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Since its first detection in the Caribbean in late 2013 , chikungunya virus ( CHIKV ) has affected 51 countries in the Americas . The CHIKV epidemic in the Americas was caused by the CHIKV-Asian genotype . In August 2014 , local transmission of the CHIKV-Asian genotype was detected in the Brazilian Amazon region . However , a distinct lineage , the CHIKV-East-Central-South-America ( ECSA ) -genotype , was detected nearly simultaneously in Feira de Santana , Bahia state , northeast Brazil . The genomic diversity and the dynamics of CHIKV in the Brazilian Amazon region remains poorly understood despite its importance to better understand the epidemiological spread and public health impact of CHIKV in the country . We report a large CHIKV outbreak ( 5 , 928 notified cases between August 2014 and August 2018 ) in Boa vista municipality , capital city of Roraima’s state , located in the Brazilian Amazon region . We generated 20 novel CHIKV-ECSA genomes from the Brazilian Amazon region using MinION portable genome sequencing . Phylogenetic analyses revealed that despite an early introduction of the Asian genotype in 2015 in Roraima , the large CHIKV outbreak in 2017 in Boa Vista was caused by an ECSA-lineage most likely introduced from northeastern Brazil . Epidemiological analyses suggest a basic reproductive number of R0 of 1 . 66 , which translates in an estimated 39 ( 95% CI: 36 to 45 ) % of Roraima’s population infected with CHIKV-ECSA . Finally , we find a strong association between Google search activity and the local laboratory-confirmed CHIKV cases in Roraima . This study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region . Our data reveal a large CHIKV-ECSA outbreak in Boa Vista , limited potential for future CHIKV outbreaks , and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region .
In August 2014 , local transmission of chikungunya virus ( CHIKV ) was detected in Brazil for the first time , with cases being reported nearly simultaneously in Oiapoque ( Amapá state , north Brazil ) and Feira de Santana ( Bahia state , northeast Brazil ) , two municipalities separated by >2000 km distance . Genetic analysis confirmed the co-circulation of distinct virus lineages in Brazil: the Asian genotype ( CHIKV-Asian ) was introduced to Oiapoque possibly from neighbouring French Guiana , while the East-Central-South-African genotype ( CHIKV-ECSA ) was introduced to Feira de Santana from a traveller returning from Angola [1] . Since 2014 and until the end of September 2018 , a total of 697 , 564 CHIKV cases have been notified in Brazil ( including 94 , 672 laboratory-confirmed cases ) . This is the largest number recorded in any of the 51 countries or territories reporting local CHIKV transmission in the Americas [2] . The virus has been circulating in the Americas since 2013 where approximately 260 million people live in areas at-risk of transmission [2–4] . Similar to the recent Zika virus epidemic [5] , the rapid spread of CHIKV in the Americas , including in Brazil , results from several factors , including the establishment and abundance of competent Aedes spp . vectors , lack of population immunity , poor housing quality , and increased mobility of vectors and humans between regions reporting current presence of the virus [6 , 7] . Chikungunya virus is an enveloped , non-segmented , single-stranded positive polarity RNA alphavirus that is a member of the Togaviridae family and is transmitted predominately by the Aedes aegypti and Aedes albopictus vectors , which are widespread in Brazil [8] . There are four main genotypes: ( i ) the West African genotype is maintained in an enzootic cycle in Africa , ( ii ) the Asian genotype , which is endemic in Asia , ( iii ) the East-Central-South-African genotype , endemic to Africa , and ( iv ) the Indian Ocean Lineage ( IOL ) genotype , an epidemic lineage that emerged from the ECSA genotype around 2004 and swept through the Indian Ocean region causing a series of explosive outbreaks [9] . The first symptoms of CHIKV infection are a rapid increase in temperature ( >38 . 9°C ) , followed by severe , often debilitating polyarthralgia . Serological data from La Reunion , Philippines and the Indian Ocean island of Mayotte suggest that 75–97% of persons infected with CHIKV develop symptomatic infections [10] . Seroprevalence data from Brazil suggests that 45 . 7 to 57 . 1% Riachão do Jacuípe and of Feira de Santana , both located in Bahia state , were exposed to CHIKV in 2015 , with a total of 32 . 7% to 41 . 2% of the population reporting symptoms [11] . Throughout Asia and the Americas , chikungunya virus outbreaks have been associated with unique clinical features [12] , including long-lasting symptoms [13] , and high mortality resulting from complications associated with CHIKV infection [14 , 15] . In Brazil , a striking proportion of 68 . 1 to 75% of the population with positive serological results reporting symptoms contracted a chronic form of the disease [13 , 16] . However , the epidemiological features , genomic diversity , and transmission dynamics of recent CHIKV outbreaks in this country remain poorly understood . Inferences that are based only on clinical-epidemiological notifications are complicated by underreporting of cases by the national reporting system [17] , mostly due to the co-circulation and co-infection with viruses that cause overlapping symptoms , such as Zika and dengue viruses [18–20] . Moreover , CHIKV serological tests may cross-react with other alphaviruses , such as Mayaro virus , that circulate in the north and centre-west regions of Brazil [21 , 22] . In this context , it is challenging to use only clinical-epidemiological and serological data to evaluate the true extent of the disease . Moreover , accurate incidence data is critical to forecast and provide prediction of the course of epidemics [23] . Until the end of 2016 , 83 . 3% of the cases in Brazil were reported in northeast region of the country [24] . However , in 2017 , Roraima state , located in the Amazon basin in the north of Brazil , reported its first large CHIKV outbreak . Roraima is the northernmost state of Brazil , lies in the Amazon basin , borders Venezuela and French Guiana to the north , and Amazonas and Pará states to the south , and its equatorial climate favours year round transmission of mosquito-borne viruses [25] . Within Brazil’s northern states , Roraima has been implicated as a stepping-stone to virus introductions from other Latin American regions , such as dengue [26] , and yellow fever virus in the past [27] . Moreover , the Amazon region has recently been highlighted as a region with high transmission potential of vector-borne diseases [4] and , more generally , a region with high potential for virus zoonoses and emergence [28] . Due to its connectivity and potential impact on global epidemiology of vector-borne and zoonotic virus from the Amazon basin , it is important to improve genomic pathogen surveillance in Roraima . By August 2018 , the public health laboratory of Boa Vista ( capital city of Roraima state ) had reported 5 , 928 CHIKV cases , 3 , 795 of which were laboratory-confirmed . Here we a use combination of on-site portable virus genome sequencing , and epidemiological analysis of case count and web search data to describe the circulation , genetic diversity , epidemic potential and attack rates of a large CHIKV outbreak in Boa Vista .
Roraima is the northernmost of Brazil’s 27 federal units ( Fig 1A ) and has an estimated population of 450 , 479 , of whom 284 , 313 live in the capital city of Boa Vista ( ibge . gov . br/ ) . Despite being Brazil’s least populated federal unit , Roraima is one of the best-connected Brazilian states in the Amazon basin [29] . Within Brazil , Roraima is connected to Amazonas state in the south via the road BR-174 . This road also connects Roraima’s capital city , Boa Vista , to the states of Bolivar and Amazonas in Venezuela in the north . Further , the road BR-401 links Boa Vista to Guyana in the east . There are four daily flights connecting Boa Vista with Brasília , capital of Brazil , as well as six weekly flights to Manaus , the capital city of Amazonas state and the biggest city in the north of the country , with connecting daily nonstop flights to all other Brazilian states/regions and international destinations , including important international airport hubs in Panamá City and Miami , USA . There are also less-commonly used seasonal fluvial networks that connect Boa Vista and Manaus via the Amazonas river . The Roraima State Central Laboratory ( LACEN-RR ) is responsible for the differential diagnosis of suspected arbovirus cases presenting to Roraima’s public health units . Between Jan 2014 and September 2018 , LACEN-RR notified 5 , 928 CHIKV cases in Boa Vista alone , 3 , 795 of these laboratory-confirmed , to the National Reportable Disease Information System ( SINAN ) . Case count time series are available from Github ( https://github . com/arbospread/chik-amazon ) . We follow the Brazilian Ministry of Health’s guidelines and define a notified CHIKV case as a suspected case characterized by ( i ) acute onset of fever >38 . 5°C , ( ii ) severe arthralgia and/or arthritis not explained by other medical conditions , and ( iii ) residing or having visited epidemic areas within 15 days before onset of symptoms . A laboratory-confirmed case is a suspected case confirmed by laboratory methods such as ( i ) virus isolation in cell culture , ( ii ) detection of viral RNA , ( iii ) detection of virus-specific IgM antibodies in a single serum sample collected in the acute or convalescent stage of infection; or ( iv ) a four-fold rise of IgG titres in samples collected during the acute phase , in comparison with a sample collected in the convalescent period . Residual anonymized clinical samples were processed in accordance with the terms of Resolution 510/2016 of CONEP ( National Ethical Committee for Research , Brazilian Ministry of Health ) , under the auspices of the ZiBRA project ( http://www . zibraproject . org/ ) . The project was approved by the Pan American Health Organization Ethics Review Committee ( PAHOERC ) no PAHO-2016-08-0029 . Residual anonymized clinical diagnostic samples were sent to Instituto Leônidas e Maria Deane , FIOCRUZ Manaus , Amazonas , Brazil , for molecular diagnostics as part of the ZiBRA-2 project . Total RNA extraction was performed with QIAmp Viral RNA Mini kit ( Qiagen ) , following manufacturer’s recommendations . Samples were first tested using a multiplexed qRT-PCR protocol against CHIKV , dengue virus ( DENV1-4 ) , yellow fever virus , Zika virus , Oropouche virus and Mayaro virus [30] . All qRT-PCR results were corroborated using a second protocol [31]; comparable Ct values were obtained with the two protocols . CHIKV positive samples tested negative for all other arboviruses tested . Samples were selected for sequencing based on Ct-value <30 ( to maximize genome coverage of clinical samples by nanopore sequencing [32] ) , and based on the availability of epidemiological metadata , such as date of onset of symptoms , date of sample collection , gender , municipality of residence , and symptoms ( Table 1 ) . We included a total of 13 samples from Roraima state plus 5 additional samples from patients visiting the LACEN-Amazonas in Manaus . Sequencing was attempted on samples with Ct-value ≤30 at Instituto Leônidas e Maria Deane , FIOCRUZ Manaus . We used an Oxford Nanopore MinION device with protocol chemistry R9 . 4 , as previously described [33] . Sequencing statistics can be found in S1 Table . In brief , we employed a protocol with cDNA synthesis using random primers followed by strain-specific multiplex PCR [33] . Extracted RNA was converted to cDNA using the Protoscript II First Strand cDNA synthesis Kit ( New England Biolabs , Hitchin , UK ) and random hexamer priming . CHIKV genome amplification by multiplex PCR was attempted using the CHIKAsianECSA primer scheme and 35 cycles of PCR using Q5 High-Fidelity DNA polymerase ( NEB ) as described in [33] . PCR products were cleaned up using AmpureXP purification beads ( Beckman Coulter , High Wycombe , UK ) and quantified using fluorimetry with the Qubit dsDNA High Sensitivity assay on the Qubit 3 . 0 instrument ( Life Technologies ) . PCR products for samples yielding sufficient material were barcoded and pooled in an equimolar fashion using the Native Barcoding Kit ( Oxford Nanopore Technologies , Oxford , UK ) . Sequencing libraries were generated from the barcoded products using the Genomic DNA Sequencing Kit SQK-MAP007/SQK-LSK108 ( Oxford Nanopore Technologies ) . Libraries were loaded onto a R9/R9 . 4 flow cell and sequencing data were collected for up to 48hr . Consensus genome sequences were produced by alignment of two-direction reads to a CHIKV virus reference genome ( GenBank Accession number: N11602 ) as previously described in [33] . Positions with≥20× genome coverage were used to produce consensus alleles , while regions with lower coverage , and those in primer-binding regions were masked with N characters . Validation of the sequencing protocol was previously performed in [33] . Genotyping was first conducted using the phylogenetic arbovirus subtyping tool available at http://www . krisp . org . za/tools . php . Complete and near complete sequences were retrieved from GenBank on June 2017 [34] . Two complete or near-complete CHIKV genome datasets were generated . Dataset 1 included ECSA-PreAm ( ECSA sampled outside the Americas ) and ECSA-Br ( ECSA sequences sampled in the Americas ) sequences . This dataset contained 36 complete genomes from the ECSA genotype , including 7 from East and Central Africa ( HM045823 from Angola 1962; HM045784 from Central African Republic 1984; HM045812 from Uganda 1982; KY038947 from Central African Republic 1983; HM045793 from Central African Republic 1986; HM045822 from Central African Republic 1978; and KY038946 from Central African Republic 1975 ) . Dataset 1 also included 29 sequences from Brazil , including the new 18 genomes reported here from the ECSA lineage and 3 genomes from the outbreak caused by the ECSA lineage in June 2016 in Maceió , Alagoas states , northeast Brazil ( Fig 1A ) [35] . Dataset 2 ( ECSA-Br ) included only the 29 Brazilian genome sequences . Using a robust nonparametric test [36] , no evidence of recombination was found in both datasets . Maximum likelihood ( ML ) phylogenetic analyses were performed for each dataset using RAxML v8 [37] . We used a GTR nucleotide substitution model with 4 gamma categories ( GTR+4Γ ) . In order to investigate the evolutionary temporal signal in each dataset , we regressed root-to-tip genetic distances against sample collection dates using TempEst [38] . For both datasets we obtained a strong linear correlation ( dataset 1: r2 = 0 . 93; dataset 2: r2 = 0 . 84 ) suggesting these alignments contain sufficient temporal information to justify a molecular clock approach . However , for dataset 1 , the Angola/M2022/1962 strain was positioned substantially above the regression line . Previous investigations have suggested this strain may have been the result of contamination or high passage in cell culture [9] , so this sequence was removed from subsequent analyses . To estimate time-calibrated phylogenies we used the BEAST v . 1 . 10 . 1 software package [39] . To infer historical trends in effective population size from the genealogy we used several different coalescent models . Because preliminary analysis indicated oscillations in epidemic size through time ( as also expected from national case report data ) , we used three flexible , non-parametric models: a ) the standard Bayesian skyline plot ( BSP; 10 groups ) [40] , b ) the Bayesian skyride plot [41] , and c ) the Bayesian skygrid model [42] , with 45 grid points equally spaced between the estimated TMRCA of the CHIKV-ECSA genotype in Brazil and the date of the earliest available isolate , collected in 18 March 2017 [42] . For comparison , we also used a constant population size coalescent model . We tested two molecular clock models: a ) the strict molecular clock model , which assumes a single rate across all phylogeny branches , and b ) the more flexible uncorrelated relaxed molecular clock model with a lognormal rate distribution ( UCLN ) [43] . Because the marginal posterior distribution of the coefficient of variation of the UCLN model did not exclude zero ( most likely due to the small alignment size ) , we used a strict molecular model in all analyses . For each coalescent model , Markov Chain Monte Carlo analyses were run in duplicate for 10 million steps using a ML starting tree , and the GTR+4Γ codon partition ( CP ) 1+2 , 3 model [43] . The epidemic basic reproductive number ( R0 ) was estimated from monthly confirmed cases , as previously described [32 , 44] . Because ( i ) the Asian genotype was circulating in the north region of Brazil since 2014 [1] , and ( ii ) we observed a relatively small number of cases both in the notified and confirmed time series , we assume cases from June 2014 and December 2016 did not represent autochthonous transmission of CHIVK-ECSA . We assume a mean generation time of 14 days , as previously reported elsewhere for an outbreak caused by an Indian Ocean lineage ( IOL ) , a subclade of the ECSA genotype [45] . We report R0 estimates for different values of the generation time ( g ) parameter , along with corresponding estimates of the epidemic exponential growth rate , per month ( r ) . Available in near-real time , disease-related Internet search activity has been shown to track disease activity ( a ) in seasonal mosquito-borne disease outbreaks , such as those caused by dengue [46] , and ( b ) in unexpected and emerging mosquito-borne disease outbreaks such as the 2015–2016 Latin American Zika outbreak [47] . Here , we investigated whether we could find a meaningful relationship between Internet search activity and the local chikungunya outbreak in Roraima . Indeed , novel Internet-based data sources have the potential to complement traditional surveillance by capturing early increases in disease-related search activity that may signal an increase in the public’s perception of a given public health threat and may additionally capture underlying increases in disease activity . Internet searches may be particularly important and indicative of changes in disease transmission early during an outbreak , when ongoing information on the virus transmission is obfuscated by a lack of medical surveillance . In addition , Internet search trends may also help track disease activity in populations that may not seek formal medical care . We used the Google Trends ( GT ) tool [46 , 47] to compile the monthly fraction of online searches for the term “Chikungunya” , that originated from Boa Vista municipality ( Roraima state ) , between January 2014 and July 2018 . For comparison , GT search activity for the term “Chikungunya” was collected for the same time period for Manaus municipality ( Amazonas state ) . The synchronicity of GT time series and notified and confirmed case counts from Boa Vista and Manaus was assessed using the Spearman’s rank correlation test in the R software [48] .
Although most CHIKV notified cases in Brazil were reported in 2016 ( Fig 1 ) , in Roraima , the majority of notified and confirmed cases in Roraima state were reported in 2017 ( 5 , 027 notified cases and 3 , 720 laboratory-confirmed infections ) . The number of cases in Roraima started increasing exponentially in January 2017 , and the outbreak peaked in July 2017 . We selected 15 RT-qPCR+ virus isolates from autochthonous cases in Roraima state ( 11 from Boa Vista , 1 from Bonfim , and 1 from Iracema municipalities ) ( Table 1 ) with a cycle threshold ( Ct ) ≤30 ( mean 20 . 3 , range 13 . 7–27 . 41 ) . We included two isolates from two infected travellers returning to Roraima in December 2014 , and an additional five isolates from Amazonas state ( all from Manaus municipality ) , sampled between July 2015 and March 2017 . In less than 48 hours genome sequence data was obtained for all selected isolates and in less than 72 hours preliminary results were shared with local public health officials and the Brazilian Ministry of Health . A mean genome coverage of 86% ( 20x ) per base pair was obtained for the sequenced data; mean coverage increased to 90% when focusing on samples with Ct<26 ( Fig 2A ) . Coverage of individual sequences and epidemiological information for each sequenced isolate can be found in Table 1 . Identification of virus genotypes was conducted using phylogenetic analysis of full-length genome datasets ( manual classification ) and using an online phylogenetic analysis tool ( automated classification ) . Both approaches identified the ECSA genotype as the dominant genotype circulating in both Roraima and Manaus between 2015 and 2017 . However , two cases from late 2014 returning from Venezuela to Roraima ( AMA294 and AMA295 ) were classified as Asian genotype , the dominant lineage circulating in Latin America . ML and Bayesian phylogenetic analyses reveal that the ECSA sequences from Brazil form a single well-supported clade ( bootstrap support = 100 ) , hereafter named as ECSA-Br clade; which contains strong temporal signal ( r2 = 0 . 84 ) as measured by a regression of genetic divergence against sampling dates ( Figs 2B and 3 ) . Thus we estimated the evolutionary time-scale of the ECSA-Br lineage using several well-established molecular clock coalescent methods . Our substitution rate estimates indicate that the ECSA-Br lineage is evolving at 7 . 15 x 10−4 substitutions per site per year ( s/s/y; 95% Bayesian credible interval: 5 . 04–9 . 55 x 10−4 ) . This estimated rate is higher than that estimated for endemic lineages , and is similar to the evolutionary rates estimated for the epidemic lineage circulating in the Indian Ocean region ( Fig 2C ) . A closer inspection of amino acid mutations indicate that the ECSA-Br strains lack both the A226V ( E1 protein ) and the L210Q ( E2 protein ) mutations that has been reported to increase virus transmissibility and persistence in Ae . albopictus populations in the Indian Ocean [49] . This is consistent with the establishment of the ECSA genotype in Brazil following the introduction of a single strain to the Americas [1] . The two isolates collected in late 2014 in Roraima cluster together and fall as expected within the diversity of other Asian genotype sequences from the Americas . Our phylogenetic reconstruction suggests at least five separate introductions of the Asian genotype strain Brazil ( S1 Fig ) , in contrast to a single introduction of the ECSA genotype followed by onward transmission . Moreover , all 13 ECSA isolates sampled in Roraima ( node C ) cluster together with maximum phylogenetic support ( bootstrap support = 100; posterior probability = 1 . 00 ) ( Fig 3 ) . We consistently estimate the date of the most recent common ancestor of ECSA-Br Roraima clade to be mid-July 2016 ( 95% BCI: late March to late October 2016 ) ( Fig 3 ) ; similar dating estimates under different coalescent models ( S2 Fig ) . In contrast to the Roraima strains , sequences from Manaus were found to be interspersed with isolates from Bahia and Pernambuco ( Fig 3 ) , indicating separate introductions of the CHIKV-ECSA lineage , some in early 2015 ( node B ) , possibly from the northeast region of Brazil . Interestingly , according to travel history reports , the first autochthonous transmission of CHIKV in Manaus was linked to an index patient who reported spending holidays in Feira de Santana ( Bahia state ) in early 2015 , during a period when this city was experiencing a large CHIKV outbreak [5] . The date of node A was estimated to be around mid-July 2014 ( 95% BCI: early Jul–late Aug 2014 ) , shortly after the arrival of the presumed index case in Feira de Santana , Bahia [5] . This is in line with a single introduction to Bahia ( node A ) , followed by subsequent waves of transmission across the northeast and southeast regions of Brazil [5 , 50 , 51] . Our demographic reconstructions indicate that the outbreak in Roraima 2017 probably represents the third epidemic wave spreading across Brazil ( S3 Fig ) . Next , we used notified case counts to estimate the basic reproductive number , R0 , of the epidemic . R0 is the average number of secondary cases caused by an infected individual and can be estimated from epidemic growth rates during its early exponential phase [44] . We find that R0 ≈ 1 . 66 ( 95% CI: 1 . 51–1 . 83 ) , in line with previous reports from other settings [52–54] . A sensitivity analysis considering different exponential growth phase periods resulted in a lower bound for R0 of around 1 . 23 ( S4 Fig ) . To gain insights into the possible magnitude of the outbreak and local surveillance capacity we used the equilibrium end state of a simple susceptible-infected-recovered ( SIR ) model: N = S + I + R , S ~ 1/R0 , I ~ 0 , with N being the total population size of Roraima . Using this simple mathematical approach , we obtain an attack rate ( R ) of 0 . 39 ( 95% CI: 0 . 36–0 . 45 ) , slightly lower than elsewhere in Brazil [13 , 16] . This corresponds to an estimated 110 , 882 ( 95% CI: 102 , 352–127 , 940 ) infected individuals , and a case detection rate of 5 . 34% ( 95% CI: 4 . 63–5 . 79 ) . This implies that approximately 1 case was notified for every 19 infections . If we assume 32 . 7–41 . 2% of the estimated infections are symptomatic , as previously reported in Bahia and Sergipe [55] , then we estimate that the local observation success of symptomatic cases was between 12 . 8–16 . 1% . However , if we assume that 75–97% of people infected with CHIKV will develop symptomatic infections , as reported for the Indian Ocean lineage [11 , 56 , 57] , then the chances of a reported a symptomatic CHIKV case decrease to 5–7% [10] . Case reports suggest that the beginning of the exponential phase of the outbreak was in December 2016 ( S4 Fig ) , while genetic data suggests that the outbreak clade emerged around July 2016 . However , between August 2014 and June 2016 , 612 CHIKV notified cases and 40 confirmed cases were reported by the LACEN-RR . It is therefore likely that prior to Jan 2017 , low but non-neglectable transmission of the Asian genotype occurred in Roraima . We investigated the public’s awareness of the chikungunya outbreak by retrospectively monitoring Google searches of the search term “chikungunya” in Roraima state from January 2014 to July 2018 ( Fig 4 ) . As a comparison , we performed a similar search focusing on the neighbouring state of Amazonas . We found that web search activity and CHIKV cases counts in Roraima are highly correlated ( notified cases: r = 0 . 89; confirmed cases: r = 0 . 92 , Fig 4D–4E ) . Additionally , the timing of the peak of Google searches corresponds to that of notified and confirmed cases with a peak in July 2017 ( Fig 4A and 4C , Fig 4B and 4F ) . It is important to note that web search activity was available weeks or months before the final number of confirmed ( and suspected ) cases were made publicly available . This fact highlights the potential utility of monitoring disease-related searches during the outbreak . Interestingly , we find some web-search activity in Roraima before June 2016 , particularly in September 2014 , March 2015 and March 2016 ( Fig 4F ) . These patterns are distinct to those in the Amazonas neighbouring state ( notified cases: r = 0 . 65; confirmed cases: r = 0 . 15 ) , which shows an early peak in November 2014 , soon after the estimated age of node B ( Fig 3B ) , followed by a peak in February 2016 and another in March 2017 ( Fig 4C ) . These multiple peaks in internet search queries are consistent with the timing of at least 3 introductions detected in our phylogenetic analyses ( Fig 3B ) , each possibly resulting in small epidemic waves of CHIKV in Manaus and Amazonas states .
In this study we characterized an outbreak caused by CHIKV in Boa Vista city , Roraima state , northern Brazil , using a combination of genetic , laboratory-confirmed and -suspected , and digital search data . Our findings show that an ECSA lineage was introduced in Roraima around July 2016 , six months before the beginning of the exponential increase in case numbers . Using simple epidemiological models , we show that on average 1 in 17 ( 95% CI: 14–20 ) symptomatic CHIKV cases , a fraction of the 110 , 882 ( 95% CI: 102 , 352–127 , 940 ) estimated number of infections , sought medical care during the outbreak of CHIK ECSA in Roraima . Incidence of CHIKV notified cases was strongly associated with fluctuation in Google search activity in Roraima . Moreover , this study represent the first effort to generate on-site complete CHIKV genome sequences . Our results deliver a genomic and epidemiological description of the largest outbreak ever reported in north Brazil , revealing the circulation of the ECSA lineage in the Amazon region . We estimate that 39% ( 95% CI: 36–45% ) of Roraima’s population was infected with CHIKV-ECSA-Br during the outbreak in 2017 . Our estimates are higher than the 20% seropositive observed in a rural community in Bahia [11] , and slightly lower than the 45 . 7–57 . 1% observed in two serosurveys conducted in the same state [13] , where the ECSA lineage also seems to predominate . The observed differences in terms of the proportion of the population exposed to CHIKV in Roraima compared to previous estimates from the northeast region could result from partial protection resulting from low-level transmission of the CHIKV-Asian genotype during 2014–2016 in the north region . Alternatively , some level of cross-protection could have been conferred by previous exposure to Mayaro virus ( MAYV ) ; Mayaro is an antigenically-related alphavirus that may provide some level of cross-reactivity [58 , 59] and is associated with Haemagogus spp . vectors [60] , but has also been identified in Culex quinquefasciatus and Aedes aegypti mosquitoes [66] . MAYV has been detected in the north [61–65] and centre-west [22 , 66–70] regions of Brazil . Moderate to high prevalence of MAYV IgM have been found in urban northern areas [61] , which could explain the limited spread of CHIKV in Manaus compared to Roraima . Finally , because CHIKV notified cases will be influenced by the apparent rate of infection associated to the genotype causing an outbreak [56] , future comparisons of epidemiological parameters across different regions from where no genotype data is available should be taken with caution . Given the rapid spread of different CHIKV lineages , novel diagnostic tools may be needed to evaluate the proportion of individuals infected by each genotype . Different CHIKV circulating lineages may have remarkably different public health consequences . Lineage-specific clinical presentations have been recently highlighted by a recent index cluster study which showed that 82% of CHIKV infections caused by the ECSA lineage are symptomatic , in comparison to only 52% of symptomatic infections caused by the Asian genotype [56] . While the Asian lineage seems to have circulated cryptically for 9 months before its first detection in the Caribbean [3] , the faster detection of the ECSA lineage in Brazil could at least in part be a consequence of a higher rate of symptomatic to asymptomatic infections of the ECSA lineage circulating in Brazil . The time lag between the phylogenetic estimate of the date of introduction of a virus lineage and the date of the first confirmed case in a given region , enables us to identify surveillance gaps between the arrival and discovery of a virus in that region [71] . We used genomic data collected over a 3-year period to estimate the genetic history of the CHIKV-ECSA-Br lineage . We estimate that the CHIKV-ECSA-Br lineage arrived in Roraima around July 2016 , whilst the first confirmed CHIKV cases in Roraima occurred earlier , in August 2014 . That the discovery date anticipates the estimated date of introduction can be explained by initial introduction ( s ) of the Asian linage ( from the north of Brazil or from other south American regions ) resulting in only limited onwards transmission , followed by the replacement of the Asian lineages by an epidemiological successful ECSA lineage . Transmission of the Asian genotype during this period is in line with an increase in notified and confirmed cases , as well internet search query data between August 2014 and June 2016 . It is also possible that ecological conditions may have dampened the transmission of the Asian genotype between August 2014 ( detection of autochthonous transmission of the Asian genotype in the north region of Brazil ) and July 2016 ( estimated arrival of the ECSA in Roraima ) . In the future , fine-scaled , high-resolution measures of transmission potential that take into account daily changes in humidity and temperature will help addressing the impact of climatic changes in the arbovirus epidemiology in the Brazilian Amazon . Nationwide molecular and seroprevalence studies combined with epidemiological modelling [72] will help to determine the proportion of cases caused by the ECSA compared to the Asian lineage in different geographic settings , and to identify which populations are still at risk of infection in Brazil . We estimated high rates of nucleotide substitution for this lineage , which equates to around 8 ( 95% BCI: 6–11 ) nucleotide substitutions per year across the virus genome . Such rates are similar to the evolutionary rates estimated for the IOL lineage; these are typical of urban and epidemic transmission cycles in locations with an abundance of suitable hosts and lack of herd immunity [9] . None of the mutations associated previously with increased transmissibility of the IOL lineage in Ae . albopictus mosquitos in the Indian Ocean region were identified in this study . However , it is currently unclear whether we should expect the same mutations to be linked with increased transmission in Aedes spp . populations both from Brazil and from Southeast Asia . Further , it is possible that CHIKV in Brazil is transmitted mainly by the Ae . aegypti vector that is abundant throughout Brazil [73] . In line with this , CHIKV-ECSA was recently detected in Aedes aegypti from Maranhão [74] and Rio de Janeiro states [75] . The past dengue serotype 4 genotype II outbreak in Brazil ignited in the north of the country , and is inferred to have been introduced from Venezuela to Roraima , before spreading to the northeast and southeast region of Brazil [76] . Our genetic analysis reveals at least four instances of ECSA-Br virus lineage migration in the opposite direction , i . e . , from northeastern to northern Brazil . Such a pattern may not be surprising due to the year-round persistence of Aedes aegypti mosquitos in the northeast and the north areas [32] . Within-country transmission will be dictated by human mobility , climatic synchrony , and levels of population immunity . Moreover , international spread of the ECSA-Br linage is expected to regions linked to Brazil . Previous analyses of dengue virus serotypes has identified a strong connectivity between north Brazil and Venezuela [26 , 77] , and northeast Brazil and Haiti [32 , 78] . In addition , Angola and Brazil are linked by human mobility and synchronous climates that have facilitated the migration of CHIKV-ECSA [1] and Zika virus ( http://virological . org/t/circulation-of-the-asian-lineage-zika-virus-in-angola/248 ) . Improving surveillance in the Amazon region may help anticipate transmission of vector-borne diseases and also spillover from wild mammals of zoonotic viruses of particular concern [28] . Genomic portable sequencing of vector-borne viral infections in the Amazon may is particularly important in the context of early identification of circulation of strains newly ( re ) -introduced from wildlife . For example , yellow fever strains collected in Roraima seem to be at the source of the 2016–2018 yellow fever virus outbreak in southeast Brazil , which has affected large urban centres in Minas Gerais , São Paulo and Rio de Janeiro [27] . In the near future , the increasing rapidity and decreasing cost of genome sequencing in poorly sampled areas , combined with emerging theoretical approaches [79] , will facilitate the investigation of possible associations between arbovirus lineage diversity , mosquito vectors , reservoir species , and transmission potential . Finally , the reported synchronicities between notified chikungunya case counts in Roraima and the chikungunya-related Internet searches originated in the region highlight the potential complementarity that Internet search activity may offer in future disease outbreaks . Specifically , given that disease-related search activity can be monitored in near-real time , early signals of increases in disease activity may be spotted weeks or months before lab-confirmed case counts may be available in an unfolding outbreak .
|
Until the end of 2017 , Brazil notified the highest number of infections caused by chikungunya virus ( CHIKV ) in the Americas . We investigated a large CHIKV outbreak in Boa vista municipality in the Brazilian Amazon region . Rapid portable genome sequencing of 20 novel isolates and subsequent genetic analysis revealed that ECSA lineage was introduced from northeastern Brazil to Roraima around July 2016 . Epidemiological analyses suggest a basic reproductive number of R0 of 1 . 66 , which suggests that approximately 39% of Roraima’s population was infected with CHIKV-ECSA . Given the dominance of the CHIKV-Asian genotype in the Americas , our data highlights the rapid spread of a less understood and poorly characterized CHIKV-ECSA genotype in Brazil . Investigations on potential associations between public health impact of CHIKV and genetic diversity of circulating strains are warranted to better evaluate its impact in Brazil and beyond .
|
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2019
|
Genomic, epidemiological and digital surveillance of Chikungunya virus in the Brazilian Amazon
|
Cytomegaloviruses ( CMVs ) have a highly restricted host range as they replicate only in cells of their own or closely related species . To date , the molecular mechanisms underlying the CMV host restriction remain poorly understood . However , it has been shown that mouse cytomegalovirus ( MCMV ) can be adapted to human cells and that adaptation goes along with adaptive mutations in several viral genes . In this study , we identify MCMV M117 as a novel host range determinant . Mutations in this gene enable the virus to cross the species barrier and replicate in human RPE-1 cells . We show that the M117 protein is expressed with early kinetics , localizes to viral replication compartments , and contributes to the inhibition of cellular DNA synthesis . Mechanistically , M117 interacts with members of the E2F transcription factor family and induces E2F target gene expression in murine and human cells . While the N-terminal part of M117 mediates E2F interaction , the C-terminal part mediates self-interaction . Both parts are required for the activation of E2F-dependent transcription . We further show that M117 is dispensable for viral replication in cultured mouse fibroblasts and endothelial cells , but is required for colonization of mouse salivary glands in vivo . Conversely , inactivation of M117 or pharmacological inhibition of E2F facilitates MCMV replication in human RPE-1 cells , whereas replacement of M117 by adenovirus E4orf6/7 , a known E2F activator , prevents it . These results indicate that E2F activation is detrimental for MCMV replication in human cells . In summary , this study identifies MCMV M117 as a novel E2F activator that functions as a host range determinant by precluding MCMV replication in human cells .
Viruses are obligate intracellular parasites . As such , they rely on suitable host cells for their replication . While some viruses can infect and replicate in cells from various tissues and different host species , others are highly adapted to their natural host and have a narrow host range [1 , 2] . Cytomegaloviruses ( CMVs ) , representatives of the β-herpesvirus subfamily , are highly species-specific as they can replicate only in cells of their own or closely related host species [3] . Human CMV ( HCMV ) , an opportunistic pathogen causing morbidity and mortality in immunocompromised individuals , replicates in cells from humans or chimpanzees , but not in cells from mice or other small animals . Consequently , HCMV pathogenesis cannot be studied in small animal models . Instead , related viruses such as the mouse and rat cytomegaloviruses ( MCMV and RCMV ) are used as models to study CMV pathogenesis in their natural hosts . Conversely , these viruses do not replicate in human cells . Early attempts to understand the CMV host species specificity have revealed that the CMVs can enter non-permissive host cells and even express a subset of viral genes , mainly of the immediate early ( IE ) class , but viral DNA replication and late gene expression are inefficient or absent [4 , 5] . Hence the CMV host cell restriction is thought to be caused by a post-penetration block to viral gene expression and replication [6] . However , the molecular mechanisms underlying the CMV host species specificity have remained largely unknown . A few studies have shown that MCMV is somewhat less restricted in its host range than HCMV [5 , 7] . An important restriction to MCMV replication in human cells is infection-induced apoptosis and the inability of MCMV to inhibit it in human cells . Enforced inhibition of apoptosis was sufficient to allow MCMV replication in human cells [8] . However , MCMV replication under these conditions was slow and inefficient , suggesting that additional checkpoints and restrictions exist . Other studies suggested that the virus’ ability to counteract suppression by PML nuclear bodies might play an important role in the viral host range [9 , 10] . An attractive and promising strategy to identify novel host range determinants is to characterize mutations in viruses adapted to cells of a foreign host [1 , 11] . Although the first report of a spontaneous MCMV adaptation to human cells was published almost 50 years ago [12] , identification and verification of adaptive mutations within the 230 kbp MCMV genome have become possible only recently with the availability of cost-efficient high-throughput sequencing [13 , 14] . The first MCMV host range factor identified with this strategy was the viral M112-113 gene [13] . One important difference between HCMV and MCMV is their dependence on the cell cycle stage . HCMV-infected cells need to be in the G1 phase in order to express viral IE genes [15 , 16] , whereas the expression of MCMV genes is independent of the cell cycle phase [17] . To facilitate viral DNA replication , these viruses arrest the cell cycle at the G1/S transition [18–23] , where the components necessary for viral replication are available , while blocking cellular DNA synthesis [24–26] . The E2F transcription factors were first described in 1986 as DNA binding proteins activating the adenoviral E2a promoter [27] . Since then , eight E2F proteins ( E2F1-8 ) have been discovered in mammalian cells and classified either as transcriptional activators ( E2F1-3 ) or repressors ( E2F4-8 ) ( reviewed in [28 , 29] ) . However , this classification is probably oversimplified as some activators can also repress gene expression [30] while the repressors , such as E2F4 , can activate the expression of certain target genes [31] . E2F1-6 transcription factors form heterodimers with dimerization partner proteins DP1 or DP2 that stabilize the DNA binding of the complex and target the transcription factors to specific promoters [32] . The transcription factor activity of the E2F family is negatively regulated by their association with cell cycle regulators of the retinoblastoma protein family ( pRb , p107 , and p130 ) , also known as pocket proteins . Phosphorylation of the pocket proteins releases the E2F-DP complex , which can then activate the expression of the E2F-dependent genes [33] . Several studies have shown that E2F activation promotes cell cycle progression into S phase , as many E2F target genes are involved in the process of DNA replication [34] . Some viruses , such as adeno- , papilloma- , and polyomaviruses promote E2F-dependent transcription and cell cycle progression towards S phase through viral proteins ( E1A , E7 , and large T , respectively ) [35] that disrupt the interaction between the pocket proteins and E2F . Similarly , the HCMV pp71 and pUL97 proteins regulate the Rb-E2F interaction by several distinct mechanisms [36–38] . Only a few viral proteins interact directly with E2F proteins and regulate their activity . The most studied is E4orf6/7 from adenovirus ( AdV ) type 5 , which was shown to interact with all canonical E2F members and activate E2F-dependent transcription [39–41] . Other viral proteins , such as HCMV IE1 , HPV16 E7 and the HIV-1 Tat protein activate E2F-dependent transcription via an interaction with only one E2F member [42–44] . It has also been shown that the CMVs transactivate the expression of the cellular genes involved in DNA replication in an E2F-dependent manner [45–47] . Here we show that the MCMV M117 protein interacts with all canonical E2F family members and activates E2F-dependent gene expression in MCMV-infected cells . M117 inactivation did not impair MCMV replication in murine cells , but massively reduced viral dissemination to the salivary glands of infected mice . By specific mutagenesis of M117 we showed that the interaction with E2F3 is of particular importance for transcriptional activation of target genes and for viral dissemination of MCMV in vivo . Intriguingly , M117 inactivation or pharmacological inhibition of E2F-dependent transcription facilitated MCMV replication in human cells while expression of the AdV E4orf6/7 protein , a known E2F activator , inhibited MCMV replication , suggesting that some E2F target proteins in human cells restrict MCMV replication .
In previous work we have reported the isolation of three human cell-adapted MCMVs ( MCMV/h1 , MCMV/h2 , and MCMV/h3 ) and described the mutations associated with adaptation to human RPE-1 epithelial cells [14] . All three adapted MCMVs carried mutations within ORF M117 , which were predicted to cause expression of truncated M117 proteins ( Fig 1A ) : in MCMV/h1 and /h2 the same point mutation ( C to A ) leads to the introduction of a premature stop codon , and in MCMV/h3 a single nucleotide deletion ( ΔT ) leads to a frameshift . We hypothesized that these mutations contributed to human cell adaptation and that M117 is a host range determinant . To test this hypothesis , the two different mutations were introduced individually into MCMV-GFP , an MCMV strain expressing the enhanced green fluorescent protein . The resulting mutant viruses were named MCMV-M117mut-h1 and MCMV-M117mut-h3 , respectively . Multistep replication kinetics in human RPE-1 epithelial cells were analyzed with both recombinant viruses . While the parental WT MCMV did not replicate in human RPE-1 cells , both MCMV-M117mut-h1 and MCMV-M117mut-h3 viruses replicated to high titers in human cells ( Fig 1B ) . However , compared to the spontaneously adapted viruses MCMV/h1 and MCMV/h3 , the constructed M117 mutants reached their peak titers several days later , indicating that additional mutations present in MCMV/h1 , MCMV/h2 , and MCMV/h3 [14] contributed to human cell adaptation . According to the MCMV genome annotation by Rawlinson [48] the M117 ORF overlaps with the m117 . 1 ORF encoded on the opposite strand ( Fig 1A ) . Which of the two ORFs is transcribed and translated into a protein has not been established yet . However , low levels of M117 transcripts , but not of m117 . 1 transcripts , were detected by RNA sequencing and ribosome profiling studies [49 , 50] . Another study reported detection of low levels of m117 . 1 transcripts [51] . Moreover , m117 . 1-derived peptide fragments have been detected in purified MCMV virions by mass spectrometry [52] . To determine whether MCMV expresses M117 or m117 . 1 proteins during infection , we constructed recombinant MCMV viruses carrying an HA tag at the 3ˈ end of ORFs M117 or m117 . 1 , respectively . The MCMV-M117-HA and MCMV-m117 . 1-HA viruses were used to infect murine fibroblasts , and expression of HA-tagged proteins was assessed by Western blot . In cells infected by MCMV-M117-HA , a protein with a molecular weight of approximately 100 kDa could be detected as early as 6 hours post infection ( hpi ) ( Fig 2A ) . The M117 protein was apparently expressed at a low level as its detection by Western blot required a long exposure . This is consistent with the low transcript levels detected in previous studies [49 , 50] . In contrast , no specific HA-tagged protein could be detected in cells infected with MCMV-m117 . 1-HA ( Fig 2A ) . The apparent molecular weight of M117-HA ( 100 kDa ) differed from its predicted molecular weight ( 62 kDa ) , suggesting posttranslational modifications of the M117 protein or expression of a protein product from a larger , possibly spliced , transcript . To exclude the latter , another recombinant MCMV carrying an HA tag sequence at the 5' end of M117 ( MCMV-HA-M117 ) was constructed . As shown in Fig 2B , fibroblasts infected by MCMV-HA-M117 expressed an HA-tagged protein of approx . 100 kDa , thus suggesting that the mass increase was due to posttranslational modifications rather than expression of a larger spliced transcript . It is also noteworthy that two closely related virus species , the Maastricht and English isolates of rat CMVs ( murid herpesviruses 2 and 8 ) contain ORFs homologous to M117 , but not to m117 . 1 . The M117 protein expression time course ( Fig 2A ) suggested that M117 belongs to the early ( β ) kinetic class . To verify this , we used a cycloheximide ( CHX ) release assay that allows selective expression of viral immediate early ( α ) genes . Cells were infected in the presence of CHX to allow α gene transcription but not translation . After 4 hours , the CHX-containing medium was replaced by either normal medium or actinomycin D ( ActD ) -containing medium . The removal of CHX allowed the synthesis of proteins from immediate early transcripts while β gene transcription was blocked by ActD . As shown in Fig 2C , the MCMV immediate-early 1 ( IE1 ) protein was expressed with immediate early kinetics , but the viral early 1 ( E1 , M112-113 ) proteins and M117 were not . We also tested the expression of M117 in the presence of phosphonoacetic acid ( PAA ) , an inhibitor of viral DNA replication and late ( γ ) protein expression . PAA inhibited the expression of the MCMV late protein gB , but not the expression of IE1 , E1 , and M117 ( Fig 2D ) . Taken together these results demonstrated that M117 is expressed with early ( β ) kinetics . Next , we wanted to determine the intracellular localization of the M117 protein during MCMV infection . Initial experiments performed with MCMV-HA-M117 did not yield satisfactory results as the immunofluorescence ( IF ) signals were very weak due to the low expression level of M117 . To increase signal intensity , a mutant virus carrying a triple Flag tag at the N-terminus of M117 ( MCMV-M117-FL ) was created . During infection , the 3xFlag-tagged M117 protein could be detected in dot-like structures in the nuclei of infected cells . These dots colocalized with the viral E1 proteins ( Fig 3A ) , which are markers for viral replication compartments [53 , 54] . In silico analysis of the M117 amino acid sequence with three different online tools ( seqNLS , NUCDISC/PSORTII and ELM ) predicted the presence of a bipartite nuclear localization signal ( NLS ) starting at position 405 ( Fig 3B ) . To test the role of the NLS in M117 nuclear localization , 3xFlag-M117 and the two C-terminal truncation mutants ( ΔCter and ΔCter2 ) were cloned in a pcDNA3 expression plasmid . The ΔCter and ΔCter2 truncated proteins correspond to the truncated M117 proteins encoded by MCMV-M117mut-h1 and MCMV-M117mut-h3 , respectively . ΔCter2 retains the predicted NLS , whereas ΔCter does not ( Fig 3B ) . As shown in Fig 3C , both full-length M117 and the ΔCter2 mutant were detected in the cell nucleus whereas ΔCter was detected predominantly in the cytoplasm . We also observed a difference in the nuclear distribution of M117 during infection and transfection , the protein being dispersed in the nucleus upon transfection ( Fig 3C ) but localizing in specific intranuclear compartments during infection ( Fig 3A ) . Taken together these findings suggest that M117 uses the predicted NLS for the localization in the cell nucleus but requires additional viral proteins or viral DNA , present during infection and absent in transfected cells , for its recruitment to viral replication compartments . The M117 ORF is encoded on the negative strand of the MCMV genome between M116 and M118 [48] . Thus , it is a positional homolog of HCMV UL117 , which is also encoded on the negative strand between UL116 and UL118 . Although the overall sequence similarity between M117 and pUL117 is low ( 24% ) , a sequence alignment of M117 homologs from rodent and primate CMVs revealed stretches of high similarity within the N- and C-terminal parts of the proteins ( S1 Fig ) . Moreover , M117 belongs to the same kinetic class and shows the same nuclear distribution as previously described for the UL117 protein ( pUL117 ) [55] . As pUL117 contributes to cell cycle regulation by suppressing host DNA synthesis [26] , we tested whether M117 is also involved in cell cycle regulation . To do this , NIH-3T3 cells were synchronized by 48 hours serum starvation and infected with MCMV expressing M117 ( MCMV-M117-FL ) or mutants lacking M117 ( MCMV-ΔM117 and MCMV-M117stop ) for additional 48 hours ( Fig 4A ) . Whereas MCMV-ΔM117 lacks the complete M117 ORF , the MCMV-M117stop virus carries a point mutation that introduces a stop codon at position 21 without changing the amino acid sequence encoded by the m117 . 1 ORF on the opposite strand . To better recognize a possible effect of M117 on host cell DNA synthesis , viral DNA replication was blocked with Ganciclovir ( GCV ) . Cells were fixed , stained for the viral protein IE1 to identify infected cells and with propidium iodide to analyze DNA content by flow cytometry . As shown in Fig 4B , cells infected with the WT MCMV expressing full length M117 predominantly showed a 2n DNA content consistent with a G1/S cell cycle arrest [17] . Conversely , a larger percentage of cells infected with the viruses lacking M117 had a 4n DNA content ( Fig 4B ) , indicating cell cycle progression through S phase and an arrest at G2/M . These data suggest that M117 has a role in the regulation of host DNA synthesis and cell cycle progression through S phase . In order to understand the mechanism of action of M117 , we tried to identify M117-interacting proteins by affinity purification-mass spectrometry ( AP-MS ) . Stable isotope labelling by amino acids in cell culture ( SILAC ) was used to compare the anti-HA immunoprecipitation products of cells infected with WT MCMV or MCMV-HA-M117 . The experiment was done in duplicate including a label switch . Proteins identified by at least 2 unique peptides and a log2 ratio ≥ 3 ( HA-M117 vs WT ) were considered as potential interaction partners . Besides M117 itself , only 4 proteins met these criteria: the viral DNA polymerase processivity factor M44 and three members of the E2F transcription factor family: E2F3 , E2F4 , and DP1 ( Table 1 ) . To verify the candidates , M117 was immunoprecipitated from MCMV-infected cells using a different antibody ( anti-Flag instead of anti-HA ) and co-precipitating proteins were analyzed by immunoblot . WT MCMV , which does not express any Flag-tagged protein , and a recombinant virus expressing 3xFlag-tagged UL117 instead of M117 ( MCMV-UL117-FL ) were used as controls . Immunoprecipitates were separated by SDS-PAGE , blotted , and probed with antibodies specific for all canonical E2F transcription factors ( E2F1-5 ) and DP1 . Blots were also probed with antibodies specific for M44 ( the viral DNA polymerase processivity factor ) and E1 ( a major constituent of viral replication compartments ) . As shown in Fig 5A , neither M44 nor E1 co-precipitated with M117 . Comparable results were obtained in repeated experiments . Thus , we could not confirm the M117-M44 interaction and considered M44 as an unspecific interactor in the AP-MS screen . In contrast , all tested members of the E2F transcription factor family interacted with M117: E2F1 , E2F3 , E2F4 , and DP-1 were highly enriched in the immunoprecipitates while E2F2 and E2F5 were detected at lower levels ( Fig 5A and S2A Fig ) . Interestingly , HCMV pUL117 did not interact with any of the E2F factors tested , suggesting that M117 and pUL117 employ different mechanisms to regulate the cell cycle . To determine which part of M117 is important for the interaction with E2F proteins , N- and C-terminal truncation mutants ( ΔNter and ΔCter ) were used for co-immunoprecipitation experiments . While deletion of the C-terminal 281 amino acids ( aa ) did not impair the co-precipitation of E2F transcription factors , deletion of the N-terminal 50 aa was sufficient to abrogate these interactions in MCMV infected cells ( Fig 5B ) . The same interactions were detected when mutant M117 proteins were expressed by plasmid transfection ( Fig 5C and S2B Fig ) , indicating that the presence of other viral proteins is not required for these interactions . Additional 50 aa deletions within the N-terminal half of M117 were constructed ( S2C Fig ) and tested for their ability to interact with E2F3 and E2F4 . The results showed that while aa 51–100 ( M117-ΔNter2 ) were also important for M117 interaction with E2F family members , the following aa 101–200 ( M117-ΔNter3 and M117-ΔNter4 ) did not play any role ( S2B Fig ) . Occasionally , a protein co-precipitating with M117-ΔNter2 was detected with the anti-E2F3 antibody ( S2B Fig ) , but this protein was not seen in other experiments . As the band representing the protein was weak and migrated slightly different than the usual E2F3 isoforms , it is unclear if this band represents an E2F3 isoform or a different cross-reacting protein . As such large deletions could affect the protein’s conformation , we tested whether an alanine substitution mutation of a highly conserved motif ( IPP→AAA , S1 and S2C Figs ) would influence the interaction with E2F transcription factors . This mutation , which was named M4 , resulted in a loss of interaction with all canonical E2F members except E2F3 and DP1 in MCMV-infected cells ( Fig 5B ) . In plasmid-transfected cells the M117 M4 mutant could still interact very weakly with E2F1 and E2F4 ( Fig 5C ) , suggesting that the M4 mutation strongly impairs the interaction with E2F1 and E2F4 , but does not abolish it completely . The M4 mutant retained the ability to bind DP1 , albeit to a lesser extent than full-length M117 , whereas the M117-ΔNter did not interact with this factor ( Fig 5B and 5C ) . These data suggest that the interaction of M117 with DP1 occurs indirectly via the binding of M117 to E2F-DP heterodimers . Another possibility is that M117 interacts independently with DP1 and E2F3 , and that the loss of interaction with DP1 leads indirectly to a loss of interaction with E2F1 and E2F4 . Finally , we observed that the C-terminal part of the protein is important for its self-interaction , as a mutant lacking the 117 final amino acids ( M117-ΔCter2 ) could not interact with the full length M117 ( Fig 5D ) . Taken together , these data show that M117 interacts with E2F transcription factors via its N-terminus , whereas the C-terminus is essential for its self-interaction ( dimerization ) . Moreover , a specific mutation leads to the loss of interaction with specific E2Fs , suggesting a change in the affinity of M117 for specific E2Fs . The E2F transcription factors have been classified as functional activators or repressors of gene expression [28 , 56] . As M117 interacted with all canonical members of the E2F family , we wanted to determine the effect of M117 on E2F-dependent transcription . For this purpose , we used a reporter plasmid containing the firefly luciferase gene under the control of an E2F-dependent promoter . NIH-3T3 cells were first co-transfected with this reporter plasmid and a control plasmid expressing Renilla luciferase and then infected either with MCMV-M117-FL or the mutant viruses . Cell lysates were harvested 24 hpi and luciferase activity was measured with a dual luciferase assay . Cells infected with MCMV expressing a 3xFlag-tagged full-length M117 ( MCMV-M117-FL ) showed an increased firefly luciferase expression compared to uninfected cells , indicating that MCMV induces E2F-dependent transcription ( Fig 6A ) . E2F-dependent luciferase expression was strongly reduced in cells infected by MCMV mutants expressing truncated M117 ( M117-ΔNter and M117-ΔCter2 ) or lacking M117 proteins ( M117stop ) ( Fig 6A ) , suggesting that both the N-terminus ( required for E2F interaction ) and the C-terminus ( required for self-interaction ) of M117 are needed to activate E2F-dependent transcription . Surprisingly , the MCMV-M117-M4 mutant virus activated E2F-dependent transcription to a similar extent as did MCMV-M117-FL , suggesting that the E2F family member E2F3 is a very potent transcription factor under these conditions . Mutation of the E2F binding site of the reporter plasmid abrogated the induction of luciferase ( Fig 6A ) , confirming that M117 induced luciferase expression in an E2F-dependent manner . To verify the results obtained with the luciferase reporter assay , we measured the impact of MCMV infection on the transcription of selected cellular genes known to be regulated by E2Fs [57] . NIH-3T3 cells were synchronized in G1 and infected with WT and mutant viruses . Total RNA was extracted at 24 hpi and used to quantify Cyclin E1 , Cyclin A2 , and PCNA transcripts by quantitative RT-PCR ( qRT-PCR ) . Similarly to what we had observed with the E2F reporter assay ( Fig 6A ) , infection with an MCMV expressing a full-length M117 ( MCMV-M117-FL ) or the M4 mutant induced the expression of the E2F target genes . This induction was significantly reduced when cells were infected with the M117-ΔNter , M117-ΔCter2 , or the M117stop mutant ( Fig 6B ) . We also analyzed the protein levels of Cyclin A2 and Cyclin B1 , representative E2F target gene products , by immunoblot . Unfortunately , none of the antibodies against mouse Cyclin E1 that we tested worked reliably in our hands . Hence we were unable to determine Cyclin E1 protein levels . As shown in Fig 6C , Cyclin A2 and B1 protein levels were upregulated upon infection with MCMV-M117-FL or MCMV-M117-M4 . In contrast , Cyclin A2 and B1 induction was much weaker after infection with the M117-ΔCter2 , M117-ΔNter or the ΔM117 mutants . The protein expression data are consistent with the qRT-PCR results . To examine the importance of E2F3 in the M117-mediated E2F dependent transcription , we generated E2F3 knockout ( KO ) NIH-3T3 cells using CRISPR/Cas9 genome editing . Two cell clones lacking E2F3 expression and two control clones ( Fig 6D ) were used in an E2F-dependent luciferase reporter assay . As shown in Fig 6E , luciferase induction by MCMV-M117-FL was similar in E2F3-positive and negative cells , indicating that E2F3 is not required for MCMV to induce E2F-dependent transcription . In contrast , luciferase induction by MCMV-M117-M4 was strongly impaired only in E2F3-negative cells , but reached comparable levels to the MCMV-M117-FL in E2F3-positive cells , indicating that the interaction of M117 with E2F3 is sufficient to induce E2F-dependent transcription . Taken together , the data in Fig 6 show that M117 is necessary for the activation of E2F-regulated genes in MCMV-infected cells . However , M117 might not be sufficient as M117 expression by plasmid transfection did not reliably activate an E2F-dependent luciferase reporter , and the intranuclear distribution of M117 protein was dependent on the presence of other viral factors ( Fig 3 ) . Thus , any functional analyses of M117 done solely in transfection experiments should be interpreted with caution . We concluded that additional factors present in MCMV-infected cells might be required for M117-dependent activation of E2F target genes . Considering the clear effects of M117 on E2F-dependent gene expression ( Fig 6 ) and cell cycle regulation in immortalized fibroblasts ( Fig 4 ) , we were surprised to see that MCMV-M117stop replicated with the same kinetics as WT MCMV in different cells such as primary MEFs ( non-immortalized cells ) , and SVEC4-10 endothelial cells ( Fig 7A and 7B ) . Other M117 mutant viruses also showed no signs of impaired replication in these murine cells ( S3 Fig ) . However , it remained possible that M117 mutant viruses had a more subtle or cell type-dependent replication and dissemination disadvantage that becomes apparent only during infection in vivo . To test this , BALB/c mice were infected intraperitoneally with WT MCMV , MCMV-ΔM117 , and MCMV-3xFlag-M117 ( MCMV-M117-FL ) , which served as a revertant of the MCMV-ΔM117 mutant . Viral titers in the spleen and lungs were determined on day 3 and 7 , and salivary gland titers were determined on day 14 post infection . Again , we did not observe any obvious replication defect for MCMV-ΔM117 in the acute phase of MCMV infection ( Fig 7C–7F ) . However , on day 14 post infection salivary gland titers of the MCMV-ΔM117 mutant were massively reduced to levels below the detection limit ( Fig 7G ) . To exclude that the salivary gland phenotype of the MCMV mutant lacking M117 was caused by an unspecific effect of the deletion on neighboring genes , we infected mice with MCMV-M117stop . We also included MCMV N- and C-terminal M117 truncation mutants as well as the MCMV-M117-M4 mutant . On day 14 post infection , salivary gland titers of MCMV-M117stop , ΔNter , and ΔCter2 were below the detection limit ( Fig 7H ) , thus confirming that a loss of M117 function was responsible for the in vivo attenuation . Strikingly , the MCMV-M117-M4 mutant attained salivary gland titers comparable to those of the MCMV-M117-FL ( Fig 7H ) , suggesting that the interaction with E2F3 ( the only E2F interaction retained by M117-M4 as shown in Fig 5B ) is sufficient not only for the activation of E2F target genes ( Fig 6 ) but also for dissemination to or replication in the salivary glands ( Fig 7H ) . In the beginning of this study , we characterized M117 as a host range determinant: mutations causing the expression of C-terminally truncated M117 proteins allowed MCMV replication in human RPE-1 cells ( Fig 1 ) . However , it has remained unknown whether expression of the N-terminal part of M117 was required for MCMV replication in human RPE-1 cells or whether any loss-of-function mutation would have the same effect . To resolve this question we infected RPE-1 cells with a set of M117 mutants and determined viral replication kinetics . As expected , MCMV-M117-FL did not replicate in RPE-1 cells . By contrast , MCMV-M117stop and both the N- and C-terminal M117 truncation mutants grew to high titers and with very similar kinetics ( Fig 8A ) . The MCMV-M117-M4 mutant showed an intermediate phenotype ( i . e . , it replicated slower and reached lower titers ) , possibly because it retained the ability to interact with E2F3 ( Fig 5B and 5D ) and activated E2F-responsive promoters ( Fig 6 ) . As RPE-1 cells are telomerase-immortalized cells , we tested whether the virus mutants were also able to replicate in primary human cells . We have previously shown that human cell-adapted MCMVs can also replicate in human embryonic lung fibroblasts ( MRC-5 cells ) , although to substantially lower titers than in RPE-1 cells [13 , 14] . Therefore , we tested whether mutation of M117 is sufficient to allow MCMV replication in MRC-5 cells . As expected , MCMV-M117-FL did not replicate in human fibroblasts , whereas all M117 mutants replicated to low titers in MRC-5 ( Fig 8B ) , indicating that the presence of a fully active M117 is detrimental for MCMV replication in human cells . To understand whether the function of M117 was similar in mouse and human cells , we performed experiments similar to the ones described above . First , we checked if M117 was able to interact with the human E2F members . M117-HA was immunoprecipitated from RPE-1 infected cells and co-precipitating proteins were analyzed by immunoblot . WT MCMV , which does not express any HA-tagged proteins , was used as a control . Immunoprecipitates were separated by SDS-PAGE , blotted , and probed with antibodies specific for two E2F transcription factors , E2F3 and E2F4 . As shown in Fig 8C , E2F3 and E2F4 co-precipitated with HA-M117 , suggesting a similar interaction pattern of M117 in human and mouse cells . Next , we looked at the activation of the E2F-dependent gene expression by qRT-PCR . RPE-1 cells were synchronized in G1 and infected with WT MCMV and MCMV-ΔM117 viruses . Total RNA was extracted at 24 hpi and used to quantify Cyclin E1 , Cyclin A2 , and PCNA transcripts . Similarly to what was observed in mouse cells , infection with a WT MCMV induced the expression of the E2F target genes Cyclin E1 and PCNA , and to a lower extent of Cyclin A2 . However , this induction was significantly reduced in absence of M117 for all the genes tested ( Fig 8D ) . Finally , we wanted to clarify whether the M117-mediated E2F activation or another hitherto unknown function of M117 precludes MCMV replication in human cells . To address this question , we tested whether HLM006474 , a pan-E2F inhibitor [58] , could facilitate MCMV replication in human RPE-1 cells . This inhibitor was shown to block the E2F DNA-binding activity [58] , but did not affect the interaction of M117 with E2Fs ( S4 Fig ) . Unfortunately , prolonged treatment with HLM006474 was not possible due to cell toxicity [58] . To restrict the duration of inhibitor treatment , RPE-1 cells were infected with WT MCMV-GFP , and treated with HLM006474 or solvent ( DMSO ) for 3 days . Viral DNA replication was then measured by qPCR . As shown in Fig 8E , MCMV DNA replication was increased substantially in the presence of the pan-E2F inhibitor HLM006474 . As E4orf6/7 from AdV 5 shares functional similarities with M117 , such as the interaction with E2Fs and activation of the E2F-dependent transcription [41 , 59] , we constructed a recombinant virus by inserting the E4orf6/7 gene into MCMV-ΔM117 . Expression of E4orf6/7 by MCMV ( Fig 8F ) abrogated the ability of MCMV-ΔM117 to replicate in human RPE-1 cells ( Fig 8G ) . These results support the concept that E2F activation is detrimental for MCMV replication in human cells and explain why loss-of-function mutations in M117 facilitate MCMV replication in these cells .
In this work we characterize the properties , functions and cellular interacting partners of M117 , a previously uncharacterized MCMV protein . M117 has sequence similarity to pUL117 , its presumed homolog in HCMV , and the two proteins show functional similarities: Both are expressed with early kinetics , localize to viral replication compartments , and contribute to the blockage of host DNA synthesis . However , there are important differences: Inactivation of UL117 in HCMV lead to a profound replication defect of the virus in cell culture [55] , whereas the absence of M117 did not affect MCMV replication in vitro ( Fig 7 ) . Moreover , the two proteins have a different mechanism of action . While pUL117 inhibits cellular DNA synthesis by inhibiting chromatin loading of the minichromosome maintenance complex [26] , MCMV M117 interacts with E2F transcription factors and activates E2F-dependent gene transcription . This activation could be the result of a recruitment of the M117-E2F complex to specific promoters . Alternatively , the binding of M117 to E2Fs could alter the interaction of E2Fs with repressors such as pRB , ARF or EAPP . This mechanism is not shared with HCMV pUL117 ( Fig 5 ) but appears to be similar to the one described for AdV 5 E4orf6/7 . The E4orf6/7 protein binds to all classical E2Fs [39] and activates E2F-dependent transcription of the viral E2 genes as well as cellular genes [40 , 41] by inducing a dimerization of E2F factors [40 , 60] . M117 shares several of these features such as the ability to interact with several E2F family members and the self-interaction that is needed to activate target gene transcription . Moreover , a recombinant MCMV expressing E4orf6/7 instead of M117 had the same replication phenotype in human cells as WT MCMV ( Fig 8G ) , indicating that E4orf6/7 can substitute for M117 under these conditions . Interestingly , the M117 M4 mutation abrogated the interaction of M117 with most E2F proteins ( Fig 5 ) . The 3 aa mutated in the M117 M4 mutant appear to be part of a larger motif that is conserved in the rat CMV homologs ( R117 and E117 ) , but only to a very limited extent in HCMV UL117 ( S1 Fig ) . This could explain the inability of UL117 to interact with E2F proteins ( Fig 5A ) . It is also possible that E2F binding requires a three-dimensional structure ( consisting of two or more protein domains ) that is not conserved in UL117 . Similar to E4orf6/7 , the absence of M117 does not affect viral replication in cell culture , suggesting that another viral protein can compensate for the loss of M117 . In the case of E4orf6/7 , the AdV E1A protein provides the redundant function by inducing pRb phosphorylation [61 , 62] . We propose that a similar mechanism could operate during MCMV infection . A strong candidate as provider of the redundant function is the MCMV protein kinase , M97 , as its HCMV homolog , pUL97 , can bind and phosphorylate pRb , thereby relieving its inhibitory effect on the E2Fs [63 , 64] . This hypothesis remains to be confirmed . However , our observation that M117 mutant viruses ( MCMV-M117stop and MCMV-ΔNter ) are still able to moderately induce E2F-dependent gene expression in infected cells ( Fig 6A and 6B ) supports the hypothesis that other viral factors are involved in the activation of E2Fs . Induction of E2F-dependent transcription by M117 ( Fig 6 ) is expected to accelerate cell cycle progression and push the cell cycle toward the S phase . However , we also found that M117 helps to block cell cycle progression , as seen when cells infected with an M117-deficient MCMV were able to progress toward the G2/M phase ( Fig 4 ) . These apparently contradictory findings can be reconciled taking into account that CMV replication induces a DNA damage response , which can lead to a cell cycle arrest at the G1/S transition [65 , 66] . As many E2F target genes belong to the DNA repair machinery , their sustained E2F-dependent transcription is beneficial for those cells experiencing replication stress [67 , 68] . We hypothesize that MCMV uses M117 to push the host cell towards S phase , which provides a favorable environment for viral DNA replication . The resulting constant E2F activation , together with the viral DNA replication , increases replication stress , which leads to cell cycle arrest . However , cells infected with an MCMV lacking a functional M117 can still enter S phase with the help of compensatory proteins ( for example , those that phosphorylate pRb , ) and activate E2F-dependent transcription to a lesser extent . However , inhibitory mechanisms exist to turn off E2F-dependent transcription [69] , thus reducing the replication stress experienced by infected cells and preventing cell cycle arrest . When we analyzed the ability of M117 mutant MCMVs to replicate and disseminate in vivo , we observed a profound drop in the salivary gland titers at 14 dpi ( Fig 7 ) , indicating that viral dissemination to or replication within the salivary glands is defective in the absence of a functional M117 . At 14 dpi , the virus is largely cleared from other organs ( spleen , lungs ) while the salivary glands remain important sites for viral persistence . The reason why M117 is important at this stage of the infection remains unclear . As putative E2F binding sites have been detected in the promoters of cytokines and chemokines [70–72] , one could speculate that the E2F transcription factors regulate the expression of cytokines or chemokines necessary for viral dissemination to or replication in the salivary glands . Interestingly , the MCMV-M117-M4 mutant activated E2F-dependent transcription ( Fig 6 ) and disseminated to the salivary glands in vivo ( Fig 7 ) to a comparable extent as WT MCMV did . These findings were somewhat surprising as the M4 mutant only retained the ability to interact efficiently with E2F3 , but not with the other canonical E2F family members . Thus , the activation of E2F3 appears to be sufficient for viral replication and dissemination in vivo . This conclusion is consistent with the results of genetic studies in mice: knockout mice lacking several E2F members were viable as long as at least one E2F3 isoform was present [73 , 74] . Finally , we demonstrated that M117 acts as a host range determinant . Activation of the E2F-dependent transcription by M117 or by E4orf6/7 is detrimental for the replication of MCMV in human RPE-1 cells , and inhibiting this activation , either by deleting M117 or by adding an inhibitor , allows the virus to replicate in human cells ( Figs 1 and 8 ) . The reason why E2F activation is detrimental to MCMV replication in human but not murine cells remains to be investigated . There is probably no simple answer to this question as E2F transcription factors affect the expression of many different genes . Some of them could have antiviral activities against MCMV that cannot be counteracted by the virus . E2F functions detrimental for viral replication might include the upregulation of Cyclin A2 , which has been shown to inhibit the immediate early gene expression of HCMV [23] . However , in our experiments , we observed only a low induction of Cyclin A2 in WT MCMV infected cells ( Fig 8C ) , an observation that argues against a crucial role of Cyclin A2 . Nonetheless , we cannot completely reject this possibility as the time point selected in human infected cells ( 24 hpi ) could be too early to observe a strong induction of Cyclin A2 gene expression . The detrimental effect of M117 in human cells could also be caused by differences in the target genes induced by the E2F factors in human vs . murine cells . Altering the viral host range by adapting a virus to cells of a different host can raise biosafety concerns if a virus with zoonotic potential is involved . This is not the case for the cytomegaloviruses: They are highly adapted to their specific host and cause persistent infections only because of numerous immune evasion mechanisms [75] , many of which do not function properly in a foreign host . Hence the zoonotic potential of the CMVs is very low , and the CMVs are not among the pathogens that could be involved in “dual use research of concern” [76] . In conclusion , this study identified MCMV M117 as a new viral E2F regulator , which is important for viral fitness in vivo . M117 also acts as a host range factor that prevents MCMV replication in human RPE-1 and MRC-5 cells . Further work needs to be done to understand the function of this protein in cross-species infection as well as the differences in E2F-mediated gene regulation between human and mouse cells .
All animal experiments were performed according to the recommendations and guidelines of the FELASA ( Federation for Laboratory Animal Science Associations ) and Society of Laboratory Animals ( GV-SOLAS ) and approved by the institutional review board and local authorities ( Behörde für Gesundheit und Verbraucherschutz , Amt für Verbraucherschutz , Freie und Hansestadt Hamburg , reference number 123/16 ) . Six to 8 week-old BALB/c female mice ( Janvier laboratories ) were infected intraperitoneally with 105 PFU MCMV per mouse as described [77] . Organs were harvested on day 3 and 7 ( spleen and lungs ) and day 14 ( salivary glands ) post infection , homogenized , and used to determine organ titers by plaque assay on M2-10B4 cells . All cells were maintained in complete Dulbecco’s modified Eagle medium ( DMEM ) supplemented with 10% fetal calf serum ( FCS ) and 100 IU Penicillin/100 μg Streptomycin at 37°C and 5% CO2 . RPE-1 cells are human telomerase reverse transcriptase immortalized human retinal pigment epithelial cells ( ATCC CRL-4000 ) . MRC-5 cells are primary human embryonic lung fibroblasts ( ATCC CCL-171 ) . Murine NIH-3T3 fibroblasts ( CRL-1658 ) , SVEC4-10 endothelial cells ( CRL-1658 ) , and M2-10B4 bone marrow stromal cells ( CRL-1972 ) were obtained from the ATCC . Murine 10 . 1 fibroblasts are spontaneously immortalized MEFs from BALB/c mice [78] obtained from Thomas Shenk ( Princeton University , USA ) . Primary MEFs were isolated from 13 . 5 day old C56BL/6 embryos following standard procedures [77] . The GFP-expressing ( MCMV-GFP ) and the “repaired” WT MCMV Smith strain ( pSM3fr-MCK-2fl ) strain have been described previously [79 , 80] . All viruses were propagated in 10 . 1 fibroblasts . For high MOI infections , a centrifugal enhancement ( 1000 × g , 30 min ) was used . For replication kinetics , cells were infected in six-well dishes . After 4 h , cells were washed twice with phosphate-buffered saline ( PBS ) , and fresh medium was added . Supernatants were harvested at different times post infection for virus titration on 10 . 1 cells using the median tissue culture infective dose ( TCID50 ) method . Mutations within the M117 locus were introduced by en passant mutagenesis [81] into the MCMV-GFP or the WT MCMV ( pSM3fr-MCK-2fl ) bacterial artificial chromosome ( BAC ) , which was used as parental wildtype ( WT MCMV ) genome . AdV 5 E4orf6/7 was PCR amplified from pcDNA-E4orf6/7 ( kindly provided by Thomas Dobner , Heinrich Pette Institute , Hamburg ) and introduced into the nonessential m02-m06 region of MCMV ( pSM3fr-MCK-2fl ) by using the pReplacer system [8] . To reconstitute infectious virus from MCMV BACs , purified BAC DNA was transfected into 10 . 1 fibroblasts using Polyfect ( Qiagen ) . The integrity and the absence of unintended mutations of the mutant BACs based on the backbone of the WT MCMV were verified by Illumina sequencing of the entire BACs ( MCMV-3xFlag-M117-FL , M117stop , ΔM117 , ΔCter , ΔCter2 , ΔNter ) . All other mutant BACs based on the backbone of MCMV-GFP ( MCMV-M117mut-h1 and -h3 , HA-M117 , M117-HA and m117 . 1-HA ) were analyzed by sequencing of the region of interest and analysis of restriction fragment patterns . The M117 coding sequence was PCR-amplified from the MCMV Smith genome using a forward primer containing a HindIII restriction site and the 3xFlag sequence and a reverse primer containing an MfeI restriction site . The PCR product was cleaved with HindIII and MfeI and inserted into expression plasmid pcDNA3 ( Invitrogen ) digested with HindIII and EcoRI . Deletions or substitutions of nucleotides were performed by PCR-driven overlap extension [82] . Transfection of NIH-3T3 cells with expression plasmids was done using Polyfect ( Qiagen ) according to the manufacturer’s protocol . The lentiviral CRISPR/Cas9 vector pSicoR-CRISPR-PuroR was used to generate E2F3 KO clones essentially as described [83] . Briefly , the E-CRISPR design tool ( www . e-crisp . org ) was used to design three guideRNAs that were cloned individually in the lentiviral vector: g1 , GATGGTCTAAAGACCCCCAA; g2 , GGATCTGAACAAGGCAGCAG; and g3 , GGACCTCAAACTGTTAACCG . Lentiviruses were generated using standard third-generation packaging vectors in HEK-293T cells . Then , NIH-3T3 cells were transduced with an E2F3 lentiviral CRISPR/Cas9 or an empty vector ( g0 ) in the presence of polybrene ( Sigma ) . The cells were selected with 2 . 5 μg/mL puromycin ( Sigma ) . Polyclonal cultures were subcultured to obtain single cell clones for each gRNA , and E2F3 protein expression was evaluated for each clone by Western blot analysis . To quantify transcripts , synchronized NIH-3T3 or RPE-1 cells were infected at a MOI of 3 TCID50/cell . Total RNA was extracted from infected cells using the innuPREP RNA Mini Kit ( Analytik Jena ) and contaminating DNA was removed using the TURBO DNA-free Kit ( Ambion ) . cDNA was synthesized from 1μg of the extracted RNA by using the RevertAid H Minus Reverse Transcriptase , oligo-dT primers , and the RNase inhibitor RiboLock ( Thermo Fisher Scientific ) . qPCR was performed on an ABI PRISM 7900HT Fast Real-Time PCR System ( Applied Biosystem ) using 10 ng of cDNA , the SybrGreen real time PCR Mastermix ( Life technologies ) . To amplify mouse transcripts , the following primers were used: Gapdh ( CCCACTCTTCCACCTTCGATG and GTCCACCACCCTGTTGCTGTAG ) , PCNA ( CACGTATATGCCGAGACCTTAGC and CTCCACTTGCAGAAAACTTCACC ) , Cyclin A2 ( GAGGGCCATCCTTGTGGACT and CACAGCCAAATGCAGGGTCT ) , and Cyclin E1 ( CAGAGCAGCGAGCAGGAGA and GCAGCTGCTTCCACACCACT ) . For the amplification of human transcripts , the following primers were used: hPCNA ( GGCACTCAAGGACCTCATCAAC and GTGAGCTGCACCAAAGAGACG ) , hGAPDH ( CCCACTCCTCCACCTTTGACG and GTCCACCACCCTGTTGCTGTAG ) , hCyclin A2 ( TGCTGGAGCTGCCTTTCATT and TGAAGGTCCATGAGACAAGGCT ) , and hCyclin E1 ( TACACCAGCCACCTCCAGACAC and CCTCCACAGCTTCAAGCTTTTG ) . Transcripts were quantified using the ΔΔCt method and normalized to a housekeeping gene ( Gapdh ) . For MCMV genome quantification , total DNA was extracted from MCMV-infected RPE-1 cells using an InnuPREP DNA Mini Kit ( Analytik Jena ) . One hundred ng of DNA was subjected to qPCR in order to quantify MCMV genome copies ( primers ACTAGATGAGCGTGCCGCAT and TCCCCAGGCAATGAACAATC ) and human β-actin gene copies ( primers GCTGAGGCCCAGTTCTAAAT and TTCAAGTCCCATCCCAGAAAG ) . NIH-3T3 cells were synchronized for 48 h by serum starvation ( DMEM/ 0 . 5% FCS ) and then infected with MCMV in the presence of 10% FCS . After 1 h , cells were washed and new media containing 50 μM Ganciclovir was added . To measure both DNA content and viral protein expression , cells were first permeabilized by incubation in 75% ethanol for at least 12 h at 4°C . Afterwards , cells were stained with antibodies against IE1 ( CROMA 101 , from Stipan Jonjic , University of Rijeka , Croatia ) and mouse-IgG-Alexa647 , before staining for DNA content with propidium iodide and analyzed by flow cytometry as previously described [22] . The luciferase reporter plasmids were kindly provided by Matthias Truss ( Charité Universitätsmedizin Berlin , Germany ) . They are based on a promoter/enhancer-less pGL2-basic ( Promega ) modified by insertion of a TATA box and an E2F binding site [84] . Plasmids pGL2-E2F-WT and pGL2-E2F-mut carry a single wildtype ( CGCGCC ) or mutant ( AAAGCC ) E2F binding site , respectively . NIH-3T3 cells were seeded in 12-wells plates ( 1×105 cells/well ) and transfected with 1 μg pGL2-E2F and 100 ng of pRL-Renilla ( Promega ) using Polyfect ( Qiagen ) . After 6 h the medium was exchanged , and after 24 h cells were infected at a MOI of 3 TCID50/cell . At 24 hpi , cells were harvested and luciferase activity was measured on a FLUOstar Omega reader ( BMG Labtech ) using a Dual Luciferase Reporter Assay ( Promega ) and according to the manufacturer’s protocol . NIH-3T3 cells were seeded onto glass coverslips coated for 30 min with 0 . 4% gelatin/PBS . On the following day , cells were infected with MCMV-3xFlagM117 at an MOI of 1 TCID50/cell or transfected with pcDNA3 expression plasmids using Polyfect ( Qiagen ) . Cells were fixed in methanol for 10 min at -20°C , washed with PBS , and blocked with PBS containing 1% gelatin . Incubations with the antibodies were carried out for 1 h at room temperature ( RT ) in 1% gelatin/PBS . Nuclei were stained for 10 min at RT with DRAQ5 ( BioStatus ) diluted 1:1000 in PBS . Coverslips were mounted on microscope slides with Aqua-Poly/Mount ( Polysciences ) and subjected to confocal laser scanning microscopy ( cLSM ) . The following antibodies were used: monoclonal antibodies against glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) ( 14C10; Cell Signaling ) , β-actin ( AC-74; Sigma ) , HA ( 3F10; Roche ) , FLAG ( M2 , Sigma-Aldrich ) , DP1 ( TFD-10; Santa Cruz ) , and Cyclin B1 ( GNS-1; Santa Cruz ) . Antibodies against MCMV gB ( M55 . 01 ) , IE1 ( CROMA101 ) , and M112-113 ( CROMA103 ) were provided by Stipan Jonjic ( University of Rijeka , Rijeka , Croatia ) , anti-M44 ( 3B9 . 22A ) was provided by Lambert Loh , University of Saskatchewan , Canada . The monoclonal antibody RSA3 against AdV 5 E4orf6/7 [85] was kindly provided by Thomas Dobner ( Heinrich Pette Institute , Hamburg ) . Polyclonal rabbit antibodies against E2F1 ( C-20 ) , E2F2 ( C-20 ) , E2F3 ( C-18 ) , E2F4 ( C-20 ) , E2F5 ( E-19 ) , and Cyclin A2 ( C-19 ) were purchased from Santa Cruz . Secondary antibodies coupled to horseradish peroxidase ( HRP ) were purchased from DakoCytomation or Jackson ImmunoResearch . Secondary antibodies coupled to Alexa-488 or Alexa-555 were from ThermoFischer . Cells grown in 6-well plates were infected at an MOI of 3 TCID50/cell . At 24 hpi , cells were lysed in a NP-40 buffer ( 50 mM Tris , 150 mM NaCl , 1% Nonidet P-40 , and Complete Mini protease inhibitor cocktail [Roche] ) . Insoluble material was removed by centrifugation . After preclearing with protein G Sepharose ( PGS , GE Healthcare ) , Flag-tagged M117 protein was precipitated with anti-Flag and PGS . Precipitates were washed 3 times with buffer 1 ( 1 mM Tris pH 7 . 6 , 150 mM NaCl , 2 mM EDTA , 0 . 2% NP-40 ) , 2 times with buffer 2 ( 1 mM Tris pH 7 . 6 , 500 mM NaCl , 2mM EDTA , 0 . 2% NP-40 ) and 1 time with buffer 3 ( 10mM Tris pH 7 . 6 ) , eluted by boiling in SDS-PAGE sample buffer ( 125 mM Tris pH 6 . 8 , 4% SDS , 20% glycerol , 10% β-mercaptoethanol , 0 . 002% bromophenol blue ) and subjected to SDS-PAGE and immunoblotting . For immunoblot analysis , cells were lysed in NP-40 buffer or in SDS-PAGE sample buffer . Equal amounts of protein ( NP-40 lysis ) or equal volumes ( sample buffer ) were subjected to SDS-PAGE followed by transfer to a nitrocellulose membrane ( Amersham ) . Proteins of interest were detected with protein-specific primary antibodies and HRP-coupled secondary antibodies by enhanced chemiluminescence ( Amersham ) supplemented with 10% of Lumigen TMA-6 ( Bioquote Limited ) . All immunoblots showed are representatives of 3 or more experiments , except for S2A and S4 Figs , which are representatives of 2 experiments . For stable isotope incorporation , cells were grown in DMEM ( high-glucose ) SILAC medium supplemented with 10% dialyzed FCS , 4 mM glutamine , 100 IU penicillin/100 μg streptomycin in the presence of either 13C6 , 15N2-lysine / 13C6 , 15N4-arginine ( SILAC heavy ) or unlabeled lysine / arginine ( SILAC light ) . All SILAC media were filtered before usage and stored at 4°C for up to 6 month . To ensure complete incorporation of SILAC amino acids ( ≥ 97% ) cells were grown for at least 5 passages in SILAC medium . For immunoprecipitation , two populations were generated , one grown in light and the other in heavy media . Either the light or the heavy labelled cells were infected with the HA-M117 , whereas the other labelled population was infected with the WT MCMV . After lysis in NP-40 buffer , HA tagged-M117 proteins were precipitated with rat anti-HA Affinity Matrix antibody ( clone 3F10 , Roche ) . Precipitates were washed 3 times with minimal washing buffer ( 50 mM Tris , 150 mM NaCl , 10% ( v/v ) glycerol , pH 7 . 5 ) and eluted by boiling in elution buffer ( 1% ( w/v ) SDS in 50 mM Tris , 150 mM NaCl , pH 7 . 5 ) . Afterwards , the samples were mixed in a light-to-heavy ratio of 1:1 for subsequent sample processing . Cysteines were reduced in the presence of 10 mM DTT at 56 °C for 30 min and alkylated using 20 mM IAA for 30 min at RT in the dark . Proteins were precipitated by diluting the samples 1:10 with ice-cold ethanol ( -40 °C ) and incubation at -40 °C for 1 h . Precipitated proteins were spun down at 20 , 000 x g at 4 °C for 40 min and the pellet was washed with 50 μl ice-cold acetone ( -40 °C ) . After 15 minutes of incubation at -40 °C proteins were spun down for 15 min at 20 , 000 x g and 4 °C . The sediment was solubilized in 7 . 5 μl 2 M guanidinium hydrochloride ( GuHCl ) and 10-fold diluted using 50 mM ABC and 1 mM CaCl2 . Proteins were digested by adding 5 μl of a 0 . 1 μg/μl trypsin solution ( Sigma-Aldrich T-1426 ) followed by incubation at 37°C for 12 . 5 h . The reaction was stopped by adding TFA to a final concentration of 1% . Samples were dried in a vacuum centrifuge , reconstituted in 0 . 1% TFA and subjected to LC-MS . NanoLC-MS/MS was conducted using a U3000 HPLC system online coupled to a Q Exactive HF ( both Thermo Scientific ) . Samples were loaded in 0 . 1% TFA on a C18 trap column ( HiChrom ACE , 100 μm x 2 cm , 5 μm particles ) and separated on a C18 main column ( HiChrom ACE , 75 μm x 30 cm , 5 μm particles ) using a 60 min linear gradient-program from 2 . 5% to 35% ACN in the presence of 0 . 1% FA at 60°C and a flow rate of 270 nL/min . The column effluent was introduced to the MS by nanoESI using a PicoTip emitter ( new objectives ) operated at 1 . 5 kV . The MS was operated in positive ion-mode using a top15 HCD data-dependant acquisition method with a resolution of 60 , 000 for MS and a resolution of 15 , 000 for MS/MS . The normalized collision energy was set to 27 and only ions with an assigned charge state of 2–4 were selected for fragmentation . Automatic gain control target values were set to 106 and 5x104 with maximum ion injection times of 120 and 250 ms for MS and MS/MS , respectively . The dynamic exclusion was set to 12 sec and the m/z = 371 . 10124 lock mass was used for internal calibration . A database search was done using Mascot v2 . 4 . 1 implemented in Proteome Discoverer v1 . 4 against a merged database comprising all Uniprot entries of Mus musculus and all Uniprot/TreEMBL entries of MCMV strain Smith and K181 ( January 2013 , 16 , 799 target sequences ) . The decoy search option was enabled and mass error tolerances were set to 10 ppm and 0 . 02 Da for MS and MS/MS . A maximum of 2 missed cleavages was allowed , Oxididation of Met and heavy labelled Arg/Lys was set as variable modification and carbamidomethylation of Cys was set as static modifications . Results were filtered for ≤ 1% FDR at the PSM level and feature quantification was done within a 2 ppm mass precision window using the precursor ion quantifier . PSM tables were exported and further processed with Microsoft Excel and R to calculate the number of unique peptides per protein in each condition and calculate median-normalized heavy/light ratios . Proteins identified with ≥ 2 unique peptides and a log2 ratio ≥ 3 ( 8-fold enrichment ) in both replicates were considered as potential M117 interaction partners . All the statistical analyses were performed with the GraphPad Prism 5 . 0 Software . A one-way ANOVA with Tukey’s multiple comparison post test was used for the analysis of the qPCR on genomic DNA . A two-way ANOVA with Bonferroni post test was used for the analysis of the luciferase reporter assays and qPCR on transcripts .
|
Human CMV is an opportunistic pathogen causing morbidity and mortality in immunocompromised individuals . It is a highly species-specific virus that replicates only in cells from humans or chimpanzees , but not in cells from mice or other laboratory animals . Mouse cytomegalovirus ( MCMV ) , the most commonly used model to study CMV pathogenesis in vivo , is also species-specific and does not replicate in human cells . However , the causes of the CMV host species specificity have remained largely unknown . Here we show that the viral M117 protein is a major factor contributing to the MCMV host species specificity . When M117 is inactivated , MCMV acquires the ability to replicate in human cells . We further demonstrate that M117 interacts with transcription factors of the E2F family and activates E2F-dependent gene expression . While this function is needed for MCMV dissemination in mice , it is detrimental for MCMV replication in human cells . The results of this study indicate that the host range of a virus , i . e . its ability to replicate in cells from different hosts , can depend on an appropriate regulation of transcription factors .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
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] |
2018
|
Activation of E2F-dependent transcription by the mouse cytomegalovirus M117 protein affects the viral host range
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Antiretroviral therapy , antibody and CD8+ T cell-mediated responses targeting human immunodeficiency virus-1 ( HIV-1 ) exert selection pressure on the virus necessitating escape; however , the ability of CD4+ T cells to exert selective pressure remains unclear . Using a computational approach on HIV gag/pol/nef sequences and HLA-II allelic data , we identified 29 HLA-II associated HIV sequence polymorphisms or adaptations ( HLA-AP ) in an African cohort of chronically HIV-infected individuals . Epitopes encompassing the predicted adaptation ( AE ) or its non-adapted ( NAE ) version were evaluated for immunogenicity . Using a CD8-depleted IFN-γ ELISpot assay , we determined that the magnitude of CD4+ T cell responses to the predicted epitopes in controllers was higher compared to non-controllers ( p<0 . 0001 ) . However , regardless of the group , the magnitude of responses to AE was lower as compared to NAE ( p<0 . 0001 ) . CD4+ T cell responses in patients with acute HIV infection ( AHI ) demonstrated poor immunogenicity towards AE as compared to NAE encoded by their transmitted founder virus . Longitudinal data in AHI off antiretroviral therapy demonstrated sequence changes that were biologically confirmed to represent CD4+ escape mutations . These data demonstrate an innovative application of HLA-associated polymorphisms to identify biologically relevant CD4+ epitopes and suggests CD4+ T cells are active participants in driving HIV evolution .
The human immunodeficiency virus-1 ( HIV-1 ) has the capacity to escape pressure exerted upon it by a number of factors including antiretroviral therapy ( ART ) , antibody and CD8+ T cells [1–4] . Escape implies a level of viral suppression sufficient to provide selection pressure for mutant genomes to emerge that are no longer sensitive . This has been clearly demonstrated with ART where combination therapy has been shown effective in controlling HIV [5] . HIV-specific CD8+ T cell and neutralizing antibody responses drive HIV escape and both have been demonstrated to be important in controlling HIV infection [4 , 6–8] . Conversely , other innate and adaptive immune responses have either not been shown to drive HIV escape or have been only demonstrated to infrequently drive the process calling into question the utility of such responses in overall viral control [9] . CD4+ T cell responses have previously been associated with viral sequence changes , but the scope and relevance of CD4+ T cells on viral control has remained unclear [10–12] . Recently , viral escape in response to CD4+ T cell responses was definitively demonstrated in the SIV model , suggesting the potential for CD4+ T cells to mediate HIV control [13] . As CD4+ T cells are the primary targets of HIV infection , their contribution to the adaptive immune response targeting HIV-1 has been relatively understudied . While the role of these cells in providing help to B and CD8+ T cells is well documented , a growing body of literature also implicates HIV-specific CD4+ T cells in exacting immunological control of HIV via direct antiviral effects [14–16] . This newly attributed function for CD4+ T cells should , if of sufficient efficacy , select for mutations that allow the virus to evade immune recognition . Using a cohort of HIV-1 subtype C chronically-infected individuals for whom the HIV sequences ( gag , pol and nef ) and HLA-II allelic data were derived , we identified amino acid changes occurring at the population level that were disproportionately associated with specific HLA-II alleles . These HLA class II-associated HIV polymorphisms ( HLA-AP ) were used to predict epitopes encompassing them . Based on this adaptation nomenclature , 2 groups of epitopes were generated: non-adapted epitopes ( NAE ) , epitopes without any evidence of HLA adaptation; and adapted epitopes ( AE ) , those containing an amino acid associated with adaptation to a specific HLA-II allele . NAE were demonstrated to be more immunogenic and with enhanced cytotoxic capabilities in eliminating HIV-pulsed targets . Furthermore , we temporally associated HIV-specific CD4+ T cell responses with the emergence of viral escape following acute HIV infection . Our findings demonstrate that HLA-AP can predict CD4+ T cell epitopes that escape and that this viral escape is more common than previously appreciated , suggesting a role for CD4+ T cell responses in HIV control .
Although HLA-I associated HIV polymorphisms have been used extensively to identify signatures of CD8+ T cell induced escape [17–20] , application of a similar methodology for HLA-II associations has not previously yielded any HIV-1 polymorphisms . Using sequences from HIV-1 gag , pol , and nef , and HLA-II allelic data from the Zambian cohort of 348 chronic HIV subtype C infected patients , HLA-II specific adaptations at the population level were identified computationally . The approach yielded 29 unique polymorphisms predicted to represent escape mutations in the context of a CD4+ T cell epitope ( Table 1 ) . Using the predicted class II polymorphisms , their respective HLA-II allele , and an in silico prediction algorithm [21] , we generated a panel of peptides containing potential CD4+ T cell epitopes . Epitopes containing a predicted polymorphism represent an adapted epitope or AE , while their non-adapted ( NAE ) counterpart contains an amino acid with no evidence of adaptation , frequently the consensus sequence ( S3 Table ) . Immunogenicity has not previously been defined for the predicted epitopes , and of the 29 unique prediction sites , 12 are entirely novel with no overlapping epitopes previously described ( www . hiv . lanl . gov , HIV Molecular Immunology Database ) . For the remaining 17 , partially overlapping epitopes , restricted by other HLA-II alleles , were reported . We tested the immunogenicity of these AE and NAE in a CD8-depleted IFN-γ ELISpot assay . Depletion of CD8+ cells prior to aliquoting cells was equally efficient when performed on PBMCs from both controller or non-controller donors . Thus , the number of CD4+ T cells placed in ELISpot wells was similar for all donors tested ( S1 Fig ) . We first tested pools of peptides containing the identified AE and NAE to screen for responses in 10 HIV seronegative ( SN ) donors , 14 chronic HIV-infected ( CHI ) patients with viral loads >10 , 000 copies ( Non-Controllers , NC ) , and 14 CHI patients with viral load <2 , 000 copies ( Controllers , C ) ( Tables 2 and S1 ) . Although there were differences in the HLA-II alleles represented in the controllers and non-controllers , this did not reach statistical significance . Initial screening demonstrated HIV-specific CD4+ T cell responses to these peptide pools in CHI patients . The magnitude of response by controllers was significantly greater as compared to both seronegative controls and non-controllers ( Fig 1A ) . We observed each predicted CD4+ epitope to be immunogenic in at least one tested individual . Among controllers , we detected a response to each of the 29 tested epitopes; in contrast , we were only able to detect responses to 13 ( 45% ) of the epitopes among all non-controllers ( Fig 1B ) . A total of 8 patients ( 5/14 controllers and 3/14 non-controllers ) had a confirmed mapped response to at least one tested epitope . For 43% of the mapped responses , the donor had the predicted HLA-II allele , whereas the remaining 57% of the time , the donor had a positive response despite not having the predicted allele . To evaluate the accuracy of the predicted epitopes and their associated HLA-II alleles , we sought to confirm that at least some of the observed positive responses were presented to the CD4+ T cells by their computationally predicted HLA-II alleles . To do so , we used single HLA-II allele transfected RM3 cell lines as antigen presenting cells ( APC ) and in vitro expanded CD4+ T cell lines as effectors [22 , 23] . CD8-depleted PBMCs from two donors previously identified to have a positive ex vivo response were expanded and then exposed to peptide-pulsed APC expressing either the HLA-II allele associated with the adapted polymorphism or a mismatched allele . In these cases ( S2 Fig ) , the predicted HLA-II restriction was shown to match the relevant allele of the APC , as the highest magnitude IFN-γ ELISpot response was detected when the peptide was presented by an RM3 cell line expressing the polymorphism-associated HLA-II allele . We next investigated differences in immunogenicity between adapted and non-adapted epitopes . Each identified polymorphism represents a prediction of HLA-II-mediated immune pressure at a single amino acid . Based on this , we hypothesized reduced immunogenicity for AE as compared to NAE . We compared the magnitude of positive IFN-γ responses from the ELISpot assays for NAE/AE pairs from CD8-depleted PBMC taken from 8 chronically-infected donors . Of the 70 pairs tested , 49 responses were found to have a reduced AE magnitude as compared to the observed NAE response ( p<0 . 0001 by Wilcoxon ranked pairs ) ( Fig 2A ) . The finding that the NAE induced a higher magnitude of responses compared to their AE counterparts can be explained by at least two different scenarios . First , as it is well known that autologous viral sequences are better at eliciting T-cell responses [24] , the limited AE immunogenicity could reflect chronically-infected individuals having virus encoding a predominance of NAE . An alternative explanation is that AE are the result of host immune pressure on NAE epitopes and subsequent viral escape . To explore these alternatives , we performed population viral sequencing , determining the dominant form of the virus in the 5 CHI individuals who demonstrated responses to the predicted epitopes and for whom plasma/PBMC samples were available ( 2 controllers and 3 non-controllers , S4 Table ) . We determined whether the dominant autologous viral sequence matched the NAE or AE at the amino acid from the identified polymorphic site ( Fig 2B ) . The highest frequency of responses ( 71% ) was observed in patients whose autologous sequence matched the non-adapted form and who were subsequently stimulated with NAE ( p = 0 . 04 compared to AE ) . Conversely , in 5/23 cases ( 22% ) where the dominant viral quasispecies encoded the AE form , NAE was found to be immunogenic , which was not significantly different from the immunogenicity of the matching AE ( 10/23 or 43% ) . Prior work has shown CD8+ T-cell mediated antigen sensitivity ( functional avidity ) is a reliable predictor of viral control [25 , 26] . To determine whether this was also evident in epitope-specific CD4+ T cells , we determined the antigen sensitivity of immunogenic NAE and AE where the epitope sequence matched the dominant viral species present in the respective patients . We tested CD8-depleted PBMCs from five different patients with 6 NAE/AE responding pairs of peptides . The functional avidity did not significantly differ between NAE and AE , with a higher NAE magnitude observed only at the lowest 10−7 M peptide concentration tested ( S3 Fig ) . Since polyfunctional CD4+ T cells , especially those making granzyme A , have been implicated in viral control [27] , we next evaluated the functionality of antigen-specific CD4+ T cells using multiparametric flow . PBMCs from 4 CHI patients were stimulated ex vivo and evaluated in an intracellular cytokine staining assay . We observed similar up regulation of cytokines and cytotoxic factors by CD4+ T cells for both NAE and AE specific responses ( S4 Fig ) . We next wanted to assess whether both NAE and AE-specific CD4+ T cells can effectively kill HIV targets . Autologous as well as HLA-II mismatched CD4+ T cell targets ( as a negative control ) were pulsed with either NAE or AE peptide and then co-cultured with the respective NAE or AE effector cells . Using a 7-AAD assay , we observed higher CD4-mediated killing of autologous NAE-pulsed targets , relative to HLA-II mismatched targets , but killing of AE-pulsed targets was significantly impaired ( Fig 2C ) . A limitation to studies in chronically-infected HIV patients is that they harbor highly heterogeneous HIV-1 variants . Therefore , it is not possible to ascertain whether an immune response reflects a de novo response elicited by that epitope or cross presentation of an epitope variant . To accurately identify epitope-induced responses , we used single genome amplification technique [28–30] to obtain transmitted founder virus ( TFV ) sequences from the plasma of 11 clade B acutely infected patients ( Fiebig stages I-III , S2 Table ) . Taking into consideration each donor’s HLA-II alleles , we determined the number of NAE and AE encoded by TFV that established infection in each acute patient ( number of encoded NAE and AE for a representative patient is shown in S5 Table ) . While the number of transmitted NAE and AE varied from individual to individual ( range of 2–10 for NAE , 2–7 for AE ) , the median numbers encoded by the TFV per infected individual were similar ( Fig 3A ) , indicating that transmission of CD4+ AE variants is relatively common . Overall , in these 11 patients , we identified 52 and 53 predicted NAE and AE , respectively , encoded in the TFV . After stimulating each patient’s PBMC with the appropriate TFV-encoded epitopes ( NAE or AE ) in an IFN-γ ELISPOT assay , only 1/53 AE peptide elicited an immune response versus 9/52 NAE specific responses ( p = 0 . 008 ) ( Fig 3B ) . Each predicted polymorphism represents a possible CD4+ T-cell escape mutation , as AE are poorly immunogenic even when encoded by the TFV . The presence of AE in the TFV , therefore , possibly represents CD4+ T cell epitopes that have escaped in a prior host . We next analyzed longitudinal sequence data from two distinct acute infection cohorts to look for evidence of longitudinal HIV sequence changes based on HLA-II associated HIV-1 polymorphisms . As shown in Fig 4A , we observed 9 changes reflective of escape and 14 of reversion among the 99 patients in these cohorts . In each of the 5 patients , where longitudinal viral load data ( pre and post escape ) were available , there was a non-significant increase in viral load at the time point immediately following escape ( mean VL increase of 72 , 675 copies , SEM = 36 , 337 , p = 0 . 06; Fig 4B ) , as compared to the time point preceding escape . Further analysis revealed no evidence of viral sequence changes at known CD8 polymorphic sites at these time points for each of the 5 donors reported and their respective repertoire of HLA-I alleles . We next looked for biologic evidence of viral escape . Limited access to samples and diminished CD4+ T cell responses in cryopreserved specimens restricted these studies [31]; however , we identified samples from time points with evidence of viral escape at predicted polymorphic sites and tested CD8-depleted PBMCs for immunogenicity to the NAE and AE in 6 patients . We found biologic evidence of viral escape in 3 of these 6 donors , with 2 instances at the Pol 68 epitope ( Fig 4C ) and one at the Pol 161 epitope ( Fig 4D ) . Based upon TFV sequence data , each individual was determined to have been infected with the NAE form at the polymorphic site before the AE became the dominant sequence at a later time point . In each case , NAE stimulation elicited a response from CD8-depleted PBMCs prior to the predicted escape . In AH-1 , a robust ELISpot response to the NAE was observed immediately prior to viral escape at the 18-month time point; no response to the AE was observed . For this patient , samples from later time points were not available . In AH-2 , a modest ELISpot response to the NAE was observed immediately prior to escape at the 9-month time point . At the subsequent 12-month collection time , the NAE response was lost; a response to AE at either time point was not observed . In AH-3 ( Fig 4D ) , initial ELISpot screening was negative for the NAE and AE at time points 12 , 18 and 21 months , however cultured ELISpot revealed evidence of the NAE but not AE response prior to viral escape at 18 months . This response was lost at the 21-month time point .
HIV-specific CD4+ T cells have been relatively understudied compared to other arms of the adapted immune response . Prior studies of HIV pathogenesis identified an association between preserved CD4+ T cell function and improved clinical progression [32] , but a lingering question has been whether the observed CD4+ T cell function simply reflects immune preservation or that this cell population influences viral immune control . Recent studies have demonstrated HIV-specific CD4+ T cell responses correlate with viral control [27] as has been demonstrated with CD8+ T cells in the past [33 , 34] . Furthermore , emerging data indicate that HIV-specific CD4+ T cells with cytolytic potential are especially important in early viral control [35] . These works suggest that CD4+ T cells should force HIV escape mutations similar to what has been extensively observed for both CD8+ T cells and neutralizing antibodies . However , prior studies have suggested that CD4+ T cells exert only limited selective pressure on HIV [12 , 36–38] . Definitive CD4+ T cell escape has been reported in SIV , but this was only described in a single rhesus macaque at a single epitope [13] . Here we demonstrate multiple lines of evidence for HIV escape from CD4+ T cell responses . Similar to HLA-I associated HIV polymorphisms , HLA-II associations were used to predict 29 sites representing viral evolution . While we did not formally demonstrate that each of these predictions represented an escape , it is interesting that every one of the predicted epitopes was found to be immunogenic . Furthermore , non-escaped epitopes or NAE were more immunogenic than AE in chronic infection , a finding not explained by preferential infection by viruses encoding NAE . Moreover , AE were poorly immunogenic in acute HIV infection where limited viral diversity of the TFV ensures the identity of the epitope eliciting the observed immune response as either NAE or AE . Finally , in 2 cohorts of acutely infected patients followed off ART for 2 years , we see evidence for CD4+ escape and temporally associate three of these responses with subsequent escape . Interestingly , several of the polymorphisms identified in this study reverted following infection into hosts no longer able to target the epitope , suggesting CD4+ T cell-induced escapes impose a viral fitness cost as has been demonstrated extensively for CD8+ T cells . This observation is consistent with HLA-I-restricted escape in which protective alleles drive escape associations at more sites and with larger effect sizes , suggesting a model in which the presence of detectable selection pressure corresponds to effective CD8 or CD4-mediated killing [18] . In sum our data provide strong evidence for CD4+ T cell responses influencing viral evolution . Despite the fact that HIV escapes from CD8+ T cells , neutralizing antibodies , and even NK cells [1–4 , 6 , 39] , it is interesting that escape from CD4+ T cells has been much more difficult to document [10–12] . This may be partially attributable to the prominence of CD8+ T cell escape , thus making it difficult to separate the effect of this immune response from those induced by CD4+ T cells . Our findings suggest CD4-mediated escape happens on a larger scale than previously appreciated , although it is unlikely to be as prevalent as CD8-mediated escape . Another difficulty in defining HLA-II polymorphisms is that HLA class II alleles bind epitopes much more promiscuously compared to HLA-I , making it more difficult to assign the polymorphism to a specific HLA-II allele . In patients with chronic infection , we mapped positive responses in donors that had the model predicted HLA-II allele , but also observed responses in donors that did not have the predicted allele . In light of the promiscuity of HLA-II binding , it is not surprising that HLA-II alleles other than those predicted by the model presented here can also present the epitopes of interest . The promiscuous response of HLA-II alleles is almost certainly influencing HIV at polymorphic sites other than those predicted by this particular model , but these changes are obfuscated by the contribution of multiple alleles . Nevertheless , the observation of compromised immunogenicity of AE in the setting of acute infection was restricted to studies of donors expressing the predicted HLA-II alleles , thereby strengthening the likelihood that HLA-II associated HIV polymorphisms predict escape from CD4 T cells . The predictions were based on HIV ( gag , pol , and nef ) and HLA-II sequences in 348 Zambians with chronic HIV infection , and it seems likely that further polymorphisms can be identified by studying more individuals and additional HIV proteins [18–20 , 40 , 41] . Our findings convincingly demonstrate both that CD4+ T cells respond to the predicted panel of polymorphic epitopes , and viral sequence change to the adapted form compromises this response . Nevertheless , CD8+ T cell responses are highly prevalent in HIV infection , so to address the possibility that CD8 responses may be driving viral escape we looked for CD8+ T cell responses to peptides yielding positive CD4+ T cell responses in a flow-based assay . In 7 unique donors we tested 19 peptides and observed CD4+ but not CD8+ T cell responses to the peptides . We also noted that none of the HLA-II alleles for which we observed polymorphisms were in significant linkage disequilibrium with HLA-I alleles . The one exception was that DQB1*06 is in negative linkage with HLA-B*57 , yet both are associated with a p24 polymorphism at position 247 ( S6 Table ) . Indeed , the one individual who had a response to the predicted CD4 epitope was DQB1*06 positive and HLA-B*57 negative . These findings speak to the possibility that multiple immune parameters ( in this case both CD4+ and CD8+ T cells ) are driving viral evolution independently and further solidify our results . Although the HLA-AP presented here were derived from a clade C infected African cohort , their immunogenicity was evaluated in both clade B and C infected samples . The consistent immunogenicity across clades suggests the predicted CD4 epitopes are shared to some extent in HIV-1 infection by different subtypes . Similar to HLA-I associated escape , site-specific viral escape may be maintained across clades [42] . Genome-wide association study ( GWAS ) has previously failed to identify HLA-II alleles that are associated with viral control , which may reflect the promiscuity of antigen presentation . Furthermore , unlike HLA-I alleles that encode a single heavy chain responsible for peptide loading and interaction with TCR , HLA-II must function as a heterodimer consisting of an alpha and beta chains . Association analyses facilitated by GWAS only assess one polymorphism at a time without testing their combinations; the ability of such an approach to accurately capture HLA allelic function is much less accurate for HLA-II alleles [43] . Prior work implicated gag-specific CD4+ responses as most relevant to viral control [27 , 44] , whereas our predictions had limited associations within Gag . A prior investigation did attempt to identify HLA-II polymorphisms using a cohort approach [38] . This analysis was done in Gag-Protease and used a similar but distinct computational method [42] . By applying a revised method [18] and extending our analysis to the rest of Pol and Nef , we identified a number of polymorphisms that were then tested biologically for validity . The majority of our predictions were outside of Gag , which would not have been picked up in this prior analysis . An important question arising from these studies concerns whether HIV-specific CD4+ T cells are playing a role in viral control . The fact that they are pressuring the virus to mutate to avoid CD4 responses certainly suggests that they do contribute to this process , albeit at a magnitude that is likely much less than CD8 responses . Furthermore , our findings demonstrate the ability of HIV-specific CD4+ T cells to induce viral escape and suggest that such escapes are not rare events . These results should serve as a springboard for future research to definitively determine the role of HIV-specific CD4+ T cells in viral control .
Chronic and acutely-infected individuals from Zambia provided written , informed consent to the Zambia University Teaching Hospital ethics committee and the Emory University institutional review board ( IRB ) prior to collection of information . Additional patients were recruited from the University of Alabama at Birmingham Adult AIDS 1917 clinic after obtaining written , informed consent and approval from the IRB at UAB . A cohort of 348 Zambian individuals chronically infected with HIV-1 subtype C had the gag , pol , and nef gene viral sequences determined by population sequencing . Virus from an additional 81 acutely infected individuals from the Zambian cohort was sequenced longitudinally and PBMC from five of these HIV-1 subtype C-acutely infected ART naïve Zambian patients were used in this study . These patients were recruited at the Zambia-Emory HIV Research Project ( ZEHRP ) in Lusaka , Zambia into the ZEHRP heterosexual transmission discordant couple cohort and the International AIDS Vaccine Initiative ( IAVI ) Protocol C; informed consent was obtained from all patients . HIV sequences were also obtained from 18 subtype-C acutely infected patients from the CHAVI cohort [29] . For the IAVI cohort , the earliest viral sequences were obtained approximately 1–2 weeks post-infection . For the Zambian cohort , the first sequences were obtained approximately 3 months post infection . Both cohorts are heterogeneous with regards to when escape or reversion occurred , as that is different for each individual . Escape was noted to occur as early as two weeks or as late as 24 months post infection; reversion occurred as early as 6 months or as late as 24 months post infection . Cryopreserved PBMC samples from ART naïve HIV-1 clade B chronically infected patients ( N = 28 ) ( S1 Table ) and acutely infected patients ( N = 11 ) ( S2 Table ) were used in this study . The chronic cohort included HIV controllers ( n = 14 , VL <2 , 000 copies/mL ) and HIV non-controllers ( n = 14 , VL >10 , 000 copies/mL ) ; both off ART . Details on the demographics and clinical features of these chronically infected individuals are shown in Tables 2 and S1 . Acute HIV infection was stratified by the Fiebig staging . Healthy HIV seronegative donors ( N = 10 ) from the Alabama Vaccine Research Clinic were used as controls . High-resolution ( 4-digit ) genotyping data for the Zambian cohort came from earlier work [43] . For additional genotyping , we applied two molecular techniques to define HLA-DRB1 and HLA-DQB1 alleles in local patients . The procedures for sequencing-based typing ( Abbott Molecular Inc . , Des Plaines , IL ) and automated DNA hybridization with oligonucleotide probes ( Innogenetics Inc . , Alpharetta , GA ) have been described elsewhere [45 , 46] . Assignment of 2-locus haplotypes was based on known patterns of linkage disequilibrium in African American and European American populations . We identified HIV polymorphisms in HIV gag , pol , and nef that were statistically enriched in 348 chronically clade C infected , antiretroviral-naïve Zambian individuals expressing specific HLA-II alleles . We then performed phylogenetically corrected logistic regression as implemented in the PhyloD software [42] . This approach takes as input a protein-specific phylogenetic tree ( as inferred by Phyml 3 . 0 [47] ) , HIV sequences , and putative predictor variables . Separate phylogenetically corrected logistic regression models are inferred for each amino acid at each site , using forward selection to select features and computing p-values using likelihood ratio tests . Overall significance is reported as q-values , which estimate the false discovery rate associated with each p-value [48]; q<0 . 2 was chosen as a threshold for experimental follow up . Only features ( amino acids at a given site , class I and class II alleles , at 2- and 4-digit resolution ) that were observed in at least 3 ( and at most N = 3 ) individuals were considered . Our initial application of PhyloD closely followed previously published applications [18] , with the exception that both class I and class II alleles were included as predictor variables . This approach yielded seven sites for which at least one amino acid was positively or negative associated with at least one HLA-II allele , called a “class-II-associated site” . An important caveat to this approach is that amino acid mixtures present a problem to logistic regression . Typically , PhyloD treats mixtures as uncertain observations by creating equally weighted fractional observations . However , HIV mixtures may represent positive evidence for incomplete selection . We therefore ran a second analysis in which all mixture amino acids were treated as positive observations of polymorphic amino acids . This analysis resulted in 16 class-II-associated sites . Although some of these sites overlapped with the initial eight sites , the specific alleles and amino acids differed , perhaps indicating different intensities of selection pressure . Finally , we reasoned that class I alleles may serve as the dominant source of selection pressure for most sites . We therefore reran the analysis ( treating mixtures as noisy observations , as in the first analysis ) such that forward selection preferentially added class I alleles and co-varying amino acids . Specifically , class I alleles and co-varying amino acids were greedily added to the model using a threshold of p<0 . 05 . Class II alleles were considered only when no other amino acid or class I allele significantly improved model fit . This analysis resulted in nine class-II-associated sites , again with little overlap with the previous two analyses . Our overall analysis yielded 29 unique sites . Because our aim in these statistical analyses was to guide experiments , we chose to follow up with all 29 class-II-associated sites that resulted from these three approaches . Using the consensus clade-B sequence , a 31 amino acid sequence was selected ( 15 amino acids upstream/downstream of the polymorphism ) . This sequence was then input into the Net MHCII prediction software ( http://www . cbs . dtu . dk/services/NetMHCIIpan ) . Using the class-II allele associated with each unique polymorphism , a 20-mer amino acid sequence with the highest HLA-II binding affinity ( IC50 < 500 nM ) was selected for synthesis and immunogenicity testing . These polymorphism containing epitopes are henceforth referred to as adapted epitopes or AE . For each predicted adapted epitope , a corresponding consensus peptide ( non-adapted epitope or NAE ) was also synthesized . In those cases where the predicted adaptation mirrored the consensus , the next most common form of clade-B amino acid residue occurring at the polymorphic site was defined as the non-adapted form . This resulted in a panel of 70 total peptides that were used to assess CD4+ T-cell reactivity . For the initial response screening , the peptides were grouped into 17 pools with 4–5 peptides per pool . Peptides encompassing the predicted CD4+ T cell epitopes and the identified amino acid polymorphisms were synthesized by New England Peptide ( NEP ) in a 96-array format and were reconstituted at 40mM in dimethyl sulfoxide and stored at -70°C until use . A modified ELISPOT assay was performed as previously described [23 , 27] . Briefly , nitrocellulose plates were coated with anti-IFN-γ antibody overnight . The next day , PBMC were CD8-depleted using magnetic beads ( Dynabeads CD8 , Invitrogen ) , and the enriched CD4+ T cells were plated at 100 , 000 cells/well and were stimulated with the appropriate peptide pool or single peptide at a final concentration of 10uM for 40h at 37°C and 5% CO2 . The cells were washed , and biotinylated anti-IFN-γ antibody was added to the plate for 2 hrs . After this incubation , streptavidin-alkaline phosphatase was added for 1hr before applying BCIP/NBT substrate for spot detection . The number of IFN-γ responses were enumerated using an ELISPOT plate reader ( CTL S6 Ultra-V Analyzer ) and the data normalized to Spot Forming Cells per million ( SFC/106 ) . A positive response was defined as 50 SFC/106 PBMCs or greater and at least 2 . 5 times background ( unstimulated media only wells ) . Phytohemagglutinin ( PHA ) was used as a positive control . In certain cases where no detectable ex vivo response was apparent , CD8-depleted PBMCs were cultured in the presence of peptide ( 10uM ) , IL-7 ( 25ng/ml ) and IL-2 ( 50IU/ml ) for 7–10 days . Expanded antigen specific cells were then re-stimulated with peptide in an IFN-γ ELISpot assay as described above . To determine avidity , four 10-fold serial dilutions of peptides were used in an IFN-γ ELISPOT assay as described above . Antigen sensitivity was determined by the peptide concentration that elicited 50% of maximal IFN-γ response ( EC50 ) for any given epitope . Flow cytometry based ICS assay was done as previously described [35 , 49 , 50] . In brief , 106 PBMCs were pulsed with peptide at 10uM in the presence of co-stimulatory antibodies ( anti-CD28 and anti-CD49D ) and anti-CD107a-FITC ( all from BD Biosciences ) for 2 hrs at 37°C . Monensin and brefeldin A ( both from BD Biosciences ) were then added and the cultures incubated for an additional 12 hrs . Next day , the cells were labeled with LIVE/DEAD cell dye ( Invitrogen ) and surface stained with anti-CD3-Pac Blue , anti-CD8-V500 , and anti-CD4-Alexa 780 ( both from BD Biosciences ) . The cells were permeabilized and labeled with anti-IFN-γ-Alexa 700 , anti-IL-2-APC , anti-TNFα-PECy7 , and anti-Granzyme A-PE ( all from BD Biosciences ) . CD3 events greater than 100 , 000 were acquired on an LSR II ( BD Immunocytometry Systems ) , and data were analyzed using FlowJo ( version 9 . 6 . 4; TreeStar ) . Polyfunctionality analysis was performed using Boolean gating and SPICE and Pestle software ( version 5 . 1; NIAID ) . HLA-II restriction assay was done essentially as described before [22 , 23] . In-vitro expanded CD4+ T cell lines were used as effectors and peptide pulsed RM3 cell line transfectants were used as antigen presenting cells ( APC ) . In brief , CD8-depleted CD4+ T cells were cultured in the presence of IL-7 ( 5ng/ml ) , nevirapine ( 1ug/ml ) , IL-2 ( 50IU/mL ) and peptide ( 5uM ) for 14 days . The RM3 cell lines were propagated , pulsed with peptide ( 10uM ) for 3 hrs and then washed thoroughly to get rid of excess peptide . The effectors ( expanded CD4+ T cells ) and the targets ( peptide pulsed RM3 cell lines ) were plated at 50 , 000 and 100 , 000 cells/well , respectively ( i . e . 1:2 E/T ratio in an ELISPOT assay ) . The culture was then incubated for 24 hrs at 37°C and 5% CO2 . We used HLA-II expressing RM3 cell lines relevant to the patient’s HLA-II allele and determined the IFN-γ production when these lines were either not pulsed or pulsed with a peptide that a ) elicited a response previously and b ) was predicted to be restricted by the same HLA-II as the HLA-II transfected cell line that was used as APC . We used two negative controls: an HLA-II mismatched irrelevant peptide and a cell line that did not express any of the patient’s HLA-II alleles . Viral RNA and genomic DNA were extracted from plasma ( 3 CHI donors ) or PBMC ( 2 CHI donors ) by using the QIAamp RNA and DNA mini kits ( Qiagen , Valencia , CA ) , and cDNA synthesis was carried out using Superscript III ( Invitrogen ) . Reverse transcription of extracted RNA was performed , in two stages: in the 1st stage incubation was set at 50°C with 5U of reverse transcriptase ( RT ) for 1 hour in the presence of 0 . 5 mM of each dNTP , 5 mM DTT , 2U/μl RNaseOUT ( RNase inhibitor ) , and 0 . 25 mM antisense primer; the 2nd stage involved incubation at 55°C with an additional 5U of RT for 2 hours . Synthesis was initiated by reverse primer: 5’-ACTACTTAGAGCACTCAAGGCAAGCTTTATTG-3’ [51] and terminated by incubation at 70°C for 15 min , followed by 20 min at 37°C with 1μl RNase H . The cDNA was used immediately for near full-length HIV-1 PCR amplification . Full-length HIV-1 genome amplification used forward primer 1 . U5Cc—HXB2 positions 538–571–5’-CCTTGAGTGCTCTAAGTAGTGTGTGCCCGTCTGT-3’ , and reverse primer 1 . 3’3’PlCb at HXB2 positions 9611–9642–5’-ACTACTTAGAGCACTCAAGGCAAGCTTTATTG-3’; the 2nd round primers were: Forward primer 2 . U5Cd at HXB2 positions 552–581–5’-AGTAGTGTGTGCCCGTCTGTTGTGTGACTC-3’ and reverse primer 2 . 3’3’plCb at HXB2 positions 9604–9636–5’-TAGAGCACTCAAGGCAAGCTTTATTGAGG-3’ [51] . PCR reactions were carried out by using the Q5 High-Fidelity DNA Polymerase ( New England BioLabs , Catalog# M0491 ) with final concentration of 1X 5X Q5 Reaction Buffer , 1X 5X Q5 High GC Enhancer , 200μM dNTPs , 0 . 5μM forward and reverse primers , and 0 . 02 U/ul Q5 DNA Polymerase . After initial 45 seconds of denaturing at 98°C , 30 cycles at 2-step temperatures involving 15 seconds denaturing at 98°C and 8 minutes annealing + extension at 72°C were done to carry out the entire amplification . The final PCR product was stabilized at 72°C for 10 minutes and incubated at 4°C until analysis . The entire ~9kb PCR fragments were sequenced using Pacific Biosciences SMRT Sequencing Technology and DNA Library was built by using SMRTbell Template Preparation Reagent Kits 1 . 0 with 3ug purified ( Promega Wizard® SV Gel and PCR clean-up System ) PCR product that contains 28 near full-length PCR reactions , which were derived from plasma or PBMC from all 5 patients . The library was examined by 2100 Bioanalyzer for purity and concentration . SMRT sequencing was carried out using the P4C2 chemistry with 1x120min acquisition mode on the PacBio RS according to standard protocol [52 , 53] . Data was analyzed using an in-house developed computational code . The final product yielded 19 ( median 5 ) near full-length HIV-1 genomes . Gene sequences for the above chronic donors have been submitted to GenBank , serial numbers pending . Acute sequences have either previously been reported [54] , or have pending serial numbers . 7-AAD assay was performed according to a modified protocol based on a prior study [55] . PBMCs from autologous or complete HLA-II mismatched HIV seropositive donors were used as target cells . CD4+ T cells were isolated from the PBMCs by CD8-depletion ( Dynabeads CD8 , Invitrogen ) and activated with PHA ( 5μg/mL ) in the presence of IL-2 ( 100IU/mL ) for 2 days . Similar to prior studies [56] , activated CD4 targets ( 1x105 cells ) were CFSE-labeled and were pulsed with the relevant HIV-1 NAE or AE peptide at 10uM for 1h before co-culturing with the appropriate NAE or AE-specific CD4+ T-cell line for 24 hrs at various E/T ratios ( 0:1 , 0 . 5:1 , 1:1 , and 1 . 5:1 ) . After incubation , the cells were surface stained with anti-CD3-Pac Blue ( BD Biosciences ) and anti-CD4-Alexa780 ( eBioscience ) before washing and staining with 0 . 25ug of 7-AAD ( BD Biosciences ) for 20 min at 4°C . Using flow cytometry , antigen-specific killing was determined by comparing the percentage of 7-AAD+ CD4 T cells in the presence of effector CD4 line relative to that in the absence of effector line ( S5 Fig ) . Statistical tests were carried out using Fisher’s exact test , paired t-test , and nonparametric Mann-Whitney U . GraphPad Prism software ( version 5 . 0 ) was used to perform these analyses . A p value of <0 . 05 was considered statistically significant .
|
In HIV , CD4+ T cells are best known as the primary targets of infection . Although emerging data has suggested a more active role in viral pathogenesis , the CD4+ T cell population remains relatively understudied . Using a novel computational approach , we predicted 29 different epitopes with mutations that potentially represent escape from CD4+ T cell responses . The predicted escaped epitopes were found to be less immunogenic than the wild type forms , suggesting that the identified escapes allow HIV to reduce its visibility to the immune system . Using longitudinal samples , we were able to show CD4+ T cells driving viral escape following acute infection . Overall , these findings significantly expand our knowledge of how CD4+ T cells can exert HIV control and influence HIV evolution , providing important implications to future vaccine development strategies .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
HLA Class-II Associated HIV Polymorphisms Predict Escape from CD4+ T Cell Responses
|
Rift Valley fever ( RVF ) is a severe mosquito-borne disease affecting humans and domestic ruminants . Mosquito saliva contains compounds that counteract the hemostatic , inflammatory , and immune responses of the host . Modulation of these defensive responses may facilitate virus infection . Indeed , Aedes mosquito saliva played a crucial role in the vector's capacity to effectively transfer arboviruses such as the Cache Valley and West Nile viruses . The role of mosquito saliva in the transmission of Rift Valley fever virus ( RVFV ) has not been investigated . Using a murine model , we explored the potential for mosquitoes to impact the course of RVF disease by determining whether differences in pathogenesis occurred in the presence or absence of mosquito saliva and salivary gland extract . C57BL/6NRJ male mice were infected with the ZH548 strain of RVFV via intraperitoneal or intradermal route , or via bites from RVFV-exposed mosquitoes . The virus titers in mosquitoes and mouse organs were determined by plaque assays . After intraperitoneal injection , RVFV infection primarily resulted in liver damage . In contrast , RVFV infection via intradermal injection caused both liver and neurological symptoms and this route best mimicked the natural infection by mosquitoes . Co-injections of RVFV with salivary gland extract or saliva via intradermal route increased the mortality rates of mice , as well as the virus titers measured in several organs and in the blood . Furthermore , the blood cell counts of infected mice were altered compared to those of uninfected mice . Different routes of infection determine the pattern in which the virus spreads and the organs it targets . Aedes saliva significantly increases the pathogenicity of RVFV .
Rift Valley fever virus ( RVFV ) is a zoonotic mosquito-borne virus which causes epizootics and associated human epidemics throughout Africa [1] , [2] . First identified in Kenya in 1931 [3] , RVFV is now considered an endemic zoonotic agent in sub-Saharan Africa causing explosive outbreaks in animals and humans . It has been observed in Egypt , Mauritania , and the Arabic Peninsula [4] , [5] , [6] . The manifestation of severe RVF disease in humans is variable . Humans may develop a wide range of clinical signs including hepatitis , retinitis , and delayed-onset encephalitis and , in the most severe cases , haemorrhagic disease . The overall case fatality ratio is estimated to be between 0 . 5% and 2% [7] , [8] , [9] . In Yemen and Saudi Arabia , a RVFV outbreak resulted in approximately 2 , 000 human infections and 250 deaths ( CDC 2000 ) . A study of the RVFV epidemic in Saudi Arabia reported a high incidence of neurological manifestations ( 17 . 1% ) in infected individuals [7] . Mosquito bites were reported to play an important role in the transmission of the disease during this outbreak . RVFV belongs to the genus Phlebovirus in the family Bunyaviridae . Its tripartite negative-strand RNA genome is composed of a large segment ( L ) that encodes the L protein , which is the viral RNA-dependent RNA polymerase; a medium segment ( M ) that encodes a single open reading frame ( ORF ) generating the NSm , G1 ( Gc ) and G2 ( Gn ) proteins and a small segment ( S ) that encodes the nucleocapsid protein ( N ) and a nonstructural protein ( NSs ) using an ambisense strategy [10] . NSs was shown to suppress interferon induction ( Billecocq et al . , 2004 ) . RVFV can be transmitted to vertebrates by several species of mosquitoes such as Aedes spp . and Culex spp . Human infections typically occur through bites from infected mosquitoes , through percutaneous/aerosol exposure during the slaughter of infected animals , or via contact with aborted fetal materials . Transmission efficiency depends on the ability of the virus to cross the various barriers in the vector [11] . Therefore , after a mosquito takes a blood meal from an infected individual , the ingested virus passes into the midgut of the mosquito where it replicates before infecting different organs in the mosquito . At the end of the extrinsic incubation period in the vector , salivary glands are infected and the virus is transmitted by saliva during a blood meal . The reproductive system of the mosquito is also infected and transovarial transmission is important for long term maintenance of the virus [12] . Worldwide RVFV is considered as a potential biological weapon . Both modified live attenuated virus and inactivated virus vaccines have been developed for veterinary use , but there are currently no commercially available vaccines for humans . During a blood meal , insects are subject to defensive responses from the vertebrate , including hemostasis and the immune response . In this context , the saliva injected by the mosquito plays multiple roles . Indeed , saliva proteins have angiogenic , anti-hemostatic , anti-inflammatory and immunomodulatory properties [13] . The various properties of the saliva proteins towards the host immune response affect the pathogen transmission . In some cases , co-injection of virus and saliva potentiates viral infection of the vertebrate [14] , [15] , [16] , [17] . In other cases , pre-exposure to saliva generates enhances mortality from subsequent viral infection via mosquito bite [18] . A longer viremia was observed in deer and chipmunks infected by mosquito bite containing La Crosse virus , another member of the Bunyaviridae family , compared to syringe injection [19] . Potentiation of infection by mosquito saliva was also demonstrated for Cache Valley virus , an orthobunyavirus that also belongs to the Bunyaviridae family [14] . These observations raise the question of whether RVFV infection is also potentiated by mosquito saliva . Since RVFV is also transmitted by blood and aerosols , the context for its transmission differs from those of other viruses studied previously . In this project , our objective was to evaluate the role of Aedes mosquito saliva in the natural transmission of RVFV . For this purpose , we make use of an animal model that allowed us to study the pathogenesis of RVFV infection . We evaluated two different routes of infection: the intraperitoneal route , which has been utilized in most previous studies of RVFV pathogenesis , and the intradermal route , which mimics the mosquito bite . We also used non-infected and RVFV-infected mosquitoes to evaluate the role of saliva in the progression of the disease . Importantly , we found that Aedes saliva potentiated RVFV infection , once again highlighting its role in arbovirus transmission .
All studies on animals followed the guidelines on the ethical use of animals from the European Communities Council Directive of November 24 , 1986 ( 86/609/EEC ) . All animal experiments were approved and conducted in accordance with the Institut Pasteur Biosafety Committee . Animals were housed in the Institut Pasteur animal facilities accredited by the French Ministry of Agriculture to perform experiments on live mice , in appliance of the French and European regulations on care and protection of the Laboratory Animals ( accreditation number B 75 15-01 and B 75 15-07 ) . The study protocols were approved by the Comité d'Ethique pour l'Expérimentation Animale ( CEEA ) - Ile de France - Paris - Comité 1 . The ZH548 strain was isolated from a human infection during the 1977 outbreak in Egypt [18] . The case was anonymous and an informed consent was not required at that time . This strain was part of a collection used by the NRC of arboviruses ( B . Le Guenno and H . Zeller ) . This collection was transmitted to us and we possess an AFSSA authorization of detention , transfer and manipulation ( since 2001 ) as a “select agent” . We used the DBA-1 and C57BL/6-NRJ mice for infections ( Janvier , France ) . Vero E6 cells were grown in DMEM supplemented with 10% fetal bovine serum ( FBS ) , 10 µg/ml of penicillin and 10 U/ml of streptomycin . C6/36 cells were grown at 28°C in plastic cell culture flasks in Leibovitz medium 15 supplemented with 10% FBS , penicillin ( 50 units/m1 ) , and streptomycin ( 50 mg/ml ) . Stocks of the virulent Egyptian ZH548 RVFV strain were produced under biosafety level 3 ( BSL3 ) conditions . In all experiments , the ZH548 strain was obtained from a cell culture of C6/36 cells . It was produced under BSL3 conditions . Dehydrated eggs of Aedes aegypti ( strain PAEA ) and Ae . vexans vexans were placed in water to hatch . Adult mosquitoes were reared in a room held at 25±1°C and 80% relative humidity , and having a light/dark ratio of 12 h/12 h . The larvae were fed on brewer's yeast tablets and adults were fed on sugar water ( 10% ) . Rabbit blood was collected in heparinized tubes ( 0 . 02% ) . Red blood cells were separated from plasma by centrifugation , washed 3 times in 1X PBS , and were resuspended in the same buffer . Five-day old female mosquitoes were placed in boxes sealed with veils and were fed on 37°C thermostated glass feeders covered with chicken skin and filled with a mixture containing 2 mL of red cells , 1 mL of virus solution ( 108 plaque forming unit ( pfu ) /mL ) and 30 µL of ATP ( 5 . 10−3 M ) . Mosquito females were blood-fed five days after hatching . Three weeks later ( corresponding to the extrinsic incubation period of RVFV in Ae . aegypti and Ae . vexans mosquitoes ) , 100 salivary glands ( SG ) were dissected and placed in 100 µL 1X PBS . The inocula used in our experiments were equivalent to a pair of SG ( or two salivary glands extracts [SGE] ) . SG-containing tubes were stored at −80°C . SGEs were prepared by sonicating the SGs ( five times at 4 min each with a pulse ratio of 2 sec on/2 sec off ) and centrifuging the crude extract at 13 , 000 rpm for 15 min at 4°C . The supernatant was transferred to clean tubes and stored at −80°C . The protein concentration was determined by spectrophotometry at 280 nm ( Nanodrop ) . Fifteen days after their blood-meal , RVFV-exposed mosquitoes were anesthetized at 4°C , legs and wings were sectioned and bodies were placed on a double-sided tape fixed on a glass slide . The proboscis was inserted manually into a 10 µL-cone filled with 5 µL of filtered 1X PBS or DMEM+Glutamax containing 2% FBS . The cone content was collected 45 min later and the virus titer in the solution was determined by plaque assay . Mice were anesthetized intraperitoneally with a mixture ketamine/xylazine consisting of 2 mL of 2% Rompun ( Bayer ) , 4 ml of Imalgene 1000 ( Merial ) , 4 ml of sterile water ( Gibco ) and 2 mL of 1X PBS ( Gibco ) . “Pathogen-free” male mice C57BL/6NRj ( Janvier ) aged four weeks and weighing 15–20 g each , were infected in a BSL3 animal facility by intraperitoneal or intradermal route in the absence or presence of either mosquito SGE ( one SG pair per inoculums = SGP: 2 µl in 20 µl ) or non-infected mosquito bites , or they were infected directly by bites from infected mosquitoes . Selected mice were euthanized five days after infection and the following organs were harvested without any perfusion: brain , liver , spleen , stomach , small and large intestine , pancreas , bladder , heart , lungs , thymus , lymph nodes and salivary glands . Brains were divided into two parts: cerebellum and brain hemispheres ( including olfactory bulbs ) . For virus titration , large organs were cut into pieces of ∼30 mg , whereas small organs like lymph nodes , salivary glands and thymus were kept whole and frozen at −80°C . Samples were then homogenized either in Trizol or in DMEM . Supernatants were collected after centrifugation . For these samples , mice were sacrificed 5 days after infection and perfused with 4% formalin . The organs removed were kept in a freshly prepared solution of formalin . The fixed tissues were embedded in paraffin , cut into 3-µm sections thick , and stained with hematoxylin and eosin ( H & E ) . RVFV-containing samples were titrated on E6 cells by the plaque assay method . Cell counts were performed on KOVA slides . E6 cells were grown in DMEM+Glutamax ( Dulbecco ) containing 10% decomplemented FBS , 10 U/mL penicillin and 10 µg/mL streptomycin in 6-well plates containing 106 cells per mL for plaque assays . Tenfold serial dilutions of each sample to be titrated were prepared in DMEM medium containing 2% FBS , 10 U/mL penicillin and 10 µg/mL streptomycin . 300 µL of inoculum dilution was deposited in each well of a 6-well plate and incubated with for 1 hr at 37°C in a CO2 incubator . Then , 4 mL of agar ( culture medium containing 2% FBS and 2% agarose ) were deposited in each well and incubated for three days . The plaques were then revealed with a 0 . 2% solution of crystal violet containing 3 . 7% formaldehyde and 20% ethanol . For the detection of anti-RVF antibodies in mouse sera , we used a microsphere immunoassay in which a purified recombinant RVF N antigen was covalently associated to color-coded microbeads ( unpublished data ) . Captured anti-RVF antibodies on coupled microspheres were detected using biotinylated anti-mouse IgG and phycoerythrin-conjugated streptavidin by FACS analysis . We used the Power SYBR Green RNA-to-Ct One-Step Kit ( Applied Biosystems , Carlsbad , California ) according to the manufacturer's protocol . It allowed amplifying a 108 bp sequence located between nucleotide 1485 and nucleotide 1593 of the M segment of RVFV . The primers selected were as follows: upper 5′-CATGGATTGGTTGTCCGATCA-3′ and lower 5′-TGAGTGTAATCTCGGTGGAAGGA-3′ . Each sample was analyzed in duplicate against a standard curve produced from a specific concentration range of synthetic RNA . We amplified the samples on an Applied Biosystems 7500 instrument using the following PCR program: a reverse transcriptase ( RT ) step for 30 min at 50°C; inactivation of the RT enzyme and activation of DNA polymerase for 10 min at 95°C; 40 PCR cycles of 15 sec at 95°C and 1 min at 60°C ( annealing temperature of primers ) , during which fluorescence data is collected; and finally , 20 sec at 95°C with ramping 19 min 59 sec for melting curves . Results were compared using two nonparametric statistical tests: Kruskal-Wallis and Mann-Whitney . The median day of death was calculated for each condition and results were compared using Kruskal-Wallis and Mann-Whitney statistical tests .
