and filtration ( 0 . 22 μm ) , and supernatants were subject to size fractionation using a 100 kD filter unit ( Centricon , Millipore ) . Protein fractions in PBS ( 200 μl ) were added to HCLE cells ( 500 μl total volume , 10 . 3 μM ShlA in the pMQ492 fraction ) and incubated for 3 h followed by calcein AM staining and microscopic analysis . To obtain micrographs , cells on glass bottomed multiwell plates ( MatTek ) were imaged with a 40X objective using an Olympus IX-81 inverted microscope with an FV-1000 laser scanning confocal system ( Olympus ) and FluoView FV10-ASW 3 . 1 imaging software . For live imaging , samples in MatTek dishes were viewed with a Nikon Eclipse Ti microscope equipped with a Photometrics Cascade 1K camera and a 40X 0 . 30 NA objective . Metamorph software was used to obtain digital images . FIJI software was used to for image analysis [99] . Galleria mellonella infection assays . G . mellonella were infected as previously described [100] , with the exception that S . marcescens was suspended in PBS with 10 μg/ml tetracycline . To enumerate S . marcescens , homogenates from individual larvae were generated using a tissue grinder ( Corning Pyrex 7725 ) in PBS with tetracycline . Lysates were serial diluted and plated on LB agar supplemented with ampicillin ( 150 μg/ml ) , chloramphenicol ( 30 μg/ml ) , and tetracycline ( 10 μg/ml ) to prevent unwanted microbial growth . To determine bacterial growth in larval homogenates , larvae were homogenized at a ratio of 2 larvae in 1 ml of PBS . When 15 ml of homogenate was obtained , it was centrifuged at 11 , 000 x g for 10 minutes to clarify the supernatant . The supernatant was heated at 95°C for 60 minutes to kill microbes and prevent melanization , which obscures optical density readings . S . marcescens cultures ( 1 ml ) grown overnight in LB were spun down ( 13 , 000 x g for 2 minutes ) and washed with PBS and then adjusted to OD600 = 0 . 05 in the larval homogenate , 150 μl was added to the wells of 96 well plates and were incubated overnight at 30°C . After 20 h , CFU were determined following serial dilution as noted above . | Bacteria must overcome host defenses to cause infection . This is especially true for corneal infections where bacteria must penetrate the epithelium in order to gain access to the stroma where bacteria can rapidly multiply , induce inflammation , and cause vision loss . Members of the Enterobacteriaceae commonly cause contact lens associated infections , but the mechanisms by which they damage corneal cells are largely unknown . Here we present evidence that Serratia marcescens and Proteus mirabilis are able to induce dramatic morphological changes in mammalian corneal cells that correlates with rapid cellular death . Secretion of ShlA-like cytolysins via type V secretion was responsible for this phenotype , and this effect was regulated by the conserved Rcs phosphorelay stress response system , including IgaA-family protein GumB . This study provides a model for stress-mediated regulation of cytolysins that induce epithelial damage and promote ocular infection . | [
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] | 2019 | Blowing epithelial cell bubbles with GumB: ShlA-family pore-forming toxins induce blebbing and rapid cellular death in corneal epithelial cells |
We compare the sets of experimentally validated long intergenic non-coding ( linc ) RNAs from human and mouse and apply a maximum likelihood approach to estimate the total number of lincRNA genes as well as the size of the conserved part of the lincRNome . Under the assumption that the sets of experimentally validated lincRNAs are random samples of the lincRNomes of the corresponding species , we estimate the total lincRNome size at approximately 40 , 000 to 50 , 000 species , at least twice the number of protein-coding genes . We further estimate that the fraction of the human and mouse euchromatic genomes encoding lincRNAs is more than twofold greater than the fraction of protein-coding sequences . Although the sequences of most lincRNAs are much less strongly conserved than protein sequences , the extent of orthology between the lincRNomes is unexpectedly high , with 60 to 70% of the lincRNA genes shared between human and mouse . The orthologous mammalian lincRNAs can be predicted to perform equivalent functions; accordingly , it appears likely that thousands of evolutionarily conserved functional roles of lincRNAs remain to be characterized .
The great majority of mammalian genome sequences are transcribed , at least occasionally , a phenomenon known as pervasive transcription [1]–[4] . More specifically , tiling array analyses of several human chromosomes have shown that over 90% of the bases are transcribed in at least one cell type [1] , [5]–[8] . The analogous analysis in mouse has demonstrated transcription for over 60% of the genome [9]–[11] . Among the transcripts there are numerous long intergenic non-coding RNA ( lincRNA ) , i . e . RNA molecules greater than 200 nucleotides in length that are encoded outside other identified genes . Some of the lincRNAs have been shown to perform various regulatory roles but the majority remain functionally uncharacterized [7] , [12]–[17] . Furthermore , the fraction of the genome allotted to lincRNAs remains unknown . A popular view that the vast majority of lincRNAs are by-products of background transcription , “simply the noise emitted by a busy machine” [18] , [19] , is rooted in their typically low abundance and poor evolutionary conservation compared to protein-coding sequences and small RNAs such as miRNAs and snoRNAs [20] . However , some of the lincRNAs do contain strongly conserved regions [21] , and most lincRNAs show reduced substitution and insertion/deletion rates suggestive of purifying selection [12] , [22] , [23] . Given the general lack of strong sequence conservation , identification of lincRNAs on genome scale relies on expression analysis which makes comprehensive characterization of the mammalian lincRNome an elusive goal . The combination of different experimental approaches applied to transcriptomes of several species has resulted in continuous discovery of new transcripts [24] , with the FANTOM project alone cataloguing more than 30 , 000 putative long non-coding transcripts in mouse tissues by full-length cDNA cloning [11] , [25] . The Support Vector Machine method has been applied to classify transcripts from the FANTOM3 project into coding and non-coding ones and accordingly estimate the number of long non-coding RNA in mouse . This analysis has led to the identification of 14 , 000 long non-coding RNAs and an estimate of the total number of such RNAs in the FANTOM3 data at approximately 28 , 000 [26] . Here we re-analyze the most reliable available sets of human and mouse lincRNAs using the latest next generation sequencing ( RNAseq ) data and apply a maximum likelihood approach to obtain a robust estimate of the size of the mammalian lincRNome . The results suggest that mammalian genomes are likely to encode at least twice as many lincRNAs as proteins .
We performed comparative analysis of the recently reported validated sets of 4662 human lincRNAs [27] and 4156 mouse lincRNAs [12] , [20] , [23] ( see Methods for details ) in an attempt to produce robust estimates of the human and mouse lincRNome sizes , and to measure the turnover of lincRNA genes in mammalian evolution . The validated sets consist of lincRNA species for which a specific profile of expression across tissues – and hence distinct functionality – are supported by multiple lines of evidence . Assuming that these sets of lincRNAs are random samples from human and mouse lincRNomes , comparison of the validated sets should yield robust estimates of the lincRNome size for each species . For this analysis , we deliberately chose to employ the validated sets only rather than the available larger sets of reported putative lincRNAs in order to reduce the effect of transcriptional noise and other artifacts . A substantial fraction of the vast mammalian transcriptome , most likely the lower expressed transcripts , is expected to be non-functional . Therefore , to minimize the contribution of transcriptional noise , cut-off values were imposed on expression levels of lincRNA genes and their putative orthologs that were used for the lincRNome size estimation . Similarly , a series of cut-off values was applied for the fraction of indels in pairwise genomic alignments ( see Methods for details ) . A computational pipeline was developed to compare the sets of validated lincRNAs from human and mouse and to identify expressed orthologs by mapping the sequences to the respective counterpart genome and searching the available RNAseq data [28] ( Figure 1 ) . We then applied a maximum likelihood ( ML ) technique to estimate the total number of lincRNA genes in the human and mouse genomes as well as the number of orthologous lincRNA genes ( see Online Methods ) . The following simplifying assumptions were made: Let Lh and Lm be the sizes of the experimentally validated sets of lincRNAs for human and mouse , respectively . Also let Kh be the number of confirmed human lincRNAs that have an expressed orthologous sequence in mouse and Km be the corresponding number of mouse lincRNAs . Finally , Kb is the number of confirmed , expressed human lincRNAs whose orthologs in mouse are also confirmed lincRNAs . If the orthology relations between the human and mouse lincRNAs are strictly one-to-one , the number of confirmed mouse lincRNAs for which the human ortholog is also a confirmed lincRNA should be Kb as well . This is indeed the case in practice , with a few exceptions . Given assumption ( 1 ) , the lincRNAs can be partitioned into three pools: i ) those present in both species , pool size Nb , ii ) unique to human , Nh-Nb , and ii ) unique to mouse , Nm-Nb; here Nh and Nm are the total sizes of the complete human and mouse lincRNomes , respectively . Assumption ( 2 ) allows us to compute the probability of observing a particular set of Kh , Km and Kb simply by counting the number of possible samples of Lh and Lm lincRNAs drawn at random from the respective pools of Nh and Nm that result in the given set of Kh , Km and Kb values: ( 1 ) Maximizing the probability P in Eq . ( 1 ) with respect to Nh , Nm and Nb , we obtain ( see Methods for details ) : ( 2 ) To assess the robustness of the estimates , ranges of open reading frame size thresholds used to eliminate putative protein-coding genes and RPKM ( reads per kilobase of exon model per million mapped reads [29] ) thresholds used to gauge the expression level were employed ( Tables 1 and 2 ) . The ML estimates converged at approximately 50 , 000 lincRNAs encoded in the human genome and approximately 40 , 000 lincRNAs encoded in the mouse genome ( Table 1 and Figure 2 ) . These are conservative estimates given the use of strict thresholds on predicted open reading frame size and expression level ( Table 1 ) , so the actual numbers of lincRNAs are expected to be even greater . Approximately two-thirds of the lincRNA genes were estimated to share orthologous relationships ( Figure 2 and Table 1 ) . The subsets of lincRNAs with the increasing expression levels were found to be smaller and slightly but consistently more conserved ( Table 2 ) , a result that is compatible with our previous observation of positive correlation between sequence conservation and expression level among lincRNAs [23] . We next used the length distributions of human and mouse lincRNAs in the validated sets to estimate the total lengths of the lincRNomes and the fraction of the genome occupied by the lincRNA-encoding sequences , once again under the assumption that the validated sets are representative of the entire lincRNomes . Strikingly , the fraction of the human and mouse euchromatic genome sequence dedicated to encoding lincRNAs was found to be more than twofold greater than the fraction allotted to protein-coding sequences and greater even than the total fraction encoding mRNAs ( including untranslated regions ) ( Table 3 ) .
The relatively poor sequence conservation and often low expression of lincRNAs hamper robust estimation of the size of the lincRNome from expression data alone and render comparative-genomic estimation an essential complementary approach . Strikingly , the estimates obtained here by combining comparative genomic and expression analysis suggest that the mammalian lincRNome is at least twice the size of the proteome [30] , [31] . Given that intron-encoded long-non-coding RNAs and non-coding RNAs encoded in complementary strands of protein-coding genes ( long antisense RNAs ) [32] are disregarded in these estimates , the total set of lncRNAs and the fraction of the genome dedicated to the lincRNA genes are likely to exceed the respective values for protein-coding genes several-fold . In order to assess the reliability and robustness of the model with respect to parameters , we produced series of estimates of the total size of the human and mouse lincRNomes and their conserved subset with varying thresholds on expression level , extent of sequence similarity and the maximum allowed open reading frame size . Nevertheless , it is impossible to rule out some sources of bias that might have affected the estimates . For example , some orthologous lincRNA genes might remain undetected because they were not included in the UCSC genome alignments due to high divergence or synteny breaks in ( for example , inversions or translocations ) . Such under-detection of orthologs could cause an underestimate of evolutionary conserved lincRNA genes although it has been reported that the of breakpoints is not large ( <250 ) for the human/mouse genomic comparison [33] , so this type of bias is likely to be negligible . Another , potentially more serious source of bias could be a correlation between two lists of lincRNA genes which again would result in biased estimates of evolutionary conserved lincRNA genes . However , because the human and mouse lincRNA sets were obtained using quite different approaches [12] , [20] , [23] , [27] , there is no reason to expect that any strong correlation between the two lists would be caused by the employed experimental and/or computational procedures . An under-estimate of the number of orthologous lincRNAs as well as the total size of the mouse lincRNome also might be caused by smaller RNAseq dataset for mouse ( 10 tissue/cell types , see Methods for details ) compared to human ( 16 tissue/cell types ) . This difference could explain the systematically smaller predicted numbers of mouse lincRNA genes ( Tables 1 and 2 ) . More generally , given that expression of a large fraction of lincRNAs appears to be tissue-specific , the availability of sufficient data for relatively small numbers of tissue/cell types could cause substantial underestimate of the size of both lincRNomes and their conserved fraction . Thus , the estimates obtained here should be regarded as highly conservative , essentially low bounds the lincRNome size and the set of orthologous lincRNA genes . Some of the transcripts identified as lincRNAs potentially might represent fragments generated from long ( alternative ) 5′UTRs or 3′UTRs of protein-coding genes . Such transcripts could results from utilization of alternative poly ( A ) addition signals and/or could represent alternative splice forms separated by long introns [3] , [18] , [19] , [34] . If many purported lincRNAs actually are fragments of protein-coding genes , one would expect a strong correlation to exist between the expression of lincRNAs and neighboring protein-coding genes . Cabili and co-workers analyzed this correlation for the set of validated human lincRNA genes [27] . Their analysis focused on those protein-coding genes that had a lincRNA neighbor on one side and a coding neighbor on the other side , and used a paired test to compare the correlation between each protein-coding gene and its lincRNA neighbor with that between the same protein-coding gene and its protein-coding gene neighbor . This comparison showed a weak opposite trend , namely that expression of pairs of coding gene neighbors was , on average , slightly but significantly more strongly correlated than the expression of neighboring lincRNA/protein-coding gene pairs . The results of this analysis appear to be best compatible with the hypothesis that any co-expression between lincRNAs and their protein-coding neighbors results from proximal transcriptional activity in the surrounding open chromatin [35] . These findings effectively rule out the possibility that the majority of lincRNAs are fragments of neighboring protein-coding genes although there are anecdotal observations that 3′UTR-derived RNAs can function not only in cis to regulate protein expression but also intrinsically and independently in trans , likely as non-coding RNAs [36] . The possibility that some lincRNA genes encode short peptides that are translated , perhaps in a tissue-specific manner , is the subject of an ongoing debate [13] , [37]–[40] . It is extremely hard to rule out such a role for a fraction of purported lincRNAs as becomes obvious from the long-standing attempts to investigate potential functions of the thousands upstream open reading frames ( uORFs ) that are present in 5′UTR of protein-coding genes in eukaryotes [41]–[44] . Although some of the uORFs are translated , the functions of the produced peptides if any remain unclear [45] . Even application of modern high-throughput techniques in simple eukaryotic model systems so far have failed to clarify this issue . For example , analysis of 1048 uORFs in yeast genes has supported translation of 153 uORFs [46] . Furthermore , numerous uORF translation start sites were found at non-AUG codons , the frequency of these events was even higher than for uAUG codons even though the frequency of non-AUG starting codons is extremely low for protein-coding genes [46] . Another intriguing recent discovery is the potential presence , in the yeast genome , of hundreds of transiently expressed ‘proto-genes’ that are suspected to reflect the process of de novo gene birth [40] . However , the functionality of these peptides remains an open question . Establishing functionality of short ORFs in mammalian genomes is an even more difficult task . For example , analysis of translation in mouse embryonic stem cells revealed thousands of currently unannotated translation products . These include amino-terminal extensions and truncations and uORFs with regulatory potential , initiated at both AUG and non-AUG codons , whose translation changes after differentiation [47] . However , contrary to these emerging indications of abundant production of short peptides , a recent genome-wide study has reported very limited translation of lincRNAs in two human cell lines [48] . In general , at present it appears virtually impossible to annotate an RNA unequivocally as protein-coding or noncoding , with overlapping protein-coding and noncoding transcripts further confounding the issue . Indeed , it has been suggested that because some transcripts can function both intrinsically at the RNA level and to encode proteins , the very dichotomy between mRNAs and ncRNAs is false [38] . Taking all these problems into account , here we adopted a simple , conservative approach by excluding from the analysis lincRNAs containing relatively long ORFs , under a series of ORF length thresholds . However , it should be noted that human and mouse lincRNAs used in this study had been previously filtered for the presence of evolutionary conserved ORFs and the presence of protein domains , and the most questionable transcripts were removed at this stage [12] , [20] , [23] , [27] . For example , 2305 human transcripts were excluded from the stringent human lincRNA set [27] under the coding potential criteria ( the presence of a Pfam domain , a positive PhyloCSF score , or previously annotated as pseudogenes ) . The majority of these discarded transcripts ( 1533 ) were previously annotated as pseudogenes [27] . Similar to the stringent set of lincRNAs , these transcripts are expressed at lower and more tissue-specific patterns than bona fide protein-coding genes , suggesting that these effectively are non-coding transcripts . Nevertheless , Cabili and co-workers employed a conservative approach and excluded them from the stringent lincRNA set [27] . Questions about functional roles of lincRNAs and the fraction of the lincRNAs that are functional loom large . For a long time , the prevailing view appeared to be that , apart from a few molecular fossils such as rRNA , tRNA and snRNAs , RNAs did not play an important role in extant cells . More recently , the opposite position has become popular , namely that ( almost ) every detectable RNA molecule is functional . It has been repeatedly pointed out that this view is likely to be too extreme [49] , [50] . Although it has been shown that many lincRNA genes are evolutionarily conserved and perform various functions [7] , [12]–[17] , an unknown fraction of lincRNAs should be expected to result from functionally irrelevant background transcription [19] . In the present work , phylogenetic conservation is the principal support of functional relevance of lincRNAs . Given that neutrally evolving sequences in human and mouse genomes are effectively saturated with mutations and show no significant sequence conservation [51]–[53] , expression of non-coding RNAs at orthologous genomic regions in human and mouse should be construed as strong evidence of functionality . It should be noted , however , that sequence conservation gives the low bound for the number of functional lincRNAs , and the lack of conservation is not a reliable indication of lack of function . First , the possibility exists that orthologous genes diverge to the point of being undetectable by sequence comparison , e . g . because short conserved , functionally important stretches are interspersed with longer non-conserved regions , as is the case in Xist , H19 , and similar lincRNAs [54] , [55] [20] . The results of this work predict that , despite the fact that on average sequence conservation between orthologous lincRNAs is much lower than the conservation between protein-coding genes [12] , [23] , 60 to 70% of the lincRNAs appear to share orthologous relationship between human and mouse , which is only slightly lower than the fraction of protein-coding genes with orthologs , approximately 80% [51] . These findings imply that , even if many of the species-specific lincRNAs are non-functional , mammalian lincRNAs perform thousands of evolutionarily conserved functional roles most of which remain to be identified .
As the human lincRNA data set , the ‘stringent set’ of 4662 lincRNAs , which is a subset of the over 8000 human lincRNAs described in a recent comprehensive study [27] , was used . The validated set of mouse lincRNA genes was constructed by merging our previously published set of 2390 lincRNA transcripts with the set of 3051 transcripts produced by Ponting and coworkers [12] . After the merge , a unique list of 4989 GenBank transcript IDs was generated , coordinates of the newest mouse assembly , mm9 , were downloaded in BED format from the UCSC Table Browser [56] , and entries shorter than 200 nt were discarded . Overlapping chromosomal coordinates were merged using the mergeBed utility from BEDtools package [57] , with the command line option -s ( “force strandedness” , i . e . merge overlapping features only if they are on the same strand ) , and unique IDs were assigned to the resulting 4156 mouse lincRNA clusters . ( format: mlclust_N where mlclust stands for mouse lincRNA cluster , and N is a unique integer number; see Supporting Table S1 ) . Expression of the lincRNAs was assessed by analysis of the available RNAseq data . For human , the run files of the Illumina Human Body Map 2 . 0 project for adipose , adrenal , brain , breast , colon , heart , kidney , liver , lung , lymph node , ovary , prostate , skeletal muscle , testis , thyroid , white blood cells , were downloaded from The NCBI Sequence Read Archive ( SRA , http://www . ncbi . nlm . nih . gov/Traces/sra; Study ERP000546; runs ERR030888 to ERR030903 ) . For mouse , RNAseq data of the ENCODE project [58] for tissues: bone marrow , cerebellum , cortex , ES-Bruce4 , heart , kidney , liver , lung , mouse embryonic fibroblast cells ( MEF ) and spleen , were downloaded from the UCSC Table Browser [56] FTP site ( ftp://hgdownload . cse . ucsc . edu/goldenPath/mm9/encodeDCC/wgEncodeLicrRNAseq/ ) . Pre-built Bowtie indices of human and mouse , based on UCSC hg19 and mm9 , were downloaded from Bowtie FTP site ( ftp://ftp . cbcb . umd . edu/pub/data/bowtie_indexes/hg19 . ebwt . zip and ftp://ftp . cbcb . umd . edu/pub/data/bowtie_indexes/mm9 . ebwt . zip , respectively ) . The reads were aligned with the cognate genomic sequences using TopHat [59] . The TopHat-generated alignments were analyzed using an ad hoc Python script that accepts alignments and genomic coordinates in SAM and BED formats , respectively , and uses the HTSeq Python package ( http://www-huber . embl . de/users/anders/HTSeq ) to calculate the number of aligned reads ( “counts” ) . The RPKM ( i . e . reads per kilobase of exon model per million mapped reads [29] ) values were calculated from the counts values . Because we were interested to determine whether particular regions are expressed in any of the analyzed tissues , the maximum value among all tissues was assigned as the expression level of lincRNA genes and putative orthologous lincRNA genes . An ORF was defined as a continuous stretch of codons starting from the ATG codon or beginning of the cDNA ( to take into account potentially truncated cDNAs ) and ending with a stop codon . The ORFs were identified by using the ATG_EVALUATOR program [60] combined with the ORF predictor from the GeneBuilder package [61] with relaxed parameters ( the program was required to correctly predict 95% of the human and mouse cDNA training sets [61] ) . Control experiments with independent human and mouse cDNA data sets [61] showed a 94–98% true positive rate depending on the ORF length threshold ( 90 , 120 or 150 nucleotides ) . However , a high rate of false positives is expected for such relaxed parameters . Analysis of human and mouse introns and UTRs data sets showed false positives rates of 10–20% depending on the threshold [60] , [61] . For the purpose of the present analysis , false positives in ORF identification represent random removal of lincRNA sequences from the samples resulting in conservative estimates of the total lincRNA number . Thus , we used the ORF cut-off values of 90 , 120 or 150 nucleotides to remove putative mRNAs for short proteins separately from the human and mouse sets of lincRNAs . To obtain the subset of human lincRNAs with expressed orthologs in mouse ( Kh ) , human lincRNA gene coordinates of assembly hg19 were converted to mouse mm9 using the liftOver tool of the UCSC Genome Browser [62] . Out of the 4662 human lincRNAs ( Lh ) , for 3529 putative orthologous regions were identified in the mouse genome . These sequences were checked for the evidence of expression in mouse tissues using the RNAseq data . Exon coordinates of putative lincRNAs were obtained by mapping their coordinates onto exons of all known genes of mm9 assembly of UCSC Genome Browser . The sums of exons were then used in expression level calculation to normalize for sequence length . Out of the 3369 putative lincRNAs for which the exon models could be determined , 2872 had expression level greater than zero . Similarly , the subset of mouse lincRNAs with expressed putative orthologs in human ( Km ) was found by converting the coordinates of initial 4156 mouse lincRNAs ( Lm ) from mm9 to hg19 and searching for the evidence of expression in human tissues . The exon models could be determined for 3656 of the 3677 putative lincRNAs , out of which 3157 had expression level greater than zero . The subset of orthologous lincRNAs ( Kb ) was obtained by selecting those lincRNAs whose putative orthologs in another species overlap with the validated lincRNAs of that species . That is , we searched for the overlap of putative orthologs of human lincRNAs ( in hg19 coordinates ) with the mouse lincRNAs ( in mm9 coordinates , minimal overlap 100 nucleotides ) . The overlap was determined using intersectBed from BEDtools package with the command line option -s ( “force strandedness” ) . This resulted in 196 pairs of unique human and mouse lincRNAs . Approximate indel values were estimated from the sequence length differences between the lincRNAs and their orthologs , i . e . the following formula was used:where LllincRNA is the total length of lincRNA exons , and Lortholog is the total length of the exons of lincRNA ortholog . Manual examination of orthologous lincRNA alignments and putative orthologs suggested that approximately 5% of the alignments with the largest INDEL values were unreliable . Thus , all lincRNA alignments with INDEL >95% were removed from further analysis . Similarly , a cut-off was imposed on expression level of putative human and mouse orthologs of lincRNA . This cut-off was set at the lowest 5% of the expression levels of the 196 orthologous validated lincRNA genes ( Supporting Table S1 ) . All putative orthologs of lincRNA genes with lower expression values were discarded under the premise that these low values could represent experimental noise , i . e . the top 95% of the expression values EXP95% was used for all analyses ( Table 1 and Supporting Table S1 ) . In addition , EXP90% , 80% , 70% , 60% , 50% , 40% , 30% , 20% , 10% were calculated to compare subsets of lincRNAs expressed at different levels ( Table 2 ) . We also used different sets of expression/indel filters combined with the 5 input parameters ( see Results ) in different experiments ( Tables 1 and 2 ) ; no substantial differences between results were found ( see Discussion for details ) . For calculating the 5 input parameters ( see Results ) , all the collected information was stored in an SQLite database , and after applying ORF , indel and expression thresholds , final data sets were assembled ( Tables 1 , 2 and Supporting Table S1 ) . Using the experimentally validated sets of human and mouse lincRNAs and the assumptions described in the main text the probability of observing a particular set of Kh , Km and Kb for the given values of Lh and Lm is given by equation ( 1 ) in the main text . Using the Sterling's approximation for the factorial , we obtain the system of nonlinear equations for the sizes Nh and Nm of the pools and their overlap Nb that maximize the likelihood P in Eq . ( 1 ) ( 3 ) ( 4 ) ( 5 ) Solving the system ( 3–5 ) for Nh , Nm and Nb we obtain Equation ( 2 ) ( see main text ) . The confidence region around the maximum likelihood estimate Eq . ( 5 ) is an ellipsoid in the {Nh , Nm , Nb} space . The directions of its axes are given by the eigenvectors of the Jacobian matrix J of second derivatives of log P and the magnitudes of the ellipsoid's axes are given by the inverse square roots of the negatives of the eigenvalues . Computing the second derivatives of log P and evaluating them at the maximum likelihood point , we obtain ( 6 ) We found that the confidence ellipsoid is highly elongated , and therefore the estimates for the pool sizes are strongly correlated with each other . The analytically estimated 95% confidence intervals are shown in Table 1 . In addition , a bootstrap analysis of the lincRNA numbers was performed . For this purpose , the initial sets of human and mouse lincRNAs were randomly resampled 1000 times and the calculation of the final numbers was performed using 95% indel and expression ( RPKM ) levels , and all ORF thresholds . The results of bootstrap analysis are given in the Supporting Table S1 . The 95% confidence intervals estimated using the boostrapping procedure ( Supporting Table S1 ) were smaller than the analytically obtained 95% confidence intervals ( Table 1 ) , thus we used the latter as conservative estimates of the 95% confidence intervals . | Genome analysis of humans and other mammals reveals a surprisingly small number of protein-coding genes , only slightly over 20 , 000 ( although the diversity of actual proteins is substantially augmented by alternative transcription and alternative splicing ) . Recent analysis of the mammalian genomes and transcriptomes , in particular , using the RNAseq technology , shows that , in addition to protein-coding genes , mammalian genomes encode many long non-coding RNAs . For some of these transcripts , various regulatory functions have been demonstrated , but on the whole the repertoire of long non-coding RNAs remains poorly characterized . We compared the identified long intergenic non-coding ( linc ) RNAs from human and mouse , and employed a specially developed statistical technique to estimate the size and evolutionary conservation of the human and mouse lincRNomes . The estimates show that there are at least twice as many human and mouse lincRNAs than there are protein-coding genes . Moreover , about two third of the lincRNA genes appear to be conserved between human and mouse , implying thousands of conserved but still uncharacterized functions . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"genomics",
"biology",
"computational",
"biology",
"evolutionary",
"biology",
"genetics",
"and",
"genomics"
] | 2013 | The Vast, Conserved Mammalian lincRNome |
Hemorrhagic fever with renal syndrome ( HFRS ) is a rodent-associated zoonosis caused by hantavirus . The HFRS was initially detected in northeast China in 1931 , and since 1955 it has been detected in many regions of the country . Global climate dynamics influences HFRS spread in a complex nonlinear way . The quantitative assessment of the spatiotemporal variation of the “HFRS infections-global climate dynamics” association at a large geographical scale and during a long time period is still lacking . This work is the first study of a recently completed dataset of monthly HFRS cases in Eastern China during the period 2005–2016 . A methodological synthesis that involves a time-frequency technique , a composite space-time model , hotspot analysis , and machine learning is implemented in the study of ( a ) the association between HFRS incidence spread and climate dynamics and ( b ) the geographic factors impacting this association over Eastern China during the period 2005–2016 . The results showed that by assimilating core and city-specific knowledge bases the synthesis was able to depict quantitatively the space-time variation of periodic climate-HFRS associations at a large geographic scale and to assess numerically the strength of this association in the area and period of interest . It was found that the HFRS infections in Eastern China has a strong association with global climate dynamics , in particular , the 12 , 18 and 36 mos periods were detected as the three main synchronous periods of climate dynamics and HFRS distribution . For the 36 mos period ( which is the period with the strongest association ) , the space-time correlation pattern of the association strength indicated strong temporal but rather weak spatial dependencies . The generated space-time maps of association strength and association hotspots provided a clear picture of the geographic variation of the association strength that often-exhibited cluster characteristics ( e . g . , the south part of the study area displays a strong climate-HFRS association with non-point effects , whereas the middle-north part displays a weak climate-HFRS association ) . Another finding of this work is the upward climate-HFRS coherency trend for the past few years ( 2013–2015 ) indicating that the climate impacts on HFRS were becoming increasingly sensitive with time . Lastly , another finding of this work is that geographic factors affect the climate-HFRS association in an interrelated manner through local climate or by means of HFRS infections . In particular , location ( latitude , distance to coastline and longitude ) , grassland and woodland are the geographic factors exerting the most noticeable effects on the climate-HFRS association ( e . g . , low latitude has a strong effect , whereas distance to coastline has a wave-like effect ) . The proposed synthetic quantitative approach revealed important aspects of the spatiotemporal variation of the climate-HFRS association in Eastern China during a long time period , and identified the geographic factors having a major impact on this association . Both findings could improve public health policy in an HFRS-torn country like China . Furthermore , the synthetic approach developed in this work can be used to map the space-time variation of different climate-disease associations in other parts of China and the World .
Hantaviruses are RNA viruses that belong to the Hantaviridae family . Hantavirus infection causes hemorrhagic fever with renal syndrome ( HFRS ) to humans . As a rodent-borne infectious disease , the main domestic animals in China carrying hantavirus ( including Hantaan virus , HTNV , and Seoul virus , SEOV ) are Apodemus agrarius and Rattus norvegicus [1 , 2] . Specifically , HTNV can survive for more than 96 days outside the host’s body under wet conditions at a temperature of 4°C [3] . Having a high viability in the environment , the viruses can be transmitted to humans by contacting to virus contaminated material , such as inhalation of aerosols generated by urine or saliva , ingestion of infected food , or directly by rodents bites [4] . It has been reported that the HFRS death rate in China was 2 . 89% during the years 1950–2014 [5] . In China , during the period 1998–2007 the number of male patients was three times higher than that of female patients , 87 . 32% of the documented HFRS cases were 15 to 60 years old , and 70% of them were farmers [6] . HFRS remains a major concern in China , because , although a declining HFRS trend has been observed at a global scale in China , there still exist certain local regions that continue to display increasing HFRS trends [7] . The HFRS infections exhibit a well-defined annual cycle that corresponds to the local variability of climate factors , anthropogenic activity and land-use change [8–10] . Specifically , a trophic cascade has been found between local climate and HFRS infections , i . e . , the local precipitation and temperature affecting the living environment and primary food production , also contribute to the growth of the rodent population and the probability of interaction between infected rodents and humans [11] . To explore the climate effects on HFRS infections , previous studies have used quantitative techniques that explicitly incorporate climate factors in the estimation of the number of HFRS cases or the disease incidence . For example , Li et al . [12] employed a seasonal autoregressive integrated moving average model and found that the HFRS cases in Heilongjiang Province were closely associated with relative humidity , maximum temperature , and the southern oscillation index . Using a structure equation model , Guan et al . [13] observed that the HFRS incidence in Huludao City was correlated with temperature , air pressure , virus-carrying index , precipitation and relative humidity; using a Bayesian time-series Poisson adjusted model was found that the HFRS outbreak was related to preceding rainfall of 2–3 months ago [14] . Moreover , the principal components regression model , the multivariate polynomial distributed lag model , and the Poisson regression model have been used to explore climate-HFRS associations in Shenyang City , Chenzhou City , and the Elunchun and Molidawahaner counties , respectively [15–17] . Local characteristics of these associations were investigated in these studies , specifically the climate factors with considerable contributions to human HFRS infections ( including the El Niño index ) . However , none of these studies was concerned with the large-scale investigation of the variation of the climate-HFRS association . Hence , a systematic quantitative study of the climate-HFRS associations at a large space-time scale is still lacking . As a global climate phenomenon , El Niño-Southern Oscillation ( ENSO ) has been found to have a large impact on local precipitation and temperature [18 , 19] and to affect local ecological conditions and animal lives , including disease-related rodents [20] . It has been suggested that ENSO played a significant role in driving the inter-annual variation of rodent- or vector-borne diseases , such as dengue fever and hantavirus cardiopulmonary syndrome [21–25] . Moreover , in previous studies ENSO has exhibited a multiannual variability , whereas a significant variation of multiannual periodicities has been reported for HFRS at several small regions of China [11 , 26 , 27] . Therefore , it is interesting to explore the internal association ( co-variation ) between ENSO and HFRS . Considering its global impact on climate , ENSO is regarded as a global climate dynamics index in the investigation of climate-HFRS associations . Although earlier studies showed that wavelet analysis is a powerful tool in handling non-stationary time series [28] , it cannot individually handle simultaneously several time series distributed at a large spatial scale , which is the case of the Chinese HFRS data of interest in this work . On the other hand , Bayesian maximum entropy ( BME , [29 , 30] ) is a powerful data modeling approach that can jointly assimilate any number of time series at various spatial locations by means of spatiotemporal random field modeling . BME integrates the available core ( or general ) knowledge about the effects of global climate dynamics on local HFRS infections with site-specific information in a realistic space-time domain . It is a versatile quantitative method that can study non-stationary , non-linear and non-Gaussian systems , which is why it has been successfully used in many scientific disciplines , such as environmental sciences , ecology , public health and epidemiology ( for a review , see , e . g . , [31] ) . In view of the above considerations , the present work proposes a synthetic quantitative approach to study the spatiotemporal variation of the “global climate dynamics-HFRS” association in Eastern China under conditions of in-situ uncertainty . This approach has four main components: ( a ) Wavelet coherency analysis is used to assess quantitatively the association between global climate dynamics and HFRS at each city . ( b ) BME is used to estimate the strength of this association at a large domain and depict its spatiotemporal characteristics in terms of detailed maps . ( c ) The geographic boundaries of strong vs . weak associations are determined by hotspot analysis . ( d ) Lastly , a gradient boosting machine ( GBM ) model is used to investigate the specific impacts of the relevant geographic information on the global climate dynamics-HFRS association .
S3 Fig presents an outline of the synthetic methodological framework used in this work . More detailed information about the various components of this framework is given below .
In total , 127 wavelet coherency spectra were obtained ( one at each city in Eastern China ) by means of wavelet coherency analysis ( S4 Fig ) . By averaging the wavelet coherency spectra in each Chinese province and autonomous region , the mean wavelet coherency spectra at 19 provinces , autonomous regions and metropolitan areas were calculated and plotted in S5 Fig . These figures indicate that the closer the provinces are , the more similar are the corresponding wavelet coherency figures . For illustration , S5B–S5D Fig show that the shapes of the wavelet coherency plots are almost the same , and the only small differences visually observed are in the coherency values . At the three provinces ( Heilongjiang , Jilin , Liaoning ) strong coherencies ( high coherency values shown in S5B–S5D Fig ) exist between HFRS and global climate dynamics during three main period bands , i . e . , 12 , 18 and 36 mos . Among the three provinces , Heilongjiang has the largest coherency value during the 36 mos band , as displayed in S5B Fig . Wavelet coherency analysis thus confirmed quantitatively that the association between HFRS cases and global climate dynamics shows a strong coherency during the 3-yrs ( 36-mos ) multiannual oscillations of the entire period 2005–2016; this phenomenon is also observed in terms of the global statistics of Fig 2 . The same three period bands ( 12 , 18 and 36 mos ) with high coherency values can be detected in terms of the characteristic bands of Fig 2A , which depict the inter-association between HFRS cases and global climate dynamics . Furthermore , by comparing the coherency variances at all cities in Fig 2B , we found that the coherency during the 36-mos band has the lowest variance among the three main bands , thus suggesting that the HFRS-climate association is more consistent during the 36-mos band . Therefore , the 30–42 mos bands were selected as coherency character bands expressing HFRS-climate associations for further analysis . Given the selected character bands ( 30–42 mos ) , the mean coherency values for the entire 2005–2016 period were calculated at each city ( thus providing the space-time coherency dataset needed for further processing ) . This dataset was then analyzed using the SEKSGUI software library [39] . The calculated empirical covariance values shown in S6 Fig imply that the coherency between HFRS and global climate dynamics is spatially dependent and temporal sustained . To the empirical covariance values we fitted the theoretical space-time model of coherency variation cC ( |h| , τ ) =0 . 88[1−3|h|2×105+12 ( |h|105 ) 3]exp[− ( 3τ40 ) 2]+0 . 12[1−3|h|4 . 4×106+12 ( |h|2 . 2×106 ) 3]exp[− ( 3τ72 ) 2] , ( 5 ) where |h| and τ denote the spatial distance ( in meters ) and temporal separation ( in months ) , respectively . The numerical 10-fold cross validation results confirmed that BME generates accurate coherency estimates ( the corresponding accuracy indicators were R2 = 0 . 991 , MAE = 0 . 00271 , and RMSE = 0 . 0139 ) . Hence , the SI section presents several of these BME-generated spatiotemporal maps that offer a detailed picture of the strength of the climate-HFRS association in Eastern China for each month of the period 2005–2016 ( 144 maps , in total ) . To avoid the edge-effects of wavelet coherency analysis at the first and last year , the 120 maps of the period 2006–2015 were used to explore further the climate-HFRS association pattern across the study area ( Fig 3A ) . Based on the calculated coherency values , the region can be divided vertically into four parts ( south , middle-south , middle-north and north parts ) suggesting that local characteristics can affect the association . In particular , the south and middle-north parts have the highest and the lowest coherency values , respectively , whereas the other two parts exhibit mediocre coherency values . A few low coherency sections were observed in the south , middle-south and north parts of the study region . In S8–S17 Figs , several cities were closely associated with global climate dynamics during the entire period 2006–2015 with consistently high coherency values . Moreover , the presence of an upward climate-HFRS coherency trend during the period 2013–2015 indicated that the level of climate impacts on the HFRS disease is becoming increasingly sensitive during this period ( see S15–S17 Figs ) . Notice that the coherency values at several locations increased during 2014 implying that the HFRS infections at these locations became more closely associated with global climate dynamics than during previous years ( S16 Fig ) . For the entire study region , the spatial heterogeneity of Fig 3A is weak , implying that both high values and low values are clustered geographically . This phenomenon is tested by hotspot analysis . In fact , more obvious clusters can be found in Fig 3B , see the geographic distribution of the hot and cold spots corresponding to the HFRS-global climate association map of Fig 3A ( the distribution of the spots in Fig 3B delimits geographically high- and low-valued clusters ) . Actually , compared to Fig 3A and 3B makes it much easier to define visually the boundaries of the hot and cold spots . Four distinct parts of the HFRS-global climate association pattern can be detected in these figures , including the south , middle-south , middle-north and north parts of the study area . Most clusters with high association coherency ( i . e . , hot spots ) are located in the south part of the study area , whereas most clusters with low coherency ( cold spots ) are located in the middle-north part . Notice that some hot spots are close to each other , and the same is true for some cold spots . As a result , a large spatial continuous hop spot area as well as a large cold spot area are generated; e . g . , see the south and the middle-north parts of Fig 3B . The other two parts don’t exhibit any noticeable distributions of continuous non-point hot/cold spots . Yet , a number of point hot/cold spots can be still found at certain places of the study area . The corresponding monthly hotspot maps are displayed in the SI section of this work ( S31 and S32 Figs ) . Furthermore , the spatial stratified heterogeneity revealed in Fig 3 was tested in terms the q-statistic . The result showed that the maps of Fig 3 exhibit strong stratified heterogeneity ( q = 0 . 80 with significance 1 . 68E-09 ) . The same process was applied in S7–S30 Figs , in which cases it was found that the q-values ranged from 0 . 65 to 0 . 84 with the associated significance ranging from 1 . 18E-09 to 2 . 00E-09 ( S33 Fig ) . Multiple linear regression modeling was initially used to test the relationship between the ten explanatory variables introduced above ( i . e . , cropland , woodland , grassland , water , urban , barren , elevation , distance to coastline and spatial coordinates ) and the response variable ( association strength ) . The results showed that all ten variables have a significant influence on the climate-HFRS association ( in all ten cases , it was found that p < 0 . 05; see S1 Table ) , whereas the R2 value of linear regression was equal to 0 . 30 with p < 2 . 2 × 10−16 . All explanatory variables together with the response variable were used to construct the GBM model . The performance of the model was evaluated in terms of a 10-fold cross validation method . It was found that the accuracy indicator values were R2 = 0 . 94 , MAE = 8 . 71 × 10−5 and RMSE = 9 . 33 × 10−3 , which is a much better performance than that of the multiple linear regression model . Fig 4A shows the relative importance of the ten explanatory variables on the climate-HFRS association obtained by the GBM model . The five most important explanatory variables were the “north coordinate” ( latitude ) , “distance to coastline” , “east coordinate” ( longitude ) , “grassland” and “woodland” with relative importance scores 37 . 84% , 27 . 75% , 11 . 29% , 4 . 56% , 4 . 55% , respectively . The corresponding partial dependence plots for the “north coordinate” , “distance to coastline” , “east coordinate” , “grassland” and “woodland” are displayed in Fig 4B–4F . These partial dependence plots show the effect of each geographic factor on the climate-HFRS association after accounting for the average effects of all other factors in the GMB model . An apparent negative relationship was detected between the “north coordinate” and the climate-HFRS association ( Fig 4B ) , i . e . , the more northward is located the city the weaker is the climate-HFRS association ( this is especially valid in the south part of the study region depicted in Fig 3A ) . On the other hand , an increasing trend with local fluctuations was found between “distance to coastline” and the climate-HFRS association ( Fig 4C ) . The nonlinear ( wave-like ) variation effect of the “east coordinate” on the climate-HFRS association was clearly revealed in the plot of Fig 4D ( e . g . , the smooth trend of the “east coordinate” has a global sine shape with local wave fluctuations ) . The partial dependence of grassland exhibits a rapid increase-decrease-stable trend as a function of the grassland area ( Fig 4E ) . The positive relationship between the climate-HFRS association and woodland is shown in Fig 4F . The other partial dependence plots can be found in the SI section ( S34 Fig ) . Furthermore , we also constructed another GBM# model in the SI section ( the symbol “#” was used to distinguish it from the GBM model discussed above ) that excluded the spatial coordinates of the ten explanatory variables in order to avoid possible interactions of the geographic factors with spatial coordinates and to obtain additional insight about the geographic factors effects on the climate-HFRS association . Comparing the results in SI ( S1 Text and S35 Fig ) with the plots of Fig 4 above , similar conclusions can be drawn about the effects of the geographic factors investigated by the GBM# and by the GBM models .
Public health scientists and officers are concerned with questions like: “Are the HFRS outbreaks in a geographical region associated with global climate dynamics ? ” “How global climate dynamics affects the HFRS transmission pattern at a large spatial scale ? ” “Which geographic factors have significant impacts on the climate-HFRS association ? ” Answers to these and similar questions can offer valuable information for HFRS early warning , monitoring , and control purposes . The present work developed a novel synthetic quantitative analysis that can help answer these scientific questions . Methodologically , this approach is based on an integration of wavelet analysis , Bayesian maximum entropy , hotspot analysis and gradient boosting machine techniques . To the best of our knowledge , this is the first study that uses such a synthetic framework to assess climate-HFRS associations at a large geographic scale ( Eastern China , covering an area of about 2 . 8 million Km2 ) and during a relatively long time period ( 2005–2016 ) . The study is characterized by the originality of the HFRS dataset and the large amount of local and regional information available about several features of the climate-HFRS association in the time-frequency and the space-time domains . A main outcome of the present study is the successful quantitative investigation of the association between global climate dynamics and human HFRS infections by wavelet analysis . Wavelet analysis uses the global climate index MEI ( a proxy expressing global climate dynamics quantitatively ) that has been found to be suitable for large-scale analysis of ecological processes [45] . It has been postulated in the literature that climate affects HFRS infections by influencing rodent-borne physiology and interaction in a complex system [46 , 47] . For example , high positive MEI values infer the presence of El Niño phenomena , leading to higher precipitation levels in southeastern China during the months of December through May [48] . Hence , sufficient precipitation will help the reproduction of rodents , directly impacting the probability of rodent-human contacts and human infections . In this work , it was found that the large-scale HFRS surveillance dataset collected at 127 cities in Eastern China during 2005–2016 and the global climate dynamics records available exhibit a strong synchronicity in multiannual cycles , including 1 , 1 . 5 and 3 yrs periods ( Fig 2 , S4 and S5 Figs ) . This finding provides strong quantitative support to an earlier claim that HFRS infections are closely associated with global climate dynamics through complicated nonlinear dynamics , including multiannual and seasonal variational patterns of both climate dynamics and rodent population [20 , 49–51] . Another outcome of this work is related to the fact that wavelet analysis detected a strong association coherence between global climate dynamics and HFRS infections in Eastern China at 3 yrs cycle , indicating that both climate index and HFRS infections possess character multi-cycles with a 3 yrs period [36] . In this sense , this work confirmed at a large scale ( Eastern China ) , what previous studies have observed at a local scale , particularly , in Changsha city , Xi’an city and Pingyi county the HFRS variation was found to be characterized by 1 and 3 yrs cycles [14 , 26 , 52] . Public health officers may appreciate this work’s finding that the corresponding wavelet coherency spectra in S4 Fig provide local information about the climate-HFRS association that can improve the understanding of the HFRS transmission pattern . Additionally , these results can be regarded as a general knowledge base for HFRS monitoring , controlling and forecasting purposes or for further research ( e . g . , global climate dynamics can serve as a potential predictor of the trends of human infections by HFRS ) . We further explored the features of the climate-HFRS association by integrating information about the temporal variation of the association at Eastern China cities using the BME theory . The space-time variability of the climate-HFRS association represented quantitatively by the coherency covariance model showed a strong temporal dependence ( S6A and S6C Fig ) , indicating that the climate-HFRS association exhibits low temporal variation , i . e . , it remains stable locally . Moreover , a strong short-range spatial dependence with weak long-range heavy tails were also observed in the covariance model plots ( S6A and S6B Fig ) . The interpretational implication of these covariance features is that the climate-HFRS association has different local characteristics than global synchronicity . The BME-generated maps of the spatiotemporal variation of the climate-HFRS association strength ( coherency values ) included high-resolution monthly maps ( 10Km × 10Km ) covering the entire study area during the period 2005–2016 ( S7–S18 Figs ) . In addition to the global findings of this work mentioned earlier , the composite spatiotemporal covariance plot of climate-HFRS association ( S6 Fig ) indicates the presence of a weak local heterogeneity combined with a strong stratified heterogeneity . In other words , clusters of high and low coherency values in the maps of climate-HFRS association reveal some interesting local features of the spatial variability of the climate-HFRS association . At this point , another potentially significant finding was the presence of an upward climate-HFRS coherency temporal trend , especially during the period 2013–2015 , which indicated that the climate impacts on HFRS in Eastern China were becoming increasingly sensitive with time . This phenomenon may be due to the fact that the frequency of extreme precipitation events shows a temporally increasing trend in the monsoon region of Asia [53 , 54] , which includes a large part of the study region . As has been reported in the relevant literature [55] , winter temperatures are warming faster than summer temperatures , with the warm-event indices increasingly significantly with time ( the temperature and precipitation effects on HFRS infections in the Eastern China region are further discussed below ) . Public health officers may find it useful to study and evaluate , as appropriate , the geographical distribution of the climate-HFRS association in the BME-generated maps , like that of Fig 3A . The same is true as regards the strong and weak associations throughout Eastern China that are clearly outlined in the hot vs . cold spot map of Fig 3B . Hence , using such maps public health officers can assess , in quantitative terms , the strength of the climate-HFRS association at a specific location compared to the strength of the association at other locations ( e . g . , more attention should be paid to climate dynamics at hot spot locations ) . In a similar context , the health officers of a city in China may benefit by any effective HFRS control measures previously implemented in other cities with similar climate-HFRS association patterns . In light of the above findings and inferences , an important further objective of this work was to investigate potential geographic determinants of the variation of climate-HFRS associations in Eastern China during 2005–2016 . Generally , global climate dynamics is a macroscopic natural process at the earth scale exerting certain impacts on microscopic climate in local or regional domains with specific geographic features . In other words , local geographic information may either strengthen or weaken the link between global climate dynamics and HFRS infections by revealing local climatic conditions that can affect the rodents’ living environment [10 , 11] . Accordingly , a machine learning technique , GBM , was employed to investigate the complex non-linear relationship between geographic factors and the climate-HFRS association in the Eastern China region . Interestingly , the most important determinants of the geographic variation of climate-HFRS association were found to be the spatial coordinates of a location and the distance to coastline ( Fig 4A ) . If , e . g . , an extreme ( strong or weak ) climate-HFRS association is detected at a specific location of Eastern China , it suggests that large-scale climate-driven effects dominate the association at this location . Notice that the geographical dependence of the climate-disease link has been observed in other parts of the World . Klempa [56] , e . g . , showed that in different parts of Europe climate dynamics affects hantavirus and its reservoir hosts in more than one ways . Such findings would be valuable for local health management purposes , since , as was suggested earlier , health officers in hot spot areas should pay more attention to the global climate effects on HFRS transmission ( this kind of information is known to help disease control and monitoring efforts , [57] ) . Notice that a location with a low “north coordinate” ( latitude ) is linked to a much stronger climate-HFRS association than one with a high “north coordinate”; Fig 4C and 4D reveal a simultaneous wave-like effect on the climate-HFRS association of the “distance to coastline” and the “east coordinate” ( longitude ) , respectively . This observation suggests that HFRS outbreaks in coastal cities or riverbanks were particularly vulnerable to global climate dynamics ( thus confirming in the Eastern China case a similar result obtained by Rosenzweig et al . [58] ) . Interestingly , as is shown in the SI section ( S1 Text and S35 Fig ) , if the GBM# model is used ( that excludes spatial coordinates from the list of geographic factors under consideration ) the partial dependencies of the geographic factors exhibit a few minor differences compared to the GBM model above . These findings deduced that interaction effects exist between the geographic factors , and that the GBM# model can provide additional information concerning the possible effects of the geographic factors . Yet another objective of this work was to study the way geographic factors impact climate-HFRS associations in Eastern China . We considered that a better investigation of the phenomenon is possible if the impacts of the geographic factors on the climate-HFRS association were divided into two parts , including impacts on climate and impacts on HFRS infections ( rodent population ) . When the geographic factors have significant effects on both local climate and HFRS infections , they were expected to also impact the climate-HFRS association . Global climate dynamics drives local climate with various consequences ( changing microclimatic conditions , including temperature , precipitation and evapotranspiration; see , [59] ) . For example , temperature variation over the western pacific region ( including China ) is controlled by ENSO [60] . In this work ( Fig 4B ) , it was observed that global climate dynamics has more significant effects along the coastal regions of south China than in other parts of the country . In addition , global climate fluctuations can cause local precipitation variation [61] . Precipitation events will directly increase the primary food production for rodents , improve virus survival and stimulate rodent reproduction [62–64] . Precipitation can affect rodent population indirectly , by positively influencing the growth of grassland and woodland . Studies have shown that the normalized difference vegetation index NDVI can represent grassland and woodland , to a certain extent [65 , 66] . It has also been proven that NDVI and the enhanced vegetation index ( EVI ) are highly correlated with rodent ( deer mouse ) density [67] . Hence , grassland and woodland have a significant contribution on the number of HFRS hosts and can further impact the climate-HFRS association ( Fig 4E and 4F ) . Moreover , woodland can develop a stable ecosystem with strong stability and resilience during a low precipitation season [68 , 69] . Specifically , woodland can improve water resource conservation or primary food production for rodents’ consumption , which also benefit the rodent population in a positive way and can further impact the climate-HFRS association . This is why the partial dependence of woodland shows a monotonically increasing trend as a function of woodland coverage ( see Fig 4F ) . Beyond precipitation , warm winter temperatures can improve the survival of rodents [11] , thus further impacting the climate-HFRS association . In this work , it was found that because of the higher winter temperatures occurring in the south part ( with low “north coordinate” ) than in the north part of the study area ( thus , improving the rodents’ living conditions in the south compared to the north ) , there exists a stronger climate-HFRS association in the south with large-scale effects ( Figs 3 and 4B ) . As a result , a growing rodent population will increase the probability of virus transmission among rodents , and , subsequently , will increase the probabilities of rodent-human contacts and HFRS infections among humans [14 , 70] . In sum , the geographical factors have two main ways of affecting the climate-HFRS association: by impacting local climate and by directly impacting HFRS infections ( these two ways are related , since they both enable the growth of local rodent populations which , in turn , increase the probability of rodent-human contact and infection ) . Hence , by taking these geographic factors into consideration , public health officers may improve their understanding of the climate-HFRS association . It is hoped that the synthetic quantitative approach ( developed in this work to map the space-time variation of climate-HFRS association in Eastern China ) could be also applied in the study of different climate-disease associations in other parts of China or the world . Lastly , future work should be directed toward integrating the general knowledge and the site-specific information of the present study to forecast HFRS outbreaks at a large spatial scale covering the entire China . | China has the largest number of HFRS infections in the world ( 9045 cases in 2016 ) . Previous studies have found that HFRS infections are related to climate . However , the spatiotemporal distribution of the association between HFRS outbreaks at a large scale and global climate dynamics ( i . e . , over Eastern China during the period 2005–2016 ) , as well as the identification of the geographic factors impacting this association have not been studied yet . This is then the dual focus of the present study . Strong synchronicities between global climate change and HFRS infections were detected across the entire study area that were linked to three main time periods ( 12 , 18 and 36 mos ) . Specifically , strong and weak associations with non-point effects were detected in the south and middle-north parts of the study region , respectively . The climate impacts on HFRS were becoming increasingly sensitive with time . On the other hand , the geographic location ( north coordinate , distance to coastline , east coordinate ) makes a considerable contribution to the climate-HFRS association . As regards land-use , grassland and woodland were found to play important contributing roles to climate-HFRS association . Certain space-time links between global climate dynamics and HFRS infections were confirmed at a large spatial scale and within a long time period . The above findings could improve both the understanding of the HFRS transmission pattern and the forecasting of HFRS outbreaks . | [
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] | 2018 | Spatiotemporal variation of the association between climate dynamics and HFRS outbreaks in Eastern China during 2005-2016 and its geographic determinants |
Neocortical pyramidal neurons ( PNs ) receive thousands of excitatory synaptic contacts on their basal dendrites . Some act as classical driver inputs while others are thought to modulate PN responses based on sensory or behavioral context , but the biophysical mechanisms that mediate classical-contextual interactions in these dendrites remain poorly understood . We hypothesized that if two excitatory pathways bias their synaptic projections towards proximal vs . distal ends of the basal branches , the very different local spike thresholds and attenuation factors for inputs near and far from the soma might provide the basis for a classical-contextual functional asymmetry . Supporting this possibility , we found both in compartmental models and electrophysiological recordings in brain slices that the responses of basal dendrites to spatially separated inputs are indeed strongly asymmetric . Distal excitation lowers the local spike threshold for more proximal inputs , while having little effect on peak responses at the soma . In contrast , proximal excitation lowers the threshold , but also substantially increases the gain of distally-driven responses . Our findings support the view that PN basal dendrites possess significant analog computing capabilities , and suggest that the diverse forms of nonlinear response modulation seen in the neocortex , including uni-modal , cross-modal , and attentional effects , could depend in part on pathway-specific biases in the spatial distribution of excitatory synaptic contacts onto PN basal dendritic arbors .
Pyramidal neurons , the principal cells of the neocortex , receive at least two broad classes of excitatory inputs . Classical driver inputs , which give rise to the neuron's basic receptive field properties , are generally associated with vertical connections from other cortical layers [1]–[3] . Non-classical excitatory inputs modulate neural responses based on sensory [4] , [5] , attentional [6] , [7] , cross-modal [8] , and other “contextual” information [9] , [10] , and are thought to be carried by the dense network of horizontal connections within a cortical area , and feedback connections from other areas [3] , [5] , [11]–[13] . Conceptually , excitatory forms of modulation include pure threshold-lowering effects which left-shift a neuronal ( or dendritic ) input-output curve without changing its gain ( Figure 1A ) , pure gain-boosting effects that multiplicatively scale input-output curves without changing their thresholds ( Figure 1B ) , as well as a spectrum of mixed effects that include both threshold and gain changes ( Figure 1C ) [for review see 14] . Previous studies have identified a variety of mechanisms that could allow one excitatory pathway to boost a cell's responsiveness to another . Some have involved direct modulation of the soma [15]–[17] , while others have focused on signal interactions through the main apical trunk , such as the coupling of apical and somatic spike-generating mechanisms [18]–[20] or the gating of distally evoked responses through the apical trunk to the soma [21]–[23] . In contrast to these relatively long range interactions that affect the entire apical tree or the cell as a whole , other studies have focused on excitatory interactions operating on a more local scale – within individual thin dendrites [24]–[33] . Among these earlier studies , however , a mechanism with the flexibility to produce a broad spectrum of excitatory classical-contextual interactions has not so far been identified . In this work we have focused on neocortical PN basal dendrites as a possible site for classical-contextual interactions , since they receive a large fraction of a PN's excitatory input that includes both vertical and horizontal connections [2] , [3] , [34] . Unlike the clear distinctions between driver and modulator synapses in the thalamus [35] , however , little is known regarding what features of excitatory synapses on PN basal dendrites lead their post-synaptic effects to be classical or contextual , or more fundamentally , what allows the activity level in one excitatory pathway projecting to these branches to alter the threshold or the gain , or both , of another pathway's evoked response . We hypothesized that the location-dependent cable properties of thin perisomatic dendrites [36]–[39] , in concert with their intrinsic voltage-dependent membrane mechanisms [38] , [40]–[42] , could lead synapses near and far from the soma to modulate each other's responses in asymmetric nonlinear ways , and thus provide a possible substrate for classical-contextual interactions directly within the PN basal dendritic tree .