We first selected an optimal mouse strain for our experimental infection model . For this purpose , we infected six C57BL/6 and six DBA-1 male mice by the intradermal route with RVFV and found that the survival curves for these two strains differed significantly . Whereas DBA-1 mice started to die at four days after infection ( D4 ) , C57BL/6 mice started to die at seven days after infection ( D7 ) . Moreover , whereas neurological symptoms ( such as hind limb paralysis ) occurred in C57BL/6 mice , no such problems were observed in DBA-1 mice ( data not shown ) . Therefore , we chose the C57BL/6 genetic background for our RVFV infection model . We next compared the mortality rates and RVFV tissue distributions in mice infected by two different routes of injection: the intraperitoneal ( IP ) and intradermal ( ID ) routes . The kinetics of infection was slower with the ID route , and a delayed mortality of two days was observed between the two routes of injection ( Figure S1 ) . At D3 , no significant differences in viremia were found between the two routes of injection . However , at D6 , viremia remained at a plateau level of 104 pfu/mL in animals inoculated via IP injection whereas virus titers significantly decreased between D3 and D6 in ID injected mice ( Figure 1 ) . Moreover , high virus titers were found in the brain of mice infected by ID injection but not in the liver whereas high titers were found in the liver of mice infected by IP at D6 but not in their brain ( Figure 1 ) . In agreement with these findings , ID-infected mice presented neurological symptoms . Since ID infection more closely mimics natural infection by the vector , all subsequent infections were performed by this route . To determine whether Ae . aegypti mosquito saliva has a role in potentiating RVFV infection , we infected mice ID with doses of virus between 10 and 104 pfu/mouse , with or without SGE from uninfected mosquitoes and calculated the median day of death of the animals for each condition . At the lower dose , not all mice died ( Figure 2 ) and 66% of the mice surviving did not present any anti-RVFV antibodies ( data not shown ) . However , in presence of saliva , all mice but one died ( Figure 2 ) and the surviving mouse presented anti-RVFV antibodies . The effects of SGE on mortality of infected mice were identified at the lower virus doses of 10 to 103 pfu/mouse ( Figure 2 ) . Median day of death calculation indicated a significant difference between virus and virus+SGE for injection of 102 and 103 pfu/ml ( p = 0 . 01 and p = 0 . 002 respectively ) ( Figure S2 ) . At higher RVFV doses , the effect of SGE on mortality rate was not significant ( p>0 . 05 ) . The weight of the infected mice also decreased as the infections proceeded ( data not shown ) . From these results , we selected 103 pfu/mouse as the reference dose for studying RVFV distribution in mice in the presence and absence of SGE . In addition , we found that the effect of the SGE was not restricted to Ae . aegypti mosquitoes as Ae . vexans SGE also increased RVFV virulence ( Figure S3 ) . Median day of death calculation indicated a significant difference between virus and virus+SGE ( p = 0 . 006 ) and virus+saliva ( p = 0 . 01 ) . However , we did not observe any difference between virus+SGE and virus+saliva ( p = 0 . 42 ) . Interestingly , we did not observe any effect on mice survival when we injected Culex pipiens pipiens SGE ( data not shown ) . We infected C57BL/6 mice with ID injections of virus ( 103 pfu/mouse ) in the presence or absence of SGE and followed the distribution of the virus in the blood and in various organs . The organs were not perfused prior collection . We sacrificed the mice at D5 because in Figure 2 infected mice died during the night between D5 and D6 . Viremia levels were very high in the infected mice , and high virus titers were also found in the liver , brain and cerebellum ( Figure 3 ) , lymphoid organs ( spleen , thymus and lymph nodes ) ( Figure S4 ) , as well as in heart , kidneys , and lungs ( Figure S5 ) . Low virus titers were found in the eyes , jejunum and ileum ( less than 103 pfu/mL ) , whereas the intestine , stomach , ceacum , colon and gallbladder contained no measurable titers . In the presence of SGE , virus titers were significantly increased ( almost 104 fold ) than those produced in the absence of SGE , in the brain cortex ( p = 0 . 024 ) , liver ( p = 0 . 004 ) and blood ( p = 0 . 004 ) ( Figure 3 ) . The virus titers in the cerebellum exhibited an opposite trend compared to the titers in the brain cortex . Indeed , in this organ , virus titers of animals infected in the presence of SGE were lower ( median value of 104 fold ) than those of animals infected without SGE ( p = 0 . 004 ) . We then analyzed the virus titers in the lymphoid organs of mice infected in the presence and in the absence of SGE . The virus titers in the inguinal lymph nodes ( p = 0 . 03 ) , spleen ( p = 0 . 004 ) and thymus ( p = 0 . 007 ) of mice infected in the presence of SGE were significantly higher than those of mice infected in the absence of SGE ( Figure S4 ) . Virus titers in the lungs ( p = 0 . 004 ) , kidneys ( p = 0 . 005 ) , bladder ( p = 0 . 004 ) and heart ( p = 0 . 01 ) of mice infected in the presence of SGE were significantly higher ( 102 fold increase ) compared to the titers found in these tissues of mice infected without SGE ( Figure S5 ) . Virus titers in the pancreas exhibited a pattern similar to that observed in the cerebellum , as these titers were significantly lower in the presence of SGE ( p = 0 . 016 ) than in absence of SGE . In contrast , the addition of SGE to the viral inoculum did not lead to any significant differences in the virus titers in the mesenteric lymph nodes ( ML ) , aortic lymph nodes ( AL ) , popliteal lymph nodes ( PL ) or salivary glands ( data not shown ) . These results correlated well with the RNA quantification results we obtained from RT-qPCR analysis of each organ ( data not shown ) . Following RVFV infection of mice with or without SGE , we found that several blood parameters were altered in infected mice compared to uninfected ones . These changes included significantly lower numbers of white blood cells and platelets ( Table 1 ) . The significant leukopenia observed in infected mice was associated with changes in the white blood cell count , with proportionally higher numbers of granulocytes and monocytes and lower numbers of lymphocytes compared to those in uninfected mice ( Table 1 ) . A 50% decrease of platelets and white blood cell counts was observed in presence of SGE in the inoculation ( Table 1 ) . To better understand the physiology of RVFV infection , we conducted histological analysis of the liver of infected mice and found significant differences between the livers of mice infected in the presence or absence of SGE ( Figure 4 ) . Indeed , mice infected in the presence of SGE exhibited signs of multifocal hepatitis ( Panels A and C ) . Inflammatory foci were randomly distributed in the liver parenchyma ( arrowheads in Panels A and C ) . These foci were characterized by prominent neutrophil infiltrations ( asterisk in Panel C insert ) that were associated with fewer numbers of lymphocytes . Necrotic hepatocytes , with acidophilic cytoplasm and a highly condensed basophilic nucleus ( pyknosis ) or a fragmented nucleus ( karyorrhexis ) were identified within the inflammatory foci ( arrow in Panel C insert ) . The profile of the liver lesions in mice infected in the absence of SGE ( Figure 4; Panels B and D ) was very different from that of mice infected in the presence of SGE . Three out of four mice exhibited hepatic necroses with very few inflammatory foci ( Panel B ) . These necrosis foci were randomly located within the parenchyma ( arrows in Panel D insert ) and were associated with few inflammatory cells ( Panel D insert ) . We collected saliva from RVFV-exposed mosquitoes to estimate the concentration of virus injected during a bite . These results showed mosquitoes may inject approximately 50±20 pfu in each bite , and that more than 50% of the mosquitoes had been infected after an artificial blood-meal . To this point , our experiments were performed with SGE , which contains a mixture of salivary and housekeeping proteins . To determine whether the unique components of saliva triggered the potentiating effect on RVFV virulence , we allowed ID-infected mice to be bitten by non-infected mosquitoes . We inoculated C57BL/6 male mice with RVFV ( 50 pfu/mouse ) by ID injection and exposed the mice to non-infected mosquito bites in the area of the ID infection . The number of blood-fed mosquitoes was determined . The weight changes of the mice were followed for 14 days thereafter . The weight curves of the infected mice corroborated with our previous results ( Figure 5 ) . In the absence of mosquito bites , mice survived for at least 11 days and died between 13 and 14 days post infection . If infection was accompanied by non-infected bites , time to death was shortened . We however did not find any clear correlation between the number of bites and the time to death . In a second series of experiments , mice were bitten by RVFV-exposed mosquitoes collected on D16 or on D19 after infected blood meal . Blood-fed mosquitoes were collected and their viral loads were determined . The weight curves for the mice bitten by mosquitoes at D16 after virus exposure were followed . Three out of five mice received 1 or 2 bites from RVFV-exposed mosquitoes . Only one mouse died 13 days after receiving four mosquito bites ( for which two out of four mosquitoes were infected ) , while the other mice survived until day 14 ( data not shown ) . The experiment was repeated with mice bitten by D19 RVFV-exposed mosquitoes ( Figure 6 ) . As before , the numbers of blood-fed mosquitoes were counted and their viral loads were determined . Mice received up to 9 bites and 3 to 6 of these bites were from infected mosquitoes . Two mice having received bites from infected mosquitoes did not die during the time of experiment ( 11 days ) . Their weight did not decrease . Mosquitoes did not feed on two mice . For the other 6 mice , death was observed from day 5 to day 10 post-feeding . The time to death did not depend on the number of blood-fed mosquitoes collected on each mouse and is more probably related to the amount of virus injected during the probing phase and to the number of uninfected bites . This amount seems highly variable in our experiment . Indeed , we were not able to identify mosquitoes that could have probed , and thereby injected virus , without taking any blood meal .
RVFV is primarily transmitted by mosquito bites and , to a lesser extent , by direct contact with infected animals , mainly sheep and goats , as reported during an RVF epidemic in southwestern Saudi Arabia [7] . However , many studies describing the pathogenesis of this virus have been conducted without considering this natural way of transmission . Indeed , the route of virus inoculation and the presence of components from the vector saliva are likely to have consequences on the immune response that is eventually developed by the host in response to the pathogen . In fact , several studies have shown that the saliva of arthropod vectors transmitting infectious diseases can play a crucial role in the ability of the vector to transmit the pathogen [15] . The mouse strain used in any model of RVFV infection is an important factor that should be carefully considered . Several different genetic strains of mice have been used previously: BALB/cByJ , C57BL/6 , 129/Sv/Pas , and MBT/Pas [20] . The BALB/cByJ , and C57BL/6 strains were found to be the least susceptible to RVFV infection . In our study , DBA-1 mice were more sensitive to the virus than C57BL/6 even though they did not exhibit any neurological symptoms . The C57BL/6 strain experienced hepatic infection as well as neurologic symptoms . These mice are therefore good models to study the most severe forms of RVF in humans , and allow the study of neuropathogenesis and progression of the virus from the periphery to the central nervous system following intradermic inoculation . A number of different studies aimed at defining the pathogenesis of RVFV in animals have employed IP , intranasal and subcutaneous inoculations [4] , [21] . Indeed , exposing mice to aerosols containing RVFV can cause infection [22] whereas other routes of exposure induce delayed death [21] . In our study , the IP and ID routes of injection led to different patterns of virus dissemination . The brain and liver were the main targets of the virus after ID and IP infection , respectively . Viremia was maintained longer after IP infection whereas survival was shorter compared to ID infection . This result showed that the route of infection is a key determinant for infection . First , after ID injection , we found the virus in many organs . High virus titers were found in the liver and in the blood early after infection at D3 , whereas at D6 , high virus titers were found in the brain , while the viremia has decreased . In agreement , mice presented neurological symptoms at D6 , characterized by compulsive or uncoordinated movements , and/or paralysis , and they also had discolored livers presenting hemorrhagic lesions . Our observations correlated well with other studies that showed that this virus causes fulminant hepatitis [7] or meningoencephalitis [23] in humans . We found other organs to be less infected , including the heart , lungs , pancreas and kidneys , which was reported previously [24] . Mice salivary glands were found to be significantly infected , raising the question of the infectivity of saliva . Viral antigens have also been detected in odontogenic and gingival epithelia [24] . In addition , we detected virus in the primary and secondary lymphoid organs and the lymphocyte numbers were lower in infected animals compared to controls . These changes could be explained by lymphocyte apoptosis in lymphoid organs ( thymus , spleen and lymph nodes ) , which was also demonstrated in BALBc mice subcutaneously infected with another RVFV strain ( ZH501 ) [24] . We also observed changes in other blood count parameters like the number of thrombocytes ( platelets ) , granulocytes and monocytes . In general , a decrease in circulating platelet number may be caused by decreased or ineffective bone marrow production , increased intramedullary destruction ( hemophagocytic syndrome ) , increased peripheral destruction ( immune-mediated or non–immune-mediated mechanisms ) , altered distribution of circulating cells ( splenic consumption or endothelial sequestration ) , or decreased cellular life span . Bone marrow was found to be infected in our study ( data not shown ) , and lower numbers of myeloid cells in the spleen and bone marrow in RVFV infection have been reported previously [24] . On the other hand , in patients with dengue hemorrhagic fever , although dengue virus-induced bone marrow suppression was shown to decrease platelet synthesis , an immune mechanism of thrombocytopenia caused by increased platelet destruction appeared to be also active [25] , [26] , [27] , [28] . Granulocytes and monocytes numbers were higher in the blood of infected animal ( Table 1 ) . Three types of granulocytes are present in peripheral blood: neutrophils , eosinophils and basophils . The count of eosinophils was found to vary as function of Rift Valley fever disease progression in mice: it first decreased at the beginning and then increased before death [29] , which could explain our findings . Granulocytes were also found to be important target cells for RVFV infection [21] and thereby represent a site of viral replication to infect other cells or organs . Monocyte numbers also increase in many other vectorial infectious diseases such as West Nile , dengue and malaria [24] , [25] , [26] . Similar changes in blood cell counts including lymphopenia and thrombopenia were reported for the Saudi Arabian epidemics of 2000 [7] . We investigated the role of vector salivary components in RVFV infection . Potentiation of virus transmission and/or pathogenicity in the presence of vector saliva has previously been described in vector/pathogen/host interactions [14] , [15] , [30] . Some of the many salivary proteins co-injected during a vector bite cause immunomodulatory effects on the host . These may include the induction of a Th2 response and the inhibition of Th1 pro-inflammatory cytokines [15] , [31] . In addition , it has been shown in vivo that Aedes mosquito bites are likely to significantly reduce T cell recruitment [16] . We tested the saliva of two Aedes species: Ae . vexans , which is an important RVFV vector in Africa and in the Arabic peninsula [32] , [33] , [34] , [35]; and Ae . aegypti , which exhibits good vector competence for the virus as shown in our study as well as in others [11] , [36] and whose genome has been sequenced . Early death was observed in the groups of mice co-injected with both Aedes SGE . In addition , the survival curves obtained for RVFV-infected mice exposed to the bites of mosquitoes corroborated those obtained with co-injected SGE and confirmed that both Ae . aegypti and vexans saliva potentiates RVFV pathogenicity . These results are comparable to those reported for mice with West Nile virus mixed with mosquito saliva [31] . Interestingly , although Culex pipiens was found to be competent to transmit RVFV [37] , we did not observe any increase of RVFV pathogenenicity in presence of salivary gland extracts from this species . We determined the effects of SGE and saliva on RVFV virulence and distribution for several organs and included histological analyses of the liver . For most organs , including liver , the brain cortex , kidneys , lungs , heart , bladder , spleen , thymus and lymph nodes , virus titers were significantly higher if SGE was included in the inoculum , in agreement , with previous studies where saliva was shown to increase the invasion of neural tissues by West Nile virus and produced higher virus titers in the brain [31] . An SGE-mediated decrease in antiviral activity at the site of inoculation might promote viral replication and infection of different cell types [20] , [21] , [38] , thereby increasing virus production in several organs and causing specific histological lesions , as observed in the liver . This is consistent with what Schneider and Higgs observed in mice infected with West Nile virus in presence of mosquito bites [31] . Early after virus inoculation , they did not observe any difference in the viral titers measured in various organs in presence or absence of saliva whereas after 7 days of infection , higher titers were observed after mosquito bites . We cannot exclude however a modification of the kinetics of virus replication and dissemination in the various tissues in the presence of saliva . Interestingly , and while the viremia is significantly increased , lower virus titers were found in the pancreas and cerebellum in presence of SGE , showing that saliva may also affect virus dissemination . With respect to the brain , our results suggest that saliva might modify the kinetics and/or the extent of invasion of specific regions . The modalities of infection of the central nervous system by RVFV are still poorly understood . Neurons and glial cells were found positive for RVFV throughout the central nervous system of infected calves [39] . Gray et al . [29] showed that the brains of RVFV ZH501 infected mice were essentially normal throughout the course of the study despite evidence of a high viral titer and significantly increased inflammatory cytokine concentrations in the brain tissue of some studied animals . The outcome of our study may suggest either that the presence of saliva at the site of inoculation may favour different ways of brain invasion or that the kinetics of infection is increased and that the cerebellum was first invaded and already partly cured at the moment of sample harvesting while the virus was spreading towards the brain cortex . Since a direct effect of saliva on the brain is unlikely , we propose that modulation of the early immune and inflammatory responses at the site of virus injection may , in turn , modulate the permeability of the blood-brain barrier , allowing virus titers in the brain to be significantly higher . Further studies on this matter are currently underway and preliminary experiments are in favor of an increase of the vascular permeability of the blood brain barrier in presence of saliva . We suggest that intermediate elements like TLR3 and IL6 might be involved in this effect . Actually , West Nile virus , by activating TLR3 ( toll-like receptor 3 ) [40] , and allowing TNFα secretion , was proposed to increase blood-brain barrier permeability . Moreover , it was shown that IL-6 played an important role in increasing brain permeability in a model of bacterial meningitis [41] , [42] . Similar mechanisms might occur in RVFV infections in the presence of saliva . Our histological analysis of infected liver showed that mice infected in the presence of SGE developed multifocal hepatitis with inflammatory foci that were randomly distributed in the hepatic parenchyma . This was also accompanied by a massive recruitment of neutrophils and lymphocytes in the liver parenchyma . CD4+ and CD8+ lymphocytes and cytokines , including TGF-β , TNF-α and IFN-γ were shown to be involved in the hepatic pathogenesis of yellow fever virus infection in combination with a direct cytopathic effect of the virus [43] . The early modulation of the innate response in the dermis caused by mosquito bites probably induces a dysregulation of the immune system and triggers the different pathologic effects observed in absence and presence of the mosquito saliva . Exposure of inoculated mice to mosquito bites confirmed that saliva components have a potentiating effect on RVFV infection . Indeed , we observed early death in mice infected by ID and bitten by uninfected mosquitoes although a clear correlation between the number of engorged mosquitoes and the time of death could not be established . This is probably explained by the time of probing that differs between mosquitoes and the length of the probing time conditioned the amount of saliva injected in the dermis . The next step was to compare infection by an infected mosquito to infection by ID . Death was observed as early as day 5 post-infection , a delay which is comparable to that of mice infected ID with 103 pfu in the presence of SGE . This observation shows that mosquitoes may inject more than 50 pfu in agreement with the detection of a discrepancy between the titers obtained by salivation and those determined in vivo [44] . Our results also showed that the bites of non-infected mosquitoes may potentiate infection caused by the bites of infected mosquitoes . It is important to note that although the number of infected mosquitoes in nature is relatively low , the number of uninfected bites is much higher . Thus , constant local stimulation with saliva may have the potential to modulate the impact of RVFV infection [45] . In conclusion , we have clearly demonstrated an overall potentiating effect of mosquito saliva on RVFV infection . Both Aedes aegypti and Aedes vexans saliva are able to decrease the survival of RVFV-infected mice . The impact of saliva components on the innate immune response at the site of bite certainly explains the facilitation observed , either by increasing the kinetics of distribution of the virus or by altering this distribution through differential targeted organs . The identification of salivary proteins involved in the facilitation of infection and determination of their mode of action could help develop new approaches for preventive or therapeutic purposes in humans .
|
Rift Valley fever is an endemic and epidemic zoonosis in Africa and the Arabic Peninsula . In humans , in the most severe cases the viral infection causes fulminant hepatitis associated with haemorrhagic fever , permanent blindness or severe encephalitis . Despite the importance of vector transmission in the spread of arboviruses , few studies on the physiopathology of viral infection have considered the role of the arthropod in the efficiency of viral infection . Moreover , the route of virus inoculation and the presence of the vector's saliva can potentially affect virus pathogenicity . Our results show that saliva from Aedes mosquitoes increases Rift Valley fever pathogenicity . Importantly , our study also revealed that RVFV transmitted via mosquito bites spread differently than virus inoculated by other routes . These observations may have interesting repercussions given the role mosquitoes were shown to play in the transmission of RVFV in humans during the last outbreak of the disease in Saudi Arabia . Identification of salivary proteins able to increase RVFV virulence may pave the way to new approaches to prevent or cure the disease .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"clinical",
"immunology"
] |
2013
|
Aedes Mosquito Saliva Modulates Rift Valley Fever Virus Pathogenicity
|
We study inter-trial movement fluctuations exhibited by human participants during the repeated execution of a virtual shuffleboard task . Focusing on skilled performance , theoretical analysis of a previously-developed general model of inter-trial error correction is used to predict the temporal and geometric structure of variability near a goal equivalent manifold ( GEM ) . The theory also predicts that the goal-level error scales linearly with intrinsic body-level noise via the total body-goal sensitivity , a new derived quantity that illustrates how task performance arises from the interaction of active error correction and passive sensitivity properties along the GEM . Linear models estimated from observed fluctuations , together with a novel application of bootstrapping to the estimation of dynamical and correlation properties of the inter-trial dynamics , are used to experimentally confirm all predictions , thus validating our model . In addition , we show that , unlike “static” variability analyses , our dynamical approach yields results that are independent of the coordinates used to measure task execution and , in so doing , provides a new set of task coordinates that are intrinsic to the error-regulation process itself .
During the repeated execution of goal-directed movements , statistical variability is always observed from one trial to the next , and this motor variability has long been a major focus of movement neuroscience [1–3] . It is generally believed that these inter-trial fluctuations contain crucial information about how the neuromotor system organizes itself to meet task requirements in the face of physical constraints , external perturbations , and motor noise [4–9] . Indeed , there is increasing evidence that inherent biological noise , which is present at multiple scales from the level of motor units down to the level of genes , may play a crucial physiological function in the nervous system [7 , 10 , 11] . However , the process by which this multiscale noise comes to be expressed as variability at the organismic level is still far from completely understood . There is an excess of body-level degrees of freedom over those needed to specify the outcome of a typical goal-directed movement , and it is natural to expect this redundancy to affect the structure of observed variability . A number of data analysis approaches [12–14] have been developed to examine the effect of this redundancy using task manifolds , which are surfaces in a suitably-defined space of biomechanical observables , or “body states” ( e . g . , joint kinematic variables ) , that contains all possible task solutions . By definition , every point in a task manifold corresponds to a body state that results in perfect task execution , and so , as a consequence , only body-level deviations away from the manifold result in error at the goal level . Originally inspired by ideas from research in redundant robotics , uncontrolled manifold ( UCM ) analysis [12 , 15–17] assumes that the task manifold is defined at each instant along a given movement trajectory , and in typical applications takes the task’s goal to be represented by the average movement in a time-normalized set of trials . The ratios of normalized variances orthogonal and tangent to a candidate manifold are then used to identify possible “control variables” , with the expectation that there should be a larger variance along the manifold than normal to it . In a similar vein , motor learning has been studied by statistically decomposing observed body-level variability into tolerance , noise , and covariation ( TNC ) empirical “costs” , [13 , 18–20] , all three of which are defined with respect to a task manifold . In contrast with UCM analysis , the TNC approach conceives of the task manifold as existing in a minimal space of variables needed to specify task execution ( e . g . , the position and velocity of a ball at release when throwing at a target ) . In addition to using its covariation cost to characterize the alignment of body-level variability with the task manifold , TNC analysis crucially relates the goal-level variability to error at the body level via its tolerance cost . This relationship between body and goal-level variability was the initial focus of a sensitivity analysis method based on the goal equivalent manifold ( GEM ) concept [14] . Like TNC , the GEM analysis defines its task manifold using only a minimal set of variables needed for task specification , however it makes direct use of an explicit goal function that serves as a hypothesis on the task strategy being used . The zeros of the goal function give body states yielding perfect task execution , and the set of all such solutions then gives the GEM . In addition to defining the GEM , the goal function provides a theoretical definition of the “passive” sensitivity ( i . e . , sensitivity independent of any applied control ) to body-level disturbances , via the singular values of the goal function’s Jacobian matrix [14 , 21] . While the initial GEM-based sensitivity analysis was useful for describing the geometrical structure of observed variability and quantifying motor performance , like the UCM and TNC approaches it did not provide an analysis of the temporal structure of observed inter-trial fluctuations . This limitation was addressed by subsequent developments that incorporated optimal control ideas with the GEM to create a dynamical , model-based data analysis framework . Optimal control in the presence of redundancy has been proposed as a theoretical basis for models of the neuromotor system [22 , 23] , and the minimum intervention principle ( MIP ) [23 , 24] posits that little or no control will be exerted along the task manifold , since to do so would entail a waste of control effort . The expanded GEM data analysis framework allows one to create theoretical models of inter-trial fluctuations that can be used for hypothesis testing against movement data from human participants [25–27] . This initial work has demonstrated the central importance of taking a dynamical approach when analyzing motor variability . A fundamental feature of variability highlighted by these studies is that inter-trial fluctuations are found to be dynamically anisotropic with respect to the GEM [25–29]: that is , it is found that the local stability and correlation properties are congruent with the local GEM geometry , with greater stability and lower temporal correlation being associated with the components of time series transverse to the GEM , and lower stability and greater correlation for times series components along the GEM . A similar directionality in correlation properties has been found in a study of skill acquisition [30] . However , such studies have tended to examine these dynamical properties in isolation , and it is not completely clear how the various temporal properties ( e . g . , local stability multipliers , lag-1 correlations , etc . ) relate , if at all , to the purely geometrical features of inter-trial variability arising from the task manifold itself ( e . g . variance ratios , passive sensitivity ) . In particular , it remains an open question whether these various features of inter-trial variability should be considered as manifestations of unique neurophysiological phenomena each in their own right , or if , conversely , they are epiphenomena that naturally arise from a single , underlying regulatory process . In this paper we present evidence that supports the latter , more parsimonious interpretation . To this end , we examine the performance of human participants as they play a virtual shuffleboard game . We chose shuffleboard for this study because it is among the simplest tasks exhibiting task-level redundancy , and is thus both mathematically and experimentally tractable . As such , it serves as a “model problem” for a much broader class of goal-directed tasks which can be expected to exhibit similar variability characteristics . Observed inter-trial fluctuations are modeled as the output of the perception-action system as participants attempt to hit the target in each trial by correcting error in the previous trial . We focus on skilled performance , and , starting with a previously-developed general model for inter-trial error correction [21 , 26 , 28] , we present a theoretical analysis using the shuffleboard task as an illustrative example . The analysis yields theoretical predictions about the geometrical and temporal structure of inter-trial variability , culminating in a prediction of how GEM geometry , passive sensitivity , and active error correction combine to yield task performance . Specifically , we show that the scaling of the root mean square ( RMS ) error at the target is determined by the total body-goal sensitivity , which is , in effect , a total “gain” mapping body-level fluctuations to the goal level . We also address a critical technical issue that arises when experimentally testing our theoretical predictions . For skilled performance , the local geometric stability properties of the fluctuations play a fundamental role , with such properties being determined theoretically by an eigenanalysis of a linearized model . Unfortunately , numerical estimates of eigenvalues and eigenvectors are known to be highly sensitive to errors in the matrix estimate [31] , which are themselves unavoidable when the matrix is found using regression on experimental data . This problem is compounded by the relatively small data sets available in typical human subjects experiments . In this paper we present a new method for estimating all of our dynamical quantities based on bootstrapping [32–34] , which allows us to estimate the complete underlying probability distribution for each quantity considered , resulting in the most robust demonstration to date of the degree to which dynamical anisotropy is present in inter-trial movement data . Furthermore , this data analysis allows us to confirm the theoretical performance scaling prediction to high precision , not only showing how the individual participants performed in this particular task , but also validating the many assumptions underlying our theoretical derivation . Studies of variability using task solution manifolds typically assume that they are embedded in a space of variables with identical physical dimension , such as , for example , joint angles [14 , 15 , 35] , muscle activation [36 , 37] , or finger forces [16 , 38 , 39] . Such situations have tended to obscure a fundamental difficulty if one intends to make inferences based on the relative magnitude of fluctuations normal and tangent to any hypothesized manifold: namely , that multivariate statistics are not invariant under coordinate transformations . This issue was recently recognized in the context of movement variability analysis [30 , 40] , but is a well-known problem in multivariate statistics . Indeed , the widespread utility of principal component analysis [41 , 42] is based in part on the fact that correlations between variables can be completely removed with properly selected linear coordinate transformations . It is clearly highly desirable that the inferences we make about the motor system be invariant under coordinate transformations . While it is possible to normalize the variables and make the data dimensionless , such an approach does not completely resolve the scaling issue because the choice of the normalizing constant is , in most cases , arbitrary . This problem becomes even more acute when the task manifold resides in a space composed of different physical quantities , for example positions and velocities . Given the central role played by local geometric stability in our approach , we are able to exploit the well-known fact that such dynamical properties are invariants that do not depend on the coordinates used [43 , 44] . We therefore show that our approach provides a coordinate-independent characterization of the variability observed in our experiments , suggesting that the local geometric stability analysis of inter-trial fluctuations provides a new set of task coordinates that are intrinsic to the error regulation process itself .
All participants provided informed consent , as approved by the Institutional Review Board at The Pennsylvania State University . Fig 1 shows a schematic of a theoretical shuffleboard game . The entire game takes place along a straight line . Starting the puck at x = 0 , the shuffleboard cue is accelerated from rest while in contact with the puck . Thereafter , the cue decelerates and , when the contact force between it and the puck reaches zero , the puck is released with position and velocity x and v , respectively . Once released , the puck slides on the board and is decelerated by the force of Coulomb friction , with kinetic coefficient μ , between the board and the puck . The puck eventually comes to rest at x = xf . The goal-level error , e = xf − L , is the distance between the final puck position and the target . Elementary Newtonian mechanics gives the equation of motion for the puck after release as x ¨ = - μ g , where g is the gravitational acceleration constant . For arbitrary initial conditions x and v just after release , and final velocity vf = 0 , the equation of motion is easily integrated to give −v2 = −2μg ( xf − x ) . Since perfect execution ( hitting the target ) requires e = xf − L = 0 , we then obtain a goal function for the task as e = f ( x , v ) = v 2 + 2 μ g ( x - L ) . ( 1 ) Any values of x and v for which e = f ( x , v ) = 0 result in perfect task execution ( zero error at the goal level ) . Dimensionless quantities x ˜ = x / R , v ˜ = v / 2 g R , and L ˜ = L / R can be defined for some length scale R . Note that the exact value of R used in this rescaling has no significant bearing on our results: it was chosen for convenience so that when plotting experimental data the rescaled release position x ˜ = x / R ≈ 1 . For the experiments described in what follows , we took L = 200cm and R = 20cm , so that the target was located at a distance of L ˜ = 10 dimensionless units . Using these rescalings in Eq ( 1 ) gives , after rearranging and dropping tildes , the goal function in dimensionless form as f ( x , v ) = v 2 μ + x - 10 . ( 2 ) Henceforth we use the dimensionless goal function of Eq ( 2 ) . There are an infinite number of states ( x , v ) that are zeros to Eq ( 2 ) , corresponding to trials that hit the target perfectly . In this simple case , we can solve for this set analytically , and find , as shown in Fig 2 , that it forms a 1D goal equivalent manifold ( GEM ) G = ( x , v ) | v 2 = μ ( 10 - x ) , ( 3 ) which has the shape of a parabola in the ( x , v ) plane . Since the performance is completely determined by the values of x and v at release , we take as our body state x = ( x , v ) T ( where the superscript T denotes the transpose ) . Note that the goal function f ( x ) ≠ 0 for “strategies” x that are not exactly on the GEM: for this task , this value is identical to the goal-level error , e . The GEM represented in Fig 2 exists independently of who or what performs the task . Actuating the shuffleboard cue with a single degree of freedom pneumatic actuator , a robot with tens of degrees of freedom , or a biological organism with thousands of degrees of freedom does not affect the requirements in the ( x , v ) body state space needed to hit the target . Furthermore , the GEM has been defined without any consideration of the control that might be applied to correct errors from one trial to the next: even a completely uncontrolled system that randomly assigned values of x and v for each trial would have the same GEM . For a skilled participant whose performance is perfect on average , we assume that the state will be near the GEM and write x = x* + u , where the operating point x * = ( x * , v * ) T ∈ G represents the average perfect trial on the GEM , and u = ( p , q ) T is a small fluctuation . Substitution into the goal function Eq ( 2 ) and linearizing about u = ( 0 , 0 ) T then gives e = ( v * + q ) 2 μ + ( x * + p ) - 10 ≈ 1 2 v * μ p q ≜ A u , ( 4 ) where A = ( ∂ f ∂ x ∂ f ∂ v ) , with derivatives evaluated at ( x* , v* ) , is the 1 × 2 body-goal variability matrix [14] that maps body-level perturbations u into goal-level error e . The null space N of A , defined by N = { u | A u = 0 } , contains fluctuations that are goal equivalent , i . e . , that to leading order have no effect on the goal level error . Using this definition , the unit tangent vector to the GEM is found to be e ^ t = 1 1 + 2 v * μ 2 - 2 v * μ 1 , ( 5 ) giving the 1D goal-equivalent subspace as N = span { e ^ t } , which is also the subspace tangent to the GEM at x* ( again , see Fig 2 ) . In contrast , the row space R of A contains fluctuations that result in error at the goal and , hence , are goal relevant . This 1D space is orthogonal to the GEM , so that R = span { e ^ n } , where e ^ n is the unit normal to the GEM given by e ^ n = 1 1 + 2 v * μ 2 1 2 v * μ . ( 6 ) Given a fluctuation u from the operating point x* , its goal-relevant and goal-equivalent components are found using the inner products u R = u · e ^ n and u N = u · e ^ t , ( 7 ) respectively . Using these , one can readily compute from observations the sample standard deviations of goal-relevant and goal-equivalent fluctuations , σ R and σ N , respectively . The singular values of the body-goal matrix A determine how fluctuations u get amplified onto the target [14] , and so determine the sensitivity of the performance to body-level errors . Since the sensitivity depends only on the goal function , it is independent of any specific inter-trial control mechanism , and so is considered to be a passive property of the task . For the shuffleboard game , A has one singular value s , which is given by [31] s = 1 + 2 v * μ 2 . ( 8 ) Thus , the passive sensitivity is a function of the friction coefficient , μ , and the speed at the operating point , v* , with the latter indicating that s is not constant along the GEM . Given s , Eq ( 4 ) can then be used to obtain the RMS goal-level error as σ e = s σ R , ( 9 ) which is a special case of the general expression obtained in [14] . Thus , the passive sensitivity “explains” the goal level error , but only when the goal-relevant fluctuations are taken as given . However , the scale of those fluctuations , σ R , is itself determined by the active process of inter-trial error correction . As discussed previously , the GEM and body-goal sensitivity are passive properties of the task that exist prior to the imposition of any error-correcting control . Here , we “close the loop” on the problem by discussing simple perception-action models of inter-trial error correction . For clarity , we present our modeling framework with a bit more generality than will ultimately be needed . Additional background and details can be found in [26 , 28] . A typical experiment for a goal-directed task with N trials results in a time series of the body state variable , { x k } k = 1 N , and a corresponding time series of goal-level errors , { e k } k = 1 N . We consider these time series to result from the process of error-correction used by participants as they make adjustments after each trial , and model the fluctuation dynamics with update equations of the form [21 , 26 , 28]: x k + 1 = x k + G I + N k c ( x k ) + ν k , ( 10 ) in which: c ( xk ) is an inter-trial , error-correcting controller depending on the current state; Nk is a matrix representing signal-dependent noise in the motor outputs [45]; and νk is an additive noise vector representing unmodeled effects from perceptual and neuromotor sources . The diagonal matrix of gains , G , is included as a convenient way to detune the model away from optimality when c is an optimal controller designed initially with G = I [26] . Error-correcting models with mathematical form similar to Eq ( 10 ) have been used to study motor learning [46–48] and to understand the effect of motor noise . These previous efforts have not focused on the role of task level redundancy , or attempted to relate body-level fluctuations to those at some external goal , as we do here . However , in contrast to these previous studies , we do not make reference to hidden internal state variables related , for example , to motor planning , but instead construct our models at the level of experimentally-observable task-relevant kinematic variables . As a consequence , our models cannot be used to disambiguate the effect of noise due to motor planning from that due to motor execution [46] . Our focus here is not on how internal “neuronal” state variables are dynamically mapped to kinematic output variables , but rather how the body-level task variables are mapped onto the goal-level task error in the presence of redundancy . Hence , our study takes place at a different level of description than studies aimed at understanding the physiological origin of motor noise and its role in motor learning . Models with the general form of Eq ( 10 ) can be viewed as the between-trial component of a hierarchical motor regulation scheme that makes error-correcting adjustments to an approximately “feed forward , ” within-trial component . Focusing once again on skilled movements , we write xk = x* + uk as was done leading up to Eq ( 4 ) , where uk are small perturbations from the operating point x* . Assuming , in addition , small noise terms Nk and νk , we can linearize the controller Eq ( 10 ) [21 , 28] about uk = 0 to obtain: u k + 1 = B u k + ν k , ( 11 ) where the matrix B = I+GJ , and J = ∂c/∂x is the Jacobian of the controller evaluated at x* . Note that , to leading order , signal dependent noise does not affect the inter-trial dynamics near the GEM [28] . Thus , small fluctuations are governed by the linear map of Eq ( 11 ) , and the eigenvalues and eigenvectors of B determine the local dynamic stability properties of the system [44 , 49 , 50] . Specifically , eigenvalues λ with magnitude near zero ( |λ|≈0 ) indicate that deviations from the GEM are rapidly corrected , whereas positive eigenvalues strictly less than but closer to one ( 0 ≪ λ < 1 ) indicate that deviations are only weakly corrected ( that is , they are allowed to “persist” ) . Note that values of λ > 1 indicate instability , indicating that deviations would continue to grow in successive trials , something that is not expected in experiments . For the shuffleboard task , the body states are 2-dimensional , so that B is a 2 × 2 matrix possessing two eigenvalues , {λw , λs} , and two eigenvectors , { e ^ w , e ^ s } , where the subscripts w and s indicate weakly and strongly stable directions , as described below . We limit our discussion to the case of real , distinct eigenvalues , which has been found to be sufficient in experimental applications to date . In [26] , c was found analytically as an optimal controller using different specified cost functions . Because goal-level error was minimized as a cost , the goal function ( which , for the current paper , is given by Eq 2 ) was built into the model , and so the effect of the GEM was explicitly included . In studies of this type , the model is used to generate simulated data , which is then statistically compared to experimental data to “reverse engineer” the controller used by human participants . Furthermore , if one wishes to study local stability properties via Eq ( 11 ) , the matrix B can , in principle , be obtained analytically by differentiation . In contrast , in this work we take a simpler , empirical approach: instead of formulating an explicit optimal controller , linear regression is used to estimate the matrix B of Eq ( 11 ) directly from the experimental fluctuation data . The eigenstructure of the estimated B is then obtained and compared to the geometry of the shuffleboard GEM ( Fig 2 ) . Thus , other than the assumption of closeness to an operating point x * ∈ G ( i . e . , of linearity ) , the controller is not assumed to to be optimal , nor is the GEM encoded into it in any way . Thus , any structure in the data related to the presence of the GEM is a property of the observed fluctuation dynamics: it has not been imposed by the model . Task manifold methods applied to a variety of motor tasks have shown that the body-level variability observed during skilled task execution will tend to have greater variance along the task manifold than normal to it . Indeed , anisotropy in the variability is typically taken to demonstrate that a hypothesized task manifold is being used to organize motor control [12 , 16] . Such results are consistent with a generalized interpretation of the UCM hypothesis and the MIP: namely , that while disturbances along the task manifold are not truly “uncontrolled” , they are , at least , more weakly controlled than those normal to it . However , movement variability may be “structured” ( i . e . , may exhibit anisotropy ) for biomechanical and/or neurophysiological reasons that are unrelated to control [36] . In addition , variance-based analyses are vulnerable to ambiguities related to the coordinate dependence of variability statistics [28 , 40] , and by themselves do not provide any insight into how observed fluctuations are dynamically generated and regulated [28 , 51] . A number of researchers have addressed this last limitation by combining task manifold ideas with time series analysis of statistical persistence [25–27 , 30 , 51–54] , as measured either via detrended fluctuation analysis ( DFA ) [55 , 56] or autocorrelations . Generally speaking , a time series exhibits statistical persistence if , given fluctuations in one direction , subsequent fluctuations are likely to be in the same direction . If subsequent fluctuations are likely to be in the opposite direction , the time series is said to be antipersistent , and if subsequent fluctuations are equally likely to be in either direction the time series is non-persistent or , alternatively , uncorrelated . As was shown in [25] , the coherent interpretation of persistence results requires the consideration of error-correcting control near the task manifold: there is greater statistical persistence along the manifold , where the control is weak , than perpendicular to it , where the control is strong . These types of results are , again , consistent with a generalized interpretation of the MIP [28] . All of the above-cited studies lead us to expect dynamical anisotropy in inter-trial fluctuations . That is , the temporal structure of fluctuations should reflect the operation of a controller that strongly acts against goal-relevant deviations by pushing subsequent body-states toward the GEM , while only weakly acting to correct goal-equivalent deviations along the GEM . Since in this paper we focus on skilled movements , we make direct use of the linearized model Eq ( 11 ) . For an ideal MIP controller , the complete absence of control along the GEM would result in neutral stability along it , as well , meaning that one eigenvector of the matrix B ( Eq ( 11 ) ) would be identical to the unit tangent e ^ t , and its associated eigenvalue would be λ = 1 . However , such a scenario in the presence of motor noise would result in an unbounded random walk along the GEM , something which has yet to be observed in experiments . Thus , we expect the inter-trial dynamics to be slightly perturbed from what one would expect for a perfect MIP controller , giving one weakly stable eigenvalue less than , but somewhat close to , 1 ( i . e . , 0 ≪ λw < 1 ) with an associated unit eigenvector ew that is close to e ^ t , but slightly rotated . In contrast , the strongly stable eigenvalue , λs , indicates vigorous correction of deviations off of the GEM , so that |λs|≈0 and es is transverse ( but not necessarily perpendicular ) to the GEM . The general geometry of the situation , in which local stability properties are overlaid on the GEM near an operating point x* , is show schematically in Fig 3 . The fluctuations uk in the original , laboratory coordinates ( e . g . , representing speed and position for the shuffleboard game ) can be transformed into new fluctuations expressed in eigencoordinates via the linear coordinate transformation u k = E z k , ( 12 ) where E is the matrix containing e ^ w and e ^ s as its columns . Note that E is not typically an orthogonal matrix because the eigenvectors of B are not usually perpendicular . Using this transformation , Eq ( 11 ) becomes z k + 1 = E - 1 B E z k + E - 1 ν k ≜ Q z k + n k . ( 13 ) where z = ( zw , zs ) T are the fluctuations expressed in weak-strong eigencoordinates , the diagonal matrix Q = E−1 BE has λw and λs along its diagonal , and n = ( nw , ns ) T is the transformed additive noise term . That is , the transformation Eq ( 12 ) decouples the dynamics in the weak and strong directions so that Eq ( 13 ) can be written as z w , k + 1 = λ w z w , k + n w , k ( 14 ) z s , k + 1 = λ s z s , k + n s , k , ( 15 ) in which zw , k and zs , k are simply the components of zk in the weak and strong directions , respectively . This “diagonalized” form of the system illustrates the action of each eigenvalue on fluctuations in their respective directions: in the absence of noise an eigenvalue close to zero will eliminate a given fluctuation on the very next trial , whereas a positive eigenvalue a bit less than 1 will allow fluctuations to persist over many trials . The decomposition of Eqs ( 14 ) and ( 15 ) is intrinsic to the fluctuation dynamics created by inter-trial error correction , and so differs significantly from “static” decompositions using , for example , the normal and tangent to the GEM , or principal component analysis [42] . From Eq ( 7 ) and the transformation Eq ( 12 ) we can relate the standard deviations of fluctuations in the goal-relevant and strongly-stable directions as u R = e ^ n · u = e ^ n · z w e ^ w + z s e ^ s ≈ β z s ⟹ σ R ≈ β σ s , ( 16 ) where β ≜ e ^ n · e ^ s = sin ( θ s ) ( see Fig 3 ) and we have assumed , consistent with a generalized MIP , that the weakly stable direction is nearly tangent to the GEM , so that e ^ w ≈ e ^ t ⇒ e ^ n · e ^ w ≈ 0 . Squaring both sides of Eq ( 14 ) , taking the ensemble average ( as indicated by angle brackets ) , and assuming that the noise and fluctuations at trial k are uncorrelated , yields z w , k + 1 2 = λ w 2 2 m u z w , k 2 + n w , k 2 ⟹ σ w = σ n w 1 - λ w 2 , ( 17 ) where σ n w 2 ≡ 〈 n w , k 2 〉 , and in which we have used the fact that at steady state 〈 z w , k + 1 2 〉 = 〈 z w , k 2 〉 ≡ σ w 2 . A similar calculation with Eq ( 15 ) gives σ s = σ n s 1 - λ s 2 . ( 18 ) Eqs ( 17 ) and ( 18 ) show that as the eigenvalues approach 0 , the “output” variance of the fluctuations approaches a minimum value equal to the variance of the “input” noise . Conversely , as the eigenvalues approach the stability boundary of 1 , the output variance becomes unbounded ( i . e . , the fluctuations approach the behavior of a random walk ) . Finally , substituting from Eq ( 16 ) into Eq ( 9 ) , using Eq ( 18 ) , and rearranging we find σ e σ n s ≈ β s 1 - λ s 2 ≜ s TOT , ( 19 ) where sTOT is the total body-goal sensitivity , which quantifies how much intrinsic body-level fluctuations are amplified at the goal level . Note that sTOT results from the interaction of the passive sensitivity ( via s ) , the local GEM geometry ( via β = sinθs ) and active control “strength” ( via λs ) . Given zw and zs time series from the diagonalized controller of Eqs ( 14 ) and ( 15 ) , we can compute the normalized lag-1 autocorrelations of the fluctuations in the weak and strong directions as R w ( 1 ) = ( z w , k + 1 ) ( z w , k ) σ w 2 and R s ( 1 ) = ( z s , k + 1 ) ( z s , k ) σ s 2 , ( 20 ) respectively . This provides a simple quantification for the statistical persistence in both directions . However , multiplying Eq ( 14 ) by zw , k , taking the ensemble average , and assuming the additive noise is uncorrelated with the fluctuations so that 〈 ( zw , k ) ( nw , k ) 〉 = 0 gives ( z w , k + 1 ) ( z w , k ) = λ w ( z w , k ) ( z w , k ) ≡ λ w σ w 2 . ( 21 ) Solving for λw in the above and comparing it to the definition Rw ( 1 ) in Eq ( 20 ) , we see that Rw ( 1 ) ≡ λw . Likewise , a similar calculation with Eq ( 15 ) shows Rs ( 1 ) ≡ λs . Thus , as a persistence measure the normalized lag-1 autocorrelation does not , theoretically speaking , provide information distinct from the eigenvalues λw and λs . We include it here to demonstrate the connection between stability and this simple persistence measure . We use it later , as well , to serve as a consistency check on our experimental eigenvalue estimates . To test for statistical persistence with a method independent from the eigenanalysis , one can apply detrended fluctuation analysis ( DFA ) [55 , 56] with linear detrending to the zw and zs time series . The DFA algorithm yields a positive exponent , α , where α < 0 . 5 indicates antipersistence in a time series , α > 0 . 5 indicates persistence and α = 0 . 5 indicates non-persistence . Contrary to its most common use in the literature , in this work we are not using DFA to claim that observed fluctuations exhibit long-range persistence , but instead employ α merely as a convenient overall measure of persistence that , unlike the autocorrelation , does not require consideration of specific lags . Additional discussion regarding the application of DFA to movement variability data can be found in [28] , including a review of its vulnerability to false positives when testing for long-range persistence [57–59] . In this subsection we show how the dynamical analysis of inter-trial fluctuations allows us to characterize observed variability in a way that is insensitive to the choice of coordinates . Starting with some original body state variable x , consider a new variable y of the same dimension as x , with each being related by a general differentiable , invertible coordinate transformation x = g ( y ) . Thus , the operating point expressed for each choice of coordinates is related by x* = g ( y* ) , and we find that small fluctuations are related to lowest order by a linear transformation from: x * + u k = g ( y * + v k ) ≈ g ( y * ) + T v k ⟹ u k = T v k , ( 22 ) where uk and vk are the fluctuations expressed in terms of the old and new coordinates , respectively , and T is the square Jacobian matrix of the transformation g evaluated at y* . Using Eq ( 22 ) to substitute for uk into the linearized controller Eq ( 11 ) then gives , in a manner analogous to that used to obtain Eq ( 13 ) : v k + 1 = T - 1 B T v k + T - 1 ν k . ( 23 ) Clearly , the matrix T−1BT on the right-hand side of the above equation is congruent to the original B , and so will have the same eigenvalues , and , hence , the same stability properties . As discussed in [28] , the GEM itself is transformed when using the new coordinates . Recall from the discussion prior to Eq ( 5 ) that the tangent to the GEM is determined from the null space of the Jacobian to the goal function , A . That is , to leading order the fluctuation uk is on the GEM whenever Auk = 0 . However , again using the transformation Eq ( 22 ) , we see that Auk = ATvk , showing that whenever uk is on the GEM expressed in terms of the original coordinates , vk is on the GEM expressed using the new coordinates . Thus , not only are the stability properties unaffected by coordinate transformations , the eigenvectors and GEM are transformed in a predictable way that preserves the topology near the operating point: that is , while changing coordinates will typically rotate and shear the picture somewhat , the overall arrangement illustrated in Fig 3 is preserved . Following the above discussion , we are led to the following four theoretical predictions , presented here as experimental hypotheses , which we here simply state directly . Additional computational details , as required to test the hypotheses , are presented in the Data Analysis section below . As a convenience to the reader , Table 1 contains a glossary of the key symbols used in stating the hypotheses . Hypotheses H1–H3 can be tested directly by examining the eigenstructure of the matrix B in Eq ( 11 ) . They are dynamical consequences of the more general hypothesis that Eq ( 11 ) is derived from a “GEM aware” controller , and hence strives to eliminate goal-relevant deviations quickly , after only one trial , while allowing goal-equivalent deviations to persist for multiple trials . In contrast , hypothesis H4 emphasizes how the overall goal-level performance ( as measured by σe ) will result from the interaction between the strongly-stable component of the intrinsic “input” noise ( measured by σns ) , inter-trial error correction , and passive sensitivity . The total body-goal sensitivity , sTOT , is an overall “gain” between body-level noise and goal-level error . We expect λs ≈ 0 , and β = sin ( θs ) <1 ( Fig 3 ) . Thus , β / 1 - λ s 2 , which is the “active factor” of sTOT will have a value on the order of unity . In contrast , the “passive factor” of sTOT , which is simply the passive sensitivity s ( Eq ( 8 ) ) , may be substantially greater than unity . Thus , a somewhat counterintuitive effect of error-correcting control is that the passive sensitivity , which is determined by task properties independent from control , may play a dominant role in determining motor performance at the goal level . Fig 4 shows a schematic representation of the experimental set-up for the shuffleboard game in a virtual environment . The participant was seated in an upright position , and in each trial moved a custom-built input device consisting of a manipulandum affixed to a low friction , single degree of freedom , linear bearing . Participants held the manipulandum with their dominant hand and pushed it in a direction parallel to the ground plane . The apparatus was configured for each participant so that at rest the upper arm was aligned with the midaxillary line and the angle between the upper arm and the forearm was approximately 90° . Each trial started with the puck at x = 0 ( recall Fig 1 ) . The participant accelerated the manipulandum from rest . Position data was acquired from the manipulandum’s motion and used to generate the motion of a virtual shuffleboard cue in real time , via custom software , which pushed the puck on the virtual court . The release of the puck happened as the cue decelerated and the virtual contact force between the cue and the puck decreased to zero . At the point of release , the position and velocity , x and v , of the puck were acquired , defining the body state for a given trial . Thereafter , the acquired values of x and v were used to compute the motion of the puck as it slid on the virtual court and was decelerated by Coulomb friction before coming to rest . The movement of the shuffleboard cue and puck during the entire trial was generated in real time by the control software and projected onto a screen . Participants could see an animated 3D scene showing the movement of the puck on the court as it moved toward a visible target line before coming to a stop . The projector ( InFocus LP70+ ) was located to the right and just behind the participants , approximately 3m from a 1 . 7m × 1 . 3m screen , with the settings adjusted for flicker-free images that filled the screen . The position and velocity data were obtained from two transducers placed on the manipulandum and collected through two 12-bit channels: an accelerometer ( ADXL320 , Analog Devices , Inc . , Norwood , MA ) was used to collect acceleration data , which was integrated to provide the velocity; the other channel collected position data from a linear variable displacement transducer ( LVDT ) ( Daytronic Corporation , Dayton , OH ) . The LVDT was also used to calibrate the accelerometer by scaling the doubly integrated acceleration signal to match the position signal . A National Instruments NIDAQCard-6024E data acquisition card was used to acquire the data to a laptop computer . A virtual instrument written in LabVIEW ( National Instruments , Austin , TX ) passed the velocity and position information in real time to a C++ program which used the Visualization Toolkit ( VTK , http://www . vtk . org ) , an open-source graphics library , to render the 3D virtual environment . Both signals were sampled at 5kHz to provide smooth animation in the virtual environment . Even though the virtual environment has no physical units per se , we designed the system so that all VTK representations of lengths matched centimeters in the physical world: the accelerometer and LVDT were calibrated and data was recorded in cm/s2 and cm , respectively . We expected the dynamical anisotropy predictions ( H1–H3 ) to depend primarily on the local geometry of the GEM , and to not , therefore , depend on the friction coefficient μ . On the other hand , the scaling prediction , H4 , depends on μ via the passive sensitivity , since s = s ( μ ) from Eq ( 8 ) . Therefore , we had each participant perform the task with two different friction levels in the virtual world , giving a total of eight different participants/conditions . For a given velocity and position at release , the time of motion before the puck stops is inversely proportional to the coefficient of friction . We therefore selected values of μ so that the time for a hypothetical ideal trial varied uniformly between 3s and 5s . This ideal trial was defined by a release position of x = 0 and release velocity v determined from the goal function Eq ( 2 ) so that the puck would stop exactly at the target . The resulting set of 8 μ values were split into two sets: the lowest 4 gave “low friction” ( LF ) conditions , and the highest 4 “high friction” ( HF ) conditions . These different friction conditions gave us inter-trial data sets generated with different passive sensitivity properties , via Eq ( 8 ) . Four healthy , right-handed male participants aged 25 , 28 , 29 and 33 years ( labeled P1–P4 ) participated in this study . Each participant was randomly assigned one HF and one LF friction condition to perform the shuffleboard task . The participants were instructed to launch the puck so that its center stopped on the target in every trial . Participants had the visual feedback from the 3D scene showing the error from a given trial . The goal-level error was also displayed momentarily on the screen providing a second , more precise , feedback on their performance . All participants were allowed to familiarize themselves with the task and the equipment , and practiced hitting the target until their average error e ( Fig 1 ) over 50 trials was less than 10% of the target distance . That is , participants practiced until the average state x ¯ = ( x ¯ , v ¯ ) T acquired over 50 trials lay within the error contours of Fig 2 . All participants achieved this level of performance within four blocks of 50 trials . Once the participants achieved the required level of performance , the data collection phase began . The body state x = ( x , v ) T and goal-level error e were recorded for each trial . For each of the two friction conditions ( LF and HF ) the participant was required to perform 500 trials . All of the data was collected over three days: two days each of four 50-trial blocks , with two blocks before noon and two in the afternoon , followed by a day of two 50 trial blocks . Each block took no more than seven minutes and the participant was given up to five minutes of rest between blocks . The last block of P1-HF was incomplete due to an experiment malfunction , so only data from the first 9 blocks ( 450 trials ) were subsequently analyzed; P3-HF had only 350 usable trials due to the entry of an erroneous friction coefficient . Typical inter-trial time series of states x = ( x , v ) T obtained from one participant over 500 trials are shown in Fig 5 ( a ) –5 ( c ) . The complete data set for each of the 8 friction conditions ( 4 participants × 2 conditions each ) consisted of time series of release position and velocity , { x k } k = 1 N and { v k } k = 1 N , respectively , and the corresponding error , { e k } k = 1 N , for each of N = 500 trials . The data was rescaled into dimensionless form , as for the goal function of Eq ( 2 ) . Note , however , that the stability and persistence properties studied here depend only on the temporal relations between consecutive trials , so the rescaling does not affect the results presented in this paper . Except as noted , all data analyses were performed using Matlab ( Mathworks , Natick , MA ) . All data and software used for this study is contained in Supporting Information S1 Data and Code . The sample mean body state x ¯ = ( x ¯ , v ¯ ) T over all trials was used to define the operating point used in Eq ( 4 ) : that is , we took x * ≡ x ¯ . Fluctuation time series were then obtained from u k = x k - x ¯ , and Eq ( 11 ) was used to estimate B via linear regression . That is , we used ordinary least squares to minimize the single-step mean-square prediction error 〈 ( uk+1 − Buk ) T ( uk+1 − Buk ) 〉 , where , again , the angle brackets denote the ensemble average . A requirement for the use of this straightforward approach to estimation [60–62] is that the state measurement error or “noise” ( as distinct from the process noise νk in Eq ( 11 ) ) not be too large . While there is no firm cutoff for how much measurement noise becomes problematic , Kantz and Screiber suggest ( see [62] , p . 251 ff . ) that ordinary least squares works well as long as the measurement errors are under about 10% . In our case the measurement precision after calibration was approximately 2% , well under the suggested cutoff . Furthermore , we cross validate the estimate of B by comparing its eigenvalues against the lag-1 autocorrelation , which is computed independently , as discussed previously following Eq ( 21 ) . The eigenvectors of B , { e ^ w , e ^ s } , and their corresponding eigenvalues , {λw , λs} , were then obtained as solutions to B e ^ = λ e ^ . A typical result of this eigenanalysis is shown in Fig 5 ( d ) . The alignment of the eigenvectors to the GEM was computed using the theoretical tangent vector from Eq ( 5 ) ( recall the schematic of Fig 3 ) . Because the empirically-determined operating point x ¯ was always close to , but never exactly on the GEM , as a check we also computed the eigenvector orientation using the tangent to the error contour passing through the operating point ( determined from by f ( x ¯ ) = e ¯ , where f is the goal function Eq ( 2 ) ) . This was found to give identical results , confirming the closeness of x ¯ to the GEM . Together with the alignment information so obtained , the estimated eigenvalues of B , which quantify the stability of the inter-trial dynamics , were used to test H1 and H2 . Next , the fluctuation time series { u k } k = 1 N in the original position-speed coordinates were transformed into time series { z k } k = 1 N expressed in eigencoordinates , via the linear coordinate transformation Eq ( 12 ) . Following the discussion surrounding Eqs ( 20 ) and ( 21 ) , statistical persistence in both directions was quantified using the lag-1 autorcorrelations Rw ( 1 ) and Rs ( 1 ) , as well as the DFA exponents αw and αs . These results allowed us to test H3 . To test the scaling relationship of H4 , the RMS goal-level error σe was computed directly from the time series , { e k } k = 1 N . Using Eq ( 8 ) , the value of μ for a given set of trials , and the velocity component of the average operating point , v ¯ ≡ v * , we obtained an estimate of s . The values of β and λs were available from the eigenanalysis . For σns , we used the estimated B and Eq ( 12 ) to compute the residual of the regression expressed in eigencoordinates , via rk = E−1 ( uk+1 − Buk ) . We then took 〈 | r s , k 2 | 〉 as an estimate of σns , where rs , k is the strongly stable component of rk . Using these estimates to evaluate Eq ( 19 ) allowed us to test H4 . All of the above analyses depend critically on the eigenvalues and eigenvectors of the matrix B . To estimate B via regression we require only data from a set of trials , which need not themselves be consecutive , together with the subsequent states that are presumed to follow under the action of B via Eq ( 11 ) . To eliminate the spurious “state update” between the last trial in each block and the first trial in the next block , we only consider the first 49 trials within each 50 trial block . In addition , to avoid possible transient “retraining” effects at the beginning of each block , we removed the first 4 trials , leaving 45 trials within each block , for a total of 450 trials per friction condition . Finally , to overcome known problems associated with the sensitivity of eigenvalue and eigenvector estimates to matrix errors [31] , such as are unavoidable with matrices estimated via regression , we used bootstrapping [32–34] to estimate the various quantities needed to test our hypotheses . For each iterate of the bootstrap , we selected a uniformly-distributed random sample of 450 states ( with replacement ) from the 450 available for each friction condition , together with the state from the next trial . In this way , we obtained an ensemble of “current states” ( xk ) and an ensemble of the corresponding “next states” ( xk+1 ) that were used to obtain one estimate of B via linear regression . This estimate of B was then used to compute one set of eigenvalues and eigenvectors . The eigenvectors were then used to obtain the fluctuation components in the weakly and strongly stable directions , zw and zs , via the transformation Eq ( 12 ) . These allowed us to estimate the lag-1 autocorrelations using Eq ( 20 ) . By choosing many such random samples , each resulting in its own estimate of B , we were able to generate an empirical probability distribution for all quantities needed to test H1 and H2 , and to partially test H3 using R ( 1 ) . The bootstrapping gave us reliable estimates of mean values together with 95% confidence intervals . For the above results , we used 10000 bootstrap iterates . Since DFA relies on the proper temporal sequence of an entire data set ( not just over a single lag as for the autocorrelation ) , the sampling procedure outlined above could not be used . In addition , because DFA does not give reliable estimates for small data sets , we concatenated all 10 trial blocks , again with the first four trials removed , and analysed the resulting data set of 460 trials at once . Such a concatenation procedure was shown in an analysis of Parkinsonian gait [63] , using data sets of 25 strides each , to give results with sufficient accuracy to distinguish Parkinsonian and healthy participants . While perhaps not accurate enough to characterize subtle differences in long-range correlated data sets , as stated earlier this is emphatically not our aim here: we merely use DFA to provide a convenient , lag-independent measure of statistical persistence , which we checked against the lag-1 autocorrelation for consistency . For this paper , once the eigenvectors were found within each iterate of the bootstrap , the entire time series of fluctuations was transformed into eigencoordinates , again via Eq ( 12 ) . The DFA exponents , αw and αs , for the two eigencoordinate fluctuations were then obtained , allowing us to complete the test of H3 . To reduce the computation time required to carry out 10000 DFA calculations for each friction condition , we used a version of the algorithm written in C [64] , that was then called from Matlab . Finally , to test H4 , another variant of the bootstrap was used . In each bootstrap iteration , 450 samples with replacement were drawn and used to estimate σe , σns , s , β and λs , as needed for Eq ( 19 ) ; this was done for all 8 friction conditions . Within this bootstrap iteration , regression was then used to estimate the parameters a and b of a fit σe/σns = asTOT + b: following Eq ( 19 ) , we expected a ≈ 1 and b ≈ 0 . Thus , after repeating this process 10000 times , we obtained estimates and confidence intervals for the slope a and y-intercept b , as required to test H4 .
Fig 6 shows empirical probability density functions ( EPDFs ) , obtained using bootstrapping , for the eigenvalues {λw , λs} of the matrix B ( Eq ( 11 ) ) . We see that in all cases they satisfy 0 ≈ |λs| ≪ λw < 1 . In aggregate , across all participants ( P1–P4 ) and friction conditions , we found λs = −0 . 03 [−0 . 24 , 0 . 14] and λw = 0 . 76 [0 . 62 , 0 . 90] , where here and throughout the stated estimate is the aggregate mean , and the closed interval represents the aggregate 95% confidence interval ( CI ) . The orientation of the eigenvectors is shown in Fig 7 , which plots the EPDFs for the angles θ w = cos - 1 ( e ^ w · e ^ t ) , and θ s = cos - 1 ( e ^ s · e ^ t ) . We see that , for all participants/conditions , the weakly stable eigenvector was very close to the tangent , and the strongly stable eigenvector made a larger transverse angle with it , so that 0 ≈ |θw| ≪ θs . Specifically , we found θw = 0 . 90° [−2 . 36° , 3 . 99°] and θs = 79 . 75° [20 . 66° , 144 . 75°] . We note that the orientation of the weakly stable subspace is tightly regulated to be near the GEM’s tangent ( i . e . , its CI is small , spanning less than 7° ) , whereas the orientation of the strongly stable subspace is not tightly regulated ( its CI spans over 124° ) . The aggregate values of the matrix components of B were found as B ( 1 , 1 ) = 0 . 76 [0 . 62 , 0 . 90] , B ( 1 , 2 ) = −0 . 26 [−2 . 03 , 1 . 19] , B ( 2 , 1 ) = −0 . 01 [−0 . 04 , 0 . 03] , and B ( 2 , 2 ) = −0 . 03 [−0 . 25 , 0 . 14] . Using the mean matrix components as a simple consistency check , we found values of λw and λs equal to the means obtained via bootstrapping , above . The results shown in Figs 6 and 7 strongly support hypotheses H1 and H2 . We found that the component of the inter-trial dynamics directed along the strongly stable subspace acted to quickly correct deviations off of the GEM that caused goal-level errors . For example , for the estimated mean value λs = −0 . 03 , Eq ( 15 ) shows that a deviation transverse to the GEM would be , in the absence of noise , reduced to 3% of its initial magnitude after only one trial . In contrast , the dynamics in the weakly stable subspace did not rapidly correct deviations that were approximately tangent the GEM , and which therefore had little effect on error at the target . For the mean value of λw = 0 . 76 , Eq ( 14 ) shows that , in the absence of noise , 9 iterates would be required to reduce an initial deviation to less than 10% of its initial value . In Fig 8 we show the EPDFs obtained for the normalized lag-1 autocorrelations of fluctuations in the two eigendirections , for all friction participants/conditions . We find in all cases that 0 ≈ |Rs ( 1 ) | ≪ Rw ( 1 ) . Specifically , we estimate Rs ( 1 ) = −0 . 03 [−0 . 24 , 0 . 14] and Rw ( 1 ) = 0 . 76 [0 . 64 , 0 . 88] . These results indicate that the trial-to-trial fluctuations in the weakly stable direction show greater persistence than those in the strongly stable direction . Furthermore , the strong control results in fluctuations that are close to uncorrelated white noise ( since Rs ( 1 ) ≈ 0 ) . As anticipated in the discussion following Eq ( 21 ) , these results are nearly identical to the local stability results in Fig 6 . The EPDFs obtained for the DFA exponents αw and αs for fluctuations in the weakly and strongly stable subspaces , respectively , are shown in Fig 9 . We found αs = 0 . 52 [0 . 44 , 0 . 59] and αw = 0 . 99 [0 . 89 , 1 . 16] . Thus , in all cases 0 . 5 ≈ αs ≪ αw , showing substantial persistence between successive fluctuations in the weakly stable direction , and nearly uncorrelated fluctuations in the strongly stable direction . Thus , the persistence results of Figs 8 and 9 are consistent with each other and , taken together , strongly confirm H3 . Finally , Fig 10 illustrates how the variability ratio σe/σns , which represents an empirical “gain” between intrinsic body-level noise and goal-level variability , was found to linearly scale with the total body-goal sensitivity sTOT ( Eq ( 19 ) ) . The light gray dots in the plot represent values obtained by bootstrapping: one such point was generated for all 8 friction conditions and linear regression was applied within each of 10000 iterations . This process yielded estimates for the slope , a = 0 . 99 [0 . 93 , 1 . 03] , and y-intercept , b = 0 . 21 [−0 . 98 , 1 . 52] . The resulting aggregate fit had an R2 of 0 . 996 . As a check , we used all 8 × 10000 points at once for a single linear fit; this did not change the fit parameters or the R2 value . The figure also includes the average values obtained for each participant/condition , computed independently by bootstrapping , together with error bars representing 95% CIs . The uneven size of the error bars , especially in the horizontal direction , reflects the nonlinearity of sTOT , particularly the factor of β = sin ( θs ) . We see that in each case the mean points fall very near the linear fit , indicating that the scaling relationship held not only in aggregate , but for each participant/condition individually . Indeed , similar fits done for each participant independently yielded R2 estimates of 0 . 962 , 0 . 991 , 0 . 979 and 0 . 992 , values not meaningfully different from the overall value . Thus , we concluded that for all participants/conditions Eq ( 19 ) holds , confirming hypothesis H4 . We conclude this section with an illustration of how our approach overcomes the potential interpretive ambiguity stemming from the coordinate dependence of variance [28 , 40] . As discussed when presenting Eqs ( 22 ) and ( 23 ) , the dynamical analysis carried out here yields quantities that are intrinsic to the observed temporal fluctuations , and hence are coordinate invariant . As a demonstration of this invariance , and its advantage in analyzing motor variability , we constructed a “worst case” coordinate transformation similar in form to Eq ( 12 ) . However , in this case we defined new fluctuation coordinates q = ( q1 , q2 ) T via u = Pq , where the matrix P was obtained from principal component analysis [42] , as follows: let P = SC , in which C is a matrix with columns composed of the eigenvectors ( i . e . , the principal components ) of the fluctuation covariance 〈uuT〉 , and S is a diagonal matrix with the square root of the inverse principal values , 1/σ1 and 1/σ2 , along its diagonal . The result of applying this transformation is that both of the new coordinates q1 and q2 have identical variance , and hence the variance “cloud” in the ( q1 , q2 ) plane is isotropic by construction ( i . e . , the variance ellipse is a circle ) . Fig 11 shows what happens when we apply this transformation to typical data from a single participant and friction condition . In Fig 11 ( a ) we see the original data and the local stability results estimated from it , whereas in Fig 11 ( b ) we see the equivalent analysis carried out on the transformed data . The eigenvalues obtained are identical in both cases , since the original matrix , B ( Eq ( 11 ) ) , and the transformed matrix , P−1BP , are congruent . Furthermore , as discussed following Eq ( 23 ) , the transformed eigenvectors maintain their qualitative relationship with the transformed GEM: that is , the weakly stable subspace is nearly tangent to the GEM , whereas the strongly stable subspace is transverse to the GEM at a much greater angle . Thus , in both cases 0 ≈ θw ≪ θs so that the local stability picture is qualitatively unchanged by the coordinate transformation , and can be used to test a candidate GEM in either case . In sharp contrast , using the shape of the variance ellipse to identify the GEM location works reasonably well for Fig 11 ( a ) , but clearly fails for the case shown in Fig 11 ( b ) . Indeed , using an approach similar to that used to create Fig 11 ( b ) , one can change the shape of the variance ellipse at will , while in all cases maintaining the proper qualitative relationship between the GEM and the weakly and strongly stable subspaces .
Understanding how humans are able to perform accurate and repeatable goal-directed movements in the presence of inherent biological noise [7–11] and neuromotor redundancy [22–24] has been a critical goal of neuroscience research ( e . g . , [45 , 46 , 48] ) since the pioneering work of Bernstein [1] . In recent years , studies addressing this question have focused on using either task manifold ideas to address redundancy ( e . g . , [12–14] ) , or time series analysis methods to study temporal correlation structure ( e . g . , [25 , 51 , 54 , 55] ) . However , these often divergent perspectives have not yet been fully unified into a comprehensive theoretical framework , and it remains an open question whether these various aspects of inter-trial variability represent distinct neurophysiological phenomena , or can be traced back to a single underlying motor regulation process . The work in this paper expands on previous efforts [25 , 28] suggesting that such a unification can be achieved by considering the inter-trial dynamics of fluctuations near a task’s goal equivalent manifold ( GEM ) . These studies have shown that a fundamental feature of such inter-trial fluctuations is that they are dynamically anisotropic in a manner that respects the local geometry of the GEM [25–29] , an observation supported by work carried out from different task manifold perspectives [30 , 54 , 65] . Using a custom-built interactive virtual environment , we studied the variability exhibited by skilled participants as they carried out repeated trials of a simple shuffleboard game . The experiments were used to test theoretical predictions obtained from a new analysis , presented in this paper , of a previously-developed general model for inter-trial error correction [25 , 28] . The assumption of skilled performance , for which body states will remain close to the GEM , yields a simple linear inter-trial control model . The further empirically-supported assumption that inter-trial error correction satisfies a generalized interpretation of the minimum intervention principle ( MIP ) , together with an analysis of geometric stability , yielded theoretical predictions about the geometrical and temporal structure of inter-trial variability , showing analytically how body-level variability generates variability at the goal level . In particular , we showed that the assumptions underlying our analysis give rise to a new scaling relationship ( Eq ( 19 ) ) , which introduces the total body-goal sensitivity , sTOT , a quantity showing how intrinsic goal-relevant fluctuations at the body level are mapped into fluctuations at the goal level . This relationship provides a unification of task manifold , control theoretic , and dynamical ( time series ) perspectives by showing specifically how the GEM geometry , passive sensitivity , and active error correction combine to yield task performance . The predictions resulting from our analysis were summarized in the form of four experimental hypothesis , which were tested using data from four participants playing the shuffleboard game . To demonstrate the generality of the dynamical anisotropy predictions ( H1–H3 ) , and , more importantly , to allow us to tease apart active and passive effects in task performance as specified by the scaling prediction H4 , we had each participant perform the task with two different friction levels , giving a total of eight different participants/conditions . All of our hypotheses were very strongly confirmed: in all cases , the difference between local stability and correlation properties in the weakly and strongly stable directions was just as predicted by theory ( Figs 6–9 ) , confirming H1–H3; and the goal-level performance scaled as predicted across all participants and friction conditions ( Fig 10 ) , confirming H4 . Given the nature of H4 , which concerns the scaling relationship Eq ( 19 ) and therefore depends on all assumptions used in its derivation , these experimental results do more than characterize the behavior for these particular participants executing this particular task . Rather , they serve to validate our general model for inter-trial error-correcting control near the GEM . Thus , while this work does not make any direct ties to underlying physiological mechanisms , our results indicate that the combined geometrical and temporal structure of observed fluctuations can be explained by a single , relatively simple process . This supports the idea that one need not posit separate neurophysiological mechanisms for controlling such disparate features as the geometric distribution of trials about the GEM , the stability of inter-trial fluctuations , and the goal-level performance , but , rather , that all such behaviors arise from a single , unified process of error regulation in the presence of task-level redundancy . Another contribution of this paper is the introduction of statistical bootstrapping [32–34] to the analysis of movement variability data . Using this approach , we were able to estimate the underlying probability distribution for quantities required by each hypothesis ( e . g . , eigenvalues , correlations , etc . ) , thus demonstrating that the predicted dynamical anisotropy is very highly significant in each case individually ( Figs 6–9 ) , without the need for conventional significance testing . Furthermore , this data analysis allowed us to confirm the theoretical performance scaling prediction ( Fig 10 ) to high precision , thus demonstrating that task performance was largely determined by passive sensitivity , which in this case was a function of the friction condition ( Eq ( 8 ) ) . This theoretical prediction is perhaps counterintuitive , because the passive sensitivity is determined entirely by the task’s goal function ( Eq ( 2 ) ) , independent from any consideration of control . However , this behavior occurs precisely because error-correcting control strongly compresses variability onto the GEM . Thus , as shown theoretically by using Eq ( 18 ) in Eq ( 16 ) ( with the understanding that λs ≈ 0 , as shown in Fig 6 ) , the scale of goal-relevant fluctuations is minimized , taking a value proportional to the scale of the strongly-stable component of the intrinsic noise . Therefore , for skilled participants , the resulting performance ( as measured by the RMS error at the goal ) is largely determined by the passive sensitivity , which is a property of the task as defined by the goal function . Finally , as shown in our theoretical discussion and demonstrated with our experimental data , the dynamical approach used for this study yields results that are invariant under quite general ( differentiable and invertible ) coordinate transformations , something that is not true for variability analyses based only on the spatial distribution of body states near a given task manifold . Even in the “worst case” scenario for which coordinates are chosen that render the variability cloud isotropic , so that it contains no information about the location of the GEM , as shown in Fig 11 , the dynamical approach yields correct information about the structure of inter-trial fluctuations . Thus , our data analysis methods resolve the persistent problem of coordinate dependence of variability measures [30 , 40] . This suggests that the dynamical coordinates , as obtained via the transformation Eq ( 12 ) , provide a set of objective , canonical coordinates for the study of inter-trial variability: that is , they represent coordinates that are intrinsic to the regulatory process responsible for inter-trial error correction . These findings again highlight the critical importance of considering fluctuation dynamics [25–27 , 30 , 51–54] in both theoretical and experimental studies aimed at understanding the neuromuscular control of complex movements . While time series analyses alone can yield important descriptive information , in the absence of any underlying model they often have limited explanatory power . Recent efforts have seen the use of time series analyses to interpret model outputs and/or predictions [46 , 48 , 54 , 66] . These efforts have yielded findings qualitatively similar to ours , and consistent with our interpretations of inter-trial variabilty presented both here and elsewhere [25 , 26 , 28 , 29] . Even though these efforts have focused on motor learning , which we do not , conceptually there is a strong affinity between these papers and the work presented here . In [46 , 54 , 66] , van Beers and colleagues used simple linear models with direct error feedback to analyze task performance when reaching to a point [46 , 66] or a line [54] . Their lag-1 autocorrelation analyses for the redundant task of reaching to a line showed strong statistical persistence along the target line and uncorrelated fluctuations perpendicular to it , precisely as we would theoretically predict and very similar to our own findings ( our Figs 8 and 9 ) . In parallel work , Abe & Sternad [30] also obtained similar results applying both lag-1 autocorrelation and DFA analyses to van Beers’ model of the same task . Both studies thus independently support the experimental results presented here . The analytical formalisms presented in the present paper , however , add several important extensions to these experimental observations . First , here we tie these time series analysis approaches directly to the stability properties of the dynamical system that generates the observed fluctuations , as determined by its eigenvalues and eigenvectors ( Figs 6 and 7 ) . Second , by formally defining the task in terms of a goal function ( Eq ( 2 ) ) , we are able to show analytically ( Eq ( 19 ) ) how active and passive properties of the task interact to affect goal level fluctuations , a theoretical prediction that we test and confirm experimentally ( Fig 10 ) . Finally , van Beers’ model accounts only for the correction of goal-relevant errors , that is , of body-level fluctuations perpendicular to the GEM , and thus implements an ideal MIP-based controller with no control acting along the task manifold . However , as we have shown in previous work using models derived using a stochastic optimal control framework [25] , and as discussed here and demonstrated experimentally by us [28] and others [36] , such “pure” MIP controllers are not observed experimentally: that is , we find that the fluctuations along the GEM do not exhibit an unbounded random walk . Furthermore , our approach allows us to demonstrate this deviation from ideal MIP behavior geometrically , as well as in terms of stability and correlation properties . A conclusion of our work is that , while the control observed experimentally is congruent with the task manifold , it is not perfectly aligned with it: instead , the direction of “minimum intervention” ( i . e . , of weakest control ) is close to , but not exactly tangent to the GEM . Nor is the direction of strongest control necessarily perpendicular to the GEM . One possible interpretation of these observations is that there are other competing costs , beyond simple error correction , that are at play during repeated task execution . Other recent attempts to connect temporal analyses to task manifold geometry [27 , 51] have similarly supported our experimental findings , but have not directly shown how such results can be predicted from a general model-based analysis , as the current work does . Dingwell et al . [27] applied lag-1 correlation analyses to a redundant reaching task , but did not directly connect those experimental analyses back to any underlying computational model . Rácz & Valero-Cuevas [51] used DFA analyses on data from a redundant , 3-finger grasping task to provide an experimental demonstration of the need to consider control as acting across both spatial and temporal domains . However , their work again did not provide mathematical theory able to explain and predict the observed behaviors . Nevertheless , in spite of these differences in experimental and/or computational approaches , each of the studies described above obtained findings consistent with our conclusion that the diverse geometrical and temporal aspects of inter-trial variability likely derive from a single underlying motor regulation process . Our approach fully integrates task manifold geometry with ideas from control and dynamical systems theory , and thereby can be used to explain the structure of observed motor variability from a model-based , theoretical perspective . The theory and methods presented in this paper are quite general , and should be applicable to the study of skilled motor performance for a wide range of discrete , or discretizable , tasks . That said , general application can be expected to encounter difficulties , especially for tasks in which the relevant body and/or goal variables are high-dimensional ( so that visualizing the GEM is difficult , if not impossible ) , as well as for tasks in which the goal function and GEM are not readily available in analytical form . In such cases , the basic theory will have to be used to formulate suitable , purely abstract , computational methods . The assumption of skilled motor behavior , which implies that all fluctuations are near the GEM , permitted us to employ linear mathematics in our study . Without this linearity , it would have been much more difficult to make such precise , analytically-derived predictions . However , we did not impose linearity as a mere analytical convenience . On the contrary , our results show that a linear model of “GEM-aware” error correction captures key facets of the observed variability structure with substantial accuracy . The main aims of this paper were to robustly demonstrate the nature of dynamic anisotropy , to show how task performance is generated by the interaction of the GEM geometry and inter-trial error correction , and to demonstrate that such an approach yields results that are not sensitive to the coordinates chosen . As such , our focus on the steady state ( i . e . , learned ) behavior of the inter-trial regulation system was appropriate . But this does not mean that the models and methods presented here would not have value for studies related to motor learning . Indeed , as discussed at some length above , models with a very similar mathematical structure have been used to precisely that end . From a dynamical systems perspective , our approach treats skilled movements as a “stochastic attractor” of the more general perception-action system engaged in motor learning . A logical point of departure for future work aimed at extending our methods to motor learning would be to study how the the “transient” portion of the a learning data set approaches the “steady-state” local geometrical structure uncovered using the methods of this paper . While such explorations would no doubt pose multiple challenges , in principle the theoretical concepts presented here could be extended to address questions of learning and/or adaptation , topics that we see as interesting aims of future work .
|
During the repeated execution of precision movement tasks , humans face two formidable challenges from the motor system itself: dimensionality and noise . Human motor performance involves biomechanical , neuromotor , and perceptual degrees of freedom far in excess of those theoretically needed to prescribe typical goal-directed tasks . At the same time , noise is present in the human body across multiple scales of observation . This high-dimensional and stochastic character of biological movement is the fundamental source of variability ubiquitously observed during task execution . However , it is becoming clear that these two challenges are not merely impediments to be overcome , but rather hold a key to understanding how humans maintain motor performance under changing circumstances , such as those caused by fatigue , injury , or aging . In this work , by studying skilled human participants as they play a virtual shuffleboard game , we demonstrate the fundamental importance of adopting a dynamical perspective when analyzing the motor variability observed over many trials . Using this dynamical approach , we can not only study the geometry of observed inter-trial variability , but can also theoretically describe and experimentally characterize how it is temporally generated and regulated . Furthermore , our theoretical framework and model-based data analysis approach helps to unify previous variability analysis approaches based on stability , correlation , control theory , or task manifolds alone . This conceptual unification supports the idea that such seemingly disparate features of motor variability arise from a single , relatively simple underlying neurophysiological process of motor regulation .
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2016
|
Error Correction and the Structure of Inter-Trial Fluctuations in a Redundant Movement Task
|
Studies have demonstrated cross-reactivity of anti-dengue virus ( DENV ) antibodies in human sera against Zika virus ( ZIKV ) , promoting increased ZIKV infection in vitro . However , the correlation between in vitro and in vivo findings is not well characterized . Thus , we evaluated the impact of heterotypic flavivirus immunity on ZIKV titers in biofluids of rhesus macaques . Animals previously infected ( ≥420 days ) with DENV2 , DENV4 , or yellow fever virus were compared to flavivirus-naïve animals following infection with a Brazilian ZIKV strain . Sera from DENV-immune macaques demonstrated cross-reactivity with ZIKV by antibody-binding and neutralization assays prior to ZIKV infection , and promoted increased ZIKV infection in cell culture assays . Despite these findings , no significant differences between flavivirus-naïve and immune animals were observed in viral titers , neutralizing antibody levels , or immune cell kinetics following ZIKV infection . These results indicate that prior infection with heterologous flaviviruses neither conferred protection nor increased observed ZIKV titers in this non-human primate ZIKV infection model .
Zika virus ( ZIKV ) , is a flavivirus originally isolated from a sentinel rhesus macaque in the Zika forest of Uganda in 1947 [1] and a human in Nigeria in 1953 [2] . Transmission occurs primarily in a human-mosquito cycle , though ZIKV can also be transmitted sexually and from mother to fetus [3] . ZIKV transmission expanded eastward from Africa to Asia where other flaviviruses are endemic , including Japanese encephalitis virus ( JEV ) and the four dengue virus ( DENV ) serotypes [4 , 5] . ZIKV reached the Americas in 2015 , a region with co-circulating DENV1-4 , YFV vaccination programs , and risk of natural YFV infection [4 , 6] . The epidemic intensified in Brazil and spread , with autochthonous transmission documented in fifty-seven other countries , including the United States [7 , 8] . ZIKV infection is typically asymptomatic or manifests as a mild clinical syndrome that often includes fever , rash , and arthralgia , and may also include conjunctivitis , pruritus , muscle pain , headache , and malaise [9] . ZIKV infection has been associated with a range of congenital and neurological abnormalities to include fetal microcephaly , with an estimated risk of 0 . 88–13 . 2% following first trimester infections [10] , and Guillain-Barre syndrome ( GBS ) in approximately 1 in 4 , 000 infected children and adults [11] . To date , 21 countries and territories are reporting either an increased incidence of GBS or laboratory confirmation of ZIKV among GBS cases [7] . Numerous ZIKV vaccine candidates are in pre-clinical and early clinical development to include safety studies planned in flavivirus primed populations [12–15] . Assessing the safety , immunogenicity , and potential for clinical benefit of ZIKV vaccine candidates in flavivirus-naïve populations would be more straightforward but the current epidemiology of ZIKV transmission makes this scenario unlikely . Heterologous flavivirus priming of vaccine trial volunteers could impact the safety profile of , and immune response to , candidate ZIKV vaccines . Pre-existing immunity to non-ZIKV flaviviruses from natural infection or immunization may also provide some level of cross-protection or attenuation upon subsequent ZIKV exposure . Concerns that ZIKV infections may be exacerbated by pre-existing flavivirus immunity are largely driven by epidemiologic and in vitro observations of DENV infections . Cross-reactive but non- or poorly-neutralizing antibodies generated against the precursor membrane ( prM ) or envelope ( E ) structural proteins of one DENV serotype are thought to mediate enhancement of infection upon subsequent exposure to a heterologous serotype through a process termed antibody-dependent enhancement ( ADE ) . In ADE , virions in complex with these antibodies gain an additional means to infect FcγR-bearing cells , leading to increased virus replication . Accordingly , studies have observed increasing viral loads in association with subsequent disease presentation in humans . [16–20] . Cell mediated immunity has also been proposed as a contributor to enhanced infection and disease [21] . Despite these observations , epidemiologic findings regarding increased disease severity during heterologous flavivirus infections have been inconsistent . In a prospective cohort , the presence of JEV-neutralizing antibodies was associated with an increased incidence of symptomatic primary DENV infections [22] , while a second study found a reduction in the severity of dengue disease in a JE-vaccinated cohort [23] . Importantly , immune sera or antibodies to DENV and YFV have demonstrated cross-reactivity with ZIKV and the capability to promote increased infection in vitro [24–28] . In the present study we investigated the potential for prior flavivirus immunity to alter ZIKV titers and immune responses using rhesus macaques , an accepted model of flavivirus infection , that were previously infected with DENV2 , DENV4 , or YFV as could reasonably be seen in a flavivirus endemic population encountering ZIKV for the first time . Viral load , presence of ZIKV in numerous biofluids , clinical events following infection , immune cell phenotypes , and serologic responses were compared between flavivirus-immune and -naïve animals . This study seeks to address the recently published in vitro findings of cross-reactive antibodies and the potential to promote increased ZIKV titers in the context of sequential , in vivo flavivirus infections .
Study events and specimen collections are outlined in S1 Table . Individual animal information is outlined in S2 Table . Six and five rhesus macaques were infected with DENV and YFV , respectively , ≥420 days prior to subcutaneous inoculation with ZIKV ( Brazil-ZKV2015 ) . Specific time intervals and neutralizing antibody titers from these prior infections are outlined in S2 and S3 Tables . Fourteen additional animals confirmed to be serologically naïve for JEV , YFV , West Nile virus ( WNV ) , DENV serotypes 1–4 , and ZIKV prior to study start were inoculated with ZIKV contemporaneously . As such , the three experimental groups are termed naïve , DENV-immune , and YFV-immune . One animal from the DENV- or YFV-immune groups and one animal from the serologically naïve group were sacrificed in sex-matched pairs at intervals throughout the study for future investigations of ZIKV tissue distribution and pathology . Sacrificing of animals at different time points throughout the study limited the availability of biological samples at later time points , accounting for the disparity in data set sample sizes between earlier and later time points . Samples from all remaining animals were included in all analyses unless otherwise stated . To verify that the sera of the DENV- and YFV-immune groups were capable of promoting increased ZIKV infection in vitro , as has been demonstrated in other studies , day 0 sera were assessed . End-point ELISA binding curves demonstrated moderate amounts of cross-reactive antibody to ZIKV in the DENV-immune group and much less cross-reactive antibody in the YFV-immune group ( S1 Fig ) . Day 0 DENV-immune sera also appreciably cross-neutralized ZIKV , with FlowNT50 titers ranging from 40–582 . However , the neutralization curves indicate less potent NAbs and incomplete neutralization of virus infectivity compared to anti-ZIKV control sera ( S2 Fig ) . Finally , the capability of sera from the DENV-immune group and the three most cross-reactive YFV-immune animals ( by end-point ELISA ) to promote increased ZIKV infection was measured using a flow cytometry-based assay of infection in FcγR-bearing cells ( U937 & K562 ) . Pre-incubation of ZIKV with DENV-immune sera promoted infection with 12 . 7- and 18 . 7-fold higher mean peak detected values in U937 and K562 cells , respectively , than virus incubated with naïve control sera ( Fig 1 ) . As expected , when YFV-immune sera were tested , these poorly cross-reactive sera promoted comparatively lower ZIKV infection , with mean peak detected values of 3 . 4- and 2 . 0-fold higher in U937 and K562 cells , respectively , compared to naïve control sera . In order to determine the impact of prior flavivirus infection on ZIKV titers and biofluid distribution in vivo , and in light of the increased ZIKV infection observed in vitro , we quantified ZIKV viral load in the peripheral blood , urine , cerebrospinal fluid ( CSF ) , vaginal fluid and saliva . These biofluids represent many of those most relevant to current ZIKV detection assays , as well as to ZIKV transmission , including vector-borne , sexual , and nonsexual human-to-human transmission , and to ZIKV-associated neurological sequelae [3 , 7 , 29] . No significant differences in RNAemia ( p = 0 . 52 , [2 , 23] degrees of freedom [d . f . ] , F statistic = 0 . 67 ) or viremia ( p = 0 . 76 , [2 , 23] d . f . , F statistic = 0 . 28 ) were observed between the three experimental groups ( Fig 2 ) , nor were there differences observed in the respective day of peak titer ( p = 0 . 45; p = 0 . 08 ) , magnitude of peak titer ( p = 0 . 12; p = 0 . 10 ) , or duration of RNAemia or viremia ( p = 0 . 60; p = 0 . 76 ) . The group by time interaction in the mixed model was significant for RNAemia ( p = 0 . 0084 , [18 , 161] d . f . , F statistic = 2 . 09 ) but not for viremia ( p = 0 . 34 , [18 , 161] d . f . , F statistic = 1 . 12 ) ; post-hoc analysis of RNAemia by day post infection indicated that the source of this significance was isolated to days 1 , 8 , and 10 . It should be noted that all day 1 values , and most of days 8 and 10 values , were below the limit of detection ( 10 genome equivalents per reaction ) and days 8 and 10 demonstrated a comparatively limited number of positive samples ( nine and four total , respectively ) , suggesting low biological significance of this finding . The relationship between RNAemia and viremia is shown by individual animals in S3 Fig , and coincides well when considering the respective limits of detection and the ratio of genome equivalents to plaque forming units ( PFU ) determined previously ( approx . 1000:1 [12] ) . All biofluid types tested exhibited ZIKV-positive specimens at one or more time points in all groups with the exception of vaginal fluid samples from DENV-immune animals , though this group contained only 2 females on day 0 . No association was observed between the magnitude or proportion of ZIKV-positive biofluids and experimental group ( Table 1 , S4 Fig ) . We next sought to determine if prior flavivirus infection could alter the development of immune responses against ZIKV . Anti-ZIKV IgM and IgG kinetics measured by ZIKV-capture ELISA demonstrated classic exposure responses in all experimental groups ( Fig 3 ) . IgM titers rose between days 7 and 9 , plateaued within two weeks , and began to decline by day 28 . Although IgM titers in the DENV-immune and YFV-immune animals appeared to decline moderately faster than in the naïve animals , the overall IgM titer curves did not differ significantly between groups ( p = 0 . 26 , [20 , 133] d . f . , F statistic = 1 . 21 ) . In contrast , IgG titer curves differed significantly between groups throughout the duration of the study ( p<0 . 0001 , [20 , 133] d . f . , F statistic = 7 . 43 ) . IgG in the DENV-immune group cross-reacted with ZIKV from day 0 at a mean titer of 1100 , rose around day 7 , and plateaued by day 14 lasting through the last time point tested ( day 28 ) . IgG titers in the YFV-immune group did not appreciably bind ZIKV on day 0 , but displayed nearly identical development to that of the DENV-immune group , achieving similar maximum titer and duration . IgG titers in the naïve group displayed similar kinetics to that of the immune groups , but plateaued approximately 13-fold lower . The peak IgG titers were significantly different between groups ( p = 0 . 029 , 2 d . f . , F statistic = 4 . 19 ) . IgM and IgG kinetics are displayed by individual animal in S5 Fig . Neutralizing antibody ( NAb ) kinetics against ZIKV of sera from naïve , DENV-immune , and YFV-immune animals were also assessed . Pre-infection ( day 0 ) neutralization titers are displayed in S4 Table; only the DENV-immune animals demonstrated cross-reactive , anti-ZIKV NAb titers , in agreement with the ELISA binding results . Despite this expected difference in neutralization capacity , NAb kinetics following ZIKV inoculation did not differ among groups ( Fig 4 ) . In all experimental groups , mean anti-ZIKV NAb titers rose from day 7 , peaked by day 14 at similar titers among groups , and remained high out to the last time point measured ( day 28 ) . Potential alterations to the immune response were assessed further by characterizing the kinetics of cellular immune activation via ex vivo whole blood immunophenotyping . Multiparametric flow cytometry was performed every 2–3 days through day 22 to identify activated CD4+ and CD8+ T cells and natural killer cells ( CD159a+ ) , as determined by HLA-DR and Ki67 dual expression , as well as CD20-HLA-DR+ and CD20+CD27+ lineage-negative B cells ( CD3-CD14-CD16-CD11c- ) , plasmacytoid ( CD303a+ ) and myeloid-lineage ( CD1c/BDCA-1+ ) dendritic cells ( HLA-DR+CD20-CD14-CD16- ) , and three populations of monocytes ( HLA-DR+CD20- ) defined by their CD14 and CD16 expression profiles ( CD14+CD16- , CD14+CD16+ , and CD14-CD16+ ) . Gating strategies are displayed in S6 Fig . Importantly , no statistically significant differences in median frequencies were found between groups for any cell population on any individual day . With regard to the kinetics of cellular immune activation irrespective of group , as expected , we saw evidence of T and NK cell activation within the first two weeks post-infection as well as movement in the frequencies of various B cell , DC , and monocyte populations ( Fig 5 ) . Activated CD4+ T cells displayed two peaks , days 4 and 9 , as did activated CD8+ T cells , with the second peak delayed relative to CD4+ T cells . Activation of both CD4+ and CD8+ T cells increased at day 22 consistent with the peak adaptive response occurring after the clearance of viremia as seen previously for DENV in humans [30–32]; investigation of later time points are necessary to further define the kinetics of this response . Plasmacytoid dendritic cells ( pDCs ) decreased in frequency in the first two weeks post-infection , whereas mDCs and CD14+CD16- monocytes increased . CD20+CD27+ lineage-negative B cells , expected to contain the memory B cell population , peaked in frequency on day 9; this kinetic profile is more consistent with what we might expect for plasmablasts , necessitating future experiments demonstrating ex vivo production and/or specificity of antibody to further define this population . Following virus challenge , all animals were observed daily for clinical course , clinical laboratory , and , in the sacrificed animals , gross pathologic evidence of ZIKV disease . Detailed findings are presented in S1 Text . There were no local or systemic signs of disease noted in the naïve compared to the primed animal groups . The same was true across a broad range of hematologic and biochemical values . Cerebrospinal fluid analyses also failed to reveal a difference between groups . Finally , except for mild peripheral lymphadenopathy noted in both naïve and YFV-primed animals , there were no other findings on gross pathologic examination .
Our results indicate that pre-existing immunity to antigenically related flaviviruses neither increased nor diminished the magnitude of ZIKV viral titers and did not alter ZIKV kinetics in peripheral blood and other biofluids , nor did it alter the kinetics of ZIKV-induced immune responses , relative to flavivirus-naïves in our cohort of rhesus macaques . Further , although there were minor fluctuations in serum chemistry values , no clinical signs were evident in the animals in association with experimental group . Experimental groups with prior flavivirus infection exhibited significantly higher peak anti-ZIKV IgG titers , but this difference did not translate into differences in peak antibody neutralization capacity . In contrast to the ZIKV infection data presented here , secondary DENV infections have revealed highly serotype-cross-reactive CD4+ and CD8+ T cells , which have been hypothesized to contribute to disease severity [30 , 31 , 33–35] . Future experiments will address the specificity and/or cross-reactivity of these cells , although T-cell responses have been shown to be predominately specific between ZIKV and DENV upon ex vivo stimulation [24] . The present study benefits from utilizing animals that were previously infected with antigenically related flaviviruses 14 months or more prior to inoculation with ZIKV . This places the animals well past the cross-protective interval and ensures a mature immune response as described for DENV [36–38] . In order to confirm that the animals used in this study were capable of generating the same in vitro biological activities as previously described , we performed ELISAs , neutralization titrations , and antibody-mediated infection assays similar to those previously published [24–28] . Accordingly , our DENV-immune animals demonstrated the capability to promote substantially increased levels of ZIKV infection in both of the human cell lines used previously , U937 and K562 , and at similar starting dilutions . Despite this in vitro capability , no alterations to ZIKV viral titers were apparent in vivo in the specimens tested . These data are consistent with a previous study of DENV infection in human infants [39] , as well as with studies of flaviviruses for which clinically apparent ADE is not known to occur; WNV , for example , exhibits in vitro ADE when using sub-neutralizing concentrations of antibody , but this does not appear to translate to observable enhancement of human illness [40] . Similarly , another study demonstrated no effects on ZIKV viremia or tissue distribution when an anti-DENV mAb with known in vitro infection-mediating capability was administered to a non-permissive mouse model 24 hours prior to ZIKV inoculation , though the authors acknowledge this discrepancy could be due to a limitation of the mouse model [24] . Additional studies with a shorter interval between initial flavivirus priming or infection and subsequent ZIKV challenge , as well as studies including pregnant females , would be required to more fully examine the potential impact of heterologous flavivirus priming . Rhesus macaques have successfully demonstrated immunologically-induced increases of DENV titers in peripheral blood previously , with both passive transfer of antibody and sequential infection experiments capable of invoking both humoral and cellular immune effects . Rhesus macaques sequentially infected with DENV2 following a heterologous serotype of DENV successfully produced consistently higher daily DENV2 viremia titers as compared to primary DENV2 infection [41] . Intravenous passive transfer with sub-neutralizing concentrations of anti-DENV pooled human cord-blood serum 15 minutes prior to infection promoted up to a 51-fold increase in cumulative DENV2 viremia titers [42] . More recently , a >100-fold increase in DENV4 viremia titers was promoted in rhesus macaques by administration of sub-neutralizing concentrations of a humanized , chimpanzee-derived , anti-DENV monoclonal antibody 24 hours prior to infection [43] . Analysis of the data from this and other investigations supports the use of non-human primates as a reproducible and informative ZIKV infection model [44] . Comprehensive autopsy and organ system examinations , currently in progress , will provide additional information in this regard . However , similar to DENV , limitations exist with using NHPs as a ZIKV disease model . This is especially apparent for relatively rare flavivirus disease manifestations , such as dengue hemorrhagic fever or accelerated disease or neurologic syndromes seen with ZIKV , where the requirement to study a hundred or more animals is infeasible . Alternatively , immunologic enhancement of ZIKV infection and any potentially associated clinical manifestations might not occur in NHPs in vivo . Our experiments do not definitively rule out a possible role of immunologic enhancement in ZIKV-associated neurological and congenital abnormalities; the present data do not address antibody-virus complexes in the context of traversing anatomical barriers , perhaps through utilization of the Fc-receptor-bearing Hofbauer cells of the placenta , nor does the present study incorporate pregnant NHPs whose varying immunological states might affect the outcome [45 , 46] . As animal models of maternal-fetal ZIKV transmission improve and more is known regarding the pathophysiology of ZIKV and in utero infection , targeted studies in flavivirus primed , pregnant animals can be performed . That said , the in vitro experiments in this and previous studies have demonstrated the potential for anti-DENV antibodies to promote subsequent ZIKV infection of FcγR-bearing cell lines in vitro , but the inability of this phenomenon to translate to increased ZIKV titers in the biofluids of an otherwise relevant in vivo model is of key importance in order to inform the approach to large scale clinical studies in flavivirus endemic human populations . It is only in these types of clinical studies where the impact of previous flavivirus infection on subsequent ZIKV diseases and its impact on the safety and efficacy of ZIKV vaccines can be definitively established .
This study was approved by the Institutional Animal Care and Use Committee , and research was conducted in compliance with the Animal Welfare Act and other federal statutes and regulations relating to animals . Experiments involving animals adhered to principles stated in the Guide for the Care and Use of Laboratory Animals from the National Research Council . The Walter Reed Army Institute of Research ( WRAIR ) is fully accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International . Previous studies have demonstrated cross-reactivity of anti- DENV antibodies in human sera against ZIKV , promoting increased ZIKV infection of cells in vitro . However , the correlation between in vitro and in vivo findings is not well characterized . As such , we evaluated the impact of heterotypic flavivirus immunity on ZIKV titers in biofluids of rhesus macaques utilizing flaviviruses with geographic and antigenic similarity: DENV serotypes 2 and 4 , and yellow fever virus . One animal from the DENV- or YFV-immune groups and one animal from the serologically naïve group were sacrificed in sex-matched pairs at intervals throughout the study for future investigations of ZIKV tissue distribution and pathology . Sample size was determined based upon availability of previously infected animals , rather than by sample size estimation using a desired power or known effect size . The number of naïve animals was chosen to exceed the combined total of previously infected animals such that future analysis of long-term serological data would still contain five animals through the final necropsy . All animals were infected with ZIKV contemporaneously in a controlled laboratory experiment . Study events and specimen collections were determined prior to study start and are outlined in S1 Table . Individual animal information , time intervals since prior flavivirus exposure , and prior exposure neutralizing antibody titers are outlined in S2 and S3 Tables . All samples were included in all analyses except where described below . Group allocation and data analysis occurred in an unblinded manner . Healthy , adult , Indian origin rhesus macaques ( Macaca mulatta ) were obtained from Covance Research Products , Alice , Texas ( colony bred ) . All animals utilized in this study were tested for JEV , WNV , YFV , and DENV1-4 antibodies by a sensitive screening virus neutralization assay prior to initial infection . Animals were anesthetized with ketamine/acepromazine ( 11 mg /Kg ) / ( 0 . 55 mg/Kg ) , intramuscularly ( IM ) , with a 1 cc syringe and 21 to 23 gauge , 3/4 to 1 inch needle in the caudal thigh prior to all procedures . Euthanasia was humanely performed via exsanguination in accordance with the AVMA Guidelines on Euthanasia prior to euthanasia after deep sedation with ketamine ( 5–12 mg/Kg ) and dexmedetomidine ( 0 . 04 mg/kg ) . Following blood collection , death was ensured by administration of sodium pentobarbital IV 1 . 0ml/4 . 5kg ( 86 . 4mg/kg ) via catheter . Death was confirmed by physical exam and auscultation to verify cardiac arrest by a licensed veterinarian . U937 ( ATCC no . CRL-1593 . 2 , ATCC , Manassas , VA ) , K562 ( ATCC no . CCL-243 , ATCC ) , and U937-DC-SIGN ( ATCC no . CRL-3253 , ATCC ) cell lines were utilized in this study . These lines were verified to be authentic , using short tandem repeat profiling , morphology , and cytochrome C oxidase I testing , and free of contamination by ATCC prior to use . ZIKV strain Brazil ZKV2015 ( ZIKV-BR ) was inoculated subcutaneously as 6 . 0 log10 genome equivalents ( 3 . 0 log10 PFU ) diluted in unsupplemented RPMI media to one mL . ZIKV stock was generated as previously described [12] . DENV2 strain S16803 , DENV4 strain H241 , and YFV strain 17D were produced in Vero-81 cell culture and inoculated subcutaneously at a dose of 4 . 5 log10 PFU in 0 . 5 ml of sterile culture fluid . DENV1-4 ( strain Western Pacific 1974 , S16803 , CH53489 , TVP-360 , respectively ) , YFV strain 17D , ZIKV strain Paraiba-Brazil/2015 , and JEV strain SA14-14-2 were utilized in ELISA , MN50 , FlowNT50 , and PRNT assays . Viruses utilized in MN50 and PRNT assays were produced in Vero cells . Viruses utilized in ELISA and FlowNT50 assay were produced in C6/36 cells . Virus used in ELISA was purified by ultracentrifugation over a 30% sucrose solution and resuspended in PBS . Samples were collected on days 4 , 7 , 10 , 14 , and 22 . Saliva and vaginal fluid were collected using sterile , dry cotton swabs then placed into 1 mL of EMEM supplemented with 10% fetal bovine serum , 1% sodium bicarbonate , and 1% L-glutamine . Urine was collected via cystocentesis under anesthetization . Samples were aliquoted and stored at -80°C until use . Viral load in sera or plasma ( RNAemia ) , CSF , urine , saliva , and vaginal fluid were determined using an RT-qPCR assay as previously described [13] . RNA was extracted from sera on days 1 , 3 , 5 , 6 , 8 , and 10 and from plasma on days 2 , 4 , 7 , and 9 due to animal welfare collection volume constraints . Viral loads were calculated as genome equivalents/mL . Limit of detection herein is defined as the lowest value in the standard curve that can be detected in greater than 95% of assay runs , which was 10 genome equivalents/reaction or 2500 genome equivalents/mL . Plaque titration of viruses in inocula and ZIKV viral load ( viremia ) in sera were determined by standard plaque assay on Vero cell monolayers . Limit of detection was 25 plaque-forming units/mL . End-point anti-ZIKV IgG and IgM ELISA titers on days 0 , 2 , 4 , 7 , 9 , 11 , 14 , 16 , 18 , 22 , and 28 were determined using ZIKV-capture ELISA as previously described [47] . This protocol utilized negative control , pre-infection serum from animal 10U015 , positive control anti-ZIKV serum from animal 09U024 on day 16 , and goat anti-monkey IgM HRP-conjugated secondary antibody ( catalog no . 074-11-031 , KPL , Gaithersburg , MD ) or goat anti-monkey IgG ( H+L ) HRP-conjugated secondary antibody ( catalog no . PA1-84631 , ThermoFisher Scientific , Waltham , MA ) ; the anti-IgG antibody might react with additional antibody isotypes due to the use of light chains in the immunogen preparation , though this has not been determined empirically . Neutralizing antibody titers in heat-inactivated sera preceding ( day -420 ) and 28 days post-inoculation ( day -392 ) with DENV or YFV were determined using a 96-well , high-throughput , ELISA-based microneutralization assay ( MN50 ) in Vero cells as previously described [48] . Neutralizing antibody titers in heat-inactivated sera pre-infection ( days -30 and 0 ) and post-inoculation with ZIKV ( days 7 , 14 , 21 , 28 ) were determined using a 96-well , high-throughput , flow cytometry-based neutralization assay cells as previously described , with modification [49] . Serial dilutions of sera are mixed with an equal volume of virus , diluted to achieve 10–15% infection of cells/well , and incubated for 1 hr at 37°C . After 1 hr of incubation , an equal volume of medium ( RPMI-1640 supplemented with 10% FBS , 1% penicillin/streptomycin , 1% L-glutamine ( 200mM ) , and 1% non-essential amino acids ( 10mM ) ) containing 5x104 U937-DC-SIGN cells are added to each serum-virus mixture and incubated 18–20 hr overnight in a 37°C , 5% CO2 , humidified incubator . Following overnight incubation , the cells are fixed , permeabilized and immunostained with flavivirus group-reactive mouse monoclonal antibody 4G2 , and secondary polyclonal goat anti-mouse IgG PE-conjugated antibody ( catalog no . 550589 , BD Biosciences , San Jose , CA ) . The percent infected cells are quantified on a BD Accuri C6 Plus flow cytometer ( BD Biosciences , San Jose , CA ) . Data were analyzed by nonlinear regression to determine 50% endpoint titers in GraphPad Prism 6 . Day 7 serum samples for animals 07U025 and 09U024 were excluded from analysis due to insufficient volume . Standard plaque-reduction neutralization tests ( PRNT ) on Vero cell monolayers were utilized as a screening tool of pre-study sera for determining serologically flavivirus-naïve animals at a 1:10 dilution of heat-inactivated sera . Neutralizing antibody titers in pre-infection ( day -30 ) sera against YFV were determined by 50% end-point titration ( PRNT50 ) . In vitro antibody-dependent enhancement of infection was quantified as previously described , with modification similar to that used in the FlowNT50 [24–26] . Beginning at 1:40 , two-fold serial dilutions of heat-inactivated day 0 sera were incubated with virus ( sufficient to infect 10–15% of U937-DC-SIGN cells ) at 1:1 for 1 hr at 37°C . This mixture is then added to a 96-well plate containing 5x104 cells ( U937 or K562 ) per well in duplicate . Cells were infected 18–20 hr overnight in a 37°C , 5% CO2 , humidified incubator . Processing and quantification continued as in the FlowNT50 methods . Fold-infection relative to control serum is reported . Samples for animals 09U024 and M228 from the YFV-immune group were not tested , as they exhibited minimal binding by ELISA . Whole blood samples were drawn on days 0 , 2 , 4 , 7 , 9 , 11 , 14 , 16 , 18 , and 22 post-infection from all live animals ( in-life draws ) and from all necropsied animals on the day of sacrifice ( necropsy draws ) . All blood processing was performed at room temperature unless otherwise specified . For in-life draws , one 2 . 7-mL blood collection tube containing sodium citrate ( BD-363083 , BD Biosciences ) was drawn from each animal . Once received in the lab , the blood was immediately transferred to a 15-mL conical tube and 100 μL was transferred into each of three FACS tubes for ex vivo phenotyping analysis . The remaining blood was centrifuged at 300 xg for 8 min , and approximately 700 μL plasma was transferred to a 2-mL purple-cap tube for subsequent centrifugation ( 1200 xg for 8 min ) , aliquoting , and cryopreservation at -80°C . The blood was then resuspended in approximately 3 mL of warm phosphate-buffered saline ( PBS ) and layered on top of 3 mL ficoll ( Ficoll-Paque PLUS , GE Healthcare ) before centrifugation at 400 xg for 30 min . The PBMC layer was transferred to a clean 15-mL conical tube and washed several times in PBS . PBMC were then resuspended in a solution of 90% fetal bovine serum ( FBS ) plus 10% dimethyl sulfoxide ( DMSO ) and transferred into cryovials for subsequent freezing . Samples were cryopreserved using a StrataCooler ( Agilent Technologies , Santa Clara , CA ) , placed at -80°C for 24–72 hours followed by long-term storage in vapor-phase liquid nitrogen . For necropsy draws , several 8-mL cell preparation tubes containing sodium citrate ( BD362761 , BD Biosciences ) were drawn from each sacrificed animal . Once received in the lab , the blood was immediately transferred to a sterile bottle and diluted 1:1 in warm PBS , then transferred onto a layer of ficoll at a 2:1 ratio in 50-mL conical tubes . Tubes were centrifuged at 400 xg for 30 min , and the PBMC layer was isolated and transferred to a clean 50-mL tube for subsequent washing and cryopreservation as described above for the in-life samples . Whole blood samples were collected on days 0 , 2 , 4 , 7 , 9 , 11 , 14 , 16 , 18 , and 22 for ex vivo immunophenotyping by multiparametric flow cytometry . Blood was collected in blood collection tubes containing sodium citrate and transferred to FACS tubes for staining with three different antibody panels , including one intracellular staining panel ( Panel 1 ) and two surface-only panels ( Panels 2 and 3 ) . Panel 1 included the following antibodies: anti-CD3-A700 ( clone SP34-2 , BD Biosciences , San Jose , CA ) ; anti-CD4-BV711 ( clone SK3 , BD Biosciences ) ; anti-CD8-BV510 ( clone SK1 , BD Biosciences ) ; anti-CD45-BV785 ( clone D058-1283 , BD Biosciences ) ; anti-CD159a-PE-Cy7 ( clone Z199 , Beckman Coulter , Indianapolis , IN ) ; anti-HLA-DR-BV650 ( clone L243 , BioLegend , San Diego , CA ) ; and anti-Ki67-A488 ( clone B56 , BD Biosciences ) . Panel 2 included the following antibodies: anti-CD3-APC-Cy7 ( clone SP34-2 , BD Biosciences ) ; anti-CD11c-BV421 ( clone 3 . 9 , BD Biosciences ) ; anti-CD14-A700 ( clone M5E2 , BD Biosciences ) ; anti-CD16-BV510 ( clone 3G8 , BD Biosciences ) ; anti-CD20-FITC ( clone L27 , BD Biosciences ) ; anti-CD27-BV650 ( clone O323 , BioLegend ) ; and anti-HLA-DR-PE-Dazzle594 ( clone L243 , BioLegend ) . Panel 3 included the following antibodies: anti-CD16-APC-Cy7 ( clone 3G8 , BioLegend ) ; anti-CD1c-BV421 ( clone L161 , BioLegend ) ; anti-CD11c-PE-Dazzle594 ( clone 3 . 9 , BioLegend ) ; anti-CD14-A488 ( clone M5E2 , BD Biosciences ) ; anti-CD303a-APC ( clone 201A , eBioscience , San Diego , CA ) ; and anti-HLA-DR-BV605 ( clone L243 , BioLegend ) . For surface staining , 100 μL staining mix was added directly to 100 μL whole blood and incubated at room temperature ( RT ) for 15 min . Then 1 mL per tube red blood cell lysis buffer ( BD Pharm Lyse , BD Biosciences ) was added , and the tubes were vortexed prior to incubation at RT for an additional 15 min . Samples were then washed several times in flow wash buffer ( 2% fetal bovine serum in phosphate-buffered saline ) . For Panels 2 and 3 , the samples were fixed using 4% formaldehyde ( RT , 15 min ) and washed . For Panel 1 , samples were resuspended in a fixation/permeabilization buffer ( Foxp3 Staining Buffer Set , eBioscience ) for 15 min at RT followed by washing and an additional permeabilization step for 15 min at RT . Samples were stained intracellularly with Ki67 antibody diluted in perm buffer for 15 min at RT and then washed . Data were acquired on a BD LSRFortessa and analyzed using FlowJo v10 and GraphPad Prism v6 software . Data points with less than 1000 events in the parent population ( for example , total CD4+ T cells ) were excluded from the analysis . Panel 2 and 3 data from Days 0 and 7 were excluded from the analysis due to technical issues . Complete necropsies were performed under biosafety level 2 by a veterinary pathologist immediately following euthanasia at scheduled post-exposure time points per protocol . Tissues from all major organ systems were collected from each animal and immersion fixed in 10% neutral buffered formalin . Select fresh tissues were collected for future RNA and virus isolation investigations . In addition , select tissues were identified for future transmission electron microscopy and fixed in a solution of 4% formaldehyde with 1% glutaraldehyde buffered by sodium phosphate monobasic at pH 7 . 4 . Histopathology samples from all major organ systems were routinely processed , embedded in paraffin , sectioned , and stained with hematoxylin and eosin . Hematologic analysis was obtained from whole blood samples collected in purple-topped EDTA tubes . Hematologic analysis was conducted using a Sysmex XT-2000iV Hematology Analyzer ( Sysmex America , Lincolnshire , IL ) . The hematology parameters analyzed included white blood cell ( WBC ) count , red blood cell ( RBC ) count , hemoglobin ( HGB ) , percentage hematocrit ( HCT ) , mean corpuscular volume ( MCV ) , mean corpuscular hemoglobin ( MCH ) , mean cell hemoglobin concentration ( MCHC ) , platelet ( PLT ) count , red cell distribution width ( RDW ) , mean platelet volume ( MPV ) , reticulocyte percentage , and reticulocyte count . References ranges utilized were in-house intervals based upon routine physicals of 200 rhesus monkeys from the WRAIR animal colony not involved in studies . Serum chemistry analysis was obtained from whole blood collected in gold-topped serum separator tubes . Serum was analyzed for glucose , urea nitrogen , creatinine , sodium , potassium , chloride , carbon dioxide , calcium , phosphorus , cholesterol , triglycerides , total protein , albumin , aspartate aminotransferase ( AST ) , alanine transaminase ( ALT ) , lactate dehydrogenase ( LDH ) , creatine kinase ( CK ) , alkaline phosphatase ( ALKP ) , gamma glutamyltransferase ( GGT ) , and total bilirubin using a Vitros 350 Chemistry System ( Ortho Clinical Diagnostics , Raritan , NJ ) . Cerebral spinal fluid was collected via lumbar puncture ( in-life and time of sacrifice ) or cisternal puncture ( time of sacrifice ) . Tubes were placed into 4°C upon collection and manipulated on ice . Tubes were mixed using low-speed vortex . Cell counts were performed using trypan blue ( 0 . 4% ) viability staining on a hemocytometer . For in-life ( low volume ) collections , aliquots of neat CSF were frozen at -80°C for protein and virus quantification . For collections performed at the time of sacrifice , a neat aliquot was frozen at -80°C for protein quantification . The remaining volume was centrifuged at 800xg for 5 minutes at 4°C . The supernatant was stored in aliquots at -80°C for virus quantification . The remaining cell pellet was resuspended in approximately 500uL residual CSF and mixed 1:1 with fetal bovine serum containing 20% dimethyl sulfoxide . Tubes were placed into StrataCoolers ( Agilent Technologies , Santa Clara , CA ) , frozen at -80°C for 24 hours , then transferred to LN2 for later use . CSF total protein analysis was obtained from CSF aliquots using a Vitros 350 Chemistry System ( Ortho Clinical Diagnostics , Raritan , NJ ) . Differences in proportions of abnormal laboratory values were assessed by Fisher’s exact test and adjusted for multiple comparisons using the False Discovery Rate ( FDR ) correction . Changes from baseline laboratory values were assessed by the Kruskal-Wallis test and were adjusted using FDR . Differences in clinical parameters ( weight and temperature ) and changes from baseline values were also assessed by the Kruskal-Wallis test and were also adjusted using FDR . Mean magnitude of peak titers were compared across groups using the Kruskal-Wallis test . Day of peak RNAemia or viremia was assessed by Kaplan-Meier analysis and logrank test . Viral loads were log10-transformed to meet test assumptions and changes in viral load and antibody titers were examined using methods of longitudinal data analysis . Specifically , we estimated changes within individual macaques and between experimental and comparison groups from a random effects linear model using the SAS MIXED procedure for repeated measures . This method was chosen to account for unequal and declining sample sizes , and it includes an estimate of variation within group . Model-selection strategies were employed to adjust for potentially important covariates . Variance-covariance structure and model-fit diagnostics were assessed for each model . Differences in peak antibody binding titers were assessed using an ANOVA model . Differences in cellular phenotyping data were determined using the Kruskal-Wallis test and adjusted using FDR . All data analyses were performed using SAS version 9 . 4 ( SAS Institute , Cary , North Carolina ) . All tests performed were two-tailed tests unless otherwise noted . Significance was assessed at α = 0 . 05 . The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request .
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Zika virus ( ZIKV ) is a mosquito-borne , emerging flavivirus . In addition to asymptomatic or mild febrile manifestations , ZIKV infection in humans is associated with comparatively rare congenital and neurological abnormalities . Previous in vitro studies have demonstrated cross-reactivity of antibodies derived from dengue virus infections with ZIKV , as well as antibody-mediated enhancement of infection in cell culture . Therefore , there is concern among vaccinologists and the public health community that the more severe disease manifestations could result from prior immunity , either from natural infection or vaccination , to antigenically-related flaviviruses ( e . g . , dengue , yellow fever , Japanese encephalitis ) . In this study , we evaluated the impact of prior immunity to dengue or yellow fever virus on ZIKV infection in a non-human primate model . After confirming that our immune cohorts were capable of recapitulating the published in vitro observations of cross-reactivity and enhancement , we looked for alteration of viral titers in peripheral blood , urine , cerebrospinal fluid , saliva , and vaginal secretions , as well as alterations in gross pathology , clinical parameters , and immune response , as compared to our flavivirus-naïve cohort . Importantly , no significant differences between flavivirus-naïve and primed animals were observed in viral titers or biofluid distribution , neutralizing antibody levels , or immune cell kinetics following ZIKV infection .
|
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2017
|
Impact of prior flavivirus immunity on Zika virus infection in rhesus macaques
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The cardiac muscarinic receptor ( M2R ) regulates heart rate , in part , by modulating the acetylcholine ( ACh ) activated K+ current IK , ACh through dissociation of G-proteins , that in turn activate KACh channels . Recently , M2Rs were noted to exhibit intrinsic voltage sensitivity , i . e . their affinity for ligands varies in a voltage dependent manner . The voltage sensitivity of M2R implies that the affinity for ACh ( and thus the ACh effect ) varies throughout the time course of a cardiac electrical cycle . The aim of this study was to investigate the contribution of M2R voltage sensitivity to the rate and shape of the human sinus node action potentials in physiological and pathophysiological conditions . We developed a Markovian model of the IK , ACh modulation by voltage and integrated it into a computational model of human sinus node . We performed simulations with the integrated model varying ACh concentration and voltage sensitivity . Low ACh exerted a larger effect on IK , ACh at hyperpolarized versus depolarized membrane voltages . This led to a slowing of the pacemaker rate due to an attenuated slope of phase 4 depolarization with only marginal effect on action potential duration and amplitude . We also simulated the theoretical effects of genetic variants that alter the voltage sensitivity of M2R . Modest negative shifts in voltage sensitivity , predicted to increase the affinity of the receptor for ACh , slowed the rate of phase 4 depolarization and slowed heart rate , while modest positive shifts increased heart rate . These simulations support our hypothesis that altered M2R voltage sensitivity contributes to disease and provide a novel mechanistic foundation to study clinical disorders such as atrial fibrillation and inappropriate sinus tachycardia .
The cardiac muscarinic receptor ( M2R ) plays a crucial role in regulating heart rate variability and vulnerability to atrial arrhythmia by modulating the acetylcholine ( ACh ) activated K+ current IK , ACh . Cardiac KACh channels are heteromultimers composed of two G-protein-coupled inward rectifier K+ channel subunits , Kir 3 . 1 and Kir 3 . 4 [1] . ACh activation of M2R triggers dissociation of the G beta-gamma subunits ( Gβɣ ) that in turn directly activate Kir 3 . x subunits to conduct IK , ACh . Unexpectedly , M2Rs were discovered to possess an intrinsic ability to sense transmembrane voltage [2] and the affinity of the receptor for ligands was noted to vary in response to changes in membrane voltage [3] . In particular , the affinity of the receptor for ACh is increased at hyperpolarized membrane potentials and decreased at depolarized potentials . The changes in affinity exert a downstream effect on the KACh channel such that the channel is more active ( more current ) at hyperpolarized potentials and less active ( less current ) at depolarized potentials . The observation that M2Rs are intrinsically voltage sensitive has profound implications for cellular signaling in excitable tissues , such as heart . For example , voltage sensitive behavior provides a mechanistic explanation for a decades-old enigmatic process called IK , ACh “relaxation” gating . Relaxation gating refers to a time-dependent change in current magnitude following a depolarizing or hyperpolarizing voltage step [4] and has important consequences for shaping the cardiac action potentials ( AP ) , especially in the sinus node . We recently proposed that relaxation gating represents a voltage dependent change in ACh affinity induced by voltage dependent conformational changes within M2R [5] . Our experimental data provide a mechanistic basis to explain the participation of IK , ACh in the modest chronotropic effects induced by resting vagal tone . As a result of conformational changes in the M2R , the affinity for ACh varies throughout the cardiac electrical cycle such that low ( subsaturating ) ACh concentrations preferentially activate IK , ACh during diastolic membrane voltages thereby slowing the spontaneous firing rate without appreciably altering AP duration ( APD ) . Alterations in the voltage sensitivity of M2R could theoretically contribute to cardiovascular diseases that clinically present with apparent changes in vagal tone . For example , genetic variants in M2R that shift the receptor occupancy into the hyperpolarized state would be expected to increase the affinity of the receptor for ACh and thus activate more KACh channels at a given ACh concentration ( or degree of vagal tone ) . Accordingly , genetic variants in M2R that shift the receptor occupancy into the hyperpolarized state might explain the clinical phenotype of vagally-mediated atrial fibrillation ( AF ) , patients who present with bradycardia in the setting of physiological ( basal ) ACh concentrations . Alternatively , genetic variants in M2R that shift the receptor occupancy into the depolarized state would be expected to decrease the affinity of the receptor for ACh and thus fewer KACh channels activate at a given ACh concentration ( or given degree of vagal tone ) . This would decrease the effects of vagal modulation of heart rate , thereby increasing basal heart rate , as observed in the syndrome of inappropriate sinus tachycardia ( IST ) . To provide insights into the contribution of M2R voltage sensitivity to cardiac electrophysiology in physiological and pathophysiological conditions , we extended our previous Markovian model of M2R [5] to incorporate Gβɣ-mediated activation of the KACh channel and integrated the revised Markovian model into a human model of the sinus node ( SN ) cell model [6] . Based on experimental data from isolated human SN cells [7 , 8] , Fabbri and colleagues recently published a comprehensive model of the human SN pacemaker cell that faithfully recapitulated the effects of autonomic modulation as well as mutations associated with SN dysfunction [6] . In the Fabbri model and its parent model [9] , IK , ACh is described by a voltage- and [ACh]-dependent gate , but the intrinsic voltage sensitivity of M2R is not incorporated . Here , we introduce a model reproducing the effects of M2R voltage sensitivity on human SN cell function under physiological and pathophysiological conditions . These simulations support our hypothesis that altered M2R voltage sensitivity contributes to disease and provide a novel mechanistic foundation to study clinical disorders such as AF and IST .
For decades , the contribution of IK , ACh to the modest chronotropic effects of ‘physiological’ or low-dose ACh has been debated [10–12] . Based on the M2R voltage-dependent properties , we predict that subsaturating ACh concentrations exert a larger effect during diastolic ( hyperpolarized ) membrane voltages , compared to the voltages during the cardiac AP ( depolarized ) [3 , 5]; thus preferentially slowing the pacemaker rate with minimal effect on APD . To test this hypothesis , we simulated the effects of varying low , sub-saturating concentrations ( e . g . , 20–100 nM ) of ACh on sinus node AP properties ( Fig 1 ) . The most striking effect of increasing ACh concentration was reduced slope of phase 4 depolarization and the corresponding increase in basic cycle length ( Fig 1A , Table 1 , Vshift = 0 ) , with minimal shortening of APD90 ( Table 2 , Vshift = 0 ) . Thus , the basic cycle length ( BCL ) increased from 827 ms in the absence of ACh , to 1585 ms in the presence of 0 . 1 μM ACh . The AP amplitude decreased steadily by up to 4 . 7 mV at the highest tested concentration of 0 . 1 μM ACh ( inset of Fig 1A ) . Simulated open probability O and IK , ACh for different ACh concentrations are shown in Fig 1B and 1C . Taken together , these simulations indicate that subsaturating concentrations of ACh slow spontaneous excitation of the SN cell by inhibiting the rise of phase 4 depolarization , without appreciably shortening APD90 or reducing the amplitude of the AP . In our previous experimental studies using isolated feline left atrial myocytes , the voltage dependence of M2R was explored by measuring the ACh concentration-IK , ACh response relationship at hyperpolarized ( -100 mV ) and depolarized membrane voltages ( +50 mV ) [3 , 5] . These experiments indicated that the affinity of the receptor for ACh was greater at hyperpolarized membrane voltages , compared to depolarized voltages . We reasoned that , similar to voltage-gated ion channels , putative disease-associated mutations in M2R might alter the voltage sensitivity of the M2R , with unique consequences for sinus node AP properties and heart rate responses . We modified rate parameters ( Eqs 5 and 6 ) to shift the receptor occupancy towards a hyperpolarized state ( higher affinity ) or a depolarized state ( lower affinity ) ( S1A Fig ) . Thus , we simulated the effects of shifting the M2R voltage sensitivity ( Fig 2 , S3C Fig ) . S1B Fig highlights the effects of voltage shifts on the state O . Negative shifts ( e . g . , Vshift of -30 mV and -150 mV ) , which caused a more hyperpolarized state of the receptor , increased the occupancy of the U1 and B1 states , as well as the state O . Negative voltage shifts resulted in a slight leftward shift in the concentration-response curve when the cell was held at +50 mV ( Fig 3E ) . Likewise , positive shifts in M2R voltage sensitive parameters caused a slight rightward shift in the concentration-response curve for a holding potential of Vh = -100 mV ( Fig 3A ) . To avoid local minima during the parameter fitting , the model was forced to favor the open state ( state O equal to 1 ) , at the maximum concentration of 10 μM ACh and to favor the closed state ( O equal to 0 ) , with no ACh present . Further , U1 was forced to be as high as possible at a holding potential of -100mV and U2 at +50 mV , in the absence of ACh . Thus , negative and positive voltage shifts did not move the steady-state concentration-response relationships outside of these ranges . Notwithstanding , the voltages experienced by the single cell model vary between -60 and +30 mV ( Fig 1A ) , within the minimum and maximum ranges defined by the parameter fitting . We previously described the kinetics of “relaxation” gating of IK , ACh in terms of activation and deactivation of KACh channels in the setting of subsaturating ACh concentrations [5] . Activation kinetics were measured by first stepping to a depolarized voltage ( +60 mV ) to close a large portion of KACh channels at a physiological voltage , followed by stepping through a range of voltages to measure activation of IK , ACh . Deactivation kinetics were assessed by a pre-pulse to a hyperpolarized voltage ( -100 mV ) to open channels , followed by variable test voltage steps to measure the rate of KACh channel closure . Accordingly , simulated IK , ACh evoked by 0 . 1 μM ACh using the activation and deactivation voltage protocols are presented in S1 Fig and the kinetic parameters are described in Table 3 . The simulations recapitulate the experimental features of IK , ACh relaxation gating [5] , as shown in S1 Fig . The effects of voltage shifts in M2R voltage sensitive parameters on IK , ACh relaxation gating parameters are shown in Fig 3 . Next , we simulated the effects of negative and positive voltage shifts in M2R voltage-sensitive parameters on sinus node APs , together with the corresponding effects on state O and IK , ACh ( Fig 4 ) . Negative shifts ( e . g . , Vshift of -10 mV and -30 mV ) , which would be predicted to increase ACh affinity , reduced the slope of phase 4 depolarization in a concentration-dependent manner , with minimal effects on AP amplitude or APD90 ( Fig 4A versus 4D , Tables 1 and 2 ) . The reduction in the slope of phase 4 depolarization induced by a negative Vshift was due to an increase in the open probability of KACh channels relative to the control condition , thereby increasing the magnitude of IK , ACh . These results indicate that shifts in the M2R voltage sensitivity impact the rate of spontaneous depolarization of sinus node APs . To further characterize the physiological consequences of positive and negative voltage shifts , we studied the effects of variable M2R voltage sensitivity on the ACh concentration-heart rate response relationship ( Fig 5A ) . Our model recapitulates experimental data [12] indicating that ACh concentrations ranging from 0 . 01 to 0 . 1 μM induce slowing of the spontaneous activity by 10% and 45% , respectively . Hyperpolarizing shifts in the M2R voltage dependent parameters shifted the relationship toward progressive spontaneous activity slowing . By contrast , depolarizing shifts in these parameters antagonized the spontaneous activity slowing induced by ACh . Taken together , these results suggest that shifts in M2R voltage sensitive parameters exert significant physiological effects on SN firing rate and AP parameters . Next , we quantified the effects of the individual ACh-influenced cardiac currents on heart rate slowing . Fig 5B illustrates the relative contributions of ACh-sensitive currents , including our new model of IK , ACh , together with formulations of the L-type Ca2+ current ( ICa , L ) and the hyperpolarized-activated ‘funny current’ ( If ) from Fabbri et al . [6] . Inspection of the individual contributions of the ACh-sensitive currents reveals that our model of IK , ACh ( incorporating the voltage-sensitivity of M2R ) accounts for roughly 50% of the slowing at ~30nM and more for higher concentrations . These results highlight the important contribution of M2R voltage sensitivity to heart rate slowing induced by ACh .
There are several limitations inherent in the application of the model to describe the kinetics and behavior of IK , ACh . First , the receptor-channel model was fit and optimized to recreate the kinetics of IK , ACh occurring at a concentration of 0 . 1 μM ACh . While this is within the range of measured concentrations of ACh , measurements at lower concentrations could enable a more accurate reconstruction of the behavior of IK , ACh and a direct comparison to the effect of If at such concentrations . Furthermore , we acknowledge that the description of the process of dissociation of Gβɣ from the M2R to the activation of the KACh channel is highly simplified . We used a simple channel opening description with a 2-state Markovian model neglecting different binding properties of different Kir subunits or cooperativity mechanisms in binding of Gβɣ . This simplification was necessary as parameters for more complex models are not identifiable with the existent experimental data . Also , the model is not able to reproduce the distinct characteristics of the deactivation protocol time constants . The experimental data indicate that the deactivation time constant is nearly voltage-independent ( Fig 3H ) , the model predicts an increase with membrane depolarization . Nonetheless , because the other simulated features have a very high similarity to the measured values ( Fig 3B , 3C , 3F and 3G ) and the time constants are in the range of less than half the length of an action potential , we believe that any error introduced does not significantly influence our findings . Additionally , dissociation or binding of Gβɣ in our model does not account for changes in the process due to other influences or any binding to sites other than the KACh channel . The SN cell model recapitulates the experimental findings that ACh inhibits If and ICa , L , which also contribute to slowing of spontaneous pacing rate [23] . We argue that unlike IK , ACh , the M2R voltage dependent effects do not influence If and ICa , L on the time scale of the AP . If and ICa , L inhibition are mediated by inhibition of the cAMP-dependent protein kinase A cascade that functions on a much slower time scale than the APD . By contrast , our simulations demonstrate that voltage dependent conformational changes in M2R influence IK , ACh throughout the cardiac AP , modulating both firing rate and APD . Finally , because our model does not fully integrate all the components of the autonomic nervous system , it is possible that the effects of the putative genetic mutations might be mitigated by compensatory changes in the autonomous nervous system’s response to changes in heart rate . The recent observation that M2Rs are intrinsically voltage sensitive has important implications for understanding the physiology and pathophysiology of parasympathetic regulation of heart rate and APD . By optimizing and integrating a new Markovian model into a human SN model , we show that low ACh concentrations preferentially slow beating rate , without shortening APD , and thereby provide additional support that IK , ACh participates in the purely chronotropic effects of basal vagal tone . Moreover , we explore the effects of altered M2R voltage sensitivity and provide a proof-of-principle foundation that altered sensitivity could result in clinical manifestations of disease states such as vagally-mediated atrial fibrillation and syndrome of inappropriate sinus tachycardia . Given the importance of parasympathetic regulation of atrial vulnerability , M2Rs represent an important therapeutic target to control or prevent atrial arrhythmias .
We developed a Markovian model to reconstruct the behavior of KACh channels at different ACh concentrations and varying transmembrane voltages ( Fig 2 ) . The model comprises 3 sub-models: ( 1 ) A Markovian model describing the kinetics of the M2R depending on different concentrations of ACh at different voltages ( M2R model ) , ( 2 ) a Markovian model describing the activation of the KACh channel based on dispersion of Gβɣ protein from the receptor to the channel ( KACh channel model ) , and ( 3 ) a model of potassium current through KACh channels . The parameters of the model were determined by iterative stochastic optimization as previously described [5] . Model parameterization was implemented in Matlab R2017a ( The Mathworks Inc . , Natick , MA ) and the Matlab Parallel Computing Toolbox . An error function based on the root mean squared differences of the measured versus simulated features of the activation protocol , deactivation protocol , and concentration response curve from [5] was minimized . Measured features were based on whole-cell voltage-clamp experiments [5] . IK , ACh for the activation and deactivation clamp protocols was recorded in the presence of 0 . 1 μM ACh . The 3 best measured currents , see S1 Fig , from [5] of each protocol were then fitted to a mono-exponential equation , averaged and then normalized to Coff at -10 mV: I ( t ) =C+Aexp ( -tτ ) ( 10 ) with the constants A and C , and the time-constant τ of activation ( on ) and deactivation ( off ) . We choose this strategy , as extracting mono-exponential features and then averaging them introduces less error in the overall reconstructed behavior than averaging the signals themselves . The same fitting approach was used during the model parameterization . Concentration response curves were measured as the resulting IK , ACh at either a holding potential of -100 mV or +50 mV at different ACh concentrations ( Fig 5A and 5E ) . The currents were then normalized to the current measured at maximal ACh concentration for each holding potential . A total of 8 simulated features fs , i , consisting of six features for the voltage clamp protocols ( i . e . Con , Coff , Aon , Aoff , τon , and τoff ) and two for the concentration response curves ( i . e . IKACh , norm , 50mV and IKACh , norm , -100mV ) , were compared to their corresponding measured features fm , i ( Fig 5B–5D and 5F–5H ) : E2=∑i=18 ( ||fm , i−fs , i||2||fs , i||2 ) 2+ ( 1−max ( O ) ) + ( ( 1−max50mV ( U2 ) ) 2+ ( 1−max−100mV ( U1 ) ) 2 ) 0μM+ ( ( 1−max50mV ( B2 ) ) 2+ ( 1−max−100mV ( B1 ) ) 2+ ( 1− ( B1+B2 ) 2 ) ) 10μM ( 11 ) Other components of the cost function were used to constrain the behavior of the model at specific ACh concentration and Vm , and to ensure high open probability of the channel . Without bound ACh and Vm of +50 mV , the state U2 was forced to be maximal . Respectively , U1 was forced to be maximal without bound ACh and a transmembrane voltage of -100 mV . Equivalently , with bound ACh , state B2 and B1 were forced to be maximal at -100 mV and 50 mV , respectively . Further , the sum of B1 and B2 was forced to be maximal with bound ACh . For simulations of single cell electrophysiology , the new receptor-channel model was integrated in the publically available model of human SN cells [6] . The formulations for the effect of ACh on ICaL and If were left unaltered throughout the experiments . The model was first exported to Matlab using OpenCOR ( www . opencor . ws ) and then modified accordingly . Numerical integration was performed by using the integrated ode15s formulation provided by Matlab . We measured BCL to characterize the rate of spontaneous activation of the simulated SN cell at varying concentration of ACh and Vshift . The maximum conductivity gK , ACh , max was set 0 . 0022 μS to reproduce previously published heart rate slowing in the presence of 0−0 . 1 μM ACh [12] . Furthermore , we measured the APD at 90% repolarization ( APD90 ) to characterize the cardiac AP . The stochastic parameterization yielded the model parameters ( Table 3 ) . In comparison to the parameterization of our previous model [5] , the fit error of the features from the activation and deactivation protocols was reduced from 1 . 5 to 0 . 68 despite the additional error terms . Respectively the squared fit error for each feature is; Con: 0 . 06 , Coff: 0 . 025 , Aon: 0 . 11 , Aoff: 0 . 014 , ton: 0 . 04 , toff: 0 . 18 , IKACh , norm , 50mV: 0 . 03 , IKACh , norm , -100mV: 0 . 003 . The total error of the features is equal to the square root of the sum of the respective squared fit errors . The corresponding modeled and measured current traces of the voltage protocols are shown in S2 Fig .
|
Heart rate regulation is dependent upon a delicate interplay between parasympathetic and sympathetic nerve activity at the level of the sinus node . Acetylcholine slows the heart rate by activating the M2 muscarinic receptor ( M2R ) that , in turn , opens the acetylcholine-activated potassium channel ( IK , ACh ) to slow the firing of the sinus node . Surprisingly , the M2R is sensitive to membrane potential and undergoes conformational changes throughout the cardiac action potential that alter the affinity for acetylcholine , with secondary consequences for IK , ACh activity . Here , we investigated the contribution of M2R voltage sensitivity to the rate and shape of the human sinus node action potential in physiological and pathophysiological conditions , using a Markovian model of the IK , ACh channel integrated into a computational model of human sinus node . The computational model allowed us to assess the effects of potential genetic variants that alter specific properties of voltage sensitivity . Our results indicate that alterations in the M2R voltage sensitivity play a significant role in the physiology and pathophysiology of the human sinus node and atria . Our computational model is relevant for future studies aimed at the design and development of anti-arrhythmic agents that specifically target the unique voltage-sensitive properties of M2R .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"ion",
"channel",
"gating",
"medicine",
"and",
"health",
"sciences",
"action",
"potentials",
"markov",
"models",
"depolarization",
"membrane",
"potential",
"electrophysiology",
"neuroscience",
"simulation",
"and",
"modeling",
"ion",
"channels",
"mathematics",
"cardiology",
"research",
"and",
"analysis",
"methods",
"sensory",
"physiology",
"proteins",
"biophysics",
"probability",
"theory",
"heart",
"rate",
"physics",
"biochemistry",
"physiology",
"biology",
"and",
"life",
"sciences",
"physical",
"sciences",
"neurophysiology"
] |
2018
|
Modeling effects of voltage dependent properties of the cardiac muscarinic receptor on human sinus node function
|
Lung disease is regularly reported in human filarial infections but the molecular pathogenesis of pulmonary filariasis is poorly understood . We used Litomosoides sigmodontis , a rodent filaria residing in the pleural cavity responsible for pleural inflammation , to model responses to human filarial infections and probe the mechanisms . Wild-type and Th2-deficient mice ( ΔdblGata1 and Il-4receptor ( r ) a-/-/IL-5-/- ) were infected with L . sigmodontis . Survival and growth of adult filariae and prevalence and density of microfilariae were evaluated . Cells and cytokines in the pleural cavity and bronchoalveolar space were characterized by imaging , flow cytometry and ELISA . Inflammatory pathways were evaluated by transcriptomic microarrays and lungs were isolated and analyzed for histopathological signatures . 40% of WT mice were amicrofilaremic whereas almost all mutant mice display blood microfilaremia . Microfilariae induced pleural , bronchoalveolar and lung-tissue inflammation associated with an increase in bronchoalveolar eosinophils and perivascular macrophages , production of mucus , visceral pleura alterations and fibrosis . Inflammation and pathology were decreased in Th2-deficient mice . An IL-4R-dependent increase of CD169 was observed on pleural and bronchoalveolar macrophages in microfilaremic mice . CD169+ tissue-resident macrophages were identified in the lungs with specific localizations . Strikingly , CD169+ macrophages increased significantly in the perivascular area in microfilaremic mice . These data describe lung inflammation and pathology in chronic filariasis and emphasize the role of Th2 responses according to the presence of microfilariae . It is also the first report implicating CD169+ lung macrophages in response to a Nematode infection .
Human filarial infections are caused by nematodes of the Onchocercidae family . These parasites are transmitted by hematophagous arthropods and have a life cycle consisting of four larval stages ( L1 to L4 ) with a moult occurring at the end of each larval stage , and an adult stage comprising separate males and females . Filarial infections cause several human diseases . Due to severe pathology that includes visual impairment and dermatitis for onchocerciasis , and lymphedema and hydrocele for lymphatic filariasis ( LF ) [1 , 2] , the World Health Organisation has marked both diseases for elimination . LF is caused by Wuchereria bancrofti , Brugia malayi and B . timori , mansonellosis by Mansonella perstans and zoonotic filariasis is mainly caused by Dirofilaria immitis a species that normally infects non-human animal hosts . Pulmonary manifestations of filarial infections are regularly reported in these human diseases [3–5] . Although infections with M . perstans are often considered asymptomatic , pleural effusions , pulmonary hypertension and peribronchic infiltrates have been described [5–7] . Tropical pulmonary eosinophilia ( TPE ) is a rare but documented manifestation of LF . The current concept of the pathogenesis of TPE suggests that it begins with lung parenchymal inflammation in individuals highly immunologically sensitized to filarial parasites . The offspring , microfilariae ( Mf; L1 ) , released from adult worms living in lymphatics are cleared in the pulmonary circulation , degenerate and release their antigenic constituents which trigger local inflammation [4 , 8] leading to an asthma-like syndrome with eosinophilia , peribronchial infiltrates and fibrosis [4 , 9 , 10] . In human pulmonary dirofilariasis the parasites accumulate in the pulmonary artery where they embolize , ultimately leading to the formation of a pulmonary nodule or coin lesion on chest x-rays [11] . Importantly , and independent of the filarial species causing the infection , the molecular pathogenesis of pulmonary filariasis is poorly understood . Litomosoides sigmodontis is a rodent filaria which is used to model the host response in human filarial infections [12] . Infective larvae ( L3 ) migrate from the skin to the pleural cavity ( PC ) within eight days [13] , where they remain for the duration of infection . In BALB/c mice , parasites mature and mate , and in about 60% of mice they release Mf that circulate in the bloodstream from approximately day 55 post infection ( p . i . ) . In approximately 40% of mice , Mf are not observed . However , LF or mansonellosis patients are also often amicrofilaremic [2 , 5 , 14] . Independently of their Mf status , cotton rats and jirds exhibit some pulmonary lesions in the patent phase of L . sigmodontis infection between 60 and 100 days p . i . [15 , 16] . Pleural cell infiltrates have been characterized through the filarial development [13 , 17 , 18] , and more recently , inflammation of the visceral pleura was observed in patent BALB/c mice [19] . The aim of this study was to provide new insight into Mf-driven lung pathology during filariasis .
All experimental procedures were carried out in accordance with the EU Directive 2010/63/UE and the relevant national legislation , namely the French “Decret No . 2013±118 , 1er fevrier 2013 , Ministère de l'Agriculture , de l'Agroalimentaire et de la Foret” . Protocols were approved by the ethical committee of the Museum National d'Histoire Naturelle ( Comité Cuvier , Licence: 68–002 ) and by the Direction départementale de la cohésion sociale et de la Protection des populations° ( DDCSPP ) ( No . C75-05-15 ) . Maintenance of the filaria L . sigmodontis Chandler , 1931 and recovery of infective larvae ( L3 ) from the mite vector , Ornithonyssus bacoti , were carried out as previously described [20] . Six weeks-old female BALB/c OlaHSD mice were obtained from Envigo; 8-week-old jirds were purchased from Janvier . Genetically modified BALB/c mice were provided by Dr Hübner ( Bonn ) . These included six to ten weeks-old homozygous ΔdblGata1 female BALB/c mice , which present a deletion of a high-affinity GATA-binding site in the GATA-1 promoter leading to selective a loss of the eosinophil lineage [21]; six to ten weeks-old Il-4ra-/-/Il-5-/- female BALB/c mice , which are deficient for the α chain of the IL-4 receptor ( IL4-Ra ) and thus lacking IL-4/IL-13 signaling and for IL-5 , leading to an absence of alternative activation of macrophages and an impaired maturation and recruitment of eosinophils , and a substantial microfilaremia when infected with L . sigmodontis [15 , 16 , 19 , 22 , 23] . All animals were maintained in the MNHN animal facilities on a 12-hours light/dark cycle . Mice were inoculated subcutaneously with a single dose of 40L3 . Analyses were performed in the patent phase at D70 p . i . At necropsy , filariae ( F ) were recovered with pleural cells by lavaging the pleural cavity with 10 ml cold PBS as described in [13] . Bronchoalveolar cells were recovered by flushing of the bronchoalveolar space with 10 ml PBS as described in [13] . The first ml of pleural wash and the first ml of bronchoalveolar lavage were stored for further immunological analysis . Pleural cells and bronchoalveolar cells were resuspended in 1 ml of PBS+2% FCS . Red blood cells were removed by hypotonic lysis and pleural cells and bronchoalveolar cells were counted . Filariae were harvested , counted , fixed in 70% ethanol and analysed by light microscopy ( Olympus BX63 microscope , DP72 camera ) . They were measured using CellSens Dimension 1 . 9 software . The recovery rate of filariae , expressed as 100 x number of worms recovered/number of larvae inoculated ( F/L3 ) was established . Female filariae from WT Mfneg , WT Mfpos , ΔdblGata1 Mfpos and Il-4ra-/-/Il-5-/- Mfpos BALB/c mice were incubated with DAPI ( 1:1000 ) for 1h and mounted in Fluoroshield Mounting Medium with DAPI ( Abcam ) . Images from the proximal portion of the uteri ( close to ovojector ) were captured with an inverted laser scanning confocal microscope ( SP5-SMD; Leica Microsystems ) with a z-stack of 20μm . The images were processed and analysed using IMARIS ( Bitplane ) to measure the proportion of microfilariae over the whole developmental stages present in the proximal uteri portion . Peripheral blood microfilaremia ( number of microfilariae ) was determined at day 60 and 70 p . i . on a 10μl Giemsa stained blood drop . Cardiac blood microfilaremia was determined at day 70 p . i . Microfilariae ( Mfs ) were isolated as described in [24] . Briefly , blood from microfilaremic jirds was collected and the microfilariae were purified using a sucrose/Percoll density gradient , resuspended in 1mL PBS and counted . Pleural and Bronchoalveolar cells were preincubated with murine Fc block CD16/CD32 and then stained with the following rat anti-mouse antibodies: anti-F4/80-APC ( 1:200; eBioscience , clone BM8 ) , anti-SiglecF-PE ( 1:200 , BD Bioscience , clone E50-2440 ) , anti-Ly6G-V450 ( 1:200 , eBioscience , clone 1A8 ) , anti-CD4-PE ( 1:200; BD Bioscience , clone RM4-5 ) and anti-CD19-APC ( 1:200; BD Bioscience , clone 1D3 ) . Macrophages were further analysed using anti-CD169-FITC ( 1:200 , Biolegend , clone 3D6 . 112 ) and CD206-PE-Cy7 ( 1:200 , Biolegend clone C068C2 ) . Fluorescence Minus One ( FMO ) controls were used for each group with a pool of cells of all groups . The samples were run on a FACSVerse flow cytometer ( BD Biosciences ) and analysed using FACSuite software . Doublets and debris were excluded . CD169 and CD206 expression is expressed as mean fluorescence intensity ( MFI ) normalized by FMO ( MFI-FMO ) . Pleural wash ( diluted 1:4 ) or bronchoalveolar ( diluted 1:4 ) fluids collected from individual mice were assayed for cytokine content by enzyme-linked immunosorbent assay ( ELISA ) in duplicate . These assays were performed according to the manufacturers’ recommendations , using the following kits , IFN-γ , CCL2 , IL-4 , IL-6 ( eBiosciences SAS , France ) , CCL11 ( Peprotech , France ) and CXCL9 ( R&D , UK ) . Results are shown as pg/mL . Detection limits were 4 pg/ml for IL-4 and IL-6 , 15 pg/ml for INF-γ , CCL2 and CXCL9 and 30 pg/ml for CCL11 . Lungs from naive and L . sigmodontis 70-day-infected WT mice and 6-months-infected jirds were removed from the chest , placed in a petri dish containing PBS and cut in 3-4mm thick sections . Sections were fixed with 2 . 5% glutaraldehyde , dehydrated with increasing concentrations of ethanol ( from 50 to 100% ) , and dried with hexamethyldisilane ( HMDS ) . Samples were then fixed on metal supports using double-sided carbon tape and metallized by sputtering gold ( Jeol FJC-1200 metallizer ) . Observations of the visceral pleura were made with a Hitachi SU3500 SEM ( MNHN Technical Electron Microscopy Platform ) . Lungs from naïve and L . sigmodontis infected WT , ΔdblGata1 and Il-4ra-/-/Il-5-/- BALB/c mice ( n = 7–15 per group ) were inflated with and fixed in 4% formalin , dehydrated in 70% to 100% ethanol baths , and then placed in toluene before paraffin embedding . Four-micron-thick serial sections were prepared and various stainings were performed: 1 ) Picrosirius red ( Bio optica , Italy ) and Masson's trichrome ( Sigma-Aldrich ) to visualize collagen fibers according to the manufacturers' recommendations; 2 ) Alcian Blue/Periodic Acid Schiff ( AB-PAS ) staining to visualize mucus producing cells using the following protocol: http://www . ihcworld . com/_protocols/special_stains/alcian_blue_pas_ellis . htm; 3 ) a cytokeratin immunostaining to visualize mesothelial cells; briefly antigens retrieval was performed using a solution of Proteinase K ( 10 μg/ml ) in Tris-EDTA buffer , then peroxidases and endogenous alkaline phosphatases were blocked by adding DualEndogenous Enzyme Block ( Dako , France ) . Sections were incubated with the mouse anti-human cytokeratins monoclonal Ab ( 1:50 , clone AE1/AE3 , Dako ) . Binding of the antibodies was detected by HRP linked universal secondary antibody ( DAKO ) and AEC substrate ( DAKO ) . The sections were counterstained with a Mayer Hematoxylin solution . Lung sections were analysed by light microscopy ( Olympus BX63 microscope , DP72 camera ) using the cell Sens Dimension 1 . 9 software . Full lobe sections were imaged by mosaic imaging and pleural pathology ( 100 x length of pathologic pleura / total perimeter ) and bronchial inflammation ( 100 x nb of AB-PAS positive bronchus sections / total nb of bronchus sections ) were measured . For each parameter , 2–3 lung sections were analysed . Lungs from naive and L . sigmodontis infected WT , ΔdblGata1 and Il-4ra-/-/Il-5-/- BALB/c mice ( n = 4–11 per group ) were prepared for confocal microscopic analysis . PCLS were preoduced as previously described [13] . Briefly , after removal of filariae , lungs were inflated with 2% low melting point agarose ( Sigma-Aldrich ) in PBS ( 40°C , pH 7 . 4 ) and covered with ice for 5 min . Lungs were removed from the pleural cavity , rinsed in PBS , fixed in PBS/PFA 4% for 2h at 4°C and stored in cold PBS/BSA1%/Azide 0 . 05% . The left lung was isolated and cut with a vibrating microtome ( Campden 5100mz ) into 300-μm slices . Lung slices were stained with the following cocktail at room temperature: first a hamster anti-mouse CD31 antibody ( 2H8 , Life Technologies , 1:200 ) was applied for 3h; secondly Alexa Fluor 488 goat anti-hamster ( 1:200 , polyclonal , Jackson ) , Alexa Fluor 594 rat anti-mouse CD68 ( 1:200 , clone FA-11 , Biolegend , company ) , Alexa Fluor 647 rat anti-mouse CD169 ( 1:200 , clone 3D6 . 112 , Biolegend ) , and DAPI ( 1:1500 ) were added for 1h . All antibodies were diluted in PBS/NGS 10%/BSA1%/TX-100 0 . 3%/Azide 0 . 05% . Several PBS washing steps were performed before and after a 2 min 4% PFA fixation and slices were transferred to glass slides , covered with buffered Mowiol 4–88 , pH 8 . 5 ( Sigma-Aldrich ) then coverslipped . Areas of about 1mm x 1mm side by 100μm deep containing perivascular spaces or visceral pleura were acquired with a confocal microscope ( Airyscan 880; Zeiss ) . At least 2 images of PVS and 1 of visceral pleura were obtained for each lung . Images were analysed using the IMARIS software ( Bitplane ) . The different planes ( z ) were stacked to obtain a three-dimensional reconstruction of the different fluorescence signals . Perivascular space volume was measured over the 50μ z-stack ( in mm3 ) using the software tools and the number of cells present in the space ( DAPI+ and DAPI+CD68+CD169+ ) was counted to determine cell concentration in the different PVS images ( number cells/mm3 ) . Lung DNA was extracted to allow the detection and quantification of pulmonary microfilariae . The protocol was adapted from Bouchery et al . 2012 . First , an 8 point standard curve was generated using lungs from naive mice to which a known number of Mf ( from 0 to 1 . 000 . 000 ) was added before DNA extraction ( see above for Mf purification ) . Lungs ( +/- Mf ) were homogenized in a fixed volume of PBS ( 500 μl ) using a Tissue Lyser II ( Qiagen ) . 100μL of homogenate solution was used for genomic DNA extraction ( QIAamp DNA Mini Kit , QIAGEN , Germany ) according to the manufacturer’s protocol and finally eluted in 150 μl of sterile water . A real-time PCR was performed with the DNA Master Plus SYBR Green Kit ( Roche Diagnostics , Meylan , France ) in a LightCycler ( Roche Diagnostics ) with an initial incubation of ten minutes at 95°C , 40 amplification cycles of ten seconds at 95 °C , of five seconds at 60 °C , and of ten seconds at 72 °C , during which the fluorescence data were collected . The 10 μl reaction mixture contained 1X DNA Master Plus SYBR Green , 4 μM of each primer , and 4 μl of template . Filarial DNA and murine DNA were detected by targeting the actin of L . sigmodontis ( L . s Actin 5'-ATCCAAGCTGTCCTGTCTCT-3’; 5'-TGAGAATTGATTTGAGCTAATG-3’ ) and the actin of Mus musculus ( M . m Actin 5'-ATTGCTGACAGGATGCAGAAG-3’; 5'-AGTCCGCCTAGAAGCACTTG-3’ ) respectively . For each sample , the ratio ( R ) of signal ( CT ) from filarial actin and murine actin was performed to normalize the results as R = CT ( L . s Actin ) / CT ( M . m Actin ) . The number of microfilariae in the lung of infected WT , ΔdblGata1 and Il-4ra-/-/Il-5-/- BALB/c mice ( n = 9–12 per group , 1 for ΔdblGata1 ) was then extrapolated using this ratio and the standard curve . Screening of inflammatory lung environment was performed with a qRT-PCR array ( Mouse Cytokines & Chemokines RT2 Profiler PCR Array , Qiagen , Germany ) according to manufacturer’s instructions . RNA extraction was performed on RNeasy Midi kit colums ( Qiagen ) . The quantity and quality of the RNAs was verified with a spectrophotometer ( Nanodrop2000 , Thermo Scientific ) and an Agilent 2100 bioanalyzer . The complementary DNAs ( cDNAs ) were produced with the First-strand cDNA kit ( Qiagen ) . A pool of cDNA from naive mice lungs ( n = 8 ) was compared with one from D70 p . i . infected mice ( n = 8 ) by profiling 84 cytokine-related genes simultaneously . The real-time PCR cycling program ( 7300 real-time PCR System , Applied biosystem ) was run and data were processed and displayed using the online RT2 Profiler PCR Array Data analysis 3 . 5 software ( Qiagen ) . Gene expression was normalized with 4 housekeeping genes ( Actb , Gapdh , Gusb , Hsp90ab1 ) . Transcripts with a fold change >2 were selected ( raw data are available on GEO https://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE115596 ) . Array results were validated by performing qRT-PCR on all individual samples ( n = 8/group ) for the highly upregulated genes Cxcl9 , Ccl2 and Il1-3 with the following couples of primers: Cxcl9 , 5’-CCATGAAGTCCGCTGTTCTTTTCC-3’; 5’-TGGGGCAAACTGTTTGAGGTCT-3’; Ccl2 , 5’-ACTGCATCTGCCCTAAGGTCTTCA-3’; 5’-TAAGGCATCACAGTCCGAGTCACA-3’; Il-13 , 5’-GGATATTGCATGGCCTCTGTAACC-3’; 5’-GTGGCGAAACAGTTGCTTTGTG-3’ . A DNA Master Plus SYBR Green Kit ( Roche Diagnostics , France ) was used in a LightCycler 2 . 0 ( Roche Diagnostics , France ) with an initial incubation of 10 min at 95°C , 40 amplification cycles of ten seconds at 95°C , of 8 seconds at 60°C , and of 10 sec at 72°C , during which the fluorescence data were collected . The 10 μL reaction mixture contained 1X DNA MasterPlus SYBR Green ( QIAGEN , France ) , 0 . 5 μM of each primer , and 5 μL of template . Gene expression was then determined relative to β-actin and GAPDH using the 2-ΔΔCT method . Transcriptional data were evaluated using Ingenuity Pathway Analysis ( IPA , Systems Inc . , USA ) and the activation of biological functions occurring in the tissue was predicted ( IPA Core Analysis ) . Data analyses were performed with Prism 5 . 0 software ( GraphPad Inc . ) . The choice of statistical tests was based on sample size and normality ( Shapiro-Wilk test ) examined prior to further analysis . Data from independent experiments were pooled when possible . When normality was established , results were analysed by one-way ANOVA test in order to determine the effect of one factor , followed by a Bonferroni's multiple comparisons post-test; otherwise non-parametric Kruskal Wallis tests followed by a Dunn's multiple comparisons post-test were used . Correlations between two datasets were analysed using the Pearson test . In all figures , the mean value is visually depicted . P values correlate with symbols as follows: ns = not significant , p > 0 . 05 , * p ≤ 0 . 05 , ** p ≤ 0 . 01 , *** p ≤ 0 . 001 . Mice were allocated randomly into experimental groups after matching for age . Specific numbers of animals can be found in corresponding figure legends .
The life cycle of the filaria L . sigmodontis is maintained in jirds ( S1 Fig ) , a rodent similarly permissive to the cotton rat , its natural host . Upon opening the pleural cavity , polyps on the lungs are regularly observed . Scanning electron microscopy of the lungs of infected jirds , six months p . i . revealed marked pathology of the visceral pleura with a bullous/hairy appearance , composed of nodule-like structures ( Fig 1A and 1B ) . To a much lesser extent , cuboidal ‘swollen’ mesothelial cells were observed on visceral pleura of BALB/c mice ( Fig 1C and 1D ) . However , histology of infected mice revealed important modifications of the visceral pleura . Normal visceral pleura is composed of a single layer of pavimentous mesothelial cells expressing cytokeratine ( Fig 1E ) . In infected BALB/c mice , mesothelial cell hypertrophy ( increased cell volume ) and hyperplasia of the visceral pleura ( increased cell number ) were observed ( Fig 1F and 1G ) . Quantification ( Fig 1H–1J ) showed that all infected mice had a large portion of visceral pleura with hypertrophic mesothelial cells and hyperplasic areas ( about 60% and 35% of the total perimeter of lung sections respectively ( Fig 1I and 1J ) . Hyperplasic areas contained a dense mesh of collagen fibers , a signature of localized fibrosis , in contrast to normal and hypertrophic areas ( Fig 1K–1M ) . To characterize lung inflammation in filariae-infected rodents , an analysis of cytokine and chemokine transcripts was performed on BALB/c lungs at 70 days p . i . The expression of 84 cytokine/chemokine-coding genes was analyzed and an upregulation of the expression of 30 genes and the downregulation of 7 genes was observed in infected mice compared to naïve mice , with some mixed Th1/Th2 signatures ( Fig 2A ) . Among them , the expression of the Th1-related cytokines Cxcl9 , Cxcl10 and Ifn-ɣ were highly increased , as well as the prototypical Th2 cytokines Il-13 and Il-4 . Il-5 expression was not modulated at this timepoint . Results were validated by individual qRT-PCR for the highly upregulated genes Cxcl9 , Ccl2 and Il-13 ( Fig 2B ) . Microfilaremic and amicrofilaremic BALB/c mice are similar . In silico analysis of the results indicated robust lung inflammation , associated with the recruitment and activation of myeloid cells ( especially macrophages and eosinophils ) and lymphocytes ( B cells , Th2 cells and Tregs ) ( Fig 2C and S1 Table ) . Furthermore , the development of Th2-associated lung pathology , such as fibrosis , asthma or airway hyper-responsiveness was also predicted ( Fig 2C ) . A molecular network linking macrophage activation , eosinophil recruitment and pulmonary fibrosis was generated using the transcriptional profiles , highlighting a central role of IL-13 and IL-4 in pathogenesis and cell recruitment/activation ( Fig 2D ) . To understand the role of Th2 cytokines in parasite outcome , two genetically modified strains of mice were compared to BALB/c wild type ( WT ) mice: 1 ) the ΔdblGata1 BALB/c mice , which lack the eosinophil lineage [21]; 2 ) the Il-4ra-/-/Il-5-/- BALB/c mice , characterized by an absence of alternative activation of macrophages and impaired maturation and recruitment of eosinophils [15 , 16 , 19 , 22] . Mf were counted in peripheral and cardiac blood of the WT and mutant mice . This revealed striking differences between the genotypes ( Fig 3A and 3B ) : 63% of WT mice show circulating Mf ( Mfpos ) but 83% of ΔdblGata1 and 100% of Il-4ra-/-/Il-5-/- were Mfpos [23] . Moreover , Mf in peripheral blood and heart were more numerous in Il-4ra-/-/Il-5-/- than in WT Mfpos mice , and ΔdblGata1 showed an intermediate phenotype ( Fig 3A and 3B ) . In WT mice , L3 migration is complete by D8 p . i . and survival of worms is stable until 2 months p . i . after which worm-burden decreases at D70 p . i . compared with D8 p . i . ( [13] and S1 Fig ) . In contrast , worm burden remained stable in both groups of mutant mice indicating extended worm survival ( Fig 3C ) . Filariae were longer in mutant mice ( males only in Il-4ra-/-/Il-5-/- mice ( Fig 3D ) and females in both mutant groups , longest in Il-4ra-/-/Il-5-/- ( Fig 3E ) ) . WT Mfpos and Mfneg mice did not present adult worm size differences . Interestingly , the uterine content of female worms themselves was different depending on the host genotype . Uteri of female parasites from WT Mfneg were empty of microfilariae ( Fig 3F and 3G ) while the proximal portion of uteri , close to the ovojector , of worms in Mfpos mice ( WT , ΔdblGata1 and Il-4ra-/-/Il-5-/- ) contained a mix of viable Mf with embryos that did not undergo morphogenesis ( Fig 3H–3J ) . The number of aborted embryos was high in parasites from WT mice ( half of uterine content ) and almost null in those from Il-4ra-/-/Il-5-/- mice; with ΔdblGata1 showing an intermediate phenotype . Mf presence was also estimated in lungs by qPCR and similar results to blood were observed ( Fig 3K ) and the number of Mf in lungs correlated with blood microfilaremia ( Fig 3l ) . Histologically , Mf were quantified in various lung compartments ( Fig 3M ) : Mf were observed mainly in lung blood circulation ( veins , arteries and capillaries—Fig 3N ) . They were also observed in perivascular spaces ( PVS ) which comprise of the interstitial collagenous sheath surrounding larger veins and arteries in the lung ( Fig 3O ) , and occasionally in alveoli . Taken together , it seems likely that the increased numbers of Mf are due to: 1 ) an increased survival of adult parasites leading to female parasites laying eggs for a longer period of time; 2 ) better development of adult worms with more fertile females; and 3 ) enhanced production of Mf with more eggs laid . Histological analysis of the lungs was performed in the different groups of mice ( Fig 4C–4G ) to stratify the inflammatory state of the visceral pleura according to Mf status and genotype . All groups of infected mice presented a large portion of the visceral pleura ( 60 to 80% ) covered with hypertrophic mesothelial cells ( Fig 4A ) but strong hyperplasia was only observed in WT Mfpos mice ( Fig 4B and 4E ) . Mucus production , as an indicator of lung inflammation , was assessed ( Fig 5 ) . Triggering of the IL-4R by IL-4 , and particularly by IL-13 , is the main cause of goblet cell metaplasia [25 , 26] . No goblet cells were present in the bronchial epithelium of naive mice ( Fig 5B and 5G ) and only a few were observed in bronchial epithelium of WT Mfneg mice ( Fig 5C and 5G ) . However , goblet cells were substantially increased in the bronchial epithelium of WT and ΔdblGata1 Mfpos mice ( Fig 5A , 5D , 5E and 5G ) revealing mucus production in these two groups of mice . These cells were mainly located adjacent to PVS ( Fig 5D and 5E ) and absent in the bronchial epithelium of Il-4ra-/-/Il-5-/- Mfpos mice ( similar to naive mice ) ( Fig 5F and 5G ) . The pleural cavity and bronchoalveolar space of the lungs are both known to be important in controlling the filarial burden by providing cells , cytokines , chemokines and other growth factors [13 , 17 , 18] . Filarial infection in WT mice induced a significant increase in cell numbers in the pleural cavity ( PC ) where the adult worms are located ( Fig 6A , S2A–S2D Fig ) with an increase in eosinophils , macrophages and neutrophils that was even more pronounced in Mfpos mice . Mf dependent changes were also observed in the bronchoalveolar lavage ( BAL ) . In contrast with the PC , increased bronchoalveolar macrophages were observed in all three groups of Mfpos mice ( Fig 6B , S2G Fig ) . Additionally , an increase in eosinophils in the bronchoalveolar space of WT Mfpos mice only was also observed ( Fig 6B , S2F Fig ) . Only a slight increase in the number of F4/80+ macrophages was observed in ΔdblGata1 and Il-4ra-/-/Il-5-/-mice versus naïve mice . Similarly , many cytokines were also increased depending on the presence of adult worms or Mf ( S3A–S3K Fig ) . The inflammatory cytokine IL-6 was increased in the PC of both infected WT groups as well as of Mfpos ΔdblGata1 mice but not in the PC of Il-4ra-/-/Il-5-/- mice ( S3A Fig ) . However IL-6 was not modified in the BAL of any groups of mice ( S3G Fig ) . The monocyte / macrophage-chemotactic and pro-fibrotic chemokine CCL2 was increased in the PC and the BAL of all the infected mice independently of the presence of Mf ( S3B Fig ) . The Th2 cytokine IL-4 , necessary for alternative activation of macrophages , was increased in PC of all infected mice ( S3C Fig ) . Increased IL-4 was found in the PC of Il-4ra-/-/Il-5-/- mice ( including naive Il-4ra-/-/Il-5-/- mice; S3C Fig ) . However , no significant differences were observed in the levels of IL-4 in the BAL of any groups of mice ( S3I Fig ) . Regulation of eosinophil maturation , recruitment , and survival is under the control of a small group of factors , including IL-5 and CCL11 . Although IL-5 was not detected , CCL11 was increased in the three groups of Mfpos mice , with lower levels in Il-4ra-/-/Il-5-/- mice ( S3D Fig ) . Again , IL-5 was not detected in BAL of any groups of mice but CCL11 was increased in the BAL of all infected groups ( S3J Fig ) . CXCL9 was increased in all the PC of the three groups of Mfpos mice but Il-4ra-/-/Il-5-/- mice had higher levels ( S3E Fig ) . In BAL , CXCL9 was increased only in Mfpos mice ( S3K Fig ) . As this could be explained by IFN-ɣ driven CXCL9 production , we also checked IFN-ɣ levels in the pleural cavity and observed that they increased in all groups of Mfpos mice ( S3F Fig ) . Specific activation of macrophages was investigated in both compartments , pleural cavity ( PC ) and bronchoalveolar space ( Fig 7A–7E ) . Expression of the mannose receptor , CD206 , a marker that has been associated with a pro-repair phenotype [27] was increased on pleural macrophages from infected WT Mfneg , WT Mfpos and ΔdblGata1 Mfpos mice , but not on those from Il-4ra-/-/Il-5-/- Mfpos mice ( Fig 7B ) , confirming an IL-4R-dependent phenotype in these macrophages [28] . CD206 was only increased on airway macrophages from WT Mfpos mice ( Fig 7C ) . Interestingly , CD169 , a marker related to a subpopulation of macrophages described under inflammatory conditions [29] was uniquely increased on pleural macrophages from infected WT Mfpos , but not Mfneg mice expressing the IL-4R ( Fig 7D ) . As in PC , CD169 expression was increased on bronchoalveolar macrophages from Mfpos mice expressing the IL-4R , i . e . WT Mfpos and ΔdblGata1 Mfpos mice ( Fig 7E ) . Considering the data above , our next step was to localize CD169-expressing lung bronchoalveolar and interstitial macrophages by imaging agarose inflated precision-cut lung slices ( PCLS ) . CD68+CD169intermediate bronchoalveolar ( airway ) macrophages were observed in all groups of mice ( Fig 8A ) . Strikingly , based on specific localization , four additional tissue-resident groups of CD68+CD169+ interstitial macrophages ( IM ) with particularly bright CD169 staining were identified in the lungs of naive and infected mice ( Fig 8 ) . These cells localized: 1 ) in the periphery of the lung along the visceral pleura ( Fig 8B and 8C ) ; 2 ) in the interstitium surrounding bronchi just below bronchial epithelium ( Fig 8D ) ; 3 ) in the PVS surrounding arteries ( Fig 8D and 8E ) ; and 4 ) surrounding veins ( Fig 8F and 8G ) . Subsequently PCLS from WT and mutant mice were imaged to further analyze the PVS ( Fig 9A–9E ) and quantify its cellular content ( Fig 9F and 9G ) . The PVS of naive mice contained few cells ( DAPI+ ) 50% of which were CD68+CD169+ IM ( Fig 9A ) . WT Mfneg mice had a similar cell content ( Fig 9B ) . However , PVS cell content of WT Mfpos and ΔdblGata1 Mfpos was markedly 2–3 times higher than that of naive or WT Mfneg mice . CD68+CD169+ IM were 30–40% of the total cell content in WT Mfpos and ΔdblGata1 Mfpos ( Fig 9C and 9D ) . Interestingly , these changes were abrogated in the PVS of Il-4ra-/-/Il-5-/- Mfpos mice ( Fig 9E ) .
Pulmonary pathology in filariasis is underestimated compared with the main manifestations of human filariases such as lymphoedemas or ocular pathologies . For example , both human Mansonella perstans and rodent Litomosoides sigmodontis can be found in the pleural cavity ( PC ) and they are both considered asymptomatic even if local PC inflammation has been described [5 , 17] . However , analysis of lung tissue has barely been performed . Here , we document a pulmonary pathology in microfilaremic ( Mfpos ) L . sigmodontis-infected rodents . Common features with TPE due to the Mf of B . malayi and W . bancrofti were observed: the presence of bronchoalveolar eosinophils and increases lung macrophage numbers , the production of mucus and the occurrence of pulmonary fibrosis [4 , 10] . Moreover , the development of lung pathology , the parasite survival , growth and fertility , as well as the microfilaremic status are conditioned by a Th2 environment in the murine host . Many patients infected by LF or mansonellosis are amicrofilaremic ( Mfneg ) [2 , 5 , 14] and similarly 40% of L . sigmodontis infected BALB/c mice are Mfneg mice . A few immune components have been identified as key players in controlling the microfilarial burden of mice ( S2 Table ) . Filarial fertility is clearly controlled by Th2 responses as infections of ΔdblGata1 ( eosinophil deficient ) and Il-4ra-/-/Il-5-/- ( wider Th2 deficiency including defect in macrophage alternative activation ) BALB/c mice result in 80 to 100% Mfpos mice [23] with 10 to 35 times higher microfilaremia . This is associated with an increase in the survival of filariae but also a better growth of the parasites and a more successful oogenesis . Both eosinophils and macrophages are known to be essential for the elimination of adult worms and Mf [17 , 30 , 31] . The decrease/absence of these cells in both mutant mice could thus explain the increased parasite survival . However even if the number of these cells is important their activation is also decisive . L . sigmodontis infection is known to induce an alternative activation macrophage-type phenotype ( AAM ) in the PC of mice [32 , 33] under the control of IL-4R [28] . Such an activation is independent of the microfilaremic status as an increase of CD206 expression was observed in all competent mice . CD169 has also been associated with an activation of a subset of macrophages under inflammatory conditions [34] . Together , increased CD206 and CD169 on human bronchoalveolar macrophages have been documented in a fibrotic setting [35] . Here Mfpos mice show an increased CD169 expression suggesting a role for CD169+ macrophages in the Mf-driven pathology . IFN-γ is known to induce CD169 expression on monocytes [29] and its increase in Mfpos mice could be responsible for the activation of CD206+ AAM . CD169 ( known as Siglec1/Sialoadhesin/MOMA-1 ) is a lectin receptor mediating the binding to neutrophils , innate lymphoid cells and dendritic cells or pathogens through sialylated glycoproteins and glycolipids [36] . L . sigmodontis Mfs are surrounded by a sheath containing such acids [37] , so it is possible that CD169 would help macrophages to adhere to Mfs to allow their phagocytosis . CD169 expression in lungs was previously thought to be specific for bronchoalveolar macrophages [38] even if some former reports noticed the presence of CD169+ cells in interstitial spaces [39 , 40] . We confirm that mouse lungs contain several groups of CD169-expressing tissue-resident macrophages with specific localizations . CD169+ tissue-resident macrophages were located at every interface area of the lungs , i . e . in alveoli ( alveolar macrophages ) and in the visceral pleura , around bronchi and blood vessels ( interstitial macrophages; IM ) and strikingly in these spaces , all the macrophages were CD169+ . The increase of IM in Mfpos mice could be due to a local proliferation of the macrophages [39] . Based on their prominent morphology and localization these cells are almost certainly the same tissue resident lung macrophages identified as likely to be yolk sac-derived cells with self-renewal properties in Runx1 lineage tracing experiments [41 , 42] . The increase of immune cells in the perivascular space ( PVS ) potentially informs us on the function of this anatomical structure . It is a connective tissue composed of extracellular matrix ( ECM ) which has a clear structural function in the maintenance of lung architecture but also in the migration of leukocytes [43] . Indeed ECM collagen fibers present in PVS may provide an attachment point for leukocyte motility around these pulmonary arteries or veins [44] . Accumulation of leukocytes has been observed in the PVS in models of lung infections , fibrosis , and allergic reactions [45–47] . It was also noticed in biopsies of patients affected by TPE [48] . Among these cells , CD169+ perivascular cells were increased during infection by another worm Schistosoma mansoni [49] . The function of such accumulation remains elusive . Because of their localization near blood vessels and airways , the cells present in PVS may have a role in the management of exogenous molecules and microorganisms . In the kidney , CD169+ perivascular macrophages play an important role in controlling inflammation by limiting neutrophil influx into the tissue [50] . CD169+ tissue-resident macrophages can stimulate innate lymphoid cell [51] but also initiate CD8+ T cell responses by binding of CD169 to dendritic cells [52] . It is unknown how Mfs escape the blood circulation , but this extravascular location seems accidental as Mfs are no longer available for transmission to the vector . PVS cells ( CD169+ IM and/or other cells like CD4 T-cells and innate lymphoid cells ) could be responsible for producing an IL-13/IL-4 rich microenvironment in response to Mfs , leading to goblet cell metaplasia and proliferation/recruitment of PVS CD169+ IM . In summary , these results suggest an unexpected role for CD169+ macrophages in response to Mf . They also support the use of chronic L . sigmodontis infection in Mfpos mice as a model of TPE , challenges the classification of L . sigmodontis infection as asymptomatic and potentially informs us on lung pathology in M . perstans infection in humans .
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Filarial infections are tropical diseases caused by nematodes of the Onchocercidae family . Infections due to filariae regularly induce pulmonary manifestations , however lung pathogenesis of human filarial infections is poorly understood . Litomosoides sigmodontis is a rodent filaria living in the pleural cavity and responsible for pleural inflammation which is used to model responses in human filarial infections . Here , we analyse lung inflammation during the chronic phase of the infection , when female parasites release their offspring ( microfilariae ) . 40% of mice do not present circulating microfilariae . We show that microfilariae enhance pleural cavity responses and induce pulmonary pathology ( bronchoalveolar eosinophilia , perivascular cell infiltrates , mucus production and fibrosis of the visceral pleura ) . Numerous groups of tissue-resident macrophages are identified at homeostasis in the lungs which increase upon infection . Th2-deficient mice present higher parasite burden but lower inflammation and pathology . Our study provides new insight in filarial lung inflammation which may help to understand pathogenesis of human infections .
|
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2019
|
IL-4 receptor dependent expansion of lung CD169+ macrophages in microfilaria-driven inflammation
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Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them . To help prepare for future influenza seasonal epidemics or pandemics , we developed a new stochastic model of the spread of influenza across a large population . Individuals in this model have realistic social contact networks , and transmission and infections are based on the current state of knowledge of the natural history of influenza . The model has been calibrated so that outcomes are consistent with the 1957/1958 Asian A ( H2N2 ) and 2009 pandemic A ( H1N1 ) influenza viruses . We present examples of how this model can be used to study the dynamics of influenza epidemics in the United States and simulate how to mitigate or delay them using pharmaceutical interventions and social distancing measures . Computer simulation models play an essential role in informing public policy and evaluating pandemic preparedness plans . We have made the source code of this model publicly available to encourage its use and further development .
Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them [1]–[9] . Detailed computer simulations will play an important role in evaluating containment and mitigation strategies for future epidemics [8] . Although many simulation models have been described in the literature , few are publicly available . Releasing the source code of models would allow others to evaluate the quality of the simulation , replicate results , and alter and improve the model . We have released the source code for a new stochastic model of influenza epidemics , FluTE . FluTE is an individual-based model capable of simulating the spread of influenza across major metropolitan areas or the continental United States . The model's structure is based on previously published work [3] , [6] , but FluTE incorporates a more sophisticated natural history of influenza , more realistic intervention strategies , and can run on a personal computer . Here , we describe the new model and illustrate how it can be used to study the dynamics of an epidemic and to investigate the population-level effects of interventions .
The simulation creates synthetic populations based on typical American communities . The population is divided into census tracts , and each tract is subdivided into communities of 500–3000 individuals based on earlier models [6] , [10] . Each community is populated by randomly generated households of size 1–7 using the US-wide family size distribution from the 2000 Census ( Table 1 ) . The household is the closest social mixing group , within which contacts between individuals occur most frequently and thus influenza is transmitted most often . The population is organized as a hierarchy of increasingly large but less intimate mixing groups , from the household cluster ( sets of four socially close households ) , neighborhoods ( 1/4 of a community ) , and the community . Although the model results are not sensitive to the exact size of these groups , including such groups creates a realistic contact network for disease transmission [11] . At night , everyone can make contact with other individuals in their families , household clusters , home neighborhoods , and home communities . In the daytime , individuals might interact with additional groups . During the day , most children attend school or a playgroup , where there is a relatively high probability of transmission . Preschool-age children usually belong to either a playgroup of four children or a neighborhood preschool , which typically has 14 students . Each community has mixing groups that represent two elementary schools , one middle school , and one high school , which typically have 79 , 128 , and 155 students , respectively . Most working-age adults ( about 72% of 19–64 year-olds ) are employed . Employment rates are determined on a tract-by-tract basis using data from the US Census 2000's Summary File 3 , table PCT35 . Employed individuals often work outside of their home communities . Each employed individual is assigned to work in a destination census tract based on commuting data taken from Part 3 of the Census Transportation Planning Package ( http://www . fhwa . dot . gov/ctpp/dataprod . htm ) , which provides information on the home and destination census tracts of workers in the United States . We eliminated commutes over 100 miles from the data as in [6] because many of these trips represent sporadic long-distance travel rather than daily commutes . Working individuals are assigned to communities and neighborhoods within their destination tracts to simulate casual community contacts during the day , and a work group of about 20 people to represent their close contacts at the workplace . Unemployed individuals remain in their home communities and do not have close daytime contacts except with members of their households who are not employed or enrolled in school . Individuals can engage in short-term , long-distance domestic travel to represent vacations and other trips . Travel in our model is based on the implementation in [6] , which uses data from the 1995 American Travel Survey data available from the U . S . Department of Transportation , Bureau of Transportation Statistics ( http://www . bts . gov/publications/national_transportation_statistics/ ) . Each day , an individual has a fixed probability of starting a trip based on an age-specific probability of traveling: 0 . 0023 for 0–4 year olds , 0 . 0023 for 5–18 , 0 . 0050 for 19–29 , 0 . 0053 for 30–64 , and 0 . 0028 for 65 and older . The traveler will stay at the destination for 0–11 nights , with 23 . 9% of trips lasting for a single day ( and no nights ) , 50 . 2% including 1–3 nights away , 18 . 5% including 4–7 nights away , and 7 . 4% for 8–11 nights . We do not include differences in travel frequency or duration during different times of the year ( e . g . , summer and holiday trips ) . The destination is a randomly selected census tract , in which a random community , neighborhood , and workplace ( if the traveler is between 19 and 64 years old ) are assigned to be the traveler's mixing groups . A random member of this community is assigned to be the traveler's contact person , and at night the traveler will behave as if he/she belongs to the contact's household , household cluster , and neighborhood . The traveler may withdraw to this household if ill . The exact implementation of short-term , long-distance travel is not important , but some long-distance travel is required in large populations for the epidemic to spread in a realistic manner . For simulations of smaller regions , such as a single county , there is no need to include long-distance travel . New infected individuals are introduced to a simulation by infecting randomly selected people . This epidemic seeding process can occur once at the beginning of a simulation or daily . In addition , one can simulate an epidemic that is seeded from international travelers . In this scenario , randomly selected individuals in the counties with one of the United States' 15 busiest international airports are infected each day , proportional to the daily traffic of these airports ( see Table 2 ) . The current modeling of the natural history of influenza is as follows: An individual is infectious for six days starting the day after becoming infected . The individual's infectiousness is proportional to the log of the daily viral titers taken from a randomly chosen one of the six experimentally infected patients described in [12] , [13] ( Figure 1 ) . An individual is asymptomatic during the incubation period , which lasts from one , two , or three days ( with 30% , 50% , and 20% probabilities , respectively ) . After incubation , the individual has a 67% chance of becoming symptomatic [14] , [15] . Symptomatic individuals are twice as infectious as asymptomatic people and may withdraw to the home after 0 to 2 days [16] ( with probabilities summarized in Table 3 ) . People who withdraw interact only with their households . Six days after infection , an individual recovers and is no longer susceptible . The simulation runs in discrete time , with two time steps per simulated day to represent daytime and nighttime social interactions . The contact probability of two individuals in the same mixing group is the probability that they will have sufficient contact for transmission during a time step . Contact probabilities of individuals within families were tuned so that the simulated household secondary attack rates match estimates from [17] ( Table 4 ) . Contact probabilities within other mixing groups were tuned so that the final age-specific illness attack rates were similar to past influenza pandemics ( Table 5 ) , particularly Asian A ( H2N2 ) and 2009 novel influenza A ( H1N1 ) influenza , and the percentage of transmissions that can be attributed to each mixing group matched those in [6] , [18]–[20] , although these values depend on the transmissibility ( ) of the disease ( Table 6 ) . These contact probabilities are in general agreement with other simulation models [8] and with a recent study of physical contacts between individuals [21] . Contact probabilities for all types of mixing groups are summarized in Table 7 . Transmission probabilities in the simulation are adjusted by multiplying all contact probabilities by a scalar , , to obtain the desired , the basic reproductive number , which is defined as the average number of secondary infections from a typical infected individual in a fully susceptible population [22] . To derive the relationship between and , we infected a single randomly selected person in an otherwise fully susceptible 2000-person community with a 74% working-age adult employment rate and counted the number of individuals that person infected , repeating this procedure 1 , 000 times for several values of . The relationship between the average number of secondary cases was approximately linear for a biologically plausible range of values: ( Figure 2 ) . However , the average number of secondary cases was higher when the index case was a child because children tend to infect more individuals ( and become infected more often ) than adults . Therefore , in a procedure borrowed from [6] , we measured the age distribution of secondary cases when the index case was randomly selected and used this distribution to weight the contribution from the various age groups to the calculation to define . The definition of applies to a population with no pre-existing immunity , an assumption that may be violated for seasonal influenza . One can use the model to simulate seasonal influenza epidemics by substituting with the desired , the average number of people a typical infected case infects in a population with pre-existing immunity . The simulated case generation time , or the time between infection of an individual and the transmission to susceptibles , was 3 . 4 days for a wide range of in a fully susceptible population ( Figure 2B ) . This is consistent with other estimates for seasonal and pandemic influenza [20] , [23] . The primary pharmaceutical intervention is vaccination . Vaccinated individuals in the simulation have a reduced probability of becoming infected ( VES ) , of becoming ill given infection ( VEP ) , and of transmitting infection ( VEI ) [24] . In the model , these efficacy parameters are implemented by multiplying the transmission probability per time step by ( 1−VES ) if the susceptible individual is vaccinated and by ( 1−VEI ) if the infectious individual is vaccinated . The probability of vaccinated individuals becoming symptomatic ( ill ) after they are infected is the baseline probability ( 67% ) multiplied by ( 1−VEP ) . Vaccines do not reach full efficacy immediately – their protective effects may gradually increase over several weeks . The default behavior in the model is that the vaccine takes two weeks to reach maximum efficacy , with the efficacy increasing exponentially starting the day after the vaccination . Because of the delay in reaching maximum efficacy , it may be necessary to vaccinate the population early . In the simulation , vaccines can be administered at least four weeks before the epidemic ( i . e . , pre-vaccination ) , during the epidemic ( reactive ) , or one dose can be administered at least three weeks before the epidemic and the boost can be administered reactively ( prime-boost ) . Antiviral agents ( neuraminidase inhibitors ) can be used for treatment of cases and for prophylaxis of susceptibles . A single course of antiviral agents is enough for 10 days of prophylaxis or 5 days of treatment . In the model , 5% of individuals taking antiviral agents prophylactically stop after 2 days and 5% taking them for treatment stop after 1 day [19] . As with vaccines , individuals taking antiviral agents can have reduced susceptibility ( AVES ) , probability of becoming ill given infection ( AVEP ) , and transmitting infection ( AVEI ) . However , unlike vaccines , the protective effects of the antiviral agents last only as long as they are being taken ( 5 to 10 days ) . When a case is ascertained , the individual is treated with antiviral agents , and that individual's household members will also each be given a course if household targeted antiviral prophylaxis ( HHTAP ) is in effect . Several non-pharmaceutical interventions can be simulated in the model . School closures are simulated by eliminating school group contacts ( including preschools and daycares but not playgroups ) for those enrolled in school , but adding daytime contacts with other household members not in school or at work and doubling their daytime neighborhood and community contact probabilities to account for their non-school activities . Schools can be closed when cases are ascertained in communities or in the schools , and they can be closed for a fixed number of days or for the duration of the simulation . During an epidemic , individuals may be requested to stay at home if they become ill . When simulating isolation of cases , individuals withdraw to the home one day after becoming symptomatic ( with a certain probability to represent the compliance probability ) . This will eliminate any daytime social contacts that they have other than with household members who are not working or at school . We simulate a liberal leave policy in a similar manner: employed individuals withdraw to the home with a pre-set compliance probability for one week one day after becoming symptomatic . During an epidemic , those living with symptomatic individuals may be requested to stay home [25] . In simulations of household quarantine , family members of symptomatic individuals will independently decide ( based on a compliance probability ) whether to obey quarantine for 7 days one day after the first individual becomes symptomatic . Individuals electing to quarantine themselves withdraw to the household and interact only with household members . If other family members become ill during quarantine , household members independently decide whether to obey quarantine for 7 days one day after each individual becomes symptomatic . FluTE is written in C/C++ and is released under the GNU General Public License ( GPLv3 , see http://www . gnu . org/licenses/gpl . html ) . The source code is available at http://www . csquid . org/software , https://www . epimodels . org/midas/flute . do , and the Models of Infectious Disease Agent Study ( MIDAS ) repository [26] . The software includes two source code files that are also freely distributable but may come with different licenses because they were written by others: one for the pseudorandom number generator ( SIMD oriented Fast Mersenne Twister ( SFMT ) pseudorandom number generator [27] ) and one to generate binomially distributed random numbers ( from Numerical Recipes in C [28] ) . Version 1 . 11 of FluTE was used to produce the results in this manuscript . A configuration file is used to specify the population to use for the simulation , the parameters for starting the epidemic , the transmissibility of the infectious agent , and the desired intervention strategies . The configuration file is text-based and can be typed in by a user or generated with a script . The simulation outputs results to text files , which can be easily parsed for plotting or statistical analysis . A parallelized version of the code supports simulations of large populations ( up to the entire continental United States ) . This version of the program assigns the populations of different counties to different processors , and OpenMPI is used to update the status of individuals who travel between communities that are located on different processors and to update the global status of the epidemic and the interventions ( e . g . , the total number of vaccines used ) . The simulation uses approximately 80 megabytes of memory per million simulated individuals . The simulation was written with several competing goals: to explicitly represent each individual in the population , to conserve memory , to run quickly , and to be ( relatively ) easy to read and modify . Each simulated individual is represented by a C structure that includes unique identifiers for the person and for each of the social mixing groups to which that person belongs , the age of the individual , the person's infection and vaccination status and dates , and other attributes . For each infected individual , the simulation identifies all susceptible individuals in that person's community who share a common mixing group , the infectiousness of the infected individual , the susceptibility of the susceptible , and the probability that transmission takes place for every time step . Although comparing each individual with every other within a community results in the number of comparisons increasing with the square of the number of individuals , community sizes are always smaller than 3 , 000 residents . Therefore , the number of comparisons made between individuals scales approximately linearly with the number of individuals in the simulation . More sophisticated algorithms could improve the simulation's performance , but may do so at the expense of the code's flexibility and readability . The running time depends on the number of individuals infected during the course of a simulation . Simulating an epidemic in a population of 10 million people can take up to two hours ( on a single processor on an Intel Core2 Duo T9400 ) , but it may take only seconds if the virus is not highly transmissible ( low ) or if there are effective interventions ( e . g . , high vaccination rates ) . On a cluster of 32 processors , simulating an epidemic covering the continental United States ( population of 280 million ) takes about 6 hours ( 192 hours of total CPU time ) .
We illustrate the use of the model by simulating epidemics in metropolitan Seattle , a major metropolitan area with a population of approximately 560 , 000 according to the US 2000 Census . We ran simulations with different values of , starting with ten infected individuals chosen at random , and found that the epidemic could peak as early as 45 days after the start if is high ( ) ( Figure 3A ) . Pre-vaccination ( with vaccine efficacies of VES = 40% , VEP = 67% , VEI = 40% , which correspond to a well-matched seasonal influenza vaccine [29] ) is likely to both lower and delay the epidemic peak ( Figure 3B ) . Use of antivirals alone ( AVES = 30% , AVEP = 60% , and AVEI = 62% [11] ) did not greatly reduce the epidemic peak , but they could reduce illness and mortality in an epidemic . Non-pharmaceutical interventions could be quite effective , but the epidemic may spike immediately upon ending the intervention ( compare permanent school closure with school closure for 60 days in Figure 3B ) . The illness attack rates in the simulation are lower than those in a SIR model with random mixing ( where [30] , where AR is the infection attack rate , and the illness attack rate is 0 . 67AR ) ( Figure 3C ) . As observed in earlier studies , models with community structure have lower attack rates than those with random mixing [31]–[33] . Simulated epidemics struck school-age children earlier than adults , which had been observed in earlier studies [6] , [34] . Therefore , we predict that early in an epidemic , the proportion of cases who are school-age children will be higher than later in the epidemic ( Figure 4 ) . This phenomenon might affect the accuracy of estimates in unfolding epidemics . For example , most confirmed cases in the recent novel influenza A ( H1N1 ) outbreaks in the United States have been school-age children [35] and several early estimates of have been above 2 [36] , [37] . In our model , we observed that infected children generate more secondary cases than infected adults ( Figure 2A ) . For example , infected school-age children would transmit to an average of other individuals in a simulated epidemic with . Therefore , estimates of could be high early in an epidemic when a disproportionate number of infections are in children . One can simulate the population of the entire continental US using the parallel version of FluTE ( mpiflute ) . The continental US had 280 million people in 64735 census tracts in 2000 , based on the US 2000 Census . In our simulations , we found that the final illness attack rates for the US to be nearly identical to those of metropolitan Seattle , but the epidemic peak for a given is later for the United States ( e . g . , 94 vs 65 days for ) ( Figure 5 ) . Therefore , simulations of a sufficiently large metropolitan area may be adequate for determining the effect of a strategy on the national level on final illness attack rates , but the nation-wide peak of the epidemic may be later than in the major metropolitan areas because of the time it takes the epidemic to reach outlying areas .
We have described a new publicly available influenza epidemic simulator , FluTE . It explicitly represents every individual in the simulation , so simulated epidemics can be studied in detail , even tracing individual transmission events . We illustrated the use of FluTE with examples in which we explored the effect of various intervention strategies on influenza epidemics in the United States and showed how transmissibility can be over-estimated early in an epidemic . The simulation was written so that one can easily set the transmissibility , vaccination policies ( e . g . , fraction of the population to vaccinate ) , and other reactive strategies ( e . g . , school closures ) . These settings can be used to investigate questions such as: 1 ) What fraction of the population will become infected or ill ? 2 ) How much vaccine coverage is required to mitigate an epidemic with a given ? 3 ) What segment of the population should be vaccinated to reduce overall illness attack rates the most ? 4 ) How long can one wait before reacting to an epidemic ? and 5 ) What range of can be managed by a particular pandemic strategy ? We have used FluTE to investigate some of these questions by simulating vaccinating children against seasonal and pandemic influenza [38] and pandemic mitigation [20] . The model was calibrated to simulate epidemics of a virus similar to 1957/1958 Asian A ( H2N2 ) and 2009 pandemic A ( H1N1 ) . We attempted to model realistic pharmaceutical and non-pharmaceutical interventions , but their effects on an epidemic have not been well quantified . The model's results are plausible and likely to be qualitatively correct , but there is insufficient data to calibrate it to produce quantitatively accurate results for the various possible disease parameters and mitigation strategies . Although the model generates realistic population-level results , the spatial dynamics of the epidemics it produces should be used for illustrative purposes only . When using the model to evaluate mitigation strategies , it is important to consider one's goals . For example , using antiviral agents to treat cases does not greatly reduce the final illness attack rate in the simulation , but it could greatly reduce mortality . The model does not directly evaluate the cost of interventions , but the numbers of cases in a simulated epidemic can be linked to cost and healthcare utilization data [39] . Differential equation models are the most popular approach to disease modeling . The simplest of these ( such as the SIR model [40] ) can be used to study epidemics analytically , and more complex versions have been used to model the dynamics of epidemics on a global scale [41] , [42] . However , if one wants to include a complicated natural history of disease or detailed intervention strategies , individual-based models , such as FluTE , may be more suitable . The current software supports a limited set of configuration options and is intended for batch runs using a scripting language . Using the model for scenarios not supported by the existing code , such as testing a novel intervention strategy or altering the contact parameters for a different attack rate pattern , would require modification of the source code , which we have released so that others can make such changes if needed . We decided to adopt the GNU General Public License ( GPL ) , so that the source code of derivative works must be released . We believe this will facilitate the sharing of improvements . The availability of source code allows others to adapt the model to simulate outbreaks of other airborne infectious diseases such as smallpox [3] , [43] , [44] or to simulate other regions of the world with different social structures [3] . In the future , we would like to make our model more accessible to non-programmers . This may involve developing a user interface or adding new parameters to the configuration file . We would also like to include intervention strategies that best reflect government pandemic mitigation plans . Achieving these goals would depend upon close collaboration with public health officials to better understand their needs and to carefully simulate existing pandemic mitigation plans and capacities . Although we have calibrated our model to the best available data , more detailed and reliable information on the natural history of influenza , influenza transmission , human behavior in response to infection , and vaccine efficacy is needed . Sensitivity analyses of similar epidemic models have shown that results are robust to uncertainty in many parameters [3] , [5] , [6] , [11] . However , more accurate model inputs would improve the quantitative predictions . Well-designed studies are needed to acquire these data .
|
Computer simulations can provide valuable information to communities preparing for epidemics . These simulations can be used to investigate the effectiveness of various intervention strategies in reducing or delaying the peak of an epidemic . We have made a detailed influenza epidemic simulator for the United States publicly available so that others may use the software to inform public policy or adapt it to suit their needs .
|
[
"Abstract",
"Introduction",
"Model",
"Results",
"Discussion"
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"public",
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"epidemiology/epidemiology",
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2010
|
FluTE, a Publicly Available Stochastic Influenza Epidemic Simulation Model
|
Arsenic is a well-established human carcinogen of poorly understood mechanism of genotoxicity . It is generally accepted that arsenic acts indirectly by generating oxidative DNA damage that can be converted to replication-dependent DNA double-strand breaks ( DSBs ) , as well as by interfering with DNA repair pathways and DNA methylation . Here we show that in budding yeast arsenic also causes replication and transcription-independent DSBs in all phases of the cell cycle , suggesting a direct genotoxic mode of arsenic action . This is accompanied by DNA damage checkpoint activation resulting in cell cycle delays in S and G2/M phases in wild type cells . In G1 phase , arsenic activates DNA damage response only in the absence of the Yku70–Yku80 complex which normally binds to DNA ends and inhibits resection of DSBs . This strongly indicates that DSBs are produced by arsenic in G1 but DNA ends are protected by Yku70–Yku80 and thus invisible for the checkpoint response . Arsenic-induced DSBs are processed by homologous recombination ( HR ) , as shown by Rfa1 and Rad52 nuclear foci formation and requirement of HR proteins for cell survival during arsenic exposure . We show further that arsenic greatly sensitizes yeast to phleomycin as simultaneous treatment results in profound accumulation of DSBs . Importantly , we observed a similar response in fission yeast Schizosaccharomyces pombe , suggesting that the mechanisms of As ( III ) genotoxicity may be conserved in other organisms .
Arsenic is a toxic element ubiquitously present in the environment . Carcinogenic properties of arsenic have been known for a long time and chronic exposure to arsenic in humans has been implicated in numerous types of cancer , including skin , lung , liver , kidney and bladder cancer [1] . On the other hand , due to its cytotoxic properties arsenic is successfully used as antileukemic drug [2] and in the treatment of tropical diseases caused by the protozoan parasites [3] . Since exposure of millions of people to high doses of arsenic in drinking water constitutes a serious health problem [4] and because of increasing use of arsenic as therapeutic agent [5] , it is of great importance to elucidate the mechanisms of arsenic toxicity and tolerance . Up to now , several mechanisms have been proposed to explain carcinogenicity of arsenic , including increased formation of reactive oxygen species ( ROS ) causing oxidative DNA damage such as single-strand breaks ( SSBs ) that can be processed to double-strand breaks ( DSBs ) during replication , inhibition of DNA repair and enhancing mutagenicity and carcinogenicity of other factors , like UV light , global changes in DNA methylation and histone modifications and spindle disruption [6] . In human cell lines exposed to arsenic an accumulation of oxidative DNA damage in the form of 8-hydroxy-2′-deoxyguanosine ( 8-OHdG ) has been shown , which is reversed by addition of antioxidants [7] . On the other hand , inhibition of mRNA synthesis of key base excision repair ( BER ) enzymes , polymerase beta , AP endonuclease , DNA ligase I and III , as well as enzymatic activity of DNA ligases , have also been observed in the presence of arsenite [As ( III ) ] [8] , [9] . These results imply that arsenic increases levels of oxidative stress and at the same time inhibits repair of oxidative DNA damage by BER . Decreased expression of nucleotide excision repair ( NER ) genes , like ERCC1 , XPF and XPA , has been detected in the cells isolated from humans exposed to arsenic in drinking water [10] . Recently it has been reported that poly ( ADP-ribose ) polymerase 1 ( PARP-1 ) is inhibited by As ( III ) and proposed that As ( III ) binding to a zinc finger domain instead of zinc is responsible for inactivation of the PARP-1 protein [11] . In support of this notion , Zhou et al . [12] have just shown that As ( III ) interacts selectively with zinc finger motifs . Thus both As ( III ) -induced decrease of BER and NER enzyme expression and inhibition of poly ( ADP-ribosyl ) ation by As ( III ) is a likely mechanism for co-carcinogenic activities of arsenic in UV light-induced skin carcinogenesis . Impairment of BER and NER action by As ( III ) likely results in accumulation of SSBs and other types of DNA lesions which perturb replication fork progression leading to fork collapse and generation of DSBs . Indeed , it has been recently demonstrated in human cell lines that As ( III ) induces replication-dependent DSBs which are repaired by HR [13] . Additionally , in As ( III ) -treated cells chromosome aberrations and formation of micronuclei are often observed [6] . As ( III ) shows high affinity to tubulin and inhibits its polymerization , thus likely contributing to spindle formation and chromosome segregation defects [14] , [15] . However , none of above mechanisms has been directly linked to carcinogenesis , while the genotoxic potential of arsenic is still the subject under debate . The yeast Saccharomyces cerevisiae proved to be an excellent model organism to study the mechanisms of action of various DNA damaging agents . It has been reported that As ( III ) delays the budding yeast cell cycle in all phases [16] and induces phosphorylation of the Rad53 checkpoint kinase ( CHK2 in humans ) [17] . Importantly , several genome-wide screens have revealed that deletion of yeast genes encoding proteins involved in sensing and repairing of DNA damage , e . g . genes for the Mre11-Rad50-Xrs2 complex ( Mre11-Rad50-Nbs1 in humans ) [18]–[21] , Yku70 involved in non-homologous end joining ( NHEJ ) [19] and homologous recombination ( HR ) proteins Rad51 [21] , Rad57 [21] and Rad52 [18]–[22] , resulted in increased sensitivity to As ( III ) . However , the role of DNA damage response in cell cycle regulation and genomic integrity during As ( III ) stress as well as the mechanisms of As ( III ) genotoxicity have never been investigated in greater detail . The purpose of this study was to identify the types of DNA damage generated by As ( III ) in budding yeast and DNA repair pathways involved in removing such lesions depending on the cell cycle stage . We also sought to investigate the role of DNA damage checkpoints in surviving exposure to As ( III ) . We have collected several lines of evidence suggesting that the effect of As ( III ) on DNA is more complex than previously thought and involves a direct generation of DSBs throughout the cell cycle in addition to oxidative and replication-associated DNA damage . We also found that budding and fission yeast simultaneously exposed to As ( III ) and the DSB-inducing drug phleomycin suffer from a massive chromosome breakage leading to cell death . This would suggest that both drugs could be combined to develop more efficacious anticancer therapies .
To study the role of DNA damage checkpoints during arsenic stress in S . cerevisiae , we first compared the phosphorylation level of the checkpoint effector kinase Rad53 ( CHK2 in humans ) in wild type cells in response to non-growth inhibitory concentration of 0 . 5 mM sodium arsenite [As ( III ) ] and other DNA damaging agents , like the DSB-inducing drug phleomycin ( PM ) and the DNA alkylating agent methyl methanesulfonate ( MMS ) . Rad53 is hyperphosphorylated in response to DSBs in all phases of cell cycle as well as during replication stress as a result of exposition of single strand DNA ( ssDNA ) gaps [23]–[25] . As expected , we found high levels of slow-migrating hyperphosphorylated form of Rad53 in response to PM and MMS ( Figure 1A ) . In agreement with a previous report [17] , 1 h treatment with 0 . 5 mM As ( III ) triggered moderate activation of Rad53 ( Figure 1A ) . Histone H2A ( yeast H2AX ) phosphorylation at S129 is considered to be a sensitive marker of both DSBs and replication fork stalling [26]–[29] . We found that 0 . 5 mM As ( III ) promotes high-level phosphorylation of histone H2A ( Figure 1A ) . However , histone H2A activation was not detected with concentrations lower than 0 . 25 mM As ( III ) . In human cells H2AX phosphorylation is induced at 10–100-fold lower concentrations of As ( III ) [13] but mammalian cells are much more sensitive to As ( III ) than yeast due to the lack of metalloid-specific detoxification transport systems [30] . Thus , we also checked the level of histone H2A phosphorylation in the acr3Δ ycf1Δ double mutant devoid of As ( III ) transporters [30] and found a dose-dependent increase of histone H2A phosphorylation starting from 0 . 05 mM As ( III ) ( Figure 1A ) . It has been suggested that in mammalian cells As ( III ) generates only replication-dependent DSBs [13] . Thus , we monitored As ( III ) -induced activation of H2A and Rad53 in various phases of the yeast cell cycle . Wild type yeast were synchronized in G1 by 5 µM α-factor and treated with 0 . 5 mM As ( III ) for 1 h or left untreated in the presence of α-factor to prevent entering S phase . Alternatively , G1-synchronized cells were released in the absence of α-factor to allow progression into S phase and after 30 min were exposed to 0 . 5 mM As ( III ) for 1 h . G2/M-arrested cells were obtained by incubation with 15 µM nocodazole followed by 1 h exposure to 0 . 5 mM As ( III ) in the presence of nocodazole to inhibit completion of mitosis . We found that histone H2A , and Rad53 are phosphorylated in S and G2/M cells exposed to As ( III ) but no DNA damage response activation was observed in G1-synchronized cells ( Figure 1B ) . Importantly , in the absence of the checkpoint adaptor/mediator protein Rad9 ( 53BP1 , BRCA1 or MDC1 in humans ) Rad53 was not hyperphosphorylated indicating that As ( III ) induces the classical DNA damage response ( Figure 1B ) . In yeast activation of DNA damage signalling cascades requires two sensor kinases Mec1 and Tel1 ( ATR and ATM in humans ) , which belong to the phosphoinositide 3-kinase-related kinases ( PIKKs ) family [23] , [31] . Tel1 is involved in sensing DSBs , while Mec1 is activated by the RPA-coated ssDNA structures , which are present at stalled replication forks but are also formed as a result of DSB resection [31] . To determine the roles of Mec1 and Tel1 in As ( III ) -induced activation of DNA damage checkpoint response , we investigated phosphorylation level of histone H2A and Rad53 in mec1-1 and tel1Δ mutants synchronized in S and G2/M phases . We found that histone H2A and Rad53 activation in G2/M cells was fully dependent on the Mec1 kinase as no phosphorylated forms of both H2A and Rad52 were detected in mec1-1 cells treated with As ( III ) , while in the tel1Δ mutant activation of H2A and Rad53 was at the wild type level ( Figure 1C ) . A similar response was observed in S phase , however , we detected a residual level of phosphorylated H2A and Rad53 in mec1-1 cells but not in the double mec1-1 tel1Δ mutant ( Figure 1C ) . This indicates that Mec1 is a major sensor kinase responsible for As ( III ) -induced activation of DNA damage signalling with a minor involvement of Tel1 kinase in S phase . Interestingly , DSB-inducer PM induces a similar pattern of DNA damage response activation in S and G2/M phases [32] , while hydrogen peroxide ( H2O2 ) and MMS trigger DNA damage response exclusively in S phase [33] , [34] . This might suggest that As ( III ) is capable of producing both replication-dependent and independent DSBs . Activation of DNA damage response often leads to cell cycle delay to allow time for DNA repair [31] . Thus , we compared cell cycle progression of wild type cells and the checkpoint-defective rad9Δ mutant upon exposure to As ( III ) . In the presence of As ( III ) , cells lacking Rad9 progressed faster through S phase than wild type cells as seen by flow cytometry analysis ( Figure 1D ) and showed G2/M checkpoint arrest defect measured by counting binucleate cells which completed mitosis ( Figure 1E ) . Analysis of G1/S transition by the α-factor-nocodazole trap assay revealed DNA damage checkpoint-independent arrest in G1 during As ( III ) treatment ( Figure 1F ) , which is in agreement with the lack of Rad53 and histone H2A phosphorylation in this phase ( Figure 1B ) . Finally , we analyzed whether activation of DNA damage checkpoints affects cell viability in the presence of As ( III ) . All tested checkpoint-defective mutants showed reduced growth on 1 mM As ( III ) -containing solid media ( Figure 1G ) . We also checked survival of these mutants during short-term acute exposure to high concentrations of As ( III ) ( Figure 1H ) and confirmed a significant role of Mec1- , Tel1- and Rad9-dependent DNA damage checkpoint activation in coping with As ( III ) toxicity . A pronounced activation of DNA damage checkpoint in S phase and DNA synthesis completion delay in the presence As ( III ) ( Figure 1 ) suggests that As ( III ) exposure leads to oxidative and replication-associated DNA damage as it is observed in mammalian cells [7] , [13] . To test this directly , we first checked whether As ( III ) induces formation of ROS by measuring oxidation of dihydrorhodamine 123 ( DHR123 ) to fluorescent product rhodamine 123 ( R123 ) by flow cytometry ( Figure 2A ) . Levels of ROS were monitored in S . cerevisiae cells at several time-points during 2 h exposure in the presence of As ( III ) as well as H2O2 or menadione used as positive controls for oxidative stress . We observed a gradual accumulation of ROS in each treatment with a maximum level at 2 h time point shown in Figure 2A . However , exposure to As ( III ) resulted only in a slight increase of R123 green fluorescence indicating the presence of low levels of As ( III ) -induced ROS . In contrast , H2O2 and menadione treatments led to a massive accumulation of R123 . Consequently , exposure of S . cerevisiae cells to As ( III ) resulted in 2-fold increase of oxidative DNA damage in the form of 8-OHdG , while H2O2 and menadione treatments caused 8 . 5-fold increase of 8-OHdG production compared to control conditions ( Figure 2B ) . The data suggest that in budding yeast As ( III ) is a weak inducer of oxidative stress and thus produces low levels of oxidative DNA damage . Next , we asked whether As ( III ) -induced oxidation of DNA leads to replication perturbations which can be monitored by detecting post-translational modifications of proliferating cell nuclear antigen ( PCNA ) , a processivity factor for DNA polymerases and platform for binding other proteins involved in DNA replication and repair [35] . PCNA is sumoylated at K164 during normal S phase to prevent unscheduled recombination events during replication and mono- and polyubiquitylated at the same residue in response to replication fork stalling due to nucleotide depletion or DNA polymerase-blocking lesions [36] . PCNA ubiquitylation is observed in response to hydroxyurea ( HU ) , MMS , UV and H2O2 treatment but not to campthotecin which causes replication fork collapse or DSB-inducing drugs like bleomycin [37] . Monoubiquitylation of PCNA is mediated by the Rad6 ubiquitin-conjugating ( E2 ) enzyme and the Rad18 ubiquitin ligase ( E3 ) and promotes the error-prone translesion synthesis ( TLS ) by recruiting TLS polymerases that are able to catalyze DNA synthesis across the damaged template [35] . Monoubiquitylated PCNA can be further polyubiquitylated by E2 Ubc13-Mms22 and E3 Rad5 to trigger an error-free mechanism of DNA damage bypass which engages template switch and recombination proteins [35] . As expected we detected ubiquitylation of PCNA in the presence of MMS used as a positive control of replication stress inducer while no ubiquitylation of PCNA was observed in response to PM exposure or in the rad18Δ mutant under any conditions studied ( Figure 2C ) . During exposure to 0 . 5 mM As ( III ) in S phase we found a faint band of monoubiquitylated PCNA indicating that cells experience some level of DNA lesions blocking replication ( Figure 2C ) . The presence of polyubiquitylated PCNA was difficult to assess as diubiquitylated and sumoylated forms of PCNA migrate roughly at the same speed in our SDS-PAGE gels . The physiological importance of PCNA ubiquitylation in coping with As ( III ) -induced replication perturbations is evident in cells lacking the Rad18 ubiquitin ligase which showed increased sensitivity to As ( III ) ( Figure 2D ) . Interestingly , the rad18Δ and rad6Δ mutants were also identified as weakly sensitive to As ( III ) in genome-wide screens [18] , [20] , [21] . In sum , our results indicate the ability of As ( III ) to produce oxidative DNA damage , however at relatively low levels compared to H2O2 or menadione , which may result in replication perturbations manifested by ubiquitylation of PCNA . In haploid yeast DSBs are mainly repaired by HR during S and G2/M phases , while NHEJ plays a minor role as this pathway is quite inefficient in re-joining imprecise DNA ends [38] . To test our hypothesis that As ( III ) is a genotoxic agent that induces DSBs in budding yeast , we investigated whether HR or NHEJ protect yeast against As ( III ) -induced DNA damage , by comparing viability of wild type and mutant cells devoid of various components of HR pathways ( rad51Δ , rad52Δ , rad59Δ ) and NHEJ ( yku70Δ , dnl4Δ ) in the presence of As ( III ) ( Figure 3A ) . We found that all HR mutants tested were more sensitive to As ( III ) than wild type supporting the notion that HR is required for the repair of As ( III ) -induced DNA damage presumably DSBs and/or ssDNA gaps that form as a result of replication perturbations . Interestingly , cells lacking Yku70 but not the DNA ligase IV Dnl4 , showed increased sensitivity to As ( III ) suggesting a NHEJ-independent role of Yku70/Yku80 complex in tolerance to As ( III ) . Importantly , BER ( apn1Δ apn2Δ ) and NER ( rad14Δ ) defective mutants were not sensitive to As ( III ) . However , the triple mutant apn1Δ apn2Δ rad51Δ showed increased sensitivity to As ( III ) compared to single rad51Δ suggesting that As ( III ) induces some oxidative damage of DNA repaired by BER , with the majority of As ( III ) -induced DNA damage being DSBs repaired by HR ( Figure 3A ) . To better assess the importance of NHEJ and HR proteins for As ( III ) tolerance , we compared survival of wild type and single yku70Δ , rad51Δ , rad52Δ mutants as well as the yku70Δ rad51Δ double mutant after 6 h exposure to high concentrations of As ( III ) ( Figure 3B ) . The rad52Δ and yku70Δ rad51Δ mutants were most sensitive to As ( III ) . The rad51Δ mutant showed intermediate sensitivity to As ( III ) , while yku70Δ were the least sensitive . This confirmed the essential role of HR in coping with As ( III ) -induced DNA damage . To show that As ( III ) -induced DNA damage is actively repaired by HR we monitored nuclear localization of Rfa1-YFP , the large subunit of ssDNA-binding RPA complex , and the DNA recombinase Rad52-YFP , that both form distinct fluorescence foci representing the DNA repair centres of multiple DSBs [39] . In asynchronously growing cells exposed to 0 . 5 mM As ( III ) for 1 h we observed 2–3-fold increase of the number of cells with Rfa1 and Rad52 foci over spontaneous levels ( Figure 3C ) . To directly demonstrate the presence of As ( III ) -induced DNA breaks throughout the cell cycle , asynchronous , logarithmically growing ( mostly in S phase ) , G1 and G2/M-synchronized S . cerevisiae cells were exposed to 1 mM As ( III ) for 1 h and analyzed by the comet assay , also known as a single cell gel electrophoresis . This method is routinely used in mammalian cells to measure levels of SSBs and DSBs as visualised by the formation of the comet tail [40] . Recently , the comet assay has been adapted and optimized for yeast cells to detect DNA breakage induced by H2O2 [41] , [42] , chemical genotoxins [42] and changes in chromatin organization [43] . A comet head represents an intact DNA , while a comet tail is composed of relaxed DNA loops as a result of DNA damage . However , in contrast to the well-defined mammalian comet tails , the typical yeast comet tails appeared rough , grainy , lumpy , with blobs of various sizes , probably due to less compacted chromatin with fewer heterochromatin domains compared to mammalian chromatin [41]–[43] . The yeast comet assay revealed that As ( III ) induces DNA breaks independently of the cell cycle phase ( Table 1 and Figure 4A ) . The high incidence of the observable DNA damage was detected in logarithmically growing ( mostly S phase ) cells ( 16 . 9% ) . In contrast , the relatively small number of G2/M cells ( 6 . 4% ) showed As ( III ) -induced DNA damage . Interestingly , 14 . 1% of G1 cells exhibited the presence of DNA breaks after As ( III ) treatment . The analysis of yeast comets summarized in Table 1 revealed that As ( III ) -induced comet tails were 2 times longer and contained between 2- and 3-fold more DNA than spontaneous tails . The level of DNA breaks were similar in asynchronous and G1 cells and slightly lower in G2/M cells . As the alkaline comet assay used in this study does not differentiate between SSBs and DSBs , we performed pulsed-field gel electrophoresis ( PFGE ) of budding yeast chromosomes isolated from asynchronous , G1- and G2/M-synchronized cells treated with As ( III ) for 6 h ( Figure 4B ) . The presence of DSBs can be visualized as the disappearance of distinct chromosome bands and accumulation of low molecular weight smear . Considering relative low levels of As ( III ) -induced DNA breaks measured with the comet assay and previously reported lack of detectable DNA breaks in PFGE in response to 1 mM As ( III ) [19] , we exposed yeast cells to much higher concentrations of As ( III ) . Fragmentation of DNA became evident after treatment with 20 mM As ( III ) and pronounced degradation of chromosomes was observed in the presence of 25 mM As ( III ) in all cell cycle phases ( Figure 4B ) . To confirm that As ( III ) -induced DNA degradation detected with PFGE are caused by replication-independent DSBs , the yeast chromosomes were prepared from G2/M-synchronized MWJ49 strain containing a circular chromosome III which does not enter the gel during PFGE unless is broken into a linear chromosome [44] . The broken chromosome III can be detected by Southern hybridization as a separate band and serves as a measurement of DSB generation . In the presence of 25 mM As ( III ) we were able to detect the linear form of chromosome III confirming that As ( III ) induces replication-independent DSBs ( Figure 4C ) . The presence of As ( III ) -induced DSBs in G1 revealed by the yeast comet assay and PFGE seemed to contradict our previous observation that As ( III ) treatment did not lead to phosphorylation of histone H2A and Rad53 in G1 cells ( Figure 1 ) which suggested that As ( III ) -induced DSBs do not form in this phase of the cell cycle . One possible explanation would be to assume that As ( III ) -induced DSBs do indeed form but are not resected in G1 and DNA damage signal is not transduced to the checkpoint pathway . It has been shown that oxidative DNA lesions caused by H2O2 treatment are silently repaired in G1 and G2/M with no activation of Rad53 kinase in these cell cycle phases [33] . In contrast , when BER is compromised by deletion of APN1 and APN2 endonuclease genes , H2O2-induced phosphorylation of Rad53 is observed in all phases of the cell cycle . It has also been reported that endonuclease-induced DSBs are not resected in G1 due to the Yku70–Yku80-dependent but NHEJ-independent protection of DNA ends [45] , [46] . In agreement with our hypothesis that in G1 As ( III ) -induced DSBs are not resected and signalled to DNA damage checkpoint , we demonstrated that the yku70Δ mutant , but not the mutants defective in NHEJ ( dnl4Δ ) or BER ( apn1Δ apn2Δ ) , showed phosphorylation of histone H2A and Rad53 in G1 after As ( III ) treatment ( Figure 5A ) . Consequently , we detected a markedly elevated level of As ( III ) -induced Rfa1 foci in the yku70Δ mutant in G1 phase indicating the presence of DSBs undergoing 5′ end resection ( Figure 5B ) . As opposed to As ( III ) , exposure to H2O2 and MMS in G1 phase did not induce the DNA damage response activation in yku70Δ mutant , while treatment with these agents but not As ( III ) led to pronounced levels of H2A and Rad53 phosphorylation in apn1Δ apn2Δ mutant ( Figure 5C ) . These results strongly suggest that DNA lesions generated by As ( III ) in G1 are quite specific and different in nature from H2O2 and MMS-induced DNA damage and thus are not processed by BER . We have thus demonstrated using several assays that As ( III ) has the ability to induce DSB in the G1 phase of the cell cycle , i . e . independently of the replication process . Although we showed generation of As ( III ) -induced DSBs outside S phase indicating that As ( III ) may act as a direct inducer of DSBs , oxidative DNA damage produced by As ( III ) might generate transcription-associated DSBs . It has been recently reported that in non-replicating mammalian cells DSBs are formed when transcription is blocked by camptothecin-induced stalling of topoisomerase I ( TOP1 ) cleavage complex which normally removes DNA supercoiling produced by transcription [47] . It has been proposed that under physiological conditions ROS-induced oxidative DNA lesions could also trap TOP1 cleavage complex and generate transcription-associate DSBs [47] , [48] . Importantly , addition of chemical inhibitors of RNA polymerase II prevented formation of transcription-linked DSBs in mammalian cells [47] . To determine whether As ( III ) can induce transcription-dependent DNA damage , we examined phosphorylation of histone H2A at S129 in cells treated with As ( III ) in the presence of thiolutin which inhibits all three RNA polymerases [49] , [50] ( Figure 6A ) . Alternatively , we shut off RNA synthesis by using the rpb1-1 allele , a temperature-sensitive mutant in the catalytic subunit of RNA polymerase II [50] , [51] ( Figure 6B ) . Under both conditions inhibition of transcription did not decrease phosphorylation of histone H2A in both asynchronous and G2/M-arrested wild type as well as in G1-synchronized yku70Δ cells treated with As ( III ) suggesting that As ( III ) -induced DNA damage is not associated with transcription ( Figure 6 ) . It has been reported that As ( III ) pretreatment can increase the cytotoxic effect of radiomimetic drug bleomycin in Chinese hamster ovary cells , probably by hampering the cellular mechanisms which inactivate bleomycin [52] . In addition , arsenic radiosensitizes cancer cell lines and solid tumors [53]–[55] . Increased death of cancer cells has been explained by elevated ROS production followed by induction of autophagy and apoptosis [53] , [54] . To test the cytotoxic effect of DSB-inducing agents combined with As ( III ) in yeast , growth of wild type cells and DNA repair mutants was tested in the presence of both As ( III ) and the bleomycin-related agent PM or As ( III ) and PM alone ( Figure 7A ) . In addition , yeast cells were exposed to 100 Gy and 500 Gy of ionizing radiation ( IR ) and then plated in the presence or absence of 0 . 5 mM As ( III ) ( Figure 7B ) . We found that As ( III ) profoundly sensitized yeast cells to PM . In the presence of both drugs the growth of all tested yeast strains , both wild type and DNA repair mutants , was strongly inhibited ( Figure 7A ) . In contrast , the combined treatment with As ( III ) and IR conferred a slight additive effect on growth inhibition of all tested strains indicating that As ( III ) only weakly increased cytotoxic effect of IR ( Figure 7B ) . Similarly , co-treatment of with As ( III ) and HU ( Figure 7C ) or MMS ( Figure 7D ) moderately increased sensitivity of wild type and DNA repair mutants to these genotoxic drugs . These findings can be interpreted that As ( III ) specifically enhances ability of PM to generate DNA damage , while in the case of IR , HU and MMS co-treatment we observed the additive cytotoxic effect of two DNA damaging agents acting separately . To investigate whether the enhanced cytotoxicity of combined treatment with As ( III ) and PM is the result of increased DNA damage in the form of DSBs , we first monitored the formation of Rad52-YFP foci in wild type during As ( III ) and PM co-treatment and noticed that the number of cells containing Rad52-foci was increased by 2-fold compared to samples treated with a single agent ( Figure 8A ) . This implies that combined treatment with As ( III ) and PM leads to accumulation of DNA damage which is repaired by HR . In order to show directly that As ( III ) sensitizes yeast to PM by inducing more DSBs , we performed PFGE and Southern analysis of yeast chromosomes isolated from the MWJ49 yeast strain containing a circular chromosome III [44] . After As ( III ) or PM treatment we observed no appearance of the linear form of chromosome III ( Figure 8B ) . However , in the case of PM some fragmentation of chromosomes was already evident as a background DNA smear . Interestingly , As ( III ) and PM co-treatment resulted in a massive breakage of chromosomes and accumulation of the singly broken chromosome III ( Figure 8B ) . Moreover , mutants devoid of RAD59 gene involved in repair of DSBs by single-strand annealing , which renders yeast cells more sensitive to both As ( III ) and PM ( Figure 7B ) , accumulated more DNA breaks after single PM and combined treatment ( Figure 8B ) . To show that the observed accumulation of DSBs is the result of direct genotoxicity of As ( III ) and PM and does not require replication to process SSBs into DSBs , wild type cells were synchronized in G1 or G2/M followed by exposure to As ( III ) and PM and analyzed by PFGE . This experiment revealed that As ( III ) and PM co-treatment caused a massive fragmentation of chromosomes also in the absence of replication ( Figure 8C ) . PM is a copper-chelating peptide which is able to bind to DNA and in the presence of oxygen converts itself to a free radical reactive complex producing oxidized apurinic/apyrimidinic ( AP ) sites , SSBs and DSBs [56] . In the case of PM-related bleomycin addition of iron ions enhances DNA damage by facilitating contact between bleomycin and DNA as well as by activating oxygen to generate free radicals [57] . Indeed , we showed that extra addition of Cu ( II ) ions increased PM-induced DNA fragmentation similarly to As ( III ) ( Figure 8D ) . We also wondered whether the free Cu ( II ) , which is present in the solution of PM added to the cells , is responsible for the observed phenomenon . However , combined exposure to As ( III ) and Cu ( II ) in the form of copper sulfate did not result in DNA breakage detectable by PFGE ( Figure 8D ) . Combination of As ( III ) and Cu ( II ) did not increase PM-dependent DNA fragmentation but instead inhibited this process , probably as a result of formation of copper arsenite which is insoluble in water ( Figure 8D ) . In sum , these observations suggest a specific interplay between As ( III ) and PM which leads to cell death as a result of increased DNA fragmentation . To test whether As ( III ) shows a similar mode of genotocixity in another model organism , we performed the PFGE analysis of chromosomes isolated from a distantly related fission yeast S . pombe exposed to increasing concentrations of As ( III ) . As shown in Figure 9A , 25 mM As ( III ) treatment caused pronounced breakage of fission yeast chromosomes . Moreover , the S . pombe mutants devoid of HR proteins Rad51 and Rad52 displayed higher sensitivity to As ( III ) than wild type ( Figure 9B ) . Consequently , combined treatment with As ( III ) and PM resulted in a complete degradation of chromosomes ( Figure 9C ) . In sum , this data indicate that the ability of As ( III ) to induce low levels of DSBs and enhance genotoxicity of PM by generating more DSBs is not restricted to budding yeast . It is thus possible that As ( III ) may act in a similar way in higher eukaryotes too .
Carcinogenic properties of As ( III ) are explained in current literature as a result of As ( III ) -induced accumulation of ROS causing oxidative DNA damage , including SSBs and other types of DNA lesions which perturb replication fork progression leading to fork collapse and generation of DSBs [4] , [6] , [7] , [13] . Besides it has been reported that As ( III ) inhibits BER and NER pathways further contributing to accumulation of oxidative DNA lesions [8] , [9] , [13] . Contrary to what was believed previously , we have discovered that As ( III ) generates not only oxidation of nitrogen bases and SSBs leading to replication-coupled DSBs but also replication-independent DSBs in all phases of the cell cycle . In wild type yeast As ( III ) induces the DNA damage checkpoint response in both S and G2/M phase ( Figure 1 ) but is also able to phosphorylate histone H2A and Rad53 kinase in G1-arrested cells when the DNA end-binding Yku70–Yku80 complex is absent ( Figure 5A ) . This suggests that As ( III ) may generate replication-independent DSBs in G1 that are normally bound by Yku70–Yku80 and activate the cell cycle checkpoint only in the yku70Δ mutant when the resection of DNA ends is not inhibited . Indeed , we observed formation of Rfa1 nuclear foci in As ( III ) -treated yku70Δ cells arrested in G1 indicating the presence of As ( III ) -induced DSBs which are resected and coated by Rfa1 ( Figure 5B ) . Accumulation of DNA breaks in all phases of the cell cycle after As ( III ) treatment was also evident in the comet assay ( Figure 4A and Table 1 ) . Since similar number of G1 wild type cells showed the presence of DNA breaks ( Table 1 ) and Rfa1 foci after deletion of YKU70 which are indicative of DSB resection ( Figure 5B ) , we conclude that As ( III ) -induced breaks detected by the comet assay mostly represent DSBs ( Figure 4A ) . In agreement with this assumption , we were able to visualize DSBs by PFGE in the absence of replication using high concentrations of As ( III ) ( Figure 4B and 4C ) . Ability of As ( III ) to generate DSBs explains increased sensitivity of HR DNA repair mutants to As ( III ) reported in genome-wide screens [18]–[22] and confirmed in this paper ( Figure 3 ) . It has been shown that replication-associated inducers of DSBs , H2O2 and MMS , trigger histone H2A and Rad53 phosphorylation exclusively in S phase [33] , [58] . Activation of the DNA damage checkpoint proteins during H2O2 or MMS treatment occurring outside replication is only observed in the absence BER enzymes , Apn1 and Apn2 endonucleases [33] , [58] ( Figure 5C ) . Formation of MMS-derived DSBs in G2/M has been recently demonstrated in yeast cells lacking AP endonucleases , probably as a result of accumulation of closely-spaced SSBs on complementary DNA strands [59] . Presence of MMS-induced DSBs in G1 has also been suggested [44] . Our data showing H2A and Rad53 phosphorylation in MMS treated G1-synchronized BER-deficient cells but not in the yku70Δ mutant provide indirect in vivo evidence about formation of DSBs with ragged ends which are derived from closely-spaced SSBs ( Figure 3C ) . Importantly , As ( III ) did not induce histone H2A and Rad53 phosphorylation in the apn1Δ apn2Δ mutant in G1 ( Figure 5C ) suggesting that majority of As ( III ) -dependent DNA lesions are not processed by BER and thus do not result from typical oxidative DNA damage . In support of this notion , we showed that As ( III ) induced only a slight increase of ROS ( Figure 2A ) and DNA oxidation ( Figure 2B ) and the apn1Δ apn2Δ mutant , which is highly sensitive to ROS-inducing agents [33] , [60] and MMS [59] , [61] , [62] , is not hypersensitive to As ( III ) ( Figure 3A ) . Moreover , As ( III ) only weakly triggers ubiquitylation of PCNA in S phase ( Figure 3C ) which is a hallmark of replication perturbations caused by UV , MMS and H2O2-induced DNA damage [36] , [37] . In sum , at least in budding yeast our results rule out the possibility that arsenic acts as a powerful DNA oxidizer and suggest that As ( III ) may directly produce DSBs independently from replication . However , the question remains how As ( III ) is able to induce DSBs . Since As ( III ) generates low level of oxidative damage ( Figure 2A and 2B ) , it is highly improbable that DSBs are formed due to the presence of closely-opposed randomly generated SSBs . Moreover , As ( III ) -induced DNA damage is not associated with transcription suggesting a direct mode of As ( III ) genotoxicity ( Figure 6 ) . It has been determined by Fourier transform infrared spectroscopy that in vitro As ( III ) is able to bind indirectly to nitrogen bases of DNA [63] , [64] but no specific As ( III ) -DNA or histone-As ( III ) complexes were detected in vivo using radioactive As ( III ) [65] . Transition metal ions like copper and iron are able to bind to DNA and histones and in situ oxidize DNA via Haber-Weiss reactions [66] . However , such action has never been demonstrated for As ( III ) and we failed to show that As ( III ) has capacity to cleave plasmid DNA in the presence of H2O2 ( data not shown ) . Taking into account the presence of As ( III ) -induced DSBs outside S phase ( Figure 4 ) and independent from transcription ( Figure 6 ) , protection of As ( III ) -induced DSBs by Yku70–Yku80 complex ( Figure 5 ) , which preferentially binds to unragged DNA ends [45] , lack of enhanced overall production of ROS in the presence of As ( III ) and high instability of ROS which are unable to diffuse for long distances , we hypothesize that in a similar way as PM As ( III ) may act in the vicinity of DNA causing in situ production of free radicals which sequentially create break in one strand and a directly opposed single-strand break on the complementary strand . Our finding that As ( III ) greatly increases the ability of PM to induce DSBs both in S . cerevisiae ( Figure 8 ) and S . pombe ( Figure 9C ) , could have important potential applications . If this also proves to be the case for bleomycin and human cancer cell lines , a combinatory therapy with As ( III ) could be envisioned in order to decrease bleomycin therapeutic dose and thus its side effects as well as to treat cancers which are weakly responsive to this drug [57] , [67] .
The S . cerevisiae and S . pombe strains used in this study are listed in Table S1 . Gene deletions were generated by the PCR-based gene replacement method [68] . The S . cerevisiae strains were grown in standard rich YPD medium or minimal ( SD ) medium supplemented with the required amino acids at 30°C . The S . pombe strains were cultivated in standard rich YES medium or Edinburgh minimal medium ( EMM ) at 30°C . For DNA damage sensitivity tests , cells were grown to logarithmic phase and 10-fold serial dilutions were spotted onto YPD plates containing various concentrations of DNA damaging agents . Alternatively , cells were irradiated at 5 Gy/min with a 60Co source before plating . To measure survival of yeast strains after acute treatment with As ( III ) , cells were grown to logarithmic phase and exposed to indicated concentrations of sodium arsenite for 6 h in minimal medium or left untreated . After treatment cells were washed with water , serially diluted and plated on YPD or YES plates . After 3 days of incubation at 30°C colony forming units were counted to determine the number of survived cells . To determine cell cycle phase-dependent response to As ( III ) treatment , yeast cells were synchronized in G1 phase by 5 µM α-factor or in G2/M phase by 15 µM nocodazole for 2 h followed by exposure to DNA damaging agents in the presence of α-factor or nocodazole to prevent cell cycle progression . Experiments were performed only when at least 90% of cells showed proper cell cycle synchronization confirmed by microscopy observations of unbudded cells showing shmoo projections ( G1-synchronized cells ) or large-budded cells with a single nuclei ( G2/M-synchronized cells ) visualized by DAPI ( 4′ , 6-diamidino-2-phenylindole ) staining . Flow cytometry analysis of DNA content was performed as previously described [69] . Briefly , for each time-point 0 . 5 ml of yeast cells were fixed with 70% ethanol , washed twice with water and incubated for 2 h with 0 . 25 µg/ml RNase at 50°C followed by 1 h incubation with 1 µg/ml pepsine at 37°C . Next , cells were sonicated , stained with 2 . 5 µM SYTOX Green for 1 h and analyzed by flow cytometry . The fraction of cells remaining arrested in G1 was determined by the α-factor-nocodazole trap assay [69] . At indicated time-points 0 . 5 ml of cell culture was washed twice with water and combined with 0 . 5 ml of YPD medium containing 10 µg/ml α-factor and 30 µg/ml nocodazole and incubated for 90 min at 30°C followed by fixation with 70% ethanol . Next , cells were examined by a light microscope to count cells with shmoo projections ( cells remaining arrested in G1 ) or large-budded cells ( post-G1 cells arrested in G2/M ) . To determine the fraction of post-mitotic cells aliquots were fixed , stained as for flow cytometry , and then observed with an Axio Imager M1 Carl Zeiss epifluorescence microscope ( GFP filter set , 40×/0 . 75 objective ) to score the percentage of binucleate large-budded cells . All cell cycle experiments were repeated a minimum of three times . Total protein extracts were prepared by the trichloroacetic acid method and resolved on SDS-PAGE , blotted onto nitrocellulose filters and probed with anti-Rad53 ( Santa Cruz , sc-6749 ) , anti-histone H2A ( phospho S129 ) ( Abcam , ab15083 ) , anti-histone H2A ( Abcam , ab13923 ) or anti-PCNA ( kindly provided by B . W . Stillman ) antibodies . Blotted membranes were stained for total protein with Ponceau S ( Sigma ) before immunodetection . To detect increased levels of ROS , wild type S . cerevisiae cells were pre-loaded with 5 µg/ml dihydrorhodamine 123 for 15 min and then exposed to various concentrations of sodium arsenite , hydrogen peroxide or menadione . At 15 , 30 , 60 and 120 min time-points aliquots of cells were taken and immediately analyzed by flow cytometry to measure levels of green fluorescence of rhodamine 123 formed after oxidation of dihydrorhodamine 123 by ROS [70] . Untreated samples were used as a control of autofluorescence level . Genomic DNA was isolated from yeast cells treated with various concentrations of sodium arsenite , hydrogen peroxide and menadione for 2 h . Next , to obtain nucleosides DNA samples were digested with P1 nuclease at 37°C for 2 h and subsequently incubated with alkaline phosphatase at 37°C for 1 h . About 10 µg/ml of DNA were used to determine oxidative DNA damage in the form of 8-hydroxy-2′-deoxyguanosine using an ELISA-based kit ( Cell Biolabs ) according to the manufacturer's instructions . The alkaline comet assay was performed according to the protocol adopted for yeast cells [41] . Approximately 106 cells from each treatment were harvested by centrifugation and mixed with 1 . 5% low melting agarose in S buffer ( 1 M sorbitol , 25 mM KH2PO4 , pH 6 . 5 ) containing 2 mg/ml zymolyase ( 20T; 20 000 U/g ) . 200 µl of this mixture were spread over a slide coated with a water solution of 0 . 5% normal-melting agarose , covered with a cover slip and incubated for 45 min at 30°C for enzymatic degradation of yeast cell walls . To solidify the gel , the slides were kept at 4°C for 10 min after which the cover slips were removed . Slides were incubated in a lysis buffer ( 30 mM NaOH , 1 M NaCl , 0 . 05% laurylsarcosine , 50 mM EDTA , 10 mM Tris-HCl , pH 10 ) for 2 h at 4°C in order to lyse yeast spheroplasts . To remove the lysis solution , the slides were washed three times for 20 min at 4°C in an electrophoresis buffer ( 30 mM NaOH , 10 mM EDTA , 10 mM Tris-HCl , pH 10 ) . The slides were then submitted to electrophoresis in the same buffer for 20 min at 25 V at room temperature . After electrophoresis , the slides were incubated in a neutralization buffer ( 10 mM Tris-HCl , pH 7 . 4 ) for 10 min , followed by consecutive 5 min incubation in 76% and 96% ethanol . The slides were then air-dried and visualized immediately or stored at 4°C for later observation . For visualization in a fluorescence microscope , the slides were stained with 2 µM YOYO-1 and 30 representative images of each slide were acquired at a magnification of ×400 using an Olympus BX61 fluorescence microscope . The images were analyzed with the help of Comet Assay IV image-analysis system software from Perspective Instruments to measure tail length ( µm ) and tail DNA ( % ) . Tail moment ( arbitrary unit ) was calculated by multiplying the percentage of DNA in the tail by the distance between the center of mass of the comet head and the center of mass of the comet tail . Preparation of agarose-embedded genomic DNA was performed with CHEF Genomic DNA Plug Kit ( BioRad ) following manufacturer's protocol . Briefly , 6×107 cells was embedded in 100 µl of 0 . 75% low-melting agarose and incubated with lyticase for 2 h at 37°C . This was followed by digestion with proteinase K for overnight at 50°C . Plugs were washed 4 times for 1 h in a Wash buffer and stored in the same buffer at 4°C . The electrophoresis was performed using CHEF-DR III Pulsed Field Electrophoresis Systems ( BioRad ) . The S . cerevisiae chromosome samples were resolved in 1% agarose at 6 V/cm for 22 h with a 60–120 s switch time ramp at 14°C . To separate the S . pombe chromosomes samples were resolved in 0 . 8% agarose at 1 . 5 V/cm for 72 h with a 1800 s switch time ramp at 14°C . Gels were stained with ethidium bromide ( 1 mg/ml ) for 1 h and destained with 0 . 5× TBE buffer for 1 h and photographed . DNA separated with PFGE was transferred to a Hybond-N+ nylon membrane ( GE Healthcare ) by a capillary transfer and UV crosslinked . Next , membrane was hybridized with the 288 nt fragment of the LEU2 gene ( present both in the circular chromosome III as well as in the chromosome II ) labeled with DIG High Prime DNA Labeling and Detection Starter Kit II ( Roche ) following manufacturer's protocol . To analyze formation of Rad52-YFP and Rfa1-YFP nuclear foci , live cells were observed with an Axio Imager M1 epifluorescence microscope ( Carl Zeiss , Germany ) equipped with a 100× oil immersion objective ( Plan-Neofluar 100×/1 . 30 ) , a GFP filter set and differential interference contrast ( DIC ) . Images were collected using AxioCam MRc digital color camera and processed with AxioVision 4 . 5 software .
|
Arsenic is a highly toxic compound which causes several types of cancer in humans . However , precise mechanisms of arsenic carcinogenesis remain elusive and are still a matter of debate . For example , the oxidative stress theory of arsenic proposes that arsenic generates reactive oxygen species producing oxidative DNA damage that can be converted to DNA double-strand breaks ( DSBs ) during replication . Using budding yeast as a model organism , we show that arsenic is able to induce DSBs in the absence of transcription , replication and pronounced oxidative stress . Importantly , we also demonstrate that arsenic greatly enhances cytotoxic activity of antitumor drug phleomycin , as evidenced by increased sensitivity and DNA fragmentation visible upon co-treatment . Our work suggests that arsenic acts as a direct inducer of DNA breaks and could be potentially used with other anticancer drugs , like phleomycin-related bleomycin , as a new combinatory therapy to treat cancers that poorly respond to these drugs . Additionally , since in many countries millions of people are exposed to high doses of arsenic in drinking water , we believe that our findings about genotoxicity of arsenic are important not only to geneticists but also to the general public .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"mutagenesis",
"cellular",
"stress",
"responses",
"cancer",
"genetics",
"genetic",
"mutation",
"model",
"organisms",
"mutation",
"types",
"genetics",
"yeast",
"and",
"fungal",
"models",
"biology",
"saccharomyces",
"cerevisiae",
"molecular",
"cell",
"biology"
] |
2013
|
Oxidative Stress and Replication-Independent DNA Breakage Induced by Arsenic in Saccharomyces cerevisiae
|
Dengue is one of the most widespread mosquito-borne diseases in the world . The causative agent , dengue virus ( DENV ) , is primarily transmitted by the mosquito Aedes aegypti , a species that has proved difficult to control using conventional methods . The discovery that A . aegypti transinfected with the wMel strain of Wolbachia showed limited DENV replication led to trial field releases of these mosquitoes in Cairns , Australia as a biocontrol strategy for the virus . Field collected wMel mosquitoes that were challenged with three DENV serotypes displayed limited rates of body infection , viral replication and dissemination to the head compared to uninfected controls . Rates of dengue infection , replication and dissemination in field wMel mosquitoes were similar to those observed in the original transinfected wMel line that had been maintained in the laboratory . We found that wMel was distributed in similar body tissues in field mosquitoes as in laboratory ones , but , at seven days following blood-feeding , wMel densities increased to a greater extent in field mosquitoes . Our results indicate that virus-blocking is likely to persist in Wolbachia-infected mosquitoes after their release and establishment in wild populations , suggesting that Wolbachia biocontrol may be a successful strategy for reducing dengue transmission in the field .
Dengue is one of the most common and widespread vector-borne diseases in the world , with up to 380 million infections estimated to occur annually [1] . The causative agent , dengue virus ( DENV ) , has expanded its geographic range in the last two decades , with more than 100 countries now affected . Infection with DENV leads primarily to self-limiting fevers but recent decades have seen a marked increase in severe dengue , with manifestations such as hypovolemic shock and hemorrhage [2] . DENV is transmitted primarily by the mosquito vector Aedes aegypti and , to a lesser extent , by its congener A . albopictus . In the absence of an effective vaccine [3] and/or antivirals , prevention of dengue transmission relies primarily on control of mosquito vectors . The failure to prevent the global spread of dengue , increasing insecticide resistance in mosquito populations and subsequent escalating costs of insecticide-based programs , as well as environmental concern over the impact of these chemicals , have spurred the development of novel , inexpensive and green vector control methods [4] , [5] . The transinfection of vector mosquitoes with the bacterium Wolbachia pipientis has emerged as a promising method for the control of dengue . Wolbachia is the most common endosymbiont of insects , thought to infect up to 40% of arthropod species [6] . A . aegypti stably transinfected with different strains of Wolbachia show reduced replication and transmission of DENV [7]–[9] . An additional advantage of using Wolbachia for biocontrol of DENV is the ability of the bacterium to propagate through a population by inducing cytoplasmic incompatibility ( CI ) in its host [10] . CI confers a fitness advantage to Wolbachia-infected females that allows these maternally transmitted bacteria to spread unaided through a population [10] . The use of Wolbachia provides a means of biocontrol that is both pesticide-free and poses minimal environmental safety concerns [11] . In laboratory trials , mosquitoes with the wMel strain of Wolbachia showed both blocking of DENV transmission and minimal fitness effects due to infection with the bacterium [9] . In addition , wMel rapidly invaded wildtype mosquito populations in semi-field cage experiments due to CI and minimal fitness costs [9] . The results facilitated the field release of wMel-infected mosquitoes in two suburbs of Cairns , Queensland , Australia [12] . Within a short period , the frequency of wMel reached fixation in the two suburbs [12] and has remained established at both sites . The persistence of the viral-blocking phenotype in field populations is fundamental to the utility of releases of Wolbachia-infected mosquitoes . The mechanisms that underpin viral interference are poorly understood but may be related to the density of Wolbachia [13] , [14] , immune pre-activation [7] , [8] , [15] , intra-host competition for cellular resources [16] , [17] or suppression of host cellular factors that are upregulated during viral infection [18] . The density of Wolbachia may decrease after several generations , as happened following the transinfection of the virulent strain of wMelPop into the novel host Drosophila simulans [19] . Wolbachia infection frequencies and associated CI effects may also be significantly lower in nature than observed in the lab , as observed in Drosophila simulans [20] . However , the wMel strain is avirulent and has limited negative effects on mosquito fitness in the laboratory [9] , suggesting that the density of the wMel strain may remain stable over time . Protection against RNA virus-induced mortality was in fact first observed in the long term , evolutionarily stable association between wMel and its Drosophila melanogaster host [21] . Here , we investigated the extent of virus blocking in field wMel-infected A . aegypti , one year following field release , using three serotypes of DENV . We found limited replication and dissemination of DENV in field wMel mosquitoes , indicating stability of the viral-blocking phenotype in wild Wolbachia-infected mosquitoes . The extent of virus blocking was similar in field mosquitoes compared to the original , wMel-infected , outcrossed lab line used for release . Interestingly , the density of Wolbachia increased following blood feeding and to a greater extent in field versus lab wMel-infected mosquitoes . We suggest that if the viral blocking effect of field wMel is dependent on Wolbachia density , repeated blood feeding on human hosts might amplify this effect . Our results reinforce the utility of Wolbachia-based technology for biocontrol of dengue .
Blood feeding of mosquito colonies using human volunteers was performed in accordance to Monash University Human Research Ethics Committee permit CF11/0766-2011000387 . Written informed consent was obtained from all volunteers who participated in the study . Dengue viremic plasma was obtained from patients enrolled in a prospective study at the Hospital for Tropical Diseases , Ho Chi Minh City , Vietnam . All patients provided written consent to participate in the study . The study protocols relevant to this work , including vector competence experiments , were reviewed and approved by the Scientific and Ethical Committee of the Hospital for Tropical Diseases ( CS/ND/09/24 ) and the Oxford Tropical Research Ethical Committee ( OxTREC 20-09 ) . The inclusion criteria were: a ) adult patients ( ≥15 years of age ) , with ≤72 hours of fever and suspected of having dengue based on clinical symptoms , b ) a positive NS1 Rapid test and c ) written informed consent . All plasma samples were anonymized ( samples were identified using numbers only ) prior to experiments . Mosquito eggs were collected in January 2012 from ovitraps placed inside the Wolbachia release zone in the Cairns suburbs of Yorkey's Knob and Gordonvale and outside , in Edge Hill , Whitfield , Edmonton and Bentley Park . Eggs collected from outside the Wolbachia release zone were Wolbachia-uninfected . Eggs on ovistrips were allowed to hatch and larvae reared in water supplemented with fish food pellets ( Tetramin , Tetra ) . Fourth instar larvae were identified as A . aegypti based on specific morphological characters . Adults ( F0 ) emerged in cages of approximately 450 individuals and were allowed to feed on 10% sucrose ad libitum . Five to seven day old females were allowed to feed on human volunteers and eggs were collected from several gonotrophic cycles . F1 adults hatched from eggs obtained in the first gonotrophic cycle were used in vector competence experiments . The wMel-infected field mosquito line and its uninfected counterpart ( derived from Wolbachia-uninfected eggs ) were denoted wMel . F and wildtype , respectively . The original laboratory-reared , outcrossed wMel-infected MGYP2 . out line [9] was used in some experiments . All mosquito colonies were kept at 26°C under a 12L∶12D light cycle and 60% relative humidity . Mosquitoes were challenged in vector competence experiments with virus strains belonging to DENV serotypes 1–3 , using virus grown in cell culture and viremic plasma from human patients . DENV-2 strain 92T and DENV-3 strain Cairns 2008 ( both isolated from outbreaks in north Queensland , Australia in 1992 and 2008 , respectively ) were grown in C6/36 cells and harvested and titered as described previously [13] . Virus was aliquoted in single-use 1 mL lots and stored at −80°C . Two separate vector competence experiments were carried out to determine if DENV could replicate and disseminate in field wMel-infected mosquitoes . For both experiments , female mosquitoes ( 5–7 days old ) were allowed to feed on viremic blood meals contained in a membrane feeder with sheep intestine as the membrane . Virus was mixed with defibrinated sheep blood to obtain final bloodmeal titers ( see below ) . Mosquitoes were allowed to feed for 1 hour , with engorged females separated from unfed ones the next day . Females were kept in plastic cups at a density of 10–12 individuals/cup and allowed access to 10% sucrose ad libitum . Females were killed under CO2 at either 7 or 14 days post infection ( p . i . ) , immediately frozen in dry ice and stored at −80°C until further processing . In the first experiment , field wMel and uninfected mosquitoes were challenged with two viremic plasma samples from Vietnam , DENV-1 – P249 ( final titer 7 . 38E+08 genomic copies/mL ) and DENV-2 – P410 ( final titer 1 . 12E+09 genomic copies/mL ) , as well as a cell-culture grown virus isolated in Australia , DENV-2 – 92T ( 9 . 30E+09 copies/mL ) as a control . In the second experiment , the field wMel-infected and two control lines , MGYP2 . out [9] and field Wolbachia-uninfected wildtype , were challenged with a viremic human plasma sample from Vietnam , DENV-1-P307 ( 2 . 46E+11 copies/mL ) , and two virus strains isolated in Australia , DENV-2-92T ( 9 . 30E+09 copies/mL ) and DENV-3-Cairns 2008 ( 3 . 58E+09 copies/mL ) . Human viremic plasmas underwent a single freeze-thaw cycle before use in vector competence experiments . RNA was extracted from mosquito bodies using Trizol reagent ( Invitrogen ) , and from heads using the QIAamp viral RNA mini kit ( Qiagen ) , following homogenization of tissues with 3 mm glass beads in a Beadbeater . A higher yield of total RNA was obtained on average from head samples using the QIAamp viral RNA mini kit versus Trizol ( F . Frentiu , unpublished data ) . For mosquitoes challenged with Vietnamese viremic plasmas , virus genome copies were estimated by qRT-PCR using FAM-labeled DENV-1 and DENV-2 hydrolysis probe sequences and standard curves from reference [22] . Virus copies in mosquitoes challenged with DENV-2-92T and DENV-3-Cairns 2008 were estimated by qRT-PCR , using hydrolysis probes specific to the 3′UTR region . Primer sequences were F: 5′-AAGGACTAGAGGTTAGAGGAGACCC-3′ and R: 5′-CGTTCTGTGCCTGGAATGATG-3′ , with probe sequence: 5′- FAM- AACAGCATATTGACGCTGGGAGAGACCAGA-BHQ1-3′ . Reactions were performed with the SuperScript® III Platinum® One-Step qRT-PCR kit ( Invitrogen ) and contained 5 µL of RNA template , 5 µM each of probe and forward and reverse primers , buffer and enzyme as per kit instructions , in a total volume of 20 µL . For head qPCRs , 10 µL of RNA template was used , with water adjusted accordingly . The number of DENV copies was calculated following a standard curve for DENV 3′UTR , constructed as in [8] . All reactions were performed using a LightCycler480 Instrument ( Roche ) with the following run conditions: 50°C for 15 min , 95°C for 2 min , followed by 45 amplification cycles of 95°C for 15 s , 60°C for 30 s and a final cooling step of 40°C for 10 s . Reactions were run in duplicate and samples where DENV failed to amplify in at least one replicate were classified as zero . Only samples where DENV amplified in both technical replicates and the amount of copies extrapolated by the LightCycler software was above the lower bound of the standard curve ( limit of detection ) were included in the analysis . All mosquitoes from field and lab wMel-infected lines that showed DENV breakthrough were tested for the presence of Wolbachia using IS5 repeat primers specific to the wMel and wMelPop strains [23] . Only one sample each from the field and lab wMel-infected mosquitoes was negative for Wolbachia . These samples were excluded from further analysis . The densities of Wolbachia were compared between field and lab strains of wMel-infected mosquitoes in a separate experiment . Five to seven-day old females from each line were fed on a mix of DENV-3 – Cairns 2008 and sheep blood and collected at 7 and 14 days post infection ( as detailed above ) for genomic DNA extraction . Control non-blood fed females from each line were maintained in parallel and collected at the same time points . Genomic DNA was extracted using the DNAEasy Blood and Tissue kit ( Qiagen ) as per the manufacturer's instructions . A multiplex qPCR amplifying the target Wolbachia-specific wsp and mosquito housekeeping RpS17 [24] genes was performed ( wsp F: 5′-CATTGGTGTTGGTGTTGGTG-3′ , R: 5′-ACACCAGCTTTTACTTGACCAG-3′ , probe: 5′-HEX-TCCTTTGGAACCCGCTGTGAATGA-BHQ1-3′; RpS17 F: 5′-TCCGTGGTATCTCCATCAAGC-3′ , R: 5′-CACTTCCGGCACGTAGTTGTC-3′ , probe: 5′-FAM-CAGGAGGAGGAACGTGAGCGCAG-BHQ1-3′ ) . The RpS17 housekeeping gene was used to normalize wsp gene copies . qPCR reactions were performed in 10 µL total volume containing 1× Lightcycler 480 Probes Master reaction mix , 5 µM each of wsp primers and probe , 2 . 5 µM each of RpS17 primers and probe and 1 µL of DNA template . Cycling was performed using a LightCycler480 Instrument ( Roche ) , with 1 cycle at 95°C for 5 min , followed by 45 amplification cycles of 95°C for 10 s , 60°C for 15 s , 72°C for 1 s , and a final cooling cycle of 40°C for 10 s . Target to housekeeping gene ratios were calculated using the Relative Quantification algorithm in the Lightcycler 480 software ( Roche ) . Tissue localization of wMel in field wMel . F and lab MGYP2 . out mosquitoes was visualized using FISH . Females were collected under CO2 and immediately placed overnight in 4% paraformaldehyde at 4°C with their wings and legs removed . Paraffin-embedded mosquitoes were sectioned in 8 µM thin slices . Slides were de-paraffinated in 100% xylene , rehydrated in an ethanol series and hybridized overnight at 37°C in a buffer containing Wolbachia-specific W2 and W3 probes [8] . Post-hybridization processing followed [8] . Slides were mounted using an antifade reagent ( Prolong Gold , Invitrogen ) and viewed with a Zeiss Axio Imager II epifluorescence microscope equipped with an Axiocam camera , using the same exposure conditions for each filter channel . Differences between mosquito lines in DENV infection rates for both vector competence experiments were analyzed using pairwise Fisher's exact tests . P-values were adjusted for multiple comparisons for each day of sampling within each experiment using the Holm method [25] , with values <0 . 05 considered significant . In experiment 1 , differences in median DENV copy numbers between lines were analyzed using Mann-Whitney U tests . In experiment 2 , differences among the three lines in copies of each virus were analyzed using Kruskal-Wallis tests , with Dunn's post-hoc multiple comparison tests . Last , we tested for significant differences in Wolbachia density between MGYP2 . out and wMel . F mosquitoes using Mann-Whitney U tests . All analyses were performed in R [26] and GraphPad Prism v . 6 ( GraphPad Software , San Diego , California USA ) .
We conducted two independent experiments to assess rates of DENV infection and replication in wildtype and wMel-infected field release mosquitoes . In experiment 1 , at day 7 p . i . , lower rates of body and head infection were detected in field wMel mosquitoes compared to wildtype for the two DENV-1 and DENV-2 viremic plasma samples and cell culture DENV-2-92T virus strains ( Table 1 ) . However , only for DENV-2 strain P410 , a viremic plasma sample , was there a statistically significant difference between the two mosquito lines ( Table 1 ) . At day 14 p . i . , rates of body and head infection were significantly lower in field wMel compared to wildtype mosquitoes for all three DENV strains , with a stronger effect in dissemination to heads ( Table 1 ) . The highest observed dissemination rate in wMel . F heads was a low 6% , compared to 62% in wildtype heads . DENV genome copy titers in heads and bodies were uniformly higher for all strains in wildtype mosquitoes compared to respective wMel . F samples at day 14 p . i . ( Figure 1 ) . For example , titers in both bodies and heads typically reached 1×108 copies for all virus strains in wildtype individuals . By contrast , most wMel . F individuals showed an absence of DENV replication ( Figure 1 ) . A similar difference in virus titers was present at day 7 p . i . , but to a lesser extent because of low infection rates ( Figure S1 ) . We next investigated whether vector competence was similar in field wMel-infected A . aegypti compared to the original wMel-infected line that had been maintained in the lab with recurrent outbreeding [9] . In experiment 2 , we estimated DENV infection rates and replication titers for three virus strains in wildtype , wMel . F and MGYP2 . out mosquitoes . We tested for statistically significant differences in infection rates only between wildtypes and wMel . F , and between wMel . F and MGYP2 . out mosquitoes ( Table 2 ) . At day 7 p . i . , significantly lower body infection rates were found in wMel . F mosquitoes versus wildtypes for DENV-2-92T and DENV-3-Cairns08 strains ( Table 2 ) . However , rates of infection across all mosquito lines and all viruses were low in general , resulting in limited power for robust statistical tests . At day 14 p . i . , significantly different infection rates between wildtypes and wMel . F mosquitoes were found for both bodies and heads across all DENV strains ( Table 2 ) . For both experiments 1 and 2 , dissemination of all virus strains by day 14 p . i . was dramatically lower in field wMel mosquitoes compared to wildtypes . There were no significant differences in infection rates between wMel . F and MGYP2 . out mosquitoes across either day post-infection . DENV titers were significantly lower across all virus strains in both heads and bodies in field wMel mosquitoes compared to wildtypes , at day 14 post-infection ( Figure 2 ) . A similar pattern was observed at day 7 post-infection , although only for bodies and the strains DENV-2-92T and DENV-2-Cairns08/09 ( Figure S2 ) . At day 14 , virus titers in wildtype mosquitoes ranged from below the limit of detection to 108 copies/µg of RNA whereas virus was observed only in a few instances in field wMel . Only in one field wMel individual was the maximum number of DENV copies observed ( Figure 2 , strain 92T body and heads panels ) . Overall , the results indicate that when breakthrough virus occurs in wMel mosquitoes , viral titers are most likely to be lower than those observed in wildtypes . We next investigated whether Wolbachia tissue tropism and density had changed significantly in field wMel mosquitoes since release in 2011 . Using FISH , we found that Wolbachia was distributed in the same tissues in field mosquitoes and in the original wMel-transinfected laboratory line , MGYP2 . out ( Figure 3 ) . In both wMel-infected lines , Wolbachia was present in two tissues that are critical in viral infection and dissemination , namely midguts and salivary glands ( Figure 3 A–B & G–H ) . Wolbachia was also present in brains , although not at high densities which was consistent with levels expected for the wMel strain [9] . Field wMel ovaries appeared highly infected with Wolbachia ( Figure 3 D ) , indicating the potential for stable transmission of the bacteria to offspring in the wild . We also examined whether Wolbachia densities change following blood-feeding in field wMel mosquitoes compared to the original MGYP2 . out line . By initially looking at whole mosquitoes we found that , by day 7 , the density of wMel had increased following blood-feeding in both lines ( Figure 4 A ) . A much higher increase in Wolbachia density was observed in field wMel mosquitoes versus MGYP2 . out ( Figure 4 A ) . Median ratios of wsp to RpS17 gene copy numbers increased significantly from 0 . 714 and 0 . 702 in non-blood fed wMel . F and MGYP2 . out , respectively , to 1 . 465 and 1 . 241 in blood-fed wMel . F and MGYP2 . out , respectively ( Figure 4 A ) . The difference in Wolbachia density between blood-fed and non-blood fed mosquitoes persisted at 14 days post feeding ( Figure 4 B ) , in the absence of repeat feeds . Median ratios of wsp to RpS17 gene copy numbers were 0 . 649 and 0 . 733 in non-blood fed wMel . F and MGYP2 . out , respectively , compared to 1 . 542 and 1 . 675 in blood-fed wMel . F and MGYP2 . out , respectively ( Figure 4 B ) . Interestingly , by day 14 , Wolbachia density continued to increase in blood-fed MGYP2 . out and field wMel mosquitoes compared to non-blood fed ones , as indicated by the slightly higher median values of normalized wsp/RpS17 ratios ( Figure 4 B ) . Following blood-feeding , increases in Wolbachia density in both field and laboratory lines were primarily localized in the bodies rather than heads ( Figure 5 ) , probably due to the bacteria replicating in ovaries .
Infection of the vector A . aegypti with Wolbachia has been proposed as a dengue biocontrol method that is environmentally friendly and able to spread unassisted in wild mosquito populations . Release of wMel-infected mosquitoes in north Queensland has indicated that this Wolbachia strain can rapidly reach fixation in wild populations [12] . Key to the utility of this biocontrol method is the maintenance of DENV-blocking following mosquito release and in subsequent generations as Wolbachia invades wild populations . Our results indicate that , one year post-release , field wMel mosquitoes show significantly reduced DENV infection and replication compared to wildtype mosquitoes . Strikingly , we found very low infection rates in mosquito heads , indicating that DENV is largely unable to disseminate to the heads in wMel mosquitoes , under the experimental conditions used here . By day 14 , in both experiments , wMel mosquitoes displayed dramatically reduced infection rates and viral titers in heads compared to wildtype . Reduced DENV dissemination and transmission rates due to the presence of native Wolbachia endosymbionts have also been found in the vector A . albopictus [27] . The pattern was observed with a range of virus titers and serotypes ( DENV-1 to -3 ) , and using both cell-cultured and viremic human plasma . We did not test for systematic differences in response to these variables here , but work with other viruses has indicated the extent of Wolbachia-mediated viral blocking is dependent on virus titer [28] . Our data suggest stability of viral blocking and Wolbachia tissue tropism since divergence of field mosquitoes from the parental wMel-transinfected laboratory line MGYP2 . out . We did not find statistically significant differences in either dengue infection rates or virus titers between field wMel and MGYP2 . out mosquitoes . However , field wMel mosquitoes may be somewhat better at blocking dissemination of DENV-1 but not DENV-2 and DENV-3 compared to MGYP2 . out ( Figure 2 ) . This is because the number of MGYP2 . out individuals infected with virus is much higher for DENV-1 than DENV-2 and DENV-3 compared to field mosquitoes . Virus was detected in a higher number of MGYP2 . out individuals for DENV-1 strain P307 , compared to the other virus strains tested . Additional experiments are needed to determine whether this effect is due to the particular strain or a phenomenon general to the DENV-1 serotype . DENV-2-92T dissemination rates in MGYP2 . out were 12 . 5% several generations after transinfection in earlier work [9] and have stayed a low 7% in our study , at least 10 generations later and with frequent outcrossing of this line ( every three generations ) . This time frame is comparable with that experienced by field mosquitoes , with the maximum number of generations per year in Cairns being 15 and populations persisting throughout the year [29] . MGYP2 . out and field wMel-infected mosquitoes have therefore retained the virus blocking phenotype described in [9] that led to the field release of Wolbachia-infected mosquitoes . Our results suggest that the virus blocking phenotype induced by wMel may be retained not just over the short term , but also over the medium to longer term . Wolbachia tissue tropism was similar in field and laboratory wMel-infected mosquitoes , with high densities of the bacterium found in the midgut and ovaries . Wolbachia was also present in the salivary glands and brains of both mosquito lines , which may contribute to the limited dissemination and replication of DENV observed in heads from the wMel-infected lines . In Drosophila simulans , high Wolbachia densities in head and midgut have been correlated with interference against Drosophila C virus [30] . Wolbachia density is critical in modulating transmission fidelity of the bacterium across generations and pathogenicity [19] . Wolbachia density changes dynamically in response to environmental variables [31] . We also found that Wolbachia density increased following blood-feeding , consistent with other studies that have shown an increase in endosymbiont density in response to high nutrient conditions [32] . Wolbachia provides a fitness benefit by modulating iron levels in D . melanogaster [33] and responds transcriptionally to iron overload [34] . Increased Wolbachia replication is most likely localized to the ovaries , although further work is needed to confirm this . Our results differ , however , from those of [35] , who showed a blood-feeding induced reduction in the native endosymbiont wFlu in the ovaries of the mosquito Aedes fluviatilis . Surprisingly , the increase in Wolbachia density was more pronounced in field wMel mosquitoes compared to the laboratory line , although only at day 7 post-infection . The reasons for this difference are unknown but may be related to poor nutrition in the field or other environmental effects . Although mosquitoes were reared in the same environment for one generation , maternal nutritional effects can be detected up to several generations later in insects [36] , [37] . Maternal effects due to poor nutrition in the field may influence offspring immune status and the ability to control infection levels , potentially resulting in higher Wolbachia densities . Dynamic changes in Wolbachia density following blood-feeding may have implications for vector competence of wMel-infected mosquitoes . The precise mechanism by which Wolbachia mediates viral blocking is not known but is positively related to density of the bacterium [13] , [14] , [38] . If blood-feeding acts to increase Wolbachia density and A . aegypti feed frequently on human hosts , viral blocking may be greater in field populations than anticipated from laboratory experiments , although further studies are needed to test this hypothesis . In laboratory experiments involving Drosophila , the density of Wolbachia has been shown to evolve to a level that is non-pathogenic to the fly but the bacteria are still maintained [19] , [39] . Understanding selection pressures on wMel-infected mosquitoes in nature will be necessary to predict how Wolbachia may evolve over the long term in field-released mosquitoes . A . aegypti infected with Wolbachia show reduced replication of other RNA viruses , such as yellow fever [28] , chikungunya [8] , [28] and West Nile [40] viruses . Wolbachia-based biocontrol may therefore have the potential to eliminate transmission of old and emerging arboviruses in addition to DENV . The maintenance of virus blocking in field release mosquitoes is critical to the success of Wolbachia-based biocontrol . Our results show that dengue virus blocking and Wolbachia density phenotypes have stayed stable in A . aegypti infected with wMel , at least 12 months following field release .
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Almost half of the world's population is at risk of contracting dengue virus , particularly in the tropics and sub-tropics . The virus is transmitted by the mosquito Aedes aegypti , a cosmopolitan species that has proved difficult to control using traditional methods . A new biocontrol strategy has been developed involving the release of mosquitoes infected with Wolbachia bacteria . Mosquitoes with the wMel strain of Wolbachia show dramatically reduced replication and transmission of dengue virus in laboratory trials . Although promising , the utility of Wolbachia biocontrol depends on field wMel-infected mosquitoes retaining the phenotype of reduced viral replication . Mosquitoes with wMel were released in the field in Cairns , Australia in early 2011 . We provide evidence that , one year later , field collected wMel mosquitoes showed reduced dengue virus replication in the body and limited dissemination to the head compared to controls . Wolbachia numbers in mosquitoes increased following blood meals , which may further decrease viral replication if the insects feed frequently . Our results indicate that Wolbachia-mediated dengue interference is sustained in field populations and shows no sign of attenuation after one year of deployment .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"dengue",
"fever",
"neglected",
"tropical",
"diseases",
"arboviral",
"infections",
"infectious",
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"vectors",
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2014
|
Limited Dengue Virus Replication in Field-Collected Aedes aegypti Mosquitoes Infected with Wolbachia
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The MRX complex together with Sae2 initiates resection of DNA double-strand breaks ( DSBs ) to generate single-stranded DNA ( ssDNA ) that triggers homologous recombination . The absence of Sae2 not only impairs DSB resection , but also causes prolonged MRX binding at the DSBs that leads to persistent Tel1- and Rad53-dependent DNA damage checkpoint activation and cell cycle arrest . Whether this enhanced checkpoint signaling contributes to the DNA damage sensitivity and/or the resection defect of sae2Δ cells is not known . By performing a genetic screen , we identify rad53 and tel1 mutant alleles that suppress both the DNA damage hypersensitivity and the resection defect of sae2Δ cells through an Sgs1-Dna2-dependent mechanism . These suppression events do not involve escaping the checkpoint-mediated cell cycle arrest . Rather , defective Rad53 or Tel1 signaling bypasses Sae2 function at DSBs by decreasing the amount of Rad9 bound at DSBs . As a consequence , reduced Rad9 association to DNA ends relieves inhibition of Sgs1-Dna2 activity , which can then compensate for the lack of Sae2 in DSB resection and DNA damage resistance . We propose that persistent Tel1 and Rad53 checkpoint signaling in cells lacking Sae2 increases the association of Rad9 at DSBs , which in turn inhibits DSB resection by limiting the activity of the Sgs1-Dna2 resection machinery .
Programmed DNA double-strand breaks ( DSBs ) are formed during meiotic recombination and rearrangement of the immunoglobulin genes in lymphocytes . Furthermore , potentially harmful DSBs can arise by exposure to environmental factors , such as ionizing radiations and radiomimetic chemicals , or by failures in DNA replication . DSB generation elicits a checkpoint response that depends on the mammalian protein kinases ATM and ATR , whose functional orthologs in Saccharomyces cerevisiae are Tel1 and Mec1 , respectively [1] . Tel1/ATM is recruited to DSBs by the MRX ( Mre11-Rad50-Xrs2 ) /MRN ( Mre11-Rad50-Nbs1 ) complex , whereas Mec1/ATR recognizes single-stranded DNA ( ssDNA ) covered by Replication Protein A ( RPA ) [2] . Once activated , Tel1/ATM and Mec1/ATR propagate their checkpoint signals by phosphorylating the downstream checkpoint kinases Rad53 ( Chk2 in mammals ) and Chk1 , to couple cell cycle progression with DNA repair [2] . Repair of DSBs can occur by either non-homologous end joining ( NHEJ ) or homologous recombination ( HR ) . Whereas NHEJ directly joins the DNA ends , HR uses the sister chromatid or the homologous chromosome to repair DSBs . HR requires that the 5’ ends of a DSB are nucleolytically processed ( resected ) to generate 3’-ended ssDNA that can invade an undamaged homologous DNA template [3 , 4] . In Saccharomyces cerevisiae , recent characterization of core resection proteins has revealed that DSB resection is initiated by the MRX complex , which catalyzes an endonucleolytic cleavage near a DSB [4] , with the Sae2 protein ( CtIP in mammals ) promoting MRX endonucleolytic activity [5] . This MRX-Sae2-mediated DNA clipping generates 5’ DNA ends that are optimal substrates for the nucleases Exo1 and Dna2 , the latter working in concert with the helicase Sgs1 [6–9] . In addition , the MRX complex recruits Exo1 , Sgs1 and Dna2 to DSBs independently of the Mre11 nuclease activity [10] . DSB resection is also negatively regulated by Ku and Rad9 , which inhibit the access to DSBs of Exo1 and Sgs1-Dna2 , respectively [11–14] . The MRX-Sae2-mediated endonucleolytic cleavage is particularly important to initiate resection at DNA ends that are not easily accessible to Exo1 and Dna2-Sgs1 . For instance , both sae2Δ and mre11 nuclease defective mutants are completely unable to resect meiotic DSBs , where the Spo11 topoisomerase-like protein remains covalently attached to the 5’-terminated strands [15 , 16] . Furthermore , the same mutants exhibit a marked sensitivity to camptothecin ( CPT ) , which extends the half-life of DNA-topoisomerase I cleavable complexes [17 , 18] , and to methyl methanesulfonate ( MMS ) , which can generate chemically complex DNA termini . The lack of Rad9 or Ku suppresses both the hypersensitivity to DSB-inducing agents and the resection defect of sae2Δ cells [10–14] . These suppression events require Dna2-Sgs1 and Exo1 , respectively , indicating that Rad9 increases the requirement for MRX-Sae2 activity in DSB resection by inhibiting Sgs1-Dna2 [13 , 14] , while Ku mainly limits the action of Exo1 [10–12] . By contrast , elimination of either Rad9 or Ku does not bypass Sae2/MRX function in resecting meiotic DSBs [11 , 13] , likely because Sgs1-Dna2 and Exo1 cannot substitute for the Sae2/MRX-mediated endonucleolytic cleavage when this event is absolutely required to generate accessible 5’-terminated DNA strands . Sae2 plays an important role also in modulating the checkpoint response . Checkpoint activation in response to DSBs depends primarily on Mec1 , with Tel1 playing a minor role [19] . On the other hand , impaired Mre11 endonuclease activity caused by the lack of Sae2 leads to increased MRX persistence at the DSB ends . The enhanced MRX signaling in turn causes unscheduled Tel1-dependent checkpoint activation that is associated to prolonged Rad53 phosphorylation [20–22] . Mutant mre11 alleles that reduce MRX binding to DSBs restore DNA damage resistance in sae2Δ cells and reduce their persistent checkpoint activation without restoring efficient DSB resection [23 , 24] , suggesting that enhanced MRX association to DSBs contributes to the DNA damage hypersensitivity caused by the lack of Sae2 . Persistently bound MRX might increase the sensitivity to DNA damaging agents of sae2Δ cells by hyperactivating the DNA damage checkpoint . If this were the case , then the DNA damage hypersensitivity of sae2Δ cells should be restored by the lack of Tel1 or of its downstream effector Rad53 , as they are responsible for the sae2Δ enhanced checkpoint signaling [20 , 22] . However , while Rad53 inactivation has never been tested , TEL1 deletion not only fails to restore DNA damage resistance in sae2Δ cells , but it exacerbates their sensitivity to DNA damaging agents [23 , 24] . Therefore , other studies are required to understand whether the Tel1- and Rad53-mediated checkpoint signaling has any role in determining the DNA damage sensitivity of sae2Δ cells . By performing a genetic screen , we identified rad53 and tel1 mutant alleles that suppress both the hypersensitivity to DNA damaging agents and the resection defect of sae2Δ cells by reducing the amount of Rad9 at DSBs . Decreased Rad9 binding at DNA ends bypasses Sae2 function in DNA damage resistance and resection by relieving the inhibition of the Sgs1-Dna2 resection machinery . Altogether our data suggest that the primary cause of the resection defect of sae2Δ cells is Rad9 association to DSBs , which is promoted by persistent Tel1 and Rad53 signaling activities in these cells .