Excitatory inputs to pyramidal neuron basal dendrites can trigger local spikes mediated primarily by N-methyl-d-aspartate receptor ( NMDAR ) channels [30] , [39] , [40] , [43]–[45] . The location-dependence of NMDA spike properties evoked by stimulation at different distances from the soma was recently demonstrated using UV laser uncaging of glutamate onto basal dendrites of layer 5 pyramidal neurons in acute slices [44] , and was further quantified herein order to set the location-dependence ( or lack thereof ) of the NMDA-AMPA peak conductance ratio in our compartmental model ( Figure 2 ) . Though more proximal sites generate larger somatic responses and have higher spike thresholds as expected from passive cable theory [36] , we found no significant difference in a measure of the local spike-thresholding nonlinearity as a function of input location ( Figure 2A–D ) . Specifically , the “nonlinearity relative to the linear extrapolation” ( NRLE ) was quantified at each stimulated site by finding the point along that site's input-output curve that maximized the ratio of the actual to the predicted voltage response based on a linear fit to all preceding data points ( Figure 2B , see Materials and Methods for further details ) . Intuitively , the maximum NRLE value occurred at the largest/sharpest upturn in the input-output curve . A comparison of NRLE values is shown for proximal and distal sites in Figure 2D ( red columns ) , with the proximal-distal cutoff at 100 µm . The difference was not significant ( proximal NRLE = 3 . 12±1 . 37 , N = 15 cells , 35 locations , distal NRLE = 3 . 21±1 . 55 , N = 10 cells , 18 locations; p = 0 . 84 ) . When NMDARs , but not AMPARs ( Alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid ) were blocked with 50 µM APV ( 2-amino-5-phosphonovaleric acid ) and 100 µM MK-801 ( ( + ) -5-methyl-10 , 11-dihydro-5H-dibenzo[a , d]cyclohepten-5 , 10-imine maleate ) , a complete collapse of the dendritic spike nonlinearity resulted , and NRLE scores dropped to values below 1 that were equivalent for both proximal and distal sites ( proximal NRLE = 0 . 76±0 . 16 , N = 10; distal NRLE = 0 . 84±0 . 37 , N = 5; p = 0 . 71 ) . We tuned our compartmental model to produce similarly uniform NRLE values ( Figure 2E–G ) , which we found could be achieved by setting a spatially uniform NMDA-AMPA peak conductance ratio along the length of the branch ( ratio was 2 . 38∶1 , corresponding to the red dashed line in Figure 2H; red points show NRLE values at different distances from the soma , corresponding to the red bars in Figure 2G ) . In general , the choice of NMDA-AMPA ratio had a straightforward effect on NRLE scores , as shown in Figure 2H for cases with higher ( magenta ) or lower ( cyan ) uniform ratios , and cases with linearly increasing ( green ) or decreasing ( blue ) ratios . The use of a uniform NMDA/AMPA ratio in our simulations meant that any location-dependent effects produced by the model arose from synaptic interactions and nonuniform cable properties rather than differences in the synapses themselves . Using the uniform NMDA-AMPA ratio that resulted from the above fitting procedure , we used the compartmental model to map out the summation “arithmetic” for two inputs delivered simultaneously to a basal dendrite . Figure 3A shows somatic voltage responses to varying combinations of proximal and distal inputs ( at 80 µm , 120 µm , and 160 µm from the soma ) , over a range of stimulus intensities ( 0 to 40 activated synapses ) . For convenience , numbers below each pair of schematic electrodes indicate spatial separations between the stimulus sites . When the two stimuli were co-localized ( 3 subplots on main diagonal ) , the branch input-output function could be described by a sigmoidal ( s-shaped ) nonlinearity of a stereotyped form ( Figure 3B ) . The finding of a sigmoidal input-output function was consistent with previous descriptions of synaptic integration in pyramidal neuron thin dendrites [28] , [31] , [39] , [40] , [43]–[45] , as was the horizontal and vertical scaling of the input-output function depending on distance ( Figure 3C ) [see also 44] . The pattern of responses grew markedly more complex when the two inputs were spatially separated ( 3 off-diagonal plots in Figure 3A ) . In the lower right panel of Figure 3A , for example , a 2-D sigmoidal structure was still apparent , but the proximal sigmoid ( corresponding to voltage values running along the x-axis and red curves in Figure 3B , C ) , and the distal sigmoid ( voltage responses along the y-axis and blue curves in Figure 3B , C ) , were now very different . This difference gave rise to an asymmetric 2-D sigmoidal function with curved , irregular contours . A representative case for stimuli at 90 and 150 µm ( Figure 4A ) is shown in 3-D format in Figure 4B . To determine whether this asymmetric pattern of 2-input summation depended on the detailed time courses of the AMPA and NMDA conductances , voltage-dependent Na+ and K+ currents , capacitive effects , or any other temporal dynamics in the full compartmental model , we tested whether the effects could be reproduced by a 2-compartment model containing only 5 time-invariant conductances , thus lacking any temporal dynamics at all ( Figure 4C ) . The responses of the 2-compartment model were nearly indistinguishable from those produced by the full compartmental model ( compare Figures 4B and 4D ) , suggesting that the proximal-distal interactions we observed depend on the voltage-dependence of the NMDA channels , and the asymmetric placement of the two stimulus sites relative to the low input-resistance soma , but not on detailed aspects of synaptic timing or other membrane dynamics ( see Figure S1 in Text S1 for details and analysis ) . Using methods analogous to those in Figures 3 and 4 , we carried out two-input summation experiments in brain slices . Proximal and distal sites were activated separately and together over a range of stimulus intensities until an NMDA spike was generated at each stimulus site . In some experiments ( i . e . , when needed ) , CNQX was applied in the bath or TTX was applied at the soma to prevent somatic spiking , which would have otherwise occluded the underlying synaptic summation effects . Example traces are shown in Figure 5A for increasing stimulus intensity at the distal electrode , including a distally-evoked dendritic spike . A similar progression is shown for the proximal site in Figure 5B , as well as for the same progression of distal inputs in the presence of a constant proximal stimulus ( Figure 5C; the proximal input level in this case corresponded to the asterisked curve in Figure 5B ) . Summary plots for this cell are shown in Figure 5D and E where the peak somatic depolarization is plotted as a function of the distal or proximal driver stimulus intensity , respectively . The curve families in Figure 5D and E are analogous to slices through the 3-D plots of Figure 4 , where different input-output curves correspond to increasing levels of modulation at the second site ( as in Figure 1 ) . Note that the assignment of driver and modulator labels to the two sites was arbitrary , and simply reflected the direction in which the data was sliced and plotted . The set of modulation levels used in Figure 5D corresponds to the lowest ( dashed ) curve in 5E , and vice versa . Triangles indicate the point where a distal spike alone was generated ( with zero proximal input ) , while the transition from square to pentagon indicates the proximal spike alone ( with zero distal input ) . The circle marks the just-suprathreshold response for the distal stimulus when the proximal bias was just-subthreshold for its own spike . Figure 5F and G . show 294 2-input summation cases from 6 cells ( the same data is broken down by cell in Figure S2 in Text S1 ) . The substantial variation seen in local spike thresholds and response magnitudes , as indicated by the scatter of like symbols , could be attributed to differences in the locations of the stimulating electrodes , differences in the relative efficiency of electrical stimulation vs . laser uncaging , and substantial cell-to-cell variation in branch diameters . To facilitate comparison of the data to model predictions , which were generated with fixed electrode locations chosen to match the average NMDA-spike responses at proximal and distal locations in our experiments , we normalized the data using fiducial points for each cell corresponding to the four symbols in Figure 5D , E ( see Materials and Methods ) . Data with and without pharmacological blockers was combined given that a case-by-case analysis revealed no systematic difference in the shapes of the input-output curves under the different conditions . Individual curves ( thin lines ) in the normalized data were color-coded to indicate coarse levels of modulation intensity , from low ( black ) to high ( blue ) ( Figure 6 ) . Average curves within in each color-coded set are shown as bold lines to facilitate comparison between model and data . The model and experimental data sets were very similar in form ( compare top and bottom rows of Figure 6 ) . Confirming the pattern evident in Figure 5D , the proximal input , when viewed as the modulator , both lowered the threshold and increased the magnitude of the distally-driven input-output curve ( Figure 6A , C , see progression from black to green to red curves ) . Slicing the same data in the orthogonal direction as was done in Figure 5E , the distal input when viewed as the modulator initially lowered the threshold of the proximally driven response ( i . e . left-shifted the input-output curve ) without increasing its magnitude , eventually leading to a flattening/linearization of the proximal input-output curve at high levels of modulation . The close match between experimental data and modeling results in Figure 6 indicates that the models capture key features of proximal-distal summation under conditions where the neuron remains subthreshold for somatic spike generation . We ran additional simulations to examine the cell's input-output behavior under more realistic in vivo-like conditions where the neuron was driven to fire action potentials . 50 Hz independent Poisson spike trains were delivered to two groups of synapses at 90 and 190 µm from the soma ( similar to the location pairs in Figures 4C and 6A , B ) , and output spike rates were recorded at the soma over a 500 ms period . Spike timing was asynchronous both within and between synapse groups . To enable a single dendrite to drive output spikes , the soma was biased with a noisy current injection that produced a ∼1 Hz background firing rate ( see Materials and Methods ) . Somatic responses are shown for separate activation of the distal ( Figure 7A ) and proximal ( Figure 7B ) sites at 3 stimulus intensities . Lower plots show the effect of increasing proximal modulation on distal input-output curves ( Figure 7C ) and vice versa ( Figure 7D ) . Colored squares correspond to traces in Figure 7A , B . Despite the much more complex dynamics in these spiking simulations compared to the subthreshold case , the results were overall very similar . The proximal input when viewed as the modulator both lowered the threshold and increased the gain of the distally-driven input-output curve ( see black bars in Figure 7C ) , whereas a distal input when viewed as the modulator only lowered the threshold but did not increase the gain of the proximal input's input-output curve ( Figure 7D ) . To verify that the nonlinear proximal-distal interaction shown in Figure 7C , D reflected a bona fide within-dendrite effect , we ran control simulations in which proximal and distal inputs were delivered to two different dendrites . In contrast to the nonlinear within-branch interactions , firing rates generated by the separate branches combined nearly linearly at the soma ( Figure 7E , F ) , consistent with linear between-branch summation reported in previous studies [28] , [30] . We also found that nonlinear within-branch interactions remained very similar when proximal and distal inputs were distributed “regionally” across multiple branches of a dendritic subtree rather than limited to a single branch ( Figure S3 in Text S1 ) . Overall , the pattern of asymmetric summation between proximal and distal sites found under simulated in vivo-like conditions closely paralleled the subthreshold results . Pending the availability of anatomical “connectome” data that establishes whether pathway-specific biases exist in the spatial targeting of excitatory synapses onto PN basal dendrites , a pathway's tendency to terminate proximally vs . distally can potentially be distinguished by electrophysiological measures . In particular , cable theory predicts that somatic EPSPs generated by proximal synapses will have faster rise times and narrower half widths than similar synapses activated distally [37] , [46] . In a possible example of this effect , data of Yoshimura et al . [47] from kitten visual cortex suggests that vertical inputs from layer 4 onto layer 2–3 pyramidal neurons , and long-range horizontal ( LH ) connections between layer 2–3 PNs , may terminate at different distances from the soma . Unitary EPSPs evoked by LH axons connecting layer 2–3 pyramidal cells at separations of 350 to 1000 um had significantly shorter half widths ( 34 . 5±19 . 9 vs . 53 . 0±28 . 1 ms , p<0 . 05 , t-test ) and faster rise times ( 3 . 9±2 . 5 ms vs . 5 . 0±2 . 5 ms , p<0 . 04 , Wilcoxon rank-sum test ) than unitary EPSPs evoked by stimulation of vertical inputs from layer 4 . Consistent with the predictions of cable theory , in compartmental simulations designed to replicate the Yoshimura et al . data ( see Materials and Methods ) , we found that the shorter half widths and faster rise times for LH connections , compared to longer half-widths and slower rise-times for vertical inputs from layer 4 , suggests that as a population , the LH connections in primary visual cortex target more proximal dendritic locations than do vertical inputs ( Figure 8 ) . In light of our findings here ( Figure 7 ) , these LH connections , which are generally thought to carry contextual information , would be expected to exert a gain-boosting effect on cell responses driven by the vertical inputs from layer 4 . This is consistent with reports of multiplicative boosting of classical receptive field responses in visual cortex by horizontally offset contextual cues [4] , [48] .
Previous studies in layer 5 and CA1 pyramidal neurons have mostly focused on nonlinear interactions between proximal and distal inputs to the apical dendritic tree [18]–[20] , [22] , [41] . Though these studies like ours are concerned with nonlinear synaptic interactions in PN dendrites , our findings and conclusions can be distinguished from earlier work in two major respects . First , the biophysical mechanisms we describe differ from previously reported mechanisms . Oakley et al . [41] explored the interaction of glutamate-evoked calcium plateau potentials ( >500 ms ) evoked at different points along the apical trunk of a layer 5 pyramidal cell; the main proximal-distal effect reported was that the response to a combined proximal and distal input was dominated by the proximal response , whereas the distally-evoked response was largely occluded . Other studies have focused on the coupling between sodium and/or calcium spike-generating mechanisms in the distal apical tuft region and the cell's main firing mechanism at the soma [18]–[20] , [22] . The Larkum et al . [19] and Jarsky et al . [22] studies focus on the gating of distally-generated sodium spikes travelling to the soma , where the gating was controlled by a depolarizing input that “rescues” the forward-propagating spike at a point on the path to the soma where it would otherwise fail . Other work [18] , [20] has examined the modulatory role played by dendritic calcium spikes . When a somatic action potential back-propagates into the apical tree and combines with a distal depolarizing current injection to trigger a dendritic calcium ( BAC ) spike , the resulting current then flows “back” to the soma to produce a burst of somatic action potentials . The number of spikes in that burst , vs . the single spike that triggered it , can be thought of as the multiplier that accounts for the cell's overall gain increase [20] . Remondes and Schuman [21] and Takashashi and Magee [23] showed similar coupling effects involving mixed fast and slow spikes evoked by temporoammonic input to the distal apical trees of CA1 pyramidal cells , where the coupling of these distal regenerative events to somatic firing was enabled by NMDA currents activated more proximally in the stratum radiatum [see also 56] . Even more complex apical-somatic coupling effects involving timing and inhibitory circuits have also been reported [57] , [58] . In contrast to these previously described mechanisms involving inputs to the main apical trunk , and/or coupling of distal Na+ and Ca2+ spikes to the soma through the main apical trunk , the location-dependent summation nonlinearity we report here depends on ( 1 ) the voltage-dependence of synaptically activated NMDA channels , previously shown to be the major regenerative current carriers in PN thin dendrites [32] , [39] , [40] , [44] , [52] , and ( 2 ) the asymmetric cable properties that result when a thin dendrite connects to a larger trunk or soma [36] . Interestingly , Branco et al . [33] have recently shown that a PN's ability to distinguish excitatory stimulus sweeps towards or away from the cell body on a basal dendrite also depends on an interaction between NMDA currents and spatially-varying cable properties . This suggests that similar biophysical building blocks may contribute to very different forms of nonlinear synaptic integration . The second major respect in which the location-dependent summation mechanism we have described differs from previously reported integrative mechanisms in PNs is the level of spatial resolution . Synaptic interactions mediated through the main apical trunk , especially when they involve coupling of distal apical and somatic spiking mechanisms [18]–[23] are acting on a relatively global scale within the dendritic arbor . In contrast , the mechanism we have identified operates within the confines of individual thindendrites [see also 33] – and could potentially account for modulatory effects that operate on a finer than receptive field scale [4] , [59] , [60] . This biophysical capability , if exploited by PNs , could explain how attentional [59] , [60] and contextual [4] influences can selectively alter the responsiveness of a single receptive field subunit within a multi-subunit “complex” cell in the cortex [4] , [59] , [60] . In order for neurons to take advantage of subunit-specific modulation effects , driver inputs representing different stimulus variants – different receptive field positions , different color channels , etc . – would need to be segregated onto different dendritic branches [26] , [27] , [61] so that they could be separately targeted by modulatory pathways . A recent report that used in vivo optical recording of Ca2+ signals to study inputs to the dendrites of orientation-tuned neurons in mouse visual cortex came close to addressing this issue [62] , but did not reach the question as to whether the different dendrites of an orientation-tuned neuron differ in some feature other than orientation , such as different receptive field locations . Some evidence has been found for spatial segregation within the dendritic trees of sensory neurons [63] , though direct evidence that such segregation occurs in the neocortex , and on what spatial scale , is currently lacking . Though our study has focused on 2-input summation effects within a single dendrite , this does not imply that each dendrite necessarily processes unique classical and/or contextual signals: the same classical and contextual pathways might project to multiple basal dendrites or the tree as a whole , while maintaining their segregation in the radial dimension . Direct evidence for excitatory pathway segregation even at this coarser level of resolution is also lacking , but has a strong precedent: the targeting of different synaptic pathways to different dendritic zones is the rule rather than the exception in CNS organization [35] , [64] , [65] , a rule that certainly applies to pyramidal neurons in other respects: apical tuft dendrites are innervated by different axons than basal dendrites both in the neocortex [66]–[70] and hippocampus [71] , and within the basal arbor itself different classes of interneurons are known to selectively target somatic-perisomatic vs . distal sites [72]–[74] , just as we propose here for excitation . Furthermore , a spatial segregation of classical and contextual excitatory inputs to basal dendrites would likely depend on location-dependent neural plasticity mechanisms . In keeping with this , Gordon et al . [75] recently showed that the rules for synaptic long-term potentiation are different at proximal vs . distal sites on pyramidal neuron basal dendrites [see also 76] , [77] . Confirmation or refutation of the modulation-by-location hypothesis will require high-resolution anatomical and physiological mapping techniques capable of identifying the major sources of excitatory synapses onto PN basal dendrites , including long-range horizontal and cortico-cortical connections [65] , [78]–[81] , in conjunction with physiological recordings of somatic and dendritic potentials under varying states of response modulation in vivo [82] , [83] . To the extent that excitatory projection biases onto PN basal dendrites are found , the present framework will be of help in interpreting the functional consequences of such biases for cortical circuit computations . The nonuniform cable properties of thin dendrites connected to main trunks or the soma mean that synapses at more proximal sites experience lower input resistances than their distal counterparts , so that a larger number of ( equivalent ) synapses is needed to push the membrane at a proximal site into the NMDA voltage-dependent regenerative range compared to a distal site ( Figure 4B , D ) . It is thus interesting to note that on apical oblique dendrites of CA1 pyramidal cells , recent evidence indicates that spine volumes and PSD areas are largest near the proximal ends of the branches and grow systematically smaller moving distally , suggesting that excitatory synaptic conductances are at least partially normalized to the local input resistance [84] . Such a scheme would help equalize the stimulus intensity requirements for pathways projecting selectively to proximal vs . distal sites on these branches , though it is not currently known whether this form of pathway segregation occurs in CA1 . The location-dependent excitatory effects reported here are intriguingly similar in form , though opposite in direction , to location-dependent inhibitory modulation effects we have recently described in these same dendrites [85] . In that related study , we found that inhibitory inputs to PN basal dendrites also differently affect a dendrite's sigmoidal input-output curve depending on their location: a distal inhibitory input increases the threshold for an NMDA spike triggered by a more proximal input , that is , it right-shifts the proximal input's sigmoidal response curve . In contrast , a proximal inhibitory input both increases the threshold and lowers the gain of the sigmoidal response to a more distal input , analogous , but opposite , to the combined threshold and gain effects associated with proximal excitatory modulation . The very similar form of these excitatory and inhibitory modulation effects strengthens the case that PN thin dendrites , by virtue of their voltage-dependent NMDA currents and asymmetric cable properties , possess significant nonlinear analog processing capabilities tied to synapse location [33] , [39] , [44] . These include the ability for excitatory and inhibitory modulatory pathways to bi-directionally manipulate the thresholds and gains of dendritic input-output curves through biases in the spatial distribution of their synaptic influences along the proximal-distal axis of perisomatic thin dendrites . In the case of excitation , biases would be set up in the direct excitatory projections onto PN dendrites . In the case of inhibition , biases would be established indirectly by manipulating a pathway's relative activation of dendrite vs . soma-targeting interneurons . If in future experiments systematic variations in excitatory synapse distributions on PN thin dendrites are determined to play a significant role in mediating classical-contextual interactions , it is understandable how such a location-based computing mechanism could have escaped notice up to this point . Unlike other modulation mechanisms in which driver and modulator synapses are distinguishable based on measurable physical characteristics , such as synapse size or post-synaptic receptor type [35] , modulation-by-location in its pure form would be locally invisible ( i . e . “dark” ) , in the sense that under the microscope , dendrites would appear to be lined with an undifferentiated population of excitatory synapses . Only when the remote source of each synaptic contact has been traced , could the nature – or even the existence – of the location-based computation be inferred . The possibility that analog location-dependent computations do routinely occur within the dendrites of neocortical PNs , that contribute to the modulation of PN response by a multitude of attentional , contextual , and cross-modal influences , highlights the continuing need for multi-disciplinary approaches in analyzing neocortical circuits .
All simulations were performed using the NEURON modeling package ( version 7 . 0 r276 ) [86] . Unless otherwise indicated , all simulation studies utilized a 3D reconstructed layer 5 pyramidal cell morphology ( see Figures 2E inset and 4A ) that was a smoothed version of the “j4” morphology [87] , [88] , to which a myelinated axon was added to model axonal spike initiation [89] . Ion channel models and distributions were constrained by a variety of data [28] , [30] , [38] , [90] , [91] . Parameters are shown in Table 1 . NEURON files are available upon request . Excitation was delivered at varying distances from the soma through combined NMDAR/AMPAR type synapses . The AMPA component in each synapse had a fixed peak conductance while the NMDA peak conductance doubled ( 2 . 23 to 4 . 46 nS ) from the first to second pulse in 50 Hz double-pulse stimulation experiments ( Figures 3–6 ) . Values were fit based on measured physiological summation nonlinearities for single and double pulse stimulation experiments [30] , were in keeping with increases in NMDA conductance upon repeated stimulation [92] , and non-saturation of the NMDA receptor [93] . Both AMPA and NMDA conductances were modeled as difference-of-exponential functions with kinetics appropriate for 35°C ( see Table 1 ) . The NMDA channel model included an instantaneous voltage-dependent Mg-block of the form B ( V ) = 1/ ( 1+e− ( V+12 ) /10 ) . Hodgkin-Huxley style sodium and potassium conductances were included in the axon , soma and dendrites , with the sodium conductance decreasing linearly to zero at a distance of 200 µm from the soma [38] . For single-pulse simulations mimicking single pulse UV glutamate uncaging in Figure 2 , NMDA peak conductance was set to 3 . 56 nS to match the NRLE of the in vitro data . Synapse clusters were centered at specified locations with 0 . 5 µm spacing [34] . Terminal dendrites were corrected for the membrane area contribution of unmodeled spines by increasing membrane capacitance and conductance by a factor of 2 . 0 [34] . In simulations with NMDAR block , the NMDA channel peak conductance was set to 0 . The axon , soma , and all dendritic subtrees containing activated synapses were divided into electrical compartments , or “segments” of length no greater than one tenth of the section's length constant at 100 Hz [94] , or 10 µm - whichever was smaller . In other dendrites , 3 segments were used per section without loss of simulation accuracy . Suprathreshold ( spike rate ) results used the same model as above except for the excitation which was in the form of unsynchronized 50 Hz Poisson trains , and the peak NMDA conductance was fixed to 3 . 9 nS . To achieve a low background firing rate ( ∼1 Hz ) , the axo-somatic spike generating mechanism the soma was biased with a noisy current injection ( 0 . 75±1 nA ) updated every integration time step ( 0 . 1 ms ) . Spike rates were averaged over the 500 ms stimulus period . For each data point ( xi , yi ) beginning with the second point on each input-output curve , a line was fit to all preceding data points , and extrapolated to the point ( xi+1 , yextrap ) . The ratio of the actual y value to the linearly extrapolated y value yi+1/yextrap was computed , and the maximum of this ratio along a given input-output curve was taken as the NRLE for that curve . The EPSP study in Figure 8 utilized a published L3 model [89] with the following changes: 1 ) Spine correction was changed to be the same as described above , which does not distort the morphology , enabling our analysis of EPSP properties versus distance , and 2 ) Rm and Cm were increased by a factor of 1 . 6 so that the EPSP half-width ranges in the model were similar to those in Yoshimura et al . [47] . Synapses were AMPA-type only and were modeled as difference-of-exponential functions with τrise , fall = 0 . 2 , 2 ms and 2 nS peak conductance . EPSP properties were similar when synapses contained mixed NMDA/AMPA conductances similar to those used elsewhere in the paper ( data not shown ) . Time-invariant voltage responses were calculated using methods described elsewhere [85] , but with the addition of a second NMDA conductance ( see Figure 4C ) . The Kirchhoff's current law equations were as follows:whereand ( 1 ) By exploiting the relationship between Vprox and Vdist: ( 2 ) to eliminate the dependence on Vprox in Eq . ( 1 ) the resulting equation was solved numerically for Vdist , then Vprox was computed using Eq . ( 2 ) . Here , B ( V ) = 1/ ( 1+e− ( V+22 ) /12 ) , slightly ‘softer’ than the magnesium block term used in the multi-compartment model . This was done to account for the “dilution” of the NMDA voltage-dependent non-linearity by co-activated AMPA channels , which were not explicitly included in the 2-compartment model . In Figure S1 in Text S1 , CTO , the ‘current-to-overcome’ , was defined as – ( Isoma-INMDA_Drive ) , corresponding to the ‘net leak’ in the control and modulation conditions . Neocortical brain slices 300–350 µm thick were prepared from 18- to 28-day-old Wistar rats . All experimental procedures were in accordance with guidelines of the Technion Institutional Animal Care and Use Committee . Extracellular solution contained 125 mM NaCl , 25 mM NaHCO3 , 25 mM glucose , 3 mM KCl , 1 . 25 mM NaH2PO4 , 2 mM CaCl2 and 1 mM MgCl2 ( pH 7 . 4 ) at 35–36°C . Intracellular solution contained 115 mM K+-gluconate , 20 mM KCl , 2 mM Mg-ATP , 2 mM Na2-ATP , 10 mM Na2-phosphocreatine , 0 . 3 mM GTP , 10 mM HEPES and 0 . 15 mM Calcium Green-1 ( CG-1 ) or 0 . 2 mM Oregon Green 488 Bapta-1 ( OGB-1 ) , pH 7 . 2 . GABAA receptor blocker bicuculline methiodide ( BCC; 1–20 µM ) was added to the extracellular solution in some experiments . Whole-cell patch-clamp recordings were made from visually identified layer-5 pyramidal neurons using infrared-differential interference contrast optics . Electrophysiological recordings were performed using Multi-Clamp 700A ( Axon Instruments , Foster City , CA ) , and the data were acquired and analyzed using Pclamp 8 . 2 ( Axon Instruments ) , Igor ( Wavemetrics , Lake Oswego , OR ) , and in-house software . All statistical analyses used the Student's t-test . The neurons were filled with a calcium-sensitive dye ( CG-1 or OGB-1 ) and the basal dendritic tree was imaged with a confocal imaging system ( Olympus Fluoview ) mounted on an upright BX51WI Olympus microscope ( Tokyo , Japan ) equipped with a 60× ( 0 . 9 n . a . ; Olympus ) water objective . The theta stimulating electrodes were filled with Alexa Fluor 647 . Full images were obtained with a temporal resolution of 1 Hz and in the line scan mode with a temporal resolution of 512 Hz . Images were analyzed using Tiempo ( Olympus ) , Igor ( Wavemetrics ) , and in-house software . Focal synaptic stimulation was performed with a theta patch pipette located in close proximity to the selected basal dendritic segment , as guided by the fluorescent image of the dendrite . We limited ourselves to dendritic regions that were more distal than the initial 50-µm segment of the basal dendrites , as we could not obtain focal synaptic activation in those regions . For the uncaging experiments , caged glutamate ( 4-methoxy-7-nitroindolinyl ( MNI ) -glutamate; Tocris , San Diego , CA ) was photolyzed with a 361 nm UV-laser beam ( Enterprise 2; Coherent , Palo Alto , CA ) using point scan mode . The caged glutamate ( 5–10 mM ) was delivered locally to a branch using pressure ejection ( 5–10 mbar ) from an MNI-glutamate-containing electrode ( 2 µm diameter ) . The four fiducial points indicated by shapes in Figure 5D , E were used to normalize the data from each of the 6 cells ( Figure 5F , G ) . The normalization results are shown in Figure 6 C , D . The square and pentagon indicate just-subthreshold and just-suprathreshold responses for the proximal spike alone , the triangle indicates the just-suprathreshold response for the distal spike alone , and the circle was just-suprathreshold for the distal stimulus when the proximal bias was simultaneously just-subthreshold for its own spike . We noted that over the data set: ( 1 ) the proximal spike was more than twice the height of the distal spike ( compare height of pentagon and triangle ) ; ( 2 ) the proximal just-subthreshold response was about 2/3 the height of the distal spike response ( compare y-coordinates of square and triangle ) ; and ( 3 ) the threshold for spike generation by a distal input was roughly cut in half when boosted by a just-subthreshold proximal bias ( compare x-coordinates of circle and triangle . Given these observations , we created a template set of fiducial points based on the average ratios found in the experiments: triangle = ( 1 , 1 ) ; square = ( 0 , 0 . 6 ) ; pentagon = ( 0 , 2 . 4 ) ; circle = ( 0 . 6 , 2 . 2 ) . For any given cell , the 2-D data ( distal drive , proximal modulation ) was scaled using the horizontal and vertical scaling factors that minimized the MSE between actual and template fiducial points . Note that only 2 scaling factors found through MSE minimization for each cell were used to scale all 29–56 data points for that cell . Overfitting was thus avoided . It is worth noting that we previously attempted a more ‘intuitive’ normalization procedure based on only the two fiducial points corresponding to the proximal and distal spikes , but because that normalization scheme did not capture threshold lowering and spike boosting affects of ‘medium’ strength modulators , that approach resulted in a poorer match between the data and the model . Thus , we used the additional fiducial points which capture more of the relevant features of each experimental data set . The data viewed from the orthogonal perspective ( proximal driver , distal modulation ) was more uniform , so that only a single fiducial point was needed for normalization: each plot was rigidly scaled to place the pentagon at the point ( 1 , 2 . 4 ) ( Figure 6D ) . | Pyramidal neurons ( PNs ) are the principal neurons of the cerebral cortex and therefore lie at the heart of the brain's higher sensory , motor , affective , memory , and executive functions . But how do they work ? In particular , how do they manage interactions between the classical “driver” inputs that give rise to their basic response properties , and “contextual” inputs that nonlinearly modulate those responses ? It is known that PNs are contacted by thousands of excitatory synapses scattered about their dendrites , but despite decades of research , the “rules” that govern how inputs at different locations in the dendritic tree combine to influence the cell's firing rate remain poorly understood . We show here that two excitatory inputs contacting the same dendrite interact in an asymmetric nonlinear way that depends on their absolute and relative locations , where the resulting spectrum of location-dependent synaptic interactions constitutes a previously unknown form of spatial analog computation . In addition to suggesting a possible substrate for classical-contextual interactions in PN dendrites , our results imply that the computing functions of cortical circuits can only be fully understood when the detailed map of synaptic connectivity – the cortical connectome – is known down to the subdendritic level . | [
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] | 2012 | Location-Dependent Excitatory Synaptic Interactions in Pyramidal Neuron Dendrites |
Cryptosporidiosis causes life-threatening diarrhea in infants , but the best available treatment is only modestly efficacious . Rodents infected with relevant Cryptosporidium species do not develop diarrhea , which complicates drug development . Cryptosporidium parvum infection of dairy calves , however , causes an illness like that seen in infants . Here , the clinical and microbiologic anti-Cryptosporidium efficacy of the piperazine-based compound MMV665917 was demonstrated in neonatal calves . Oral administration of MMV665917 ( 22 mg/kg once daily ) was begun two days after the onset of severe diarrhea and continued for seven days . Treatment resulted in prompt resolution of diarrhea , and reduced total fecal oocyst shedding by ~94% . MMV665917 was useful for treatment , rather than just prophylaxis , since it was safe and effective when administered well after the onset of diarrhea . Furthermore , even though all animals received intensive supportive care , there was a strong trend towards improved secondary health outcomes , including general health , appetite , and dehydration measures amongst treated animals . These data establish MMV665917 as an outstanding lead compound for Cryptosporidium drug development .
Diarrhea still causes over 10% of childhood deaths [1] . Although cryptosporidiosis was previously recognized as a major contributor to diarrhea in endemic areas , a recent multicenter study in Africa and Asia found that Cryptosporidium infections , mostly due to Cryptosporidium hominis or Cryptosporidium parvum , are the third most common cause of severe diarrhea in young children [2] . Cryptosporidium infections are also strongly associated with malnutrition and delayed development [2] . Furthermore , cryptosporidiosis is a prevalent cause of chronic diarrhea in AIDS patients [3] , and is responsible for over 85% of waterborne diarrhea outbreaks in the United States [4] . Treatments for cryptosporidiosis in the most affected populations are poor . Nitazoxanide is the only drug with proven efficacy in immunocompetent people , in whom it shortens the illness by approximately one day . Nitazoxanide is equivalent to a placebo for HIV positive people , and data from very young , malnourished children come from a study of only 47 children; 14/25 ( 56% ) nitazoxanide recipients were improved at seven days , while 5/22 ( 23% ) placebo recipients were improved [5 , 6] . There is a dire need to develop more effective treatments for people with cryptosporidiosis . Cryptosporidium parvum infection in calves is an economic concern for beef and milk producers , and may contribute to contamination of water supplies and human disease outbreaks . In a nationwide survey of 1103 US farms , Cryptosporidium was present on over 50% of farms , infecting 48% of all calves aged 1–3 weeks [7] . Although most outbreaks of human cryptosporidiosis are due to anthroponotic transmission of human restricted isolates , zoonotic transmission of livestock associated isolates has caused large outbreaks [8] . Controlling cryptosporidiosis in calves would therefore be of economic benefit and reduce the burden of human disease . We and others previously used a cell-based assay to identify potential Cryptosporidium drug leads [9–12] , in combination with follow-up in vivo studies in immunocompromised mice . One of the most promising compounds found to date , MMV665917 , was identified within the Medicines for Malaria Venture “Malaria Box” , an open access collection of 400 compounds with activity against the erythrocyte stages of Plasmodium falciparum [10 , 13] . MMV665917 is a piperazine-based compound with high selectivity for the blood stages of malaria parasites and for Cryptosporidium species . Its potency is roughly equivalent for multiple C . parvum lab and field isolates , and for the C . hominis TU502 isolate , and MMV665917 treatment reduces parasite shedding to below detectable limits in a highly immunocompromised mouse model of chronic C . parvum infection ( Jumani , et al . Submitted manuscript ) . A limitation of the existing mouse cryptosporidiosis models , however , is that infected mice do not develop diarrhea . Thus , while MMV665917 has proven microbiologic efficacy in immunocompromised mice , its clinical efficacy for treating cryptosporidiosis remains unknown . Neonatal calves infected with C . parvum shed oocysts at high levels and develop diarrhea similar to that seen in young children , providing a clinical model for drug testing [14] . This study’s purpose was to determine if MMV665917 is both clinically and microbiologically efficacious in dairy calves . We report pharmacokinetic ( PK ) data from uninfected calves and infected calves with diarrhea , and the results of a clinical efficacy study .
Animal studies were approved by the University of Vermont ( UVM ) Institutional Animal Care and Use Committee ( IACUC ) . The University of Vermont has an Animal Welfare Assurance with the Office of Laboratory Animal Welfare ( OLAW ) of the National Institutes of Health , and is registered as a Research Institution by the United States Department of Agriculture . The University complies with the recommendations of the Guide for the Care and Use of Laboratory Animals ( 8th ed . , NRC 2011 ) and with the Animal Welfare Act and its associated regulations ( USDA-APHIS "Blue Book , " available at www . aphis . usda . gov/animal-welfare ) . Holstein bull calves were acquired at birth from Green Mountain Dairy ( Sheldon , VT ) , given synthetic colostrum with 200g of IgG ( Land O’Lakes , Ardent Hills , MO ) and bovine coronavirus and Escherichia coli antibodies ( First Defense Bolus , Immucell Corporation , Portland , ME ) within two hours of birth , and transported to UVM . Uninfected animals were group-housed in a pen for PK studies . For studies of infected calves , animals were initially group-housed and infected at 24–48 hours of age during an interruption in bottle feeding by oral administration of ~5×107 viable C . parvum Iowa isolate oocysts ( Bunch Grass Farms , Deary , ID ) suspended in 10 mL of deionized water . Animals were moved to individual raised pens immediately after infection , and observed twice daily at feeding times for clinical signs , which were quantified according to a standardized scoring rubric ( Table 1 ) ; fecal consistency , general health , hydration status , and appetite data were collected . Clinical microbiologic studies for adventitious infectious agents including Salmonella culture , aerobic bacterial culture with E . coli genotyping , and rotavirus and coronavirus testing were performed on all calves at the onset of diarrhea at the Cornell Health Diagnostic Center ( Ithaca , NY ) . Animals with severe diarrhea and other symptoms were supported aggressively , including administration of oral electrolytes , intravenous fluids , and flunixin meglumine ( Banamine , Merck ) as needed . MMV665917 was suspended for dosing in 1% hydroxypropyl methyl-cellulose in water at a final volume of 10 mL per dose . Doses were squirted into the calves’ mouths during interruptions in bottle feeding . For PK studies , fecal samples were collected at the indicated times by manual anal stimulation . For treatment efficacy studies , daily fecal samples were obtained from collection bins located under each pen . Fecal samples used for parasite quantification were dried at 90°C until a stable weight was reached , and C . parvum abundance per gram of fecal dry matter was measured using a previously validated qPCR assay [15] . To our knowledge , this qPCR assay is the most sensitive method currently available . The lower limit of detection is ~100 oocysts/gram of dried feces . Serum samples were analyzed by liquid chromatography-tandem mass spectrometry ( LC/MS/MS ) , using compound spiked into control serum as a standard . Fecal MMV665917 was measured by homogenizing feces in PBS ( 0 . 1 g/mL ) in a polypropylene tube and then further dilution prior to addition of an internal standard ( enalapril ) and acetonitrile protein precipitation . The supernatant was transferred to a fresh tube and dried using a speed vac . Samples were then resuspended and analyzed using LC/MS/MS . Data were analyzed using GraphPad Prism version 6 . 00 . The area under the curve ( AUC ) was calculated for each animal using a plot of the indicated parameter vs . time and a baseline score of one ( i . e . a calf with a score of one every day ( no diarrhea ) would have an AUC of 0 ) . The AUC for oocyst shedding was determined from a plot of the Log10 transformed fecal oocyst shedding per gram of fecal dry matter vs . time using a baseline of 2 ( Log10100 ) and including the first day of drug dosing . p values were determined using the unpaired one-way student’s t test . Graphs were labeled for Fig preparation using Adobe Illustrator CS5 .
It remains unknown if both intestinal and systemic compound concentrations are required for in vivo efficacy , but achieving a total sustained serum concentration of 3× the EC90 in an immunocompromised mouse model previously reduced parasites to below detectable levels , while mice treated at lower doses quickly relapsed ( Jumani , et al . Submitted manuscript ) . To determine a comparable MMV665917 dosing regimen for clinical efficacy studies in the calf model , we therefore began with an experiment in which uninfected animals received a single oral dose , followed by measurement of serum and fecal compound concentrations ( Fig 1A ) . The total MMV665917 serum concentration exceeded the target concentration of 3× the EC90 within 12 hours after receipt of 22 mg/kg orally , and this level persisted for over 24 hours . The fecal concentration of MMV665917 exceeded 3× the EC90 after just two hours , and persisted for over 24 hours . These data suggested the possibility of efficacy using a once daily dose of 22 mg/kg . Because it remained possible that diarrhea in Cryptosporidium infected calves would alter the PK profile of MMV665917 , we conducted a pilot study in infected animals using 22 mg/kg once daily administered for seven days beginning on day four post-infection , two days after the onset of severe diarrhea ( Fig 1B ) . This dose resulted in sustained fecal and serum concentrations in excess of the target concentration . MMV665917 also appeared to be safe and well tolerated at this dose , since no adverse effects or taste aversion were noted . We next tested the clinical and microbiologic efficacy of MMV665917 for treatment of cryptosporidiosis using the calf model . Neonatal bull calves were infected by oral administration of C . parvum Iowa isolate oocysts . The high inoculum used consistently resulted in infection and onset of severe diarrhea ~72 hours after administration ( Figs 2A and 3A ) . Infected calves received either MMV665917 ( 22 mg/kg once daily for seven days ) or vehicle alone ( negative control ) beginning on day four after infection , the time point corresponding to the second day of severe diarrhea . MMV665917 treatment reduced diarrhea severity within one day ( Fig 2A ) , which corresponded to a two log reduction in the number of oocysts per gram of fecal dry matter within two days of beginning treatment ( Fig 3A ) . Interestingly , low level oocyst shedding continued despite ongoing treatment and complete resolution of diarrhea . This was consistent with prior observations of the natural history of Cryptosporidium infection in dairy calves , which demonstrated persistent low level oocyst shedding after the resolution of illness ( observations out to 28 days following infection; S1 Fig ) . MMV665917 treatment reduced both the severity of diarrhea and the numbers of oocysts shed . The AUC for each animal calculated from a plot of the fecal consistency vs . time ( including the first day of drug dosing ) was used to quantify the magnitude of the reduction in diarrhea over the course of the study . Consistent with the general clinical observation of caregivers , MMV665917 treatment dramatically reduced the number of animal days with moderate-to-severe diarrhea ( Fig 2B ) . Similarly , calculation of the AUC for Log10 transformed oocyst shedding by each animal demonstrated that MMV665917 treatment reduced overall shedding by ~94% ( geometric mean of total oocyst shedding of 91 , 743 vs . 1 , 458 , 631 for treated vs . control ) , despite delaying treatment until the peak of diarrhea ( Fig 3B ) . The effect of MMV665917 treatment on overall health , dehydration , and appetite of C . parvum infected calves was quantified using a standardized scoring system ( Table 1 ) and calculation of the AUC for each parameter . All calves received aggressive supportive care in an attempt to mitigate unnecessary suffering , which limited the magnitude of differences that might be observed between the experimental groups . Nonetheless , there was a strong trend towards improved health with MMV665917 treatment as assessed by each of these secondary clinical outcome measures ( Fig 4 ) .
These studies validate the efficacy of the piperazine-based anti-Cryptosporidium drug lead MMV665917 in a clinical model of disease . This is a critical extension of previous mouse studies , because mice infected with C . parvum do not develop diarrhea . Dairy calves , on the other hand , develop a diarrheal illness very similar to that observed in infants following infection with C . parvum [14] , one of the two main human pathogens . Our data show that MMV665917 is both clinically and microbiologically effective for treatment of cryptosporidiosis in new-born calves . Since C . parvum is also an important pathogen of cattle , these data represent a key step for drug development directed towards treatment of both calves and people afflicted with cryptosporidiosis , and provide a strong rationale for further optimization of the piperazine-based MMV665917 chemotype . It was somewhat surprising that diarrhea did not reduce the fecal or serum concentrations of MMV665917 following oral administration , which may simplify dose optimization . Finally , it should be noted that the method used in this study of housing calves in confined pens is stressful to animals , and therefore , likely immunosuppressive [16] , which further emphasizes the clinical efficacy of MMV665917 . This study has several limitations . Recently published target product profiles for anti-Cryptosporidium drugs specify a typical treatment duration of only 3 to 4 days for most patients ( severely immunocompromised patients may require more prolonged treatment ) [17 , 18] . Thus , additional studies are needed to determine the minimum duration of MMV665917 that is efficacious . Also , only bulls were included due to limited access to heifers , so further studies are needed to address possible sex differences in MMV665917 efficacy . Despite prior studies demonstrating comparable in vitro potency against both C . parvum and the C . hominis TU502 isolate ( Jumani , et al . Submitted manuscript ) , confirmation of in vivo efficacy against C . hominis is also needed , e . g . using the gnotobiotic piglet model [19] . Although no toxicity in animals has been observed , in vitro patch clamp studies demonstrated partial inhibition of the human ether-a-go-go ( hERG ) potassium channel by physiologically relevant concentrations of MMV665917 , which indicates the possibility of cardiac toxicity . Additional safety studies are therefore needed to assess the possibility of cardiotoxicity , and medicinal chemistry optimization to increase potency and selectivity is likely warranted . Although the optimal pharmacokinetic properties for the MMV665917 series ( e . g . high vs . low systemic bioavailability ) remain to be determined , it is also possible that the hERG liability can be addressed by modifications that result in lower oral absorption . In any case , such medicinal chemistry optimization would likely be aided by knowledge of the molecular mechanism of MMV665917 , which remains unknown for both Cryptosporidium and Plasmodium species . Nonetheless , based on its outstanding clinical and microbiologic efficacy and the relative ease of synthesizing it and related compounds , MMV665917 represents an excellent starting point for a full-fledged anti-Cryptosporidium drug lead optimization program . | Cryptosporidiosis is an important cause of life-threatening diarrhea for young children and immunocompromised people , and Cryptosporidium parvum , one of the two main human Cryptosporidium pathogens , is also an important cause of diarrhea in dairy calves . Yet , there are no reliably effective drugs for treating cryptosporidiosis . Anti-Cryptosporidium drug development is complicated by the fact that infected rodents do not develop diarrhea . Here , a dairy calf model of cryptosporidiosis was used to demonstrate that the piperazine-based compound MMV665917 , a compound identified within the open-access Medicines for Malaria Venture “Malaria Box” , reduces both diarrhea and parasite shedding when given once daily for seven days to dairy calves infected with C . parvum . These data establish MMV665917 as one of just several compounds with proven efficacy for treating dairy calves with cryptosporidiosis , and an outstanding lead to develop for humans . | [
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] | 2018 | Clinical and microbiologic efficacy of the piperazine-based drug lead MMV665917 in the dairy calf cryptosporidiosis model |
The initial contact of European populations with indigenous populations of the Americas produced diverse admixture processes across North , Central , and South America . Recent studies have examined the genetic structure of indigenous populations of Latin America and the Caribbean and their admixed descendants , reporting on the genomic impact of the history of admixture with colonizing populations of European and African ancestry . However , relatively little genomic research has been conducted on admixture in indigenous North American populations . In this study , we analyze genomic data at 475 , 109 single-nucleotide polymorphisms sampled in indigenous peoples of the Pacific Northwest in British Columbia and Southeast Alaska , populations with a well-documented history of contact with European and Asian traders , fishermen , and contract laborers . We find that the indigenous populations of the Pacific Northwest have higher gene diversity than Latin American indigenous populations . Among the Pacific Northwest populations , interior groups provide more evidence for East Asian admixture , whereas coastal groups have higher levels of European admixture . In contrast with many Latin American indigenous populations , the variance of admixture is high in each of the Pacific Northwest indigenous populations , as expected for recent and ongoing admixture processes . The results reveal some similarities but notable differences between admixture patterns in the Pacific Northwest and those in Latin America , contributing to a more detailed understanding of the genomic consequences of European colonization events throughout the Americas .
The population history of indigenous peoples of the Americas is of perennial interest to scholars studying human migrations . The Americas were the last continents historically peopled by modern humans , with recent evidence supporting an initial human entry via Beringia after the last glacial maximum [1]–[4] . Despite the absence of a deep written record , abundant archaeological sites and rich anthropometric , cultural , and linguistic variation in the Americas have long facilitated thriving programs of investigation of Native American population history and relationships [1] , [5]–[8] . Population-genetic approaches applied to dense genome-wide datasets have recently expanded the forms of evidence available for studies of human migration [9]–[14] . In the Americas , genomic studies have been of particular value in understanding the diversity of admixture processes that indigenous communities have experienced with non-native populations following European contact [13] , [15]–[21] . Studies have identified considerable variation in the level of admixture among populations , in the level of admixture among individuals within a population , in the contributions from different source populations , and in the magnitudes of the various ancestry contributions at different points in the genome [13] , [15] , [20]–[23] . Most of this genomic work has focused on populations in Latin America and the Caribbean , evaluating the demographic impact of colonizing individuals of European and African descent on local indigenous groups , and relatively few genome-wide investigations have been performed specifically on indigenous North American populations . Owing , in part , to differences in colonization practices between the British and French in North America and the Spanish and Portuguese in Central and South America , North America experienced a substantially different history of admixture [24] . In the Pacific Northwest , extensive contact with non-native populations began relatively recently , with the Russian expansion and the maritime fur trade in the 1700s . These events allowed indigenous communities to initially receive economic benefits from trade without the disruptive effects of colonization [25] . Multiple immigrant groups then entered the region in the 1800s , as Russian Alaska was transferred to the United States , and as borders between the United States and British-controlled Canada were settled . For example , Scandinavians migrating to Alaska were early contributors to the forestry and fishing industries [26] . In addition , the construction of the Canadian Pacific railway between 1881 and 1885 in British Columbia employed numerous Chinese and Japanese immigrants [27] . These immigrant groups had ample opportunity to intermarry with indigenous members of a variety of local communities . To obtain a detailed picture of the genetic landscape of the Pacific Northwest of North America , we generated data on over 600 , 000 genome-wide single-nucleotide polymorphisms ( SNPs ) in 104 indigenous individuals from four coastal communities in Southeastern Alaska and British Columbia and two communities living in interior British Columbia . We combined these data with existing data from other geographic regions that together encompass 64 worldwide populations . This worldwide dataset allowed us to investigate the genetic structure of indigenous populations of the Pacific Northwest both locally and in relation to continental and worldwide geographic scales , and to further analyze the admixture landscape in the region . The results uncover both differences in the admixture patterns seen among indigenous Pacific Northwest populations as well as notable differences from comparable patterns observed in admixture studies of Latin America , illuminating differences in the histories of admixture experienced by Native American populations from across the American landmass .
Various analyses of population structure placed the Pacific Northwest populations in relatively close genetic proximity , suggesting that these populations share an indigenous component of ancestry more recent than their divergence from other groups . Native American populations were distributed from north to south along a single branch of the neighbor-joining tree , as would be expected under a scenario with a common origin for all of the Native American groups followed by a north–south serial-founder model [16] , [28]–[32] , [34] . Hierarchical genetic structure among Native American populations detected using Admixture identified clusters specific to Northern , Central , and Southern indigenous American populations within a broader cluster comprising all Native Americans , as might be expected under the model . In the Pacific Northwest , both our MDS analysis and an Admixture cluster at K = 10 revealed substantial genetic differentiation between coastal and interior populations . It is perhaps plausible that these population groups descend from different groups along separate migratory routes from Beringia into North America [4] , [48] . However , because both population groups clustered together consistently in all other Admixture analyses , and they are placed nearby in MDS plots and in the neighbor-joining analysis , our results provide stronger support for a shared origin for the Pacific Northwest populations , and , after the initial peopling of the region , divergence due to isolation and drift . This scenario is consistent with paleoanthropometric studies that also proposed recent isolation , drift , and ecological differences to explain skeletal differences between coastal and interior individuals in British Columbia [49] , [50] . Genetic diversities among Pacific Northwest populations were higher than expected under a serial-founder model , as the model predicts intermediate levels of diversity between Northeast Asians and Central and South Americans [31] , [32] . Instead , however , heterozygosity levels among Pacific Northwest populations are substantially closer to those of Eurasian populations than to those of Central or South Americans . This result parallels the patterns observed in African Americans and Mexican Americans , two recently European-admixed populations in the Americas , who also showed inflated levels of genetic diversity compared to African and Native American source populations , respectively [9] , [29] , [34] . It is thus possible that admixture events following European contact might explain high genomic diversity in the Pacific Northwest populations in relation to Central and South Americans [16] , [24] , [25] . Our MDS and Admixture analyses produced high mean levels of European admixture in Pacific Northwest populations compared with Native American populations from Central and South America . Indeed , we observed high levels of European admixture in the Tlingit , Tsimshian and Haida populations comparable in magnitude to the recently admixed Mexican American population . This result contrasts with patterns in the Amazonian Karitiana and Surui populations , for which no admixture signals were evident , and with the low levels of European admixture observed in Colombians and Central American groups [13] , [18]–[21] , [23] . Our estimates of the most recent time of admixture support a longer history of European admixture among Central American admixed populations than among Pacific Northwest populations , with the within-population variance of individual admixture estimates across individuals higher in the Pacific Northwest . This result accords with the delayed post-European contact admixture processes in the Pacific Northwest relative to Central and South America [24] , the later arrival of Russian and Northern European migrants in the Pacific Northwest fur trade toward the end of the 1700s , and the later colonization period centered on fishing and canning [25] , relative to the Spanish and Portuguese colonial periods beginning after 1492 . We detected signals of East Asian admixture in several Pacific Northwest populations , particularly the interior Splatsin and Stswecem'c groups . Consistent with previous studies , we observed no signal of genome-wide East Asian admixture in our set of Central and South American populations [28] , [29] , [34] , [51] . It is possible that the East Asian admixture signal in the Pacific Northwest could represent waves of ancient Asian migrations into the Americas prior to European contact , or an inability of Admixture to fully separate genetic signals from similar groups . However , two features of the pattern support the view that it represents recent East Asian admixture . First , high variance in East Asian admixture proportions across individuals within Pacific Northwest populations indicates a relatively short and recent history of East Asian admixture , a pattern uniquely observed in this region of the Americas . Second , the pattern differs noticeably between the coastal and interior groups , two sets of populations that are otherwise difficult to distinguish . Thus , we surmise that the evidence for East Asian admixture reflects the documented history of Chinese and Japanese immigrants to British Columbia working in the mining , railway and cannery industries in the second half of the 19th century [52] , and that these groups had different influences on the coast and in the interior [53] . While our approach using two different methods [43] has provided simple strategies for estimating admixture times , the complexity of the admixture pattern in the Pacific Northwest , likely involving both European and East Asian sources and a different pattern in coastal and interior groups , suggests that simple models may be somewhat limited in applicability to the region . Future theoretical development of admixture models—that , for example , explicitly formulate pre- and post-contact admixture periods—together with approximate Bayesian computation or other techniques that can more fully incorporate admixture patterns into inference of the mechanistic admixture model , will help to enhance understanding of the variable histories of admixture experienced by indigenous American populations , both in the understudied Pacific Northwest and throughout the hemisphere .
We collected DNA samples for 101 individuals from six indigenous populations of British Columbia ( Nisga'a n = 8; Splatsin n = 16 , Stswecem'c n = 15; Tsimshian n = 32 ) and Southeastern Alaska ( Haida n = 12; Tlingit n = 18 ) , and for three Seri individuals from northwestern Mexico ( Figure 1 ) . Collection of the Haida and Tlingit samples was approved by the Institutional Review Board ( IRB #10379 ) at Washington State University , as described by Villanea et al . [54] . Appropriate informed consent and sample collection protocols for the communities from British Columbia and Alaska was approved by Institutional Review Boards at the University of Illinois ( IRB #10538 ) . Each participant from British Columbia and Alaska provided familial anthropology information concerning geographic and tribal affiliation of their maternal and paternal lines . For all individuals and populations , knowledge of family histories , including possible recent admixture events , were obtained through classical familial anthropology interviews . The presence of related individuals in a dataset can influence genetic diversity patterns [40] , [55] . We therefore identified pairs of close relatives in the initial dataset using identity-by-state ( IBS ) allele-sharing and the likelihood approach of Relpair ( v2 . 0 . 1 ) [56] , [57] . Following Pemberton et al . [40] , Relpair was applied to five non-overlapping sets of 9 , 999 SNPs ( the maximum number of markers allowed by Relpair ) in which all SNPs were separated by at least 100 kb . In these analyses , we considered only the 210 , 639 autosomal SNPs that were polymorphic in all seven indigenous populations , using genetic map positions obtained by interpolation on the Rutgers combined physical–linkage map [58] , [59] . We set all putative pairwise relationships to “unrelated , ” the genotyping error rate to 0 . 001 ( a likely overestimate ) , and the critical value for likelihood ratio computation to 100 . We only considered first- and second-degree relationship inferences , as cousin inferences are less reliable than inferences for closer relationships [40] , [56] , [57] . To exclude intra-population relative pairs , separately in each population , we applied Relpair using count estimates of allele frequencies in that population . To exclude inter-population relative pairs , we applied Relpair to the whole dataset using count estimates of allele frequencies in the dataset . We identified 24 intra-population first- and second-degree relative pairs that involved 36 distinct individuals: 11 in the Tsimshian population ( four parent–offspring , two full-sibling , and five avuncular , involving 15 individuals in total ) , six in the Splatsin population ( one parent–offspring , two full-sibling , and three half-sibling , involving eight individuals ) , three in the Stswecem'c population ( one parent–offspring , one full-sibling , and one avuncular , involving five individuals ) , and two each in the Haida ( two parent–offspring , involving four individuals ) and Tlingit ( one parent–offspring and one full-sibling , involving four individuals ) populations . No inter-population pairs of close relatives were identified . To minimize the number of individuals excluded , we first removed from the dataset 11 individuals that appeared in more than one pair . Next , we removed five individuals appearing in only a single pair , selected on the basis of higher levels of missing data . Following the removal of the 16 related individuals from the preliminary dataset containing 565 , 635 autosomal SNPs , we repeated the population-genetic quality control procedure ( Stage 3 , Figure S5 ) and excluded 20 , 914 SNPs monomorphic in the sample of 85 individuals and 339 SNPs with at least 10% missing data . Thus , our final dataset contained 544 , 384 autosomal SNPs with genotypes in 85 unrelated individuals from seven populations ( Table 1 ) . A version of this dataset restricted to the 82 unrelated individuals from six British Columbian and Alaskan populations newly sampled and genotyped here can be requested from R . S . M . for population and evolutionary history studies in accord with the informed consent documents used for this study . To investigate the indigenous populations in relation to genetic variation in other populations , we merged the indigenous Northwest dataset with similar publically available data for the 11 populations in release 3 of HapMap project [60] and the 53 populations represented in the HGDP-CEPH cell line panel . First , we separately prepared and merged the HapMap Phase III and HGDP-CEPH datasets using the pipeline of Pemberton et al . [61] and considering only autosomal SNPs; SNPs on the mitochondrion and on the X and Y chromosomes were excluded . | We collaborated with six indigenous communities in British Columbia and Southeast Alaska to generate and analyze genome-wide data for over 100 individuals . We then combined this dataset with existing data from populations worldwide , performing an investigation of the genetic structure of indigenous populations of the Pacific Northwest both locally and in relation to continental and worldwide geographic scales . On a regional scale , we identified differences between coastal and interior populations that are likely due to differences both in pre- and post-European contact histories . On a continental scale , we identified differences in genetic structure between populations in the Pacific Northwest and Central and South America , reflecting both differences prior to European contact as well as different post-contact histories of admixture . This study is among the first to analyze genome-wide diversity among indigenous North American populations , and it provides a comparative framework for understanding the effects of European colonization on indigenous communities throughout the Americas . | [
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] | 2014 | Patterns of Admixture and Population Structure in Native Populations of Northwest North America |
The Drosophila homolog of Casein Kinase I δ/ε , DOUBLETIME ( DBT ) , is required for Wnt , Hedgehog , Fat and Hippo signaling as well as circadian clock function . Extensive studies have established a critical role of DBT in circadian period determination . However , how DBT expression is regulated remains largely unexplored . In this study , we show that translation of dbt transcripts are directly regulated by a rhythmic RNA-binding protein ( RBP ) called LARK ( known as RBM4 in mammals ) . LARK promotes translation of specific alternative dbt transcripts in clock cells , in particular the dbt-RC transcript . Translation of dbt-RC exhibits circadian changes under free-running conditions , indicative of clock regulation . Translation of a newly identified transcript , dbt-RE , is induced by light in a LARK-dependent manner and oscillates under light/dark conditions . Altered LARK abundance affects circadian period length , and this phenotype can be modified by different dbt alleles . Increased LARK delays nuclear degradation of the PERIOD ( PER ) clock protein at the beginning of subjective day , consistent with the known role of DBT in PER dynamics . Taken together , these data support the idea that LARK influences circadian period and perhaps responses of the clock to light via the regulated translation of DBT . Our study is the first to investigate translational control of the DBT kinase , revealing its regulation by LARK and a novel role of this RBP in Drosophila circadian period modulation .
The Drosophila doubletime ( dbt , a . k . a . discs overgrown , dco ) gene encodes a protein homologous to human casein kinase I isoforms ( CKI ) [1] , [2] , in particular CKIδ and CKIε [3] . It is known that the DOUBLETIME ( DBT/CKIδ/ε , hereafter referred to as “DBT” ) kinase regulates cell proliferation , differentiation and cell polarity by functioning in Wnt [4] , [5] , Hedgehog [6]–[9] , Fat [10]–[13] and Hippo signaling [14] , [15] pathways . Those studies demonstrated roles of DBT in growth , development , organ size determination , and tumor suppression . The kinase is also well known for its role in the core molecular mechanism of the circadian clock ( [1] , [2] , reviewed in [16]–[18] ) . The molecular oscillator regulating locomotor activity rhythms is comprised of a transcription-translation feedback loop wherein accumulation of clock proteins regulates clock gene transcription and protein production . Transcriptional mechanisms are common to the circadian clocks of organisms ranging from cyanobacteria and fungi to plants and animals [18]–[22] , although recent studies have indicated that conserved non-transcriptional clocks mediate certain types of circadian rhythms [23] . Casein kinase I ( CKI ) is required for period determination in vertebrates as well as insects . For example , in hamster and mouse , a gain-of-function mutation of CKIε ( CKIεtau ) , causes shortening of circadian period [24] , [25] whereas inhibition of CKIδ kinase activity in zebrafish disrupts circadian rhythmicity in locomotor activity [26] . In humans , a mutation in the key clock protein PERIOD 2 perturbs its phosphorylation by CKIε and is associated with Familial Advanced Sleep Phase Syndrome ( FASPS ) , as a result of an abnormally short circadian period [27]–[31] . Interestingly , mutations in CKIδ were also found to cause FASPS in humans [32] . In Drosophila , the role of DBT in circadian period determination has been studied extensively . DBT was first shown to regulate PER accumulation [2] , introducing a cytoplasmic lag into the circadian molecular loop . It was later established that DBT promotes progressive phosphorylation of PER , which facilitates interaction between PER and Slimb , an F-box/WD40-repeat protein that helps target PER for degradation in the proteasome [33]–[35] . Many DBT phosphorylation sites in the PER protein have been mapped [36]–[38] . Phosphorylation of residues in the so called “short-period domain” by DBT , gated by phosphorylation of a key residue by another kinase called NEMO/NLK , affects progression of the molecular cycle [39] . Phosphorylation of an N-terminal serine residue ( S47 ) by DBT was identified as a key step in controlling the speed of the clock [40] . DBT is also required for phosphorylation of CLOCK ( CLK ) , another key component of the Drosophila molecular clock [41] , [42] , although it was later found that DBT does not phosphorylate CLK directly but rather plays a non-catalytic role in CLK phosphorylation [43] . Despite extensive studies of DBT function , the mechanisms regulating expression of this protein are largely unknown . In a previous genome-wide study we identified dbt mRNA as a potential target of the LARK RBP , which has been implicated in translational control and clock function [44]–[52] . This suggested the possibility that dbt might be translationally regulated by LARK . Here we describe a detailed study of DBT regulation by LARK . We demonstrate that LARK can bind to and enhance translation of different transcript isoforms of dbt in clock cells of the adult fly head . The effect is most prominent with dbt transcripts RC and RE . Translation of dbt-RC undergoes circadian changes in free-running conditions , whereas translation of dbt-RE is light inducible . Consistent with the known role of DBT in circadian period determination , altered LARK expression in the PDF neurons affects period length , and this effect can be modified by dbt mutations . The role of LARK in modulating circadian period through DBT is further supported by the observation that increased LARK expression delays nuclear degradation of the PERIOD clock protein . Our study is the first to examine translational regulation of the DBT kinase and it supports a role of LARK in the modulation of circadian period .