We have previously described our search for extragenic mutations that suppress the CPT hypersensitivity of sae2Δ cells [13] . This genetic screen identified 15 single-gene suppressor mutants belonging to 11 distinct allelism groups . Analysis of genomic DNA by next-generation Illumina sequencing of 5 non allelic suppressor mutants revealed that the DNA damage resistance was due to single base pair substitutions in the genes encoding Sgs1 , Top1 , or the multi-drug resistance proteins Pdr3 , Pdr10 and Sap185 [13] . Subsequent genome sequencing and genetic analysis of 2 more non allelic suppressor mutants allowed to link suppression to either the rad53-H88Y mutant allele , causing the replacement of Rad53 amino acid residue His88 by Tyr , or the tel1-N2021D allele , resulting in the replacement of Tel1 amino acid residue Asn2021 by Asp . Both rad53-H88Y and tel1-N2021D alleles restored resistance of sae2Δ cells not only to CPT , but also to phleomycin ( phleo ) and MMS ( Fig 1A ) . While both rad53-H88Y and tel1-N2021D fully rescued the hypersensitivity of sae2Δ cells to phleomycin and MMS , the CPT hypersensitivity of sae2Δ cells was only partially suppressed by the same alleles ( Fig 1A ) , suggesting that they did not bypass all Sae2 functions . Both rad53-H88Y and tel1-N2021D suppressor alleles were recessive , as the sensitivity to genotoxic agents of sae2Δ/sae2Δ RAD53/rad53-H88Y and sae2Δ/sae2Δ TEL1/tel1-N2021D diploid cells was similar to that of sae2Δ/sae2Δ RAD53/RAD53 TEL1/TEL1 diploid cells ( S1 Fig ) , suggesting that rad53-H88Y and tel1-N2021D alleles encode hypomorphic variants . Furthermore , both variants suppressed the hypersensitivity to DNA damaging agents of sae2Δ cells by altering the same mechanism , as sae2Δ rad53-H88Y tel1-N2021D triple mutant cells survived in the presence of DNA damaging agents to the same extent as sae2Δ rad53-H88Y and sae2Δ tel1-N2021D double mutant cells ( Fig 1B ) . The MRX complex not only provides the nuclease activity for initiation of DSB resection , but also it promotes the binding of Exo1 , Sgs1 and Dna2 at the DSB ends [10] . These MRX multiple roles explain the severe DNA damage hypersensitivity and resection defect of cells lacking any of the MRX subunits compared to cells lacking either Sae2 or the Mre11 nuclease activity . As Sae2 has been proposed to activate Mre11 nuclease activity [5] , we asked whether the suppression of sae2Δ DNA damage hypersensitivity by Rad53-H88Y and Tel1-N2021D requires Mre11 nuclease activity . Both rad53-H88Y and tel1-N2021D alleles suppressed the hypersensitivity to DNA damaging agents of sae2Δ cells carrying the nuclease defective mre11-H125N allele ( Fig 1C ) . By contrast , sae2Δ mre11Δ rad53-H88Y and sae2Δ mre11Δ tel1-N2021D triple mutant cells were as sensitive to genotoxic agents as sae2Δ mre11Δ double mutant cells ( Fig 1D ) , indicating that neither the rad53-H88Y nor the tel1-N2021D allele can suppress the hypersensitivity to DNA damaging agents of sae2Δ mre11Δ cells . Altogether , these findings indicate that both Rad53-H88Y and Tel1-N2021D require the physical presence of the MRX complex , but not its nuclease activity , to bypass Sae2 function in cell survival to genotoxic agents . A single unrepairable DSB induces a DNA damage checkpoint that depends primarily on Mec1 , with Tel1 playing a minor role [19] . This checkpoint response can be eventually turned off , allowing cells to resume cell cycle progression through a process that is called adaptation [25–27] . In the absence of Sae2 , cells display heightened checkpoint activation that prevents cells from adapting to an unrepaired DSB [20 , 22] . This persistent checkpoint activation is due to increased MRX amount/persistence at the DSB that in turn causes enhanced and prolonged Tel1 activation that is associated with persistent Rad53 phosphorylation [20–22 , 28] . If the rad53-H88Y mutation impaired Rad53 activity , then it is expected to suppress the adaptation defect of sae2Δ cells by lowering checkpoint activation . We addressed this point by using JKM139 derivative strains , where a single DSB at the MAT locus can be generated by expression of the HO endonuclease gene under the control of a galactose-dependent promoter . This DSB cannot be repaired by HR because of the deletion of the homologous donor loci HML and HMR [27] . We measured checkpoint activation by monitoring the ability of cells to arrest the cell cycle and to phosphorylate Rad53 after HO induction . Both rad53-H88Y and sae2Δ rad53-H88Y cells formed microcolonies of more than 2 cells with higher efficiency than either wild type or sae2Δ cells ( Fig 2A ) . Furthermore , the Rad53-H88Y variant was poorly phosphorylated after HO induction both in the presence and in the absence of Sae2 ( Fig 2B ) . Thus , the rad53-H88Y mutation suppresses the adaptation defect of sae2Δ cells by impairing Rad53 activation . DNA damage-dependent activation of Rad53 requires its phospho-dependent interaction with Rad9 , which acts as a scaffold to allow Rad53 intermolecular authophosphorylation and activation [29–31] . Interestingly , the His88 residue , which is replaced by Tyr in the Rad53-H88Y variant , is localized in the forkhead-associated domain 1 of the protein and has been implicated in mediating Rad9-Rad53 interaction [32] . Thus , we asked whether the Rad53-H88Y variant was defective in the interaction with Rad9 . When HA-tagged Rad9 was immunoprecipitated with anti-HA antibodies from wild type and rad53-H88Y cells grown for 4 hours in the presence of galactose to induce HO , wild type Rad53 could be detected in Rad9-HA immunoprecipitates , whereas Rad53-H88Y did not ( Fig 2C ) . This defective interaction of Rad53-H88Y with Rad9 could explain the impaired checkpoint activation in sae2Δ rad53-H88Y double mutant cells . Tel1 signaling activity is responsible for the prolonged Rad53 activation that prevents sae2Δ cells to adapt to the checkpoint triggered by an unrepairable DSB [20 , 22] . Although telomere length in tel1-N2021D mutant cells was unaffected both in the presence and in the absence of Sae2 ( S2 Fig ) , the recessivity of tel1-N2021D suppressor effect on sae2Δ DNA damage hypersensitivity suggests that the N2021D substitution impairs Tel1 function . If this were the case , Tel1-N2021D might suppress the adaptation defect of sae2Δ cells by reducing the DSB-induced persistent Rad53 phosphorylation . When G1-arrested cell cultures were spotted on galactose-containing plates to induce HO , wild type , sae2Δ , tel1-N2021D and sae2Δ tel1-N2021D cells accumulated large budded cells within 4 hours ( Fig 2A ) . This cell cycle arrest is due to checkpoint activation . In fact , when the same cells exponentially growing in raffinose were transferred to galactose , Rad53 phosphorylation was detectable about 2–3 hours after galactose addition ( Fig 2B ) . However , while sae2Δ cells remained arrested as large budded cells for at least 30 hours ( Fig 2A ) and showed persistent Rad53 phosphorylation ( Fig 2B ) , wild type , tel1-N2021D and sae2Δ tel1-N2021D cells formed microcolonies with more than 2 cells ( Fig 2A ) and decreased the amounts of phosphorylated Rad53 ( Fig 2B ) with similar kinetics 10–12 hours after HO induction . Therefore , the Tel1-N2021D variant impairs Tel1 signaling activity , as it rescues the sae2Δ adaptation defect by reducing the persistent Rad53 phosphorylation . The N2021D substitution resides in the Tel1 FAT domain , a helical solenoid that encircles the kinase domain of all the phosphoinositide 3-kinase ( PI3K ) -related kinases ( PIKKs ) [33 , 34] , suggesting that this amino acid change might reduce Tel1 kinase activity . Western blot analysis revealed that the amount of Tel1-N2021D was slightly lower than that of wild type Tel1 ( Fig 2D ) . We then immunoprecipitated equivalent amounts of Tel1-HA and Tel1-N2021D-HA variants from both untreated and CPT-treated cells ( Fig 2E , top ) , and we measured their kinase activity in vitro using the known artificial substrate of the PIKKs family PHAS-I ( Phosphorylated Heat and Acid Stable protein ) [35] . Both Tel1-HA and Tel1-N2021D-HA were capable to phosphorylate PHAS-I , with the amount of phosphorylated substrate being slighly higher in Tel1-N2021D-HA than in Tel1-HA immunoprecipitates ( Fig 2E , bottom ) . This PHAS-I phosphorylation was dependent on Tel1 kinase activity , as it was not detectable when the immunoprecipitates were prepared from strains expressing either kinase dead Tel1-kd-HA or untagged Tel1 ( Fig 2E , bottom ) . Thus , the tel1-N2021D mutation does not affect Tel1 kinase activity . Interestingly , the FAT domain is in close proximity to the FATC domain , which was shown to be important for Tel1 recruitment to DNA ends [36] , suggesting that the Tel1-N2021D variant might be defective in recruitment/association to DSBs . Strikingly , when we analyzed Tel1 and Tel1-N2021D binding at the HO-induced DSB by chromatin immunoprecipitation ( ChIP ) and quantitative real time PCR ( qPCR ) , the amount of Tel1-N2021D bound at the DSB turned out to be lower than that of wild type Tel1 ( Fig 2F ) . This decreased Tel1-N2021D association was not due to lower Tel1-N2021D levels , as the ChIP signals were normalized for each time point to the amount of immunoprecipitated protein . Thus , the inability of sae2Δ tel1-N2021D cells to sustain persistent Rad53 phosphorylation after DSB generation can be explained by a decreased association of Tel1-N2021D to DSBs . As both Rad53-H88Y and Tel1-N2021D reduce checkpoint signaling in sae2Δ cells , we asked whether the increased DNA damage resistance of sae2Δ rad53-H88Y and sae2Δ tel1-N2021D cells was due to the elimination of the checkpoint-mediated cell cycle arrest . This hypothesis could not be tested by deleting the MEC1 , DDC1 , RAD24 , MEC3 or RAD9 checkpoint genes , because they also regulate DSB resection [37–39] . On the other hand , an HO-induced DSB activates also the Chk1 checkpoint kinase [40] , which contributes to arrest the cell cycle in response to DSBs by controlling a pathway that is independent of Rad53 [41] . Importantly , chk1Δ cells do not display DNA damage hypersensitivity and are not defective in resection of uncapped telomeres [38 , 41] . We therefore asked whether CHK1 deletion restores DNA damage resistance in sae2Δ cells . Consistent with the finding that Chk1 contributes to arrest the cell cycle after DNA damage independently of Rad53 [41] , Rad53 was phosphorylated with wild type kinetics after HO induction in both chk1Δ and sae2Δ chk1Δ cells ( Fig 3A ) . Furthermore , CHK1 deletion suppresses the adaptation defect of sae2Δ cells . In fact , both chk1Δ and sae2Δ chk1Δ cells spotted on galactose-containing plates formed microcolonies of more than 2 cells with higher efficiency than wild type and sae2Δ cells ( Fig 3B ) , although they did it less efficiently than mec1Δ cells , where both Rad53 and Chk1 signaling were abrogated [41] . Strikingly , the lack of Chk1 did not suppress the hypersensitivity to DNA damaging agents of sae2Δ cells ( Fig 3C ) , although it overrides the checkpoint-mediated cell cycle arrest . To rule out the possibility that CHK1 deletion failed to restore DNA damage resistance in sae2Δ cells because it impairs DSB resection , we used JKM139 derivative strains to monitor directly generation of ssDNA at the DSB ends in the absence of Chk1 . As ssDNA is resistant to cleavage by restriction enzymes , we followed loss of SspI restriction sites as a measure of resection by Southern blot analysis under alkaline conditions , using a single-stranded probe that anneals to the 3’ end at one side of the break . Consistent with previous indications that Chk1 is not involved in DNA-end resection [38] , chk1Δ single mutant cells resected the DSB with wild type kinetics ( Fig 3D ) . Furthermore , CHK1 deletion did not exacerbate the resection defect of sae2Δ cells ( Fig 3E ) . Altogether , these data indicate that the prolonged checkpoint-mediated cell cycle arrest of sae2Δ cells is not responsible for their hypersensitivity to DNA damaging agents . As the checkpoint-mediated cell cycle arrest was not responsible for the DNA damage hypersensitivity of sae2Δ cells , we asked whether Rad53-H88Y and/or Tel1-N2021D suppressed the sae2Δ resection defect . We first measured the efficiency of single-strand annealing ( SSA ) , a mechanism that repairs a DSB flanked by direct DNA repeats when sufficient resection exposes the complementary DNA sequences , which can then anneal to each other [3] . The rad53-H88Y and tel1-N2021D alleles were introduced in the YMV45 strain , which carries two tandem leu2 gene repeats located 4 . 6 kb apart on chromosome III , with a HO recognition site adjacent to one of the repeats [42] . This strain also harbors a GAL-HO construct for galactose-inducible HO expression . Both Rad53-H88Y and Tel1-N2021D bypass Sae2 function in SSA-mediated DSB repair . In fact , accumulation of the SSA repair product after HO induction occurred more efficiently in both sae2Δ rad53-H88Y ( Fig 4A and 4B ) and sae2Δ tel1-N2021D ( Fig 4C and 4D ) than in sae2Δ cells , where it was delayed compared to wild type . To confirm that Rad53-H88Y and Tel1-N2021D suppress the SSA defect of sae2Δ cells by restoring DSB resection , we used JKM139 derivative strains to monitor directly generation of ssDNA at the DSB ends . Indeed , sae2Δ rad53-H88Y ( Fig 5A ) and sae2Δ tel1-N2021D ( Fig 5B ) cells resected the HO-induced DSB more efficiently than sae2Δ cells , indicating that both Rad53-H88Y and Tel1-N2021D suppress the resection defect of sae2Δ cells . The DSB resection defect of sae2Δ cells is thought to be responsible for the increased persistence of MRX at the DSB [43] . Because Rad53-H88Y and Tel1-N2021D restore DSB resection in sae2Δ cells , we expected that the same variants also reduce the amount of MRX bound at the DSB . The amount of Mre11 bound at the HO-induced DSB end turned out to be lower in both sae2Δ rad53-H88Y and sae2Δ tel1-N2021D than in sae2Δ cells ( Fig 5C ) . Therefore , the Rad53-H88Y and Tel1-N2021D variants restore DSB resection in sae2Δ cells and reduce MRX association/persistence at the DSB . Consistent with the finding that Rad53-H88Y and Tel1-N2021D do not fully restore CPT resistance in sae2Δ cells ( Fig 1A ) , and therefore do not bypass completely all Sae2 functions , the rad53-H88Y and tel1-N2021D mutations were unable to suppress the sporulation defects of sae2Δ/sae2Δ diploid cells ( Fig 5D ) , suggesting that they cannot bypass the requirement for Sae2/MRX endonucleolytic cleavage to remove Spo11 from meiotic DSBs . The MRX complex not only provides the nuclease activity for initiation of DSB resection , but also allows extensive resection by promoting the binding at the DSB ends of the resection proteins Exo1 and Sgs1-Dna2 [6 , 7 , 10] . Suppression of the DNA damage hypersensitivity of sae2Δ cells by Rad53-H88Y and Tel1-N2021D requires the physical presence of the MRX complex but not its nuclease activity ( Fig 1C and 1D ) . As the loading of Exo1 , Sgs1-Dna2 at DSBs depends on the MRX complex independently of its nuclease activity [10] , we asked whether the investigated suppression events require Exo1 , Sgs1 and/or Dna2 . This question was particularly interesting , as Rad53 was shown to inhibit resection at uncapped telomeres through phosphorylation and inhibition of Exo1 [38 , 44] . As shown in Fig 6A , sae2Δ suppression by Rad53-H88Y and Tel1-N2021D was Exo1-independent . In fact , although the lack of Exo1 exacerbated the sensitivity to DNA damaging agents of sae2Δ cells , both sae2Δ exo1Δ rad53-H88Y and sae2Δ exo1Δ tel1-N2021D triple mutants were more resistant to genotoxic agents than sae2Δ exo1Δ double mutant cells ( Fig 6A ) . By contrast , neither Rad53-H88Y nor Tel1-N2021D were able to suppress the sensitivity to DNA damaging agents of sae2Δ cells carrying the temperature sensitive dna2-1 allele ( Fig 6B ) , suggesting that Dna2 activity is required for their suppressor effect . Dna2 , in concert with the helicase Sgs1 , functions as a nuclease in DSB resection [7] . The dna2-E675A allele abolishes Dna2 nuclease activity , which is essential for cell viability and whose requirement is bypassed by the pif1-M2 mutation that impairs the nuclear activity of the Pif1 helicase [45] . The lack of Sgs1 or expression of the Dna2-E675A variant in the presence of the pif1-M2 allele impaired viability of sae2Δ cells even in the absence of genotoxic agents . The synthetic lethality of sae2Δ sgs1Δ cells , and possibly of sae2Δ dna2-E675A pif1-M2 , is likely due to defects in DSB resection , as it is known to be suppressed by either EXO1 overexpression or KU deletion [11] . Thus , we asked whether Rad53-H88Y and/or Tel1-N2021D could restore viability of sae2Δ sgs1Δ and/or sae2Δ dna2-E675A pif1-M2 cells . Tetrad dissection of diploid cells did not allow to find viable spores with the sae2Δ dna2-E675A pif1-M2 rad53-H88Y ( Fig 6C ) or sae2Δ dna2-E675A pif1-M2 tel1-N2021D genotypes ( Fig 6D ) , indicating that neither Rad53-H88Y nor Tel1-N2021D can restore the viability of sae2Δ dna2-E675A pif1-M2 cells . Similarly , no viable sae2Δ sgs1Δ spores could be recovered , while sae2Δ sgs1Δ rad53-H88Y and sae2Δ sgs1Δ tel1-N2021D triple mutant spores formed very small colonies that could not be further propagated ( Fig 6E and 6F ) . Finally , neither Rad53-H88Y nor Tel1-N2021D , which allowed DNA damage resistance in sae2Δ exo1Δ cells ( Fig 6A ) , were able to suppress the growth defect of sgs1Δ exo1Δ double mutant cells even in the absence of genotoxic agents ( Fig 6G ) . Altogether , these findings indicate that suppression by Rad53-H88Y and Tel1-N2021D of the DNA damage hypersensitivity caused by the absence of Sae2 is dependent on Sgs1-Dna2 . The Rad53-H88Y protein is defective in interaction with Rad9 ( Fig 2C ) and therefore fails to undergo autophosphorylation and activation , prompting us to test whether other mutations affecting Rad53 activity can bypass Sae2 functions . To this end , we could not use rad53Δ cells because they show growth defects even when the lethal effect of RAD53 deletion is suppressed by the lack of Sml1 [46] . We then substituted the chromosomal wild type RAD53 allele with the kinase-defective rad53-K227A allele ( rad53-kd ) , which does not impair cell viability in the absence of genotoxic agents but affects checkpoint activation [47] . The rad53-kd allele rescued the sensitivity of sae2Δ cells to CPT and MMS to an extent similar to Rad53-H88Y ( Fig 7A ) . Furthermore , accumulation of the SSA repair products occurred more efficiently in sae2Δ rad53-kd cells than in sae2Δ ( Fig 7B and 7C ) , indicating that the lack of Rad53 kinase activity bypasses Sae2 function in SSA-mediated DSB repair . Suppression of sae2Δ may be peculiar to Tel1-N2021D , which is poorly recruited to DSBs ( Fig 2F ) , or it might be performed also by TEL1 deletion ( tel1Δ ) or by expression of a Tel1 kinase defective variant ( Tel1-kd ) . Indeed , the Tel1-kd variant , carrying the G2611D , D2612A , N2616K , and D2631E amino acid substitutions that abolish Tel1 kinase activity in vitro ( Fig 2E ) [35] , rescued the hypersensitivity of sae2Δ cells to genotoxic agents to an extent similar to Tel1-N2021D ( Fig 8A ) . The lack of Tel1 kinase activity bypassed also Sae2 function in DSB resection , because sae2Δ tel1-kd cells repaired a DSB by SSA more efficiently than sae2Δ cells ( Fig 8B and 8C ) . By contrast , and consistent with previous studies [23 , 24] , TEL1 deletion was not capable to suppress the hypersensitivity to DNA damaging agents of sae2Δ cells ( Fig 8A ) . Rather , tel1Δ sae2Δ double mutant cells displayed higher sensitivity to CPT than sae2Δ cells ( Fig 8A ) . Altogether , these data indicate that the lack of Tel1 kinase activity can bypass Sae2 function both in DNA damage resistance and DSB resection , but these suppression events require the physical presence of the Tel1 protein . As impairment of Tel1 function rescued the sae2Δ defects , we asked whether Tel1 hyperactivation exacerbates the DNA damage hypersensitivity of sae2Δ cells . We previously isolated the TEL1-hy909 allele , which encodes a Tel1 mutant variant with enhanced kinase activity that causes an impressive telomere overelongation [48] . As shown in Fig 8D , sae2Δ TEL1-hy909 double mutant cells were more sensitive to DNA damaging agents than sae2Δ single mutant cells . This enhanced DNA damage sensitivity was likely due to Tel1 kinase activity , as sae2Δ cells expressing a kinase defective Tel1-hy909-kd variant were as sensitive to DNA damaging agents as sae2Δ cells ( Fig 8D ) . Thus , impairment of Tel1 activity bypasses Sae2 function at DSBs , whereas Tel1 hyperactivation increases the requirement for Sae2 in survival to genotoxic stress . The absence of Tel1 failed not only to restore DNA damage resistance in sae2Δ cells ( Fig 8A ) , but also to suppress their SSA defect ( Fig 9A and 9B ) . The difference in the effects of tel1Δ and tel1-kd was not due to checkpoint signaling , as Rad53 phosphorylation decreased with similar kinetics in both sae2Δ tel1-kd and sae2Δ tel1Δ double mutant cells 10–12 hours after HO induction ( Fig 9C ) . Interestingly , SSA-mediated DSB repair occurred with wild type kinetics in tel1-kd mutant cells ( Fig 8B and 8C ) , while tel1Δ cells repaired a DSB by SSA less efficiently than wild type cells ( Fig 9A and 9B ) , suggesting that Tel1 might have a function at DSBs that does not require its kinase activity . Indeed , TEL1 deletion was shown to slight impair DSB resection [19] . Furthermore , it did not exacerbate the resection defect [19] and the hypersensitivity to DNA damaging agents of mre11Δ cells ( Fig 9D ) , suggesting that the absence of Tel1 can impair MRX function . Tel1 was also shown to promote MRX association at DNA ends flanked by telomeric DNA repeats independently of its kinase activity [49] , and we are showing that suppression of sae2Δ by Tel1-N2021D requires the physical presence of the MRX complex ( Fig 1D ) . Thus , it is possible that the lack of Tel1 fails to bypass Sae2 function at DSBs because it reduces MRX association at DSBs to a level that is not sufficient to restore DNA damage resistance and DSB resection in sae2Δ cells . Indeed , the amount of Mre11 bound at the HO-induced DSB was decreased in tel1Δ , but not in tel1-kd cells , compared to wild type ( Fig 9E ) . In agreement with a partial loss of Tel1 function , the Tel1-N2021D variant , whose association to DSBs is diminished compared to wild type Tel1 but not abolished ( Fig 2F ) , only slightly decreased Mre11 association to the DSB ( Fig 9E ) . As the rescue of sae2Δ by Tel1-N2021D requires the physical presence of the MRX complex , this Tel1 function in promoting MRX association to DSBs can explain the inability of tel1Δ to bypass Sae2 function in DNA damage resistance and resection . The suppression of the DNA damage hypersensitivity of sae2Δ cells by Rad53-H88Y and Tel1-N2021D requires Dna2-Sgs1 ( Fig 6B–6G ) . Because Sgs1-Dna2 activity is counteracted by Rad9 , whose lack restores DSB resection in sae2Δ cells [13 , 14] , we asked whether suppression of the DSB resection defect of sae2Δ cells by Rad53 or Tel1 dysfunction might be due to decreased Rad9 association to the DSB ends . We have previously shown that wild type and sae2Δ cells have similar amounts of Rad9 bound at 1 . 8 kb from the DSB ( Fig 10A ) [43] . However , a robust increase in the amount of Rad9 bound at 0 . 2 kb and 0 . 6 kb from the DSB was detected in sae2Δ cells compared to wild type ( Fig 10A ) [14] . Strikingly , this enhanced Rad9 accumulation in sae2Δ cells was reduced in the presence of the Rad53-kd or Tel1-kd variant , which both decreased the amount of Rad9 bound at the DSB also in otherwise wild type cells ( Fig 10A ) . Thus , Rad9 association close to the DSB depends on Rad53 and Tel1 kinase activity . Rad9 inhibits DSB resection by counteracting Sgs1 recruitment to DSBs [13] and , as expected , Sgs1 binding to DSBs was lower in sae2Δ cells than in wild type ( Fig 10B ) . By contrast , the presence of Rad53-kd or Tel1-kd variants increased the amount of Sgs1 at the DSB in both wild type and sae2Δ cells ( Fig 10B ) . Together with the observation that the suppression of sae2Δ hypersensitivity to genotoxic agents by Rad53 and Tel1 dysfunctions requires Sgs1-Dna2 , these findings indicate that the lack of Rad53 or Tel1 kinase activity restores DSB resection in sae2Δ cells by decreasing Rad9 association close to the DSB and therefore by relieving Sgs1-Dna2 inhibition . Although both rad53-kd and tel1-kd cells showed some lowering of Rad9 binding at DSBs compared to wild type cells ( Fig 10A ) , they did not appear to accelerate SSA , suggesting that this extent of Rad9 binding is anyhow sufficient to limit resection in a wild type context . Rad9 is known to be enriched at the sites of damage by interaction with histone H2A that has been phosphorylated on serine 129 ( γH2A ) by Mec1 and Tel1 [50–53] . As the lack of γH2A suppresses the SSA defect of sae2Δ cells [14] , Tel1 activity might increase the amount of Rad9 bound at the DSB in sae2Δ cells by promoting generation of γH2A . Indeed , the hta1-S129A allele , which encodes a H2A variant where Ser129 is replaced by a non-phosphorylatable alanine residue , thus causing the lack of γH2A , suppressed the resection defect of sae2Δ cells ( S3 Fig ) . Furthermore , γH2A formation turned out to be responsible for the enhanced Rad9 binding close to the break site , as sae2Δ hta1-S129A cells showed wild type levels of Rad9 bound at the DSB ( Fig 10C ) . Finally , γH2A formation close to the DSB depends on Tel1 kinase activity , as γH2A at the DSB was not detectable in sae2Δ tel1-kd cells ( Fig 10D ) . Altogether , these data indicate that Tel1 promotes Rad9 association to DSB in sae2Δ cells through γH2A generation .
Cells lacking Sae2 not only are defective in DSB resection , but also show persistent DSB-induced checkpoint activation that causes a prolonged cell cycle arrest . This enhanced checkpoint signaling is due to persistent MRX binding at the DSBs , which activates a Tel1-dependent checkpoint that is accompanied by Rad53 phosphorylation [20 , 22] . While failure to remove MRX from the DSBs has been shown to sensitize sae2Δ cells to genotoxic agents [23 , 24] , the possible contribution of the DNA damage checkpoint in determining the DNA damage hypersensitivity and the resection defect of sae2Δ cells has never been studied in detail . We show that impairment of Rad53 activity either by affecting its interaction with Rad9 ( Rad53-H88Y ) or by abolishing its kinase activity ( Rad53-kd ) suppresses the sensitivity to DNA damaging agents of sae2Δ cells . A similar effect can be detected also when Tel1 function is compromised either by reducing its recruitment to DSBs ( Tel1-N2021D ) or by abrogating its kinase activity ( Tel1-kd ) . These suppression effects are not due to the escape of the checkpoint-mediated cell cycle arrest , as CHK1 deletion , which overrides the persistent cell cycle arrest of sae2Δ cells , does not suppress the hypersensitivity of the same cells to DNA damaging agents . Rather , we found that impairment of Rad53 or Tel1 signaling suppresses the resection defect of sae2Δ by decreasing the amount of Rad9 bound very close to the break site . As it is known that Rad9 inhibits Sgs1-Dna2 [13 , 14] , this reduced Rad9 association at DSBs relieves inhibition of Sgs1-Dna2 activity that can then compensate for the lack of Sae2 function in DSB resection . In this view , active Rad53 and Tel1 increase the requirement for Sae2 in DSB resection by promoting Rad9 binding to DSBs and therefore by inhibiting Sgs1-Dna2 . Consistent with a role of Sgs1 in removing MRX from the DSBs [54] , the relieve of Sgs1-Dna2 inhibition by Rad53 or Tel1 dysfunction leads to a reduction of MRX association to DSBs in sae2Δ cells . Our finding that Tel1 or Rad53 inactivation can restore both DNA damage resistance and DSB resection in sae2Δ cells is apparently at odds with previous findings that attenuation of the Rad53-dependent checkpoint signaling by decreasing MRX association to DSBs suppresses the DNA damage hypersensitivity of sae2Δ cells but not their resection defect [23 , 24] . Noteworthy , the bypass of Sae2 function by Rad53 or Tel1 dysfunction requires the physical presence of MRX bound at DSBs , which is known to promote stable association of Exo1 , Sgs1 and Dna2 to DSBs [10] . Thus , we speculate that a reduced MRX association at DSBs allows sae2Δ cells to initiate DSB resection by relieving Rad9-mediated inhibition of Sgs1-Dna2 activity . As DSB repair by HR has been shown to require limited amount of ssDNA at DSB ends [55 , 56] , the ssDNA generated by this initial DSB processing might be sufficient to restore DNA damage resistance in sae2Δ cells even when wild type levels of resection are not restored because DSB-bound MRX is not enough to ensure stable Sgs1 and Dna2 association . Surprisingly , TEL1 deletion , which relieves the persistent Tel1-dependent checkpoint activation caused by the lack of Sae2 , did not restore DNA damage resistance and DSB resection in sae2Δ cells . We found that the lack of Tel1 protein affects the association of MRX to the DSB ends independently of its kinase activity . As the rescue of sae2Δ by Tel1-N2021D requires the physical presence of the MRX complex , this reduced MRX-DNA association can explain the inability of TEL1 deletion to restore DNA damage resistance and resection in sae2Δ cells . Therefore , while an enhanced Tel1 signaling activity in the absence of Sae2 leads to DNA damage hypersensitivity and resection defects , a sufficient amount of Tel1 needs to be present at DSBs to support MRX function at DSBs . How do Rad53 and Tel1 control Rad9 association to DSB ? Rad53-mediated phosphorylation of Rad9 does not appear to promote Rad9 binding to the DSB [57 , 58] . Because Rad53 and RPA compete for binding to Sgs1 [59] , it is tempting to propose that impaired Rad53 signaling activity might shift Sgs1 binding preference from Rad53 to RPA , leading to increased Sgs1 association to RPA-coated DNA that can counteract Rad9 binding and inhibition of resection . In turn , Tel1 and Mec1 can phosphorylate Rad9 [60 , 61] , and abrogation of these phosphorylation events rescues the sensitivity to DNA damaging agents of sae2Δ cells [14] , suggesting that Tel1 might control Rad9 association to DSBs directly through phosphorylation . On the other hand , Tel1 promotes generation of γH2A [50–53] , which counteracts DSB resection by favoring Rad9 association at the DSB [43] . We show that expression of a non-phosphorylatable H2A variant in sae2Δ cells suppresses their resection defect and prevents the accumulation of Rad9 at the DSB . Furthermore , γH2A generation close to the break site depends on Tel1 kinase activity . Thus , although we cannot exclude a direct control of Tel1 on Rad9 association to DNA ends , our findings indicate that Tel1 acts in this process mostly through γH2A generation . Altogether , our results support a model whereby Tel1 and Rad53 , once activated , limit DSB resection by promoting Rad9 binding to DSBs and therefore by inhibiting Sgs1-Dna2 . Sae2 activates Mre11 endonucleolytic activity that clips the 5’-terminated DNA strand , thus generating 5’ and 3’ tailed substrates that can be processed by Exo1/Sgs1-Dna2 and Mre11 activity , respectively ( Fig 10E , left ) . When Sae2 function fails , defective Mre11 nuclease activity causes increased MRX persistence at the DSB that leads to enhanced and prolonged Tel1-dependent Rad53 activation . As a consequence , Tel1- and Rad53-mediated phosphorylation events increase the amount of Rad9 bound at the DSB , which inhibits DSB resection by counteracting Sgs1-Dna2 activity ( Fig 10E , middle ) . Dysfunction of Rad53 or Tel1 reduces Rad9 recruitment at the DSB ends and therefore relieves inhibition of Sgs1-Dna2 , which can compensate for the lack of Sae2 in DNA damage resistance and resection ( Fig 10E , right ) . Altogether , these findings indicate that the primary cause of the resection defect of sae2Δ cells is an enhanced Rad9 binding to DSBs that is promoted by the persistent MRX-dependent Tel1 and Rad53 signaling activities . ATM inhibition has been proposed as a strategy for cancer treatment [62] . Therefore , the observation that dampening Tel1/ATM signaling activity restores DNA damage resistance in sae2Δ cells might have implications in cancer therapies that use ATM inhibitors for synthetic lethal approaches to threat tumors with deficiencies in the DNA damage response .
The yeast strains used in this study are derivatives of W303 , JKM139 and YMV45 strains and are listed in S1 Table . Cells were grown in YEP medium ( 1% yeast extract , 2% peptone ) supplemented with 2% glucose ( YEPD ) , 2% raffinose ( YEPR ) or 2% raffinose and 3% galactose ( YEPRG ) . To search for suppressor mutations of the CPT-sensitivity of sae2Δ mutant , 5x106 sae2Δ cells were plated on YEPD in the presence of 30μM CPT . Survivors were crossed to wild type cells to identify by tetrad analysis the suppression events that were due to single-gene mutations . Genomic DNA from two single-gene suppressors was analyzed by next-generation Illumina sequencing ( IGA technology services ) to identify mutations altering open reading frames within the reference S . cerevisiae genome . To confirm that rad53-H88Y and tel1-N2021D mutations were responsible for the suppression , either URA3 or HIS3 gene was integrated downstream of the rad53-H88Y and tel1-N2021D stop codon , respectively , and the resulting strain was crossed to wild type cells to verify by tetrad dissection that the suppression of the sae2Δ CPT sensitivity co-segregated with the URA3 or HIS3 allele . DSB end resection at the MAT locus in JKM139 derivative strains was analyzed on alkaline agarose gels as previously described [63] . DSB formation and repair in YMV45 strain were detected by Southern blot analysis using an Asp718-SalI fragment containing part of the LEU2 gene as a probe as previously described [63] . Quantitative analysis of the repair product was performed by calculating the ratio of band intensities for SSA product with respect to a loading control . Protein extracts for western blot analysis were prepared by TCA precipitation . ChIP assays were performed as previously described [64] . Data are expressed as fold enrichment at the HO-induced DSB over that at the non-cleaved ARO1 locus , after normalization of each ChIP signals to the corresponding amount of immunoprecipitated protein and input for each time point . Fold enrichment was then normalized to the efficiency of DSB induction . The kinase assay and coimmunoprecipitation were performed as previously described [48] . Rad53 was detected by using anti-Rad53 polyclonal antibodies ( ab104232 ) from Abcam . γH2A was immunoprecipitated by using anti-γH2A antibodies ( ab15083 ) from Abcam .
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Genome instability is one of the most pervasive characteristics of cancer cells and can be due to DNA repair defects and failure to arrest the cell cycle . Among the many types of DNA damage , the DNA double strand break ( DSB ) is one of the most severe , because it can cause mutations and chromosomal rearrangements . Generation of DSBs triggers a highly conserved mechanism , known as DNA damage checkpoint , which arrests the cell cycle until DSBs are repaired . DSBs can be repaired by homologous recombination , which requires the DSB ends to be nucleolytically processed ( resected ) to generate single-stranded DNA . In Saccharomyces cerevisiae , DSB resection is initiated by the MRX complex together with Sae2 , whereas more extensive resection is catalyzed by both Exo1 and Dna2-Sgs1 . The absence of Sae2 not only impairs DSB resection , but also leads to the hyperactivation of the checkpoint proteins Tel1/ATM and Rad53 , leading to persistent cell cycle arrest . In this manuscript we show that persistent Tel1 and Rad53 signaling activities in sae2Δ cells cause DNA damage hypersensitivity and defective DSB resection by increasing the amount of Rad9 bound at the DSBs , which in turn inhibits the Sgs1-Dna2 resection machinery . As ATM inhibition has been proposed as a strategy for cancer treatment , the finding that defective Tel1 signaling activity restores DNA damage resistance in sae2Δ cells might have implications in cancer therapies that use ATM inhibitors for synthetic lethal approaches that are devised to kill tumor cells with defective DSB repair .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Sae2 Function at DNA Double-Strand Breaks Is Bypassed by Dampening Tel1 or Rad53 Activity
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Persistent human papillomavirus ( HPV ) infection is the leading cause of cervical cancer . Although the fundamental link between HPV infection and oncogenesis is established , the specific mechanisms of virus-mediated transformation are not fully understood . We previously demonstrated that the HPV encoded E6 protein increases the activity of the proto-oncogenic transcription factor STAT3 in primary human keratinocytes; however , the molecular basis for STAT3 activation in cervical cancer remains unclear . Here , we show that STAT3 phosphorylation in HPV positive cervical cancer cells is mediated primarily via autocrine activation by the pro-inflammatory cytokine Interleukin 6 ( IL-6 ) . Antibody-mediated blockade of IL-6 signalling in HPV positive cells inhibits STAT3 phosphorylation , whereas both recombinant IL-6 and conditioned media from HPV positive cells leads to increased STAT3 phosphorylation within HPV negative cervical cancer cells . Interestingly , we demonstrate that activation of the transcription factor NFκB , involving the small GTPase Rac1 , is required for IL-6 production and subsequent STAT3 activation . Our data provides new insights into the molecular re-wiring of cancer cells by HPV E6 . We reveal that activation of an IL-6 signalling axis drives the autocrine and paracrine phosphorylation of STAT3 within HPV positive cervical cancers cells and that activation of this pathway is essential for cervical cancer cell proliferation and survival . Greater understanding of this pathway provides a potential opportunity for the use of existing clinically approved drugs for the treatment of HPV-mediated cervical cancer .
Human papillomaviruses ( HPV ) are a leading cause of squamous cell carcinomas of the ano-genital and oropharyngeal epithelium [1] . High-risk HPVs ( HR-HPV ) , exemplified by HPV16 and 18 , are responsible for >99% of cervical , and between 30–70% of oropharyngeal cancers [2] . HR-HPVs encode three oncogenic proteins: E5 , E6 and E7 , which interact with a multitude of host factors to manipulate signalling pathways necessary for cellular transformation . Whilst the role of the membrane protein E5 in cellular transformation is relatively poorly understood , it has been shown to activate EGFR signalling [3] , which is necessary for transformation in vivo [4] . EGFR activation is linked to the virus-coded ion channel ( viroporin ) activity of E5 [5–7] . In contrast , the E6 and E7 oncoproteins have been conclusively shown to play a pivotal role in HPV-mediated transformation [8] . The E7 protein promotes progression of cells through the S phase of the cell cycle via an ability to bind and inactivate pocket protein family members including pRb [9] , resulting in release of the E2F transcription factor [10] . Additionally , E7 stimulates the DNA damage response , driving viral replication and genomic instability [11 , 12] . HPV E6 forms complexes with host E3 ubiquitin ligases and mediates proteasomal degradation of a number of host targets including the p53 tumour suppressor protein , as well as increasing telomerase activity in order to prevent apoptosis and immortalise infected cells [13] . HR-E6 proteins also bind and regulate a selection of PSD95/DLG/ZO-1 ( PDZ ) domain containing proteins [14 , 15] . In addition to these classical interactions , emerging evidence shows targeting of additional signalling pathways , including the Wnt and Hippo pathways , contributes to transformation by the HPV oncoproteins [16–18] . The transcription factor signal transducer and activator of transcription ( STAT ) 3 is an essential regulator of cellular proliferation , differentiation and survival [19] . It is a bona fide oncogene and its aberrant activation has been observed in a growing number of malignancies [20] . As such , STAT3 has become an attractive therapeutic target in a diverse range of cancers , including bladder , ovarian and head and neck squamous cell carcinoma ( HNSCC ) [21] . Oncogenic viruses can activate STAT3 to drive cellular proliferation , necessary for viral replication and tumourigenesis [22] . Using a primary keratinocyte cell culture model , we previously demonstrated that E6 activates STAT3 signalling during the productive HPV18 lifecycle [23] . STAT3 activation was essential for the hyperplasia observed in HPV-containing keratinocyte raft culture models . Increased STAT3 protein expression and phosphorylation also correlated with cervical disease progression in a panel of cytology samples [23] . Although we identified that Janus kinase 2 ( JAK2 ) and MAP kinases were necessary for STAT3 phosphorylation in HPV-containing primary keratinocytes , our understanding of the mechanisms by which E6 mediates this process remains incomplete . Furthermore , inhibition of STAT3 activity in cervical cancer cells results in a profound reduction in cellular proliferation and the induction of apoptosis [24 , 25] , yet the mechanisms underpinning STAT3 activation and function in this scenario remain unknown . A number of extracellular stimuli including cytokines and growth factors induce STAT3 phosphorylation and signalling [21] . This requires the phosphorylation of tyrosine 705 ( Y705 ) and serine 727 ( S727 ) , resulting in STAT3 dimerisation and nuclear translocation , where it is able to regulate gene expression [20] . In particular , members of the IL-6 family of cytokines are key mediators of STAT3 activation through their interactions with the gp130 co-receptor [26] . Here , we show that HPV positive cervical cancer cells have higher levels of phosphorylated STAT3 protein when compared with those that are HPV negative . This results from increased IL-6 production and release , leading to autocrine and paracrine activation of STAT3 via a signalling pathway requiring the IL-6 co-receptor gp130 . Mechanistically , we show that IL-6 production is controlled by E6-mediated stimulation of NFκB signalling , which appears to be dependent on an upstream signalling pathway requiring the Rac1 GTPase and the AKT protein kinase . Finally , we demonstrate a correlation between NFκB activation , IL-6 expression and cervical disease progression , suggesting that targeting the IL-6 pathway to prevent STAT3 activation may have therapeutic benefits in cervical cancer .
We analysed the level of STAT3 phosphorylation in a panel of six cervical cancer cell lines to establish whether HPV augmentation of STAT3 phosphorylation was evident . The panel included two HPV negative ( HPV-; C33A and DoTc2 ) , two HPV16 positive ( HPV16+; SiHa and CaSKi ) and two HPV18 positive ( HPV18+; SW756 and HeLa ) lines . Both HPV16+ and HPV18+ cancer cells retained markedly higher levels of STAT3 phosphorylation at both Y705 and S727 residues compared to the HPV negative cell lines ( Fig 1A and 1B ) . The overall abundance of STAT3 protein was also increased in the HPV positive compared with HPV negative cervical cancer cells ( Fig 1A and 1B ) and this correlated with an increase in the levels of STAT3 mRNA expression in HPV positive compared to the HPV negative cell lines ( Fig 1C ) . Together , these data demonstrate increased levels of STAT3 expression and phosphorylation in HPV positive cervical cancer cell lines . As STAT3 can be regulated by extracellular stimuli , we investigated whether HPV promotes the secretion of factors capable of inducing STAT3 phosphorylation . C33A cells ( HPV- ) incubated with conditioned media ( CM ) from HeLa ( HPV18+ ) or CaSKi ( HPV16+ ) cells showed an increase in STAT3 phosphorylation on both Y705 and S727 residues over time compared to treatment with CM from C33A cells ( Fig 2A and 2B ) . STAT3 phosphorylation reached a peak between 30 minutes and 1 hour ( Fig 2A and 2B ) . This was accompanied by a significant increase in STAT3 nuclear accumulation within C33A cells treated with HeLa or CaSKi-CM ( Fig 2C; quantified in 2D ) . These data indicate that a factor ( s ) secreted into the media from HPV+ cells induces STAT3 phosphorylation in target cells . To identify the secreted factor responsible for inducing STAT3 phosphorylation , we focused on members of the IL-6 family of pro-inflammatory cytokines , as these have a well-studied role in the activation of STAT3 [27] . Firstly , the mRNA expression levels of key members of the family were measured by RT-qPCR . In both HeLa and CaSKi cells , IL6 , IL10 , LIF ( Leukaemia inhibitory factor ) and OSM ( Oncostatin M ) mRNA levels were significantly higher than in C33A cells ( Fig 3A ) , with IL6 showing the greatest increase . Building on this , we analysed IL6 mRNA expression in all six cervical cancer cell lines . HPV16+ and HPV18+ cells displayed a significantly higher level of IL6 mRNA expression compared with HPV negative cells ( Fig 3B ) , which correlated with intracellular IL-6 protein expression analysed by western blot ( Fig 3C ) . Finally , an IL-6 specific ELISA confirmed that HPV positive but not HPV negative cells secreted IL-6 ( Fig 3D ) . These data indicate that HPV positive cell lines express and secrete significantly higher levels of IL-6 compared with HPV negative cell lines . IL-6 signalling is initiated by an interaction between IL-6 and the IL-6 receptor ( IL-6R ) –gp130 co-receptor complex [21] . IL-6 and gp130 blocking antibodies were utilised to interrogate their requirement for STAT3 phosphorylation in cervical cancer cells . Firstly , we confirmed that IL-6 mediated STAT3 phosphorylation in C33A cells treated with HPV positive CM by pre-incubating with the gp130 blocking antibody before treatment . Separately , the IL-6 neutralising antibody was added to CM before addition to C33A cells . Both treatments reduced HPV positive CM induced STAT3 phosphorylation ( Fig 4A ) and nuclear translocation ( Fig 4B ) . Thus , IL-6 secreted from HPV positive cervical cancer cells can induce the activation of STAT3 in HPV negative cervical cancer cells via IL-6/gp130 signalling . To confirm that autocrine IL-6/gp130 signalling was also required for STAT3 activation in HPV+ lines , HeLa cells were pre-incubated with IL-6 and gp130 neutralizing antibodies . Incubation with either neutralising antibody reduced STAT3 dual phosphorylation and nuclear translocation ( Fig 4C and 4D ) , confirming an autocrine mechanism of STAT3 activation . Together , these data demonstrate that HPV-induced IL-6 causes autocrine and paracrine activation of STAT3 signalling in cervical cell lines . The increased STAT3 phosphorylation observed in HPV containing normal keratinocytes is driven by the E6 oncoprotein [23] . Additionally , HPV16 E6 has previously been demonstrated to induce IL-6 secretion in non-small cell lung cancer ( NSCLC ) cells [28] . Therefore , the ability of E6 to induce IL-6 expression in cervical cells was assessed by transfection of C33A cells with an IL-6 promoter luciferase reporter combined with either GFP-E6 or GFP expression plasmids . Expression of HPV18 E6 significantly increased IL-6 promoter activity compared with the GFP control ( Fig 5A ) . This correlated with an increase in endogenous IL6 mRNA expression ( Fig 5B ) and IL-6 protein expression ( Fig 5C ) . E6 expression also resulted in a significant increase in IL-6 secretion into the culture media ( Fig 5D ) . To rule out the possibility of the transformed nature of C33A cells contributing to the E6-dependent increase in IL-6 levels , we also expressed HPV18 E6 in primary normal human keratinocytes ( NHK ) . In untransformed cells , E6 increased IL6 mRNA and protein expression compared to control , and this correlated with an increase in the abundance of IL-6 protein detected in the culture media ( S1A–S1C Fig ) . To demonstrate that endogenous E6 could induce IL-6 expression in HPV+ cancer cells , HeLa ( Fig 5 ) or CaSKi ( S2 Fig ) cells were treated with two E6 specific siRNAs . Knockdown of E6 led to a significant reduction in IL6 mRNA expression ( Fig 5E and S2A Fig ) , IL-6 protein expression ( Fig 5F and S2B Fig ) and secretion ( Fig 5G and S2C Fig ) . To confirm that the E6-mediated activation of STAT3 by IL-6 was also working through the canonical gp130 –IL6R receptor complex , we incubated E6 expressing cells with neutralizing antibodies against gp130 and IL-6 . As expected , incubation with either antibody led to a reduction in the E6-mediated phosphorylation of STAT3 ( Fig 5H ) . Activation of STAT3 by HPV18 E6 is independent of interactions with E6AP , p53 and cellular PDZ domains [23] . To address whether IL-6 production requires these functions , wildtype and mutant HPV18 E6 proteins deficient in their ability to bind p53 , E6AP or PDZ domains were expressed in C33A cells . As predicted , the mutant E6 proteins increased IL-6 protein expression to levels similar as wildtype ( S3 Fig ) . Together , these data demonstrate that IL-6 expression and secretion are increased by a mechanism independent of the p53 destabilising , and PDZ binding functions , of E6 . The NFκB transcription factor is an important regulator of IL-6 expression , which is activated in response to a range of extracellular ligands such as TNFα [29] . HR-E6 has previously been shown to activate NFκB signalling under hypoxic conditions [30 , 31] . However , to assess whether NFκB is necessary for increased IL-6 expression under normoxic conditions , we first tested whether expression of HPV18 E6 in isolation would activate NFκB in C33A cells . Using an NFκB driven luciferase reporter plasmid , overexpression of E6 induced NFκB activity compared to a GFP control ( Fig 6A ) . Canonical NFκB signalling results in the phosphorylation of the p65 subunit and its nuclear translocation , where it is transcriptionally active in complex with additional NFκB subunits including p50 [29] . E6 over-expression in C33A or NHK cells induced robust p65 phosphorylation , without affecting total p65 protein levels ( Fig 6B ) . In contrast , siRNA knockdown of E6 in HeLa cells reduced p65 phosphorylation ( Fig 6C ) , together suggesting that HPV E6 activates canonical NFκB . To understand the role of NFκB in E6-driven IL-6 production , we employed a dual approach to prevent NFκB activation in C33A cells overexpressing HPV18 E6 . Cells were treated either with a small molecule inhibitor ( IKKi ) targeting the IKKα/β complex , which phosphorylates and activates NFκB , or transfected with a plasmid encoding a mutant IκBα protein ( IκBm ) , which cannot be degraded and as such retains inactive NFκB in the cytosol [32] . Inhibition of NFκB using either IKKi or IκBm led to a significant reduction in E6-mediated IL6 mRNA expression ( Fig 6D ) , IL-6 protein levels ( Fig 6E ) and secretion ( Fig 6F ) . Importantly , both strategies effectively inhibited NFκB activity as judged by a reduction in p65 phosphorylation ( Fig 6E ) . We also tested if NFκB activity was required for mediating the increased IL-6 levels seen in HeLa and CaSKi cells . In these cells , inhibition of NFκB led to a reduction in IL6 mRNA expression , IL-6 protein levels and secretion ( Fig 6G–6I ) . Collectively , these data demonstrate that HR-E6-mediated IL-6 expression requires active NFκB . It was necessary to test whether NFκB was also needed for the activation of STAT3 . As proof of principle , we tested the ability of the NFκB activator TNFα to induce STAT3 phosphorylation . As expected , treatment of serum starved C33A cells with TNFα caused robust p65 phosphorylation , which peaked at 0 . 5 hours after treatment ( S4 Fig ) . This was coupled with an increase in IL-6 expression , which remained high up to 24 hours post treatment . Importantly , TNFα treatment also caused an increase in STAT3 phosphorylation and nuclear translocation , observed to peak approximately 2 hours post treatment ( S4A and S4B Fig ) . We next set out to link NFκB activation by E6 to STAT3 phosphorylation . For this , HPV18 E6 was overexpressed in C33A cells , with or without treatment with the NFκB inhibitor IKKi , or co-expression of IκBm . E6 noticeably increased the levels of p65 and STAT3 phosphorylation and inhibition of NFκB by either approach reduced STAT3 phosphorylation ( Fig 7A ) . Blockade of NFκB activity also reduced STAT3 phosphorylation in HeLa ( Fig 7B and 7C ) and CaSKi ( S5A and S5B Fig ) cells , suggesting that E6 mediated STAT3 phosphorylation is depended on NFκB activity . To ascertain if NFκB was essential for the paracrine activation of STAT3 in C33A cells , we took CM from HeLa cells in which NFκB was inhibited and added this to C33A cells . This failed to induce STAT3 phosphorylation ( Fig 7D ) and nuclear translocation ( Fig 7E; quantified in S6A Fig ) . Importantly , inhibition of NFκB activity had no effect on STAT3 nuclear translocation mediated by treatment with exogenous IL-6 ( Fig 7F; quantified in S6B Fig ) , demonstrating that NFκB is upstream of IL-6 secretion . Together , these data suggest that NFκB is required for the autocrine and paracrine activation of STAT3 . NFκB is activated by multiple upstream signalling components in a stimulus and tissue-dependent manner [33] . In searching for upstream activators , we initially focused on known targets of HR-E6 with a link to NFκB signalling . The PI3K/AKT signalling pathway is frequently activated in cervical cancers due to mutations in the PIK3CA gene [34] , and AKT can activate NFκB and mediate IL-6 expression in some cancers [35–37] . Finally , AKT has previously been shown to be activated by E6 [38] . We therefore tested whether AKT was involved in NFκB activation and IL-6 secretion in HPV positive cervical cancer cell lines . First , we confirmed that E6 activates AKT , as measured by an increase in AKT phosphorylation . Over expression of HPV18 E6 in C33A and NHK cells led to a marked increase in AKT phosphorylation at both threonine 308 and serine 473 , without affecting levels of total AKT protein ( Fig 8A ) . Conversely , siRNA knockdown of E6 in HeLa cells reduced AKT phosphorylation ( Fig 8B ) , confirming that HPV18 E6 activates AKT . To interrogate the contribution of AKT activation to IL-6 production , E6 expressing cells were treated either with a potent allosteric inhibitor of AKT ( AKTi ) , targeting the AKT1 and 2 isoforms [39] or transfected with a plasmid encoding a catalytically inactive AKT mutant ( AKT-DN ) [40] . Inhibition of AKT by either approach led to a statistically significant reduction in IL6 mRNA expression ( Fig 8C ) , coupled to a smaller loss in protein expression and secretion ( Fig 8D and 8E ) . To confirm that the AKT-mediated increase in IL-6 was transduced via NFκB , we measured p65 phosphorylation levels in E6 expressing C33A cells treated with either AKTi or co-transfected with AKT-DN . As expected , a loss of AKT phosphorylation was observed , indicating that the inhibition strategy was successful , and this was coupled with a reduction in IL-6 protein expression ( Fig 8D ) and a partial reduction in p65 phosphorylation , suggesting that AKT lies upstream of NFκB in the regulation of IL-6 . We also validated the impact of AKT inhibition on IL-6 production in both HeLa and CaSKi cells . Interestingly , inhibition of AKT in CaSKi cells had a greater effect in reducing IL6 mRNA expression ( Fig 8F ) , IL-6 protein levels ( Fig 8G ) and secretion ( Fig 8H ) than in HeLa cells . Furthermore , AKT inhibition led to a greater reduction in p65 phosphorylation in CaSKi cells ( Fig 8G ) . These data confirm that AKT contributes to IL-6 production through the regulation of NFκB . Strikingly , there appear to be cell line differences in the requirement for AKT , with ablation of AKT kinase activity having a more significant impact on signalling in CaSKi than in HeLa cells . Based on the observation that inhibition of AKT reduced IL-6 production , particularly in CaSKi cells , we tested whether blockade of AKT activity would also impact on STAT3 phosphorylation . HPV18 E6 expressing C33A cells treated with AKTi or co-expressing AKT-DN showed a loss of AKT phosphorylation coupled to a modest reduction in STAT3 phosphorylation at both residues ( Fig 9A ) . Levels of STAT3 phosphorylation were also measured in HeLa and CaSKi cells treated with increasing concentrations of AKTi or over-expressing the AKT-DN protein . Whilst these inhibitory strategies reduced AKT phosphorylation in both cell lines , the corresponding reduction in STAT3 phosphorylation in HeLa cells was minor and mirrored the small reduction in IL-6 protein expression ( Fig 9B and 9C ) . In contrast , loss of AKT activity corresponded with a greater reduction in IL-6 expression and STAT3 phosphorylation in CaSKi cells ( S7A and S7B Fig ) . To ascertain if AKT was essential for the paracrine activation of STAT3 in C33A cells , we took CM from HeLa cells in which AKT was inhibited either by treatment with AKTi or co-expression of AKT-DN and added this to C33A cells . CM from cells with inhibited AKT caused less STAT3 phosphorylation ( Fig 9D ) and nuclear translocation ( Fig 9E; quantified in S8A Fig ) compared to controls . Importantly , inhibition of AKT activity had no effect on STAT3 nuclear translocation mediated by exogenous IL-6 ( Fig 9F; quantified in S8B Fig ) , demonstrating that AKT is upstream of IL-6 secretion . Together , these data suggest that AKT is an E6 effector playing a minor role in the autocrine and paracrine activation of STAT3 . Whilst our data points to a role for AKT as an E6-effector protein with the potential to activate NFκB and IL-6 production , it is clear that other cellular factors are required and likely play a more prominent role in the signalling pathway . As part of our efforts to identify such candidates , we investigated the possible involvement of the small GTPase Rac1 as it has previously been shown to regulate both AKT and STAT3 signalling [41–44] . In addition , Rac1 is active in a number of skin and oral SCCs , and experiments from mouse models suggest that it acts as a proto-oncogene [45–47] . Rac1 can facilitate papilloma formation in HPV negative 8 transgenic mice [48] and is active in HPV-mediated respiratory papillomatosis [49 , 50] . We therefore measured the levels of active Rac1 ( Rac1-GTP ) in E6-expressing C33A cells using an affinity precipitation assay [51] . Expression of HPV18 E6 increased Rac1-GTP levels compared with control cells ( Fig 10A ) and siRNA depletion of E6 from HeLa cells resulted in a reduction in active Rac1 compared to a scramble control ( Fig 10B ) . Together , these data indicate that E6 activates Rac1 . We next set out to determine if the Rac1 GTPase links E6 to IL-6 production . To this end we used two well characterised approaches to inhibit Rac1 function . C33A cells expressing HPV18 E6 were treated with the Rac1 inhibitor NSC23766 ( NSC ) or co-transfected with a transdominant mutant Rac1 ( Rac1 T17N - Rac1-DN ) and IL-6 mRNA levels were measured by RT-qPCR . Inhibition of Rac1 activity with either NSC or Rac1-DN potently inhibited IL-6 mRNA expression in E6 expressing cells ( Fig 10C ) . Inhibition of Rac1 function also impaired E6-induced p65 phosphorylation , supporting a role for Rac1 in the E6 stimulation of NFκB ( Fig 10D ) . Rac1 inhibition was accompanied by a significant reduction in IL-6 protein expression and secretion into the culture media ( Fig 10D and 10E ) . Active Rac1 was also critical for p65 phosphorylation , IL6 mRNA expression and IL-6 protein expression and secretion in both HeLa and CaSKi cells ( Fig 10F–10H ) . We also noted that blockade of Rac1 function reduced AKT dual phosphorylation either in cells expressing HPV18 E6 in isolation or in HPV positive cervical cancer cells ( Fig 10D and 10G ) . Collectively the results indicate a key role for Rac1 in E6-regulated IL-6 production upstream of AKT and NFκB . We examined whether Rac1 was also necessary for STAT3 activation by E6 . Chemical inhibition of Rac1 or over-expression of the Rac1-DN mutant decreased the dual phosphorylation of STAT3 in HPV18 E6 expressing C33A cells ( Fig 11A ) . Similarly , NSC addition to HeLa ( Fig 11B ) or CaSKi ( S9A Fig ) resulted in a dose-dependent decrease in STAT3 phosphorylation . Confirmatory results were obtained in cells overexpressing the transdominant Rac1 mutant ( Fig 11C and S9B Fig ) . To explore if Rac1 contributed to the paracrine activation of STAT3 in C33A cells , we took CM from HeLa cells in which Rac1 was inhibited and added this to C33A cells . This failed to induce STAT3 phosphorylation ( Fig 11D ) and nuclear translocation ( Fig 11E; quantified in S10A Fig ) . Crucially , Rac1 inhibition had negligible effect on STAT3 nuclear translocation mediated by treatment with exogenous IL-6 ( Fig 11F; quantified in S10B Fig ) , demonstrating that Rac1 is upstream of IL-6 secretion . STAT3 is a key mediator of cell proliferation [52 , 53] . Given this information it was pertinent to investigate the consequences of inhibiting STAT3 activation in HPV positive cervical cancer cells by the application of two chemically distinct inhibitors of STAT3 ( cryptotanshinone and S3I-201 ) or by transfecting cells with a pool of STAT3 specific siRNA [23] . Growth curves were performed with HeLa and CaSKi cells treated with DMSO or STAT3 inhibitors or transfected with scramble or STAT3 specific siRNA . Compared to controls , blockade of STAT3 activity or loss of its expression resulted in a significant reduction in cell growth over the time course of treatment ( Fig 12A and 12B ) . Additionally , treatment with STAT3 inhibitors or depletion of STAT3 protein suppressed the ability of HeLa and CaSKi cells to form colonies under anchorage-dependent ( Fig 12C and 12D ) and anchorage-independent ( Fig 12E and 12F ) conditions . To further evaluate the impact of STAT3 inhibition , we assessed the levels of key cell cycle proteins . STAT3 phosphorylation was decreased when treated with increasing concentrations of cryptotanshinone ( Fig 12G ) and this correlated with a decrease in cyclin D1 expression , which we previously identified as a STAT3 target in HPV-containing primary keratinocytes [23] . Loss of cyclin D1 expression was associated with an increase in the levels of the cyclin dependent kinase inhibitor p21WAF1/KIP1 ( Fig 12G ) . Changes to the complement of cell cycle control proteins as a result of STAT3 inhibition correlated with a loss in HPV oncoprotein expression in both HeLa and CaSKi cells ( Fig 12G ) . Similar effects on cyclin D1 , p21 and HPV oncoprotein expression were observed in cells treated with STAT3-specific siRNA ( Fig 12H ) . These observations prompted us to explore whether upstream components in the STAT3 activation pathway are also necessary for HPV positive cancer cell proliferation . To this end colony formation assays were used to measure anchorage-dependent growth of HeLa and CaSKi cells in which NFκB was inhibited either by treatment with the IKKi small molecule inhibitor or by over-expression of the transdominant IκBa protein . NFκB inhibition significantly reduced the ability of HPV positive cancer cells to form colonies ( S11A Fig ) . Next , we tested the upstream activators of NFκB . Blockade of Rac1 activity with the NSC compound or overexpression of Rac1-DN was detrimental to HPV positive cancer cell proliferation and resulted in approximately 50% fewer colonies than the controls ( S11B Fig ) . Finally , we assessed the contribution of AKT to HPV positive cancer cell proliferation . Loss of active AKT , either as a result of AKTi treatment or overexpression of the catalytically inactive AKT mutant , also impaired cell proliferation ( S11C Fig ) . Similar differences in anchorage-independent growth were observed when these proteins were perturbed ( S11D and S11E Fig ) . When compared , loss of Rac1 and NFκB activity reduced proliferation in both HeLa and CaSKi cells , whilst the impact of AKT inhibition was more pronounced in the CaSKi cells . Collectively , these observations provide evidence that the STAT3 activation pathway is crucial for HPV positive cancer cell proliferation . In light of the impact of STAT3 inhibition on HPV+ cervical cancer cell proliferation , we sought to address whether the absence of active STAT3 induced apoptosis . STAT3 activity was inhibited in HeLa and CaSKi cells by treatment with STAT3 small molecule inhibitors for 6 and 24 hours ( Fig 13A ) or STAT3 protein depleted by transfection of a pool of STAT3-specific siRNA ( Fig 13B ) , and the degree of phosphatidylserine exposure on the plasma membrane measured by Annexin V stain . At both 6 and 24 hours post treatment , inhibition of STAT3 or loss of STAT3 protein led to a significant increase in apoptosis compared to controls in both cell lines . We next demonstrated the activation of caspase 3 by measuring the degree of cleavage of the caspase 3 substrate poly ( ADP ) ribose polymerase ( PARP ) by western blot . As shown , inhibition of STAT3 activity ( Fig 13C ) or loss of STAT3 protein ( Fig 13D ) promoted the appearance of the faster migrating , proteolytically cleaved , form of PARP . Appearance of cleaved PARP was coincident with reduced expression of the anti-apoptotic Bcl-2 family protein Bcl-XL . RT-qPCR revealed the loss of survival factors such as Bcl-XL ( bcl2l1 ) and Survivin ( birc5 ) to be at the transcriptional level ( Fig 13E and 13F ) . Thus , STAT3 is essential for HPV+ cervical cancer cell survival . STAT3 has been shown to engage in mechanisms to augment NFκB activation and maintain IL-6 expression in a number of cancers and inflammatory disorders [54–57] . To investigate if such a positive feedback loop exists in cervical cancer cells we used siRNA to deplete STAT3 from HeLa and CaSKi cells and then measured the impact on IL-6 expression ( S12 Fig ) . Upon STAT3 depletion we observed a marked reduction in the levels of IL-6 mRNA , IL-6 protein expression and secretion , indicating that STAT3 likely drives a mechanism to maintain enhanced IL-6 expression in cervical cancer cells . The IL-6—STAT3 signalling axis has emerged as a key contributor to carcinogenesis in a number of cancers [21] , often resulting in increased IL-6 expression as observed in lung cancer and head and neck cancers [58 , 59] . We analysed cervical liquid-based cytology samples from a cohort of HPV16+ patients representing the progression of disease development ( CIN1-CIN3 ) and compared this to HPV- normal cervical tissue to explore the role of IL-6 in cervical disease . Firstly , we observed an increase in the levels of IL6 mRNA expression , which correlated with disease progression through CIN1-CIN3 ( Fig 14A ) , with the greatest increase observed in CIN3 samples when compared with normal cervical tissue . Importantly , we also noted an increase in IL-6 protein levels , which correlated with disease progression ( Fig 14B ) , again showing the largest increase in CIN3 . Analysis of a larger cohort of clinical samples revealed a breadth in the levels of IL-6 protein expression , particularly in the CIN3 samples , which separated into 2 subsets; IL-6 high ( n = 9; 45% ) and IL-6 low ( n = 11; 55% ) ( Fig 14C , left ) . To view the spread of IL-6 expression , we performed a Box and Whisker plot analysis ( Fig 14C , right ) . The data clearly show that despite the presence of IL-6 outliers , levels of IL-6 protein expression are higher in the majority of CIN3 samples , with the IL-6 low subset still significantly higher when compared to healthy controls . To corroborate these findings in primary tumours , we mined an available microarray database of normal cervical samples against cervical cancer samples and revealed a statistically significant increase in IL6 mRNA expression in the cervical cancer samples ( Fig 14D ) . As with our analysis of CIN , IL-6 expression in the cervical cancer cases clearly separates into 2 subsets; IL-6 high ( n = 7; 25 . 9% ) and IL-6 low ( n = 20; 74 . 1% ) . As our mechanistic analysis revealed a significant role for NFκB in IL-6 production , we wished to determine whether expression and activation of this critical transcription factor was also increased in the patient samples available . Western blot analysis revealed an increase in both the levels of total and phosphorylated p65 protein that correlated with disease progression ( Fig 14B ) . Quantification of the larger cohort of cytology samples showed that this increase was statistically significant ( Fig 14E–14G ) . Together , these data demonstrate that p65 and IL-6 levels are increased in HPV associated cervical disease .
Oncogenic viruses can activate STAT3 to increase cell proliferation , enhance viral replication and this ultimately can contribute to tumourigenesis [22] . Previously , we used a primary cell culture model to show that the E6 oncoprotein activates STAT3 signalling in primary keratinocytes during the HPV18 lifecycle [23] . We revealed that STAT3 activation correlates with cervical disease progression . Mechanistically , we demonstrated that JAK2 and MAP kinases were responsible for phosphorylating STAT3 in HPV containing cells . Despite these advances , the host factors co-opted by E6 to drive these events were not fully explored . In this report we identified the upstream signalling pathway responsible for STAT3 phosphorylation in HPV positive cells . We reveal that E6 regulates a signalling pathway necessary for production of the cytokine IL-6 . Further , we identified a key role for the small GTPase Rac1 in activating NFκB , which induced IL-6 transcription . Ultimately , we deciphered a signalling circuit critical for STAT3 activation by HPV ( Fig 15 ) . Dysregulation of inflammatory cytokine signalling is an emerging mechanism in transformation and IL-6 is over-expressed in diverse cancers , correlating with increased STAT3 activity [21] . IL-6 displays pleiotropic functions , being both pro-inflammatory and immunosuppressive by interacting with the surrounding stroma of tumours [60] . In HNSCC and oral squamous cell carcinoma , serum levels of IL-6 are significantly higher than control patients and serum IL-6 is a potential biomarker for these cancers [61] . Additionally , targeting IL-6 in combination with EGFR inhibitors such as Cituximab is currently being investigated as a potential therapy for HNSCC due to the resistance to EGFR inhibition seen in many tumours [62 , 63] . In cervical cancer , IL-6 expression promotes tumour proliferation by inducing vascular epithelial growth factor ( VEGF ) -dependent angiogenesis in a STAT3 dependent manner [64] and has also been suggested as a potential biomarker [65] . HPV16 and HPV18 E6 oncoproteins have been demonstrated to be required for the expression and secretion of IL-6 in NSCLC cells [28]; however , the role of E6 in driving IL-6 expression in cervical cancer is unclear . Furthermore , the contribution of IL-6 to STAT3 activation in cervical cancer remains poorly defined . The increased phosphorylation of STAT3 in HPV positive cervical cancer cells was attributed to an increase in IL-6 expression by HPV E6 and the induction of autocrine/paracrine IL-6/gp130/STAT3 signalling . In cancer cells , EGFR signalling can induce STAT3 activation [66]; however , the data here identified that blockade of IL-6 or gp130 signalling using neutralising antibodies abolished STAT3 phosphorylation , suggesting that IL-6/gp130 is the major determinant for STAT3 phosphorylation in HPV+ cervical cancer cells . Interestingly , whilst anti-IL-6 treatment did reduce the levels of STAT3 activation , it was not as effective as when cells were treated with the anti-gp130 antibody . Whilst we cannot discount that this difference reflects the efficacy of the antibody reagents , an alternative explanation could be provided by the observation that HPV positive cervical cells show increased expression of a number of gp130 binding cytokines ( e . g . OSM , LIF and IL-10 ) . These may be responsible for the residual STAT3 phosphorylation observed [67 , 68] . We identified NFκB as an essential upstream mediator of IL-6 expression . NFκB is a key component of the inflammatory response and a key hallmark of cancer [69] . The induction of inflammation by diverse mechanisms contributes to around 20% of cancers . Previous data suggests that inflammation induced by HPV infection may contribute to HPV induced cervical cancers [70 , 71] . Indeed , several genes known to be induced by the inflammatory response , including COX-2 [72] , are up-regulated in cervical cancer . The role of NFκB in cervical carcinomas remains controversial , with HPV showing the potential to both activate and inhibit the transactivation function of NFκB [30 , 73 , 74] . HPV E6 has been reported to increase the expression of NFκB components and induce NFκB DNA binding activity , increasing pro-inflammatory cytokine expression [75] . Additionally , E6 can reduce the expression of the deubiquitinase CYLD , a known negative regulator of NFκB signalling , in hypoxic cells [31] . In contrast , E6 has been shown to inhibit NFκB transcriptional activity , whilst HPV E7 can attenuate p65 nuclear translocation [76] . The data presented here demonstrate that HPV18 E6 increases the phosphorylation of p65 , essential for its nuclear translocation and transactivation capability . Furthermore , we demonstrate that NFκB is essential for IL-6 expression in HPV positive cervical cancer cells . Our study uncovered a signalling circuit linking E6 to NFκB activation and IL-6 production . Chief amongst these , we found that the Rac1 GTPase was crucial in mediating the activation of NFκB . Cells expressing E6 were enriched for the GTP bound form of Rac1 , indicating that E6 has the ability to activate the GTPase function of Rac1 . The mechanism by which this occurs is currently not known , although it does not require interactions with E6AP , p53 or cellular PDZ domain containing proteins as classical E6 mutants deficient in these abilities are still able to increase IL-6 expression and STAT3 phosphorylation . Use of small molecule inhibitors or dominant negative forms of Rac1 support the idea that Rac1 GTPase function and interaction with downstream targets are crucial for the E6-mediated activation of NFκB . In this regard , we also identified a role for the protein kinase AKT in HPV-mediated NFκB activation . AKT can be activated by Rac1 [43] and has been shown to regulate NFκB under certain circumstances [36 , 77 , 78] . In PTEN-null cells , AKT activates NFκB through binding of the downstream components mTOR and Raptor to the IKK complex , stimulating NFκB activation [77] . Additionally , AKT can directly phosphorylate and activate IKKα at T23 to enhance p65 phosphorylation [36] . Our data demonstrate that AKT contributes to the phosphorylation of p65 and the expression on IL-6 in HPV positive cervical cancer; however , inhibition of AKT only partially reduced IL-6 expression , suggesting alternative components upstream may be involved in NFκB mediated IL-6 expression . Of particular interest , we noted that CaSKi cells appeared more sensitive to inhibition of AKT than HeLa cells . In cervical cancer , the PIK3CA gene is extensively mutated , with the most common mutation ( E545K ) resulting in constitutive PI3K/AKT signalling [79] . This oncogenic mutation can activate IKK/NFκB signalling and increase IL-6 secretion and paracrine STAT3 activation in epithelial cells [37] . Interestingly , whilst HeLa cells have wild type PIK3CA , CaSKi cells encode the E545K mutant [80] . It may therefore be possible that in cells with constitutive PI3K/AKT signalling , AKT inhibition has a greater contribution to the NFκB/IL-6 signalling axis than in cells expressing wild type PIK3CA [80] . Loss of active STAT3 had a significant impact on both cervical cancer cell proliferation and survival . The increased apoptosis observed was coupled with a loss of expression of key pro-survival factors such as Bcl-XL and Survivin , reinforcing the concept that STAT3 inhibition is deleterious to HPV cancer cell survival [24 , 25] . However , it was imperative to obtain a more comprehensive understanding of the host pathways necessary for STAT3 activation . Interestingly , targeting of key upstream factors necessary for the autocrine activation of STAT3 also impaired proliferation indicating that this signalling circuit is essential in cervical cancer cells . The NFκB–IL-6—STAT3 signalling axis is important to cancer biology . We previously demonstrated increased STAT3 phosphorylation in cervical disease [23] and we now demonstrate a similar link between IL-6 levels and cervical disease . We noted increased IL-6 mRNA expression in high-grade cervical disease samples and in cervical cancer samples compared to healthy controls . Interestingly , we observed that IL-6 protein expression in CIN3 and cervical cancer clearly stratifies into two sub-populations; IL-6 high and IL-6 low . These findings suggest there may be diversity in the requirement for IL-6 in HPV positive cervical cancers . As STAT3 can be activated by several soluble factors in cervical cancer cells , such as OSM [67] , EGF [81] and IL-10 [82] , it is possible that the IL-6 low cancers might be dependent on these additional cytokines to maintain active STAT3 . Furthermore , IL-6 independent STAT3 activation can be found in other cancers , including head and neck cancers and haemopoietic cancers [83–85] , suggesting that not all cancers that have high STAT3 activity necessarily have high IL-6 expression . In diffuse large B-cell lymphoma ( DLBCL ) , a subgroup called the activated B cell–like ( ABC ) DLBCL , are characterised by high IL-6 expression and STAT3 activity and , importantly , are selectively sensitive to JAK inhibition when compared to germinal center B-cell ( GCB ) DLBCL [86] . Our data demonstrate that although IL-6 may be essential for the activation of STAT3 in our cervical cancer cell culture system , the heterogeneity of IL-6 expression observed in clinical samples of cervical disease and cervical cancers warrants further investigation to allow the proper stratification of potential therapeutics targeting this pathway . The data presented here demonstrate that NFκB is essential for the induction of IL-6 and the autocrine/paracrine induction of STAT3 phosphorylation in HPV+ cervical cancer cells . We identify that the Rac1 GTPase and protein kinase AKT lie upstream of NFκB/IL-6 signalling . Although therapies are not currently available , strategies to target the NFκB–IL-6 –STAT3 signalling axis may benefit the treatment of HPV+ cancers .
Cervical cytology samples were obtained from the Scottish HPV Archive ( http://www . shine/mvm . ed . ac . uk/archive . shtml ) , a biobank of over 20 , 000 samples designed to facilitate HPV associated research . The East of Scotland Research Ethics Service has given generic approval to the Scottish HPV Archive as a Research Tissue Bank ( REC Ref 11/AL/0174 ) for HPV related research on anonymised archive samples . Samples are available for the present project though application to the Archive Steering Committee ( HPV Archive Application Ref 0034 ) . RNA and protein were extracted from the samples using Trizol as described by the manufacturer ( ThermoFischer Scientific , USA ) and analysed as described . C33A ( HPV negative cervical carcinoma ) , DoTc2 4510 ( HPV negative cervical carcinoma ) , SiHa ( HPV16 positive cervical squamous carcinoma ) , CaSKi ( HPV16 positive cervical squamous carcinoma ) , SW756 ( HPV18 positive squamous carcinoma ) and HeLa ( HPV18 positive cervical epithelial adenocarcinoma ) cells were purchased from ATCC and grown in Dulbecco’s modified Eagle’s media ( DMEM ) supplemented with 10% Foetal Bovine Serum ( FBS ) ( ThermoFischer Scientific , USA ) and 50 U/ml penicillin/streptomycin ( Lonza ) . NHK cells were purchased from Lonza and maintained as described [7] . The IKKα/β inhibitor IKK inhibitor VII was purchased from Calbiochem and used at a final concentration of 5 μM unless otherwise stated . The AKT1/2 inhibitor AKT VIII was purchased from Calbiochem and used at a final concentration of 5 μM unless otherwise stated . Recombinant human IL-6 was purchased from R&D Systems and used at a final concentration of 20 ng/mL unless otherwise stated . Recombinant TNFα was purchased from PeproTech EC Ltd and used at a final concentration of 10 ng/mL . All compounds were used at concentrations required to minimise potential off-target activity . Neutralising IL-6 antibody ( ab6628 ) was purchased from Abcam and used at a final dilution of 1:400 . Neutralising gp130 antibody ( MAB228 ) was purchased from R&D Systems and used at a final concentration of 1 μg/mL . Plasmids expressing HPV18 E6 sequences were amplified from the HPV18 genome and cloned into peGFP-C1 with SalI and XmaI restriction enzymes [23] . The plasmid driving Firefly luciferase from the IL-6 promoter was a kind gift from Prof Derek Mann ( University of Newcastle ) and used as previously described [87]; the ConA promoter ( that contains tandem NFκB response elements ) [88] and a constitutive Renilla luciferase reporter ( pRLTK ) were previously described [87] . The IκBα S33/36A mutant was a kind gift from Prof Ronald Hay ( University of Dundee ) . pLNCX myr HA AKT1 K179M ( AKT-DN ) vector was purchased from Addgene ( Addgene , 9006 ) and murine retrovirus envelope and GAG/polymerase plasmids were kindly provided by Professor Greg Towers ( University College London ) . pcDNA-GFP-Rac1-T17N ( Rac1-DN ) was kindly provided by Professor Adrian Whitehouse ( University of Leeds ) . MSCV-HA-HPV18 E6 was kindly provided by Dr Elizabeth White ( University of Pennsylvania ) . For siRNA experiments , two siRNA sequences specifically targeting HPV18 E6 were purchased from GE Healthcare with the following sequences: 5’CUAACACUGGGUUAUACAA‘3 and 5’CTAACTAACACTGGGTTAT‘3 . For HPV16 , a single siRNA targeting the HPV16 E6 protein was purchased from Santa Cruz Biotechnology ( SCBT; sc-156008 ) . For each experiment , 40 nM of pooled siRNA was used and cell lysates were harvested after 72 hours . Transient transfections were performed with a DNA to Lipofectamine 2000 ( ThermoFischer ) ratio of 1:2 . 5 . 48 h post transfection , cells were lysed in Leeds lysis buffer for western blot [88] . 48 hr post-transfection , cells were trypsinised and reseeded in a six well plate at 500 cells per well and left to incubate for 14–21 days . Colonies were then stained ( 1% crystal violet , 25% methanol ) and colonies were counted manually . Each experiment was repeated a minimum of 3 times . Cells were transfected as required . 60 mm dishes were coated with a layer of 1% agarose ( ThermoFischer Scientific , USA ) in 2X DMEM ( ThermoFischer Scientific , USA ) supplemented with 20% FBS . 48 hr post-transfection , cells were trypsinised and added to 0 . 7% agarose in 2X DMEM ( ThermoFischer Scientific , USA ) supplemented with 20% FBS at 1000 cells/mL . Once set , DMEM supplemented with 10% FBS and 50 U/mL penicillin was added . The plates were then incubated for 14–21 days . Each experiment was repeated at least three times unless stated otherwise . Visible colonies were counted manually . Annexin V apoptosis assay ( TACS Annexin V kit; 4830-250-K ) was performed as indicated on the product datasheet . Briefly , cells were seeded in 6 well plates at a density of 1 x 106 cells/mL and were treated as required per experiment . Cells were then trypsinised and collected by centrifugation at 700 x g for 5 mins . Cells were then washed in cold PBS and re-centrifuged . 1x106 cells were then incubated in 100 μL Annexin V reagent ( 10 μL 10 x binding buffer , 10 μL propidium iodide , 1 μL Annexin V-FITC ( diluted 1 in 500 ) and 880 μL ddH2O ) for 15 mins at room temperature in the dark . 400 μL of 1 x binding buffer was then added before analysis by flow cytometry . Samples were processed on an LSRFortessaTM cell analyzer ( BD ) and the PI histograms analysed on modfit software . Total protein was resolved by SDS-PAGE ( 10–15% Tris-Glycine ) , transferred onto Hybond nitrocellulose membrane ( Amersham biosciences ) and probed with antibodies specific for phospho-STAT3 ( S727 ) ( ab32143 , abcam ) , phospho-STAT3 ( Y705 ) ( 9131 , Cell Signalling Technology ( CST ) ) , STAT3 ( 124H6: 9139 , CST ) , phospho-NFκB p65 ( S536 ) ( 93H1; 3033 , CST ) , NFκB p65 ( D14E12; 8242 , CST ) , phospho-AKT ( T308 ) ( 244F9; 4056 , CST ) , phospho-AKT ( S473 ) ( D9E; 4060 , CST ) , AKT ( 9272 , CST ) , IL-6 ( ab6672 , abcam ) , HA ( HA-7 , Sigma H9658 ) , GFP ( B-2: sc-9996 , SCBT ) , FLAG ( F3165 , Sigma ) , GAPDH ( G-9 , SCBT ) , PARP-1 ( 9542 , CST ) and Bcl-xL ( 2764 , CST ) . Western blots were visualized with species-specific HRP conjugated secondary antibodies ( Sigma ) and ECL ( Thermo/Pierce ) . Densitometry analysis was performed using ImageJ analysis software ( NIH , USA ) . pLNCX AKT vector ( Addgene , 9006 ) and MSCV-HA-18E6 were transfected into HEK293TT cells with murine retrovirus envelope and GAG/polymerase plasmids ( kindly provided by Professor Greg Towers , University College London ) using PEI transfection reagent as previously described [23] . After 48 hours the media was removed from the HEK293TT cells and added to HeLa cells for 16 hours . After this time , the virus was removed and replaced with DMEM and cells were harvested 48 hours after transduction . Total RNA was extracted using the E . Z . N . A . Total RNA Kit I ( Omega Bio- Tek ) according to the manufacture’s protocol . One μg of total RNA was DNase treated following the RQ1 RNase-Free DNase protocol ( Promega ) and then reverse transcribed with a mixture of random primers and oligo ( dT ) primers using the qScriptTM cDNA SuperMix ( Quanta Biosciences ) according to instructions . RT- qPCR was performed using the QuantiFast SYBR Green PCR kit ( Qiagen ) . The PCR reaction was conducted on a Corbett Rotor-Gene 6000 ( Qiagen ) as follows: initial activation step for 10 min at 95°C and a three-step cycle of denaturation ( 10 sec at 95°C ) , annealing ( 15 sec at 60°C ) and extension ( 20 sec at 72°C ) which was repeated 40 times and concluded by melting curve analysis . The data obtained was analysed according to the ΔΔCt method using the Rotor-Gene 6000 software [89] . Specific primers were used for each gene analysed . U6 served as normaliser gene . Cells were seeded into 12 well dishes and transfected the following day using PEI with reporter plasmids expressing firefly luciferase under the control of the IL-6 promoter or the ConA promoter , which contains tandem repeats of a κB-response element [87 , 90] . Where appropriate , cells were co-transfected with plasmids expressing GFP or GFP-E6 . To normalise for transfection efficiency , pRLTK Renilla luciferase reporter plasmid was added to each transfection . After 24 hours , samples were lysed in passive lysis buffer ( Promega ) and activity measured using a dual-luciferase reporter assay system ( Promega ) as described [91] . Cells were seeded onto coverslips and , 24 hr later , were transfected as required . 24 hr after transfection , cells were fixed with 4% paraformaldehyde for 10 min and then permeabilised with 0 . 1% ( v/v ) Triton for 15 minutes . Cells were then incubated in primary antibodies in PBS with 4% BSA overnight at 4°C . Primary antibodies were used at a concentration of 1:400 . Cells were washed thoroughly in PBS and then incubated with Alex-fluor conjugated secondary antibodies 594 and Alexa 488 ( 1:1000 ) ( Invitrogen ) in PBS with 4% BSA for 2 hours . DAPI was used to visualise nuclei . Coverslips were mounted onto slides with Prolong Gold ( Invitrogen ) . Quantification of nuclear localisation was quantified as described [92] . The human IL-6 DuoSet® ELISA was purchased from R&D Systems and was used according to the manufacturer’s instructions . The activation of Rac1 was determined by pulldown assay as previously described [51] and following the manufacturer’s instructions ( Cell Biolabs ) . Cell lysates were incubated with PAK PBD agarose beads , which have a high affinity for GTP-Rac1 . Affinity precipitated activated Rac1-GTP levels were then analysed by immunoblotting using a Rac1 specific antibody ( Cell Biolabs ) . For microarray analysis , a dataset of 27 cervical cancer cases and 23 normal cervix samples was utilised . Microarray data was obtained from GEO database accession number GSE9750 . Where indicated , data was analysed using a two-tailed , unpaired Student’s t-test .
|
Persistent infection with HPV is the predominant cause of anogenital and oral cancers . Transformation requires the re-wiring of signalling pathways in infected cells by virus encoded oncoproteins . At this point , a comprehensive understanding of the full range of host pathways necessary for HPV-mediated carcinogenesis is still lacking . In this study we describe a signalling circuit resulting in the aberrant production of the IL-6 cytokine . Mediated by the HPV E6 oncoprotein , it requires activation of the NFκB transcription factor . The autocrine and paracrine actions of IL-6 are essential for STAT3 activation in HPV positive cervical cancers and loss of the pathway results in increased cancer cell death and a reduction in proliferation . This study provides molecular insights into the mechanisms by which a virus encoded oncoprotein activates an oncogenic pathway and identifies potential targets for therapeutic intervention .
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2019
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Autocrine STAT3 activation in HPV positive cervical cancer through a virus-driven Rac1—NFκB—IL-6 signalling axis
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The genetic model plant Arabidopsis thaliana , like many plant species , experiences a range of edaphic conditions across its natural habitat . Such heterogeneity may drive local adaptation , though the molecular genetic basis remains elusive . Here , we describe a study in which we used genome-wide association mapping , genetic complementation , and gene expression studies to identify cis-regulatory expression level polymorphisms at the AtHKT1;1 locus , encoding a known sodium ( Na+ ) transporter , as being a major factor controlling natural variation in leaf Na+ accumulation capacity across the global A . thaliana population . A weak allele of AtHKT1;1 that drives elevated leaf Na+ in this population has been previously linked to elevated salinity tolerance . Inspection of the geographical distribution of this allele revealed its significant enrichment in populations associated with the coast and saline soils in Europe . The fixation of this weak AtHKT1;1 allele in these populations is genetic evidence supporting local adaptation to these potentially saline impacted environments .
Uncovering the genetic polymorphisms that underlie adaptation to environmental gradients is a critical goal in evolutionary biology , and will lead to a better understanding of both the types of genetic changes and the gene functions involved . Such understanding will not only provide insight into how organisms may respond to future global climate change , but will also provide tools for the development of agricultural systems and ecological services that are more resilient to such changes . Patterns of phenotypic diversity across environmental gradients can be indicative of adaptive responses to selection , and evaluation of these patterns has the potential to lead to the identification of the genetic polymorphisms underlying these adaptive responses . Numerous studies in animals and plants have identified phenotypic clines in various life history traits , but only a few have determined the genetic changes driving such traits . In Arabidopsis thaliana , plasticity in seasonally regulated flowering appears to be modulated by a network of gene interactions responsive to both vernalization and photoperiod signals [1] . Adaptive clines in resistance to oxidative stress and chilling [2] , and wing size [3] in Drosophila melanogaster are modulated by the Insulin-like Receptor ( InR ) and Drosophila cold acclimation ( Dca ) genes , respectively . While adaptation to high altitude in Peromyscus maniculatus ( Deer mice ) is associated with enhanced pulmonary O2 loading driven by alterations in α-globin and β-globin genes [4] . These genetic changes are all associated with adaptation to variation in environmental factors that vary with latitude or altitude . Such systematic variation has greatly facilitated the discovery of these loci and their adaptive significance . Clines in various life history traits have also been identified in plants growing on serpentine [5] , saline [6] , [7] , and mine impacted soils [8] . Progress has been made in outlining the genetic architecture of these adaptive traits [5] , [8]–[10] , though a molecular genetic understanding is still needed . A . thaliana is broadly distributed in its native Europe and central Asia , where it experiences a wide range of altitudinal , climatic , and edaphic conditions , leading to a range of selective pressures [11] . Whether the wide variety of natural phenotypic and genetic variation observed in A . thaliana [12] contributes to its local adaptation is an important unresolved question that is currently attracting a significant amount of attention [13] . Because of its relevance to crop production , salinity tolerance in plants has been studied intensively [14] , and natural plant populations adapted to such conditions have provided an excellent system for studying the evolutionary mechanisms of adaptation and speciation in coastal [6] , [10] and salt marsh [7] , [9] , [15]–[18] environments . The primary effects of excess Na+ on plants are water deficit resulting from a water potential gradient between the soil solution and plant cells , and cytotoxicity due of intracellular Na+ accumulation [14] . To overcome these effects plants must both accumulate solutes for osmotic regulation , and detoxify intracellular Na+ either by limiting its accumulation , or by compartmentalizing Na+ into the vacuole . In addition , Na+ compartmentalization facilitates vacuolar osmotic adjustment that is necessary to compensate for the osmotic effects of salinity by maintaining turgor pressure for cell expansion and growth . Plants therefore need to strike a balance between the accumulation of Na+ to maintain turgor , and the need to avoid Na+ chemical toxicity , and this balance will depend in part on soil salinity levels . Given the critical role Na+ accumulation plays in salinity tolerance , we used this life history trait to probe the global A . thaliana population for signals of adaptive selection for growth in saline impacted environments .
We grew 349 accessions of A . thaliana in a controlled common garden in non-saline soil , and analyzed leaf Na+ accumulation . We observed a wide range of leaf Na+ accumulation across the accessions ( 330–4 , 848 mg kg−1 dry weight ) . If this natural variation in leaf Na+ accumulation capacity is related to adaptation to growth in saline soils we would expect to find evidence of an adaptive cline , or a gradient of leaf Na+ accumulation that correlates with the geographical distribution of variation in soil salinity . Salinity impacted soils are expected to occur in coastal regions due to air born deposition of sea spray which can occur many tens of km inland [19]–[22] , but can also occur in areas distant from the coast through high Na+ in the soil or ground water . Elevated soil salinity can also be caused by inappropriate irrigation practices such as irrigation with saline water or poor drainage . To test for the existence of an adaptive cline in leaf Na+ accumulation capacity and soil salinity we related leaf Na+ accumulation capacity to the distance of the collection site for each accession to the coast , or to the nearest known saline soil , whichever is the shortest . We focused on European accessions since a good soil salinity map exists for this region [23] , which left 300 accessions . Regressing the distance to the coast , or nearest known saline soil , on leaf Na+ for all 300 accessions revealed a significant relationship ( p-value<2e-12 ) , establishing that accessions with elevated leaf Na+ are more likely to grow in potentially saline impacted soils ( Figure 1A and 1B ) . To investigate the genetic architecture underlying this cline in leaf Na+ accumulation capacity we performed a genome-wide association ( GWA ) study ( previously described for a smaller data set [24] ) to identify regions of the genome at which genetic variation is associated with leaf Na+ accumulation capacity . The 337 A . thaliana accessions used in our GWA study , which are a subset of the 349 accessions phenotyped for leaf Na+ , were genotyped using the Affymetrix SNP-tilling array Atsnptile1a which can interrogate 248 , 584 SNPs . To assess evidence of association between SNPs and leaf Na+ accumulation we used a mixed-model approach [25] to correct for population structure , as previously described [24] . In the current analysis we identified a single strong peak of SNPs associated with leaf Na+ , with the peak centered on AtHKT1;1 ( Figure 2 ) , a gene known to encode a Na+-transporter [26] . Accessions with a thymine ( T ) at the SNP most significantly associated with leaf Na+ at position 6392276 bp on chromosome 4 ( Chr4:6392276 ) have significantly higher leaf Na+ than accessions with a cytosine ( C ) at this same position ( 2 , 325 vs . 955 mg Na+ kg−1 dry weight , p-value<2e-16 ) . This SNP explains 32% ( without accounting for population structure ) of the total variation in leaf Na+ accumulation observed . Previously , in independent test crosses between the high leaf Na+ accessions Ts-1 and Tsu-1 ( both containing a T at Chr4:6392276 ) and the low leaf Na+ accession Col-0 ( containing a C at Chr4:6392276 ) QTLs for leaf Na+ centered on AtHKT1;1 were identified in both F2 populations [27] . Such genetic evidence provides independent support that the peak of SNPs associated with leaf Na+ observed in our GWA analysis , centered at AtHKT1;1 ( Figure 2 ) , represents a true positive association and not a false positive driven by the high degree of population structure known to exist in A . thaliana [24] . Reduced expression of AtHKT1;1 in Ts-1 and Tsu-1 was concluded to drive the elevated leaf Na+ observed in these two accessions [27] . Here , we expand on this observation by establishing the strength of the AtHKT1;1 alleles in four further high Na+ accumulating accessions ( Bur-1 , Duk , PHW-20 and UKNW06-386 ) that all contain a T at Chr4:6392276 , along with a low leaf Na+ accession ( Nd-1 ) with a C at Chr4:6392276 . By examining the leaf Na+ accumulation in F1 plants from crosses of each of these accessions to Col-0hkt1-1 and Col-0HKT1 , we were able to establish a significant correlation between leaf Na+ accumulation and the strength of the AtHKT1;1 alleles ( Figure 3A ) . These crosses confirmed that all accessions tested with elevated leaf Na+ , and that contain a T at Chr4:6392276 , have hypofunctional alleles of AtHKT1;1 relative to the Col-0 allele . Furthermore , analysis of the expression of AtHKT1;1 in the same set of accessions revealed that allelic variation in AtHKT1;1 strength is modulated at the level of gene expression ( Figure 3B ) , consistent with what was previously observed for Ts-1 and Tsu-1 [27] . Though the SNP most significantly associated with leaf Na+ ( Chr4:6392276 ) is unlikely to be causal for these AtHKT1;1 expression level polymorphisms , this SNP can be used as a linked genetic marker to determine the type of AtHKT1;1 allele present , with a T at this SNP being associated with weak AtHKT1;1 alleles . Using the SNP at Chr4:6392276 as a genetic marker for the type of AtHKT1;1 allele ( strong or weak ) allowed us to test the hypothesis that the leaf Na+ soil salinity cline we observe in European populations of A . thaliana ( Figure 1A and 1B ) is associated with weak alleles of AtHKT1;1 . By comparing the means of distances to the coast , or known saline soil , for the collection site of all 300 accessions with and without a T at Chr4:6392276 , we determined that a significant association ( parametric test p-value = 0 . 0001; non-parametric Wilcoxon rank-sum test p-value = 0 . 0062 ) exists between A . thaliana growing on potentially saline impacted soils and the presence of a weak allele of AtHKT1;1 ( Figure 1A and 1B ) . Such a strong correlation between the presence of allelic variation at AtHKT1;1 known to drive elevated leaf Na+ , and the observed cline in leaf Na+ and saline soils , is evidence for the involvement of AtHKT1;1 in determining this geographical distribution . Furthermore , using 13 SNPs within a 20kb region centered on HKT1;1 to define the HKT1;1 haplotype , we identify 7 haplotypes ( 6 if you combine haplotypes with only 1 SNP different ) in accessions with high leaf Na+ ( >2 , 500 ppm ) , suggesting that weak alleles of HKT1;1 have arisen independently multiple times . However , to be credible it is also important to provide evidence that selection for growth on saline soils could be acting on the phenotype driven by allelic variation at AtHKT1;1; in this case elevated leaf Na+ . Such evidence is provided by the previous observation that the weak allele of AtHKT1;1 in the coastal Tsu-1 A . thaliana accession not only causes elevated leaf Na+ but is also genetically linked to the elevated salinity tolerance of this accession [27] . In A . thaliana AtHKT1;1 functions to unload Na+ from xylem vessels in the root , controlling translocation and accumulation of Na+ in the shoots [26] , [28] . Therefore , modulation of its function would allow the balancing of Na+ accumulation in the shoot with soil salinity . We note here that the hkt1-1 null mutation in the Col-0 background causes plants to exhibit dramatic leaf Na+ hyperaccumulation and increased NaCl sensitivity [29] , [30] . We interpret this to mean that expression of AtHKT1;1 in the hkt1-1 null mutant is reduced to such an extent that leaf Na+ accumulation saturates the capacity for cellular detoxification of Na+ by vacuolar compartmentalization . We propose that the naturally occurring weak alleles of AtHKT1;1 , that we show are associated with populations growing in potentially saline impacted environments , allow sufficient Na+ to accumulate in leaves for osmotic adjustment , conferring elevated Na+ tolerance . However , these weak , but not complete loss-of-function AtHKT1;1 alleles , do not saturate the mechanism whereby the accessions avoid Na+ cytotoxicity . The basis of this Na+ detoxification mechanism remains to be determined , though an active leaf vacuolar Na+ compartmentalization mechanism driven by AtNHX1 is one likely candidate . In conclusion , here we provide evidence supporting the involvement of specific cis-regulatory polymorphisms at AtHKT1;1 in the potentially adaptive cline in leaf Na+ accumulation capacity we observe in A . thaliana populations to saline impacted environments . We have identified a strong association between the AtHKT1;1 allele frequency in A . thaliana populations and their growth on potentially saline impacted soils ( Figure 1A and 1B ) . Further , we have confirmed by GWA mapping , experimental complementation crosses , and gene expression studies , that this allelic variation directly causes changes in the clinally varying leaf Na+ accumulation phenotype via cis-regulatory polymorphisms ( Figure 2 and Figure 3 ) . And , finally , we have previously established that the weak AtHKT1;1 alleles we show to be associated with potentially saline soils , are also linked to elevated salinity tolerance [27] , providing a plausible mechanistic link between selection for growth on saline soils and variation in AtHKT1;1 allele frequency . Such discoveries provide tantalizing evidence that points to selection acting at AtHKT1;1 in natural populations of A . thaliana in adaptation to growth in saline environments .
Plants were grown in a controlled environment with 10 h light/14 h dark ( 90 µmol m−2s−1 photosynthetically active light ) and 19 to 22°C , as previously described [31] . Briefly , seeds were sown onto moist soil ( Promix; Premier Horticulture ) in 10 . 5″×21″ 20 row trays with various elements added to the soil at subtoxic concentrations ( As , Cd , Co , Li , Ni , Rb , and Se [31] ) and the tray placed at 4°C for 3 days to stratify the seeds and help synchronize germination . Each tray contained 108 plants , six plants each from 18 accessions , with three plants of each accession planted in two different parts of the tray . Each tray contained four common accessions ( Col-0 , Cvi-0 , Fab-2 and Ts-1 ) used as controls , and 14 test accessions . Trays were bottom-watered twice per week with 0 . 25-strength Hoagland solution in which Fe was replaced with 10 µM Fe-HBED[N , N′-di ( 2-hydroxybenzyl ) ethylenediamine-N , N′-diacetic acid monohydrochloride hydrate; Strem Chemicals , Inc . ) . After 5 weeks plants were non-destructively sampled by removing one or two leaves and the elemental composition of the tissue analyzed by Inductively Couple Plasma Mass Spectroscopy ( ICP-MS ) . The plant material was rinsed with 18 MΩ water and placed into Pyrex digestion tubes . For complementation experiments plants were crossed to Col-0 or Col-0hkt1-1 and approximately 12 F1 plants were grown in the conditions described above . A set of 360 A . thaliana accessions were selected from 5 , 810 worldwide accessions to minimizing redundancy and close family relatedness , based on the genotypes at 149 SNPs developed in a previous study [32] . Figure S1 and Table S1 show the genetic variation in the core set of 360 accessions vs . a random set of 360 accessions chosen from the genotyped 5 , 810 accessions . From the selected core set of 360 accessions a subset of 349 were phenotyped using ICP-MS , and of these 337 were genotyped using the Affymetrix SNP-tilling array Atsnptile1 which contains probe sets for 248 , 584 SNPs . Details of the SNP-tilling array and methods for array hybridization and SNP-calling are the same as previously described [24] . In brief , approximately 250 ng of genomic DNA was labeled using the BioPrime DNA labeling system ( Invitrogen ) and 16 µg of the labelled product hybridized to each array . SNPs were called using the Oligo package after slight modifications . Quality control ( QC ) of the genotypes , and imputation of the missing SNPs were performed following the procedure previously described [24] , except that a 15% mismatch rate was used to filter out low quality arrays . After QC and imputation , the 337 accessions had genotypes for at least 213 , 497 SNPs . The core set of 360 accessions selected are all available from the Arabidopsis Biological Resource Center ( http://abrc . osu . edu/ ) , and the SNP genotypes for the 337 accessions used for the GWA study are available from http://borevitzlab . uchicago . edu/resources/genetic/hapmap/BaxterCore/ . Samples were analyzed as described by Lahner et al . [31] . Tissue samples were dried at 92°C for 20 h in Pyrex tubes ( 16×100 mm ) to yield approximately 2–4 mg of tissue for elemental analysis . After cooling , seven of the 108 samples from each sample set were weighed . All samples were digested with 0 . 7 ml of concentrated nitric acid ( OmniTrace; VWR Scientific Products ) , and diluted to 6 . 0 ml with 18 MΩ water . Elemental analysis was performed with an ICP-MS ( Elan DRCe; PerkinElmer ) for Li , B , Na , Mg , P , S , K , Ca , Mn , Fe , Co , Ni , Cu , Zn , As , Se , Rb , Mo , and Cd . A liquid reference material composed of pooled samples of A . thaliana leaves was run every 9th sample to correct for ICP-MS run to run variation and within-run drift . All samples were normalized to the calculated weights , as determined with an iterative algorithm using the best-measured elements , the weights of the seven weighed samples , and the solution concentrations , implemented in the Purdue Ionomics Information Management System ( PiiMS ) [33] ( for a full description see www . ionomicshub . org ) . Data for all elements is available for viewing and download at www . ionomicshub . org in trays 1478–1504 . To quantify the levels of AtHKT1;1 mRNA in roots of the various accessions studied , we used a protocol similar to that of Rus et al . [27] . Roots from plants grown under identical conditions to those used for ICP-MS analysis were separated from the shoots and rinsed thoroughly with deionized water to remove any soil contamination . The samples were frozen in liquid nitrogen and stored at −80°C until extraction . Total RNA was extracted , and DNase digestion was performed during the extraction , using the Invitrogen PureLink RNA Mini Kit . Two micrograms of total RNA were used as a template to synthesize first-strand cDNA with random hexamers , using SuperScript II Reverse Transcriptase ( Invitrogen Life Technologies ) . Quantitative real-time PCR ( qRT-PCR ) was performed with first strand cDNA as a template on four technical replicates from three independent biological samples for each accession , using a sequence detector system ( StepOne Plus , Applied Biosystems ) . For normalization across samples within a qRT-PCR run the expression of the Actin 1 gene ( At2g37620 ) was used with the following primers: CPRD66 , 5′-TGG AAC TGG AAT GGT TAA GGC TG-3′ and CPRD67 , 5′-TCT CCA GAG TCG AGC ACA ATA C-3′ . For quantification of AtHKT1;1 the following primers were used: HKT-RTF , 5′-TGG GAT CTT ATA ATT CGG ACA GTT C-3′ and HKT-RTR , 5′-GAT AAG ACC CTC GCG ATA ATC AGT-3′ . The fold induction relative to AtHKT1;1 expression in Col-0 roots was calculated following the method of Livak and Schmittgen [34] . CT values were determined based on efficiency of amplification . The mean CT values were normalized against the corresponding Actin 1 gene and ΔCT values calculated as CTAtHKT1;1–CTActin 1 . The expression of AtHKT1;1 was calculated using the 2∧ ( ΔCT ) method [34] . To normalize between samples analyzed in separate qRT-PCR runs , we divided the ΔCT for each line by the ΔCT of Col-0 roots in that run . ICP-MS measurements below zero and extreme outliers ( those values that were greater than the 90th percentile + percentile ) within each tray were removed . To account for variation in the growth environment , the four control accessions included in each tray were used to create a tray specific normalization factor . Briefly , for each element , each control accession in a given tray was compared to the overall average for that accession across all trays to obtain an element×line×tray specific normalization factor . The four element×line×tray factors in a give tray were then averaged to create a tray×element normalization factor for the tray . Every value for the element in the tray was then multiplied by the normalization factor . See Figure S2 for data of control accessions before and after the normalization . The mean of each accession was then used for all subsequent analysis . Normalized Na+ values and their frequency distribution can be found in Dataset S1 and Figure S3 . Genotype calls for all 349 accessions were obtained using the methods previously described [24] . GWA analysis was done with correction for confounding using a mixed-model that uses a genetic random effect with a fixed covariance structure to account for population structure [25] implemented in the program EMMA [24] . The contribution of the best performing SNP ( C or T at Chr4:6392276 = isT ) was checked using un-normalized Na+ data and the linear model: ( 1 ) using the lm and anova functions from R v2 . 9 . 1 . The control accessions were excluded from this analysis . The output of the statistical model can be found in Text S1 . Although the samples were nested in trays , Figure S4 indicates that the best performing SNP is essentially evenly distributed across all trays . The geographical location of each accession was obtained from TAIR ( www . arabidopsis . org ) . When processing the original data , we found an inconsistency for one of the high-Na accessions , CS28373 ( also known as Jm-1 ) . The listed latitude and longitude ( 49 , 15 ) of the accession do not match the location name “Jamolice” from where this accession was collected . The town Jamolice is located at 49 . 0721283 latitude and 16 . 2532139 longitude ( http://www . gpsvisualizer . com/geocode ) . In the interests of consistency , we used the original coordinates , although altering the location did not materially change the analysis . The distance to the coast or saline/sodic areas was calculated by obtaining the longitudes and latitudes of the shoreline/coast from the National Oceanic and Atmospheric Administration's National Geophysical Data Center ( NOAAs NGDC http://www . ngdc . noaa . gov/ngdc . html ) and the saline and sodic soils data from the European Soils database [23] . The pointDistance function in R 2 . 10 . 0 and the package raster were used to calculate the Great-circle distance to the shoreline or saline/sodic areas . We created a variable ( toSeaSal ) representing the shortest distance from the target accession to the shoreline/coast or saline/sodic area . The accession coordinates , distance to sea , distance to saline environment and SNP genotype at Chr4:6392276 can all be found in Dataset S1 . The method used to collect accessions and assemble the population might introduce unintended confounding effects that violate the assumption of independent locations used by our models . To determine whether the locations of the accessions were spatially dependent we performed a Mantel test [35] on the distances from the 300 accessions to the coast or known saline/sodic areas . The simulated p-values of 50 permutations tests with 999 repeatedly simulated samples are 0 . 996 , indicating that an assumption of independency for the response variable toSeaSal is acceptable . To test for associations between leaf Na+ ( Na ) , genotype at the highest scoring SNP ( C or T at Chr4:6392276 = isT ) , and the distance to the nearest coast or saline/sodic area ( toSeaSal ) , we used the package lm in R 2 . 10 . 0 to fit linear models , with the weights determined by the following approach . First , to quantify the strength of the relationship between toSeaSal and the leaf sodium Na , we fit the data into a linear model and regressed toSeaSal on Na . ( 2 ) Second , we applied a regression approach to single-factor analysis [36] between toSeaSal and isT and tested if the average distance to coast or saline/sodic areas of samples having the high Na T allele is significantly different from the average of samples having the C allele . ( 3 ) Finally , we regressed toSeaSal on the interaction between Na and isT to inspect how the two predictors jointly affect the distance to sea or saline/sodic . ( 4 ) To perform the significance tests on the linear coefficients , Na should be centered at the mean [36] . The extent of variation of distances to saline environments changes with both leaf Na+ concentrations and genotypes ( Figure S5 ) . Therefore , all three models account for this heterogeneity of variation , and parameters of the models are fitted using weighted least squares . The variances of the error terms in equation 2 , 3 , and 4 are not constant , and are related to the predictors according to the diagnosis on the model residuals . The models were fit using iterative weighted least squares [36] . In addition to the parametric test ( model 3 ) , we performed a non-parametric test ( Wilcoxon rank-sum test or Wilcoxon-Mann-Whitney test [37] ) using the wilcox . test function in R package stats , to assess whether toSeaSal is higher in the lines with the T allele than those with the C allele at Chr4:6392276 . The p-value of the Wilcoxon rank-sum test is 0 . 006224 indicating that both the parametric and non-parametric approaches reach the same conclusion . The statistical output of all models can be found in Text S1 .
|
The unusual geographical distribution of certain animal and plant species has provided puzzling questions to the scientific community regarding the interrelationship of evolutionary and geographic histories for generations . With DNA sequencing , such puzzles have now extended to the geographical distribution of genetic variation within a species . Here , we explain one such puzzle in the European population of Arabidopsis thaliana , where we find that a version of a gene encoding for a sodium-transporter with reduced function is almost uniquely found in populations of this plant growing close to the coast or on known saline soils . This version of the gene has previously been linked with elevated salinity tolerance , and its unusual distribution in populations of plants growing in coastal regions and on saline soils suggests that it is playing a role in adapting these plants to the elevated salinity of their local environment .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"genetics",
"and",
"genomics/functional",
"genomics",
"plant",
"biology/plant-environment",
"interactions",
"evolutionary",
"biology/plant",
"genetics",
"and",
"gene",
"expression",
"ecology/spatial",
"and",
"landscape",
"ecology",
"plant",
"biology/plant",
"genetics",
"and",
"gene",
"expression",
"genetics",
"and",
"genomics/population",
"genetics"
] |
2010
|
A Coastal Cline in Sodium Accumulation in Arabidopsis thaliana Is Driven by Natural Variation of the Sodium Transporter AtHKT1;1
|
Genetic exchange is a powerful tool to study gene function in microorganisms . Here , we tested the feasibility of generating Leishmania hybrids by electroporating genomic DNA of donor cells into recipient Leishmania parasites . The donor DNA was marked with a drug resistance marker facilitating the selection of DNA transfer into the recipient cells . The transferred DNA was integrated exclusively at homologous locus and was as large as 45 kb . The independent generation of L . infantum hybrids with L . major sequences was possible for several chromosomal regions . Interfering with the mismatch repair machinery by inactivating the MSH2 gene enabled an increased efficiency of recombination between divergent sequences , hence favouring the selection of hybrids between species . Hybrids were shown to acquire the phenotype derived from the donor cells , as demonstrated for the transfer of drug resistance genes from L . major into L . infantum . The described method is a first step allowing the generation of in vitro hybrids for testing gene functions in a natural genomic context in the parasite Leishmania .
Leishmaniasis is a complex of diseases caused by parasites of the genus Leishmania for which there is an estimated 12 million people infected in tropical and subtropical areas of the world [1] . The clinical manifestations of the disease are often correlated with the infecting Leishmania species and range from self-healing cutaneous sores ( cutaneous leishmaniasis ) to deadly visceral pathologies ( visceral leishmaniasis ) [1] . The Leishmania genomes are characterized by a high degree of gene synteny and contain a surprisingly low number of species-specific genes relative to clinical diversity [2] , [3] . While Leishmania parasites are usually considered as diploid , recent evidence revealed a sizable variation in chromosome copy numbers between species [3] , [4] . Hence , the tropism of leishmaniasis is likely to come from a combination of species-specific genes identified to date [2] , [5] and from differences in gene copy number and expression between species [6] , [7] . The occurrence of a sexual cycle for Leishmania has long been debated but the abundance of hybrid parasites described in nature [8]–[10] suggested that the exchange of genetic material can occur in the field . These observations received experimental confirmations where genetic crosses were made between Leishmania strains in the sand fly vector [11]–[13] . While powerful , achieving the generation of hybrid parasites in vitro would bring a distinct advantage for studying the contribution of genetic loci to the expression of particular phenotypic traits . Since its inception in the early 90's , gene transformation by electroporation has changed the field of parasitology , enabling constant progress in reverse genetic tools . However , these tools allow functional studies mostly at the level of single genes , at least in the natural genomic context [14] . Also , highly homologous sequences are required between the donor and recipient DNAs for successful recombination in Leishmania [15] , which prevent , in general , the use of single constructs for inactivating the same genes in different species . Cross-species gene replacement was nonetheless described once in L . donovani [16] . Given the frequency of hybrid parasites in the field and their importance in shaping Leishmania population's heterogeneity , we assessed the possibility of generating cross-species recombinants in vitro by heterologous genomic DNA ( gDNA ) transfection . We describe a knock-in protocol based on whole genome transformation ( WGT ) that will be useful for studying the role of species-specific genomic loci and of nucleotide polymorphisms pertaining to the biology of Leishmania . We show that genomic regions up to 45 kb can be selectively transferred between Leishmania species and that inactivating the mismatch repair gene MSH2 can further facilitate the recovery of cross-species hybrids .
L . major Friedlin , L . infantum JPCM5 and L . infantum ( MHOM/MA/67/ITMAP-263 ) promastigotes were grown at 25°C in SDM-79 medium supplemented with 10% heat inactivated fetal bovine serum and 10 µg/ml hemin . Transfectants were selected with 300 µg/ml of hygromycin ( HYG ) ; 1 , 500 µg/ml of paromomycin ( PM ) ; 100 µg/ml of blasticidin ( BLA ) ; 120 µg/ml of puromycin ( PUR ) ; or 40 µg/ml of neomycin ( NEO ) . Electroporation was done in 2-mm cuvette using 400 µl of cells ( 1×108 of parasites ) resuspended in HEPES-NaCl buffer [17] at 500 µF , 450 V ( 2 . 25 kV/cm ) as previously described [18] . Transfection efficiency was evaluated by transfecting 1×108 parasites with 20 µg of gDNA or 5 µg of linear digested DNA , taking into account the number of colonies obtained and the number of parasites transfected . Following electroporation , parasites were grown in drug-free media overnight and then plated on SDM-agar ( 1% Noble Agar , Nunc . ) containing the appropriate drug using the same concentration as in liquid SDM-79 medium . Colonies were counted from SDM-agar plates after growing 10 to 14 days at 25°C and the transformation efficiencies expressed per 10 µg of DNA . The L . major Friedlin MF80 . 3 mutant was selected from a cloned parental population using a stepwise selection until they were resistant to 80 µM of miltefosine ( MF ) [19] . Miltefosine ( MF ) was purchased from Cayman Chemical ( Ann Harbor , USA ) and trivalent antimony ( SbIII ) was purchased from Sigma ( Saint Louis , USA ) . N-methyl-N′-nitro-N-nitrosoniguanidine ( MNNG ) was purchased from Sigma ( Saint Louis , USA ) and was dissolved in 100% DMSO . Growth curves were obtained by measuring absorbance at 600 nm as previously described [20] . Total DNA was isolated using DNAzol reagent ( Invitrogen ) as recommended by the manufacturer . For quantitative Southern blots , the genomic DNA was digested with appropriate restriction enzymes and migrated in 0 . 8% agarose gels . Southern blots , hybridizations and washes were performed following standard protocols [21] . For every gene inactivation cassette , two pairs of primers were used to amplify regions of 500–600 bp upstream and downstream of the target gene . These DNAs were then fused to the NEO , HYG or BLA genes by overlap extension PCR [22] , [23] . After electroporation , the integration of the inactivation cassette was confirmed by PCR and Southern blots . The inactivation of the gene pyridoxal kinase ( LmjF30 . 1250 ) in L . major was previously described [19] . The pSP72-αBLAα-LRP plasmid was generated by cloning the Leucine Rich Repeat Protein ( LRP ) gene amplified from L . major with primer F-LRP ( 5′ GCG GATATCGCTGTTGGTGTTCGTGTCGTC ) and Primer R-LRP ( 5′ GCG ATCGATCAGAGGCGGAGTGGGCTGTCC ) into EcoRV and ClaI restriction sites of the pSP72-αBLAα- vector . The pSP-αPURα-MSH2 plasmid was generated by cloning the MSH2 gene amplified from L . infantum with primer F-MSH2 ( 5′ CGCTCTAGACGCACATGCACCTACGCACG ) and Primer R-MSH2 ( 5′ CGCTCTAGACAAACAAGGATAGCGAGAAG ) into the single XbaI restriction site of the psp72-αPURα vector . All the primers used for these constructs are listed in Table S1 . The pulse field gel electrophoresis was performed as previously described [24] . Briefly , we prepared low-melting point agarose blocks containing Leishmania parasites resuspended in HEPES buffer at a cell density of 1×108 parasites/ml . Parasites were lysed by incubating the blocks in lysis buffer ( 0 . 5 M EDTA [pH 9 . 5]; 1% SLS; 50 mg/ml of proteinase K ) . Chromosomes were resolved by a BioRad ( Hercules , California , USA ) contour-clamped homogeneous electric field ( CHEF ) mapper at a constant temperature of 14°C . Saccharomyces cerevisiae chromosomes were used as molecular weight markers . Chromosomes were revealed by ethidium bromide staining . Multilocus sequencing analyses were performed with Leishmania hybrids by amplifying the genes located in the vicinity of the integrated selection marker using primers specific for genomic regions conserved between L . major and L . infantum . Primers were designed with Primer3 [25] and are listed in Table S2 . PCR products were amplified using Phusion High Fidelity DNA polymerase ( New England Biolabs , Inc . ) and sequenced by conventional Sanger sequencing . Sequences were analyzed with the Lasergene software ( DNASTAR , Inc . ) and compared to the L . major and L . infantum sequences available at GeneDB ( www . genedb . org ) . Genomic DNAs were prepared from mid-log phase cultures of L . infantum 263 transfected with gDNA derived from L . major MF80 . 3ΔLmjF13 . 1540::NEO/LmjF13 . 1540 and from the clone 1 of L . infantum JPCM5 transfected with gDNA derived from L . major LmΔLRP::NEO/LRP as previously described [26] . Their sequences were determined by Illumina HiSeq1000 101-nucleotides paired-end reads which assembled into 4849 and 2774 contigs of at least 500 nucleotides for the L . infantum 263 and L . infantum JPCM5 hybrids , respectively . Sequence reads from each hybrid were aligned to the reference genome L . infantum JPCM5 [2] available at TriTrypDB ( version 4 . 0 ) [27] using the software bwa ( bwa aln , version 0 . 5 . 9 ) with default parameters [28] . The maximum number of mismatches was 4 , the seed length was 32 and 2 mismatches were allowed within the seed . The detection of single nucleotide polymorphisms ( SNPs ) was performed using samtools ( version 0 . 1 . 18 ) , bcftools ( distributed with samtools ) and vcfutils . pl ( distributed with samtools ) [29] , with a minimum of three reads to call a potential variation prior to further analysis . The sequence data are available at the EMBL European Nucleotide Archive ( http://www . ebi . ac . uk/ena ) , accession number ERP001431 ( samples ERS138995 and ERS138996 corresponding to the L . infantum 263 hybrid transfected with gDNA derived from LmMF80 . 3ΔLmjF13 . 1540::NEO/LmjF13 . 1540 and the L . infantum JPCM5 hybrid transfected with LmΔLRP::NEO/LRP gDNA , respectively ) . Several python ( version 2 . 4 . 3 ) scripts and bash ( version 3 . 2 ) scripts were created to further analyze the data . The quality assessment software samstat ( v1 . 08 ) was used to generate quality reports [30] .
Our work was carried out with L . major and L . infantum , two species respectively responsible for cutaneous and visceral leishmaniasis that have an estimated 20–100 million years of divergence [31] , [32] . Our strategy for selecting hybrid parasites was to introduce selectable markers ( usually the NEO gene ) into specific L . major genes , to electroporate total gDNA extracted from these recombinant parasites into recipient cells and to recover recombinant hybrids thriving under selection pressure . The first locus that was studied encodes for a leucine rich repeat protein ( LRP ) on chromosome 34 ( LmjF34 . 0550 ) that we showed to be involved in resistance to antimonials [33] , the chemotherapeutic mainstay against Leishmania . We generated mutants haploid for LRP by inserting NEO cassettes made to target either the LRP gene of L . major Friedlin ( LmjF34 . 0550 ) or L . infantum strain 263 ( LinJ34_V3 . 0570 ) ( Figure 1 ) , giving rise to the LmΔLRP::NEO/LRP and Li263ΔLRP::NEO/LRP haploid lines , respectively ( Figure 1B , 1D , lanes 2 ) . We also successfully obtained LRP null mutants for both species ( LmΔLRP::NEO/NEO and Li263ΔLRP::NEO/NEO ) by loss of heterozygosity [34] after one round of allelic inactivation and higher drug selection ( Figure 1B , 1D , lanes 3 ) . Consistent with the role of LRP in antimonial resistance , the LmΔLRP::NEO/NEO and Li263ΔLRP::NEO/NEO mutants were more sensitive to antimonials ( Figure 1 and data not shown ) . We also generated haploid mutants for genes present on chromosome 1 ( LmjF01 . 0315 ) , 5 ( LmjF05 . 0610 ) , 13 ( LmjF13 . 1540 ) and 30 ( LmjF30 . 1250 ) of L . major Friedlin . With the exception of the L . major LmΔPK::NEO/PK mutant haploid for LmjF30 . 1250 ( pyridoxal kinase gene ) that has already been published [19] , all other single NEO disruptions were generated for this study and molecular evidence for the haploid mutants can be found in Figure S1 . Whole genome transformation ( WGT ) has proven useful when working with naturally transformable microorganisms [35] , [36] and electroporation was tested for rendering Leishmania cells competent to receive total gDNAs from other Leishmania strains . We first electroporated total gDNA derived from L . infantum Li263ΔLRP::NEO/LRP into wild-type ( WT ) L . infantum 263 recipients cells and recovered recombinant clones resistant to paromomycin , a drug for which NEO bestows resistance . The NEO marker integrated at the appropriate locus in most clones ( Table 1 ) , as determined by Southern blot analysis of digested DNA ( data not shown ) but also of chromosome sized blots since a NEO probe hybridized to chromosome 34 in recombinant clones but not in the initial L . infantum 263 WT cells ( Figure 2A , lanes 1 and 2 ) . Similar results were obtained for L . major Friedlin , where electroporation of gDNA derived from L . major LmΔLRP::NEO/LRP single disruptant into L . major Friedlin WT parasites led to transfectants growing in the presence of paromomycin ( data not shown ) . Again , the NEO gene integrated properly at chromosome 34 in the recovered recombinants , as determined by Southern blot analysis of chromosome sized blots ( data not shown ) . We also succeeded in electroporating total gDNA derived from L . infantum Li263ΔLRP::NEO/LRP into L . infantum JPCM5 WT recipients and isolated recombinants which have integrated the NEO marker at the level of chromosome 34 ( Figure 2A , compare lanes 5 and 6 ) . The latter results indicated that gDNAs electroporated in Leishmania can integrate at homologous loci , at least in the same strains or species . We then tested whether we could cross the species barrier and electroporated total gDNA derived from L . major LmΔLRP::NEO/LRP into either L . infantum 263 or JPCM5 WT cells . This indeed seemed to have occurred since a NEO marker was found to have integrated at the proper chromosome in both L . infantum strains ( Figure 2A , lanes 3 and 7 ) . This is significant as the construct used for inactivating the targeted allele is species-specific but the use of gDNAs allowed crossing the species barrier . The integration of the NEO marker into the homologous locus did not occur in all transfectant clones however , as the smear obtained in PFGE blots for one L . infantum 263 transfectant suggested a circularization of a NEO containing DNA fragments ( Figure 2A , lane 4 ) . This was indeed confirmed by the recovery of circular episomes from this transfectant by alkaline lysis ( data not shown ) . In most transformation experiments the majority of clones had donor DNA integrated but episomal DNA was also observed in other clones ( Table 1 ) . While L . major and L . infantum are highly syntenic [2] , there are nonetheless differences between homologous genes at the nucleotide level ( mean 90% genome identity ) and we capitalized on these natural single nucleotide polymorphisms ( SNPs ) to measure the extent of exchanged DNA between both species . By targeted sequencing of genomic regions located upstream and downstream of the NEO gene in one hybrid clone of L . infantum 263 and two hybrid clones of L . infantum JPCM5 , we could infer that DNA fragments ranging from 20 kb to 40 kb were exchanged at the LRP locus between L . major and L . infantum ( Figure 2B ) . For example , when we sequenced the LmjF34 . 0540 gene ( LinJ34_V3 . 0560 ) in the 263 hybrid clone 1 we found an hybrid sequence with one allele with L . major and one allele with L . infantum sequences ( Table S3 ) . Sequencing of PCR fragments was done similarly with genes upstream and downstream of LinJ34_V3 . 0560 to find the first genes ( LinJ34_V3 . 0530 and LinJ34_V3 . 0630 ) upstream and downstream NEO with exclusively L . infantum sequences . The genes in between were hybrids between L . infantum and L . major ( Table S3 ) . In this specific hybrid transfectant , the contiguous DNA transferred was estimated to be at least 40 kb . We used a similar strategy of multilocus sequencing to characterize the extent of DNA exchange in the hybrids JPCM5 clone 1 ( Table S4 ) and clone 2 ( Table S5 ) . Interestingly , both L . infantum alleles were replaced by the L . major sequences in the JPCM5 clone 1 hybrid parasite , most probably by loss of heterozigocity ( Figure 2B and Table S4 ) . We also performed paired-ends next generation sequencing of the whole genome of the L . infantum JPCM5 hybrid clone 1 . Sequence analysis revealed a single stretch of 1055 SNPs ( 381 within coding sequences ) derived from L . major that spanned positions 212 , 950 to 234 , 918 ( 48 SNPs/kb ) . In contrast , only 131 SNPs were detected for the rest of the 1 . 8 Mb sequence of chromosome 34 upstream and downstream of the integrated L . major DNA fragment ( 0 . 07 SNP/kb ) . Most importantly , analysis of the sequenced genome revealed that no other genomic fragments derived from L . major Friedlin were co-transferred elsewhere in the genome ( Figure 2B , hybrid JPCM5 ( 1 ) ) . Thus , targeted sequencing confirmed that we could generate L . infantum hybrid parasites containing up to 40 kb of contiguous L . major Friedlin sequence and whole genome sequencing confirmed this and also informed that no other DNAs inserted elsewhere in the genome . The integration was stable and maintained in the absence of selective pressure ( not shown ) . Importantly , hybrids acquired the phenotype of the donor cells since every L . infantum 263 or L . infantum JPCM5 hybrid clones with a LRP/NEO integrated DNA had an increased sensitivity to SbIII ( Figure 1F and data not shown ) . The ability to select for the integration of NEO-marked gDNA from L . major into L . infantum recipients was not unique to the LRP locus . We recently inactivated one allele of the pyridoxal kinase gene in L . major ( LmjF30 . 1250 ) [19] and the electroporation of gDNA derived from this haploid mutant ( LmΔPK::NEO/PK ) into L . infantum 263 and JPCM5 WT cells allowed recovering hybrid transfectants thriving under paromomycin pressure . Hybridization of chromosome sized blots confirmed the proper integration at the level of chromosome 30 ( Figure 3A ) and targeted sequencing of individual genes upstream and downstream of the NEO marker in both L . infantum hybrid strains ( Tables S6 and S7 ) estimated that DNA fragments of 12 and 18 kb derived from L . major Friedlin had been exchanged at the PK locus of both L . infantum strains ( Figure 3D ) . In the L . infantum 263 recipient , we observed both integration at the level of the chromosomal locus and a circular amplicon ( Figure 3A , lane 2 ) . To test the generality of hybrid formation , we generated haploid L . major Friedlin mutants for the LmjF01 . 0315 ( LmΔLmjF01 . 0315::NEO/LmjF01 . 0315 ) or LmjF05 . 0610 ( LmΔLmjF05 . 0610::NEO/LmjF05 . 0610 ) genes ( Figure S1 ) , both coding for proteins of unknown function . Electroporating L . infantum 263 WT cells with gDNA derived from LmΔ01 . 0315::NEO/LmjF01 . 0315 yielded paromomycin-resistant hybrids that had properly integrated the NEO gene at the level of chromosome 1 ( Figure 3B , lane 4 ) . Using our targeted DNA sequencing approach of individual genes around the NEO marker ( Table S8 ) , we could estimate that a 40 kb contiguous L . major DNA fragment replaced the L . infantum sequence in one allele ( Figure 3E ) . Two bands were observed when hybridizing with the probe specific to chromosome 1 ( Figure 3B ) , but this is probably related to the size polymorphism already reported for this chromosome [37] . It is hence probable that the NEO marker integrated in the chromosome with higher molecular weight ( Figure 3B , lane 4 ) . The integration of the NEO marker did not occur in the chromosome 1 of L . infantum JPCM5 however , as the smear obtained in PFGE blots for this transfectant indicated a circularization of the NEO cassette ( Figure 3B , lane 2 ) . However , the same L . infantum cells transfected with gDNA from LmΔLmjF05 . 0610::NEO/LmjF05 . 0610 failed to lead to any transfectants ( Figure 4F ) . This suggested that hybrid formation differed between genomic loci targeted by WGT . The efficiency of generation of hybrids containing up to 40 kb of sequences from another species was found to be low . Indeed , while the efficiency of transfection for NEO disruption PCR constructs targeting single genes was calculated to be 1×10−7 , this was decreased about 10 fold when transfecting whole gDNA ( Table 1 ) . The lack of integration observed for some gDNAs , for example the gDNA derived from L . major LmΔLmjF05 . 0610::NEO/LmjF05 . 0610 into L . infantum ( Figure 4F ) , could be due to several reasons but it could possibly occur if recombination between non identical DNAs was made more permissive . We first assessed whether overexpressing the RAD-51 recombinase gene ( LinJ28_V3 . 0580 ) in L . infantum parasites [38] could increase recombination efficiency and lead more easily to hybrids but this has not been the case ( results not shown ) . We then assessed whether the generation of hybrids with heterologous DNA would be more efficient in cells impaired for the mismatch repair ( MMR ) machinery since it was showed to prevent recombination between divergent sequences [39] , [40] . In the related trypanosomatid parasite Trypanosoma brucei , the inactivation of the MMR gene MSH2 increased the efficiency of recombination between mismatched DNAs [41] . L . infantum has a single MSH2 gene ( LinJ33_V3 . 0420 ) and we generated a L . infantum 263 MSH2 null-mutant ( Li263ΔMSH2::HYG/BLA ) by two successive rounds of allelic inactivation using HYG and BLA inactivation cassettes ( Figure 4A ) conferring resistance to hygromycin and blasticidin , respectively . The inactivation of MSH2 in Li263ΔMSH2::HYG/BLA was confirmed by Southern blot analysis of restricted DNA and by PCR using specific MSH2 primers ( Figure 4B ) . A MSH2 chromosomal null mutant complemented in trans for MSH2 was also generated by transfecting Li263ΔMSH2::HYG/BLA with the rescue plasmid pSP72αPURα-MSH2 ( data not shown ) . Impairing with the MMR machinery is usually associated with an increased tolerance to N-methyl-N′-nitro-N-nitrosoniguanidine ( MNNG ) , an alkylating agent that interferes with the proper replication of DNA by methylating the O6 position of guanine . While the L . infantum MSH2-deficient line had no significant growth difference in comparison to wild-type cells , we observed a small but significant increase in resistance to MNNG ( Figure S2 ) . Interestingly , the MSH2 null mutant was more proficient in recombination for small heterologous linear DNA fragments ( Figure 4D ) but not for those using homologous fragments ( Figure 4C ) . Most importantly , the inactivation of MSH2 in L . infantum also allowed recovering a higher number of recombinants following electroporation with cross-species gDNA derived from L . major LmΔLRP::NEO/LRP ( Figure 4E ) . By sequencing PCR fragments for genes upstream and downstream of NEO ( Tables S9 and S10 ) , we could determine that fragments of 35–45 kb were transferred in two independent clones of the L . infantum MSH2 null mutant hybrids ( Figure 3F ) . Transfection in the MSH2 null mutant also allowed recovering recombinants when transfecting with gDNAs that otherwise did not led to hybrids with WT recipients . Indeed , while we could never recover paromomycin-resistant transfectants when transforming L . infantum 263 WT parasites with gDNA extracted from a L . major Friedlin line inactivated for one allele of the LmjF05 . 0610 gene ( LmΔLmjF05 . 0610::NEO/LmjF05 . 0610 ) ( Figure S1 ) , the transformation of the L . infantum MSH2 null mutants consistently yielded recombinant parasites ( Figure 4F ) . The hybridization of chromosome sized blots confirmed that the NEO gene integrated in the proper chromosome for every aforementioned WGTs ( Figure 3C ) . The described procedure could prove very useful for applications regarding the role of genomic loci or SNPs in conferring a particular phenotypic trait like virulence or drug resistance . In Leishmania , the miltefosine transporter ( MT ) is a phospholipid flippase located at the plasma membrane of the parasite [42] . Point mutations in MT are correlated to resistance to MF [19] , [42] , a drug used for the treatment of antimonial-resistant infections in endemic regions [1] . We previously showed that the L . major Friedlin LmjF-MF80 . 3 miltefosine resistant mutant has a three nucleotide deletion ( M547del ) on both alleles of its MT gene ( LmjF13 . 1530 ) [19] . The inactivating role of the mutations was inferred from transfection of episomal copies of the MT gene . In order to reconstruct MF resistance by WGT of LmjF-MF80 . 3 gDNA , one allele of the LmjF13 . 1540 gene located immediately downstream of MT on chromosome 13 was replaced by the NEO marker in LmjF-MF80 . 3 , giving rise to the LmMF80 . 3ΔLmjF13 . 1540::NEO/LmjF13 . 1540 mutant ( Figure S1C ) . The LmjF13 . 1540 gene codes for a protein of unknown function and its inactivation did not alter the MF resistance levels of LmjF-MF80 . 3 ( data not shown ) . The transfection of L . infantum 263 WT parasites with gDNA derived from LmMF80 . 3ΔLmjF13 . 1540::NEO/LmjF13 . 1540 yielded paromomycin-resistant recombinants that integrated the NEO marker on the same chromosome as the MT gene ( chromosome 13 ) ( Figure 5A ) . Multi-locus PCR sequencing of the L . infantum recombinant ( Table S11 ) estimated the size of the exchanged DNA to approximately 25 kb ( Figure 5B ) . Furthermore , degenerate primers allowing the amplification of MT from both L . major ( LmjF13 . 1530 ) and L . infantum ( LinJ13_V3 . 1590 ) were used to amplify the MT locus in one representative L . infantum hybrid and the cloning of these amplified MT fragments into the pGEM-T-easy plasmid revealed a allele frequency of 60/40% for L . infantum WT/LmjF-MF80 . 3 among E . coli clones ( Figure 5C ) . The L . infantum 263 hybrid thus integrated the M547del mutation from LmjF-MF80 . 3 on one of its MT allele while maintaining the other allele unaltered . This was confirmed by paired-ends next generation sequencing of the whole genome of this hybrid parasite , which further revealed that no other genomic fragment from LmMF80 . 3ΔLmjF13 . 1540::NEO/LmjF13 . 1540 integrated elsewhere in the genome . Whole genome sequencing revealed a single stretch of 29 , 2 kb with 541 SNPs ( 301 within coding sequences ) derived from L . major that spanned positions 596 , 277 to 625 , 504 ( 19 SNPs/kb ) on one allele of chromosome 13 that were transferred to L . infantum 263 . In contrast only 35 SNPs were detected for the rest of the 645 kb sequence of chromosome 13 upstream and downstream the integrated L . major DNA fragment ( 0 . 05 SNP/kb ) . Most importantly , and as a proof-of-principle of our facile strategy to introduce knock-ins in Leishmania , an increased resistance to MF was specifically observed for the L . infantum hybrid that acquired the M547del from LmjF-MF80 . 3 at their MT locus ( Figure 5D ) .
Homologous gene targeting is a powerful reverse genetic approach allowing to test the functions of specific gene products in trypanosomatid parasites like Leishmania [14] . However , available tools only allow performing studies at the level of genes or small DNA fragments and do not allow investigating the role of large genomic loci or of easy assessment of specific point mutations in a natural genomic context . The most critical parameters for successful homologous recombination in Leishmania are the degree of homology and the length of homologous sequences between the donor and recipient DNAs [15] . While gene content and synteny is highly conserved between species of Leishmania , the high degree of variations observed at the level of nucleotide sequences [2] , [3] usually preclude the use of unique DNA constructs for targeting homologous loci between species ( Figures 4D , 4F ) . Genetic exchange among natural populations of Leishmania has long been suspected [10] , [43] and recently received experimental confirmation [11] , with some hybrids even reported to acquire increased fitness or transmission potential [44] . In rare cases are these hybrids crossing the species barrier but natural hybrids between L . major and L . infantum have been described [10] . In this study , we describe a protocol based on WGT that enables the transfer of large DNA fragments between strains and species of Leishmania . Integrations occurred at different genomic loci on distinct chromosomes in recipient cells and up to 45 kb of heterologous gDNA was exchanged between species . Such size limitation could be due to several factors like breakage of the high molecular weight DNA during transformation or structural variations in the genome of recipient cells that would disrupt the progress of recombination . This contrasts with the genome-wide heterozygosity that seems to be happening for hybrids generated in the sand fly vector either in a natural context [10] or in experimental settings [11]–[13] . Notwithstanding , genetic crosses performed in the sand fly vector normally only delimits phenotypic traits to loci covering tens of genes and our approach should thus reveal a valuable complement for narrowing down the list of candidates . Targeted sequencing analyses indicated that recombination events took place between and within orthologous genes in hybrid recombinants , which is consistent with the extensive synteny of Leishmania genomes [2] . Interestingly , we noticed that in the two events where the whole genomes of hybrids were sequenced those recombination events occurred in regions of highest homology ( recombination sites were in regions of 95% identities while the average region was 90% identical ) . The presence of a selection marker on either one or two alleles in the donor gDNAs did not affect the efficiency of transformation ( results not shown ) but the rates of targeting were different depending on the donor and recipient strains of Leishmania . Indeed , our results are consistent with the degree of divergence at the nucleotide level between Leishmania species [2] , [45] since we were unable to obtain L . major or L . infantum hybrids when using donor gDNAs derived from two independent L . ( V . ) braziliensis lines having a NEO marker integrated at distinct genomic locations , ( result not shown ) . This correlates with the recombination events described in natural populations of Leishmania , which mainly implicates closely related species like L . major/L . infantum [10] , L . panamensis/L . braziliensis or L . panamensis/L . guyanensis [46]–[48] . We focused our transformation experiments with L . infantum as the recipient cell of heterologous DNA . We succeeded once in creating a L . major hybrid with L . infantum DNA ( results not shown ) but this was more difficult and transformation of other L . infantum gDNA donors in L . infantum never led to L . major transformants being either integrated or episomal ( data not shown ) . This may relate to the ten-fold lower efficiency of transformation of L . major [49] , [50] and one might thus be successful at obtaining L . major recombinant hybrids by improving transfection efficiencies . While we were able to recover recombinants for most of the genomic loci tested , some chromosomal locations were nonetheless targeted less efficiently . The MMR machinery plays a critical role in maintaining genetic stability by correcting for base mismatches that can arise through replication errors or chemical damage [51] and also influences the frequency of homologous recombination between divergent sequences [41] , [52] . Interestingly , interfering with the MMR machinery in Leishmania increased the number of hybrid clones for these loci less amenable to hybrid formation , probably by dimming the barriers for recombination between mismatched DNA ( Figure 4 ) . We also found a background of transfectants maintaining the selection marker as part of extrachromosomal amplicons for most loci ( Figure 2A , lane 4; Figure 3B , lane 2 , Table 1 ) . The hybridization of chromosome-sized blots from several independent hybrid clones indicated that the relative abundance of chromosomal targeting and episomal maintenance of the selection marker varied depending on the donor gDNAs but in the majority of clones , the DNA was integrated ( Table 1 ) . Extrachromosomal circles can be generated by homologous recombination between repeated genomic sequences in Leishmania [53] , [54] . It is thus likely that these circles were generated by recombination between repeated sequences present on large DNA fragments including the NEO marker . Extrachromosomal circles were not stable and were lost in the absence of selective pressure ( not shown ) . Whole genome transformation in naturally competent bacteria was shown to lead to the acquisition of several distinct donor DNA segments that optimally replace up to 3% of the genome of recipient cells [35] . This is in contrast to the unique integration events observed in the genome of Leishmania hybrids ( Figure 2B , Figure 5B ) , for which homologous recombination were restricted to genomic loci surrounding the selection marker as shown by whole genome sequencing . It may be possible to further increase the efficiency of recombination by manipulating the expression of recombination enzymes and more loci could be targeted by the use of additional selection markers in the same cell . On the other hand , this controlled recombination prevents the likelihood of phenotypic artefacts due to surrogate DNA exchange events . The method presented here is now allowing the in vitro generation of hybrid parasites allowing for testing for gene functions in a natural genomic context . This technique of hybrid formation has also the potential to be useful for other microbial pathogens .
|
Leishmania spp . are pathogenic protozoa characterized by a substantial diversity in pathogenesis and virulence despite their considerable synteny at the genome level . The existence of genetic exchange was recently proven experimentally in the sand fly vector where hybrid parasites were isolated and generated . Here , we show the feasibility of generating Leishmania hybrids by electroporating genomic DNA of donor cells into recipient Leishmania parasites . This methodology was made possible by introducing a drug resistance marker in the donor Leishmania cells that could be used for selecting recombinant recipient parasites . Integrations of exogenous DNA fragments as large as 45 kb were possible for several chromosomal regions and took place at homologous loci in recipient Leishmania strains . Our observations are the first step for the generation of in vitro hybrids for assessing gene function under natural genomic contexts and this technology may be applicable to other pathogens .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"molecular",
"cell",
"biology",
"leishmaniasis",
"biology",
"microbiology",
"parasitic",
"diseases",
"parasitology"
] |
2012
|
Generation of Leishmania Hybrids by Whole Genomic DNA Transformation
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Confirmatory diagnosis of visceral leishmaniasis ( VL ) , as well as diagnosis of relapses and test of cure , usually requires examination by microscopy of samples collected by invasive means , such as splenic , bone marrow or lymph node aspirates . This causes discomfort to patients , with risks of bleeding and iatrogenic infections , and requires technical expertise . Molecular tests have great potential for diagnosis of VL using peripheral blood , but require well-equipped facilities and trained personnel . More user-friendly , and field-amenable options are therefore needed . One method that could meet these requirements is loop-mediated isothermal amplification ( LAMP ) using the Loopamp Leishmania Detection Kit , which comes as dried down reagents that can be stored at room temperature , and allows simple visualization of results . The Loopamp Leishmania Detection Kit ( Eiken Chemical Co . , Japan ) , was evaluated in the diagnosis of VL in Sudan . A total of 198 VL suspects were tested by microscopy of lymph node aspirates ( the reference test ) , direct agglutination test-DAT ( in house production ) and rK28 antigen-based rapid diagnostic test ( OnSite Leishmania rK39-Plus , CTK Biotech , USA ) . LAMP was performed on peripheral blood ( whole blood and buffy coat ) previously processed by: i ) a direct boil and spin method , and ii ) the QIAamp DNA Mini Kit ( QIAgen ) . Ninety seven of the VL suspects were confirmed as cases by microscopy of lymph node aspirates . The sensitivity and specificity for each of the tests were: rK28 RDT 98 . 81% and 100%; DAT 88 . 10% and 78 . 22%; LAMP-boil and spin 97 . 65% and 99 . 01%; LAMP-QIAgen 100% and 99 . 01% . Due to its simplicity and high sensitivity , rK28 RDT can be used first in the diagnostic algorithm for primary VL diagnosis , the excellent performance of LAMP using peripheral blood indicates that it can be also included in the algorithm for diagnosis of VL as a simple test when parasitological confirmatory diagnosis is required in settings that are lower than the reference laboratory , avoiding the need for invasive lymph node aspiration .
Visceral leishmaniasis ( VL ) , also known as kala-azar , is a vector-borne disease caused by parasitic protozoa of the Leishmania donovani complex , which are transmitted by female sandflies . VL affects mainly children and young adults , and can be fatal if left untreated . It is characterized by fever , weight loss , wasting , and splenomegaly; lymphadenopathy is especially frequent in VL patients in Sudan , where it can be the only clinical manifestation accompanying fever [1] . Sudan ranks third among the VL high-burden countries after India and South Sudan , which together with Bangladesh , Brazil and Ethiopia account for 90% of VL cases worldwide , according to recent WHO estimates [2] . Access to accurate diagnosis is one of the main challenges for VL control in Sudan , where out of the 3 , 520 VL cases reported in 2014 , only 62% of them had a confirmatory diagnosis in the laboratory [2–4] . Usually , the first approach for laboratory diagnosis of cases suspected of VL in Sudan is serology , using either the direct agglutination test ( DAT ) or rK39-based rapid diagnostic tests ( RDT ) . The second approach is lymph node aspirate microscopy . Lymphadenopathy is an important sign in VL patients in Sudan , and enlarged nodes are usually found during clinical examination . Despite its limited sensitivity ( 52–65% ) , examination of lymph node aspirates is preferred over bone marrow or spleen aspirates because it is easier and safer , and can be performed by paramedical staff . Examination of bone marrow or splenic aspirates improves sensitivity ( 75–95% ) , but this requires experienced personnel , and should be performed in hospitals where blood transfusion is available , which might be needed in case of an adverse event . The accuracy of microscopic examination is also influenced by the ability of the laboratory technician and the quality of the reagents used . Bone marrow and splenic aspiration , however , are rarely performed in Sudan due to technical and logistical difficulties , and are limited to reference laboratories [3 , 5 , 6] . Parasite confirmation by tissue aspirate microscopy is also used for test-of-cure , since serology is useless for this purpose as anti-Leishmania antibodies remain detectable up to several years after cure [1 , 7] . Thus , this is another scenario where approaches to confirm Leishmania infection that are less invasive are required . In recent years molecular tests such as the polymerase chain reaction ( PCR ) and quantitative real-time PCR , when performed on peripheral blood , have shown high sensitivity and specificity in the diagnosis of VL and treatment monitoring [8–11] . Unfortunately , these require well-equipped facilities and trained personnel , and since in most cases in-house protocols are used , there is an important lack of standardisation , limiting their use to reference laboratories . To make molecular diagnosis available in low resource settings , more user-friendly , design-locked and field-amenable options are therefore needed . One method that could meet such criteria is loop-mediated isothermal amplification ( LAMP ) of DNA: it is performed at constant temperature ( 60–65°C ) for target DNA amplification rather than thermocycling; is highly specific , based on a set of four primers recognizing six distinct regions on the target; it has high amplification efficiency and enables amplification within a short time; results can also be visualized using simple detection methods . Therefore , LAMP has emerged as a powerful tool for point-of-care diagnosis [12 , 13] . A LAMP assay , Loopamp Leishmania Detection Kit ( Eiken Chemical Co . , Japan ) , based on dried down reagents immobilised in the reaction tube that can be stored at room temperature , was developed in a collaboration between Eiken Chemical Co . , FIND and partners . In the present study , we report on the evaluation of the performance of Loopamp Leishmania Detection Kit in the diagnosis of VL using peripheral blood in Sudan .
The study was carried out between December 2014 and February 2016 at two sites in Sudan: Bazoura Rural Hospital ( BRH ) in Gedaref State , and the Institute of Endemic Diseases ( IEND ) in Khartoum . Patients presenting themselves at BRH or referred to IEND , presenting clinical signs and symptoms suggestive of VL: fever of more than two weeks plus either weight loss , splenomegaly or lymphadenopathy , were considered VL suspects . Once malaria was ruled out by microscopy of finger prick blood films the patients were prospectively and consecutively enrolled in the study if they fulfilled additional inclusion criteria: i ) provision of informed consent and ii ) judged possible to obtain peripheral blood and lymph node aspirates . Patients with previous history of VL or being under treatment for VL , pregnant women , patients in extremis or having severe concomitant illness , and those unable to provide informed consent were excluded from the study . The sample size was designed around estimating the sensitivity of Loopamp Leishmania Detection Kit with a binomial error margin of ±8% . Assuming a prevalence of 45% and a LAMP sensitivity of 85% , we estimated that 192 VL suspects would be recruited , thus we aimed to recruit 200 VL suspects . The study was carried out in conformity with the Helsinki Declaration , and ethical approval was obtained from the Research Ethics Committee of the Institute of Endemic Diseases , University of Khartoum ( Reference N°: 1/2014 ) . Participants were informed about the objectives and procedures of the study , and benefits and risks were also explained . Written informed consent was obtained from all participants /parents or guardians in the presence of independent witnesses before collecting samples . Confidentiality was assured by assigning a study code to each participant , and patient information was kept controlled at each of the study sites following IEND requirements . The full study protocol can be accessed by request to the authors . Five ml peripheral blood was collected from each patient , both in Serum Separator and Heparin Vacutainer tubes ( Becton Dickinson ) . Buffy coat was obtained from 3 ml heparin-treated peripheral blood by centrifugation at 8 , 000 X g; the buffy coat was transferred to an Eppendorf tube and re-suspended in residual plasma to allow for a 200–250 μl volume buffy coat suspension . Whole blood , buffy coat and serum aliquots were kept at -20°C until analysis . Lymph node aspirates were taken from enlarged lymph nodes , and a Giemsa stained smear was prepared for microscopy . When collected at BRH , whole blood and serum samples were periodically transferred to IEND during the study , maintaining a cold chain . After examination , smears of lymph node aspirates were also transferred to IEND , where they were examined again . Giemsa stained smears were examined using Primo Star microscopes ( Carl Zeiss Microscopy GMBH , Germany ) . Leishmania amastigotes were confirmed under 1000x magnification . Lymph node aspirate microscopy ( LNA-M ) was considered as the reference test of the study . Serum samples ( 50 μl ) were tested with the rK28-based RDT OnSite Leishmania rK39-Plus ( CTK Biotech , Inc . , USA ) following the manufacturer’s instructions . This test is based on the rK28 antigen , a chimeric protein composed by the first two 39 amino acid repeats of the Sudanese kinesin homologue LdK39 flanked by the repeat sequences of HASPB1 ( or K26 ) and the whole open reading frame of HASPB2 ( or K9 ) [14] . Results were recorded after 15 minutes , and whenever an invalid result was obtained , the test was repeated immediately . Serum samples were tested by an in house DAT produced at IEND following the procedure described by Harith et al . [15] . Samples with a titre ≥1:3 , 200 were considered as positive . Titres of 1:800 and 1:1600 were considered as borderline . Peripheral blood samples were processed following two different methods prior to LAMP analysis: Boil & Spin: 95 μl heparin-treated whole blood or 95 μl buffy coat were mixed with 5 μl 10% SDS by inversion 10 times in a 1 . 5 ml Eppendorf tube , allowed to stand for 10 min at room temperature ( RT ) and mixed again . After adding 400 μl PCR grade H2O the mixture was incubated in a heating block at 90°C for 10 min . The mixture was spun down for 3 min at maximum speed in a bench top centrifuge ( 13 , 000 rpm ) , the supernatant was recovered and processed immediately or stored at -20°C until analysis by LAMP . QIAamp DNA Mini kit ( QIAGEN ) : 200 μl heparin-treated whole blood or 100 μl buffy coat were processed following the instructions provided in the kit . The DNA was eluted in 200 μl PCR grade water and processed immediately or stored at -20°C until analysis by LAMP . The Loopamp Leishmania Detection Kit uses primers targeting two different regions of the Leishmania genome: the 18S rRNA gene and the kDNA minicircles , and is specific to the Leishmania genus . Bst DNA polymerase is used for amplification , and the dried reagents include calcein to allow for the visual judgement of the amplified products without opening the reaction tubes . The kit includes negative and positive controls; the positive control is an artificial construct based on DNA sequences from L . donovani isolates from India and Sudan ( GenBank Accession Numbers Y11401 and X07773 ) . Three μl of the DNA obtained by the two DNA extraction methods described above were used for the LAMP reaction . This was run for 40 min at 65°C in the Loopamp LF-160 incubator ( Eiken Chemical Co . , Japan ) , the results were visualized under blue LED light illumination , using a visualization unit that is integral to the incubator . Fig 1 shows an example of positive and negative samples visualized under blue LED light illumination . LAMP reactions were performed after the other diagnostic tests , by a technician who was blinded from the results of these tests . Participants who were positive by LNA-M were considered VL cases , while all other subjects were considered non-VL cases . Epidat 3 . 0 was used to calculate sensitivity , specificity , positive and negative predictive values , and concordance between tests ( Cohen’s kappa coefficient ) [16] . The false discovery rate ( FDR ) was calculated as 1—the positive predictive value ( PPV ) and the false omission rate ( FOR ) as 1—the negative predictive value ( NPV ) , considering the calculated sensitivity and specificity . Where sensitivity or specificity was calculated to be 100% , an arbitrary value of 99 . 9% was used for illustrative purposes . The FDR and FOR were plotted against prevalences ranging from 0–100% to illustrate their change over the range of potential disease contexts . FDR and FOR were chosen as they are more directly applicable to field studies than PPV and NPV . This approach assumes that sensitivity and specificity do not change with prevalence . McNemar’s test was applied to compare data from LAMP with different sample types ( buffy coat vs . whole blood ) and sample preparation methods ( QIAgen vs . Boil & Spin ) . A STARD Checklist is provided as S1 Table .
A total of 198 VL suspects were included in the study . Fig 2 shows the workflow of testing samples from VL suspects . Only 185 VL suspects were tested by all methods , as during the process , 12 peripheral blood samples were lost for LAMP and one serum sample was lost for rK28 RDT testing . Ninety seven patients suspected of VL tested positive by LNA-M , and were thus considered as true VL cases . All other VL suspects were considered as non-cases , and therefore controls for purposes of the analysis . Table 1 shows the demographic and clinical data from the 198 patients suspected of VL that were included in the study . Most of the cases were males younger than 15 years , with lymphadenopathy ( 89 . 7% ) , splenomegaly ( 89 . 7% ) , hepatomegaly ( 66 . 0% ) and weight loss ( 54 . 6% ) as the main clinical signs and symptoms . Table 2 shows the results of the different diagnostic tests in the group of 185 VL suspects that were tested by all methods . The results were quite similar to those obtained when data from all the 198 VL suspects were analysed together ( S2 Table ) . No invalid result was recorded for the rK28 RDT , and the VL case missed by this test was found to be positive both by LAMP ( any sample and sample preparation method ) and DAT . Twelve patients had borderline results ( BL ) by DAT , eight of these were negative by microscopy , serology and LAMP , while the other four patients all had positive results in the tests applied . We conducted two separate analyses , in which we considered borderline results as either negative or positive . Of the two serological test used , the rK28 RDT presented higher sensitivity ( 98 . 81% ) and specificity ( 100% ) than DAT , considering borderline results as either negative ( 88 . 10% and 78 . 22% ) or positive ( 91 . 67% and 70 . 30% ) . The Loopamp Leishmania Detection Kit had high specificity ( 99 . 01% ) , regardless of the type of sample tested ( whole blood or buffy coat ) or the sample processing method . The sensitivity was also high , with the best results obtained with whole blood processed either by the Boil & Spin method ( 97 . 62% ) or by the QIAgen columns ( 100% ) . There were no significant differences between the sensitivities or specificities of LAMP in whole blood vs . buffy coat , being these processed either with the Boil & Spin method ( WB and BC ) or with the QIAamp DNA Mini Kit ( WB QIA and BC QIA ) , McNemar's p > 0 . 1 . At low prevalence , the performance of LAMP is similar to the RDT in terms of the numbers of false positives that are detected ( Fig 3 ) . Any of the LAMP methods as well as the RDT had a very good agreement with LNA-M ( k = 0 . 96–0 . 99 ) , while the agreement between DAT and LNA-M was inferior ( k = 0 . 60–0 . 65 , good agreement ) . More details on the concordance of the different tests are provided in S3 Table ) .
Loop-mediated isothermal amplification ( LAMP ) is a nucleic acid amplification test that combines rapidity , simplicity , and high specificity . Since the test was first developed by Notomi et al . several LAMP tests have been developed to aid in the diagnosis of infectious and hereditary diseases [12 , 13] . The WHO has recently endorsed a LAMP test developed by Eiken Chemical Co . for use in the diagnosis of tuberculosis , and another test developed by this company has shown a high performance in the diagnosis of malaria [17–19] . Takagi et al . were the first to show the feasibility of diagnosing VL and post-kala azar dermal leishmaniasis ( PKDL ) using LAMP [20] . Since then , a number of other LAMP tests have been developed and applied to different uses , including screening of Leishmania infection in sandflies , diagnosis of canine leishmaniasis and detection of human asymptomatic infection [21–25] . Kothalawala et al . used a LAMP test targeting the kDNA minicircles for the diagnosis of cutaneous leishmaniasis ( CL ) in Sri Lanka , which had 82 . 6% sensitivity and 100% specificity when compared to microscopy [26] . A lower sensitivity ( 58 . 2% ) was obtained by Nzelu et al . using a LAMP test targeting the 18S rRNA gene for the diagnosis of CL and mucocutaneous leishmaniasis in Peru , but the specificity was not determined [27] . Other studies evaluating LAMP for VL diagnosis have shown a good diagnostic performance using different types of samples , of more than 90% sensitivity and up to 100% specificity ( Table 3 ) . To the best of our knowledge , the Loopamp Leishmania Detection Kit is the first LAMP test , available as a kit , which has been evaluated for VL diagnosis . It is in a ready-to-use format , with an additional advantage of being based on dried reagents , and therefore does not need a cold chain for transport and storage . The kit has a shelf life of one year if stored between 1 and 30°C , and stability testing has shown that it remains stable for 12 months at 30°C . It contains a primer combination targeting two different regions of the Leishmania genome , which makes this test Leishmania genus specific and can be used across the different endemic regions to diagnose all forms of leishmaniasis . The rK28 RDT included in this study ( OnSite Leishmania rK39-Plus , CTK Biotech , Inc . , USA ) presented a very good diagnostic performance , 98 . 81% sensitivity and 100% specificity . Similar results were obtained by Mukhtar et al . in a previous study in Sudan , where the rK28 RDT had 94 . 5% sensitivity and 97 . 6% specificity in serum samples and 92 . 5% and 100% when using whole blood [32] . The excellent performance of rK28 RDT makes it ideal for primary diagnosis of VL . We have also shown that the performance of LAMP using peripheral blood is excellent . It is a rapid method that maintains simplicity throughout all steps , from extraction of DNA , to detection of amplification . A sensitivity and specificity of 97 . 6% and 99 . 1% can be obtained with the simple Boil & Spin method . All this indicates that Loopamp Leishmania Detection Kit can be included in the algorithm for diagnosis of VL in settings that are lower than the reference laboratory , replacing the need for invasive lymph node aspiration when parasite confirmation is needed in 97 . 6% of the cases using the Boil & Spin method for sample preparation ( 99 . 1% using QIAamp DNA Mini kit ) . Given the high performance of the rK28 RDT in this study LAMP would support diagnosis in cases where serology is profitless: VL suspects testing negative by serology , diagnosis of relapses or second VL episodes , and as a test of cure ( Fig 4 ) .
|
Tissue aspiration , either from spleen , bone marrow or lymph node , remains the Gold Standard for parasitological confirmation in patients suspected of visceral leishmaniasis ( VL ) , and is often used for detection of relapses , and as a test of cure . The procedure is invasive , with risks of severe complications , requires skilled personnel to perform , and appropriate facilities to manage severe adverse events , if they occur . These drawbacks can be solved by using sensitive diagnostic test based on peripheral blood . Nucleic acid amplification tests ( NAAT ) are sensitive for the detection of Leishmania parasites in blood; however , in VL-endemic settings , most NAAT are restricted to well-equipped laboratories . A robust NAAT , Loopamp Leishmania Detection Kit has recently been developed in a collaboration between FIND , Eiken Chemical Co . Ltd . , Japan and other partners . We have evaluated this kit in Sudan and obtained a sensitivity of 97 . 6% and specificity of 99 . 1% , using DNA obtained from peripheral blood through a simple boil and spin method . Its simplicity and excellent diagnostic performance make this kit ideal for parasitological confirmation of VL in less equipped laboratories .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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"leishmaniasis",
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"life",
"sciences",
"organisms"
] |
2018
|
Sensitive and less invasive confirmatory diagnosis of visceral leishmaniasis in Sudan using loop-mediated isothermal amplification (LAMP)
|
Human cystic and alveolar echinococcosis are helmintic zoonotic diseases caused by infections with the larval stages of the cestode parasites Echinococcus granulosus and E . multilocularis , respectively . Both diseases are progressive and chronic , and often fatal if left unattended for E . multilocularis . As a treatment approach , chemotherapy against these orphan and neglected diseases has been available for more than 40 years . However , drug options were limited to the benzimidazoles albendazole and mebendazole , the only chemical compounds currently licensed for treatment in humans . To compensate this therapeutic shortfall , new treatment alternatives are urgently needed , including the identification , development , and assessment of novel compound classes and drug targets . Here is presented a thorough overview of the range of compounds that have been tested against E . granulosus and E . multilocularis in recent years , including in vitro and in vivo data on their mode of action , dosage , administration regimen , therapeutic outcomes , and associated clinical symptoms . Drugs covered included albendazole , mebendazole , and other members of the benzimidazole family and their derivatives , including improved formulations and combined therapies with other biocidal agents . Chemically synthetized molecules previously known to be effective against other infectious and non-infectious conditions such as anti-virals , antibiotics , anti-parasites , anti-mycotics , and anti-neoplastics are addressed . In view of their increasing relevance , natural occurring compounds derived from plant and fungal extracts are also discussed . Special attention has been paid to the recent application of genomic science on drug discovery and clinical medicine , particularly through the identification of small inhibitor molecules tackling key metabolic enzymes or signalling pathways .
In human infections , established E . granulosus cysts ( or metacestodes ) can develop and reach the mature , fertile state . Protoscoleces are then produced from the germinative layer inside the cyst . Spillage of viable protoscoleces after spontaneous or traumatic cyst rupture or during surgical intervention can give rise to new cysts ( recurrence ) . Drugs against CE have been tested both against the metacestode and against the protoscoleces . In AE patients the metacestode usually does not produce protoscoleces , and the majority of the studies carried out to assess the therapeutic efficacy of drugs against AE have been done in the larval stage of the parasite . However , some authors have also tested defined drugs against E . multilocularis protoscoleces isolated from in vivo metacestodes obtained in the murine model [10] . For both CE and AE , activity of the compounds can be assayed in vitro and in vivo , although the number of agents reaching human clinical trial has been very limited . Lately , drugs have also been tested in vitro against stem cells derived from the germinative layer of the metacestode [11 , 12] , both for CE and AE . Measurement of drug activity against protoscoleces is mainly directed towards the identification of effective compounds to reduce the risk of CE recurrence after surgery . The parasitocidal effect of drugs against protoscoleces can be measured in vitro using simple procedures involving vital staining with eosin or other vital dyes [13] . Some authors combine this vital staining with the investigation of the ultra-structural changes originated after drug exposure as seen in electron microscopy [14] , the measurement of indirect markers of parasite damage including nucleosomal fragmentation and apoptosis-related enzyme activities in treated protoscoleces [14] , and , in few cases , the assessment of cyst formation capacity of in vitro treated protoscoleces after intraperitoneal injection into rodents , compared with non-treated parasites [15] . A novel movement-based assay has been recently developed for in vitro-drug screening using E . multilocularis protoscoleces cultured in microwell plates . Morphological effects caused by the active compounds tested are then directly measured and quantified by image analysis [10] . Assays against protoscoleces can also be done after the intra-cyst inoculation of the drug to test its scolicidal activity [16] , and by the administration of the drug to rodent models shortly before or after intraperitoneal infection with viable protoscoleces to mimic accidental spillage in the peritoneal cavity during a surgical intervention [17] . In general , drug testing against protoscoleces in any of those modalities is of advantage to translate the results mainly to avoid secondary CE in patients . As we mention hereinafter , a number of drugs and compounds have shown good protoscolicidal activity . Thus , drugs against the metacestode are much more urgently needed . Drug activity can be measured in vitro against both E . granulosus s . l . and E . multilocularis metacestodes maintained in culture , although E . multilocularis is the preferred experimental model due to the relative simplicity in obtaining parasite material from experimentally infected mice and the feasibility of maintaining and multiplying in vitro cultured vesicles of the parasite compared to E . granulosus cysts ( Fig 1 ) [5 , 18] . However , the in vitro vesicular model has some limitations regarding the extrapolation of the in vitro effects to the in vivo scenario . First , assessment of total loss of parasite viability after treatment ( parasitocidal effect ) is difficult . This has been most frequently approached by the study of macroscopic alterations ( e . g . , shrinking of cysts or detachment of the germinative layer ) [19] , microscopical changes in the germinative layer ( destruction of the cells in the layer ) [20] , or leaking of parasite-derived compounds to the culture medium and subsequent assessment of their associated enzyme ( e . g . alkaline phosphatase , phosphoglucoisomerase ) activity [5 , 21 , 22] . Although these assays correlate well with parasite damage , parasitocidal activity could only be totally proven after inoculation of the treated parasitic material into a rodent model , or , alternatively , re-culturing the material in vitro in order to prove the lack of parasite growth . Second , the development of the cysts in primary infections in natural hosts ( after oral infection with parasite eggs ) differs from the development of the cysts in vitro , both for CE and AE . For CE , cyst growth usually leads to the formation of the external laminated and adventitial layers of variable thickness [23] . In AE patients , cysts grow forming a stromatous mass [23] . In both cases , access of drugs to the living parasite cells is more limited than in the in vitro conditions . In addition , because cells growing in vitro are not the exact dissociated replicates of their in vivo counterparts , in vitro models do not take into consideration the potentially synergistic antiparasitic effect of the host's immune system , which may , at least partially , explain some of the outcomes observed in in vivo models . Nevertheless , the in vitro vesicular model has shown to be very valuable for the high-throughput screening of compounds , specially applying defined assays that show to correlate well with the loss of parasite activity , e . g . the measurement of phosphoglucoisomerase ( PGI ) activity in the culture medium after drug exposure , avoiding the unnecessary use of experimental animals [24] . Nevertheless , concentration range of drugs tested in vitro should consider that bioavilability in vivo , both in plasma and intra-cyst , can be three to ten-fold lower than in the in vitro systems ( e . g . , see “Albendazole” section ) . Additionally , toxicological and adverse effects should be taken into account when high-dose in vitro studies are to be translated to in vivo conditions . Similar limitations , although less pronounced , are found in the in vivo rodent models . These are usually based on the experimentally-induced development of the parasite after intraperitoneal injection of viable protoscoleces ( for E . granulosus ) or micro-cyst ( for E . multilocularis ) into rodents ( secondary infection ) [5] . Development of the parasite within the peritoneal cavity resembles more accurately the situation of a recurrence in CE natural hosts than that of a primary infection . However , this approach has some limitations when attempting to recreate a natural ( usually primary liver ) infection in the natural host of E . multilocularis . It should also be noted that intraperitoneal rodent models may be hampered by variations in the efficacy of systemic drug treatments . Differences in cyst location ( e . g . , intraperitoneal vs . intraparenchymatous ) may have important consequences in terms of parasite's exposure and achievable tissue concentration of the drug . Additionally , the elected time point after infection to start the drug treatment is of importance for the outcome of the treatment [25] . In few cases , the treatment has been done directly in naturally infected animals for CE , such as sheep [26] . The in vivo models have been also used to assess parasite viability after in vitro treatment [27] . Assessment of parasite damage after treatment in in vivo models has been usually done by estimating the mean cyst number and , more frequently , the mean biomass weight of cysts developed in infected , treated rodents compared with those figures from infected , non-treated animals [13] . Occasionally , drug-induced cyst damage and scolicidal activity has been assessed macro- and microscopically in in vivo models [28] . When only cyst weight differences are found , cysticidal activity cannot be guaranteed and instead a parasitostatic effect could be attributed to the tested drug . Of special importance is the assessment of drug effectiveness against the stem cells of the parasite in AE , since the uncontrolled growth of the metacestode and the growing foci distant from the primary lesion are presumably propitiated by the stem cells present in the germinative layer of E . multilocularis [29] . The recent availability of the genome and transcriptome data for both E . granulosus and E . multilocularis is also of importance for the definition of new drugs that could target defined parasite-specific molecules [11 , 30 , 31] . Very few drugs have reached trials in patients . The best characterized drugs are BMZ , which have been use both against CE and AE for many years . Lately , recommendations on the use of BMZ for the stage-specific treatment of CE and AE patients have been produced [3] . Nevertheless , evidence-based data supporting specific dosage and duration of BMZ treatment , either for the prevention of recurrence in CE due to protoscoleces spillage or for the fully effective elimination of the parasite , are not available to date . For other drugs different from BMZ , assessment of treatment efficacy in patients has been usually done retrospectively ( e . g . , for praziquantel ) [32] , and in a low number of patients with heterogeneous clinical pictures and management , precluding the extraction of sound conclusions and hampering the generalization of the obtained results [3] . A wide range of chemically synthetised molecules , including anti-virals , antibiotics , anti-parasites , anti-mycotics , immunomodulatory agents , and inhibitor compounds of key metabolic enzymes or signalling pathways have been evaluated in in vitro and in vivo experimental settings in order to assess their potential effect against human CE and AE . However , some of these synthetic compounds have been studied comparatively less thoroughly that their counterparts of the BZD family . Thus , their actual chemotherapeutic efficacy and safety of use remains unclear in many cases . A summary of these molecules and compounds , together with their therapeutic performance is presented in Table 3 . Following , detailed information is given on the different compounds , their mode of action ( when available ) , and effectivity against E . granulosus and E . multilocularis in vitro and in vivo at the different dosages and administration regimes assayed by different authors . While information on the use of BMZ against AE and CE has been compiled only from 2008 , drugs and compounds different from BMZ are presented historically , allowing the reader to identify most of the agents that have been assayed to seek for their potential use in the treatment of human AE and CE . In the last few years , a growing number of plant- and fungus-derived products have been tested against CE and AE , seeking for alternative natural compounds for the effective treatment of both diseases . Nevertheless , the vast majority of these molecules have been exclusively assayed in vitro against E . granulosus protoscoleces , and only three of them have been evaluated for its activity in the murine in vivo model ( Table 4 ) . In general , these compounds are naturally occurring biocides with low toxicity , acting synergistically with synthetic compounds against pathogen resistant strains , and as such they can be used as general purpose disinfectants [189] . Although some of them have shown effects potentially similar to ABZ , none of them have been tested , alone or in combination , in CE or AE patients . Drugs assayed against CE and AE can be classified in scolicidal and/or cysticidal . Application of scolicidal compounds either intra-cyst or peri-interventionally is used to minimise the risk of recurrence in CE patients during surgical or percutaneous procedures . To be effective , scolicidal agents must deliver their effects in the shortest therapeutic time period without eliciting undesirable adverse events . In recent years several compounds have been proposed as candidate drugs to substitute the recommended 20% saline solution as scolicidal agent . From these , glucose 50% , cetrimide , and H2O2 have a rapid effect on protoscoleces , but should be further evaluated for potential cytotoxic effects before being safely recommended for human use . Biogenic selenium particles , thymol , and several plant extracts have also shown promising scolicidal properties , and are regarded as non-toxic compounds at the concentrations used to exert their chemotherapeutic activity . Nevertheless , the main drawback of most of those compounds lies in the highly variable procedures involved in their in-house preparation , an inherent feature that makes difficult the assessment of the results obtained in different studies . In this regard , thymol is a commercially available compound and as such could be easily used in standardized trials to prove its therapeutic performance , particularly in those clinical cases in which biliary communication of cysts could advise against intra-cyst injection of 20% saline or alcohol as scolicidal agents . The efficacy of scolicidal compounds at the systemic level ( usually peri-operatively ) has been far lesser investigated . In this specific clinical setting , candidate drugs should ideally combine high solubility and intra-cyst bioavailability with elevated scolicidal efficiency , easy administration regimen ( preferably at low dose ) , and absence of side effects . Monensin , praziquantel , imanitib and 2-methoxyestradiol may well comply with most of these requirements , but further in vivo assays are needed to clearly demonstrate the adjunctive activity of these drugs at different regimes and also to prove their safety of use . The advantages of defining a good scolicidal agent rely in its use to avoid secondary CE in patients . Disadvantages of testing only the scolicidal activity of drugs is that a good scolicidal agent can show no activity against the metacestode , and that scolicidal drugs are of no use in AE patients . In spite of this , majority of drug testing studies against Echinococcus are still performed in vitro against protoscoleces . Drugs directed against the larval stages of E . granulosus and E . multilocularis should also share the same characteristics already mentioned for systemic scolicidal compounds . Unfortunately , most of the drugs assayed to date against CE and AE cysts do not fulfil these criteria . Many other factors may influence the parasitocidal activity of a given drug treatment against CE and AE . Particularly relevant is the time during the dosing interval of the administered drug , for which there is currently no consensus , not even for the best known compounds used until now , the members of the BMZ family . Other variables that could affect the effectivity of the treatment include the number , size , location , developmental stage and condition of cysts . Most of these variables are usually not considered during the chemotherapeutic evaluation process of a given compound . An additional and important variable affecting the outcome of drug treatment in CE and AE is the time post-infection in which drugs are used . In this respect , it has been shown by several authors that the in vivo treatment of CE and AE is more effective when applied at early post-infection times regardless of the drug used . This fact may explain , at least partially , the failure or limited success of therapies in CE and AE patients frequently reported in the literature , where treatments usually starts at a late , chronic stage of the disease . Similarly , the route of administration seems to be crucial for some compounds to exert their activity , since some drugs demonstrate parasitocidal properties in intraperitoneal administration but show little or no effect in more convenient regimes , e . g . , oral administration . Both CE and AE are still very much neglected diseases for which the current drug of choice is ABZ . Accessibility to ABZ is impaired by limited distribution and elevated cost not only in socioeconomically disadvantages areas , but also in a number of developed countries . Additionally , this compound seems to exert a parasitostatic , rather than a parasitocidal , effect against both parasites and no alternative drug is available for patients with AE who experienced severe side effects and cannot be treated with ABZ ( or MBZ ) . This also seems to be the case for the vast majority of alternative drugs assayed to date , since in vivo assays have evidenced changes in cyst weight , but reduction in cyst number are rarely observed . Could ABZ or other drug from those that have already shown parasitostatic effects be parasitocidal under specific conditions ? In an attempt to improve the intra-cyst bioavailability of ABZ , different formulations have been assessed aiming to increase the solubility , absorption , and stability of the drug . These improvements have translated into enhanced drug effectivity and should be further explored , e . g . by using nanoparticles that lead to increased intra-cyst drug levels , or novel drug enantiomers with higher bioavailability and activity . An additional strategy to overcome the problem of drugs’ solubility is represented by the salification of sulfynil-benzimidazoles with sodium hydroxide solution . The proposed two-step production of the enantiomers of RBZNa and TCBZSONa ( i . e . enantioseparation of racemic sulfoxides by HPLC on chiral stationary phase and successive transformation of the benzimidazole scaffold into a sodium salt form ) is simple and it seems to be suitable for implementation on a semi-industrial or industrial scale . The main benefit of using water-soluble RBZNa and TCBZSONa salts is the possibility to prepare novel anthelmintic formulations with higher levels of bioavailability , downscaling currently recommended human dosage , thus possibly decreasing side adverse events than those currently reported for RBZ , ABZ and TCBZ . A second line of investigation that seems promising is the use of therapies based on the combination of two or more agents , since some components have shown to act synergistically , e . g . together with ABZ , against the parasite , and importantly some of them have shown activity specifically against the stem cells of the parasite . Development of synergistic combinations of drugs can overcome toxicity and other side effects associated with high doses and/or long time dosage of single drugs . From those molecules assayed in in vivo models as an alternative for BMZ compounds , very few have reached clinical use . One example is nitazoxanide , which showed high activity in preliminary in vitro and in vivo studies , but when used in patients obtained results were discouraging . Clinical translation of drugs assayed in vivo has not been tackled systematically , and number of treated patients have been usually low and their clinical status too variable to extract robust evidence-based conclusions . Thus , there is still an urgent need for defining new compounds or improved formulations of those already assayed , and also for a careful design of clinical protocols that could lead to the draw of a broad international consensus on the use of a defined drug , or a combination of drugs , for the effective treatment of CE and AE both in complicated and non-complicated cases . Interestingly , data on the genome of both E . granulosus and E . multilocularis have been recently released [30 , 31] . These data have shown that the parasites display several sets of family molecules related both with the activity of already known drugs ( e . g . , praziquantel ) and also with the activity of potentially new drugs that could find their targets in specific parasite enzymes ( e . g . , protein kinases ) . Reasons for the reduced efficacy reported for some drugs against larval stages and potential new targets could be extracted from these genomic data . An orphan drug is defined as a compound that has been developed specifically to treat a rare medical condition . It is easier to gain marketing approval for an orphan drug , and there may be other financial incentives to encourage the development of compounds which might otherwise lack a sufficient profit motive . Despite the fact that both CE and AE are classified as orphan diseases ( http://www . orpha . net/consor/cgi-bin/index . php ? lng=EN ) , none of the drugs tested so far against these diseases have been specifically developed against them , but have previously been licensed based on the activity demonstrated against other infectious and non-infectious conditions .
|
Human cystic and alveolar echinococcosis ( CE and AE ) , caused by the larval stages of the helminths Echinococcus granulosus and E . multilocularis , respectively , are progressive and chronic diseases affecting more than 1 million people worldwide . Both are considered orphan and neglected diseases by the World Health Organization . As a treatment approach , chemotherapy is limited to the use of benzimidazoles , drugs that stop parasite growth but do not kill the parasite . To compensate this therapeutic shortfall , new treatment alternatives are urgently needed . Here , we present the state-of-the-art regarding the alternative compounds and new formulations of benzimidazoles assayed against these diseases until now . Some of these new and modified compounds , either alone or in combination , could represent a step forward in the treatment of CE and AE . Unfortunately , few compounds have reached clinical trials stage in humans and , when assayed , the design of these studies has not allowed evidence-based conclusions . Thus , there is still an urgent need for defining new compounds or improved formulations of those already assayed , and also for a careful design of clinical protocols that could lead to the draw of a broad international consensus on the use of a defined drug , or a combination of drugs , for the effective treatment of CE and AE .
|
[
"Abstract",
"Introduction"
] |
[
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] |
2018
|
Progress in the pharmacological treatment of human cystic and alveolar echinococcosis: Compounds and therapeutic targets
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Cryptosporidium parvum is a protozoan parasite that infects the gastrointestinal epithelium and causes diarrheal disease worldwide . Innate epithelial immune responses are key mediators of the host's defense to C . parvum . MicroRNAs ( miRNAs ) regulate gene expression at the posttranscriptional level and are involved in regulation of both innate and adaptive immune responses . Using an in vitro model of human cryptosporidiosis , we analyzed C . parvum-induced miRNA expression in biliary epithelial cells ( i . e . , cholangiocytes ) . Our results demonstrated differential alterations in the mature miRNA expression profile in cholangiocytes following C . parvum infection or lipopolysaccharide stimulation . Database analysis of C . parvum-upregulated miRNAs revealed potential NF-κB binding sites in the promoter elements of a subset of miRNA genes . We demonstrated that mir-125b-1 , mir-21 , mir-30b , and mir-23b-27b-24-1 cluster genes were transactivated through promoter binding of the NF-κB p65 subunit following C . parvum infection . In contrast , C . parvum transactivated mir-30c and mir-16 genes in cholangiocytes in a p65-independent manner . Importantly , functional inhibition of selected p65-dependent miRNAs in cholangiocytes increased C . parvum burden . Thus , we have identified a panel of miRNAs regulated through promoter binding of the NF-κB p65 subunit in human cholangiocytes in response to C . parvum infection , a process that may be relevant to the regulation of epithelial anti-microbial defense in general .
The protozoan parasite , Cryptosporidium parvum , is a causative agent of human gastrointestinal disease worldwide [1] . C . parvum infects the gastrointestinal epithelium to produce a self-limiting diarrhea in immunocompetent individuals but is potentially life-threatening in immunocompromised persons , especially those with the acquired immunodeficiency syndrome ( AIDS ) [1] , [2] . Transmission occurs via the fecal-oral route . Humans are infected by ingesting C . parvum oocysts; oocysts then excyst in the gastrointestinal tract releasing infective sporozoites . C . parvum sporozoites can also travel up the biliary tract to infect the epithelial cells lining the biliary tract ( i . e . cholangiocytes ) [1] , [3] . Mediated by specific ligands on the sporozoite surface and receptors on the host cells , the sporozoite attaches to the apical membrane of epithelial cells and forms a parasitophorous vacuole in which the organism remains intracellular but extracytoplasmic [3] . The sporozoite then matures and undergoes further development of its life cycle . With this unique extracytoplasmic niche within epithelial cells preventing a direct infection of other cell types , C . parvum is classified as a “minimally invasive” mucosal pathogen [1] . Because of the “minimally invasive” nature of C . parvum infection , innate immune responses by epithelial cells are critical to the host's defense against infection . Toll-like receptor ( TLR ) - and nuclear factor-kappaB ( NF-κB ) -mediated signaling pathways are important components in epithelial innate immunity to C . parvum infection [4] , [5] . TLRs are transmembrane proteins with highly conserved structural domains [6] . Upon engagement of the TLRs by specific ligands , various adaptor molecules including myeloid differentiation factor 88 ( MyD88 ) are selectively recruited to the receptors forming a complex referred to as the “signalosome” [6] , [7] . The signalosome then triggers a series of downstream events including activation of the NF-κB [6]–[8] . NF-κB subunits bind to the κB sites within the promoters/enhancers of target genes resulting in the transcriptional regulation of multiple genes important to epithelial anti-C . parvum defense [4] , [5] . MicroRNAs ( miRNAs ) , a newly identified class of endogenous small regulatory RNAs of ∼24 nucleotides , are emerging as key mediators of many biological processes and impact gene expression at the posttranscriptional level [9] , [10] . Similar to other RNA molecules , most of miRNAs are initially transcribed as primary transcripts ( termed pri-miRNAs ) by Poly II and processed by the RNase III Drosha ( in the nucleus ) and a second RNase III Dicer ( in the cytoplasm ) to generate mature miRNA molecules [11]–[13] . However , molecular mechanisms underlying miRNA gene transcriptional regulation are largely unclear [14] . Recent studies on expression of miRNA genes have revealed potential transcriptional regulation by transcription factors , such as NF-κB and C/EBPα [15] , [16] . While much of our understanding of the cellular processes modulated by miRNAs has come from studies on development and tumorigenesis , the role of miRNAs in immune responses is now being gradually uncovered [17]–[19] . The importance of miRNAs in cell-mediated immunity is highlighted by Dicer conditional knockout mice . Specific deletion of dcr-1 in the T cell lineage resulted in impaired T cell development and aberrant T helper cell differentiation and cytokine production [20] . In addition , miRNA expression is impacted by cytokines in some model systems . Both interferon ( IFN ) -α and IFN-β modulate expression of several miRNAs required for their anti-viral responses following infection with hepatitis C virus [21] . The TLR4 ligand , lipopolysaccharide ( LPS ) , impacts expression of miR-132 , miR-146 , and miR-155 in human THP-1 monocytes [15] , [22] . Further characterization of miR-146 revealed that this miRNA may function as a negative regulator of tumor necrosis factor receptor-associated factor 6 and interleukin-1 receptor associated kinase 1 [15] . Recent studies also implicate specific miRNAs in controlling various epithelial cell processes such as regulation of cellular differentiation , determination of epithelial cell fate ( cell death and proliferation ) , initiation and regulation of anti-microbial immunity , fine-tuning of inflammatory responses , and activation of specific intracellular signaling pathways [17]–[19] , [23] . Using a non-malignant human cholangiocyte cell line ( H69 ) that expresses multiple TLRs including TLR4 [5] , we previously demonstrated that infection of human cholangiocytes by C . parvum in vitro mimics parasitial apical invasion and TLR4/NF-κB-dependent epithelial responses in vivo [3] . Moreover , let-7 regulates TLR4 expression via translational suppression in human cholangiocytes and is involved in epithelial defenses against C . parvum [24] . Members of the miR-98/let-7 family also regulate expression of cytokine-inducible SH2-containing protein ( CIS ) in cholangiocytes following C . parvum infection [25] . Together , these findings demonstrate that miRNAs levels in epithelial cells are altered by C . parvum infection and may regulate epithelial anti-C . parvum immune responses . In this study , we performed an array analysis of miRNA expression in H69 cells following C . parvum infection and LPS stimulation . The analysis revealed significant alterations in miRNA expression in cholangiocytes following C . parvum infection or treatment with LPS . Of those miRNAs upregulated by C . parvum infection , we identified potential NF-κB binding sites in the promoter elements of several miRNA genes . Inhibiting activation of NF-κB p65 blocked C . parvum-induced upregulation of a panel of miRNA genes . Promoter binding and transactivation of the NF-κB p65 subunit of each selected miRNA gene was confirmed by chromatin immunoprecipitation assay and promoter luciferase reporter analysis . Furthermore , functional inhibition of the NF-κB p65-binding miRNAs increased C . parvum burden in cholangiocytes in vitro . These data demonstrate that a panel of miRNAs is regulated through promoter binding of the NF-κB p65 subunit in human cholangiocytes and these miRNAs are involved in epithelial defense in response to C . parvum infection , suggesting a role of miRNAs in regulation of epithelial anti-microbial defense .
To globally assess miRNA expression in epithelial cells following C . parvum infection , we performed a microarray analysis of mature miRNA expression in H69 cells [26] . The miRCURY™ LNA human microRNAs assays ( version 8 . 1; Exiqon; Vedbaek , Denmark ) covers a total of up to 600 known human mature miRNAs and were used as previously described [27] . The quality of the RNA was verified using an Agilent 2100 Bioanalyzer ( Figure S1 ) . A total of 383 mature miRNAs were detected in the uninfected H69 cells . Of the miRNAs expressed , miR-23b , miR-30b , miR-30c , and miR-125b expression were significantly increased in H69 cells after exposure to live C . parvum infection for 12 h ( p< = 0 . 05; Figure 1A and Table S1 ) . Five additional miRNAs ( miR-15b , miR-16 , miR-27b , miR-24 , and miR-21 ) showed a tendency to increase ( 0 . 05<p< = 0 . 20 ) ( Figure 1A ) . A total of 19 miRNAs were significantly downregulated ( p< = 0 . 05 ) and 30 additional miRNAs showed a tendency to decrease ( 0 . 05<p< = 0 . 20 ) following C . parvum infection ( Figure 1A and Table S1 ) . Sham-infected control cells ( H69 cells exposed to heat-inactivated C . parvum oocysts after incubation at 65°C for 30 min ) displayed a similar miRNA expression profile as non-infected control samples ( Table S1 ) . Microarray analysis of mature miRNAs was also performed on H69 cells treated with LPS ( 1 µg/ml for 8 h ) . Interestingly , most of the miRNAs upregulated by C . parvum also displayed an increased expression in cells treated by LPS ( Figure 1B and Table S1 ) . Nevertheless , increased expression of additional 13 miRNAs was identified in LPS-treated cells but not in cells exposed to C . parvum . A total of 31 miRNAs showed a decreased expression in LPS-treated cells and 10 of them were also downregulated by C . parvum ( Figure 1B and Table S1 ) . No LPS contamination in the C . parvum preparation was detected using the Limulus Amebocyte Lysate ( LAL ) test kit ( Bio-Whittaker ) ( data not shown ) . All microarray data were described in accordance with MIAME guidelines and deposited at ArrayExpress ( accession number: E-MEXP-2050 and E-MEXP-2052 ) . Real-time PCR analysis using primers and probes for mature miRNAs ( Ambion ) was performed to assess the kinetics of selected miRNAs in H69 cells following C . parvum infection . Increased expression of miR-125b , miR-21 , miR-23b , miR-30b and miR-16 was detected in H69 cells following C . parvum infection for 12 h to 24 h , but not in the early time points ( 2 h to 8 h ) ( Figure 2A ) . Increased expression of miR-125b , miR-16 , miR-23b , miR-21 and miR-30b , as well as decreased expression of miR-98 , was further confirmed in cells following C . parvum infection for 12 h by Northern blot ( Figure 2B ) . An increased expression of the precursors for miR-125b , miR-16 , miR-21 and miR-23b was also detected in cells following C . parvum infection by Northern blot ( Figure 2B ) . No positive signal for the above human miRNAs was detected in C . parvum RNA using the probes or primers for miRNA real-time PCR ( data not shown ) and Northern blot ( Figure 2C ) , demonstrating the specificity of these probes for human miRNAs . Downregulation of selected miRNAs induced by C . parvum , including miR-98 , miR-320 and miR-424 , was further confirmed by bead-based multiplexed miRNA expression assay using the FlexmiR™ Select kit ( Figure 2D ) . For those miRNAs that did not show significant alterations in cells following C . parvum infection as revealed by the microarray analysis , we selected miR-326 for bead-based multiplexed analysis and no change was detected in C . parvum infected cells ( Figure 2D ) , further confirming the accuracy of the array data . Differential alterations in the mature miRNA expression profile of C . parvum-infected H69 cells suggest that miRNA gene expression is finely controlled in epithelial cells in response to C . parvum infection . One potential mechanism for selectively altering miRNA levels is through activation of distinct intracellular signaling pathways and nuclear transcription factors [15] , [16] . This mechanism is consistent with our previous data demonstrating that C . parvum infection activates the NF-κB pathway in cholangiocytes through microbial recognition of TLR4 and TLR2 [28] . We hypothesized that activation of the NF-κB pathway is involved in the transcription of select miRNAs upregulated by C . parvum . Based on TFSEARCH ( http://www . cbrc . jp/research/db/TFSEARCH . html ) and MOTIF ( http://motif . genome . jp/ ) database searches [29] , [30] , many of these miRNA genes have putative NF-κB binding sites in their potential promoter elements [31]–[34] ( Table 1 ) . Several miRNAs upregulated in H69 following C . parvum infection are cluster miRNAs; e . g . , miR-23b , miR-27b and miR-24 are from the mir-23b-27b-24-1 gene cluster and miR-15b and miR-16 from the mir-15b-16-2 cluster [31] , [32] . The promoters of the mir-125b-1 and mir-30b genes have not been characterized and it is unknown whether they have potential NF-κB binding sites . Transactivation of most NF-κB-dependent genes requires NF-κB p65 binding to the promoter [8] and nuclear translocation of p65 was demonstrated following C . parvum infection of cholangiocytes [28] . Coupled with the results showing some similar changes in miRNA expression in H69 cells treated with LPS ( which activates TLR4/NF-κB signaling in H69 cells ) , we then focused on determining whether p65 binds to the promoter and transactivates the miRNA genes upregulated by C . parvum infection . We then analyzed the kinetics of alterations of the primary transcripts ( pri-miRNAs ) for select mature miRNAs upregulated by C . parvum as listed in Table 1 . H69 cells were exposed to C . parvum for various periods of time and pri-miRNAs of interests were quantified by real-time PCR ( primers listed in Table S2 ) . Expression of pri-miR-125b-1 , pri-miR-21 , pri-miR-23b-27b-24-1 , pri-miR-30b , pri-miR-30c-1 , pri-miR-15a-16-1 , and pri-miR-15b-16-2 showed a time-dependent increase in cells following C . parvum infection , with a peak at 8 h or 12 h after exposure to the parasite ( Figure 3 ) . In contrast , no significant increase of pri-miR-125b-2 and pri-miR-30c-2 was detected in cells after exposure to C . parvum infection ( Figure 3 ) , suggesting a differential expression of the primary transcripts of C . parvum-upregulated miRNAs . To test whether NF-κB p65 subunit is involved in C . parvum-induced transactivation of pri-miR-125b-1 , we exposed H69 cells to C . parvum infection in the presence of SC-514 , an IKK2 inhibitor that prevents p65-associated transcriptional activation of the NF-κB pathway [35] . SC-514 blocked the C . parvum-induced increase of pri-miR-125b-1 ( Figure 4A ) . To further test the potential transactivation of mir-125b-1 gene by p65 subunit , rapid amplification of 5′ complementary DNA ends ( 5′-RACE ) PCR was used to identify the 5′ end of pri-miR-125b-1 . Primers were designed to amplify pri-miR-125b-1 based on the sequence obtained from the Sanger miRNA Registry ( Table S2 ) . Database analysis revealed two potential p65 binding sites in the upstream sequence of mir-125b-1 ( Figure 4B ) . Increased binding of p65 to the binding site at −1059 , but not the putative binding site at −2455 , in the promoter element of mir-125b-1 gene ( Figure 4B ) was demonstrated by chromatin immunoprecipitation ( ChIP ) analysis using specific primers for each putative binding site ( Table S2 ) . C . parvum-induced transactivation of the mir-125b-1 gene by p65 was further confirmed by using luciferase reporter gene constructs that spanned the mir-125b-1 promoter ( Figure 4C ) . C . parvum infection increased luciferase activity in cells transfected with the luciferase constructs that encompassed the binding site for p65 at −1059 in the promoter region of mir-125b-1 gene . A mutant of the p65 binding site at −1059 blocked C . parvum-induced luciferase activity . In addition , SC-514 significantly inhibited the increase of luciferase activity induced by C . parvum infection ( Figure 4C ) . Moreover , p65-associated transactivation of the mir-125b-1 promoter was also confirmed by the upregulation of luciferase activity after p65 overexpression in the cells ( Figure 4D ) . As an additional control , we analyzed IL-8 transactivation , a p65-dependent process induced by C . parvum in epithelial cells [36] . NF-κB p65-dependent increase of IL-8 mRNA expression and binding of p65 to the promoter of IL-8 gene in cells exposed to C . parvum were confirmed ( Figure S2 ) . Together , these data demonstrate that p65 binding to the promoter element of the mir-125b-1 gene mediates mir-125b upregulation in H69 cells in response to C . parvum infection . The dynamics of p65 nuclear translocation were confirmed by Western blot analysis of p65 in the nuclear extracts from H69 cells following C . parvum infection ( Protocol S1 and Figure S3 ) , correlated to the kinetics of C . parvum-induced expression of pri-miRNAs in cells ( Figure 3 ) . Consistent with previous results , maximal p65 translocation was observed at 8 h after exposure to C . parvum [5] . Using the same approaches , we analyzed p65 promoter element binding in C . parvum-induced transcription of pri-miR-21 , pri-miR-23b-27b-24-1 , pri-miR-30b , pri-miR-30c-1 , pri-miR-30c-2 , pri-miR-15a-16-1 , and pri-miR-15b-16-2 . Our data are summarized in Table 2 and presented in detail in Figures S4 , S5 , S6 and S7 . Specifically , p65 binding to the putative p65 binding site around +1395 of the mir-21 gene appears to be associated with C . parvum-induced transcription of pri-miR-21 ( Figure S4 ) . C . parvum increases transcription of pri-miR-23b-27b-24-1 cluster , as well as the host gene transcript , C9orf3 , via promoter binding of p65 to a binding site at −1254 of the immediate upstream of the gene ( Figure S5 ) . Increased transcription of pri-miR-30b induced by C . parvum is p65-dependent ( Figure S6 ) . Nevertheless , it appears that C . parvum infection increases transcription of pri-miR-30c-1 , pri-miR-15a-16-1 and pri-miR-15b-16-2 in cholangiocytes through a p65-independent mechanism ( Figure S7 ) . To test whether miRNAs are involved in cholangiocyte defense responses against C . parvum infection , we assessed parasite burden over time in cultured cholangiocytes transfected with various anti-miRs thereby inhibiting function of specific C . parvum-upregulated miRNAs . Anti-miRs ( anti-miR™ miRNA inhibitors ) are commercially available , chemically modified single stranded nucleic acids designed to specifically bind to and inhibit endogenous miRNAs [21] . Cells were transfected with specific anti-miRs ( 30 nM , Ambion ) or a mixture of anti-miRs to miR-125b , miR-23b and miR-30b ( a total of 30 nM with 10 nM for each ) , and then exposed to C . parvum . Following incubation with a constant number of C . parvum sporozoites for 2 h to allow sufficient host-cell attachment and cellular invasion [3] , [24] , cells were washed with culture medium to remove non-attached and non-internalized parasites . Cells were then cultured for an additional 2 h or 22 h . Parasite burden was assessed in the samples using a real-time PCR approach as we previously reported [24] . The parasite burden following exposure to C . parvum for 2 h was similar in all cultures , including those transfected with the siRNA to Drosha or the specific anti-miRs ( Figure 5A and 5C ) , suggesting that those miRNAs do not affect initial parasite host cell attachment and cellular invasion . Additionally , SC-514 treatment did not impact parasite burden at this time point ( Figure 5A ) . Consistent with our previous studies [24] , a significant increase in parasite burden was identified in SC-514-treated H69 cells 24 h after initial infection ( Figure 5B ) . Cells transfected with the siRNA to Drosha displayed an increased parasite burden as compared to control cells ( Figure 5B ) . Interestingly , we also detected a significantly higher parasite burden 24 h after initial infection in cells treated with the anti-miRs to miR-125b , miR-23b , and miR-30b , as well as a mixture of three anti-miRs , compared with that in control cells ( Figure 5D ) ; anti-miRs to miR-16 and miR-21 did not impact infection burden ( Figure 5D ) . Increase of parasite burden 24 h after initial infection in H69 cells treated with SC-514 or select anti-miRs was further confirmed by immunofluorescent microscopy ( Figure 5E ) . The targets of a majority of known miRNAs are still yet to be identified . C . parvum-responsive miRNAs may regulate the expression of proteins of various functions related to epithelial anti-C . parvum defense . Using computational analyses as previously reported [19] , [37]–[39] , we identified a variety of potential targets of C . parvum-responsive miRNAs selected on the basis of their known involvement in immune related responses ( Table S3 ) .
There is emerging evidence that miRNAs play a critical role in the regulation of both innate and adaptive immunity [17]–[19] . A better understanding miRNA expression changes in epithelial cells following C . parvum infection will provide new insights in miRNA-associated epithelial defense to C . parvum . Using an in vitro model of human biliary cryptosporidiosis , we report significant alterations in miRNA expression profiles in epithelial cells following C . parvum infection . Our analysis of miRNAs upregulated by C . parvum in H69 cells revealed that mir-125b-1 , mir-23b-27b-24-1 , mir-21 , and mir-30b genes are transactivated via potential promoter binding of the NF-κB p65 subunit . These data provide several insights relevant to miRNA expression regulation in cholangiocytes following C . parvum infection . First , similar to the regulation of miRNA genes in other cells [16] , [40] , [41] , promoter binding of transcription factors regulates miRNA genes in epithelial cells in response to C . parvum infection . Therefore , transcription factor-mediated miRNA expression and subsequent gene regulation at the posttranscriptional level through miRNA targeting may be an important element of host responses against C . parvum infection . Since similar alterations in miRNA expression profile were identified in LPS-treated cells , this observation may also be relevant to cellular gene regulation in general . Second , transactivation of miRNA genes that produce the same mature miRNA can be differentially controlled . Specifically , both mir-125b-1 and mir-125b-2 genes can produce mature miR-125b , but only transactivation of mir-125b-1 gene was detected in cells following C . parvum infection . Indeed , differential activation of genes for the same mature miRNA molecule has been previously reported [31] . Finally , transactivation of genes of cluster miRNAs or as introns in other gene alleles may be controlled by the same promoter element . Of note , miR-23b , miR-27b and miR-24 are cluster gene miRNAs and co-transcribed with a host gene , C9orf3 [31] . C . parvum infection upregulates expression of the mature forms of these three miRNAs , as well as pri-miR-23b-27b-24-1 and the host gene transcript , C9orf3 . Our data are consistent with recent studies demonstrating transcriptional control of genes that code cluster miRNAs or that encode both miRNAs and other host transcripts [31] , [32] . The NF-κB family of transcription factors consists of five members , p50 , p52 , p65 ( RelA ) , c-Rel , and RelB [8] . The transcription activation domain ( TAD ) necessary for the positive regulation of gene expression is present only in p65 , c-Rel , and RelB [8] . Thus , promoter binding of p65 , c-Rel and RelB is usually associated with gene transactivation [8] , [42]–[44] . Because they lack TADs , p50 and p52 may repress transcription unless they associate with a TAD-containing NF-κB family member or another protein capable of coactivator recruitment [8] , [45] , [46] . Increased nuclear translocation of p65 and p50 was previously reported in human cholangiocytes following C . parvum infection [28] . In this study , we demonstrated that promoter binding of the NF-κB p65 subunit is required for transactivation of the mir-125b-1 , mir-23b-27b-24-1 , mir-21 and mir-30b genes in cells following C . parvum infection . Although transactivation of mir-30c-1 and mir-15b-16-2 genes was observed in C . parvum-infected cells and potential NF-κB binding sites were identified in their promoter elements , inhibition of p65 activation failed to inhibit transactivation of either mir-30c-1 or mir-15b-16-2 in H69 cells following C . parvum-infection . In addition , miR-146b , miR-155 , and miR-9 have been reported to be NF-κB-dependent miRNAs in monocytes or neutrophils [15] , [47] , [48] . Although miR-146b and miR-155 are expressed in cholangiocytes , no upregulation of either miR-146b or miR-155 was detected in H69 cells following C . parvum infection . Given the complexity and variability in the gene structure for each miRNA , it is obvious that multiple mechanisms are involved in the transcriptional regulation of human miRNA genes [32] , [33] , [49] . Therefore , transcription of miRNA genes is expected to be a dynamic process in response to the constant alterations in intracellular signals . miRNA expression thus reflects the final integrated result of multiple interrelated signals on miRNA transcription . In this regard , other transcription factors , such as AP-1 , c-myc , C/EBPα , may also be involved in the transcriptional regulation of miRNA genes in epithelial cells in response to C . parvum infection . Future studies will focus on whether nuclear translocation of p50 is involved in the C . parvum-induced down-regulation of miRNA expression . miRNAs have been identified in both mammalian and nonmammalian cells including virus and parasites [9] , [14] , [50] , [51] . Expression of miRNAs in C . parvum has not yet been examined and whether C . parvum-derived miRNAs can be localized in infected host cells is unknown . Nevertheless , the probes used in the microarray analysis in this study are human-miRNA specific with minimal cross-interaction with known miRNAs from other species . Cells of sham-infection control ( host cells plus heat-inactivated C . parvum oocysts ) displayed a similar expression profile of human miRNAs compared with non-infected control cells as assessed by microarray analysis . Finally , by Northern blot and real-time PCR , no positive signal was detected in C . parvum RNA alone using the probes/primers for selected human miRNAs , confirming host-cell specificity of detected miRNAs . The TLR/NF-κB signaling is critical to innate epithelial immune defenses to microbial infection including parasites [4] , [52] . We previously demonstrated that TLR4 and TLR2 are involved in cholangiocyte immune response to C . parvum infection via activation of NF-κB [5] . Here , we expanded our previous studies by demonstrating that miRNAs may also regulate TLR/NF-κB-mediated epithelial anti-C . parvum defense . We indentified a panel of miRNA genes that are transactivated via p65 promoter binding in cholangiocytes in response to C . parvum infection . Transfection of cells with anti-miRs to miR-125b , miR-23b or miR-30b , but not anti-miRs to miR-16 or miR-21 , significantly increased parasite burden in cholangiocytes . The molecular mechanisms by which C . parvum-responsive miRNAs modulate epithelial anti-C . parvum defense are largely unclear . Previous studies demonstrated that let-7 regulates TLR4 expression and is involved in epithelial defense against C . parvum [24] . Various immune related genes are identified as potential targets for these C . parvum-responsive miRNAs using computational analyses . The concept that a pathogen encodes mRNAs targeted by host miRNAs has recently emerged as an important mechanism of host anti-viral defense [21] . Likewise , it is of interest to test the possibility that host cell miRNAs target the internalized parasite mRNAs and silence genes of the pathogen . The direct C . parvum-host cell cytoplasmic tunnel-connection [53] could mediate exchange of molecules , including miRNAs , between the host cells and internalized parasite . Further investigation should test whether p65 promoter binding transactivates LPS-responsive miRNA genes . This also raises the possibility that transactivation of miRNA genes through promoter binding of NF-κB subunits may be involved in host anti-microbial responses in general . In summary , this first miRNA profiling in cholangiocytes in response to C . parvum infection in vitro revealed significant alterations in cellular miRNA expression . The mechanism by which C . parvum induces upregulation of a panel of miRNAs in cholangiocytes involves transactivation of miRNA genes through promoter binding of the NF-κB p65 subunit . In addition , functional inhibition of the upregulated miRNAs increases C . parvum infection burden in cholangiocytes in vitro thereby implicating these miRNAs in host cell defense to the parasite . These data demonstrate a key role for miRNAs in epithelial immune responses against C . parvum infection and may provide new insights into general mechanisms of the regulation of epithelial anti-microbial immunity .
C . parvum oocysts of the Iowa strain were purchased from a commercial source ( Bunch Grass Farm , Deary , ID ) . H69 cells ( a gift of Dr . D . Jefferson , Tufts University ) are SV40 transformed normal human cholangiocytes originally derived from liver harvested for transplant . These cholangiocytes continue to express biliary epithelial cell markers , including cytokeratin 19 , gamma glutamyl transpeptidase and ion transporters consistent with biliary function and have been extensively characterized [26] . An in vitro model of human biliary cryptosporidiosis using H69 cells was employed in these studies . Before infecting cells , C . parvum oocysts were treated with 1% sodium hypochlorite on ice for 20 min followed by extensive washing with DMEM-F12 medium . Oocysts were then added to the cell culture to release sporozoites to infect cells [54] . Infection was performed in culture medium ( DMEM-F12 with 100 U/ml penicillin and 100 µg/ml streptomycin ) containing viable C . parvum oocysts ( oocysts with host cells in a 5∶1 ratio ) . Inactivated organisms ( treated at 65°C for 30 min ) were used for sham infection controls . All experiments were performed in triplicate . For the inhibition experiments , SC-514 ( Calbiochem ) was added to the medium . Cells were pre-treated with SC-514 for 1 h prior to C . parvum infection . SC-514 was used at a concentration of 100 µM , which showed no cytotoxic effects on H69 cells or on C . parvum sporozoites , in these studies . Real-time PCR and immunofluorescent microscopy were used to assay C . parvum infection as previously reported [24] . Briefly , primers specific for C . parvum 18s ribosomal RNA ( forward: 5′-TAGAGATTGGAGGTTGTTCCT-3′ and reverse: 5′-CTCCACCAACTAAGAACGGCC-3′ ) were used to amplify the cDNA specific to the parasite . Primers specific for human plus C . parvum 18s were used to determine total 18s cDNA [24] . Data were expressed as copies of C . parvum 18s vs total 18s . For immunofluorescent microscopy , cells were fixed with 2% paraformaldehyde and incubated with a polyclonal antibody against C . parvum ( a gift from Dr . Guan Zhu , Texas A&M University ) followed by anti-rabbit FITC-conjugated secondary antibody ( Molecular Probes ) and co-staining with 4′ , 6-diamidino-2-phenylindole ( DAPI , 5 µM ) to stain cell nuclei . Labeled cells were assessed by confocal laser scanning microscopy . The Exiqon ( Vedbaek , Denmark ) miRCURY LNA microRNA arrays and service to process the samples were used [27] . Briefly , H69 cells were grown to 80% confluence and exposed to C . parvum oocysts for 12 h or LPS ( 1 µg/ml ) for 8 h . Total RNAs from H69 cells or C . parvum oocysts were prepared with the mirVana™ miRNA Isolation Kit according to the manufacturer's instruction ( Ambion ) . The quality of isolated RNAs was verified by an Agilent 2100 Bioanalyzer profile ( Figure S1 ) . A mixture of equal amounts of total RNAs from the control and C . parvum-infected cells were used as the reference pool . A total of 2 µg RNA from each sample was then labeled with the Hy5™ fluorescent label and the reference pool labeled with Hy3™ using the miRCURY™ LNA Array labeling kit ( Exiqon ) . The labeled samples and reference pool were then mixed pair-wise and hybridized to the miRCURY™ LNA array containing capture probes targeting all human miRNAs listed in the miRBASE version 8 . 1 ( Exiqon ) . After hybridization , the slides were scanned and quantified signals normalized by Exiqon using the global Lowess ( Locally Weighted Scatterplot Smoothing ) regression algorithm . Normalized Hy5/Hy3 ratios were used for further analysis as previously reported [55]–[57] . A bead-based multiplex sandwich immunoassay , read with a Luminex 200 system ( Luminex ) , was used to measure the concentrations of selected miRNAs as previously reported [57] . Briefly , total cellular RNAs are isolated using the mirVana™ miRNA Isolation Kit ( Ambion ) . An amount of 0 . 5 µg of total RNAs was used for Biotin-labeling using the FlexmiR MicroRNA Labeling Kit for selected miRNAs ( Luminex ) . Signals for miRNAs were recorded and standardized to the standard beads according to the manufacturer's instructions ( Luminex ) . For real-time PCR analysis of mature miRNAs , total RNAs were extracted using the mirVana™ miRNA Isolation kit ( Ambion ) . An amount of 0 . 05 µg total RNAs was reverse-transcribed by using the Taqman MicroRNA Reverse Transcription Kit ( Applied Biosystems ) . Comparative real-time PCR was performed in triplicate using Taqman Universal PCR Master Mix ( Applied Biosystems ) on the Applied Biosystems 7500 FAST real-time PCR System . Mature miRNA-specific primers and probes were obtained from Applied Biosystems . Normalization was performed by using RNU6B primers and probes . Relative expression was calculated by using the comparative CT method [56] . For analysis of pri-miRNAs , total RNA was isolated from cells with Trizol reagent ( Ambion ) . RNAs were treated with DNA-free™ Kit ( Ambion ) to remove any remaining DNA . Comparative real-time PCR was performed by using the SYBR Green PCR Master Mix ( Applied Biosystems ) . Specific primers for pri-miRNAs were listed in Table S2 . All reactions were run in triplicate . The Ct values were analyzed using the comparative Ct ( ΔΔCt ) method and the amount of target was obtained by normalizing to the endogenous reference ( GAPDH ) and relative to the control ( non-treated cells ) [58] . Total RNAs harvested as above were run on a 15% Tris/Borate/EDTA ( 90 mM Tris/64 . 6 mM boric acid/2 . 5 mM EDTA , pH 8 . 3 ) –urea gel ( Invitrogen ) and transferred to a Nytran nylon transfer membrane ( Ambion ) . LNA DIG-probes for selected miRNAs ( Exiqon ) were hybridized using UltraHyb reagents ( Ambion ) according to the manufacturer's instructions with blotted snRNA RNU6B as a control . 5′-RACE PCR was utilized to identify 5′ end of miRNA primary transcripts to localize the start sites of mir-125b-1 , mir-30b and mir-30d . Primer sequences are listed in Table S2 . The SMART™ RACE cDNA Amplification Kit ( Clontech ) was used for the analysis . Total RNA was isolated for H69 cells treated with a Drosha siRNA ( Santa Cruz biotechnology ) as previously reported [32] . ChIP analysis was performed with a commercially available ChIP Assay Kit ( Upstate Biotechnologies ) in accordance with the manufacturer's instructions . In brief , 1×106 H69 cells were cultured in 15-cm culture dishes and exposed to C . parvum in the presence or absence of SC-514 for 8 h . The chromatin fraction was immunoprecipitated for overnight at 4°C using anti-NF-κB p65 ( Upstate Biotechnologies ) . PCR amplification was performed in a total volume of 25 µl with specific primers . The forward and reverse primers used for each gene were listed in Table S2 . Promoters of miRNAs were amplified by PCR from human genomic DNA . PCR primers were listed in Table S2 . The PCR products were separated by agarose gel electrophoresis , and the DNA fragments then isolated and cloned in the restriction enzyme digested pGL3 Basic Vector ( Promega ) using T4 DNA ligase ( Fisher scientific ) . All constructs were confirmed by sequencing . Mutations were introduced into the NF-κB binding sites using the QuikChange site-directed mutagenesis kit ( Stratagene ) . H69 cells were transfected with each reporter construct for 24 h and then exposed to C . parvum oocysts for 8 h in the presence or absence of SC-514 followed by assessment of luciferase activity . Luciferase activities were then measured and normalized to the control β-gal level . The luciferase activity of each construct was compared with that of the promoterless pGL3 basic vector .
|
MicroRNAs ( miRNAs ) are newly identified small non-coding RNAs that regulate gene expression at the posttranscriptional level . While much of our understanding of the cellular processes modulated by miRNAs has come from studies on development and tumorigenesis , the role of miRNAs in immune responses is now being gradually uncovered . Nevertheless , whether miRNA-mediated posttranscriptional gene regulation is involved in the fine-tuning of epithelial cell immune responses against pathogen infection remains undefined . Cryptosporidium parvum is a protozoan parasite that infects gastrointestinal epithelium . TLR/NF-κB-mediated innate immune responses by epithelial cells are critical to the host's defense to infection . Using an in vitro model of human cryptosporidiosis , we show here differential alterations in the miRNA expression profile in biliary epithelial cells following C . parvum infection . Promoter binding of NF-κB p65 subunit accounts for the upregulation of a panel of miRNA genes in cells infected by C . parvum . Importantly , functional inhibition of several NF-κB p65-dependent miRNAs in epithelial cells increases C . parvum infection burden . Our findings suggest that host epithelial cells activate NF-κB signaling to regulate miRNA expression in response to C . parvum infection . Moreover , NF-κB-mediated miRNA expression is involved in epithelial anti-microbial defense . Our study provides new insights into epithelial cell immunoregulation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"immunology/cellular",
"microbiology",
"and",
"pathogenesis",
"immunology/immune",
"response",
"gastroenterology",
"and",
"hepatology/biliary",
"tract",
"immunology/innate",
"immunity",
"microbiology/innate",
"immunity",
"infectious",
"diseases/protozoal",
"infections",
"immunology/immunity",
"to",
"infections",
"infectious",
"diseases/gastrointestinal",
"infections"
] |
2009
|
NF-kappaB p65-Dependent Transactivation of miRNA Genes following Cryptosporidium parvum Infection Stimulates Epithelial Cell Immune Responses
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During lytic Kaposi’s sarcoma-associated herpesvirus ( KSHV ) infection , the viral endonuclease SOX promotes widespread degradation of cytoplasmic messenger RNA ( mRNA ) . However , select mRNAs escape SOX-induced cleavage and remain robustly expressed . Prominent among these is interleukin-6 ( IL-6 ) , a growth factor important for survival of KSHV infected B cells . IL-6 escape is notable because it contains a sequence within its 3’ untranslated region ( UTR ) that can confer protection when transferred to a SOX-targeted mRNA , and thus overrides the endonuclease targeting mechanism . Here , we pursued how this protective RNA element functions to maintain mRNA stability . Using affinity purification and mass spectrometry , we identified a set of proteins that associate specifically with the protective element . Although multiple proteins contributed to the escape mechanism , depletion of nucleolin ( NCL ) most severely impacted protection . NCL was re-localized out of the nucleolus during lytic KSHV infection , and its presence in the cytoplasm was required for protection . After loading onto the IL-6 3’ UTR , NCL differentially bound to the translation initiation factor eIF4H . Disrupting this interaction , or depleting eIF4H , reinstated SOX targeting of the RNA , suggesting that interactions between proteins bound to distant regions of the mRNA are important for escape . Finally , we found that the IL-6 3’ UTR was also protected against mRNA degradation by the vhs endonuclease encoded by herpes simplex virus , despite the fact that its mechanism of mRNA targeting is distinct from SOX . These findings highlight how a multitude of RNA-protein interactions can impact endonuclease targeting , and identify new features underlying the regulation of the IL-6 mRNA .
The posttranscriptional fate of mRNA , including translation , subcellular localization , and stability , is tightly controlled through complex networks of RNA-protein interactions . Many mRNA regulatory elements are located in the 3’ untranslated region ( UTR ) , where they recruit factors that control the levels of the mRNA and its encoded protein both during homeostasis and in response to changes in the cellular environment [1] . In many cases the mechanisms by which these RNA-protein complexes assemble to direct a particular outcome remain unknown , although the best characterized elements are those that promote rapid degradation of mRNAs through recruitment of specific decay enzymes [2–4] . In this regard , mRNA stability is a key point of regulation that is readily engaged during pathogenesis . Viruses have evolved ways to both circumvent and hijack cellular mRNA decay pathways [5 , 6] . In particular , gamma-herpesviruses ( HVs ) , including Kaposi’s sarcoma-associated herpesvirus ( KSHV ) and Epstein-Barr virus ( EBV ) , use RNA degradation as a means to broadly control both cellular and viral gene expression [7–10] . During their lytic replication cycle , gamma-HVs promote widespread acceleration of mRNA decay through the activity of the virally-encoded mRNA-specific endonuclease SOX . SOX internally cleaves cytoplasmic mRNAs in a site-specific manner and promotes their subsequent degradation by the cellular 5’-3’ exonuclease Xrn1 [11] . The importance of SOX-induced mRNA degradation has been demonstrated in vivo using the model virus murine gamma-HV 68 ( MHV68 ) , which displays defects in viral trafficking , cell type specific replication , and latency establishment upon introduction of a point mutation in SOX that selectively inhibits its mRNA degradation activity [7 , 9] . Despite this widespread mRNA degradation , approximately one-third of mRNAs appear to escape SOX-induced cleavage . Although in many instances ‘escape’ is likely a reflection of a secondary transcriptional compensation rather than a failure of SOX to cleave the mRNA , a subset of escapees are truly refractory to SOX targeting [12 , 13] . These are thought to escape SOX cleavage either because they lack a functional SOX targeting sequence or because they possess specific protective features that render them inaccessible to the viral nuclease . This latter class of escapees is of particular interest , as their characterization could reveal pathways of mRNA regulation that are inaccessible to viral or cellular endonucleases . Interleukin-6 ( IL-6 ) is an immunomodulatory cytokine important for survival of KSHV-infected B cells [14–16] , and its mRNA is directly refractory to SOX-induced decay [17 , 18] . IL-6 expression spikes during KSHV infection both as a consequence of transcriptional and post-transcriptional control by the virus [17 , 18] . The ability of the IL-6 mRNA to escape SOX cleavage has been mapped to a specific protective sequence that resides within its 3’ UTR [18] . Fusion of the IL-6 3’ UTR to an mRNA that is normally targeted by SOX renders the mRNA protected , indicating that this RNA element somehow overrides the SOX targeting mechanism . This element recruits a largely undefined complex of cellular proteins , although two components have been identified as HuR and AUF1 and shown to participate in the protective phenotype [18] . Here , we sought to gain a more detailed understanding of how the IL-6 3’ UTR promotes escape from viral endonuclease targeting . Using a ribonucleoprotein ( RNP ) purification strategy coupled with mass spectrometry , we identified a set of proteins that specifically associate with this protective sequence . Depletion of at least five of these proteins adversely impacts protection , suggesting that the complex as a whole impacts SOX targeting . Among these , nucleolin ( NCL ) emerged as having the most robust contribution to IL-6 mRNA escape . We found that its re-localization during infection , coupled with specific long-range protein interactions formed only in the context of RNA binding , are prominent components of the protective phenotype . Finally , we demonstrate that the IL-6 3’ UTR also blocks mRNA degradation by the unrelated herpes simplex virus endonuclease vhs , suggesting a protective mechanism that operates across distinct endonuclease targeting strategies .
The majority of cellular mRNAs , as well as reporter mRNAs such as GFP , are endonucleolytically cleaved by the KSHV SOX protein and subsequently degraded . However , the 3’ UTR of the IL-6 mRNA contains a sequence element that protects it against SOX cleavage [18] . Fusion of the IL-6 3’ UTR to a GFP reporter mRNA ( GFP-3’IL-6 ) prevents SOX-induced cleavage , indicating that protection is transferrable . A 100 nucleotide ( nt ) region of the IL-6 3’ UTR ( nt 790–890 ) is known to be involved in protection [18] . However , deletion of this 100 nt sequence does not eliminate protection from SOX , suggesting that additional flanking sequences might also contribute to escape . To more precisely define the region involved in the escape mechanism , we deleted larger fragments in IL-6 3’UTR , and identified a 200 nt-long sequence encompassing the original element ( nt 689–890 ) that was both necessary and sufficient to confer resistance of the GFP-3’IL-6 fusion to cleavage by SOX ( Fig 1A ) . We refer to this domain as the SOX-resistant element ( SRE ) . RT-qPCR measurements of GFP mRNA levels showed that deletion of the SRE ( GFP-IL-6SRE ) eliminated protection from SOX-induced decay , whereas fusion of just the 200 nt SRE to GFP ( GFP-IL-6 SRE ) was sufficient to confer protection against SOX in transfected 293T cells ( Fig 1B ) . These results were confirmed by measuring the half-life of GFP 3’ IL-6 , SRE and ΔSRE in the presence or absence of SOX ( S1 Fig ) . As observed previously , removing the SRE from the reporter results in stabilization of the transcript , due to the deletion of portions of AU-rich destabilization elements present in the IL-6 3’ UTR [18] . Sequence elements that impact mRNA stability generally function through the specific recruitment of RNA binding proteins that control message fate . To identify the set of factors specifically associated with the SRE , we applied a recently developed ribonucleoprotein ( RNP ) purification tool based on the conditional activity of the Csy4 ribonuclease from the bacterial CRISPR antiviral system ( Fig 1C ) [19] . Briefly , the Csy4 variant H29A/S50C binds extremely tightly ( 50 pm KD ) to a 28 nt CRISPR RNA hairpin , and can be activated to cleave at a precise position in the hairpin in the presence of imidazole [19] . A hairpin-fused RNA segment and its associated RNP complex can therefore be purified by incubation over beads bound by recombinant Csy4 H29A/S50C , released in the presence of imidazole , and subjected to mass spectrometry ( MS ) to identify each of the bound proteins . The CRISPR hairpin sequence was thus fused to the IL-6 SRE or , as a control , to an unrelated sequence corresponding to IL-6 coding region similar in size ( nt 251 to 450 ) , and the in vitro transcribed RNAs were bound to Csy4-coupled beads . Each fragment was then incubated with lysates from B cells stably infected with KSHV ( TREX-BCBL-1 ) or from 293T cells , as the latter were used for the initial IL-6 SRE characterization experiments and thus contain the necessary cohort of factors required for SRE-mediated protection . After stringent washing , the RNP complexes were released by imidazole treatment and subjected to MS ( Fig 1C ) . Of the 450 proteins identified by MS ( S1 Table ) , 23 were specifically associated with or strongly enriched ( at least 7-fold over the control ) on the SRE-containing IL-6 RNA from both TREX-BCBL-1 and 293T lysates ( Table 1 ) . Each of these 23 proteins had a minimum of 3 peptide hits from the IL-6 SRE RNA purification , and a maximum of 1 peptide hit from the control RNA purification . Both AUF1 and HuR , the two known components of the SRE RNP [18] , were re-identified as specific SRE-binding proteins in this manner , indicating that this is a robust methodology for revealing functionally relevant RNA-protein interactions . GO term analysis of this set of SRE-binding proteins revealed seven functional groupings , with a clear enrichment of RNA binding proteins and proteins involved in RNA regulation , as would be expected for factors that control the post-transcriptional fate of an mRNA ( Fig 1D and S2 Table ) . To determine whether the complex of SRE-binding proteins was involved in the IL-6 escape mechanism , we selected 10 candidates for further analysis based on the robustness of their interaction and their putative or characterized roles in the regulation of RNA stability . These included nucleolin ( NCL; the interaction with the most peptide hits ) , as well as STAU1 , hnRNP U , DHX57 , and DHX36 , IGF2BP1 , YTHDC2 , NPM1 , HNRNPAB and ZC3HAV1 . Each factor was individually depleted from 293T cells using specific siRNAs , and the abundance of the GFP-3’IL-6 mRNA in the presence and absence of SOX was measured by RT-qPCR ( Fig 2A and 2B ) . The SRE-containing GFP-3’IL-6 mRNA was protected against SOX-induced degradation in 293T cells transfected with a control nonspecific siRNA ( Fig 2A ) . However , siRNA-mediated depletion of five out of the ten SRE binding proteins significantly decreased the protective effect of the IL-6 3’ UTR ( Fig 2A ) . Out of these five proteins , only NCL knock down resulted in a reduced steady state level of the reporter independently of SOX ( S2 Fig ) , which is not surprising given its known role as a regulator of RNA maturation [20] . It is possible that the effect of these SRE binding protein on IL-6 escape are underestimations of the contribution of each factor towards SRE-mediated protection , as the siRNA treatments resulted in only partial depletion of each endogenous transcript ( Fig 2B ) . However , these data indicate that at least a subset of the SRE-binding proteins we identified by MS are functionally linked to IL-6 escape from degradation by SOX . The strongest decrease in SRE-mediated protection was observed in cells depleted of NCL , and thus we decided to pursue this interaction in more detail . To confirm the interaction of NCL with the IL-6 SRE in vivo , we immunoprecipitated ( IP ) endogenous NCL from 293T cells transfected with either GFP-3’IL-6 or GFP-ΔSRE , and performed qRT-PCR to measure the level of co-precipitating RNA . We observed a ~10-fold enrichment of GFP-3’IL-6 over the mock ( IgG ) IP , but detected no enrichment of the GFP-ΔSRE construct or the negative control RNA ARF1 ( an a priori non-NCL target ) ( Fig 3A and 3B ) . Thus , NCL exhibits an SRE-dependent interaction with the IL-6 3’ UTR in vivo . NCL contains four RNA binding domains ( RBD ) that , when mutated , have been shown to compromise the ability of the protein to bind target RNA [21] . We therefore hypothesized that the RBD should be required for the ability of NCL to potentiate the protective effect of the SRE in complementation assays . To evaluate the importance of this domain in conferring protection from SOX , we first engineered 293T cells to stably express two doxycycline-inducible short hairpin ( sh ) RNAs targeting nucleolin ( 293TΔNCL ) . Doxycycline treatment of these cells resulted in an ~80% reduction of endogenous NCL protein ( Fig 3C ) and , in agreement with the NCL siRNA-based depletion data , rendered the GFP-3’IL-6 mRNA susceptible to SOX-induced degradation ( Fig 3D ) . We first confirmed that the alterations in RNA abundance upon NCL depletion were due to changes in mRNA stability by measuring the half-life of GFP 3’ IL-6 , SRE and ΔSRE in this cell line in the presence or absence of SOX ( S3 Fig ) . We then constructed a mutant version of NCL in which key residues within RBD1 ( F347/Y349 ) and RBD2 ( I429/Y431 ) required for RNA binding were mutated to aspartic acid ( NCLmutRBD ) [21] . Although transfection of WT NCL into doxycycline-treated 293TΔNCL cells rescued protection of the GFP-3’IL-6 mRNA in the presence of SOX , no protective effect was conferred by transfection of the NCLmutRBD ( Fig 3E ) . Ectopic expression of WT NCL not only rescued the protection phenotype , but also increased the basal levels of GFP expression . As we observed in S2 Fig , NCL depletion decreased GFP mRNA steady state levels , but ectopic expression of NCL rescued this decrease ( S4 Fig ) , likely explaining the increase observed in Fig 3E . We confirmed by Western blotting that both proteins were expressed equivalently ( Fig 3F ) . These observations demonstrate that NCL must bind to the SRE to confer protection against SOX . NCL is enriched in the nucleolus , but can also be present to a lesser extent in the nucleoplasm , cytoplasm , and at the plasma membrane [22 , 23] . Cleavage of mRNA by SOX takes place in the cytoplasm [24 , 25] , and thus presumably sufficient cytoplasmic NCL must be present to ensure IL-6 protection during lytic KHSV infection . We monitored endogenous NCL localization in cells latently and lytically infected with KHSV by immunofluorescence assay ( IFA ) and by subcellular fractionation . First , we performed IFA for NCL in KSHV-positive TREX-BCBL-1 cells that were either latently infected or treated with doxycycline to induce lytic replication . In latently infected TREX-BCBL-1 cells , NCL expression was predominantly nucleolar , in agreement with previous reports [26] ( Fig 4A and S1 Video ) . However , upon lytic reactivation , NCL localization shifted dramatically to the nucleoplasm and to punctate granules within the cytoplasm ( Fig 4A and S2 Video ) . We also used subcellular fractionation to monitor NCL localization in a second cell type , KSHV-positive iSLK . 219 cells [27] . Similar to the TREX-BCBL-1 cells , iSLK . 219 cells contain a doxycycline-inducible version of the major KSHV lytic transactivator RTA that enables lytic reactivation . In latently infected iSLK . 219 cells , NCL remained almost exclusively nuclear ( Fig 4B ) . However , in lytically reactivated iSLK . 219 cells , a proportion of NCL was redistributed into the cytoplasm ( Fig 4B ) . These results indicate that lytic KSHV infection induces re-localization of NCL , including into the cytoplasm where SOX-induced mRNA cleavage takes place . NCL is a shuttling protein and contains in its N-terminal region a bipartite nuclear localization signal ( NLS ) [28] . To determine which population of NCL is important for SRE-mediated protection from SOX , we generated an NCL NLS mutant ( NCLΔNLS ) that was restricted to the cytoplasm , as well as a version of NCL fused to a nuclear retention signal ( NRS-NCL ) that was restricted to the nucleus ( Fig 4C ) . We verified by Western blot ( WB ) that these constructs were expressed at similar levels ( Fig 4C ) . It should be noted that although the intensity of the nuclear staining of WT NCL made it difficult to detect the cytoplasmic population by IFA , subcellular fractionation experiments confirmed that in 293T cells both endogenous and transfected WT NCL could be detected in both compartments ( S5 Fig ) . We next evaluated the ability of each protein to rescue SRE-mediated escape from SOX degradation in the 293TΔNCL cell line . Both WT NCL and NCLΔNLS rescued levels of the GFP-3’IL-6 mRNA in the presence of SOX ( Fig 4D ) . However , NRS-NCL was unable to rescue GFP3’IL-6 mRNA from SOX degradation ( Fig 4D ) Taken together , these results demonstrate that cytoplasmic NCL is involved in SRE-mediated protection . Finally , we analyzed whether depletion of NCL from iSLK . 219 cells by siRNA treatment impacted IL-6 mRNA levels and/or the lytic KSHV lifecycle . Indeed , NCL knockdown reduced the abundance of IL-6 mRNA during the KSHV lytic cycle compared to cells treated with control siRNAs ( S6A Fig ) . This effect is not as robust as the effects of NCL depletion in the context of SOX transfection , likely because during infection KSHV has several other mechanisms to transcriptionally and post-transcriptionally increase IL-6 abundance [29 , 30] . We also detected a robust impairment of expression of KSHV late gene expression as measured by K8 . 1 levels , as well as a corresponding failure of the infected cells to produce progeny virions in supernatant transfer assays ( S6B and S6C Fig ) . These results are supportive of a role for NCL in IL-6 protection in the context of KSHV infection , although NCL clearly plays additional crucial roles in the KSHV lifecycle . To determine whether the location of the SRE might impact protection , we tested the effect of moving the SRE from the 3’ UTR to the 5’ UTR on the GFP reporter ( GFP-5’ SRE ) . Unlike the GFP-3’ SRE mRNA , the GFP-5’ SRE mRNA was degraded in SOX-expressing cells , indicating that SRE positioning is important ( Fig 5A ) . This could be explained if ribosome scanning through the 5’ UTR disrupted NCL binding to the SRE , and/or if NCL positioning on an mRNA impacted its interactions with other mRNA-bound proteins to potentiate protection from SOX . We tested the first part of this hypothesis by measuring the efficiency with which NCL associated with the GFP-5’ SRE compared to GFP 3’ SRE . NCL displayed significantly reduced binding to the GFP-5’ SRE mRNA in RNA IPs , suggesting that the SRE RNP does not assemble efficiently if located in the 5’ UTR ( Fig 5B ) . We next pursued the idea that once recruited to the SRE , NCL-induced protection from SOX may involve its interaction with other cellular proteins . Previously described protein interactions of NCL largely occur through its C-terminal arginine-glycine repeat ( RGG ) region [23 , 31–35] . NCLΔRGG failed to protect the GFP-3’IL-6 mRNA from SOX in the doxycycline-treated 293TΔNCL cell line ( Fig 5C and 5D ) , indicating a role for protein interactions in the SRE escape function of NCL . It should be noted that although the ΔRGG mutant is expressed at lower levels , increasing the amount transfected to produce levels matching those of WT did not rescue the protection phenotype ( S7 Fig ) . Because the 5’ cap and 3’ poly ( A ) tail are defining mRNA features and positionally fixed , we hypothesized that interactions with one or more factors bound to these elements might impact the SRE-related function of NCL . We further reasoned that protein-protein interactions related to SOX resistance might be enhanced specifically during lytic KSHV infection , when NCL relocalization occurs . Using a targeted approach , we therefore searched for mRNA-associated factors that displayed selective or enhanced binding to NCL during lytic KSHV infection using co-immunoprecipitation ( co-IP ) assays . We found the cap-associated translation initiation factor eIF4H to selectively immunoprecipitate NCL from lytically but not latently infected iSLK219 cells ( Fig 6A ) . This enrichment appeared specific to eIF4H , as we detected no differential interaction profile for NCL with additional mRNA cap- or tail-bound proteins including eIF4G , eIF4E , eIF4B and PABPC ( S8 Fig ) . The interaction between NCL and eIF4H was disrupted when the lysates were treated with RNase ( Fig 6A ) , in agreement with the idea that these proteins are not normally stably associated , but are brought together in the context of mRNA-bound NCL via a long-range interaction . Furthermore , the NCLΔRGG mutant failed to bind eIF4H in co-IP assays ( Fig 6B ) , while still being able to bind specifically to a SRE containing reporter ( Fig 6C ) , suggesting that the failure of this mutant to protect SRE-containing mRNAs from SOX may be due , at least in part , to its inability to bind eIF4H . We reasoned that if the NCL-eIF4H interaction played a role in the escape of SRE-containing mRNAs from SOX cleavage , then depletion of eIF4H should decrease the efficiency of escape . Indeed , similar to our results with NCL , siRNA-mediated depletion of eIF4H rendered the GFP-3’IL-6 susceptible to degradation by SOX ( Fig 6D ) . Depletion of eIF4H did not affect the expression of SOX , NCL , or XrnI , arguing against a generalized impediment of protein translation in these experiments ( S9 Fig ) . This was not unexpected , given that an increasing number of translation factors previously thought to have generalized roles in translation , including the eIF4F complex , have instead been shown to be selectively required for only specific types of host mRNAs [36 , 37] . Viruses that promote widespread degradation of mRNA generally do so by encoding endonucleases or endonuclease-activating proteins [38–40] . We therefore explored the possibility that the IL-6 SRE might also confer protection against additional viral endonucleases . Herpes simplex virus ( HSV ) encodes an mRNA-targeting endonuclease ( vhs ) that , while not homologous to KSHV SOX , degrades most mRNAs during infection [41–44] . To test whether the SRE conferred protection against HSV-1 vhs , we measured by RT-qPCR the ability of vhs to degrade the GFP reporter mRNA fused to the IL-6 3’ UTR versus the control IL-6 5’ UTR . Intriguingly , the IL-6 3’ UTR as well as IL-6 SRE conferred complete protection from vhs , while the GFP mRNA containing the IL-6 5’UTR or ΔSRE was readily degraded ( Fig 7A ) . To determine whether protection from vhs-mediated cleavage required NCL , we co-expressed vhs and GFP-3’IL-6 in the 293TΔNCL cell line . Upon Dox treatment to deplete NCL , GFP-3’IL-6 was no longer protected from vhs ( Fig 7B ) . Thus , the SRE-containing IL-6 3’UTR can block mRNA cleavage by at least two non-homologous endonucleases via an NCL-dependent mechanism .
RNA degradation rates are heavily impacted by the cohort of proteins associated with each transcript , and here we define an RNP complex that inhibits viral endonuclease targeting . Unlike the majority of mRNAs in the cytoplasm that are degraded by the SOX endonuclease during lytic KSHV infection , the IL-6 mRNA is strongly induced and directly refractory to cleavage by SOX [8 , 17] . Although other mRNAs can also escape cleavage , IL-6 is the only mRNA known to escape via a dominant protective mechanism . We found that the 200 nt IL-6 protective element directs assembly of a large RNP complex , of which five components associated with the regulation of mRNA stability have now been shown to contribute to escape from SOX [18] . Notably , this escape element also functions to guard mRNAs against the HSV-1 vhs nuclease , despite the fact that vhs and SOX are unrelated and cleave mRNAs at distinct sites [11 , 45] . This key observation suggests that the underlying mechanism of escape does not involve a SOX-specific feature but instead must involve the general accessibility of the mRNA to these ( and perhaps other ) cytoplasmic endonucleases . Although not homologous , SOX and vhs do share certain features in their RNA targeting strategies . Both proteins selectively cleave mRNA but not RNAs transcribed by RNA Polymerase I or III [44 , 46 , 47] . Furthermore , both proteins can target mRNAs prior to recruitment of the 40S ribosomal subunit , suggesting that ongoing translation of the target mRNA is not required for cleavage [46] . However , translation may nonetheless play some role in targeting , as vhs cleavage sites can be altered by mutating the target mRNA start codon or Kozak consensus context , and SOX can cleave mRNAs in polysomes [11 , 40 , 48] . While the factor ( s ) involved in recruiting SOX to its mRNA targets remain unknown , vhs recruitment involves interactions with the translation initiation factors eIF4H and eIF4AI/II [49 , 50] . Once brought to the mRNA , vhs tends to cleave in a cap-proximal manner in the 5’ UTR or near the start codon [48 , 51] , whereas SOX requires a specific recognition sequence that can be located at sites far downstream from the cap [11 , 40 , 48] . The observation that SOX and vhs cleave mRNAs at distinct sites suggests that there must be differences in their mechanisms of targeting . In this regard , SRE-mediated protection could occur by blocking a factor required for both SOX and vhs recruitment to mRNAs . It is notable that eIF4H has been shown to bind vhs and help direct it to mRNAs [48 , 49 , 52 , 53] . However , unlike with vhs , no interaction between SOX and eIF4H have been reported in the literature , arguing against eIF4H accessibility as the feature underlying endonuclease escape for both vhs and SOX . The escape mechanism for these viral proteins is therefore expected to be different , although it is possible that an additional factor required for both SOX and vhs recruitment is occluded or displaced by the SRE RNP . Alternatively , the SRE may direct localization of the IL-6 mRNA into SOX- and vhs-inaccessible sites in the cytoplasm . Although the fate of IL-6 during HSV-1 infection remains unknown , other specific mRNAs have been shown to escape degradation by vhs , some of which contain AU-rich elements in their 3’ UTR [54 , 55] . This has been studied most intensively for the IEX-1 mRNA , however , at present , reports differ as to what form of the IEX-1 mRNA is stabilized during infection and the precise role of vhs in altering IEX-1 mRNA decay [55–59] . Both GADD45β and the ARE-containing TTP mRNAs have also been shown to be directly refractory to vhs-mediated decay and are up-regulated at the protein level during HSV-1 infection [54 , 55 , 57] . Like IEX-1 and TTP , the IL-6 3’ UTR contains an ARE , which overlaps with the SRE [17] . While it is perhaps notable that the best-studied herpesviral escapees contain AREs , ARE-bearing mRNAs are not enriched in the overall pool of SOX escapees and the majority of ARE mRNAs are susceptible to degradation by SOX [13] , arguing against this being the feature driving the IL-6 protective mechanism . Among the proteins identified to selectively bind the SRE , NCL was the most potent modulator of escape . NCL has diverse roles in RNA biogenesis and has been previously shown to affect mRNA turnover [20] . Although the effects of NCL differ depending on the target transcript , it has been reported to interact with the 3′UTR of numerous mRNAs and enhance their stability . Known targets include amyloid precursor protein ( APP ) , β-globin , Bcl-2 , Bcl-xL , interleukin 2 ( IL-2 ) , and the growth arrest- and DNA damage-inducible 45 ( GADD45A ) [60–63] . NCL stabilization of mRNAs has also been linked to its ability to bind AREs [61 , 64 , 65] . One notable example is NCL-mediated stabilization of the GADD45A mRNA which , similar to IL-6 , occurs via the binding of NCL at its 3’UTR [63] . GADD45A is one of the transcripts identified by RNAseq as being refractory to SOX cleavage [13] and to be up-regulated during HSV-1 infection [66] . Similar to what we observed during KSHV infection , stabilization of GADD45A is associated with the re-localization of NCL from dense nuclear foci to the nucleoplasm and cytoplasm upon arsenic-induced stress [63] . Thus , redistribution of NCL may contribute to stabilization of multiple stress-responsive mRNAs upon chemical or viral insults . Although NCL clearly contributes to SRE function , the composition of the 200 nt SRE complicates the ability to make a direct and selective link between NCL and SOX escape . For example , a portion of the SRE contains AU-rich sequences , which are elements with established roles in the destabilization of many labile mRNAs [67] . Furthermore , the facts that NCL has been implicated in numerous aspects of mRNA biology and can impact the abundance of non-SRE mRNAs ( such as GFP ) highlight the broad effects this protein has in cells . Thus , it is possible that depletion of NCL has secondary effects on mRNA accumulation that indirectly influence the stability of IL-6 in SOX-expressing cells . Nonetheless , our observations that NCL binds specifically to the SRE and that this binding in the cytosol is required for protection against SOX suggest that at least some aspects of SRE-mediated escape from SOX are connected to the presence of NCL in the SRE-bound protein complex . In this regard , NCL-induced mRNA stabilization often involves its interaction with other RBPs , including HuR [63] and AUF1 [68] , both of which are important for IL-6 escape from SOX degradation [18] . Given that NCL is a highly connected protein [23 , 31–35] , it could act as a hub to assemble larger protein complexes , perhaps explaining its potent role in the escape mechanism . For example , it interacts with several of the identified SRE-binding proteins , including NPM1 [69 , 70] and STAU1 [71 , 72] . Here , we describe a novel interaction between NCL and the helicase accessory factor eIF4H . The fact that the NCL-eIF4H interaction selectively occurs during lytic but not latent KSHV infection suggests that this interaction is facilitated by NCL relocalization to the cytoplasm , although infection could also alter the translational requirements for eIF4H . The RNA-dependent nature of the NCL-eIF4H interaction indicates that these proteins associate in the context of mRNA-bound NCL , rather than freely in the cytoplasm , and demonstrates the importance of long-range interactions in mediating protection from SOX . Differential interactions between NCL and other translation-linked proteins were not observed , suggesting that NCL and eIF4H may selectively associate with specific mRNAs . In this regard , it is possible that eIF4H does not play a widespread role in translation but is instead recruited to a subset of mRNAs including IL-6 . While not yet explored for eIF4H , it has recently been shown that the cap binding complex eIF4F is preferentially required for the translation of mRNAs that contain 5’ pyrimidine-rich elements [36 , 37] . Furthermore , eIF4H has a closely related homolog in mammalian cells , eIF4B , which might play a role redundant to that of eIF4H on other mRNAs [73 , 74] . It will be of interest to determine whether additional NCL-bound mRNAs recruit eIF4H and , additionally , whether other NCL and eIF4H-bound mRNAs escape SOX and vhs . Furthermore , it would be interesting to explore whether KSHV infection favors differential expression of the translation initiation complex components and whether this influences viral gene expression and/or escape from viral induced host shutoff . Cytoplasmic NCL has been shown to be co-opted by a diverse set of viruses , including to help mediate the human respiratory syncytial virus entry , HIV gag complex assembly , and poliovirus virion formation [75–78] . NCL also plays a positive role in HSV-1 infection [75] , where , similar to KSHV infection , it is relocalized to the nucleoplasm and cytoplasm [79 , 80] . Thus , although NCL is directly involved in mediating protection of IL-6 , it is likely that its cytoplasmic relocalization during KSHV reactivation plays additional roles in the viral lifecycle , as its depletion also causes strong defects in K8 . 1 late gene expression and virion production . At present it is difficult to distinguish its role in IL-6 mRNA accumulation during KSHV infection from its additional crucial roles in the viral life cycle . NCL localization has been linked to its phosphorylation state [81 , 82] . Thus , one possibility is that NCL is phosphorylated by one of the herpesviral protein kinases , although infection may also activate NCL-targeting cellular kinase cascades . Future studies are anticipated to reveal whether the cytoplasmic population of NCL is posttranslationally modified during infection , and whether this facilitates its interactions that form the basis for SRE-mediated protection .
The KSHV-positive B cell line bearing a doxycycline-inducible version of the major lytic transactivator RTA ( TREX-BCBL-1 ) [83] was maintained in RPMI medium ( Invitrogen ) supplemented with 10% fetal bovine serum ( FBS; Invitrogen ) , 200 μM L-glutamine ( Invitrogen ) , 100 U/ml penicillin/streptomycin ( Invitrogen ) , and 50 μg/ml hygromycin B ( Omega Scientific ) . Lytic reactivation was induced by treatment with 20 ng/ml 2-O-tetradecanoylphorbol-13-acetate ( TPA; Sigma ) , 1 μg/ml doxycycline ( BD Biosciences ) , and 500 ng/ml ionomycin ( Fisher Scientific ) for 48h . 293T cells ( ATCC ) were grown in DMEM ( Invitrogen ) supplemented with 10% FBS . The KHSV-infected renal carcinoma cell line iSLK . 219 bearing doxycycline-inducible RTA were grown in DMEM supplemented with 10% FBS [84] . KSHV lytic reactivation of the iSLK . 219 cells was induced by the addition of 0 . 2 μg/ml doxycycline ( BD Biosciences ) and 110 μg/ml sodium butyrate for 48 h . For supernatant transfer experiments , the supernatant of iSLK . 219 cells reactivated or not was collected after 48h , filtered through a . 45uM filter and spinfected onto fresh 293T for 1h at 1500rpm . Cells were then fixed and mounted onto slides to visualize with a confocal microscopy on a Zeiss LSM 710 AxioObserver microscope . 293TΔNCL were generated by lentiviral transduction . Briefly , psPAX2 and pMD2 . G lentiviral plasmids were co-transfected with pTRIPZ plasmids encoding Doxyclyclin inducible shRNAs targeting NCL ( V2THS_36645 and V2THS_36643 from Open Biosystems , kindly provided by Chih-Wen Peng at Tzu-Chi University ) . Supernatant containing viral particles was collected 48h later , filtered , complemented with 8 μg/mL polybrene and centrifuged onto target 293T cells . For DNA transfections , cells were plated and transfected after 24h when 70% confluent using linear PEI ( polyethylenimine ) . For small interfering RNA ( siRNA ) transfections , 293T cells were reverse transfected in 12-well plates by INTERFERin ( Polyplus-Transfection ) with 10 μM of siRNAs . siRNAs were obtained from IDT as DsiRNA and sequences are as described in S3 Table . 48h following siRNA transfection , the cells subjected to DNA transfection as indicated . For time course experiments , half-live were measured by transfecting 293T or 293TΔNCL cells with the indicated plasmids in 6-well plates . The cultures were split after 6 h into 12-well plates and 12 h later treated with 5 μg/mL Actinomycin D ( ActD ) for the indicated times . The extracted RNAs were subjected to qPCR analysis and GFP mRNA levels were normalized to the level of 18S rRNA . The full-length IL-6 cDNA in pCMV-SPORT6 . 1 was obtained from Invitrogen . Sequence numbering for IL-6 refers to Homo sapiens interleukin 6 ( interferon , beta 2 ) , mRNA ( GenBank accession number BC015511 . 1 ) . The GFP-IL-6 3’UTR and GFP-IL-6 SRE fusion constructs were described previously [18] , and the GFP-IL-6 3’UTR ΔSRE construct was obtained by overlap PCR into the pcDNA3 . 1 IL-6 3’UTR plasmid cut with BlpI and XbaI with the following primers ( primers sequences are described in S4 Table ) ; IL-6 ΔSRE PCR1 and PCR2 , forward and reverse . The Csy4 recognition motif was fused to the SRE or IL-6 nucleotide sequence 251–450 by PCR with the Csy4 primers ( S4 Table ) and cloned into the KpnI and XhoI sites of pcDNA3 . 1 . NCL was obtained from 293T total cDNA and cloned into the Gateway entry vector pDON207 ( Invitrogen ) using the following primers ( S4 Table ) : NCL-Forward and Reverse . It was then transferred into the gateway-compatible destination vector pCiNeo-3xFlag to generate Flag-NCL fusions . For the NCL ΔRGG mutant , the same forward primer was used , but with ΔRGG Reverse primer was . Other mutations were introduced with the Quickchange site directed mutagenesis protocol ( Agilent ) using the following primers: NCL ΔNLS; NCLmutRBD mutant was generated in a two-step process to introduce mutations both in the RNA binding domains 1 and 2 as described in [21]: RBD1 mutating F347 and Y349 into D in NCL RBD1 domain; to generate the final NCLmutRBD , this RBD1 mutant was further mutated at residues I429 and Y431 into D in the RBD2 domain . The final NCLmutRBD mutant thus contains 4 mutations . Csy4 H29A/S50C was expressed and purified using the same protocol as wild-type Csy4 ( generously provided by R . Haurwitz , H . Y . Lee , and J . Doudna ) [19 , 85] . Plasmids expressing the Csy4 RNA binding motif fused to segments of IL-6 were in vitro transcribed using the T7 Maxiscript kit ( Ambion ) . Transcribed RNA ( 20 μg ) was mixed with purified recombinant Csy4 protein ( 200 pmol ) and magnetic beads for 2h in lysis buffer [10 mM HEPES ( pH 8 . 0 ) , 3 mM MgCl2 , 5% glycerol , 1 mM dithiothreitol ( DTT ) , 150 mM NaCl , 0 . 1% octyl β-d-glucopyranoside , 10 mM imidazole , 1× protease inhibitor] . Lysate from TREX-BCBL1 or 293T cells ( 1 mg ) was then added to the beads for 2h , whereupon the beads were washed 7 times with lysis buffer containing 150 to 300 mM NaCl . RNA and its associated cellular proteins were released from the Csy4-bound beads by the addition of 500 mM imidazole for 2h to activate the cleavage activity of Csy4 . Eluates were processed , trypsin digested , and concentrated for LC-MS/MS . Digested peptide mixtures were analyzed by LC-MS/MS on a Thermo Scientific Velos Pro ion trap mass spectrometry system equipped with a Proxeon Easy nLC II high pressure liquid chromatography and autosampler system . Specific protein bands were excised from a gel and subjected to in-gel tryptic digestion . The gel bands were reduced with 10 mM dithiothreitol ( Sigma-Aldrich ) at 56°C for 1 hour , followed by alkylation with 55 mM iodoacetamide ( Sigma ) at room temperature in dark for 45 minutes . The samples were then incubated overnight with 100ng trypsin ( Promega ) at 37°C . The peptides formed from the digestion were extracted using 50% acetronitrile and 5% formic acid , and then re-suspended in 10 μl of 0 . 1% formic acid in water and analyzed by on-line LC-MS/MS technique . The LC separation was performed using a NanoAcquity UPLC system ( Waters ) while the MS/MS analysis was performed using a LTQ Orbitrap XL mass spectrometer ( Thermo Scientific ) . During the LC separation step , 0 . 1% formic acid in water was used as the mobile phase A and 0 . 1% formic acid in acetonitrile was employed as the mobile phase B . Following the initial equilibration of the column in 98% A /2% B , 5 μL of the sample was injected . A linear gradient was started with 2% B and increased to 25% B in 33 mins followed by an increase to 60% B in the next 12 mins at a flow rate of 400 nL/min . The subsequent MS analysis was performed using a top six data-dependent acquisition . The sequence includes one survey scan in the FT mode in the Orbitrap with mass resolution of 30 , 000 followed by six CID scans in LTQ , focusing on the first six most intense peptide ion signals whose m/z values were not in the dynamically updated exclusion list and their intensities were over a threshold of 1000 counts . The analytical peak lists were generated from the raw data using an in-house software , PAVA [86] . The MS/MS data were searched against the UniProt database using an in-house search engine Protein Prospector ( http://prospector . ucsf . edu/prospector/mshome . htm ) . Total RNA was harvested using Zymo RNA extraction columns following the manufacture's manual . cDNAs were synthesized from 1 μg of total RNA using AMV reverse transcriptase ( Promega ) , and used directly for quantitative PCR ( qPCR ) analysis with the DyNAmo ColorFlash SYBR green qPCR kit ( Thermo Scientific ) . Signals obtained by qPCR were normalized to 18S . Cells were lysed in low-salt lysis buffer [NaCl 150mM , NP-40 0 . 5% , Tris pH8 50mM , DTT 1mM , protease inhibitor cocktail] and protein concentrations were determined by Bradford assay . Equivalent quantities of each sample were incubated overnight with the indicated antibody , and then with G-coupled magnetic beads ( Life technologies ) for 1h . Where indicated , specific beads coupled to antibodies were used ( M2 anti-flag beads; Sigma ) . Beads were washed extensively with lysis buffer . Samples were resuspended in Western blot loading buffer before resolution by SDS-PAGE . Where indicated , RNAse A and T1 were added to the lysates . Cell lysates were prepared in lysis buffer and quantified by Bradford assay . Equivalent amounts of each sample were resolved by SDS-PAGE and Western blotted with the following antibodies: Rabbit anti-NCL ( Abcam ) , Mouse anti-NCL ( Santa Cruz ) , Rabbit anti-eIF4H ( Cell signaling ) . Rabbit anti-Flag ( Sigma ) , Mouse anti hnRNPC1/C2 ( Abcam ) , Rabbit anti-H3 ( Cell Signaling ) , Rabbit anti-Xrn1 ( Sigma ) , Mouse anti-Strep ( Qiagen ) . Primary antibodies were followed by HRP-conjugated goat anti-mouse or goat anti-rabbit secondary antibodies ( Southern Biotechnology , 1:5000 ) . 293T or TREX-BCBL1 cells were grown on coverslips , and fixed in 4% formaldehyde for 20 min at room temperature . Cells were then permeabilized in 1% Triton-X-100 and 0 . 1% sodium citrate in PBS for 10 min , saturated in BSA for 30 min and incubated with the indicated antibodies . After 1h , coverslips were washed in PBS and incubated with AlexaFluor594 or AlexaFluor488 secondary antibodies at 1:1500 ( Invitrogen ) . Coverslips were washed again in PBS and mounted in DAPI-containing Vectashield mounting medium ( VectorLabs ) to stain cell nuclei before visualization by confocal microscopy on a Zeiss LSM 710 AxioObserver microscope . All results are expressed as means ± S . E . M . of experiments independently repeated at least three times . Unpaired Student's t test was used to evaluate the statistical difference between samples . Significance was evaluated with pValues as follows: * p<0 . 1; ** p<0 . 05; *** p<0 . 01 .
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During replication of Kaposi’s sarcoma-associated herpesvirus ( KSHV ) , the vast majority of mRNAs in the cytoplasm are cleaved and degraded by the viral nuclease SOX . However , some mRNAs escape this fate , including the transcript encoding the immunoregulatory cytokine IL-6 . Here , we discover that this escape is mediated by a group of proteins that associates with a sequence element on the IL-6 mRNA . One of these proteins is nucleolin ( NCL ) , a factor with diverse roles in RNA processing that is frequently co-opted during viral infection . During KSHV replication , a proportion of NCL is redirected from the nucleolar subcompartment of the nucleus into the cytoplasm , where it binds both the IL-6 3’ UTR and a complex of cellular proteins including the translation initiation factor eIF4H . This network of interactions is required for escape from virus-induced degradation . Collectively , these findings reveal novel interplay between the SOX escapees and the cellular mRNA stabilization machinery , and shed light on the complex crosstalk between viruses and hosts over the control of gene expression .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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A Ribonucleoprotein Complex Protects the Interleukin-6 mRNA from Degradation by Distinct Herpesviral Endonucleases
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Epigenetic variation , such as heritable changes of DNA methylation , can affect gene expression and thus phenotypes , but examples of natural epimutations are few and little is known about their stability and frequency in nature . Here , we report that the gene Qua-Quine Starch ( QQS ) of Arabidopsis thaliana , which is involved in starch metabolism and that originated de novo recently , is subject to frequent epigenetic variation in nature . Specifically , we show that expression of this gene varies considerably among natural accessions as well as within populations directly sampled from the wild , and we demonstrate that this variation correlates negatively with the DNA methylation level of repeated sequences located within the 5′end of the gene . Furthermore , we provide extensive evidence that DNA methylation and expression variants can be inherited for several generations and are not linked to DNA sequence changes . Taken together , these observations provide a first indication that de novo originated genes might be particularly prone to epigenetic variation in their initial stages of formation .
DNA mutations are the main known source of heritable phenotypic variation , but epimutations , such as heritable changes of gene expression associated with gain or loss of DNA methylation , are also a source of phenotypic variability . Indeed , several stable DNA methylation variants affecting a wide range of characters have been described , mainly in plants [1]–[3] . In most instances , epimutations are linked to the presence of structural features near or within genes , such as direct [4]–[6] or inverted repeats [7] , [8] or transposable element ( TE ) insertions [9] , which act as units of DNA methylation through the production of small interfering RNAs ( siRNAs ) [3] , [10] . Examples of epimutable loci in Arabidopsis thaliana ( A . thaliana ) include the PAI [7] and ATFOLT1 genes [8] , which have suffered siRNA-producing duplication events in some accessions and also the well characterized FWA locus , which contains a set of SINE-derived siRNA-producing tandem repeats at its 5′end [4] , [5] . Repeat-associated epimutable loci are almost invariably found in the methylated form [5]–[9] in nature , which reflects , at least in part , that DNA methylation is particularly well-maintained over repeats [11] , [12] . Indeed , epigenetic variation at PAI , ATFOLT1 and FWA has only been observed in experimental settings . Similarly , sporadic gain or loss of DNA methylation associated with changes in gene expression has only been documented in A . thaliana mutation accumulation lines [13] , [14] and examples of natural epigenetic variation in other plant species are few [15]–[17] . Here we report a case of prevalent natural epigenetic variation in A . thaliana , which concerns a de novo originated gene [18] . We show that expression of this gene , named Qua-Quine Starch ( QQS ) , is inversely correlated with the DNA methylation level of its promoter and that these variations are stably inherited for several generations , independently of DNA sequence changes . Based on these findings , we speculate that epigenetic variation could be particularly beneficial for newly formed genes , as it would enable them to explore more effectively the expression landscape than through rare DNA sequence changes .
The A . thaliana Qua-Quine Starch ( QQS , At3g30720 ) was first described as a gene involved in starch metabolism in leaves [19] , [20] . Despite being functional and presumably already under purifying selection ( dN/dS = 0 . 5868; p-value<0 . 045 ) , QQS is likely a recent gene that emerged de novo . Indeed , QQS has no significant similarity to any other sequence present in GenBank [18] , [19] , suggesting that it originated from scratch since A . thaliana diverged from its closest sequenced relative A . lyrata around 5–10 million years ago . Furthermore , QQS encodes a short protein ( 59 amino acids ) and it is differentially expressed under various abiotic stresses [18] , which are also hallmarks of de novo originated genes [21]–[23] . As shown in Figure 1 , QQS is surrounded by multiple transposable element sequences ( Figure 1A ) and contains several tandem repeats in its promoter region and 5′UTR ( Figure 1B ) . In the Columbia ( Col-0 ) accession , these tandem repeats are densely methylated and produce predominantly 24 nt-long siRNAs ( Figure 1B , Figure S1A and S1B ) . Publically available transcriptome data [24] , [25] and results of RT-qPCR analyses ( Figure S1C ) show that steady state levels of QQS mRNAs are higher in several mutants affected in the DNA methylation of repeat sequences , including met1 ( DNA METHYLTRANSFERASE 1 ) , ddc ( DOMAINS REARRANGED METHYLTRANSFERASE 1 and 2 and CHROMOMETHYLASE 3 ) , ddm1 ( DECREASE IN DNA METHYLATION 1 ) and rdr2 ( RNA-DEPENDENT RNA POLYMERASE 2 ) , which abolishes the production of 24 nt-long siRNAs as well as most CHH methylation . These findings indicate that QQS expression is negatively controlled by DNA methylation and point to the siRNA-producing tandem repeats as being potentially involved in this repression . We first observed epiallelic variation at QQS unexpectedly , in a Col-0 laboratory stock ( hereafter referred to as Col-0* ) with increased expression of the gene and decreased DNA methylation of its promoter and 5′UTR repeat elements ( Figure 2A ) . No sequence change could be detected in the Col-0* stock within a 1 . 2 kb region covering the QQS gene ( Figure 1B ) , which excluded local cis-regulatory DNA mutations at the QQS locus as being responsible for DNA methylation loss in Col-0* . Additionally , comparative genomic hybridization analysis as well as genome-wide DNA methylation profiling using methylated DNA imunoprecipitation assays revealed no major differences between Col-0 and Col-0* ( Figure S2 ) . We next investigated the QQS epigenetic status in pooled seedlings ( S1 ) derived from the selfing of 12 individual Col-0* plants ( Figure S3 ) . Results revealed a range of QQS epialleles and a strong negative correlation between DNA methylation and expression of the gene ( Figure 2B and 2C ) . To explore further this variation , a single S1 individual was then selfed for each of the 12 lines and seedlings ( S2 ) were analyzed in pool for each line , as above ( Figure S3 ) . Remarkably , the differences in QQS expression and DNA methylation observed at the S1 generation were also observed at the S2 generation ( Figure 2B and 2C ) . Taken together , these results suggest therefore the existence of a range of epiallelic variants at QQS , which are stably inherited for at least one generation . The inheritance of QQS hypomethylated epialleles was also examined in a random sample of 19 ddm1-derived epigenetic Recombinant Inbred Lines ( epiRILs ) obtained by crossing a Col-0 wild-type ( wt ) line with an hypomethylated Col-0 ddm1 line [26] . High DNA methylation/low expression and low DNA methylation/high expression of QQS were observed in 14 and 5 epiRILs , respectively ( Figure 2D ) . This is consistent with Mendelian segregation of the highly methylated/lowly expressed Col-0 wt and lowly methylated/highly expressed Col-0 ddm1 parental QQS epialleles ( 75%/25% expected because of backcrossing rather than selfing of the F1; Chi2 = 0 , 017 , p-value>0 . 05 ) . Indeed , examination of the epi-haplotype obtained for 17 of these epiRILs [27] confirmed the wt or ddm-origin of the QQS locus in each case ( data not shown ) . These results demonstrate therefore that , like many other ddm1-induced epialleles [28] , [29] , QQS hypomethylated epialleles can be stably inherited for at least eight generations and are not targets of paramutation . We next investigated the degree to which DNA methylation of QQS and of flanking TEs are independent from each other . To this end , we first analyzed DNA methylation patterns of TE sequences flanking QQS in a series of epiRIL with contrasted QQS epialleles . Unlike for ddm1-derived QQS , hypomethylation was not inherited for the three TEs located immediately upstream of the gene , as they did systematically regain wt DNA methylation levels ( Figure 3A and 3B ) , presumably because of their efficient targeting by RNA-directed DNA methylation ( RdDM ) [28] . In addition , although the TE just downstream of QQS was always hypomethylated when inherited from ddm1 , hypomethylation was also observed in one epiRIL that inherited the QQS region from the wt parent . Thus , there is no strict correlation between DNA methylation at QQS and this downstream TE . We next examined the effect of several T-DNA and transposon insertions located ∼3 . 1 kb or 153 bp upstream of the transcription start site ( TSS ) , 653 bp downstream of the 3′UTR and within the second coding exon of QQS . Whereas three of these insertions had no effect on DNA methylation and expression levels of QQS , the T-DNA insertion located closest to the TSS was associated with a drastic reduction of DNA methylation of both the promoter and 5′UTR of the gene , as well as with an increase in QQS expression ( Figure 3A and 3C ) . However , this insertion had no impact on DNA methylation of upstream and downstream TEs ( Figure 3A and 3D ) . Taken together , these results suggest that epigenetic variation at QQS is most likely determined by sequences within the promoter and 5′UTR of the gene , not by the TEs that are located immediately upstream or downstream . We next investigated the possibility that QQS is subject to epigenetic variation in natural populations . To this end , we first analyzed QQS expression and DNA methylation in 36 accessions representing the worldwide diversity [30] . QQS was methylated and lowly expressed in 29 accessions , but unmethylated and highly expressed in seven accessions distributed over the entire geographic range ( Figure 4A ) . This indicates that epigenetic variation at QQS is widespread in nature . In contrast , upstream and downstream TEs were consistently methylated in all accessions ( Figure S4A and S4B ) , thus confirming that the epigenetic state at QQS is not determined by that of flanking TEs . We then sequenced a 2 . 8 kb interval encompassing the QQS gene and its flanking regions from the seven accessions carrying the hypomethylated/highly expressed epiallele as well as from three accessions carrying a methylated/lowly expressed epiallele . Although several SNPs and indels were identified ( Figure S4C ) , no correlation between any specific sequence alterations and QQS DNA methylation or expression states could be established ( Figure 4A ) . In addition , while Kondara and Shahdara have identical QQS sequences , they have contrasted DNA methylation/expression patterns at the locus ( Figure 4A and Figure S4C ) , which provides further evidence that natural epiallelic variation at QQS is independent of local cis-DNA sequence polymorphisms and is thus most likely truly epigenetic . Analysis of a Cvi-0 vs . Col-0 Recombinant Inbred Line ( RIL ) population revealed in addition that QQS expression is controlled by a large-effect local-expression quantitative trait locus ( local-eQTL; http://qtlstore . versailles . inra . fr/ ) [31] . This suggests that like the Col-0 wt and Col-0 ddm1 QQS epialleles ( Figure 2D ) , the Cvi-0 hypomethylated QQS epiallele is stably inherited across multiple generations . This further demonstrates that epigenetic variation at QQS is not appreciably affected by sequence or DNA methylation polymorphisms located elsewhere in the genome and indicates also that QQS is not subjected to paramutation [29] . To validate experimentally the causal relationship between DNA methylation and repression at QQS , seedlings of several accessions were grown in the presence of the DNA methylation inhibitor 5-aza-2′-deoxycytidine ( 5-aza-dC ) . In the two accessions Col-0 and Shahdara , which harbor distinct methylated and lowly expressed QQS alleles , treatment resulted in reduced DNA methylation and increased expression of QQS ( Figure S4D ) . In contrast , seedlings of Jea , Kondara and Cvi-0 accessions , all of which harbor a demethylated/highly expressed QQS allele , did not show further reduction of DNA methylation or increased expression when grown in the presence of the demethylating agent ( Figure S4D ) . Moreover , whereas expression of QQS in F1 hybrids derived from crosses between Col-0 ( methylated QQS ) and Kondara ( hypomethylated QQS ) , was always higher for the epiallele inherited from the hypomethylated parent , further confirming that QQS is not subjected to paramutation [29] , treatment with 5-aza-dC reduced dramatically this expression imbalance , most likely as a consequence of demethylation of the Col-0-derived QQS allele ( Figure S4E ) . Taken together , these results clearly demonstrate that DNA methylation at QQS is causal in repressing expression of the gene . Finally , we asked whether epigenetic variation at QQS could be observed in natural settings or if such variation only emerged in the laboratory , where accessions are grown under controlled growth conditions . To this end , we analyzed QQS expression and DNA methylation in plants grown from seeds directly collected from wild populations in Tajikistan , Kyrgyzstan and Iran ( NeoShahdara , Zalisky and Anzali populations , respectively ) . Widespread QQS epiallelic variation was observed , both between and within these diverse wild populations ( Figure 4B ) . In addition , QQS epigenetic variation was examined in the offspring ( after two single seed descent generations ) of 25 NeoShahdara individuals . These individuals were randomly sampled among a single patch of several thousands of plants that presumably represent the direct descendants of the Shahdara accession . Based on 10 microsatellite markers and one InDel marker , two genetically distinct subpopulations could be identified . While QQS was highly methylated/lowly expressed in all 16 individuals of subpopulation #1 , clear differences in DNA methylation and expression were detected among the 9 individuals of subpopulation #2 ( Figure 4C ) . Whether epiallelic variation at QQS in subpopulation #2 reflects inherent fluctuations or an intermediary stage in the route to fixation of one of the two epiallelic forms remains to be determined .
QQS is a protein-coding gene that likely originated de novo in A . thaliana within a TE-rich region ( Figure 1A ) . We have shown that this gene , which contains short repeat elements matching siRNAs ( Figure 1B , Figure S1A and S1B ) , varies considerably in its DNA methylation and expression in the wild ( Figure 4 ) . We also show that these variations are heritable and independent of the DNA methylation status of neighboring TEs or of DNA sequence variation , either in cis or trans ( Figure 2 and Figure 3 , Figures S2 and S4 ) . Thus , we can conclude that QQS is a hotspot of epigenetic variation in nature . Consistent with this , QQS is among the few genes for which spontaneous DNA methylation variation was observed in Col-0 mutation accumulation lines [13] . Cytosine methylation at QQS concerns CG , CHG and CHH sites , which is the pattern expected for sequences with matching siRNAs ( Figure 1B , Figure S1B ) . All three types of methylation sites likely contribute to silencing of QQS , as judged by the reactivation of QQS in the met1 , ddm1 , ddc and rdr2 mutant backgrounds ( Figure S1C; [24] , [25] ) . Yet , among the different DNA methyltransferases targeting DNA methylation at QQS , MET1 may play a more prominent role , given that DNA methylation at this locus is only fully erased in met1 mutant plants [25] . QQS demethylated epiallelic variants may thus preferentially arise through spontaneous [13] or stress-induced [10] defects in DNA methylation maintenance and be stably inherited for multiple generations as a result of the concomitant loss of matching siRNAs , which would prevent efficient remethylation and silencing of the gene [28] , [29] . Indeed , although we could not detect QQS siRNAs by Northern blot analysis , presumably because of their low abundance , deep sequencing data indicate that they accumulate less in met1 mutant plants than in wild type Col-0 [25] . Few genes have been shown so far to be subject to heritable epigenetic variation in A . thaliana [5]–[8] , [13] , [14] , [32] and QQS is unique among these in exhibiting this type of variation in nature ( Figure 4 ) . This therefore raises the question as to what distinguishes QQS from other genes , such as FWA , for which epigenetic variation can be readily induced in the laboratory in advanced generations of ddm1 and met1 mutant plants [5] , [33] , but for which this type of variation is not observed among accessions [11] , [34] . One possibility is that unlike QQS epivariants , fwa-hypomethylated epialleles are strongly counter-selected because of their potentially maladapted phenotype , namely late flowering [5] . Consistent with this explanation , epiallelic variation with no phenotypic consequences has been documented at FWA in other Arabidopsis species . In these cases , however , inheritance across multiple generations has not been rigorously tested [35] . Another possibility is that de novo originated genes , such as QQS , are particularly prone to heritable epigenetic variation . This is a reasonable assumption considering that these genes tend to lack proper regulatory sequences initially , unlike new gene duplicates , which by definition come fully equipped [21] . In turn , given that epigenetic variation enables genes to adjust their expression in a heritable manner much more rapidly than through mutation while preserving the possibility for rapid reversion , it could prove particularly beneficial in the case of genes that are created from scratch . Once the most adaptive expression state is reached , it could then become irreversibly stabilized ( i . e . genetically assimilated ) through DNA sequence changes . Although speculative , this proposed scenario could be highly significant given the recent discovery that de novo gene birth may be more prevalent than gene duplication [23] .
A . thaliana accessions were obtained from the INRA Versailles collection ( dbsgap . versailles . inra . fr/vnat/ , www . inra . fr/vast/collections . htm ) [30] , [36] , [37] . Insertion lines were obtained from the GABI-Kat at University of Bielefeld , Germany ( GABI-Kat 755C03 and 522C07 ) [38] , the ABRC at Ohio State University ( SALK 003195C ) and University of Wisconsin , Madison , US ( WiscDsLoxHs077_09 ) [39] . Seeds of ddm1-2 [40] , rdr2-1 [41] and ddm1-derived epiRIL lines [26] were provided by V . Colot . NeoShahdara individuals were genotyped with 10 microsatellite markers ( NGA8 , MSAT2 . 26 , MSAT2 . 4 , NGA172 , MSAT3 . 19 , ICE3 , MSAT3 . 1 , MSAT3 . 21 , MSAT4 . 18 , ICE5; http://www . inra . fr/vast/msat . php ) and one InDel marker in MUM2 gene ( MUM2_Del-LP TGGTCGTTATTGGGTCTCGT , MUM2 Del-RP TTAAGAACGCCCGAGGAATA ) . For expression and DNA methylation assays , seedlings were grown in vitro ( MS/2 media supplemented with 0 , 7% sucrose ) for eight days in a culture room ( 22°C , 16 hours light/8 hours dark cycle , 150 µmol s−1 m−2 ) . Treatment with 5-aza-2′-deoxycytidine was performed as described in [8] . Total RNA was isolated as described in [42] and cDNA was synthetized using oligo ( dT ) primers and IMPROM II reverse transcriptase ( Promega ) . Real time PCR reactions were run on an Applied Biosystems 7500 Real-Time PCR System using Platinum SYBR green ( Invitrogen ) . QQS expression levels relative to Actin2/PP2A or PP2A/GAPDH internal references were calculated using the formula ( 2- ( Ct QQS – mean Ct internal references ) ) *100 . Primers are listed in Table S1 . Total DNA was isolated using Qiagen Plant DNeasy kit following the manufacturer's recommendations . Digestion was carried out overnight at 37°C with 200 ng of genomic DNA and 2 to 8 units of McrBC enzyme ( New England Biolabs ) . Quantitative PCR was performed as described above on equal amounts ( 2 ng ) of digested and undigested DNA samples using the primers described in Table S1 . Results were expressed as percentage of molecules lost through McrBC digestion ( 1- ( 2- ( Ct digested sample - Ct undigested sample ) ) ) *100 . As a control , the percentage of DNA methylation for At5g13440 , which is unmethylated in wt , was estimated in all analyses . To assess the relative contribution of each allele to the population of mRNA in F1 individuals from reciprocal crosses between Col and Kondara , a single pyrosequencing reaction using the primers QQS_pyro_F1 ( PCR ) - TCAAAATGAGGGTCATATC ATGG , QQS_pyro_R1-biotin ( PCR ) - ATTGGATACAATGGCCCTATAACT and QQS_pyro_S1 ( Pyrosequencing ) - GATATTGGGCCTTATCAC was set up on a SNP polymorphic between the QQS parental coding sequences ( Figure S4C; position +285 ) . Pyrosequencing was performed on F1 cDNA , as well as on 1/1 pools of parents cDNA to establish the allelic contribution to QQS expression . F1 genomic DNA is used as pyrosequencing control to normalize against possible pyrosequencing biases . Anything significantly driving allele-specific expression in hybrids is by definition acting in cis , since F1 nuclei contain a mix of all trans-acting factors [43] , [44] . CGH experiments were performed for Col-0* vs . Col-0 using Arabidopsis whole-genome NimbleGen tiling arrays [45] . The normalmixEM function of the mixtools package on R was used to found the normal distribution for the distribution of the Col-0*/Col-0 ratio with an expected number of gaussians of two . A Hidden Markov model [46] was used to find regions with copy number variation . DNA was extracted using DNeasy Qiagen kit and MeDIP-chip was performed on 1 . 8 µg of DNA as previously described in [47] . The methylated tiles were identified using the ChIPmix method [48] . Probes methylated in one line only ( Col-0 or Col-0* ) were used to create domains . Domains contain at least three consecutive or nearly consecutive ( 400 nt min , with one gap of 200 nt max ) tiles with identical methylation patterns . Available QQS coding-sequences ( 464 different accessions ) were downloaded from the “Salk Arabidopsis 1001 Genomes” database ( http://signal . salk . edu/atg1001/index . php ) . A . suecica QQS sequence ( coming from the A . thaliana genome of this allotetraploid [49] ) was also included in the analysis . The aligned sequences were used to calculate the probability of rejecting the null hypothesis ( H0 ) of strict-neutrality ( dN = dS; where dN = number of nonsynonymous and dS = number of synonymous substitutions per site ) in favor of the alternative hypothesis of purifying selection ( HA; dS>dN ) . The analysis was done using the MEGA5 software under the Nei-Gojobori method [50] with the variance of the difference calculated by the bootstrap method with 100 replicates . Our overall analysis of 465 sequences rejected H0 in favor of HA ( dN/dS = 0 . 5868; p-value<0 . 045 ) .
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Epigenetics is defined as the study of heritable changes in gene expression that are not linked to changes in the DNA sequence . In plants , these heritable variations are often associated with differences in DNA methylation . So far , very little is known about the extent and stability of epigenetic variation in nature . In this study , we report a case of extensive epigenetic variation in natural populations of the flowering plant Arabidopsis thaliana , which concerns a gene involved in starch metabolism , named Qua-Quine Starch ( QQS ) . We show that in the wild QQS expression varies extensively and concomitantly with DNA methylation of the gene promoter . We also demonstrate that these variations are independent of DNA sequence changes and are stably inherited for several generations . In view of the recent evolutionary origin of QQS , we speculate that genes that emerge from scratch could be particularly prone to epigenetic variation . This would in turn endow epigenetic variation with a unique adaptive role in enabling de novo originated genes to adjust their expression pattern .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"plant",
"science",
"plant",
"evolution",
"genetics",
"plant",
"genetics",
"population",
"genetics",
"epigenetics",
"biology",
"dna",
"modification",
"evolutionary",
"biology"
] |
2013
|
Extensive Natural Epigenetic Variation at a De Novo Originated Gene
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The detailed assessment of nematode activity and viability still remains a relatively undeveloped area of biological and medical research . Computer-based approaches to assessing the motility of larger nematode stages have been developed , yet these lack the capability to detect and analyze the more subtle and important characteristics of the motion of nematodes . There is currently a need to improved methods of assessing the viability and health of parasitic worms . We describe here a system that converts the motion of nematodes through a light-scattering system into an electrical waveform , and allows for reproducible , and wholly non-subjective , assessment of alterations in motion , as well as estimation of the number of nematode worms of different forms and sizes . Here we have used Brugia sp . microfilariae ( L1 ) , infective larvae ( L3 ) and adults , together with the free-living nematode Caenorhabditis elegans . The motion of worms in a small ( 200ul ) volume can be detected , with the presence of immotile worms not interfering with the readings at practical levels ( up to at least 500 L1 /200ul ) . Alterations in the frequency of parasite movement following the application of the anti-parasitic drugs , ( chloroquine and imatinib ) ; the anti-filarial effect of the latter agent is the first demonstrated here for the first time . This system can also be used to estimate the number of parasites , and shortens the time required to estimate parasites numbers , and eliminates the need for microscopes and trained technicians to provide an estimate of microfilarial sample sizes up to 1000 parasites/ml . Alterations in the form of motion of the worms can also be depicted . This new instrument , named a "WiggleTron" , offers exciting opportunities to further study nematode biology and to aid drug discovery , as well as contributing to a rapid estimate of parasite numbers in various biological samples .
Understanding nematodes , the most numerous multicellular organisms known , is important for the advancement of both basic biological knowledge and improving global health . The free-living nematode Caenorhabditis elegans , for example , has been a model for investigating the fundamentals of genetics and aging . In the medical and veterinary world parasitic nematodes cause of some of the most debilitating and serious diseases that contribute to the global challenges in achieving improved human and animal health . Intestinal and vessel-dwelling nematodes infect more than 2 billion people with serious health and economic consequences [1] , Much of the laboratory based research into parasitic nematodes to date has utilized either relatively subjective in vitro assays based on observer interpretation , or have been focused on in vivo approaches that often still involve subjective approaches . There have been a number of non-subjective mechanical techniques developed to study nematode activity , including those that measure changes in motility . In 1986 a micromotility meter , a comparatively inexpensive and easily operated device , was described for the quantification of motility of large nematodes [2] . This , and more recent devices , such as the real time cell monitoring system based on impedance [3] , have been used to investigate the effects of anthelminthic agents on parasitic nematodes . The screening of compounds for potential new anti-parasite candidates has increased in recent years as global health programs focus more sharply on eliminating the major neglected tropical infections caused by helminths including nematodes such as Onchocerca volvulus , Wuchereria bancrofti and Brugia sp . [4] . This push to find new drugs that will work against these parasites requires improved technologies including better use of the commonly used parameter of parasite motion as a predictor of parasite health [5–8] . Present techniques are lacking in utility; some address only the larger stages of parasites and cannot quantify or measure microscopic larval stages [5] , whilst others are not compatible with use in remote field settings because of cost or complexity [6–8] . C . elegans has an episodic swimming pattern that has been well-documented [9] , and the motion of nematodes has commonly been used as an indicator of the health of the worms . Filarial parasites in particular have a very specific pattern of motion , such as the “filarial dance” seen in lymphatic filariasis using ultrasonography [10]; this motility is reduced after administration of anthelmintic treatment . Here a technology is described that improves the capture the details of the complex motion of these parasites in solution and the characteristics of alterations in this motion . This system also allows evaluation of potential anti-worm agents in vitro by quantifying the number of viable worms present in test samples . To describe our new system we have primarily used Brugia pahangi , a filarial worm similar to the 3 species that cause human lymphatic filariasis , and have also included data on C . elegans , the archetypical nematode .
The animals used to supply the parasites used in this study were infected and maintained under standard institutional approval monitored and proved by the Animal Use Committee of Western Michigan University ( WMU ) . Animals were maintained in the approved and monitored animal facilities at WMU . The WiggleTron ( WT ) ( Fig . 1A ) operates on many of the same principles as its predecessor , the B&P Instruments Micromotility Meter [2] . The WT has , however , improved sensitivity in detection , decreased noise , better placement of the photo-detectors , and increased sampling rate as compared to the B&P machine . The WT ultimately converts sample organism movements into an analog voltage signal which once sampled is analyzed for its amplitude and frequency composition time . The sample-containing vial is illuminated from below by a white LED emitting ~5 milliwatts of visible optical power into the base of the vial . The LED and sample tube are separated by an opaque ring which retains stray light , reduces thermal conduction into the sample vial , and prevents damage to the LED lens . Temperature within the sample vial is consistently 32 ± 1°C . The light passes up through the sample reflecting dynamically off any movement within the vial , onto large PIN photo-detectors , connected in parallel , flanking the sides of the vial . Unlike the original micro-motility meter , these photo- detectors span vertically from the base of the vial up to just below the meniscus level of the liquid sample . This reflected light energy is converted to an analog of the movement , amplified at 0 . 40 , 4 . 0 or 40 μV/pA to accommodate various sizes of sample organism , using negative feedback resistance to determine the optimal situation . The sample vial is held firmly by support fingers that in turn are stabilized by a superstructure that also supports and aligns the photo-detectors . All samples were evaluated in 31mmH X 6 mm OD borosilicate glass tubes ( Sigma , pn . 24715 ) with 200μl samples . This system could be miniaturized and made suitable for use in field situations , as well as be constructed to test multiple samples at the same time allowing for large scale screening of compounds . The cost of the basic equipment and software components for a simple version of this system was approximately $4 , 500–$6000 . Tubes were placed within the WT over the light source and allowed to equilibrate for at least one minute prior to initiating acquisition . Each sample population ( containing parasites ) as well as control ( medium only ) was prepared in triplicate . The analog voltage output signal was digitized at 1 kHz with a DT9816 ( Data Translation , Inc . , Marlboro , Massachusetts , USA ) 16 bit ADC controlled by Quick-DAQ software ( Data Translation , Inc . , Marlboro , Massachusetts , USA ) . The recording duration used for pilot studies was 30 seconds , however after experimentation it was found that to accommodate the 2N time requirement for low frequency FFT resolution of 0 . 1Hz [11] , this testing time be standardized for all samples at 33 seconds . The proprietary Quick-DAQ * . hpf data files were converted to * . csv files containing time interval and voltage amplitude . The voltage amplitude was multiplied by 3276 then converted to RMS value to represent better the sample’s bit depth for 16 bit resolution of the ±10 V input range of the DT 9816 , making the resulting amplitude values integer numbers and thus easier to interpret and compare quickly . This number ( 3276 ) was selected as it is the factor that best converts bit number into an arbitrary unit that allows for easier comparisons; this technique is commonly used in electronic science [12] . Thus it is not a specific “unit” as such but a non-dimensional unit used solely for the comparison between two or more samples studied by this equipment . Each sample was run 3 times on the WT . The mean and standard deviation for each sample was calculated using the scaled RMS values from these individual runs . This yields a number that can be used to compare the motion of the worms in each sample based on the amplitude of motion . Dead parasites ( transferred to 95% ethanol ) , then transferred back to fresh medium followed the same procedure for sample preparation , measurement , and analysis . Further , the ( * . csv ) files can be imported into SignalLab SIGVIEW ( Mitov Software LLC , Moorpark , California , USA ) . This software allows FFT analysis to look at differences in the frequency of motion of the sample and highlight differences graphically at different frequencies of movement . Brugia pahangi microfilariae . B . pahangi microfilariae were obtained from Filariasis Research Reagent Resource Center ( FR3 , Atlanta , Georgia , USA ) . Upon receipt , microfilariae were placed in approximately 25ml of fresh medium ( RPMI 1640 supplemented with 10% fetal bovine serum ( FBS ) and 1% penicillin and streptomycin ) and agitated till at a uniform distribution within the medium . 10 ul of this suspension was then transferred to 100 ul of fresh medium in a well on a 96-well plate . This was repeated 4 times . The contents of the wells were examined under light microscope to determine parasite health ( highly active and with normal anatomical appearance ) . Once parasites were determined to be healthy and free from debris , all 4 wells were counted for living parasites to determine the density of microfilariae in suspension . This density number was then used to generate dilutions to allow us to prepare samples ranging from 10 to 50 , 000 worms suspended in 200 ul of medium . Each sample was then run on the WT and analyzed as described earlier the results from each population were averaged to provide a snapshot of motility amplitude of the range of populations . Samples were then prepared using dead microfilariae from 10–50 , 000 worms and run and analyzed in the same manner , populations of live versus dead worms could then be compared . Since the samples were prepared in triplicate each population could then be averaged to generate a plot of population as a function of measured and analyzed RMS amplitude . For tube populations from 0–1 , 500 worms , this plot yielded a function capable of predicting the population of parasites within the sample tube . Unknown population samples were then prepared , run , and analyzed as described above . The equation resulting from the known population was used to calculate the population of microfilariae in the unknown tubes . The population of each of the unknown tubes was then found using the same method used to find concentrations of microfilariae described previously and compared to the calculated population . Brugia pahangi infective larvae . B . pahangi infective larvae ( L3’s ) were obtained from FR3 . Upon receipt , L3’s were placed in approximately 1ml of fresh medium ( RPMI 1640 supplemented with 10% fetal bovine serum ( FBS ) and penicillin and streptomycin ) and agitated to mix uniformly within the medium . 20ul of this suspension was then transferred to a small petri dish containing approximately 2ml of medium . The dish was investigated under light microscopy to determine parasite health . Once parasites were determined to be healthy and free of debris , they were counted to determine the density of L3’s in suspension . Samples containing between 10 and 200 L3’s in 200 ul of medium were then prepared . Samples with less than 10 worms were also prepared by pipetting a single worm at a time under the stereoscope into the same type of vials described previously; each sample prepared in this manner also had a final volume of 200 ul . Samples were prepared in triplicate . All samples were then covered with Parafilm ( Pechiney Plastic Packaging Co . , Chicago , USA ) and placed in the freezer for 2 days after live analysis . Afterward , the tubes were thawed and inspected to make sure the parasites were dead . Tubes with the dead parasites were then run on the WT and analyzed as previously described . Both live and dead L3’s were then compared at each worm population level . Brugia pahangi adult parasites . Adult B . pahangi , both male and female were obtained from FR3 . Upon receipt , parasites were placed in approximately 5 ml of fresh medium ( RPMI 1640 supplemented with 10% FBS and penicillin and streptomycin ) in a large petri dish . Individual worms were picked up using a glass Pasteur pipette and transferred into 200 ul of medium in the same type of vials described previously , 1 parasite per vial . Samples were run on the WT and analyzed as previously described . These samples were then covered with Parafilm and placed in the freezer for 2 days . Afterward , the tubes were thawed and inspected to make sure the parasites were dead . Tubes with the dead parasites were then run on the WT and analyzed as previously described and their results compared to living adult worms . Caenorhabditis elegans L1 stage . Mature , egg-producing C . elegans were bleached . The eggs were harvested , washed and allowed to hatch on a plate containing agar with no food , arresting their development at the L1 stage to ensure a uniform larval stage for analysis . Samples from 0–100 worms were prepared as previously described , however rather than using medium C . elegans were run in normal saline ( 0 . 9% NaCl ) to ensure that they remained arrested in L1 . Samples of live and dead C . elegans were run as previously described , FFT frequency analysis was done as previously described , using 100 L1’s . Infective larvae ( L3 ) . Twenty-one samples , each containing two B . pahangi L3’s were prepared in 198 ul of medium in the same vials described earlier . These 21 samples were grouped into 7 groups of three . These groups included one control group , and three treatment groups for the drugs imatinib mesylate ( Gleevec , Novartis ) and chloroquine ( Sigma-Aldrich Co , New Jersey , USA ) , both at levels of 100nM , 500nM , and 100uM . Each sample was run prior to treatment on the WT . Two microliters of medium were added to each tube in the control group , two microliters of a 10uM drug solution were added to the tubes in the 100nM groups , two microliters of a 50uM drug solution added to the tubes in the 500nM groups , and two microliters of a 10mM drug solution were added to the 100uM groups . Each tube was covered with Parafilm M Barrier Film ( Bemis NA , Neenah , Wisconsin , USA ) and then tested at 1 , 24 , 48 and 72 hour ( s ) post treatment . Adults . Twenty-one samples , each containing one B . pahangi adult female , were prepared in 198 ul of medium in the same vials described earlier . These 21 samples were grouped into 7 groups of three . These groups included one control group , and three treatment groups for the drugs imatinib mesylate and chloroquine at levels of 100nM , 500nM , and 100uM . Each sample was run pre-treatment , treated , covered , and analyzed at the same time points as described with the L3 treatment . Three groups of 10 B . pahangi L3’s were analyzed on the WT immediately upon receipt from FR3 . Other L3’s were plated in medium and allowed to slowly degrade while sitting on the bench . After 1 day of monitoring via microscopy , degraded worms showing uncharacteristic and lethargic motion under the scope were then analyzed on the WT . Instead of the normal fluid motion , seen in healthy worms , these worms appeared to flick only one end of their body . The same process was repeated at 48 hours . These data , and data from the fresh L3’s , were then imported into Sigview ( www . sigview . com ) . Fast Fourier Transform ( FFT ) analysis was done to look at spikes at specific frequencies of motion . By comparing FFT diagrams from blank samples and samples with worms we established that worm motion takes place below 16Hz . Further , visual analysis of many FFT diagrams , specific to the worm type being studied showed some general patterns . Based on these patterns each L3 sample was broken into frequency ranges of 0 . 1–2Hz , 2–8Hz , and 8–16Hz . This was also carried out for C . elegans . RMS amplitude for each frequency range was summed for each sample and averaged across the population group . Then a ratio was calculated relating the three frequency ranges to each other . A one-way ANOVA was used , followed by post hoc Tukey’s test to compare the means for each sample group and determine significance of RMS amplitudes for all of the worms run on the WiggleTron [13] . This analysis was done using JMP 11 software ( www . jmp . com ) .
Analysis of the data from the WT shows that the device can detect parasite presence and that detection results from parasite motion within the tube . A real-time trace of motion follows a sinusoidal pattern with the majority of the movement , taking place at frequencies less than 20Hz ( Fig . 1B & 1C ) . All the worms studied , when healthy , show a periodic motion when viewed under a microscope , bending or twisting around a center point on the worm’s body . This results in a cyclic bending-unbending or twisting-untwisting motion . The detector’s baseline RMS amplitude for no motion is zero . This motion of the worm scatters light , either increasing or decreasing the amount of light received by the photodiodes . This yields an elevated or lessened RMS amplitude based on the direction of motion and nature of the light scattering . Based on the cyclic motion of the worm , a sinusoidal RMS amplitude is detected . Expectedly , due to big physical differences , live worms yield dramatically different RMS amplitudes based on population size , type/species , and larval stage within each tube ( Fig . 1D ) . However , despite the difference in their RMS amplitudes , they are all similar in that live worms yield RMS amplitudes that are significantly larger than blank tubes . Results obtained from adults of both sexes , L3’s , microfilariae , and L1’s all show that dead worms are functionally non-existent and give results similar to blank tubes when analyzed within the WT ( Figs . 2B , 2C , 3A , 4A & 5A ) . There is however , with parasite numbers well above the normal infection or test levels usually likely to be examined ( >500 mf/200ul ) , a significant impact on RMS amplitude seen . Fig . 2C shows that at 100 or 500 mf/ 200ul there in no effect of adding an equivalent number of dead similar worms . Analysis of the data from microfilariae the WT shows that this system can estimate different numbers of worms based on the amplitude of RMS amplitude ( motion ) . For microfilariae there is a positive correlation between amplitude and worm number in samples up to 5 , 000 worms . With numbers of microfilariae greater than 5 , 000 the signals resulting from worm motion no longer consistently correlate with increases in worm population . However , two further general characteristics of the WT’s ability to capture motion were seen: firstly the maximum RMS amplitude possible for the present experimental conditions occurs at 17 , 500 microfilariae , and secondly at numbers higher than 17 , 500 microfilariae there is a decline in signal with an increase in population . With populations of 0–1500 microfilariae , the increase in RMS amplitude resultant from an increase in population is linear with a sensitivity of 300 worms ( p = 0 . 0079 ) . Analysis of data with B . pahangi L3’s , and C . elegans L1’s shows an increase in RMS amplitude along with population from 0–100 worms . The B . pahangi L3 sensitivity is 5 worms ( p = 0 . 0166 ) , whereas the sensitivity for C . elegans L1’s is 50 worms ( p = 0 . 0014 ) . Due to the size of the adult Brugia parasites , multiple worms were not run within the same tube for this study . Analysis of over 400 adult worms from the peritoneal cavity of girds shows that adult worm sex can be determined based on amplitude alone through the use of the WiggleTron ( p<0 . 0001 ) . Using known RMS amplitude values for each population , population as a function of RMS amplitude can be plotted and used to estimate the population size of an unknown sample . Microfilariae were used to investigate the predictive nature as there is a need for a quick , easy field test to confirm and quantify microfilariaemia in endemic populations . Functions generated using results from 0–1 , 500 microfilariae can estimate within 20% error the population of microfilariae within a tube for numbers of worms less than 200 . Multiple tests yielded an error of 16 . 7% when testing a population of 175 worms . At higher numbers , the non-linear relationship between RMS amplitude and population failed to estimate the population number with an accuracy of +/- 20% , and this makes prediction using the WT unreliable for this situation . Analysis of the data from the WT shows that after treatment with prospective anti-filarial drugs , there is a significant difference in the amplitude of the RMS amplitude between treated and control groups . Forty-eight hours post treatment , results from L3’s showed a significant decrease in motion across all treatment groups and the control group ( Fig . 3 ) . The treatment groups receiving the highest doses , approximately 100x known lethal dosage ( LD100 ) of each drug , yielded results that were nearly identical to that of dead worms or blank tubes . The changes in worm motion were significant earlier , 1hour post treatment ( hpt ) for the chloroquine 100uM group , and 24 hpt in the imatinib mesylate 100uM group . The lower treatment levels showed that there was still some motion in the worms , yet their activity level as compared to the control group was greatly reduced . This was confirmed by light microscopy . Analysis of treated adults did not show as drastic results as the L3’s at lower treatment levels , yet the highest treatment groups of each drug showed a significant decrease in activity after treatment . After 72 hours all but the highest treatment levels exhibited some activity ( Fig . 4B & 4C ) . FFT analysis of fresh B . pahangi L3’s , and naturally degraded L3’s also shows that the WT can be used to analyze parasite health . There is a peak range in the frequency of motion for these worms between 4Hz and 8Hz ( Fig . 1C ) ; degraded L3’s lacked activity at this peak range ( Fig . 1C ) . This is further shown by comparing the summed motion at different frequency ranges . The healthy L3’s had a significantly different ratio of mid-range frequency of motion compared to high frequency motion or low frequency motion than their microscopically confirmed degraded L3 counterparts ( Fig . 3D ) . C . elegans showed a peak of motion between the ranges of 3Hz to 8Hz ( Fig . 5B ) . When compared to similar sized B . pahangi microfilariae , the L1’s showed a different pattern of motion; specifically their peak activity was at higher frequency ranges than the activity of the Brugia microfilariae ( Fig . 5B ) . When allowed to starve for 48 hours , C . elegans L1’s showed significant changes in the pattern of their motion . This is shown by relating the mid-range frequency component of their motion to the low and high range frequency components , then comparing fresh versus starved worms ( Fig . 5C ) . The fresh and starved worms had significantly different ratios of mid-range to low and high-range to low ( p<0 . 0001 ) , whereas the ratios of their mid-range motion compared to high was similar ( p = 0 . 3095 ) . Both the fresh and starved worms showed significant differences in signal across all frequency ranges from that of the blank tube ( p<0 . 0001 ) .