In a previous genome-wide study , we showed that dbt mRNA , but not other clock mRNAs , was associated with LARK in vivo [44] . The dbt gene produces multiple alternatively spliced transcripts . Earlier versions of genome annotation provided by FlyBase ( up to Release 5 . 30 ) show three splice variants – dbt-RA , dbt-RB , and dbt-RC – that share protein-coding and 3′UTR sequence but differ at the 5′UTR ( Figure S1A ) . However , the most recent annotation ( release R5 . 49 ) included a fourth transcript , dbt-RD , that appears to be identical to dbt-RB but with a longer 3′UTR ( Figure S1B ) . This difference is presumably based on recent genome-wide RNA sequencing data that includes sequence reads mapping to regions that extend beyond the previously annotated 3′UTR . However , we do not believe there is sufficient evidence to distinguish transcript D from transcript B; i . e . , there may be only one transcript with a long 3′UTR . Thus we did not treat dbt-RD as an independent transcript , but instead focused our studies on the dbt RA , RB and RC transcripts . In addition , we found EST evidence suggesting the existence of an unannotated transcript with a unique 5′UTR , likely resulting from an alternative transcription start site . Two ESTs ( GenBank gi 49381530 and gi 103690325 ) align perfectly to the 5′ region of the gene in a manner distinct from all previously annotated transcripts . We named this previously unannotated transcript dbt-RE . Studies described below demonstrate the expression of this novel transcript . To determine if dbt transcripts are associated with LARK , in vivo , we quantified RNAs that co-immunoprecipitated specifically with LARK from head tissue lysates of adult flies . Quantitative Real-Time PCR ( Q-RTPCR ) using primers specific to each isoform demonstrated that dbt transcripts were enriched after anti-LARK immunoprecipitation ( IP ) . Enrichment values , relative to transcript abundance after IP with an unrelated antibody ( anti-EGFP ) were 7 . 7 , 4 . 5 , 6 . 2 and 10 . 2 fold , respectively , for dbt-RA , RB , RC , and RE ( Figure 1A ) . These results demonstrate an association between LARK and all dbt alternative transcripts in vivo . These IP results do not distinguish between direct binding by LARK versus indirect association because of the presence of the RNA binding protein ( RBP ) and dbt mRNAs in the same complex . To test whether LARK can directly bind dbt mRNAs , we conducted UV cross-linking assays [53] using radio-labeled dbt transcripts produced by in vitro transcription ( see Material and Methods ) and a purified recombinant LARK protein containing both RNA Recognition Motifs ( RRMs ) [48] . This analysis showed that LARK binds to dbt mRNAs in a concentration-dependent manner and at concentrations as low as 100 nM ( Figure 1 , B and C ) . In contrast , LARK binding to an unrelated mRNA ( GlutR2 ) was barely discernible at a concentration of 1 µM protein , indicative of specificity ( Figure 1B ) . Thus , LARK can directly bind dbt mRNAs . To test the hypothesis that LARK regulates translation of the DBT protein , we examined the effect of altered LARK expression on DBT abundance . To our surprise , pan-neuronal overexpression of LARK ( in elav-gal4; uas-lark/+ flies ) revealed a novel immunoreactive DBT band that was of lower molecular weight than the previously described protein ( Figure 2A ) . To our knowledge , such a DBT immunoreactive protein has not previously been reported . In our experiments , however , the novel DBT band was consistently observed in all LARK overexpression ( OE ) samples but never in control ( OC ) samples . Furthermore , the band was detected at three different zeitgeber times ( ZTs ) : ZT2 , ZT7 and ZT14 . We note that higher molecular weight bands are also detected by the DBT antibody ( Figure S6 ) with LARK or DBT OE ( seen with DBT OE on a longer exposure ) . As these bands are too big to represent single proteins encoded by dbt mRNAs and only seen with LARK or DBT OE , we think they must represent aggregates of DBT ( see Discussion ) . It is possible that the novel smaller DBT band represents an isoform that , in the absence of increased LARK expression , is normally present at a low undetectable level . To test this idea , we examined head tissue lysates of elav-gal4; uas-dbt/+ flies , which overexpress DBT in all neurons . We found that the novel protein was revealed by DBT overexpression ( Figure 2B ) , indicating that it may represent a rare isoform of the protein . Interestingly , this novel isoform exhibits a diurnal oscillation: in LARK OE flies , it is more abundant at ZT2 than at ZT14 ( Figure 2A ) . Similarly , in DBT overexpressing flies , it can be detected at ZT2 but not ZT14 ( Figure 2B ) . In contrast to LARK OE , LARK knockdown ( KD ) does not produce a detectable effect on DBT protein level when assayed by Western analysis ( Figure 2A ) . We attempted to show that the novel DBT band corresponded to a previously uncharacterized isoform of the kinase by examining null dbt mutants that survive to larval and early pupal stages ( adult null mutants do not survive ) . However , LARK overexpression at these stages did not induce the novel band ( Figure S7 ) . Thus , it may represent an adult-specific form of DBT . To directly assess the effect of altered LARK expression on translation of DBT , we used the Translating Ribosome Affinity Purification ( TRAP ) technique to isolate Ribosome bound RNAs from LARK OE , KD and the respective control flies ( OC and KC ) . The TRAP technique was originally developed in mouse [54] . We and others have adapted the technique for use in Drosophila by constructing transgenic flies carrying a uas-EGFP-L10a construct that expresses EGFP-tagged ribosomes in target tissues when crossed to a GAL4 line; this permits isolation of translating mRNAs from target tissues [55] , [56] . As LARK is known to have a pan-neuronal expression pattern in the adult head [4] , we first generated flies with altered LARK expression in all neurons using elav-gal4 in combination with uas-larkRNAi ( for KD ) or uas-lark ( for OE ) . As indicated previously , knockdown or overexpression of wild-type LARK using these UAS constructs is associated with altered circadian behavioral rhythmicity [49] , [51] . We included the uas-EGFP-L10a transgene in the OE or KD flies to allow isolation of translating mRNAs from all neurons . We found that LARK OE or KD did not significantly affect translation of dbt-RA , RB or RE . However , translation of dbt-RC was significantly increased in these experiments ( Figure 2C , left ) by LARK OE . Based on the knowledge that LARK and DBT both have circadian functions , we next examined the effect of altered LARK level on the translation of dbt transcripts in clock cells . In these experiments , we expressed uas-lark and uas-EGFP-L10a in clock cells using the tim-uas-gal4 driver [57] . In contrast to pan-neuronal LARK OE , overexpression specifically in clock cells promoted translation of all dbt transcripts , with the effect on dbt-RC being the most dramatic ( 8 fold increased; Figure 2C , right ) . LARK KD caused a small but statistically significant decrease in the translation of all transcripts . To test whether the translational changes result from altered abundance of dbt transcripts or changes in translational status , per se , we examined dbt transcript levels in total RNA extracted from control and LARK OE flies . We found that overexpression of LARK in all clock cells of the fly head did not significantly affect the abundance of RA , RB or RE in total RNA samples . However , there was an approximate 2 . 6 fold increase in RC abundance ( Figure S2 ) . Such an increase in abundance cannot account for the observed 8 . 3 fold increase in translation of RC ( Figure 2C , right ) . Thus , it is likely that LARK OE results in changes in dbt-RC translational status . Taken together , the results of these experiments demonstrate that LARK promotes translation of DBT , in particular a previously unidentified DBT isoform . The observation that LARK expression in clock cells had more dramatic effects on dbt than pan-neuronal expression of the protein suggests that regulation of dbt translation by LARK may occur predominantly in clock neurons . An alternative but less likely explanation is that tim-uas-gal4 drives higher expression of LARK than elav-gal4 . However , we observed a similar level of expression for the two drivers when they were used with a uas-GFP reporter transgene . In wild-type flies , LARK shows a circadian oscillation in abundance; the level of LARK is high during the day and low at night [47] . If LARK promotes translation of DBT , then the translational profile of DBT might also display a circadian rhythm . To test this hypothesis , we sampled the translational profiles of the four different dbt transcripts at 4-hour intervals under entrained conditions ( LD 12∶12 ) and during the first 2 days of free-running conditions ( DD ) . We emphasize that the endogenous LARK level was not manipulated in these experiments . We found that translation of dbt-RA displayed a low-amplitude rhythm in LD ( peak to trough change is ∼2 fold ) , whereas dbt-RB and dbt-RC did not display rhythmic changes in translation . In contrast , dbt-RE displayed robust diurnal changes , with an 8-fold difference between trough-to-peak levels in LD ( Figure 3 , left panel; p = 0 . 036 ) . The rhythms of RA and RE were greatly damped or eliminated when flies were released into free-running conditions ( DD1 and 2 ) . Interestingly , translation of dbt-RC appeared to begin cycling in DD , with a trough-to-peak change of about ∼2–3 fold ( Figure 3 , right panel; DD1 , p = 0 . 036 , DD2 , p = 0 . 0003 ) . dbt-RB translation did not exhibit significant rhythmic changes in LD or DD ( Figure 3 ) . Previous studies of total RNA extracted from whole adult head did not find significant circadian cycling of the dbt messages [1] , [58] , although Abruzzi et al . reported a low-amplitude cycling of RC in LD that did not reach their cutoff ( 1 . 4 fold change ) for statistical significance . In agreement with those studies , we did not find significant cycling of the dbt-RC transcript in DD1 or dbt-RE in LD when abundance of these transcripts was examined in total RNA extracted from the same head lysate used in the TRAP assay ( Figure S3 ) . We conclude that RE and RC exhibit translational cycling in LD and DD , respectively . The observations that translation of dbt-RE displays a robust cycle under LD but not DD , and that peak translation occurs shortly after lights-on suggest that its translation might be induced by light . To test this hypothesis , we entrained tim-uas-gal4; uas-EGFP-L10a flies for 4 days under LD 12∶12 conditions and then released them into constant darkness ( DD ) on the fifth day . During the first day of DD , the flies were divided into two groups; at CT12 ( i . e . the beginning of subjective night ) one group received light stimulation while the other was maintained in darkness . We then performed TRAP analysis using head tissues from the two groups of flies and examined translation of dbt-RE at 0 . 5 , 1 , 2 , 3 , 4 and 5 hours after CT12 . As shown in Figure 4 , translation of dbt-RE steadily increased , peaking at 4 hours following light exposure . In contrast , translation of dbt-RE remained relatively unchanged in the control group not exposed to light ( Figure 4A ) . Statistical significance of the result was verified by a two-way ANOVA , which revealed light exposure as a factor influencing changes in translational level ( p = 2 . 91×10−5 ) . Together with the observation that dbt-RE abundance does not cycle in total RNA , this experiment strongly suggests that translation of dbt-RE is induced within clock cells of the adult head by light exposure . We next examined whether the light-induced translation of dbt-RE is affected by altering LARK expression . We asked this question by comparing differences in ribosome-bound dbt-RE levels between flies receiving light stimulation at CT12 ( the beginning of subjective night ) and those maintained in constant darkness . Ribosome-bound RE transcript was examined in LARK knockdown , LARK OE and control flies at CT12 and CT 16 , with or without light stimulation . Relative to controls and LARK OE , LARK knockdown flies had significantly decreased light-induced RE translation ( Figure 4B ) . These results support a role for LARK in the light-induced regulation of dbt-RE . The DBT kinase regulates PER phosphorylation and period of the circadian clock . Mutations that affect DBT level or its kinase function are known to alter period length of locomotor activity rhythms [1] , [2] , [59] . Given the observed effects of LARK expression on dbt , we tested whether alterations of LARK affect circadian period . We employed fly strains carrying a uas-larkRNAi transgene [51] for selective knockdown of LARK in specific subsets of neurons . This transgene was expressed throughout development , because we have not been successful in producing an adult-specific knockdown of LARK [50] . In order to achieve a more effective knockdown , the RNAi transgene was expressed in a background heterozygous for lark1 , a null mutation of the gene [45] . As shown in Figure 5 ( A and B ) and Table S1 , knockdown of LARK in the PDF neurons – important circadian pacemaker cells – caused an approximate 0 . 85 h shortening of circadian period . This effect is caused by specific knockdown by LARK , because the introduction of a uas-lark transgene into the LARK KD background reverted the period shortening ( Figure S4 , Table S1 ) . Further , the effect is likely to be mediated by DBT because the period shortening was also corrected by introducing a uas-dbt transgene ( Figure S4 , Table S1 ) . Predictably , conditional , adult-specific overexpression of LARK had the opposite effect , causing a 1 . 5 h lengthening of period ( Figure 5 , A , C , Table S1 ) . It is of interest that LARK overexpression in this experiment caused period lengthening , because a previous study showed that conditional , high-level LARK overexpression , achieved using two copies each of pdf-gal4 and uas-lark ( Figure 5E , panel d ) , caused arrhythmic behavior [50] . We note that the present study utilized a “milder” level of LARK overexpression , achieved using only one copy each of pdf-gal4 and uas-lark , revealing an effect on period . In addition , overexpression of LARK in this study was conditional and restricted to the adult stage , in contrast to a previous study which showed that mild overexpression of LARK throughout development caused increased arrythmicity rather than a lengthened period [49] . In the current study , the different levels of LARK OE and the effectiveness of LARK KD were validated by immunohistochemistry using anti-LARK antibody ( Figure 5E ) . In contrast to wild-type LARK OE , a mutant LARK protein lacking function RRM domains [48] , did not cause lengthening of period when overexpressed by pdf-Gal4 ( Figure 5 , A , D , Table S1 ) . We note that a previous study demonstrated that the UAS-wild-type and UAS-mutant lark transgenes are expressed at similar levels when driven by the same Gal4 driver [48] . These results indicate that the RNA-binding activity of LARK is required for the observed effects on behavior . To confirm an effect on circadian period in LARK OE and KD flies , we looked at the cycling of PERIOD protein in the PDF neurons in conditions of constant darkness ( DD ) . Abundance and localization of the PERIOD protein were examined every 4 hours for a 24-hour period by immunohistochemistry and confocal imaging . Because the period altering effects are small , especially in the case of LARK KD , we allowed the effect to accumulate for 4 days in DD . On day 4 , the phase of the oscillator should have advanced by almost 4 hours in LARK KD flies , allowing the difference to become detectable when sampling every 4 hours . Indeed , we found that the phase of PER cycling is advanced in KD flies and delayed in OE flies ( Figure S5 ) , consistent with results of the behavioral analyses . To further test the possibility that LARK influences period length by modulating expression of DBT , we investigated genetic interactions between altered LARK expression and chromosomal dbt mutations including dbtL , dbtS , dbtP and dbtAR . We found that overexpression of LARK lengthened period in all the dbt mutant backgrounds tested . Interestingly , the period lengthening effect of LARK OE varied in different mutant backgrounds . The effect was more dramatic in mutants with short period than in mutants with long period . For example , overexpression of LARK caused a lengthening of ∼2 . 5 hour and ∼2 . 6 h , respectively , in the dbtS/+ and dbtP/+ backgrounds . In contrast , it caused only 1 . 1 and 0 . 63 h period lengthening in dbtL and dbtAR backgrounds ( Figure 6 , A and C ) . Such non-additive effects suggest a genetic interaction between lark and dbt . Similarly , knockdown of LARK caused period shortening in all dbt mutant backgrounds , with the effect being most prominent in a long-period background ( dbtAR/+; Figure 6 , B and D ) . Our previous research found that high level LARK overexpression , using two copies each of pdf-gal4 and uas-lark , resulted in complete arrythmicity [50] . Research by others has shown that overexpression of a wild-type form of DBT in clock cells has a minimal effect on period but causes a reduction in rhythmicity [60] . We asked whether the arrhythmic behavior caused by high-level LARK expression is mediated through DBT . To address this question , we generated pdf-gal4/+; uas-lark/uas-dbt flies that carry a single copy of each responder transgene . Such flies were arrhythmic compared to controls that only expressed the uas-dbt or uas-lark transgenes ( Figures 5 and 7 ) , indicative of an interaction between the genes . This interaction required DBT kinase activity , as overexpression of LARK and DBTD132N , a mutant form of DBT devoid of kinase activity [4] did not cause significant arrhythmicity ( Figure 7 ) . In contrast , overexpression of DBTD132N suppressed the period-lengthening effect of mild LARK OE , possibly due to a dominant-negative effect caused by competition of the kinase-dead protein with wild-type protein . The average period for flies overexpressing LARK alone and flies overexpressing both LARK and DBTD132N were 25 . 1±0 . 06 hours and 22 . 67±0 . 11 , respectively ( Table S1 ) . We note that a previous study by Muskus et al . ( 2007 ) showed that expression of a different kinase-dead mutation of DBT ( DBTK38R ) in clock cells caused a lengthened period or arrythmicity [60] . Thus , it is surprising that expression of DBTD132N alone did not have obvious effects on period length or rhythmicity in our experiments ( Table S1 ) . However , Muskus et al drove expression of DBTK38R in all clock cells throughout development using a tim-gal4 driver . In this study we used the pdf-gal4 driver to direct expression of DBTD132N only in LNvs . More importantly , to avoid effects caused by potential developmental defects , we used the TARGET method [61] to confine expressing of DBTD132N to adulthood . These factors may explain the differences between our observations and those of Muskus et al ( 2007 ) . DBT kinase is involved in multiple steps of the sequential phosphorylation of PERIOD , priming the clock protein for ubiquitin-mediated degradation ( reviewed in [18] ) . PER degradation rate is a key determinant of circadian period length ( reviewed in [18] ) . To test the possibility that LARK modulates period length by regulating DBT-dependent PER degradation , we monitored PER nuclear degradation in the PDF-positive large ventral lateral neurons ( l-LNvs ) by immunohistochemistry and confocal imaging . We found that LARK OE caused a reduced rate of PER degradation during the initial 2 . 5 hours after lights on in an LD cycle ( Figure 8 ) . This result suggests that LARK modulation of DBT results in altered PER degradation .
Despite many studies of DBT function in cellular signaling pathways and circadian period determination , little is known about the regulation of DBT itself . In this study we show that translation of dbt transcripts are regulated by a clock-controlled RBP called LARK . We provide direct evidence that LARK promotes the translation of dbt transcripts in clock cells . Western Blot analyses reveal a previously undescribed smaller isoform of DBT promoted by LARK overexpression ( Figure 2 ) . Although we could not examine this smaller protein in null mutants ( see Results ) - to show specificity of the DBT antibody - three observations suggest that it corresponds to a novel DBT isoform . First , LARK can bind to dbt transcripts and overexpression of the RBP promotes the appearance of the novel DBT immunoreactive band . Second , overexpression of dbt , similar to LARK , results in the appearance of the novel protein . Finally , the novel protein shows circadian changes in abundance that are in phase with those of LARK . Together , these findings indicate the existence of a novel DBT isoform , encoded by one or more dbt transcripts that are regulated by LARK . As previously mentioned , LARK or DBT OE are associated with the appearance of higher molecular weight DBT immunoreactive bands in addition to the novel short isoform . ( Figure S6 ) . Individual proteins of these size classes cannot be encoded by known dbt mRNAs . Therefore , they likely represent aggregates of DBT . Their formation might be facilitated by interaction with the short isoform , which we postulate may act as a scaffold due to its lack of a kinase domain . Although we hypothesize that the short isoform is responsible for the period altering effect , our results do not rule out the possibility that these higher molecular weight complexes contribute to the observed phenotypes . As demonstrated by Western analysis , the novel isoform has a slightly lower molecular weight compared to the known isoform of DBT , indicating a shorter amino acid sequence . Since the four alternative transcripts encode the same Open Reading Frame ( ORF ) and differ only in their 5′UTR , it is possible that binding of LARK promotes translation from an AUG , or an unconventional initiation sites such as CUG , GUG , UUG , or ACG , downstream of the conventional start codon . It is known that translation of another target of LARK , E74A , utilizes at least three alternative initiator codons: two minor forms of the protein are initiated at a CUG and an AUG , while the most abundant form initiates at a CUG [62] . Similar to DBT , our previous studies of E74A show that LARK overexpression dramatically increases E74A protein abundance , changing the level from barely detectable to very high [44] . Of note , the mammalian homolog of LARK , RNA Binding Motif Protein 4 ( RBM4 ) , is known to promote cap-independent , internal ribosome entry site ( IRES ) -mediated translation when phosphorylated by the p38 MAPK pathway [63] . It is possible that the smaller isoform of DBT results from IRES-mediated translation . At present , we do not know which dbt transcript expresses the short DBT isoform although all four transcripts are capable of encoding it . We also note that our results do not rule out an alternative but unlikely possibility that LARK OE results in DBT proteolytic cleavage resulting in the smaller isoform . However , the observations that LARK binds dbt RNA and promotes ribosome association of dbt transcripts without causing a significant change in abundance of the larger DBT isoform indicates that LARK may promote translation of the small isoform . As the conserved kinase domain of DBT starts close to the 5′ terminus at amino acid 15 , any alternative initiation site downstream of the original AUG is likely to affect kinase activity . Thus , it is possible that the short DBT isoform has no kinase activity but rather plays a structural role . A non-catalytic role of DBT has been suggested by others in a recent study . Yu et . al . ( 2009 ) found that PER-DBT binding , but not DBT catalytic activity , is required for CLK hyperphosphorylation and transcriptional repression and proposed a model in which DBT plays a novel , noncatalytic role in recruiting additional kinases that phosphorylate CLK , thereby repressing transcription [36] . Our results indicate that both the LARK-induced short isoform and full length wild-type DBT are required to exert the period lengthening effect , as co-expressing a kinase-dead form of full length DBT abolishes the period-lengthening effect of LARK OE ( Figure 7 ) . These results suggest that the short-isoform and full-length kinase may interact to set the speed of the clock . A plausible hypothesis is that the short DBT isoform serves as a non-catalytic subunit which modulates full-length DBT kinase . Thus , the ratio of short to full-length DBT may be important for modification of PER . In a previous genome-wide study we identified many mRNAs that are associated with LARK in vivo [44] . Among these LARK-associated mRNAs , only three others encode proteins that are known to be involved in circadian function: flapwing ( flw ) , no receptor potential A ( norpA ) , and dunce ( dnc ) . We did not detect association of LARK with canonical clock mRNAs ( per , tim , clk , cyc , etc . ) . Thus it seems likely that the effect of LARK on period is mediated by DBT . How might LARK regulate DBT and circadian period ? As already indicated , RBM4 ( mammalian LARK ) is activated and shuttles to the cytoplasm to regulate IRES-dependent translation in response to p38 phosphorylation [64] . Interestingly , evidence suggests that p38 may have roles in circadian clock function [65] , [66] , and it is known to mediate circadian output and/or clock responses to light in several systems [67] , [68] . Thus , the known clock regulation of LARK [47] may , in part , depend on p38-mediated phosphorylation of the protein . In turn , changes in LARK amount or activity might regulate DBT translation , as suggested by our study . Alterations in DBT expression are predicted to modulate circadian period , by affecting either the accumulation or degradation of PER . Our results show that PER degradation in clock neurons is prolonged , in vivo , by increased LARK expression ( Figure 8 ) . PER degradation requires binding of SLIMB , an F-box protein that helps target proteins to the ubiquitin–proteasome degradation pathway [34] , [35]; SLIMB binding to PER requires a series of sequential phosphorylation events on PER [40] . These include phosphorylation at S661 and residues within a so-called “per-short domain” , spanning amino acids S585 to Y601 , to which mutations that shorten period have been mapped ( perS and perT; [69]–[74] ) . Chiu et al . ( 2011 ) have shown that phosphorylation of the per-short domain by the NEMO and DBT kinases ( including S589 , a DBT target residue ) slows down phosphorylation of PER S47 , a critical event for binding of SLIMB and PER degradation [40] . Lack of per-short domain phosphorylation leads to faster degradation of PER and short-period behavioral rhythms [40] . These results are consistent with a previous study suggesting that the per-short domain regulates the activity of DBT against PER [75] . Thus , enhanced or prolonged phosphorylation of this domain may lengthen period . We postulate that increased LARK expression and production of a short , non-catalytic DBT isoform leads to delayed PER degradation and lengthened circadian period by altering the timing of DBT-mediated phosphorylation of the per short domain . The observation that dbtP , which is a hypomorphic allele of dbt , enhances the period lengthening effect of LARK OE ( compare Figure 6 with Figure 5 , also see Table S1 ) suggests that alteration of the short to full-length DBT ratio may be responsible for period lengthening . Interestingly , a mutant form of DBT ( DBTAR ) that was suggested to play a non-catalytic , auxiliary role – similar to our proposal for the DBT short isoform – also causes period lengthening in heterozygotes [75] . Our analysis of DBT regulation revealed a dbt transcript showing light-inducible translation that is affected by LARK levels ( Figure 4 ) . This novel transcript , dbt-RE , shows a translational oscillation that is in phase with LARK abundance in LD conditions and it can be induced by light in dark conditions . Together with the observation that LARK abundance is highest at the beginning of the day [47] , these results suggest that this RNA-binding protein may be light inducible in addition to showing circadian variation . In LD conditions , the light-induced increase in LARK level may up-regulate translation of dbt-RE . Based on the observation that dbt-RE represents an extremely small fraction of all ribosome-associated dbt transcripts ( ∼0 . 56% ) captured by TRAP , it is possible that such a light-induced event occurs only in a small number of adult head clock cells , perhaps only in cells that mediate the light response . Although a role for LARK and DBT in pacemaker light sensitivity has not been reported , our study suggests it may be of interest to explore this possibility .
The following stocks were obtained from the Bloomington Stock Center ( stock number in parenthesis ) : w1118 ( 5905 ) , elav-gal4 ( 458 ) , uas-dbt ( 26269 and 26274 ) dbtP ( 12164 ) and uas-dicer2 ( 24650 ) . uas-lark , uas-larkRRM and uas-larkRNAi were described previously [49] , [51] . uas-EGFP-L10a is a transgenic line generated in our lab that carries a UAS construct for expressing EGFP-tagged mouse ribosomal protein L10a [55] . tim-uas-gal4 was obtained from Dr . Justin Blau , pdf-gal4 was obtained from Dr . Patrick Emery , dbtL , dbtS , dbtAR were provided by Dr . Paul Hardin , uas-dbtD132N was provided by Dr . Marek Mlodzik . Flies were raised in incubators set at 25°C and 60% humidity and a light-dark cycle consisting of 12 hours of light and 12 hours of dark ( LD 12∶12 ) unless specified otherwise . For Western Blot ( Figure 2 ) experiments , genotyppes are: KD , elav-gal4 ( /+ ) ; uas-dicer2/+; uas-larkRNAi/+ . KC , elav-gal4 ( /+ ) ; uas-dicer2/+ . OE , elav-gal4 ( /+ ) ; uas-lark/+ . OC , elav-gal4 ( /+ ) . DBT overexpression , elav-gal4 ( /+ ) ; uas-dbt/+ . Control for DBT overexpression , elav-gal4 ( /+ ) ; +/+ . Note that “elav-gal4 ( /+ ) ” denotes the fact that male flies are hemizygous for elav-gal4 and female flies are elav-gal4/+ . For TRAP experiments , genotypes for examining the effect of altered LARK expression in all neurons are: KD , elav-gal4 ( /+ ) ; lark1 uas-larkRNAi/uas-EGFP-L10a . C , elav-gal4 ( /+ ) ; uas-EGFP-L10a/+ . OE , elav-gal4 ( /+ ) ; uas-lark/uas-EGFP-L10a . Genotypes for examining the effect of altered LARK expression in all clock cells are: KD , w1118; tim-uas-gal4/+; lark1 uas-larkRNAi/uas-EGFP-L10a . C , w1118; tim-uas-gal4/+; uas-EGFP-L10a/+ . OE , w1118; tim-uas-gal4/+; uas-lark/uas-EGFP-L10a ( Figure 2 ) . The genotype for examining circadian ( figure 3 ) or light-induced ( Figure 4 ) translation of dbt transcripts is w1118; tim-uas-gal4/+; uas-EGFP-L10a/+ . For locomotor behavior assays , genotypes are: KD , w1118; pdf-gal4 uas-dicer2/+; lark1 uas-larkRNAi/+ . KC , w1118; pdf-gal4 uas-dicer2/+ . OE , w1118; pdf-gal4/+; Tub-gal80ts uas-lark/+ . OC , w1118; pdf-gal4/+; Tub-gal80ts/+ . OERRM , w1118; pdf-gal4/uas-larkRRM . pdf>dbt alone: pdf-gal4/+; uas-dbt/+ . pdf>dbt with LARK OE: pdf-gal4/+; uas-dbt/Tub-gal80ts uas-lark . pdf>dbtD132N alone: pdf-gal4/+; uas-dbtD132N/+ . pdf>dbtD132N with LARK OE: pdf-gal4/+; uas-dbtD132N/Tub-gal80ts uas-lark . To prevent developmental effects known to be caused by LARK OE , the crosses and progeny were reared at 23°C until the time of experiment , when they were transferred into 30°C to deactivate the protective effect of Tub-gal80ts and allow OE to be achieved . To examine genetic interaction between LARK OE or KD and various chromosomal mutations of dbt , virgin females from either the w1118; pdf-gal4; uas-lark Tub-gal80ts strain ( for OE ) or the w1118; pdf-gal4 uas-dicer2; lark1 uas-larkRNAi/TM2 Ubx strain ( for KD ) were crossed to males of the dbtL , dbtS , dbtP , or dbtAR , respectively , and male progeny of the crosses were used for the behavioral analyses . Polyclonal rabbit anti-LARK antibodies [47] were used for IP of LARK protein . A mono-clonal mouse anti-EGFP ( clone 19C8 from MACF ) , was used as a control for unspecific bindings of RNAs to antibody-coupled Dynabeads . The antibodies were coupled to Dynabeads ( Invigrogen ) according to manufacturer's instruction . Flies of the w1118 strain were entrained to LD 12∶12 for 3 days and then flash frozen in liquid nitrogen at ZT2 . Heads were harvested and homogenized in a mild lysis buffer containing 100 mM KCl , 5 mM MgCl2 , 10 mM HEPES PH 7 . 0 , 0 . 5% Ipegal-CA630 , 1 mM DTT , 1 mM PMSF , and 10 µg/ml protease inhibitor cocktail ( Sigma ) . The homogenates were incubated on ice for 5 minutes and centrifuged at 14 , 000× g for 20 minutes at 4°C . Cleared lysates were incubated with antibody coupled Dynabeads at 4°C for 1 hour . Following incubation , the supernatants were removed and the beads were washed 6 times using a buffer containing 20 mM HEPES-KOH ( pH 7 . 4 ) , 5 mM MgCl2 , 350 mM KCl , 1% IGEPAL-CA630 , and 0 . 5 mM DTT . RNAs were extracted from the immunoprecipation using the Trizol LS reagent ( Invitrogen ) and reverse transcribed into cDNA using Superscript II reverse transcriptase ( Invitrogen ) with random hexamers . The various dbt transcripts in the anti-LARK immunoprecipitated and anti-EGFP immunoprecipitated samples were analyzed by Q-RT-PCR using primers specific to each transcript ( see below ) . RNA transcripts used in the UV cross-linking assays were synthesized in vitro using 32P-UTP and the MEGAscript Kit ( Ambion ) . The cDNA template for dbt was obtained from the Drosophila Genomics Resource Center ( EST clone LD 27173 ) and for GluR2 was obtained from Dr . Joel D . Richter . A LARK N-terminal GST fusion protein containing the N-terminal RNA-binding domains ( two RRM domains and one RTZF ) was synthesized and purified using the Pierce GST Purification Kit . RNA-protein binding reactions were carried out according to [53] . Briefly , 1×105 cpm of in vitro synthesized RNA transcript and varying amounts of LARK-GST fusion protein were added to 2X GR buffer ( 20 mM HEPES , pH 7 . 6 , 100 mM KCl , 2 mM MgCl2 , 0 . 2 mM ZnCl2 , 20% glycerol , 2 mMDTT ) , 10 ng t-RNA , 1 . 2U Rnase OUT ( Life Technologies ) , and 1 mM DTT and incubated on ice for 10 min . followed by RT for 10 min . 50 mg of heparin was added to the mixture followed by UV exposure at 440 mJ for 3 min . RNase A ( 10 ng ) was added and incubated for 30 min at 37°C . The products were resolved by SDS-PAGE and binding was detected using a Typhoon Phosphoimager ( GE Healthcare ) . Flies of designated genotypes were raised at 25°C under standard conditions . Newly emerged adult flies were transferred into an incubator and entrained to LD 12∶12 at 30 . 5°C for 3 full days and then flash froze in liquid Nitrogen at the appropriate zeitgeber times on day 4 . Heads of the frozen flies were harvested and ground into fine powder in liquid Nitrogen . The frozen powder was mixed with a mild lysis buffer ( 100 mM KCl , 5 mM MgCl2 , 10 mM HEPES PH 7 . 0 , 0 . 5% IGEPAL-CA630 , 1 mM DTT , 1 mM PMSF , and 10 µg/ml protease inhibitor cocktail ( Sigma ) , incubated on ice for 5 minutes , and centrifuged at 14 , 000× g for 20 minutes at 4°C . Cleared tissue lysate was obtained after the centrifugation and the concentration of total protein was determined . Approximately 10 ug samples of total protein were loaded onto 12% polyacrylamide gels . Electrophoresis and western blotting were carried out according to standard protocols . The DBT proteins were detected using anti-DBT antibodies provided by Dr . Jeffrey Price ( University of Missouri-Kansas City ) . Flies carrying the uas-EGFP-L10a construct [55] were crossed to appropriate gal4 lines to express GFP-tagged ribosomes in desired cell types . Details of the TRAP method are described in [55] . Briefly , fly tissues were homogenized in a buffer containing 20 mM HEPES-KOH ( pH 7 . 4 ) , 150 mM KCl , 5 mM MgCl2 , 10 µg/ml protease inhibitor cocktail ( Sigma ) , 0 . 5 mM DTT , 20 unit/µl SUPERase . In RNase inhibitor ( Invitrogen ) , and 100 µg/ml cycloheximide . Thirty mM DHPC and 1% IGEPAL-CA630 were added to the cleared tissue lysates . The mixtures were incubated on ice for 5 minutes and cleared again by centrifuging at 14 , 000× g for 20 minutes . The cleared lysates were applied to magnetic beads covered by purified anti-EGFP antibodies and incubated at 4°C with gentle rotating for 1 hour . After the IP , the beads were washed with a buffer containing 20 mM HEPES-KOH , pH 7 . 4 , 5 mM MgCl2 , 350 mM KCl , 1% IGEPAL-CA630 , 0 . 5 mM DTT and 100 µg/ml cycloheximide . RNAs were extracted from the beads using the Trizol-LS Reagent ( Invitrogen ) . Total RNA samples were treated with DNase I ( Invitrogen ) to eliminate potential contamination with genomic DNA . RNAs isolated from TRAP experiments were used directly since these RNAs usually do not carry genomic DNA contamination . Treated total RNAs or TRAP RNAs were primed with random hexamers ( Ambion ) and reverse transcribed into cDNAs using the Superscript II reverse transcriptase ( Invitrogen ) . Quantification of the relative abundance of specific transcripts in the cDNA samples was conducted by Q-RT-PCR using 2X SYBR green PCR Master Mix ( Applied Biosystems ) and specific primers . Data were collected with Strategene Mx3000 or Mx4000 . A pair of primers specific for the Ribosomal Protein 49 ( Rp49 ) gene , which is known to be transcribed and translated at a constant rate throughout the circadian cycle ( Huang and Jackson , unpublished observation ) , was used as an internal reference to account for variation in the input cDNA amount . Sequences for specific primers were: Rp49-F: GCCCAAGATCGTGAAGAAGC , Rp49-R: CGACGCACTCTGTTGTCG , dbt-RA-F: GATGCAAAACAACCCTTCGAATAC , dbt-RA-R: CCCAGGCGATATTTGTTACC , dbt-RB-F: AACGTAAGTGTCGAATTAGAAG , dbt-RB-R: CTGGCACTGTCCTTTCGTCT , dbt-RC-F: GCGACTGTGGCAACTACAAC , dbt-RC-R: CTGGCACTGTCCTTTCGTCT , dbt-RE-F: CGCTGCAGATGCGATAAAAA , dbt-RE-R: GATTTGCGTTGCCTTTCTGG . Locomotor activity was assayed using 2- to 3-day-old males and the Drosophila Activity Monitoring ( DAM ) system ( Trikinetics , Waltham , MA ) . Flies were loaded into activity monitors and placed in incubators set at either 30°C ( for flies carrying Tub-gal80ts ) or 23°C ( for flies not carrying Tub-gal80ts ) , they were entrained to LD 12∶12 for 4–5 days and then released into constant darkness ( DD ) for an additional 7–10 days . Visualization of actograms and the analysis of rhythmicity and period length were performed using a signal processing toolbox [76] within the MATLAB software package ( MathWorks ) . The toolbox analyzes circadian rhythmicity of fly locomotor activity by applying an autocorrelation analysis . The Rythmicity Index ( RI ) is defined as the height of the third peak in the correlogram resulting from this analysis ( counting the peak at lag 0 as the first peak ) . Period length is determined by Fourier analysis [76] . Flies were considered rhythmic if they had a high RI value ( generally greater than 0 . 2 ) as well as obvious rhythmicity by visual inspection of the actogram . To visualize PER cycling in the PDF neurons , adult flies were harvested at appropriate circadian times and fixed in 4% paraformaldehyde solution . Brains were dissected from the heads and washed in PBS and PBS-T ( 0 . 05% Triton X-100 ) . For assessing LARK abundance in PDF neurons , adult flies were harvested at ZT 2 and brains were dissected prior to fixation . After dissection , the brains were fixed in 4% paraformaldehyde solution and then washed in PBS and PBS-T . Immunohistochemistry was carried out according to standard procedure for staining whole mount fly brains . Primary antibodies were used at the following dilutions: Rabbit anti-PER ( 1∶10000 , R . Stanewsky ) , mouse anti-PDF ( 1∶10 , DSHB ) , Rabbit anti-LARK ( 1∶1000 , [47] ) . Secondary antibodies , goat anti-mouse IgG ( Alexa-488 conjugated , Molecular Probes ) and goat anti-rabbit ( Cy3 conjugated or Alexa-488 conjugated , Molecular Probes ) were used at a dilution of 1∶300 and an incubation time of at least 5 hours . Confocal images were acquired from brain whole mounts using a Leica TCS SP2 AOBS microscope within the Tufts Center for Neuroscience Research ( CNR ) Imaging Core . Blind scoring for PER nuclear versus cytoplasmic localization in the s-LNvs was accomplished by using the following scoring system: 0 = no staining in nuclei , 1 = mixture of nuclear and cytoplasmic staining , and 2 = nuclear staining only . To assess the time course of PER degradation in the nuclei of l-LNvs , a custom ImageJ macro program was used to quantify PER immunoreactivity . All l-LNvs in a brain hemisphere of a particular animal were imaged as a 3D stack with optical sections in 1 µm steps under a 63× oil lens objective . The section with the largest cell diameter , i . e . the middle section of the cell , was identified and an ROI was drawn manually outlining the nucleus . Average pixel intensity within the ROI was calculated for each individual l-LNv cell in a brain hemisphere . The value obtained for individual cells were then further averaged among all cells in a same brain hemisphere to get a value for each individual animal . | The CKI family of serine/threonine kinase regulates diverse cellular processes , through binding to and phosphorylation of a variety of protein substrates . In mammals , mutations in two members of the family , CKIε and CKIδ were found to affect circadian period length , causing phenotypes such as altered circadian period in rodents and the Familial Advanced Sleep Phase Syndrome ( FASPS ) in human . The Drosophila CKI δ/ε homolog DOUBLETIME ( DBT ) is known to have important roles in development and circadian clock function . Despite extensive studies of DBT function , little is known about how its expression is regulated . In a previous genome-wide study , we identified dbt mRNAs as potential targets of the LARK RBP . Here we describe a detailed study of the regulation of DBT expression by LARK . We found that LARK binds to and regulates translation of dbt mRNA , promoting expression of a smaller isoform; we suggest this regulatory mechanism contributes to circadian period determination . In addition , we have identified a dbt mRNA that exhibits light-induced changes in translational status , in a LARK-dependent manner . Our study is the first to analyze the translational regulation of DBT , setting the stage for similar studies in other contexts and model systems . | [
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] | 2014 | Translational Regulation of the DOUBLETIME/CKIδ/ε Kinase by LARK Contributes to Circadian Period Modulation |
Spx is a global transcriptional regulator present in low-GC Gram-positive bacteria , including the model bacterium Bacillus subtilis and various human pathogens . In B . subtilis , activation of Spx occurs in response to disulfide stress . We recently reported , however , that induction of Spx also occurs in response to cell wall stress , and that the molecular events that result in its activation under both stress conditions are mechanistically different . Here , we demonstrate that , in addition to up-regulation of spx transcription through the alternative sigma factor σM , full and timely activation of Spx-regulated genes by cell wall stress requires Spx stabilization by the anti-adaptor protein YirB . YirB is itself transcriptionally induced under cell wall stress , but not disulfide stress , and this induction requires the CssRS two-component system , which responds to both secretion stress and cell wall antibiotics . The yirB gene is repressed by YuxN , a divergently transcribed TetR family repressor , and CssR~P acts as an anti-repressor . Collectively , our results identify a physiological role for the YirB anti-adaptor protein and show that induction of the Spx regulon under disulfide and cell wall stress occurs through largely independent pathways .
In its natural habitat , the soil-dwelling bacterium Bacillus subtilis is continuously exposed to stressful conditions that can compromise its survival . To adapt , bacteria must be able to sense the stress and respond accordingly . Adaptation to stress often requires the interplay of multiple signaling pathways and regulators . At the transcriptional level , gene expression is controlled by modulation of the activity of transcription factors , which through precise molecular interactions redirect the activity of RNA polymerase at specific sets of genes [1] . In B . subtilis , for example , the cell envelope stress response is mediated by the individual or coordinated action of extracytoplasmic ( ECF ) sigma factors ( e . g . σΜ , σW , and σX ) [2] , two-component signal transduction systems ( e . g . LiaRS and BceSR ) [3] , and other transcription regulators ( e . g . Spx ) [2–4] . The activity of transcription factors can be regulated by changes in their expression or allosteric regulation of their activity . Adaptation to stress may also involve regulated proteolysis of transcription factors [5] . Proteolysis mediated by the Clp ATP-dependent proteases plays a critical role in regulation , as it permits the selective degradation of specific sets of proteins [5] . The proteins degraded by the Clp proteases generally contain a protein tag , which is recognized by either the protease itself or an adaptor and targets them for degradation [5] . When degradation requires an adaptor , the synthesis of an anti-adaptor protein can antagonize its activity , and allow the stabilization of the target protein [6–8] . In B . subtilis , for example , the proteolysis of the master regulator of competence ComK requires the adaptor protein MecA and the ClpCP protease . The presence of ComS , an anti-adaptor protein , allows ComK accumulation by interfering with the MecA-ComK interaction [8] . Also , in Escherichia coli and Salmonella , a set of anti-adaptors expressed under various environmental conditions ( e . g . phosphate starvation , DNA damage , or magnesium starvation ) permits stabilization , against ClpXP-mediated proteolysis , of the sigma factor RpoS through direct interaction with the adaptor RssB [6 , 7] . The Spx protein is a global regulator in Bacillus subtilis , and other low-GC Gram-positive bacteria ( Phylum Firmicutes ) [9–12] . Induction of the Spx regulon is best understood in the case of disulfide stress , but it is also noted under conditions that result in protein denaturation and misfolding ( i . e . heat shock or ethanol stress ) [9 , 13] . Recently , cell wall stress was also reported to trigger the induction of the Spx regulon [4] . Spx controls the expression of a large number of genes that help the cells to cope with stressful conditions , and includes genes involved in the synthesis of cysteine and bacillithiol , as well as the thioredoxin system , and the ATP-dependent Clp proteases [9 , 14 , 15] . While the functional role of the Spx regulon during disulfide and heat stress is fairly well understood [9 , 13] , its role during cell wall stress is less clear . A complex regulatory network drives the expression , stability , and activity of Spx . At the transcriptional level , the expression of spx is driven from at least three promoters controlled by different sigma factors: σB , σM , and σA [4 , 16–18] . The induction of the σM-dependent promoter ( i . e . PM1 ) is important for activation of the Spx regulon in response to cell wall stress [4] , whereas expression of spx from the intergenic promoters is sufficient to complement an Δspx knockout mutant for diamide resistance [9 , 18] . The functional role of the σB promoter in the induction of the Spx regulon has not yet been defined . Additionally , the protein repressors PerR and YodB modulate the expression of spx in response to hydrogen peroxide and electrophilic compounds , respectively [19] . The activity of Spx is modulated by a redox-sensing switch ( i . e . contains a CxxC motif ) located at its N-terminus [20] , which increases the activity of the protein when oxidized . Oxidation of Spx is , however , not required for the induction of all Spx-regulated genes [4 , 14 , 15] , and thus the requirement for Spx oxidation seems to depend on the specific nature of the stress . It is still unknown , however , the extent to which the oxidation status of Spx impacts the composition of the regulon . Although spx is highly transcribed in exponentially growing cells , Spx levels remain low due to active proteolysis [21] . Spx degradation occurs upon binding of the adaptor protein YjbH to a region near the Spx C-terminus , which targets the protein for degradation via the ATP-dependent protease ClpXP [22–24] . Under disulfide stress , the oxidation of YjbH and ClpX , as well as the aggregation of YjbH , result in a dramatic reduction in Spx proteolysis [22 , 23 , 25]: accumulation of Spx , along with the oxidation of its redox switch , then lead to activation of the regulon . Accumulation of Spx under cell wall stress , by contrast , largely depends on transcriptional up-regulation of spx , although post-transcriptional effects also appear to play a role [4] . Here we demonstrate that , in addition to transcriptional induction of spx by an alternative sigma factor ( i . e . σM ) [4] , stabilization of Spx is also required for full induction of the Spx regulon in response to cell wall stress . Interestingly , this stabilization is mediated by the YirB anti-adaptor protein , which is rapidly induced under conditions of cell wall stress but not disulfide stress . The expression of yirB itself is regulated by the coordinated action of both a two-component system ( i . e . CssRS ) and a TetR-like repressor ( i . e . YuxN ) . Notably , we found that CssR~P activates the yirB promoter by acting as an anti-repressor of YuxN-mediated repression . Finally , we show that activation of the Spx regulon by cell wall stress and disulfide stress takes place through largely independent pathways , providing an example of orthogonality in signal transduction pathways . This study further expands the diversity of regulatory mechanisms known to govern induction of the Spx regulon in response to stress .
Previously we demonstrated that , unlike disulfide stress , induction of the Spx regulon in response to cell wall stress is driven by upregulation of the spx gene through a σΜ-dependent promoter ( i . e . PM1 ) [4] . Consistent with this , cells harboring a non-functional PM1 ( i . e . PM1* ) promoter display a dramatic decrease in both Spx accumulation and induction of Spx-controlled genes in response to cell wall active antibiotics [4] . Over the course of those experiments , however , we noted that even under conditions wherein spx cannot be induced , cell wall stress still led to a slight increase in the concentration of Spx and upregulation of Spx-controlled genes [4] . This suggested that Spx stabilization may also contribute to induction of the Spx regulon . To further define if stabilization is important under cell wall stress , we studied Spx accumulation in cells with conditional expression of spx from an IPTG-inducible promoter ( i . e . Phs-spx ) ( Fig 1A ) . Since these cells are unable to induce spx transcription in response to cell wall antibiotics , an increase in Spx levels might reflect protein stabilization . As seen in the wild-type strain [4] , treatment with different cell wall antibiotics elicited Spx accumulation in the conditional strain ( Fig 1B ) , while the spx mRNA levels were not elevated upon antibiotic treatment ( Fig 1C ) . Induction of the Spx-controlled gene trxB was also observed in response to fosfomycin and vancomycin , but not ampicillin ( Fig 1C ) . In WT , induction of trxB in response to ampicillin is maximal after 20 min of treatment [4] , which likely explains why no induction was observed here . Nevertheless , these results further support our hypothesis that cell wall stress results in increased Spx activity independent of transcriptional induction . Altogether , these observations suggest that both transcriptional and post-transcriptional mechanisms are important for induction of Spx-controlled genes in response to cell wall stress . When overexpressed , the YirB protein functions as an anti-adaptor protein that can inhibit the YjbH adaptor resulting in stabilization of Spx [26] . However , the physiological role of YirB has not been defined , and it is not important under diamide stress conditions [26] . We thus hypothesized that YirB is responsible for stabilization of Spx in response to cell wall stress . To determine if YirB affects Spx accumulation , we measured Spx protein levels in both WT and ΔyirB cells in response to vancomycin stress . Consistent with our hypothesis , deletion of YirB caused a decrease in the overall Spx levels , as well as a change in the dynamics of Spx accumulation: while in the WT strain the Spx protein was rapidly accumulated , cells lacking YirB displayed a significant delay in the accumulation of Spx ( Fig 2A ) . In the absence of YirB , Spx accumulated to generally lower levels ( Fig 2A ) . This decrease in Spx levels was reflected in reduced expression of the Spx-dependent target gene trxB in response to vancomycin treatment ( Fig 2B ) . As expected , ectopic complementation of the yirB null mutation restored the wild-type phenotype ( Fig 2B ) . In the course of these studies , we also observed that cells lacking YirB displayed overall reduced trxA and trxB promoter activity during growth in LB medium ( Fig 2C ) , suggesting that YirB also affects basal expression of Spx-controlled genes in growing cells . As expected , the impact of the deletion of yirB on both trxA and trxB was eliminated in cells lacking the adaptor protein YjbH ( Fig 2D ) . Since YirB is a putative anti-adaptor protein [26] , we reasoned that cells lacking YirB should display reduced Spx stability . To test this idea , we treated log phase cells with vancomycin , incubated the cells for 10 min to allow accumulation of Spx ( and potentially YirB ) , and monitored protein half-life in chloramphenicol treated cells by western blot ( Fig 2E and 2F ) . Under these conditions , the half-life of Spx in WT was ~2 min , whereas in ΔyirB the half-life was reduced to < 1 min ( Fig 2E and 2F ) . Importantly , the decrease in the stability of Spx in ΔyirB cells was not due to abnormally elevated YjbH levels . Indeed , we observed that deletion of YirB led to slightly lower levels of YjbH after 10 min of induction ( i . e . when the Spx chase was carried out ) ( Fig 2G ) , which is consistent with the fact that yjbH is itself an Spx-controlled gene [4 , 14] . The spx gene is under exceptionally complex control , since several promoters ( i . e . PA , PM1 , PM2 , and PB ) [4 , 16–18] and repressors ( i . e . PerR and YodB ) [19] modulate its expression . Induction of spx in response to cell wall stress , for instance , is driven from PM1 as shown in Fig 3A ( right box ) . In order to separate any potential effects of YirB on spx transcription and determine the actual contribution of YirB to Spx accumulation , we studied Spx dynamics in engineered WT and ΔyirB cells featuring conditional expression of spx ( Fig 3A ) . When cells were grown in the presence of a fixed concentration of inducer ( i . e . LB medium + 60 μM IPTG; Fig 3A , scenario i ) , we observed that accumulation of Spx occurred in a vancomycin-dependent fashion ( Fig 3B , left two panels ) , as previously seen ( Fig 1B ) . Deletion of yirB reduced , but did not completely eliminate , the vancomycin-induced accumulation of Spx ( Fig 3B ) . Deletion of yirB also affected induction of trxB ( S1A Fig ) . These results suggest that YirB-dependent stabilization of Spx ( Fig 2E and 2F ) is important for accumulation of Spx and activation of its regulon in response to cell envelope stress . Under cell wall stress the expression of spx is dynamic since the PM1 promoter is induced in response to antibiotic treatment ( Fig 3A , right box ) . To assess the contribution of YirB under conditions wherein spx is induced , we studied the effect of artificial induction of spx on Spx levels in the engineered WT and ΔyirB cells ( Fig 3A , scenario ii ) . For this , cells were grown in LB broth + 20 μM IPTG ( i . e . basal induction levels ) and then treated with inducer to reach 60 μM IPTG , thereby mimicking the effect of antibiotic induction of spx from the PM1 promoter . In the absence of vancomycin , addition of inducer resulted in only a transient accumulation of Spx ( Fig 3C , first panel ) , and this effect was independent of YirB . This suggests that induction of spx from Phs is sufficient for transient accumulation of Spx protein , and the concomitant induction of the σΜ regulon is not required . However , much stronger and long-lasting induction of Spx was observed if there was both an increase in spx transcription and antibiotic treatment ( Fig 3C , left two panels ) . Deletion of yirB resulted in minor differences between WT and ΔyirB under unstressed conditions; however , cell wall stress resulted in increased Spx accumulation and trxB induction in a YirB-dependent fashion ( Fig 3C and S1B ) . Altogether , these results show that YirB stabilizes Spx under cell wall stress , and that activation of spx transcription and Spx stabilization are additive . Further , they suggest that stabilization of Spx can still occur in a YirB-independent fashion . While accumulation of Spx in response to disulfide stress relies on reduced proteolysis [22 , 23 , 25] , Spx accumulation in response to cell wall stress is more complex as it requires both σΜ-dependent spx upregulation [4] and YirB-mediated Spx stabilization . To study how both transcriptional induction and stabilization together contribute to activation of the Spx regulon , we monitored the induction of the trxA and trxB genes using lacZ transcriptional fusions in WT , ΔyirB , PM1* , and ΔyirB PM1* cells . Deletion of yirB or inactivation of PM1 ( i . e . PM1* ) led to a significant decrease in the induction of both fusions . Furthermore , in the ΔyirB PM1* double mutant the trxA and trxB genes were no longer responsive to vancomycin treatment ( Fig 4A and 4B ) . Assessment of the protein levels also provided evidence of additivity , which was more noticeable early after induction ( Fig 2A and Fig 4C ) . These results demonstrate that both transcriptional induction and stabilization are required for full induction of Spx-controlled genes in response to cell wall stress . They also show that the previously observed induction of Spx-regulated genes in absence of PM1 [4] was largely due to YirB . Our time course studies ( Fig 2A ) suggested that YirB is important for the rapid accumulation of Spx early after antibiotic treatment . In support of this , we also noted that cells lacking YirB , yet still able to induce PM1 , displayed a delay in induction of trxA and trxB in response to vancomycin treatment ( Fig 4A and 4B ) . Furthermore , using RT-qPCR , we noticed that whereas the expression of trxB and yjbH ( i . e . two Spx-controlled genes ) was strongly and rapidly induced , with maximal expression 10 min after treatment , σM-dependent induction of spx and the autoregulated sigM gene was not maximal until 20 min after treatment ( Fig 4D ) . The observed dynamics of both accumulation of Spx and induction of Spx-controlled genes therefore reflect both protein stabilization by YirB ( most important early after vancomycin treatment ) and increased transcription of spx ( most important at later times ) . Our current and previous findings [4] suggest that induction of the Spx regulon in response to cell wall stress and disulfide stress may occur through fully independent pathways . First , transcriptional induction of spx is only important under cell wall stress conditions [4]; second , unlike disulfide stress , the redox-sensing switch plays a limited role in induction of Spx-controlled genes in response to cell wall-active antibiotics [4]; and third , YjbH aggregation , which is critical for Spx accumulation under disulfide stress , seems to play no role in Spx stabilization under vancomycin treatment ( S2 Fig ) . Instead , the anti-adaptor protein YirB stabilizes Spx against proteolysis ( Figs 2 and 3 ) . To further determine whether the activation of the Spx regulon occurs through independent pathways , we studied the induction dynamics of trxA and trxB in response to disulfide stress in cells lacking yirB ( and/or PM1 ) ( Fig 4A and 4B ) . Remarkably , in cells treated with diamide , deletion of YirB ( or PM1 , as expected [4] ) had no effect on induction of both trxA and trxB . Likewise , inactivation of both YirB and PM1 had no effect on the responsiveness of both fusions to disulfide stress ( Fig 4A and 4B ) . We noted , however , a slight decrease in the induction of trxA in the ΔyirB PM1* strain ( Fig 4A ) . Altogether , the present evidence suggests that activation of Spx in response to disulfide and cell wall stress takes place through orthogonal pathways ( Fig 4A and 4B ) . We next sought to determine how YirB activity might itself be regulated . First , we monitored yirB mRNA levels under conditions known to induce the Spx regulon including vancomycin ( cell wall stress ) , diamide ( disulfide stress ) , and ethanol treatment [9 , 25] . Remarkably , only vancomycin treatment resulted in a significant induction of yirB , which suggests that the role of YirB is specific to the cell wall stress response ( Fig 5A ) . This may also explain why no differences in induction of the Spx regulon were previously found between WT and ΔyirB under disulfide stress [26] . The yirB gene is located downstream of cssRS and divergently transcribed from yuxN ( see below ) . The cssRS genes encode a two-component system ( TCS ) that is known to respond to secretion stress [27] , and yuxN encodes a putative repressor in the TetR family with yet unknown activity . We reasoned that since yirB and cssRS are genetic neighbors , the CssRS TCS might regulate yirB under cell wall stress . This hypothesis is supported by the fact that up-regulation of two CssRS-controlled genes ( htrA and htrB ) has been previously noted in response to cell wall stress [28 , 29] . Moreover , a global transcriptomic study of B . subtilis cells growing under a variety of conditions showed that the expression of yirB is highly correlated with htrB , which is a divergently transcribed gene regulated by the cssRS TCS [30] . Consistent with our hypothesis , cells lacking CssR were unable to induce yirB upon treatment with vancomycin; ectopic complementation of CssR fully restored the WT phenotype ( Fig 5B ) . Furthermore , point mutations that replaced the conserved aspartic acid in the phosphorylation site of CssR by the amino acid alanine ( i . e . CssRD52A ) completely prevented induction of yirB following vancomycin treatment , further suggesting that the CssRS two-component system is responsible for upregulation of yirB in response to cell wall stress ( Fig 5C ) . Since YirB seems to be most important for the increased accumulation of Spx early after antibiotic stress ( Fig 4 ) , we hypothesized that the CssRS system would be induced rapidly after antibiotic challenge . Indeed , both yirB and htrB mRNAs accumulated rapidly after vancomycin challenge ( Fig 4D and Fig 5 ) . To further characterize the role of CssR in regulation of yirB we isolated RNA from vancomycin treated cells and used 5’ RACE to define the transcription start site . Transcription initiates 51 nt upstream of the start codon , and two putative CssR boxes [31] were apparent just upstream of the -35 region ( Fig 6A and 6B , S3 and S4 Figs ) . We first used promoter truncations ( i . e . PyirB ( x ) -yirB ) to monitor the effect of upstream sequences on yirB mRNA levels ( Fig 6B and 6C ) . Interestingly , truncations that contained either only the RNA polymerase ( RNAP ) binding-site [i . e . PyirB ( -40 ) ] or both the RNAP binding-site and putative CssR BoxII [i . e . PyirB ( -57 ) ] displayed high yirB mRNA basal levels and were unresponsive to cell wall stress . The inclusion of predicted BoxI [i . e . PyirB ( -122 ) and PyirB ( -538 ) ] sufficed to restore the WT phenotype: a low basal level and induction by vancomycin ( Fig 6B ) . Next , we introduced point mutations to disrupt the most conserved positions in BoxI or BoxII . Point mutations in BoxI rendered yirB mRNA basal levels high and unresponsive to vancomycin , while point mutations in the predicted CssRS BoxII had little effect ( Fig 6D ) . The activity of trxB was also affected by the mutations in PyirB ( S5 Fig ) . Since CssR is required for induction of yirB ( Fig 5 ) , we initially hypothesized that CssR would bind to CssR BoxI to activate transcription . However , our promoter truncation analysis reveals that PyirB is highly active in cells in which BoxI is deleted ( Fig 6B and 6C ) , and this is supported by the effect of point mutations ( Fig 6D ) . These observations imply that BoxI is itself a negative regulatory element for PyirB activity . Analysis of this DNA region in B . subtilis , as well as other Bacillus species ( S4 Fig ) , revealed the presence of a conserved palindromic sequence that lies on top of the predicted CssR BoxI ( Fig 6B and S4 ) . Likewise , we noted that a similar palindromic region is present in between positions +6 and +28 relative to PyirB; this palindrome overlapped the divergent yuxN promoter ( S4 Fig ) . These observations suggest a model in which YuxN , a TetR-like repressor , binds to this palindromic sequence as a repressor , both for yirB and its own transcription . The role of CssR in this system could then be as an anti-repressor to alleviate the YuxN-dependent repression by binding to the overlapping CssR BoxI . To test this model , we explored the role of YuxN in regulating expression of both yirB and yuxN . For this , we first studied whether YuxN binds the palindromic sequences . We reasoned that if YuxN binds the palindromes , deletion of YuxN would have no effect on expression from constructs lacking these DNA boxes . Using lacZ transcriptional fusions of truncated PyirB ( as shown in Fig 6H ) , we found this to be the case: deletion of YuxN in WT led to a dramatic increase in beta-galactosidase activity when the promoter contained both DNA boxes ( i . e . see promoter i ) , however yuxN deletion had virtually no effect on the yirB promoters lacking one or both palindromes . Thus , we conclude that the palindromes are indeed YuxN boxes and that these two sites function cooperatively ( Fig 6H ) . Next , we studied whether YuxN regulated the expression of yirB and/or yuxN itself . Deletion of YuxN resulted in a dramatic increase in the basal levels of both yirB and yuxN expression , and ectopic complementation restored the WT phenotype ( Fig 6E ) . These results are consistent with YuxN acting as a repressor of both yirB and yuxN . If CssR functions as an anti-repressor for YuxN , then deletion of cssR should have no effect in a strain lacking YuxN . Indeed , this is the case since PyirB is both fully derepressed and unresponsive to vancomycin in the ΔcssR ΔyuxN strain , as seen for the ΔyuxN mutant ( Fig 6F ) . The cooperative role of the two YuxN boxes in mediating repression of yirB ( Fig 6H ) leads us to speculate that YuxN may form a repression loop that prevents access of RNA polymerase to both the yirB and yuxN promoters . Binding of CssR~P to CssR BoxI likely prevents YuxN binding to the overlapping binding site , alleviates YuxN repression and allows transcription . This model also explains the induction of yuxN in response to cell wall stress ( Fig 6G ) , even though no apparent CssR binding sites are located upstream of PyuxN ( S4 Fig ) .
The accumulation of Spx and the induction of its regulon in response to disulfide stress occurs through reduced proteolysis [22 , 23 , 25 , 32] . Proteolysis is regulated by 1 ) oxidation and aggregation of the adaptor protein YjbH [22 , 25] and 2 ) a decrease in proteolytic activity of the ClpXP protease [32] . In response to cell wall stress , and unlike disulfide stress , transcriptional induction of spx takes place and is required for maximal accumulation of Spx and induction of the regulon [4] . Once the Spx protein is accumulated it primarily remains in the reduced state; reduced Spx is then capable of modulating transcription [4] . Notably , we observed that although transcriptional induction is critical for cell wall stress induction of the Spx regulon , a post-transcriptional event was also implicated in this response ( Fig 1 ) [4] . Here we report that , in addition to transcriptional control [4] , Spx stabilization against ClpXP-mediated proteolysis is also required for full and timely induction of Spx-controlled genes in response to cell wall stress . Remarkably , we found that , unlike disulfide stress , this stabilization during cell wall stress is mediated by the anti-adaptor protein YirB . YirB was originally identified , through a yeast two-hybrid screen for YjbH-interacting proteins , as a small basic protein that was able to modulate Spx protein levels when artificially overexpressed [26] . YirB was found to modulate Spx levels through direct binding to the adaptor protein YjbH , which resulted in reduced binding of YjbH with Spx and therefore reduced ClpXP-mediated Spx proteolysis [26] . Although YirB bound YjbH with high affinity , and its overexpression significantly increased the stability of Spx , YirB did not affect Spx accumulation in response to diamide treatment . This suggested that YirB was likely important under other stress conditions . Cell wall stress indeed provides such a condition , as the regulatory mechanisms that result in induction of the Spx regulon in response to cell wall antibiotics display remarkable differences relative to disulfide stress [4] . Analysis of cells with conditional or native control of spx indeed showed that cells lacking YirB display reduced accumulation of Spx under both cell wall stress and active growth ( Figs 2 , 3 and 4 ) . The yirB gene lies upstream of the cssRS two-component system , and divergent from a gene encoding a putative transcription factor YuxN , a repressor protein of the TetR family . The genetic proximity between yirB and cssRS , as well as the correlation in the expression database between htrB , a CssRS-controlled gene , and yirB rendered the CssRS TCS as an attractive candidate for regulation of yirB under cell wall stress [30] . Genetic and transcriptomic analyses of the expression of yirB revealed that CssRS is indeed required for the transcriptional induction of yirB under cell wall stress ( Fig 5 ) . Additionally , we found that YuxN represses yirB , and CssR~P appears to be required as an anti-repressor to antagonize YuxN ( Fig 6 ) . In agreement with previous findings [26] , diamide treatment did not lead to induction of the yirB gene , nor did deletion of yirB have a significant impact on the induction of trxB in the presence of diamide ( Fig 4 ) , suggesting that the stabilization of Spx mediated by YirB represents a hallmark of cell wall stress . The CssRS TCS has shown to be induced by hypersecretion of soluble proteins such as the α-amylase , and therefore has been long associated to protein secretion stress [27 , 33] . The specific molecular signals that lead to its induction , however , are not yet fully understood [33] . Interestingly , cell wall stress also led to induction of CssRS , as upregulation of htrB and yirB took place following vancomycin treatment . Previous transcriptomic studies also revealed induction of htrB in response to cell wall stress [28 , 29] . We hypothesize that two events might potentially result in induction of CssRS under cell wall stress . First , the induction of regulons such as σM , σW , or LiaRS ( which include several lipoproteins and membrane proteins ) might lead to secretion stress . Indeed , mutants lacking σW displayed reduced induction of the CssRS regulon , however mutants lacking σM or LiaR exhibited increased CssRS activity ( S6 Fig ) . Alternatively , protein aggregation might occur as a direct effect of cell wall damage under antibiotic treatment . Further studies are required to unveil the underlying mechanisms . Induction of Spx may be advantageous under secretion stress since Spx controls the expression of protein chaperones and proteases [14] . The induction of the Spx regulon in response to cell wall stress in B . subtilis thus involves the timely expression of spx itself by σΜ ( an ECF sigma factor ) and the anti-adaptor yirB by CssRS ( a two-component system ) ( Fig 7 ) . YirB is more important for early induction of the regulon , while upregulation of spx appears to be more important in later stages ( Fig 7 ) . Although the role of Spx in adaptation to cell wall antibiotics remains undefined , this study provides further evidence of the regulation mechanisms that control its induction . Importantly , the regulatory mechanisms that govern the induction of the Spx regulon in response to cell wall stress and disulfide stress take place through largely independent pathways , and thus provide a notable example of orthogonality in signal transduction systems . Our findings suggest a critical role of YirB in the activation of the Spx regulon; however , accumulation of Spx still occurs in cells lacking YirB ( Figs 3 and 4 ) , suggesting that further mechanisms are at play .