Nematodes are organisms of interest to both basic and applied scientists for two major reasons: they are complex entities that can be studied to understand basic biological mechanisms of an early animal organism , and secondly because they cause some of the most devastatingly chronic animal and human diseases in the world . The methodology described in this present communication , the WT , can potentially assist both these communities . By describing the motion of worms in a detailed quantitative manner , with high degree of statistical strength , it is possible to both to record subtle changes in the activity of individual worms and secondly , it can assist in quickly and reliably confirming parasite presence and estimating the numbers of parasites present within the limitations of the machine . The motion of nematodes has been an area of interest for many years and in many disciplines , including plant parasitology [14] , and the biology of the iconic biology research nematode , C . elegans [15] . Another important reason to record and understand changes in motion of nematodes is to monitor the effect of external agents , such as anthelminthic drugs , on target parasites . With further testing and improvements to the current WT , it is possible that this technique may be able to detect changes in forms of motion that reflect drug effects on specific organs within the worms; and thus reflect the probable target organs and aid in the search for new anthelmintic agents . Currently the common methods for assessing the effects of potential anthelminthic use a subjective visual assessment of motility , and method that is difficult to standardize between observers . The examples presented here show that depression in motion in the presence of anti-worm compounds ( Figs . 3 & 4 ) can be easily visualized and parameters such as time course be recorded . The issue of the effect of the meniscus is very central to the improvements we have managed to achieve in this current system . The original system of Bennett and Pax [2] utilized the meniscus in the recording . The location of the recording photoreceptor diodes in a position just below the meniscus contributed significantly to the improved sensitivity of this new version of this light-scattering system . Thus in our system the same volume is used in the same type of tube for every experiment and thus the meniscus is positioned in the same place relative to the diodes for each these experiments . This positioning of the photodiodes below the meniscus lessens the effect that the meniscus has on the detection of light changes related to worm motion . We believe that the system does indeed allow for a “reproducible estimation” of the number of worms present in a small volume , at least within a range that is practically useful for screening the loads of parasites present in solutions , although it is true that this is an approximated figure and not truly a count . We believe nevertheless this does have application in situations where detection of a “cut off” level of parasites is needed , such as screening hyper-infected patients for special treatment . The ability to estimate the numbers of organisms present in small volumes , and to do this with very high numbers of worms present in the solution , i . e . up to approximately 1 , 000 parasites per ml in the case of filarial microfilariae ( Fig . 2 ) could be of interest to epidemiological studies needed for a number of today’s global health programs . Although antigen/antibody tests are the most commonly used currently for parasite disease field programs , there are still occasions where estimation of the number of worms in biological fluid is important and most serological tests are poorly quantitative and sample standard sample tests time consuming or unreliable . In lymphatic filariasis , where there is a major ongoing global program to eliminate the infections and disease , antigen tests can offer false positives and in the case of the ICT antigen test , false negatives [16–18] . The preparation of preparing a blood smear and microscopic examination requires a skilled technician and microscope , as well as potentially exposes the technician to other blood-borne pathogens [15] . This motion based WT system , especially when further miniaturized could be a useful system for field laboratories . This is most urgently needed for screening large numbers of people in endemic areas of loiasis , a filarial worm that when present in high numbers in the blood ( > 8 , 000 mf/ml ) can induce fatal reactions following treatment with the standard anti-filarial drug ivermectin [19]; knowing the number of parasites circulating in individuals before treating them with this drug is essential . The two experiments presented here showing the effects of anthelminthic agents on worm health , using the examples of chloroquine and imatinib ( Fig . 4 ) , demonstrate that the WT , with its assumed superior objectivity compared to direct observation , is a welcome contribution to the current drug screening efforts . Chloroquine has been shown previously to affect filariae [20] , and imatinib ( a tyrosine-kinase inhibitor that was originally shown to act on a neoplastic cell enzyme ) has been shown to damage the trematode helminth , Schistosoma mansoni [21]; our observations here are the first demonstration of anthelminthic effect of imatinib on a filarial nematode . The ability to analyze and differentiate between healthy and affected nematodes in screening assays could be enhanced using a 96-well plate version of this system . Multiple compounds , at multiple dilutions could be run simultaneously and analyzed for effects on worm movement . Compounds that show promise could be easily identified and investigated further . Refinements in the analysis , through comparison of motion to worm pathology , and video analysis may even allow the machine to identify motion types that are indicative of certain types of damage , narrowing future research into specific mechanisms of damage to the worm . Although the WT system is currently portable and easy to operate , further development that includes automation of the analytic steps and miniaturization of the equipment could enhance its suitability for use in non-laboratory settings . However , in its present form it already will deliver results that require little more than putting the sample into a tube , introducing the tube to the hand-held collector , and pushing a button on the computer . This system eliminates the need for a specialist technician and allows for multiple analyses and repeated sampling where needed . The ability to function with nematodes of differences sizes , ranging from 300um to 1–2 cm long , brought about by the increased sensitivity to changes in light sensing is likely to be a welcome improvement from older systems . New generations of the instrument focusing on miniaturization would assist in the goal of developing a hand-held version for detection of parasites in settings outside research laboratory , and multi-well plate versions will increase simultaneous sample quantity for more efficient laboratory high throughput screening to enhance the search for new anti-parasite agents . We have shown here that the WT has the capability of detecting , quantifying , and analyzing the motion of nematodes in a small volume of liquid . This system can be an invaluable tool for field confirmation and quantification of parasite loads , screening a large number of compounds , and confirming drug-induced damage to nematodes; in addition it should greatly enhance further understanding of the biology of movement in nematodes .
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Assessment of the health and number of nematodes still relies heavily on subjective monitoring of their motion . Although less-subjective techniques exist that utilize the motility as the primary indicator , the current approaches tend to be designed for use with larger worms and not for early developmental stages . We have describe here a sensitive technique that converts the motion of nematodes into electrical waveforms , which then be used for an estimation of the number parasites present , and for detailed analysis of alterations in their movements . Using parasites of different sizes , including different stages of Brugia sp . and Caenorhabditis elegans , we have shown that the system can analyse samples containing up to 1000 microfilariae/ml , and can be used to used to detect the decrease in motility as a worm loses viability . We have also demonstrated its use in assessing the effects of chloroquine and imatinib on filariae . This sensitive technique is likely to be value to research and field laboratories where there is a need to rapidly estimate the number of parasites present in liquid samples , and can be used in drug screening programs to assess the effects of different anthelminthics .
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[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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Analysis of Nematode Motion Using an Improved Light-Scatter Based System
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Although T cells are critical for host defense against respiratory fungal infections , they also contribute to the immunopathogenesis of Pneumocystis pneumonia ( PcP ) . However , the precise downstream effector mechanisms by which T cells mediate these diverse processes are undefined . In the current study the effects of immune modulation with sulfasalazine were evaluated in a mouse model of PcP-related Immune Reconstitution Inflammatory Syndrome ( PcP-IRIS ) . Recovery of T cell-mediated immunity in Pneumocystis-infected immunodeficient mice restored host defense , but also initiated the marked pulmonary inflammation and severe pulmonary function deficits characteristic of IRIS . Sulfasalazine produced a profound attenuation of IRIS , with the unexpected consequence of accelerated fungal clearance . To determine whether macrophage phagocytosis is an effector mechanism of T cell-mediated Pneumocystis clearance and whether sulfasalazine enhances clearance by altering alveolar macrophage phagocytic activity , a novel multispectral imaging flow cytometer-based method was developed to quantify the phagocytosis of Pneumocystis in vivo . Following immune reconstitution , alveolar macrophages from PcP-IRIS mice exhibited a dramatic increase in their ability to actively phagocytose Pneumocystis . Increased phagocytosis correlated temporally with fungal clearance , and required the presence of CD4+ T cells . Sulfasalazine accelerated the onset of the CD4+ T cell-dependent alveolar macrophage phagocytic response in PcP-IRIS mice , resulting in enhanced fungal clearance . Furthermore , sulfasalazine promoted a TH2-polarized cytokine environment in the lung , and sulfasalazine-enhanced phagocytosis of Pneumocystis was associated with an alternatively activated alveolar macrophage phenotype . These results provide evidence that macrophage phagocytosis is an important in vivo effector mechanism for T cell-mediated Pneumocystis clearance , and that macrophage phenotype can be altered to enhance phagocytosis without exacerbating inflammation . Immune modulation can diminish pulmonary inflammation while preserving host defense , and has therapeutic potential for the treatment of PcP-related immunopathogenesis .
Pneumocystis ( Pc ) is an opportunistic fungal respiratory pathogen that causes life-threatening pneumonia in patients suffering from defects in cell-mediated immunity , including those with acquired immunodeficiency syndrome ( AIDS ) and immunosuppression secondary to chemotherapy or organ transplantation . Pneumocystis pneumonia ( PcP ) remains a leading cause of death among HIV-infected patients and a significant cause of AIDS-related mortality and morbidity [1] . For example , mortality rates of 50% or higher have been reported for AIDS patients with severe PcP [2] , [3] , and despite major advances in health care , the mortality associated with PcP has changed little over the past 25 years . In addition , as more powerful anti-inflammatory treatments are developed for various underlying diseases , more cases of PcP are occurring in non-HIV patients and in previously unreported clinical settings [4]–[6] . Recent studies also indicate that Pc colonization can exacerbate chronic obstructive pulmonary disease [7] . Therefore , improving the treatment of patients suffering from both HIV- and non HIV-related PcP remains a central concern of the health care community . Although the direct pathogenic capabilities of the Pneumocystis organism itself are poorly understood , the role of the host's immune response as a major contributor to PcP-related lung injury has come to the forefront . In patients , the clinical severity of PcP is dictated by the degree of pulmonary inflammation , rather than by the organism lung burden [8]–[14] . Specifically , T cell and neutrophilic responses have been linked to PcP-related lung injury in patients [10] , [15] . A clinical example of the immunopathogenic nature of PcP is the severe disease that has been reported in AIDS patients following successful anti-retroviral treatment [16]–[18] . This distinct clinical syndrome , termed Immune Reconstitution Inflammatory Syndrome ( IRIS ) or Immunorestitution Disease ( IRD ) , occurs when CD4+ T cell-mediated immunity is restored following a period of immunosuppression . The recovery of immune function restores protective adaptive immunity , but does so at the cost of initiating a severe immunopathological response to a pre-existing Pc infection . An IRIS-like presentation of PcP has also been described in non-HIV infected patients following the successful tapering of steroid therapy or bone marrow engraftment [19] , [20] . Importantly , patients with non-HIV presentations of PcP and IRIS seem to develop a more fulminant and acutely immunopathogenic disease than patients with a classical AIDS-related presentation in which CD4+ T cell function is chronically and profoundly depressed [10] , [21]–[24] . The immunopathogenesis of PcP has been confirmed by controlled studies in Pc-infected severe combined immunodeficient ( SCID ) mice . Following adoptive transfer of normal splenocytes these mice develop disease that is pathologically similar to clinical reports of IRIS . When the host's immune system is restored , an intense T cell-mediated immune response brings about organism clearance with the undesired consequence of severe lung damage and respiratory deterioration [25]–[30] . Our laboratory has demonstrated that CD4+ T cells predominate in the lungs at the time of maximal injury and that depleting this population prevents the onset of acute disease [28] , [31] . Other studies have demonstrated that CD4+ T cells are robustly pathogenic in the setting of immune recovery and PcP [26] , [27] , [32] , [33] . While existing evidence unquestionably demonstrates that T cell responses are directly involved in both the clearance of Pc and the generation of immune-mediated lung injury , the specific downstream effector mechanisms have not been elucidated . Alveolar macrophages ( AMs ) are likely involved in both of these processes , but their in vivo role remains incompletely defined . Sulfasalazine ( SSZ ) is a potent anti-inflammatory drug commonly used to treat the inflammatory consequences of Crohn's disease and Rheumatoid Arthritis [34]–[36] . SSZ modulates immune responses by altering macrophage and T cell responses [37]–[39] . Many effects of SSZ are related to its function as a potent inhibitor of NF-κB [39] , [40] , a signaling pathway that is important for inflammatory responses to Pc [38] , [41] , [42] , [43] . Therefore , we hypothesized that the potent immunomodulatory properties of SSZ could alleviate lung injury and improve outcome in a mouse model of PcP-related IRIS . SSZ was highly effective for attenuating the immune-mediated lung injury associated with PcP , with the unexpected finding that SSZ also accelerated fungal clearance . Moreover , we developed a multispectral imaging flow cytometer-based method to assess Pc phagocytosis in vivo . Using this technology we established that the macrophage is the downstream effector for CD4+ T cell-dependent clearance of Pc from the lung , and that SSZ enhances clearance by promoting AM phagocytosis .
SSZ is used clinically to treat conditions in which inflammation is integral to pathogenesis . To test the efficacy of SSZ for reducing the severity of PcP-related IRIS , infected SCID mice were immunologically reconstituted with wild type splenocytes , and then treated with either SSZ or PBS vehicle beginning at day 1 post-reconstitution ( PR ) . Respiratory rates and body weights were monitored non-invasively , and dynamic lung compliance and resistance were measured at 13 , 18 and 25 days PR . These times correspond to the early , peak , and resolution phases of PcP in this model . As expected , the PBS-treated mice with IRIS exhibited progressive disease that was characterized by dramatic weight loss and elevated respiratory rates . These mice lost an average of 17±2% body weight by day 12 , and 24±3% by day 16 PR . Thereafter , the mice began to gain weight coincident with the resolution of disease ( Figure 1A ) . These mice also exhibited elevated respiratory rates , which increased dramatically to an average of 441±9 respirations per minute at day 12 and 487±13 respirations per minute by day 17 PR ( Figure 1B ) . In contrast , the SSZ-treated mice exhibited only slight variations in body weight and respiratory rate over this same period , and had a generally healthy appearance . Direct pulmonary function measurements were taken at days 13 , 18 , and 25 PR . Dynamic lung compliance and lung resistance are derived from pressure and volume measurements recorded on live ventilated mice . Lung compliance is a measure of the lungs ability to stretch during the respiratory cycle , and is considered a measure of alveolar health . Mice with PcP have reduced compliance compared to healthy mice , indicating that the lungs are less elastic and generate greater pressure during respiration . Lung resistance is a measure of air flow limitation to and from the gas exchange surface , and can be negatively affected by airway and alveolar inflammation . Mice with PcP have increased resistance compared to healthy mice . Both of these measures are good indicators of the severity of PcP . PBS-treated mice with IRIS developed a drastic deterioration of pulmonary function over the course of the study . A severe reduction in dynamic lung compliance was observed by day 13 PR , and by day 18 these mice demonstrated a 59% deficit in lung compliance ( Figure 1C ) . In contrast , the SSZ-treated mice suffered only a 19% reduction in lung compliance over this same period , and recovered to nearly normal pulmonary function by day 25 PR . Similarly , a dramatic difference in resistance values was observed between the SSZ- and PBS-treated IRIS mice ( Figure 1D ) . The SSZ-treated mice exhibited significantly lower lung resistance than the vehicle group at all time points , supporting the conclusion that SSZ decreases the magnitude of the pulmonary function deficits associated with PcP , and attenuates overall disease severity . To determine the effect of SSZ treatment on epithelial damage and alveolar permeability during PcP , albumin content was measured in the bronchoalveolar lavage ( BAL ) fluid . Elevated levels of albumin in the BAL fluid indicates damage to the tight junctions between alveolar epithelial cells and serves as a marker for the severity of PcP . PBS-treated mice with PcP had significantly elevated albumin levels on days 13 and 18 PR as compared with normal uninfected mice ( Figure 1E ) . In contrast , the SSZ-treated mice had lower albumin levels than PBS-treated mice at both time points ( Figure 1E ) . While albumin levels returned toward baseline in both groups by day 25 , they remained significantly lower in the SSZ-treated mice . These data demonstrate that SSZ attenuates damage to the alveolar-capillary barrier , which contributes to the preservation of pulmonary function during PcP . Total cell counts , differentials , and flow cytometry were also performed on BAL cells from experimental mice . PBS-treated IRIS mice had significantly elevated numbers of total BAL cells compared to SSZ-treated mice at all time points ( Table 1 ) . Differential staining revealed that the reduced number of cells in SSZ-treated mice relative to PBS-treated mice was mainly a reflection of fewer lymphocytes and neutrophils at all time points ( Table 1 ) . As neutrophil numbers are predictive of disease severity , fewer neutrophils in SSZ-treated mice was also an indicator of less severe disease . Despite a reduction in total cells , it was notable that SSZ-treated mice had more AMs than PBS-treated mice at day 18 . Flow cytometry analyses revealed that SSZ-treated mice had fewer CD4+ and CD8+ T cells than PBS-treated mice at 13 and 18 days PR . By day 25 PR the reduced BAL cells in SSZ-treated mice was mainly a reflection of reduced CD4−/CD8− lymphocytes ( possibly B cells ) and neutrophils . Histological examination of hematoxylin and eosin stained lung sections showed that the PBS-treated mice exhibited a more intense , wide-spread inflammatory response than the SSZ-treated mice . Pulmonary inflammation in PBS-treated mice was characterized by the accumulation of monocytic and polymorphonuclear aggregates throughout the alveoli , although the inflammation appeared less intense by day 25 ( Figure 2A–C ) . In contrast , evidence of inflammation in the SSZ-treated mice at days 13 and 18 PR was mostly limited to perivascular and peribronchial regions , and the alveoli were mainly free from cellular infiltrates ( Figure 2D , E ) . Furthermore , the inflammation was almost completely resolved by day 25 in the SSZ-treated mice ( Figure 2F ) . Elevated cytokine production is a characteristic of PcP-related inflammation . To determine whether the reduced severity of PcP observed in SSZ-treated mice was associated with blunted chemokine and cytokine production in the lung , MCP-1 , RANTES , TNF-α , and IFN-γ levels were measured in the BAL fluid . Cytokine and chemokine levels were elevated above control levels in the lungs of PBS-treated IRIS mice , consistent with the physiological and histological data showing severe inflammatory disease . In contrast , lung levels of MCP-1 , RANTES , TNF-α and IFN-γ in the SSZ-treated group were all significantly lower than the PBS-treated group at all time points ( Figure 3A–D ) . Reduced cytokine levels in the SSZ-treated mice were associated with reduced inflammatory disease in these mice . To study the effect of SSZ on fungal clearance , the lungs of experimental mice were examined for Pc burden using real-time PCR . Both PBS- and SSZ-treated mice had significant lung Pc burdens on day 13 PR ( Figure 4A ) . Although the PBS-treated mice showed little reduction in Pc burden by day 18 ( log 6 . 77±0 . 07 ) , the SSZ-treated mice exhibited a 4-log reduction between days 13 and 18 PR ( log 2 . 25±0 . 42 ) ( Figure 4A ) . By day 25 PR , Pc burdens in the PBS-treated IRIS mice were reduced by an average of 2 logs , while Pc was undetectable in nearly all individual SSZ-treated animals ( Figure 4A ) . The above data were combined from 8 independent experiments . The enhanced clearance of Pc in SSZ-treated mice was confirmed by enumerating Pc cysts in the lung homogenates with Gomori's methenamine silver stain ( data not shown ) . Therefore , SSZ accelerates the fungal clearance kinetics in this model . Adaptive immunity is critical for the clearance of Pc from the lungs . To determine whether the mechanism by which SSZ enhances Pc clearance requires the adaptive immune system , non-reconstituted Pc-infected SCID mice were administered either PBS vehicle , SSZ ( 200 mg/kg/day ) , or trimethoprim sulfamethoxazole ( TMP-SMX ) ( 16 mg/kg/day ) . As expected , PBS-treated SCID mice had high Pc burdens at both 13 and 20 days post-treatment ( Figure 4B ) . Similarly , the SSZ-treated group also had high Pc burdens at both time points and did not clear the Pc infection ( Figure 4B ) , demonstrating that SSZ had no direct Pc killing effect . In contrast , the TMP-SMX-treated group showed reduced Pc burden at both time points ( Figure 4B ) . The role of CD4+ T cells in host defense against Pc has been well-documented . To determine whether the mechanism of SSZ-enhanced clearance is CD4+ T cell-dependent , Pc-infected SCID mice were immune reconstituted and then CD4+ T cell depleted . The Pc burdens of PBS- and SSZ-treated mice were determined at days 18 and 25 PR . Neither PBS- nor SSZ-treated mice cleared the Pc infection in the absence of CD4+ T cells ( Figure 4C ) . Thus , the mechanism by which SSZ enhances Pc clearance requires a CD4+ T cell response . These data demonstrate that SSZ does not have direct anti-Pc activity , and that SSZ-enhanced clearance arises from modulation of the CD4+ T cell-mediated immune response . Although it has been inferred that AMs are responsible for CD4+ T cell-mediated clearance of Pc , there is little in vivo evidence to support this . Therefore , a multispectral imaging flow cytometry-based method was developed to quantify AM phagocytosis of Pc in vivo . The Amnis ImageStream , which combines digital imaging with traditional flow cytometry , allowed for dual staining of AM surface markers and internalized Pc . Because of the large number of cells that can be rapidly evaluated , a quantitative assessment of AM internalization of Pc was generated . This method was used to assess AM phagocytic activity in SSZ and PBS treated animals at various time points . CD11c was used as a marker for AMs , and a pool of five monoclonal antibodies that recognize the surface of mouse Pc were used to determine internalization of Pc relative to the AM . Figure 5 ( Panel A ) shows representative images of brightfield ( BF ) , CD11c ( green ) , Pc ( red ) , and CD11c-Pc merged . The no internalization control is a representative cell with CD11c signal , but no Pc internalization ( Figure 5A ) . Control staining was performed without inclusion of anti-Pc antibodies . As expected , no red signal was observed in these cells . The flow cytometer data were then quantified for AMs from individual SSZ or PBS treated mice at days 13 , 17/18 , and 21 PR . The percentage of AMs with internalized Pc in SSZ-treated mice was significantly higher than in PBS-treated mice at day 17/18 PR ( Figure 5B ) . Furthermore , when the absolute number of AM with internalized Pc was determined , the difference was even more striking . SSZ-treated mice had a 9-fold greater number of AM with internalized Pc than PBS-treated mice at days 17/18 PR ( Figure 5C ) . Importantly the number of AM with internalized Pc increased dramatically in PBS-treated mice at day 21 PR , coincident with Pc clearance and recovery from infection . These data indicate that AM-mediated clearance also occurs in PBS-treated mice , but that SSZ treatment accelerates this T cell-dependent process . A CD4+ T cell response was required for Pc clearance in both PBS and SSZ-treated animals . To determine whether CD4+ T cells are required for AM phagocytosis of Pc , infected SCID mice were immune reconstituted and given SSZ , SSZ plus anti-CD4 antibody , PBS , or PBS plus anti-CD4 antibody . As expected , SSZ-treated mice exhibited a large increase in AM phagocytosis of Pc at day 17/18 PR ( Figure 5D ) , and also exhibited significant fungal clearance at this time with an average Pc burden of log 2 . 8±1 . 1 ( as assessed by kexin gene copies ) . In contrast , SSZ-treated mice that were depleted of CD4+ T cells displayed nearly undetectable levels of AM phagocytosis of Pc ( Figure 5D ) , and maintained high average Pc lung burdens of log 7 . 5±0 . 1 ( p<0 . 05 compared to SSZ-treated mice ) . Likewise , PBS-treated animals displayed increased AM phagocytosis at day 21 PR , but phagocytosis was nearly undetectable in the absence of CD4+ T cells ( Figure 5D ) . Consistent with these results , PBS-treated mice had lower average Pc burdens than the PBS plus anti-CD4 group ( log 6 . 7±0 . 5 versus log 7 . 6±0 . 01; p<0 . 05 ) . Together , these data demonstrate that AM phagocytosis is the effector mechanism for CD4+ T cell-dependent clearance of Pc from the lung , and that SSZ alters the lung immune response in a manner that accelerates the macrophage-mediated phagocytosis of Pc . In order to validate the ImageStream data , confocal microscopy was used to confirm the internalization and localization of Pc within AMs . BAL cells were recovered from PBS- and SSZ-treated mice at time points when AMs are actively phagocytosing Pc . Based on the data in Figure 5 , the time points chosen were day 21 PR for PBS-treated mice , and day 17 PR for SSZ-treated mice . Cells were stained with DAPI ( blue ) , anti-Pc antibody ( green ) , anti-CD11c antibody ( gray ) , and anti- lysosomal-associated membrane protein-1 ( LAMP-1 ) antibody ( red ) . LAMP-1 is a lysosome-specific protein , and was used to co-localize Pc staining to the phagolysosome inside AMs . As shown in Figure 6 , we found that Pc signal co-localized with LAMP-1 signal inside CD11c+ AMs from both PBS- ( Day 21 ) and SSZ- ( Day 17 ) treated animals . The “Control” Panel shows a direct comparison between an AM with Pc and one without Pc next to each other in the same field . The cell without Pc ( top ) shows more diffuse LAMP-1 staining , while the bottom cell shows more focal LAMP-1 staining that co-localizes with Pc signal . This panel demonstrates differential staining and specificity of LAMP-1 and Pc antibodies . These data validate the quantitative ImageStream data as a measure of Pc internalization . Macrophages are immune effector cells for T cell-dependent responses , and distinct macrophage phenotypes with differential effects on host defense and inflammation have been identified [44] , [45] . Classically activated macrophages ( CAM ) are induced by TH1 cytokines , produce inducible nitric oxide synthase ( INOS ) , and are pro-inflammatory . In contrast , alternatively activated macrophages ( AAM ) are induced by TH2 cytokines , produce arginase ( ARG ) , are highly phagocytic , and produce anti-inflammatory mediators . Our studies have demonstrated that SSZ has profound effects on CD4+ T cell-dependent macrophage responses to Pc . Therefore , to determine whether SSZ alters PcP-related IRIS by modulating the polarity of the T helper response and subsequent AM effector phenotype , TH cytokine levels and macrophage activation state were assessed in experimental mice . SSZ treatment caused a dramatic decrease in lung IFN-γ production ( Figure 3 ) , with a concomitant increase in lung IL-4 production compared to PBS-treated mice ( Figure 7A ) . Thus SSZ produced a significant shift in the IL-4 to IFN-γ ratio in the lungs ( Figure 7B ) , effectively creating a pro-TH2 lung cytokine environment . In contrast , PBS-treated IRIS mice exhibited a pro-TH1 lung cytokine environment . To determine whether SSZ treatment altered AM phenotype , AMs from SSZ- and PBS-treated IRIS mice at day 13 PR were assessed for INOS and ARG protein expression . Because other cell types were present in the BAL fluid from mice with PcP , CD11c was used as a surface marker for AMs . CD11c positive AMs from PBS-treated IRIS mice stained intensely for INOS ( Figure 8A ) , but weakly for ARG ( Figure 8B ) . In contrast , CD11c positive AMs from SSZ-treated mice stained weakly for INOS ( Figure 8A ) , but intensely for ARG ( Figure 8B ) . Measurement of mean fluorescent intensity of INOS and ARG staining in CD11c positive cells was used to quantify the differential expression of CAM and AAM markers in SSZ- and PBS-treated mice ( Figure 8C , D ) . These data demonstrate that SSZ promotes alternative activation of AMs , which is associated with reduced immunopathogenesis but enhanced phagocytosis and accelerated fungal clearance .
IRIS is a clinical manifestation of PcP that occurs in certain patients when cell-mediated immunity is restored following a period of immune suppression and infection [16] , [18] , [19] , [46] , [47] . The resulting acute pulmonary inflammatory response restores host defense , but also produces severe pathology . The current study demonstrates that modulation of the immune response dramatically reduces the severity of PcP-related IRIS . The SSZ-mediated reduction in physiological impairment was associated with abrogated cytokine responses , reduced immune cell recruitment to the lung , and reduced histological evidence of inflammation . Unexpectedly , SSZ did not impair , but actually enhanced the host's ability to clear the Pc infection , indicating that the immune pathways leading to injury are at least partly independent of the pathways leading to clearance . Macrophages are equipped to recognize and eliminate pathogens as well as promote or resolve inflammation . To test the hypothesis that SSZ enhances Pc clearance via downstream functional alteration of AMs , a multispectral imaging flow cytometry-based method was developed to assess and quantify the in vivo Pc phagocytic activity of AM . This technology demonstrated that AM are effector cells for CD4+ T-cell mediated Pc clearance , and that SSZ enhances clearance by accelerating the AM phagocytic response . Subsequent studies found that SSZ promotes alternative activation of AMs , which is associated with reduced immunopathogenesis , but enhanced phagocytosis and fungal clearance . These data demonstrate that AM can be phenotypically modified to enhance fungal phagocytosis and clearance without ehnancing their pro-inflammatory properties , and also provide in vivo evidence that macrophage phagocytosis is the mechanism of CD4+ T cell-dependent Pc clearance from the lung . SSZ is a clinically important immunomodulatory therapy for inflammatory diseases such as inflammatory bowel disease and rheumatoid arthritis [34]–[36] . Most of the beneficial effects of SSZ are attributed to its function as a potent inhibitor of NF-κB . SSZ directly inhibits the activity of Inhibitor of κB Kinase ( IKK ) , effectively preventing downstream κB-dependent transcriptional events [39] , [40] . Recent clinical studies have confirmed that the beneficial effects of SSZ in patients with ulcerative colitis are in fact related to inhibition of NF-κB activation in the mucosa , which results in reduced cytokine production , and less severe inflammation [48] . In addition to IKK inhibition , other mechanisms of SSZ action have been described . SSZ inhibits 5-aminoimidazole-4-carboxamidoribonucleotide transformylase causing the release of adenosine [49] , [50] , which controls inflammation at least partly through inhibition of NF-κB signaling [51] . Other investigators found that SSZ may alleviate inflammation in a mouse model of inflammatory bowel disease by interacting with PPAR ( peroxisome proliferator-activated receptor ) nuclear receptors [52] . It is noteworthy that a common mechanism of all of these interactions is related to NF-κB inhibition , and it seems likely that SSZ-mediated blockade of NF-κB is central to the beneficial effects observed in our model . In fact , a highly specific IKK inhibitor , BMS-345541 , mimicked the beneficial effects of SSZ on PcP-related lung injury and pulmonary dysfunction , suggesting that NF-κB plays an important role in the immune cascade leading to the development of PcP . However , BMS-345541 did not enhance pathogen clearance . Therefore , SSZ may have other , IKK-independent , immunomodulatory properties that account for the beneficial effects on AM phagocytosis and pathogen clearance . The beneficial action of SSZ may result from its effects on a single cell type , or more likely , from its combined effects on several cell types that contribute to injury and disease . Potential lymphocyte targets of SSZ include CD4+ , CD8+ , and B lymphocytes . SSZ has pro-apoptotic effects on activated T cells [37] , which may contribute to the reduced T cell numbers and inflammation found in PcP-related IRIS . SSZ also influences macrophage function through the induction of apoptosis , as well as alteration of macrophage inflammatory responses [53] , [54] . SSZ blocked TNF production and also abrogated IL-12 expression and NO production by stimulated macrophages [55] . Modification of macrophage IL-12 may represent a mechanism by which SSZ alters the nature of the T cell response during IRIS . NF-κB is also involved in pulmonary epithelial cell inflammatory responses to Pc [38] , [41] , [56] , providing another potential target for the action of SSZ . While the immunopathology associated with PcP and IRIS requires T cells , other cell types likely contribute to the overall disease process , and therefore the effectiveness of SSZ reported here likely results from multiple points of action . Our studies have found that SSZ produces a TH2 shift in the lung cytokine environment during PcP-related IRIS , and that this shift is reflected in the phenotype of alveolar macrophages . TH2 cytokines lead to alternative activation of macrophages , and consistent with a TH2 cytokine shift we found that AMs isolated from SSZ-treated mice express high levels of the AAM marker ARG , but low levels of the CAM marker INOS ( Figure 8 ) . In contrast , AMs from PBS-treated IRIS mice display a CAM phenotype with high expression of INOS . It is notable that despite a well-documented role for INOS in host defense , these data suggest that enhanced Pc phagocytosis in SSZ-treated mice is associated with an alternatively activated AM phenotype with low expression of INOS . Based on our results , we believe that increased phagocytosis by alternatively activated macrophages is the mechanism of enhanced Pc clearance . However , a role for INOS in Pc killing cannot be excluded . Although we observe less staining in AMs from SSZ-treated mice , they are not totally devoid of INOS protein . More extensive studies will be required to determine the contribution of INOS in this model . Although we have not demonstrated that the TH2 shift is solely responsible for the beneficial effects of SSZ during PcP , it is possible that TH2 cytokines acting through AAM effectors can increase fungal clearance while reducing immunopathogenesis . For example , TH2 cytokines enhance macrophage phagocytosis of Candida albicans by inducing macrophage expression of mannose receptor ( MR ) [57] , [58] and dectin-1 [59] . These pattern recognition molecules are markers of the AAM phenotype , and have known roles in anti-fungal host defense . Similarly a TH2 shift in SSZ-treated mice could enhance phagocytosis of Pc by eliciting AAM with increased expression of MR and dectin-1 . In addition , a TH2 shift may also attenuate the immunopathogenesis of PcP by reducing the production of pro-inflammatory TH1 cytokines , while enhancing production of anti-inflammatory TH2 cytokines . Elevated lung levels of the TH1 cytokines TNF-α and IFN-γ are associated with PcP-related lung injury and respiratory impairment [28] . In contrast , TH2-derived AAMs produce the potent anti-inflammatory cytokines IL-10 and TGF- β [44] , which can dampen inflammatory responses and may contribute to the reduced inflammation and injury in SSZ-treated mice . Importantly , the anti-inflammatory potential of AAMs has been established in vivo by studies showing that the adoptive transfer of in vitro programmed AAMs attenuates immunopathogenesis in mouse models of inflammatory disease [60] . Although these findings are consistent with a SSZ-induced shift in the polarity of the T cell response , further studies are required to establish whether TH2 cytokines and alternative activation of AMs are directly responsible for the beneficial effects of SSZ during PcP . Clinical studies have found that the severity of PcP correlates with the degree of pulmonary inflammation , but not with organism burden [9]–[14] . Controlled animal studies support these clinical observations , and have provided direct evidence that the immune response is a major pathogenic component of PcP [26] , [28]–[31] , [61] . Consequently , antibiotic treatment does not always produce rapid improvement of patients with severe PcP , because organisms and antigen may continue to drive the pathological immune response . The efficacy of SSZ in dramatically attenuating the severity of PcP supports the contention that adjunctive immunomodulatory therapy that target the T cell response is critical to optimal treatment of patients . Currently , adjunctive corticosteroids are commonly used for the clinical treatment of PcP . The broad anti-inflammatory and immunosuppressive properties of steroids are presumed to provide benefit , but concrete evidence that steroids improve survival is lacking . Our group has recently published a study demonstrating that specific disruption of the T cell response to Pc with anti-CD3 antibody has beneficial effects in a mouse model of PcP-related IRIS [62] . While both SSZ and anti-CD3 altered the T cell response to Pc and reduced immunopathogenesis , they produced differential outcomes with respect to fungal clearance . Anti-CD3 produced a profound inhibition of T cell responses which reduced disease , but also prevented the clearance of Pc from the lung . In contrast , SSZ dampened PcP-related immunopathogenesis without suppressing TH responses to a degree that prevented eradication of the organism . SSZ not only reduced T cell-mediated inflammation , but altered the nature of the T cell response by promoting TH2 lung cytokine environment and alternative activation of macrophages . It is likely that the preservation of TH2 responses combined with a shift in the polarization of AMs in SSZ-treated mice is responsible for the differential effects of SSZ and anti-CD3 . Another important aspect of our work is the development of a multispectral imaging flow cytometer-based method to assess the in vivo phagocytic activity of AM during a T cell-mediated immune response by quantifying the percentage of AMs that contain internalized Pc . Understanding the mechanisms controlling Pc phagocytosis is an area of great interest , and many investigators have utilized various techniques to perform in vitro assessments of Pc phagocytosis [63]–[70] . However , demonstrating an in vivo role for AM phagocytosis in the clearance of Pc has been more difficult . AM with associated Pc have been observed in the BAL fluid of patients and animals [71]–[74] . However , this was in the setting of active PcP , the level of phagocytosis appeared low , and the significance to organism clearance was not determined . Others have performed in vivo assessments of phagocytosis immediately ( within 24 hours ) following a bolus inoculation of labeled Pc [75] , [76] . In addition , short-term depletion of AMs in rats reduced the clearance of Pc over the initial 24 hours post-inoculation [77] . While these studies were able to demonstrate a role for AM in vivo , the timing indicates that the investigators were evaluating the innate immune response to a bolus inoculation of Pc , rather than the CD4+ T cell-mediated response which is required for natural clearance of Pc from the lung . Using this new technology we were able to develop an assay to show that AMs are effector cells for the clearance of Pc during a natural CD4+ T cell-mediated immune response in vivo . The advantages of these ImageStream-based data are that: 1 ) internalized Pc was distinguished from attached Pc; 2 ) a large number of AM from each animal was rapidly assessed to provide quantification of the phagocytic response; 3 ) the dependence of phagocytic activity on the presence of CD4+ T cells was demonstrated; and 4 ) the CD4+ T cell-dependent increase in phagocytic activity correlated with the clearance kinetics of Pc . Importantly , the ImageStream data was validated using confocal microscopy to co-localize intracellular Pc with the lysosome protein LAMP-1 . These data indicate that Pc is located within the phagolysosome of AM , consistent with phagocytosis of the pathogen . The multispectral imaging flow cytometry technology should provide a valuable tool for further study of Pc phagocytosis in vivo . In summary , the results of this study indicate that the immune response to Pc can be modulated in a manner that reduces inflammatory consequences of PcP while enhancing the pathogen clearance through increased AM phagocytic capacity . We also developed a method for in vivo quantification of AM phagocytosis of Pc , and provide evidence that the macrophage is the ultimate effector for the CD4+ T cell-mediated clearance of Pc from the lungs . Immune modulation of T cell and AM functions should be considered potential therapeutic targets for the treatment of immune complications of PcP . Macrophages are equipped to recognize and eliminate pathogens as well as promote and/or resolve inflammation . Our results indicate that the phagocytic function of macrophages can be enhanced with a concomitant reduction in their pro-inflammatory properties . Enhancement of AM-mediated clearance of Pc may prove less inflammatory and generally superior to antibiotic therapy alone .
Severe combined immunodeficient ( SCID ) mice on a C . B-17 background ( C . B-Igh-1b/Icr Tac-Prkdcscid ) were purchased from Taconic ( Hudson , NY ) , or obtained from a breeding colony at the University of Rochester . The mice were housed using micro-isolator technology and fed sterilized food and water . To induce infection SCID mice were co-housed with Pc-infected SCID mice . Pc organisms were isolated as previously described [38] . Pc cysts were enumerated by standard Gomori's methenamine silver stain . Sulfasalazine ( SSZ ) ( Sigma , St . Louis , MO ) was administered once daily by intra-peritoneal ( i . p . ) injection at a dose of 200 mg per kg of body weight . Trimethoprim Sulfamethoxazole ( TMP-SMX ) ( SICOR Pharmaceuticals , Inc . Irvine , CA ) was administered once daily i . p . at a dose calculated to give 16 mg per kg of body weight of the Trimethoprim component of the drug combination . This dose was based on the therapeutic dose given to humans for the treatment of PcP . To induce infection SCID mice were intra-nasally inoculated with 1×105 purified Pc based on cyst count . Three weeks later the mice were immunologically reconstituted with 5×107 congenic spleen cells from normal C . B-17 mice . CD4+ T cells were depleted by i . p . injection of monoclonal antibody specific for mouse CD4 ( clone GK1 . 5 , ATCC TIB207 ) . Antibody injections ( 250 µg per mouse ) were given one day prior to and one day after immune reconstitution . Thereafter , antibody was administrated every four days for the duration of the experiment . Lung compliance and resistance were measured in live ventilated mice using a whole body plethysmograph ( BUXCO Electronics Inc . , Wilmington , NC ) connected to a Harvard rodent ventilator ( Harvard Apparatus , Southnatic , MA ) as previously described [78] . Dynamic lung compliance was normalized to the peak body weight of the animal . Respiratory rates were measured using whole body unrestrained chambers ( BUXCO Electronics Inc ) . Data was collected and analyzed using the Biosystems XA software package ( BUCXO Electronics Inc . ) . Right lung lobes were lavaged with four , one-ml aliquots of 1X Hank's balanced salt solution . Cell-free lavage fluid ( approximately 3 . 5 ml per mouse ) was frozen at −80°C . BAL cells were enumerated , and then differentials and multi-parameter flow cytometric analyses were performed . Anti-CD4-Fluorescein ( clone RM4-4 ) and anti-CD8a-Peridinin Chlorophyll-α Protein ( clone 53-6 . 7 ) , were purchased from BD Biosciences ( San Diego , CA ) . The anti-CD4 clone RM4-4 was used to confirm CD4+ cell depletion in vivo because it is not blocked by the CD4-depleting antibody ( clone GK1 . 5 ) . Cells were analyzed on a FACSCalibur ( BD Biosciences , San Jose , CA ) , with at least 10 , 000 events routinely analyzed for each Pc-infected mouse . At least 5 , 000 events were analyzed from uninfected control mice . For fixation the lungs were inflated with 15 cm gravity flow-pressure of 10% formalin ( Sigma , St . Louis , MO ) . The lungs were fixed in situ for 10 minutes under gravity flow pressure , and then removed from the animal and placed in fixative for 16 h at 4°C . Lung tissue was embedded in paraffin and 4 µM sections were cut . Hematoxylin and eosin was used to visualize tissue . Total protein concentration was determined in cell-free lavage by the colorimetric assay of Lowry . Albumin concentration was determined using the Mouse Albumin ELISA Quantitation kit from Bethyl Laboratories ( Montgomery , TX ) . TNF-α , IFN-γ , MCP-1 , and RANTES ELISA kits were used according to the manufacturer's instructions ( R&D , Minneapolis , MN ) . Since Pc cannot be cultured , a real-time PCR method was used to quantify lung burden . For quantification of Pc burden in right lung lobes , quantitative PCR using TaqMan primer/fluorogenic probe chemistry and an Applied Biosystems Prism 7000 Sequence Detection System ( Applied Biosystems , Foster City , CA ) was performed with a primer/probe set specific for the mouse Pc kexin gene as previously described [78] . For quantitation of Pc phagocytosis , an ImageStream multispectral imaging flow cytometer ( Amnis Corporation , Seattle , WA ) was used [79] , [80] . With this technology the number of BAL AM with internalized Pc was directly quantified . CD11c was used as a surface marker to identify AM , while anti-Pc antibodies were used to stain internalized Pc . Whole lungs were lavaged and BAL cells were washed with ice cold PBS with 1%BSA ( PBA ) , and incubated with mouse Fc Block ( BD Biosciences , San Diego , CA ) for 5 min on ice . Cells were then surface stained with anti-CD11c-phycoerythrin ( clone HL3 , BD Biosciences ) for 30 minutes on ice and washed with PBA . The cells were then permeabilized with BD Cytofix/Cytoperm Fixation and Permeabilization Solution ( BD Biosciences ) , and incubated with a pool of five different anti-Pneumocystis monoclonal antibodies for 30 minutes on ice . These antibodies were generated in our laboratory and were chosen because they recognize five different epitopes on the surface of Pc as determined by western blot and IFA ( 4F11 , 2B5 , 3D6 , 1F1 , 1F5 ) . Characterization of antibody 4F11 has been published [81] , but the remaining antibodies have not been further characterized . Following a wash step , the cells were incubated with Alexa Fluor 647 goat anti-mouse IgG ( H+L ) ( Invitrogen Molecular Probes , OR ) for 30 minutes on ice . Stained cells were washed , pelleted , and resuspended in 50 µl of ice cold 1% paraformaldehyde in PBS ( Electron Microscopy Sciences , PA ) . Samples were stored at 4°C in the dark until analyzed . Twenty thousand to forty thousand event image files were collected for each sample on an ImageStream100 using 200 mW of 488 nm and 90 mW of 658 nm laser power . The data obtained were analyzed using the ImageStream Data Exploration and Analysis Software ( IDEAS , Amnis ) , which quantifies morphometric and photometric parameters on a per-cell basis for large populations of collected events [79] , [82] . Single AM cells were gated as those events with normal brightfield area , high brightfield aspect ratio and CD11c positive staining . Each analyzed file contained at least 5000 AM events , enabling routine statistical analysis . AM that had phagocytosed Pc were identified by gating on CD11c+ events with high Pc-AF647 Max Pixel values ( discriminates punctuate Pc from diffuse background staining and autofluorescence ) and high Pc Internalization values . The Internalization score is a ratio of the intensity of bright red staining inside the cell ( defined by eroding the CD11c mask 6 pixels ) to the bright red staining in the membrane ( defined by subtracting the latter mask from the CD11c mask dilated 3 pixels ) , and the higher the score the greater the concentration of Pc inside the cell . In order to condition the measurement to Pc particles in sharp focus ( and thus in the central focal plane of the cell ) , only the mean of the upper quartile pixel intensities , weighted by the max pixel intensity , is used to compute the ratio [83] . The percentage of AM with internalized Pc was derived directly from the ImageStream data . The absolute number of AM with internalized Pc that was recovered from each animal was calculated by multiplying this percentage by the total number of AM recovered . Cells were stained with the identical antibodies under the identical conditions described for ImageStream analyses with the following exceptions . Anti-mouse CD11c-AlexaFluor 488 ( Invitrogen Molecular Probes , OR ) was used instead of CD11c-PE . Also , in some experiments , biotinylated anti-mouse CD107a ( LAMP-1 ) ( Biolegend , CA ) was used to co-localize intracellular Pc with lysosomes . Cells were first stained with anti-CD11c and anti-Pc antibodies as described above . After a wash and second permeabilization step , cells were stained with biotinylated anti-CD107a antibody for 30 minutes on ice followed by streptavidin conjugated with PE-Texas Red ( BD Bioscience , CA ) . After fixation , cells were centrifuged onto glass slides , mounted with anti-fade Vectashield ( Vector Laboratories , CA ) , and coverslipped for optimal imaging . Cells were imaged using an FV1000 Olympus Laser Scanning Confocal Microscope using an I×81 inverted microscope and a 60× objective with zoom of 4 . Lasers used were 405 , 488 , 559 , and 635 optimized to reduce photo-bleaching and used sequentially . Differential Interference Contrast ( DIC ) was performed using the 559 laser . Pixel dwell times were 8 us/pixel and 1024×1024 pixel format for high resolution imaging . Parameters were maintained consistent throughout imaging . All the images presented are the originals without post-processing . BAL cells were collected and centrifuged onto glass slides . Cells were fixed with 3% paraformaldehyde and initially stained with hamster anti-mouse CD11c ( Abcam , MA ) followed by either goat anti-hamster AF594 or goat anti-hamster AF488 ( Invitrogen Molecular Probe , Oregon ) secondary antibody . After permeabilization with 0 . 2% Triton ×−100 in phosphate buffered saline , cells were stained with rabbit anti-mouse iNOS ( Abcam , MA ) with goat anti-rabbit AF488 ( Invitrogen Molecular Probe , Oregon ) secondary antibody , or goat anti-mouse Arginase ( Santa Cruz Biotechnology , CA ) with donkey anti-goat AF546 ( Invitrogen Molecular Probe , Oregon ) secondary antibody . Slides were mounted with anti-fade Vectashield ( Vector Laboratories , CA ) and coverslipped for optimal imaging . A Nikon Eclipse E400 fluorescence microscope was used for photomicroscopy . All photographs for a given protein were taken with identical exposure settings . The ImageJ software ( National Institutes of Health ) was used to quantify the mean fluorescent intensity of iNOS and Arginase staining in CD11c positive alveolar macrophages . One-way analysis of variance was performed with the SigmaStat 2 . 0 software ( Jandel , San Rafael , Calif . ) . The Student-Newman-Keuls method was used for all pair-wise multiple comparisons . All animal protocols were pre-approved by University Committee on Animal Resources ( UCAR ) at the University of Rochester Medical Center according to the guidelines of the Association for Assessment and Accreditation of Laboratory Animal Care International .
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Pneumocystis is a fungal respiratory pathogen that causes life-threatening pneumonia ( PcP ) in immunosuppressed patients . PcP remains an infectious complication of AIDS and cancer , and is emerging in previously unrecognized clinical settings . Despite dramatic advances in health care and the availability of antibiotics to treat this infection , mortality rates have improved little over the past 25 years . T cell-mediated immunity is critical for host defense against respiratory fungal infections . However , T cells also cause PcP-related inflammation and lung injury . The results of the current study indicate that the immune response to Pneumocystis can be modulated to reduce tissue damaging inflammation while enhancing anti-fungal host defense . Alveolar macrophages recognize and eliminate pathogens from the lung and also regulate inflammation . We have identified alveolar macrophages as the effector cells for T cell-dependent clearance of Pneumocystis from the lung , and demonstrated that macrophage phenotype can be altered to enhance microbe elimination without promoting inflammatory injury . These results suggest that the effector mechanism of T cell-mediated fungal clearance is distinct from the effector mechanism of T cell-mediated lung inflammation and injury . This conceptual advance can be exploited to develop more effective therapeutic strategies to block inflammation while preserving host defense .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
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"microbiology/immunity",
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"pathology/pathophysiology",
"immunology/immunomodulation",
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2010
|
Immune Modulation with Sulfasalazine Attenuates Immunopathogenesis but Enhances Macrophage-Mediated Fungal Clearance during Pneumocystis Pneumonia
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Schistosoma japonicum causes major public health problems in China and the Philippines; this parasite , which is transmitted by freshwater snails of the species Oncomelania hupensis , causes the disease intestinal schistosomiasis in humans and cattle . Researchers working on Schistosoma in Africa have described the relationship between the parasites and their snail intermediate hosts as coevolved or even as an evolutionary arms race . In the present study this hypothesis of coevolution is evaluated for S . japonicum and O . hupensis . The origins and radiation of the snails and the parasite across China , and the taxonomic validity of the sub-species of O . hupensis , are also assessed . The findings provide no evidence for coevolution between S . japonicum and O . hupensis , and the phylogeographical analysis suggests a heterochronous radiation of the parasites and snails in response to different palaeogeographical and climatic triggers . The results are consistent with a hypothesis of East to West colonisation of China by Oncomelania with a re-invasion of Japan by O . hupensis from China . The Taiwan population of S . japonicum appears to be recently established in comparison with mainland Chinese populations . The snail and parasite populations of the western mountain region of China ( Yunnan and Sichuan ) appear to have been isolated from Southeast Asian populations since the Pleistocene; this has implications for road and rail links being constructed in the region , which will breach biogeographical barriers between China and Southeast Asia . The results also have implications for the spread of S . japonicum . In the absence of coevolution , the parasite may more readily colonise new snail populations to which it is not locally adapted , or even new intermediate host species; this can facilitate its dispersal into new areas . Additional work is required to assess further the risk of spread of S . japonicum .
In China schistosomiasis in humans is caused by infection with the parasitic blood-fluke Schistosoma japonicum ( Trematoda: Digenea ) . Schistosomiasis causes major public health problems in China and the Philippines[1] . Despite over 45 years of integrated control efforts , approximately one million people , and more than 1 . 7 million bovines and other mammals , are currently infected in mainland China[2] . The disease develops after direct penetration of the skin by free-swimming parasite larvae ( cercariae ) released from the snail intermediate host . Exposure to cercariae of S . japonicum occurs through contact with wet vegetation or walking through rice fields or other flooded areas inhabited by infective snails . In the case of S . japonicum , only sub-species of the snail Oncomelania hupensis ( Gastropoda: Pomatiopsidae ) are able to act as intermediate host[3] . The snails become infected by similarly mobile and penetrative larvae ( miracidia ) passed in the feces of definitive hosts , which include a wide variety of mammals ( up to 28 genera and 7 orders [1 , 4 , 5] ) . Much of the transmission in mainland China occurs across the generally flat and marshy lake-land areas around the middle to lower Yangtze river , where Oncomelania hupensis is the snail intermediate host . In the highland areas of Southwest China ( Sichuan and Yunnan ) O . hupensis robertsoni is the intermediate host . Fewer people are infected in the highland areas; however , recrudescence is most marked in this region and in Sichuan between 1989 and 2004 , the disease re-emerged in 8 counties ( prevalence: 1 . 4% to 18 . 3% in humans , and up to 22 . 3% in cattle and 0 . 16% in snails ) [6] . A third subspecies is found in China , O . hupensis tangi , which is endemic to hilly or coastal areas of Fujian , Guangdong and Guangxi provinces , although S . japonicum transmission appears to have been interrupted in these areas . In the Philippines , a further sub-species is responsible for transmission , namely O . hupensis quadrasi , and in Sulawesi O . hupensis lindoensis is responsible . Other subspecies exist in Taiwan and in Japan ( where the only other species of Oncomelania , O . minima , is also found ) but these are not , or are no longer , relevant to human health[7] . Clearly , S . japonicum continues to pose a serious public health problem and inter-disciplinary research is required to understand the patterns of transmission and persistence of the disease . Phylogeographical studies can shed light on the problem , particularly in determining where the disease comes from , explaining current distributions of the intermediate host and predicting future epidemiology . Comparative phylogenetics can help detect patterns of host-parasite coevolution and indicate any potential for regional adaptation . Despite the potential of such approaches , relatively little work has been done in this area for S . japonicum . The present study was therefore performed in order to apply current phylodynamic techniques to the estimation of sources and tracts of dispersal for this parasite and to test for the signatures of host-parasite coevolution during the evolution of S . japonicum and its intermediate hosts ( the latter necessarily having the defining influence on the distribution of the parasite ) . Strictly , the techniques used here test for phylogenetic congruence rather than directly for coevolution . The absence of phylogenetic congruence would make long-term coevolution unlikely; thus providing an indirect test for the latter . The study aimed to utilise the largest and most geographically extensive data set available ( Fig 1 ) . A geographical strain complex has been revealed within Schistosoma japonicum using partial DNA sequences of mitochondrial genes [22 , 23] . In 2005 microsatellites were used to assess variation among S . japonicum populations from 8 geographical locations in 7 endemic provinces across mainland China . The populations were found to fall into two main clades , a Sichuan/Yunnan clade and a lake/marshland clade of the middle and lower Yangtze river drainage[24] . The finding was later corroborated[25] using partial mitochondrial gene sequences ( cytb-nd4L-nd4 , cox3 , nad1 nad4 , nad5 and 16S-12S ) , with the additional observation that the lake/marshland clade included a highly diverse lower Yangtze sub-clade[25 , 26] . Molecular phylogenetic studies of Oncomelania hupensis are relatively few in number , but a major study in 2009[19] suggested that O . hupensis populations across China fall into three main clades . These were a middle/lower Yangtze lake and a marshland clade ( O . hupensis hupensis ) , a Sichuan/Yunnan mountain clade ( O . h . robertsoni ) , a clade corresponding to populations of the hilly littoral areas of Fujian ( O . h . tangi ) and a clade of the karst region of Guangxi ( O . h . hupensis or , according to the 2009 authors , O . h . guangxiensis ) . A more recent study used complete mitochondrial genome sequences to obtain mean genetic distance estimate of 12% for the protein coding genes between O . h . hupensis and O . h . robertsoni[13] . A study with similarly wide geographical coverage to that used here has been performed[27]; this employed DNA sequence variation in O . hupensis to indicate that isolation by distance was more significant in shaping genetic divergence than isolation by environment; however , this study which covered 29 localities , was population genetic ( not comparative phylogenetic ) and did not include the parasite . Although there have been past population phylogenetic studies of both Oncomelania and S . japonicum none has used as geographically diverse , taxon and character rich , data set as the present study . Also , this is the first quantitative comparison of the phylogenetic history of the snails and the parasites . Relatively few phylogenetic studies have considered the origins of these taxa , although Davis[28] proposed a Gondwanan origin for the Pomatiopsidae ( including Oncomelania and proto-S . japonicum ) , with rafting to mainland Asia ( via the Indian Craton after the break up of Gondwana ) and colonisation of Southeast Asia and China ( Tibet/Yunnan ) via the northern-India-Myanmar , Brahmaputra-Irrawaddy river corridor in an West to East direction , around 18 Ma . In contrast , an East to West hypothesis has been proposed for the Chinese Pomatiopsidae taxa[29] , with precursors of Oncomelania colonising originally from Australasia and via the Philippines , along island chains created by low sea levels and by tectonic movements ( rafting ) . After reaching Japan , Proto-Oncomelania gives rise to Oncomelania hupensis in mainland China; the latter then recolonises Japan , the Philippines and Sulawesi ( replacing antecedent forms ) . In a recent paper[30] , the East to West hypothesis was tested and the radiation across China dated at 15–5 Ma ( by molecular clock ) ; however , the radiation of S . japonicum did not appear to be isochronous with that of the present day intermediate hosts[31 , 32] . Nevertheless , the history of host utilization in Schistosoma has been regarded as an evolutionary battle with snail defences[11 , 33–37] , with the schistosome under significant pressure to evolve counter measures to snail immune responses , or to track snail divergence in an evolutionary arms race ( the ‘Red Queen hypothesis’[38] ) . Schistosomiasis researchers postulating coevolution have evidenced this by citing restriction of the parasites to certain snail lineages[11] , high levels of genetic variation in naturally exposed snail populations[34] , and evidence for selection in schistosomes exposed to snails previously selected for resistance[36] . The latter study[36] did use genetic ( microsatellite ) variation to demonstrate higher rates of parasite divergence in resistant laboratory lines of snails; however , this was over a very short time-scale and the resistant populations had not evolved under natural conditions . The study also used the Schistosoma mansoni:Biomphalaria glabrata system ( which involves far higher infection rates than seen with S . japonicum–see Discussion ) . Consequently , further studies are needed into the role of coevolution in the evolutionary history of Schistosoma . The present investigation was performed in view of the lack of studies on S . japonicum comparing the parasite and snail intermediate host evolutionary histories , the alternative hypotheses regarding the origins of these taxa and the colonisation of mainland China , and the recent availability of additional DNA sequence data ( improving geographical coverage ) . It is important to address these questions because they can help explain the current distribution of the parasite within the range of the snails , which is relevant to snail control strategies and the potential for range expansion , and to help assess the likely impacts of environmental manipulation such as the South-to-North-Water-Transfer project in China and the construction of road links . The Greater Mekong Subregion ( GMS ) Chengdu-Kunming corridor and GMS North-South Corridor from Yunnan , through Laos and to Thailand ( NSEC1 ) , both involve tunnels and rapid links through the mountains of Sichuan and Yunnan to Laos[39] . Consequently , the work will not only improve our understanding of host-parasite coevolution , but also shed light on the impacts of development in the region .
Three new samples of Oncomelania were taken and sequenced for this study; these were O . hupensis from Jiangshan in Jiangxi Province , China ( cox1 ) , and from Xinjin in Chengdu , Sichuan Province , China ( cox1 and rrnL ) , and O . hupensis nosophora from Kanagawa Kiyokawa in Honshu , Japan ( cox1 and rrnL ) –these loci all belonging to the mitochondrial genome , with partial DNA sequences of each locus obtained using the popular Folmer[40] and Palumbi[41] primers , to allow comparisons with data from earlier studies . The three samples were identified on the basis of conchology , morphology and ecological habit ( following[9] ) . The identifications were performed by YS and NH , two greatly experienced medical malacologists . The DNA sequencing followed procedures detailed elsewhere[30] . The remainder of the data were obtained from GenBank to give a total of 265 cox1 sequences and 70 rrnL sequences , apparently orthologous with the new sequence data above . Sequence data for Tricula hortensis from Sichuan China , also a pomatiopsid snail[42] , were included for use as an outgroup . In addition to the data for Oncomelania , 14 complete cox1 and cox3 DNA sequences were obtained from the GenBank for samples from 14 Schistosoma japonicum transmission localities across China . A corresponding Schistosoma mekongi sequence was obtained as an outgroup taxon for the S . japonicum analyses . Full details of the data used and sampling range are given in Fig 1 and Tables 1 , 2 and 3 . The data set included all available relevant sequence data in the GenBank at the time of searching; however , some data ( 10 sequences ) were excluded because of uncertain origin ( e . g . , DQ112269 , DQ112270 ) and taxonomy ( e . g . , EU780224 ) . The cox1 and cox3 loci were chosen following earlier work , which indicated that , for Schistosoma , cox3 was the locus of choice in terms of consistent phylogenetic signal and sufficient number of phylogenetically informative characters per site; this was followed by nad4 , however , the present data showed a haplotype diversity <1 at this locus and cox1 was used because it gave high support values and “correct” topology in the same study[43] . Many of the localities listed in Tables 1 and 2 were not published either in GenBank or in the papers where the data were first presented . In these cases the localities were found by accessing field work reports cited in the paper presenting the sequence data ( if present ) , matching published sample codes with associated accession numbers , reference to museum specimen accession numbers , contacting original researchers ( or the local officials who accompanied them or those who arranged their collections ) and referring to the personal observations of the present authors . In some cases , incomplete ( e . g . , to County level only ) location data was given , or ambiguously transliterated place names , in these cases location records were completed and transliterations resolved . The locations in Tables 1 and 2 have been changed ( where necessary ) to use the closest place name ( village etc ) appearing on Google Maps; this is for the convenience of future authors . After submission of this manuscript , new data for Philippine and Japanese Schistosoma japonicum were added to the GenBank by unpublished authors of another laboratory . These data are included in Table 3 , but were not included in the hypothesis testing; nevertheless , a phylogeny was estimated using this extended data set in order to assess the impact of the new data on the conclusions of this study ( if any ) . Sequence data were extracted from GenBank using Biopython 1 . 61 Bio . SeqIO[44] . The sequences were aligned using MUSCLE 3 . 8 . 31[45] , with default settings . To reduce computing time in subsequent analyses , the alignments were inspected in SeaView 4 . 4 . 2[46] and the first 240 and last 60 bps of the complete cox1 gene for the S . japonicum ( worm ) alignment were excluded ( the ingroup showed no variation in these regions ) . Taxa with identical sequences at a locus ( gene ) were then excluded , leaving one representative of each haplotype: for the worms identical sequences only occurred within villages or townships , but for the snails identical sequences were found up to county level . In data sets where sequences for two loci were concatenated , data were only excluded if sequences were identical between two taxa at both loci . The final data set for the worms comprised a concatenated cox1+cox3 sequence , and had 16 taxa ( 19 in the extended data set ) and 1994 characters ( after removal of 2 identical sequences ) . As cox1 and rrnL data were not both available for all snail taxa , there were two data sets for the snails . The cox1 data set comprised 146 taxa and 599 characters ( after removal of 129 identical sequences ) and a second data set was made using pyfasta 0 . 5 . 2 to select all cox1 sequences for which there was a corresponding rrnL sequence; these sequences were then concatenated to produce a cox1+rrnL “both loci” alignment of 51 taxa and 1110 characters . The reading frame of the protein coding loci was determined using ExPASy Translate[47] . In addition to the alignments for individual sequences , population level data sets were produced for the snails because these were expected to be easier to visualise and detect dispersal tracts . To achieve this , the geographical range of the samples was divided into 10 biogeographical regions ( see Fig 1 ) such that within each region there was no barrier to dispersal of Oncomelania; thus there would be only isolation by distance and no major ecological ( e . g . , lack of suitable habitat ) or physical ( e . g . , mountain ranges or ridges ) barriers; however it should be noted that the Tai Hu Plain ( THP ) region is likely to be interrupted by industrialised belts where there are no Oncomelania habitats . In contrast , each region is separated by mountains or similar areas of highland or sea . Consensus sequences were produced for the individuals within each region and a population sequence alignment estimated . The population data set included 13 ingroup taxa ( JAP has two island populations , and the Philippines ( PHL ) was also included ) . Phylogenetic analysis was performed using two fundamentally different approaches; the non-parametric Maximum Parsimony ( MP ) approach and the parametric Maximum Likelihood approach . Two contrasting methods were used so that resilience of the hypothesis to changes in method and associated assumptions could be used to reveal weakly supported clades . The rationale was that any clade that was represented in phylogenies found by both methods ( and well supported ) would be a reliable reconstruction of phylogenetic history for these taxa . In addition , the strategy helps reveal artefacts associated with a specific class of methods . RAxML 7 . 4 . 8[48] was chosen to implement the ML analysis because , among currently available programs , RAxML has shown best performance in terms of inference times and final likelihood values , and has a rapid boot-strapping algorithm which allows clade support to be estimated in reasonable time frames , even when estimating null distributions . A series of test runs were used to determine optimum values or states for the settings of the RAxML analyses ( details published elsewhere[30] ) . The apparently optimum partitioning strategy and evolutionary model for each partition was determined using PartitionFinder 1 . 0 . 1[49] , under a BIC criterion and models restricted to those implementable in RaxML . The chosen models for the snails were: cox1 , GTR+G codons CP123; cox1+rrnL , GTR+G codons CP123 and rrnL separately partitioned; populations , GTR+G codons CP111 cox1 and rrnL partitioned separately . For the worms the models were , for cox1+cox3 , GTR+G codons CP112 with cox1 and cox3 codons in the same partition ( i . e . , there were two only partitions ) . RAxML was run with 100000 bootstrap replicates , using every fifth tree found by bootstrapping as a starting tree for a series of 20 , 000 full ML searches . The CAT approximation in RAxML was not used . Three main runs were performed with different random number seeds . After checking that the independent runs led to trees of the same topology and very similar levels of support ( ±1% ) , the bootstrap trees for all three runs were pooled and a 100% ( strict ) majority rule consensus tree reported . For the hypothesis testing , a data set was constructed that included all snail taxa for which there was a worm sample taken at the same locality . These data included ten taxa and 1994 characters . The model and partition scheme for the worms was the same as for the full worm data set , and for the snails a two partition model was again chosen: GTR+G ( rrnL , cox1codon1 , cox1codon2 ) and cox1codon3 . POY 5 . 1 . 1[50] ( parallelised build ) was used to implement a Maximum Parsimony approach . The use of MP afforded an analysis free of the assumptions underlying ML methods , and the use of POY with its dynamic homology approach ( where characters ( transformation series ) are inferred during the process of phylogenetic reconstruction ) frees the analysis of any effects particular to the alignment inferred by MUSCLE[51] . A sensitivity analysis was used to choose the weighting ( gap cost etc ) and partition schemes for each data set , protocol published elsewhere[52] . In order to test whether the evolution of the DNA sequences was consistent with a particular hypothesis , such as coevolution of Oncomelania hupensis and Schistosoma japonicum , the Incongruence Length Difference test[53] ( ILD ) was used as implemented in PAUP* 4 . 0b10[54] , with 5000 replicates . The test employed a sub-set of the data which included only polymorphic sites ( for reasons published elsewhere[55] ) . The test , which randomly exchanges segments between the snail and worm data partitions , should give ML outcomes which are not significantly different from those of the original data if the snails and worms evolved to a common history . The ILD has been shown to be rather conservative when used as a test of topological congruence if phylogenies with trees of similar topologies are compared , with the opposite effect observed if the trees compared differ markedly in structure ( e . g . , internal branch length differences ) [56 , 57] . Noise in the phylogenetic signal can also lead to type-I errors in the ILD test[58] . Consequently , the hypotheses were also tested using Monte Carlo simulation in the manner of the SOWH test[59] . In the case of the test for coevolution , the test statistic is the likelihood ratio of the phylogeny inferred for the worm data ( unconstrained ) and the same phylogeny inferred with the evolutionary history constrained to that of the snails ( represented by the ML tree estimated for the snail data ) . A null distribution of the test statistic was calculated by simulating many data sets using Seq-Gen 1 . 3 . 3–1[60] and the ML parameters of the substitution model inferred for the worm data , but constrained under the null hypothesis ( the ML tree for the original worm data constrained by the snail ML tree ) . For each simulacrum the ML tree was estimated both unconstrained and constrained by the snail ML tree , and a likelihood ratio computed . The null distribution then being a distribution for the amount of discord expected to occur when the worm phylogeny had evolved according to the same history as the snails . If the likelihood ratio for the original data falls above the 95th percentile of the null distribution , the hypothesis that both worms and snails evolved to the same ( i . e . , the worms' ) phylogenetic history can be rejected at P<0 . 05 . The replicates were performed using RAxML ( with settings as for the original worm data , but bootstrapping set to terminate according to a convergence criterion based on the extended majority rule consensus trees ) , and they continued until the null distribution appeared to have stabilised , as judged by a plateau of t-values with increasing replicate number . In cases where the topologies resulting from phylogenetic analysis by ML and MP did not agree for a particular data set , a strict consensus tree was generated from the two trees so that discordant clades were represented by polytomies . Consequently , the resolved clades in the final trees for each data set were those supported by both methods . In order to visualise the phylogeographies of both snails and worms , the phylogenies were mapped in Marble Virtual Globe 1 . 8 . 3 using the Phylo2GE R script . In addition , phylogenies were compared ( topologically ) using the compare2Trees algorithm[61] , which scores each pair of branches , between the trees , according to the common taxon partitions they define , with the branches then paired so as to maximise the overall score; this process yields a score ( S ) value for a pair of trees .
To enable RAxML and reduce computing time 129 identical and/or ambiguous cox1 sequences were excluded from the original snail data set ( i . e . , the sequence alignment for Oncomelania ) to leave 146 taxa . Only one of the 129 exclusions involved identical sequences at the inter-regional scale . The haplotype diversity by region was roughly inversely proportional to the sampling intensity ( i . e . , number of sequences per region ) , except for YEB and PHL , and to a lesser degree SCB , which had small sample sizes and low haplotype diversities ( Table 4 ) . Replicate phylogenetic analyses run for the snail data , with different random seeds and only the cox1 data , failed to result in a common tree ( S<0 . 88 ) , and there was poor agreement between the results of the ML and MP searches ( S<0 . 55 ) ; the phylogeny also contained many unresolved clades . Consequently , the cox1 data were considered to lack phylogenetic signal and were not considered further in this study . In contrast , the phylogenies estimated for both loci ( cox1 and rrnL concatenated ) showed good agreement among replicate runs ( S>0 . 92 ) and between ML and MP ( S>0 . 75 ) . The strict ( 100% ) consensus tree between the ML and MP searches is given in Fig 2 . Considering O . hupensis , the only biogeographical regions characterised as monophyletic clades are JAP and YEB . Nevertheless , the Sichuan populations ( SCB and SAV ) , which lie in an isolated mountainous area , form an unresolved near-monophyletic clade , except for three SAV individuals which form a further unresolved clade at the base of the O . hupensis clade ( this could be a result of long branch attraction due to saturation or a lack of apomorphies in younger clades[62] , with slippage of long branches leading to SAV taxa , towards the root of the tree ) . The YEB populations , also mountainous but separated from the Sichuan populations by the Hengduan Range , formed a distinct basal clade at the same level as the three extraneous SAV samples . Thus , the basal clades of the phylogeny are occupied solely by O . h . robertsoni ( and O . minima ) . The remaining major clade , which appears derived from O . h . robertsoni contains all the other O . hupensis samples , including the non-Chinese taxa O . h . quadrasi ( Philippines ) , which is basal to the clade , and O . h . nosophora ( Japan ) –suggesting that these taxa did not diverge in situ . Although O . h . nosophora is monophyletic and O . h . robertsoni is near monophyletic ( it's apparent polyphyly might be explained by long branch attraction ) , O . h . hupensis is polyphyletic and includes O . h . tangi and O . h . formosana ( of FCP and Taiwan , respectively ) ; this suggests that the latter two may be populations of O . h . hupensis . The GCP taxon lies at the base of the Chinese O . h . hupensis clade and this gives some support to the case for O . h . guangxiensis . The populations of the lake and marshland region ( DLB , FCP and THP ) form an unresolved clade , suggesting that there are few barriers to migration ( gene-flow ) between them . In view of this , the population phylogeny ( where data for individuals is pooled to provide consensus sequences for each region ) provides a representative summary of the phylogeny ( Fig 3 ) . The population phylogeny agrees with that for both loci , based on individuals , except that it shows GCP as forming a sub-clade , of the Lake and Marshland , Taiwan and Japan clade , with PLB and DLB . The phylogeny estimated for the worms ( Fig 4 ) differed from that of the snails in certain key features . For example , some DLB and THP populations are basal to the western mountain clades ( YEB , SCB and SAV ) . As in the snail phylogeny , the Taiwan population falls within a clade comprised solely of Lake and Marshland mainland Chinese taxa; however , this clade excludes DLB and so contains only THP , PLB and TAI , also the Taiwan sample clusters with PLB forming a clade derived from the Chikou THP samples . The snail and corresponding worm phylogeny ( i . e . , that estimated in exclusion of taxa not held in common; Fig 5 ) showed a low level of correspondence ( S = 0 . 46 ) . Consequently , it was necessary to test the null hypothesis that the snails and worms had evolved to a common evolutionary history , i . e . , that of the snails . Initially the ILD test was used to detect significant conflict in the phylogenetic signals of the snail and worm data . The test was significant ( P = 0 . 00004 ) suggesting that the two data partitions are the result of different evolutionary processes . To test further the null hypothesis , a SOWH test was performed; this resulted in a likelihood ratio for the observed data ( unconstrained / constrained by the null hypothesis tree ) of 75 . 52 and a 95th percentile for the null distribution of 4 . 26 . Consequently , the null hypothesis can be rejected in the light of these data ( P<0 . 0001 ) . In view of these findings it appears highly unlikely that the evolutionary radiation of Schistosoma japonicum across China was shaped or driven by that of the snail intermediate hosts . Geospatially projected phylogenies ( Fig 6 and Files A and B in S1 Dataset ) assist in phylogeographical interpretation and in the present study they reveal clear differences between the radiations of the snails and the worms . The map for the snails ( Fig 6A ) suggests initial colonisation of the valleys of the western mountains ( SAV , SCB , YEB ) by a proto-Oncomelania hupensis robertsoni; thereafter these lineages , established in their respective valleys and basins , appear to have stabilised after initial divergence ( no further cladogenesis ) , and remained so throughout most of the history of O . hupensis . The mountain clade appears to have given rise to the Lake and Marshland and East-coast clades ( THP , FCP ) of Chinese O . h . hupensis , with radiations back into Japan ( as O . h . nosophora ) and to Taiwan and the Philippines more recently in the history of this species . A second , slightly more recent , radiation from DLB , west to GCP and eastwards to PLB , then occurs . In contrast the worms show a history where the Lake and Marshland ( eastern ) populations appear to involve cladogenic events that occur throughout the history of Chinese S . japonicum , whereas the western mountain taxa are stable following initial establishment in their respective valleys . Unlike the snails , the worms show a most recent colonisation event of Taiwan that is associated with the PLB region rather than THP/FCP . After submission of this manuscript , new data for Philippine and Japanese Schistosoma japonicum were added to the GenBank . In order to determine the position of these additional populations in the phylogeography and their congruence with the snail phylogenies , an extended data set was subjected to phylogenetic analysis . File C in S1 Dataset and S1 Fig give the resulting kml and an image showing the extended phylogeny projected onto a globe , respectively .
Of the four Chinese Oncomelania hupensis sub-species described by Davis[9] , only two are supported in the present study . Oncomelania h . robertsoni is not polyphyletic and all individuals sampled of this sub-species are basal in the phylogeny; therefore , this taxon is supported . In contrast , O . h . hupensis is polyphyletic and includes O . h . tangi and O . h . formosana; this suggests that O . h . tangi and O . h . formosana are not valid sub-species , but are O . h . hupensis . Indeed O . hupensis populations can demonstrate considerable differences in morphology ( mostly of the shell ) and yet cluster together genetically[11]; therefore it is possible that all three sub-species in the large derived clade indicated by phylogenetic analyses for both loci and for snail populations ( Figs 2 and 3 ) are in fact O . h . hupensis . The phylogeny estimated for the worms , in which the lowland populations form a clade distinct from those of the highland populations ( SAV , SCB and YEB ) , is consistent with morphological , host-utilisation , and maturation rate observations that suggested independent lineages or sub-species for the highland and lowland S . japonicum in China[63] . Nevertheless , O . h . hupensis appears paraphyletic with two DLB ( and one THP ) populations forming separate clades near the base of the tree . Divergence of some Hunan/Hubei ( DLB ) populations away from those of other Lake and Marshland regions could result from the particularly long history of intensive control efforts[4] in these provinces , with slippage of these clades towards the outgroup owing to long branch attraction coupled with a lack of apomorphies among younger clades[64] . It is also interesting to note that the zoophilic strain[65] from Taiwan is not genetically distinct from those strains capable of infecting humans , although it is one of the two most derived members of the lake and marshland clade . The lack of concordance between the snail and worm phylogenies found in the present study could result from heterochronous evolution of the host and parasite in response to different palaeo-geographical or climatic environments . In the closely related taxon , Schistosoma mekongi , the radiation of the parasite ( dated 2 . 1–1 . 0 Ma ) was shown to be independent of that of its intermediate host ( 10–5 Ma ) . Divergence events among the snails were considered to be a concerted response to the final Indosinian orogeny around 5 Ma , with S . mekongi colonising the snails across its present range much later ( early Pleistocene ) [31 , 32] . Using a molecular clock the introduction of O . hupensis across mainland China has been dated to the early Miocene ( c . a . , 22 Ma ) , with high rates of cladogenesis 8–2 Ma and linked to the exceptionally warm and humid climate in the region at that time and tectonic upheaval in Japan[30] . The divergence of the Schistosoma japonicum clade has been dated at 4 . 6 Ma[32]; this , implies that the radiation of O . hupensis occurred before that of S . japonicum . If the radiation of the snails and worms is heterochronous there is no opportunity for coevolution; the implication is also that ancestral intermediate hosts differed from those of the present , which again makes coevolution unlikely . Coevolution might be expected in Schistosoma species such as S . mansoni , which infect snail populations at relatively high prevalence and achieve high rates of cercariogenesis[66] , but seems unlikely in S . japonicum because of its lower prevalence in the intermediate host populations . The prevalence of natural infections in China ranges from 0 . 038% ( Jiangsu in 2011 ) to 7 . 8% ( Anhui in 2013 ) [67] . In cases where the snails experience a low probability of becoming infected , they are under little pressure to invest resources in defence[68] . In contrast , prevalences as high as 75 . 7% have been reported for natural populations of S . mansoni in Biomphalaria glabrata in Brazil[69] . Factors such as the generalised nature of gastropod immune systems , and evidence for frequent host switches in the parasites’ evolutionary histories , also make a “Red Queen” scenario unlikely for these schistosomes[32 , 68 , 70 , 71] . Consequently , molecular clock dating for other members of the S . sinensium clade and their intermediate hosts ( also close relatives of Oncomelania ) and the low prevalence of infection in O . hupensis suggest that the lack of evidence for coevolution found in this study is to be expected . It could be argued that comparison of naturally infected ( and infective ) snails , rather than snails from the local populations transmitting the parasite ( but not necessarily themselves infected ) would be more likely to reveal signs of coevolution , i . e . , there could be sub-populations or sub-strains of snails that have been coevolving with the worms , rather than the general snail populations sampled in this study . The existence of such sub-populations is questionable , as is the existence of resistant and susceptible lineages of snails in schistosomiasis . It has been shown that any snail taken from a natural population of B . glabrata will become infected if exposed to enough miracidia from a natural S . mansoni population[72] . Consequently , a “resistant” snail line is merely a sub-population selected to be discordant with the epitopes expressed by a particular Schistosoma line . Even authors working on the B . glabrata-S . mansoni association , have observed a complete reversal in resistance phenotype after a few laboratory generations and note that genotypic responses would only occur in associations where prevalences are high[36] . In view of this , it is unlikely that resistant sub-strains of O . hupensis exist and infection probably occurs more at random across the general snail population ( perhaps influenced by ecology and spatial coincidence ) . Nevertheless , it would be interesting to repeat the present study using naturally infected snails from the localities studied and seek to detect any signs of coevolution . As mentioned above , earlier studies date the introduction of O . hupensis to mainland China at around 22 Ma , at which time the region was significantly less mountainous , and three general clades appear to have been rapidly established; these span China , with the O . h . robertsoni clade in the far West , the Dongting Lake Basin ( DLB ) clade in the center of the Lake and Marshland region , and the Tai Hu Plain ( THP ) clade near the East coast of mainland China ( Fig 6A ) . O . h . robertsoni appears to have diverged little since its initial colonisation of the mountain valleys in which it is found today , and its lineages have probably been isolated therein since the second major uplift of the Himalaya about 7 Ma[73] . The other two clades appear to have undergone two successive , more recent , cladogenic events , which in the case of the DLB clade , gave rise to the GCP and PLB populations ( to the West and East , respectively; Fig 6A node 3 ) . The THP clade gave rise to FCP , Taiwan , Japanese and Philippine populations of O . h . hupensis ( Fig 6A node 2 ) . Such a recolonisation of Japan by mainland Chinese O . hupensis is consistent with the “East to West” hypothesis[29] . The divergence of the western clades is likely to have occurred around 8 Ma when the Himalayan uplift altered global climate and triggered increasing aridity in the region , which would have fragmented existing Oncomelania populations[30] . Interestingly , the Taiwan population is also included in the lake and marshland clades even though Taiwan has been separated from the mainland since Pleistocene[74 , 75]and the more recent divergences within O . hupensis occurred before 2 Ma . It is possible that tsunami events could have exchanged snails between the mainland and Taiwan . Indeed , the March 2011 Pacific tsunami demonstrated that large aggregates of material may cross even oceanic distances in less than 15 months and that freshwater pools on these may harbour viable communities of exotic aquatic organisms ( including molluscs ) [76] . Oncomelania is also capable of aestivating out of water for several months . In addition , intermittent land bridges occurred , linking Taiwan during the Quaternary[77] . The relative lack of genetic variation among the Taiwan populations also suggests a recent colonisation of the island ( or extinction of long established lineages followed by recent recolonisation ) . The Guangxi Plain ( GCP ) populations formed a clade distinct from other O . hupensis and may have been isolated from the other O . hupensis taxa since the late Miocene/late Pliocene by uplift along the margins of the Youjiang Basin ( Jiangnan range ) [78 , 79] . Although the radiation of S . japonicum is described above as occurring around 4 Ma later than that of the snails , the western ( mountain ) clades of the parasite still show the same initial divergence and then absence of cladogenesis as do the snails . The ancestral hosts of S . sinensium group parasites appear to be rodents ( especially Rattus and its sister group ) and it is therefore likely that S . japonicum radiated in China in concert with the Pliocene radiation of Rattus which began in Southeast Asia[80] . After colonising the valleys of Sichuan and Yunnan in rodents radiating into China from Southeast Asia , the parasites would become isolated in these valleys by cooling and increasing aridity in the Pleistocene[81]; thus suppressing further cladogenesis . In contrast , the lake and marshland clades undergo a series of cladogenic events spread from around the early Pliocene towards the Recent . Initially DLB and THP clades are established , together with a second THP clade that is derived from the O . h . robertsoni clades ( Fig 6B node 1 ) , this is followed by progressive diversification of one branch of the second THP clade ( Fig 6B node 2 ) , whilst the DLB-associated THP clade remains stable . The second THP clade most recently gives rise to an ancestral form that diversifies into a PLB and a Taiwan clade ( Fig 6B node 3 ) . The possibility of a long-distance dispersal from Sichuan in the western mountains to THP near the East coast of China ( Fig 6B arrow ) is an intriguing one; however , the possibility of misidentification or laboratory error concerning Genbank deposited sequences must also be considered where highly inconsistent relationships are found The introduction needs to be dated in future work and might be related to traffic down the Yangtze river ( human activities ) and the extensive cladogenesis and spread of the Sichuan strain in the coastal lowland areas is an unexpected event , which might relate to better development of the parasite in naïve human hosts ( or presence of a more dynamic host population than in the mountain regions ) . Analysis of the extended data set ( S1 Fig ) shows the Japanese S . japonicum arising from the same basal THP lineage as the Taiwan population . In contrast the Philippine clade arises from the basal YEB clade along with taxa from Sichuan . Although this relationship appears to mirror that of the snail phylogeny , it is a relatively recent divergence in the parasites and a relatively earlier one in the snails; thus it does not increase the degree of phylogenetic congruence between the hosts and parasites . The possibility of extensive radiation and dispersal , after long-distance introduction of a Sichuan strain of S . japonicum to the coastal region , is important in view of the fact that the mountains of Yunnan and Sichuan appear to have formed a barrier to dispersal of O . h . robertsoni transmitted S . japonicum for perhaps millions of years . The observation is particularly relevant in the context of the South-to-North-Water-Transfer project ( Eastern Route ) which will transfer water from endemic areas in Jiangsu province to areas in Shandong Province , towards the Yellow river , where O . hupensis has yet to be found but where conditions appear to be favorable for transmission[82] . Oncomelania ( and the associated schistosomiasis ) are most widespread in the lake and marshland areas of the middle and lower Yangtze river drainage; the distribution of snail and parasite in the mountainous areas of Sichuan in more patchy , and in Yunnan they are found only in a restricted area around Dali[83] . As the GMS road projects will breach the mountain ranges between Sichuan and eastern China and Sichuan and Yunnan ( and further South into Laos and Thailand ) , it is important to understand the colonisation history of S . japonicum . The present work has led to the rejection of the hypothesis of coevolution for Schistosoma japonicum and Oncomelania hupensis on the basis of the samples available . The finding is consistent with models regarding the relative timing of the radiations of the two groups proposed in earlier studies , and with observations of a low prevalence of infection in these snails . Nevertheless , it is still possible that the parasites show some adaptations to a snail population through which they have been cycling for some time , but the analysis does suggest that the worms are not highly evolved/restricted to a particular sub-species or strain of snail . Consequently , host-switching or acquisition is more likely than would be implied by a Red Queen scenario . The findings also suggest that O . h . formosana ( of Taiwan ) and O . h . tangi ( of Fujian ) might be O . h . hupensis and not distinct sub-species . The phylogeographical reconstructions suggest that at least one long-distance dispersal event occurred across China between the western mountain populations of S . japonicum and the East coast region . The event appears to have triggered extensive cladogenesis and dispersal ( including to Taiwan ) on the East coast . Consequently , further work is necessary to confirm and to date this long-distance dispersal and to detect any further such events , so that their origins and driving forces can be determined . Further work is also required with a richer data set as support for some of the clades indicated in the analyses was less than 90% . The findings are particularly important in view of the infrastructure development plans which will breach the mountain barriers between Sichuan , Yunnan and Southeast Asia . The results also have implications for the spread of S . japonicum as , in the absence of coevolution , the parasite may more readily colonise new snail populations to which it is not locally adapted , or even new intermediate host species , and this can facilitate its dispersal into new areas . The work also lends support to the East-West hypothesis for the origin and dispersal of Oncomelania and the Pomatiopsidae .
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Schistosomiasis is a disease caused by a parasitic worm transmitted to humans by certain species of freshwater snails . In spite of several decades of intensive coordinated control schistosomiasis still infects around 1 million people in China . In order to understand the potential for spread of the disease into new areas and new snail species , it is helpful to know if the snails and parasites in China are coevolved; this means that evolutionary divergence in one group ( the snails ) is matched by a corresponding divergence in the other ( the parasites ) , which is what would be expected if the two groups are locked in an evolutionary arms race . DNA-sequence data were collected for snails and parasites from the same localities . The findings indicated that coevolution was unlikely to have occurred . The implications of this are that host-switching or acquisition is more likely than previously thought . Consequently , there is a greater potential for spread of the parasite into new areas . The role of mountain barriers in confining schistosomiasis to certain regions was highlighted; this is important in view of the current plans to breach these barriers by road and rail construction that will link China and Southeast Asia .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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Comparative Phylogenetic Studies on Schistosoma japonicum and Its Snail Intermediate Host Oncomelania hupensis: Origins, Dispersal and Coevolution
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Clonorchis sinensis is a group-I bio-carcinogen for cholangiocarcinoma ( CCA ) . Although the epidemiological evidence links clonorchiasis and CCA , the underlying molecular mechanism involved in this process is poorly understood . In the present study , we investigated expression of oncogenes and tumor suppressors , including PSMD10 , CDK4 , p53 and RB in C . sinensis induced hamster CCA model . Different histochemical/immunohistochemical techniques were performed to detect CCA in 4 groups of hamsters: uninfected control ( Ctrl . ) , infected with C . sinensis ( Cs ) , ingested N-nitrosodimethylamine ( NDMA ) , and both Cs infected and NDMA introduced ( Cs+NDMA ) . The liver tissues from all groups were analyzed for gene/protein expressions by quantitative PCR ( qPCR ) and western blotting . CCA was observed in all hamsters of Cs+NDMA group with well , moderate , and poorly differentiated types measured in 21 . 8% ± 1 . 5% , 13 . 3% ± 1 . 3% , and 10 . 8% ± 1 . 3% of total tissue section areas respectively . All CCA differentiations progressed in a time dependent manner , starting from the 8th week of infection . CCA stroma was characterized with increased collagen type I , mucin , and proliferative cell nuclear antigen ( PCNA ) . The qPCR analysis showed PSMD10 , CDK4 and p16INK4 were over-expressed , whereas p53 was under-expressed in the Cs+NDMA group . We observed no change in RB1 at mRNA level but found significant down-regulation of RB protein . The apoptosis related genes , BAX and caspase 9 were found downregulated in the CCA tissue . Gene/protein expressions were matched well with the pathological changes of different groups except the NDMA group . Though the hamsters in the NDMA group showed no marked pathological lesions , we observed over-expression of Akt/PKB and p53 genes proposing molecular interplay in this group which might be related to the CCA initiation in this animal model . The present findings suggest that oncogenes , PSMD10 and CDK4 , and tumor suppressors , p53 and RB , are involved in the carcinogenesis process of C . sinensis induced CCA in hamsters .
The Chinese liver fluke , Clonorchis sinensis Looss 1907 , is widely distributed in East Asia with some heavily endemic zones in China , Taiwan , Vietnam , Russia , and the Republic of Korea . In 2009 , C . sinensis was reclassified as a group-I biocarcinogen for human cholangiocarcinoma ( CCA ) by the International Agency for Research on Cancer ( IARC ) based on epidemiological data [1 , 2] . Recently it was included in the control programs of neglected tropical diseases by WHO [3] . C . sinensis infection causes clonorchiasis , which is characterized by hyperplasia of biliary epithelium and metaplasia of mucin secreting cells in the intrahepatic bile duct [3] . The infection forms intrahepatic neoplastic lesion leading to mass forming CCA in Syrian golden hamsters when introduced with N-nitrosodimethylamine ( NDMA ) [4] . Syrian golden hamsters serve as a suitable model to study this parasite mediated carcinogenesis [4 , 5] . The molecular mechanism of C . sinensis induced CCA is little known [6] and it is crucial to understand its pathophysiology and to design efficient treatment strategy for CCA patients residing in the endemic region of the liver fluke . The development of CCA is a multi-step process at genetic level in which alterations of oncogenes and tumor suppressors as well as cell-cycle , apoptosis , and angiogenesis related genes are involved [7] . Recently it has been found that PSMD10 ( also known as gankyrin ) , a regulatory subunit of 26S proteasome is upregulated in human CCA . It is also overexpressed in other types of cancer , including colorectal , pancreatic , and breast cancer . PSMD10 can regulate negatively most important tumor suppressors , p53 and retinoblastoma ( RB ) . Its binding with CDK4 ( cyclin-dependent kinase 4 ) further degrades RB . The RB pathway is crucially important and found to be inactivated almost all types of human cancer [8] . RB1 , p16INK4 and CDK4 are the major components of RB pathway , essential for cell cycle regulation specially for G1/S transition . RB1 is the first tumor suppressor gene cloned in hereditary retinoblastoma . p16INK4 interferes the bindings with D-type cyclins as CDK4 or CDK6 inhibitor . Moreover , p16INK4 prompts p21 or p27 release from cyclin D-CDK complex . Differential expression of p16INK4 as well as CDK4 leads to dysregulated progression of cell cycle in many cancers . One study also demonstrated alterations of RB pathway related genes such as RB1 , p16INK4 , cyclin D1 , and CDK4 in hamster CCA model of opisthorchiasis [9] . Beside these the apoptosis related genes were differentially expressed in the hamster CCA model [10] . Akt/PKB is the key driver of PI3K/Akt signal transduction pathway and its aberrant expression associated with malignancy [11] . Akt also inhibits apoptosis via the modulation of caspase 9 . The apoptosis usually begins with BAX accumulation on the mitochondrial surface leading to the release of cytochrome c which binds to caspase 9 along with other molecules and initiates the cell death cascade [10] . It has been shown that suppression of PSMD10 can cause apoptosis through BAX and caspase 9 mediated intrinsic pathway in hepatocellular carcinoma cells [12 , 13] . A comprehensive understanding of oncogenesis of C . sinensis-associated CCA is currently unknown , however , a previous study observed proliferative effect of C . sinensis excretory-secretory products ( ESP ) on different cell lines in vitro [14] . In this context , it is important to observe the changes of oncogenes and tumor suppressors at the molecular level . The present study investigated the involvement of oncogenes , PSMD10 , CDK4; gene related to cellular proliferation , Akt/PKB , as well as tumor suppression , p53 and RB in CCA induced by C . sinensis infection .
The animal experiment protocol was reviewed and approved by the institutional animal care and use committee ( IACUC ) of Seoul National University , Seoul , Korea ( SNU-100826-2 ) and followed the National Institutes of Health ( NIH ) guideline for the care and use of laboratory animals ( NIH publication no . 85–23 , 1985 , revised 1996 ) . It is accredited by the Ministry of Food and Drug Administration and also by the Ministry of Education , Science and Technology ( LNL08-402 ) as an animal experiment facility . The laboratory has been monitored and inspected regularly by the Ministry and the IACUC of Seoul National University . Syrian golden hamsters , weighing about 70 g , were purchased from the Central Laboratory Animals Inc . ( Seoul , Korea ) . Animals were housed at 21°C ± 2°C with 60% humidity and a 12-hour light-dark cycle , with free access to rat chow ( Samtako Bio Korea Inc . , Gyeonggi , Korea ) and tap water . All of the experiments were conducted with an effort to minimize the number of animals used and the suffering caused by the procedures used in the present study . All manipulations of animals were carried out in animal biosafety level-2 ( ABL-2 ) facilities in accordance with ABL-2 standard operating practices . Hamsters were euthanized with 2–3 times doses of anesthetics ( mixture of xylazine [10 mg/kg; Bayer , Korea] and zoletil-50 [30 mg/kg , Virbac , France] ) followed by cervical dislocation as a subsequent secondary measure . The metacercariae of C . sinensis were collected from naturally infected freshwater fish Pseudorasbora parva in Korea . We purchased the fish by licensed fishermen by the local district government , Bureau of Agriculture and Fishery of Gyeongsangnam-do , Korea . The fish flesh was digested in 0 . 5% pepsin solution with HCl and C . sinensis metacercariae were isolated under stereomicroscopic identification [15] . Male Syrian golden hamsters ( Mesocricetus auratus ) of 4–5 weeks old were divided randomly into 4 groups including 15 animals each . Group I ( Ctrl . ) was uninfected control , Group II ( Cs ) received 30 metacercariae of C . sinensis , Group III ( NDMA ) drank NDMA mixed water , and Group IV ( Cs+NDMA ) received both metacercariae and NDMA water . The hamsters of the Group II and IV were infected with the metacercarae by intra-gastric intubation , and those of the Group III and IV received NDMA at a concentration of 12 . 5 ppm in drinking water for 8 weeks ad libitum . After 4 , 8 , 12 and 16 weeks , the hamsters were sacrificed and checked for the pathological and molecular changes . To detect the PCNA , collagen I and collagen IV immunohistochemisty procedures were carried out using a Histomouse MAX kit ( Zymed Laboratories , Invitrogen Immunodetection , San Francisco , CA ) . The antigen was retrieved through incubation with citrate buffer ( pH = 6 ) at 100°C in a water bath for about 1 hour . At primary antibody application step , PCNA monoclonal antibody ( 1:100; Clone IPO-38 , Cat#10004805 , Cayman Chemical , Ann Arbor , MI ) or collagen I mouse monoclonal antibody ( 1:100; anti-collagen I antibody [COL-1] , Cat# ab6308 , Abcam , Seoul , Korea ) or collagen IV rabbit polyclonal antibody ( 1:100; Anti-Collagen IV , Cat# ab6586 , Abcam , Seoul , Korea ) was used . The 3-amino-9-ethylcarbazole ( AEC ) was utilized for the production of red to pink color with horseradish peroxidase ( HRP ) conjugated secondary antibody . A portion of the liver tissues from the hilar region of the livers of all hamsters were snap frozen in liquid nitrogen and stored in it for extraction of RNA . Total RNA was isolated using RNeasy plus mini kit ( Cat# 74134 , Qiagen , Hilden , Germany ) according to the manufacturer’s instructions . Reverse transcription of 1–3 μg of total RNA was done by Maxim RT premix ( Cat# 25081 , Gyeonggi-do , Korea ) cDNA synthesis kit . The cDNA was kept at -70°C until use . The primer pairs for PSMD10 was designed using primer BLAST of NCBI and for CDK4 , p16INK4 , RB1 , p53 , Akt/PKB , BAX , caspase 9 and the housekeeping gene , glyceraldehydes-3-phosphate dehydrogenase ( GAPDH ) were chosen from published articles . Published sequences were matched with the sequences of the GenBank and summarized in Table 1 . SYBR Green I ( Applied Biosystems , Waltham , MA ) DNA binding dye was used as fluorophore . After PCR amplification , melting curve analysis was performed to verify the PCR products . The standard curve was prepared for the determination of PCR efficiency . Before real-time PCR , all of the reactions were confirmed as single band in agarose gel electrophoresis by conventional PCR . Single band was also observed after real-time PCR as well ( S1 Fig ) . Gene expressions were calculated using 2-ΔΔCT ( Livak ) method . To determine the oncogenesis related protein levels in the hamster tissue , proteins were extracted according to the conventional method . Briefly , about 100 mg of the tissue was taken from each sample and grounded to a powdered preparation with liquid nitrogen . Needle homogenization was performed . The samples then underwent a process of 10 minutes homogenization and/or sonication in the presence of tissue protein extracting solution ( lysis buffer containing 50 mM Tris-Cl ( pH = 8 . 0 ) , 150 mM NaCl , 0 . 1% SDS , 100 μg/mL PMSF , 2 μg/mL aprotinin , 2 μg/mL leupeptin , and 1% NP40 ) . After cooling on ice for 30 minutes , and centrifugation at 14 , 000 g for 5 minutes at 4°C , the supernatants were collected . Proteins were separated ( 40 μg/lane ) by sodium dodecyl sulfate-polyacrylamide gel electrophoresis ( 8–12% SDS-PAGE ) . The concentration of proteins was determined by bicinchoninic acid ( BCA ) protein assay ( Pierce , Thermo Scientific , Rockford , IL ) using Nanodrop-1000 ( Thermo Scientific , Wilmington , DE ) according to manufacturer’s instruction . After electrophoresis , the proteins were electro-transferred to polyvinylidene fluoride ( PVDF ) membranes , blocked in 5% non-fat milk for 1 hour at room temperature ( RT ) and washed with PBST ( PBS with 0 . 1% Tween ) , and probed with following primary antibodies: CDK4 ( C-22: SC-260 , Santa Cruz Biotechnology Inc . Santa Cruz , CA ) , Akt1 ( C-20: SC-1618 , Santa Cruz , CA ) , p53 ( FL-393: SC-6243 , Santa Cruz , CA ) , RB ( C-15: SC-50 , Santa Cruz , CA ) , and actin ( I-19: SC-1616 , Santa Cruz , CA ) . The membranes were then incubated with HRP-conjugated anti-rabbit ( 1:4 , 000 dilution; Cat# 81–6120 , Zymax , Camarillo , CA ) or anti-goat ( 1:2000 dilution; Cat# P-0449 , Dako , Ely , UK ) secondary antibody . Finally the blots were treated with enhanced chemiluminescence reagents ( WEST-ZOL Plus Kit , iNtRON Biotechnology , Seongnam , Korea ) and exposed to X-ray film . The images were obtained by the transmission scanner with the internal control of the actin protein levels and relative quantitative analysis was carried out based on the image band density ratio with ImageJ software of NIH , Bethesda , MD . GenBank accession numbers for each gene were as follows; Organism: Mesocricetus auratus; PSMD10 , AF443797 . 1; Akt/PKB , M94355 . 1; RB1 , GQ246228; p53 , Y08900; p16INK4 , AF292567; CDK4 , GQ246229; BAX , AJ582075 . 1; Caspase-9 , NM_015733; GAPDH , U10983 . Protein accession numbers ( NCBI ) for each protein were as follows; Organism: Mus musculus; Actin , P68134; Akt1 , P31750; RB , P13405; TP53 P02340; CDK4 , P30285 . Data obtained from the experiments were analyzed by Microsoft Excel ( Ed . 2007 , USA ) , GraphPad Prism 5 and SPSS-19 statistical software . Comparisons of results were performed using a Student’s t-test . P values < 0 . 05 were considered as significant .
Mass forming lesions ( MFL ) were detected from gross observation of the liver’s surface and then from 2–4 mm slices of formalin-fixed livers . Representative slices from each lobe of the liver from each hamster were subjected to routine H&E staining ( Fig 1 ) . All hamsters in the Cs+NDMA group developed CCA leading to single or multiple MFLs . The CCAs originated in the Cs+NDMA group were categorized in well , moderately , and poorly differentiated types based on their histopathological features ( Fig 2 ) . In average , CCA was found in about 46% of the total tissue area of the Cs+NDMA group . Among CCA types , well differentiated CCA ( WDC ) was most prevalent and observed in 21 . 8% ± 1 . 5% of the total tissue area . Moderately differentiated CCA ( MDC ) was found in 13 . 3% ± 1 . 3% of the total tissue area and poorly differentiated CCA ( PDC ) was in 10 . 8% ± 1 . 3% of tissues ( Fig 2A ) . Beside this , one hamster of the NDMA group showed WDC and MDC restricted in a very limited area ( 0 . 5% ± 0 . 5% and 0 . 03% ± 0 . 3% respectively ) ( S1 Table ) . We also observed a time dependent progression of CCA from the 8th to 16th week of infection in the Cs+NDMA group ( Fig 2B ) . About 12% of the total tissue area was occupied by WDC at the onset of CCA at the 8th week and increased to 14 . 2% and 21 . 8% after 12 and 16 weeks of infection respectively . A very tiny fraction showed PDC after 8 weeks of infection , however , it increased to 10 . 8% of the total tissue area after 16 weeks ( S2 Table ) . Proliferating cell nuclear antigen ( PCNA ) is a homotrimeric molecule , facilitates DNA polymerase δ and is essential for DNA replication [18] . It serves as a proliferative marker for different types of cancer and important in the context of genotoxic stress [19] . In the current study , immunohistochemistry showed strong positive reaction against PCNA antibody only in the Cs+NDMA group among 4 groups of hamsters . PCNA was mostly accumulated in the cells of bile duct epithelium and the stroma , which confirmed the development of CCA ( Fig 3C ) . The presence of collagen fibers type I and IV was evaluated using immunohistochemistry in the Cs+NDMA group . Though positive staining was not observed in the 4th week of infection for collagen I but from the 8th to 16th week it showed strong positive staining . In the present study , we also observed positive reaction for collagen IV after 16 weeks of infection ( Fig 4 ) . Differential expression of genes/proteins was recognized in CCA by a number of studies [10 , 20–23] . In the present study , the relative expression of mRNA by real-time PCR ( Fig 5 ) showed that PSMD10 and CDK4 genes were over-expressed ( P = 0 . 034; P = 0 . 006 ) in the tumor tissues of the Cs+NDMA group hamster’s liver . Tumor suppressor gene p53 was downregulated both in the tumor ( Cs+NDMA-T; P < 0 . 001 ) and adjacent normal tissues ( Cs+NDMA-N; P < 0 . 001 ) but upregulated in the NDMA group ( P = 0 . 036 ) , and remained same in the Cs group . However , the other tumor suppressor RB1 demonstrated no change in tumor tissue of the Cs+NDMA group ( P = 0 . 440 ) . CDK4 inhibitor p16INK4 showed upregulation in the tumor ( P < 0 . 001 ) and adjacent normal tissues ( P < 0 . 001 ) as well as in the Cs group ( P = 0 . 007 ) but remained same in the NDMA group . An increase of p16INK4 in Cs+NDMA group was almost 27 fold which was highly significant . Akt/PKB showed slight upregulation but it was not significant ( Fig 5 ) ( S3 Table ) . Apoptosis related genes , BAX and caspase 9 , showed significant downregulation in CCA tissue ( P = 0 . 002; P = 0 . 002 ) compared to that in the control . Western blot analysis using Akt1 , CDK4 , p53 , and RB primary antibodies detected the proteins in the hamster tissues ( Fig 6 ) . Both p53 and RB proteins were found under-expressed in the Cs+NDMA group , however , CDK4 and Akt1 were increased . The increase of CDK4 ( P = 0 . 001 ) and decrease of p53 ( P = 0 . 043 ) and RB ( P = 0 . 021 ) were statistically significant ( Fig 6 ) ( S4 Table ) . Significant downregulation of RB protein also observed in the Cs group ( P = 0 . 024 ) .
In the present study , we detected CCA masses in all hamsters of the Cs+NDMA group . The histopathological analysis revealed well , moderate , and poorly differentiated CCA with necrotic center . The CCA tissues contained abundant collagen type I and mucin , and showed PCNA overexpression . A multifunctional gene PSMD10 and cell cycle regulatory oncogene CDK4 along with tumor suppressors ( p53 , RB ) were found to be expressed differentially in the CCA tissues suggesting their involvement in the process of CCA development in the C . sinensis and NDMA induced CCA hamster model . MFL is the main pathological finding of C . sinensis and NDMA induced CCA in the hamster model . All of the hamsters of the Cs+NDMA group developed the MFL of CCA , which is the first report that observed 100% prevalence of C . sinensis induced CCA . Further analysis of MFL revealed that all of three grades of CCA ( WDC , MDC and PDC ) were mixed present at the later time of infection . The histologic progression of CCA has occurred in a sequence from WDC to PDC ( Fig 2B ) in a time dependent manner , starting from the 8th week of infection . Such findings suggest that the CCA in this model begins from well differentiated type and later replaced gradually by poorly differentiated type . In the present study , we observed WDC and MDC in one MFL of the NDMA group ( 0 . 57% of total tissue area ) . Though the average areas were negligible , it suggested that CCA might be developed in the NDMA group when the 12 . 5 ppm dose of NDMA was introduced for 8 weeks and the hamsters were kept for 16 weeks . Optimization of dose and time for NDMA should be considered for the further improvement of this model . Collagens are the major component of the stroma which normally maintains tissue integrity . Type I collagen was found to be associated with the progression of CCA in the animal model and considered as a predictive marker for Opisthorchis viverrini induced CCA in human [24] . The collagen fibers were also evident from squamous cell carcinoma , colon carcinoma [25 , 26] and serve as a distinguishing characteristic of hepatocellular carcinoma and CCA [27] . The collagen type I in extracellular matrix ( ECM ) interacts with certain molecules such as periostin and activates Akt signaling pathway in CCA [28] . In the present study , the presence of abundant collagen fibers in and around the CCA stroma suggests strong ECM interactions . Among collagens , collagen type I serves as binding site for type I transmembrane receptor tyrosine kinases within the ECM and helps to mediate different stromal/cellular signaling [29] . Strong immunohistochemical staining for type I collagen just after 8 weeks of infection indicates activation of a number of signaling pathways in development of CCA . The increased level of such fibrillary collagen was maintained throughout the study period . Besides collagen I , we observed collagen type IV overexpression lately at the 16th week of infection which may indicate tumor invasion . Tumor cell survival , proliferation , and migration are highly dependent on ECM and collagen type IV which may serve as permissive substrates for tumor cell migration [30] . In gastrointestinal adenocarcinoma , elevated collagen IV level in peritoneal sample significantly associated with poor prognosis [31] . Therefore the presence of type IV collagen in the stroma of CCA might be due to the advancement of malignant CCA . The chronic inflammation caused by C . sinensis along with NDMA triggers activation of hepatic stellate cells , which may be precursors of both hepatocytes and cholangiocytes [30] . The inflammation and cellular activation can foster the collagen deposit . The CCA is a type of adenocarcinoma [17] which produces mucin . We checked mucin production and observed ample amount of mucin in the CCA tissues both by alcian blue and rapid mucin staining . At the cellular level , we observed extensive conversion of cholangiocytes to mucin secreting cells in the Cs+NDMA group about 7 and 5 folds more than that of the Cs and NDMA groups respectively ( P < 0 . 001; P = 0 . 001 ) ( S2 Fig ) ( S5 Table ) . Such mucin production is evident from different types of adenocarcinoma involving the pancreas , lungs , breast , ovary , colon and other organs [32] . The mucin secretion is well-known in the hyperplastic biliary mucosa of clonorchiasis [3] . Basically mucin secretion is one of local protective reactions to the parasite in the mucosa . Higher numbers of mucin producing cells in the CCA tissue suggest that the mucin was continuously produced in the neoplastic tissue . PCNA is an important marker for the detection of rapidly dividing cells in many cancerous tissues [33] . Our observation of strong positive reactions against PCNA in Cs+NDMA group but not in the tissues of other groups indicates higher proliferation activity in that particular group . PCNA can be a marker molecule of CCA in human clonorchiasis , which requires further evaluation . The present study recognized overexpression of a novel oncogene named PSMD10 in C . sinensis mediated CCA . Expression of PSMD10 was shown in endometrial , breast , and colorectal cancer [34–36] and very recently in human CCA [37] . Infection with C . sinensis can be one of the reasons for such increase . p16INK4 was downregulated in earlier studies with O . viverrini [9] , but we observed a 6-fold increase in the Cs and 27-fold in the Cs+NDMA group . Overexpression of p16INK4 was evident from cervical intraepithelial neoplasia [38] . The overexpressed p16INK4 failed to suppress CDK4 which indicated possible aberrant changes in this gene . In western blot analysis , the expression of RB protein was significantly decreased , which suggests a possible mutation in RB1 or rapid degradation of RB protein . Such mutated RB pathway gene can cause overexpression of p16INK4 [39 , 40] . Moreover , a study also suggested association of PSMD10 with the degradation of RB protein [41] . The p53 plays an important role in both tumor suppression and apoptosis . Previous studies found the overexpression of p53 in early infection of O . viverrini [10 , 42] , however , after long term infection with C . sinensis and NDMA treatment , p53 was downregulated in our model . In addition , CDK4 was upregulated significantly . Upregulation of oncogenes PSMD10 and CDK4 and downregulation of tumor suppressor p53 and RB confirmed carcinogenic changes at the genetic level in the present CCA model . One of the important hallmarks of cancer is avoidance of apoptosis . BAX localization on the mitochondrial membrane causes the release of cytochrome c release , which in turn activates the caspase cascade resulting apoptotic cell death [12] . In the present study , downregulation of apoptosis related genes , BAX and caspase 9 has occurred probably by the upregulation of PSMD10 [13] . Further study should be performed to elucidate the signaling pathway involving genes/proteins PSMD10 , CDK4 , p53 , and RB . The possible interactions between the genes/proteins in the development of CCA are summarized in S3 Fig . In conclusion , the underlying mechanism of CCA development relies on the alteration at the genetic level , which varies depending on the etiological agents . Continuous mechanical and chemical irritation by C . sinensis and NDMA may cause genetic alterations . Such accumulated genetic changes produce aberrant proteins leading to neoplastic transformation . An upregulation of PSMD10 and CDK4 genes along with the downregulation of tumor suppressor gene p53 and protein RB is more likely to be associated in C . sinensis and NDMA induced transformation of bile duct epithelial cells in Syrian golden hamsters . Downregulated BAX and caspase 9 may make more survival of the transformed cells possible , and the transformed cells initiate uncontrolled proliferation to form CCA mass . Overexpressed PCNA is detectable from the tumor tissue , which may serve as a marker of CCA in clonorchiasis .
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Clonorchis sinensis is a helminth parasite and a carcinogenic agent for cholangiocarcinoma ( CCA ) or bile duct cancer in humans . Though a large and compelling body of evidence suggests an association between C . sinensis and CCA , the mechanism underlying at the genetic/proteomic level is little known . To explore the underlying molecular mechanism we investigated a number of genes/proteins in C . sinensis induced hamster CCA model . Here C . sinensis induced CCA successfully in all hamsters when introduced with N-nitrosodimethylamine . The histopathology confirmed the development of CCA and detected excessive collagen fibers , mucin and cell division related protein . The quantitative PCR analysis showed increased levels of oncogenes PSMD10 , CDK4 and decreased level of tumor suppressor gene p53 . The western blot analysis observed significant decrease of another tumor suppressor called RB protein . Genes/protein expressions were matched well with the pathological changes of CCA hamster . The present study suggests that oncogenes , PSMD10 and CDK4 , and tumor suppressors gene p53 and protein RB , are involved in the carcinogenesis process of C . sinensis induced CCA in hamsters .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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Involvement of PSMD10, CDK4, and Tumor Suppressors in Development of Intrahepatic Cholangiocarcinoma of Syrian Golden Hamsters Induced by Clonorchis sinensis and N-Nitrosodimethylamine
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Epistatic interactions among genes can give rise to rugged fitness landscapes , in which multiple “peaks” of high-fitness allele combinations are separated by “valleys” of low-fitness genotypes . How populations traverse rugged fitness landscapes is a long-standing question in evolutionary biology . Sexual reproduction may affect how a population moves within a rugged fitness landscape . Sex may generate new high-fitness genotypes by recombination , but it may also destroy high-fitness genotypes by shuffling the genes of a fit parent with a genetically distinct mate , creating low-fitness offspring . Either of these opposing aspects of sex require genotypic diversity in the population . Spatially structured populations may harbor more diversity than well-mixed populations , potentially amplifying both positive and negative effects of sex . On the other hand , spatial structure leads to clumping in which mating is more likely to occur between like types , diminishing the effects of recombination . In this study , we use computer simulations to investigate the combined effects of recombination and spatial structure on adaptation in rugged fitness landscapes . We find that spatially restricted mating and offspring dispersal may allow multiple genotypes inhabiting suboptimal peaks to coexist , and recombination at the “sutures” between the clusters of these genotypes can create genetically novel offspring . Sometimes such an offspring genotype inhabits a new peak on the fitness landscape . In such a case , spatially restricted mating allows this fledgling subpopulation to avoid recombination with distinct genotypes , as mates are more likely to be the same genotype . Such population “centers” can allow nascent peaks to establish despite recombination . Spatial structure may therefore allow an evolving population to enjoy the creative side of sexual recombination while avoiding its destructive side .
Sexual recombination has long been a puzzling evolutionary strategy ( see [1 , 2] ) . Recombination has the potential to create novel high-fitness genotypes in a population , but also to destroy high-fitness lineages by recombining them with genetically distinct lineages . Whether recombination speeds or slows adaptation depends largely on the relative strengths of its creative and destructive effects . One of the earliest adaptive explanations for recombination is the Fisher-Muller effect , in which beneficial alleles in different lineages can recombine into a single lineage , speeding adaptation [3 , 4] . The Fisher-Muller effect exemplifies the creative aspect of sex , and many studies have shown faster adaptation due to Fisher-Muller dynamics [5–8] . However , the Fisher-Muller effect assumes that beneficial alleles remain beneficial when recombined into new genetic backgrounds . This assumption is necessarily broken in multi-peaked fitness landscapes [9] , which arise when genetic interactions among loci yield multiple high-fitness allele combinations separated by valleys of low-fitness intermediate genotypes . In such landscapes , the adaptive effects of recombination are more complex . Studies on two-locus rugged landscapes focus on escape from suboptimal peaks , and have found that modest levels of recombination may speed adaptation slightly , while substantial recombination slows or halts adaptation entirely [10–12] . However , studies on rugged landscapes with more than two loci yield conflicting results , variously reporting recombination as slowing adaptation [13] , speeding adaptation [14] , or having complex effects dependent on the topography of a fitness landscape , the population inhabiting it , and the time scale considered [15–17] . Studies on empirical fitness landscapes report recombination as speeding adaptation [6 , 18] or having complex effects dependent on the fitness topography and rate of recombination [15] . The varied results described above may partly depend on the genetic variation that a particular landscape supports . If there are multiple suboptimal peak genotypes , these competing lineages may interact . Depending on the topography of the fitness landscape , recombination between individuals on different suboptimal peaks may create an offspring in the attractive domain of a novel peak , termed “peak-jumping” [15 , 19] . Thus , in topographies that permit peak-jumping , when subpopulations occupy different suboptimal peaks , recombination may allow peak-jumping to novel , higher peaks [19 , 20] . What conditions might enable a recombining population to maintain the diversity required for peak-jumping ? Restricted mating and dispersal ( which we call “local reproduction” ) may promote population-wide diversity by slowing the spread of high-fitness genotypes and creating competitive refugia for lower-fitness genotypes [21 , 22] . However , the same spatial restriction that allows population-wide diversity also impedes recombination between those diverse types , as mating occurs largely within monotypic clusters . Martens and Hallatschek [22] show that recombination between spatially abutting lineages ( which we call “sutures” ) can be sufficient to speed adaptation due to Fisher-Muller effects in their smooth landscape model . In some rugged landscapes , recombination at sutures may allow peak-jumping . However , lineages founded by peak-jumping events are particularly prone to early extinction as recombination may disrupt the rare allele combinations and consequently prevent establishment—recombination with the majority genotype may pull fledgling peak populations off their precipices and into the valley between [23] . On the other hand , recombination within monotypic clusters ( which we call “centers” ) may allow high fidelity of rare allele combinations , but also prevent the creation of such rare allele combinations as no effective recombination is occurring . Which effects of sutures and centers dominate , and in what circumstances ? In this paper , we examine the combined effects of recombination and local reproduction on adaptation on rugged landscapes .
In our simulation , a population inhabits an n × n square lattice . Each lattice point may be empty or may house one organism . Organisms have a haploid genotype of L loci , where the allele at each locus is either a 0 or a 1 . Each genotype has an associated survival probability ( SG ) . Unless otherwise indicated , populations are initialized with individuals of the genotype farthest from the optimal genotype ( that is , G0 such that H ( G0 , Gopt ) = L , where H is the Hamming distance operator and Gopt is the optimal genotype ) , with each lattice point having an SG0 probability of starting occupied . Evolution occurs via discrete update steps described below , and simulations conclude when the optimal genotype reaches a predefined frequency , or when a predefined number of epochs have occurred , where an epoch is defined as n × n updates . At each update , a point is chosen at random . If this focal point houses an individual of genotype G , the individual dies with probability 1 − SG , and the lattice point becomes empty . If the focal point is already empty , then a birth event can occur . For a birth event , two parents are needed . The first parent is chosen from a pre-defined dispersal neighborhood about the focal point , and second parent is chosen from a pre-defined mating neighborhood about the first parent . For simplicity , we set the sizes of these two neighborhoods equal , and call the radius of this neighborhood the “reproductive distance” . If there are no parents who satisfy the criteria , no birth event occurs . We focus on two extreme cases . In our “local reproduction” condition , a focal point’s neighborhood is defined by the lattice points immediately to the north , east , south and west ( the Von Neumann neighborhood ) ; in our “global reproduction” condition , the neighborhood is defined as the entire lattice , minus the focal point . Once the parents are chosen , an offspring genotype is formed by recombination and mutation . To simulate recombination , one of the two parents is chosen at random to contribute the allele at the first locus , and between-locus crossover occurs with probability r . Thus r = 0 yields no crossing over , while r = 0 . 5 yields independent assortment of parental alleles . To simulate mutation , each locus of the recombined offspring’s binary genotype changes its allelic state ( 0→1 or 1→0 ) with probability μ . Finally , the offspring is born , and inhabits the initially-empty lattice point .
On rugged fitness landscapes , populations may become trapped on a suboptimal fitness peak . It is also possible for a population to discover multiple distinct suboptimal peaks before any single peak genotype has fixed . Localized reproduction may promote the coexistence of multiple peaks by increasing the time-to-fixation of a newly discovered peak . Thus , localized reproduction may foster the diversity of genotypes required for peak-jumping via recombination ( e . g . , the creation of peak genotype 1111 due to recombination between suboptimal peak genotypes 0011 and 1100 ) [19] . However , localized reproduction precludes peak-jumping unless the peak lineages are physically close . Physical proximity could result if two expanding peak lineages eventually abut , allowing meaningful recombination at the suture between the distinct genotypes . Such sutures between subpopulations may allow repeated discovery of genotypes in the domain of attraction of a higher fitness genotype . Indeed , in a representative simulation of intermediate recombination with local reproduction from Fig 1 , multiple suboptimal peak genotypes coexist ( 0011 and 1100 ) , and the globally optimal genotype ( 1111 ) is repeatedly created at the sutures between these subpopulations ( Fig 2B , S1 Video ) . In a parallel representative run with global reproduction , no such sutures exist , because an intermediate genotype , once discovered , quickly sweeps to near fixation ( Fig 2A , S1 Video ) . Does local reproduction encourage sutures between subpopulations ? To test this , we simulate a two-locus landscape with two peak genotypes ( 10 and 01 ) and two valley genotypes ( 00 and 11 , the latter of which is lethal ) . The population is initialized on genotype 00 , and we track how frequently genotype 11 is created , and how it is created . We find that genotype 11 is created by recombination more frequently in local rather than global reproductive schemes , while it is created by mutation at approximately the same frequency in the two schemes ( S3 Fig ) . Once a peak genotype is discovered , it may be lost due to subsequent recombination with unlike types , lowering the genotypic fidelity of its lineage [25] . When recombination rates are high , such loss may prevent a genotype from establishing [10 , 11 , 26] . However , spatially segregated populations may harbor population “centers” , in which mating pairs are likely to be genetically similar , preserving genotypic fidelity . Such centers may allow rare genotypes to persist in a population despite recombination . To examine the effect of centers on the establishment of a novel peak genotype , we model adaptation on a two-locus landscape in which a population may escape from suboptimal peak genotype 00 by crossing an adaptive valley ( genotypes 10 and 01 ) to optimal peak genotype 11 . We find a three-way interaction between recombination , reproductive distance , and centers ( p = 0 . 03 , Manly’s permutation test ) . Frequent recombination slows the establishment of the optimal peak genotype in global but not local reproductive schemes ( S4 Fig , top row ) . However , if ‘centers’ are prohibited—that is , if a rare peak genotype ( i . e . , a peak genotype comprising less than 1% of the population ) happens to select a homotypic neighbor as a mate , the mate is replaced with a random individual in the population—then the local and global reproductive schemes have similar results: when recombination is frequent , valley-crossing is effectively prohibited ( S4 Fig , bottom row ) . Nonspatial analysis of the two-locus rugged landscape suggests that valley-crossing is effectively prohibited when the recombination rate exceeds the selective advantage of the distant peak , as genetic loss due to recombination outpaces selection [10 , 11 , 26] . We too find a threshold above which valley-crossing is effectively prohibited , unless centers are provided by local recombination . The adaptive effects of local inbreeding have been investigated since at least Wright , who focused on the resultant decrease in the effective population size [27 , 28] . The corresponding increase in drift may allow subpopulations to cross adaptive valleys through sequential fixation [29] , which may speed valley crossing for the population as a whole [30] . Here , we focus rather on the local decrease in the effective recombination rate ( that is , the actual change in linkage disequilibrium due to recombination [31] ) which occurs in ‘centers’ , and protects rare allelic combinations regardless of their origin . While recombination may allow a population to more quickly climb a local peak , it can also trap populations on suboptimal peaks [17] . However , recombination may aid escape from suboptimal peaks if the landscape topography permits peak-jumping [14 , 19 , 32] . For peak-jumping to occur , multiple suboptimal peak genotypes must coexist in a population . For peak-jumping to substantially speed adaptation , distant peaks cannot be easily accessible by mutation . Thus , there is a limited range of mutation rates in which peak-jumping speeds adaptation: mutation rates must be high enough to create a diversity of genotypes , but not so high that all genotypes are easily accessible . By slowing the spread of high-fitness genotypes , local reproduction allows greater variation at lower mutation rates , and therefore expands the window in which recombination speeds adaptation ( Fig 3 ) . Similarly , larger lattices are more likely to allow variation , as more time is required for a fitter genotype to displace a less-fit genotype . Indeed , the larger the lattice , the more recombination speeds adaptation ( S5 Fig ) . Local reproduction promotes the coexistence of distinct types in a population , and recombination between distinct types may speed adaptation . Thus , at intermediate levels of recombination ( r = 0 . 1 ) , local reproduction expands the range of mutation rates for which recombination speeds adaptation . This expanded range persists at high levels of recombination ( r = 0 . 5 ) , while the corresponding range for global reproduction disappears entirely . Without the centers provided by local reproduction , high levels of recombination trap populations on suboptimal peaks . The protective effect of centers is robust to occasional global reproduction ( S6 Fig ) . Sutures should be most effective when recombination between two suboptimal peaks can create offspring in the attraction basin of a third , higher peak , allowing for peak-jumping . Centers should be most effective when novel peaks are discovered via peak-jumping , as recombination between the nascent peak and the majority genotypes can create low-fitness offspring . Thus the ability of sutures and centers to modulate the effects of recombination—to harness the creative aspect and mitigate the destructive aspect—may also be sensitive to the particular topography of a rugged landscape . The full topographies of some naturally occurring fitness landscapes have been measured for small subsets of their genotype spaces [33] . De Visser et al . [15] generated 5-locus empirical fitness landscapes by introducing deleterious mutations into the asexual fungus A . niger , and measuring the fitness effects of five individual mutations and all combinations thereof . Two complete 5-locus fitness landscapes were generated , with 32 genotypes each ( though the landscapes are not completely independent as they share four of their five loci of interest ) . Both landscapes were found to be rugged , with multiple local maxima and minima . However , only one of the landscapes ( which we call PJ+ ) had suboptimal peaks which could recombine into the attraction basin of the optimal peak; the other landscape ( PJ− ) did not . De Visser et al . found that recombination generally slows or halts the establishment of the optimal genotype in either landscape , though there was a window of very infrequent recombination that could speed adaptation in PJ+ and very slightly and rarely speed adaptation in PJ− ( see [15] , supplement B1 ) . We create landscapes parallel to PJ+ and PJ−for our model ( e . g . , replacing relative fitness with relative survival probabilities ) , and simulate evolution as before . We find a significant three-way interaction between recombination , reproductive distance , and fitness landscape topology on the waiting time for optimal genotype establishment ( p<0 . 001 , Manly’s permutation test ) . On PJ+ , recombination slows or prevents the establishment of the optimal genotype when reproduction is global , but never slows or prevents adaptation when reproduction is local ( Fig 4 , top panel ) . On PJ− , whose topography is less conducive to landscape exploration via recombination , we find similar results to PJ+ when reproduction is global , but high recombination ( r = 0 . 5 ) still slows the generation and establishment of the optimal genotype when reproduction is local ( Fig 4 , bottom panel ) . In our test landscape and in two empirically-derived landscapes , sufficiently high rates of recombination prohibit the establishment of a novel high-fitness peak when reproduction is global , but this destructive side of recombination is alleviated when reproduction is local . Moreover , in landscape topographies that allow peak-jumping ( our test landscape and , to a lesser extent , PJ+ ) , recombination can speed the establishment of novel high-fitness peaks . Thus , the landscape topography affects the ability of local reproduction to mediate the effects of recombination: accentuating exploration via “sutures” while mitigating recombinatory destruction of rare genotypes via “centers” . We suggest the greatest effect of sutures occurs when peak-jumping is possible , and the greatest effect of centers occurs when novel peaks are created via peak-jumping . The prevalence of such topographical features and spatial restrictions—and therefore how relevant “sutures” and “centers” are to natural populations—remains an empirical question . It is possible , though , that by creating “sutures” , spatially structured populations may efficiently explore rugged landscapes via recombination , and by creating “centers” , those same populations may permit the establishment of novel peaks despite recombination . Spatially structured populations may therefore harness recombination’s constructive effects while mitigating its destructive effects on adaptation in rugged landscapes .
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For a novel genotype to establish in a population , it must ( 1 ) be created , and ( 2 ) not be subsequently lost . Recombination is a double-edged sword in this process , potentially fostering creation , but also hastening loss as the novel genotype is being recombined with other genotypes , especially when rare . In this study , we find that spatial structure may affect both the creative and destructive aspects of recombination in rugged fitness landscapes . By slowing the spread of high-fitness genotypes , spatially restricted mating and dispersal may allow diverse subpopulations to arise . Reproduction across the borders of these subpopulations—at “sutures”—may create genetic novelty . Depending on the topography of the fitness landscape , such novelty may be in the domain of attraction of a new , higher peak; the population may “peak-jump” to an area of genotype space unlikely to be explored by mutation alone . Lineages founded by peak-jumping events are particularly prone to early extinction , as recombination with unlike genotypes may disrupt the rare allele combination and thereby produce low-fitness offspring . However , these fledgling peak lineages may be protected from early extinction by mating within small homotypic clusters—in “centers” . Thus , spatial structure may allow a population to create rare genotypes via recombination , and allow those rare genotypes to persist despite recombination .
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2016
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Evolution at ‘Sutures’ and ‘Centers’: Recombination Can Aid Adaptation of Spatially Structured Populations on Rugged Fitness Landscapes
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Repetitive sequences are a conserved feature of many bacterial genomes . While first reported almost thirty years ago , and frequently exploited for genotyping purposes , little is known about their origin , maintenance , or processes affecting the dynamics of within-genome evolution . Here , beginning with analysis of the diversity and abundance of short oligonucleotide sequences in the genome of Pseudomonas fluorescens SBW25 , we show that over-represented short sequences define three distinct groups ( GI , GII , and GIII ) of repetitive extragenic palindromic ( REP ) sequences . Patterns of REP distribution suggest that closely linked REP sequences form a functional replicative unit: REP doublets are over-represented , randomly distributed in extragenic space , and more highly conserved than singlets . In addition , doublets are organized as inverted repeats , which together with intervening spacer sequences are predicted to form hairpin structures in ssDNA or mRNA . We refer to these newly defined entities as REPINs ( REP doublets forming hairpins ) and identify short reads from population sequencing that reveal putative transposition intermediates . The proximal relationship between GI , GII , and GIII REPINs and specific REP-associated tyrosine transposases ( RAYTs ) , combined with features of the putative transposition intermediate , suggests a mechanism for within-genome dissemination . Analysis of the distribution of REPs in a range of RAYT–containing bacterial genomes , including Escherichia coli K-12 and Nostoc punctiforme , show that REPINs are a widely distributed , but hitherto unrecognized , family of miniature non-autonomous mobile DNA .
Short repetitive sequences are a feature of most genomes and have consequences for genome function and evolution [1] , [2] . Often attributable to the proliferation of selfish elements [3] , [4] , short repeats also arise from amplification processes , such as replication slippage [5] and via selection on genome architecture [6]–[8] . Repetitive DNA in bacterial genomes is less prominent than in eukaryotes , nonetheless , an over abundance of short oligomers is a hallmark of almost every microbial genome [9] . Known generically as interspersed repetitive sequences , these elements have a history of exploitation as signatures of genetic diversity ( e . g . , [10]–[12] ) , but their evolution , maintenance and mechanism of within- and between-genome dissemination are poorly understood [9] , [13]–[16] . Interspersed repetitive sequences fall into several broad groups each sharing short length ( individual units range from ∼20 to ∼130 bp ) , extragenic placement , and palindromic structure [9] , [17] . REPs ( repetitive extragenic palindromic sequences ) – also known as PUs ( palindromic units ) – range from ∼20 to ∼60 bp in length , possess an imperfect palindromic core , are widespread among bacteria , and occur hundreds of times per genome [13] , [18]–[23] . While often existing as singlets , REPs also form a range of complex higher order structures termed BIMEs ( bacterial interspersed mosaic elements ) [14] . CRISPRs ( clustered regularly interspaced short palindromic repeats ) are a further , higher order composite of REP-like sequences that are formed from direct repeats of short ( ∼30 bp ) palindromic sequences interspersed by similar size unique non-repeated DNA ( [24]; reviewed in [25] ) . Recent work shows that the unique sequences are often phage derived and that CRISPRs , along with associated proteins , confer resistance to phage by targeting viral DNA [25] , [26] . Non-autonomous DNA transposons form a more distinct family of repetitive sequences defined by their size ( ∼100 to ∼400 bp ) and presence of terminal inverted repeats . Also known generically as MITEs ( miniature inverted repeat transposable elements ) , non-autonomous transposons depend on transposase activity encoded by co-existing autonomous transposons for dissemination [4] . Identified initially in plants [27] , where evidence of active transposition has been obtained [28] , recent bioinformatic analyses suggest that they also occur in bacteria [29] , [30] . For example , ERICs ( enterobacterial repetitive intergenic consensus ) – found in a range of enteric bacteria including Escherichia coli , Salmonella and Yersinia [31] – and NEMISs ( Neisseria miniature insertion sequences ) in pathogenic neisseriae [32] are thought to be non-autonomous transposons ( MITEs ) . Scenarios for the origins and functional significance of non-autonomous elements , and to a lesser extent CRISPRs , can be envisaged , but this is not so for the majority of short interspersed repetitive sequences . Nonetheless , studies of specific elements in particular genetic contexts have uncovered evidence of functional roles ranging from transcription termination and control of mRNA stability , to binding sites for DNA polymerase I ( reviewed in [9] ) . However , the fact that the distribution and abundance of elements show substantial among-strain diversity [16] , [22] suggests that the range of functional roles is incidental , arising from , for example , co-option or genetic accommodation [31] . Differences in the distribution and abundance of repetitive elements among closely related strains carries additional significance in that it suggests that the evolution of these elements is independent of the core genome . This is particularly apparent from comparisons of closely related strains . For example , Pseudomonas fluorescens isolates SBW25 and Pf0-1 are closely related and yet highly dissimilar in terms of the nature , abundance and distribution of interspersed repetitive elements [22] , even , as we show here , at the level of REPs . While this may reflect unequal rates of element loss , an alternative possibility is independent acquisition . Implicit in this suggestion is the notion that repetitive elements are genetic parasites [13] , [31] , [33] . The idea that REPs are selfish elements is not new [13] , [31] , [33]; however , there is little evidence – either direct or indirect – to support such an assertion . Indeed , the small size of REPs makes a mechanism for autonomous replication difficult to envision , however , the recent discovery of a proximal association between REPs and IS200-like elements , termed RAYTs ( REP-associated tyrosine transposases ) [23] , raises interesting possibilities and suggests shared ancestry between RAYTs and certain REP families . Evolutionary approaches to the analysis of sequence motifs can be highly informative [34] . While there is a ready tendency to assume that motifs recognized by search algorithms have functional significance , this need not be so . Neutral evolutionary processes alone ( nothing more than random chance ) ensure that short sequences will occur multiple times within any given genome . Thus , before concluding functional significance , it is necessary to test the null hypothesis of chance . Should this hypothesis be rejected , then the conclusion that over-abundance of short sequences is attributable – at least in part – to natural selection is sound . Moreover , evidence for selection justifies the assumption of functional significance . A key issue , however , is the level of biological organization at which functionality has been selected . There are two distinct possibilities: short repeats may have evolved because of selective benefits conferred on the cell , but alternatively , they may deliver benefits at the level of the gene – more specifically , at the level of a genetic element , of which the repeat sequence is a component . Distinguishing between these two alternatives is possible , although not necessarily straightforward . Indeed , whereas on initial emergence , selection is likely to operate exclusively at one level , over time , it is likely to shift to encompass multiple levels [4] , [16] . Here , we take a fresh and unbiased look at bacterial genome sequences in order to analyze the frequency and nature of short sequence repeats . Our approach is informed by evolutionary theory and begins free of assumptions regarding functional significance . Accordingly , the null hypothesis that short sequence repeats are no more frequent than expected by chance is the initial focus . We begin by interrogating the P . fluorescens SBW25 genome . Using suitable null models we show that over-abundant oligomers – which cannot be accounted for by chance alone – fall into three separate groups , each with characteristics typical of REPs . Highly significant differences in patterns of REP abundance and diversity between SBW25 and a second closely related P . fluorescens strain led us to question the hypothesis that the causes of REP diversity are linked to cellular function . This prompted a search for a replicative unit , which , based on patterns of REP distribution , we argue is a REP doublet . We refer to these entities as REPINs ( REP doublets forming hairpins ) and provide evidence from population sequencing for the existence of a putative transposition intermediate . Finally , extension to a range of RAYT-containing bacterial genomes including E . coli K-12 and Nostoc punctiforme indicate that REP sequences , organized as REPINs , define a class of hitherto unrecognized miniature non-autonomous mobile DNA .