All bacterial strains are listed in Table 1 . Bacillus subtilis strains ( all based on the B . subtilis 168 wild-type ) were grown under standard conditions: lysogeny broth ( LB ) ( 10 g tryptone , 5 g yeast extract and 5 g NaCl per liter ) broth at 37°C with vigorous shaking , unless otherwise stated . Escherichia coli DH5α was used for plasmid construction . Antibiotics were added to the growth medium when appropriate: 100 μg ml-1 ampicillin for E . coli , and 1 μg ml-1 erythromycin plus 25 μg ml-1 of lincomycin ( MLS , macrolide-lincomycin-streptogramin B resistance ) , 10 μg ml-1 chloramphenicol , 100 μg ml-1 spectinomycin , and 10 μg ml-1 kanamycin for B . subtilis . The knockout mutants were obtained from BGSC ( Bacillus Genomic Stock Center ) , and the erythromycin cassette removed using the plasmid pDR244 [34] . The strains with clean deletions in the yirB , cssR and yuxN genes were constructed by removing the erythromycin resistance cassette from the strains BKE33029 , BKE33010 , and BKE33030 using the pDR244 plasmid . The BKE knockout mutant strains , the pDR244 plasmid , as well as the transformation method were obtained from the BGSC ( Bacillus Genomic Stock Center ) . The complementation of yirB was obtained by PCR amplification of the coding sequence and promoter region with the primers DR242 and DR244 ( all primers used are in S1 Table ) , which were cloned into the EcoR1 and HindIII restriction sites in pDG1662 , which integrates into the amyE locus ( BGSC ) . Similarly , complementation of cssR ( primers DR264 and DR259 ) and yuxN ( primers DR387 and DR388 ) was done by integration of corresponding pDG1662 derivatives . The point mutation in the CssR phosphorylation site was obtained using the mutagenic primers DR278 and DR279 , which were used for overlap PCR along with the primers DR264 and DR259 . The fragment containing the mutation was cloned into pDG1662 . The PtrxB-lacZ reporter was constructed by PCR amplification of the trxB promoter ( primers DR112 and DR107 ) and inserted into pDG1663 ( BGSC ) , which integrates at the thrC locus . The vector was amplified using DR104 and DR113 , digested with DpnI , and used for Gibson cloning . Similarly , the PtrxA-lacZ , PyirB-lacZ , and PyuxN-lacZ transcriptional fusions were constructed by PCR amplification of the promoter using the primers DR404 and DR405 , DR242 and DR243 , and DR387 and DR408 , respectively . The fragments were cloned into the pDG1663 vector . All constructions were verified by PCR and sequencing . For construction of the yirB promoter truncations the forward primers DR347 , DR348 , DR349 , DR350 and DR242 with EcoRI restriction site , and the reverse primer DR244 with HindIII restriction site were used to amplify the different fragments . For mutagenesis of the predicted CssRS boxes the mutagenic primers DR305 and DR306 , and DR340 and DR341 were used . The primers DR242 and DR244 were used as external primers . The inserts were cloned into pDG1662 . All constructions were verified by PCR and sequencing . For construction of the truncations in Fig 6H , the promoter regions were amplified using the primers: i ) DR349 and DR431 , ii ) DR349 and DR430 , iii ) DR350 and DR431 , and iv ) DR350 and DR430 . The fragments were then cloned into pDG1663 by restriction cloning . All constructions were verified by PCR and sequencing , and then transformed in HB18501 , HB18506 , HB23044 , and HB23078 to produce the strains HB23171-HB23186 . A total of 5 ml of cells were collected , washed in PBS , and resuspended in 150 μl of disruption Complete EDTA-free Protease Inhibitor Cocktail . The cells were disrupted by sonication , and then centrifuged for 15 min at 13 , 500 rpm at 4°C . The soluble fraction was collected and quantified using the Bradford Assay . Reducing sample buffer was added to the protein extract , and then 5 μg of protein were loaded in a 4–20% SDS-PAGE . Proteins were transfer onto a PVDF membrane using the TransBlot Turbo Transfer System ( Bio-Rad , USA ) . The membrane was blocked using 5% protein blotting blocker dissolved in TTBS for 1 h . at RT . Then , the primary antibodies were resuspended in 0 . 5% protein blotting blocker dissolved in TTBS and incubated for 16 h at 4°C . Finally , an anti-rabbit HRP-conjugated secondary antibody was added and incubated for 2 h at RT . The membrane was revealed using the Clarity Western ECL substrate and visualized in a Gel documenter . Protein fractionation was performed as previously described [25] . For quantification of Spx , the intensity of the bands was measured using the Image Lab 5 . 2 . 1 software ( Bio-Rad , USA ) The cells were grown until OD600 reached ~0 . 5 . Then , cells were treated or not with different chemicals , and incubated at 37°C with agitation . After specific time points , samples were taken , washed twice in PBS , and finally resuspended in 900 μl of Z buffer ( 60 mM Na2HPO4 , 40 mM NaH2PO4 , 10 mM KCl , MgSO4•7H2O ) supplemented with 400 μM DTT . Optical density at 600 nm was measured , and then the cells were lysed using 100 μg ml-1 lysozyme at 37°C for 30 min . Next , 200 μl of 4 mg ml-1 ONPG were added to the lysate , and the reaction was incubated at 28°C until the samples produced a visible yellow color . The reaction was stopped by adding 500 μl of 1 . 0 M Na2CO3 . The absorbance was then measured at 420 nm and 550 nm , and β-galactosidase activity was determined using the following equation: Miller Units = 1000*[OD420-1 . 75*OD550]/ ( t*v*OD600 ) , where t is time in minutes and v is the volume of culture used in the reaction . It is important to note that the values of β-galactosidase activity after treatment with cell wall active antibiotics might underestimate the effect of the drug on gene expression . This result was previously noted using another stable protein reporter ( i . e . GFP ) and is due to partial lysis elicited by antibiotic treatment . RNA was isolated using the hot phenol-chloroform method as previously described [4] . RNA concentration and purity were determined using spectrophotometry , while RNA integrity was checked using denaturing agarose gels . Northern blot was performed on nylon membranes using radiolabeled RNA probes as previously described [4] . The yirB RNA probe was obtained using the primers P45 and DR282; the htrB probe was generated using the primers P47 and DR283; and the spx probe was obtained using the primers DR319 and DR320 . The RT-qPCR was performed as previously reported [4] . The primers used for spx were P11 and P12 , for sigM were P31 and P32 , for trxB were P13 and P14 , for yjbH were P17 and P18 , for gyrA were P33 and P34 , for yirB were P45 and P46 , for htrB were P47 and P48 , and for murAA were P3 and P4 . In order to determine the stability of Spx in WT and ΔyirB , cells were grown on 50 ml of LB broth up to OD600 = 0 . 5 . Then vancomycin was added to a final concentration of 1 μg ml-1 to induce the stress response , cells were incubated for 10 min at 37°C with shaking , and then pre-warmed chloramphenicol [100 μg ml-1 , final concentration] was added to stop protein synthesis . Samples ( 1 . 5 ml ) were taken after 0 , 1 , 2 , 3 , and 5 min , and proteolysis was stopped by mixing the cells with 150 μl of pre-chilled 100% trichloroacetic acid ( TCA ) . Cell suspensions were centrifuged at 13 , 500 rpm for 10 min at 4°C , and the pellet was washed twice with ice-cold acetone in order to remove all TCA . The cell pellets were air dried for 10 min , resuspended in 130 μL of solubilization buffer ( 1% SDS , 1 mM EDTA , 100 mM Tris-HCl , pH 8 . 0 ) , and sonicated . A volume of 5 μl of the protein sample was load in a 4–20% SDS-PAGE gel , and western blot was carried out as previously described . Cells were grown up to OD600 = 0 . 5 and treated with 1 μg ml-1 vancomycin . After 10 min of incubation , 5 ml of sample were collected , and RNA was isolated using the RNeasy Kit ( Qiagen ) following manufacturer’s instructions . The RNA was treated with Turbo DNase , and then purified by phenol-chloroform extraction . The RNA was quantified using a Nanodrop , its purity assessed by the 260/280 ratio , and integrity monitored by agarose gel electrophoresis . A total of 1 μg of RNA was reverse transcribed using the P46 primer and the Reverse Transcription Reagents ( Thermo Fisher Scientific , US ) following manufacturer’s instructions . The cDNA was column purified and then treated with the terminal transferase enzyme using CTP to add a homopolymeric cytosine tail at the 3’ end . Then , the cDNA was PCR amplified using the abridged anchor primer ( AAP ) and DR288 primers by using a touchdown PCR followed by a conventional PCR . The PCR product was verified by electrophoresis and sequenced using the DR289 primer . | Bacillus subtilis Spx is the founding member of a large family of redox-stress sensing transcriptional regulatory proteins , and Spx orthologs are important for oxidative stress and virulence in several Gram-positive pathogens . Spx controls a large regulon in response to disulfide stress . Disulfide stress induces the Spx regulon through post-translational events that involve both stabilization of Spx against proteolysis and protein oxidation . We previously reported that genes in the Spx regulon are also induced in response to antibiotics that target the synthesis of the bacterial cell wall . Interestingly , we show that this induction is mechanistically distinct from disulfide stress as it involves transcriptional induction of spx by an alternative sigma factor . We show here that stabilization of Spx also requires a novel anti-adaptor protein , YirB , which prevents Spx degradation by binding to and inhibiting the activity of the adaptor protein YjbH . Induction of spx and Spx stabilization are both required for full and timely induction of the genes in the Spx regulon in response to cell wall stress . We further show that induction of the genes in the Spx regulon in response to either cell wall stress or disulfide stress takes place through largely independent pathways . | [
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] | 2018 | Stabilization of Bacillus subtilis Spx under cell wall stress requires the anti-adaptor protein YirB |
The C . elegans AWC olfactory neuron pair communicates to specify asymmetric subtypes AWCOFF and AWCON in a stochastic manner . Intercellular communication between AWC and other neurons in a transient NSY-5 gap junction network antagonizes voltage-activated calcium channels , UNC-2 ( CaV2 ) and EGL-19 ( CaV1 ) , in the AWCON cell , but how calcium signaling is downregulated by NSY-5 is only partly understood . Here , we show that voltage- and calcium-activated SLO BK potassium channels mediate gap junction signaling to inhibit calcium pathways for asymmetric AWC differentiation . Activation of vertebrate SLO-1 channels causes transient membrane hyperpolarization , which makes it an important negative feedback system for calcium entry through voltage-activated calcium channels . Consistent with the physiological roles of SLO-1 , our genetic results suggest that slo-1 BK channels act downstream of NSY-5 gap junctions to inhibit calcium channel-mediated signaling in the specification of AWCON . We also show for the first time that slo-2 BK channels are important for AWC asymmetry and act redundantly with slo-1 to inhibit calcium signaling . In addition , nsy-5-dependent asymmetric expression of slo-1 and slo-2 in the AWCON neuron is necessary and sufficient for AWC asymmetry . SLO-1 and SLO-2 localize close to UNC-2 and EGL-19 in AWC , suggesting a role of possible functional coupling between SLO BK channels and voltage-activated calcium channels in AWC asymmetry . Furthermore , slo-1 and slo-2 regulate the localization of synaptic markers , UNC-2 and RAB-3 , in AWC neurons to control AWC asymmetry . We also identify the requirement of bkip-1 , which encodes a previously identified auxiliary subunit of SLO-1 , for slo-1 and slo-2 function in AWC asymmetry . Together , these results provide an unprecedented molecular link between gap junctions and calcium pathways for terminal differentiation of olfactory neurons .
The nervous system generates a tremendous diversity of cell types that enable formation of functional neural circuits for information processing and mediating behaviors . Cellular diversity is especially important in the developing sensory system as it allows animals to detect different cues in the environment . However , the molecular mechanisms that generate neuronal diversification are only partly understood . One way to generate cellular diversity in the nervous system is to specify different fates and functions of individual cell types across the left-right axis . Left-right asymmetry in the nervous system is present throughout the animal kingdom [1–3] . For example , anatomical and functional asymmetries in the human nervous system have been described , such as the greater size of the planum temporale in the left hemisphere , and the localization of language to the left hemisphere of the brain [4] . Defects in brain asymmetry have been correlated with various neurological diseases such as dyslexia and schizophrenia [5] . In the C . elegans nervous system , two pairs of head sensory neurons display molecular and functional asymmetries: the ASE taste neurons and the AWC olfactory neurons [6–9] . The left and right AWC olfactory neurons appear symmetric at the anatomical and morphological level . However , the two AWC neurons differentiate asymmetrically into two distinct subtypes , one default AWCOFF and one induced AWCON , at both molecular and functional levels in late embryogenesis [10–12] . The AWCON subtype expresses the G-protein coupled receptor ( GPCR ) gene str-2 and functions to detect the odorant butanone [11 , 12] . The AWCOFF subtype expresses the GPCR gene srsx-3 and functions to sense the odorant 2 , 3-pentanedione [12 , 13] . AWC asymmetry is stochastic , such that the AWCON subtype is induced on the left side of the animal in 50% of the population and on the right side of the animal in the other 50% [11] . AWC asymmetry is maintained throughout the life of an animal [11 , 14 , 15] . The default AWCOFF subtype is specified by a calcium-activated protein kinase pathway . In this pathway , calcium entry through voltage-gated calcium channels ( the pore-forming α1 subunits UNC-2/N-type or EGL-19/L-type and the regulatory α2δ subunit UNC-36 ) activates a kinase cascade that consists of UNC-43 calcium/calmodulin dependent protein kinase ( CaMKII ) , the TIR-1 ( Sarm1 ) adaptor protein , NSY-1 MAP kinase kinase kinase ( MAPKKK ) , and SEK-1 MAPKK [10 , 11 , 16 , 17] . TIR-1 assembles a calcium-signaling complex containing UNC-43 ( CaMKII ) and NSY-1 ( MAPKKK ) at postsynaptic sites in the AWC axons , in a manner dependent on microtubules and the kinesin motor protein UNC-104 , to promote the AWCOFF subtype [10 , 18] . Intercellular calcium signaling through a transient embryonic neural network , formed between AWC and other neurons via the NSY-5 gap junction protein innexin , coordinates precise AWC asymmetry [19] . In addition , NSY-5 and the NSY-4 claudin-like protein function in parallel to antagonize calcium signaling through mir-71-mediated downregulation of tir-1 expression in the AWCON subtype [20–22] . However , the mechanism by which NSY-5 gap junctions and NSY-4 claudin suppress unc-2/unc-36 and egl-19/unc-36 calcium signaling to induce the AWCON subtype is only beginning to be understood . The ky389 and ky399 alleles were identified from a forward genetic screen for mutants with two AWCON neurons ( 2AWCON phenotype ) [11] . The ky389 and ky399 mutations were revealed as gain-of-function ( gf ) alleles of slo-1 in a study demonstrating a central role of slo-1 in behavioral response to ethanol [23] . slo-1 encodes a conserved voltage- and calcium-activated large conductance BK potassium channel [24 , 25] . Activation of SLO-1 ( Slo1 ) channels causes hyperpolarization of the cell membrane , thereby reducing cellular excitability and limiting calcium entry through voltage-gated calcium channels [26] . The 2AWCON phenotype of slo-1 ( gf ) mutants suggests a sufficient role of slo-1 ( gf ) in promoting AWCON . However , the effect of slo-1 loss-of-function mutations on AWC asymmetry and the mechanism by which slo-1 functions to control AWC asymmetry remained unaddressed . Here we demonstrate that both slo-1 and slo-2 BK channels are necessary for the establishment of AWC asymmetry . We show that slo-1 and slo-2 act redundantly downstream of nsy-5 ( innexin gap junction protein ) and in parallel with nsy-4 ( claudin ) to antagonize the function of unc-2 and egl-19 ( voltage-gated calcium channels ) in the induced AWCON subtype . Asymmetric expression of slo-1 and slo-2 in the AWCON neuron , which is dependent on NSY-5 and NSY-4 , is necessary and sufficient for AWC asymmetry . In addition , SLO-1 and SLO-2 BK channels localize close to UNC-2 and EGL-19 voltage-gated calcium channels , suggesting that SLO channels may inhibit calcium channels through functional coupling and negative feedback . Our results also suggest that slo-1 and slo-2 may regulate AWC communication to control AWC asymmetry through modulating UNC-2 synaptic puncta and synaptic vesicle clustering . Thus , our study identifies an unprecedented role of SLO BK potassium channels in mediating transient gap junction signaling for inhibition of a calcium channel-activated kinase cascade in terminal differentiation of olfactory neurons .
Wild-type animals have one default AWCOFF neuron , expressing the GPCR gene srsx-3 , and one induced AWCON neuron , expressing the GPCR gene str-2 ( Fig 1Ai and 1B ) . Both slo-1 ( ky389gf ) and slo-1 ( ky399gf ) mutations resulted in expression of the AWCON marker str-2 in two AWC neurons ( 2AWCON phenotype ) ( Fig 1Aii , 1B and 1C ) , as shown previously [11] . Both slo-1 ( ky389gf ) /+ and slo-1 ( ky399gf ) /+ heterozygous animals displayed a less penetrant 2AWCON phenotype ( Fig 1B ) , confirming their characterization as dominant gain-of-function mutants . We set out to further characterize the AWC phenotypes of slo-1 ( gf ) mutants . We found that the AWCOFF marker srsx-3 was not expressed in either of the AWC neurons of slo-1 ( gf ) mutants ( Fig 1Aii and 1B ) , consistent with the 2AWCON phenotype of the mutants ( Fig 1Aii and 1B ) . In addition , overexpression of slo-1 ( T1001Igf ) and slo-1 ( E350Kgf ) , containing ky389gf and ky399gf mutations , respectively , in AWC in a wild-type background also caused a strong 2AWCON phenotype ( 73%-75% ) ( Fig 1B ) . However , overexpression of wild-type slo-1 only caused a very weak 2AWCON phenotype ( 1% ) when injected at the same concentration as the slo-1 ( T1001Igf ) and slo-1 ( E350Kgf ) transgenes ( Fig 1B ) . Our results are consistent with the previous electrophysiological study suggesting that slo-1 ( ky389gf ) and slo-1 ( ky399gf ) mutations result in increased SLO-1 channel activity in dopaminergic neurons [23] . Although slo-1 ( gf ) mutants caused a strong 2AWCON phenotype , we found that loss-of-function ( lf ) mutations in slo-1 did not display any defects in AWC asymmetry ( Fig 1B and 1C ) . This suggests that slo-1 may function redundantly with other genes to establish AWC asymmetry . Since slo-2 encodes the only other calcium-activated SLO-like potassium channel in C . elegans and its expression overlaps with slo-1 [24 , 27 , 28] , we hypothesized that slo-1 and slo-2 may function redundantly to control AWC asymmetry . Similar to slo-1 ( lf ) mutants , slo-2 ( lf ) mutants did not exhibit abnormalities in AWC asymmetry ( Fig 1B and 1D ) . However , slo-1 ( eg142lf ) ; slo-2 ( ok2214lf ) double mutants had a complete penetrance of two AWCOFF neurons ( 2AWCOFF phenotype ) : the expression of the AWCON marker str-2 was lost and the AWCOFF marker srsx-3 was expressed in both AWC neurons ( Fig 1Aiii and 1B ) . Together , these results suggest that slo-1 and slo-2 have essential and redundant roles in promoting the AWCON subtype . To determine whether slo-1 and slo-2 affect general AWC fate , we examined the expression of two general AWC markers , the guanylyl cyclase gene odr-1 and the homeodomain protein encoding gene ceh-36 , both of which are expressed in both AWC neurons in wild-type animals . Both slo-1 ( ky399gf ) and slo-1 ( eg142lf ) ; slo-2 ( ok2214lf ) double mutants displayed normal expression of odr-1 and ceh-36 ( Fig 1B ) , suggesting that general AWC identity is not affected by the mutations . The 2AWCON phenotype of slo-1 ( gf ) mutants and the 2AWCOFF phenotype of slo-1 ( lf ) ; slo-2 ( lf ) double mutants ( Figs 1Aii , 1Aiii , 1B and 2A ) indicate that the two BK potassium channels function to promote the induced AWCON subtype . To shed light on how slo-1 and slo-2 promote AWCON , we investigated where they are located within the AWC asymmetry pathway by generating double and triple mutants of slo-1 , slo-2 , and other genes previously implicated in AWC asymmetry ( Fig 2A ) . The slo-1 ( gf ) 2AWCON mutants were crossed with 2AWCOFF mutants including nsy-5/innexin ( lf ) , nsy-4/claudin ( lf ) , unc-43/CaMKII ( gf ) , and tir-1/Sarm1 ( gf ) [11 , 18 , 20 , 21] . The 2AWCOFF phenotype of nsy-5 ( lf ) mutants was completely suppressed by slo-1 ( gf ) mutants ( Fig 2A ) , suggesting that slo-1 acts downstream of nsy-5 gap junctions to specify AWCON ( Fig 2B ) . nsy-4 ( lf ) ; slo-1 ( gf ) double mutants had mixed 2AWCON and 2AWCOFF phenotypes ( Fig 2A ) , suggesting that slo-1 acts in parallel with nsy-4 claudin in promoting AWCON ( Fig 2B ) . Furthermore , the 2AWCON phenotype of slo-1 ( gf ) was nearly completely suppressed by unc-43 ( gf ) and tir-1 ( gf ) mutations ( Fig 2A ) ; the 2AWCOFF phenotype of slo-1 ( lf ) ; slo-2 ( lf ) double mutants was almost completely suppressed by the unc-43 ( lf ) mutants ( Fig 2A ) , which is consistent with the previous notion that slo-1 acts upstream of unc-43 ( CaMKII ) [16] ( Fig 2B ) . Since our genetic results put slo-1 and slo-2 ( BK potassium channels ) at a position similar to unc-2/unc-36 and egl-19/unc-36 ( voltage-gated calcium channels ) in the AWC asymmetry pathway , we examined the genetic interaction of slo-1 and slo-2 with unc-36 . unc-36 ( e251lf ) mutants have a strong 2AWCON phenotype [11] ( Fig 2A ) and were crossed into the slo-1 ( lf ) ; slo-2 ( lf ) 2AWCOFF mutants . We found that the 2AWCON phenotype of unc-36 ( lf ) and the 2AWCOFF phenotype of slo-1 ( lf ) ; slo-2 ( lf ) were significantly mutually suppressed in unc-36 ( lf ) ; slo-1 ( lf ) ; slo-2 ( lf ) triple mutants ( Fig 2A ) . These genetic analyses suggest antagonistic and parallel functions of BK potassium channels ( slo-1 and slo-2 ) and voltage-gated calcium channels ( unc-36 ) in AWC asymmetry ( Fig 2B ) . unc-2 and egl-19 , both of which encode α1 subunits of voltage-activated calcium channels , were shown to have partially redundant functions in AWC asymmetry [13] . unc-2 ( lj1lf ) mutants had a mixed 2AWCON and 2 AWCOFF phenotype , while a reduction of function ( rf ) allele of egl-19 did not display any AWC asymmetry defects . However , egl-19 ( rf ) ; unc-2 ( lf ) double mutants caused a strong 2AWCON phenotype reminiscent of unc-36 ( lf ) mutants [13] ( Fig 2A ) , which supports partially redundant functions of egl-19 and unc-2 in AWC asymmetry . To test whether unc-2 and egl-19 interact with slo-1 and slo-2 to establish AWC asymmetry , we determined genetic relationship between unc-2 , egl-19 , slo-1 , and slo-2 . The 2AWCOFF phenotype of slo-1 ( lf ) ; slo-2 ( lf ) was only slightly suppressed or not suppressed in slo-1 ( lf ) ; slo-2 ( lf ) unc-2 ( lf ) or egl-19 ( rf ) ; slo-1 ( lf ) ; slo-2 ( lf ) mutants , respectively ( Fig 2A ) . These results suggest that unc-2 ( lf ) or egl-19 ( rf ) alone are not sufficient to suppress the slo-1 ( lf ) ; slo-2 ( lf ) 2AWCOFF phenotype . However , egl-19 ( rf ) ; slo-1 ( lf ) ; slo-2 ( lf ) unc-2 ( lf ) quadruple mutants displayed a high 2AWCON phenotype , which resembled egl-19 ( rf ) ; unc-2 ( lf ) mutants ( Fig 2A ) . This result suggests that unc-2 and egl-19 act redundantly to antagonize slo-1 and slo-2 function to promote the AWCOFF identity . Taken together , these genetic results suggest that slo-1 and slo-2 ( BK potassium channels ) act downstream of nsy-5 ( innexin ) and in parallel with nsy-4 ( claudin ) to antagonize the function of unc-2/unc-36 and egl-19/unc-36 ( voltage-gated calcium channels ) to induce AWCON ( Fig 2B ) . Both slo-1 and slo-2 are widely expressed in neurons and muscles [25 , 28] . To determine if slo-1 and slo-2 are expressed in AWC neurons , we crossed odr-1p::TagRFP ( expressed in both AWC neurons ) with slo-1p::GFP and slo-2p::GFP transgenic strains . We found that GFP expressed from slo-1p and slo-2p was colocalized with the AWC marker odr-1p::TagRFP ( Fig 3A and 3C ) , suggesting that slo-1 and slo-2 are expressed in AWC . To determine if slo-1 and slo-2 are expressed asymmetrically in AWC neurons , we compared their respective expression level in AWC left ( AWCL ) and AWC right ( AWCR ) . Although slo-1 and slo-2 are expressed in both AWC neurons in the majority of wild-type animals , both slo-1 and slo-2 are asymmetrically expressed in AWCL or AWCR in a stochastic manner ( Fig 3B and 3D , AWCL>AWCR versus AWCL<AWCR are indistinguishable ) . Random asymmetry of slo-1 and slo-2 expression in AWC neurons is consistent with the stochastic nature of AWC asymmetry . In contrast , nsy-5 ( ky634lf ) and nsy-4 ( ky627lf ) mutants exhibited a significant increase in the percentage of animals that expressed slo-1 and slo-2 symmetrically in AWCL and AWCR ( Fig 3B and 3D , AWCL = AWCR ) . This data suggests that nsy-5 ( innexin ) and nsy-4 ( claudin ) are required for the asymmetric expression of slo-1 and slo-2 in AWC neurons , and is consistent with our genetic analysis demonstrating that nsy-5 acts in parallel with nsy-4 to promote AWCON through slo-1 and slo-2 ( Fig 2B ) . As a control , we examined the asymmetric expression of slo-1 and slo-2 in unc-43 ( n498gf ) /CaMKII mutants , which cause a 2AWCOFF phenotype , similar to that caused by nsy-5 ( ky634lf ) and nsy-4 ( ky627lf ) . We found that the asymmetric expression of both slo-1 and slo-2 was unaffected by the unc-43 ( n498gf ) mutation ( Fig 3B and 3D ) . This suggests that unc-43 ( CaMKII ) does not regulate the expression of slo-1 and slo-2 , and is consistent with our genetic results , which place slo-1 and slo-2 upstream of unc-43/CaMKII . The result also supports that the effect of nsy-4 and nsy-5 loss-of-function mutations on asymmetric expression of slo-1 and slo-2 was not due to the 2AWCOFF phenotype . We also compared expression level of slo-1 and slo-2 in AWCON and AWCOFF , and found that slo-1 and slo-2 are expressed predominantly in the AWCON cell ( Fig 3E–3H ) . These results are consistent with the hypothesis that slo-1 and slo-2 promote AWCON in a cell-autonomous manner . To determine the site of slo-1 and slo-2 function in promoting AWCON , we performed genetic mosaic analysis in slo-1 ( lf ) ; slo-2 ( lf ) mutants containing an integrated AWCON marker ( str-2p::GFP ) transgene and the extrachromosomal array odr-3p::slo-1 ( overexpressor ( OE ) ) ; odr-1p::DsRed or odr-3p::slo-2 ( OE ) ; odr-1p::DsRed . Both odr-3p::slo-1 ( OE ) and odr-3p::slo-2 ( OE ) transgenes rescued the 2AWCOFF phenotype in slo-1 ( lf ) ; slo-2 ( lf ) mutants and also caused a slight 2AWCON overexpression phenotype ( Fig 4A and 4C ) . Since extrachromosomal transgenes are unstable and can be randomly lost at each cell division , the co-injected marker odr-1p::DsRed ( normally expressed in both AWC ) was used to indicate the presence of the slo-1 ( OE ) or slo-2 ( OE ) array in AWC . Specifically , we determined if retention of the slo-1 ( OE ) or slo-2 ( OE ) array in only a single AWC cell causes a bias of AWCON choice in that cell when the mosaic animals exhibited a wild-type 1AWCON/1AWCOFF phenotype . We found that the slo-1 ( OE ) ; slo-2 ( lf ) AWC became AWCON and the slo-1 ( lf ) ; slo-2 ( lf ) AWC became AWCOFF in the majority of mosaic animals in which slo-1 was expressed only in a single AWC neuron ( Fig 4B ) . Similarly , the slo-1 ( lf ) ; slo-2 ( OE ) AWC became AWCON and the slo-1 ( lf ) ; slo-2 ( lf ) AWC became AWCOFF when mosaic animals expressed slo-2 only in a single AWC neuron ( Fig 4D ) . Together , these results support that slo-1 and slo-2 act cell autonomously to specify AWCON . We did observe a very small percentage of mosaic animals in which the slo-1 ( lf ) ; slo-2 ( lf ) AWC became AWCON ( Fig 4B and 4D ) . This suggests that although slo-1 and slo-2 have a largely cell-autonomous role in promoting the AWCON fate , they may also have a nonautonomous role . This is similar to other genes in the AWC asymmetry pathway , such as nsy-5 and nsy-4 which display both autonomous and nonautonomous roles in AWC asymmetry [20 , 21] . Mosaic analysis was also performed in transgenic lines in which slo-1 ( T1001Igf ) , containing the ky389gf mutation , was overexpressed in a wild-type background , resulting in a strong 2AWCON phenotype ( Fig 4E ) . When the transgene was retained in only one of the two AWC cells , the slo-1 ( gf ) cell became AWCON and the wild-type cell became AWCOFF in the majority of mosaic animals ( Fig 4F ) . This result is consistent with a largely cell-autonomous function of slo-1 in promoting AWCON , and also suggests that the AWC with slo-1 ( gf ) activity may become hyperpolarized , allowing the cell to reduce calcium influx and take on the AWCON subtype . SLO-1 and SLO-2 have overlapping expression patterns and have been suggested to potentially form heteromeric channels [24 , 28 , 29] . In addition , it has been shown that BK channels and N-type voltage-gated calcium channels localize in close proximity to achieve functional coupling of these channels [30] . To determine if SLO-1 , SLO-2 , UNC-2 ( N/P/Q-type calcium channels ) , and EGL-19 ( L-type calcium channels ) localize in close proximity in AWC , we generated single copy transgenes expressing functional translational reporters driven by the AWC odr-3 promoter using Mos1-mediated single copy insertion [31–33] . The tagged proteins expressed in these transgenes were functional in rescuing respective mutant phenotypes [34] ( S1 Fig , Materials and Methods ) . These single copy insertion transgenes showed that GFP::UNC-2 , SLO-1::TagRFP , SLO-1::GFP , SLO-2::TagRFP , and GFP::EGL-19 were mainly localized on the plasma membrane of AWC cell bodies and also displayed a punctate pattern along AWC axons ( Fig 5 and S2 Fig ) , similar to the previously shown localization pattern of GFP::UNC-2 in AWC [34] . Since these channels were localized throughout the plasma membrane of the AWC cell body and had distinct punctate patterns in AWC axons , we focused on analyzing their localization in relation to each other in AWC axons . We found that both SLO-1::TagRFP and SLO-2::TagRFP were localized adjacent to GFP::UNC-2 and GFP::EGL-19 in AWC axons ( Fig 5A and 5B , S2A and S2B Fig ) . In addition , SLO-2::TagRFP is located close to SLO-1::GFP in AWC axons ( Fig 5C ) . The Coloc 2 plugin in Fiji was used to quantify colocalization of these proteins in AWC axons using three different algorithms ( Pearson’s correlation coefficient , Spearman’s rank correlation coefficient , and Li’s ICQ ) . Each of the algorithms displayed positive correlation indices ( Fig 5D and S2C Fig ) . This further supports that UNC-2 and EGL-19 localize close to SLO-1 and SLO-2 , and that SLO-1 and SLO-2 are localized in close proximity as well . These results support the notion that BK potassium channels ( SLO-1 and SLO-2 ) and voltage-gated calcium channels ( UNC-2 and EGL-19 ) may function in close proximity for rapid activation of SLO-1 and SLO-2 channels by locally increased calcium levels near UNC-2 and EGL-19 calcium channels . It has been shown that communication between the pair of AWC neurons via chemical synapses in axons is important for induction of the AWCON subtype [11] . Our genetic data suggests that slo-1 and slo-2 are required for the specification of the induced AWCON subtype . In addition , SLO-1 and SLO-2 displayed distinct punctate localization patterns in AWC axons . Thus , we examined whether slo-1 and slo-2 regulate localization of synaptic markers in AWC neurons . To do so , we generated Mos1-mediated single copy insertion transgenes expressing fluorescently tagged synaptic markers , GFP::UNC-2 and YFP::RAB-3 , driven by the AWC odr-3 promoter ( Figs 5A , 5B and 6 ) . UNC-2 is localized to presynaptic active zones and RAB-3 is a synaptic vesicle marker [34] . In wild type , GFP::UNC-2 was localized in the AWC axon and cell body , and YFP::RAB-3 was mainly localized in a punctate pattern in the AWC axon as shown previously [34] ( Fig 6 ) . In slo-1 ( ky399gf ) animals , the intensity of GFP::UNC-2 or YFP::RAB-3 was not significantly affected in the AWC axon and cell body ( Fig 6 ) . However , slo-1 ( eg142lf ) ; slo-2 ( ok2214lf ) mutants displayed significant reduction in intensity of GFP::UNC-2 and YFP::RAB-3 in the AWC axon and cell body ( Fig 6 ) . These results suggest that slo-1 and slo-2 are required for localization and/or stability of synaptic markers , UNC-2 and RAB-3 , in AWC neurons , which may contribute to the 2AWCOFF phenotype caused by the slo-1 ( eg142lf ) ; slo-2 ( ok2214lf ) mutations . Our genetic mosaic analysis suggests a minor role of nonautonomous function of slo-1 and slo-2 in establishing AWC asymmetry ( Fig 4 ) , which is consistent with a possible role of slo-1 and slo-2 in regulating synaptic communication of AWC neurons . In addition , autofluorescence of the gut found in wild-type animals was visibly decreased in slo-1 ( eg142 ) ; slo-2 ( ok2214lf ) mutants ( S3A Fig ) , suggesting that the SLO channels are required for gut autofluorescence . As a control , the intensity of GFP expressed from the transgene odr-3p::GFP was analyzed in wild-type and mutant backgrounds , and no significant effect was observed in slo-1 ( ky399gf ) and slo-1 ( eg142lf ) ; slo-2 ( ok2214lf ) mutants ( S3B Fig ) . This result rules out the possibility that the activity of the odr-3 promoter is regulated by slo-1 and slo-2 , and also supports the notion that the effect of slo-1 ( lf ) ; slo-2 ( lf ) mutations on UNC-2 and RAB-3 is mainly at the subcellular localization level . It is also possible that slo-1 ( lf ) ; slo-2 ( lf ) mutations may affect unc-2 and rab-3 at post-transcriptional levels , such as translation efficiency , mRNA and/or protein stability . Previous studies have shown that slo-1 ( lf ) or slo-2 ( lf ) mutations result in increased neurotransmitter release at the neuromuscular junction in the ventral nerve cord [25 , 35] . However , a recent study showed that UNC-2 localization is not affected at the presynaptic terminals of neuromuscular junctions in slo-1 ( lf ) mutants [36] . Thus , previous findings did not demonstrate a correlation between increased neurotransmitter release and increased localization of UNC-2 or RAB-3 at presynaptic sites of the neuromuscular junction in slo-1 ( lf ) or slo-2 ( lf ) mutants . To examine whether the localization of UNC-2 and RAB-3 is affected in ventral cord motor neurons in slo-1 ( lf ) ; slo-2 ( lf ) mutants , we quantified the intensity of GFP::UNC-2 and RAB-3::mCherry driven by the unc-25 promoter , which is expressed in ventral cord motor neurons [34] . We examined the axons located anterior to VD5 and DD3 neurons in wild type and slo-1 ( lf ) ; slo-2 ( lf ) mutants at the L4 stage , but no significant difference was observed ( S4 Fig ) . This suggests that slo-1 and slo-2 do not play an apparent role in the localization of these presynaptic markers in the ventral nerve cord . The different effects of slo-1 and slo-2 mutations on the localization of synaptic markers in AWC neurons and ventral cord motor neurons suggest that slo-1 and slo-2 take on a different function in AWC neurons than in the ventral cord motor neurons . Although no apparent effect of slo-1 ( lf ) ; slo-2 ( lf ) mutations on the localization of UNC-2 and RAB-3 was observed in ventral cord motor neurons , the effect of slo-1 and slo-2 mutations on locomotion was performed by analyzing the wavelength and wave width of body wave tracks of wild type , slo-1 ( lf ) , slo-2 ( lf ) , and slo-1 ( lf ) ; slo-2 ( lf ) animals . We found that the wavelength of the worm track was not affected in the mutants , however the wave width was significantly increased in slo-1 ( lf ) , slo-2 ( lf ) , and slo-1 ( lf ) ; slo-2 ( lf ) mutants ( S5 Fig ) . These results suggest that slo-1 and slo-2 are required for normal locomotion . Previous studies have identified several modulators of SLO-1 activity in muscles using forward genetic screens . Since genes may interact in similar pathways in different tissues , we chose these candidate genes to determine whether they may also modulate SLO-1 activity in AWC neurons . bkip-1 mutants were identified from a screen for suppressors of the lethargic phenotype of slo-1 ( gf ) mutants . BKIP-1 ( BK channel Interacting Protein ) , a single pass membrane protein , functions as an auxiliary subunit of SLO-1 to assist in regulating neurotransmitter release and regulate the surface expression of the channel [37] . Similar to bkip-1 , ctn-1 ( α-catulin ) , identified from two independent screens for suppressors of the slo-1 ( gf ) lethargic phenotype , also regulates surface localization of SLO-1 in both muscles and ventral nerve cord motor neurons [38 , 39] . In addition , components of the dystrophin-associated protein complex ( DAPC ) , including dys-1 ( dystrophin ) , dyb-1 ( dystrobrevin ) , stn-1 ( syntrophin ) , and dyc-1 ( C-terminal PDZ-domain ligand of nNOS ) , control the localization of SLO-1 in muscles but not in neurons [40 , 41] . Furthermore , islo-1 , encoding a transmembrane protein , functions as an adaptor protein that links the DAPC to SLO-1 for SLO-1 localization in muscles [40] . To determine whether bkip-1 , ctn-1 , dys-1 , and islo-1 play a role in AWC asymmetry , we first examined expression of the AWCON marker str-2p::GFP in their respective loss-of-function mutants , but did not see any defects in AWC asymmetry ( Fig 7A ) . We then determined whether bkip-1 ( lf ) , ctn-1 ( lf ) , dys-1 ( lf ) , and islo-1 ( lf ) mutants suppress the slo-1 ( gf ) 2AWCON phenotype in AWC asymmetry by performing double mutant analysis . We found that dys-1 ( cx18 ) ; slo-1 ( ky399gf ) , ctn-1 ( eg116 ) ; slo-1 ( ky399gf ) , and islo-1 ( eg978 ) ; slo-1 ( ky399gf ) all displayed the same 2AWCON phenotype as slo-1 ( ky399gf ) animals ( Fig 7A ) . This suggests that dys-1 , ctn-1 , and islo-1 are not required for slo-1 function in AWC asymmetry . However , bkip-1 ( zw2 ) completely suppressed the 2AWCON phenotype of both slo-1 ( ky389gf ) and slo-1 ( ky399gf ) mutants to wild type ( Fig 7A ) , indicating that bkip-1 is required for slo-1 function in promoting AWCON . As shown by our results , slo-1 ( lf ) and slo-2 ( lf ) single mutants did not display AWC asymmetry defects ( Figs 1B and 7A ) . However , both bkip-1 ( lf ) ; slo-1 ( lf ) and bkip-1 ( lf ) ; slo-2 ( lf ) displayed a 2AWCOFF phenotype ( Fig 7A ) , supporting a role of bkip-1 in both slo-2 and slo-1 function , respectively . However , the 2AWCOFF phenotype of bkip-1 ( lf ) ; slo-1 ( lf ) and bkip-1 ( lf ) ; slo-2 ( lf ) was not 100% as seen in slo-1 ( lf ) ; slo-2 ( lf ) double mutants ( Fig 7A ) , suggesting that bkip-1 is not the only factor required for slo-1 and slo-2 function in AWC asymmetry . We also determined whether slo-2 is required for slo-1 function by crossing slo-2 ( lf ) mutants into both slo-1 ( ky389gf ) and slo-1 ( ky399gf ) alleles . We found that slo-2 ( lf ) did not suppress the slo-1 ( gf ) 2AWCON phenotype ( Fig 7A ) , suggesting that slo-2 is not required for slo-1 function in AWC asymmetry . Previous work demonstrates a role of bkip-1 in regulating the surface expression of SLO-1 in muscle dense bodies and the nerve ring [37] . We therefore determined whether bkip-1 affects SLO-1 localization in AWC neurons by examining a functional SLO-1::GFP translational reporter driven by the AWC odr-3 promoter in wild type and bkip-1 ( zw2 ) mutants ( Fig 7B ) . We found that in bkip-1 ( zw2 ) mutants , SLO-1::GFP intensity was significantly reduced in AWC axons ( Fig 7B and 7C ) but is not significantly affected in cell bodies ( Fig 7D ) . This suggests that bkip-1 is required for appropriate localization of SLO-1 in AWC axons but not in the AWC cell body . Consistent with the result suggesting that bkip-1 is not the only factor required for slo-1 function in AWC asymmetry ( Fig 7A ) , this result also suggests that slo-1 activity could be required in both the AWC axons ( dependent on bkip-1 ) and cell bodies ( independent of bkip-1 ) . We also examined whether bkip-1 ( zw2 ) mutants display altered the localization of SLO-2::GFP in AWC axons , but did not find a significant effect ( S6 Fig ) . This result suggests that slo-2 may require bkip-1 in a manner independent of appropriate localization . bkip-1 may be required for appropriate slo-2 expression levels , or BKIP-1 may physically interact with SLO-2 . Together , our results showed that bkip-1 is the only one of the known modulators of slo-1 activity in muscles to be also required for slo-1 and slo-2 function in AWC asymmetry . Thus , our results suggest that slo-1 and slo-2 need a different set of regulators for their function in AWC asymmetry . The voltage-dependent activation of SLO-1 and SLO-2 channels is modulated by calcium ( for SLO-1 and SLO-2 ) and chloride ( for SLO-2 ) [24 , 26] . To determine whether any chloride channels or other voltage-gated potassium channels might be involved in establishing left-right AWC asymmetry , we examined AWC asymmetry in mutants of selective channels that have been shown to be expressed in the nervous system ( WormBase ) . Although the majority of mutants examined did not display an AWC asymmetry defect ( S7A Fig ) , a gain of function mutation in unc-103 ( ERG voltage-gated potassium channel ) resulted in a slight 2AWCON phenotype ( S7B Fig ) . In addition , a gain of function mutation in egl-2 ( EAG voltage-gated potassium channel ) caused a high penetrance of the 2AWCON phenotype ( S7B Fig ) , as previously shown [11] . We found that the egl-2 ( n693gf ) mutation suppressed the 2AWCOFF phenotype observed in slo-1 ( eg142 ) ; slo-2 ( ok2214 ) double mutants , nsy-5 ( ky634lf ) , unc-43 ( n498gf ) , and tir-1 ( ky648gf ) single mutants ( S7B Fig ) . This suggests that egl-2 may function downstream of these genes to promote the AWCON fate . Alternatively , it is possible that egl-2 may function at the same level as slo-1 and slo-2; and that the production of 2 AWCON neurons by egl-2 ( gf ) in the slo-1 ( eg142 ) ; slo-2 ( ok2214 ) mutants is because egl-2 ( gf ) is sufficient to cause enough membrane hyperpolarization to induce AWCON even in the absence of slo-1 and slo-2 . Like slo-1 ( lf ) and slo-2 ( lf ) mutants , loss-of-function mutations in egl-2 did not cause a significant effect on AWC asymmetry nor did slo-1 ( lf ) ; egl-2 ( lf ) double mutants ( S7B Fig ) , suggesting that egl-2 may act redundantly with other factor ( s ) in promoting AWCON .
Here we identify an essential role of SLO BK potassium channels in asymmetric differentiation of one pair of olfactory neurons . Our findings reveal a functional link between gap junctions and SLO channels in inhibition of voltage-gated calcium channels for diversification of olfactory neurons . To the best of our knowledge , stochastic AWC asymmetry is the first system in which SLO channels are implicated in terminal neuron differentiation , stochastic cell fate determination , and left-right patterning . Our results suggest antagonistic and parallel functions of BK potassium channels ( SLO-1 and SLO-2 ) and voltage-gated calcium channels ( UNC-2/UNC-36 and EGL-19/UNC-36 ) downstream of NSY-5 gap junctions in AWC asymmetry . UNC-2/UNC-36 and EGL-19/UNC-36 activate a CaMKII-MAP kinase cascade to specify the default AWCOFF subtype , while SLO-1 and SLO-2 inhibit the calcium channel-activated kinase cascade to promote the induced AWCON subtype ( Fig 8 ) . Calcium and voltage are potential signals that mediate intercellular communication between the two AWC neurons and other neurons in the NSY-5 gap junction network to coordinate stochastic AWC asymmetry [19 , 20] . In addition , both SLO BK channels and voltage-gated calcium channels generate voltage and calcium signals , and are subject to calcium- and voltage-dependent activation and inactivation [26 , 42] . The regulatory loop between gap junctions , SLO BK channels , and voltage-gated calcium channels can potentially generate sustained differences in calcium-regulated signaling outputs between the two AWC cells through positive and negative feedback mechanisms , leading to asymmetric differentiation of AWC cells . This extends the previous model of NSY-5 function in AWC asymmetry by identifying SLO BK channels as the mediators of transient gap junction signaling for antagonizing voltage-gated calcium channel pathways . Signaling via NSY-5 gap junctions may lead to transcriptional regulation of slo-1 and slo-2 in order to ensure that these genes are expressed asymmetrically in the AWC neurons . Studies have shown that connexin gap junction proteins are capable of regulating gene expression . For example , gap junction communication mediated by Cx43 is required for ERK phosphorylation of the transcription factor Sp1 , which in turn leads to appropriate expression of an osteoclastin transcriptional element [43] . It has been suggested that gap junctions may allow diffusion of second messengers such as calcium and cyclic nucleotides , which subsequently can influence gene transcription [43 , 44] . It has also been suggested that C-terminal tails of connexins may bind to particular proteins , which can then contribute to regulating gene expression [44] . It is possible that NSY-5 gap junctions use similar mechanisms to regulate slo-1 and slo-2 gene expression . SLO-1 is 55% identical to its mouse orthologue Slo1 and SLO-2 is 41% identical to its mammalian orthologue Slack , while SLO-1 is only 18% identical to its nematode paralogue SLO-2 along the entire channel peptide [28] . SLO-1/Slo1 and SLO-2/Slack have overlapping expression patterns and may form heteromeric channels [24 , 28 , 29] . However , functional relationships between SLO-1/Slo1 and SLO-2/Slack have not yet been demonstrated in any biological contexts . Our results show that SLO-1 localizes in close proximity to SLO-2 in AWC neurons . In addition , our results suggest that slo-1 and slo-2 have complete functional redundancy in AWC asymmetry , since loss-of-function mutations in either gene alone did not cause any defects in AWC asymmetry while slo-1 ( lf ) ; slo-2 ( lf ) double mutants displayed a complete penetrance of the 2AWCOFF phenotype . Functional redundancy between SLO-1/Slo1 and SLO-2/Slack may represent one of the general mechanisms for their roles in other systems . The voltage range of activation of BK channels is modulated by different intracellular factors including calcium ( for SLO-1 , Slo1 , and SLO-2 ) , chloride ( for SLO-2 and Slack ) , sodium ( for Slack ) , pH , and phosphorylation [24 , 26] . None of the mutants of chloride channels we examined displayed any AWC asymmetry defects . In addition , although SLO-2 shares a complete redundant function with SLO-1 in AWC asymmetry , it has not been shown that the activation of SLO-1 channels is sensitive to chloride . These findings suggest that SLO-2’s redundant role with SLO-1 in establishing AWC asymmetry may be more dependent on sensitivity to calcium than to chloride . Calcium-activated BK channels and voltage-gated calcium channels have been shown to localize in close proximity to ensure selective and rapid activation of BK channels by a local increase in cytosolic calcium level [30] . The sensitivity of vertebrate Slo1 channels to calcium provides an important negative feedback for calcium entry in many cell types . For example , activation of Slo1 channels causes transient membrane hyperpolarization , which limits calcium entry through voltage-gated calcium channels to control the burst of calcium action potentials in cerebellar Purkinje cells and to regulate synaptic transmission in presynaptic terminals [26] . Our genetic results and findings that SLO-1 and SLO-2 localize close to UNC-2 and EGL-19 voltage-gated calcium channels are consistent with the physiological roles of vertebrate Slo1 channels in inhibiting voltage-gated calcium channels through functional coupling and negative feedback . By analogy to functional coupling between Slo1 and voltage-gated calcium channels in vertebrates , SLO-1 and SLO-2 may couple with UNC-2/UNC-36 and EGL-19/UNC-36 to generate oscillation of cytosolic calcium and voltage signals to coordinate stochastic AWC asymmetry through a feedback loop . In this hypothetical feedback loop , an increase in voltage triggers voltage-gated calcium channels to open , leading to an increase in intracellular calcium levels . High calcium levels allow the coupled calcium-activated BK channels to open , resulting in a decrease in voltage . The decreased voltage causes the voltage-gated calcium channels to close , leading to a decrease in intracellular free calcium levels and the subsequent closure of calcium-activated BK channels and an increase in voltage . This would initiate another cycle of calcium and voltage oscillation . Previous studies identified two forms of intercellular communication important for AWC asymmetry: one is mediated by NSY-5 gap junctions between the cell body of AWC and other neurons in a network [19 , 20]; the other is by synaptic connection between two AWC axons [10 , 11] . Since SLO-1 and SLO-2 are localized in proximity to UNC-2 and EGL-19 at the AWC axons , functional coupling between BK channels ( SLO-1 and SLO-2 ) and voltage-activated calcium channels ( UNC-2 and EGL-19 ) may occur at AWC axons . Our study has revealed that SLO-1 and SLO-2 have different functions and interacting partners in AWC olfactory neurons than in ventral cord motor neurons . Our genetic analysis suggests that BK potassium channels ( SLO-1 and SLO-2 ) act to antagonize calcium channels ( UNC-2/UNC-36 and EGL-19/UNC-36 ) to promote the AWCON identity . A recent report suggests that in M4 motor neurons , UNC-2 and UNC-36 function to activate SLO-1 , which in turn antagonizes the EGL-19 calcium channel to inhibit synaptic transmission at the M4 neuromuscular junction [45] . A recent study showed that UNC-2 localization is not affected at the presynaptic terminals of neuromuscular junctions in slo-1 ( lf ) mutants [36] . However , our results suggest that slo-1 and slo-2 are required for appropriate localization or stability of presynaptic markers UNC-2 and RAB-3 in AWC axons . We also show that SLO-1 and SLO-2 localize in close proximity to both UNC-2 and EGL-19 calcium channels in AWC neurons , in contrast to a report that SLO-2 exclusively couples with EGL-19 but not with UNC-2 in ventral cord motor neurons [35] . BK channels are ubiquitously expressed and have a staggering repertoire of functions in different tissues . To achieve functional diversity , BK channels , which assemble as tetramers of pore-forming α-subunits , can form complexes with various auxiliary β-subunits . For example , the β1 subunit changes gating and calcium sensitivity of Slo1 α subunits , and β2 subunits promote fast inactivation of Slo1 channels [26] . In addition , functional diversity of Slo1 channels can be achieved by alternative splicing , posttranslational modifications , and heteromultimer formation [26] . In C . elegans , several modulators have been identified for surface expression and activity of SLO-1 channels in muscles and neurons [37–41] . Our results show that the auxiliary subunit BKIP-1 is the only previously identified modulator of SLO-1 to be required for SLO-1 and SLO-2 function in asymmetric AWC differentiation . AWC asymmetry may provide an effective model system to identify novel modulators of SLO BK channels in vivo due to the ease of unbiased forward genetic screens in identifying biologically relevant genes and robust phenotypic readouts of SLO channel activity .
Wild type is strain N2 , C . elegans variety Bristol . Strains were maintained by standard methods [46] . Mutants used were as follows: nsy-5 ( ky634 ) I [20] , dys-1 ( cx18 ) I [47] , ctn-1 ( eg116 ) I [38] , avr-14 ( ad1302 ) I [48] , bkip-1 ( zw2 ) II [37] , clh-1 ( qa900 ) II , clh-1 ( qa901 ) II , clh-2 ( ok636 ) II , clh-3 ( ok763 ) II , unc-36 ( e251 ) III [46] , tir-1 ( ky648gf ) III [18] , nsy-4 ( ky627 ) IV [21] , unc-103 ( e1597gf ) III , egl-19 ( n582 ) IV [49] , islo-1 ( eg978 ) IV [40] , unc-43 ( n498gf ) IV [50] , unc-43 ( n1186 ) IV , slo-1 ( ky399gf ) V [11] , slo-1 ( ky389gf ) V [11] , slo-1 ( eg142 ) V [40] , slo-1 ( js118 ) V [25] , slo-1 ( js379 ) V [25] , egl-2 ( n693gf ) V , egl-2 ( n693n904 ) V , exp-2 ( sa26ad1426 ) V , shw-3 ( ok1884 ) V , clh-6 ( ok791 ) V , avr-15 ( ad1051 ) V , slo-2 ( ok2214 ) X ( C . elegans knockout consortium ) , slo-2 ( nf100 ) X [51] , egl-36 ( n728 ) X , egl-36 ( n728n398 ) X , and clh-4 ( ok1162 ) X , unc-2 ( lj1 ) X [52] . Integrated transgenes used include kyIs140 [str-2p::GFP; lin-15 ( + ) ] I [11] , vyIs76 [ceh-36p::myrTagRFP; ofm-1p::DsRed] I , vyIs58 [odr-1p::TagRFP] I , vyIs56 [odr-1p::TagRFP] III , vyIs68 [str-2p::TagRFP; srsx-3p::GFP] II [7] , vySi8 [odr-3p::slo-2c::TagRFP; unc-119 ( + ) ] II , vySi18 [odr-3p::GFP::unc-2; unc-119 ( + ) ] II , vySi23 [odr-3p::slo-1a::TagRFP; unc-119 ( + ) ] II , vySi38 [odr-3p::slo-1a::GFP; unc-119 ( + ) ] II , vySi39 [odr-3p::YFP::rab-3; unc-119 ( + ) ] II , vySi58 [odr-3p::slo-2::TagRFP; unc-119 ( + ) ] IV , vyIs51 [str-2p::2xnlsTagRFP; ofm-1p::DsRed] V [18] , vyIs74 [ceh-36p::myrTagRFP; ofm-1p::DsRed] V , otIs264 [ceh-36p::TagRFP] [53] , kyIs479 [unc-25p::GFP::unc-2; unc-25::mCherry::rab-3; odr-1p::mCherry] [34] , vyTi2 [odr-3p::GFP::egl-19] , and vyTi4 [odr-3p::GFP::egl-19] . Transgenes maintained as extrachromosomal arrays include vyEx842 , 843 [nsy-5p::slo-1 ( 7 . 5 ng/μl ) ; odr-1p::DsRed ( 15 ng/μl ) ; ofm-1p::DsRed ( 30 ng/μl ) ] , vyEx1573 , 1574 , 1575 , 1576 [nsy-5p::slo-1 ( T1001Igf ) ( 7 . 5 ng/μl ) ; odr-1p::DsRed ( 15 ng/μl ) ; ofm-1p::DsRed ( 30 ng/μl ) ] , vyEx822 , 823 [nsy-5p::slo-1 ( E350Kgf ) ( 7 . 5 ng/μl ) ; odr-1p::DsRed ( 15 ng/μl ) ; ofm-1p::DsRed ( 30 ng/μl ) ] , vyEx1539 , 1540 [slo-1p::GFP ( 15 ng/μl ) ; ofm-1::DsRed ( 30 ng/μl ) ] , vyEx1684 [slo-1p::2xnlsGFP ( 5 ng/μl ) ] , vyEx1701 [slo-1p::2xnlsGFP ( 2 ng/μl; pRF4 ( rol-6 ( su1006 ) ( 50 ng/μl ) ] , sEx10749 [slo-2p::GFP; pCeh361] , vyEx1122 , 1151 [odr-3p::slo-1 ( 30 ng/μl ) ; odr-1p::DsRed ( 15 ng/μl ) ; ofm-1p::DsRed ( 30 ng/μl ) ] , vyEx1682 [ceh-36p::myrTagRFP ( 5 ng/μl ) ] , vyEx1239 [odr-3p::slo-2c ( 30 ng/μl ) ; odr-1p::DsRed ( 15 ng/μl ) ; ofm-1p::DsRed ( 30 ng/μl ) ] , vyEx1572 [odr-3p::slo-2d ( 30 ng/μl ) ; odr-1p::DsRed ( 15 ng/μl ) ; ofm-1p::DsRed ( 30 ng/μl ) ] , vyEx1418 [odr-3p::slo-1::GFP ( 20 ng/μl ) ; ofm-1p::DsRed ( 30 ng/μl] , vyEx1393 , 1367 [slo-1p::slo-1 ( 15 ng/μl ) ; odr-1p::DsRed ( 15 ng/μl ) ; ofm-1p::DsRed ( 30 ng/μl ) ] , vyEx1266 [slo-1p::slo-1::GFP ( 7 . 5 ng/μl ) ; ofm-1p::DsRed ( 30 ng/μl ) ] , vyEx1594 [odr-3p::slo-1::TagRFP ( 30 ng/μl ) ; ofm-1p::DsRed ( 30 ng/μl ) ] , vyEx1325 , 1326 [odr-3p::slo-2c::TagRFP ( 30 ng/μl ) ; elt-2p::GFP ( 5 ngl/μl ) ] , and vyEx611 [odr-3p::GFP ( 7 . 5 ng/μl ) ; elt-2p::CFP ( 7 . 5 ng/μl ) ] . To make nsy-5p::slo-1 , a 3420 bp fragment of full-length slo-1a cDNA was amplified from snb-1p::slo-1a ( pBK3-1 ) [25] and cloned into a vector containing a 5556 bp of nsy-5 promoter [20] . nsy-5p::slo-1 ( T1001Igf ) and nsy-5p::slo-1 ( E350Kgf ) were generated by site directed mutagenesis of nsy-5p::slo-1 using a QuikChange II XL Site-Directed Mutagenesis Kit ( Stratagene ) . slo-1p::GFP was made by replacing slo-1a::GFP in the slo-1p::slo-1a::GFP vector containing a 5239 bp of slo-1 promoter [25] with GFP . slo-1p::slo-1 was generated by subcloning the 3420 bp of slo-1a coding region into the vector containing a 5239 bp of slo-1 promoter . odr-3p::slo-1 was made by subcloning the 3420 bp of slo-1a coding region into a vector containing the odr-3 promoter ( Roayaie et al . 1998 ) . odr-3p::slo-2c and odr-3p::slo-2d were generated by cloning 3261 bp of slo-2c and 3351 bp of slo-2d , respectively , into the odr-3p vector . odr-3p::slo-1::GFP was made by subcloning the slo-1a::GFP translation fusion from slo-1p::slo-1a::GFP [25] into the odr-3p vector . To make odr-3p::slo-1::TagRFP , TagRFP was inserted into the slo-1a cDNA at a location corresponding to a region of the protein between S8 and S9 , the same insertion site as GFP in slo-1p::slo-1a::GFP [25] , using fusion PCR . odr-3p::slo-2c::TagRFP was made by inserting TagRFP into the slo-2c cDNA at a location corresponding to a region of the protein between the last 16th and 15th amino acids from the C-terminus , the same insertion site as GFP in a slo-2::GFP translation fusion construct [28] , using fusion PCR . For Mos1-mediated single copy insertion ( MosSCI ) of these translational reporter transgenes , a pAB1 construct [14] , derived from a pCFJ151 MosSCI insertion vector for integration on chromosome II [31] , was modified to generate pAB1 . 1 that includes a new set of restriction enzyme sites . odr-3p::slo-1::TagRFP , odr-3p::slo-2::TagRFP , and odr-3p::YFP::rab-3 fragments were subcloned into pAB1 . 1 to generate pAB1 . 1::odr-3p::slo-1::TagRFP , pAB1 . 1::odr-3p::slo-2::TagRFP , and pAB1 . 1::odr-3p::YFP::rab-3 respectively . To make pAB1 . 1::odr-3p::GFP::unc-2 , partially overlapped fragments of linearized pAB1 . 1 vector backbone as well as odr-3p::GFP and GFP::unc-2 , both of which were PCR amplified from odr-3p::GFP::unc-2 [34] , were assembled and ligated using Gibson Assembly ( New England Biolabs; Ipsiwich , MA ) . pAB1 . 1::odr-3p::slo-1::GFP was made by Gibson Assembly of 3 partially overlapped fragments of pAB1 . 1::odr-3p vector backbone linearized from pAB1 . 1::odr-3p::slo-2::TagRFP , odr-3p::slo-1::GFP , and unc-54 3’UTR . odr-3p::slo-2::TagRFP fragment was cloned into the pCFJ356 MosSCI insertion vector for integration on chromosome IV [33] to generate pCFJ356::odr-3p::slo-2::TagRFP . odr-3p::GFP::egl-19 miniMos construct was generated by replacing snt-1p::HALO in the snt-1p::HALO::egl-19 miniMos construct ( pSAM354 ) , containing a section of egl-19 gDNA ( exons 5–9 and introns in between the exons ) sandwiched between two stretches of cDNA ( exons 1–4 and 10–17 ) , with an odr-3p::GFP fragment from odr-3p::GFP::unc-2 [33] . We found that a set-18p::GFP::egl-19 transgenic array rescued the locomotory phenotypes of the egl-19 ( n582 ) hypomorph mutant , supporting that GFP::EGL-19 translational reporter is functional . Transgenic strains were generated by injecting DNA constructs into the syncytial gonad of adult worms ( P0 ) as previously described [54] . F1 worms expressing fluorescent transgenes were picked and cloned ( 1 worm per plate ) . The F1 clones that have F2 progeny containing fluorescent transgenes were selected as transgenic lines and analyzed . MosSCI lines were generated using the direct insertion protocol as previously described [31 , 33] . Briefly , pAB1 . 1::odr-3p::GFP::unc-2 ( 22 ng/μl ) , pAB1 . 1::odr-3p::slo-2::TagRFP ( 71 ng/μl ) , pAB1 . 1::odr-3p::slo-1::TagRFP ( 107 ng/μl ) , pAB1 . 1::odr-3p::slo-1::GFP ( 43 ng/μl ) , or pAB1 . 1::odr-3p::YFP::rab-3 ( 26 ng/μl ) was injected along with hsp16 . 4p::peel-1 ( 10 ng/μl ) , eft-3p::mos-1 ( 50 ng/μl ) , rab-3p::mCherry ( 10 ng/μl ) , myo-2p::mCherry ( 2 . 5 ng/μl ) , and myo-3p::mCherry ( 5 ng/μl ) into ~100 EG4322 ( ttTi5605 II; unc-19 ( ed3 ) III ) worms cultured at 15 or 20°C . pCFJ356::odr-3p::slo-2::TagRFP ( 34 ng/μl ) was injected along with hsp16 . 4p::peel-1 ( 10 ng/μl ) , eft-3p::mos-1 ( 50 ng/μl ) , rab-3p::mCherry ( 10 ng/μl ) , myo-2p::mCherry ( 2 . 5 ng/μl ) , and myo-3p::mCherry ( 5 ng/μl ) into ~100 EG6703 ( unc-19 ( ed3 ) III; cxTi10816 IV ) worms cultured at 15 or 20°C . Three injected worms were picked to one plate and cultured at 25°C until starvation ( ~1 week ) . The starved worms were heat shocked at 34°C for two hours to activate the negative selection marker PEEL-1 , which kills animals carrying extrachromosomal arrays . After recovery at 25°C for four hours , worms that were rescued for the unc-119 phenotype and lacked the three mCherry co-injection markers were cloned out from separate plates . The presence of single copy inserts was verified by PCR . miniMos integration was done as previously described [55] . Briefly , odr-3p::GFP::egl-19 miniMos construct containing a hygromycin resistance cassette ( 17 . 5 ng/μl ) was injected along with hsp16 . 4p::peel-1 ( 10 ng/μl ) , eft-3p::mos-1 ( 50 ng/μl ) , rab-3p::mCherry ( 10 ng/μl ) , myo-2p::mCherry ( 2 . 5 ng/μl ) , and myo-3p::mCherry ( 10 ng/μl ) into ~100 vySi8 II; unc-119 ( ed3 ) III and vySi23 II; unc-119 ( ed3 ) III worms cultured at 15–20°C . Three injected animals were picked per plate and cultured at 25°C . Three days after injection , hygromysin was added directly onto the plate to a final concentration of 0 . 25 mg/ml and cultured further until starvation ( ~1 week ) . The starved worms were heat shocked at 34°C for two hours to kills animals carrying extrachromosomal arrays . After recovery at 25°C for four hours , worms that survived and lacked the three mCherry co-injection markers were cloned out to determine homozygosity . Transgenic strains expressing fluorescent markers or fluorescently tagged proteins were mounted onto 2% agarose pads and anesthetized with 5mM sodium azide ( Sigma ) or 7 . 5mM levamisole ( Sigma ) . Z-stack images were acquired at room temperature ( 20–22°C ) using Zeiss Axio Imager Z1 or M2 microscopes , each of which is equipped with a motorized focus drive , a Zeiss objective EC Plan-Neofluar 40x/1 . 30 Oil DIC M27 , a Piston GFP bandpass filter set ( 41025 , Chroma Technology ) , a TRITC filter set ( 41002c , Chroma Technology ) , and a Zeiss AxioCam CCD digital camera ( MRm for Z1 and 506 mono for M2 ) driven by the Zeiss imaging software ( AxioVision for Z1 and ZEN for M2 ) . For comparison of fluorescence intensity , all animals in each set of experiments were subjected to the same exposure time . Fluorescence intensity was measured with AxioVision or ZEN imaging software or NIH ImageJ image processing software . Since the background autofluorescence varies between some genetic backgrounds ( S3A Fig ) , fluorescence intensity of reporter transgenes was subtracted by background fluorescence intensity to obtain corrected fluorescence intensity . Images shown in Figs 1A , 3A , 3C , 3E , 3G , 5A , 5B , 5C , 6A , 6B and 7B , as well as S2A , S2B , S3A , S3B , S4A and S6A Figs were processed with Adobe Photoshop; the same degree of brightness and contrast adjustment was applied to all images in each set of experiments for comparison of fluorescence intensity ( Figs 6A , 6B and 7B , as well as S3A , S3B and S6A Figs ) . Genetic mosaic analysis was performed with various unstable extrachromosomal transgenic arrays in either wild type or slo-1 ( eg142lf ) ; slo-2 ( ok2214lf ) mutants . Three different experiments were performed to determine the sites of slo-1 and slo-2 function in AWC asymmetry . odr-3p::slo-1 was injected into slo-1 ( lf ) ; slo-2 ( lf ) mutants to determine whether slo-1 acts cell autonomously or nonautonomously to rescue the 2AWCOFF mutant phenotype . A similar experiment was performed using the odr-3p::slo-2 extrachromosomal array . In the third experiment , nsy-5p::slo-1 ( T1001Igf ) was injected into wild-type animals . In all three experiments , the odr-1p::DsRed marker ( expressed in AWC and AWB ) was included in the injection mix to serve as an indicator for presence or absence of the extrachromosomal transgene in AWC . The AWCON and AWCOFF neurons were determined using expression of a stable integrated str-2p::GFP ( AWCON marker ) transgene . Transgenic strains were passed for minimum of six generations to allow the transgenes to stabilize before scoring for mosaic animals . Colocalization was quantified using the Coloc 2 plugin ( http://fiji . sc/Coloc_2 ) in Fiji [56] . Three different algorithms were used: Pearson’s correlation coefficient , Spearman’s rank correlation coefficient , and Li’s ICQ . For each colocalization class , images of at least three animals were used for quantification . Positive values of each coefficient indicate positive correlation , values close to zero indicate no correlation , and negative values indicate anti-correlation . Pearson's correlation coefficient ranges from -1 to +1; Spearman’s rank correlation coefficient ranges from -1 to +1; Li's ICQ value ranges from -0 . 5 to +0 . 5 Locomotion analysis was performed on L4 animals in wild type , slo-1 ( eg142 ) , slo-2 ( ok2214 ) , and slo-1 ( eg142 ) ; slo2 ( ok2214 ) animals . Single animals of each genotype were placed on a bacterial lawn and allowed to make tracks . The worm tracks as well as individual worms were imaged and analyzed in ImageJ [57] . All animals were placed on the same batch of NGM plates seeded with the same batch of HB101 and were imaged on the same day . Wavelength was measured as the distance between wave peaks , and at least 3 wavelengths were measured and averaged per animal . The wavelength was normalized by the body length of the animal . Wave width was measured as the distance from the peak to the trough of the worm wave . At least 3 wave widths were measured and averaged per animal . The wave width was normalized by the body length of the animal . | Cell type diversity is important for the nervous system to function properly . Asymmetric differentiation of neurons along the left-right axis is one way to achieve diversity; however , the molecular mechanisms used to establish neuronal asymmetry are only partly understood . In the nematode C . elegans , the AWC sensory neuron pair displays stochastic asymmetric identities . Communication between neurons , including the two AWC neurons , through gap junctions inhibits calcium channels in one AWC neuron , resulting in two distinct AWC identities . How gap junctions repress calcium channels in one AWC is not well understood . We show that voltage- and calcium-activated potassium channels provide a molecular link between gap junctions and calcium channels to establish AWC neuronal asymmetry . We show that potassium channels are asymmetrically expressed in AWC neurons , which is dependent on gap junctions . We also find that potassium channels localize close to calcium channels in AWC , suggesting they may functionally couple to establish AWC asymmetry . In addition , our results show that potassium channels regulate the localization of synaptic markers in AWC for asymmetry . Furthermore , we identify an auxiliary subunit of the potassium channels required for their function in establishing AWC asymmetry . These results shed light on mechanisms used to diversify neuronal cell types . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2016 | SLO BK Potassium Channels Couple Gap Junctions to Inhibition of Calcium Signaling in Olfactory Neuron Diversification |
The Tibetan grey wolf ( Canis lupus chanco ) occupies habitats on the Qinghai-Tibet Plateau , a high altitude ( >3000 m ) environment where low oxygen tension exerts unique selection pressure on individuals to adapt to hypoxic conditions . To identify genes involved in hypoxia adaptation , we generated complete genome sequences of nine Chinese wolves from high and low altitude populations at an average coverage of 25× coverage . We found that , beginning about 55 , 000 years ago , the highland Tibetan grey wolf suffered a more substantial population decline than lowland wolves . Positively selected hypoxia-related genes in highland wolves are enriched in the HIF signaling pathway ( P = 1 . 57E-6 ) , ATP binding ( P = 5 . 62E-5 ) , and response to an oxygen-containing compound ( P≤5 . 30E-4 ) . Of these positively selected hypoxia-related genes , three genes ( EPAS1 , ANGPT1 , and RYR2 ) had at least one specific fixed non-synonymous SNP in highland wolves based on the nine genome data . Our re-sequencing studies on a large panel of individuals showed a frequency difference greater than 58% between highland and lowland wolves for these specific fixed non-synonymous SNPs and a high degree of LD surrounding the three genes , which imply strong selection . Past studies have shown that EPAS1 and ANGPT1 are important in the response to hypoxic stress , and RYR2 is involved in heart function . These three genes also exhibited significant signals of natural selection in high altitude human populations , which suggest similar evolutionary constraints on natural selection in wolves and humans of the Qinghai-Tibet Plateau .
Species inhabiting the Qinghai-Tibet Plateau exist in low oxygen tension environments and must adapt to low oxygen tension [1] . Documenting the genetic mechanisms for adaptation to hypoxia can provide insights into the process of evolution under extreme conditions and hypoxia-related disease in humans . Compared with their lowland counterparts , Tibetan human populations show unique adaptations , such as low hypoxic pulmonary vasoconstrictor response , high levels of blood oxygen saturation , and low hemoglobin ( Hb ) levels [1]–[2] . The genetic basis for some of these phenotypes has been identified and hypoxia-related genes ( such as EPAS1 , EGLN1 ) have experienced strong selection in Tibetans [3]–[10] . Past studies of complete genomes have not found these genes to be under selection in other highland vertebrates , such as deer mice [11] , the yak [12] , the ground tit [13] , and Tibetan antelope [14] . However , these studies have used a comparative genomic approach involving the analysis of genome sequences from a variety of divergent species . A potentially more powerful approach utilizes complete genome sequences from populations of the same species , conditional on the knowledge of their demographic history and gene flow . The grey wolf , Canis lupus , is the most widely distributed terrestrial mammal with a geographic range spanning latitudinal and altitudinal gradients and including as many as 32 sub-species [15] . Rates of gene flow among grey wolf populations are high [16] , reflecting large average dispersal distances [17] . Nonetheless , significant genetic differences among populations have been identified that correlate with environmental variation , suggesting a process of habitat selection that is based on natal conditioning [18] . The Tibetan grey wolf ( C . lupus chanco ) is a relatively large form having a more wooly coat [19]–[20] that occupies habitats on the Qinghai-Tibet Plateau , implying local adaptation to low oxygen tension [12] . The genetic basis of such adaptation , however , remains unknown . Here we compare the whole genomes of low- and high- altitude populations of wolves from China in order to explore adaptation to hypoxia in the Qinghai-Tibet Plateau wolf population .
Eight wolves that represented four distinct populations from lowland ( Xinjiang and Inner Mongolia ) and highland ( Tibet and Qinghai ) ( Fig . 1 and S2; Table S1 ) were selected for genome sequencing on an Illumina HiSeq 2000 platform . The short reads from an additional wolf from one locality in Inner Mongolia used on a previous study ( RKWL [21] ) were also included . PCR duplicates were detected and marked in Picard ( http://picard . sourceforge . net ) . From 6 . 69% to 15 . 96% of reads in each sample were PCR duplicates and all of the PCR duplicates were excluded from downstream analyses . Then , after removing adapters and low quality reads ( quality value of < = 5 for > = 50% of reads ) , we generated 5 . 9 billion 100-bp reads in total ( from 686 to 763 million reads per sample ) , which covered 535 . 84 Gb bases ( from 61 . 3 Gb to 68 . 69 Gb per sample; Table S2 ) . All the alignments were done in Bowtie2 , and each individual had more than a 98% alignment rate ( Table S2 ) . After running the genotyping pipeline , the total coverage of these nine Chinese wolves was 231 . 3-fold and every sample had more than 20-fold effective genome-wide mean coverage ( Fig . 2; Table S2 ) . In order to further control the data quality and remove false positives , we applied genome ( GF2 ) and sample filters ( SF ) to obtain a final SNP dataset for each Chinese wolf . All the samples had more than 1 . 3 billion total useable sites , which covered more than 60% of the reference genome ( 61 . 97%∼63 . 13%; Table S3 ) . Slightly more than 1% of the total sites were filtered out in each individual by excluding the CpG sites ( Table S4 ) . The number of SNPs was very similar among individuals ( about 3 million , from 2 , 925 , 783 to 3 , 482 , 449 ) . However , the two wolves from Tibet ( 2 , 925 , 783 and 3 , 010 , 114 ) had relative fewer SNPs ( Table S3 ) . To quantify genome-wide heterozygosity , for each wolf we calculated the ratio of passed-filter heterozygous genotype calls against all passed-filters sites ( GF2 and SF; Table S3 ) . The autosomal heterozygosity was the highest in two Xinjiang wolves ( 0 . 001597 and 0 . 001632 ) and the lowest in two Tibet wolves ( 0 . 000705 and 0 . 000862 ) , which is only about half that in Xinjiang wolves ( Table S3 ) . Highland wolves had lower autosomal heterozygosity than lowland wolves ( P = 0 . 03 , one-way ANOVA ) . Based on the SNPs from each sample , we created a merged SNPs dataset . Across these nine wolves , we found 7 , 509 , 614 SNPs in the merged dataset . After the removal of sites that were missing in one or more the samples , 6 , 645 , 354 SNPs remained in the merged SNP dataset ( Table S3 and S4 ) . A dataset of 266 , 299 pruned SNPs was obtained from the 7 , 509 , 614 SNPs of the nine Chinese wolves after removing SNPs with high pairwise genotypic association . The genome wide STRUCTURE results showed that the five lowland wolves ( IM06 , IM07 , RKWL , XJ24 , and XJ30 ) grouped with each other whereas the four highland wolves ( TI09 , TI32 , QH11 , and QH16 ) were in another group from K = 2 to K = 5 ( Fig . 3 ) . The likelihood values was highest for K = 3 or K = 4 ( Fig . 3 ) . Qinghai appears as a transitional zone between Tibet and lowland ( Xingjiang and Inner Mongolia ) populations ( Fig . 1 ) , which was consistent with the STRUCTURE result because at K = 2 , the Qinghai individuals were intermediate between Tibet and lowland wolves ( Fig . 3A ) . The PCA exhibited a clearer picture of the groupings . PC1 explained 24 . 86% while PC2 explained 12 . 27% of the overall variation ( Fig . 3B ) . The four highland wolves clustered together , while the five lowland wolves were significantly separated from the highland wolves along PC1 . Unlike the STUCTURE results , PC2 strongly separated Xinjiang wolves and Inner Mongolian wolves from each other , but the four highland wolves were still clustered together . These results were also consistent with the geographic distribution of the samples ( Fig . 1 ) . The pairwise sequentially Markovian coalescent model ( PSMC [22] ) revealed that the nine Chinese wolves exhibited similar demographic trajectories until about 80 , 000 years ago ( Fig . 4 ) . Thereafter , all populations except Tibet experienced some population growth or stagnation until about 24 , 000 years ago . The growth phase occurred around the Greatest Lake Period ( 30 , 000–40 , 000 years ago ) , during which the forested habitats appropriate for wolves increased [23] . In contrast , the two Tibetan wolves experienced a continuous population decline beginning 55 , 000 years ago . However , all wolf populations appeared to decline beginning at the last glacial maximum ( 21 , 000–17 , 000 years ago ) , when the expansion of glaciers in the northern hemisphere likely decreased the extent of the habitat suitable for wolves . However , PSMC loses resolution for dates earlier than about 20 , 000 year ago because of the lack of recombination events [21]–[22] , so the timing of this event is less certain . The genomic signatures of positive selection in highland wolves were evaluated using two metrics: FST and Δπ ( Fig . 5 ) . Using these metrics , we identified 902 outlier regions which included 1548 genes potentially under selection . The 1548 genes included 229 significant GO ( Gene Ontology ) terms ( Table S6 ) and several significant enrichment categories included genes involved in response to stimulus ( Table S6 ) . Additionally , we defined an a priori candidate list of 1351 hypoxia-related genes ( Table S5 ) . Of these 1548 putatively selected genes , 84 were potentially related to hypoxia ( Table S5 ) . The GO enrichment ( Table S7 ) of the 84 hypoxia-related genes showed strong enrichment for the HIF ( Hypoxia-Inducible Factors ) signaling pathway ( KEGG:04066 , 6 genes ) , ATP binding ( GO:0005524 , 14 genes ) , and response to oxygen-containing compound ( GO:1901700 , 7 genes; GO:1901701 , 5 genes ) . A total of 2598 SNPs in coding regions were found with a significant difference at the 5% level between genotypes of highland and lowland wolves . Of these 2598 SNPs , 893 were non-synonymous in 683 genes ranging from 1 to 12 per gene . Fifty-two of these SNPs were from 43 hypoxia-related genes with 1 to 4 SNPs per gene . Finally , of the 893 non-synonymous SNPs , a relevant change in protein function was suggested for 119 SNPs with SIFT [24] , 330 SNPs with MAPP [25] , and 193 SNPs with PolyPhen2 [26] ( Fig . 6 ) . The three methods had in common 33 SNPs from 32 genes ( Fig . 6 ) . However , only one of these was a hypoxia-related gene ( RYR2; Fig . 5 ) . In total , 17210 bp of DNA sequences from 17 genes were re-sequenced in 35 wolves and 108 SNPs were found among them ( Table S8 ) . Of the 108 SNPs , 18 SNPs were not found in the whole genome data , 64 were located in introns , 34 in exons ( 14 synonymous and 20 nonsynonymous ) , and 10 in UTRs ( Table S8 ) . A total of 6 nonsynonymous SNPs from 3 hypoxia-related genes ( EPAS1 , RYR2 , and ANGPT1; ranging from 1 to 3 per gene ) that were under selection at the top 5% level as indicated by FST and Δπ metrics were confirmed through re-sequencing ( Fig . 5 and 7 ) . All the 6 variants showed significantly different distributions of genotypes between highland and lowland wolves ( Fig . 7 and Table S9 , P≤3 . 57E-07 ) . As defined by these nonsynonymous SNPs , two alleles from RYR2 were only present in highland wolves ( Fig . 7 and Table S9 ) . In addition , one synonymous variant and one variant in an intron from RYR2 , one variant in intron in ANGPT1 , 21 of 26 variants in introns from EPAS1 , also showed significantly different distributions of alleles and genotypes between highland and lowland wolves ( Fig . 7 and Table S9 , P≤8 . 01E-05 ) . Linkage disequilibrium ( LD ) analysis with the Haploview software [27] showed that the 3 hypoxia-related genes were located in single LD blocks ( Fig . 7 ) . Linkage analysis of re-sequenced genes showed complete linkage disequilibrium ( r2 = 1 ) for 2 variants in ANGPT1 , 23 variants in EPAS1 , and 4 variants in RYR2 ( Fig . 7 ) .
Since the average altitude of Tibet plateau is substantially higher than our other localities , the more dramatic and extended population decline of Tibetan wolves may reflect more severe habitat loss there during the initial stages of glaciation [28]–[29] . Human migration into the Tibetan Plateau may have also contributed to the steeper decline of Tibetan wolves ( Fig . 4 ) . The earliest evidence of human occupation of the Tibetan Plateau consists of flakes and microliths found at 4500 to 5200 m in northern Tibet similar to those of northern Asian tool cultures dated 25 , 000 to 50 , 000 years ago [30] . Qi et al . [31] found that there have been two distinct , major prehistoric migrations of modern humans into the Tibetan Plateau . The first human migration occurred approximately 30 , 000 years ago followed by a migration 7–10 thousand years ago . The rapid growth of the human population on the Qinghai-Tibet Plateau could have resulted in the loss of habitats appropriate for large wildlife species as well as over exploitation , which then contributed to the population decline of the Tibetan grey wolves . Positively selected hypoxia-related genes in highland wolves , identified with FST and Δπ metrics ( Table S6 and S7 ) , are enriched in the HIF signaling pathway ( P = 1 . 57E-6 ) , ATP binding ( P = 5 . 62E-5 ) , and the response to oxygen-containing compound ( P≤5 . 30E-4 ) . Specifically , 198 genes under selection ( Table S6 and S7 ) were related to response to stimulus ( Table S6 and S7 ) and the main stimulus in the high altitude population is low oxygen supply [1] . These categories appear to be biologically relevant to living at high altitudes by providing energy and oxygen for tissues and organs . In addition , given the population bottleneck experienced by the Tibetan wolf ( Fig . 4 ) , we expect average FST values may be inflated , however , this is not expected to produce locus specific effects on genes involved in the hypoxia pathway ( e . g . [32] ) . Combining results of FST and Δπ , 84 hypoxia-related genes appeared to be under selection ( Table S7 ) . To identify which of them could be responsible for local adaptation in the Tibetan plateau , we identified nonsynonymous SNPs ( denoted “highland SNP” ) in the genome data whose genotypes were homozygous reference in lowland wolves and homozygous alternative in Tibetan wolves ( and either heterozygous or homozygous alternative in Qinghai wolves ) . Of the 84 genes , only three genes ( EPAS1 , RYR2 , and ANGPT1 ) matched such criteria . Three highland SNPs were found in EPAS1 , two in RYR2 , and one in ANGPT1 ( Fig . 7 ) . Moreover , SIFT , MAPP , and PolyPhen2 all identified that one of the two highland SNPs in RYR2 ( located in exon 8: chr04:2778722 , Table S9 ) might affect protein function and resulted in a Ser-to-Thr ( S214T ) amino acid change in highland wolves . In addition , the highland SNP in ANGPT1 , a T-to-C transition ( SNP name: chr13_8141664; Table S9 ) found in exon 4 , resulted in a Met-to-Val ( M201V ) amino acid change in highland wolves . The M201V mutation in ANGPT1 was predicted to be benign by PolyPhen2 , however , the same SNP was found to affect protein function with high probability in MAPP ( MAPP score = 30 . 01 , column score = 24 . 07 , P = 2 . 924E-6 ) and with high confidence in SIFT . Multiple amino acid alignments of orthologs showed that these two amino acid variants ( M201V and S214T ) were only found in highland wolves ( Fig . 7 ) . Additional sequencing in a larger panel of wolves showed these highland SNPs in the above 3 genes had a frequency difference between highland and lowland wolves greater than 58% ( P≤3 . 57E-07 , Table S9; Fig . 7 ) . However , analysis of these sequences for additional substitutions showed that some variants in these genes were in complete linkage disequilibrium ( r2 = 1; Fig . 7 ) leaving open the possibly that high-altitude adaptation in the Tibetan wolves may involve multiple substitutions . Gene function prediction showed that EPAS1 and ANGPT1 function in the HIF pathway were involved in the response to hypoxic stress ( Fig . 8 ) . EPAS1 is a prime regulator during chronic hypoxia and directly regulates key genes such as erythropoietin ( EPO ) , and vascular endothelial growth factor ( VEGF ) [33]–[34] . ANGPT1 can increase tissue vascularization and result in increased oxygen delivery [35] . In addition , RYR2 initiates cardiac excitation-contraction coupling by Ca2+-induced Ca2+ release [36] and some amino acid mutations in RYR2 have been linked to heart failure in humans [37] . These three genes were found to be under selection for hypoxia adaptation in human populations living in high altitude . Specifically , ANGPT1 was under positive selection in humans from Tibet [38] , EPAS1 was found to exhibit a significant signal for natural selection in humans from highland Qinghai-Tibet , the Andes , and Mongolia [3]–[10] and RYR2 was under selection and within the top 0 . 1% of hits in high-altitude Ethiopian populations [39] . Consequently , highland wolves have evolved hypoxia adaptations at the molecular level in parallel with these human populations . Finally , Ji et al . [9] found a significant increase in the frequencies of some hypoxia related alleles with increased-altitude in humans . In this study , we observed a similar trend in the EPAS1 gene . Geographically , Qinghai appears as a transitional zone between Tibet and lowland ( Xingjiang and Inner Mongolia ) populations ( Fig . 1 ) . All individuals from Tibet are fixed for a single haplotype spanning the 31 variants of EPAS1 , and four individuals from Qinghai are also fixed for this haplotype with the remaining individuals being heterozygous ( Fig . 7 ) . In contrast , in the low altitude populations of Xinjiang and Inner Mongolia , we observe lower heterozygosity and allele frequencies for this haplotype ( Fig . 7; Table S9 ) . In conclusion , through the analysis FST and Δπ ( Fig . 5 ) and re-sequencing ( Fig . 7 ) , we find consistent support for positive selection on three hypoxia-related genes in highland wolves of the Qinghai-Tibet Plateau . These genes potentially enhance function under hypoxic conditions by increasing oxygen delivery ( EPAS1 and ANGPT1; Fig . 8 ) , or heart ( RYR2 ) function . Given that these genes also appear under selection in high altitude populations of humans , a common genetic toolkit for rapid acclimation to hypoxia may be emerging . The grey wolf is a particularly dramatic example of the process of adaptation to high altitude environments given that high rates of migration among populations should stymie local adaptation . However , in grey wolves , dispersing individuals may select habitats similar to those they experienced during a prolonged maturation period in their natal pack [18] . Thus , despite the potential to disperse over large distances , fidelity to natal habitats may assist the process of local adaptation in wolves and other species .
Blood samples were collected from 35 grey wolves from four distributions in China ( Fig . 1 and Table S1 ) . Of these , 30 individuals were verified as wild-born from a specific geographic locale and five individuals were captive-born from wild-born parents ( Fig . 1 and Table S1 ) . The latitude and longitude of wild-born parents was used for captive-born individuals . Samples were mapped with DIVA-GIS ( version 7 . 5 ) ( http://www . diva-gis . org/gdata ) ( Fig . 1 ) . All activities followed the legal requirements and institutional guidelines set out by the government of P . R . China . Consent was given from all relevant institutions to obtain samples . Genomic DNA from blood was isolated using a standard proteinase K digestion and phenol-chloroform extraction procedure [40] . Twenty-six polymorphic microsatellite loci ( Table S10 ) were used to analyze the genetic structure of the 35 Chinese wolves with previously published procedures [41] . We performed a series of independent runs using population clusters ( K ) from 1 to 10 , assuming an admixture model and with burn-in and replication values set at 50 , 000 and 1 , 000 , 000 , respectively , in STRUCTURE [42] . We ran three independent simulations for each K value and checked the consistency of results . In addition , the 35 Chinese wolves were genotyped on a MassARRAY for single nucleotide polymorphism . MALDI-TOF mass spectrum genotyping were evaluated to determine if some of them had significant domestic dog admixture/ancestry by analysis of 25 of the top 27 dog-wolf ancestry informative markers ( AIM ) identified in vonHoldt et al [43] through pairwise FST comparison of 912 domestic dogs and 155 grey wolves . Three of the 25 AIM markers were polymorphic in the panel of wolves and not useful for admixture/ancestry analysis ( Table S11 ) . Based on the final panel of 22 AIM markers , 4 of the wolves had <90% of the respective diagnostic wolf alleles and were thus considered to have significant dog admixture/ancestry and eliminated from the genomic analyses ( Table S11 ) . Based on the above microsatellite and AIM data ( Fig . S2; Table S10 and S11 ) , eight individuals ( Fig . 1 and S2; Table S1 ) that represented four distinct populations from lowland ( Xinjiang and Inner Mongolia ) and highland ( Tibet and Qinghai ) regions were chosen for complete genome sequencing at BGI , Shenzhen , China . In addition , short reads of an additional sample ( RKWL ) from Inner Mongolia in a previous genome study [21] were processed together with the eight wolves . All short reads were aligned to the dog genome ( boxer genome , CanFam3 . 1 ) using Bowtie2 [44] under the local alignment algorithm with very sensitive model settings and proper insert sizes . Other parameters were set as default . After mapping the short reads to the reference genome , we applied two major tools , Picard ( http://picard . sourceforge . net ) and Genome Analysis Toolkit ( GATK ) toolset [45] , to process the alignments in order to perform genotype calls . The whole pipeline converted the short reads to bam format alignment files [46] , and genotype calls were placed in a vcf format ( http://www . 1000genomes . org/node/101 ) from bam files after multiple steps ( Fig . S3 ) . We describe the details of our pipeline in a supplementary file ( Protocol S1 ) . After producing the genotype calls from GATK , we applied several conservative data quality filters to further control the data quality , grouped into two levels: genome filters ( GF , which was based on the reference genome's features and polymorphism across samples ) and sample filters ( SF , which was based on the genotype calls of each sample ) . We describe the details of the filters in a supplementary file ( Protocol S2 ) . The Ti/Tv for all the nine Chinese wolves was close to ∼2 . 3 with a mean of 2 . 34 ( range: 2 . 321–2 . 355; Table S12 ) , which was similar to other complete genome sequencing studies [45] , [47]–[48] . Furthermore , we compared our genome data with the Illumina SNP chip calls of RKWL [21] , which included more than 170 , 000 high quality markers throughout the genome . All three types of genotype calls had very high concordance ( homozygous reference: 99 . 77%; heterozygous: 99 . 82%; homozygous non-reference: 99 . 97% ) . In addition , a total of 17 , 210 bp DNA sequences from 17 genes ( Table S9 ) were used to check the genotype calls of the remaining eight genomes in this study ( Table S1 ) . Ninety SNPs from the 17 , 210 bp DNA sequences were found in the eight complete genomes . Among all 720 genotypes from the 90 SNPs , only 2 genotypes in one individual ( IM07 ) were not found in re-sequencing data . We used publicly available information regarding gene locations in the dog genome ( canFam3 . 1 ) to build a comprehensive set of transcribed and coding regions . Gene coordinates were retrieved from Ensembl ( release 70 , downloaded on Feb 11th 2013 from ftp://ftp . ensembl . org/pub/release-70/gtf/canis_familiaris/Canis_familiaris . CanFam3 . 1 . 70 . gtf . gz ) and NCBI ( ftp://ftp . ncbi . nih . gov/genomes/Canis_lupus_familiaris/GFF/ref_CanFam3 . 1_top_level . gff3 . gz , downloaded on Feb 11th 2013 ) . The total set comprised 28 , 538 genes and 51 , 781 transcripts , many of them redundant between the two annotation sources . We considered as duplicated entries genes that: 1 ) had overlapping coordinates and; 2 ) had similar gene names or symbols; or 3 ) had any of their transcripts sharing more than 60% of the exons ( corresponding to the threshold used by NCBI in a similar NCBI/Ensembl matching ) . Transcripts with the exact same exon coordinates were considered duplicates , while transcripts with partial differences were considered alternative transcripts of the same gene . We also tested the transcripts for apparently intact open reading frames: proper start and stop codons , a coding region multiple of 3 bp and no in-frame stop codons . Finally , the complete set of non-redundant coding regions with apparent intact coding frames ( ‘unique CDS OK’ set ) used for our analyses had 30 , 533 transcripts corresponding to 21 , 108 genes . In order to build a comprehensive set of annotated hypoxia-related genes in the domestic dog , we searched the available information from four different sources with keywords “hypoxia” and “HIF” ( Hypoxia-Inducible Factors pathway ) in CanFam3 . 1 on the UCSC genome browser database [49] ( http://genome . ucsc . edu/cgi-bin/hgGateway ? hgsid=323162145 ) , Ensembl [50] ( http://www . ensembl . org/Canis_familiaris/Info/Index ) , SeqGene files from the NCBI database ( http://www . ncbi . nlm . nih . gov/gene ) , and UniProt [51] ( http://www . uniprot . org/ ) . We also downloaded genes associated with Gene Ontology annotation terms [52] ( http://www . geneontology . org/ ) and KEGG pathways [53] ( http://www . kegg . jp ) via Entrez Gene that may be involved in a hypoxia response via HIF activation with keywords “hypoxia” and “HIF” . These methods identified 534 genes . Moreover , in order to obtain a maximal extensive annotation of the genomic complement of hypoxia-related genes in dog , we searched for hypoxia-related genes in humans from RefSeq [54] , KnownGene [55] and VEGA [56] , and then mapped them to dog genome using BLASTP for homology-based gene prediction . The alignments shorter than 150 bp or the target sequences with no chromosome locations in CanFam3 . 1 were discarded . Moreover , some putative hypoxia-related genes in human [5] , [9] were also used to search for their homologs in the dog genome . Since it is difficult to find univocal chromosome locations in the dog genome for the homologous microRNAs between human and dog , the candidate list of hypoxia genes did not include microRNAs . Similarly , potential candidate genes identified in the mitochondrial genome and on the X chromosome were not considered in this study . The SNPs of the nine Chinese wolves were pruned to remove SNPs with high pairwise genotypic association ( r2 ) for a proper use in principal components analysis ( PCA using Eigensoft ) and Bayesian clustering analysis ( using STRUCTURE ) . Highly linked SNPs with r2>0 . 2 were removed from the dataset of variant calls using PLINK [57] with the setting “indep-pairwise 50 5 0 . 2” . Then , the pruned SNPs dataset was used for the Bayesian inference program STRUCTURE ( v2 . 3 . 4 [42] ) to assess genetic admixture of the nine Chinese wolves . We utilized 10 , 000 burn-in iterations and 10 , 000 MCMC iterations in STRUCTURE ( v2 . 3 . 4 ) , with three repetitions of these parameter settings for each number of K populations interrogated . The alpha and likelihood statistics were monitored and verified to reach convergence before both the 10 , 000 burn-in and 10 , 000 MCMC iterations were completed during each repetition for each number of K populations analyzed . We compared likelihood values ( averaged over 3 runs ) for each K value assessed , and the parameter Δ [58] for K = 1 to 5 with the cluster assignment results . Moreover , to visualize the dominant relationships in the merged SNP dataset of nine Chinese wolves , we used the smartpca program distributed in the Eigensoft package for principal component analysis ( PCA [59] ) . We used the pairwise sequentially markovian coalescent ( PSMC [22] ) to infer the demographic history of all the nine Chinese wolves . Briefly , the method uses the distribution of heterozygote sites across the genome and a Hidden Markov Model to reconstruct the history of effective population sizes . The following parameters were used: numbers of iterations = 25 , time interval = 64*1 , mutation rate per generation = 1 . 0×10−8 and generation time = 3 . Evidence for selection was evaluated by contrasting FST and Δπ calculated from for the genome sequences of highland and lowland wolves [60]–[62] . The highland wolves included two individuals from Tibet and two from Qinghai and the lowland wolves included five individuals from Inner Mongolia and Xinjiang , groupings consistent with population structure analyses ( Fig . 1 and 3 ) . For calculations of FST and Δπ , we used a sliding window approach in which we divided the reference genome into overlapping windows of size 100 kb with 20 kb increments . For each 100 kb-window , we computed summary statistics using only sites that pass the GF2 filter ( Protocol S2 ) and where genotypes were observed and pass SF in all wolves ( Protocol S2 ) . For each summary statistic , we computed empirical percentiles by ranking each window for FST and Δπ and transforming the ranks to percentiles ( % FST and % Δπ ) . We then calculated a “joint” empirical percentile ( % Joint ) ( 1 ) by computing the product of the empirical percentiles obtained for the two summary statistics in each window [ ( % Product ) = ( % FST ) * ( % Δπ ) ] and ( 2 ) ranking each window by the products ( % Product ) and transforming the ranks to percentiles ( % Joint ) . For each metric , we defined the windows with FST>0 . 259 and Δπ>5 . 311 ( corresponding to top 5% level for joint empirical percentile ) as outlier windows . Since the outlier windows are often clustered together in the genome , we joined outlier windows and intervening sequence to define outlier regions when windows were found within 200 kb of each other . The set of genes from our selection hits were tested for significant enrichment in Gene Ontology ( GO ) categories , Kegg/Reactome pathways ( KGR ) and Human Phenotype Ontologies ( HPO ) using the online tool g:Profiler [63] ( http://biit . cs . ut . ee/gprofiler/ ) . All genes of dog annotated in Ensembl were used as background set , and the Benjamini-Hochberg false discovery rate [64] was applied to correct for multiple testing . We only reported significantly enriched categories that included ≥5 genes and with multiple testing corrected P value≤0 . 05 . For functional prediction of non-synonymous coding SNPs , we focused on protein sequences whose mutations had significant differences at the 5% level in the distributions of genotypes between highland and lowland wolves , tested by the association test in the Haploview software [27] . Specifically , individuals from Tibet had to be all homozygous alternatives , whereas at least three homozygous reference and no homozygous alternatives had to be found in lowland wolves . However , the population structure analysis based on genome wide SNPs showed that the two Qinghai wolves were closer to Tibet wolves or intermediate ( Fig . 3 ) , which is consistent with their geography ( Fig . 1 ) . Consequently , no homozygous reference genotypes found in Qinghai wolves were used to identify SNPs with the significant difference at the 5% level between the highland and lowland wolves . We identified orthologs through protein BLAST search in GenBank and multi-protein sequence alignment in MUSCLE [65] for prediction of functional variation with Multivariate Analysis of Protein Polymorphism ( MAPP [25] ) . An alignment with more than 10% gaps or less than 60% identity between each protein and its lowland ortholog was considered a different form of transcript or false annotation [66] . SIFT [24] , MAPP [25] , and PolyPhen2 [26] were used to predict the putatively functional importance of non-synonymous coding SNPs . Thresholds in determining whether a given metric predicted these SNPs to be functional were as follows: PolyPhen2 “PROBABLY/POSSIBLE DAMAGING” , SIFT “AFFECT PROTEIN FUNCTION” , and MAPP “Bad Amino Acids” . In order to further identify potential targets of selection , a set of SNPs and associated genomic sequences were re-sequenced in additional wolf samples . Three criteria were used to select these SNPs: ( 1 ) the genes should be listed in hypoxia-related gene candidate list and identified as outliers by Δπ and F-statistic; ( 2 ) the distributions of selected alleles had to be highly differentiated between lowland and highland groups as in the paragraph “Prediction of functional variation” , but homozygous references in all lowland wolves; and ( 3 ) the selected alleles must have biological effects . Based on these three criteria , 6 non-synonymous SNPs from 3 hypoxia-related genes ( ANGPT1 , EPAS1 , and RYR2; Table S8; Fig . 5 and 7 ) were used for validation in an extended study involving all 35 individuals . Moreover , 14 non-synonymous SNPs from 11 hypoxia-related genes and 10 SNPs located at 5′ UTR ( untranslated region ) or 3′ UTR from 3 hypoxia-related genes were used for validating the 8 genome data ( excluding RKWL ) by Sanger sequencing ( Table S8 ) . Primer sets ( Table S8 ) for amplifying the target sequences were designed based on the dog de novo assembly ( CanFam3 . 1 ) . After PCR , all products were subsequently sequenced using an ABI 3730XL ( Applied Biosystems ) . Linkage disequilibrium ( LD ) , chi-square and p-values for the allele frequencies in highland ( Tibet + Qinghai ) vs . lowland ( Xinjiang + Inner Mongolia ) wolves for the re-sequenced SNPs from the 3 hypoxia-related genes ( ANGPT1 , EPAS1 , and RYR2 ) were assessed with the Haploview program [27] . | Understanding the genetic mechanisms that allow some individuals to live at high altitudes under hypoxic conditions can provide insight into the evolutionary constraints of adaptation to extreme conditions and the development of hypoxia-related disease in humans . The Tibetan grey wolf ( Canis lupus chanco ) has long existed on the Qinghai-Tibet Plateau , where low oxygen tension exerts unique selection pressure on individuals . Comparing the complete genome sequences of 4 grey wolves from high altitude and 5 from low altitude , we identify three candidate genes for high-altitude adaptation ( EPAS1 , ANGPT1 , and RYR2 ) that show strong signals of selection . The three genes potentially enhance function under hypoxic conditions by increasing oxygen delivery ( EPAS1 and ANGPT1 ) and heart ( RYR2 ) function . These genes also appear under selection in high altitude human populations , which suggesting there may be limited pathways for adapting to high altitude existence . | [
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] | 2014 | Hypoxia Adaptations in the Grey Wolf (Canis lupus chanco) from Qinghai-Tibet Plateau |
Hematopoietic progenitors undergo differentiation while navigating several cell division cycles , but it is unknown whether these two processes are coupled . We addressed this question by studying erythropoiesis in mouse fetal liver in vivo . We found that the initial upregulation of cell surface CD71 identifies developmentally matched erythroblasts that are tightly synchronized in S-phase . We show that DNA replication within this but not subsequent cycles is required for a differentiation switch comprising rapid and simultaneous committal transitions whose precise timing was previously unknown . These include the onset of erythropoietin dependence , activation of the erythroid master transcriptional regulator GATA-1 , and a switch to an active chromatin conformation at the β-globin locus . Specifically , S-phase progression is required for the formation of DNase I hypersensitive sites and for DNA demethylation at this locus . Mechanistically , we show that S-phase progression during this key committal step is dependent on downregulation of the cyclin-dependent kinase p57KIP2 and in turn causes the downregulation of PU . 1 , an antagonist of GATA-1 function . These findings therefore highlight a novel role for a cyclin-dependent kinase inhibitor in differentiation , distinct to their known function in cell cycle exit . Furthermore , we show that a novel , mutual inhibition between PU . 1 expression and S-phase progression provides a “synchromesh” mechanism that “locks” the erythroid differentiation program to the cell cycle clock , ensuring precise coordination of critical differentiation events .
Hematopoietic progenitors execute a cell division program in parallel with a differentiation program in which lineage choice is followed by lineage-specific gene expression . In many differentiation models , cell cycle exit , driven by cyclin-dependent kinase inhibitors ( CDKI ) , is a prerequisite for terminal differentiation , establishing a key interaction between the cell cycle and differentiation programs [1]–[3] . However , it is unclear how the cell cycle and differentiation programs might be linked prior to cell cycle exit . Such links are presumably required to ensure the correct number of differentiated progeny . In addition , it has been speculated that the reconfiguration of chromatin at sites of lineage-specific genes , a necessary step preceding lineage-specific gene expression , may be innately dependent on DNA replication [4] , [5] . An intriguing possibility is that the clockwork-like mechanisms regulating orderly cell cycle transitions may also be used , in the context of differentiating cells , to coordinate key steps in differentiation . Here we studied differentiation of the enucleated red blood cell lineage , which first arises from hematopoietic stem cells in the fetal liver on embryonic day 11 ( E11 ) . It replaces a transient , nucleated yolk-sac erythrocyte lineage and persists throughout life . Although many of the committal events that lead to the erythroid phenotype are known , their precise timing in erythroid differentiation , and the manner in which they are coordinated with each other and/or with the cell cycle machinery , is poorly understood . Thus , survival of erythroid progenitors requires both the hormone erythropoietin ( Epo ) , and its receptor , EpoR , a class I cytokine receptor expressed by erythroid progenitors [6] . However , the precise time in erythroid differentiation when progenitors become dependent on Epo had not been defined . The master transcriptional regulator GATA-1 is responsible for the erythroid gene expression profile , in combination with a number of additional transcriptional regulators , including FOG-1 , EKLF , SCL/Tal-1 , LMO2 , Ldb1 , E2A , and Zbtb7a [7]–[10] . Though GATA-1 functional activation must precede erythroid gene induction , its precise timing in primary differentiating progenitors is not known . GATA-1 functions are antagonized by PU . 1 , an Ets transcription factor that acts as a master regulator in the myeloid and B-cell lineages . The mutual inhibition between PU . 1 and GATA-1 is thought to underlie cell fate choice in multipotential progenitors [11]–[14] . PU . 1 has been implicated in erythroleukemia [13] , [15] , but its physiological function in erythropoiesis is not known . Erythroid gene induction by GATA-1 requires an “open chromatin” conformation in the vicinity of erythroid-specific genes . The erythroid-specific β-globin locus is one of the best studied models of lineage-specific gene expression [16] , [17] . The active locus is characterized by early replication during S-phase , higher sensitivity to DNase I digestion , low levels of DNA methylation , and post-translational histone tail modifications associated with actively transcribed genes . Conversely , the same locus in non-erythroid cells is DNase I resistant , replicates late in S-phase , and contains histone tail modifications characteristic of silent chromatin . In spite of the detailed knowledge contrasting chromatin states in erythroid cells with non-erythroid cells , the precise time during erythroid differentiation when chromatin reconfiguration occurs is not known . Furthermore , it is not known whether this reconfiguration involves a number of sequential stepwise alterations occurring over a number of cell cycles/differentiation stages or whether the many changes entailed in chromatin activation occur simultaneously . Here we studied erythroid differentiation using a flow-cytometric assay that identifies sequential stages in erythroid differentiation directly within primary hematopoietic tissue . We found that in mouse fetal liver in vivo , upregulation of CD71 marks cells that are synchronized in S-phase of a single cell cycle , corresponding to the last generation of erythroid colony-forming cells , approximately three cell cycles prior to terminal cell cycle exit . A number of differentiation milestones , whose precise timing in erythroid development was previously unknown , occur during early S-phase of this cycle . These include the onset of Epo dependence , activation of GATA-1 function , and the opening up of chromatin at the β-globin locus . We show that S-phase progression during this specific cell cycle is dependent on downregulation of p57KIP2 and is required for execution of these differentiation milestones , including the reconfiguration of chromatin at the β-globin locus . Further , this S-phase dependent rapid differentiation transition is regulated by PU . 1 through a newly identified , mutual antagonism between S-phase progression and PU . 1 expression that coordinates the precise locking of the differentiation program to the cell cycle clock as cells enter a terminal differentiation phase .
Mouse fetal liver between E11 and E15 is primarily an erythropoietic tissue . Cell surface markers CD71 and Ter119 may be used to identify differentiation-stage specific subsets , directly in primary tissue [18]–[20] . Here we divided freshly harvested fetal liver cells into six CD71/Ter119 subsets that we termed S0 to S5 and that form a developmental sequence ( Figure 1A ) . Cells isolated from subsets S1 to S5 show morphological features characteristic of erythroid maturation , including decreasing cell and nuclear size , nuclear condensation , and hemoglobin expression ( Figure 1A , right panel ) . The precise proportion of fetal liver cells within each of the CD71/Ter119 subsets is a function of embryonic age , with the majority of cells being in the early , S0 and S1 subsets in E12 . The more mature , S3 to S5 subsets are gradually populated with cells during subsequent embryonic days ( E13 to E15 ) [20] . The EpoR−/− fetal liver is small and lacks morphologically identifiable hemoglobinized erythroblasts of the enucleated ( definitive ) lineage [6] . Here we found that EpoR−/− fetal liver does not contain subsets S1 to S5 ( Figure 1B ) . This suggested that in the definitive erythropoietic lineage that gives rise to adult-type enucleated red cells , EpoR becomes essential on or prior to the transition from S0 to S1; subsets S1 to S5 are composed almost entirely of Epo-dependent erythroblasts . Of note , the small number ( ≈5% ) of Ter119+ cells in the EpoR−/− fetal liver are all nucleated erythrocytes of the transient yolk-sac ( primitive ) lineage ( Figure S1A ) . Erythroid progenitors have traditionally been identified by their in vitro colony-forming potential . “Colony forming unit-erythroid” ( CFU-e ) are defined as cells that give rise to colonies containing 8 to 32 hemoglobinized cells after 2–3 days of in vitro culture in Epo [21] . We investigated the colony-forming potential of cells sorted from each of the S0 to S3 subsets ( Figure 1C ) . CFU-e potential was exclusive to S0 and S1 and was lost with the transition to S2 . Cells in S2 and S3 gave rise to small , 2 to 4 cell clusters ( Figure 1C , right panel ) . The frequency of CFU-e obtained from sorted S0 cells was 65%–70% of the frequency from sorted S1 ( Figure 1C ) . S1 consists entirely of Epo-dependent cells of similar maturation , with CFU-e potential ( Figure 1A–C ) . Assuming similar plating efficiency for sorted S0 and S1 ( of ≈30% , Figure 1C ) , this suggested that CFU-e make up 65%–70% of the S0 subset . This is in agreement with our finding that fetal liver cells expressing non-erythroid lineage markers , which were limited to S0 , formed up to 30% of this subset ( Figure 1D , Figure S1B ) . Non-erythroid colony-forming progenitors were also restricted to S0 , where they formed less than 5% of all colony-forming cells ( Figure 1C ) . Our conclusion that 65%–70% of S0 cells are CFU-e was further supported by single cell RT-PCR , which showed that 68% of S0 cells expressed EpoR mRNA ( Figure S1C ) . In all the experiments that follow , “S0” refers to S0 cells from which cells expressing non-erythroid markers were excluded by flow-cytometric gating or sorting . To examine the cell cycle status of erythroid subsets S0 to S5 in vivo , we injected pregnant female mice with the nucleotide analogue bromodeoxyuridine ( BrdU ) and harvested fetal livers 30 min post-injection . We sorted cells from each of S0 to S5 and stained them with antibodies directed at BrdU ( Figure 1E , F ) . Cells that incorporated BrdU were in S-phase of the cell cycle at the time of harvesting . Subsets S4 to S5 showed a rapid decline in the number of S-phase cells , consistent with cell cycle exit of terminally differentiating cells . Unexpectedly , we noted that ≈90% of S1 cells were in S phase , as compared with ≈50% of cells in S0 ( Figure 1E , F ) . In addition , the intensity of the BrdU fluorescence within S1 cells was approximately 50% higher than in S0 , suggesting a higher rate of DNA synthesis ( Figure S1D ) . Similar experiments with EpoR−/− fetal liver showed that EpoR appears to have no effect on progenitor cell cycle status ( Figure S1E ) . Consistent with the higher number of S-phase cells in S1 , we found a corresponding increase in the E cyclins in S1 compared with S0 ( Figure 1G ) . Strikingly , we noted >30-fold decrease in the CDKI p57KIP2 mRNA , but no significant change in the mRNA of other members of the CIP/KIP CDKI family; there was induction in p27KIP1 later in differentiation , in subsets S2 and S3 ( Figure 1G and Figure S1F ) [22] , [23] . The p57KIP2 protein also decreased at the S0 to S1 transition ( Figure 1G lower panel ) . The finding that nearly all S1 cells were in S-phase could be due to an unusual cell division cycle with short or no gap phases . Alternatively , S1 cells may be synchronized in S-phase of the cycle . The latter explanation would require that cells spend only a brief period of a few hours in S1 , lasting through part or all of a single S phase . The preceding G1 phase of this same cell cycle would have occurred prior to the transition from S0 to S1 . The G2 and M phases of this same cycle would occur as cells upregulate Ter119 and transition into S2 . To investigate these possibilities , we isolated S0 cells by flow-cytometry , labeled them with the cell-tracking dye carboxyfluorescein diacetate succinimidyl ester ( CFSE ) , and followed their Epo-dependent differentiation into S1 in vitro ( Figure 1H ) . By 10 h , 53% of S0 cells transitioned into S1 in the absence of cell division , as indicated by a single CFSE peak for S1 ( solid red histogram , t = 10 h ) that was identical in intensity to that of the CFSE peak for S0 ( blue histogram , t = 10 h; median CFSE fluorescence for both S1 and S0 peaks = 4 , 400 ) . This suggested that the transition from S0 to S1 occurred in the absence of cell division , within a single cell cycle . Four hours later , at t = 14 h , essentially all S1 cells had divided once , as indicated by the halving of the CFSE signal ( red histogram at t = 14 h , CFSE fluorescence = 2 , 100 ) . The simultaneous division of S1 cells suggested they were synchronized in their cell cycle phase . By contrast , only a portion of S0 cells , which were presumably asynchronous in their cell cycle phase , had divided at this time , resulting in a biphasic CFSE peak ( blue histogram , t = 14 h ) . Taken together , these results suggest that the most mature CFU-e progenitor ( “CFU-e . 2” , Figure 1I ) , capable of giving rise to an eight-cell colony , traverses S0 , S1 , and enters S2 within a single cell cycle . This progenitor arises in S0 , becomes Epo dependent , and upregulates CD71 , transitioning into S1 during S-phase of its cell cycle . Upregulation of Ter119 occurs at approximately the same time that it completes its cycle and divides , giving rise to progeny that lack CFU-e activity in S2 ( Figure 1C ) . These conclusions are consistent with essentially all S1 cells being in S-phase ( Figure 1E , F ) , and with our finding that nearly all S1 cells are sensitive to hydroxyurea , a drug that specifically targets S-phase cells ( Figure S2A ) . These conclusions are consistent with a number of other observations: the loss of CFU-e activity with Ter119 expression ( Figure 1C , [24] ) , the short time span ( <15 h ) that freshly sorted S0 cells require to transition through S1 and into S2 ( compare with an estimated cell cycle length of 16 h for a CFU-e cell that will undergo three cell divisions in 48 h , giving rise to an eight cell colony ) , and with early work suggesting that Epo dependence first occurs in early S-phase of a specific CFU-e cell generation [25] . These conclusions are also consistent with the finding that EpoR−/− embryos have normal numbers of CFU-e [6]: though EpoR−/− embryos lack S1 cells , all the CFU-e in S1 first arise as Epo-independent cells in S0 , where they are presumably retained in the EpoR−/− fetal liver . There are two ways to explain how upregulation of CD71 , a differentiation event , might coincide with S-phase , a cell cycle event . These events may have each been initiated in parallel by a common upstream regulator , such as the EpoR , since both occur at the time that cells become EpoR dependent . Alternatively , there may be a direct mechanistic link between the differentiation and cell cycle programs . To distinguish these possibilities , we examined whether a block to S-phase progression would interfere with CD71 upregulation ( Figure 2 ) . We incubated sorted S0 cells in vitro for 10 h in the presence of Epo , and either in the presence or absence of aphidicolin , an inhibitor of DNA polymerase that arrests S-phase progression [26] . At t = 10 h , cells were washed free of aphidicolin and incubated in Epo alone for an additional 10 h ( Figure 2A ) . In the initial 10 h of incubation , there was an Epo-dependent transition of cells from S0 to S1 ( Figure 2C , rows 1 and 5 ) . However , the presence of aphidicolin blocked this transition ( Figure 2C , rows 2 & 3 , t = 10 h ) . Both S-phase and the transition into S1 resumed once the cells were washed free of aphidicolin ( Figure 2C , rows 2 & 3 , t = 20 h ) . These observations suggested that the transition from S0 to S1 occurred during S-phase and required both Epo and S-phase progression . We also examined the effect of mimosine , a plant amino acid that blocks cell cycle progression in late G1 [27] . We incubated sorted S0 cells in Epo and in the presence or absence of mimosine . By 4 h of incubation , the majority of cells were arrested in G1 . However , a small fraction of cells ( 12% ) could be seen in S-phase at t = 4 h ( Figure 2C , row 4 , BrdU/7AAD at t = 4 h ) . Presumably , at the time mimosine was added , these cells were advanced in their cell cycle beyond the point at which mimosine exerts its block . BrdU/7AAD analysis showed that these cells were in the early half of S-phase and expressed the highest CD71 levels within the S0 subset ( Figure 2D , cells marked in red ) . By t = 10 h , no S-phase cells were seen in S0 , presumably because they have now transitioned into S1 , where a similar number of cells ( 15% ) had newly appeared ( Figure 2C , row 4 , BrdU/7AAD for S0 at t = 10 h , and CD71/Ter119 for S1 at t = 10 h ) . These observations were consistent with the onset of CD71 upregulation occurring in early S-phase in S0 , culminating in the transition to S1 later within that same S-phase . CD71 , the transferrin receptor , is required during erythroid differentiation in order to facilitate cellular uptake of iron for hemoglobin synthesis . CD71 is also expressed , albeit at lower levels , on all cycling cells . We therefore examined whether , in the context of S1 cells , CD71 might be required specifically for S-phase progression . We used RNAi to prevent CD71 upregulation in S0 cells during their incubation in Epo ( Figure S2B , C ) . The failure of these cells to upregulate CD71 did not interfere with the number of cells in S-phase ( Figure S2B ) . Therefore , the link between S-phase progression and CD71 upregulation in S1 cells is not due to a cell cycle function for this gene . To investigate the link between S-phase and the erythroid differentiation program , we examined expression of erythroid transcriptional regulators and erythroid-specific genes in freshly sorted fetal liver subsets and in fetal brain ( Figure 3A ) . We found that the GATA-1 mRNA was present in S0 cells , at 200-fold higher levels than in fetal brain ( Figure 3A ) and 40-fold higher level than in Mac-1+ cells ( Figure S3A ) . It increased a further ≈2-fold with the transition from S0 into S1 and continued to increase in S2 and S3 . Of note , total RNA per cell decreased 4-fold over the course of differentiation from S2 to S4 ( Figure S3B ) , suggesting an overall modest increase in GATA-1 mRNA per cell over this period . Other erythroid transcriptional activators and GATA-1 associated factors , including EKLF , NF-E2 [28] , SCL/Tal-1 , and Lmo2 , showed a similar expression pattern to that of GATA-1 ( Figure 3A ) . Therefore , expression of GATA-1 and of other activators of the erythroid transcriptional program precedes the transition from S0 to S1 . By contrast , we found that PU . 1 , a repressor of GATA-1 function , and GATA-2 , a target of GATA-1-mediated repression [29] , were both downregulated ≈30-fold and ≈20-fold , respectively , at the S0 to S1 transition , becoming undetectable with further differentiation ( Figure 3A ) . Prior to its downregulation , the level of PU . 1 in S0 cells was comparable to that of myeloid Mac-1+ cells ( Figure S3A ) . PU . 1 protein levels also declined with the transition from S0 to S1 ( Figure S3C ) . EpoR−/− fetal liver cells , though apparently arrested at the S0 stage ( Figure 1B ) , have a similar expression pattern of transcriptional regulators to wild-type S1 ( Figure 3A ) . Therefore , downregulation of PU . 1 and GATA-2 at the S0 to S1 transition , as well as the preceding induction of GATA-1 , are independent of EpoR signaling . We examined expression of several erythroid-specific GATA-1 target genes: β-globin ( Hbb-b1 ) ; the first enzyme of heme synthesis , aminolevulinic acid synthase 2 ( ALAS2 ) ; and the anion exchanger Band 3 ( Slc4a1 ) , a major erythrocyte membrane protein [30] . There was a modest increase in their expression at the S0 to S1 transition , followed by a 30–100-fold induction during subsequent differentiation in S2 and S3 ( Figure 3A ) . Expression of the EpoR gene , itself a GATA-1 target , increased 10-fold above its S0 level with the transition to S1 ( Figure S3D ) . Taken together , induction of erythroid GATA-1 target genes and repression of GATA-2 suggest that GATA-1 function is activated at the S0 to S1 transition . The modest increase in GATA-1 mRNA at this time suggests that its activation may be principally a result of PU . 1 downregulation . We had found that S-phase progression at the transition from S0 to S1 was required for CD71 upregulation ( Figure 2 ) . We therefore examined whether S-phase progression at this time was also required for induction of erythroid-specific genes . We cultured sorted S0 cells in Epo for 10 h , a period sufficient for 25%–50% of cells to transition into S1 ( Figures 1H , 2C ) , and examined the effect of adding aphidicolin to the culture . Cells were then washed free of aphidicolin , continuing incubation in Epo alone . Cells incubated in Epo alone for the entire period showed ≈50- to 100-fold induction in the mRNAs for β-globin , Band 3 , and ALAS2 ( Figure 3B , red curves ) . By contrast , cells that were subject to aphidicolin treatment during the initial 10 h showed reduced mRNA induction by the end of the culture period ( Figure 3B , blue curves ) . The reduced mRNA levels corresponded closely to the levels predicted had there been a 10 h delay in the time course of induction for each of the genes ( Figure 3B , black curves ) . Therefore , induction of erythroid-specific genes was likely blocked during the incubation period in aphidicolin . We also examined whether S-phase arrest interferes with erythroid gene induction if applied at the S1 stage of differentiation . We sorted S1 cells and incubated them in Epo , either in the presence or absence of aphidicolin . Unlike S0 cells , aphidicolin-mediated S-phase arrest of S1 did not interfere substantially with their induction of erythroid specific genes , as shown by the unperturbed induction of β-globin , Alas2 , and Band 3 ( Figure 3C , Figure S3E ) or with the upregulation of Ter119 ( Figure S3F ) . Therefore , S-phase progression is required for activation of erythroid-specific genes , specifically at the S0 to S1 transition , but not a few hours later when the cells have traversed into S1 . The lack of effect of aphidicolin on mRNA induction in S1 suggests its effects in S0 are not due to non-specific suppression of transcription . Transcripts for PU . 1 and GATA-2 are markedly downregulated at the transition from S0 to S1 ( Figure 3A ) . We examined whether S-phase arrest interferes with their downregulation . Sorted S0 cells were incubated in Epo for 4 h , at which time , just prior to their transition into S1 ( Figure 2C ) , aphidicolin was added to the cultures for a period of 10 h . Cells were then washed free of aphidicolin and incubated in Epo for a further 10 h . Aphidicolin halted the downregulation of both PU . 1 and GATA-2 , which resumed once the cells were washed free of the drug ( Figure 3D , E ) . Similar results were obtained in cells treated with mimosine ( Figure S3G ) . Therefore , S-phase progression is required for downregulation of PU . 1 and GATA-2 at the S0 to S1 transition . Of note , GATA-1 , Nfe2 , and Lmo2 mRNAs , which did not change significantly during the transition from S0 to S1 ( Figure 3A ) , were not altered significantly by the aphidicolin treatment ( Figure 3E , Figure S3H ) . We also examined the effects of aphidicolin or mimosine treatment on morphological maturation of S0 cells cultured in Epo . Following 10 h in Epo in the presence of aphidicolin or mimosine , cells appeared larger than cells incubated in Epo alone . This suggested that , while S-phase progression and the erythroid differentiation program had both arrested , cell growth was not perturbed ( Figure 3F ) . Cells were then washed free of aphidicolin or mimosine and cultured in Epo alone . By 20 h , erythroid maturation had resumed in cells that were initially incubated in cell cycle blocking drugs , as judged by decreasing cell size , nuclear condensation , and decreased nuclear to cytoplasmic ratio , but was nevertheless delayed when compared with control cells . These results are consistent with the effect of S-phase arrest on gene expression ( Figure 3B , D , E ) and suggest that S-phase progression at the S0 to S1 transition is a key requirement for activation of the erythroid differentiation program . Expression of p57KIP2 mRNA decreases over 30-fold at the S0 to S1 transition , and this is associated with downregulation of the p57KIP2 protein ( Figure 1G ) . To examine the effect of preventing p57KIP2 downregulation , we generated a point mutant of p57KIP2 , p57T329A , analogous to a proteolysis-resistant human p57KIP2 mutant [31] . Sorted S0 cells were infected with bicistronic retroviral vectors expressing either wild-type p57KIP2 or p57T329A , linked through an internal ribosomal entry site ( IRES ) to a human CD4 ( hCD4 ) reporter; control cells were infected with retroviral vector expressing the IRES-hCD4 construct only ( MICD4 ) . To allow expression of the transduced p57KIP2 , infected cells were cultured for 15 h in stem-cell factor ( SCF ) and interleukin 3 ( IL-3 ) , cytokines that sustain viability of progenitors but , unlike Epo , do not support differentiation from S0 to S1 . Infected S0 cells were then transferred to Epo for 14 h ( Figure 3G ) . Expression of either wild-type ( unpublished data ) or mutant p57KIP2 , but not expression of MICD4 , resulted in a block to S-phase progression and inhibited the transition from S0 to S1 ( Figure 3G ) . Further , PU . 1 mRNA was >3-fold higher in cells expressing p57KIP2 compared with control cells expressing vector only ( Figure 3H ) , suggesting that , as in the case of aphidicolin-mediated S-phase arrest , p57KIP2-mediated S-phase arrest prevents downregulation of PU . 1 at the transition from S0 to S1 . Erythroid morphological maturation , but not cell growth , of p57T329A-transduced cells was also arrested ( Figure S3I ) . Taken together , upregulation of CD71 , which defines the transition from S0 to S1 , identifies a key differentiation transition within the last generation of CFU-e ( “CFU-e . 2” , Figure 3I ) . It marks the onset of EpoR dependence and occurs exclusively during S-phase of the cell cycle . Induction of GATA-1 and other activators of the erythroid transcriptional program precedes this transition , whereas induction of erythroid-specific genes such as β-globin and Ter119 follows it . The S0 to S1 transition coincides with rapid downregulation of p57KIP2 , PU . 1 , and GATA-2 . Both Epo and S-phase progression are required for upregulation of CD71 . S-phase progression at the S0 to S1 transition requires the downregulation of p57KIP2 and is in turn required for the downregulation of PU . 1 and GATA-2 and the subsequent activation of erythroid-specific genes . By contrast , S-phase arrest in S1 cells does not affect erythroid gene activation ( Figures 3C , S3E–F ) . Both PU . 1 and GATA-2 were rapidly and dramatically downregulated at the transition from S0 to S1 ( Figure 3A , Figure S3A ) . We examined the effect of preventing this downregulation by expressing either PU . 1 ( Figure 4A–D ) or GATA-2 ( Figures 4E , S4C , D ) in S0 cells using retroviral constructs and a similar strategy to that described above for p57KIP2 . Following infection , S0 cells were cultured for 15 h in IL-3 and SCF and then transferred to Epo for 24 h , when CD71/Ter119 and cell cycle profiles were examined ( Figure 4A–C ) . We divided the PU . 1 expression profile at t = 24 h into 7 sequential hCD4 gates labeled ( i ) to ( vii ) ( Figure 4A ) , each containing cells with increasing levels of the hCD4 reporter and , therefore , increasing levels of PU . 1 . By measuring PU . 1 protein directly in fixed and permeabilized cells using a PU . 1-specific antibody and flow-cytometry , we found that hCD4 protein expression was a reliable reporter of exogenous PU . 1 protein expression in our system ( Figures 4D , S4A–B ) ; expression of transduced PU . 1 was also measured by qPCR ( Figure S4D ) . Sequential hCD4 gates were also obtained for control cells expressing the empty MICD4 vector . PU . 1 expression blocked transition from S0 to S1 , with the number of cells transitioning into S1 declining as PU . 1 expression increased ( Figure 4B , upper panels ) . PU . 1 expression also resulted in a decrease in the number of S-phase cells , with cells arresting principally at the transition from G1 to S-phase , though there was also an increase in the number of cells within G2 or M ( Figure 4B , lower panels ) . The decrease in the number of cells in S1 was paralleled by decreased S-phase cell number , suggesting a direct correlation between the PU . 1-mediated block of the transition from S0 to S1 , and its inhibitory effect on S-phase ( Figure 4C ) . Therefore , PU . 1 inhibits both S-phase and erythroid differentiation at the S0 to S1 transition . Since the downregulation of both PU . 1 and p57KIP2 are required for S-phase progression and for the transition from S0 to S1 ( Figure 3G , Figure 4B , C ) , we examined whether PU . 1 may be a regulator of p57KIP2 . However , we found that exogenous expression of PU . 1 did not prevent downregulation of p57KIP2 ( Figure S4E ) . Therefore , PU . 1's inhibitory effect on S-phase is not mediated via p57KIP2 . In contrast to PU . 1 , expression of GATA-2 in S0 cells did not prevent transition into S1 , though it somewhat reduced the subsequent transition from S1 to S2 ( Figure 4E ) . GATA-1 overexpression in S0 cells had the opposite effect , of promoting the transition from S1 to S2 . There was no significant effect of either GATA-1 or GATA-2 on the cell cycle profile ( Figure 4E ) . A long-standing hypothesis suggests that DNA replication may provide an opportunity for the restructuring of chromatin at tissue-specific gene loci [4] , [5] . Given the requirement for DNA replication for the transition from S0 to S1 , we asked whether chromatin change may be taking place at this time . The β-globin gene locus ( Figure 5A ) is a well-studied model of tissue-specific gene expression . The features that characterize the open chromatin conformation at the actively transcribed locus in erythroid cells have been established , but the time during development when the active chromatin conformation is acquired is not known . We therefore set out to examine whether the S0 to S1 transition might coincide with an alteration in the structure or function of chromatin at this locus . The timing of replication of the β-globin locus is correlated with its chromatin state . In higher eukaryotes the timing of replication of genes correlates with their transcriptional activity [32] . Housekeeping genes replicate early in S-phase , whereas silent chromatin and heterochromatin replicate late . The β-globin locus replicates in mid to late S-phase in non-erythroid cells , and early in S-phase in erythroid cells [33] . We examined the timing of replication of the β-globin locus in S0 and S1 cells sorted from fresh fetal liver . Individual alleles were identified using fluorescence in situ hybridization ( FISH ) with a probe directed at the β-major gene . Cells in S-phase were identified by positive staining for BrdU incorporation . Nuclei from at least 100 S-phase cells from either S0 or S1 were examined in each of two experiments ( Figure 5B ) . Using this approach , two single dots ( “SS” ) suggest that neither of the β-globin alleles had yet replicated . Nuclei in which both alleles have replicated contain a pattern of two double dots ( “DD” ) . Replication of only one allele results in one single and one double dot ( SD ) [33] . We found that the number of cells with a DD pattern increased from only 15% in S0 to over 50% in S1 ( Figure 5B ) , suggesting a switch in the timing of replication from late to early S-phase . In addition , an average of 36% of S0 cells , but only 21% of S1 , had an SD pattern , consistent with a switch from late , asynchronous replication in S0 to early , synchronous replication in S1 [33] . A key indicator of open chromatin at the β-globin LCR is the presence of hypersensitivity ( HS ) sites ( Figure 5A ) . We prepared nuclei from freshly sorted S0 or S1 cells and tested their sensitivity to DNase I digestion . Following digestion , we measured remaining DNA using quantitative PCR , with amplicons within HS2 , HS3 , and HS4 [34] . Results were expressed as a ratio to the DNase I resistant , non-expressing neural gene , Nfm . We found that S0 cells were relatively resistant to DNase I , while S1 cells were hypersensitive at all tested HS sites ( Figure 5C ) . Therefore , the S0 to S1 transition coincides with the onset of DNase I hypersensitivity at the β-globin LCR . We also examined E12 . 5 EpoR−/− whole fetal livers , which do not contain S1 cells ( Figure 1B ) . We found that EpoR−/− fetal livers were resistant to DNase I , whereas whole fetal livers from wild-type or heterozygous littermates showed the expected hypersensitive sites ( Figure 5D ) . We therefore concluded that DNase I hypersensitivity develops at the S0 to S1 transition , synchronously with the onset of EpoR dependence . Since the transition from S0 to S1 coincides with , and requires , S-phase progression , we examined whether development of DNase I hypersensitivity at the β-globin LCR also requires S-phase progression . We incubated sorted S0 cells in Epo , in the presence or absence of aphidicolin , for 10 h . Over this period 25%–50% of S0 cells transition into S1 , a process arrested by aphidicolin ( Figures 1H , 2C ) . At the end of a 10-h incubation period , nuclei were prepared and digested with varying concentrations of DNase I . There was a clear increase in DNase I sensitivity in cells incubated in Epo alone , relative to cells incubated in Epo and aphidicolin ( Figure 5E ) . Therefore , the development of DNase I hypersensitivity at the S0 to S1 transition is dependent on S-phase progression . The switch in timing of replication and in DNase I hypersensitivity at the S0 to S1 boundary suggested the β-globin LCR was undergoing structural changes . To investigate these , we used chromatin immunoprecipitation ( ChIP ) to determine specific histone tail modifications at the β-globin LCR in freshly sorted S0 , S1 , and in fetal brain . We used ChIP-qPCR for amplicons at the β-globin LCR HS sites , or at a control , neural gene , Nfm . Changes in histone modifications were expressed as a ratio , between S0 and either S1 or fetal brain ( Figure 5F , G ) . Figure 5F summarizes data pooled from seven experiments with various immunoprecipitating antibodies as indicated . A comparison of S1 with S0 shows a 7-fold decrease in trimethylation of histone 3 lysine 27 ( H3K27me3 , p = 0 . 019 , paired t test ) , a mark associated with silent chromatin , and a 2 . 5-fold increase in histone 3 lysine 4 dimethylation , a mark associated with active chromatin ( H3K4me2 , p = 0 . 032 ) , at the HS2 site of the β-globin LCR . A similar trend for these two modifications was also found at other HS sites ( p = 0 . 0006 and p = 0 . 011 for H3K4me2 and H3K27me3 , respectively , pooling all HS sites ) . An increase in acetyl marks in histones H3 and H4 associated with active chromatin was also seen consistently across the HS sites tested , though it did not reach statistical significance . Of note , no significant changes in histone marks were found between S0 and S1 at the Nfm gene . Further , there was no significant change in total histone occupancy of the HS sites between S0 and S1 , as determined by ChIP with antibodies directed against total H3 and H4 ( Figure 5F ) . We noted that H3K27me3 , associated with silent chromatin , and H3K4me2 , associated with active chromatin , were both enriched in S0 compared with fetal brain ( Figure 5G , lower panel ) . These results were suggestive of bivalent chromatin at the β-globin LCR in S0 , and loss of the repressive H3K27me3 mark with transition into S1 ( Figure 5G , upper panel , 5F ) . We examined DNA methylation of six CpG dinucleotides , three each at the HS1 and HS2 sites of the β-globin LCR ( Figures 5A , 6A ) . Genomic DNA was prepared from sorted hematopoietic cell subsets from fresh fetal liver , including S0 , S1 , megakaryocytic CD41+ , myeloid Mac-1+ , and Lin−Sca1+Kit+ ( LSK ) cells , enriched for hematopoietic stem-cells . We also examined EpoR−/− fetal livers depleted of cells expressing lineage markers , and fetal brain . DNA methylation at each of the six CpGs was obtained following bisufite conversion of genomic DNA , PCR amplification at HS1 and HS2 , and pyrosequencing . In fetal brain methylation levels were high , at ≈60%–80% , for all six CpG dinucleotides . Methylation levels were lower in all hematopoietic cell subsets ( Figure 6A ) . Methylation levels were largely similar in all hematopoietic , Epo-independent cell subsets examined: LSK , Mac-1+ , CD41+ , S0 , and EpoR−/− cells . The onset of Epo dependence in S1 was associated with a marked reduction in DNA methylation in all six CpG dinucleotides , with the level of methylation dropping to virtually undetectable levels in S1 for four of the six CpGs . We found that DNA demethylation also took place in freshly sorted S0 cells allowed to differentiate in vitro ( Figure 6B , C ) . Demethylation in vitro occurred earlier at the HS1A , B , C , and HS2C than at HS2A , B ( Figure 6C , red lines ) , in agreement with results in vivo ( Figure 6A ) . Demethylation in vitro was arrested at all CpGs if either aphidicolin or mimosine were added to the incubation medium , and resumed when these drugs were removed ( Figure 6B , C ) . Therefore , DNA demethylation , initiated at the transition from S0 to S1 , is dependent on S-phase progression . These results are suggestive of a passive demethylation process , due to loss of maintenance methylation at nascent DNA . We examined HS1 and HS2 DNA methylation levels in S0 cells transduced with PU . 1 ( as in Figure 4A ) and incubated in Epo for 24 h . DNA methylation was significantly higher at 3 of the 6 CpGs in S0 cells transduced with PU . 1-ICD4 , compared with control cells transduced with MICD4 ( Figure 6D ) . Therefore , PU . 1 expression , along with its inhibitory effect on erythroid differentiation , also impaired DNA demethylation , possibly due to its inhibitory effect on S-phase in these cells ( Figure 4C ) .