Defining repetitive DNA on the basis of short sequences ranging from 10–20 nucleotides is simple and can be done logically without invoking heuristics and approximations ( for longer sequences exact repetitions are rare ) . Figure 1 shows that the P . fluorescens SBW25 genome harbors numerous repetitive sequences: the most common 10-mer occurs 832 times; the most common 20-mer occurs 427 times . While these numbers appear significant , it is possible that they are no more than expected by random chance . To test this hypothesis , 100 random genomes were generated , with the same dinucleotide content , replication bias and length , as the SBW25 genome . The frequency of the most abundant oligonucleotides was determined from both leading and lagging strands . Figure 1 shows that the most abundant 10-mer from the randomly generated genomes occurs 304 times . For longer sequence lengths this number rapidly decreases ( four instances in the case of 20-mers ) : the number of repeats expected by chance alone is thus much lower than observed . In total , there are 108 different 10-mers and 14 , 351 different 20-mers that occur significantly more often in the P . fluorescens genome than the most abundant oligonucleotides from randomly generated genomes ( P<0 . 01 , Figure S1 ) . While compelling evidence for the existence of over-representation of short sequences , gene duplications could in part account for these findings [35] . We therefore sought an alternative null model . P . fluorescens Pf0-1 , one of the closest relatives of SBW25 , shares the same GC-content and has a highly similar dinucleotide content ( Table S1 ) ; coding density differs by 1 . 7% and the genome length differs by 4% ( 6 , 722 , 539 bp for SBW25 and 6 , 438 , 405 bp for Pf0-1 , [22] ) . The close similarity means that any bias in the representation of short sequences due to duplicative evolutionary processes , or other selective mechanisms , should be similar in both genomes . As in SBW25 , over-represented short sequences in Pf0-1 are more frequent than expected by chance ( Figure 1 ) , however , a considerable difference in short sequence frequency is apparent . The difference between SBW25 and Pf0-1 is greatest at a sequence length of 16 , where the most abundant sequence in SBW25 occurs 618 times – over 11 times more frequently than the most abundant 16-mer in Pf0-1 ( Figure S2 ) . On the basis of comparisons to both the random null model and the Pf0-1 genome we deemed all SBW25 16-mers occurring more than 55 times ( the frequency of the most abundant 16-mer in Pf0-1 ) to be over-represented . This led us to reject the null hypothesis that chance alone explains the occurrence of short repetitive sequences in the SBW25 genome . Accordingly , we attribute over-representation of oligonucleotides to selective processes . The collection of over-represented 16-mers together encompasses 96 different sequences; however , a cursory glance suggested that many share similarity . Using a grouping method designed to detect overlapping subsets of sequences ( Methods and Figure S3 ) , the 96 sequences were found to be members of just three separate sequence groups ( GI , GII and GIII ( Figure S4 ) ) , each containing an imperfect palindrome ( the palindrome overlaps the most abundant 16-mer in GI and GII , but is part of the most abundant 16-mer in GIII ( Table 1 ) ) . The most abundant 16-mers of each group together occur 1 , 067 times . The majority of these sequences are extragenic; only 14 16-mers overlap with genes . Together these data show that the three groups of 16-mers are over-represented in the SBW25 genome , contain an imperfect palindromic core and are primarily extragenic . Possessing the hallmarks of repetitive extragenic palindromic ( REP ) sequences , we conclude that the three groups of 16-mers are , for all intents and purposes , synonymous with REPs . In order to accommodate the possibility of related family members , we generated a pool of sequences that differed to GI , GII and GIII sequences by up to four bases . This generated 488 , 373 different 16-mers of which 1 , 861 were located in extragenic space . To define the proportion of false positives the search was repeated by interrogating randomly generated extragenic space ( with the same dinucleotide content and length of each individual extragenic space ) for matches to the 488 , 373 different 16-mers . This showed that 12% of all sequences with up to four substitutions are false positives ( sequences unrelated to GI , GII or GIII ) . Repeating the analysis with the subset of sequences , which differ firstly by three and subsequently , two substitutions showed that 2% and 0 . 2% of matches are false positive , respectively . For two substitutions the false positive rate is low enough to conclude that the described repetitive sequence families consist of at least 1 , 422 members ( Table 2 ) . The precise number of members belonging to each of the GI , GII and GIII groups cannot be determined because with a degeneracy of two , some sequences fall into more than one group . The selective causes for the prevalence of GI , GII and GIII sequences in the SBW25 genome are of considerable interest . Although implicit in many studies is the notion that REP-like sequences have evolved because of their selective benefit to the cell ( as transcription binding sites , termination signals and the like [20] , [36] , [37] ) , it is also possible that selection has favored their evolution as a consequence of benefits delivered to a genetic ( parasitic ) element , of which the repeat sequence is a component . The highly significant differences in the frequency , nature and genomic location of short repetitive sequences in SBW25 , compared to Pf0-1 make a compelling case for the latter . If the prevalence of GI , GII and GIII sequences is a consequence of gene-level selection , then this implies the existence of a replicative entity – a genetic element that has the capacity to reproduce within the genome . The distribution of REP sequences is likely to provide some information . One way to quantify the distribution is to measure distances between neighboring REP sequences and compare these to distances between REPs generated by a null ( random ) model . If individual REPs are randomly distributed then this would suggest the individual REP as replicative unit . If the distance between adjacent REPs is non-random , then this may suggest the evolving entity is some higher order arrangement of REPs . To construct the null model , 1 , 053 ( the number of invariant GI , GII and GIII sequences in extragenic space ) non-overlapping 16 bp segments were positioned at random within the extragenic space of the SBW25 genome . This process was repeated 10 , 000 times and the average occurrence of the distance between neighboring elements calculated . Equivalent data for the 1 , 053 over-represented REPs is shown in Figure 2 . A comparison between the two histograms reveals marked differences in the distributions of distances between next-neighbors . Most striking is the strong bias toward specific inter-element distances . This marked skew shows that REPs are not independently distributed and is suggestive of an underlying copying mechanism involving at least two REP sequences . Of note is the fact that doublets typically comprise pairs of identical GI , GII or GIII sequences and are rarely mixed ( although some exceptions are discussed below ) ( Figure 2 ) . To explore the possibility that the replicative unit is an entity comprised of two REP elements ( a REP doublet ) we determined the number of singlets , doublets , triplets and higher order arrangements of REPs ( REP clusters ) by examining the 400 bp flanking either side of each REP for the presence of REP sequences ( Figure S5 ) . Once again , the results of this analysis were compared to the null ( random ) model used above . According to the random model , 58% of all REP sequences are expected to occur as singlets , whereas data from SBW25 shows that just 18% are singlets . In contrast , 61% of all REPs are organized as doublets , which is significantly greater than the 17% expected by chance ( Table 3 ) . Interestingly , REP triplets are rarer than expected , whereas several higher order arrangements of REPs , including two sets of twelve ( see below ) , are more frequent than expected ( Table 3 ) . The highly significant over-representation of REP doublets suggests that the doublet defines an appropriate replicative unit . If true , then the distribution of doublets across extragenic space should be unaffected by neighboring REP elements and should thus conform approximately to a null ( random ) model . To test this hypothesis , random distributions of REP doublets over extragenic space were compared to actual REP clusters found in SBW25 ( Table 4 ) . However , because the distance between REPs ( in the doublet conformation ) varies ( Figure 2 ) , two random models were generated based on the two most common inter-REP spacings: 71 bp ( a doublet of GI REPs ) and 110 bp ( a doublet of GII REPs ) . Simulations were based on the random assignment of 560 REP doublets ( corresponding to the sum of REP clusters ( of two or more ) in Table 3 ) to extragenic space and were repeated 10 , 000 times . Although the two segments differ significantly in size , simulations for each family gave remarkably similar results ( Table 4 ) . Together these data show that the observed number resembles that predicted if the doublets are randomly distributed . A further prediction concerns evolutionary processes affecting doublets vs . singlets . If REP doublets are the replicative unit , then singlets are likely to derive from doublets , either by decay ( divergence ) of the neighboring element , or by destruction of the doublet through insertion or deletion . In either case the REP singlet is expected to be non-functional ( immobile ) and thus subject to random genetic drift . REP doublets on the other hand – being ( according to our hypothesis ) functional and potentially mobile – are expected to be shaped by selection: genetic diversity of REP singlets should thus be greater than doublets . To test this hypothesis we extracted GI , GII and GIII sequences from the SBW25 genome plus all related sequences that varied by up to two positions . Since only two nucleotide differences distinguish GII and GIII sequences from a GI sequence , GII and GIII sequences were defined by two fixed ( invariant ) positions ( GII: 2T , 6C; GIII: 6A , 13T ) . After extraction , sequences from each group were divided into a set of 16-mers obtained from singlets , a set of 16-mers from doublets and a set of 16-mers obtained from clusters ( where a cluster contains three or more REPs ) . For all nine sequence groups ( three from each GI , GII and GIII group ) the pairwise identity was calculated ( Figure 3 , see Methods for details ) . The average pairwise identity of 16-mers obtained from REP doublets is significantly greater than the average pairwise identity of 16-mers obtained from REP singlets: this is true for comparisons within each of the REP groups ( P<1e-10 for GI; P<1e-8 for GII and GIII ) . Analysis of the organization of REP doublets shows that in the majority of cases , pairs of REPs ( 93% of all 430 REP doublets ) – of either the GI , GII , or GIII types – are organized as two inverted REP sequences that overlap the most abundant 16-mer ( Figure 4A and 4B ) . While the spacer region between REPs shows less conservation than evident in the REPs themselves , secondary structure predictions for ssDNA shows that the conserved bases on each side pair resulting in a hairpin ( Figure 4E ) . Thus , while selection appears to favor highly conserved nucleotide arrangements for REP and adjacent sequences , the critical features of the intervening sequence would appear to be length , and capacity to form a hairpin . Indeed , compensatory changes on either side of the predicted hairpin are common ( Figure 4A ) . Finally , if our assertion that the doublet defines a replicative entity is correct , then evidence of movement could in principle come from population sequencing . To this end we interrogated 55 , 768 , 706 paired-end Illumina reads ( 36–76 bp long ) obtained from sequencing DNA extracted from 5×10e9 SBW25 cells , for evidence of insertion and excision events . A total of 18 putative insertions were detected , however , the possibility of false positives could not be discounted . A similar search for excision events proved more profitable: three single reads were identified which mapped to three different locations on the genome , each corresponding to unique sequences flanking a GI REP doublet ( Figure 4C and Figure S6 ) . However , the expected doublet was absent from all sequence reads leading us to conclude that these sequences were from DNA molecules from which the doublet had excised . Additionally , we observed 200 individual sequence reads spanning a GII REP doublet indicating its excision from the entire population ( Figure S6 ) . That these events could result from machine and/or chemistry error is improbably low . Furthermore , a search for evidence of REP singlet deletions from the ∼56 million Illumina reads failed to find evidence of a single such event ( see Methods ) . Details of the three excised GI doublets are shown in Figure 4C and 4D . Of particular interest is the asymmetrical nature of the deleted sequence: in all instances it begins ( in the left-hand ( 5′ ) end ( Figure 4B ) ) at the start of the invariant sequence defined by the most conserved 16-mer and extends through the spacer region into the second REP sequence . However , rather than finish at the end of the conserved 16-mer , the deletion truncates at the 3′-end of the right-hand REP sequence , leaving the last ∼6 bp of invariant sequence intact ( Figure 4C ) . Secondary structure predictions show a hairpin structure with a 5′-single strand tail . Although the structures of the hairpins are not identical ( due to differences in the sequence of the space region ) the 5′-tail is a feature of the excised entity in all instances ( Figure 4E ) . It is possible that the excised sequences define a putative transposition intermediate . Together the above analyses implicate REP doublets as a unit of selection: a family of mobile DNA that has , until now , eluded recognition . Although REP doublets have previously been noted as one of many different higher order arrangements of REPs , they have not before been implicated as replicative entities [16]–[20] . Furthermore , in previous discussions of higher order arrangements it has been assumed that the singlet is the basic building block . In contrast , our data supports the view that REP singlets are defunct remnants of once functional REPINs . Because of their likely evolutionary relevance , a label that defines the replicative entity appears warranted . Henceforth we refer to REP doublets forming hairpins as REPINs . While the majority of REPINs exist as singlets , some higher order arrangements are apparent ( above and Table 4 ) . These are of two main types: those showing a distinctive ordering and those with no apparent structure . REPINs occurring in ordered clusters are typically arranged as tandem repeats of nearly identical REPINs – including the flanking sequences ( Figure S7 ) . With 16 such clusters distributed throughout the genome , these arrays are the most common higher order arrangement of REPINs in SBW25 . The largest cluster consists of four REPINs ( plus an additional REP sequence ) with a total length of over 700 bp . Three higher order REPIN clusters are of particular note: one from each of the three distinctive REPIN groups ( GI , GII and GIII ) each located adjacent to one of the three recently identified REP-associate tyrosine transposases ( RAYTs , [23] ) ( pflu3939 , pflu4255 and pflu2165 ) . The fact that a different REPIN cluster is located beside each of the RAYTs , combined with the fact that REPINs ( and REPs ) in SBW25 come in three distinct flavors , raises the possibility that RAYTs are intimately linked to REPIN mobilization ( Figure 5 ) . REPINs in clusters lacking obvious organization are found in five regions of the genome and typically consist of two unrelated REPINs . Close inspection suggests that these clusters are formed by insertion of REPINs into , or next to , existing REPINs . REPs also form higher order arrangements . These are of two distinct types: the first involves highly organized tandem arrays of GI and GIII REP sequences: GI REPs are separated from GIII REPs by 112 bp; GIII REPs are separated from GI REPs by 72 bp . Five such tandem arrays are located at ∼2 Mbp all of which are found in forward orientation , six are found ∼4 Mbp in reverse orientation ( at a distance of ∼2 Mbp from the origin of replication ) . The two largest tandem arrays both contain 12 GI and GIII sequences , one found at ∼4 . 1 Mbp the other at ∼2 . 5 Mbp ( Figure S8 ) . These two arrays are almost identical copies of each other , but found in opposite orientations on opposite sides of the genome . The second type of tandemly organized REP sequences consists solely of evenly spaced GI sequences found at two positions in the genome . Similar to the GI–GIII tandem arrays one GI tandem array is found in forward and the other one in reverse orientation . REPIN dissemination could occur via the exploitation of a functional transposase encoded separately within the genome . Non-autonomous DNA transposons ( MITEs ) do precisely this and typically consist of two inverted repeats . REPINs also consist of two inverted repeats ( REP sequences ) and , as mentioned above , may exploit the putative transposase encoded by RAYTs . If REP sequences in other genomes are components of REPINs – and disseminate via RAYT-encoded transposase activity – then , given the broad distributions of RAYTs [23] , REPINs are likely to be a common feature of bacterial genomes; they are also likely to share common ancestry . Although a fully comprehensive among-genome analysis is beyond the scope of this paper we nonetheless analyzed REP sequence clusters in a variety of genomes containing RAYTs . To this end REP sequences were selected from 18 different bacterial strains including all fully sequenced Pseudomonas genomes , the genomes of E . coli K-12 DH10B and Salmonella enterica serovar Paratyphi A AKU 12601 ( chosen because of their significance for REP research ) and the genomes of Thioalkalivibrio HL-EbGR7 and N . punctiforme PCC73102 ( chosen because of their distant relation to Pseudomonas ) . A phylogenetic analysis of the RAYTs was firstly undertaken ( Figure S9 ) . Notably , RAYTs from these strains form two distinct evolutionary lineages with evidence of multiple independent introductions . For example , the genus Pseudomonas is separated into two sets of species defined by the presence of either ‘clade I’ or ‘clade II’ RAYTs . The genome of Thioalkalivibrio contains one clade I and one clade II RAYT . Several other genomes , in addition to SBW25 , contain more than a single RAYT , but these almost never cluster . In fact the most closely related RAYTs are found in different genomes . Overall the distribution of RAYTs among distantly related organisms shows evidence of lateral gene transfer; however , at the species level , lateral gene transfer does not seem to occur frequently as evident by the fact that RAYT phylogeny is largely congruent with the relationship among species ( Figure S9 ) . Since REP sequences have been shown to be associated with RAYT genes ( this work and [23] ) , we interrogated non-coding DNA flanking each RAYT for 16-mers that were repetitive , extragenic and palindromic , that is , are REPs . In each instance a REP was identified ( Table S2 ) . To test the hypothesis that REPs are organized as REPINs an analysis of the distribution of REPs was performed on each genome as described above ( also see Methods ) and included all REP sequences that differed from the consensus by up to two nucleotides . Results were expressed as the ratio of REP singlets to doublets , where ratios greater than two indicate that REPs occur predominantly as singlets . Ratios less than two mean that REPs occur predominantly as doublets . Figure 6 shows a histogram of singlet to doublet ratios for REP sequences associated with clade I RAYTs . Of the 20 REP sequence classes ( one associated with each RAYT , some genomes contain more than one RAYT e . g . , SBW25 ) 17 had singlet to doublet ratios of less than two , indicating that most REPs occur as doublets . The majority of doublets contained REPs as inverted pairs ( Table S3 ) as expected of REPINs . Our simple search method did not return conclusive results for clade II REP sequences . One possibility is that the REPIN structure in these genomes is less conserved . To this end we performed a secondary structure prediction on a sample of REP sequences . In all instances we found the general REPIN composition to hold ( two inverted REP sequences separated by a short stretch of DNA and forming a hairpin , Figure S10 ) , with the exception of REP sequences found in P . stutzeri: interestingly no REPINs were identified in this genome . We also analyzed higher order arrangements for clade I REP sequences , but these were not present in all analyzed genomes . They were predominantly found in P . syringae and P . fluorescens , although two REP sequence classes were also detected in P . putida ( Table S3 ) . No correlation was found between the singlet to doublet ratio and cluster formation . Taken together , the systematic cluster analysis of clade I REP sequences and secondary structure prediction of a selection of clade II REP sequences suggest that the organization of REP sequences into REPINs is a necessary condition for REP sequence distribution .
Short interspersed repetitive sequences are widely distributed in bacteria , but past studies have shed little light on their evolutionary origins . We began by examining the abundance and distribution of short sequences in P . fluorescens SBW25 and showed , by comparison against a random ( null ) model , and subsequently against Pf0-1 , that short sequences are over-represented . Moreover , we found that short repetitive sequences fall into three distinct groups ( GI , GII and GIII ) , each bearing characteristics typical of REP sequences , that is , they are repetitive , extragenic and palindromic . In order to discount the possibility that REP sequences are the product of mutation pressure ( a possibility already called into doubt by comparison to the random model ) we took advantage of the closely related Pf0-1 genome . Comparisons using this null model – based upon a genome likely to have been shaped by similar underlying evolutionary processes – allowed us to emphatically reject the possibility that REP evolution can be explained by drift . Our data thus indicate natural selection as the primary driver of REP sequence evolution . A critical issue is the nature of the entity upon which selection acts . Evidence that this entity comprises a doublet of REP sequences – a REP doublet forming a hairpin structure ( REPIN ) – came firstly from analysis of the distribution of REPs in extragenic space . The striking departure from a random model shown in Figure 2 , along with clear bias toward specific distances between REPs , pointed to the REPIN as the replicative entity . The hypothesis was further tested by examining the distribution of REP doublets in extragenic space , by measuring nucleotide diversity in singlets versus doublets , and by analysis of the conserved features of REPINs . Finally , the existence of REPINs as actively mobile entities was bolstered through the discovery of four deletion events that may define putative transposition intermediates ( Figure 4 ) . A previous analysis of the SBW25 genome using various repetitive DNA finding algorithms [22] revealed numerous repeat families . Two of these , the so named R0 and R2 repeats have characteristics similar to REPINs; indeed , a comparison ( Table S4 ) shows a correspondence between REPINs and the R0 and R2 repeats . In general R0 repeats map to GI REPINs , while R2 repeats correspond to a mixture of both GII and GIII REPINs . The mechanism by which REPINs are disseminated is a central , but unresolved issue . Recently , a hypothesis concerning REP sequence distribution was put forward [23] . The authors proposed that REP movement is effected by RAYTs – so named Y1 transposases – that are distantly related to the IS200/IS605 family of insertion sequences . Integral to the transposition of IS608 ( a member of the IS200/IS605 family ) are two imperfect ( REP-like ) palindromes that flank either side of the insertion sequence and which are recognized by the transposase [38] . Whereas Nunvar et al . [23] suggested that REPs are moved by RAYTs , our data leads us to predict that it is the REPIN ( and not the REP ) that is mobilized via the RAYT: REPINs could be transposed by a RAYT dimer encoded in trans that recognizes the REP doublet . This mechanism would result in the strong conservation of the two REP sequences that define a REPIN ( Figure S11 ) . The suggestion that RAYTs are integral to REPIN movement is given additional support by the discovery of excision events that appear to define the transposition intermediate . At first glance the footprints differ from expectations given that they do not encompass the full extent of the conserved REPIN ( Figure 4B ) . However the asymmetrical nature of the putative intermediate is telling , particularly in light of the unusual mechanism of IS608 transposition . IS608 transposes via a single stranded intermediate and exploits singled stranded DNA at the replication fork; moreover , the intermediate involves pairing of asymmetric ends [38]–[40] . Assuming the excised DNA ( Figure 4C and 4D ) is a transposition intermediate then a key issue is re-establishment of the symmetrical REPIN . This could happen if the 5′-tail was involved in target recognition and paired with complementary sequence . In this regard it is of interest to note that the 5′-tail of the putative intermediate , which secondary structure predictions show is unlikely to form part of the hairpin ( Figure 4E ) , is complementary to the 3′-end of the REPIN . It is possible that a recognition event involving pairing between complementary sequences , perhaps mediated via the RAYT , integrates back into DNA leading to the formation of a new REPIN . Although further insight requires molecular investigations , there exist a number of striking parallels with the mechanism of transposition of the IS200/IS605 family of insertion sequences to which RAYTs – and their associated REPINs – are related . While the argument for REPINs as replicative entities is supported by substantive data , REP singlets are nonetheless a notable feature of the SBW25 genome . Our data – particularly the significantly lower pairwise identity of REP singlets compared to REP doublets – suggests that these singlets are non-functional remnants of REPINs . But this does not explain why REP singlets are common . A close analysis of REP singletons reveals several possible routes for single REP sequences to emerge from REPINs . One possibility stems from limitations of our sequence search algorithms . When REPINs evolve neutrally successive acquisition of point mutations naturally leads to one REP becoming more decayed than the partner . If the less decayed REP is only just on the verge of recognition by our sequence search , then it is likely that the more decayed REP partner sequence will escape detection . A biologically plausible possibility is that singlets arise from insertion of DNA into REPINs . Indeed , earlier studies have noted that REP sequences are targets for certain insertion sequences [22] , [41] , [42] . REP singlets could also arise by deletion of the sequence between two REPs within a single REPIN leading to a long palindromic structure that contains only a single REP sequence: precisely such events can be seen in the genome of SBW25 ( F . Bertels and P . B . Rainey , unpublished ) . A further possibility is that selection may act to preserve individual REP sequences because of specific functional consequences [16] , [36] . A finding of note is the existence of several higher order arrangements of REPs and REPINs within the SBW25 genome , indeed , several such clusters occurred at a frequency above that expected from the null model ( Table 3 and Table 4 ) . Interestingly the majority of these clusters – at least those containing more than three REP sequences or REPINs – were arranged as highly ordered tandemly repeated units . This , combined with the fact that higher order arrangements were not found in all REPIN containing-genomes ( Table S3 ) , indicates a second mechanism for REP/REPIN cluster formation and suggests specific functional roles for these structures . Extension of our analysis to a set of related ( Pseudomonas ) and unrelated ( E . coli , S . enterica , N . puctiforme and Thioalkalivibrio ) genomes each known to contain RAYTs showed that REPs in these bacteria are present in the immediate vicinity of RAYTs: moreover , in accord with predictions , these REPs are organized as REPINs . This finding greatly bolsters our conjecture that REPINs are a unit of selection , are RAYT associated , and widely distributed . In addition , the apparently general nature of the association between REPINs and RAYTs , combined with substantial diversity among the elements themselves , suggests that the diversity of REPINs ( REPs ) and RAYTs is a consequence of longstanding co-evolution between RAYTs and their respective REPINs . The case for REPINs as widely distributed replicative entities is strong , but there remains much to be discovered , particularly regarding the mechanism of transposition , and the relationship between REPINs and RAYTs . A further unknown is the evolution of the entities themselves . One possibility is that REPINs are derived from the imperfect palindromic ( REP ) sequences flanking an ancestral IS200-like element – thus becoming non-autonomous elements [4] – but with a twist . Whereas non-autonomous elements exploit the transposase of extant transposons , the transposons they parasitize remain capable of autonomous replication . In contrast , RAYTs appear to be incapable of self-mobilization and exist as single copy entities ( in those genomes harboring more than a single RAYT each RAYT is distinctive and present as just a single copy ) . This suggests that REPINs evolved a means of parasitizing an IS200-like ancestor that not only caused divergence of RAYTs from an IS200-like precursor , but did so in such a way as to enslave the RAYT . Just what keeps this association from extinction is among the more intriguing questions for future research , but suggests the existence of either an addiction system that ensures death of any cell that loses RAYT functionality , or a functional role for the RAYT in cell physiology that is somehow linked to REP function . Finally , our evolutionary approach to the analysis of short repeats and discovery of REPINs and their associated RAYTs may prove useful for elucidating the origins of different kinds of short , repetitive , interspersed palindromic sequences such as NEMISs [32] , ERICs [31] and small dispersed repeats ( SDR ) [43] . Indeed , REPINs themselves could conceivably constitute the building blocks for a range of more complex repetitive structures . For example , REPINs that incorporate DNA beneficial to a host bacterium are likely to have an advantage over standard REPINs . In this regard it is possible that CRISPRs [24] and related mosaic entities are derived from REPIN-like elements .
100 genomes with the same dinucleotide content of the leading/lagging strand and length as the genome of P . fluorescens SBW25 were generated by randomly choosing nucleotides according to their occurrence probability based on the preceding nucleotide . To account for dinucleotide skew in the leading or lagging strand of the SBW25 genome , the dinucleotide content of the top strand was determined for the first half of the genome and of the bottom strand for the second half of the genome [22] . Sequence frequencies for all oligonucleotides of length 10 to 20 were determined using a sliding window with a step size of one for leading and lagging strand separately . The most abundant oligonucleotide for each sequence length was determined . This analysis was conducted for randomly generated genomes as well as for P . fluorescens SBW25 and Pf0-1 . All oligonucleotides of the chosen sequence length that occur more often in SBW25 than in Pf0-1 were ordered into groups using the following algorithm: 1 , Select the most abundant 16-mer from the list of 16-mers that occur more frequently than the most abundant 16-mer in Pf0-1; 2 , interrogate the SBW25 genome; 3 , extract all occurrences including 20 bp of flanking DNA; 4 , concatenate , separating each sequence by a vertical bar ( a symbol that is not part of the genomic alphabet ) ; 5 , search all remaining 16-mers from the list against the generated string; 6 , remove from the list of 16-mers all those sequences found within the generated string and place into the same group as the query; 7 , repeat until the list of 16-mers is empty ( Figure S3 ) . The genome was searched for related elements by introducing base pair substitutions into the most abundant sequence of each group to a maximum of four . The newly generated sequences , as well as the most abundant sequence of each group , were then used to interrogate the genome and the number of occurrences was counted . In order to determine the false positive rate , a simulation program was written to determine the number of sequences found in randomly generated extragenic space ( with the same dinucleotide content ) . In order to produce a null model against which the observed next-neighbor distances could be compared , 1 , 053 segments of length 16 were randomly assigned to the extragenic space of SBW25 . The simulation was repeated 10 , 000 times and for each simulation the distances to neighboring segments were determined . Additionally , the formation of clusters by GI , GII and GIII sequences with up to two mismatches ( 1 , 422 sequences ) was measured . A cluster of REP sequences was defined as a group of REP sequences where each REP sequence has two neighboring REP sequences within the group that are separated by less than 400 bp ( the next-neighbor distances showed no significant deviations from randomly expected distances above 400 bp ) and a maximum of two REP elements that have only one neighbor within the group which is separated by less than 400 bp . The same method was applied when distributing doublets randomly over the genome . Instead of 1 , 422 16 bp long segments , 560×71 bp and 560×110 bp long segments respectively , were randomly assigned . The number of REP doublets was determined by only counting doublets and clusters of doublets . For clusters that contain an odd number of REP sequences , only the even proportion was counted , thus excluding singlets . To compare the rate of decay between REP singlets and REP sequences that are part of clusters , REP sequences were divided into their respective groups and then subdivided depending on whether they are found in clusters , or as singlets . In order to include related sequences , the 16-mers were allowed to vary at up to two positions . Since GI 16-mers differ from GII and GIII 16-mers by only two nucleotides , GII and GIII sequences also had to have two group-specific bases ( GII: 2T , 6C; GIII: 6A , 13T ) . The significance of the singlet decay data was tested using a permutation test . Nine different REP sequence pools were created . Three sequence pools for each sequence group , one of which contained REP singlets , one REP doublets and one greater REP cluster sequences . Two sequences were randomly drawn without replacement from a specific sequence pool and their pairwise identity ( the number of sites that are identical between the two sequences divided by the total number of sites ) was calculated . This procedure was repeated until the sequence pool was empty . The whole process was repeated 100 , 000 times for each sequence pool , resulting in the calculation of 100 , 000 average pairwise identities ( mean ) . For GI sequences the maximum mean calculated for REP singlets never exceeded the minimum mean for REP sequences arranged as doublets . For GII and GIII sequences the maximum mean of REP singlets did exceed the minimum mean of REP sequences from doublets when more than 1 , 000 means were produced , hence the lower significance of 1e-8 . Additionally , for GI and GIII sequences the maximum mean for singlets also never exceeds the minimum mean for clusters ( P-value 1e-10 ) . The average of the calculated means and the standard deviation are displayed in Figure 3 . Since REP sequences have been shown to be associated with RAYT genes [23] , we looked for 16-mers that were repetitive , extragenic and palindromic in the non-coding DNA flanking RAYT genes . The most frequent 16-mers found within the flanking DNA were also part of or contained a palindrome and were found predominantly in extragenic space , thereby fulfilling all REP sequence prerequisites ( Table S2 ) . These 16-mers were then used for a subsequent cluster analysis ( flanking clade I RAYTs ) or a sample DNA secondary structure prediction ( flanking clade II RAYTs ) . Blast searches were performed using NCBI Blast [44] . The genome was browsed using Artemis [45] . Inverted repeats were identified using Repeat Finder [46] . The multiple alignments in Figure 4 were displayed with Geneious [47] ( due to the perfectly conserved distances between the 16-mers , the sequences were aligned after extraction from the genome , no alignment method was needed ) . DNA secondary structures were predicted using the mfold web server [48] . The RAYT phylogenetic tree was based on a translation alignment ( ClustalW2 [49] ) as implemented within Geneious [47] . The tree was constructed using a neighbor-joining [50] bootstrap analysis ( 1000 replicates ) also embedded in Geneious . Pseudomonas fluorescens SBW25 ( NC_012660 . 1 ) [22] Pseudomonas fluorescens Pf0-1 ( NC_007492 . 2 ) [22] Pseudomonas fluorescens Pf-5 ( NC_004129 . 6 ) [51] Pseudomonas syringae phaseolicola 1448A ( NC_005773 . 3 ) [52] Pseudomonas syringae syringae B728a ( NC_007005 . 1 ) [53] Pseudomonas syringae tomato DC3000 ( NC_004578 . 1 ) [54] Pseudomonas entomophila L48 ( NC_008027 . 1 ) [55] Pseudomonas putida W619 ( NC_010501 . 1 ) Pseudomonas putida KT2440 ( NC_002947 . 3 ) [56] Pseudomonas putida F1 ( NC_009512 . 1 ) Pseudomonas putida GB-1 ( NC_010322 . 1 ) Pseudomonas aeruginosa PAO1 ( NC_002516 . 2 ) [57] Pseudomonas aeruginosa PA7 ( NC_009656 . 1 ) [58] Pseudomonas aeruginosa LESB58 ( NC_011770 . 1 ) [59] Pseudomonas mendocina ymp ( NC_009439 . 1 ) Pseudomonas stutzeri A1501 ( NC_009434 . 1 ) [60] Salmonella enterica serovar Paratyphi A AKU_12601 ( NC_011147 . 1 ) [61] Escherichia coli K-12 DH10B ( NC_010473 . 1 ) [62] Thioalkalivibrio sp HL-EbGR7 ( NC_011901 . 1 ) Nostoc punctiforme PCC 73102 ( NC_010628 . 1 ) Pure genomic DNA was isolated from a single SBW25 colony using a combination of chloroform , CTAB and column ( Qiagen DNeasy Blood & Tissue Kit ) purification techniques . The genomic DNA was sheared to ∼400 bp and 76 bp paired-end were sequenced on two channels of an Illumina GA-II flowcell using standard protocols . Raw data were filtered to generate a set of sequences no less than 36 bp in length . After mapping short reads to the SBW25 genome using the Mosaik software suite ( http://bioinformatics . bc . edu/marthlab/Mosaik ) , reads that could not be mapped were screened for REPIN excisions . The screening was accomplished in two steps: 1 , for each REPIN present in the SBW25 genome 12 bp of the 5′ and 3′ flanking sequences were extracted; 2 , since all reads are shorter than 76 bp , none of the extracted flanking sequences should occur within one read , hence reads containing both 5′ and 3′ REPIN flanking sequences contain an excision . Details of the sequences from which REPINs were excised are given in Figure S6 . In order to identify excisions of short palindromic sequences it was necessary to define a seed sequence . The GI and GII sequences described above do not overlap the palindromic region and hence are not suitable for this purpose ( Table 1 ) . We therefore used an 18-mer containing the palindrome of the GI REP as the seed sequence ( GGGGGCTTGCCCCCTCCC ) . From this seed sequence we generated a set of 18-mers with up to five mismatches . These sequences matched a total of 1376 positions in the SBW25 . This set of 1376 sequences encompassed all three GI , GII and GIII REP sequence groups and their relatives . In addition , to allow for the possibility of inexact excisions of palindromes , we allowed the excision to include three additional base pairs on each side of the seed sequence . Armed with this set of sequences we interrogated the ∼56 million Illumina-generated sequence reads for evidence of excision events .
|
DNA sequences that copy themselves throughout genomes , and make no specific contribution to reproductive success , are by definition “selfish . ” Such DNA is a feature of the genomes of all organisms and evident by virtue of its repetitive nature . In bacteria the predominant repetitive sequences are short ( ∼20 bp ) , extragenic , and palindromic . These so-called REP sequences may occur many hundreds of times per genome , but their origins and means of dissemination have been a longstanding mystery . We show that REPs are components of higher-order replicative entities termed REPINs , which are themselves thought to be derived from REP sequences that flanked an ancestral autonomous selfish element . In this ancestral state the REP sequences were likely to have been critical for the movement of the selfish element , but were devoid of any capacity to replicate independently . REPINs , on the other hand , have evolved to have a life of their own , albeit one that exploits—even enslaves—a genetic element upon which their existence depends . REPINs are the ultimate non-autonomous , super-streamlined , selfish element and are widespread among bacteria .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"genome",
"evolution",
"genome",
"sequencing",
"coevolution",
"genome",
"complexity",
"comparative",
"genomics",
"biology",
"evolutionary",
"genetics",
"genetic",
"drift",
"adaptation",
"natural",
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2011
|
Within-Genome Evolution of REPINs: a New Family of Miniature Mobile DNA in Bacteria
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Myeloid blood cells are largely resistant to infection with human immunodeficiency virus type 1 ( HIV-1 ) . Recently , it was reported that Vpx from HIV-2/SIVsm facilitates infection of these cells by counteracting the host restriction factor SAMHD1 . Here , we independently confirmed that Vpx interacts with SAMHD1 and targets it for ubiquitin-mediated degradation . We found that Vpx-mediated SAMHD1 degradation rendered primary monocytes highly susceptible to HIV-1 infection; Vpx with a T17A mutation , defective for SAMHD1 binding and degradation , did not show this activity . Several single nucleotide polymorphisms in the SAMHD1 gene have been associated with Aicardi-Goutières syndrome ( AGS ) , a very rare and severe autoimmune disease . Primary peripheral blood mononuclear cells ( PBMC ) from AGS patients homozygous for a nonsense mutation in SAMHD1 ( R164X ) lacked endogenous SAMHD1 expression and support HIV-1 replication in the absence of exogenous activation . Our results indicate that within PBMC from AGS patients , CD14+ cells were the subpopulation susceptible to HIV-1 infection , whereas cells from healthy donors did not support infection . The monocytic lineage of the infected SAMHD1 -/- cells , in conjunction with mostly undetectable levels of cytokines , chemokines and type I interferon measured prior to infection , indicate that aberrant cellular activation is not the cause for the observed phenotype . Taken together , we propose that SAMHD1 protects primary CD14+ monocytes from HIV-1 infection confirming SAMHD1 as a potent lentiviral restriction factor .
Cells of the myeloid lineage are more refractory to HIV-1 infection than T-cells [1]–[4] . HIV-2 and SIV from sooty mangabeys ( SIVsm ) but not HIV-1 encode the accessory protein Vpx [5] that provides a replication advantage in human myeloid cells [6] , [7] . Moreover , Vpx deficient HIV-2/SIVsm viruses are attenuated in vivo [8] . The delivery of Vpx in trans through virus-like particles ( VLP ) also enables HIV-1 to infect otherwise resistant primary human cells such as monocytes [3] , [9] , [10] or dendritic cells [6] , [11] . Furthermore , Vpx promotes HIV infection of macrophages and PMA-differentiated THP-1 cells [12] . Vpx is packaged into budding virions via interaction with the p6 domain of Gag [13] and is active during the early steps of infection in the target cell [5] . Lentiviral accessory proteins counteract known restriction factors such as APOBEC3G or tetherin by mediating their ubiquitin/proteasome-dependent degradation [14] , [15] . Similarly , it has been proposed that Vpx allows lentiviral escape by targeting a myeloid cell-specific restriction factor [3] , [16] , [17] for proteasomal degradation [18] . Two recent publications identified Sterile Alpha Motif ( SAM ) Domain and HD domain-containing protein 1 ( SAMHD1 ) as the Vpx-sensitive restriction factor that inhibits HIV-1 infection of macrophages and dendritic cells [19] , [20] . The SAMHD1 gene is mutated in a subset of patients suffering from Aicardi-Goutières syndrome ( AGS ) , an early-onset disease that resembles a congenital viral infection [21] . This syndrome is characterized by familial encephalopathy with predominantly neurologic symptoms [22] and increased production of interferon alpha ( IFNα ) in the brain [23] . Single nucleotide polymorphisms ( SNP ) in RNASEH2 , TREX1 and SAMHD1 genes have been associated with autoimmunity disorders such as AGS and systematic lupus erythematosus [22] . It has been assumed that the absence of the endonuclease RNASEH2 or the exonuclease TREX1 leads to accumulation of endogenous nucleic acids inducing type I IFN-mediated immune response [24] , [25] . In contrast , the role of SAMHD1 in nucleic acid metabolism is not well defined . Moreover , cerebral vasculopathy and strokes accompanied by an altered cytokine secretion pattern have been reported in patients with SNPs in the SAMHD1 gene [26]–[29] . In this report , in addition to confirming independently the findings by Laguette et al . and Hrecka et al . [19] , [20] , we provide further evidence for the role of SAMHD1 as interferon-induced factor restricting HIV-1 replication in monocytes , the progenitors of macrophages and dendritic cells . We demonstrate that SAMHD1 is targeted for ubiquitin-mediated degradation in a Vpx-dependent fashion in primary CD14 positive monocytes . We also found that unstimulated primary peripheral blood mononuclear cells ( PBMC ) from two AGS patients lacking endogenous SAMHD1 can support viral replication whereas cells from healthy donors encoding wild-type ( WT ) SAMHD1 were resistant to HIV-1 infection . Microscopy imaging of infected AGS and healthy donor cells suggest that CD14+ cells of monocytic morphology are the cells targeted by HIV-1 in the absence of SAMHD1 .
To uncover novel Vpx ( VpxSIVsmPBi ) -interaction partners in 293T cells , tandem affinity purification was performed and isolated proteins were identified by mass spectrometry analysis ( Figure 1A and S1 ) . In addition to confirmed Vpx interacting proteins such as VprBP [30] and DDB1 [17] we isolated a 72 kDa protein , which was determined to be SAM domain and HD domain containing protein 1 ( SAMHD1 ) . In order to confirm the protein interaction , endogenous SAMHD1 was co-immunoprecipitated with HA-VpxSIVsmPBi , whereas interaction with an inactive Vpx mutant , T17A ( Figure 1B ) [6] , [12] , was significantly reduced ( Figure 1C ) . The functional relevance of the SAMHD1-Vpx interaction on a single cell level was further determined by confocal fluorescence microscopy . We observed that expression of wild-type ( WT ) Vpx leads to a drastic reduction of endogenous nuclear SAMHD1 levels ( Figure 1D ) . Of note , Vpx T17A displayed a cellular distribution similar to that of its WT counterpart ( both in nuclei and cytoplasm ) , but was unable to deplete SAMHD1 ( Figure 1D ) . Next we probed for the importance of ubiquitin-conjugated protein degradation in the Vpx-mediated reduction of SAMHD1 . We observed that the peptide aldehyde proteasome inhibitor MG132 blocked Vpx-mediated depletion of SAMHD1 in THP-1 cells ( Figure 1E ) . The Vpx mutant T17A failed to induce degradation of SAMHD1 ( Figure 1E ) . Our findings are in agreement with the recent reports of Laguette et al . [20] and Hrecka et al . [19] that identified SAMHD1 as a VpxSIVmac251 and VpxHIV2 interacting protein . Taken together , these results demonstrate that Vpx targets SAMHD1 for ubiquitin-mediated degradation . We next tested the hypothesis that the efficiency of HIV-1 infection in monocytic cells correlates directly with Vpx-mediated degradation of SAMHD1 . We transduced PMA-differentiated THP-1 cells with VLPs carrying WT Vpx , the Vpx T17A mutant or empty VLPs and subsequently infected them with a single-cycle VSV-G pseudotyped HIV-1 luciferase reporter virus ( HIV-1-luc ) . We found that HIV-1 infection was 12 . 6-fold higher in the presence of WT Vpx , compared to mutant Vpx or empty particles ( Figure 2A ) , and this phenotype correlated with the degradation of SAMHD1 in these cells ( Figure 2A , lower panel ) . To test the efficiency of HIV-1 restriction by endogenous SAMHD1 , we infected differentiated THP-1 cells stably expressing shRNA targeting SAMHD1 or a non-targeting control shRNA with HIV-1-luc ( Figure 2B , lower panel ) . Infection with single-round HIV-1-luc was up to 4 . 5-fold higher in SAMHD1 shRNA expressing cells than in control cells ( Figure 2B ) . Next , we assessed whether Vpx-mediated HIV-1 infection also affects SAMHD1 levels in primary monocytes . Therefore , monocytes were infected with a lentiviral HIV vector expressing GFP ( HIV-1-EGFP ) in the presence or absence of Vpx . In line with the experiments in THP-1 cells ( Figure 2A ) , delivery of Vpx relieved restriction of HIV-1-EGFP whereas Vpx T17A did not render these cells susceptible for HIV-1 ( Figure 2C ) . Also in monocytes , the permissiveness to HIV-1 correlated with the Vpx-induced reduction of SAMHD1 in a ubiquitin-dependent pathway ( Figure 2D ) . We conclude that monocytes express SAMHD1 as an interferon-inducible factor ( Figure 2E ) that is degraded upon Vpx-supported HIV-1 infection confirming the results in dendritic cells [20] and macrophages [19] . To determine whether cells with a nonsense mutation in SAMHD1 obtained from AGS patients might be more susceptible to viral infection , we tested HIV-1 infectivity in PBMC from two related AGS patients described previously [28] . The cause of AGS in these patients was assigned to an homozygous mutation in SAMHD1 , which introduces a premature stop codon at position 164 . This results in a truncated protein lacking the HD domain ( Figure 3A ) . The composition of PBMC subpopulations from AGS patients showed no obvious SAMHD1-dependent deviation from PBMC of healthy donors ( Figure 3B ) . PBMC from patients homozygous for SAMHD1 R164X as well as WT SAMHD1 were stimulated with interleukin 2 ( IL-2 ) and PHA followed by subsequent infection with the replication-competent CCR5-tropic HIV-1 SF162 . Interestingly , HIV-1 spread in both healthy and AGS primary cells to a comparable degree ( Figure 3C , left panel ) . Western blot analysis of infected PBMC confirmed the absence of full-length , but also truncated SAMHD1 in AGS patients ( Figure S2 ) , suggesting that the R164X mutation reduces protein stability or induces nonsense-mediated decay of the transcript . To exclude the impact of mitogen-stimulated T-lymphocytes on HIV-1 replication that might conceal the restrictive role of SAMHD1 , we repeated this experiment in the absence of IL-2/PHA stimulation . In non-stimulated cells , HIV-1 spread far more rapidly in SAMHD1 R164X PBMC than in PBMC from healthy individuals ( Figure 3C , right panel ) . These findings suggest that , in the absence of exogenous stimulation , SAMHD1 deficiency renders a subpopulation of cells within PBMC susceptible to HIV-1 replication . However , upon mitogenic T-cell stimulation , the absence of SAMHD1 has no further advantage for HIV-1 replication likely because the bulk of the viral replication occurs in activated T-lymphocytes masking the putative replication in less abundant cell populations . To confirm the SAMHD1-dependent effect of HIV-1 replication in non-stimulated PBMC , we infected AGS and healthy donor PBMC with R7/3-YU2-EGFP , a CCR5-tropic HIV virus that encodes GFP in place of Nef [31] , [32] . However , due to the limited availability of clinical specimen from AGS patients , we could perform these experiments only with PBMC from one of the two AGS patients ( Donor 2 ) . Despite low viral input ( MOI: 0 . 01 ) we observed also in this experimental setup , a sustained replication in non-stimulated AGS PBMC starting as early as day 3 after infection ( Figure 3D ) . No p24 production was observed in PBMC from the healthy Donor 4 within seven days of infection ( Figure 3D ) . These results indicate that the absence of SAMHD1 due to the R164X mutation supports a spreading replication of HIV-1 in non-stimulated primary cells normally refractory to HIV-1 . Next , we sought to further define the primary cell population infected with R7/3-YU2-EGFP . The infections of PBMC from Donor 2 ( SAMHD1 -/- ) and healthy Donor 4 ( SAMHD1 +/+ ) were inspected by live cell fluorescence microscopy at day 7 . In agreement with the replication data ( Figure 3D ) , 10% of SAMHD1 -/- cells ( Donor 2 ) were GFP/HIV-1 positive at day 7 post infection whereas PBMC from Donor 4 did not yield green fluorescent cells at any time point ( Figure 4A ) . Because most of the HIV-1 positive cells were much larger than T-lymphocytes and exhibited a morphology similar to myeloid cells , we stained the cells for the myeloid cell marker CD14 at day 7 post infection in order to determine the susceptibility of this lineage to HIV-1 . Counting the cells represented in independent microscopic images ( Donor 2: 16 images and Donor 4: 12 images ) revealed that within the SAMHD1-deficient specimen 80% of GFP/HIV-1+ cells were positive for CD14 ( see Figure 4B and 4C for examples and Figure 4D for quantification ) . Interestingly , at day 7 of the experiment , the overall percentage of CD14+ cells was higher in the AGS sample ( Donor 2: 26% HIV-1 infected , 34% mock infected versus Donor 4: 7% and 8% respectively; 12 independent images; Figure S3 ) , although the frequency of CD14+ cells post isolation were comparable between Donor 2 and Donor 4 ( Figure 3B ) . In summary , these live cell microscopy experiments support the notion that within non-stimulated PBMC lacking functional SAMHD1 , CD14+ monocytic cells are the subpopulation that are highly susceptible to HIV-1 infection . To determine the interferon and cytokine/chemokine responses during HIV-1 replication , we analyzed the culture supernatants of R7/3-YU2-EGFP or non-infected cells from Donor 2 ( SAMHD1 -/- ) and Donor 4 ( SAMHD1 +/+ ) using multiplex-ELISA . Prior to infection , cytokine and chemokine levels were low or undetectable in Donor 2 , suggesting that the cells were not activated due to the absence of SAMHD1 ( Figure 5 , purple line ) . Only in AGS PBMC , early pro-inflammatory cytokines such as IL-6 , IP-10 , TNFα and MIP-1β were induced during the seven day course of HIV-1 replication ( Figure 5 , green and orange lines ) . IL-6 and IP-10 were stimulated more than 20-fold at day 3 and more than 15-fold at day 4 , respectively , compared to the low level induction in healthy donor 4 , suggesting an early inflammatory reaction upon HIV-1 in SAMHD1-deficient PBMC ( Figure 5 , orange and blue lines ) . These cytokines are also indicative of a cytokine response primarily produced by cells of monocytic origin [33] , [34] . Notably , IFN-α , IFN-γ , the CCR5-ligand RANTES and the cytokine IL-1β were neither induced upon HIV-1 replication in SAMHD1-deficient cells nor upon HIV-1 incubation with healthy donor PBMC ( Figure 5 ) . We also could not detect evidence for secretion of bioactive type I interferon using a sensitive interferon bioassay ( Figure S4 ) .
In this study , we determine the role of SAMHD1 as a HIV-1 restriction factor in human monocytes confirming and extending the findings observed in other myeloid cells [19] , [20] . Previous reports have determined that residue 17 in Vpx is crucial for the infection of macrophages and dendritic cells [6] , [12] . Our results , using a Vpx T17A mutant , explain this observation by revealing that the Vpx-SAMHD1 interaction most probably occurs via the region encompassing Vpx residue 17 . Moreover , we confirm the effect of the proteasome inhibitor MG132 on the reversibility of Vpx-mediated degradation of SAMHD1 [19] , [20] . MG132 inhibition of the proteasome can also have the effect of depleting cellular ubiquitin levels and , thus , block any ubiquitin-dependent processes [35] . Vpx-mediated SAMHD1 depletion may , therefore , be due to proteasomal degradation or other ubiquitin-dependent mechanisms ( e . g . , ubiquitin dependent recruitment to the lysosome ) . SAMHD1 consists of a sterile alpha motif ( SAM ) , that can serve as a protein-binding [36] or RNA-binding domain [37] and a HD domain characterized by a doublet of histidine/aspartic acid residues . The latter is presumed to bind nucleic acids [38] and to serve as a phosphohydrolase/nuclease domain [39] , [40] . As with other HIV-1 restriction factors such as Tetherin , TRIM5α and APOBEC3G that are up-regulated by interferon [41] , [42] , we find that SAMHD1 is regulated by type I IFN . This is consistent with earlier reports suggesting that the host molecule targeted by Vpx is inducible by type I interferon , which was reported to magnify the Vpx phenotype on HIV-1 infection in macrophages [12] . Besides SAMHD1 , the myeloid-specific protein APOBEC3A was reported to be counteracted by Vpx [9] , [43] , suggesting that either protein might act as co-factor for antiviral activity . Expression of Vpx or silencing of SAMHD1 was reported to induce viral DNA accumulation [3] , [20] , suggesting that the restriction takes effect at or before reverse transcription [44] . Since SAMHD1 is located in the nucleus ( see Figure 1D and [20] , [25] ) , it either might act on components of the pre-integration complex after nuclear entry or it is exported to the cytoplasm during the early phases of infection . Most interestingly , we observe a spreading replication of HIV-1 in non-stimulated PBMC from AGS patients homozygous for SAMHD1 R164X . Although one should take into account that cells of only one AGS patient were analyzed , our data suggest that predominantly cells of the CD14 positive monocytic lineage became highly susceptible targets for HIV-1 compared to HIV-1 resistant cells of healthy donors . The infected patient cells displayed an early inflammatory cytokine secretion profile that might be interpreted as a monocytic cell specific response to HIV-1 infection . We conclude therefore that SAMHD1 protects monocytic cells from HIV-1 infection . Upon T-cell stimulation in PBMC , the enabled HIV-1 replication did not additionally benefit from SAMHD1 deficiency , allowing the speculation that SAMHD1 might not contribute to HIV-1 restriction in T-cells . However , in this context other restriction-associated cellular determinants and cell type-specific SAMHD1 expression level have to be considered in future studies . In conclusion , our study sheds light on how HIV-1 and the host's antiviral innate immune responses intersect . Understanding cell-type specific barriers to HIV-1 infection such as mediated by SAMHD1 will be important to develop innovative therapies and vaccines .
Buffy-coats obtained from anonymous blood donors were purchased from the German blood donation center . Whole blood was obtained from AGS patients that signed an informed consent . The research has been approved by the Ethics Committee of the Chamber of Physicians Westfalen-Lippe and the Medical Faculty of the Westfalian Wilhelms University Münster ( Reference No 2006-556-f-S ) and performed according to the principles expressed in the Declaration of Helsinki . Codon-optimized SIV Vpx from SIVsm PBj1 . 9 was cloned into pNTAP of the Interplay Mammalian TAP System ( Stratagene ) . 293T cells were transfected and cultivated for 48 hours . One hour before lysis , cells were incubated with 100 ng/ml PMA . Purification was performed as described in the manufacturer's instructions . Proteins associated with the Calmodulin-binding beads were subjected to SDS-PAGE , stained with Coomassie brilliant blue , digested with trypsin and analyzed by tandem mass spectrometry ( MS/MS ) at the Paul-Ehrlich-Institute . Codon-optimized N-terminal HA-tagged SIV Vpx derived from SIVsm PBj1 . 9 [9] and N-terminal FLAG-tagged SAMHD1 were cloned into pcDNA3 . 1 . The Vpx T17A mutant was generated using the Site-Directed Mutagenesis Kit ( Stratagene ) . Codon-optimized SIV Vpx from SIVsm PBj1 . 9 was cloned into pNTAP of the Interplay Mammalian TAP System ( Stratagene ) . HEK 293T and HeLa cells were grown in Dulbecco's modified Eagle's medium , THP-1 cells were grown in RPMI medium , both containing 1 mM L-glutamine and 10% fetal calf serum ( FCS ) . Anonymized buffy coats were purchased from the German blood donation center for isolation of primary human monocytes with the Monocyte Isolation Kit II ( Miltenyi ) and the isolated cells were cultured as described previously [9] . For stimulation , monocytes were incubated with interferon α ( Sigma # I4784 & ProSpec # Cyt204B ) . PBMC were isolated using a Ficoll gradient from whole blood obtained from healthy donors and AGS patients that signed an informed consent . Of note , AGS patient Donor 1 , but not Donor 2 was treated with immunosuppressive medication at time of blood collection . PBMC were cultivated in RPMI , Pen/Strep , and 20% FCS . HEK 293T cells were co-transfected with the SIV PBj1 . 9-derived packaging construct PBj-psi10 [10] , pMD . G coding for VSV-G and the appropriate pcDNA3 . 1 expression plasmid encoding WT Vpx or Vpx T17A for generation of Vpx-containing VLPs . For generation of empty VLPs , pcDNA3 . 1 was used instead of a Vpx-expressing plasmid as described earlier [9] . For generation of HIV-1 EGFP , the plasmid pHR-CMV-EGFP , the HIV-1 packaging construct pCMVΔR8 . 9 and pMD . G for generation of HIV-1 particles were used as described before [10] . Production of HIV-1-luc single-cycle reporter particles was performed by transfection of HEK 293T cells with pNL4 . 3R+E- luc3 [45] and pCMV-VSV-G using Lipofectamine 2000 ( Invitrogen ) according to the manufacturer's instructions . Purification of particles and titration of HIV-1 EGFP was described earlier [10] . The amount of VLPs and HIV-1-luc was determined with the Lenti RT Activity Kit ( Cavidi ) . The VLPs were normalized in comparison to PBj-derived vectors of known infectivity . The amount of VLPs per cells was given as MOI-equivalents ( MOIeq ) . Transduction of THP-1 cells with VLPs was performed with a MOI of 2 . Infection of the cells was accomplished with 2 . 5 ng RT HIV-1-luc two hours after VLP transduction . For single-round infection , monocytes were exposed to HIV-1-EGFP for 4 hours and subjected to flow-cytometry analysis five days post-transduction . For MG132 treatment , the cells were cultured with 50 µM MG132 ( Calbiochem ) for 30 minutes before transduction . Infections were done with two different CCR5 using HIV-1 viral stocks ( SF162 , R7/3 EGFP ) . For analysis of HIV-1 SF162 virus replication , PBMC were infected in triplicate with 0 . 05 MOI of R5-tropic HIV-1 SF162 and cultured up to day 14 . Virus in the supernatant was quantified with the Lenti RT Activity Kit ( Cavidi ) . For FACS analysis of PBMC , the cells were fixed and stained with PE-labelled anti-CD14 , FITC-labelled anti-CD3 , PE-labelled anti-CCR5 ( all BD ) and PE-labelled anti-CD4 ( DAKO ) according to the manufactureŕs instructions . For the infections performed with virus stock HIV-1 R7/3 envYU2-EGFP [31] , [32] , 2×105 PBMC were infected in triplicate with 0 . 75 ng or 3 . 75 ng p24 equivalent for 5 hours . Cells were washed after infection and cultured for 7 days in a 96 well plate . Culture supernatants were collected every day and stored at −80°C . Viral spread was monitored by measuring p24 concentrations in the culture supernatants using a p24 ELISA assay ( XpressBio ) and by monitoring GFP expression by fluorescent microscopy . 293T cells were transiently transfected with the respective plasmids using Lipofectamine 2000 ( Invitrogen ) according to the manufactureŕs instructions . For transfection of HeLa cells , Fugene 6 ( Roche ) was used in accordance with the manufacturer's instructions . For CoIP transfected cells were lysed , sonicated and incubated with anti-HA beads ( Roche ) . After 1h incubation at 4 C , the beads were washed with lysis buffer and associated proteins were subjected to SDS-PAGE . Cells were lysed in RIPA buffer and sonicated . When using interferon , monocytes were incubated with IFN-α ( ProSpec , cat# Cyt204B or Sigma cat#I4784 ) 48 hours before lysis . Protein extracts were separated via SDS-PAGE and transferred to a nitrocellulose membrane ( GE Healthcare ) . For detection , anti-HA ( Roche ) , anti-SAMHD1 ( abcam ) , anti-tubulin and anti-GAPDH ( all Cell Signaling Technology ) were used as primary antibodies . Secondary HRP-conjugated anti-mouse and anti-rabbit antibodies were obtained from GE Healthcare . HeLa cells were seeded on a LabTek chambered coverglass ( Nunc ) and transfected with expression plasmids for Vpx using Fugene 6 ( Roche ) . After 24 hours , cells were fixed , permeabilized and blocked as described previously [9] . Cells were incubated with anti-HA ( Roche ) and anti-SAMHD1 ( abcam ) primary antibodies and stained with secondary Alexa-Fluor 594 anti-rabbit , Alexa-Fluor 488 anti-mouse antibodies ( both Invitrogen ) and DAPI ( Chemicon ) . Images were acquired with a ZEISS LSM Meta confocal microscope . Live cell imaging of infected and non-infected PBMC from Donor 2 ( SAMHD1 -/- ) and Donor 4 ( SAMHD1 +/+ ) was performed at the Microscopy Core Facility at MSSM , NY . At day 7 of infection , cells were washed once carefully with warm PBS/1% FBS and stained with anti-human CD14-PE ( Clone MEM-15 , Abcam , USA ) and mouse IgG1-PE ( Clone X40 , BD Biosciences , USA ) for 30 minutes in the 96 well-plate in which the infections were performed . After three washes Hoechst 33342 ( 10 µM final concentration ) stain was added for 30 minutes . Imaging was performed on Olympus IX70 microscope with a live cell imaging system ( 37°C , 5% CO2 ) . Images were acquired with 20x and 40x lenses . THP-1 stable cell lines were generated by transduction with lentiviral vectors encoding unspecific shRNA ( pLKO-nontarget ) or shRNA specific to SAMHD1 ( shSAMHD1 #1 TRCN0000343807: sequence: CCGGCCCTGAAGAAGATATTTGCTTCTCGAGAAGCAAATATCTTCTTCAGGGTTTTTG ) ; shSAMHD1 #2 TRCN0000343808: sequence CCGGGCCATCATCTTGGAATCCAAACTCGAGTTTGGATTCCAAGATGATGGCTTTTTG ) ( all Sigma ) and selected with puromycin . For HIV-1 luciferase reporter assays , 2 . 5×104 THP-1 cells were stimulated with 5 ng/ml PMA ( Calbiochem ) overnight and infected by spin-occulation with HIV-1-luc . Luciferase activity was detected using BriteLite reagent ( PerkinElmer ) according to the manufacturer's instructions 24 hours post infection . Quantification of IL-6 , IP-10 , TNF-α , MIP-1β , IFN-α , IFN-γ , RANTES and IL-1β release in supernatants of infected and non-infected PBMC from Donor 2 ( SAMHD1 -/- ) and Donor 4 ( SAMHD1 +/+ ) was performed using the MILLIPLEX Multi-Analyte Profiling Human Cytokine/Chemokine Kit ( Millipore , MA , USA ) according to the manufacturer's instructions . Data were analyzed using the Milliplex Analyst software . Functional type I interferon was detected using a bioassay previously described [46] . Vero cells were incubated with serial dilutions of culture supernatant of uninfected or HIV-1 infected PBMC for 24 hours and then infected with GFP-encoding Newcastle disease virus ( NDV-GFP ) ( MOI of 1 ) . GFP was measured 18 hours post-infection . A serial dilution of recombinant IFN-β served as positive control and standard .
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Lentiviral accessory proteins play important roles in antagonizing host proteins aimed at suppressing HIV-1 replication at a cellular level . The SIV/HIV-2 protein Vpx counteracts SAMHD1 , a previously unknown antiviral factor within myeloid blood cells , rendering these cells permissive to primate immunodeficiency viruses . We confirm in this study that Vpx interacts with SAMHD1 leading to ubiquitin-mediated degradation of SAMHD1 , and renders CD14 positive monocytes susceptible to HIV-1 infection . We provide new insights into the ability of SAMHD1 to protect monocytic cells from HIV-1 infection by using primary cells from patients with Aicardi-Goutières syndrome ( AGS ) lacking endogenous SAMHD1 expression . We show that peripheral monocytic cells of AGS patients are highly permissive to HIV-1 . Thus , our study demonstrates that SAMHD1 is critical for restriction of HIV-1 infection in monocytes adding SAMHD1 as a novel innate defense factor .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"immunodeficiency",
"viruses",
"host",
"cells",
"immunity",
"virology",
"innate",
"immunity",
"viral",
"transmission",
"and",
"infection",
"biology",
"microbiology",
"host-pathogen",
"interaction"
] |
2011
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SAMHD1-Deficient CD14+ Cells from Individuals with Aicardi-Goutières Syndrome Are Highly Susceptible to HIV-1 Infection
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Infection of mammalian cells with vesicular stomatitis virus ( VSV ) results in the inhibition of cellular translation while viral translation proceeds efficiently . VSV RNA synthesis occurs entirely within the cytoplasm , where during transcription the viral polymerase produces 5 mRNAs that are structurally indistinct to cellular mRNAs with respect to their 5′ cap-structure and 3′-polyadenylate tail . Using the global approach of massively parallel sequencing of total cytoplasmic , monosome- and polysome-associated mRNA , we interrogate the impact of VSV infection of HeLa cells on translation . Analysis of sequence reads in the different fractions shows >60% of total cytoplasmic and polysome-associated reads map to the 5 viral genes by 6 hours post-infection , a time point at which robust host cell translational shut-off is observed . Consistent with an overwhelming abundance of viral mRNA in the polysome fraction , the reads mapping to cellular genes were reduced . The cellular mRNAs that remain most polysome-associated following infection had longer half-lives , were typically larger , and were more AU rich , features that are shared with the viral mRNAs . Several of those mRNAs encode proteins known to positively affect viral replication , and using chemical inhibition and siRNA depletion we confirm that the host chaperone heat shock protein 90 ( hsp90 ) and eukaryotic translation initiation factor 3A ( eIF3A ) —encoded by 2 such mRNAs—support viral replication . Correspondingly , regulated in development and DNA damage 1 ( Redd1 ) encoded by a host mRNA with reduced polysome association inhibits viral infection . These data underscore the importance of viral mRNA abundance in the shut-off of host translation in VSV infected cells and link the differential translatability of some cellular mRNAs with pro- or antiviral function .
Infection of mammalian cells by vesicular stomatitis virus ( VSV ) results in a profound shut-off of host cell gene expression . This host cell shut-off occurs at the level of mRNA transcription through inhibition of RNA polymerase II by the viral-encoded matrix protein ( M ) [1–3] . The M protein also forms a complex with ribonucleic acid export 1 ( Rae1 ) and nucleoporin 98 ( Nup98 ) [4] thus suppressing host cell mRNP export from the nucleus , including that of mature cellular mRNAs [5–8] . VSV infection also inhibits protein synthesis by manipulation of the host-cell translation machinery , particularly at the level of translation initiation [9 , 10] . Eukaryotic initiation factor 4E ( eIF4E ) —the rate limiting factor for translation initiation—recognizes the 7mGpppN mRNA cap structure as part of the eIF4F complex , and in concert with other translation initiation factors facilitates the recruitment of the small 40S ribosomal subunit to the mRNA prior to scanning to the initiating methionine where the 60S subunit joins [11 , 12] . VSV infection results in the rapid dephosphorylation of eIF4E itself , for which the functional consequences are unclear , and of its binding protein ( eIF4E-BP1 ) leading to eIF4E sequestration and the suppression of translation initiation [9 , 10] . Viral gene expression evades the shut-off mechanisms employed to suppress host gene expression . As VSV RNA synthesis occurs entirely within the cytoplasm , viral RNA synthesis is not subject to the inhibitory effects of M on RNA polymerase II and mRNA export from the nucleus . The VSV RNA synthesis machinery comprises a ribonucleoprotein complex of the negative-sense genomic RNA completely encased by a nucleocapsid protein ( N ) sheath and associated with the viral polymerase complex [13] . The viral transcriptase copies the N-RNA template into 5 monocistronic mRNAs that are structurally indistinct to those of the host-cell with respect to their 5′ cap and 3′ polyadenylate tail [14–20] . The enzymes necessary for mRNA synthesis , namely an RNA dependent RNA polymerase ( RdRp ) and a set of capping enzymes , reside within the viral large protein ( L ) [17 , 19 , 21–27] . VSV L protein cannot engage the N-RNA template directly , but instead depends on the viral phoshoprotein ( P ) to facilitate the interaction [28–33] . Messenger RNA polyadenylation is also catalyzed by L through reiterative transcription by the RdRp of a U7 tract that resides at the end of each gene [34–38] . This program of viral transcription results in the cytoplasmic synthesis of 5 mRNAs that depend upon the host machinery for their translation , and must therefore avoid the shut-down mechanisms that effectively suppress host mRNA translation . Metabolic labeling studies demonstrate that 4 hours post VSV infection of baby hamster kidney cells in culture , total translation is suppressed to about 65% the level of uninfected controls [39] . Extraction of mRNA from infected cells coupled with its in vitro translation confirmed that the cellular mRNAs remain intact and are competent for translation [39] . The VSV mRNAs are present in an approximately 2–3 fold excess of the total cellular mRNA , leading to the model that competition between viral and cellular mRNAs for ribosomes results in the dominance of viral translation [39 , 40] . Polysome analysis also demonstrates that the cellular mRNAs are associated with significantly fewer ribosomes in infected cells [39] . For example , infection results in the movement of actin mRNA from polysomes containing 12 or more ribosomes to those containing 5 [39] . This movement reflects the competition between viral and cellular mRNA for ribosomes and the limited pool of eIF4E . The competition model predicts that the kinetics of viral mRNA synthesis and the levels of viral mRNA should correlate closely with host shut-off . Tests of this prediction yielded conflicting results . The kinetics of host shut-off and viral mRNA accumulation correlate well for many strains of VSV , consistent with the competition model [39 , 40] . Inhibition of host protein synthesis is , however , largely unaffected following coinfection of cells with increasing quantities of defective interfering ( DI ) particles that suppress viral mRNA levels up to 14-fold [41] . A similar result was obtained for a VSV mutant that is restricted for genome replication at 39°C , and yields only 30% of the wild type levels of viral mRNA [41] . Collectively , these studies suggest additional mechanisms may contribute to the shut-off of host cell protein synthesis . Specific features of the viral mRNAs that contribute to their efficient translation have not been defined . The 5′ untranslated regions of VSV mRNAs are short , being 10–15 nucleotides for the viral N , P and L mRNAs that encode the proteins required for RNA replication [42 , 43] . How such short 5′ UTRs serve as effective initiators of translation is unclear . Evidence for differential translation of viral mRNA comes from small interfering RNA suppression of eIF4E , which inhibits host gene expression but has no impact on viral gene expression [44] . Viral translation is also hypersensitive to the loss of ribosomal protein L40 , suggesting different mRNA features facilitate translation of viral versus host mRNA [45] . Flanking cellular or reporter genes by the conserved viral 10-nt gene-start and 13-nt gene-end sequences , and inserting them into the viral genome is sufficient to mediate their efficient translation [46] . By contrast , expression of the same genes following transfection of plasmid DNA into cells and subsequent VSV infection does not offer this translational advantage [46] . Thus , transcription of the mRNAs from the viral genome appears to contribute to their efficient translation . In the present study , we interrogate global mRNA translation in VSV infected cells using RNAseq analysis of the cytoplasmic mRNA transcriptome , and parallel sequencing of polysome-associated mRNAs . We obtain support for the model that an overabundance of viral mRNA contributes to host shut-off by leading to a re-distribution of cellular ribosomes onto viral mRNA . By combining this RNAseq analysis with examining the distribution of specific viral and cellular mRNAs within polysomes , we also demonstrate that mRNAs shift to smaller polysomes . Analysis of cellular mRNAs less-sensitive to this global shut-down of translation identifies several host proteins that promote viral replication . Similar analyses revealed the abundance of viral mRNA contributes to the host-cell shut-off for other viruses including coronaviruses , influenza and vaccinia [47–49] .
To interrogate the impact of VSV infection on global translation we isolated total cytoplasmic , monosome- and polysome-associated mRNA from HeLa cells at 2 and 6 hpi and compared the relative sequence reads obtained by deep-sequencing ( Fig 1A ) . Statistical analysis of sequencing reads between biological replicates from each fraction yields a Pearson correlation of >0 . 97 for cytoplasmic , monosome- and polysome-associated mRNA pools validating reproducibility between the replicates . As visible in the polysome profiles ( Fig 1B ) , VSV infection results in a small but reproducible increase in the pool of monosomes and large polysomes at 2 hpi , and a collapse of large polysomes and an increase in monosomes by 6 hpi . Mapping of the sequence reads to the viral and host genome highlights that by 6 hpi >60% of the total reads in the cytoplasmic and polysome fractions are viral ( Fig 1C ) . This increase from the <1% observed at 2 hpi ( Fig 1C ) emphasizes the impact of the exponential phase of viral RNA replication and secondary transcription of the viral genome on mRNA production . The viral sequence reads map to all 5 genes , with clear dips in coverage at gene-junctions ( S1 Fig ) . Consistent with the order of transcription of the viral genome and the localized transcriptional attenuation at gene-junctions [50–53] , the relative reads that map to each viral gene generally diminish with distance from the single 3′ promoter ( Fig 1D and S1 Fig ) . Analysis of the sequencing reads that map to cellular genes supports that like the viral mRNAs , the level of reads in the polysome fraction mirrors that in the total cytoplasmic fraction at 2 and 6 hpi ( Fig 1C ) . This result demonstrates that the majority of mRNAs are polysome-associated in proportion to their abundance . The abundance of the 5 viral mRNAs at 6 hpi supports the model that viral mRNAs outcompete cellular mRNAs for ribosomes [39] . We note that viral mRNAs are , however , underrepresented ( 49% ) and cellular mRNAs overrepresented ( 51% ) in the monosome fraction at 6 hpi , compared to their cytoplasmic abundance ( Fig 1C ) . This finding is consistent with a differential effect on viral versus host mRNA translation . To determine how VSV infection affects the distribution of the population of mRNAs between total cytoplasmic , monosome or polysome fractions , we plotted the transcript per million ( TPM ) for each individual mRNA mapped to the human and viral genome in all 3 fractions ( Fig 2 ) . At 2 hpi , reads that map to the viral genes in each fraction are similar in abundance to those reads that map to highly expressed cellular genes ( Fig 2A ) . The reads that map to any given cellular gene alter within a relatively narrow range , with few genes showing a greater than 2-fold change in the relative number of sequence reads ( Fig 2B ) . For the population of mRNAs , the relative reads obtained from the polysome fraction mirrored the relative reads in the total cytoplasmic fraction , consistent with the abundance of an mRNA being a determinant of its translatability . By 6 hpi , reads that map to each of the 5 viral genes—with the exception of L—exceed the reads that map to any individual cellular gene ( Fig 2C , red triangles ) . This is concurrent with a decrease in reads that map to the majority of cellular genes in cytoplasmic , monosome and polysome-associated fractions ( Fig 2C ) . There were , however , some distinctions between the monosome and polysome fractions . For the majority of the population of cellular mRNAs , reads were most reduced in the polysome fraction compared to the total cytoplasmic fraction ( Fig 2D ) . A smaller reduction in reads was observed in the monosome fraction , and some cellular mRNAs even showed an increase in reads compared to the total cytoplasmic fraction ( Fig 2C ) . This may reflect differences in the movement of cellular mRNAs from large polysomes to monosomes or out of the pool of translating ribosomes . We next mined our sequence data for evidence of differential translation of cellular mRNAs following VSV infection . For this analysis we divided the polysome TPM by the total cytoplasmic TPM as an indicator of the efficiency with which any given mRNA is translated . We also performed a similar analysis for the monosome pool . We are cognizant of the fact that such ratios ignore the movement of any given mRNA from larger to smaller polysomes , and will likely represent an underestimate of the extent of any translational regulation . To identify the subset of the population of cellular mRNAs with the highest probability for translational regulation in infected cells , we plotted the fold change in TPM at 2 and 6 hpi ( Fig 3A–3D ) . At 2 hpi the monosome or polysome-associated reads changed within a narrow range for the majority of cellular genes ( Fig 3A ) . The marked shut-off of host protein synthesis observed by metabolic labeling suggests that at 6 hpi the association of cellular mRNA with polyribosomes would alter significantly at the population level . Although we observe a global reduction in polysome-associated reads for the bulk of the population of cellular mRNAs the reduction is less than 2–3 fold . Accompanying this global reduction in polysome-associated reads , we also observe an increase in monosome-associated reads with more than half the mRNAs within the population exhibiting a >2-fold increase ( Fig 3B and 3D ) . From the above ratios we selected the subset of cellular mRNAs that exhibit the largest changes in relative polysome-associated reads at 6 hpi to determine whether those mRNAs shared any common features . For this purpose , we selected those mRNAs that change >2 standard deviations of the mean and thus exceed the 95% confidence interval . This analysis identified 364 cellular mRNAs as candidates for translational upregulation and 138 cellular mRNAs as candidates for translational downregulation following VSV infection ( Fig 3B and 3D ) . Consistent with monosome and polysome-associated reads at 2 hpi changing within a narrow range , only 4 genes with increased and 20 with decreased polysome association , overlap between 2 and 6 hpi ( Fig 3C and 3D ) . Within the monosome fraction 8 genes with increased and 6 with decreased monosome association overlap from 2 to 6 hpi . We next determined whether shared functional or sequence elements are present within the specific subsets of 364 mRNAs with increased polysome association , or the 138 mRNAs with decreased polysome association ( Fig 3B and 3D , blue and green dots ) . For the 364 genes with significantly increased polysome-associated reads , gene ontology analysis identifies functions in RNA binding , helicase and NTPase activities , among others ( Fig 3E and S3 Dataset ) . The 138 genes with decreased polysome-associated reads are associated with cellular responses to stimuli and signaling activities ( Fig 3F and S3 Dataset ) . This gene ontology analysis reveals that the up and down regulated transcripts comprise distinct functional groups . At 6 hpi the cytoplasmic abundance of cellular mRNAs correlates with their polysome association at 6 hpi ( Fig 4A and 4B ) , consistent with mRNA abundance being a determinant of translatability . As described above , we use as an indicator of translation efficiency ( TE ) of an mRNA the ratio of polysome to total cytoplasmic associated reads . To determine whether there are shared features between the 364 mRNAs with evidence of enhanced polysome association or the 138 with reduced polysome association , we extracted mRNA sequences and annotations from the UCSC Genome Browser . Assisted by published datasets we examined whether the half-life , size , GC content or poly ( A ) tail length correlate with increased or decreased polysome association ( Fig 4C–4F and S2 Fig ) [54 , 55] . Cellular mRNAs with increased polysome-associated reads tended to have a longer half-life , were typically larger , and were more AU-rich ( Fig 4C–4E and S2 Fig ) . Correspondingly , those with decreased polysome-associated reads tended to have shorter half-lives , higher GC content , and were typically smaller . The correlation between higher AU content and increased polysome-associated reads was most evident for the coding region and 3′ UTR ( S2 Fig ) . The effect of length was predominantly a determinant of the ORF and not the 5′ or 3′ UTR ( S2 Fig ) . There was no correlation between poly ( A ) tail length and polysome-associated reads at 6 hpi ( Fig 4F ) . This analysis highlights that the cellular mRNAs that exceed the 95% confidence interval for increased polysome-associated reads in response to VSV infection are most similar to the viral mRNAs in that they are typically longer and more AU rich . We next examined whether cellular mRNAs that exhibit increased polysome association encode proteins that are pro- or antiviral . Among the 364 cellular mRNAs with increased polysome association several encode known proviral factors including the heat shock proteins ( HSP ) 90 , 70 , and 60 . Previous work demonstrated that inhibition of HSP90 inhibits viral replication , and linked inhibition of those chaperones to defects in L protein folding [56–58] . We independently verified the proviral function of HSP90 using the inhibitor 17-[2- ( Dimethylamino ) ethyl]amino-17-desmethoxygeldanamycin ( 17-DMAG ) [59 , 60] . Infection of HeLa cells with VSV that expresses eGFP as a marker of infection demonstrates that 17-DMAG has no effect on the fraction of cells infected , but slows the rate of eGFP expression ( Fig 5A and S3 Fig ) . This was not simply due to defects in eGFP folding , as metabolic labeling of viral RNA substantiates the defect in gene expression ( S3 Fig ) . We also found that polysome association of the mRNA encoding eukaryotic initiation factor 3 subunit A ( eIF3a ) , increases after infection . To test whether this reflects a specific proviral function of eIF3a , we used siRNA depletion to reduce eIF3a and measured viral gene expression using reporter viruses expressing eGFP or luciferase . Both reporter viruses displayed a sensitivity to the loss of eIF3a ( Figs 5B and S3 ) . As expected , depletion of eIF3a also reduced cellular translation in uninfected cells , but that reduction was modest as evidenced by expression of a CMV promoter driven renilla luciferase reporter ( Fig 5B ) . Translation of the CMV driven reporter , however , reflects the accumulated steady-state levels of luciferase mRNA . We therefore measured the effect of eIF3a depletion on viral vs host translation by metabolic incorporation of [35S]-methionine in infected and uninfected cells ( Fig 5B ) . Following eIF3a depletion we observed a 55% reduction in viral M protein synthesis over a 30 minute time period , which is similar to the 56% reduction in host protein synthesis measured in mock infected cells . This analysis supports a proviral role for 2 cellular mRNAs that encode proteins with important house-keeping functions that remain polysome-associated following VSV infection . Among the 138 cellular mRNAs that exhibit reduced polysome association following infection was DNA-damage inducible transcript 4 ( DDIT4 ) which encodes regulated in development and DNA-damage response 1 ( Redd1 ) [61–63] . Existing studies demonstrate that DDIT4/Redd1 restricts the replication of negative-strand RNA viruses , including VSV . Depletion of DDIT4/Redd1 by siRNA increased viral gene expression as evidenced from infection of cells with VSV-eGFP , and by metabolic labeling of viral protein synthesis ( Fig 5C , S3 Fig ) . Consistent with the enhancement of viral gene expression following DDIT4 depletion , we obtained an approximately 10-fold increase in viral titers ( Fig 5C ) . Depletion of DDIT4/Redd1 also increases cellular protein synthesis likely reflecting its role as a negative regulator of mTOR ( Fig 5C and S3 Fig ) . The above analysis supports that the polysome association of some host mRNAs following VSV infection correlates with their pro- or antiviral functions , but does not directly demonstrate that the level of polysome association is associated with a change in synthesis of the corresponding protein . To independently examine whether changes in polysome association of host mRNAs affect synthesis of the corresponding protein we selected the heat shock protein ( HSP70 ) and Y-box binding protein 1 ( YBX1 ) as representative mRNAs with increased and decreased polysome association , respectively . We selected those mRNAs based on their high-levels of expression , stability , and availability of antibodies suitable for the selective immunoprecipitation of the corresponding protein . We compared the effect of VSV infection on protein synthesis by selective immunoprecipitation of proteins following metabolic incorporation of [35S]-methionine from 3–6 hours post infection ( Fig 5D ) . Synthesis of HSP70 3–6 hpi is indistinguishable to that synthesized during a 3h period from mock infected cells ( Fig 5D ) . By contrast , YBX1 synthesis decreases more than two-fold ( Fig 5D ) . This result confirms for 2 cellular mRNAs that the extent of polysome association observed by our RNAseq analysis is reflected in synthesis of the corresponding host proteins . For our experiments we pooled fractions that contained 3 or more ribosomes prior to sequencing of the polysome-associated mRNA . As a result , we do not assess the impact of the redistribution of mRNAs toward smaller polysomes . We therefore selected a subset of cellular mRNAs ( Fig 6A ) , and interrogated their distributions across polysomes using reverse transcription and quantitative PCR . As controls , we analyzed the distribution of N and G mRNAs as representative viral transcripts translated by soluble and endoplasmic reticulum-associated ribosomes , respectively [64] . Consistent with the robust production of viral proteins at 6 hpi , the VSV N and G mRNAs were localized in fractions corresponding to 3 or more ribosomes ( Fig 6B ) . For two cellular mRNAs with increased polysome TPM—collagen type IV alpha 2 ( COL4A2 ) and alpha-actinin-4 mRNA ( ACTN4 ) –the mRNAs remained associated with larger polysomes in infected cells ( Fig 6C ) . Two cellular transcripts that were largely unaltered in their polysome associated TPM–β-actin ( ACTB ) and glyceraldehyde 3-phosphate dehydrogenase ( GAPDH ) –remained polysome-associated , although there was a shift toward smaller polysomes and some GAPDH transcripts exited polysomes ( Fig 6D ) . For two representative cellular mRNAs with decreased polysome TPM—transforming growth factor B induced factors ( TGIF1 ) and ubiquitin conjugating enzyme E2 B ( UBE2B ) –the mRNAs largely exited the polysome fractions , and those that remained were predominantly present on smaller polysomes ( Fig 6E ) . In all cases examined , dissociation of polysomes with EDTA shifted the mRNA distribution toward the fractions corresponding to free ribosomal subunits ( S4 Fig ) . These qPCR data highlight the shift towards smaller polysome fractions for some cellular mRNAs , which also likely contributes to suppression of host protein synthesis . This shift might also explain our finding that HSP70 protein synthesis is relatively unaffected by viral infection ( Fig 5D ) , although the mRNA exhibits increased polysome association . The abundance of viral mRNA and the suppression of translation initiation through reducing the pool of eIF4E will both contribute to the movement of mRNAs toward smaller polysomes . Recognition of the mRNA cap-structure by eIF4E requires that the guanine-N-7 position of the 7mGpppNmN cap is methylated [65] . We previously reported a panel of recombinant VSVs containing amino acid substitutions within the L-encoded mRNA cap methylase domain that are defective in viral mRNA cap methylation [25] . Mutants VSV-LG4A and VSV-LG1670A contain substitutions in the binding site for the methyl donor s-adenosyl methionine ( SAM ) and ablate all viral mRNA cap methylation ( VSV-LG4A ) or guanine-N7 but not ribose-2′-O methylation ( VSV-LG1670A ) [25] . As VSV mRNA is relatively insensitive to the loss of eIF4E [44] , we would anticipate that the methylation status of the mRNA cap-structure would have little impact on polysome association . Analysis of the distribution of VSV N and G mRNA within polysomes at 6 hpi revealed a similar distribution in cells infected with wild-type virus as well as those infected with VSV-LG1670A and VSV-LG4A ( Fig 7A–7C ) . Correspondingly , the rate of viral protein synthesis in cells infected with VSV-LWT and VSV-LG1607A measured by a 10-minute pulse of [35S]-methionine is similar ( S5 Fig ) . These results demonstrate that defects in viral mRNA cap methylation do not significantly alter the rate of viral protein synthesis , consistent with a reduced dependence on eIF4E [25] . To directly test whether manipulating eIF4E levels affects viral translation we depleted eIF4E levels approximately 10-fold using a peptide-conjugated morpholino ( PPMO ) and measured the rates of VSV-LWT and VSV-LG1607A viral protein synthesis by a 10-minute pulse of [35S]-methionine at various times post-infection ( Fig 7D–7F ) . Depletion of eIF4E decreased the rate of viral protein synthesis in VSV-L1670A infected cells , but not LWT infected cells ( Fig 7E and 7F ) . This was not due to sequestration of eIF4E by differential activation of eIF4E-BP1 between VSV-LWT and VSV-LG1607A infected cells , as the kinetics of eIF4E-BP1 dephosphorylation are the same during both infections ( S6 Fig ) . We previously reported that although VSV-L1670A is defective in mRNA cap methylation , up to 20% of the mRNA cap-structures are guanine-N7 methylated . We interpret this finding as indicative of an eIF4E dependent mechanism of translation early in infection .
The sequence data reported here provides some support for the model that the VSV mRNAs overwhelm the pool of cellular mRNA leading to a redistribution of ribosomes onto viral messages [39] . Evidence in support of this model is based on massively parallel sequencing of mRNAs associated with polysomes , compared with those present in the cytoplasm . As a fraction of the total cytoplasmic mRNA , the VSV mRNAs represent ~1% by 2 hpi , but more than 60% by 6 hpi , illustrating the power of exponential amplification of the viral genome . As a result , the viral N , P , M and G mRNAs far exceed the abundance of any given cellular mRNA , and even the least abundant viral mRNA–that encoding the L polymerase–is present at similar levels to the most abundant cellular mRNA . Thus , one contributor to host cell shut-off in VSV infected cells appears to relate to the synthetic capabilities of the viral polymerase in transcription of viral mRNA . Similar conclusions have recently been reached for other viruses . Infection of cells with mouse hepatitis virus ( MHV ) a positive-strand RNA coronavirus that replicates within the cytoplasm results in 80–90% of the cytoplasmic mRNA being viral by 5 hpi [47] . For influenza A virus , a segmented negative-strand RNA virus that replicates in the nucleus , >50% of the total mRNA in the cytoplasm is viral [48] . In this case however , the viral endonuclease PA-X degrades cellular mRNA which further contributes to the dominance of viral mRNA [66 , 67] . For vaccinia virus , a DNA virus that replicates entirely within the cytoplasm , degradation of host mRNA through the viral encoded decapping enzymes D9 and D10 also helps the viral mRNAs overwhelm those of the host cell [49 , 68 , 69] . Collectively these studies indicate that one shared mechanism for host cell shut-off in virus-infected cells is competition for host cell ribosomes through tipping the balance between viral and host mRNA . Earlier work concludes that viral mRNA abundance is not the determinant of host cell shut-off [41] . When VSV mRNA levels were suppressed up to 14-fold by using defective interfering particles of VSV or a viral mutant defective in transcription , host shut-off was still observed . We did not directly test how suppressing viral mRNA levels impacts host shut-off in this study , but rather conclude that abundance is only part of the mechanism by which the virus induces host cell shut-off–as discussed below . We also obtained evidence in support of additional mechanisms that contribute to host cell shut-off in VSV infected cells . We confirmed earlier work that demonstrated a suppression of the pool of the rate limiting factor for initiation , eIF4E , by altering the phosphorylation status of its negative regulator , eIF4E-BP1 , which results in eIF4E sequestration [9] . Differences in sensitivity to reductions in eIF4E may contribute to the overrepresentation of cellular mRNA we observe in monosome fractions during infection . We also provide new evidence in support of a phase of VSV gene expression that is dependent on eIF4E through the use of a viral mutant partially defective in guanine-N7 methylation [25] and by the suppression of cellular pools of eIF4E . When eIF4E levels are suppressed 10-fold , we unmask a defect in viral protein synthesis in cells infected with VSV-VSV-LG1670A a mutant with a 4-fold defect in methylation at the guanine-N7-position of the cap-structure . We suspect that this significantly underestimates the eIF4E dependent phase of viral replication since transformed cell lines , like the HeLa cells used here , have higher constitutive levels of eIF4E [70] . Our findings are consistent with a model where viral mRNAs initially compete with cellular mRNAs and translate in an eIF4E dependent manner . As infection progresses and the shut-down of host transcription , mRNA export and eIF4E sequestration continue , the process of initiation is increasingly less dependent on eIF4E . The mechanism by which the viral mRNAs become less dependent on eIF4E remains uncertain , but earlier studies demonstrate that neither the 5′ or 3′ UTR of viral mRNAs facilitate this efficient translation . Ongoing transcription of viral mRNA from the viral genome has also been linked to efficient protein synthesis [46 , 71] . Whether this reflects the fact that the virus is an efficient producer of mRNA that supports the competition model , or whether there is a temporal requirement for continued viral mRNA synthesis is uncertain . As obligate intracellular parasites , viruses depend upon host cell functions for their replication . Our sequence analysis provides evidence that VSV infection differentially impacts the polysome association of cellular mRNAs . Several host mRNAs increased in polysome association include genes with known “proviral” functions for entry and replication including heparan sulfate , clathrin , and HSP90 [56 , 72–74] . Similarly , host mRNAs with decreased polysome association included genes with published roles in restricting VSV replication such as interferon regulatory factor 1 ( IRF1 ) , DDIT4 , and TXNIP [62 , 63 , 75] . It is difficult to definitively determine whether this reflects evolution of the virus to contend with the environment in which it finds itself or a bona-fide pro and antiviral effect of a given host protein . Our efforts to address this are confounded by the essential house-keeping nature of many of the proteins encoded by host mRNAs that remain polysome associated . An example of this is provided by enhanced polysome association of eIF3a on VSV infection–a protein that is required for assembly of the multisubunit eIF3 complex . That complex also includes eIF3d which has demonstrated cap-binding ability , and directs eIF4E-independent translation of select mRNAs [76–79] . Depletion of eIF3A , however , resulted in an equivalent reduction in the rates of viral and host translation–inconsistent with a specialized need for eIF3 components in VSV protein synthesis . In this study , we validated that the effect of VSV infection on the polysome association of 2 host mRNAs–HSP70 and YBX1—had a concordant impact on protein synthesis . Although synthesis of HSP70 did not increase per se , this is likely explained by the shifting of many cellular mRNAs towards smaller polysomes . This finding highlights the fact that the designation of RNAs as having “increased” or “decreased” polysome association is imprecise , and reflects the complexities of how any given host gene is regulated . Nevertheless , the general finding that mRNAs with “increased” polysome association on VSV infection are typically larger , have longer half-lives and higher AU content–features that are shared with the viral mRNA–highlights commonalities among mRNAs that remain polysome-associated and thus are more efficient in competing for ribosomes during host shut-off . The cellular mRNAs that exhibit reduced translation efficiency were shorter , have shorter half-lives and higher GC content . Although we validated changes in translatability and differential impacts on viral gene expression for a few cellular genes , it would be of significant interest to perform stable isotope labelling by amino acids in cell culture ( SILAC ) to non-radioactively label newly synthesized cellular proteins , quantify them on a genome-wide scale and correlate those data with the RNAseq results presented here . In addition to suppression of host translation through mRNA synthesis and eIF4E manipulation , the VSV matrix protein inhibits host RNA polymerase II transcription [1 , 3] , and blocks nuclear export of mature mRNAs through complex formation with the nuclear pore components Rae1 and Nup98 [4–8] . A well characterized viral mutant ( VSV-MM51R ) fails to interact with the nuclear pore complex and exhibits a delayed kinetics of host shut-off [6 , 10 , 80] . A similar analysis to that described here of cells infected with such a mutant may help delineate the extent to which ongoing synthesis and export of cellular mRNA impacts host cell shut-off . We anticipate that over the time course of VSV infection , the contribution of ongoing synthesis and export of host mRNA from the nucleus will result in a relatively modest increase in the fraction of the cytoplasmic mRNA that is cellular . This study highlights a strategy shared among distinct viruses to commandeer the host translational machinery by outcompeting cellular mRNAs . Precisely where the tipping point between viral and host mRNA levels with respect to this shut-off occurs is uncertain . For VSV , a viral mutant that makes less mRNA than the wild type yet still exhibits host cell shut-off suggests that shut-off can be achieved with less than the 60% of total cytoplasmic mRNA observed here [41] . Additional work will be required to define whether a specific tipping point exists and how this is influenced by other viral strategies such as eIF4E suppression or blocking host gene transcription .
HeLa cells ( a gift from James Hogle ) were maintained in Dulbecco’s modified Eagle medium ( DMEM; Invitrogen , Carlsbad , CA ) supplemented with 10% fetal bovine serum ( FBS; Tissue Culture Biologicals , Tulare , CA ) . Viral stocks were grown on Syrian golden hamster kidney BSRT7 cells ( a gift from K . Conzelmann ) , and purified on linear 15–45% sucrose gradients prepared in NTE ( 10 mM Tris pH 7 . 4 , 100 mM NaCl , 1 mM EDTA ) . Viral titers were determined by plaque assay on African green monkey kidney Vero cells ( ATCC , CCL-81 ) . For infections , cells were first washed with Hanks’ Balanced Salt Solution ( HBSS ) and incubated with virus for 1 hour at 37°C in serum free medium , washed with HBSS and subsequently incubated with medium supplemented with 2% FBS . For polysome profiling , HeLa cells were treated with DMEM containing 100 μg ml-1 cycloheximide at 37°C for 3 minutes . Cells were washed twice with 1X ice-cold phosphate buffered saline ( PBS ) containing 100 μg ml-1 cycloheximide , and kept on ice or at 4°C . Cells were scraped into a 1 . 5 ml microcentrifuge tube in 1X PBS with 100 μg ml-1 cycloheximide , and pelleted at 300 ✕ g for 10 minutes . Cells were resuspended in 250 μl of a hypotonic buffer of 5 mM Tris ( pH 7 . 4 ) , 2 . 5 mM MgCl2 , 1 . 5 mM KCl , and RNAsin ( Promega , Madison , WI ) , supplemented with cycloheximide to 100 μg ml-1 and DL-Dithiothreitol ( DTT ) to 3 μM . The detergents Triton X-100 0 . 5% ( vol/vol ) and sodium deoxycholate 0 . 5% ( wt/vol ) were then added sequentially , cells were briefly vortexed , and incubated for 15 minutes on ice and clarified by centrifugation at 12 , 000 ✕ g for 2 min . Polysomes were separated on sucrose gradients prepared on a Gradient Master Station ( Biocomp , Fredericton , Canada ) using 10% and 50% ( wt/vol ) sucrose dissolved in 15 mM Tris ( pH 7 . 4 ) , 15 mM MgCl2 , and 150 mM NaCl supplemented with RNAsin and 100 μg ml-1 cycloheximide . Following centrifugation for 2 hours at 40 , 000 ✕ g in a Beckman Coulter ultracentrifuge using an SW40Ti rotor , 500 μl fractions were collected from the top of the gradient while monitoring absorbance at λ = 254 nm on a Gradient Master Station . RNA was extracted from total cytoplasmic , polysome , or monosome fractions using LS Trizol ( Invitrogen ) according to the manufacturer’s protocol . Equal amounts of RNA as determined by spectrophotometry using absorbance at 260 nm on a Nanodrop 2000 ( Thermo Fisher , Waltham , MA ) were subject to library preparation using the Illumina TruSeq vII RNA Library Preparation Kit ( Illumina , San Diego , CA ) , and sequenced at the Whitehead Institute ( Cambridge , MA ) on an Illumina HiSeq2500 . Reads were trimmed and mapped to the concatenated hg38 and VSV genomes using CLC Genomics Workbench ( Qiagen , Redwood City , CA ) . Mapping parameters were as follows; mismatch cost 2 , insertion cost 3 , deletion cost 3 , length fraction 0 . 8 , similarity fraction 0 . 8 , and a maximum of 10 hits per read . Raw sequence data is available from the NCBI Sequence Read Archive ( SRA ) under the primary accession code SRP158625 . Transcripts per Kilobase Million ( TPM ) was calculated for genes with 56 or more mapped reads in the cytoplasmic fraction of both uninfected and infected cells using the total number of mapped exon reads . To identify cellular mRNAs that were potential targets for translational regulation in infected cells , we determined the TPM in the polysome fraction/TPM in the total cytoplasmic fraction for each individual mRNA . This ratio was determined for uninfected and infected cells , and presented as the log2 fold change . Gene ontology analysis was performed in R using GOseq . UTRs and CDS sequences were downloaded from the UCSC table browser using “KnownCanonical” mRNA identifiers . Non-protein coding RNAs were excluded from the analysis . Poly ( A ) tail length and mRNA half-lives were from published data sets [54 , 55] . Graphs and statistical analyses were performed in R using the “wilcox_test” statistical test , the “density” kernel density estimation , and “geom_boxplot” or “geom_density” functions in ggplot and cowplot . Total RNA was recovered from polysome fractions using LS Trizol according to the manufacturer’s protocol . RNA ( 500 ng ) was annealed with oligo d ( T ) 20 and reverse-transcribed using Superscript III Reverse Transcriptase ( Thermo Fisher ) at 50°C for 1 hour . Following digestion of the RNA strand with RNaseA and RNaseH for 15 min at 37°C , reactions were diluted 1:5 for cellular gene-specific qPCR or 1:125 for viral gene-specific qPCR . Quantitative PCR was performed using Power Sybr Green ( Thermo Fisher ) and relative amounts determined by ΔΔCt . Forward ( F ) and Reverse ( R ) primers were as follows: ACTB ( F ) 5′ ACCCAGCACAATGAAGATCA 3′ , ( R ) 5′ CTCGTCATACTCCTGCTTGC 3′; ACTN4 ( F ) 5′ ACATCTCCGTGGAAGAGACC 3′ , ( R ) 5′ GGAAGTTCTGCACATTGACG 3′; COL4A2 ( F ) 5′ AACGGGATTCCATCAGACAC 3′ , ( R ) 5′ ATGCCTCTTATTCCTGGTTCC 3′; DDIT4 ( F ) 5′ CGGAGGAAGACACGGCTTA 3′ , ( R ) 5′ ACAAGTGTTCATCCTCAGGGT 3′; GAPDH ( F ) 5′ AGCCTCAAGATCATCAGCAATG 3′ , ( R ) 5′ ATGGACTGTGGTCATGAGTCCTT 3′; TGIF1 ( F ) 5′ CACCGTTACAATGCCTATCC 3′ , ( R ) 5′ GATTTGGATCTTTGCCATCC 3′; UBE2B ( F ) 5′ CAATTCAGTCTCTGCTGGATG 3′ , ( R ) 5′ AACAATGGCCGAAACTCTTT 3′; VSV G ( F ) 5′ GTGGGATGACTGGGCTCCAT 3′ , ( R ) 5′ CTGCGAAGCAGCGTCTTGAA 3′; VSV N ( F ) 5′ GAGTGGGCAGAACACAAATG 3′ , ( R ) 5′ CTTCTGGCACAAGAGGTTCA 3′ Polysome distribution is presented as the fraction of total recovered RNA for each individual polysome fraction . For inhibition of HSP90 , cells were incubated throughout the course of the experiment in 2 . 5 μM 17-[2- ( Dimethylamino ) ethyl]amino-17-desmethoxygeldanamycin ( 17-DMAG; AdipoGen Corp , San Diego , CA ) . For siRNA depletions , cells were pretreated with siRNAs against DDIT4 ( D-010855-01 ) , eIF3a ( D-019534-03 ) , or non-targeting siRNA #2 ( D-001210-02 ) , and #3 ( D-001210-03 ) Dharmacon ( Lafayette , CO ) for 48 h . Briefly , Lipofectamine 2000 ( Thermo Fisher ) was diluted 100-fold in Optimem ( Invitrogen ) , and incubated for 15-minutes with an equal volume of siRNA in Optimem . Reverse transfections were performed in 24 well plates with 5 . 5 x 104 HeLa cells per well at a final concentration of 50 nM siRNA in a total volume of 600 μl . Images of rVSV-eGFP infected cells were acquired using a 10× objective on a Nikon Eclipse TE300 microscope ( Nikon Instruments , Melville , NY ) equipped with a Spot RT SE18 Monochrome camera ( Diagnostic Instruments , Sterling Heights , MI ) . For cytometry , cells were washed in HBSS , trypsinized , fixed in 4% paraformaldehyde at 4°C for 15 minutes and measured using a FACSCalibur ( Cytek Development , Freemont , CA ) . Cytometry data was analyzed using FlowJo ( FlowJo Inc , Ashland , OR ) . For mean fluorescence intensity ( MFI ) we gated on live cells identified by forward and side-scatter . To measure the % infected cells we subtracted those cells that fell within the gate established from uninfected control cells . For luciferase assays , where indicated HeLa cells were transfected with siRNA , and the medium replenished at 24 h . Cells were transfected 6 h later with 25 ng pRL-CMV ( Promega ) , and activity measured 24 h later . For viral driven luciferase reporters siRNA transfected cells were infected at 48 h and monitored 6 h later . Luciferase expression was measured in a SpectraMax L microplate reader using the appropriate reagents according to the manufacturer’s instructions ( Promega , E1501 and E2810 ) . For depletion of host factors by peptide-conjugated morpholinos ( PPMOs ) approximately 2 . 0 x 104 HeLa cells per well of a 24 well plate were treated 24 h later with 15 μM of the indicated PPMO . At 24 h post treatment , the media was replaced with fresh medium containing 15 μM PPMO , and used for testing 24 h later . Cells were washed twice with ice-cold 1X PBS and lysed in Rose Lysis Buffer consisting of 10 mM Tris-HCl ( pH 7 . 4 ) , 66 mM EDTA , 0 . 4% w/v sodium deoxycholate , and 1% v/v NP-40 on ice for 15 minutes . Rose Lysis Buffer was supplemented with Phosphatase Inhibitor Cocktail 2 ( Sigma-Aldrich , St . Louis , MO ) and Halt Protease and Phosphatase Inhibitor Cocktail ( Thermo Fisher ) for detection of phospho-eIF4E-BP1 . Lysates were clarified , protein input was normalized by Bradford Assay and proteins resolved on polyacrylamide gels– 10% for eIF3a and eIF4E or 12% , eIF4E-BP1 . Proteins were transferred to nitrocellulose membranes for 90 minutes , eIF4E and eIF4E-BP1 , or 120 minutes , eIF3a , at 100v . Membranes were blocked with Odyssey Blocking Buffer in PBS ( LI-COR , Lincoln , NE ) for 1 h at room temperature , and incubated overnight at 4°C with the following primary antibodies: rabbit anti-eIF3a ( Cell Signaling , #3411 ) , rabbit anti-eIF4E ( Cell Signaling , #9742 ) , rabbit anti-4E-BP1 ( Cell Signaling , #9452 ) , rabbit anti-phospho-4E-BP1 Ser65 ( Cell Signaling , #9451 ) , rabbit anti-phospho-4E-BP1 Thr37/46 ( Cell Signaling , #2855 ) , mouse anti-actin ( Millipore , #MAB1501 ) , mouse anti-actin ( Sigma , #A5316 ) . Membranes were washed 3X with 1X PBS-T for 5 minutes at room temperature , and incubated with the relevant secondary antibodies: goat anti-mouse IRDye 680RD ( LI-COR , #925–68070 ) or goat anti-rabbit IRDye 800CW ( LI-COR , #925–32211 ) , for 1 hour at room temperature . Membranes were washed again and kept in 1X PBS , and scanned on an Odyssey CLx ( LI-COR ) . HeLa cells were starved in DMEM lacking L-methionine ( Corning , #17-204-Cl ) for 30 minutes , prior to addition of [35S] Express Protein Labeling Mix ( Perkin Elmer , Waltham , MA ) at 0 . 11 mCi ml-1 . Cell lysates were prepared as described above and separated on a low-bis 10% polyacrylamide gel . The gel was dried for 1 . 5 h at 80°C in a vacuum gel drier and detected using a phosphoimager . Quantitative analyses of band intensities was performed in ImageQuant TL v8 . 1 ( GE Healthcare , Marlborough , MA ) . For radioimmunoprecipitations , 4 . 0 x 106 HeLa cells plated in 10 cm dishes ( Corning ) were starved of methionine for 1 h at 24 h post-plating , and labeled with [35S]-Express for 3 h . Cells were washed twice with ice-cold 1X PBS , collected by scraping and subsequent centrifugation for 2 minutes at 4°C and 2 , 000 ✕ g and lysed in 1 ml of 50 mM Tris ( pH 7 . 4 ) , 150 mM NaCl2 , 1 mM EDTA , 1% v/v NP40 , 2 mM DTT , supplemented with Pierce Protease Inhibitor ( Thermo Fisher ) on ice for 15 minutes . Protein input was normalized by Bradford Assay , SDS was added to 0 . 1% , and 450 μl lysate was pre-cleared for 1h at 4°C on a nutator with 50 μl pre-washed Pierce Protein A Agarose Beads . Protein A beads were pelleted by centrifugation for 2 minutes at 4°C and 2 , 000 ✕ g and the labeled supernatant incubated with primary antibody at 4°C overnight . The antibodies used for immunoprecipitation were 4 μg anti-YB1 ( Abcam , #ab76149 ) and 5 μg anti-HSP70 ( Enzo , #ADI-SPA-822 ) . Immune complexes were isolated using 50 μl pre-washed Pierce Protein A Agarose Beads , by incubating for 4 hours at 4°C . Bead complexes were collected by centrifugation for 2 minutes at 4°C and 2 , 000 ✕ g , washed 5X with 950 μl ice-cold IP lysis buffer with 0 . 1% SDS , on an orbital shaker for 3 minutes at room temperature . Protein-antibody complexes were eluted by boiling in 4X SDS loading buffer , the beads pelleted for 2 minutes at 4°C in a microcentrifuge and the supernatant loaded on a 10% polyacrylamide gel . After electrophoresis the gel was dried and imaged using a phosphoimager . Approximately 1 . 5 x 106 HeLa cells were plated per well of a 6-well dish and 24 hours later incubated with phosphate free media ( Gibco , 11971–025 ) for 1 h . Thirty minutes before infection , actinomycin D-mannitol ( Sigma , #A5156 ) was added to a final concentration of 5 μg ml-1 . Infections were carried out in phosphate free media supplemented with 10 μg ml-1 actinomycin D and 2 . 5 μM 17-DMAG . At 1 hpi cells were washed , fresh medium added , and supplemented 3 h later with [32P]-orthophosphoric acid ( Perkin Elmer , #NEX053H ) 0 . 20 μCi μl-1 . Cells were harvested at 6 hpi in Rose Lysis Buffer , and total RNA was extracted using LS Trizol . RNA was separated on a 6M Urea-Agarose gel as previously described , and detected using a phosphoimager [81] .
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Viruses co-opt the host translational machinery and frequently suppress host cell protein synthesis . Many positive-strand RNA viruses manipulate initiation factors while bypassing their need for viral protein production using internal ribosome entry sites . Negative-strand RNA viruses and DNA viruses produce mRNAs that contain host-like 5′ cap-structures and 3′ polyadenylate tails . Those similarities necessitate a different mechanism for controlling viral versus host protein synthesis . We infected cells with vesicular stomatitis virus and sequenced polysome-associated mRNAs at 2 and 6 hours post-infection providing 2 snapshots of how infection alters translation . We present evidence that the 5 viral mRNAs outcompete cellular mRNAs for ribosomes and demonstrate that individual host mRNAs vary in the extent to which their polysome association is altered by infection . Host mRNAs that are more abundant , have longer half-lives , greater than average length , and a similar AU content to the viral mRNAs were more likely to be enriched among polysome-associated cellular mRNAs . Several of the enriched mRNAs encode proteins that promote viral replication , whereas mRNAs that exhibit the largest decrease in polysome association include those that encode antiviral functions .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"medicine",
"and",
"health",
"sciences",
"vesicular",
"stomatitis",
"virus",
"pathology",
"and",
"laboratory",
"medicine",
"hela",
"cells",
"gene",
"regulation",
"pathogens",
"messenger",
"rna",
"biological",
"cultures",
"microbiology",
"polyribosomes",
"viruses",
"virus",
"effects",
"on",
"host",
"gene",
"expression",
"rna",
"viruses",
"cell",
"cultures",
"cellular",
"structures",
"and",
"organelles",
"research",
"and",
"analysis",
"methods",
"small",
"interfering",
"rnas",
"medical",
"microbiology",
"gene",
"expression",
"microbial",
"pathogens",
"viral",
"replication",
"cell",
"lines",
"ribosomes",
"biochemistry",
"rna",
"rhabdoviruses",
"cell",
"biology",
"nucleic",
"acids",
"virology",
"viral",
"pathogens",
"protein",
"translation",
"genetics",
"biology",
"and",
"life",
"sciences",
"cultured",
"tumor",
"cells",
"non-coding",
"rna",
"organisms"
] |
2019
|
Global analysis of polysome-associated mRNA in vesicular stomatitis virus infected cells
|
Ascaris lumbricoides and Necator americanus are soil-transmitted parasites with global geographic distribution , and they represent some of the most common and neglected infections in the world . Periodic treatment with mass drug administration ( MDA ) in endemic areas is the recommended action put forth by the World Health Organization . However , MDA can cause the selection of subpopulations that possess the genetic ability to overcome the mechanism of drug action . In fact , beta-tubulin gene mutations ( codons 167 , 198 and 200 ) are correlated with benzimidazole resistance in nematodes of veterinary importance . It is possible that these SNPs also have strong correlation with treatment resistance in the human geohelminths A . lumbricoides , Trichuris trichiura and hookworms . Here , we aimed to investigate the presence of some of these canonical molecular markers associated with parasite resistance to benzimidazole in N . americanus and A . lumbricoides collected from six Brazilian states . Nested-PCR and PCR-RFLP were used to detect mutations at codons 167 and 198 in 601 individual eggs of A . lumbricoides collected from 62 human stool samples; however , no mutations were found . Codons 198 and 200 were tested in 552 N . americanus eggs collected from 48 patients using the same methodology , which presented a relative frequency of 1 . 4% and 1 . 1% , respectively . The presence of these SNPs in N . americanus eggs is an important finding , indicating that with high benzimidazole drug pressure there is potential for benzimidazole resistance to be selected in this hookworm . However , at these low frequencies it does not indicate that there is at present any benzimidazole resistance problem . This is the first systematic study performed in South America , and the study yielded a landscape of the genetic variants in the beta-tubulin gene and anthelmintic resistance to soil-transmitted parasites detected by a simple , rapid and affordable genotyping assay of individual eggs .
Soil-transmitted helminth infections represent important , neglected , tropical diseases that affect approximately one-fourth of the global population . Notably , 820 million people are infected with Ascaris lumbricoides , and 439 million people are infected with hookworms ( Necator americanus or Ancylostoma duodenale ) [1 , 2] . These parasites can cause abdominal pain , colic , diarrhea , nausea , vomiting and , in more severe cases , death of the host . Hookworm infection is the most common cause of iron deficiency anemia and protein-energy malnutrition in children living in developing countries [3] . The standard approach for geohelminth control , including hookworms and A . lumbricoides , is large-scale preventive chemotherapy predominantly using benzimidazoles through mass drug administration ( MDA ) , based on the drug’s performance in overall reductions in prevalence and reductions in the extent and severity of infection [4] . Nevertheless , this inexpensive and highly effective strategy can potentially select subpopulations of parasites that become resistant to treatment . Single nucleotide polymorphisms ( SNPs ) in the beta-tubulin gene at codons 167 ( TTC , TTT/Phenylalanine → TAC , TAT/Tyrosine ) , 198 ( GAG , GAA/Glutamic acid → GCG , GCA/Alanine ) and 200 ( TTC/ Phenylalanine → TAC/Tyrosine ) have been linked to benzimidazole resistance in several helminths [5–7] . SNPs at codons 198 [8] and 200 [9 , 10] have been reported in hookworms . These common resistance-associated polymorphisms are not frequently found in those populations that did not respond to treatment [9 , 11] . Conversely , a mutation at codon 167 was detected at high frequencies in A . lumbricoides samples [9] , while mutations at codon 198 and 200 have never been described for this species . Brazil is a tropical developing country with high incidence of geohelminths infection . It is estimated that 10 , 448 , 507 pre-school-age and school-age children require preventive chemotherapy [12] . MDA has been performed by the government , according to the free attendance health policy guidelines [13] . Nonetheless , there is a lack of studies that have investigated the presence of molecular markers related to parasite resistance to the available drugs . Here , we evaluate the frequency of some of the canonical codons in N . americanus and A . lumbricoides that are involved in the process of benzimidazole resistance in specimens from six Brazilian states . To our knowledge , this is the first systematic study performed in South America that examines SNPs present in soil-transmitted helminth human infections associated with benzimidazoles resistance .
This work is approved by the Comitê de Ética em Pesquisa—COEP ( CAAE 61047216 . 7 . 0000 . 5149 ) from Universidade Federal de Minas Gerais ( UFMG ) . As we had used human feces obtained from commercial laboratories performing pathology analysis , an informed consent document was not required . We did not obtain any subject identification and the data were analyzed anonymously . Human coproparasitological collection and screening analysis was performed in six Brazilian states . Positive samples for A . lumbricoides and N . americanus were stored in 10% formaldehyde for later molecular analysis . The initial isolation of eggs was performed according to Ritchie ( 1948 ) with modifications [14] . In summary , 2 ml of stool suspension was homogenized , filtered through gauze and transferred to a 15ml tube . Five ml of sulfuric ether was added and to the suspension and then stirred vigorously , followed by 1 minute centrifugation at 14 , 000 x g . The supernatant was discarded . Eggs were washed with in a new step by adding 500 μl of 1 . 0% and 5 . 0% of hypochlorite for 10 minutes to the N . americanus and A . lumbricoides samples , respectively . The material was centrifuged at 14 , 000 x g , and the supernatant was discarded . The eggs were washed again using 500 μl of ultrapure water , followed by centrifugation at 14 , 000 x g . The supernatant was then discarded . The pellet was resuspended in 100 μl of ultrapure water for N . americanus . A . lumbricoides eggs processing included the additional steps of a ) incubation at 30 °C in 500 μl of 0 . 2 N sulphuric acid for 30 days ( for larvae development ) , b ) centrifugation at 14 , 000 x g and discard of the supernatant , c ) washing ( resuspension in 500 μl of ultrapure water , centrifugation at 14 , 000 x g and discard of the supernatant ) , d ) incubation with 500 μl of 1 . 0% hypochlorite up to the point at which the outerlimiting membrane dissolved using a microscope for visual confirmation , e ) repetition of steps a-c followed by the addition of 100 μl of ultrapure water . For DNA extraction , the eggs from both N . americanus and A . lumbricoides were observed under an optical microscope , individually pipetted into a volume of 1 μl and transferred to a 500 μl microcentrifuge tube containing 10 μl of buffer , as described by Lake and colleagues [15] and modified by Diawara and colleagues [9] . In total , 864 A . lumbricoides eggs from 64 patients and 552 N . americanus eggs from 48 patients , collected in six Brazilian states , were analyzed . None of these samples came from polyparasited patients . Table 1 shows the collection sites , as well as the number of patients and eggs of A . lumbricoides and N . americanus collected from each state . All primers were designed using Primer3 ( http://bioinfo . ut . ee/primer3-0 . 4 . 0/ ) based on beta-tubulin nucleotide sequences for N . americanus ( EF392851 . 1 ) and A . lumbricoides ( EU814697 . 1 ) from GenBank and WormBase ParaSite ( N . americanus: PRJNA72135 , Assembly GCA_000507365 . 1; A . lumbricoides: PRJEB4950 , Assembly GCA_000951055 . 1 ) ( Table 2 ) . Controls were constructed for the absence ( wild-type ) and presence of the mutation for each codon for each species . To construct a wild-type control allele for codons 198 and 200 ( N198/200Na ) , PCR amplification was performed with the primers Fa198/200Na + Rab198/200Na ( 325 bp ) and genomic DNA from N . americanus . The primers AltubF + AltubR ( 596 base pairs , bp ) and DNA collected and pooled from A . lumbricoides eggs were used to construct the wild-type control allele for both codons 167 ( N167Al ) and 198 ( N198Al ) . PCR amplifications for the wild-type controls were performed using GoTaq Green Master Mix ( Promega , USA ) , with a final concentration of 0 . 2 μM for each primer , according to the following program: 95°C for 5 min , 30 cycles at 95°C for 30 s , 60°C for 45 s , 72°C for 60 s and a final step of 72°C for 8 min . To construct the mutated controls for codons 167 ( M167Al for A . lumbricoides ) , 198 ( M198Na for N . americanus; M198Al for A . lumbricoides ) and 200 ( M200Na for N . americanus ) , site-directed mutagenesis was performed using the Megaprimer-PCR technique . First , for N . americanus the wild-type N198/200Na was used as a template for codons 198 and 200 with the primer combinations Fm198Na + Rab198/200Na ( 263 bp ) and Fm200Na + Rab198/200Na ( 263 bp ) , respectively . For A . lumbricoides , the wild-type N167Al DNA template was used to perform the megaprimer-PCR for mutated codon 167 with the primers AlMega167R + AltubF ( 146 bp ) , while AlMega198F + AltubR was used to perform megaprimer for mutated control 198 ( 94 bp ) . The Fm198Na , Fm200Na , AlMega167R and AlMega198F primers were designed to introduce a mismatch that mimics the mutated sequence corresponding to each codon ( Table 2 ) . The site-directed mutagenesis was performed using Kapa HiFi polymerase ( Kapa Biosystems , USA ) following the manufacturer instructions , and a final concentration of 0 . 2 μM for each primer , with cycling conditions of 95°C for 3 min , 30 cycles at 98°C for 20 s , 50°C for 45 s , 72°C for 45 s and a final step of 72°C for 8 min . The reaction products were subjected to electrophoresis on 1 . 0% agarose gels ( w/v ) ( Midsci , USA ) stained with GelRed ( Biotium , USA ) . The fragments were excised from the gel , purified ( Illustra GFX PCR DNA and Gel Band Purification Kit , GE Healthcare , UK ) , and measured for concentration . Approximately 20 ng of the first reaction product was used as a megaprimer in combination with 1 μM final concentration of the primers Fa198/200Na for mutated M198Na and M200Na ( respectively mutated codon 198 and 200 , 325 bp each ) for N . americanus , 1 μM of primer AltubR and 1 μM of AltubF for M167Al and M198Al , respectively ( 596 pb each ) , using Kapa HiFi polymerase ( Kapa Biosystems , USA ) according to the manufacturer instructions with cycling conditions of 95°C for 3 min , 30 cycles at 98°C for 20 s , 60°C for 45 s , 72°C for 45 s and a final step of 72°C for 8 min . The fragments were subsequently cloned using the pGEM-T Easy Vector System ( Promega , USA ) , transformed into XL1-blue cells ( Phoneutria , Brazil ) and recovered via miniprep ( Wizard Plus Miniprep DNA Purification System , Promega , USA ) . The clones were sequenced , and the absence/presence of the mutations was successfully confirmed . In silico analysis of A . lumbricoides and N . americanus beta-tubulin nucleotide sequences retrieved from GenBank and WormBase ParaSite databases were performed using the NEBcutter V2 . 0 tool ( http://www . labtools . us/nebcutter-v2-0/ ) in order to search for restriction sites that could be used to distinguish between the mutated and the wild type alleles ( of 198 and 200 for N . americanus; and 167 and 198 for A . lumbricoides ) so that a PCR-RFLP approach could be employed . The enzymes RsaI ( Promega , USA ) and BmsI ( Thermo Fisher Scientific , USA ) were chosen to differentiate between mutated and unmutated codons 167 and 198 of A . lumbricoides . Sites for enzymes Alw26I and HpyAV ( Thermo Fisher Scientific , USA ) were present in the N . americanus sequence and therefore used to distinguish between mutated and unmutated alleles for the codons 198 and 200 of N . americanus , respectively . A suitable enzyme that could differentiate between mutated and unmutated codon 200 of A . lumbricoides was not found . This same situation was observed for codon 167 of N . americanus . For N . americanus , an initial PCR was performed using one primer pair to amplify the codons 198 and 200 ( Fa198/200Na + Rab198/200Na; 325 bp ) using GoTaq Green Master Mix ( Promega , USA ) , with 0 . 2 μM of each primer and 4 . 2 μl of the buffer containing the DNA of a single egg . The cycling conditions followed the same parameters as described for the wild-type control synthesis . A semi-nested PCR was performed using 1 μl from the first PCR reaction employing primers Fb198/200Na + Rab198/200Na ( 315 pb ) , using the same PCR conditions as described above . One μl of the products from the second reaction was digested at 37°C for 1 hour with 1 unit of enzyme ( Alw26I and HpyAV for the codons 198 and 200 ) in a total volume of 15 μl . The products were subjected to electrophoresis in a 6 . 0% polyacrylamide gel ( w/v ) stained with GelRed ( Biotium , USA ) . For A . lumbricoides , an initial PCR was performed using one primer pair to amplify the codons 167 and 198 ( AltubF + AltuR; 596 bp ) . One μl of the PCR product was used as a template for a nested PCR with Al167F + Al98R ( 608 pb ) . The second reaction showed a larger amplicon because the primers had M13 adapters ( Table 2 ) . The PCRs and digestions performed for A . lumbricoides were performed at the same volumes and conditions as used for N . americanus , except for the enzymes used . The enzymes RsaI and BmsI were used for digestion of codons 167 and 198 , respectively . The products were subjected to electrophoresis in a 1 . 5% agarose gel ( w/v ) stained with GelRed ( Biotium , USA ) . The expected fragment sizes after the digestion of each genotype of each codon are listed in Table 3 . Samples with positive PCR-RFLP mutations were sequenced for confirmation . A negative control sample was included in all amplification runs . Extreme care was taken to avoid contamination with another sample and/or with the control plasmids . Tubes containing the control plasmids were handled in a different room where the DNA samples were manipulated , and filter tips were used in all procedures . Fig 1 shows the methodological scheme adopted for the analysis of all the SNPs in this work .
We analyzed a total of 1153 geohelminths individual DNA samples from eggs belonging to 110 independent human feces samples collected from six Brazilian states . No mutations were detected in all 601 A . lumbricoides eggs analyzed for codons 167 and 198 of beta-tubulin gene . Mutation at codon 198 of N . americanus was observed in three localities: 1 ) Ceará , with 3 . 0% positivity ( 3/100 ) : one homozygous and two heterozygous eggs from the same patient; 2 ) Minas Gerais , with 3 . 75% positivity ( 3/80 ) : one patient had one heterozygous and one homozygous egg ( nine eggs evaluated ) , and another patient had one heterozygous egg ( 18 eggs analyzed ) ; and 3 ) Bahia , with 2 . 0% positivity ( 2/101 ) : one patient with one homozygous and one heterozygous egg ( 20 eggs analyzed ) . Considering all the regions analyzed , 1 . 4% ( 8/552 ) of the eggs examined were found to have the mutation at codon 198 . The tests performed examining codon 200 of N . americanus showed the presence of the mutation in two states . In Maranhão there was 3 . 6% ( 4/111 ) positivity: one homozygous egg from one patient who had 12 eggs evaluated; another homozygous egg from one patient who had 11 eggs evaluated , and two homozygous eggs from one patient with 10 genotyped eggs . In Bahia there was 2% ( 2/101 ) positivity: two heterozygous eggs , one of which was also heterozygous at codon 198 , from a patient with 20 eggs evaluated . Therefore , the percentage of examined eggs positive for the mutation at codon 200 was 1 . 1% ( 6/552 ) . It is noteworthy that beta-tubulin gene from an egg ( from a Bahia patient ) was heterozygous for codon 198 and codon 200 . S1 Fig shows a representative image of polyacrylamide gel of the PCR-RFLP for N . americanus . S2 Fig shows a representative image of agarose gel of the PCR-RFLP for A . lumbricoides . Fig 2 illustrates the genotypes found for codons 198 and 200 in 552 N . americanus egg samples collected from six Brazilian states .
Treatment with benzimidazoles is the foremost approach for soil-transmitted helminth control; however , the indiscriminate use of these drugs in a target population selects naturally resistant parasites capable of surviving exposure to the drug and can produce resistant offspring [4 , 16 , 17] . This selective pressure has been associated with the occurrence of SNPs in codons 167 , 198 and 200 of the beta-tubulin gene of several helminths [5 , 18] . We evaluated the frequency of some of these canonical SNPs in A . lumbricoides and N . americanus collected from six Brazilian states by PCR- RFLP technique . Mutations related to resistance to benzimidazoles have been detected by diverse techniques for helminths [10 , 19] and fungi [20] . In the present work , a PCR- RFLP molecular screening test was performed to detect mutations in the beta-tubulin gene of A . lumbricoides and N . americanus , and controls were synthesized for absence and presence of each SNP analyzed in both species . The PCR- RFLP technique requires the creation or disruption of a restriction endonuclease’s cleavage site by the mutation . In some cases , however , commercially endonucleases are not capable to detect the nucleotide change , as observed for the codons 167 of N . americanus and 200 of A . lumbricoides . A wide range of molecular techniques may be employed for the analysis of these SNPs . Methodologies based on qPCR and sequencing have been described for analysis of SNPs in the beta-tubulin gene [19 , 21] . Rashwan and colleagues [8] developed a genotyping assay of SNPs on the N . americanus beta-tubulin gene using the SmartAmp2 method . We therefore aim to overcome this limitation by analyzing these SNPs using ARMS-PCR or tetraprimer ARMS-PCR , as performed by our group for A . caninum [10 , 22 , 23] . None of the individual DNA samples of A . lumbricoides presented mutation at codon 167 . This mutation was initially described in Haemonchus contortus and later reported in Teladorsagia circumcincta , cyathostomes , Haemonchus placei and Trichuris trichiuria [24] . Notably , a mutation at codon 167 with a distinct elevated frequency was detected in A . lumbricoides collected from different endemic areas [9] . This finding was not replicated for codon 167 [25] or for any of the three canonical codons in an expanded drug-resistant sampling in Africa [26] . Schwenkenbecher and colleagues [19] detected a very-low-frequency mutation at codon 167 and 200 in hookworms collected from children who received treatment periodically , suggesting that these data may be associated with possible qPCR experimental error . Ishii and colleagues [27] detected a high frequency ( 61 . 2% ) of this mutation in cyathostomines from Paraná , Brazil . Contrary to the results for most species , polymorphisms at codon 167 were more frequent than mutations at codon 200 in cyathostomes [28] . Analysis of 110 feces samples from patients from Sri Lanka infected with N . americanus also showed positive results for the mutation at codon 198 , but the frequency per helminth was not detected due to the approach of pooling larvae samples instead of searching for SNPs individually [8] . A . caninum adults and eggs collected from dogs in the United States showed no mutation at codon 198 [29]; similarly , no mutation was observed in a large number of A . caninum ( 327 adult worms ) obtained from two different states in Brazil [10] . A lack of investigation at codon 198 of the beta-tubulin gene may lead to an underestimation of the reported frequencies . Therefore , it is likely that this mutation has not been extensively described in human hookworms because of the scarcity of available data , rather than being absent in these worms . The mutation at codon 200 in N . americanus presented a relative frequency of 1 . 1% in the Brazilian samples . A frequency of 2 . 3% of individual eggs analyzed in this species was detected in patients from Kenya; but not detected in samples from Haiti , Panama [9] and Sri Lanka [8] . The highest frequency of this SNP was reported in 36% N . americanus samples from Haiti where patients had been submitted to MDA [30] . N . americanus Brazilian population showed homozygous and heterozygous alleles for codons 198 and 200 . Curiously , one egg showed mutation in both codons demonstrating compound heterozygosity . None of the samples evaluated in this study exhibited concurrently homozygous mutations at both codons , as observed for other helminths . [31 , 32] . Eighty nine eggs of N . americanus and 163 eggs of A . lumbricoides did not result in PCR amplifications ( results not counted in the sampling number ) . Three hypotheses might may have accounted for the amplification failure: 1 ) another mutation ( not related to resistance ) at the primer’s sequence preventing its annealing and further amplification; 2 ) sample loss during egg transfer into the lysis buffer; and 3 ) damage of samples conserved with formaldehyde . The third hypothesis appears to be more likely , since the degradation of DNA in the presence of this preservative has been reported [33 , 34] . The medical records of the patients used in the present study were not available , which was a limitation in our analysis . Information regarding the presence of anthelmintic treatment and the drug periodicity would potentially clarify the correlation between SNPs in beta-tubulin gene and benzimidazole resistance in those humans . The absence and low frequency of the selected mutations herein raises the hypothesis that the studied populations did not undergo a mass treatment , or if they did , the periodicity of the chemoprophylaxis was not enough to confer high levels of mutated alleles . The PCR-RFLP approach , largely used in multi-organism DNA genotyping for decades , has proved to be an affordable , easy and high-throughput screening assay to detect mutations in a substantial number of individual helminths eggs . A . lumbricoides individual samples showed no mutations at the tested beta-tubulin codons 167 and 198 . Low frequencies of mutations at codons 198 and 200 of N . americanus individual eggs were observed . In a scenario of highly indiscriminate use of albendazoles , the establishment of drug resistance in N . americanus populations might likely arise . We suggest the inclusion of a comprehensive number of samples encompassing additional geographical regions , to investigate the genetic landscape of those mutations in populations subjected to MDA . The understanding of the genetic components in the dynamics of drug resistance is essential: early monitoring increases the likelihood of delaying the establishment of resistant parasites in the populations .
|
The soil-transmitted helminths Ascaris lumbricoides and the hookworms ( Necator americanus and Ancylostoma duodenale ) are the most prevalent intestinal helminths of humans . The standard approach for geohelminth control is large-scale preventive chemotherapy predominantly using benzimidazoles through mass drug administration . Nevertheless , this inexpensive and highly effective strategy can potentially select subpopulations of parasites that become resistant to treatment . In veterinary parasites , intensive reliance on the same anthelmintics has led to the emergence of benzimidazole resistance , but this is not yet proven to helminth parasites of humans . Here we describe a PCR-RFLP approach for single nucleotide polymorphisms ( SNPs ) detection at codons 167 and 198 in the beta-tubulin gene of A . lumbricoides , and SNPs at codons 198 and 200 in the beta-tubulin gene of N . americanus of Brazilian populations . A . lumbricoides samples showed no mutations in any codons , and mutation at codons 198 and 200 were observed at low frequencies in N . americanus . The observed data posit important public health issues: the mutations are a substrate for selective pressure and a long-term mass drug administration could allow to the selection of parasites resistant to benzimidazole in Brazil .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"invertebrates",
"chemical",
"compounds",
"helminths",
"hookworms",
"animals",
"organic",
"compounds",
"necator",
"americanus",
"organisms",
"mutation",
"ascaris",
"ascaris",
"lumbricoides",
"molecular",
"biology",
"techniques",
"research",
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"methods",
"artificial",
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"extension",
"benzimidazoles",
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"chain",
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] |
2018
|
PCR-RFLP screening of polymorphisms associated with benzimidazole resistance in Necator americanus and Ascaris lumbricoides from different geographical regions in Brazil
|
Yellow fever ( YF ) is endemic in much of Brazil , where cases of the disease are reported every year . Since 2008 , outbreaks of the disease have occurred in regions of the country where no reports had been registered for decades , which has obligated public health authorities to redefine risk areas for the disease . The aim of the present study was to propose a methodology of environmental risk analysis for defining priority municipalities for YF vaccination , using as example , the State of São Paulo , Brazil . The municipalities were divided into two groups ( affected and unaffected by YF ) and compared based on environmental parameters related to the disease's eco-epidemiology . Bivariate analysis was used to identify statistically significant associations between the variables and virus circulation . Multiple correspondence analysis ( MCA ) was used to evaluate the relationship among the variables and their contribution to the dynamics of YF in Sao Paulo . The MCA generated a factor that was able to differentiate between affected and unaffected municipalities and was used to determine risk levels . This methodology can be replicated in other regions , standardized , and adapted to each context .
Brazil has an extended enzootic or endemic area for sylvatic yellow fever ( YF ) , where cases of the disease are annually reported . The highest frequency of the disease occurs between January and April , when high levels of rainfall and an increase in the vector population coincide with greater agricultural activity [1]–[5] . In Brazil , endemic cases of the disease were limited to the northern , middle , western , and pre-Amazon regions until 1999 [4] , [6] . Since then , YF has progressively expanded its territory , and a gradual increase of reported cases has been observed near the traditional boundaries of endemic zones . This expansion highlights the need to redefine the areas of risk [6]–[9] . Until 2008 , four distinct epidemiologic area types for YF were acknowledged in Brazil: endemic areas ( where vaccination against YF was recommended ) , transition areas ( also known as epizootic or emergence areas ) , potential risk areas ( where vaccination against YF was not recommended ) and disease-free areas ( where YF did not occur and vaccination against YF was not recommended ) [4] , [6] . Zones classified as —transition , and —potential risk , have no records of virus circulation and no indication for YF vaccination . However , these areas possess some environmental parameters that are compatible with the establishment and maintenance of the disease; thus , there was a need for increased YF surveillance activities in those regions . Nevertheless , these parameters were subjectively defined and the non-vaccination of supposedly at-risk people generated ethical problems for Brazilian health authorities . The transition and potential risk zones were eliminated in 2008 . Therefore , only two area types are currently acknowledged: endemic ( where vaccination against YF is recommended ) and disease-free ( where vaccination against YF is not recommended ) . In public health emergency situations , the municipalities where vaccination should be recommended are defined by classification methods based on affected or expanded areas . Thus , municipalities are considered to be affected when the virus circulation can be detected , which occurs when YF epizooties are confirmed in nonhuman primates , when there are confirmed human cases , or when the virus is isolated in mosquitoes [6] , [7] . Municipalities within 30 km of a municipality where virus circulation has been detected are also considered to be affected areas [6] . The YF vaccine was considered completely safe until 2001 , as there had been no reports of serious adverse reactions associated with its administration . However , 12 serious cases were reported in 2001 [10]–[12] , and 39 additional cases were identified worldwide through May of 2009 [13]; to date , over 50 cases have been reported [13]–[15] . Two types of serious adverse reactions are commonly reported: neurotropic disease , which is caused by the invasion of the nervous system by the vaccine virus , and viscerotropic disease , which is a pan-systemic infection that is similar to the infection caused by the wild-type virus [13] . A dilemma is thus created for the public health authorities: what proportion of the at-risk population should be vaccinated to minimize the total number of fatal cases from the natural infection of the yellow fever virus ( YFV ) or the vaccine virus ? This problem applies to the State of Sao Paulo and to other states located in the southern and southeastern regions of Brazil . Briand et al . ( 2009 ) [16] developed a methodology for prioritization of areas for vaccination against YF for countries in Africa , using Multiple Correspondence Analysis . Although , in this study the authors had as limitation: the lack of information available , working with a small number of variables . Using the current situation of the State of Sao Paulo , Brazil , as an example for definition of priority areas for vaccination against YF , this paper aims to adapt the methodology of risk analysis proposed by Briand et al , ( 2009 ) [16] in a context with more availability of information , allowing the use of environmental variables potentially related with the eco-epidemiology of YF .
The study was conducted in the State of Sao Paulo , Brazil . Sao Paulo is composed of 645 municipalities , has an area of approximately 250 , 000 km2 , and has an estimated population of 40 million people . There are currently 429 municipalities in the YF-endemic zone and 216 in the disease-free zone . Aiming to select variables with the most relevance for the eco-epidemiology of YF , two groups were defined for comparison: municipalities that were affected and municipalities that were unaffected by the disease . The study used a case-control model with an ecological approach . The Text S1 shows the resume of the steps used in this study . Municipalities with confirmed YFV circulation in their territory and the adjacent municipalities were considered to be affected [6] . There were a total of 12 municipalities with confirmed YFV circulation and 57 adjacent municipalities . The 12 confirmed municipalities and 18 randomly selected adjacent municipalities were included in this study and constituted a sample of 30 cases , which is the minimum necessary for the use of the desired statistical analysis . The unaffected or eligible control municipalities consisted of all of the municipalities that had no reported cases of YF and that were at least 100 km away from any affected municipality . Figure 1 illustrates the methods used to outline these areas and the municipalities selected for this study . Each municipality was analyzed relative to the moment before the occurrence of YF in its region or prior to its inclusion as an area of recommended vaccination . Following Briand et al . ( 2009 ) [16] , the variables were selected to relate to risk allocation based on vulnerability according to three main axes: exposition , susceptibility , and resilience . The authors considered exposition as the capacity for YFV to circulate in a municipality . Thus , data included were related to the environment ( land occupation , forest fragmentation , wind direction influences , distance for biodiversity conservation unities , distance for municipalities with YFV circulation and proportion of riparian forest ) , the vectors ( temperature , humidity and pluviosity ) , and the hosts ( human displacements and illegal animal trafficking ) . Susceptibility was considered as the number of hosts without immunity for YFV that lived in each municipality . The immune human population was calculated as the proportion of immunized people divided by total population of the municipality . Non-human primates comprised the registered species occurrence in each municipality classified by a score according with the importance of each species as YFV amplifier [17] . Susceptibility also included the risk of urbanization of the disease , based on levels of infestation of Aedes aegypti in the municipality , using the Breateau Index [18] . Resilience was defined as the capacity of each municipality to detect the YFV circulation in its territory ( Surveillance for Febrile Ictero-hemorrhagic Syndrome ) , as well as , its capacity of confrontation an outbreak of YF ( Medical care capacity ) . The Text S2 shows the variables analyzed in the study . The secondary data were primarily obtained from the Internet . The free software Terraview 3 . 3 . 1 was used for distance measurements . Historical series were created for the variables temperature , pluviosity , and humidity using the monthly averages from November to May ( months with a greater occurrence of YF ) . The mean pluviosity divided by the mean real evapotranspiration ( RET ) in the same period was used as a humidity indicator [19] . Variables that showed statistically significant associations ( chi-squared test , p<0 . 05 ) were selected for the multiple correspondence analysis ( MCA ) . For the application of MCA , all the variables were categorized and treated like qualitative variables . The MCA is an exploratory and descriptive multivariate statistical technique for categorical data analysis . The technique is appropriate for the analysis of contingency tables with a large number of variables . The method analyses the mass distribution , by the pattern of the frequency for the considered categories , aiming to identify the uniformity of the distribution . This analysis was performed to evaluate the relationships among the selected variables and to obtain factors that best represent all variables , considering the level of significance ( weight ) of each to explain total sample variability ( inertia ) . Thus , the graphic obtained can be studied like a geographic map , analyzing the relationship of proximity by projections of the factors , in way that each point represents each variable . STATISTICA 7 software was used to perform the MCA .
The bivariate analysis identified seven variables associated with YFV circulation ( Table 1 ) . The MCA generated 12 factors to explain the total sample variability ( inertia ) . One of the factors could independently explain 28 . 1% of the total sample variability . None of the other 11 factors were able to independently explain more than 10% of the sample variability . The analysis of the graphic ( Figure 2 ) allows visualization of the relationship between the variables used for the construction of F factor . The graph contains only one dimension , and each point's disposition represents the position of each variable . Three main clusters of variables could be noted . The first cluster shows a collection of variables that represent , in theory , lower risk for the occurrence of YF . These variables are represented by extreme values: greater distances to areas with recommended vaccination against YF ( DIST_VAC:1 ) and biodiversity conservation units ( DIST_BCU:1 ) , smaller proportions of riparian forest ( RIPA:3 ) , fewer routes of illegal wildlife traffic ( TRAF:3 ) , less humidity ( HUMI:1 ) , less influence of the direction of dominant wind routes ( WIND:3 ) , and no surveillance for SFIHS ( SFIHS:2 ) . The second cluster shows variables of intermediate values and the third shows opposite values of those observed in the first cluster . The variable distance to area with recommended vaccination against YF was the only exception observed , where values for —adjacent or up to 30 km ( DIST_VAC:1 ) and —31 to 100 Km ( DIST_VAC:2 ) were clustered between the first and second clusters . The weights of each variable ( Table 2 ) were identified by MCA , based on geometric distance between than in the graphic . Thus , these values were used on the equation , and the F factor was calculated for each municipality . It's known that municipalities without the SFIHS are less resilient . So , the association of this variable with the YFV circulation was considered as protection factor . Thus , the positive sign of the variable was inverted for the calculation of the F factor , in way that , municipalities without SFIHS had its F factor increased , and so , considered more vulnerable . Analyzing the graph ( Figure 3 ) allows us to observe the difference between cases group 1 ) and controls ( group 2 ) according to the F factor . All municipalities from control group ( non-affected ) showed values under zero . So , this was defined as the cut point to differentiate risk and no risk . The scale of risk was divided in two to turn the model able to give priority for municipalities with higher F factor values . Thus , the priority levels for vaccination against YF in municipalities of the State of Sao Paulo were: F factor<0 . 0 = low risk; 0 . 0<F factor<2 . 0 = some risk; F factor>2 . 0 = high risk .
The study used a large number of variables . Much of the work focused on the collection and standardization of the information from secondary sources ( i . e . the internet ) . The 60 municipalities evaluated in the case-control step was the minimum necessary to support the statistical analysis . The State is composed of 645 municipalities , thus , the collection of all information for each municipality would be unfeasible . Therefore , effort was made to identify the most important variables . This approach , using a subset of municipalities , simplified and optimized the method for broader application to target municipalities with not currently indication for YF vaccination . The use of secondary data that are available on the Internet is one limitation of this methodology , especially given that the data were not collected for this purpose . However , the authors sought to incorporate official published data on each subject . Therefore , the limitation is admitted for a better replicability of the method . The study showed the importance of a large number of variables for the ecoepidemiology of YF . The distance between the municipality and areas with recommended vaccination against YF can be considered an important criterion for the prioritization of a municipality for YF vaccination . Municipalities from affected regions were , for the most part , close to or even inside of areas with recommended vaccination against YF at the moment of the case occurrence . The occurrence of YF in municipalities with a small proportion of susceptible individuals indicates the importance of vaccination coverage of close to 100% for populations living in areas of risk , as is recommended by Brazil's Ministry of Health [6] . Municipalities located in affected regions were closer to biodiversity conservation units ( BCU ) . Mosquito species that serve as vectors for YF are mainly found in well-conserved forest patches [20] . It is possible that BCUs favor the proliferation of these species and increase the chances of disease maintenance by serving as stepping stones for the geographic expansion of the disease . The Brazilian Forest Code includes the riparian forests in the category of permanently protected areas . Thus , forest patches are more frequently maintained in these environments and generate more stable ecological corridors . These forests represent one of the few environments that allow the displacement of non-human primate populations . Affected municipalities were closer to main illegal wildlife traffic routes . Trafficking of illegal wildlife can be an important source for the dissemination of viremic non-human primates from areas of virus circulation . Every year , large numbers of non-human primates that originate from YF-endemic regions , such as the Amazon , are apprehended from illegal trafficking [21] . These animals are often returned to forest environments without adequate ecological and sanitary evaluations , which allows for contact between these viremic hosts and vectors of the disease [22] . Climatic factors , such as humidity and temperature , have a direct influence over the abundance of YF mosquito vector species , as well as virus multiplication in its arthropod reservoirs [23]–[26] . Unlike the humidity calculated as a percentage relative to the availability of water vapor in the air , the RET is calculated in mm3 , which allows for the evaluation of its relationship with the pluviosity and hydrologic balance of the region . Given that the RET takes into consideration several factors , it is a more complete indicator of climatic conditions than the isolated values of pluviosity and temperature; therefore , it better represents the context of topography and land occupation in the municipalities [19] , [27] . Another climatic factor that presented a statistically significant association between the groups was the influence of dominant wind routes that arrive at each municipality . The biological plausibility of this hypothesis is related to the possibility of dispersion of mosquito vectors by dominant winds [28]–[31] . Causey et al . ( 1950 ) [29] evaluated the dispersion patterns of mosquitoes of the genus Haemagogus spp . And Sabethes spp . in the State of Minas Gerais , Brazil . Dispersion capabilities of up to 11 km were observed . The authors concluded that environments composed of forest patches , agriculture , and pasture favor the expansion of YF by increasing the wind dispersion of mosquitoes . The importance of active Surveillance for Febrile Ictero-hemorrhagic Syndrome ( SFIHS ) was also demonstrated by the present study . The affected municipalities mostly coincided with regions of the state where this surveillance system had been implemented . Therefore , municipalities without SFIHS had less resilience , meaning a lower capacity for disease detection to address a possible virus circulation in its territory . Due to the large number of important variables for YF eco-epidemiology in this study , it is possible to visualize the complexity of the disease . Several factors probably act simultaneously and in different combinations to determine virus establishment and maintenance in a region . Therefore , multivariate analysis techniques are important for the evaluation of the influence of each variable on the disease's eco-epidemiology . Variables that showed greater contributions to the variability of the municipalities in relation to the F factor observed in this study were influence of the direction of dominant wind routes , number of illegal wildlife traffic routes , proportion of riparian forest , and the implantation of surveillance of FIHS . The grouping of the variable distance to area with recommended YF vaccination into groups of —up to 30 km , and —31 to 100 km , suggests a possible need to increase the current 30-km radius for the areas considered to be at risk ( expanded areas ) during outbreaks of YF . The legislation that establishes the YF surveillance system in Brazil [6] defines that this System must be based on confirmed cases rather than predictions about the occurrence of the disease in areas of potential risk . The main purpose of the system is focused on the rapid detection of suspect cases and the adoption of emergency measures that will prevent an epidemic outbreak . The previous approach for risk classification of YF in Brazil , using —transition , and —potential risk , areas for guiding control measures , allowed for the intensification of surveillance in areas of known environmental potential for disease establishment . However , this approach was highly subjective because the criterions for defining areas were not described in a systematic way . The difficulty in replicating courses of action led to the simplification that is the current method [32] . However , it is extremely important that a surveillance system , such as that for YF—a fatal disease with great potential for outbreaks—works with models for supporting an evidence-based public-health decision-making process to guide actions in outbreak emergency situations . In the long run , the goal is to interrupt the expansion of the disease to large populated areas or known vulnerable populations . The present study has proposed a methodology for the definition of vulnerable regions for YF using environmental variables and a systematic design that focuses on a regional scale . The difference between the current method and the method proposed can be noted by the fact that all control municipalities , which were located in area with YF vaccination indicated , but without registration of YFV circulation , were classified as without risk in this study [6] , [32] . In this sense , it is recommended that , within the vaccination , municipalities classified as in —risk , pass through an analysis of its structural capacity for confrontation of a YF outbreak , considering: the number of technicians trained and sensitized for: detection of YF suspected cases , treatment and laboratorial diagnosis resources , viability for detection of epizootic events in non-human primates , capacity for conduction of entomological studies , and viability for timely conduction of campaigns of vaccination for target populations when required . In the case of municipalities classified as “high risk” , it is recommended that , in addition to the measures cited above , the organization of surveillance system for SIHFS be conducted , once this system increases the sensitivity of the Yellow Fever Surveillance System in other regions of State affected by the disease [32] . It is also recommended that professionals using this methodology visualize the geographic distribution of municipalities according with the risk classification . This type of approach can be useful for organization of the action measures for disease control . Moreno & Barata ( 2011 ) [32] showed that , in Sao Paulo State , the municipalities with higher risk are the most populated . In cases like these , the increase of surveillance measures can be an option more feasible both financially as well as operationally . The increased geographic expansion of emergent diseases , such as YF , exposes the health surveillance systems to the need to seek methodologies with multidisciplinary approaches that are able to adapt to different regional realities . Using locally relevant environmental variables and a systematic design , the methodology proposed in this study was able to differentiate municipalities according to their vulnerability for the occurrence of YF . This methodology can be replicated in other regions , standardized , and adapted to each context .