PU . 1 , whose physiological function in erythropoiesis had not been clear , plays a pivotal role at the S0 to S1 transition , through its cross-antagonism with S-phase progression . This cross-antagonism is lineage and differentiation stage-specific , since it presumably does not operate in myeloid and B-cell lineages where PU . 1 is an essential transcriptional activator . Similarly , within the erythroid lineage , this mutual antagonism must be activated specifically in the last generation of CFU-e . Its premature activation at an earlier CFU-e cycle may be predicted to result in premature transition into S1 and consequently , in a reduced number of differentiated progeny . This prediction helps explain previous observations , where erythroid cells from PU . 1-null embryos were found to differentiate prematurely and to have reduced self-renewal capacity [36] . These observations are consistent with the PU . 1-null phenotype mimicking premature downregulation of PU . 1 . The mutual inhibition between PU . 1 and S-phase may also explain findings in the T-cell lineage , where exogenous expression of PU . 1 at the pro-T cell stage was found to block both thymocyte expansion and differentiation [37] . Previous work documented cross-antagonism between PU . 1 and GATA-1 , showing them to interfere with each other's transcriptional functions through a variety of mechanisms including direct physical binding [11]–[14] . We propose that the activation of erythroid terminal differentiation at the S0/S1 boundary is due to functional activation of GATA-1 ( Figure 7B ) . Though present in S0 cells prior to the transition into S1 ( Figure 3A ) , GATA-1 function is inhibited by PU . 1 . Downregulation of PU . 1 at the S0 to S1 transition alleviates this inhibition , allowing GATA-1-mediated activation of erythroid gene induction . Among its known targets , GATA-1-mediated transcriptional repression of GATA-2 [29] would account for our observation that GATA-2 is downregulated at the S0 to S1 transition ( Figure 3A ) . This scheme places the decrease in GATA-2 downstream of the cross-antagonism between PU . 1 and GATA-1 ( Figure 7B ) and explains why exogenous high levels of GATA-2 , unlike PU . 1 , do not block the transition from S0 to S1 ( Figure 4 ) . Based largely on immortalized progenitor-like cells , the antagonism between GATA-1 and PU . 1 was proposed to underlie a binary cell fate choice in cells expressing both GATA factors and PU . 1 . An increase in GATA-1 would result in PU . 1 suppression and the erythro-megakaryocytic cell fates , whereas an increase in PU . 1 would suppress GATA-1 and give rise to the myelo-lymphocytic lineages [11]–[14] . However , our data show that CFU-e cells , considered committed erythroid progenitors , express PU . 1 at levels equivalent with those found in cells of the myeloid lineage ( Figure S3A ) . Our results are consistent with previous reports of PU . 1 expression in early erythroid progenitors , including the expression of a GFP reporter “knocked in” to the PU . 1 gene locus in S0 ( CD71lowTer119negative ) fetal liver cells [36] , [38] . The biochemical nature of commitment to the erythroid lineage is unknown at present . It is possible that CFU-e cells prior to PU . 1 downregulation , which are also expressing GATA-1 and GATA-2 , are in fact multipotential cells that may give rise to either myeloid or erythro-megakaryocytic lineages . In this case , the cross-antagonism between PU . 1 and GATA-1 would simultaneously be responsible for a lineage choice , as well as facilitate activation of the erythroid gene expression program at the S0 to S1 transition should this choice be in favor of the erythroid lineage . Our ability to isolate CFU-e cells expressing high levels of PU . 1 prior to their transition into S1 should facilitate further study of this issue . Why is S-phase progression coupled to the erythroid differentiation program at the S0 to S1 boundary ? Linking developmental transitions to cell cycle phases may serve as a strategy for their correct developmental timing [39] and may ensure the correct number of differentiated progeny . Another possibility is that S-phase progression plays a direct role in the re-configuration of chromatin at erythroid-specific gene loci . DNA replication was proposed to provide an opportunity for structural changes in chromatin , since the passage of the replication fork transiently disrupts nucleosomes [4] , [5] . Indeed , S-phase is essential for activation or silencing of some genes in yeast [40] , [41] and metazoa [39] , [42]–[45] , though it is not known that this is due to a requirement in the reconfiguration of chromatin . However , S-phase is not required for activation of other developmental genes [46]–[50] . Further , in recent years the structure of chromatin was found to be much more dynamic outside S-phase than originally suspected [51] . It is therefore unclear whether there is an innate requirement for DNA replication in the reconfiguration of chromatin during activation of lineage-specific genes , or what specific aspects of chromatin restructuring might require S-phase . Here we found that S-phase is required for DNA demethylation and for formation of DNase I hypersensitive sites . The requirement for DNA replication suggests that DNA demethylation is passive , due to a decrease in maintenance methylation of the nascent DNA strand [52] . This raises the possibility that formation of DNase I hypersensitive sites may require DNA replication because it might be contingent on DNA demethylation . Alternatively , DNase I hypersensitivity may require S-phase progression in order to lift a direct repressive effect of PU . 1 on chromatin [13] . Our examination of EpoR−/− fetal liver shows that the EpoR becomes essential for erythroid differentiation at the S0/S1 boundary . The principal function of EpoR at this time is its pro-survival signaling: EpoR−/− erythroid progenitors undergo apoptosis but their cell cycle status is unaltered , suggesting that EpoR signaling is not required for S-phase progression ( Figure S1E ) . These findings are consistent with the established role of EpoR as a survival factor that does not affect the erythroid cell cycle [53] . EpoR signaling is probably also dispensable for downregulation of PU . 1 at the S0 to S1 transition , since both PU . 1 and GATA-2 are low in EpoR−/− cells ( Figure 3A ) . In spite of both S-phase progression and PU . 1 downregulation being apparently unimpaired , EpoR−/− cells fail to develop DNase I HS sites and fail to undergo DNA demethylation at the β-globin LCR ( Figures 5D , 6A ) . It has been reported that exogenous expression of bcl-xL facilitates Epo-independent differentiation of erythroblasts [54] arguing against a direct requirement for EpoR signaling in chromatin reconfiguration . Therefore , EpoR−/− cells may be undergoing rapid apoptosis prior to the time when the chromatin change would have otherwise taken place . Other than its survival function , EpoR is probably directly required for CD71 upregulation , via Stat5 [55] , [56] . However , EpoR signaling results in CD71 upregulation only if S-phase is allowed to proceed ( Figure 2 ) . Thus , while the onset of Epo dependence occurs synchronously with committal chromatin and transcriptional events in erythroid differentiation , there is apparently no direct requirement for EpoR signaling in these events , other than ensuring cell survival . The principal function of Epo in erythropoiesis is to determine the number of differentiated erythrocytes , via Epo concentration [57] . The S0 to S1 transition may have evolved as the time of onset of Epo dependence as it represents a biochemical commitment to erythroid differentiation , setting in motion chromatin and transcriptional transformations that lead to expression of erythroid-specific genes . This therefore represents the earliest time in erythroid differentiation when Epo may regulate cell number specifically within the erythroid lineage , with minimal lateral effects on other hematopoietic cells . The β-globin LCR had long been studied as a model of chromatin at sites of lineage-specific genes . However , the time in erythroid differentiation when the locus switches from a “closed” to an “open” conformation had not been clearly defined . Further , it was not known whether activation of the locus develops in a step-wise fashion over several cell cycles and differentiation stages or whether it occurs rapidly in a single step . Our findings show that , strikingly , the locus transitions to an active conformation rapidly , within S-phase of a single cell cycle . Further , several distinct functional and biochemical changes that characterize the active chromatin conformation appear to develop simultaneously . We found marked differences between S0 and S1 cells in DNA methylation and in DNase I hypersensitivity at the LCR . These transformations could be reproduced when purified S0 cells transitioned into S1 in vitro ( Figures 5 , 6 ) . Both DNA demethylation and DNase I hypersensitivity required S-phase progression for their development . Further , we also found that development of histone-tail modifications characteristic of active chromatin , as well as the switch in the timing of replication of the locus from late to early S-phase , both coincide with the transition from S0 to S1 ( Figure 5 ) . Therefore , our findings support an “all or none” model for the state of chromatin , previously hypothesized based on the probabilistic nature of developing DNase I hypersensitivity in a range of mutated chicken β-globin enhancer constructs [58] . Previous work showed that while the highest levels of DNase I accessibility at the β-globin LCR are attained in mature erythroid progenitors , the β-globin LCR is already poised for expression in earlier multipotential progenitors , contributing to low-level β-globin transcription ( “priming” ) [59] , [60] . The β-globin LCR was found to already contain DNase I hypersensitive sites in cell lines resembling early hematopoietic progenitors [61] . Here we find that the β-globin LCR appears poised for change prior to the transition from S0 to S1 . Thus , LSK and S0 cells have similar DNA methylation levels that are substantially lower than in fetal brain , suggesting chromatin already primed for expression at the LSK stage ( Figure 6A ) . Histone tail modifications in the LCR similarly suggest that chromatin in S0 is poised for change , as it is enriched with both H3K4me2 , a mark associated with active chromatin , and with H3K27me3 , a mark found in silent chromatin ( Figure 5G ) . The LCR is therefore marked as a bivalent domain , which may denote chromatin that is silent but primed for activation [62] , [63] . Regardless of the precise state of chromatin readiness in earlier hematopoietic progenitors , however , our results show a clear switch in chromatin conformation at the S0 to S1 transition . The clear switch we identified at the β-globin LCR occurs in synchrony with other switch-like transformations at the transition from S0 to S1 , including the onset of Epo dependence and activation of GATA-1 function . Our ability to identify this transition with precision in vivo and manipulate it genetically in vitro should facilitate further study of the pivotal link between the cell cycle clock and the committal chromatin decisions that bring about the erythroid phenotype .
Fetal livers ( E12 . 5–E14 ) were mechanically dissociated and immunostained as described [64] . Immunofluorescence was measured on an LSRII ( BD Biosciences , CA ) and data analyzed using FloJo ( Tree Star , CA ) . Cells were sorted on a FACSAria , FACSVantage ( BD Biosciences ) , or MoFlo ( Beckman Coulter ) cell sorters . In a small number of experiments StemSep columns ( StemCell Technologies ) were used . Freshly harvested fetal liver cells were sorted and cultured in medium containing 20% fetal calf serum and 2 U/ml Epo ( Amgen ) for up to 48 h . BrdU ( 100 µl of 10 mg/ml ) was injected intra-peritonealy to pregnant mice and embryos were harvested 30–50 min later . In vitro , cells were pulsed with BrdU for 30 min . BrdU incorporation was detected using BrdU flow kit ( BD Biosciences ) . Cell tracking with CFSE ( carboxyfluorescein diacetate succinimidyl ester ) was performed on sorted S0 , incubated with 2 . 5 µM CFSE ( Invitrogen ) for 10 min at 37°C . Retroviral transduction was by spin infection of sorted S0 cells at 2 , 000 rpm , 37°C on fibronectin coated dishes in 5 µg/ml polybrene ( Sigma ) . Transduced cells were incubated overnight in the presence of 100 ng/ml SCF and 10 ng/ml IL3 ( Peprotech , Rocky Hill , NJ ) and were then transferred to Epo-containing medium for the indicated times . Quantitative RT-PCR was performed as described [64] . DNase I hypersensitivity assays were performed as described [34] with modifications to amplicons ( see Supplemental Methods ) . ChIP-qPCR was performed on 106 cells/sample of sorted S0 , sorted S1 , or fetal brain . Cells were cross-linked in 1% formaldehyde , sonicated , and incubated overnight with a range of antibodies ( see Supplemental Data ) , followed by 3–4 h of incubation with Protein G-magnetic beads ( Invitrogen ) . Cross-links were reversed and purified DNA measured by qPCR using the same amplicons as in the DNase I hypersensitivity assay . Genomic DNA or cells were treated with sodium bisulfite ( Zymo Research , Orange , CA ) . Bisulfite-converted DNA was amplified by PCR and methylation levels measured using pyrosequencing at EpigenDx ( Worcester , MA ) . See Text S1 for additional methods , primer sequences , and antibodies . | Hematopoietic progenitors that give rise to mature blood cell types execute simultaneous programs of differentiation and proliferation . One well-established link between the cell cycle and differentiation programs takes place at the end of terminal differentiation , when cell cycle exit is brought about by the induction of cyclin -dependent kinase inhibitors . It is unknown , however , whether the cell cycle and differentiation programs are coordinated prior to cell cycle exit . Here , we identify a novel and unique link between the cell cycle clock and the erythroid ( red blood cell ) differentiation program that takes place several cell division cycles prior to cell cycle exit . It differs from the established link in several respects . First , it takes place at the onset , rather than at the end , of erythroid terminal differentiation , preceding the chromatin changes that enable induction of red cell genes . Second , it is initiated by the suppression , rather than the induction , of a cyclin -dependent kinase inhibitor . It therefore causes the cell to enter S-phase , rather than exit the cell cycle . Specifically , we found that there is an absolute interdependence between S-phase progression at this time in differentiation , and a key commitment step in which , within a short few hours , cells become dependent on the hormone erythropoietin , undergo activating changes in chromatin of red cell genes , and activate GATA-1 , the erythroid master transcriptional regulator . Arresting S-phase progression at this time prevents execution of this commitment step and subsequent induction of red cell genes; conversely , arresting differentiation prevents S-phase progression . However , once cells have undergone this key commitment step , there is no longer an interdependence between S-phase progression and the induction of erythroid genes . We identified two regulators that control a “synchromesh” mechanism ensuring the precise locking of the cell cycle clock to the erythroid differentiation program during this key commitment step . | [
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] | 2010 | A Key Commitment Step in Erythropoiesis Is Synchronized with the Cell Cycle Clock through Mutual Inhibition between PU.1 and S-Phase Progression |
The 3-O-sulfotransferase ( 3-OST ) family catalyzes rare modifications of glycosaminoglycan chains on heparan sulfate proteoglycans , yet their biological functions are largely unknown . Knockdown of 3-OST-7 in zebrafish uncouples cardiac ventricular contraction from normal calcium cycling and electrophysiology by reducing tropomyosin4 ( tpm4 ) expression . Normal 3-OST-7 activity prevents the expansion of BMP signaling into ventricular myocytes , and ectopic activation of BMP mimics the ventricular noncontraction phenotype seen in 3-OST-7 depleted embryos . In 3-OST-7 morphants , ventricular contraction can be rescued by overexpression of tropomyosin tpm4 but not by troponin tnnt2 , indicating that tpm4 serves as a lynchpin for ventricular sarcomere organization downstream of 3-OST-7 . Contraction can be rescued by expression of 3-OST-7 in endocardium , or by genetic loss of bmp4 . Strikingly , BMP misregulation seen in 3-OST-7 morphants also occurs in multiple cardiac noncontraction models , including potassium voltage-gated channel gene , kcnh2 , affected in Romano-Ward syndrome and long-QT syndrome , and cardiac troponin T gene , tnnt2 , affected in human cardiomyopathies . Together these results reveal 3-OST-7 as a key component of a novel pathway that constrains BMP signaling from ventricular myocytes , coordinates sarcomere assembly , and promotes cardiac contractile function .
Vertebrate heart development requires an accurate integration of patterning and morphogenetic events , leading eventually to the formation of a fully functional heart . It initiates with the specification of the different tissue lineages that will compose the mature heart , followed by an intricate set of differentiation events that will transform the early heart field into a mature , beating organ . This transformation is defined by the subspecialization of regions of the primitive heart tube to acquire characteristics of contractile myocardium or region-specific maintenance of noncontracting myocardium . These complex events are orchestrated by a network of signals and transcription factors that could act differentially depending upon specific spatiotemporal cues . Among the important players are major signaling pathways such as BMP signaling and Wnt signaling , which set the early stages of differentiation [1]–[4] , and the T-box ( Tbx ) family of transcription factors that confer chamber or nonchamber identity to the primitive heart tube [5] . Ultimately , generation of a beating heart is the goal of these processes . For the heart to contract , contractile proteins must be produced and assembled into sarcomeres and their contraction must be coupled to the cycling electrophysiological activity . The heart starts beating during the late stages of heart tube formation and through its mechanical action , affects subsequent differentiation steps as shown in studies correlating defective morphogenesis with abnormal function [6]–[9] . Despite this understanding of heart development , critical questions remain in the field and unknown players remain to be discovered . In this study , we focus on the role in heart development of an enzyme , 3-O-sulfotransferase-7 ( 3-OST-7 ) , that modifies heparan sulfate proteoglycans ( HSPGs ) . HSPGs are cell surface and extracellular matrix ( ECM ) molecules composed of a core protein to which glycosaminoglycan ( GAG ) chains are covalently linked . The ability of HSPGs to interact with signaling ligands and receptors and ECM components place them at a unique advantage to modulate complex biological processes such as morphogenesis , tissue repair , and host defense [10]–[12] . The specificity of interactions of an HSPG and its environment is due , in part , to the GAG chains [12]–[14] . The GAG chains in HSPGs are unbranched , charged polysaccharides composed of 50 or more repeating disaccharide units of N-acetylglucosamine and glucuronic acid . These chains are subjected to several kinds of modifications: N-deacetylation/N-sulfation , epimerization , and O-sulfation . Not all disaccharide residues are modified , resulting in GAG chains with relatively small clusters of modified units interspersed among large sections of unmodified units [15] . This gives rise to an astounding level of structural heterogeneity , producing GAG chains with varying specificities for protein binding [10] . The repertoire of modifying enzymes differs between cells [10] , which in theory could impact how a cell interacts with a ligand , a neighboring cell , or the ECM . Previous gene knockdown and knockout studies have begun to document the roles for these modifying enzymes [14] , but none has been implicated in heart development . In this study , we focus on a rare and specific kind of O-sulfation , 3-O-sulfation , performed by a family of enzymes , the 3-O-sulfotransferases ( 3-OSTs ) . 3-OSTs catalyze transfer of a sulfate group to the hydroxyl of the third carbon of N-sulfated glucosamine residues [15] . Previous work in our lab has identified and cloned the 3-OST family in zebrafish [16] . Gene expression analysis reveals dynamic spatial and temporal expression patterns for the eight 3-OST family members suggesting distinct roles in the developing embryo . Here we show that morpholino ( MO ) knockdown of one of eight 3-OST family members in zebrafish , 3-OST-7 ( aka hs3st1l1 ) , specifically results in a noncontracting cardiac ventricle at 48 hours post fertilization ( hpf ) . Surprisingly , electrical and calcium transients in cardiomyocytes appear to be normal , suggesting that normal electrophysiological signaling in cardiomyocytes is uncoupled from cardiomyocyte contraction . Further exploring the noncontracting phenotype , we show that 3-OST-7 functions to negatively regulate BMP signaling in cardiomyocytes and to allow tpm4 mRNA accumulation , which then allows normal sarcomere organization and contraction . The roles of 3-OST-7 and BMP signaling reveal a novel mechanism for the regulation of cardiac cell function .
To begin elucidating the role of 3-OST-7 in development , we injected zebrafish embryos with either a translation-blocking MO ( MO1 ) or a splice-blocking MO ( MO2 ) . Knockdown with MO2 was verified by reverse transcription ( RT ) -PCR analysis ( Figure 1I ) . Embryos injected with either MO exhibited similar phenotypes indicative of a cardiovascular phenotype: pericardial edema and blood pooling at 48 hpf ( Figure 1A and 1B ) . Visualizing the heart in living transgenic Tg ( cmlc2:gfp ) zebrafish [17] revealed that 3-OST-7 morphants had a hypoplastic cardiac ventricle that did not contract normally ( Figure 1F and 1G; Video S2 ) , resulting in poor blood circulation ( Video S4 ) . In contrast , sibling control embryos had normal cardiac contraction cycles , with sequential diastole and systole , and normal blood circulation ( Figure 1C and 1D , Videos S1 and S3 ) . In contrast to the ventricle in 3-OST-7 morphants , atrium contraction was normal and similar to control ( Figure 1C , 1D , 1F , and 1G ) . In embryos injected with MO2 , only 47%±1% ( n = 124 ) had normal ventricular contraction , whereas all control embryos had normal cardiac contraction ( n = 137 ) ( Figure 1J ) . To assess the specificity of 3-OST-7 knockdowns , we injected MOs against two other members of the 3-OST family , 3-OST-5 and 3-OST-3z , and found that MO-injected embryos had normal cardiac ventricular contraction ( Figure 1J ) . Knockdown of 3-OST-5 and 3-OST-6 resulted in other distinct phenotypes , including altered cilia function and left-right patterning [18] . Together , these results indicate that ventricular cardiac contraction defects are a specific phenotype of 3-OST-7 knockdown , and not knockdown of other members of the 3-OST family , including 3-OST-5 , a member of the same subgroup as 3-OST-7 . In order to determine what is causing the hypoplasticity of the 3-OST-7 morphant ventricle , we examined cell number and cell volume . Utilizing the transgene Tg ( cmlc2-DsRed-nuc ) [19] , which labels cardiomyocyte nuclei , we counted the total number of cardiomyocytes in both control embryos and 3-OST-7 morphants . The cardiomyocyte cell number was similar in control ( 298±10 , n = 10 ) and 3-OST-7 morphant ( 288±12 , n = 10 ) , indicating that changes in cell number were not the cause for the hypoplastic ventricle in 3-OST-7 morphants . In contrast , by measuring ventricular myocyte volume in 3D-reconstructions of optical sections of the cardiac tube , we found that the cellular volume of individual ventricular myocytes was significantly reduced in 3-OST-7 morphants compared to control embryos ( Figure 1E and 1H , p = 0 . 01 ) , thus suggesting that cell shape changes were correlated with the observed hypoplasticity of 3-OST-7 morphant ventricles . Individual atrial myocyte volume was similar ( p = 0 . 10 ) between control ( 207±11 µm3 , n = 7 ) and 3-OST-7 morphant ( 183±11 µm3 , n = 10 ) . When using MOs to knockdown gene function , an important control is to rescue MO phenotype by co-expression of the targeted gene . We utilized the Tol2kit cloning system [20] to create stable , germline-transmitted transgenic Tg ( β-actin:3-OST-7-IEP ) zebrafish that expressed 3-OST-7 under the control of the β-actin promoter for ubiquitous expression throughout early development . To preclude inhibition of transgenic expression of 3-OST-7 , the MO binding sequence is not present in the construct . We placed an IRES-EGFP-polyA ( IEP ) downstream of the 3-OST-7 coding region , which enabled identification of individual transgenic embryos expressing 3-OST-7 by co-expression of EGFP . Constitutive expression of 3-OST-7 reduced the contraction defect in 3-OST-7 morphants , compared to nontransgenic morphants ( Figure 1K ) . 3-O-sulfotransferases modify HSPGs , which typically function at the cell surface , making it possible that they modulate cell-cell signaling into 3-OST-expressing cell and/or into neighboring cells . 3-OST-7 is expressed ubiquitously early in development [16] . In the ventricle at 48 hpf , the myocardium is directly apposed to the endocardium , so either cell lineage could be a source for 3-OST-7 function . To refine our understanding of 3-OST-7 in cardiac ventricular contraction , we asked which ventricular cell lineage required 3-OST-7 in order to allow normal ventricular contraction . We created stable transgenic zebrafish lines that express 3-OST-7 under the control of the cmlc2 ( aka myl7 ) promoter in myocardial-specific lineages , or expressing 3-OST-7 under the control of the fli1 promoter in endothelial/endocardial-specific lineages . The 3-OST-7 MO binding sequence is not present in either construct , therefore the MO would not inhibit transgenic expression of 3-OST-7 . Both transgenes have an IRES-EGFP tag downstream of 3-OST-7 coding region , enabling identification of embryos that express 3-OST-7 in either endocardium or myocardium by co-expression of EGFP . These transgenic embryos were injected with 3-OST-7 MO and compared with nontransgenic , MO-injected sibling embryos . We observed significant rescue of ventricle contraction in morphants in which 3-OST-7 was expressed in endocardium , Tg ( fli1:3-OST-7-IEP ) , that was comparable to rescue by ubiquitously expressed 3-OST-7 in transgenic Tg ( β-actin:3-OST-7-IEP ) morphants ( Figure 1K ) . In contrast , transgenic expression of 3-OST-7 in cardiomyocytes by Tg ( cmlc2:3-OST-7-IEP ) was not sufficient to rescue cardiac contraction ( Figure 1K ) . While the fli1 driver rescues to the same extent as the ubiquitous driver , it is possible that other tissues might also utilize 3-OST-7 . Also , it should be noted that it is not possible to conclude that 3-OST-7 is not also required in cardiomyocytes earlier in development . Transgenic cmlc2 expression begins at approximately 16 hpf , while the fli1-driven transgene starts being expressed at approximately 12 hpf , as assessed by co-expression of EGFP with 3-OST-7 ( unpublished data ) . Thus , it is possible that the inability of the cmlc2:3-OST-7 transgene to rescue is due to expression that is too late to be effective . Nonetheless , these results indicate that expression of 3-OST-7 in endocardium is sufficient to rescue the contraction of myocardium , suggesting 3-OST-7 functions to regulate cell-cell signaling across these apposed tissues . We explored several possible causes of ventricular noncontraction in 3-OST-7 morphants , including alterations in cardiac patterning or cardiomyocyte development . We used in situ hybridizations ( ISH ) and transgenic fish to assess whether the heart field is correctly specified in 3-OST-7 morphants . Hand2 and nkx2 . 5 , whose combined expressions define cardiac precursor cells in the lateral plate mesoderm [21] , have similar expression patterns in both control embryos and 3-OST-7 morphants ( Figure S1A–S1D ) . Similarly , expression patterns of cmlc2 ( myocardial marker ) , amhc ( atrial marker ) , and vmhc ( ventricular marker ) were unaltered in 3-OST-7 morphants ( Figure S1E and S1F , S1I–S1L ) . Endocardial precursor patterning was similar in control and 3-OST-7 embryos ( Figure S1G and S1H ) , as assessed in Tg ( fli1:EGFP embryos ) [22] . Together these results demonstrate that heart field specification , early endocardial development , and myocardial development proceed normally in 3-OST-7 morphants , and that early mispatterning is not likely the cause for the noncontracting ventricle . To determine whether ventricular noncontraction in 3-OST-7 morphants was due to defects in cardiomyocyte physiology , we assessed coupling of contraction to excitation . A fully functional heart characteristically undergoes excitation-contraction coupling , a physiological process whereby an electrical stimulus ( action potential ) is converted to a mechanical response ( contraction ) [23] . We first assessed whether the morphant ventricle could generate action potentials and calcium transients . To record action potentials , we performed patch clamp analysis on either the atrium or ventricle ( Figure 2A and 2B ) as previously described [24] . As expected , atria of 3-OST-7 morphants generated action potentials comparable to atria of control embryos ( Figure 2C and 2D ) . Surprisingly , however , action potentials were also obtained for the noncontracting ventricles of 3-OST-7 morphants and these action potentials were similar to those recorded for ventricles of control embryos ( Figure 2E and 2F ) . Moreover , analysis of action potential parameters revealed that there were no statistically significant differences between control embryos and 3-OST-7 morphants ( Tables S1 and S2 ) . These results indicate that the ion channels responsible for generating and propagating these action potentials were intact and physiologically functional in 3-OST-7 morphants . A primary function of the cardiac action potential is to trigger the increase in intracellular calcium that initiates cardiac contraction [25] . To assess whether this increase occurs in 3-OST-7 morphant ventricles , we used two different techniques to image changes in intracellular calcium . In the first technique , explanted embryonic hearts were imaged by high-speed confocal microscopy using the calcium indicator Fluo-4 . The amplitude and the decay of recorded calcium transients were measured to assess the release and re-uptake of intracellular calcium . Similar calcium waves were observed in hearts of both control embryos and 3-OST-7 morphants ( Videos S5 and S6 ) . The 3-OST-7 morphant atria and ventricles generated calcium transients ( Figure 2H and 2J ) similar to those generated by atria and ventricles from control embryos ( Figure 2G and 2I ) . There were no significant differences in the calcium transient amplitude and calcium transient decay between ventricles of 3-OST-7 morphant embryos and ventricles of control embryos ( Figure 2K and 2L ) . In the second technique , 3-OST-7 MO or control MO was injected into transgenic Tg ( cmlc2:gCaMP ) s878 embryos [26] that allowed for live calcium imaging in intact zebrafish . Similar to the other technique , calcium waves were detected in 3-OST-7 morphant hearts ( Videos S7 and S8 ) and comparable optical maps were generated for both control embryos and 3-OST-7 morphants ( Figure 2M and 2N ) . There were no observed differences in conduction velocity . Together these results demonstrated the ability of the noncontracting ventricle of 3-OST-7 morphants to release calcium from the sarcoplasmic reticulum and to re-uptake it at the end of the cycle . These results indicate that the intracellular components that are critical for calcium cycling are functional in 3-OST-7 morphants . In addition , the normal propagation of calcium waves in 3-OST-7 morphant hearts indicates that the gap junctions and excitatory ion currents critical for normal cell-cell conduction were also intact . Our observations that action potentials and calcium transients were normal in 3-OST-7 morphants with noncontracting ventricles indicate that excitation was uncoupled from contraction . Moreover , this suggests that the failure of contraction in 3-OST-7 morphants might be due to defects in the myocardial contractile apparatus , which is the direct target of calcium ions released from the sarcoplasmic reticulum during electrical excitation of the heart . To determine whether ventricular noncontraction of 3-OST-7 morphants is due to aberrant sarcomeres , we used immunohistochemistry ( IHC ) and transmission electron microscopy ( TEM ) to visualize the sarcomeric structure of the heart . Using MF20 and phalloidin to stain sarcomeric myosin and the actin filaments , respectively , we found that these filaments were disorganized in 3-OST-7 morphant hearts compared to the orderly filament organization in hearts of control embryos ( Figure S2 ) . IHC analysis also showed diminished cardiac troponin T ( Tnnt2 ) and tropomyosin ( Tpm ) organization in 3-OST-7 morphant hearts ( Figure 3B and 3F ) compared to control embryo hearts ( Figure 3A and 3E ) . Myofibrils with distinct sarcomeric structures such as A-bands , I-bands , and Z-discs were evident by TEM in control hearts ( Figure 3C ) . In contrast , the myofibrils were reduced and disorganized in 3-OST-7 morphant hearts ( Figure 3G ) . Together these results demonstrate the noncontraction of the ventricle in 3-OST-7 morphants is correlated with disorganization of sarcomere proteins . Since it appears that 3-OST-7 is required for sarcomere organization , and for Tnnt2 and Tpm protein levels ( Figure 3B and 3F ) , we asked whether 3-OST-7 MO affects RNA transcript accumulation for either of these sarcomeric genes . ISH analysis of tnnt2 RNA expression at 20 hpf , 24 hpf , and 48 hpf in morphants revealed that tnnt2 transcript levels were similar to control ( Figure S3A , S3B , S3E , S3F , S3I , S3J ) . In contrast , transcript levels of tpm4 were reduced in 3-OST-7 morphants compared to control embryos ( Figures 3D , 3H , S3C , S3D , S3G , and S3H ) . In hearts obtained by bulk disruption of 48 hpf embryos [27] , tpm4 transcript levels were reduced 3 . 8-fold in 3-OST-7 morphants ( p = 6 . 2×10−4 ) , as assessed by microarray analysis . Similar to ISH data , tnnt2 transcript levels were unchanged in the microarray analysis ( p>0 . 05 ) . Together , these results suggest that 3-OST-7 MO leads to a reduction of tpm4 RNA accumulation , which then leads to reduced Tpm protein accumulation . We suggest that cardiac Tpm4 serves as a “lynchpin” protein downstream of 3-OST-7 function; when Tpm4 is reduced , sarcomeres fail to be stably organized , and other sarcomeric proteins are degraded in response . Consistent with this idea , tnnt2 RNA is present but Tnnt2 protein is diminished in 3-OST-7 morphants . We predicted that if Tpm4 serves as a lynchpin protein in 3-OST-7 function , then we should be able to rescue sarcomere organization and ventricular contraction in 3-OST-7 morphants by injection of tpm4 RNA . Injection of tpm4 RNA alone in control embryos had no perceived gross morphological effect , nor did it alter cardiac function ( Figure S4 ) . Strikingly , injection of tpm4 RNA in 3-OST-7 morphants rescued ventricular contraction as assessed by looking at contraction in 48 hpf embryos ( p = 0 . 0097 , Figure S4 ) and by measuring ejection area ( p<0 . 05 , Figure 3L ) . In keeping with the rescued ventricular contraction , tpm4 RNA injection in 3-OST-7 MO also rescued the organization and expression of sarcomeric proteins Tnnt2 and Tpm , and rescued the TEM appearance of sarcomeric structures in myofibrils ( Figure 3I–3K ) . In contrast with the ability of tpm4 RNA to rescue cardiac contraction in 3-OST-7 morphants , transient transgenic expression of tnnt2 did not rescue cardiac contraction . As a control , embryos that were transgenic for a construct that drives cardiac expression of tnnt2-IRES-EGFP under the control of the cmlc2 promoter had normal cardiac contraction . 3-OST-7 MO injected into this transgenic ( scored by EGFP expression ) resulted in decreased cardiac contraction , at frequencies comparable to 3-OST-7 MO in non-transgenic siblings ( Figure S5 ) . Together these results demonstrate that Tpm4 serves as a downstream lynchpin of 3-OST-7 function for normal cardiac ventricular contraction . In addition to myofibrillogenesis and onset of contraction , the cardiac maturation program involves a comprehensive patterning of myocardial cells into either contracting chamber myocardium ( atrium or ventricle ) or nonchamber , noncontracting myocardium ( sinus venosus , atrioventricular or AV canal , and outflow tract ) [28] , [29] . To determine whether this patterning occurs in 3-OST-7 morphants , we performed ISH for tbx2 ( tbx2b in zebrafish ) and anf in 48 hpf control embryos and 3-OST-7 morphants . Tbx2b is normally expressed in the AV canal ( nonchamber myocardium ) at 48 hpf [30] , and we observed a similar pattern of expression in both control embryos and 3-OST-7 morphants ( Figure 4A and 4D ) . Similarly , anf , which is normally expressed in atrium and ventricle ( chamber myocardium ) at 48 hpf , had a similar pattern of expression in 3-OST-7 morphants ( Figure S7C and S7D ) . Together these results suggest that 3-OST-7 morphants undergo normal patterning and segregation of chamber and nonchamber myocardium . We also investigated whether two major developmental signaling pathways , FGF and Notch signaling , are involved in 3-OST-7 regulation of ventricular contraction . FGF signaling was a strong candidate because it requires HSPG GAG chains for receptor-ligand complex formation [13] , [31]–[33] . If loss of contraction caused by knockdown of 3-OST-7 occurs through deficient FGF signaling , direct perturbation of FGF signaling should mimic the noncontracting ventricle phenotype of 3-OST-7 morphants . However , FGF receptor 1 ( fgfr1 ) knockdown resulted in ventricles that were smaller but had normal contractility ( Figure S6A ) . Similarly , reducing or abolishing FGF signaling either in the zebrafish fgf8/ace mutant or by treatment with the FGFR inhibitor SU5402 also resulted in small hearts with particularly notable reductions of the ventricle , but no reported alterations in contraction [34] , [35] . The normal cardiac contraction in FGF pathway manipulations suggests that FGF signaling is not a component of the 3-OST-7-dependent pathway . In Drosophila , the Notch pathway is dependent on 3-O-sulfation by 3-OST-B [36] . More importantly , deltaD , a Notch ligand , was one of the most downregulated genes in the microarray analysis comparing control embryo hearts and 3-OST-7 morphant hearts at 48 hpf ( 7 . 0-fold decreased , p = 1 . 86×10−2 ) . To determine whether 3-OST-7 regulates ventricular contraction by way of the Notch signaling pathway , we assessed whether the noncontracting ventricle phenotype is recapitulated in deltaD/aeiAG49 mutant embryos [37] . Embryos carrying a homozygous mutation in the deltaD gene were identified by misshapped somites posterior to the ninth somite [37] and separated from wild-type or heterozygous siblings at 18 hpf . The hearts were then scored for ventricular contraction at 48 hpf . Cardiac contraction was normal in deltaD/aeiAG49 mutants ( n = 34 mutants; n = 94 wild-type siblings ) . Since DeltaD is one of four Delta ligands in zebrafish , it is possible that other Delta ligands might be compensating for loss of DeltaD in deltaD/aeiAG49 mutants . To more broadly block Notch signaling , we used DAPT , a γ-secretase inhibitor . Continuous treatment from 5 hpf , when cells are fated to become myocytes [38] , to 48 hpf did not result in ventricular noncontraction at 48 hpf ( Figure S6B ) , but disrupted somite formation , indicative of treatment efficacy . Treatments during narrower developmental windows gave similar results , with normal cardiac contraction ( Figure S6B ) . Together these results suggest that Notch signaling is not a component of the 3-OST-7-dependent pathway for cardiac contraction . Bmp4 , versican , and notch1b expression patterns are progressively restricted to the AV junction during cardiac development . All three genes are expressed along the antero-posterior length of the heart at 24 hpf and are subsequently restricted to the AV canal and excluded from expression in the maturing ventricle by 48 hpf ( Figures 4B , 4C , and S7A ) , as previously reported [39]–[41] . However , in contrast to controls , in 3-OST-7 morphants bmp4 ( Figure 4F ) and versican ( Figure S7B ) were ectopically expressed in ventricles at 48 hpf . Bmp4 and versican remained ectopically expressed in ventricular myocytes at 3 days postfertilization ( n = 40 embryos ) . In contrast to bmp4 and versican , notch1B was expressed solely in the AV canal of 3-OST-7 morphants ( Figure 4E ) , similar to control embryos , and tie2 expression , assessed in Tg ( tie2:EGFP ) embryos , was expressed normally in the AV canal in both control and 3-OST-7 morphant embryos ( Figure S7E and S7F ) . Normal notch1B and tie2 expression suggest that the failure of bmp4 and versican to become AV canal-restricted was not merely due to developmental delay , nor to an overall mispatterning of AV boundaries . Together these results indicate 3-OST-7 morphant hearts achieve normal AV boundary formation , but fail to exclude bmp4 expression from ventricular myocytes . To investigate whether ectopic expression of bmp4 in the ventricle affects BMP signaling , we performed IHC for phosphorylated-Smad1/5/8 ( P-Smad ) , a downstream marker for Bmp signaling . P-Smad was localized most strongly in the nuclei of AV canal cells in control hearts ( Figure 4G ) , which corresponds to bmp4 being normally restricted to that region at 48 hpf . In contrast , P-Smad was found strongly expressed in the nuclei of ventricular cells in 3-OST-7 morphant hearts as well as in nuclei of AV canal cells ( Figure 4H ) , which corresponds to the ectopic expression of bmp4 in the ventricle . In order to quantify this effect , we divided the ventricle images into six domains ( domain 1 contains the AV junction and domain 6 was the region farthest from the AV junction ) and counted the number of P-Smad-positive nuclei within each domain ( Figure 4I ) . In 3-OST-7 morphants , an increased number of P-Smad-positive nuclei were present even in the domains farthest from the AV , while there were very few P-Smad positive nuclei outside the AV domain in control hearts . Interestingly , the number of P-Smad positive nuclei in 3-OST-7 morphants appears as a gradient , with the highest numbers close to the AV junction ( Figure 4I ) . We also utilized the transgenic Tg ( BRE:d2GFP ) fish [42] to visualize dynamic transcriptional response to BMP signaling in live embryos . In control embryos , GFP expression in the heart was observed primarily in the AV junction ( Figure 4J and 4K ) . In contrast , GFP expression was expanded to the whole ventricle in 3-OST-7 morphants ( Figure 4L and 4M ) , in keeping with the expanded bmp4 RNA expression and the expanded P-Smad nuclear staining . These results suggest that the role of 3-OST-7 is to confine bmp4 expression and downstream BMP response to the AV junction , and to prevent BMP signaling from spreading into ventricular myocardium at 48 hpf . To investigate whether other components of the BMP signaling pathway are involved in the 3-OST-7 morphant phenotype , we performed ISH analysis on nine BMP receptors at four different developmental timepoints ( 17 somite stage , 24 hpf , 36 hpf , and 48 hpf ) : bmpr1aa ( alk3a ) , bmpr1ab ( alk3b ) , bmpr1ba ( alk6a ) , bmpr1bb ( alk6b ) , bmpr2b , acvr1l ( alk8 ) , acvr2aa ( acvr2a ) , acvr2b , and acvrl1 ( alk1 ) ( Table S3 ) . Of these , bmpr2b and alk8 had altered heart expression in 3-OST-7 morphants , with strongly increased bmpr2b expression in the heart ( Figure S8C ) and alk8 expression in the outflow tract ( Figure S8D ) that were not observed in controls ( Figure S8A and S8B ) . The expansion of BMP signaling into the ventricular myocardium in 3-OST-7 morphants provides a correlation between absence of ventricular contraction and expanded or ectopic expression of bmp4 in ventricular myocardium . To determine whether this correlation occurs in other distinct pathways that lead to defective contraction , we examined bmp4 expression in morphants of the potassium channel gene kcnh2 and sarcomeric protein cardiac troponin T gene tnnt2 . Kcnh2 and tnnt2 mutants both have “silent” ( i . e . , noncontracting ) hearts and MO knockdown of these genes phenocopy the mutant phenotypes [24] , [43] , which we scored as percent of embryos with cardiac contraction defect ( Figure 5A ) . Bmp4 expression is significantly expanded in the kcnh2 and tnnt2 morphants ( Figure 5B ) , which we classified and scored in three categories: normal AV-restricted expression ( AV only , blue , Figure 5B ) , ectopic expression expanded into ventricle ( AV+V , red , Figure 5B ) , and ectopic expression expanded into both atrium and ventricle ( entire heart , green , Figure 5B ) . Strikingly , only 23 . 4% and 5 . 7% of embryos had normal AV-restricted expression with injection of kcnh2 and tnnt2 MO , respectively ( blue , Figure 5B ) . Most of the morphants ( 76 . 6% and 94 . 3% for kcnh2 and tnnt2 morphants , respectively ) had expanded , ectopic expression of bmp4 in the ventricle ( red and green , Figure 5B ) . Interestingly , in kcnh2 , tnnt2 , and 3-OST-7 morphants , the percentage of ectopic bmp4 expression correlated with percentage of noncontraction ( comparing Figure 5B and 5A ) . For example , knockdown of 3-OST-7 resulted in 56 . 9% of embryos having ventricular noncontraction ( Figure 5A ) and 48 . 8% had ectopic bmp4 expression ( red and green , Figure 5B ) , the least noncontraction and ectopic bmp4 expression fractions observed among the three MO knockdowns . In contrast , knockdown of tnnt2 resulted in 99 . 4% of embryos with noncontraction ( Figure 5A ) , the highest noncontraction fraction among the three knockdowns , which correlated with the highest fraction of ectopic bmp4 expression ( red and green , Figure 5B ) . These results demonstrate that the correlation between noncontraction and ectopic bmp4 expression is conserved in three very distinct models of defective cardiac contraction . The above results indicate a correlation between expanded BMP expression in ventricular myocytes and failure to contract , but they do not address causality . Is expansion of BMP expression , as seen in 3-OST-7 morphants , capable of preventing ventricular contraction ? To test the hypothesis that the ectopic expression of bmp4 in the ventricle causes a noncontracting phenotype , we utilized the transgenic Tg ( hsp70:bmp2b ) zebrafish [44] and performed heat-shock to induce BMP signaling . We crossed heterozygous Tg ( hsp70:bmp2b ) /+ fish to wild-type AB and subjected half of the progeny to heat-shock ( 37°C for 30 min ) at 12 hpf , while leaving the remaining half untreated ( Figure 6A ) . We scored for ventricular noncontraction , and then confirmed presence of the heat-shock transgene by PCR . We found that heat-shock at 12 hpf ( Figure 6A ) , but not at 24 hpf and 36 hpf ( Table S4 ) , resulted in ventricular noncontraction . These results indicate that ectopic overexpression of BMP is capable of blocking ventricular contraction , but do not test whether the expanded expression of BMP observed in 3-OST-7 morphants is causative of the noncontracting phenotype . If the function of 3-OST-7 is to reduce or constrain BMP expression from ventricular myocytes , and excessive BMP is causative of contraction defects in 3-OST-7 morphants , then reduction of endogenous BMP levels in 3-OST-7 morphants should alleviate the ventricular contraction defect . To test this hypothesis , we utilized the zebrafish bmp4st72 mutant [45] and asked whether genetic reduction of bmp4 will rescue the noncontracting ventricle phenotype caused by knockdown of 3-OST-7 . We injected 3-OST-7 MO into embryos from crosses between bmp4st72/+ heterozygotes , with uninjected embryos from the same genetic crosses serving as control ( Figure 6B ) . The embryos were then segregated by cardiac phenotype: normal hearts or noncontracting ventricles at 48 hpf . In some cases a slight AV morphological defect was also observed , as part of the bmp4st72 mutant phenotype seen in both uninjected and injected embryos , and these were counted among the normally contracting hearts . The individual embryos were then genotyped . In uninjected embryos , all embryos displayed normal cardiac contraction , regardless of wild-type , heterozygous , or homozygous genotype for bmp4st72 ( Figure 6B ) , indicating that cardiac contraction was not affected in the absence of 3-OST-7 MO . In siblings that were genotypically wild-type for bmp4 ( +/+ ) and injected with 3-OST-7 MO , the percentage of embryos with normal ventricular contraction was only 47 . 5% , similar to the range seen in other 3-OST-7 MO experiments ( Figure 6B ) . Strikingly , the percentage of embryos with normal cardiac contraction was increased for 3-OST-7 MO injected bmp4st72 mutants ( −/− ) , with 73 . 7% of these mutants having a contracting ventricle ( Figure 6B ) . Genomic DNA sequencing of the individual injected bmp4st72 mutants confirmed that the 3-OST-7 MO targeted sequence was correct in bmp4st72 mutants . These results indicate that reduction of endogenous BMP signaling is capable of rescuing ventricular contraction in 3-OST-7 morphants . Combined with the observation that ectopic BMP signaling can cause a noncontracting ventricle phenotype , these results indicate that 3-OST-7 functions to constrain BMP signaling to the AV junction and to reduce BMP signaling in the ventricle , thereby allowing normal cardiac ventricular contraction .
In this study we demonstrate that 3-OST-7 , one of the enzymes that places a rare 3-O-sulfation on GAG chains on HSPGs , has a novel and highly specific function in cardiac development . In 3-OST-7 knockdown zebrafish , early cardiac cell specification , patterning , cardiac tube looping , and cardiomyocyte electrophysiology are normal , but ventricle contraction is defective . We show that 3-OST-7 is required for the normal accumulation of tpm4 mRNA in the ventricle . Tpm4 protein appears to be a lynchpin in ventricular sarcomere assembly and stabilization , because overexpression of Tpm4 protein by tpm4 mRNA injection in 3-OST-7 morphants rescues the levels and organization of other sarcomeric proteins , rescues sarcomere structure , and rescues ventricular contraction . Tpm4 is also reduced in the atrium in 3-OST-7 morphants , but either this level of reduction is not sufficient to affect atrial contraction or some other contractile component might compensate functionally for diminished Tpm4 in the atrium . In contrast , transgenic overexpression of cardiac troponin T tnnt2 cannot rescue cardiac contraction in 3-OST-7 morphants . Thus , knockdown of 3-OST-7 uncouples contraction from the normally functioning excitation cycle by perturbing tpm4 mRNA accumulation , leading to defective myofibrillogenesis . This places the 3-OST-7-dependent 3-O-sulfation of extracellular GAG chains as the first member of an otherwise unknown signaling pathway that is upstream of tpm4 regulation and coordinated sarcomere assembly . We propose that 3-OST-7 functions in the endocardium by modifying HSPGs at the interface between endocardium and myocardium in order to constrain BMP signaling to the AV junction and dampen BMP signaling in functional myocardium ( Figure 7 ) . The cardiac ventricular contraction defect in 3-OST-7 morphants could be rescued by ubiquitous transgenic expression of 3-OST-7 and by lineage-specific expression in the endocardium , but surprisingly not by lineage specific expression in the myocardium . This would suggest 3-O-sulfation of HSPGs by 3-OST-7 mediates cell-cell communication between myocardium and endocardium to regulate tpm4 transcription ( Figure 7 ) . In the presence of normal 3-OST-7 function , BMP signaling is constrained to the AV junction and precluded from functional myocardium , as reflected in high levels of P-Smad in nuclei in the AV junction and little or no P-Smad in adjacent functional cardiomyocytes . Since 3-OST-7 appears to be ubiquitously expressed , the spatial regulation of BMP4 signaling is likely due to positive feedback loops within the BMP pathway that are constrained by 3-OST-7 function . Other studies support the idea of positive feedback loops , showing that ectopic BMP expression activates endogenous BMP expression in Xenopus embryos , and correspondingly , loss of BMP ligands swirl ( bmp2b ) , somitabun ( smad5 ) , or snailhouse ( bmp7 ) in zebrafish mutants results in loss of bmp2b expression [46]–[49] . We do not know whether this constraint on BMP signaling occurs by direct interaction of BMP4 and/or its receptors with 3-OST-7 modified HSPGs , or indirectly through other pathways , but it would be exciting in future studies to assess if BMP4 directly bind to specifically modified , 3-O-sulfated HSPGs . The constraint of BMP signaling allows functional cardiomyocytes to accumulate normal levels of tpm4 mRNA and Tpm4 protein , which then serves as a lynchpin for the organization of normal contractile apparatus . The importance of BMP regulation is evident both from the ability of excessive BMP signaling to block cardiac contraction and the ability of reduced BMP levels to rescue contraction in 3-OST-7 MO . In the absence of 3-OST-7 function , the normal endogenous BMP signaling that occurs in the AV junction at 48 hpf spreads ectopically into myocardium beyond its normal boundaries in the AV junction , most likely mediated by the BMP receptor BMPR2B , which we show to be ectopically expressed in 3-OST-7 morphant hearts . This results in high levels of P-Smad in the nucleus of ventricular myocytes . High levels of BMP signaling result in reduced levels of tpm4 mRNA , thereby removing the Tpm4 lynchpin and leading to failure of contractile apparatus organization . It is not known whether the reduction of tpm4 mRNA is due to direct transcriptional suppression by the increased levels of P-Smad in the ventricular nuclei , or to indirect effects . Thus , although ventricular myocytes have normal cycling calcium and electrophysiology , they are incapable of contracting . Interestingly , other models of cardiac noncontraction ( kcnh2 and tnnt2 morphants ) also display expanded expression of bmp4 , suggesting there might be an inappropriate positive feedback loop between overexpression of BMP and a failure of cardiomyocytes to contract . We would not expect manipulations of the BMP4 pathway to rescue ventricular noncontraction in the kcnh2 and tnnt2 morphants or mutants , since other critical components , of either the excitation-contraction coupling process or contractile machinery , are still missing . It is interesting to note that zebrafish tbx5 [50] , apc [51] , foxn4 [30] , and tmem2 [52] , [53] mutants that have a similar expansion of bmp4 expression in the ventricle also have poor contractility , although the noncontraction phenotype in these mutants appears to be less penetrant and have a later onset than 48 hpf . These genes have been shown to control AV canal formation , and experiments in the tmem2 mutants have shown that expanded bmp4 expression facilitates expansion of the AV canal markers hyaluronan synthase 2 and Alcama [53] , suggesting an expansion of noncontracting , nonchamber myocardium . Our results uncover a unique role for bmp4 in promoting a noncontracting , nonchamber myocardium in that other markers that distinguish between chamber and nonchamber myocardium were normal ( tbx2 , anf , and notch1b ) . The ability of bmp4 to drive myocardium toward noncontracting , nonchamber myocardium is constrained by 3-O-sulfation function ( Figure 7 ) . It is striking that the regulation of BMP signaling can be controlled by a rare modification of 3-O-sulfation on HSPGs , and that loss of this regulation has dramatic effects on the ability of the heart to function . Even more striking is that other 3-OST family members , many of which are expressed ubiquitously in these early stages of development [16] , do not compensate for the loss of 3-OST-7 . Knockdown of other 3-OST family members have distinct phenotypes and regulate other cell signaling pathways , including FGF signaling [18] , but do not have the cardiac ventricular contraction defect described here for 3-OST-7 . The regulation of ligand gradients and signaling by HSPG modification enzymes has been shown in Drosophila [11] , [14] , which has a limited number of genes for each step in the pathway . This level of precise regulation has not been described in vertebrates , in which each enzymatic step has large number of family members . Here , our results suggest that 3-OST-7 has a unique ability to generate a distinct modification on GAG chains of HSPGs , and this modification is necessary for the spatial regulation of BMP signaling during cardiac development , necessary for ventricle contraction .
All zebrafish experiments were performed in accordance to protocols approved by IACUC . Zebrafish were maintained under standard laboratory conditions at 28 . 5°C . In addition to Oregon AB wild-type , the following transgenic and mutant lines were used: Tg ( cmlc2:GFP ) [17] , ( Tg ( cmlc2-DsRed-nuc ) [19] , Tg ( fli1:EGFP ) [22] , Tg ( cmcl2:gCaMP ) s878 [26] , Tg ( hsp70:bmp2b ) [44] , Tg ( BRE:d2GFP ) [42] , bmp4st72 [45] , and deltaD/aeiAG49 [37] . MO oligonucleotides were obtained from Gene Tools , LLC . The following sequences and concentrations were used: translation-blocking 3-OST-7 MO1 , 5′-CACATAACTCAGAAGATTGGCCATG-3′ , 5 . 4 ng; splice-blocking 3-OST-7 MO2 , 5′- CACATCTGGAAGACACAAGAGAGAG-3′ , 1 . 8 ng; 3-OST-5 MO , 5′-GTCCAGTCAGGTCAAGGGCAGCTCA-3′ , 2 . 7 ng; 3-OST-3Z MO , 5′-GTCCAGTCAGGTCAAGGGCAGCTCA-3′ , 5 . 4 ng; translation-blocking kcnh2 MO [24] , 2 . 3 ng; translation-blocking tnnt2 MO [43] , 4 ng; translation-blocking fgfr1 MO1 [54] , 4 ng; and translation-blocking fgfr1 MO2 [54] , 8 ng . Embryos were injected at the 1–2 cell stage . The Tol2kit cloning system was used to generate Tg ( β-actin:3-OST-7-IEP ) , Tg ( cmlc2:3-OST-7-IEP ) , and Tg ( fli1:3-OST-7-IEP ) . Multisite recombination reactions were performed as previously described [20] . Transposase RNA was synthesized using mMessage mMachine kit ( Ambion ) . 25 pg of transposase RNA and 30 pg of β-actin:3-OST-7-IEP , cmlc2:3-OST-7-IEP or fli1:3-OST-7-IEP plasmid DNA were injected into wild-type AB fish at the one-cell stage . Potential transgenic founders ( TF ) were identified by scoring for GFP expression in hearts ( cmlc2:3-OST-7-IEP and fli1:3-OST-7-IEP ) or ubiquitous GFP expression ( β-actin:3-OST-7-IEP ) . Potential TFs were then crossed to wild-type AB fish to check for GFP expression . Those that gave GFP-positive transgenic embryos were subsequently used for rescue experiments where 3-OST-7 MO2 was injected into embryos from TF×AB matings . At 48 hpf , embryos were sorted by GFP fluorescence , then scored for ventricular noncontraction . For tpm4 rescue experiments , tpm4 RNA was synthesized using the mMessage mMachine kit ( Ambion ) from the linearized pXT7-tpm4-tv1 expression vector [55] . 175 pg of RNA was co-injected with 5 . 4 ng of 3-OST-7 MO1 at the one-cell stage . For tnnt2 rescue experiments , 25 pg of transposase RNA , 30 pg of cmlc2:tnnt2-IRES-EGFP [56] , and 5 . 4 ng 3-OST-7 MO1 were injected into wild-type AB fish at the one-cell stage . Those that gave GFP-positive transgenic embryos were scored for rescue of ventricular noncontraction . 48 hpf explanted hearts were placed in physiological solution containing 0 mM Ca2+ and 10 µM blebbistatin . The sarcolemma was labeled using wheat germ agglutinin conjugated to Alexa Fluor 555 ( Invitrogen ) . Using a confocal microscope ( LSM 5 Live Duo , Carl Zeiss ) equipped with a 40× oil immersion lens , samples were excited with a 543 nm laser and emission collected with a long-pass 560 nm filter . Image stacks were acquired with a resolution of 0 . 2 µm×0 . 2 µm×0 . 2 µm . Correction of depth-dependent attenuation , deconvolution , and 3D reconstruction of confocal images were performed as previously described [57] . Digoxigenin-labeled antisense riboprobes were synthesized using Digoxigenin RNA Labeling Kit ( Roche ) . cDNA plasmids encoding hand2 , nkx2 . 5 , cmlc2 , amhc , vmhc , tnnt2 , tpm4 [55] , bmp4 , versican , notch1B , anf , tbx2b , bmpr1aa ( alk3a ) , bmpr1ab ( alk3b ) , bmpr1ba ( alk6a ) , bmpr1bb ( alk6b ) , bmpr2b , acvr1l ( alk8 ) , acvr2aa ( acvr2a ) , acvr2b , acvrl1 ( alk1 ) [58] , sdc2 , sdc3 , and sdc4 were used . ISH were performed as previously described [59] , with anti-digoxigenin antibody incubation carried out using a Biolane HTI machine . Embryos were cleared in 70% glycerol and photographed with a Nikon SMZ1000 camera . Digital images were processed with Adobe Photoshop CS4 . Ca2+ transients were recorded as previously described [60] . Fluorescent signals ( F ) were normalized to baseline values ( Fo ) . The maximum Ca2+ transient amplitude ( FMax/Fo ) was determined by averaging the peak amplitude of three consecutive transient signals . The decay of the calcium transient was determined by a monoexponential fit of the decaying signal and averaging value of three consecutive transient signals . 48 hpf zebrafish was placed on a coverglass . Electromechanical isolation was achieved with 2 , 3-BDM ( Sigma ) at 10 mmol/l applied 15 minutes before imaging . Single plane widefield epifluorescence images of the heart were obtained with a Nikon TE-2000 inverted microscope using a 40× Plan Apo air objective , Xcite-120 ( Exfo ) widefield epifluorescent source and standard FITC filter set . Images were acquired with a Coolsnap HQ camera ( Photometrics ) using Metavue software ( Molecular Devices ) in stream acquisition mode at a frame rate of 30 ms/frame ( 512×512 pixels ) . Image processing consisted first of manual adjustment of minor spatial shifts of the image over a temporal imaging series . Then , the fluorescence intensity of each pixel in a 2D map was normalized to its percentage between the minimum and maximum recorded values of the pixel over the full series . Isochronal lines at 20 ms intervals were obtained by identifying the maximal spatial gradient for a given time point . The color-coded scheme in each panel and video describes progressive activation of the heart with white/red cells and black/blue cells indicating depolarization and repolarization , respectively . Software processing was performed with Metavue software and procedures written in MATLAB ( MathWorks ) . IHC using the primary antibodies MF20 ( Developmental Studies Hybridoma Bank , 1∶10 ) , CT3 ( Developmental Studies Hybridoma Bank , 1∶10 ) , CH1 ( Developmental Studies Hybridoma Bank , 1∶10 ) , and P-Smad1/5/8 ( Cell Signaling Technology , 1∶100 ) was performed as previously described [54] . Secondary antibody , either donkey anti-mouse AlexaFluor488 ( Molecular Probes ) or goat anti-mouse AlexaFluor488 ( Molecular Probes ) , was used in 1∶100 dilution . Images were acquired using an Olympus Fluoview FV300 laser scanning confocal microscope . Digital images were processed with Adobe Photoshop CS4 . Embryos from bmp4st72/+×bmp4st72/+ matings were injected with 3-OST-7 MO . At 48 hpf , the hearts were scored for noncontracting ventricle or wild-type phenotype . Genomic DNA was extracted from each individual embryo and genotyped using the following dCAPS primers , 5′-TGGTGAGGCACAACACCTCCAACTAG-3′ ( forward ) and 5′-CCGAGTCAGCGGGTGACTTTTGCCGTC-3′ ( reverse ) . The PCR products were digested with SpeI ( NEB ) and ran in 3% agarose gel . Digestion with SpeI releases 250 bp band in wild-type , 230 bp band in mutant , and both in heterozygotes . DNA genotyped to be from mutants were sequenced to verify compatibility with 3-OST-7 MO . Statistical significance was analyzed using Student's t-test . Analysis was performed using GraphPad Prism ( version 6 . 00 for Mac GraphPad Software ) . Results are considered significant when p<0 . 05 and results are expressed as mean ± standard error of the mean ( SEM ) . | A highly complex environment at the cell surface and in the space between cells is thought to modulate cell behavior . Heparan sulfate proteoglycans are cell surface and extracellular matrix molecules that are covalently linked to long chains of repeating sugar units called glycosaminoglycan chains . These chains can be subjected to rare modifications and they are believed to influence specific cell signaling events in a lineage specific fashion in what is called the “glycocode . ” Here we explore the functions of one member of a family of enzymes , 3-O-sulfotransferases ( 3-OSTs ) that catalyzes a rare modification ( 3-O-sulfation ) of glycosaminoglycans in zebrafish . We show that knockdown of 3-OST-7 results in a very specific phenotype , including loss of cardiac ventricle contraction . Knockdown of other 3-OST family members did not result in the same phenotype , suggesting that distinct 3-OST family members have distinct functions in vertebrates and lending in vivo evidence for the glycocode hypothesis . Mechanistically , we found that cardiac contraction can be rescued by reducing the amount of endogenous BMP4 , and can be blocked by increasing BMP signaling , suggesting that the glycocode generated by 3-OST-7 is necessary to constrain BMP signaling in the heart for normal cardiac contraction . Furthermore , we show that tropomyosin4 ( tpm4 ) is downstream of 3-OST-7 function , indicating that Tpm4 is key in this pathway to building the sarcomere , the functional contraction unit of the cardiomyocyte . | [
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] | [] | 2013 | 3-OST-7 Regulates BMP-Dependent Cardiac Contraction |
Mycobacterium tuberculosis is an intracellular pathogen . Within macrophages , M . tuberculosis thrives in a specialized membrane-bound vacuole , the phagosome , whose pH is slightly acidic , and where access to nutrients is limited . Understanding how the bacillus extracts and incorporates nutrients from its host may help develop novel strategies to combat tuberculosis . Here we show that M . tuberculosis employs the asparagine transporter AnsP2 and the secreted asparaginase AnsA to assimilate nitrogen and resist acid stress through asparagine hydrolysis and ammonia release . While the role of AnsP2 is partially spared by yet to be identified transporter ( s ) , that of AnsA is crucial in both phagosome acidification arrest and intracellular replication , as an M . tuberculosis mutant lacking this asparaginase is ultimately attenuated in macrophages and in mice . Our study provides yet another example of the intimate link between physiology and virulence in the tubercle bacillus , and identifies a novel pathway to be targeted for therapeutic purposes .
With nearly 1 . 3 million lives claimed in 2012 , as reported by the World Health Organization , tuberculosis ( TB ) remains the major cause of death due to a single bacterial pathogen . A better understanding of the interactions between Mycobacterium tuberculosis , the etiologic agent of TB , and its human host may help improve current therapies . In particular , unraveling the microbial mechanisms involved in uptake and catabolism of host-derived nutrients required by the pathogen during its life cycle may identify targets for novel antimicrobials [1]–[3] . The TB bacillus is an intracellular microorganism that thrives inside host macrophages . Although M . tuberculosis can be found in the host cell cytosol at later stages of infection [4]–[6] , the prevailing consensus is that the pathogen resides and multiplies mostly within phagosomes , which fuse poorly with host cell lysosomes and barely acidify ( pH∼6 . 5 ) [7]–[10] . In macrophages activated by immune cell-derived cytokines , such as interferon ( IFN ) - γ , and microbial ligands , such as Escherichia coli-derived lipopolysaccharide ( LPS ) , the pH of the mycobacterial phagosome drops below 5 . 5 , and mycobacterial growth is constrained to some extent [8] , [11] , [12] . The ability to block phagosome maturation and avoid lysosomal degradation is considered chief among M . tuberculosis virulence strategies , although the molecular mechanisms involved in this process are likely to be multiple and remain yet to be fully elucidated [10] . In addition to being slightly acidic , the mycobacterial phagosome is considered an environment in which nutrient availability is limited [1] , [3] , [13] . Such multiple stresses typically translate into a marked remodeling of the mycobacterial transcriptional landscape soon after phagocytosis , as supported , for example , by the induction of acid-responsive genes and those involved in utilization of alternative carbon sources , such as host-derived fatty acids and cholesterol [14]–[18] . Carbon metabolism reprogramming , in particular , appears instrumental in mycobacteria adaptation to their host , and a number of studies identified major pathways used by M . tuberculosis to gather carbon during infection [19]–[24] . In addition to carbon , nitrogen is an essential component of biomolecules , such as amino acids , nucleotides and organic co-factors . Although several studies provided insight into the regulation mechanisms of the central nitrogen metabolism in M . tuberculosis , showing in particular the key role of the glutamine synthetase GlnA1 and its regulator GlnE in this process [25]–[29] , the mechanisms by which nitrogen is acquired by the bacillus , and the main nitrogen sources used during infection remain poorly characterized . In this context , we recently reported that M . tuberculosis employs the membrane transporter AnsP1/Rv2127 to capture aspartate and exploit this amino acid species as a nitrogen source during infection [30] , [31] . Here we further report that the AnsP1 homologue AnsP2 ( AroP2/Rv0346c ) , a predicted asparagine transporter , and that AnsA ( Rv1538c ) , a predicted asparaginase [32] , allow asparagine uptake and deamination , respectively . The hydrolysis of asparagine in turn allows M . tuberculosis to assimilate nitrogen into downstream metabolites such as glutamate and glutamine . In parallel , this system of asparagine acquisition supports the in vitro mycobacterial growth in acidic conditions through ammonia release and pH buffering . Finally , we provide evidence that AnsA is released into the M . tuberculosis culture filtrate in vitro and within the mycobacterial phagosome . Thus AnsA is important for phagosome acidification arrest and intracellular survival of the pathogen inside macrophages , ultimately serving as a virulence factor . Collectively , these results provide compelling evidence that asparagine is an important additional source of nitrogen for M . tuberculosis during host colonization , and identify AnsA and the asparagine transport system as potential novel targets to be considered for therapeutic purposes .
Because asparagine is known to be one of the best nitrogen sources used by M . tuberculosis in vitro [33] , [34] , we reasoned that the pathogen may have a transport system in place to scavenge this amino acid from its host . Among putative transporters , AnsP2/Rv0346c became an obvious candidate based on its high primary sequence identity ( 58% ) with the Salmonella enterica asparagine transporter AnsP [35] . Moreover , ansP2 expression is markedly induced in M . tuberculosis in the lungs of patients with TB , which may reflect an important role for this putative transporter in a natural setting [36] . In order to evaluate whether AnsP2 transports asparagine , we first performed a 14C-asparagine uptake experiment with wild-type M . tuberculosis H37Rv and an ansP2-deficient mutant strain that we generated by recombineering [30] , [37] . In agreement with the functional annotation of AnsP2 , we found asparagine transport was partially impaired in the mutant as compared to its wild-type counterpart ( Fig . 1A ) . This phenotype was reversed upon genetic complementation of the mutant strain with an integrative cosmid harboring the ansP2 gene region ( Fig . 1A ) , thus demonstrating the implication of AnsP2 in asparagine uptake . Based on these results , we hypothesized the ansP2-KO mutant should be affected in its ability to grow in the presence of asparagine as sole nitrogen source . Surprisingly , we found the mutant multiplied equally to the wild-type strain under this condition ( Fig . 1B ) , indicating the reduced amount of asparagine imported by the mutant strain ( Fig . 1A ) was nevertheless sufficient to promote bacterial growth . Moreover , the ansP2-KO mutant was not attenuated in immune-competent mice ( Fig . 1C ) . Altogether , while these results identify AnsP2 as an asparagine transporter in M . tuberculosis , they also allude to the presence of one or more additional yet to be identified transporter ( s ) responsible for the uptake of this amino acid species . Once asparagine is scavenged by the bacillus , we inferred it must undergo an assimilation process carried out by asparaginases , which hydrolyze this amino acid into aspartate and ammonia . Indeed , asparaginase activity was described several decades ago in lysates of various mycobacteria species , including M . tuberculosis [38] , [39] . In the M . tuberculosis genome , a unique gene by the name of ansA is predicted to encode an asparaginase [32] , and whose homologue was recently proven to hydrolyze asparagine in vitro in the closely related attenuated vaccine strain Mycobacterium bovis BCG [40] . Building upon these observations , we decided to produce and purify a recombinant HIS6-tagged version of AnsA in the M . tuberculosis-related fast grower Mycobacterium smegmatis in order to evaluate its asparaginase activity . The recombinant enzyme , with a predicted molecular weight of 34 kDa , was immuno-detected both in total bacterial lysate and after purification on a nickel column using an appropriate anti-HIS6 antibody ( Fig . 1D ) . The ability of recombinant AnsA to hydrolyze asparagine was then assessed in a coupled enzymatic reaction in which the ammonia generated after asparagine deamination is used in a secondary reaction to form glutamate via a NADPH-dependent glutamate dehydrogenase . Disappearance of NADPH was followed as a marker of asparagine consumption in the reaction mixture , and revealed that AnsA mediates asparagine hydrolysis ( Fig . 1E ) . By contrast , we found AnsA could not hydrolyze glutamine ( Fig . 1E ) , indicating the enzyme is void of any significant glutaminase activity frequently associated to asparaginases [30] , [41] . Since AnsA is the only predicted asparaginase in M . tuberculosis [32] , as opposed to in other bacteria such as E . coli [42] , we deduced that the genetic inactivation of AnsA should have a significant impact on asparagine metabolism in this species . Given that ansA might be essential in M . tuberculosis [24] , we designed a conditional inactivation strategy to knock this gene out [43] ( Figure S1 ) . Unexpectedly , we could readily generate a viable ansA-KO mutant strain , revealing ansA is not essential in M . tuberculosis , as suggested by other studies [44] , [45] . The apparent contradiction between the observed viability of the mutant and the essentiality predicted by Griffin et al . [24] can be reconciled when considering that for the high density transposon insertion screen asparagine was used as the main nitrogen source in the culture medium; it is most likely that under these conditions an ansA-KO mutant is impaired in growth . Consistent with this assumption , and with the observed enzymatic activity of AnsA in vitro , we found the growth of the ansA-KO mutant was impaired , although not fully abolished , when asparagine was provided as sole nitrogen donor ( Fig . 1F ) . It is likely that the remaining minimal growth of the mutant observed under this condition is due to residual asparagine deamination mediated by other yet to be identified amidases present in M . tuberculosis . As a control , the ansA-KO mutant replicated equally to the wild-type strain in the presence of another nitrogen source , such as glutamate ( Figure S2 ) , suggesting that ansA inactivation does not lead to general growth defects . Equally important , we found the ansA-KO mutant was impaired in host tissue colonization ( Fig . 1G ) , thus suggesting a role for asparagine catabolism in M . tuberculosis virulence . The results above suggested M . tuberculosis exploits asparagine from host tissues during infection to support growth . In agreement with previous studies reporting asparagine is a preferred source of nitrogen in M . tuberculosis [33] , [34] , we found this amino acid does not support mycobacterial growth when provided as sole carbon and energy source ( Figure S3 ) . To further understand the role of asparagine assimilation in M . tuberculosis , we used targeted metabolomics to follow nitrogen incorporation in the ansP2- and ansA-KO mutants during growth on 15N2-labeled asparagine . As compared to wild-type M . tuberculosis , we found the ansP2-KO mutant was impaired in nitrogen incorporation from asparagine into other amino acids , such as glutamate and glutamine , which serve as initial nitrogen providers in the central nitrogen metabolism; this phenotype was reversed upon genetic complementation with a functional ansP2 allele ( Fig . 2A ) . Strikingly , total asparagine content of the ansA-KO strain at the steady state in a medium containing asparagine as sole nitrogen provider was found ∼1 , 000-fold higher than in its wild-type and complemented counterparts ( Fig . 2B ) , a likely consequence arising from the impaired asparagine catabolism in the mutant . In line with this hypothesis , the amounts of total ( Fig . 2B ) , as well as newly synthetized ( Fig . 2C ) , glutamate and glutamine were reduced in the mutant strain , further indicating a clear impairment of nitrogen incorporation from asparagine into downstream metabolites in the absence of AnsA . Of notice , nitrogen assimilation from asparagine was not completely abolished in the ansA-KO mutant , and this phenotype paralleled the residual growth of the mutant in the presence of asparagine reported above ( Fig . 1F ) . Altogether , these results reveal that asparagine-derived nitrogen is fully assimilated in M . tuberculosis , and that AnsP2 and AnsA are involved in this process . A recent study reported asparagine is the best among the few amino acids that can support M . tuberculosis resistance to acid stress [46] . This feature most likely relies on the specific release of the weak base ammonia and subsequent pH buffering that accompany asparagine consumption [46] . Building upon this observation , we found the growth of the ansP2-KO strain , in the presence of asparagine as sole nitrogen provider , was greatly reduced at pH 5 . 5 as compared to the wild-type and complemented strains ( Fig . 3A ) . This phenotype correlated with a markedly diminished capacity of the mutant to secrete ammonia and neutralize pH of the culture medium ( Fig . 3B , C ) . In the same conditions , the phenotypes of the ansA-KO mutant were even more pronounced . Indeed , mycobacterial growth , asparagine-mediated ammonia secretion and pH buffering were totally abolished in the absence of AnsA ( Fig . 3D–F ) . In line with these results , nitrogen assimilation from asparagine into glutamate and glutamine was fully abrogated in the ansA-KO mutant at acidic pH ( Figure S4A ) . In order to rule out the possibility that the observed defect in ammonia secretion and pH buffering in the ansA-KO mutant was due to the growth defect of the mutant at acidic pH , we repeated the experiment reported in Fig . 3D–F using a more dense bacterial suspension and a shorter time course , with and without asparagine as sole nitrogen source . We resuspended bacteria at an OD600 of 1 . 5 in acidic culture medium and measured ammonia secretion and pH at 0 , 2 , 4 , 18 and 24 hours after inoculation . In these conditions , the ansA-KO mutant was still completely impaired in ammonia secretion and pH buffering , as compared to its wild-type and complemented counterparts ( Figure S4B–D ) . Collectively , these results unequivocally demonstrate that , in particular in an acidic environment , asparagine catabolism partially requires AnsP2 and is strictly dependent on AnsA to sustain M . tuberculosis growth in the presence of asparagine . These results also underline that asparagine hydrolysis , ammonia release , pH buffering and growth in acidic conditions are intrinsically linked molecular events in M . tuberculosis . We next evaluated to what extent the sensitivity of our mutants to acid stress may impact their ability to survive in an acidic phagosome and to parasitize host macrophages . We first assessed whether asparagine can access the mycobacterial phagosome inside infected cells . To this aim , we employed secondary ion mass spectrometry ( SIMS ) , a method that allows the visualization of isotopic labeling and metabolites in biological samples with sub-micrometer resolution . We infected mouse bone marrow-derived macrophages ( BMMs ) with 13C-labelled M . tuberculosis H37Rv for 20 hours , and pulsed the infected cells with 15N-asparagine for 4 h before SIMS analysis . Our data clearly indicate that exogenously provided asparagine accumulates in the mycobacterial phagosome ( in ≈50% of them in Fig . 4A ) , as compared to the host cell cytosol ( Fig . 4A , B ) . Regarding mycobacterial growth , the ansP2-KO mutant was found not affected in its ability to survive in IFNγ- and LPS-activated BMMs , in which the pH of the mycobacterial phagosome readily drops below 5 . 5 ( [8]; Figure S5 ) . This result correlates with the remaining amount of ammonia secretion observed in this mutant ( Fig . 3B ) . On the other hand , the intracellular survival of the ansA-KO strain was strongly impaired in activated BMMs ( Fig . 4C ) . Strikingly , labeling of infected cells with the acidotropic dye LysoTracker and phagosomal pH measurement at early time-points after infection revealed that the phagosomes harboring the ansA-KO mutant acidified more readily compared to those containing the wild type or complemented strains ( Fig . 4D–F ) . In line with this finding , we also found that V-ATPase , the proton pump responsible for phagosomal acidification , accumulated in larger amounts in phagosomes containing the ansA-KO mutant than in vacuoles containing its wild-type or complemented counterparts ( Figure S6A , B ) . Consistent with these observations , treatment of BMMs with bafilomycin A1 , a specific V-ATPase inhibitor preventing phagosome acidification [47] , restored the ability of the ansA-KO mutant to multiply intracellularly ( Fig . 4G ) . Whether the attenuation phenotype of the ansA-KO mutant inside macrophages is a cause or a consequence of impaired asparagine hydrolysis and subsequent reduced ammonia production and pH buffering capacity is difficult to delineate , as these molecular events are intrinsically linked one to each other; nevertheless , our results clearly establish AnsA is required for intracellular survival of M . tuberculosis . Strikingly , M . tuberculosis AnsA is more similar to the periplasmic ( type II ) asparaginase AnsB than to the cytosolic ( type I ) enzyme AnsA from E . coli ( 35% vs . 28% identity , respectively ) [42] , suggesting AnsA might be a secreted asparaginase in M . tuberculosis . We addressed this important issue using different and complementary approaches: i ) quantification of asparaginase activity in cell-free culture supernatants by mass spectrometry ( MS ) ; ii ) immune-detection of AnsA-HIS6 fusion protein in culture filtrates from recombinant M . tuberculosis strains; iii ) analysis of AnsA secretion in phagosomes of M . tuberculosis-infected macrophages by electron microscopy ( EM ) . We incubated bacterial culture supernatants from the wild type , ansA-KO and complemented strains with 15N-asparagine and monitored 15N-aspartate production by MS . Our data revealed that an asparaginase activity could be detected in the M . tuberculosis culture supernatant , unless ansA was genetically inactivated ( Fig . 5A ) . Consistently , we immuno-detected the AnsA-HIS6 fusion protein in culture filtrate , as well as in the cell pellet , of recombinant M . tuberculosis by Western blotting ( Fig . 5B ) . As expected , the strictly cytosolic protein GroEL2 was detected in the cell pellet only , indicating the absence of bacterial lysis . Because AnsA does not contain a classical signal peptidase I cleavage site in its N-terminal end , we investigated whether alternative secretion systems , such as the SecA2 secretion system [48] , [49] or the ESX-1 and ESX-5 type VII secretion systems [50] might be involved in AnsA secretion . To this aim , we transformed ESX-1 , ESX-5 and SecA2-KO mutants with the AnsA-HIS6 fusion-encoding plasmid , purified the culture filtrate from exponentially growing cultures , and immuno-detected the fusion protein using the anti-HIS6 antibody . Our data indicate that AnsA secretion is independent of SecA2 and ESX-1 ( Fig . 5B ) . As a control , the SecA2-dependent protein SodA was not detected in the supernatant of the SecA2-KO strain . Surprisingly , secretion of AnsA was impaired in the ESX-5 mutant ( Fig . 5B , C ) , indicating the involvement of this type VII secretion system in the secretion of the enzyme . In order to evaluate whether AnsA is also secreted in the phagosomal lumen inside macrophages , we used EM and Ni-NTA-Nanogold to detect AnsA-HIS6 in ultrathin sections of cells infected with M . tuberculosis carrying or not the AnsA-HIS6 fusion-encoding genetic construct . Gold particles were detected in the phagosomal lumen , strongly suggesting AnsA is also secreted in host cells during infection ( Fig . 5D ) . Collectively , this study puts forward an acquisition system for asparagine that not only protects against phagosomal acidification , but also serves to assimilate nitrogen from this amino acid species , with a central role for the asparaginase AnsA in enhancing the fitness of M . tuberculosis during host colonization .
Identifying the nutrients used by M . tuberculosis to assimilate essential elements , such as carbon and nitrogen , is key to understanding host-pathogen interactions in TB . In this context , we recently reported that aspartate is a key nitrogen source used by M . tuberculosis during infection [30] , [31] . Here we further show that asparagine can serve as an additional source of nitrogen for the pathogen through transport by the amino acid permease AnsP2 , and subsequent hydrolysis by the asparaginase AnsA ( Fig . 6 ) . Furthermore , our results establish a unique link between mycobacterial physiology and virulence since we show AnsA has a dual function in both nitrogen assimilation and in protection against acid stress in vitro and inside host cells ( Fig . 4 ) . Our results are most likely relevant from a physiological viewpoint since asparagine is present at 50–60 µM in the human plasma [51] , and is 2- to 4-fold more concentrated in white blood cells [29] , [51] , [52] . In addition , we further show here that asparagine accumulates in the mycobacterial vacuole inside infected macrophages . Altogether , these observations indicate that asparagine is most likely readily accessible to M . tuberculosis during infection in vivo . Regarding asparagine uptake in M . tuberculosis , it is clear from the present study that one or more transporter ( s ) complement the function of AnsP2 , since the ansP2-KO mutant was only partially impaired in nitrogen incorporation from asparagine in vitro , and it was not attenuated inside host cells and in vivo . The AnsP2 paralogue AnsP1 ( 72% identity ) is an obvious candidate to fulfill this function [32] . However , we previously reported that the M . tuberculosis ansP1-KO mutant grows and incorporates asparagine equally well , compared to the wild-type strain , when grown on asparagine as sole nitrogen source [30] . Furthermore , we found the ansP1-KO mutant transports asparagine to the same extent as the wild-type strain in vitro ( data not shown ) . In addition to AnsP1 , two other putative amino acid transporters , namely CycA/Rv1704c and GabP/Rv0522 [32] , show some similarity with AnsP2 ( 38% and 34% identity , respectively ) and may contribute to asparagine transport . The construction of multiple mutants inactivated in two or more of these candidates will be required in order to uncover the complete asparagine transport machinery in M . tuberculosis , which will be the purpose of future study . Nevertheless , our results identify AnsP2 as an important asparagine transporter in M . tuberculosis , in particular at acidic pH . Beyond the complexity of asparagine uptake , further efforts should be allocated to deciphering the exact contribution of AnsA to mycobacterial virulence . Whether attenuation of the ansA-KO mutant in vivo is due to its inability to counteract phagosome acidification and/or to incorporate nitrogen from asparagine resulting in an impaired fitness will require careful investigation; however such an investigation will be made difficult by the intrinsically linked nature of the asparagine hydrolysis , ammonia release and pH buffering phenomenons in M . tuberculosis , as revealed by our study and in a previous report [46] . In this context , it is worth noticing that , like AnsA , another mycobacterial hydrolase , namely the urease , was proposed to play a part both in nitrogen acquisition and in counteracting phagosome acidification through hydrolysis of urea and subsequent release of ammonia [53]–[55] . However , unlike for AnsA , mycobacterial mutants deficient in urease production are barely impaired in intracellular survival and their capacity to persist or multiply in vivo is not affected [53]–[55] . Finally , a role for asparaginase in virulence of other bacterial pathogens , including Helicobacter pylori , Campylobacter jejuni and Salmonella typhimurium , has been reported [56]–[60] . In these species , asparaginase is secreted into the periplasm and is thought to contribute to host colonization either through direct microbial asparagine utilization in vivo [56] , or through indirect starvation-mediated exhaustion of immune cells following asparagine depletion in infected tissues [57]–[60] . The M . tuberculosis asparaginase AnsA does not contain any detectable signal sequence in its N-terminal end . Yet , we show that this enzyme is secreted in vitro and inside infected macrophages through an alternative SecA2- and ESX-1-independent pathway that relies , at least partially , on the ESX-5 type VII secretion system [50] . The exact mechanism of AnsA secretion , and the extent to which ESX-5 is involved in this process , remain to be further delineated; however it is worth noticing that AnsA contains two sequences resembling the ESX secretion signal consensus YXXXD/E: Y207PGSD211 and Y282GPGHD287 [61] . Whether these motifs play a part in AnsA secretion will need to be understood; equally important will be to understand the role of AnsA beyond nitrogen supply to the pathogen , possibly in asparagine depletion and immune cell exhaustion , as reported for other pathogens [57] . In conclusion , our study provides yet another example of the tight connections forged throughout evolution between physiology and virulence in microbial pathogens . It also highlights the need to further explore the expanding field of metabolism and infection in order to accelerate the identification and validation of novel strategies to combat infections and disease .
Mycobacteria were grown at 37°C in Middlebrook 7H9 medium ( Difco ) supplemented with 10% albumin-dextrose-catalase ( ADC , Difco ) and 0 . 05% Tween-80 ( Sigma ) , or on Middlebrook 7H11 agar medium ( Difco ) supplemented with 10% oleic acid-albumindextrose- catalase supplement ( OADC , Difco ) . When required , kanamycin , hygromycin , streptomycin ( 50 µg/mL ) or zeocin ( 25 µg/mL ) were added to the culture media . The ESX-1 and ESX-5 mutants have been described previously [62] , [63] . A SecA2 mutant carrying a kanamycin-inactivated copy of the secA2/rv1821 gene was constructed using a similar strategy based on the ts-SacB technology ( Bottai et al . Unpublished data ) . For growth tests with asparagine as a carbon source , bacteria were grown in Sauton's modified medium ( pH 6 . 5–7 . 0 ) containing , 0 . 5 g/L KH2PO4 , 0 . 5 g/L MgSO4 , 50 mM asparagine , 0 . 05% tyloxapol ( Sigma ) and supplemented with or without 10 g/L glycerol and 15 mM ( NH4 ) 2SO4 . For growth tests with asparagine as sole nitrogen source , bacteria were grown in Sauton's modified medium containing 0 . 05% Tween-80 , 0 . 5 g/L KH2PO4 , 0 . 5 g/L MgSO4 , 2 g/L citric acid , 10 g/L glycerol and 5 mM asparagine prepared in tap water and neutralized to pH 7 . 0 or pH 5 . 5 with NaOH before autoclaving . Cultures were performed in triplicate in glass tubes and bacterial growth was monitored measuring turbidity ( in McFarland units ) over time using a Densimat apparatus ( BioMerieux ) . The ansP2-KO mutant strain of Mycobacterium tuberculosis H37Rv containing a disrupted ansP2 ( Rv0346c ) ::KanR allele was constructed by allelic exchange using recombineering [30] , [37] . H37Rv:pJV53 was grown in 7H9-ADC-Tween 80 in the presence of hygromycin until mid-log phase and expression of the recombineering enzyme was induced by 0 . 2% acetamide ( Sigma ) overnight at 37°C . After induction , electrocompetent bacteria were prepared . Electroporation was performed with a linearized fragment of a kanamycin resistance cassette-interrupted ansP2 gene flanked with homologous regions ( 400–500 bp length ) . After 72 h incubation at 37°C , bacteria were plated onto 7H11-OADC agar medium in the presence of kanamycin . For the complementation of the ansP2-KO strain , we used the pYUB412-derived integrative cosmid I541 , which contains a hygromycin resistance cassette and harbors a fragment encompassing the region 398 to 432 kbp in the genome of M . tuberculosis H37Rv . For the ansA-KO strain construction , a second copy of the ansA gene was first integrated in the chromosome of wild type H37Rv at the bacteriophage insertion site attL5 . For this , we used the plasmid pGMCS-Puv15-ansA which contains the ansA gene under the control of the Psmyc promoter and a streptomycin resistance cassette[64] . After selection of streptomycin resistant clones , the original ansA gene was disrupted using a linearized digestion fragment of kanamycin resistance cassette-interrupted ansA gene flanked with homologous regions ( 450–600 bp length ) . The additional copy of ansA was then deleted by replacing pGMCS-Puv15-ansA with the plasmid pGMCZq17 , which contains a zeocine resistance cassette . Selection of a zeocin resistant clone resulted in an ansA-KO strain and proved that ansA is not essential . For complementation of the ansA-KO strain , the pYUB412-derived integrative cosmid I16 encompassing the region 1 , 719 to 1 , 756 kbp in the genome of M . tuberculosis H37Rv , and containing a hygromycin resistance cassette was used . Asparagine uptake experiments were carried out as described elsewhere with minor modifications [46] . Briefly , bacteria were grown in Middlebrook 7H9 containing 0 . 05% Tween 80 and asparagine ( 5 mM ) at 37°C . Bacteria were harvested by centrifugation when an OD600∼0 . 5 was reached . Bacterial pellets were washed twice in uptake buffer [50 mM Tris-HCl pH 6 . 9 , 15 mM KCl , 10 mM ( NH4 ) 2SO4 , 0 . 05% Tween 80] and resuspended in the same buffer . Radiolabeled 14C-asparagine ( PerkinElmer ) and non-labeled asparagine ( Sigma ) were mixed ( 3∶1 ) and added to 5 mL of cell suspensions to obtain a final concentration of 20 µM asparagine . The mixtures were incubated at 37°C and 250 µL of samples were removed at the indicated time points . Bacteria were collected on a 0 . 45 µm Spin-X centrifuge tube filter ( Costar ) by mixing with an equal volume of 10% paraformaldehyde ( Polyscience , Inc ) containing 0 . 1 M LiCl ( Sigma ) . Filters radioactivity was determined in a liquid scintillation counter ( Packard ) . The uptake rate was expressed in desintegration per minute ( DPM ) per total protein concentration ( 14C-Asn ( DPM ) . µg protein-1 ) . Bacteria were grown in supplemented 7H9 with 0 . 05% Tween-80 until OD600∼1 . 10 mL of cultures were removed and washed twice with DPBS and used for inoculation of 200 mL Sauton's modified medium containing 0 . 05% Tween-80 , 0 . 5 g/L KH2PO4 , 0 . 5 g/L MgSO4 , 2 g/L citric acid , 10 g/L glycerol and 5 mM asparagine prepared in tap water and buffered to pH 5 . 5 with NaOH before autoclaving . Bacteria were incubated at 37°C and , at indicated time points , 1 mL of culture was removed and centrifuged at 1 , 300 rpm for 2 min to collect supernatants . To determine ammonium concentration , supernatants were diluted 4-fold in DPBS and 50 µL of diluted samples were mixed in a 96 plate with 50 µL of Nessler's reagent ( Fluka ) and incubated for 20 min at room temperature . 100 µL of NaOH were then added to stop the reaction prior to measurement of OD520 using a µQuant apparatus ( BIO-TEK instruments , Inc ) . pH was measured directly in 1 mL of culture supernatant using a pH-meter . The ansA gene was cloned into a pVV16 vector allowing the constitutive expression of C-terminus HIS6-tagged fusion proteins under the control of a GroEL2 promoter and carrying kanamycin and hygromycin resistance cassettes . The pVV16 ansA-his6 vector was electroporated into the non-pathogenic fast-grower Mycobacterium smegmatis mc2155 strain and clones containing pVV16 ansA-his6 were selected on solid medium containing kanamycin and hygromycin . At OD600∼1 , 5 , 15 mL of cultures were centrifuged and washed with DPBS and bacteria were resuspended in 1 mL of lysis buffer containing 50 mM NaH2PO4 pH 8 . 0 , 300 mM NaCl and 10 mM imidazole and broken with glass beads ( 0 . 1–0 . 25 mm ) for 10 min at 30 m/s using a Bead Beater apparatus ( Retscher , BioBrock scientific ) . AnsA-HIS6 protein was purified from 600 µL of lysates using the Ni-NTA Spin kit ( QIAGEN ) and eluted in an elution buffer containing 50 mM NaH2PO4 , 300 mM NaCl and 400 mM imidazole at pH 8 . AnsA-HIS6 purified fraction was quantified using the Bradford method . For enzymatic tests , we used the L-Asparagine/L-Glutamine/Ammonia Assay Kit ( Megazyme ) following manufacturer's recommendations and using asparagine or glutamine ( final concentration 0 . 6 mM ) as substrates . The buffer used in this assay contains glutamate dehydrogenase , NADPH and 2-oxoglutarate , so that enzymatic activities were measured by following the disappearance of NADPH along time as an indirect indication of asparagine deamination at 340 nm using a SAFAS Monaco mc2 spectrophotometer and the SAFAS SP 2000 software . The procedures were as previously described [62] . Immunoblot analyses were carried out with mouse monoclonal antibodies raised against EsxA ( Hyb76-08 , Antibodyshop , BioPorto Diagnostics ) or SodA ( NR-13810 , clone CS-18 , produced in vitro , received from BEI resources N°SOE76725 ) , or with a rabbit polyclonal antibody against the HIS6 tag ( eBioscience ) . As control , culture supernatants were also analyzed by Western blot for the presence of GroEL2 ( anti-GroEL2 monoclonal antibody , Colorado State University , NIH , NIAID contract N°AI75320 ) . Bacteria were cultivated to an OD600 of 1 in 7H9-0 . 05% Tween-80 . Bacteria were centrifuged and resuspended in DPBS ( 3-fold concentration ) . 1 mL was transferred to a filter ( Fisher ) mounted on a filtration device ( Fisher ) and connected to a trap and vacuum line . Filters were transferred to a 7H10 based agar medium ( Sigma ) supplemented with asparagine ( 2 mM ) or to solid media containing 0 . 5 g/L KH2PO4 , 0 . 5 g/L MgSO4 , 2 g/L citric acid , 10 g/L glycerol , aspartate ( 2 mM ) and 1 . 5% agar ( Invitrogen ) prepared in tap water and neutralized to pH 6 . 5–7 . 0 with NaOH before autoclaving . Plates were incubated for 5 days at 37°C . Three filters were used per strain and time point . For labeling experiments , filters were transferred on equivalent plates where aspartate was replaced by 15N2-asparagine ( 2 mM , Sigma , Purity 98 atom % 15N ) and incubated for 0 . 5 , 2 , 4 or 8 h at 37°C . At each time point , filters were plunged into 1 mL acetonitrile/methanol/water ( 2∶2∶1 , v/v/v ) mixture at −40°C . Bacteria were then broken by glass beads using a bead-beater ( 5 min at 30 m/s ) . After centrifugation , supernatants were collected and filtered through a Spin-X column 0 . 2 µm at 14 , 000 rpm for 15 min . Extracts were stored at −80°C before analysis . Aqueous normal phase liquid chromatography was performed using an Agilent 1200 LC system equipped with a solvent degasser , binary pump , temperature-controlled auto-sampler ( set at 4°C ) and temperature-controlled column compartment ( set at 20°C ) , containing a Cogent Diamond Hydride Type C silica column ( 150 mm×2 . 1 mm; dead volume 315 µl ) , from Microsolv Technology Corporation . Flow-rate of 0 . 4 ml/min was used . Elution of polar metabolites was carried out using gradient 3[65] . Briefly , solvent A consists in deionized water ( Resistivity ∼ 18 MΩ cm ) , 0 . 2% acetic acid and solvent B consists in acetonitrile and 0 . 2% acetic acid , and the gradient as follows: 0 min 85% B; 0–2 min 85% B; 2–3 min to 80% B; 3–5 min 80% B; 5–6 min to 75% B; 6–7 min 75% B; 7–8 min to 70% B; 8–9 min 70% B; 9–10 min to 50% B; 10–11 min 50% B; 11–11 . 1 min to 20% B; 11 . 1–14 min hold 20% B . Accurate mass spectrometry was carried out using an Agilent Accurate Mass 6230 TOF apparatus . Dynamic mass axis calibration was achieved by continuous infusion , post-chromatography , of a reference mass solution using an isocratic pump connected to a multimode ionization source , operated in the positive-ion mode . ESI capillary and fragmentor voltages were set at 3 , 500 V and 100 V , respectively . The nebulizer pressure was set at 40 psi and the nitrogen drying gas flow rate was set at 10 L/min . The drying gas temperature was maintained at 250°C . The MS acquisition rate was 1 . 5 spectra/sec and m/z data ranging from 80-1 , 200 were stored . This instrument routinely enabled accurate mass spectral measurements with an error of less than 5 parts-per-million ( ppm ) , mass resolution ranging from 10 , 000–25 , 000 over the m/z range of 121–955 atomic mass units , and a 100 , 000-fold dynamic range with picomolar sensitivity . Data were collected in the centroid mode in the 4 GHz ( extended dynamic range ) mode . Detected m/z were deemed to be identified metabolites on the basis of unique accurate mass-retention time identifiers for masses exhibiting the expected distribution of accompanying isotopomers ( 21035735 ) . Typical variation in abundance for most of the metabolites stayed between 5 and 10% under these experimental conditions . Under the experimental conditions described above , M+1 arising from 15N incorporation can be readily distinguished from M+1 arising from natural abundance 13C , therefore allowing direct monitoring of 15N labeling . The extent of 15N labeling for each metabolite was determined by dividing the summed peak height ion intensities of all 15N labeled species by the ion intensity of both labeled and unlabeled species , expressed in percent . Bone marrow cells were flushed from the femurs and tibias of 6–8 weeks old female C57BL/6 mice , and cultured in Petri dishes ( 2 . 106 cells/dish ) in RPMI 1640 GlutaMax ( GIBCO ) supplemented with 10% fetal calf serum ( FCS , Pan-Biotech ) and 20 ng/mL macrophage colony-stimulating factor ( M-CSF , Peprotech ) at 37°C in the presence of 5% CO2 . At day 6 , cells were transferred to 24-well plastic plates ( 2 . 105 cells/well ) . For macrophage activation , cells were incubated with 10 ng/mL interferon gamma ( IFNγ , Peprotech ) and 5 ng/mL LPS ( Invivogen ) overnight prior to infection . Infection was performed in triplicate at a multiplicity of infection of 0 . 1 bacterium per cell for 4 h at 37°C . Cells were then washed 2 times with DPBS before addition of fresh medium . At day 0 , 2 and 5 , cells were lysed in 0 . 01% Triton X-100 ( Sigma ) , and serial dilutions of the lysates were plated onto 7H11-OADC agar medium for CFU scoring . For infection experiments using Bafilomycin A1 ( Sigma ) , cells were pre-incubated 1 h with 100 nM bafilomycin A1 prior to infection and removed at 24 h post-infection . SIMS analysis was carried out using a modified version of a previously described protocol [30] . Briefly , for 13C labeling , bacteria were grown in minimal medium containing 0 . 5 g/L KH2PO4 , 0 . 5 g/L MgSO4 , 15 mM NH4SO4 , 10 g/L 13C glycerol supplemented with 0 . 05% tyloxapol ( Sigma ) and neutralized to pH 6 . 5–7 . 0 with NaOH before filtration . In order to overcome the difficulties encountered during the sample preparation stage in our previous experiments due to incomplete resin infiltration [30] , in the present study cells were deposited directly on clean Silicon chips , and were infected and labeled . Macrophages were infected at a multiplicity of infection of 10 bacteria per cell with 13C labeled-bacteria for 4 hours . At 20 h post-infection , the culture medium was replaced by fresh RPMI containing 10% FCS and 5 mM 15N1 ( amine ) -asparagine . After 4 h at 37°C , cells were fixed with 4% PFA , 2 . 5% glutaraldehyde in a 0 . 1 M cacodylate buffer ( pH 7 . 4 ) . The detailed analytical conditions for SIMS imaging were described previously [30] . Briefly , a NanoSIMS-50 Ion microprobe ( CAMECA , Gennevilliers , France ) operating in scanning mode was used [66] . A Cs+ primary ion beam steps over the surface of the sample and four secondary ion species ( 12C− , 13C− , 12C14N− , 12C15N− ) were monitored simultaneously to create images of these selected ion species . The identification of bacteria location was highlighted by high 13C content while the asparagine uptake was revealed by 15N enrichment . Prior to image acquisition , the upper layer of the cells was eroded away using high density primary Cs+ ion bombardment until the underlying structures with 13C-labeled bacteria could be observed . Consequently , analysis of 15N enrichment could be performed . The image acquisition was then carried out using multiframe mode . The primary beam intensity was 1 pA with a typical probe size of 100 nm ( distance between 16%–84% of peak intensity from a line scan ) and the raster size ranges from 40 to 50 µm in order to image a whole cell with an image definition of 512×512 pixels . With a dwell time of 2 ms per pixel , up to 25 frames were acquired and the total analysis time was 3 hours . Image treatment was performed using ImageJ software [67] . First , multiframe images were properly aligned using CN− images as reference before a summed image was obtained for each ion species . A map of 13C atomic fraction was deduced from 12C− and 13C− images . In parallel , regions of interest were manually defined based on the 13C− map so as to outline individual bacterium for data extraction . For 15N/14N ratio quantification , a sample containing no labeled cells was used as working reference for adjusting the detectors . Finally , the 13C map , as well as the one for 15N/14N ratio , are displayed in Hue-Saturation-Intensity ( HSI ) mode . These HSI color images were generated using OpenMIMS , an ImageJ plugin developed by Claude Lechene's Laboratory ( http://nrims . harvard . edu/software ) [68] . Although the cellular structures were less visible using this method compared to the ones obtained with thin sections of resin-embedded cells , we have shown in the previous study [30] that the results were similar , either for 13C labeling , or for 15N enrichment . Mouse bone marrow-derived macrophages infected with either the wild type strain of M . tuberculosis H37Rv or the recombinant strain over-expressing His-tagged AnsA were first fixed for 1 h at room temperature with a mixture of EM grade 2 . 5% paraformaldehyde ( Euromedex ) and 0 . 1% glutaraldehyde ( Sigma ) prepared in 0 . 1 M Na-cacodylate buffer , pH 7 . 2 , containing 5 mM CaCl2 , 5 mM MgCl2 and 0 . 1 M sucrose . Cells were then washed twice with the same buffer for 15 min each , once with the same buffer containing 50 mM NH4Cl for 15 min and once with the same buffer devoid of sucrose for 5 min . Cells were scraped off the culture dishes with a rubber policeman and concentrated in 1% agar prepared in the same buffer devoid of sucrose . Cells were then processed for embedding in Lowicryl HM20 using the PLT ( progressive lowering of temperature ) procedure [69] . High-resolution labeling of His-tagged AnsA was performed on thin sections ( 90 nm-thick ) deposited onto carboned-coat nickel EM grids as previously described [70] , [71] . Briefly , grids were sequentially floated on i ) water for 5–10 min , ii ) PBS-1% BSA for 5 min to block unspecific sites , iii ) 5 nm Ni-NTA-Nanogold diluted 5-fold in PBS containing 0 . 5% BSA and 0 . 05% Tween 20 for 30 min , iv ) 5 mM imidazole for 1 min , v ) PBS for 3×1 min , and vi ) distilled H2O for 2×5 min . All incubations were carried out at room temperature . Sections were either not stained or slightly stained for 30 sec with 1% uranyl acetate in distilled water , and observed under the electron microscope ( Zeiss 912 ) . Murine macrophages were prepared as described above , plated after 6 days of differentiation on cover glasses at 2 . 105 cells/well in a 24-well plates , and activated with IFNγ ( 10 ng/mL ) and LPS ( 5 ng/mL ) overnight prior to infection . 10 mL of bacteria grown until OD600 of 1 in complete 7H9 were centrifuged for 7 min at 4 , 000 rpm , and washed two times with 20 mL DPBS . For bacteria labeling , pellets were suspended in 250 µL of Alexa Fluor 488 succinimidyl ester ( Fisher ) ( 1 . 5 µL Alexa Fluor 488 in 248 . 5 µL DPBS ) or , for intra-phagosomal pH measurement , in 250 µL Alexa Fluor 647-NHS ester and 5-carboxyfluorescein succinimidyl ester ( Fisher ) ( 1 . 5 µL each in 247 µL DPBS ) , and incubated at room temperature for 45 min . Bacteria were then washed two times with 20 mL DPBS and disaggregated manually for 30 sec with sterile glass beads . Bacteria were then resuspended in 7 mL of complete RPMI and centrifuged for 5 min at 1 , 200 rpm to remove aggregates . The OD600 of bacterial suspensions was then measured to determine the number of bacteria . Cells were infected at an MOI of 10 bacteria/cell for 1 h at 37°C and washed two times with DPBS before addition of fresh medium . After 1 and 3 h infection , cells were stained with 1 µM LysoTracker Red DND-99 ( Molecular Probes ) in complete RPMI for 1 h , washed with DPBS and fixed for 2 h with PFA 4% at room temperature . For immuno-detection of the V-ATPase , a rabbit polyclonal antibody ( Synaptic Systems ) was used at 1/100 dilution . Cover glasses were then mounted on glass slides using a VECTASHIELD Hardset Mounting Medium with DAPI ( Cliniscience ) and stored overnight at 4°C . Images were acquired with an LSM710 microscope equipped with a 40× 1 . 30 NA objective ( Carl Zeiss , Inc . ) , recorded with Zen software ( Carl Zeiss , Inc . ) , and analyzed with ImageJ software . All images were acquired with the same confocal microscope settings . The LysoTracker or V-ATPase signal intensity of every phagosome was measured with ImageJ software and the same threshold was applied for each condition to count the proportions of LysoTracker- or V-ATPase-positive phagosomes . See Figure 3 and S6 for examples of phagosomes that were considered positive for LysoTracker and V-ATPase , respectively . Quantification of LysoTracker- and V-ATPase-positive phagosomes was realized for ≈300 phagosomes per condition . For phagosomal pH measurement , we used a modified version of a protocol we previously described [72] . Briefly , macrophages were pulsed with the dual dye-coupled ( Alexa Fluor 647 , 5-Carboxyfluorescein ) mycobacteria ( MOI 50 ) for 15 min and washed 3 times with PBS . The cells were then incubated at 37°C for the indicated times and immediately analyzed by FACS , using a gating FSC/SSC selective for macrophages . The ratio of the mean fluorescence intensity ( MFI ) emission between the two dyes was determined . Values were compared with a standard curve obtained by resuspending the cells that had phagocytosed labeled bacteria for 1 h at a fixed pH ( ranging from pH 5 . 7 to 7 . 3 ) and containing 0 . 1% Triton X-100 . Cells were immediately analyzed by FACS to determine the emission ratio of the two fluorescent probes at each pH value . All animal experiments were performed in animal facilities that meet all legal requirements in France and by qualified personnel in such a way to minimize discomfort for the animals . All procedures including animal studies were conducted in strict accordance with French laws and regulations in compliance with the European community council directive 68/609/EEC guidelines and its implementation in France . All protocols were reviewed and approved by the Comité d'Ethique Midi-Pyrénées ( reference MP/04/26/07/03 ) . Six- to eight-week-old female C57BL/6 mice were anesthetized with a cocktail of ketamine ( 60 mg/kg; Merial ) and xylasine ( 10 mg/kg; Bayer ) and infected intranasally with 1 , 000 CFUs of the various mycobacterial strains in 25 µL of PBS-0 . 01% Tween 80 . At 21 days post-infection , five mice per strain tested were sacrificed and lung and spleen homogenates were plated onto 7H11 agar plates for CFU scoring . | Tuberculosis ( TB ) is still responsible for nearly 1 . 3 million deaths annually . There is an urgent need to identify novel drug targets in the tubercle bacillus , Mycobacterium tuberculosis , in order to develop novel therapeutics . To proliferate inside its human host , and ensure its spreading , M . tuberculosis must adapt its nutritional requirements and metabolism to the molecular environment it encounters during infection . Elucidating the origin , nature , and acquisition mechanisms of the nutrients required by M . tuberculosis inside its host may help identify targets for novel antimicrobials . In this study we asked how the TB bacillus acquires nitrogen , a vital constituent of all living organisms , from host tissues . We show the amino acid asparagine to be an important source of nitrogen for the bacillus , and we identify two bacterial proteins , AnsP2 and AnsA , that allow the pathogen to capture and ‘digest’ asparagine , respectively . In addition , we report that asparagine ‘digestion’ allows the pathogen to resist the host immune defense and to survive inside host cells and tissues . This study paves the way for future research into M . tuberculosis nitrogen metabolism , and for the development of alternative therapeutic strategies to impair nitrogen acquisition by the bacillus and treat patients with TB . | [
"Abstract",
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"Results",
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] | [
"microbial",
"metabolism",
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] | 2014 | Mycobacterium tuberculosis Exploits Asparagine to Assimilate Nitrogen and Resist Acid Stress during Infection |
Kupffer cells ( KCs ) represent the major phagocytic population within the liver and provide an intracellular niche for the survival of a number of important human pathogens . Although KCs have been extensively studied in vitro , little is known of their in vivo response to infection and their capacity to directly interact with antigen-specific CD8+ T cells . Here , using a combination of approaches including whole mount and thin section confocal microscopy , adoptive cell transfer and intra-vital 2-photon microscopy , we demonstrate that KCs represent the only detectable population of mononuclear phagocytes within granulomas induced by Leishmania donovani infection that are capable of presenting parasite-derived peptide to effector CD8+ T cells . This restriction of antigen presentation to KCs within the Leishmania granuloma has important implications for the identification of new candidate vaccine antigens and for the design of novel immuno-therapeutic interventions .
Kupffer cells ( KCs ) , first identified in 1876 , are now recognised as the major population of mononuclear phagocytes to inhabit the resting liver . Lining the sinusoids , KCs express a wide range of phagocytic and innate recognition receptors , including CD32 [1] , lectin receptors [2] and TLRs ( notably TLR2 , 3 , 4 and 9 ) [3] , and their avid phagocytic activity has been associated with the clearance of blood borne pathogens and the maintenance of immune homeostasis [4] . Although for many years regarded as a homogenous population , recent data suggest that KCs may be divided into two sub-populations , one sessile and radiation resistant , the other motile and bone marrow derived and expressing higher levels of the costimulatory molecule CD80 [5] , reminiscent of the CX3CR1+ subset of monocytes that were recently shown to patrol healthy tissues including blood vessels and the skin [6] . In spite of the importance for KCs in the uptake of pathogens , data on their role in the presentation of pathogen-derived antigens is scarce , with most studies focusing on the role of sinusoidal endothelial cells [7] and hepatocytes [8] in the induction of CD8+ T cell tolerance , or the ability of hepatic stellate cells and dendritic cells ( DCs ) to prime CD4+ , CD8+ and NKT cells [9] , [10] . In addition to providing a first line of defense against pathogens , KCs are also believed to be involved in downstream events associated with chronic disease , notably in granulomatous inflammation . Granulomas are well-defined mononuclear cell-rich aggregates that ideally serve to ‘contain and control’ pathogen spread [11] , [12] , but when unregulated may also contribute to disease pathology [13] . Experimental infection with visceralising species of Leishmania provides , along with experimental mycobacterial infection , some of the best characterised models for evaluating granuloma form and function [14] , [15] , particularly within the hepatic microenvironment . In experimental visceral leishmaniasis ( VL ) , current models of hepatic granuloma formation , based largely upon data obtained using static imaging approaches , suggest that infected KCs create the central nidus of the granuloma , fusing with other mononuclear phagocytes of less well-defined origin , and ultimately attracting lymphocytes and monocytes [16] through chemokine secretion [17] , [18] . More recent studies using BCG infection have provided some additional information on macrophage dynamics and T cell motility within hepatic granulomas during this infection [19] but fail to directly address KC function . In spite of the fact that granuloma macrophages harbour much of the hepatic pathogen load during experimental VL , and there have been numerous reports of intracellular infection with Leishmania parasites affecting macrophage APC function [20] , [21] , [22] the role of KCs as antigen presenting cells in these models has yet to be directly addressed . In experimental VL , CD8+ T cell responses are required for the effective clearance of parasites [23] , provide one of the best correlates of protection following vaccination [24] and can be used effectively in adoptive immunotherapy [25] . These and other data [26] , [27] , [28] have fuelled interest in the potential for immuno-prophylactic or immuno-therapeutic expansion of CD8+ T cells as a means of disease control . In the present study , therefore , we have directly addressed the question of whether KCs laden with intracellular Leishmania can be directly recognized by antigen-specific effector CD8+ T cells . Our data demonstrate that the majority of amastigote-infected cells within the core of a granuloma represent KCs that have migrated from neighbouring sinusoids , and by flow cytometry , only this population of KCs expresses detectable Kb-SIINFEKL complexes after infection of mice with OVA-transgenic L . donovani . To determine whether KCs engage in cognate interactions with CD8+ T cell in situ , we used intra-vital 2-photon microscopy to quantify T cell recruitment into and behaviour within individual granulomas . These studies show that effector CD8+ T cells accumulate in granulomas in an antigen-specific manner , as a result of having prolonged interactions with amastigote-laden KCs . Thus , we provide the first evidence that KCs undergo cognate interactions with CD8+ T cells in the context of Leishmania infection , a result which has important implications for the development of immunotherapy against this intracellular pathogen .
L . donovani amastigotes are usually identified in tissue based on their characteristic staining pattern after H&E staining of thin sections [14] , with the sensitivity of detection , particularly for individual parasites being improved by immuno-histology using polyclonal or monoclonal antibodies [29] . To more readily observe parasites by fluorescent microscopy , we generated stable infective clones of L . donovani expressing tdTomato ( tdTom; [30] ) , a fluorochrome amenable to both confocal and multi-photon imaging . We first infected mice with tdTom-L . donovani and examined their distribution in the liver at day 14 p . i . ( Figure 1 ) in conjunction with staining for F4/80 , a marker of mature KCs [31] and CD11c , a marker characteristically associated with DCs [32] . L . donovani amastigotes were readily apparent both at low magnification , where individual amastigotes within heavily-infected cells could not be resolved ( Figure 1A ) , and at higher magnification , where individual parasites were easily distinguished ( Figure 1B ) . Parasites were observed in two main anatomical locations: within granulomas , where they were predominantly associated with the core , and within the parenchyma , where by DAPI staining they appeared to be within isolated cells in areas largely devoid of local inflammatory reactions ( Figure 1C ) . Almost invariably , amastigotes in either location were found within F4/80+ cells ( Figure 1A–C ) . The close apposition and membrane interdigitation of F4/80+ cells made it difficult to score individual cells , so we did not attempt to calculate the percentage of F4/80+ cells that were infected within the core of the granuloma . Reminiscent of the pattern of staining with NLDC-145 , a DEC 205-specific antibody [33] , a diffuse but detectable level of CD11c expression was also observed on cells at the core of many , but not all , granulomas . These CD11c+ cells also expressed somewhat lower levels of F4/80 , compared to the F4/80+ CD11c− cells that occupied the granuloma mantle ( Figure 1D–F ) . Heterogeneity of expression of CD11c within granulomas did not correlate with the presence or absence of amastigotes . In contrast , CD11b+ cells were usually found in the granuloma mantle , with some clearly identifiable as neutrophils based on nuclear morphology . Importantly , the large amastigote-laden cells at the granuloma core that co-stained for F4/80 and CD11c were almost uniformly CD11b− ( Figure 1G–I ) . These data , together with previously published studies [33] suggest that the majority of intra-granuloma amastigotes are found within F4/80+ cells , and some of these cells acquire markers in this local micro-environment that are often associated with DC . Although flow cytometry might be expected to provide a means for further phenotypic analysis of tdTom-L . donovani infected macrophages , separation of tdTom-L donovani positive cells by cell sorting ( Figure S1A and B ) , followed by cytospin and Giemsa staining ( Figure S1C ) indicated that parasites became associated with a range of different cell types , including macrophages , monocytes , lymphocytes and polymorphonuclear cells . In many cases , parasites were bound rather than internalised by these cells . Similarly , co-preparation of cells after mixing of liver tissue from C57BL/6 ( CD45 . 2 ) mice that were infected with WT-L . donovani and from B6 . CD45 . 1 mice that were infected with tdTom-L . donovani clearly demonstrated transfer of tdTom-L . donovani from CD45 . 1 to CD45 . 2 cells . Hence , flow cytometry does not provide a reliable means to further characterise the phenotype of cells infected in situ . Although macrophages are acknowledged to be a central feature of granulomatous inflammation , the precise origin of these cells has not been directly determined . To address this issue , we first studied the distribution of liver resident and inflammatory phagocytes in naïve and L . donovani-infected mice . KCs in the liver of uninfected mice show a characteristically uniform distribution , lining the sinusoids and forming a reticular surveillance network [34] . To more fully determine the spatial context in which KCs line the sinusoids , we performed whole mount immuno-histochemistry , using F4/80 as a marker of mature KCs ( Figure 2 ) . In naïve mice , large KCs with extensive projections were readily apparent within sinusoidal spaces ( Figure 2A , and Video S1 ) forming a regular uniformly distributed phagocytic network . In contrast , in mice infected for 14 days with L . donovani , many KCs were aggregated within granulomas , leaving large areas of the sinusoidal network devoid of detectable KCs ( Figure 2B and Video S1 ) . Strikingly , although not participating in the granulomatous inflammatory response , KCs that remained isolated within the sinusoidal network nevertheless displayed morphological changes , which could be quantified as a reduced total cell volume compared to KCs in uninfected mice ( Figure 2C , D ) . Although losing the spatial information provided by whole mount immunohistochemistry , we isolated hepatic mononuclear cells and labeled with F4/80 and CD11c to identify four populations of cells in both naive ( Figure 2E ) and L . donovani infected ( Figure 2F ) livers . While all four populations were present in both naïve and infected mice , the proportions changed with infection . CD11c−F4/80− cells ( Figure 2E and F , R1 ) accounted for 51 . 7+/− 5 . 13% of F4/80+ cells in naïve mice and 38 . 88 +/− 4 . 34% in infected mice . CD11chiF4/80int cells ( Figure 2E and F , R2 ) accounted for 17 . 11 +/− 3 . 12% in naïve mice and 19 . 29 +/− 3 . 31% in infected mice . CD11chiF4/80hi cells ( Figure 2E and F , R3 ) accounted for 13 . 39 +/− 2 . 51% in naïve mice and 13 . 5 +/− 2 . 96% in infected mice . Finally , CD11cintF4/80int cells ( Figure 2E and F , R4 ) accounted for 7 . 83 +/− 0 . 87% in naïve mice and 14 . 67 +/− 4 . 82% in infected mice . MHCII expression , used as a surrogate marker for macrophage activation , was shown to be upregulated on all four populations upon infection ( Figure 2G–J ) . These data suggest that most KCs in the infected liver , even if not recruited into granulomas , had responded to the developing inflammatory environment . To determine if the aggregation of KCs in granulomas was due to a re-distribution of liver-resident KCs , or whether this reflected the recruitment/differentiation of blood or BM-derived precursors after infection had been established , we used fluorescent nanobeads ( NBs ) to label KCs ( and other potential liver-resident phagocytic cells ) prior to infection . Such cells could then be subsequently discriminated from inflammatory phagocytes recruited after infection ( Figure 3A–F ) . We first analysed the distribution of these NBs after intravenous injection into naïve mice . As shown in Figure 3A , NBs were readily ingested by liver-resident F4/80+ KC in uninfected mice , providing a readily detectable measure of their phagocytic activity . Most KCs were phagocytic ( ∼74% , n = 42 ) , with a variable phagocytic load of NBs . Within individual KCs , multiple ‘patches’ of NB labeling could often be observed , presumably reflecting uptake of NBs into discrete phagosomes . These patches also varied in size , a result that might reflect either aggregation of NBs during injection and/or coalescence of multiple phagosomes each containing small numbers of NBs . NBs were also phagocytosed by desmin+ hepatic stellate cells in naïve mice ( ∼66% of desmin+ cells contained NBs , n = 90 ) , but large aggregates were rarely observed in these cells ( Figure 3B ) . CD11b+ cells are rare in the resting liver as determined by immuno-histochemistry [35] , and when observed , these cells did not contain NBs ( Figure 3C ) . We then injected mice with NBs and 4–12 h later , infected them with L . donovani . The distribution of NB+ cells was then observed at both day 14 p . i . ( Figure 3D–F ) and at d28 p . i . ( data not shown ) , with similar results being obtained at each time point . NBs were readily observed in L . donovani- infected mice , confirming their value as a long-term cell tracer . NBs were highly concentrated in granulomas , largely at the core , and almost exclusively within F4/80+ KCs ( Figure 3D ) . In contrast , although occasionally present within granulomas , hepatic stellate cells were normally excluded from the core of the granuloma and usually did not contain readily distinguishable NBs ( Figure 3E ) . Strikingly , NBs were also not observed in CD11b+ cells ( presumptive monocytes , DC and neutrophils ) either at the core of the granuloma or when more peripherally dispersed at the granuloma mantle ( Figure 3F ) . To confirm that the distribution of NBs in granulomas was not the result of rapidly recruited inflammatory cells , NBs were injected and the mice infected with L . donovani 12 hours later as described above . No significant infiltration of inflammatory cells was observed 6 hours after infection , with the proportions of CD11b− , CD11bint and CD11bhi cells being similar between mice that received NBs only or mice that received NBs and L . donovani , whether measured in terms of either the frequency or absolute number of cells ( Figure S2 ) . These data suggest that NB distribution after infection reflects KC redistribution and is not influenced by rapidly recruited inflammatory cells . Collectively , these data therefore strongly support the contention that the core of the granuloma is derived almost exclusively from resident KCs recruited from the sinusoids early during the inflammatory process . As a first step to determining whether cells within hepatic granulomas could present MHC class I-restricted antigens derived from L . donovani amastigotes , we infected mice with double transgenic L . donovani made by transfecting an OVA-expressing L . donovani clone ( PINK; [25] ) with tdTom . OVA expressed by PINK is localised to the parasite plasma membrane by virtue of the HASPB N-terminal dual acylation sequence [36] , and is available for in vivo recognition by Kb- restricted OVA257–263 ( SIINFEKL ) -specific TCR transgenic CD8+ T cells [25] , [37] . To determine which cells could process and present SIINFEKL derived from these transgenic parasites , we first used 25-D1 . 16 , a mAb specific for this MHC-peptide complex [38] . By immunohistochemistry , however , we were unable to detect expression of this complex in any cells within the infected liver ( data not shown ) , probably reflecting the very low levels of complex expressed in this physiological setting . Although loosing the spatial information provided by immuno-histochemistry , we next used flow cytometery as a more sensitive assay to detect whether this complex was expressed and on which cells ( Figure 4 ) , comparing the expression of 25-D1 . 16 on hepatic mononuclear cells isolated from mice infected with either PINK or WT L . donovani . Four discrete populations were identified on the basis of CD11c and F4/80 expression ( Figure 4A and B , gates 1–4 ) . In comparison to ‘control’ staining determined from analysis of mice infected with WT L . donovani , no expression of 25-D1 . 16 was observed in CD11c−F4/80− cells ( ( Figure 4C , R1 ) nor in CD11chiF4/80int cells ( Figure 4D , R2 ) . These CD11chiF4/80int most likely equate to the small number of intra-granuloma DCs observed by histology ( Figure 1 ) . We also could not detect specific staining in CD11chiF4/80hi cells ( Figure 4E , R3 ) though the high autofluorescence of these cells may have precluded detection of low levels of 25-D1 . 16 expression . In contrast , CD11cintF4/80int cells from mice infected with PINK , which represented 11 . 47±1 . 4% of total hepatic leucocytes , contained two populations of cells with differing intensity of expression complexes recognised by 25-D1 . 16 ( Figure 4F , R4 ) . Importantly , CD11cintF4/80int cells mice infected with WT L . donovani ( a genetic control for non-specific mAb binding ) were not stained with 25-D1 . 16 . CD31+ liver sinusoidal endothelial cells account for approximately 35% of the total hepatic mononuclear cells , but are negative for F4/80 and CD11c . Similarly , hepatic stellate cells , noted for their strong autofluorescence and high side scatter properties [39] make up approximately 3% of the hepatic mononuclear cells in these preparations and are likely located within the R3 population , based on expression of F4/80 and CD11c expression ( data not shown ) . Neither the F4/80− nor the R3 population however expressed MHCI-peptide complexes as determined by 25-D1 . 16 staining . These data argue , therefore , for expression of the Kb-SIINFEKL epitope on restricted population ( s ) of L . donovani-infected hepatic cells whose phenotype as determined by flow cytometry closely resembles that of infected F4/80+CD11clo KCs at the core of the granuloma ( Figure 1 ) . Although we detected MHC-peptide complex on presumptive intra-granuloma KCs , the inherent loss of spatial information associated with flow cytometry prompted us to seek alternate approaches to identify antigen recognition by CD8+ T cells in situ . As real-time imaging of T cell dynamics has been shown to be a valuable tool for analysing T cell-APC [40] and T cell-target [41] interactions , and we had already established an adoptive transfer model that provided indirect evidence for cognate antigen recognition by CD8+ T cells , we combined these approaches to study the dynamics of CD8+ T cells in the liver of L . donovani-infected mice . First , to establish the nature of the T cell environment into which adoptively transferred cells would be imaged , we used hCD2 . GFP reporter mice [42] to visualise the entire T cell ( and NK cell ) content of the L . donovani granuloma . In mice infected with either wild type L . donovani or tdTom-L . donovani , prominent accumulations of T cells were observed from d14 onwards ( Figure 5 and data not shown ) . These accumulations were heterogeneous in nature with the T cells demarcating a structure that varied from being a large flat accumulation of cells close to the collagenous liver capsule ( Figure 5A , B and Video S2 ) to more compact , rounded accumulations of cells that protruded further into the parenchyma ( Figure 5C and Video S2 ) . Examination of the total volume of the T cell accumulations at d14 ( Figure 5D ) and d25 ( Figure 5E ) showed that while the response was heterogeneous in nature throughout the time course of infection studied , smaller granulomas were more frequent in early infection , while larger accumulations were seen later in the response . Most T cell accumulations had readily detectable parasites ( Figure 5F and G and Video S3 ) , confirming that these accumulations were indeed granulomas , though as shown earlier using DAPI staining ( Figure 1A ) , infected macrophages could also be found in the parenchyma in the absence of local T cell recruitment ( Figure 5H and I and Video S3 ) . Second harmonic imaging of collagen ( Figure 5A–C and F–I ) also confirmed earlier reports indicating that the L . donovani granuloma is not highly fibrotic in mice [43] , [44] and in some instances migration of T cells along collagen fibres within individual granulomas was observed ( data not shown ) . As the tracking of T cells inside BCG-induced granulomas has suggested that the granuloma microenvironment inhibits the motility of T cells in a non-antigen specific manner [19] , we compared the dynamics of OT-I T cells found within WT L . donovani- induced granulomas with those found in the liver parenchyma of the same infected mice . As shown in Figure 5J-L , we found no significant difference in cell velocity or track length whether cells were moving in the parenchyma or within granulomas . Although the meandering index was higher for cells outside of granulomas , this might reflect the influence of the sinusoidal network on the path of the cell movement . Additional analysis of the instantaneous velocities of cells shown in Video S5 , also failed to show any obvious difference in the pattern of instantaneous velocity for OT-I cells inside compared to outside of granulomas ( Figure S3 ) . Hence , unlike the BCG granuloma , the L . donovani induced granuloma does not appear to pose a major physical barrier to CD8+ T cells motility . To study the antigen-specific behaviour of CD8+ T cells in granulomas , we labelled effector memory-like CD62Llo OT-I T cells [45] with CMTMR and adoptively transferred these cells into hCD2 . GFP mice infected 21d earlier with either WT L . donovani or PINK . The fate of these OT-I T cells in the liver was then followed for up to12 h post transfer . Within 4 h of transfer , transferred OT-I T cells were detected in the liver and found to be primarily within sinusoids ( Figure 6A and Video S4 ) but by 12 h post-transfer , large numbers were fully embedded within granulomas ( Figure 6B and Video S4 ) . From full 3D-reconstructions of granulomas , we scored the number of OT-I T cells embedded within granulomas in mice infected with either WT L . donovani or PINK at either 4 h or 12 h post transfer . Although antigen-independent accumulation of OT-I T cells was observed at 4 h ( Figure 6C ) , by 12 h , antigen-specific accumulation of OT-I T cells was evident ( Figure 6D ) . Importantly , granuloma volume , a surrogate measure of the number of T cells , was not significantly different in mice infected with these two parasite lines , ruling this out as one possible explanation for the effect observed ( Figure 6E ) . As an alternate means to confirm the antigen specificity of intra-granuloma CD8+ T cell accumulation , we also transferred effector memory-like influenza-specific F5 CD8+ T cells into WT L . donovani and PINK infected mice . No difference in F5 T cell accumulation was observed in the granulomas in these mice ( Figure 6F ) . Altered accumulation of CD8+ T cells within granulomas could be the result of altered rates of immigration or emigration . To distinguish between these possibilities , we examined the dynamics of OT-I T cell movement within individual granulomas in WT L . donovani and PINK-infected mice 5–14 h post-transfer of OT-I T cells . We calculated the rate at which OT-I T cells entered granulomas by dividing the number of cells entering or exiting the granuloma in each imaging period by the length of the imaging period in minutes . No significant differences were seen in the rate at which OT-I T cells entered granulomas in WT L . donovani- and PINK-infected mice ( Figure 7A ) . In contrast , the rate at which OT-I T cells left granulomas in PINK-infected mice was slower than in WT L . donovani-infected mice ( Figure 7B ) . The finding that exit rate , but not entrance rate , was influenced by the presence or absence of cognate antigen suggested that OT-I T cells behaved differently if antigen was available . To determine whether this was reflected in altered velocity , we calculated the average velocity of OT-I cells ( n = 311 cells from 43 imaging fields ) in PINK-infected and OT-I cells ( n = 266 cells from 48 imaging fields ) in WT L . donovani-infected hCD2 . VaDs Red mice ( here used to identify the border of the granuloma by endogenous labelling of all other T cells ) . The results of this analysis demonstrated that OT-I T cells moved significantly more slowly in the presence of cognate antigen ( Figure 7C , D , E and Video S5 ) . The meandering index ( calculated by diving the displacement of the cell from its original starting point by the total track length of that cell ) was significantly higher for OT-I T cells transferred into PINK-infected mice than those transferred into WT L . donovani- infected mice ( Figure 7E ) . This was reflected by significantly lower track lengths for OT-I cells transferred into PINK infected mice and therefore in the presence of cognate antigen ( Figure 7F ) . As further independent confirmation that the difference in dynamics of OT-I in the presence and absence of antigen was due to antigen recognition and not due to other differences in the granulomas formed following infection with PINK and WT L . donovani , we labelled OT-I T cells with hoescsht-33342 and F5 T cells with CFSE and co-transferred equal numbers into PINK-infected mice . In these experiments , granulomas were visualised by pre-injection of fluorescent NBs to mark the core of the granuloma ( Figure 2 ) . In agreement with the data generated using OT-I cells transferred into mice infected with WT L . donovani or PINK parasites , OT-I cells had slower average velocity than F5 T cells imaged simultaneously in granulomas of PINK-infected mice ( Figure 7H , I and Video S6 ) . Thus , the presence or absence of cognate antigen determines the dynamics of CD8+ T cell motility in hepatic granulomas . To determine whether this antigen-dependent reduction in CD8+ T cell motility was due to more extensive or more prolonged interactions with granuloma-resident cells presenting MHCI-peptide complexes , we first asked whether transferred OT-I cells interacted with the granuloma-associated KCs , by labelling the latter at the onset of infection with NBs , as described above . Transferred OT-I cells were observed to make frequent contacts with NB-labelled KCs ( defined by large aggregates of NBs; Figure 8A and B and Video S7 ) . However , the presence of cognate antigen did not influence either the percentage of OT-I T cells interacting with NB+ cells ( Figure 8C ) or in the duration of these contacts ( Figure 8D ) . On the other hand , as shown above , not all granuloma-associated KCs contained amastigotes ( Figure 1 ) and similarly not all cells with this phenotype expressed detectable Kb-SIINFEKL complexes ( Figure 4 ) . Many NB+ KC would be expected , therefore , to be devoid of antigen/parasites , and represent KCs recruited during the process of granuloma development ( Figure 2 ) , with the net effect of diluting out any the effect of any antigen-specific interactions between KCs and OT-I cells . Therefore , to more directly assess the potential of infected KCs to present OVA peptide , we infected mice with tdTom-PINK or tdTom-WT L . donovani and evaluated the interaction of these cells with CFSE-labelled transferred OT-I T cells ( Figure 8E and F and Video S8 ) . As with NB-labelled cells , OT-I T cells made multiple contacts with amastigote-infected KCs within granulomas containing both PINK and WT L . donovani . However , both the frequency of intra-granuloma OT-I T cells that engaged in this behaviour ( Figure 8G ) and the subsequent duration of these contacts ( Figure 8H ) was clearly influenced by the presence of cognate antigen . These studies provide the first direct evidence of intra-granuloma antigen recognition by CD8+ T cells and for in situ presentation of MHCI-restricted peptides by KCs .
Granulomas are well-recognised as a central feature of the pathogenesis of human [46] , [47] , canine [48] and experimental [49] VL , and most if not all perturbations of immune function made under experimental conditions can be related to alterations in granuloma form and function [14] , [50] . Nevertheless , the processes by which these structures form around initially infected KCs and how the microenvironment they create serves to guide and focus host effector function remain poorly understood . Here , we provide the first direct in situ evidence that KCs serve as targets for antigen recognition by granuloma-infiltrating CD8+ T cells . In addition , our study , together with that of Egen and colleagues using experimental BCG infection [19] , help dispel the notion of the granuloma as being a static tissue structure and reveal the intricate dynamics of lymphocytes within this unique microenvironment . Historically , granulomatous inflammation during L . donovani infection has been classified on the basis of the histological response that occurs around each infected KC , providing both a quantitative means to score granuloma ‘maturation’ and a surrogate measure of the quality of the host protective response [14] , [50] , [51] . Our studies using fluorochrome-reporter transgenic parasites and mice , whole mount confocal and 2-photon microscopy , performed here as a prelude to the analysis of antigen presentation within granulomas , also provide new insight into some of the basic features of granuloma formation . For example , our data shows that a significant proportion of the sinusoidal KC network becomes incorporated within developing granulomas , yet at the same time even those KCs not directly engaged in the process undergo profound morphological changes indicative of activation . Such changes in morphology have been used previously in vitro [52] and ex vivo [53] as correlates of macrophage activation , but cell volume has not previously been measured in situ . The correlation of cell volume with increased expression of cell surface MHCII suggests that it is a true indication of macrophage activation , opening new avenues for the use of whole mount microscopy in the study of KC activation in the study of diseases such as liver injury [54] or liver regeneration following resection or transplantation [55] . Our results also confirm earlier observations [56] that some infected KCs fail , at least for many days or even weeks , to form a focus for inflammation . This marked asynchrony in granuloma development has been the subject of debate [50] and has recently been subjected to systems biology-based approaches [57] , [58] , but the key determinants of this response remain to be identified . In a recent study in the model organism zebrafish , macrophages infected with BCG were able to migrate out of granulomas [56] . Although migration of L . donovani-infected KCs might also give rise to a population of infected cells apparently uninvolved in the granuloma formation , we do not believe that this scenario is likely in the intact mammalian host , as in neither our studies nor in those of Egen et . al [19] has KC exit from granulomas been observed . The main focus of this study , however , was on identifying the nature of the cells which engaged with effector CD8+ T cells within the granuloma microenvironment , and in this regard , we provide the first in vivo evidence of a cognate interaction between KCs and antigen-specific CD8+ T cells . Whereas KCs were abundant in granulomas , CD11chi F4/80− DCs were notable by their relative paucity , a finding also reflected in the low frequency of CD11chiF4/80−/int DC observed in mononuclear cell preparations made from infected mice . Although CD11c+ cells were detectable , co-labelling with F4/80 , the presence of high numbers of intracellular amastigotes and labelling with NBs confirmed that most of these cells were KCs on which CD11c expression had been aberrantly induced ( as is also the case for DEC-205 [33] ) . Likewise , we observed few CD11b+CD11c+ cells in granulomas , and CD11b+ cells rarely contained intracellular amastigotes . These later data are in stark contrast to the situation observed in the lesions of mice infected with L . major , where the bulk of the amastigote load has been reported to reside within CD11b+CD11c+ ‘inflammatory monocytes’ or ‘TipDC’ [59] , [60] . Our data are , however , consistent with earlier reports that indicated both a preference by L . donovani for infection of ‘resident’ compared to inflammatory macrophages and the greater capacity of L . major to stimulate CD11b+ cell recruitment even to hepatic sites of infection [61] . To determine the capacity of these infected KCs to interact in a cognate manner with effector CD8+ T cells , we first tried using immunohistochemical approaches and flow cytomtery to identify which cells could process SIINFEKL from OVA-transgenic PINK parasites and then form complexes recognised by mAb 25-D1 . 16 [38] . We were unable to detect expression by any immunohistochemical approach we tested ( including teramide labelling ) . By flow cytometry , however , we could detect specific staining on CD11cintF4/80int cells that we believe represent intra-granuloma KCs . Such staining was notably absent on CD11chiF4/80−/int DCs . These ex vivo analyses should however be viewed with some caution . First , granulomas cannot be specifically isolated for analysis , and as a consequence cells analysed by flow cytometry may originate from any anatomical compartment within the infected liver . Second , we cannot exclude the possibility that MHCI-peptide complexes and/or whole parasites are either shed or transferred to other cells during the isolation procedure . Such transfer of MHCI-peptide complexes has been noted under in vitro culture conditions [62] , [63] and indeed transfer of parasites between populations of cells during tissue disruption and subsequent cell isolation has been noted by us ( Figure S1 ) and by others [59] . It is , however unlikely that processing of antigen into MHCI is able to occur within the 30 min collagenase digestion step , or the 10 min density gradient centrifugation steps both of which were performed at room temperature , as detection of MHC-I-peptide complexes takes >1 hr following virus infection [64] and is likely to follow similar kinetics following Leishmania infection . All other processing steps were performed on ice . Whilst analysis of the expression of MHCI-peptide complex expression might , therefore , also suffer from the same technical difficulties , we believe this is unlikely . Third , only low numbers of MHCI-peptide complex are required for productive engagement with CD8+ T cells [65] , well below that detectable by mAb staining . These caveats notwithstanding , our data suggested that KCs and not DCs expressed such complexes in most abundance . It should also be noted that sessile KCs are not readily isolated by the methods we used [5] and as such have been largely excluded from this ex vivo analysis . We cannot therefore comment on whether such KCs do or do not express complexes recognised by 25-D1 . 16 . To more definitively identify the sites of antigen presentation , we therefore turned to intra-vital imaging of adoptively transferred CD8+ effector cells . CD62Llo effector CD8+ T cells generated in vitro using antigen expansion and IL-2 , were chosen for analysis , as these cells have previously been shown to bring about a rapid and antigen-specific reduction in hepatic parasite burden [25] . Furthermore , analysis of the fate of such cells may provide clues as to how similar effector cells induced by vaccination may behave . We used similar methods to those of others working in lymphoid tissue [66] , [67] , in tumor microenvironments [68] , [69] , in BCG granulomas [19] and in the brains of Toxoplasma gondii infected mice [70] , [71] to define the dynamic behaviour of CD8+ T cells in hepatic granulomas caused by L . donovani and our results not surprisingly showed marked similarities in T cell behaviour . The dynamic nature of the T cell compartment within the L . donovani granuloma was also clearly evident in all the imaging that we performed . Though superficially similar to that reported for BCG infection , contrasts between L . donovani and BCG granulomas can be noted . For example , whilst T cells were reported to stay within the granuloma structure following BCG injection [19] , we found that endogenous T cells , as well as adoptively transferred antigen-specific and non-antigen specific CD8+ T cells , could readily migrate out of granulomas , indicating a net flux through this ‘compartment’ . Additionally , while a marked difference in the velocity of cells tracked within and outside of BCG induced granulomas showed that the granuloma per se was capable of inducing a change in cell movement [19] , CD8+ T cells migrated without apparent constraint into , within and out of L . donovani granulomas , and non-antigen specific cells showed the same speed of cell movement whether located inside or outside of granulomas . Similarly , analysis of the instantaneous velocity of cells within and outside of granulomas showed no obvious differences , confirming the presence of antigen as the only factor that induces a change in cellular behaviour . The differences in behaviour of T cells in these two types of granuloma may be attributable to differences in composition of the mononuclear cell mantle or reflect differences in other environmental factors e . g . the level of fibrosis [43] , [44] . The traffic of antigen-non-specific T cells through granulomas also provides a timely reminder that the histological identification of T cells within granulomas , in the absence of dynamic measurement , is neither an indicator of antigen-specificity nor a good marker for the effector capacity of these structures . In most cases , we validated our approach by cross-over experiments in which on the one hand we used adoptive transfer of OT-I T cells into mice infected with WT L . donovani or PINK parasites , and on the other hand , we used co-transfer of OT-I and F5 T cells into PINK-infected mice . While labelling with NBs was sufficient to allow the identification of the core of the granuloma , it does not delimit the extent of the granuloma . Hence , CD8+ T cells often appear distant from the core of the granuloma , they were still maintained within its boundaries . Cells frequently migrated near to and , in fact , through the NB-labelled core , but the interactions with NB-labelled cells were not sufficient to demonstrate antigen-specific interactions . This result is not surprising , given that not all cells present in the granuloma core contained parasites ( Figure 1 ) and the effect of any antigen-specific contacts with infected NB+ cells would likely be diluted out by interactions with non-infected NB+ cells . Meandering of antigen-specific CD8+ T cells was extensive , as might be predicted from the dense packing of lymphocytes within granulomas and whereas migration upon collagen fibres was noted , this was not seen in all instances . Numerous contacts were also made between CD8+ T cells and amastigote-infected KCs . Importantly , as measured by all these parameters , the intra-granuloma behaviour of effector CD8+ T cells was markedly influenced by the presence of cognate antigen . In spite of clear data supporting intra-granuloma antigen recognition by CD8+ T cells , we have not to date observed evidence of direct effector activity of these transferred CD8+ T cells , such as dispersal of amastigotes or their loss of apparent viability . The failure to do so may be due to the length of time taken for CTL to lyse targets in vivo , with target cell lysis in vivo reported to take as little as 17 min in the case of target cells pulsed with high doses of peptide [72] or as long as 6 hours for tumour targets [73] . Additionally , there are technical limitations to these methods as the maximum imaging window we can achieve is 10 h , and this may be insufficient to observe degradation of amastigotes ( and/or tdTom protein ) subsequent to cytokine-mediated macrophage activation . Similarly , as KC integrity was not directly imaged in these experiments , it is possible that host cell lysis occurs but amastigotes were rapidly re-engulfed by neighbouring KCs . Furthermore , we cannot rule out that after recognition , CD8+ T cells exert their leishmanicidal effect indirectly and over a longer time frame than examined here . Additional developments in imaging technology and new tools to study macrophage responsiveness to activation signals in real time will be required to conclusively address this issue . Although our data are the first to directly demonstrate KC interactions with effector CD8+ T cells , KC-mediated priming of CD8+ T cells was recently demonstrated using cell lines in vitro [74] and also with freshly isolated KCs ex vivo [75] , suggesting that further studies into the role of KC in presenting Leishmania-derived antigens to naïve CD8+ T cells at the initiation of infection are also now warranted . In conclusion , we have shown that KCs laden with amastigotes serve as the principal target for antigen recognition by effector CD8+ T cells within the granuloma microenvironment . Our data suggest that if CD8+ T cell recognition is to form the basis for prophylactic or therapeutic vaccination , then it will be essential to understand the rules which govern MHC class I epitope selection within infected KCs , as well as within those APC ( e . g . DCs ) that are responsible for induction of CD8+ T cell responses . Furthermore , chemotherapeutic or immunotherapeutic interventions that enhance antigen presentation by KCs may prove highly beneficial .
C57BL6 mice were obtained from Charles River ( UK ) . hCD2 . GFP [42] and VaDS Red B6 and Rag-1−/− F5 mice , originally a kind gift from Dimitris Kioussis ( NIMR , Mill Hill , UK ) , and Rag-1−/− OT-I mice were bred and housed under specific pathogen-free conditions and used at 6–12 weeks of age . The Ethiopian strain of Leishmania donovani ( LV9 ) and OVA expressing LV9 ( PINK ) [25] were maintained by serial passage in Rag-1−/− mice . Amastigotes were isolated from infected spleens , as previously described [24] , and mice were infected with 2×107 L . donovani amastigotes intravenously ( i . v . ) via the tail vein in 200 µl of RPMI 1640 ( GIBCO , Paisley , UK ) . For pre-labelling of liver-resident macrophages , PD nanobeads ( 545 marked ) ( Sigma ) were pre-injected into mice i . v . 5–24 hours prior to injection of L . donovani amastigotes . All experiments were approved by the University of York Animal Procedures and Ethics Committee and performed under UK Home Office license ( ‘Immunity and Immunopathology of Leishmaniasis’ Ref # PPL 60/3708 ) . Tandem Tomato fluorescent protein ( tdTom ) gene [30] was cloned into the plasmid pSSU-Neo-Infantum to give pSSU-Neo-Infantum-tdTom [76] [Oyola et . al . manuscript in prep] . WT L . donovani and L . donovani HASPB::OVA ( PINK ) promastigotes [25] , [36] were transfected with this construct ( which targets genes into the ribosomal locus of L . donovani ) and clones selected by serial dilution in the presence of neomycin . Clones were checked for correct integration of the tdTom gene by PCR and Southern Blotting of BamHI and ScaI digested genomic DNA with a 586 bp probe against the neomycin phosphotransferase gene . Confocal microscopy was performed on 8–10 µm frozen sections . For tissue containing tdTom expressing parasites , tissue was fixed in 4% paraformaldehyde ( PFA ) for two hours before overnight incubation in 30% sucrose and embedding in Optimal Cutting Temperature ( OCT ) medium ( Sakura ) . For all other labelling , tissue was snap-frozen in OCT and sections fixed in ice cold acetone for 8 min . F4/80 , CD11c and CD11b antibodies were conjugated to Alexa488 or Alexa647 ( eBioscience , UK ) and Rabbit anti-desmin ( Abcam ) was detected with goat-anti Rabbit-647 ( Invitrogen ) . For whole mount confocal microscopy , thick tissue sections were cut with a scalpel blade and labelled as previously described [77] . Briefly , sections were fixed in 4% PFA for 15 min at room temperature ( RT ) , washed in PBS-Triton ( 0 . 15% ) and blocked for 2 hours at RT . All subsequent antibody labelling steps were performed for 8 hours or overnight at 4°C followed by final fixing in 4% PFA for 15 min at RT followed by dehydration in methanol . Samples were optically cleared in BABB ( sigma ) and imaged using a Zeiss LSM510 axioplan microscope ( Carl Zeiss Microimaging ) . Data were rendered and analysed using Volocity software ( Improvision ) . Cell volumes were calculated by generating a measurement item based on RGB and exclusion of objects <300 µm3 and >15 0000 µm3 . All objects were manually checked for accuracy before data were plotted and analysed in Prism v5 . 1 ( Graphpad ) . Hepatic mononuclear cells were prepared from the livers of wild type and PINK L . donovani infected livers , or livers from C57BL/6 mice injected with 100 µg SIINFEKL peptide I . V , following collagenase digestion as previously described [78] . Briefly , livers were perfused with PBS containing 2%FCS and digested in 350 µg/mL collagenase D ( Worthington , UK ) for 30 min at RT . Digested livers were passed through a 100 µm cell strainer , washed twice in 2%FCS . PBS and hepatocytes removed by centrifugation on a 33% percoll density gradient for 12 min at 693 g . The remaining cell pellet was kept for further analysis . Isolated cells were labelled with 25-D1 . 16-biotin [38] and streptavidin-Alexa488 as well as CD11c-PeCy7 , F4/80-Alexa647 and CD11bPE or pacific blue ( eBioscience , UK ) . Cells were sorted based on expression of tdTom , with approximately 3000 sorted cells spun onto glass slides , fixed in methanol and stained with Giemsa for morphological analysis . CD8+ T cells resembling effector memory cells were derived in vitro as described previously [45] . Briefly , splenocytes from naive OT-1 transgenic mice were incubated with 10 µg/ml OVA257–264 ( Cambridge Bioscience ) for 1 h at 37°C , washed , and cultured for a further 48 h . Cells were then washed and incubated for a further 5–9 days with 20 ng/ml recombinant hIL-2 . CD62-L low cells were enriched to >95% purity by negative selection using anti-CD62-L microbeads ( Miltenyi ) . Enriched cells were labeled with 5 µM CFSE or CMTMR ( invitrogen ) or 6 µM Hoescht 33342 ( Sigma ) before transfer of 2×107 cells to recipient mice by intravenous injection . Freshly removed liver tissue was placed in 35 mm coverslip bottom Petri dishes ( MatTek corporation ) , kept moist with PBS and imaged on an inverted LSM 510 multiphoton microscope ( Carl Zeiss Microimaging ) . Images were acquired with a 40×1 . 1 water immersion objective and fluorescence excitation provided by a Chameleon XR Ti:sapphire laser ( Coherent ) tuned to 872 nm . Data were rendered and analysed using Volocity software ( Improvision ) . Granuloma volumes were calculated by drawing regions of interest in Volocity to get a 3D volume measurement in µm3 . Exported videos were arranged in After Effects software ( Adobe ) . Mice were anaesthetised with a combination of ketamine ( 100 mg/kg ) , xylazine ( 10 mg/kg ) and acepromazine ( 1 . 7 mg/kg ) given intraperitoneally . After 60 min , anaesthesia was maintained by subcutaneous injections of half doses approximately every 45 min . The abdomen of the animal was shaved , and a ∼1 . 5 cm midline incision made to expose the xiphoid process which was retracted to allow dissection of the falciform ligament . The left lobe of the liver was then gently exteriorised and the animal inverted onto a glass coverslip mounted within a custom made imaging platform . The liver was covered with sterile saline-soaked gauze to prevent dehydration and the mouse stabilised with micropore tape ( 3 M ) . Images were acquired on an inverted LSM 510 multiphoton microscope ( Carl Zeiss Microimaging ) ( as above ) which was maintained at 36°C by a blacked-out environmental chamber ( Solent Scientific , UK ) . For 4D analysis , 20–35 µM Z stacks were acquired with a Z distance of 2–3 µM approximately every 15–30 sec . Data were rendered and analysed using Volocity software ( Improvision ) and cell tracking performed manually , or automatically with manual checking . Entrance and exit rates were calculated by monitoring the number of OT-I cells entering or exiting granulomas , as defined by the endogenous T cell border or the presence of nanocrystals within each imaging window and dividing this number by the time of each imaging window in minutes , to get a rate of OT-I entrance and exit per minute . All granulomas imaged were included in this analysis , irrespective of whether they had associated OT-I cells . | Leishmania donovani is a protozoan parasite that causes severe disease in humans with associated pathology in the spleen and liver . In experimental models of L . donovani infection , the hepatic response to infection is characterised by the presence of a focal mononuclear cell-rich inflammatory response ( a granuloma ) surrounding cells infected with intracellular amastigotes . Granulomas provide focus to the ensuing immune response , helping to contain parasite dissemination and providing the major effector site responsible for parasites elimination from the liver . Although granulomas are believed to form around infected resident liver macrophages ( Kupffer cells ) , the role of these cells in intra-granuloma antigen presentation is currently unknown . As CD8+ T cells have been shown to play an important role in hepatic resistance to L . donovani following natural infection , vaccination and during immunotherapy , we asked which cells within the granuloma microenvironment serve as targets for antigen recognition by effector CD8+ T cells . Here we provide evidence that the heavily infected mononuclear cell core of the granuloma is composed almost entirely of Kupffer cells , many having migrated from the surrounding sinusoids . Furthermore , by intra-vital 2-photon microscopy , we show that only Kupffer cells laden with intracellular amastigotes are able to form long-lasting antigen-specific interactions with CD8+ T cells within the granuloma microenvironment . These data have important implications for the understanding of how granulomas function to limit infection and may have important implications for the development of vaccines to Leishmania that are designed to induce CD8+ T cell responses . | [
"Abstract",
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"immunology/cellular",
"microbiology",
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] | 2010 | Dynamic Imaging of Experimental Leishmania donovani-Induced Hepatic Granulomas Detects Kupffer Cell-Restricted Antigen Presentation to Antigen-Specific CD8+ T Cells |
A recent drug interaction study reported that when azithromycin was administered with the combination of ivermectin and albendazole , there were modest increases in ivermectin pharmacokinetic parameters . Data from this study were reanalyzed to further explore this observation . A compartmental model was developed and 1 , 000 interaction studies were simulated to explore extreme high ivermectin values that might occur . A two-compartment pharmacokinetic model with first-order elimination and absorption was developed . The chosen final model had 7 fixed-effect parameters and 8 random-effect parameters . Because some of the modeling parameters and their variances were not distributed normally , a second mixture model was developed to further explore these data . The mixture model had two additional fixed parameters and identified two populations , A ( 55% of subjects ) , where there was no change in bioavailability , and B ( 45% of subjects ) , where ivermectin bioavailability was increased 37% . Simulations of the data using both models were similar , and showed that the highest ivermectin concentrations fell in the range of 115–201 ng/mL . This is the first pharmacokinetic model of ivermectin . It demonstrates the utility of two modeling approaches to explore drug interactions , especially where there may be population heterogeneity . The mechanism for the interaction was identified ( an increase in bioavailability in one subpopulation ) . Simulations show that the maximum ivermectin exposures that might be observed during co-administration with azithromycin are below those previously shown to be safe and well tolerated . These analyses support further study of co-administration of azithromycin with the widely used agents ivermectin and albendazole , under field conditions in disease control programs .
The operational efficiency of disease elimination programs in developing countries could be improved by integrating delivery of several interventions at local ( village and district ) levels [1]–[3] . In areas endemic for co-infection with filarial nematodes and Chlamydia trachomatis , one such integrated disease elimination strategy would be based on mass administration of a three-drug combination: ivermectin for onchocerciasis , albendazole for lymphatic filariasis and azithromycin for trachoma . Regular administration of this combination would also be predicted to reduce other infectious agents including soil transmitted nematodes and bacterial sexually transmitted diseases [4] . A recent pharmacokinetic study evaluated co-administration of azithromycin , ivermectin and albendazole [5] , and showed that mean ivermectin pharmacokinetic parameters , area under the concentration-time curve ( AUC ) and maximum concentration ( Cmax ) , were increased by 31% and 27% , respectively relative to a baseline period . The variability in this interaction was large , with two individuals having 3-fold increases in ivermectin AUC . Increased ivermectin exposures could potentially have safety implications , as high dose ivermectin animal studies and observations of human overdose have reported signs and symptoms of central nervous system ( CNS ) toxicity including emesis , mydriasis and ataxia [6] . However a recent safety study demonstrated no significant toxicity in the CNS or other body systems , with ivermectin doses up to 10 times the highest labeled dose of 200 µg/kg [7] , [8] . The purpose of this analysis was to model the ivermectin pharmacokinetic data from the recently reported interaction study [5] , to further characterize the interaction , and explore the sources of variabilities between subjects and across treatments . The model was also used to simulate the outcomes of 1000 trials , to ensure that peak ivermectin exposures seen during co-administration did not exceed those observed in the high dose safety and pharmacokinetic study [7] .
Data from a historical Phase I study with intensive sampling in healthy subjects was used to develop a population pharmacokinetic model for ivermectin [5] . All subjects provided written informed consent according to local requirements before entering the study , and the protocol and Informed Consent Form were approved by the local Institutional Review Board . This was a three-arm crossover study , where subjects were administered single-dose regimens of the following treatments in random order: ( i ) azithromycin 500 mg; ( ii ) ivermectin 200 µg/kg of total body weight rounded to the nearest 3 mg plus albendazole 400 mg; and , ( iii ) all 3 drugs administered concurrently . All doses were administered with 240 mL of water and a standardized breakfast . Prior to dosing and breakfast , subjects fasted overnight and then abstained from any further food for 4 hours after study drug administration . Study arms were separated by washout periods of 3 weeks . Full details of the study are provided in [5] . Blood samples were collected predose and at 0 . 5 , 1 , 1 . 5 , 2 , 3 , 4 , 6 , 8 , 10 , 12 , 24 , 36 , 48 , 72 , 96 , 120 , 144 , and 168 hours after drug administration during each of the study phases . Samples were collected into heparinized Vacutainers . Blood samples were centrifuged at 3000 rpm for 15 minutes and the plasma samples were collected in plain plastic tubes without anticoagulant and then stored at −80°C . Samples were shipped frozen overnight on dry ice to BAS Analytics ( West Lafayette , IN ) for sample analyses . Ivermectin is detected in the body as two metabolites ( 22 , 23-dihydroavermectin-B1a ( H2B1a ) and 22 , 23-dihydroavermectin-B1b ( H2B1b ) , and these were assayed using a validated high performance liquid chromatography system with liquid chromatography/mass spectrographic detection . The assays were linear over the ranges of 2 . 5–1000 . 0 ng/mL and 2 . 5–20 . 0 ng/mL , respectively . The precision values for both assays were <10% . In terms of accuracy , while the bias was not exceeded ( ±15% ) for H2B1b for either the high or low quality control ( QC ) samples , they were for H2B1a during long-term stability testing ( −21 . 8% at the low QC and −17 . 3% for the high QC ) ( see [5] ) . Plasma concentration-time data were analyzed using standard noncompartmental analytical software ( WinNonlin 4 . 1; Pharsight Corporation , Mountain View , CA ) , and key parameters are shown in Figure 1 . The data analysis presented here is for ivermectin data from the ivermectin plus albendazole arm ( Baseline Phase ) , and from the ivermectin , albendazole plus azithromycin arm ( Interaction Phase ) . Eighteen healthy Caucasian volunteers were enrolled in and completed this study ( 9 males and 9 females , mean [±SD] age , 39 . 4±10 . 5 years , weight 78 . 2±12 . 4 kg , ivermectin dose 15 . 5±2 . 6 mg ) . All the data from both arms of the cross-over study were fitted simultaneously . The data set contained pooled pharmacokinetic , demographic/covariate , and dosing information . Data were analyzed using nonlinear mixed-effects modeling with the NONMEM software system , Version V , Level 1 . 1 ( GloboMax LLC , Ellicott City , MD ) with the PREDPP model library and NMTRAN subroutines . Computer resources included personal computers with Intel Pentium 4 processors , Windows XP Professional operating system , the GNU Fortran Compiler , GCC-2 . 95 ( Win-32 version also known as G77; GNU Project , http://www . GNU . org/ ) . Key pharmacokinetic parameters from the modeling are described in Figure 1 . The first-order conditional estimation method with η-ε interaction ( FOCEI ) was employed for all model runs . Individual estimates of pharmacokinetic parameters were obtained using POSTHOC ( an empirical Bayesian estimation method ) . The random effect models sufficiently described the error distributions . For this analysis all interindividual errors were described by exponential error models on selected parameters ( Equation 1 ) . ( 1 ) where: Pi is the true parameter value for individual i , is the typical population value ( geometric mean ) of the parameter , ηPi are individual-specific interindividual random effects for individual i and parameter P and were assumed to be independently and identically distributed following a normal distribution with mean 0 and variance omega ( ω ) squared ( η∼N ( 0 , ω2 ) ) . The data could not support a full covariance block for the OMEGA matrix . Modeling began with the assumption of no covariance between interindividual random effects ( diagonal ω matrix ) . Later , the covariance between clearance ( CL ) and volume of distribution in the central compartment ( Vc ) was estimated . For pharmacokinetic observations in this analysis , the residual error model was described by a combined additive and proportional error model ( Equation 2 ) . ( 2 ) where: Cij is the jth measured observation ( plasma concentration ) in individual i , is the jth model predicted value ( plasma concentration ) in individual i , εpij and εaij are proportional and additive residual random errors , respectively , for individual i and measurement j and are assumed to be independently and identically normally distributed , following a normal distribution with mean 0 and variance sigma ( σ ) squared ( ε∼N ( 0 , σ2 ) ) . For each treatment arm , separate residual errors were explored . The pharmacokinetic models were evaluated for goodness of fit and were then subjected to predictive check model evaluation . For more detailed technical information on these methods , please see NONMEM user's guide [9] . After the structural pharmacokinetic model was established , known physiologic relationships were incorporated into the covariate-parameter models . For example , the change in physiologic parameters as a function of body size was both theoretically and empirically described by an allometric model ( Equation 3 ) [10] ( 3 ) where: the typical individual value of a model parameter ( TVP ) was described as a function of individual body weight ( WTi ) , normalized by a reference weight ( WTref ) , which was 70 kg . θTVP is an estimated parameter describing the typical pharmacokinetic parameter value for an individual with weight equal to the reference weight and θallo is an allometric power parameter ( which can be estimated or fixed to a value of 0 . 75 for clearances , and a value of 1 for anatomical volumes ) . Assessment of model adequacy and decisions about increasing model complexity were driven by the data and guided by goodness-of-fit criteria , including: ( i ) visual inspection of diagnostic scatter plots ( observed vs . predicted concentration , residual/weighted residual vs . predicted concentration or time , and histograms of individual random effects; ( ii ) successful convergence of the minimization routine with at least 2 significant digits in parameter estimates; ( iii ) plausibility of parameter estimates; ( iv ) precision of parameter estimates; ( v ) correlation between model parameter estimation errors <0 . 95 , and ( vi ) the Akaike Information Criterion ( AIC ) , given the minimum objective function ( OBJ ) value and number of estimated parameters [9] . The criteria for successful runs were restricted to successful convergence using FOCE with interaction , good diagnostics for the model-fit for all data of the different treatment periods , and reasonable estimates for fixed and random effect parameters . Model evaluations included comparisons of the OBJ between hierarchical models . A decrease in OBJ corresponding to a chi-square distribution with α = 0 . 01 and degrees of freedom equal to the difference in the number of estimated parameters between the two models was used as the criterion for model comparisons . Final model parameter estimates were reported with a measure of estimation uncertainty including the asymptotic standard errors ( obtained from the NONMEM $COVARIANCE step ) . A limited covariate modeling approach emphasizing parameter estimation given the available data , rather than stepwise hypothesis testing , was implemented for this population pharmacokinetic analysis . The study population contained equal numbers of males and females . As such , age , weight and gender were explored as potential covariates . First , pre-defined covariate-parameter relationships were identified based on exploratory graphics , mechanistic plausibility of prior knowledge , and then a full model was constructed , with a fixed allometric relationship of body weight on clearance and volume parameters . Interindividual variability could not be incorporated on all fixed-effects parameters to get successful FOCE runs . For residual variance , a separate residual error was assigned for each of the treatment arms . A combined additive and proportional error model was used with 4 parameters to be estimated for the residual error . Various population models were evaluated , but only two models that best described the data ( as determined by the log likelihood criterion and visual inspection ) are presented . The first modeling approach was a population model that included all subjects . Because some of the modeling parameters and their variances were clearly not normally distributed , and showed asymmetric distribution , a mixture model was developed . A second modeling approach was a population mixture model as it met our criteria for model adequacy and provided supporting evidence of the dichotomy of the observed individual data . Each subpopulation would have an associated submodel with different fixed or random effects . This model was adopted to accommodate the fact that only some of the individuals exhibited a pronounced increase in ivermectin bioavailability during the interaction arm of the study . It was preferred over a population model with and without outlier individuals , as it gave a better fit to the data as measured by change in OBJ , and met our criteria for a successful run in terms of a complete successful convergence with reasonable estimate for precision for both fixed and random effects . Model development was guided by various goodness-of-fit criteria , including diagnostic scatter plots . Checking of the individual fits was also employed as part of judging the model performance for each patient . The final model and parameter estimates were then investigated with the predictive check method . This method was similar to the previously described posterior predictive check , but assumes that parameter uncertainty is negligible , relative to interindividual and residual variance [11] . The basic premise is that a model and parameters derived from an observed data set should produce simulated data that are similar to the original observed data . The predictive check is a useful adjunct to typical diagnostic plots , in that the predictive check provides information about the performance of random-effects parameter estimates , whereas typical diagnostic plots are primarily informative about the fixed-effects parameter estimates . The predictive check model evaluation step was performed by using the final model and its parameter estimates to simulate data under the same experimental design of the original data . One thousand Monte Carlo simulation replicates of the original data set were generated using the final non-mixture and mixture population pharmacokinetic models . Distributions of Cmax across all data simulations were compared with Cmax distribution in the observed data set . The simulated data from each of the 1000 virtual trials ( 18000 subjects for each treatment period ) were assembled , and the similarity between the actual observed data and simulated data was examined by comparing the 95% predictions intervals of the simulated data with the original observed data .
Ivermectin concentration-time data were best described by a two-compartment pharmacokinetic model with first-order elimination and absorption ( Figure 3 ) . Covariance between CL and Vc elements of the OMEGA matrix was incorporated in the model . The use of different residual variance models stratified by the treatment with and without shared additive components was explored and incorporated into the structural model . Inclusion of age or gender as covariates did not contribute additional information for explaining pharmacokinetic variability based on OBJ differences in hierarchical models , model convergence , as well as diagnostic graphics . Therefore , none of these covariates was included as a covariate in the final population pharmacokinetic model . Importantly , the available data for this investigation contained a relatively small number of subjects and a limited age range , and so formal hypothesis ( significance ) testing for covariate effects was not considered . The final non-mixture model had 7 fixed-effect parameters and 8 random-effect parameters as shown in Table 1 . Population pharmacokinetic parameters ( CL , Vc , Q , Vp; see Figure 1 ) were standardized to a 70 kg person using the allometric size model [10] . In parametric nonlinear mixed effects modeling , the distribution of ηs is assumed to be normal ( mean = 0 , variance = ω2 ) . With each model developed , we checked the distribution of ηs , and their mean values . The η distribution indicated a clear violation of the normality assumption . It was necessary to modify the original model to improve η distribution diagnostics . A mixture modeling approach was considered as the distribution of some of the pharmacokinetic parameters and inter-individual variabilities indicated a lack of homogeneity . The final mixture model had 9 fixed-effect parameters and 8 random-effect parameters as shown in Table 2 . Goodness-of-fit plots for the final model are shown in Figure 4 . The mixture model differed from the non-mixture model in only two parameters: one defining the difference between the two subpopulation in terms of bioavailability , the second defining the partition of the population between the two subpopulations . Using this approach , inter-individual variability distribution was modeled as two subpopulations ( A and B ) . The unknown mixture distribution was estimated at an individual level . The estimate for each subpopulation included different fixed effects parameters , different variance parameters , estimation of fraction of individuals in each subpopulation , and each individual was assigned to the most likely subpopulation . The proportion of subjects in subpopulations A and B was estimated as 55% and 45% , respectively . Both the population and individual predictions adequately described the AUC profiles for each subject ( Figure 5 ) , as displayed by the baseline and interaction phases for subpopulation B . A similar fit of individual data was observed for Subpopulation A ( data not shown ) . Figure 6 displays median , 97 . 5th , and 2 . 5th quantiles of the simulated data as lines with the observed data plotted as individual points . Less than 5% of the observed data were outside these 95% prediction intervals . No biased pattern or any tendency for over- or underestimation was noted for the different treatment periods , or for the two subpopulations . This finding gives confidence in the model performance in predicting the expected ivermectin exposures under different circumstances . Simulated maximum concentrations for each individual's Cmax values were summarized across 1000 simulation replicates of the original population pharmacokinetic database and plotted as box plots ( Figure 7 ) . The upper panel shows box plots of the observed ivermectin Cmax for baseline and interaction periods for all subjects , and for the two subpopulations . The lower panel shows box plots for ivermectin Cmax from 1000 simulated trials for the non-mixture model ( all subjects ) , and the mixture model ( subpopulations A and B ) . The mixture model pattern predictions for the two subpopulations were very consistent with the observed data [5] . Extreme values were: non-mixture model: 201 . 2 ng/mL; mixture model subpopulation A: 115 . 3 ng/mL; B: 175 . 5 ng/mL .
There are a number of interesting findings from this analysis of data from an interaction study of ivermectin and azithromycin . This is the first published population model of ivermectin pharmacokinetics . It demonstrates the utility of population mixture modeling as an approach to explore drug interactions , especially where there may be population heterogeneity . The mechanism for the interaction was identified ( an increase in bioavailability in one subpopulation ) . The model was used to simulate multiple clinical trials , to identify the maximum exposures that might be observed during co-administration , which permits comparison with previously published safety and pharmacokinetic data . Ivermectin has been approved for use in humans for 2 decades , yet relatively limited pharmacokinetic data have been published . Recent studies using modern assay methods have characterized its pharmacokinetics using noncompartmental methods in the context of drug combination studies for treatment of onchocerciasis and lymphatic filariasis [12]–[14] , or in high doses for treatment of head lice [7] . The calculated model parameters are in close agreement with those determined using noncompartmental methods [5] . A two compartment model is consistent with the disposition of ivermectin in man and other species , with a high volume of distribution into a peripheral compartment [15] . Ivermectin is metabolized extensively in the liver via cytochrome P450 isozyme ( CYP ) 3A4 [16] . It is both a substrate for the transporter P-glycoprotein ( Pgp ) [17] , [18] , as well as a moderately potent Pgp inhibitor at concentrations consistent with clinical exposures in the present study ( IC50 0 . 18–0 . 4 µM; [19] , [20] ) . The variability of the magnitude of change in ivermectin pharmacokinetics observed in the interaction phase [5] complicated the interpretation of the presence or absence of a drug interaction , as the response was very inconsistent among individuals . One of the objectives of this analysis was to explore how nonlinear mixed-effects modeling could be used to analyze such heterogeneous and highly variable experimental data from a relatively small number of subjects , with intensive pharmacokinetic sampling . The initial non-mixture model provided an adequate description of ivermectin pharmacokinetic data , however interindividual variability was not homogeneous and could not be explained by the available covariates . A mixture model was able to resolve this , and provided an explanation for the observed differences in bioavailability seen in the clinical study . Mixture modeling assumes two or more subpopulations exist , rather than a single homogeneous one [21] , and the final model has two additional fixed parameters , one relating to subpopulation differences in ivermectin bioavailability , and the other defining the two subpopulations . The final mixture model provided a good description of ivermectin data from both treatment periods . Goodness-of-fit criteria revealed that the final model was consistent with the observed data and that no systematic bias remained . The data points ( Figure 4 ) are scattered closely and randomly around the line of identity , and the homogenous and random distributions of weighted residuals indicate the error model was suitable for describing the variance of the data . The model evaluation results provided evidence that both the fixed-effects and random-effects components of the final model were reflective of the observed data as well . The fact that less than 5% of the data were located outside the 2 . 5-97 . 5th quantile range suggests that the model accurately describes the central tendency and the variability of the data for the two subpopulations and for the two treatment periods , despite the large number of parameters and the low number of patients who participated in the study . The predictive check shows there is no bias at any phase of the pharmacokinetic profile , which makes the model useful in predicting ivermectin blood concentrations , when given alone or co-administered with azithromycin . Typically , a mixture modeling approach would not be considered at the outset of a population pharmacokinetic analysis . Because of the unexplained remaining variability ( see above ) , in the present analysis , the following decision rules were used in the evaluation of the mixture model: ( i ) The Estimation step and Covariance step terminated successfully; ( ii ) 95% CI for Mixture partition did not include 0 nor 1; and ( iii ) the change in the OBJ between mixture and non-mixture models was >5 . 99 ( χ2; p<0 . 05 , 2df ) . In the present analysis , the difference was 19 . 8 . The mixture model identified the interaction between azithromycin and ivermectin to be due to changes in bioavailability in Subpopulation B . Their mean estimate of bioavailability ( F ) was 1 . 37 relative to baseline , whereas F was unchanged for Subpopulation A ( 0 . 97 ) . Inspection of noncompartmental data for Subpopulation B were consistent , showing higher Cmax and earlier Tmax values ( Cmax A: 54 . 3 ng . h/mL; B: 67 . 8 ng . h/mL; Tmax A: 4 . 1 h; B: 3 . 4 h ) . There were no differences in apparent clearance or volume of distribution . However the mechanism for the increase in bioavailability is unclear . Azithromycin , like ivermectin , is a substrate for Pgp , however it has minimal inhibitory effects on this transporter in vitro [20] . Although ivermectin is extensively metabolized by CYP3A4 [16] , azithromycin has no inhibitory activity against this enzyme [22] . There are no other plausible metabolic or transporter mechanisms that could explain an interaction , and no clinical covariates were identified that characterized either subpopulation . In addition , mean pharmacokinetic parameters of ivermectin were similar in both subpopulations in the baseline phase ( mean AUC A: 1019; B: 805 ng . h/mL; Cmax A: 52; B: 45 ng/mL; Tmax A: 5 . 3; B: 4 . 8h ) . The model was used to simulate the range of peak ivermectin concentrations that might be encountered if azithromycin and ivermectin were co-administered . These simulated data were then compared with the Cmax data reported in the high-dose ivermectin safety study [7] . The median simulated Cmax data ( 46 . 0 , 34 . 1 and 40 . 3 ng/mL for non-mixture model , mixture models A and B respectively ) were approximately 5–7-fold lower than the 261 ng/mL value reported by Guzzo et al [7] . Indeed , the most extreme individual simulated values ( 201 . 2 , 115 . 3 and 175 . 5 ng/mL for non-mixture model , mixture models A and B respectively ) were still lower than the mean value reported in the high-dose study [7] . These data give a high level of confidence that peak exposures that are predicted to occur if ivermectin and azithromycin were co-administered would never exceed mean values seen under high dose conditions [7] , and which in this study were safe and well tolerated . In the Amsden et al interaction study [5] , ivermectin was dosed with food ( a high-fat breakfast ) . Food has been shown to increase the bioavailability of ivermectin over 2-fold [7] . Because dosing of patients in Africa is unlikely to be with high fat meals , extreme peak ivermectin concentrations would be half of those reported in the simulation . Interestingly , simulations from both the mixture model and the non-mixture model had generally similar predictions of ivermectin exposures ( average estimates and variability ) . Both models confirmed that the maximum concentration achieved in the interaction phase would not exceed 201 ng/mL ( Figure 7 ) . In spite of adding two parameters to the non-mixture model; the final parameter estimates for both models were very similar ( Tables 1 and 2 ) . The inflation of variability and projections of extreme values for both sets of simulations is a consequence of using 1000 replicates , where the chances of sampling from the very extreme values of random error distributions are more probable . However predicting extreme high values , even if they are very rare , is very useful from a safety perspective , and provide a “worst case” scenario of any extreme high exposures that might be encountered in a clinical setting/trial during co-administration . There are several important caveats to this analysis . The data collected from the drug interaction study was not intended for population analysis , and a larger data set would have been desirable . The use of a mixture model could be criticized on the basis that random variations in the data could be ascribed post hoc to population differences . Indeed , although the mixture model identified two populations on the basis of different effects on bioavailability , it is unclear mechanistically what this difference might be due to . Finally , modeling and simulation can advise but cannot supplant clinical data . The findings from this study should be confirmed in further clinical or pharmacokinetic studies . In conclusion , this analysis demonstrates the utility of a population model approach to analyze drug interaction data . The mechanism for the interaction was identified ( an increase in bioavailability in one subpopulation ) . The model was also used to simulate multiple clinical trials , to identify the maximum exposures that might be observed during co-administration , and provides confidence that the peak ivermectin exposures would never exceed mean exposures that have previously been shown to be safe and well tolerated . | This paper describes the use of a modeling and simulation approach to explore a reported pharmacokinetic interaction between two drugs ( ivermectin and azithromycin ) , which along with albendazole , are being developed for combination use in neglected tropical diseases . This approach is complementary to more traditional pharmacokinetic and safety studies that need to be conducted to support combined use of different health interventions . A mathematical model of ivermectin pharmacokinetics was created and used to simulate multiple trials , and the probability of certain outcomes ( very high peak blood ivermectin levels when given in combination ) was determined . All simulated peak blood levels were within ranges known to be safe and well tolerated . Additional field studies are needed to confirm these findings . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"mathematics/statistics",
"pharmacology/drug",
"interactions"
] | 2008 | The Effect of Azithromycin on Ivermectin Pharmacokinetics—A Population Pharmacokinetic Model Analysis |
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