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Yellow fever ( YF ) is an infectious disease , transmitted by mosquitoes , and very common in North and Middle East region of Brazil , where cases of the disease are reported every year . Since 2008 , outbreaks of the disease have occurred in regions of the country where no reports had been registered for decades , which has obligated public health authorities to redefine risk areas for the disease . The aim of the present study was to propose a methodology of environmental risk analysis for defining priority municipalities for YF vaccination . The municipalities were divided into two groups ( affected and unaffected by YF ) and compared based on environmental parameters related to the disease's epidemiology . Statistical analysis was used to identify associations between the variables and virus circulation , as well as , to evaluate the relationship among the variables and their contribution to the dynamics of YF . The MCA generated a factor that was able to differentiate between affected and unaffected municipalities and was used to determine risk levels . This methodology can be replicated in other regions , standardized , and adapted to each context .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"science",
"policy",
"biology",
"veterinary",
"science"
] |
2012
|
Methodology for Definition of Yellow Fever Priority Areas, Based on Environmental Variables and Multiple Correspondence Analyses
|
West Nile virus ( WNV ) is an emerging flavivirus capable of infecting the central nervous system ( CNS ) and mediating neuronal cell death and tissue destruction . The processes that promote inflammation and encephalitis within the CNS are important for control of WNV disease but , how inflammatory signaling pathways operate to control CNS infection is not defined . Here , we identify IL-1β signaling and the NLRP3 inflammasome as key host restriction factors involved in viral control and CNS disease associated with WNV infection . Individuals presenting with acute WNV infection displayed elevated levels of IL-1β in their plasma over the course of infection , suggesting a role for IL-1β in WNV immunity . Indeed , we found that in a mouse model of infection , WNV induced the acute production of IL-1β in vivo , and that animals lacking the IL-1 receptor or components involved in inflammasome signaling complex exhibited increased susceptibility to WNV pathogenesis . This outcome associated with increased accumulation of virus within the CNS but not peripheral tissues and was further associated with altered kinetics and magnitude of inflammation , reduced quality of the effector CD8+ T cell response and reduced anti-viral activity within the CNS . Importantly , we found that WNV infection triggers production of IL-1β from cortical neurons . Furthermore , we found that IL-1β signaling synergizes with type I IFN to suppress WNV replication in neurons , thus implicating antiviral activity of IL-1β within neurons and control of virus replication within the CNS . Our studies thus define the NLRP3 inflammasome pathway and IL-1β signaling as key features controlling WNV infection and immunity in the CNS , and reveal a novel role for IL-1β in antiviral action that restricts virus replication in neurons .
West Nile virus ( WNV ) is a single stranded , positive sense RNA virus of the flaviviridae family , and is a prototypical Flavivirus related to Yellow fever virus , Tick borne encephalitis virus , Japanese encephalitis virus ( JEV ) and Dengue virus [1]–[2] , all of which are major public health threats . Among these viruses , WNV has emerged into the Western hemisphere and continues its spread through into North America [3] . WNV is normally maintained in mosquito and avian reservoirs , with infection of human and other animals occurring through contact with infected mosquitoes [4]–[5] . Infection is largely controlled acutely; however WNV can spread to the central nervous system ( CNS ) , leading to encephalitic disease and death [6]–[7] . Overall however , the immune processes within the CNS that serve to control WNV infection and pathogenesis are not well defined . WNV pathogenesis has been studied in murine models of infection to show that the virus initially replicates in epithelial cells and skin Langerhans dendritic cells ( DCs ) at the site of mosquito inoculation [8] . The virus then traffics to the draining lymph node , leading to secondary viremia and infection of the spleen where it can replicate in macrophage and DC subsets [5] , [9] . After amplification in peripheral tissues , WNV spreads to the CNS , where it replicates in neurons , causes neuronal destruction , and imparts inflammation leading to encephalitis that is comparable to human disease [5]–[7] . Both innate and adaptive immune defenses serve to control tissue tropism and initial spread of virus into to the CNS [10]–[13] , while T lymphocyte responses are involved in mediating clearance of virus following CNS entry [14]–[15] . In particular , CD8+ T cells are thought to be the main contributors to late CNS clearance of WNV through mechanisms involving IFN-γ , TNF-α and perforin [13]–[14] , [16] . The inflammatory response is a key component in protective immunity against WNV infection . However , this response must be kept in check to limit bystander destruction of both peripheral and CNS tissues . For example encephalitis , which is marked by inflammatory cell recruitment to the CNS , has been shown to be both protective as well as destructive to CNS tissue during WNV infection [17] . Recruitment of populations of peripheral CD45+ leukocytes into the CNS has been shown to be important for limiting WNV pathogenesis [18]–[20] . In contrast , in other studies CD45+ leukocytes were shown to enhance susceptibility to WNV , likely due to increased immune-pathology associated with inflammatory cell-mediated destruction of CNS tissue . Thus , while inflammation is required for clearance of WNV in the CNS , the timing and magnitude of this inflammatory response must be tightly regulated to avoid off target pathology . IL-1 signaling is involved in multiple aspects of the immune response to infection including immune regulation of inflammation , modulation of adaptive immune programs and direct antiviral control of pathogens [21]–[24] . These processes are driven by IL-1α and IL-1β which signal through the IL-1R1 ( IL-1Rα ) and MyD88 to drive downstream NF-κB activation and subsequent expression of genes whose products regulate the immune response to infection [21] , [25]–[26] . Activation of IL-1 requires two distinct signals , “signal 1” which drives mRNA expression in an NF-κB-dependent manner and “signal 2” which processes the cytokine to its functional form [27] . “Signal 2” processing of IL-1β to its active form is mediated by inflammasomes , signaling structures comprised of NOD-like receptors ( NLRs ) , adaptor molecules such as ASC and the effector , Caspase-1 [27]–[28] . In contrast , IL-1α is not processed by the inflammasome and is instead thought to processed and activated by other host protease pathways [29] suggesting that the majority of immune responses driven by inflammasome activation are mediated by IL-1β and not IL-1α . Several distinct inflammasomes have been described based upon their inclusion of a specific NLR or signaling-initiator molecule , including the NLRP1 , NLRC4 , NLRP3 , RIG-I and AIM2 [30] . Of these , the NLRP3 inflammasome has been the best characterized to mediate IL-1β secretion in response to RNA viruses in vitro and in vivo [24] , [31] . Inflammasome activation and IL-1β signaling are important for immunity against several viruses including Influenza A , hepatitis B , Sendai and vesicular stomatitis virus ( VSV ) [24] and drive host responses that regulate cellular infiltration to sites of infection [32]–[35] , adaptive immunity [23] , [36] and direct viral control in combination with other host factors such as IFN-α/β ( type I IFN ) , IFN-γ and TNF-α [21]–[22] , [37] . In the context of CNS infection , IL-1 signaling has been associated with both protection and enhancement of disease . The synergistic effects of IL-1β and TNF-α were associated with protection against encephalitis by the neurotropic virus HSV-1 [35] while IL-1β−/− animals showed increased pathogenesis and lethality to Sindbis virus [38]–[39] . Thus , IL-1 signaling likely functions in a context-dependent manner to control or exacerbate disease . Little is known about IL-1 signaling in immunity to flavivirus infection . Recently , JEV was shown to trigger IL-1β secretion from astrocytes and microglia [40] , and this was subsequently shown to be dependent on the NLRP3 inflammasome [41] . In addition , IL-1β expression was shown to be important for recruitment of DCs to the lymph node after WNV infection [8] . Thus , inflammasome signaling may integrate with multiple immune pathways to participate in the control of Flavivirus infection . In this study , we systemically examined the role of IL-1 signaling in WNV infection to show that IL-1β signaling driven by the NLRP3 inflammasome acts to mediate protective immunity against infection . We reveal a novel role for IL-1β in specifically limiting viral replication within the CNS . Mechanistically , IL-1β synergizes with type I IFN to control virus replication . Moreover , we found that the lack of viral control in Il-1r−/− mice correlated with defects in CNS inflammation , T lymphocyte effector activity , and neuropathology . Our observations link the production of IL-1β in the CNS to restriction of WNV replication in neurons and limitation of CNS disease and thus we conclude that the NLRP3 inflammasome and IL-1 signaling are important determinants of immune regulation that impart protective CNS inflammation and control of WNV infection .
In order to assess whether IL-1 was associated with human WNV infection , we examined cytokine expression in the plasma from individuals infected with WNV . Blood donors , testing positive for WNV RNA after routine blood screening were enrolled in a follow-up study to assess their plasma cytokine levels over a six-month period after their initial blood donation ( index ) . We observed that the levels of IFN-γ and TNF-α , immune factors important in immunity to WNV , [13] , [18] were enhanced in individuals infected with WNV and the expression of these factors was maintained for long periods of time in these individuals ( Figure S1A , B ) . In addition to these known host restriction factors , the levels of IL-1β were enhanced in the plasma of WNV+ individuals and displayed significant increase over time ( trend analysis ) at 7 , 21 , 42 , and 180 days post-index when compared to normal controls ( Cntrl ) ( Figure 1A; trend analysis ( p<0 . 0001 ) , inset ) . This was similar to the expression of the IL-1r antagonist ( IL-1ra ) , a natural regulator of IL-1β [25] , which is known to track with expression of the cytokine ( Figure 1B; trend analysis ( p = 0 . 003 ) , inset ) . In contrast , levels of IL-1α in the plasma were not altered by WNV infection at any time-point tested ( Figure S1C ) . These data are consistent with the expression of IFN-γ and TNF-α , and is in line with recent data demonstrating that WNV RNA persists at low levels out to 200 days post-index in whole blood of infected humans [42] and in vivo in peripheral tissues of mice [43] for extended periods of time . We found that WNV RNA levels decreased from day 7 to day 21 post-index ( Figure 1C ) . This correlated with the induction of IL-1β at day 7 , suggesting that initial viral load might drive the expression of the cytokine . In contrast , an inverse correlation was found between the levels of WNV viral load and the levels of IL-1β in plasma during the first six weeks post-index ( GEE estimate = −1 . 28 , p = 0 . 01 ) . Together , these data demonstrate that IL-1β expression but not IL-1α expression is associated with WNV infection in humans and indicates that WNV infection triggers the inflammasome signaling pathway to induce IL-1β during infection . To evaluate the role of IL-1β signaling in immunity against WNV infection , we assessed infection in a well characterized murine model of WNV subcutaneous ( s . c ) footpad inoculation [5] , [9] . C57BL/6-WT ( WT ) or mice deficient in their ability to respond to IL-1α or IL-1β , IL-1Rα chain−/− ( Il-1r−/− ) , were challenged with 102 plaque-forming units ( PFU ) of a virulent strain of WNV , WNV-TX [44] . Il-1r−/− mice were found to be highly susceptible to WNV infection ( Figure 2A ) displaying increased mortality ( 73 . 3% mortality compared to 23% in WT mice ) . WT mice presented with clinical signs of disease , including mild-paresis and weight loss , by day 6 post-infection ( p . i . ) with WNV . These responses peaked by day 10 p . i . and the majority of mice were fully recovered by day 16 p . i . ( Figures 2B , C ) . While Il-1r−/− mice displayed identical onset of clinical disease and weight loss as compared to WT mice , they presented with enhanced disease/hind limb dysfunction ( clinical scoring ) , weight loss and eventual death by day 10 p . i . ( Figures 2A , B , C ) , thus demonstrating an important role for this signaling pathway in preventing late stage WNV-mediated disease . IL-1β , but not IL-1α , requires processing via the NLRP3-inflammasome for its functional secretion and activity against multiple viruses [29] . Therefore we next examined whether NLRP3 signaling was responsible for the observed phenotype in Il-1r−/− animals infected with WNV . We found that mice lacking NLRP3 ( 58 . 3% mortality ) or its downstream effector , Caspase-1 ( 50% mortality ) , displayed increased susceptibility and clinical disease in response to WNV challenge ( Figure 2D , S2A–D ) . This outcome was in contrast to infection of mice lacking NLRC4 , which mediates a distinct inflammasome not associated with IL-1β processing in response to viral infection [24] . In these mice , the absence of NLRC4 did not influence susceptibility ( Figure 2E ) or clinical disease ( Figures S2E , F ) to WNV infection compared with WT controls . Thus , these observations are consistent with WNV infection triggering “signal 2” processing of IL-1β in vivo through the NLRP3 inflammasome to mediate immunity . In addition to inflammasome processing of IL-1β , we also examined the requirement for Myd88 , the adaptor protein that propagates both IL-1 and TLR signaling [26] . Similar to our observations in Il-1r−/− and NLRP3-inflammasome deficient animals , Myd88−/− animals were highly susceptible to WNV challenge ( 100% mortality ) ( Figure 2F ) . These results correlate with recent observations in mice deficient in MyD88 , which display enhanced mortality to WNV due to lack of CNS-specific control of the virus [19] and likely reflects the essential role of MyD88 in signaling the response to IL-1β [25]–[26] . Together , these data are consistent with a model in which IL-1β activation via the NLRP3 inflammasome and signaling via MyD88 act as the major pathways involved in mediating the Il-1r−/− phenotype to control late stage WNV disease . In order to more fully understand the contribution of IL-1 signaling in the in vivo response to WNV , we examined IL-1α and IL-1β expression in tissues known to be active sites of viral replication in WT mice [5] , [9] . WNV infection induced variable expression of both IL-1α and IL-1β in the draining popliteal lymph node ( DLN ) and spleen of infected mice ( Figures S3A , B ) however neither cytokine were detected in the serum of infected WT animals at any time-point tested ( data not shown ) . In contrast to these peripheral tissues , we found the most dramatic differences in IL-1α and IL-1β in the brains of infected animals . Here , IL-1β reached detectable levels by day 6 p . i . and was maintained at high levels through day 9 p . i . when the cytokine level peaked ( Figure 3D ) . This was in contrast to IL-1α which was expressed only at low levels throughout the course of infection ( Figure 3D ) suggesting that IL-1β may play the predominant role in immunity against WNV . We observed no difference in the magnitude of IL-1α ( data not shown ) or IL-1β ( Figure S3C ) levels in the CNS between WT and Il-1r−/− animals . We next assessed whether the tissue-specific expression of IL-1β influenced WNV replication within peripheral organs , blood , and the CNS . We observed no difference in the kinetics or magnitude of viral load detected between WT and Il-1r−/− deficient animals within the spleen or serum ( Figures 3B , C ) , and this was consistent with the lack of appreciable IL-1β at the peak of viral replication in these tissues ( Figures S2B , data not shown ) . In contrast , we observed a modest trend of increased viral load at day 2 post infection in the DLN ( Figure 3A ) , suggesting a role for IL-1β signaling in immunity to WNV at early time-points . Despite only minimal differences in viral load in peripheral organs , viral load in the brains of Il-1r−/− mice was increased when compared to WT mice as early as day 8 p . i . and this persisted through day 10 p . i . ( Figure 3E ) . A similar enhancement of viral load was observed in the brains of MyD88 and NLRP3-deficient animals ( Figures S4A , B ) , as well as , in day 10 spinal cords of all IL-1 signaling-deficient animals ( Figures S4C ) . The difference in viral control were not due to earlier entry of virus in the CNS as virus was first detected in the CNS at day 6 p . i . with similar magnitude of viral load in both strains ( Figure 3E ) . Instead , the initial differences in viral control occurred between day 7 and 8 p . i . and correlated to a time-point in which IL-1β was detected at high levels in WT mice ( Figure 3D , E ) . Together , these data suggest NLRP3 inflammasome activation of IL-1β and the subsequent actions of IL-1β operate to limit the replication and/or spread of WNV within the CNS . Type I interferon ( IFN ) signaling has been shown to contribute to control of tissue tropism and CNS control of WNV [9] , [11]–[12] . Therefore , we tested whether type I IFN could be involved in the lack of viral control in the DLN and CNS of inflammasome-deficient animals . We did not observe a significant difference in secretion of IFN-β in the serum or spleen of infected Il-1r−/− or WT animals ( data not shown ) . In contrast , we did observe a significant reduction in IFN-β expression in the DLN at day 2 p . i . in Il-1r−/− mice as compared to their WT counterparts ( Figure S3D ) . This difference correlated to a trend of increased viral load ( Figure 3A ) but did not appreciably impact overall peripheral virus replication ( Figures 3B , C ) . In contrast to peripheral tissues , we observed differential expression of IFN-β within the CNS between WT and Il-1r−/− animals . WT mice displayed early IFN-β expression within the CNS with peak levels at day 7 p . i . ( Figure 3F ) . This was consistent with the peak of viral load in these mice suggesting a direct correlation between virus replication and type I IFN production . In contrast , Il-1r−/− animals showed a delay in expression of IFN-β , with levels tracking with maximal viral load and peaking at day 9 p . i . ( Figure 3F ) . Importantly , the magnitude of the peak of IFN-β expression was not significantly altered between WT and Il-1r−/− animals despite significantly higher viral loads in the absence of IL-1β signal ( Figures 3E , F ) . These observations suggest that sustained IL-1β signaling in the CNS is important in maintaining efficient activity and/or early type I IFN signaling that controls WNV infection . IL-1β signaling has been associated with various immune functions including regulation of cell recruitment and inflammation , modulation of adaptive immunity and direct anti-viral activity . Therefore we assessed these activities as possible mechanisms by which IL-1β mediated WNV control in the CNS . We first examined CNS infiltration of total CD45+ leukocytes as well as a subpopulation of CD45+CD11b+ cells ( a population which is comprised of macrophage dendritic cell and neutrophil subsets ) as these cell populations have been previously associated with immunity against WNV in the CNS [18]–[20] . Brains of WT or Il-1r−/− mice were harvested at day 6 , 7 , 8 and 10 p . i . with WNV and the kinetics of CD45+ leukocyte infiltration were assessed by flow cytometry . We observed minimal infiltration of CD45+ leukocytes in the brains of WT or Il-1r−/− mice at day 6 p . i . ( Figures 4C ) . However , by day 7 p . i . , the numbers of total cellular infiltrates , ( Figure 4B ) , as well as the frequency and total numbers of CD45+ leukocytes ( Figures S5A , 4C ) and CD11b+/CD45+ infiltrates ( Figures S5B , 4A , D ) was increased in WT animals . This was followed by a peak in accumulation of cell infiltrates at day 8 p . i . and subsequent reduction in cell numbers by day 10 p . i . ( Figures S5A , B , 4A–C ) which tracked with parallel kinetics of viral load in the CNS of WT mice ( Figure 3E ) . Conversely , Il-1r−/− mice displayed reduced numbers total cell infiltrates ( Figure 4B ) as well as frequency and total numbers of CD45+ leukocytes ( Figures S5A , 4C ) and CD11b+/CD45+ ( Figures S5B , 4A , D ) at day 7 p . i in the CNS . Furthermore , despite reaching levels of infiltrates comparable to WT mice at day 8 p . i . , Il-1r−/− animals showed a continued increase in immune cell infiltrates through day 10 p . i . , suggesting that the magnitude of inflammation was directly correlated to viral load ( Figure 3E ) in the CNS in these animals . Resting microglia express CD11b but are distinguished from activated microglia or infiltrating myeloid cells by lower levels of CD45 expression . We observed the numbers of resting microglia , ( CD11b+/CD45lo ) , were reduced in the CNS at early times ( day 6–7p . i . ) in WT and Il-1r−/− animals ( Figures 4E , S5C ) suggesting increased activation of a subset of microglia upon viral entry into the CNS in both strains of mice . However , while the numbers of non-activated microglial cells was restored to basal levels by day 10 p . i . in WT mice they remained predominantly active day 10 p . i . in Il-1r−/− animals further suggesting that lack of IL-1β signaling imposes a disruption in CNS inflammatory homeostasis during WNV infection ( Figures 4A , E , S5C ) . Pro-inflammatory cytokines ( TNF-α , IL-6 ) , and chemokines ( CCL5 , CCL2 ) which are involved in the recruitment of CD45+ leukocytes , were also enhanced in the CNS of Il-1r−/− animals at late time-points when compared to WT controls ( Figures 4F–I ) implying that the increase in these inflammatory mediators likely contributes to the increased inflammation within the CNS of Il-1r−/− mice . In contrast , IL-6 ( Figure 4F ) and CCL2 ( Figure 4I ) were expressed at comparably lower levels at day 7 p . i . in the CNS of Il-1r−/− animals and associated with reduced infiltration of peripheral inflammatory leukocytes . Interestingly we observed increased inflammatory responses in the CNS of NLRP3-deficient animals , which displayed high CNS viral load and enhancement of IL-6 , TNF-α and CCL5 levels after WNV infection ( Figures S5D–F ) . Together , these observations indicate that the NLRP3-inflammasome and IL-1β signaling act early during WNV infection to mediate efficient CNS recruitment of immune cells and control CNS viral load . Regulated inflammation in the brain is an important component of the immune clearance of neurotropic viral pathogens [17] . This process is consistent with the regulated CNS inflammation observed in WNV-infected WT mice ( peak inflammatory CNS response at day 8 which was reduced by day 10 p . i . ( Figure 4 ) . Thus , in the absence of IL-1β signaling , the enhanced inflammation observed in Il-1r−/− mice might actually be detrimental to the host . Indeed , hematoxylin and eosin ( H&E ) stained histological sections of brain tissue from Il-1r−/− animals revealed encephalitis at day 10 p . i . marked by perivascular cuffing and inflamed meninges ( Figure 5A; black arrows , compare top and bottom panels ) . Tissue damage was associated with multiple regions of the CNS and included edema and hemorrhage ( Figure 5A; Forebrain ) , mononuclear meningitis ( Figure 5A; meninges ) and neuronal dropout ( Figure 5A-Midbrain; white arrows ) We also observed enhanced macrophage staining ( MAC-2 ) throughout the CNS tissue of WNV-infected , Il-1r−/− , mice at day 10 p . i . ( Figure 5B ) . Increased accumulation of MAC-2+ cells was observed in the forebrain and hippocampus-thalamus but was most evident in the midbrain , where we observed a 22-fold increase in MAC-2 expression in Il-1r−/− compared to WT controls ( Figure 5B , C ) . This expression was most prominent in and around blood vessels ( Figure 5B; black arrows ) , and within the parenchyma of Il-1r−/− but not WT brain tissue sections ( Figure 5B , bottom panel ) . This pattern of staining was comparable to the regions of immune infiltrates identified by H&E staining ( Figure 5A ) and suggests that increased infiltration of macrophage subsets is associated with the tissue damage observed in the CNS of Il-1r−/− animals . Thus we conclude IL-1β-dependent control of WNV in the CNS regulates the magnitude of inflammation during acute infection to reduce tissue damage . CD8+ T cell responses are important for clearing WNV infection from the CNS [14]–[16] . We therefore assessed: 1 ) total Ag-specific cell accumulation , 2 ) cytokine secretion properties and 3 ) cytolytic properties of CD8+ T cells within the CNS of WT and Il-1r−/− mice . Similar to infiltrating leukocytes , the initial entry of total CD8+ ( Figures 6A ) as well as WNV-NS4b-restricted ( antigen-specific ) T cells ( Figures 6B ) into the CNS was delayed in Il-1r−/− animals when compared to WT mice . However , by day 10 p . i . total CD8+ ( Figure 6A ) , CD4+ ( data not shown ) and antigen-specific CD8+ T cells ( Figure 6B ) , were enhanced in Il-1r−/− animals , further demonstrating a breakdown in the regulation of inflammation . Interestingly , although the total number of antigen-specific cells was increased in the absence of IL-1β signaling , the frequency of these cells within the CD8+ T cell pool was reduced at each time-point tested compared to wild-type mice ( Figure 6C ) , thus suggesting that effector activity in the CNS might be altered in these mice . In order to test this , total cells were recovered from the CNS at day 8 and day 10 p . i . and stimulated ex vivo with the immunodominant T cell epitope peptide-WNV-NS4b ( NS4b ) . We did not observe any differences between Il-1r−/− and WT cells in their frequency of cytokine production at day 8 p . i . ( data not shown ) . However , by day 10 p . i . , the frequency of TNF-α+/IFN-γ+ double positive and TNF-α+ , single cytokine producing cells were significantly lower in Il-1r−/− cells when compared to WT infected mice ( Figures 6D , E ) . In contrast , the frequency of IFN-γ+ single cytokine expressing CD8+ T cells were comparable between the two genotypes , demonstrating an overall loss in multi-functionality but not complete dysfunction in Il-1r−/− CD8+ T cells ( Figures , D , E ) . In addition , restimulation of equal numbers of WT or Il-1r−/− total brain cells ( 2 . 5e5 ) with the NS4b peptide promoted significantly less IFN-γ production at both time-points tested ( Figure 6F ) consistent with the reduced frequency of antigen-specific cells at these time-points ( Figure 6C ) . Cytolytic activity was also found to be compromised in Il-1r−/− T cells , as defined by reduced frequency of cells expressing perforin and this was accompanied by a significant increase in granzyme B/perforin low cells by day 10 p . i . ( Figure 6H , I ) . Taken together these data serve to link dysregulated inflammation in the CNS of Il-1r−/− mice with defective antigen-specific CD8+ T cell effector cytokine and cytolytic activity in the CNS . Despite a requirement for IL-1β signaling in regulating the T lymphocyte response , humoral immunity remained relatively intact as we observed no differences in the levels of WNV-specific serum IgM and IgG or neutralizing activity of these antibodies between WT and Il-1r−/− deficient animals ( Table S1 ) . Thus , IL-1β signaling is important for maintaining proper T but not B lymphocyte effector activity during WNV infection . To determine whether IL-1β signaling acted directly within the CNS to control WNV replication , mice were challenged with a low dose of WNV-TX ( 5 PFU ) , via intracranial ( i . c . ) inoculation and assessed for viral load and cytokine responses within the CNS . Similar to our observations in peripheral challenge , Il-1r−/− mice showed a significant enhancement of viral load in the brain ( Figure 7A ) as well as spinal cord ( data not shown ) when compared to WT , i . c . infected , animals , suggesting that IL-1β signaling imparts CNS-intrinsic control of WNV replication . In agreement with this notion , brain tissue sections stained for WNV-antigen showed more widespread and increased intensity staining in Il-1r−/− when compared to those from WT animals ( Figure 7D , E ) . Staining of viral antigen was associated primarily in cortical , hippocampal and mid-brain neurons with sparse staining in the endothelium ( Figure 7D; black arrows indicate staining in endothelial cells ) demonstrating a distinct tropism for neuronal cells . Similar to peripherally challenged mice ( Figure 3F ) the expression of IFN-β was enhanced at day 4 p . i in Il-1r−/− animals ( Figure 7B ) . Furthermore , in WT mice , i . c . WNV infection triggered IL-1β production in the brain by day 2 p . i . and this was maintained through day 4 p . i . ( Figure 7C ) . Thus , these data indicate that CNS innate immune signaling and IL-1β production are triggered directly by WNV infection and reveal that IL-1β signaling is an essential component of CNS-intrinsic virus restriction . To determine how IL-1β signaling mediates CNS-intrinsic control of WNV , we examined WNV infection ex vivo in cortical neurons , a primary target cell for WNV replication within the CNS . While a direct antiviral role for IL-1β signaling in neurons has not yet been defined , a previous study demonstrated that neurons from Myd88−/− animals presented with increased viral load after WNV infection when compared to their WT counterparts [19] . Thus , we reasoned that Myd88-dependent IL-1β signaling might promote an antiviral state in these cells . Cortical neurons were prepared from WT and Il-1r−/− mice as previously described [45] and were purified to greater than 95% based on staining for the neuronal marker , NeuN ( data not shown ) . Cultures were infected with WNV ( MOI = 1 ) and single-step growth curve analysis and their host response to WNV infection was examined . Il-1r−/− cells showed significantly higher viral loads at 24 hr and 48 hr p . i . when compared to their WT controls ( Figure 8A ) . This increase was also observed in multi-step growth curve analysis after infection with a lower MOI ( 0 . 01 ) , although this was not maintained through 48 hrs ( Figure S6A ) . We found that WT neurons produced IL-1β as early as 12 hr p . i . after virus challenge and this persisted throughout the course of infection ( Figure 8B ) , thus suggesting that neurons might contribute in part to the total IL-1β response in the CNS . The production of IL-1β was detectable in Il-1r−/− cells but at generally lower levels than WT ( Figure 8B ) . Remarkably , we observed enhanced IFN-β production in Il-1r−/− neurons at both MOIs ( Figures 8C , S6B ) , however this only effective at reducing viral load after low MOI infection ( Figure 8A , S6A ) . These observations demonstrate that IL-1β signaling contributes to the control of WNV infection in cortical neurons and may operate to enhance the antiviral response mediated by type I IFN signaling . To determine whether IL-1β could impart suppression of WNV replication in cortical neurons , cells were pre-treated for 24 hrs with either media alone , or IL-1β ( 10 ng/ml ) , infected with WNV ( MOI = 1 ) and then assessed for viral load in the supernatant . IL-1β treatment of cells resulted in a reduction of detectable WNV at 24 hr ( 2 . 5 fold ) and 48 hr ( 1 . 7 fold ) p . i . compared to non-treated cells ( Figure 8D ) . This level of reduction was similar to the fold increase in viral titers observed in Il-1r−/− neurons ( Figure 8A; 24 hr , 2 . 3 fold , 48 hr , 2 . 1 fold ) thus demonstrating that IL-1β imparts a response that contributes to the control of WNV replication . In WNV-infected Il-1r−/− mice we consistently observed increased levels of type I IFN , either in whole tissue ( Figures 3F , 7B ) or from cortical neurons ( Figure 8C , S6B ) but this level was insufficient to control the viral load . Thus the actions of IL-1β might function to enhance the antiviral effect of type I IFN against WNV infection . To test this idea , we conducted experiments in which cortical neurons were either left untreated or pretreated for 24 hrs with IL-1β ( 10 ng/ml ) , IFN-β ( 100 IU/ml ) or both cytokines together , followed by WNV infection and assessment of viral load . Similar to our previous results , IL-1β treatment led to a 2 . 1-fold reduction in virus at 24 hr p . i while treatment of neurons with IFN-β reduced viral load by 13 . 5-fold at 24 hr p . i . , consistent with previous studies [11]–[12] ( Figure 8E ) . Remarkably , when neurons were pretreated with both IL-1β and IFN-β , we observed near complete control of WNV at 24 hr ( 1500-fold reduction of viral load compared to control; Figure 8E ) . Further , these results were prolonged as the fold reductions by each cytokine were maintained through 48 hrs p . i . ( Figure S6C ) . We also observed that pre-treatment of neurons with both IL-1β and IFN-β in the context of WNV infection led to an increase in mRNA ( Figure S6D ) and protein expression ( Figure 8F ) of IFN-β and interferon stimulated genes ( ISGs ) , STAT1 , IFIT1 , IFIT2 and IFIT3 , molecules known to participate in control of WNV [46]–[47] . This response was comparable to induction by type I IFN in the absence of infection ( Figure 8F ) , suggesting that despite the known ability of WNV to antagonize these responses [44] , [48] , the synergy of IL-1β and type I IFN might act to overcome this antagonism and promote increased viral control . The induction of ISGs was not observed with IL-1β treatment alone ( Figure 8F ) , demonstrating that combined signals induced by viral infection , type I IFN and IL-1β were required for the synergistic activation of these antiviral genes . Therefore we conclude that IL-1β synergizes with type I IFN to enhance antiviral gene programs that control WNV infection in cortical neurons and thus , IL-1β acts as a key host restriction factor in the control of WNV infection .
Our observations support a model in which IL-1β signaling functions as a host restriction factor to control WNV replication within the CNS . WNV restriction by IL-1β occurs in a manner dependent on the ability of IL-1β to synergize with type I IFN to promote a robust antiviral program in neurons . Further , the capability for IL-1β signaling to control viral load is essential for regulating protective CNS inflammation to control WNV disease , as a lack of IL-1β signaling associates with a breakdown of immunity marked by rapid and uncontrolled viral spread through the CNS , hyper-active inflammatory response and defective CD8+ T lymphocyte effector activity . Thus , IL-1β is fundamental for the control of WNV infection and immunity . To date , three distinct inflammasomes have been described to participate in IL-1β activation in response to viral infection . These include the NLRP3 [32] , [34] , [36] , [49] , RIG-I [50] and AIM2 [51]–[53] inflammasomes . While AIM2 is responsible for activation to DNA viruses , both NLRP3 and RIG-I have been associated with IL-1β activation in response to RNA viruses ( reviewed in [24] ) . We found that the defects in immunity observed in Il-1r−/− mice infected with WNV were pheno-copied in mice deficient in NLRP3 or Caspase-1 suggesting that the NLRP3-inflammasome acts as the predominant pathway for triggering IL-1β production in vivo during WNV infection . This is not surprising as NLRP3 activation of IL-1β has been shown to occur in response to multiple RNA and DNA viruses including influenza , Sendai and adenoviruses [24] as well as JEV , a WNV related Flavivirus [41] . Further , our observations that NLRP3 signaling is important for limiting lethality and tissue destruction during WNV infection in vivo is consistent with models of influenza infection which have also shown a requirement for NLRP3 and IL-1β signaling in protective immunity against the virus [32] , [34] , [36] as well as in limiting collagen deposition and necrosis of lung tissue [34] and thus demonstrate a broad range for NLRP3 signaling in immunity to virus infection . While NLRP3 and Caspase-1 deficient animals succumbed to WNV infection with similar kinetics and frequency we did observe a trend for increased virulence when compared to Il-1r−/− animals ( Figure 2A , D ) . While this maps the majority of IL-1 signaling to NLRP3 activation , it is possible that other pathways might contribute to this response . As RIG-I has recently been shown to mediate both the activation of “signal 1” as well as “signal 2” in response to vesicular stomatitis virus ( VSV ) in an NLRP3-independent manner [50] and RIG-I [9] , [44] , [54] plays important roles in sensing and triggering of innate immune pathways against WNV virus , it is possible that this pathway may contribute in addition to NLRP3 in the full activation of IL-1β activation during WNV infection in vivo . The contribution of IL-1 signaling to protective immunity against virus infections has largely been attributed to its ability to drive chemokine signaling pathways that recruit immune cells to sites of viral replication [38] , [39] , [40] . Although CNS recruitment of CD45+ monocytes and T lymphocytes was largely increased during WNV infection , in the absence of IL-1 signaling , we did observe a reduced frequency and total number of these cells at day 7 post infection ( Figure 4 ) and this is consistent with previous studies that showed that IL-1β was important for optimal cellular recruitment to the DLN after WNV infection [8] . Therefore , it is possible that this reduction in initial leukocyte and lymphocyte recruitment is sufficient to allow for enough virus to seed infection in neurons and increase the likelihood of CNS spread . Interestingly , despite early differences in cellular recruitment and inflammation in the CNS , by later time-points , we observed a dramatic enhancement in inflammation in Il-1r−/− animals ( Figure 4 ) . This is in contrast to recent studies examining WNV infection in Myd88 [19] and TLR7 [20] deficient animals which show dramatic reduction in cellular infiltrates and inflammation within the CNS . Thus , it is likely , that while IL-1β signaling contributes to cellular recruitment , TLR signaling via MyD88 might play a dominant role in maintaining these responses over time . As CD8+ T cells represent a key component in late CNS control of WNV , it is interesting that IL-1 signaling defects were associated with decreased effector activity of these cells . Our data suggest that increased viral load influence this defect directly by driving increased inflammatory cytokine responses and a reduced frequency of antigen-specific cells to total CD8+ cells . However , in addition , it is also possible that IL-1β signaling itself is required to directly promote the optimal T cell effector response . This outcome is similar to observations of influenza infection in which IL-1R and NLRP3-inflammasome deficient animals display defective CD4+ and CD8+ T lymphocyte responses in the absence of increased inflammation [36] . Furthermore , MyD88 signaling was found to act in a T cell intrinsic manner to control both proliferation and acquisition of effector responses during LCMV [55]–[56] and vaccinia virus infection [57]–[58] , while direct IL-1 signaling in has been shown to influence the development of multiple T lymphocyte effector populations under multiple experimental conditions [23] . Our data are in agreement with a role for IL-1β signaling in driving T cell effector activity during viral infection . Such action might occur against WNV infection by either of two mechanisms: First , IL-1β signaling could indirectly limit inflammation and overstimulation of cells in the CNS that otherwise occurs under conditions of uncontrolled virus replication and dissemination [9] , [19]–[20] . Secondly , IL-1β signaling could directly drive a response , likely in a Myd88-dependent manner , to positively regulate immune cell effector activity against WNV . We observed a significant reduction in type I IFN in the DLN at day 2 p . i . in Il-1r−/− mice that correlated with a modest increase in viral load ( Figures S3D , 3A ) . This result is notable because the observation occurred at a time-point that is associated with the accumulation of macrophages and DC subsets trafficking into the DLN from the site of primary infection , wherein type I IFN signaling is associated with control of the virus in these cell types [9] . We have also observed reduced type I IFN responses and increased viral replication in primary Il-1r−/− macrophages and DCs infected with WNV in vitro ( Ramos , HJ; unpublished observations ) . Furthermore , it has been proposed that viral entry to the CNS could in part be mediated by a “Trojan horse” mechanism in which immune cells harboring WNV infiltrate into the CNS and seed viral infection in neurons [5] . Together , these observations raise the possibility that the lack of type I IFN in the DLN in Il-1r−/− mice is associated with decreased control of virus within macrophages and DCs , which then infiltrate and seed the CNS with virus in an enhanced manner that promotes the robust inflammatory disease observed in Il-1r−/− mice . In this sense IL-1β would serve to control virus levels in infected inflammatory cells and thereby restrict virus seeding into the CNS that might occur through infiltration of infected cells . Type I IFN and to a lesser extent , IFN-γ , and TNF-α , have also been shown to mediate anti-viral responses to WNV [13] , [18] and our results now implicate IL-1β as a component of innate antiviral signaling and response against WNV infection . In support of this , a protective role for IL-1β in combination with TNF-α was shown to be important to the control of hepatitis B virus [21]–[22] . In addition , in vitro studies in hepatocyte cell lines revealed that this effect was mediated by the ability of IL-1β to augment type I and type II IFNs antiviral activities in mechanisms dependent on STAT-1 and P38 MAP kinase [21] . This phenomenon of IL-1β synergy has also been observed in epithelial cell infection with VSV [37] . Therefore , we propose that in the context of WNV infection , IL-1 acts synergistically with type I IFN , and possibly type II IFN and/or TNF-α to mediate an antiviral program to control WNV in the CNS . We found that IL-1β treatment of WT cortical neurons ex vivo resulted in reduced levels of detectable virus in the supernatants of infected neurons however , this response was not sufficient by itself to fully inhibit the virus . Interestingly , the viral suppression we observed occurred between 24 and 48 hrs of treatment suggesting that IL-1β signals a response in neurons that restricts virus amplification rather than initial infection . This kinetics are suggestive of a mechanism by which products of IL-1β -responsive genes serve to impart control of WNV replication , thus suppressing virus spread within the CNS . Indeed , our data demonstrate that IL-1β acts synergistically in the innate antiviral response along with IFNs and possibly other cytokines to ultimately control virus replication . In line with this notion , we observed that IL-1β and type I IFN synergized to enhance the expression of ISGs such as the IFIT family members IFIT1 , 2 , 3 . This is of interest as recent studies have implicated these antiviral effectors in the control of CNS specific viruses such as VSV [59] . Furthermore , recent data had identified IFITs as important in anti-viral control of WNV [46]–[47] and this is dependent on their ability to block the viral replication cycle [46] . Therefore , IL-1β might control WNV through its ability to modulate ISGs that impart antiviral actions against WNV replication . Control of WNV replication in the CNS is paramount for protection against disease . Our study shows that IL-1β production and signaling are important for protective immunity against WNV suggesting that the NLRP3-inflammasome and IL-1 signaling also likely impact immunity to other Flaviviruses . It has been observed that dengue , yellow fever ( YFV ) , St . Louis encephalitis ( SLEV ) and WNV all trigger IL-1β expression from populations of myeloid derived cells in vitro , while YFV , SLEV and WNV have each been linked to suppression of IL-1β signaling at various levels in vitro [60]–[62] . Taken together , these observations along with those made in this study identify IL-1β as a key host restriction factor in immunity against Flavivirus infection .
All animal experiments were approved by the University of Washington Institutional Animal Care and Use Committee ( IACUC ) committee guidelines ( protocol number: 4158-01 ) and follow the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . Mouse infections and manipulations were performed under anesthesia of ketamine and xylazine , and every effort was made to limit suffering . All human subjects provided written-informed consent under a University of California , San Francisco Institutional Review Board approved protocol . WNV isolate , TX 2002-HC ( WNV-TX02 ) , was titered by a standard plaque assay on BHK-21 cells and working stocks of WNV-TX were generated as previously described [9] . BHK-21 cells were cultured in Dulbecco's modified Eagle medium ( DMEM ) supplemented with 10% fetal bovine serum ( FBS ) , HEPES , L-glutamine , sodium pyruvate , antibiotic-antimycotic solution , and nonessential amino acids . The 43 WNV+ subjects included in this study were enrolled in 2009 and 2010 by Blood Systems Research Institute ( BSRI ) through the United Blood Services network of blood centers . Blood donors who tested positive for WNV RNA by routine donation screening using the WNV Procleix Transcription Mediated Amplification ( TMA ) assay were asked to return to their local blood donation center for enrollment after informed consent was completed under a University of California , San Francisco Institutional Review Board approved protocol . Upon enrollment , blood donors agreed to return to their blood center for subsequent follow up visits . Infection was confirmed using follow-up samples showing sero-conversion to anti-WNV IgM . Samples were collected at regional blood centers and were shipped by overnight courier to BSRI . Blood was processed within 24 hours and plasma aliquots were frozen immediately for long term storage . The WNV+ subjects were 58% male with an average age of 51 years old . The control subjects ( Cntrl . ) used in this study were 21 BSRI staff members who consented to donate blood for this study and they were 43% male with an average age of 48 years old . Quantification of WNV viral load in follow-up human plasma specimens was assayed by real-time reverse transcription-polymerase chain reaction as previously described [42] . C57BL/6 ( WT ) and IL-1Rα deficient mice were purchased from Jackson Laboratories , Bar Harbor , ME . NLRP3 [63] , Caspase-1 [64] and NLRC4 [65] were generously provided by Dr . Vishva Dixit ( Genentech , San Francisco , CA ) , Dr . Chris Wilson ( University of Washington , Seattle , WA ) and Dr . Alan Aderem ( Seattle Biomed , Seattle , WA ) . All mice were genotyped for positive identification and were bred in specific pathogen-free conditions in the animal facility at the University of Washington . Experiments were performed in accordance with the University of Washington Institutional Animal Care and Use Committee guidelines . Age-matched six to ten week old mice were inoculated subcutaneously ( s . c . ) in the rear footpad with 100 PFU of WNV-TX 02 in a 10 µl inoculum diluted in phosphate buffered saline ( PBS ) supplemented with 1% heat-inactivated FBS . Mice were monitored daily for morbidity and mortality . For clinical scoring , infected mice were monitored daily for signs of hind limb dysfunction and paresis . Mice were scored using the following scale from 1–6: 1 , ruffled fur/lethargic , no paresis; 2 , very mild to mild paresis; 3 , frank paresis involving at least one hind limb and/or conjunctivitis; 4 , severe paresis; 5 , true paresis; 6 , moribund . To determine in vivo viral burden , s . c infected mice were euthanized , and perfused with 20–30 ml of PBS to remove blood from tissues . Whole tissue were removed , weighed , and homogenized in 500 µl ( spleen , brain ) or 200 µl ( spinal cord ) of PBS containing 1% heat-inactivated FBS using a Precellys 24 at 1500 RPM for 20 seconds ( Bertin Technologies , France ) . Sample homogenates were then titered by plaque assay on BHK cells as previously described [9] . For analysis of viral load within the draining lymph nodes ( DLN ) , the popliteal DLN was harvested and homogenized as described above in 350 µl of RNA extraction buffer ( RLT , Qiagen ) , and total RNA was extracted using an RNeasy kit ( Qiagen ) . DNase treated RNA ( Qiagen ) was then reversed transcribed to cDNA using a 1∶1 mixture of random hexamers and oligodT primers with the iScript select cDNA synthesis kit ( Biorad ) . WNV-specific RNA copy number was measured by single-step Real Time-quantitative PCR ( qRT-PCR ) using Taqman technology via specific primer sets and probes as previously described [9] . For serum samples , viral RNA was isolated from 50 µl of serum from mock or WNV-TX infected samples using the QIamp Viral RNA isolation kit ( Qiagen ) . Isolated viral RNA was then subjected to cDNA synthesis and qRT-PCR for assessment of WNV copy number as described above . Whole brain tissue was isolated from mice perfused as described above . Tissue was lysed in 1 ml per brain RIPA buffer containing a cocktail of protease and phosphatase inhibitors ( Sigma ) . Lysis was facilitated by homogenization using the Precellys ( Bertin Technologies , France ) as described above . Protein extracts ( 20 µg ) were analyzed by immunoblotting . The following primary antibodies were used to probe blots: goat anti-WNV NS3 ( R&D systems ) ; rabbit anti-ISG54 ( IFIT2 ) and rabbit anti-ISG49 ( IFIT3 ) , kindly provided by Dr . G . Sen; mouse anti-tubulin ( Sigma ) and rabbit anti-STAT1 , ( Cell Signaling ) . Secondary antibodies included peroxidase-conjugated goat anti-rabbit , donkey anti-goat and goat anti-mouse ( Jackson Immunoresearch ) . Total RNA was extracted from tissues and cDNA was generated as described above . Cytokine expression was then assessed by one-step SYBR Green RT-qPCR using an ABI 7800 machine . Similarly RNA was extracted from neurons using 350 µl/sample buffer RLT as described for DLN samples . Specific primer sets for GAPDH , IL-1α , IL-1β , IFNβ , TNFα , and IL-6 are described as follows: mGAPDH forward: CAACTACATGGTCTACATGTTC , mGAPDH reverse: CTCGCTCCTGGAAGATG; mIFNβ forward: GGAGATGACGGAGAAGATGC mIFNβ reverse: CCCAGTGCTGGAGAAATTGT; mIL1α forward:TCTATGATGCAAGCTATGGCT , mIL-1α reverse: CGGCTCTCCTTGAAGGTGA; mIL1β forward: ACGGACCCCAAAAGATGAAG , mIL1β forward: CACGGGAAAGACACAGGTAG; mIL6 forward: GTTCTCTGGGAAATCGTGGA , mIL6 reverse: TGTACTCCAGGTAGCTATGG; mTNFα forward: CATCTTCTCAAAATTCGAGTGACAA , mTNFα reverse:TGGGAGTAGACAAGGTACAACCC; mIFIT1 , mIFIT2 and mIFIT3 were purchases as pre-mixed SuperArray primer sets ( Qiagen ) . WNV-specific IgM and IgG , levels were determined by an ELISA using purified recombinant E protein as previously described [66] . The neutralization titer of serum antibody was determined using the plaque reduction neutralization assay as previously described [67] . The dilution at which 50% of plaques were neutralized was determined by comparing the number of plaques formed from WNV-infected sera samples to mock infected sera samples . Mock-infected or WNV-infected mice were sacrificed by exsanguination and perfused with PBS-4% paraformaldehyde , pH 7 . 3 . Brains were embedded in paraffin and 4–6 µm sections were prepared and stained with hematoxylin and eosin ( H&E ) or immunohistochemistry by the UW Histology and Imaging Core . H&E-stained sections were evaluated for viral-induced neuropathology . Antibodies for immunohistochemical detection included for for macrophages , rat anti mouse MAC-2 , Clone M3/38 , ( Cedarlane , Cat No . CL8942AP ) ; and for West Nile virus , rabbit anti-WNV , clone 7H2 + rabbit anti-WNV polyclonal ( BioReliance , Cat No . 81-002 , 81-015 ) . Immunohistochemical staining was performed on a Leica Bond Automated Immunostainer with Leica Refine ( DAB ) detection and hematoxylin counterstain . Images were captured using a Nikon 80i Eclipse microscope with a digital camera with NIS Elements Basic research imaging software . Quantitation for MAC-2 and WNV was performed with the Visiopharm histoinformatics software ( Visiopharm ) on representative regions of two sets of brain sections and is representative of the ratio of specific staining to the total area of the tissue . . For quantification of WNV and MAC-2 , slides were scanned in Brightfield at a 20× objective using the Nanozoomer Digital Pathology slide scanner ( Hamamatsu; Bridgewater , New Jersey ) . The digital images were then imported into Visiopharm software ( Hoersholm , Denmark ) for analysis . Using the Visiomorph Digital Pathology module , regions of interest ( ROIs ) were applied around the relevant areas on each slide and consisted of one rectangular ROI within each of three areas—the forebrain , midbrain , and thalamus—on each section . The images were processed in batch using these configurations to generate the desired outputs ( areas of staining and normal tissue , in square microns ) , from which the percent of WNV or MAC2 staining was calculated . Splenocytes were isolated by grinding on frosted glass slides , washed counted , and re-suspended in RPMI 1640 containing 10% FBS before cell surface staining or in vitro stimulation . For staining , cells were washed once in PBS and once in PBS+0 . 5% BSA ( FACS wash ) in a 96 well plate format and then stained in 50 µl FACs wash plus directly-conjugated antibodies specific to CD8 , CD4 , and CD3 ( Biolegend ) . WNV-specific CD8+ T cells were identified using a Db-restricted NS4b peptide tetramer directly conjugated to either Phycoerythrin ( PE ) or allophycocyanin ( APC ) . For intracellular cytokine staining , cells were stimulated with 1 µM of the immune-dominant peptide NS4b ( SSVWNATTA ) for 4 hrs at 37°C in the presence of golgi-stop ( BD-PharMingen ) . After stimulation , cells were washed twice in FACS wash and stained for cell surface markers followed by permeabilization-fixation using the Cytofix-Cytoperm Kit ( BD-PharMingen ) and stained with a Pacific Blue-conjugated IFN-γ and FITC-conjugated TNF-α antibody ( eBiosciences ) or FITC-conjugated perforin and PE-CY7-conjugated granzyme B at 4°C for 30 min , washed and analyzed by flow cytometry . Flow cytometry was performed on a BD LSRII machine using BD FACSDiva software . Cell analysis was performed on FlowJo ( v . 8 . 7 . 2 ) software . For isolation of CNS immune cells , euthanized mice were perfused with 20–30 ml of PBS to remove residual intravascular leukocytes . Brains were isolated and minced in RPMI media , rigorously triturated , and digested with Liberase ( Roche ) and type I DNase in serum-free RPMI media at 37°C for 1 hr . Immune cells were isolated after gradient centrifugation over 25% Percoll followed by a wash and secondary centrifugation over a 30% Percoll gradient . Cell pellets were isolated and washed twice and counted . Cells were resuspended in 50 µl FACS wash and stained for surface expression of CD4 , CD8 , CD33 , CD11b and CD45 ( Biolegend ) . For intracellular staining , cells were stimulated with 1 µM of NS4b peptide ( SSVWNATTA ) and stained as described above for IFN-γ , TNF-α , and granzyme B and perforin . Cells were analyzed as described above for splenocytes . Mice were euthanized and blood was collected for serum preparation via exsanguination . Serum was isolated by separating in microtainer ( BD Biosciences ) at 10 , 000 rpm for 8 minutes . Brain , spleen , and lymph nodes were isolated and weighed after perfusion with 20 ml of PBS and homogenized using the Precellys ( Bertin Technologies , France ) as described above in 1 ml of RIPA buffer . Protein concentration was assessed by Bradford colorimetric assay ( Biorad ) and 200 µg of total protein were loaded for IL-1β ( Biolegend ) , IL-1α ( Biolegend ) and IFNβ ELISA ( PBL Biomedical Laboratories ) via the manufactures protocol . Concentration of cytokine was then normalized to the weight of total tissue . For Luminex , 12 . 5 µl of tissue lysate or serum was run on an 11-plex assay ( Miltenyi Biosciences ) followed by analysis on a Bioplex 200 ( Biorad ) . Concentration of cytokine was then normalized to total weight of tissue . For human plasma cytokine analysis , plasma samples were assayed for IL-1β ( 0 . 06 pg/ml ) and TNF-α ( 0 . 05 pg/ml ) using the High Sensitivity Human Cytokine kit ( Millipore , Billerica , MA , USA ) , which has a minimum detectable concentration as indicated above and for TNF-α , and for IFN-γ ( 0 . 1 pg/ml ) , IFN-α2 ( 24 . 5 pg/ml ) IL-1ra ( 2 . 9 pg/ml ) , andIL-1α ( 3 . 5 pg/ml ) using the Human Cytokine/Chemokine kit ( Millipore ) which has minimum detectable concentrations as indicated above . Plasma samples were assayed following the manufacturer's protocols . Standard curves were run in duplicate , and samples were tested in duplicate . Acquisition was done on a Labscan 100 analyzer ( Luminex ) using Bio-Plex manager 6 . 1 software ( Bio-Rad ) . For in vivo viral burden analysis Kaplan-Meier survival curves were analyzed by the log-rank test . For all in vitro studies statistical analysis was performed via unpaired two-tailed student T-test . For in vivo viral burden and immune cell analysis experiments statistical significance was calculated using the Mann-Whitney test . A p-value≤0 . 05 was considered significant . All data were analyzed using Prism software ( GraphPad Prism5 ) . For human patient studies , cytokine levels were compared between WNV+ subjects and - normal controls at each time-point using one-way analysis of variance ( ANOVA ) . Trend analyses were used to evaluate whether a statistically significant increase or decrease of cytokine levels was observed in the time post-index within the WNV+ subjects; to detect monotonously increasing or decreasing trend of cytokine quantities over time , Page's trend tests were applied on each cytokine using the R Package ‘concord’ . A generalized linear model with repeated measures ( Proc genmod ( GEE ) SAS 9 . 2 ) was used to analyze in plasma the correlation between WNV viral load and levels of cytokines/chemokines measured at one , three , and six weeks post-index donation . Statistical significance was defined as a p-value≤0 . 05 .
|
Since its introduction into North America in 1999 , West Nile virus ( WNV ) has emerged as a leading cause of viral encephalitic disease in the United States . While low level inflammation is important for clearance of WNV , high levels of inflammation are associated with increased disease . The goal of this study was to identify host signaling pathways that control the balance of inflammation and protective immunity to WNV . Using a mouse model of infection , we identified a central nervous system ( CNS ) -intrinsic requirement for the NLRP3 inflammasome and IL-1β signaling in limiting WNV associated disease within the CNS . First , IL-1β signaling was essential for regulating the magnitude and kinetics of inflammation within CNS . Secondly , the absence of IL-1β signaling disrupted the quality of the effector T lymphocyte response against the virus . Finally , these dysregulated immune responses were linked to a direct ability for IL-1β signaling to synergize with type I IFN signaling and limit virus replication within cortical neurons , key target cells of WNV infection within the CNS . Together this study identifies the NLRP3 inflammasome and IL-1β signaling as key restriction factors that act to regulate viral load and the quality of inflammatory responses within the CNS to impart protective immunity against WNV infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"inflammation",
"immunity",
"virology",
"immunology",
"biology",
"microbiology"
] |
2012
|
IL-1β Signaling Promotes CNS-Intrinsic Immune Control of West Nile Virus Infection
|
Growth rate and yield are fundamental features of microbial growth . However , we lack a mechanistic and quantitative understanding of the rate-yield relationship . Studies pairing computational predictions with experiments have shown the importance of maintenance energy and proteome allocation in explaining rate-yield tradeoffs and overflow metabolism . Recently , adaptive evolution experiments of Escherichia coli reveal a phenotypic diversity beyond what has been explained using simple models of growth rate versus yield . Here , we identify a two-dimensional rate-yield tradeoff in adapted E . coli strains where the dimensions are ( A ) a tradeoff between growth rate and yield and ( B ) a tradeoff between substrate ( glucose ) uptake rate and growth yield . We employ a multi-scale modeling approach , combining a previously reported coarse-grained small-scale proteome allocation model with a fine-grained genome-scale model of metabolism and gene expression ( ME-model ) , to develop a quantitative description of the full rate-yield relationship for E . coli K-12 MG1655 . The multi-scale analysis resolves the complexity of ME-model which hindered its practical use in proteome complexity analysis , and provides a mechanistic explanation of the two-dimensional tradeoff . Further , the analysis identifies modifications to the P/O ratio and the flux allocation between glycolysis and pentose phosphate pathway ( PPP ) as potential mechanisms that enable the tradeoff between glucose uptake rate and growth yield . Thus , the rate-yield tradeoffs that govern microbial adaptation to new environments are more complex than previously reported , and they can be understood in mechanistic detail using a multi-scale modeling approach .
Growth rate and yield are basic features of microbial life that are widely implicated in cell fitness , adaptation , and evolution [1] . The specific growth rate , μ , represents the number of doublings of bacterial density per unit time [10] . The yield , Y , is the ratio between μ and the rate of substrate consumption [10 , 11] . The mathematical relation between μ and Y can be written as: Y = μ M s u b s t r a t e · q s u b s t r a t e ( 1 ) where Msubstrate is the molecular weight of the substrate and qsubstrate is the substrate uptake rate . In the context of modeling the phenotypic relation between substrate uptake , metabolism , and biomass growth , there is a great interest in developing quantitative descriptions of the relationship between μ and Y . The wide-ranging measurements of μ and Y ( Fig 1A ) across microbial communities and environments raised interest into the exact nature of the μ–Y relationship [1] . At low μ , positive correlations between μ and Y have been observed [8] , and these can be explained by non-growth-associated cell maintenance requirements that make slow growth inefficient [11] . At high μ , negative correlations between μ and Y are observed [5] , and for E . coli , this can be explained by a tradeoff between metabolic efficiency and enzymatic efficiency that lead to decreasing Y at high μ [12 , 13] . In particular , E . coli exhibits a tradeoff between respiration , which has higher energy yield per carbon substrate ( more metabolically-efficient ) , and acetate fermentation , which requires less enzyme per carbon substrate ( more proteome-efficient ) . Therefore , acetate excretion increases linearly with μ above a threshold growth rate ( green and blue lines in Fig 1B ) [5] . [1] summarized these observations where positive μ–Y correlation at low μ and negative μ–Y correlation at high μ are different parts of a bell-shaped μ–Y curve ( Fig 1A ) . However , recent experiments suggest that adaptation to new environments can modify the bell-shaped μ–Y tradeoff [3 , 14 , 15] . Microorganisms rapidly adapting to environmental niches [17 , 18] , and adaptation mechanisms can be studied directly through adaptive laboratory evolution ( ALE ) [19] . When strains are adapted through ALE for growth in a liquid minimal medium , they achieve higher μ compared to the wild-type ( Fig 1A ) , ALE-adapted strains have been shown to rapidly acquire regulatory mutations that modify proteome allocation , but they do not acquire new metabolic capabilities within the time frame of reported short-term ( 4 to 8 weeks ) adaptation experiments [3 , 15 , 20] . By analyzing ALE-adapted strains , we can reveal the strategies that allow cells to optimize their proteome allocation for growth in an environmental niche , subject to the constraints of their metabolic capabilities ( i . e . their repertoire of pathways ) and constraints on the kinetic efficiencies of their enzymes [3 , 20 , 21] . Contrary to the negative μ–Y relationship at high μ observed in wildtype strains , the endpoint strains of ALE experiments of E . coli selected for high μ in a minimal medium do not have μ–Y data points aligning on the bell-shape curve in Fig 1A , but reveal an uncorrelated relationship between μ and Y [3 , 15] . In these experiments , strains exhibited little variation in μ but high variation in Y and acetate excretion rate qac . Previous studies similarly reported that overflow metabolism can be nearly eliminated through genetic engineering without any effect on growth rate in E . coli [2 , 4] . Thus , the negative μ–Y correlation at high growth rates does not appear to be a fundamental constraint on fast-growing cells . A mechanistic model of the full μ–Y relationship must be able to reconcile the bell-shaped curve observed for individual strains with the uncorrelated μ–Y phenotypes seen in ALE-adapted strains ( Fig 1A ) . A number of theoretical and computational models have been developed to describe rate-yield tradeoffs . For the positive μ–Y correlation , maintenance requirements can be quantitatively described using algebraic growth laws [8 , 11] . The maintenance requirement has been modeled as non-growth associated maintenance ( NGAM ) in the genome-scale models ( GEMs ) of metabolism , which can be simulated as an optimization problem , predicting μ and Y when substrate uptake rates ( e . g . qglc ) are known [22] . For the negative μ–Y correlation , quantitative models of overflow metabolism have been developed [5–7] . In particular , quantitative measurements of E . coli growth in well-controlled environments revealed a linear-threshold response of acetate excretion ( qac ) with increasing μ [5] . To represent the full range of the μ–Y relationship , a constraint allocation flux balance analysis model ( CAFBA ) was reported that combines a GEM with proteome allocation constraints [6] . A similar solution can be formulated from a bottom-up reconstruction of metabolism and macromolecular expression ( ME-model , [9] ) that incorporates the protein synthesis pathways into a GEM and applies coupling constraints related to enzyme kinetics parameters on each individual reaction . However , none of these models have been used to explain experiments where μ and Y are decoupled through laboratory evolution or genetic engineering . In this study , we show that the wide range of μ–Y observations in E . coli can be explained by a two-dimensional rate-yield tradeoff , where the first dimension is the characteristic μ–Y tradeoff associated with acetate overflow metabolism and the second dimension is a tradeoff between glucose uptake rate ( qglc ) and Y that appears during ALE adaptation . We employ a multi-scale modeling approach to provide a mechanistic description of the two-dimensional rate-yield tradeoff . By deriving the relationship between the ME-model and the previously reported small-scale proteome allocation model [5] , we are able to develop a workflow for modifying ME-model parameters to fit experimental data , and we achieve quantitative predictions for simulations of μ–Y ( the first dimension of the rate-yield tradeoff ) . This multi-scale modeling approach predicts a two-dimensional rate-yield tradeoff , and it suggests that the second dimension of the tradeoff can be explained by changes in P/O ratio and the flux balance between glycolysis and pentose phosphate pathway . This multi-scale modeling approach predicts the systemic response of the cell to growth selection , representing the relationships between P/O ratio , glycolytic-PPP flux balance , and the two dimensions of the rate-yield tradeoff .
To explore the metabolic constraints on E . coli growth , adaptive laboratory evolution ( ALE ) was used to adapt E . coli K-12 MG1655 to maximize growth at 37°C in a liquid culture with a minimal medium containing glucose [3] . Eight independent experiments were performed on an automated ALE platform to achieve 8 . 3 × 1012 to 18 . 3 × 1012 cumulative cell divisions [23] . Phenotype characterization was performed on eight ALE endpoint strains , including quantitative measurements of μ , qglc , qac , and other common metabolic byproducts of E . coli ( Materials and methods ) . A diversity of metabolic phenotypes was observed in the ALE endpoint strains . Through ALE , μ increased from 0 . 7 h-1 for wild-type ( red triangles in Fig 1A–1D ) to 0 . 95–1 . 10 h-1 ( red circles with error bars in Fig 1A–1D ) . Based on previous reports , we expected a linear relationship between μ and qac . However , ALE endpoint strains achieved a wide ranging qac from 3 . 9–11 . 4 mmol gDW-1 h-1 ( where wild-type qac was 3 . 9 mmol gDW-1 h-1 . While we did not observe a correlation between μ and qac in these strains ( Fig 1B ) , there was a clear correlation between qglc and qac ( Fig 1D ) . Two of the ALE endpoint strains with similar μ ( 3% difference ) but distinct Y ( 30% difference ) have been processed for 13C metabolic flux measurements ( S11 Table ) . The measured metabolic fluxes using 13C metabolic flux analysis ( 13C MFA , see “Materials and methods” ) shows the positive correlation between TCA fluxes , qTCA , and Y for the ALE strains . For the ALE strain with larger Y , qglc and qac are lower and qTCA is higher . Therefore , for a fixed μ , Y increases as qTCA increases and qac decreases , indicating a pathway switch between the TCA cycle and acetate overflow depending on qglc . Therefore , combining with the referenced study [5] , for a wild-type strain , there is a μ–Y tradeoff . And for the isogenic ALE strains , a qglc–Y tradeoff appears . For both tradeoffs , Y varies with the pathway switch between TCA cycle and acetate overflow . In this paper , we call the μ–Y and qglc–Y tradeoffs a two-dimension rate-yield tradeoff , since they are tradeoffs between different “rates” ( growth rate μ and glucose uptake rate qglc ) and the same yield ( glucose yield Y ) , and they share the same phenotypic behavior of TCA–aceate overflow pathway switch . Correlations between qglc , Y , and qac have been observed previously for E . coli strains [2–4] , and moreover , a bacterial engineering approach has been reported to vary qac by manipulating the substrate uptake system [24] . In one of these studies , [4] showed that switching electron transport chain ( ETC ) enzyme selection ( and thereby modifying the P/O ratio ) can cause a qglc–Y tradeoff at a low μ of 0 . 15 h-1 . ALE gained qac and Y decoupled from μ , which seemingly differs from the reported correlation between μ–Y and μ–qac [5 , 8] . The ME-model used in this study simulates the relationships between these qglc–qac and qglc–Y tradeoffs , connecting to the mechanisms of μ–Y tradeoffs ( the bell-shaped curve in Fig 1A ) by established models [5 , 6] . To enable our analysis , it is important to note that ALE endpoint strains rapidly acquire regulatory mutations , but they do not acquire new metabolic capabilities within the time frame of these experiments [3 , 15 , 20] . The linear correlation between qac and μ reported previously was identified for an isogenic strain [5 , 8] . In contrast , our observations of a decoupling between qac and μ appear when comparing adapted strains . However , because these adapted strains have only regulatory mutations , their phenotypes represent the limits of what E . coli cells can achieve while bounded by metabolic and proteomic constraints ( but not by regulation ) . This type of adaptation and the associated phenotypic tradeoffs are useful for understanding cellular adaptation to ecological niches where regulatory adaptation can occur rapidly [18] . To explain these experimental observations , we sought a modeling approach that could quantitatively predict the μ–Y and μ–qac relationships . Our modeling approach starts with fitting the linear-threshold ( blue line in Fig 1B ) mu–qac relation [5] using the framework of ME-model [9 , 16] . We first considered a previously reported coarse-grained model of proteome allocation [5] that describes E . coli overflow metabolism ( Fig 1E ) . [5] solves Y and qac as functions of μ , and assuming that the cells pick the maximum Y under each particular μ . This indicates that high-Y growth strategies have a fitness benefit in spatially structured environments , for instance , the wild-type cultures collected from colonies , that has been demonstrated through a Y-selection system [14] , and more efficient strategies also leave more resources for cells that are hedging against future stresses [20] . The evolutionary history of E . coli includes growth in structured environments and a wide range of stresses that could have placed a selection pressure on increasing Y . Therefore , we focused on fitting the observed wild-type chemostat [8] and uptake titration [5] data for the Y-maximized growth solution ( green and blue data points in Fig 2 ) . The coarse-grained proteome allocation model [5] was intended to make predictions at high μ and thus only captures the negative μ–Y relation ( Fig 2A ) . The parameters in the coarse-grained model have a strong experimental basis in fine-grained protein abundances measurements in high growths , and the model simulates accurate predictions of μ–qac [5] . We also considered the genome-scale ME-model iJL678-ME [16] . With the default parameter settings in the ME-model , simulations had a poor quantitative prediction [9] of μ–qac to the uptake titration data ( S3F Fig ) . As [5] has shown experimentally that the overflow metabolism is fundamentally caused by the tradeoff between metabolic efficiency ( reaction stoichiometry ) and protein efficiency ( enzyme turnover rate ) . Since the reaction stoichiometry in the ME-model has been mass-balanced and well established , we suspect that this poor fit from the ME-model can be explained by inaccurate genome-wide enzyme turnover rates ( keffs ) that ME-model researchers have been seeking to improve [16 , 25 , 26] . We sought to modify the keffs to fit the μ–qac data . However , since each of the 5266 reactions in the genome-scale ME-model has a keff parameter , it is difficult to directly fit the parameters to measured data . Therefore , we pursued a multi-scale modeling approach where the coarse-grained model was used to analyze the effects of proteome-efficiency at the level of coarse-grained pathways instead of each individual reaction , which helps to tune the fine-grained parameters in the ME-model . To connect the coarse-grained and fine-grained models , we first found that the proteome efficiency ( ε ) parameters in the coarse-grained model share a conceptual basis with the enzyme efficiency parameter keffs in ME-models ( “3 Proteome constraints in the ME-model” in S1 Appendix ) . Thus , we were able to reformulate the coarse-grained model within the framework as the ME-model ( S1 Fig ) . The resulting small-scale ME-model ( SSME-model ) has parameters directly analogous to those in the genome-scale ME-model ( See “5 SSME-model parameters derivation” and “6 Matlab and COBRAme implementation” in S1 Appendix ) . The resulting SSME-model generates identical μ–Y and μ–qac predictions to the proteome allocation model . The SSME-model is a good tool for keff parameter sensitivity analysis [27] , which provides insights on how to modify the keff of the ME-model to achieve quantitative fit . As a result , we gained predictions for μ–Y and μ–qac from both the SSME- and ME-models ( blue curves in Fig 2 ) . Details of the ME-model modifications are in the S1 Appendix ( “8 Experimental data fitting” ) . In summary , with the multi-scale modeling approach , we identified the reactions whose enzymes turnover rates are too high to match the observed phenotypes . Those reactions are involved in different pathways , including the TCA cycle , Entner-Doudoroff pathway , glyoxylate shunt , nucleotide salvage , and fatty acids metabolism ( S3 Table ) . Three global parameters , unmodeled protein fraction ( UPF ) , growth-associated maintenance ( GAM ) , and non-growth-associated maintenance ( NGAM ) ( S2 Table ) were then used to predict the phenotype from different strains ( green , blue and red curves in Fig 2 ) . The reason for only modifying global parameters to simulate the ALE adaptation is that the mutations in the ALE strains do not directly related to the enzyme turnover rate ( keff value ) of a particular metabolic reaction . According to previous ALE studies [3] , most mutations occur in genes associated with regulations or translations . Even in the cases where mutations might directly change a keff , this is hard to model . Therefore , rather than exploring the mechanistic effects of ALE mutations , we focused on the phenotypic changes in the endpoint strains . Some recent studies have shown how individual mutations can have wide-reaching effects on gene expression , metabolic pathway activity , and cell phenotype [3 , 20] . The most obvious difference between the SSME-model derived from [5] and ME-model for these phenotypic predictions is the expanded solution space of the ME-model ( Fig 2 ) . However , much of the ME-model solution space corresponds to very low yield metabolic solutions . If Y is maximized during simulations of the SSME-model and ME-model ( achieved by minimizing qglc at a given μ ) , the resulting predictions are more similar between the models and lie closer to experimental data ( solid blue curves in Fig 2 ) . For the growth-rate-dependent Y-maximized solutions ( solid curves in all 4 panels ) , though the qac lines looks similar , the Y lines looks very different in the low growth regime . Where the SSME-model predicts a constant high Y , the ME-model predicts an initially low Y that increases rapidly with μ . This is because the additional non-growth maintenance energy ( NGAM ) added in the ME-model . We can also see that in Fig 2C , among the three different solution curves from the ME-model , the curve with lower NGAM has a higher Y at low μ . The NGAM parameters for the different curves are shown in S1 Table in Supporting information . In fact , by adding complexity to the SSME-model or simplifying the ME-model , many intermediate models can be built . As a result of data fitting , we achieved a quantitative fit of chemostat [8] and batch [5] uptake titration data with the Y-maximized ME-model solutions ( blue and green curves in Fig 2C and 2D ) . The ALE-adapted strains ( red circles in Fig 2 ) do not align well with the Y-maximizing solutions ( red curves in Fig 2 ) , but they are encompassed by the ME-model solution space . Further analysis of these ALE data points and the corresponding ME-model solutions were used to understand the phenotypic diversity of these adapted strains . Feasible solutions other than the Y-maximized solution are achieved through the activation of alternative metabolic pathways which are sub-optimal . The SSME-model does not capture the ALE data points with high qac ( red region in Fig 2B ) , while the genome-scale ME-model does ( red region in Fig 2D ) . Moreover , the ME-model predicts feasible growth at lower Y in the μ–Y solution space than the SSME-model . We sought to determine which pathways are responsible for the lower Y and higher qac in ME-model that was not captured by the SSME-model . Removing reactions from the ME-model can decrease the size of the solution space ( S5 , S6 and S7 Figs , “8 Solution space variation” in S1 Appendix ) , making the solution space more similar to the SSME-model solution space . We employed a workflow to identify 24 reactions ( S6 Table ) that are not activated in the Y-maximized solutions but are used to enable higher qac at lower Y . We observed that these 24 reactions are part of metabolically inefficient pathways that are alternatives to the Y-optimal pathways . By extension , metabolically inefficient pathways can be added to the SSME-model to increase the size of the solution space ( S7 Fig ) , making it more similar to the ME-model solution space . Thus , the modified SSME-model can achieve low Y ( S7A Fig ) at high qac ( S7C Fig ) . Therefore , the difference in predictions of ME-model from the SSME-model is a result of the greater range of metabolic capabilities of the genome-scale model . We can now put forward a theory to connect the correlations in μ–Y ( Fig 1A ) ( and the associated acetate curve in qac-–Y , Fig 1B ) with the negative correlation in qglc-–Y ( Fig 1C ) and positive qglc—qac correlations ( Fig 1D ) . To see the relationship between the three variables μ , qglc , and Y we generated ME-model solution spaces in qglc and Y at increasing lower bounds of μ ( Fig 3A ) . These solution spaces represent the flexibility in the model to achieve a particular growth rate . At the Y-maximized limit of these solution space , we see the established negative μ–Y tradeoff where increasing growth rate requires increasing qglc and decreasing Y ( dashed arrow marked as “d1” in Fig 3A ) coupling with increasing qac ( top edges of solution spaces in Fig 3B ) . This is the first dimension of the rate-yield tradeoff , “d1” . Considering only “d1” , one would expect the acetate production rate in all strains to be fully defined by the growth rate . In the case of this 1-dimensional tradeoff , all points in Fig 3A would appear on the line at the top of the blue solution spaces ( parallel to the dotted “d1” line ) . However , we observed another degree of freedom in the phenotypic space . At a given μ , evolved strains can acquire higher qglc , higher qac , and lower Y . The “d2” tradeoff is defined by a linear correlation in qglc–qac ( Fig 3B ) and a corresponding inverse proportional tradeoff in qglc–Y ( Fig 3A ) . The “d2” tradeoff is also predicted by ME-model simulations . At a given μ , the ME-model solution spaces extend toward lower Y and higher qglc , revealing this inverse proportional relationship in qglc-Y . The second dimension “d2” can also be seen in qac–qglc where the ME-model predicts the qac–qglc correlation observed in ALE endpoint as the qac–maximized edges of the solution spaces ( Fig 3B ) . The solution spaces predicted by ME-model show broad feasible ranges of acetate production qac at a given qglc and μ ( “bold” solution spaces in Fig 3B ) , so the qglc–Y tradeoff is not required by the model . On the other hand , the relationship between qglc and Y is a strict tradeoff in the model ( “thin” solution spaces in Fig 3A ) . Therefore , the ME-model suggests that qglc–Y is the more fundamental second dimension of the rate-yield tradeoff . To verify that hypothesis , one would look for mutant strains where qglc increased while the other three phenotypic variables remained fixed ( a shift to the right in Fig 3B ) . We sought to identify the particular alternate metabolic strategies in the ME-model that could enable a qglc–Y tradeoff by identifying the differential pathway usage at a fixed high μ ( 1 . 05 h-1 in the ME-model ( Fig 3C ) . The model predicts that when qglc increases from the Y-maximized state ( minimum qglc ) , flux through the proton-coupled NAD ( P ) transhydrogenase increases ( reaction THD2pp , catalyzed by pntAB . In addition , a pathway switch between two different NADH dehydrogenase reactions , NADH5 ( ndh and NADH16pp ( nuo , appears at high qglc . In fact , each of or any combination of the 24 reactions in S6 Table can be activated in the ME-model to achieve high qglc , high qac , and low Y . There are two common threads among these pathway activations . First , they all reduce the P/O ratio in the simulations ( Fig 3C ) . NADH5 transports fewer protons to the periplasm per electron than NADH16pp . And increasing THD2pp flux drains the proton gradient without contributing to ATP production , thereby reducing P/O ratio ( Fig 3D ) . Second , with the activation of those 24 reactions , glycolytic flux increases ( Fig 3D ) and pentose phosphate pathway flux decreases ( Fig 3C ) . By comparing to the 13C metabolic flux analysis ( Fig 3E and 3F ) , the ME-model shows quantitative predictive power for the second-order rate-yield tradeoff . Experiments that introduce proton leakage have shown a shift towards high qac and low Y [5] in the same μ . It has also been shown that the variation of P/O ratio can uncouple the regulation of cytochrome oxidase from the cellular ATP demand [4] . More broadly , energy dissipation through proton leakage is known to be a method of metabolic control in bacteria [28 , 29] . To clarify the effect of decreasing of P/O ratio in the ME-model , we added a reaction in the model representing proton leakage ( Methods ) . As a result , we see the Y-maximized solution with decreased P/O ratios have higher qglc , higher qac , and lower Y at a given μ ( Fig 4 ) . Finally , experiments have shown that knocking out gnd leads to increased qglc and qac and decreased Y with little change in μ [30] . The ME-model also predicts that gnd knockout mutants ( “gnd knockout simulation” Methods ) will have increased qglc , qac and decreased Y ( Fig 4 ) . Since the ALE experiments do not introduce leaky proton or knock out any genes , it is also possible that multiple mechanisms working together , where the ME-model points to the systemic mechanisms for this fundamental second-order tradeoff . The exact pathways involved can be determined in future experiments . Alternative explanations of the rate-yield tradeoff have been proposed , including membrane [31 , 32] and cytosolic crowding [33 , 34] . It is difficult to rule out these alternative constraints on cell growth , and it may be that multiple constraints operate at the same time . However , it is encouraging to see that the ME-model can explain the complex relationship between μ , Y , qac , and qglc with only metabolic and proteome allocation constraints . In the future , it will be possible to extend ME-models with additional constraints . For example , it has been proposed that the unmodeled protein fraction ( UPF ) is growth-rate dependent , and thus existing proteome allocation models with fixed UPF are inaccurate [34] . If this is indeed the case , then SSME- and ME-models with cytosolic crowding constraints can be developed to fully represent the interplay between crowding , proteome allocation , and pathway selection .
The E . coli ME-model provides a mechanistic and predictive model of rate-yield tradeoffs . It successfully reconciles several experimental data sets: i ) uptake titration at low growth [8] , ii ) batch culture at higher growth rates [5] , and iii ) ALE endpoint strains ( this study ) . These data sets , when analyzed with the ME-model , show the existence of a two-dimensional rate-yield tradeoff . The first dimension ( “d1” ) rate-yield tradeoff is μ–Y tradeoff and the second dimension ( “d2” ) is qglc–Y tradeoff . From a mathematical perspective , one can describe the observed tradeoffs as correlations between any pair of the four variables μ , Y , qglc , and qac . The two particular dimensions of the tradeoff that we describe , μ–Y ( “d1” ) and qglc–Y ( “d2” ) , are motivated by two different trends in our physiological observations . First , the previously-reported strong linear correlation between μ and Y [5] occurs for isogenic cultures under carbon limitation . The second dimension “d2” appears when comparing laboratory evolution endpoint strains , where qglc , qac , and Y are observed to vary at a fixed μ , with a linear relationship in qglc–qac and a corresponding inverse proportional relationship in qglc–Y . This two-dimensional tradeoff cannot be deciphered from simpler intuitive models , but it can be derived from the comprehensive set of metabolic and gene expression pathways represented by the ME-model . Furthermore , this study employed a multi-scale modeling approach where a small-scale model was used to guide parameter estimation in the genome-scale ME-model . This approach—which has been termed Tunable Resolution ( TR ) modeling [35]—was essential to the success of the study , and we expect that both small-scale and genome-scale models will continue to play an important role in understanding the genotype-phenotype relationship . The two-dimensional rate-yield tradeoff appears as a result of ALE selection for μ when alternative pathway selection strategies achieve the same growth rate . Proton leakage and alternative ETC pathway selection are plausible mechanisms for modifying the P/O ratio and creating the qglc–Y tradeoff . In addition , the flux ratio between glycolysis ( GAPD , gapA ) and the pentose phosphate pathway ( GND , gnd ) might play a significant role in the qglc–Y tradeoff . Those mechanisms can be tested experimentally . Finally , revealing the underlying regulation would be of great interest for establishing a deeper understanding of rate-yield tradeoffs . Combining ME-models with known regulatory mechanisms to explain cellular choices would achieve a long-standing goal in systems biology [36] .
Phenotypic data including μ , qglc , qac , and excretion rates of other metabolic byproducts were collected for ALE endpoint strains ( “1 Phenotypic characterization of E . coli strains” in S1 Appendix ) . In addition , 13C fluxes were measured from two of the strains with different growth rate and different glucose yield ( “2 13C metabolic flux analysis” in S1 Appendix ) . Reference data points of rate-yield , growth-acetate relations of wild-type MG1655 and NCM3722 E . coli strains were collected from published studies [5 , 8] . The coarse-grained proteome allocation model from [5] was reformulated as a small-scale ME-model ( SSME-model , detail in “5 SSME-model parameters derivation” in S1 Appendix ) and implemented by the COBRAme framework [16] . The genome-scale model iJL1678-ME was modified to fit experimental data by modifying the keffs ( enzyme turnover rate ) of TCA cycle reactions , blocking target reactions , and modifying UPF ( unmodeled protein fraction ) , GAM ( growth associate maintenance energy ) , and NGAM ( non-growth associate maintenance energy ) ( “8 Experimental data fitting” in S1 Appendix ) . Solution spaces were generated using flux balance analysis ( incorporated in COBRAme ) in the ME-model ( “7 Solution space of the ME-model” in S1 Appendix ) . To determine the effect of modifying P/O ratio on ME-model solution spaces , a reaction representing proton leakage was added to the ME-model ( “10 P/O ratio manipulation” in S1 Appendix ) . The effect of the gnd knockout was demonstrated by blocking the reaction GND in ME-model simulations ( “11 gnd knockout simulation” in S1 Appendix ) .
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This study reconciles multiple existing microbial rate-yield tradeoff theories with experimental data . There is great interest in developing quantitative descriptions of the relationship between growth rate and growth yield [1] . However , some reported experiments [2–4] in the literature do not agree with existing theories [5–7] . Specifically , overflow metabolism in E . coli can either be coupled [5 , 8] or decoupled [2–4] from growth rate . We found that adaptive laboratory evolution ( ALE ) experiments of E . coli reveal a two-dimensional rate-yield tradeoff in adapted strains where the dimensions are ( i ) a tradeoff between growth rate and growth yield , previously reported by [5] , and ( ii ) a tradeoff between substrate uptake rate and growth yield . The appearance of this two-dimensional tradeoff during adaptation suggests that microorganisms adapting to new environments are subject to a more complex set of rate-yield tradeoffs than previously reported [5 , 6] . In this study , the two-dimensional rate-yield tradeoff is quantitatively explained through our multi-scale modeling approach , combining a previously reported small-scale proteome allocation model [5] with a genome-scale model of metabolism and gene-expression ( ME-model ) [9] . The modeling approach is also instrumental to future studies .
|
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2019
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Laboratory evolution reveals a two-dimensional rate-yield tradeoff in microbial metabolism
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Fusion and fission of mitochondria maintain the functional integrity of mitochondria and protect against neurodegeneration , but how mitochondrial dysfunctions trigger neuronal loss remains ill-defined . Prohibitins form large ring complexes in the inner membrane that are composed of PHB1 and PHB2 subunits and are thought to function as membrane scaffolds . In Caenorhabditis elegans , prohibitin genes affect aging by moderating fat metabolism and energy production . Knockdown experiments in mammalian cells link the function of prohibitins to membrane fusion , as they were found to stabilize the dynamin-like GTPase OPA1 ( optic atrophy 1 ) , which mediates mitochondrial inner membrane fusion and cristae morphogenesis . Mutations in OPA1 are associated with dominant optic atrophy characterized by the progressive loss of retinal ganglion cells , highlighting the importance of OPA1 function in neurons . Here , we show that neuron-specific inactivation of Phb2 in the mouse forebrain causes extensive neurodegeneration associated with behavioral impairments and cognitive deficiencies . We observe early onset tau hyperphosphorylation and filament formation in the hippocampus , demonstrating a direct link between mitochondrial defects and tau pathology . Loss of PHB2 impairs the stability of OPA1 , affects mitochondrial ultrastructure , and induces the perinuclear clustering of mitochondria in hippocampal neurons . A destabilization of the mitochondrial genome and respiratory deficiencies manifest in aged neurons only , while the appearance of mitochondrial morphology defects correlates with tau hyperphosphorylation in the absence of PHB2 . These results establish an essential role of prohibitin complexes for neuronal survival in vivo and demonstrate that OPA1 stability , mitochondrial fusion , and the maintenance of the mitochondrial genome in neurons depend on these scaffolding proteins . Moreover , our findings establish prohibitin-deficient mice as a novel genetic model for tau pathologies caused by a dysfunction of mitochondria and raise the possibility that tau pathologies are associated with other neurodegenerative disorders caused by deficiencies in mitochondrial dynamics .
The dynamic behavior of mitochondria that constantly divide and fuse is pivotal to maintain their pleiotropic activities and their distribution within cells . Conserved protein machineries in the outer and inner membrane of mitochondria mediate membrane fusion events , ensure cristae formation and regulate the interaction of mitochondria with the endoplasmic reticulum [1]–[3] . Loss of mitochondrial fusion leads to neuronal loss in mice , highlighting the vulnerability of neurons for deficiencies in mitochondrial dynamics [4]–[6] . Mutations in the dynamin-like GTPases MFN2 and OPA1 , which mediate mitochondrial membrane fusion , cause neurodegeneration in Charcot-Marie-Tooth disease type 2A and autosomal dominant optic atrophy , respectively [7]–[9] . Moreover , defects in mitochondrial dynamics are associated with multiple neurodegenerative diseases , including Parkinson's , Alzheimer's ( AD ) and Huntington's disease [10]–[12] . Recent evidence identified prohibitins in the mitochondrial inner membrane as novel modulators of mitochondrial fusion [13]–[15] . Prohibitins comprise a conserved and ubiquitously expressed protein family [16] , [17] . Two homologous proteins , prohibitin-1 ( PHB1 ) and prohibitin-2 ( PHB2 ) , assemble into large ring complexes in the inner membrane with putative functions as protein and lipid scaffolds [18] . The genetic interaction of yeast PHB1 and PHB2 with genes involved in the mitochondrial cardiolipin and phosphatidyl ethanolamine metabolism suggests that prohibitin complexes may also affect the lipid distribution in the inner membrane [19] . Consistently , PHB1 and PHB2 are homologous to members of the SFPH-family that were found in association with membrane microdomains in various cellular membranes [20] , [21] . Despite emerging evidence for a scaffold function of prohibitins [16] , only limited information is available on the physiological relevance of a defined spatial organization of the inner membrane for mitochondrial activities . Loss of prohibitin genes in Caenorhabditis elegans and mice results in embryonic lethality , pointing to essential functions during embryonic development [22] , [23] . Knockdown of PHB1 and PHB2 in adult , non-neuronal tissues of C . elegans influences aging by moderating fat metabolism and energy production [24] . However , it remained unclear whether prohibitins affect mitochondrial respiratory activities directly . In mammalian cells , prohibitins appear to affect mitochondrial respiration in a cell-type specific manner . While knockdown of PHB1 impaired complex I activity in endothelial cells [25] , mitochondrial respiratory function was not affected in prohibitin-deficient mouse embryonic fibroblasts ( MEFs ) [13] . These studies identified the processing of OPA1 as the central process regulated by prohibitins in vitro . The function of OPA1 in mitochondrial fusion and cristae morphogenesis depends on the presence of both long and short forms of OPA1 , the latter being generated by proteolytic processing of long forms [26]–[29] . Loss of PHB2 destabilizes long OPA1 forms and inhibits mitochondrial fusion , resulting in the fragmentation of the mitochondrial network and an increased susceptibility of the cells towards apoptotic stimuli [13] , [15] . Interestingly , a destabilization of long OPA1 forms has also been observed in cells lacking m-AAA proteases [30] , ATP-dependent quality control enzymes with regulatory functions during mitochondrial biogenesis [4] , which assemble with prohibitin complexes in the inner membrane of yeast , mammalian and plant mitochondria [31] , [32] . Mutations in m-AAA protease subunits cause axonal degeneration in spinocerebellar ataxia , hereditary spastic paraplegia , and a spastic-ataxia neuropathy syndrome [33]–[35] . These results prompted us to assess in vivo the role of prohibitins in neurons , which contain high levels of prohibitins and are particularly vulnerable to disturbances in mitochondrial dynamics . Using conditional gene ablation in mice , we demonstrate that a post-natal loss of PHB2 in the forebrain triggers massive neurodegeneration which is associated with the accumulation of aberrant mitochondria and hyperphosphorylation of the microtubule-associated protein tau .
Previous experiments using a genetic loss-of-function approach to uncover physiological functions of PHB2 revealed an early embryonic lethality phenotype in mice [13] , [23] . To circumvent gene ablation during embryogenesis , conditional Phb2 mice ( Phb2fl/fl ) were bred to mice expressing the Cre recombinase under control of the postnatally expressed CaMKIIα promoter ( CaMKIIα-Cre ) [36] resulting in neuron-specific PHB2-deficient mice ( Phb2fl/fl;CaMKIIα-Cre; hereafter referred to as Phb2NKO mice ) . This mouse line shows a defined and restricted recombination pattern and a progressive increase in recombination efficiency after completed neuronal development [36] . Histological examinations of brains derived from CaMKIIα-Cre mice crossed to ROSA26-LacZ reporter mice revealed selective Cre-mediated recombination in forebrain regions including the cortex , striatum and hippocampus , to a minor extent in hypothalamic regions , but not in hind- and midbrain regions like the cerebellum ( Figure S1 ) [37] . To demonstrate efficient depletion of Phb2 , in-situ hybridization against the endogenous Phb2 mRNA was performed . Notably , Phb2 mRNA was virtually depleted in hippocampal neurons of 8-week-old Phb2NKO mice ( Figure 1A ) . Consistently , immunoblotting of tissue lysates prepared from various brain compartments of mice of different age revealed maximal depletion of PHB2 in Cre-expressing tissues at 14-weeks , but not in the cerebellum where Cre recombinase is not expressed ( Figure 1B ) . Notably , PHB2 depletion was accompanied by efficient loss of its assembly partner PHB1 ( Figure 1B ) . This observation is consistent with previous findings in cultured MEFs [13] and demonstrates that prohibitin subunits are functionally interdependent in neurons in vivo . Homozygous Phb2NKO mice were born at expected mendelian ratios , showed normal fertility and were anatomically indistinguishable from their WT littermates . From 12 to 14 weeks of age , however , Phb2NKO mice progressively developed aging-related phenotypes , including weight loss , cachexia and kyphosis ( Figure 1C , 1D; Figure S2 ) . Furthermore , Phb2NKO mice , but not control littermates , showed an excessive pathological grooming behavior characterized by facial hair loss and self-inflicted facial lesions ( Figure 1C ) . An extensive analysis of behavioral and cognitive abilities in early-stage 8-week-old Phb2NKO animals revealed decreased hippocampus-dependent learning abilities and memory formation ( Figure S3 ) , and an impairment of innate fear behavior and motor coordination ( Figure S4 ) ( for details , see Text S1 ) . The phenotypes of Phb2NKO animals deteriorated with age and led to premature death of Phb2NKO mice starting at the age of 14 weeks ( Figure 1E ) . The maximal lifespan of Phb2NKO mice was 22 weeks only . Survival was not affected in homozygous Phb2fl/fl or heterozygous Phb2fl/WT;CaMKIIα-Cre ( Phb2HET ) mice ( Figure 1E ) . We therefore conclude that PHB2 in the forebrain is essential for postnatal mouse survival . To investigate the underlying defects at the cellular level , we analyzed gross brain morphology of Phb2NKO and control brains . Phb2NKO brains were indistinguishable from controls in size , weight and gross morphology at 14 weeks of age ( Figure 2A ) . In contrast , at the age of 20 weeks we observed a massive atrophy of Phb2NKO forebrains , which was accompanied by a severe total brain weight loss ( Figure 2A ) . Histological examinations of Phb2NKO brains further supported the progressive nature and severity of the phenotypes . Nissl stainings and semithin sections from Phb2NKO animals revealed that the region most prominently affected was the hippocampus , which undergoes progressive degeneration over time , culminating in the almost complete loss of neurons in both the dentate gyrus ( DG ) and cornu ammonis ( CA ) regions at 20 weeks of age ( Figure 2B , Figure S5A ) . At this age , cortical neurons in all layers also appeared affected in Phb2NKO mice , showing shrinkage of the cell body and loss of processes ( Figure S5B ) . Since the hippocampal region appeared to be a preferential target in the absence of PHB2 , we analyzed this area in more detail . Neuronal loss was accompanied by a progressive development of astrogliosis , as demonstrated by increased GFAP reactivity already observable at 6 weeks of age in the DG ( Figure 2B ) . At this age , a significant fraction of DG neurons in Phb2NKO mice appeared vacuolated and neuronal loss was already apparent ( Figure 2D , 2E ) . At 14 weeks , the DG consisted of only one neuronal layer , with more than 50% of residual neurons showing degenerative features ( Figure 2C–2E ) . Remarkably , while DG neurons were markedly reduced in number already at 14 weeks ( Figure 2E ) , neurons in the CA1 region were less affected and neuronal loss became apparent only in 20-week-old Phb2NKO mice ( Figure 2F , Figure S6 ) . TUNEL staining of the hippocampal DG regions revealed few positive neuronal cell bodies , suggesting that neuronal loss in Phb2NKO brains is at least partially caused by apoptosis ( Figure S5 ) . We therefore conclude that PHB2 is generally required for neuronal survival in vivo . However , the time-course and severity of neuronal degeneration show regional differences . To define whether the depletion of PHB2 affects mitochondrial ultrastructure in neurons at early stages of the pathological process , we analyzed the DG of young Phb2NKO mice by transmission electron microscopy . DG neurons of 6-week-old Phb2fl/fl control mice contained mitochondria with a normal appearance characterized by lamellar-shaped cristae inside double-membrane layered organelles ( Figure 3A ) . In contrast , several neurons in the DG of Phb2NKO mice contained mitochondria with almost complete absence of lamellar cristae ( Figure 3A ) . Moreover , in some cases these mitochondria appeared moderately swollen . These ultrastructural features account for the appearance of vacuolated neurons observed in semithin sections ( Figure 2C ) . The number of neurons containing mitochondria with defective ultrastructure was further enhanced in 14-week-old animals confirming the progressive nature of this pathology ( not shown ) . To further investigate whether lack of PHB2 affects the mitochondrial network in neurons in a cell-autonomous manner , we isolated primary hippocampal neurons from conditional E18 . 5 Phb2fl/fl and Phb2fl/WT embryos and infected them with lentiviruses expressing nuclear-targeted Cre recombinase to genetically inactivate Phb2 in vitro . The mitochondrial network in these neurons was visualized by the simultaneous infection with lentiviral particles encoding a mitochondrially targeted EGFP ( Su9-EGFP ) . Tubular mitochondria were present in the cell body and along the neurites in Phb2fl/fl ( Figure 3B; a , a′ ) and Phb2fl/WT neurons , which were infected with Cre-expressing lentiviruses ( NLS-Cre::Phb2fl/WT ) ( Figure 3C ) . In contrast , mitochondria were greatly fragmented and clustered in perinuclear regions of >70% of infected Phb2fl/fl neurons ( NLS-Cre::Phb2fl/fl ) ( Figure 3B; b , b′ ) . We further evaluated the mitochondrial distribution in Phb2-depleted neurons and determined the total number of mitochondria protruding into the neurites . Strikingly , neurites of Cre-infected Phb2fl/fl neurons contained fewer mitochondria when compared to controls consistent with the perinuclear clustering of fragmented mitochondria after acute loss of prohibitins ( Figure 3D ) . Different isoforms of the dynamin-like GTPase OPA1 with seemingly varying activities exist , which are expressed in a tissue-specific manner in mice [38] . The expression of OPA1 isoform 1 predominates in the central nervous system giving rise to bands b ( L-OPA1 ) and , upon proteolytic processing , to band e ( S-OPA1 ) [38] . To examine whether depletion of PHB2 affects the accumulation of OPA1 in neuronal tissue in vivo , we analyzed Phb2NKO and control forebrain lysates by immunoblotting with OPA1-specific antibodies . The loss of prohibitins was accompanied by the selective loss of the L-OPA1 isoform b in the hippocampus ( Figure 3E ) , cortex and striatum but not in the cerebellum ( Figure S7 ) . These alterations occurred in a time-dependent manner simultaneous with the depletion of prohibitins and were already detected at 10 weeks of age . This does not reflect a general impairment of the biogenesis of mitochondrial inner membrane proteins , as various subunits of respiratory chain complexes accumulated at similar levels in the brain of Phb2NKO and control animals ( Figure 3E; Figure S7 ) . Overall , these data demonstrate that neuronal PHB2 ensures stabilization of L-OPA1 and the maintenance of the mitochondrial network and ultrastructure in vivo . Surprisingly , ultrastructural examination of hippocampi of 14-week-old Phb2NKO mice revealed the accumulation of straight tubular structures in unmyelinated neuronal processes . These filamentous structures measure about 12–20 nm in diameter ( mean 20 . 8 nm±0 . 323; range 9 . 9–25 . 72 nm ) and are reminiscent of inclusions composed of aberrantly phosphorylated species of the microtubule-associated protein tau . Although morphologically distinct from paired helical filaments ( PHF ) , they are similar to those found in ‘classical’ intracytoplasmic inclusions of tau-positive astrocytes and neurons , which are observed in several neurodegenerative conditions such as frontotemporal dementia and other tauopathies ( Figure 4A ) [39] . To explore a role for Phb2 in tau phosphorylation , hippocampal tissue sections were immunostained with AT-8 antibodies , which selectively recognize phosphorylated species of tau ( phospho-Ser202 and phospho-Thr205 ) . Intraneuronal inclusions were detected in the DG but not in other hippocampal regions of Phb2NKO mice as early as at 6 weeks but not in control littermates , and accumulated in both cell body and neurites ( Figure 4B ) . We substantiated these observations by immunoblotting using phospho-tau specific AT-8 antiserum ( Figure 4C ) . Several hyperphosphorylated tau species selectively accumulated in hippocampal lysates from 14-week-old Phb2NKO mice , but not in lysates from control mice ( Figure 4C ) . Several kinases have been implicated in tau phosphorylation both in vitro and in vivo [40] , [41] . We therefore assessed the activation status of candidate kinases by immunoblotting of hippocampal extracts of Phb2NKO mice . Phosphorylated , active forms of the extracellular signal-regulated MAP kinases ERK1/2 and of the c-Jun N-terminal kinase JNK were detected specifically in Phb2NKO mice ( Figure 4C ) . In contrast , the β-form of glycogen synthase kinase ( GSK3 ) , another putative major tau kinase , was robustly inactivated by phosphorylation at Ser position 9 ( Figure 4D ) . Concomitantly , this was accompanied by the parallel activation of the upstream kinase AKT suggesting that the AKT-GSK3 axis might not be causative for the increased tau pathology in Phb2NKO mice ( Figure 4D ) . Similarly , cyclin-dependent kinase 5 ( CDK5 ) apparently does not contribute to tau hyperphosphorylation in Phb2NKO mice as we did not detect proteolytic conversion of its substrate p35 to p25 in Phb2-deficient hippocampal lysates ( Figure 4D ) . Taken together , we conclude from these experiments that deletion of Phb2 activates MAP kinases leading to tau hyperphosphorylation and the deposition of aberrant filamentous structures in hippocampal neurons . Mitochondrial dysfunction is an early phenomenon in many human tauopathies [42] , [43] . To examine whether compromised mitochondrial respiratory function might be the underlying defect causing tau pathology and neurodegeneration in Phb2NKO mice , we monitored respiratory activities in situ and in isolated PHB2-deficient brain mitochondria . Enzymatic COX/SDH stainings on whole brain cryosections of 6-week-old Phb2NKO brains did not provide evidence for the presence of respiratory deficient cells ( Figure S8 ) . Consistently , substrate-driven respiration was not affected in mitochondria that had been isolated from hippocampal tissues of 12-week-old Phb2NKO mice ( Figure 5A ) . Consistently , we obtained no evidence for increased ROS production and oxidative damage in 14-week-old Phb2NKO mice ( Figure S9 ) . While not apparent in young mice , OXPHOS activities declined with age and were decreased significantly in 18-week-old Phb2NKO mice ( Figure 5B ) . Mitochondria isolated from hippocampi of these mice were generally able to consume oxygen , as the basal mitochondrial respiration in the presence of pyruvate was similar in 18-week-old Phb2NKO and control mitochondria . However , respiration rates in PHB2-deficient mitochondria decreased significantly in the presence of saturating concentrations of ADP to maximally stimulate respiration , indicating that coupling is impaired in mitochondria depleted of PHB2 . Moreover , enzymatic activities of complex I ( monitored in the presence of glutamate and malate ) , complex II ( in the presence of succinate ) and of complex IV [in the presence of TMPD ( N , N , N′ , N′-Tetramethyl-1 , 4-phenylendiamine ) ] were significantly reduced in mitochondria isolated from 18-week-old Phb2NKO mice suggesting that respiratory activities in hippocampal tissues progressively deteriorate over time in the absence of PHB2 ( Figure 5B ) . The broad functional impairment of respiratory complexes in aged PHB2-deficient mice could be explained by a loss of the mitochondrial genome ( mtDNA ) , which encodes essential respiratory chain subunits . We therefore determined mtDNA levels by quantitative real-time PCR analysis of mtDNA isolated from several neuronal tissues of Phb2NKO and control mice . Strikingly , mtDNA levels relative to nuclear DNA deteriorated in a progressive manner in the hippocampus and striatum but not in the cerebellum of Phb2NKO mice ( Figure 5C , 5D , Figure S10 ) . In 20-week-old Phb2NKO animals , relative mtDNA levels were reduced to 30% of controls in the hippocampus , providing a rationale for the decreased respiratory activities in these mice . It is noteworthy that mtDNA levels were not affected in cortical PHB2-deficient mitochondria ( Figure S10 ) , pointing to neuronal-specific differences in the mechanisms that stabilize mtDNA . In conclusion , these experiments demonstrate that PHB2 is required for the maintenance of mtDNA in neuronal mitochondria . The loss of PHB2 in the forebrain leads to a progressive destabilization of mtDNA and ultimately to an impaired respiratory function . However , respiratory deficiencies become apparent at significantly later stages than tau phosphorylation suggesting that they are not the primary cause for the tau pathology in PHB2-deficient mice .
We observe massive degeneration of PHB2-deficient neurons in the forebrain . Neurons expressing Cre recombinase are lost or severely affected in Phb2NKO mice , demonstrating a general requirement of prohibitins for neuronal survival in vivo . TUNEL stainings of DG neurons suggest that apoptosis contributes to neuronal loss but other types of cell death cannot be excluded . Consistently , depletion of prohibitins was found to facilitate apoptosis in different cell types in vitro [13] , [44] , [45] . It is noteworthy that the susceptibility towards apoptosis appears to vary between different cell types [13] , [44] , [45] . Similarly , the loss of PHB2 in Phb2NKO mice leads to faster death of DG neurons when compared to CA1 neurons , pointing to neuron-specific differences . The loss of hippocampal neurons in Phb2NKO mice is associated with anxiolytic behavior and deficiencies in memory function and in learning abilities . Moreover , Phb2NKO mice develop progressive cachexia and kyphosis . In view of massive neuronal loss in the hippocampal region of Phb2NKO mice , it appears likely that reduced food intake causes these phenotypes . As Phb2 might only be partially deleted in the hypothalamic region of Phb2NKO mice [36] , it remains to be determined how the loss of PHB2 in the forebrain causes these phenotypes , which are reminiscent of other mouse lines harboring dysfunctional mitochondria [46] , [47] . Regardless , they are likely the consequence of the massive neuronal loss in Phb2NKO mice rather than reflecting specific functions of prohibitins in the forebrain . Ring complexes formed of multiple PHB1 and PHB2 subunits act as scaffolds in the inner membrane affecting the spatial organization of membrane proteins and lipids [16] , [48] . Previous studies in proliferating cells in vitro revealed that prohibitin complexes ensure the accumulation of L-OPA1 within mitochondria [13] . We now extend these findings to adult neurons in vivo and establish an essential role of prohibitins for the maintenance of mitochondrial ultrastructure . Destabilization of L-OPA1 in the absence of PHB2 likely inhibits fusion and ongoing fission events lead to the fragmentation of the mitochondrial network in hippocampal neurons . Moreover , we demonstrate that prohibitin scaffolds are required to maintain the mitochondrial genome , which is progressively lost in neurons lacking PHB2 and likely explains respiratory deficiencies that occur in aged PHB2-deficient neurons . Notably , mtDNA is absent in fusion-incompetent mitochondria in MFN2-deficient fibroblasts [5] , indicating that mitochondrial fusion or the protein machinery involved is required to maintain mtDNA . It is therefore conceivable that neurons lacking PHB2 lose mtDNA because mitochondrial fusion is inhibited . Alternatively , PHB2 acting as a membrane scaffold may directly affect the stability of mitochondrial nucleoids in neurons . Prohibitins have been identified as peripheral components of mitochondrial nucleoids and were found to maintain their organization and stability at least in some cell lines in vitro [14] , [49] . In yeast , depletion of prohibitins in combination with components affecting the accumulation of phosphatidyl ethanolamine in mitochondrial membranes induces the loss of the mitochondrial genome [19] , [50] , supporting a critical role of the membrane environment for the maintenance of mtDNA . Taken together , our observations demonstrate that neuronal survival in vivo critically depends on prohibitin scaffolds in the inner membrane and identify the processing of OPA1 and the stability of the mitochondrial genome as processes within mitochondria , whose perturbation leads to neurodegeneration in the absence of prohibitins . Our findings also provide insight into the cellular mechanisms through which a dysfunction of mitochondria leads to neurodegeneration . The observation of impaired OPA1 processing and defective mitochondrial ultrastructure preceding massive neuronal loss in Phb2NKO mice supports emerging evidence that neurons are particularly susceptible to perturbations in mitochondrial dynamics . Studies on the cerebellum of MFN2-deficient mice revealed electron transport deficiencies of Purkinje cells prior to neuronal death , which are consistent with the lack of mtDNA nucleoids observed in fibroblasts [5] . The dependence of mtDNA stability and respiratory activity on mitochondrial fusion provides an elegant mechanism to explain neuronal loss in MFN2-deficient mice [5] . However , while the lack of PHB2 destabilizes mtDNA in the hippocampus and striatum , respiratory deficiencies manifest only in aged Phb2NKO mice , indicating that alternative mechanisms lead to neurodegeneration in this model . The analysis of mitochondrial morphology in PHB2-deficient hippocampal neurons suggests that deficiencies in mitochondrial distribution may trigger neuronal loss . Fragmented mitochondria accumulate in the perinuclear region of hippocampal neurons lacking PHB2 in vitro and are depleted from neurites . The surprising observation of tau hyperphosphorylation and aggregation provides a possible explanation for the altered distribution of mitochondria in PHB2-deficient neurons . Consistent with an important role for neurodegeneration , we detected tau phosphorylated at AT-8 sites already in 6-week-old Phb2NKO mice , i . e . before neuronal loss becomes apparent . Tau is predominantly present in axons , where it binds and stabilizes microtubules and regulates axonal transport processes [43] , [51] , [52] . Hyperphosphorylated forms of tau were found to detach from microtubules , accumulate in the soma and are prone to aggregation . Consistently , phosphorylated tau was found to interfere with the binding of kinesin motors to mitochondria and distinct vesicles affecting cargo-selective anterograde transport in cultured neurons [52] . Moreover , phosphorylation of tau at AT-8 sites was recently found to modulate mitochondrial movement in cortical neurons [53] . It is therefore conceivable that tau hyperphosphorylation in the absence of PHB2 causes mitochondrial transport deficiencies triggering progressive neuronal loss in Phb2NKO mice . Hyperphosphorylation of tau has been observed in AD brains [54] . Stress-activated kinases like JNK and ERK1/2 have been implicated in the hyperphosphorylation of tau during AD . In fact , fibrillar Aβ can induce ERK activation , abnormal phosphorylation of Tau , and progressive neurodegeneration [55] . In addition , JNK-related kinases are activated in AD brains and are associated with the development of amyloid plaques [56] . However , despite extensive studies on tau hyperphosphorylation , the complexity of kinases and phosphatases involved has precluded to define its pathogenic role for AD until now [57] . Regardless , the discovery of tau hyperphosphorylation and filament formation upon loss of PHB2 sheds new light on the possible role of mitochondria in neurodegeneration in AD and related disorders . While mitochondrial dysfunction has been recognized as a prominent , early event in a number of tauopathies including AD [51] , it remained open whether mitochondrial defects are of direct pathogenic relevance or secondary to other cellular deficiencies . Our analysis of Phb2NKO mice provides first genetic evidence that a dysfunction of mitochondria can trigger tau hyperphosphorylation and aggregation . We detected phosphorylated tau in PHB2-deficient hippocampal neurons lacking apparent respiratory defects or evidence for oxidative damage strongly suggesting that other mechanisms induce tau pathologies in this model . Perturbations in mitochondrial dynamics and ultrastructure that occur early in Phb2NKO mice and may interfere with axonal trafficking are attractive candidates . Our findings therefore raise the possibility that tau pathologies might be associated with other neurodegenerative disorders caused by deficiencies in mitochondrial dynamics . Studies along these lines may turn out to be of relevance for tauopathies as well .
Animals were anesthetized with avertin and perfused intracardially with 4% paraformaldehyde in PBS . Brain were removed , post-fixed overnight with 4% paraformaldehyde in PBS and conserved in 0 . 12 M phosphate buffer . Immunohistochemistry and immunofluorescence were performed on 30 µm sagittal vibratome sections , as previously described [58] . Anti-GFAP antibodies were purchased by NeoMarkers ( Fremont , CA , USA ) . Anti-4-HNE antibodies were purchased from Abcam ( Cambridge , UK ) . Immunohistochemistry with anti-AT-8 ( Thermo Fisher Scientific , Walthman , MA , USA ) was performed with Vector M . O . M . Immunodetection kit ( Vector Lab , Burlingame , CA , USA ) according to the manufacturer's protocol . For TUNEL assays , tissues were frozen on liquid nitrogen vapour for 5 s after fixation and then conserved in liquid nitrogen . TUNEL assays were performed on 20 µm thick coronal frozen sections with ApopTag Plus Peroxidase In Situ Apoptosis Detection Kit ( Chemicon International Temecula , CA ) according to the manufacturer's protocol . All immunohistochemical and immunofluorescence analyses were performed on at least three mice per genotype . Age-matched Phb2NKO and control mice ( n = 3 for each genotype ) were anesthetized intraperitoneally with avertin and perfused with 2% glutaraldehyde in PBS . Brains were removed and postfixed in 0 . 12 M phosphate buffer/2% glutaraldehyde . After treatment with osmium tetroxide , brains were embedded in Epon ( Fluka , Buchs SG , Switzerland ) . Semithin ( 1 µm ) coronal sections were cut from hippocampus and cerebral cortex . To quantify the number of DG neurons with degenerative features , we performed morphometry on semithin sections by scoring the percentage of DG neurons with abnormal morphology and vacuoles in the cytoplasm , and by counting the number of neurons in the DG and CA1 areas ( n = 3 per genotype ) . Morphometric analyses were performed blinded to the mouse genotype . For ultrastructural analyses , blocks of tissue were selected for electron microscopy after light microscopy examination of semithin sections . Ultrathin sections ( 70 nm ) were cut , collected on 200 mesh copper grids ( Electron Microscopy Sciences , Hatfield , PA , USA ) and stained with uranium acetate ( Plano GMBH , Wetzlar , Germany ) and lead citrate ( Electron Microscopy Sciences ) . To obtain specific probes for in situ hybridization , the coding sequence of the mouse Phb2 ( nucleotides 1–900 ) cDNA was PCR-amplified from mouse liver cDNA , subcloned and used as templates to transcribe either sense or antisense digoxygenin-labeled riboprobes using the DIG RNA labeling kit ( Roche ) . Vibratome sections were permeabilized with proteinase K ( 10 µg/ml ) for 10 min . In situ hybridization was performed essentially as described previously [59] . Frozen brain cryosections were thawed and incubated in COX staining solution ( DAB , cytochrome c , sucrose , catalase , phosphate buffer pH 7 . 4 ) , SDH staining solution ( succinic acid , phosphate buffer pH 7 . 4 ) or both in a humid chamber for 15 min at 37°C . Slides were washed three times with water for 5 min . For dehydration samples were incubated in increasing concentrations of ethanol: 90% EtOH for 1 min , 95% EtOH for 1 min and 100% EtOH for 1 min . Subsequently , the sections were washed two times in xylol for 2 min each and finally mounted in mounting medium . Mouse primary hippocampal neurons were isolated from E18 . 5 embryos ( Phb2fl/fl and Phb2fl/wt ) and grown on coverslips for 7 DIV before transduction with lentiviral vectors . Detailed experimental procedures are found in the supplement .
|
Mitochondria are the major site of cellular ATP production and are essential for the survival of neurons . High ATP levels are required to sustain neuronal activities and axonal transport of macromolecules and organelles . The functional integrity of mitochondria depends on fusion and fission of their membranes , which maintain a dynamic mitochondrial network in cells . Interference with these processes causes neurodegenerative disorders that are characterized by axonal degeneration of distinct neurons . However , how an impaired fusion affects mitochondrial activities and neuronal survival remains poorly understood . Here , we have addressed this question by analyzing forebrain-specific knockout mice lacking prohibitins . Prohibitin complexes form membrane scaffolds in the inner membrane , which we now show are required for mitochondrial fusion , ultrastructure , and genome stability in neurons . Loss of prohibitins triggers extensive neurodegeneration associated with behavioral and cognitive deficiencies . Surprisingly , we observe hyperphosphorylation and filament formation of the microtubule-associated protein tau , reminiscent of a large group of neurodegenerative disorders termed tauopathies . Our findings , therefore , not only provide new insight into how defects in mitochondrial fusion affect neuronal survival , but also point to an intimate relationship of deficiencies in mitochondrial dynamics and tau pathologies .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"biochemistry",
"neurological",
"disorders",
"neurology",
"genetics",
"biology",
"molecular",
"cell",
"biology",
"neuroscience",
"genetics",
"and",
"genomics"
] |
2012
|
Loss of Prohibitin Membrane Scaffolds Impairs Mitochondrial Architecture and Leads to Tau Hyperphosphorylation and Neurodegeneration
|
The high mutation rate of hepatitis C virus allows it to rapidly evade the humoral immune response . However , certain epitopes in the envelope glycoproteins cannot vary without compromising virus viability . Antibodies targeting these epitopes are resistant to viral escape from neutralization and understanding their binding-mode is important for vaccine design . Human monoclonal antibodies HC84-1 and HC84-27 target conformational epitopes overlapping the CD81 receptor-binding site , formed by segments aa434–446 and aa610–619 within the major HCV glycoprotein E2 . No neutralization escape was yet observed for these antibodies . We report here the crystal structures of their Fab fragments in complex with a synthetic peptide comprising aa434–446 . The structures show that the peptide adopts an α-helical conformation with the main contact residues F442 and Y443 forming a hydrophobic protrusion . The peptide retained its conformation in both complexes , independently of crystal packing , indicating that it reflects a surface feature of the folded glycoprotein that is exposed similarly on the virion . The same residues of E2 are also involved in interaction with CD81 , suggesting that the cellular receptor binds the same surface feature and potential escape mutants critically compromise receptor binding . In summary , our results identify a critical structural motif at the E2 surface , which is essential for virus propagation and therefore represents an ideal candidate for structure-based immunogen design for vaccine development .
An estimated 180 million people worldwide are infected with Hepatitis C virus ( HCV ) . Only about 20% of the infected individuals are able to spontaneously clear the virus during acute infection leading to chronic infection in 80% of the cases . Chronic HCV infection is a major cause of liver cirrhosis and liver cancer and therefore became the leading indication for liver transplantation [1] , but the rapid re-infection of the engrafted liver leads to poor survival rates of transplanted patients [2] . One of the major challenges in HCV therapy is the great genetic diversity of the virus resulting from the rapid and error-prone activity of the RNA polymerase NS5B . Consequently , the six major genotypes differ by up to 30% at the nucleotide level [3] and within the major glycoprotein E2 by up to 34% at the amino acid level . The rapid replication results in generation of up to 1012 virus particles per day in an infected individual , representing a population of circulating variants that can quickly react to selective pressures such as the adaptive host immune response or antiviral therapies . This requires special considerations for the design of vaccines and therapeutics . The current HCV therapy includes pegylated alpha interferon ( IFN-α ) , ribavirin and one of the recently approved HCV NS3 protease inhibitors Boceprevir and Telaprevir for genotype I infections [4] , [5] , and IFN-α and ribavirin for infections with other genotypes . However , the limitations of these regimens are the associated severe side effects [6] and sustained virological response ( SVR ) rates that vary considerably with the viral genotype . The natural emergence of viruses resistant to both of the available direct-acting antivirals [7] suggests that HCV will remain a major global health burden despite the approval of the recently developed antiviral strategies , illustrating the urgent need for development of a safe and efficient HCV vaccine . The role of neutralizing antibodies in the course of HCV infection in vivo has been analyzed by a number of studies . A protective effect for anti-HCV antibodies was suggested by screening of HCV-infected patients receiving Hepatitis B polyclonal immunoglobulins containing anti-HCV antibodies [8] . Also , antibodies directed against the major envelope glycoprotein E2 were shown to prevent non-homologous virus infection after vaccination in chimpanzees [9] . Broadly neutralizing human polyclonal and monoclonal antibodies ( mAbs ) protected in a passive transfer experiment against heterologous virus challenge in human liver–chimeric Alb-uPA/SCID mice [10] , [11] . Various studies provided evidence that the presence of high titers of neutralizing antibodies are associated with viral clearance during acute HCV infection [12] , [13] , and that these antibodies are directed to specific epitopes [14] . More recently , a broadly neutralizing human mAb was reported to prevent and treat HCV infection in chimpanzees [15] . Lastly , immunization of immunocompetent humanized mice with vaccinia virus expressing HCV structural proteins resulted in a robust antibody response that protected from challenge with heterologous HCV in some of the animals , and correlated with the serum level of antibodies to E2 [16] . A key challenge for the design of a safe and efficient B-cell vaccine is to know whether the elicited antibodies permit the virus to escape from neutralization by mutations in the viral glycoproteins . This has been suggested by several studies analyzing the mechanism of escape from neutralizing antibodies [17] , [18] , [19] , [20] , identifying three patterns of virus escape for JFH-1 HCVcc propagated under selective immune pressure by increasing concentrations of a neutralizing antibody [20] . These results underscore the ability of the virus to react to selective pressure exerted by neutralizing antibodies and emphasize the need to find highly conserved epitopes that are not associated with virus escape . Recently , we identified a group of broadly neutralizing , human monoclonal antibodies termed HC84-1–HC84-27 [21] from a random paired scFv-expressing yeast display library . This group of antibodies recognizes a cluster of conformational epitopes that lie within a continuous region in HCV E2 encompassing residues 434 to 446 ( according to H77 polyprotein numbering ) termed “epitope II” [22] . In addition , most of these mAbs appear to have an additional contact at tryptophan 616 . The fact that no virus escape was observed upon passaging of a genotype 2a isolate in the presence of any of those antibodies indicated that this cluster of epitopes is resistant to neutralization escape [21] . Epitope II is involved in binding the cellular receptor CD81 [23] , which is in line with the fact that the HC84 antibodies inhibit binding of E2 to CD81 [21] . Based on the assumption that HCV E2 adopts a class II fusion protein fold we have recently reported a model of the domain organization of HCV E2 suggesting that the glycoprotein is composed of three domains: DI , DII and DIII , as in the “class II” fusion proteins from flaviviruses and alphaviruses [24] . The recently reported structure of the major glycoprotein E2 of the closely related pestiviruses showed , however , that this assumption does not hold for the pestivirus E2 , which is an elongated molecule consisting of four β-sandwich domains arranged linearly from N to C terminus [25] and does not have a class II fold . These results therefore cast doubt on a class II based model for HCV E2 . Epitope II elicits neutralizing antibodies [21] as well as non-neutralizing antibodies that interfere with neutralizing antibodies directed against a conserved linear epitope located within residues 412 to 423 [26] . Notably , conflicting findings on the relationship of antibodies to epitope II and aa412–423 have been reported recently , showing mainly additive neutralizing activities when antibodies against both epitopes were combined [27] , [28] . The crystal structure of a synthetic peptide mimicking the epitope aa412–423 has been reported recently in complex with Fab fragments derived from broadly neutralizing antibodies . It shows a β-hairpin conformation that exists as an exposed flap-like structure with an N-linked glycan at one side and the antibody binding to the other side [29] , [30] , [31] . In the present study we report the crystal structures of Fab/peptide complexes derived from two human mAbs of the HC84 group ( HC84-1 and HC84-27 , respectively ) . The peptide is derived from the epitope II ( 434-NTGWLAGLFYQHK-446; residues in bold are highly conserved across genotypes ) . These structures reveal the determinants of the mAb interaction with this cluster of epitopes , allowing for improved design of immunogens properly presenting one of these epitopes .
We had previously reported that the human monoclonal antibodies HC84-1 and HC84-27 bind to a peptide encompassing residues 434–446 of the precursor polyprotein of the H77 strain , although the interaction depends on the epitope conformation [21] . Therefore , we performed co-crystallization trials at 20°C as described in Materials and Methods . Both complexes crystallized and diffracted to at least 2 . 2 Å resolution ( Table 1 ) . The structures were determined by the molecular replacement method using the variable and constant regions of an unrelated human Fab fragment as separate search models ( see Materials and Methods ) . Difference maps calculated after refinement of the recombinant Fab molecules revealed well-defined electron density for the peptide in both structures ( Figure S1 ) , which we used to manually build an atomic model . The resulting structures of the two complexes are displayed in Figure 1 . Because the observed peptide conformation could be influenced by its crystalline environment , we analyzed the packing contacts in both crystals . The HC84-1 complex crystals ( space group C2221 ) showed that the epitope II peptide packs about a 2-fold axis of the crystal against its counterpart from a symmetry related complex ( grey arrow , see Figure S2A ) , implying that crystal contacts could affect its conformation . However , in the complex with HC84-27 ( space group P1 ) , the peptide makes no crystal packing contacts and yet it adopts a very similar conformation ( Figure S2B ) . These observations are strong indications that the peptide conformation observed in both structures corresponds to the one present in the native polypeptide chain . Given that receptor-blocking neutralizing antibodies like the HC84 antibodies bind to the surface of the native virion , we conclude that this peptide conformation is similar to the one adopted by the corresponding segment of E2 at the virion surface . The peptide corresponding to epitope II forms a 1 . 5 α-helical turn spanning residues W437-F442 displaying the typical extensive main chain hydrogen bonding pattern of an α-helix ( Table S4 ) . It continues at the C-terminal side of the helix in an extended conformation comprising residues Y443-K446 ( Figure 2A+D ) . No electron density was observed for the N-terminal residues ( one in HC84-1 and two in HC84-27 ) , indicating that they are disordered in the complex . These residues therefore likely do not participate in the epitope . A comparison of the structures of HC84-1 and HC84-27 showed important differences in the elbow angle between variable and constant domains of the Fabs ( 132° and 145° for HC84-1 and HC84-27 , respectively ) . In contrast , a superposition of the variable domains and the peptides of both complexes revealed only small differences , indicating a very similar antigen-binding mode for both Fabs . This was expected , because the two heavy chains are essentially identical ( apart from three residues at the N-terminus ) and the light chains share ∼76% identical amino acids in the variable region ( Figure 1C+D ) . Therefore , we will discuss the binding mode that is common to both Fabs and highlight differences that are due to sequence variation between the two antibodies . Antigen binding buries an area of 588 . 7 Å2 and 725 . 3 Å2 on HC84-1 and HC84-27 ( Table S1 ) , with shape complementarity indexes of 0 . 74 and 0 . 81 , respectively ( Table S2 ) [32] . The peptide is bound such that the N- and C-terminal ends interact with the heavy and light chain , respectively . At the heavy-chain side , the paratope forms a hydrophobic binding surface with contacts to W437-L441 within the short α-helical turn . This surface extends into a hydrophobic cavity into which the aromatic side chain of F442 at the C-terminal end of the epitope helix inserts ( Figures 1A–B and 3A–B ) . The walls of the cavity are formed by residues from all three heavy-chain complementarity determining regions ( CDRs ) and framework residues around the CDR-H2 loop . The peptide makes essentially hydrophobic interactions with the heavy chain ( Table S3 ) , as highlighted by the hydrophobicity pattern of the paratopes ( Figure 3A–B ) . The peptide/Fab complexes are further stabilized by hydrogen bonds between the peptide main chain and the CDR-H3 loop ( Table S3 ) . On the peptide side , analysis of the solvent-accessible surface area that is buried in the complex shows that mainly residues L441 and F442 interact with the heavy chain , with 60–90% of their solvent accessible surface area buried by heavy chain binding . The interactions with the light chain include an extensive hydrogen-bonding network by the side chain of K446 to the CDR-L1 and CDR-L2 loops and in case of HC84-1 also the CDR-L3 loop . This is further stabilized by a hydrogen bond between Y443 at the N-terminal part of the extended segment and SL93 within the CDR-L3 loop . In addition , there are stacking interactions between WL90 and Y443 . The C-terminal extended segment of the peptide crosses the edge of the cavity with the side chain of Q444 forming a hydrogen bond to QL49 and van der Waals interactions with YL31 of HC84-27 . It terminates with the side chain of K446 forming a salt bridge with DL50 . In mAb HC84-1 YL31 is replaced by serine and QL49 is replaced by aspartic acid , leading to a change of the Q444 side chain conformation when compared to the HC84-27 complex and loss of the respective side chain interactions . This altered conformation results in a drastically decreased buried surface area of Q444 ( 20 . 06 Å2 and 133 . 76 Å2 for HC84-1 and HC84-27 , respectively; Figure 2F–G ) . Likely , the loss of these interactions is the main reason for the considerably smaller solvent-accessible surface area on the light chain buried by peptide binding ( 242 . 7 Å2 and 337 . 8 Å2 for HC84-1 and HC84-27 , respectively ) . This is also reflected in the total buried solvent-accessible surface area on the Fab ( Table S1 ) . The main contact residues for HCV E2 binding of both monoclonal antibodies have been mapped to L441 and F442 by alanine scanning mutagenesis [21] . In addition , HC84-27 binding is impaired by substitution of residues Y443 and K446 as well as one residue located in region II ( W616 ) . In line with these epitope mapping data the structure of the HC84-27 complex revealed additional electron density close to a distinct region of the paratope with contacts to the CDR-L3 loop and possible main chain interactions with the C″-strand of the HC84-27 heavy chain ( Figure 4A–D ) . This electron density was clear enough to trace the main chain , but not the side chains and suggested a second binding site , which was not present in the corresponding HC84-1 complex , thereby correlating with an additional contact residue for HC84-27 at W616 . The presence of this extra density in a binary complex of HC84-27 and the epitope II peptide suggested a binding event independent of the amino acid sequence . We therefore also determined the structure of a ternary complex HC84-27 with two peptides ( epitope II and a peptide corresponding to aa610–619; peptide 2 ) , but although density in the second binding site appeared better defined , we were still unable to unambiguously assign side chains . Extensive experiments to characterize the Fab/peptide interaction at this second binding site ( e . g . , cocrystallization of a HC84-27 in complex with peptide aa610–619 ) did not further clarify the interactions between peptide 2 and the Fab fragment at this binding site . Further biochemical and structural studies will be required to unambiguously identify the binding mode at this second binding site of HC84-27 . Superposition of the epitope II peptide from the two complexes revealed a root mean square deviation ( rmsd ) per residue of 0 . 2–0 . 9 Å for the segment A439-Y443 calculated over all atoms ( Figure 2B , dark grey ) , which is close to the positional error of the coordinates . In contrast , for residues outside this central helical region the rmsd was 1 . 6–3 . 9 Å . The amino acid backbone of the framing residues ( L438 , Q444 and H445 ) is also structurally very similar as revealed by calculation of the rmsd over the main chain ( Figure 2B , light grey ) . The marked difference between the two rms deviations observed for those residues ( calculated over the main chain and over all atoms , respectively ) showed that the main chain adopts a defined conformation , while the corresponding side chains are more flexible . We also calculated the mean temperature factors ( B-factors ) per residue for both peptides and observed a similar distribution over the peptide . B-factors for A439-Y443 were at least ∼10 Å2 lower than for residues outside of this region ( Figure 2C ) . Together with the contact analysis , these results strongly suggest a highly ordered and stable antibody/antigen complex interface and an interaction that is dominated by hydrophobic contacts between the heavy chain CDRs ( and framework residues surrounding the CDR-H2 ) and the short α-helical turn within epitope II . Antibody diversity is generated by the combinatorial association of V , D , and J germline segments , and is further diversified at the actual junctions ( VL–JL , VH–D , and D–JH ) due to imprecise joining and addition of “N region” nucleotides . Somatic mutations , possibly driven by antigenic selection , can further contribute to the diversity of antibodies and lead to increased affinity and specificity during antibody maturation [33] , [34] . Germline analysis using IMGT V-QUEST and junction analysis [35] of the HC84-1 and -27 antibodies revealed the closest homologous germ-line genes to be IGHV1-69*01 F , IGHJ4*02 F and IGHD3-22*01 for the almost identical heavy chains . The light chain of HC84-1 uses IGLV3-1*01 F and IGLJ1*01 F and the light chain of HC84-27 is derived from IGLV3-21*03 F and IGLJ2*01 F , the two VL genes being 75% identical at the amino acid level . Heavy chains derived from IGHV1-69*01 F are frequently found in antibodies directed against HCV E2 [36] , [37] , indicating that this VH gene is preferentially used in the specific immune response to HCV E2 . Interestingly , a group of antibodies recognizing the coreceptor-binding site on human immunodeficiency virus ( HIV ) gp120 selectively uses the same VH gene . This has been attributed to a strict dependence on a hydrophobic patch in the CDR-H2 , given that IGHV1-69 is the only VH gene with hydrophobic residues at specific positions forming contacts that are conserved within this group of antibodies [38] . These residues ( IH52 and FH55 ) are also conserved in HC84-1 and -27 and contribute to the important hydrophobic interactions with L441 and F442 . A more exhaustive sequence analysis revealed that all nine HC84 antibodies use the same VH gene and while IH52 is conserved across all heavy chains , FH55 is in some antibodies replaced by other hydrophobic amino acids thereby maintaining the hydrophobic surface . In contrast , the VL gene usage within the HC84 antibody group is much less conserved as indicated by the usage of three different kappa VL genes and three different lambda VL genes . While we cannot fully exclude that the LC of HC84-1 and -27 derive from the same germline rearrangement and hence represent two ( closely related ) outcomes of a single clonal lineage , the LC diversity observed in the HC84 group shows no requirement for a particular lineage within the HC84 group . Given that the HC84 group has been isolated from a combinatorial library it remains unknown , if heavy and light chains of the two antibodies were paired in the original patient , however , peptide-reactive antibodies against epitope II have been found with high prevalence in patient sera compared to antibodies of other specificities [28] . Together with the neutralizing activity of these patient antibodies [28] , the specific binding mode that is dominated by the heavy chain and the similar biological activities and epitope mapping results for the nine HC84 antibodies , these observations suggest that HC84-1 and HC84-27 could be found in HCV infected patients . We aligned the HC84-1 and -27 antibodies to their closest homologous germ-line genes and identified somatic mutations in this alignment ( Figure 1C+D , asterisks ) . Antibodies using the IGHV1-69 gene often acquire somatic mutations during antigenic selection that are located in or close to the CDRs , indicating a positive selection for antigen binding [37] . Mapping of the junction in CDR-H3 and the somatic mutations onto the molecular surface of the paratope revealed that this junction encloses the hydrophobic cavity at one side ( Figures 4D+E ) . The ridge on the opposite side of the cavity is formed by MH59 downstream of CDR-H2 and SL93 and NL93 in HC84-1 and HC84-27 , respectively , both of which make a hydrogen bond to the OH atom of Y443 . Together this demonstrates that the junction in CDR-H3 and somatic mutations acquired during antibody maturation contribute to the formation of the hydrophobic surface binding the epitope II peptide . One major challenge for neutralizing antibodies in the course of HCV infection is the highly diverse population of viral variants that is found in patients . In the presence of neutralizing antibodies escape variants within this virus population will have a selective advantage over neutralization-sensitive variants . In spite of this , mAbs HC84-1 and HC84-27 neutralize a broad spectrum of HCV genotypes and do not allow neutralization escape [21] . To understand the structural basis of this broadly neutralizing activity and the resistance to neutralization escape we analyzed ∼7000 epitope II sequences from the Los Alamos HCV database ( http://hcv . lanl . gov ) . While T435 , G436 , A439 and Y443 are highly conserved , Q444 and H445 are much less conserved ( Figure 2E ) . Sequence analysis of position 446 revealed that a large majority of sequences carry either lysine or arginine , indicating a requirement for a positively charged residue at this position . F442 , which is a key determinant of binding to both broadly neutralizing antibodies , is surprisingly poorly conserved ( ∼60% of the sequences ) . Notably , sequence analysis revealed that F442 can be replaced only by a bulky hydrophobic residue in the remaining sequences ( e . g . , isoleucine or leucine ) , which is likely to also insert into the hydrophobic pocket . Similar effects were observed for L438 and G440 , which are also less conserved , but are replaced in the majority of the cases by isoleucine and alanine , demonstrating the requirement for a hydrophobic and small amino acid , respectively ( Figure 2E ) . In solution , the isolated epitope II peptide is likely to adopt multiple conformations that are in equilibrium with each other , and the antibodies select the observed conformation for binding . Secondary structure predictions of E2 using different algorithms indeed provide contradictory results for this segment ( Figure S3 ) with only a minority of the algorithms predicting the observed α-helical turn . Within folded E2 , this segment would not be free to adopt multiple conformations , and the fact that the antibodies recognize folded E2 means that the binding determinants are presented in the same way at the protein surface . Our results imply that the aromatic side chains of F442 and Y443 are both exposed on one side of the helix , and to a lesser extent also the aliphatic side chains of L438 , A439 and L441 . Of these amino acids , systematic mutagenesis studies have shown that only L438 and A439 tolerate mutations without compromising CD81 binding and thus viability of the virus [23] , suggesting that the other exposed residues within this region directly participate in receptor binding . The organization of the epitope II region is therefore compatible with the hydrophobic patch in CD81 that was identified as the target pocket [39] . Such patches on the surface of glycoproteins are often shielded from solvent by N-linked glycans . The protruding patch formed by residues F442 and Y443 ( Figure 3C+F ) is very close in sequence to glycan N4 ( corresponding to N448 ) , suggesting a role of this glycan in masking this region of the protein . This is also in line with the reported glycan shielding of the CD81 binding site , with glycans attached to N417 ( N1 ) , N423 ( N2 ) , N448 ( N4 ) , N532 ( N6 ) and N645 ( N11 ) modulating the sensitivity of HCV infectious particles ( HCVcc ) to neutralizing antibodies [40] . While the presence of glycan N4 thus potentially complicates the design of an efficient E2 vaccine targeting the hydrophobic protrusion within epitope II , the viability of a mutant N448Q HCVcc JFH-1 virus is not compromised [40] , indicating a valid alternative for both life vaccines and subunit vaccines consisting of recombinant HCV E2 . It is also worth noting that the observed organization of the epitope II region is reminiscent , as pointed out by Drummer and colleagues [23] , of the aromatic and glycine rich fusion loop of class II fusion proteins . In the case of the flavivirus envelope protein , the fusion loop also features an α-helical turn exposing aromatic and aliphatic side chains , similar to the observed conformation of epitope II in our structures . Our previous model for the domain organization of the HCV E2 ectodomain used the experimental disulfide connectivity and biochemical data on the composite nature of the CD81 binding site , but it also relied heavily on the assumption that the members of the various genera of the Flaviviridae family would have structurally homologous membrane fusion proteins in spite of a lack of sequence conservation [24] . This was strengthened by the observation that the membrane fusion proteins from the alphaviruses ( Togaviridae family ) , and now also from the phleboviruses ( a genus within the Bunyaviridae family of negative sense RNA viruses; [41] ) share the common “class II” fusion protein fold in the absence of any sequence conservation . The recently reported structure of the E2 glycoprotein of bovine viral diarrhea virus ( BVDV-1; PDB accession code 2YQ2 ) , a member of the closely related pestivirus genus within the Flaviviridae family , demonstrated that pestivirus E2 does not have a class II fold , and may have receptor binding function but not be responsible for membrane fusion . BVDV E2 is an elongated molecule consisting of four sequential β-sandwich domains arranged linearly and named A through D from N- to C-terminus [25] . This structure gives space for three alternative models for the domain organization of the HCV E2 ectodomain . If HCV E2 were homologous to BVDV E2 , the data from the antibody/peptide complexes , using the structures of epitope 413–423 [29] , [30] , [31] and now of epitope II , would suggest that domain A would be relatively unstructured , with the hypervariable region 1 ( HVR1 ) at the N-terminus , followed by the flap formed by aa412–423 that is not part of a folded domain and extending to the epitope II region that can be mimicked by an isolated peptide . This interpretation is in line with the observed disulfide bond that links a cysteine at the very N-terminus of pestivirus E2 with another one further downstream , stabilizing the fold of pestiviral domain A; this cysteine is absent in HCV E2 allowing for increased structural flexibility of the HVR1 . If such a model were correct , the data concerning the CD81 contact residues would suggest that the CD81 binding domain would be centered in domain B , and parts of domain A ( aa412–423 and the epitope II region ) and domain C ( the 613–618 region ) would contribute to receptor binding . The current evidence does not rule out , however , that E2 HCV may indeed be a class II fusion protein . The lipid binding properties of CD81-primed , acid-treated HCV E2 [42] would be in line with a role in interactions with cellular membranes for virus entry . In this case , the recent structures of Fab/peptide complexes indicate that the assignment of domain I would have to be revised to begin after the aa413–123 “flap” region , and the strands reassigned such that the 1 . 5 helix of epitope II would be at the interface with domain III , indicating that residues currently assigned to domain II would have to complete domain I . Domain II would thus be smaller by about 6 residues . Finally , the last hypothesis is that the HCV E2 glycoprotein adopts an entirely unrelated fold . Notably , the evolutionary constraints on the overall fold of an attachment glycoprotein are more relaxed than those for a fusion protein , which potentially leads to less structural similarity , and in some cases altogether different genes may be used for otherwise related viruses , like is the case between the arenaviruses and the bunyaviruses . In conclusion , there are too many uncertainties left and only a structure of the HCV E2 ectodomain - or at least an isolated domain - can provide a definite answer . Nevertheless , the crystal structure of the epitope II in complex with two broadly neutralizing human antibodies provide structural insight into the neutralization mechanism of two antibodies of the HC84 group . Together with the sequence analysis of epitope II , it also provides evidence to explain why these antibodies are resistant to neutralization escape . Structural knowledge about interactions between broadly neutralizing antibodies – in particular those that are resistant to neutralization escape – is essential to understand the immune response against HCV E2 and to employ structure-based vaccine design to elicit neutralizing antibodies of similar specificity and efficiency [43] .
Synthetic genes that were codon optimized for Drosophila melanogaster coding for heavy and light chains of the Fab regions of each antibody were cloned into a Drosophila S2 Fab expression vector described previously [44] containing a double Strep tag for efficient affinity purification . Drosophila S2 cells were transfected as reported previously [45] . For large-scale production cells were induced with 4 µM CdCl2 at a density of approximately 7×106 cells/ml per ml for 8 days , pelleted and Fabs were purified by affinity chromatography from the supernatant using a StrepTactin Superflow column followed by size exclusion chromatography using a Superdex200 column . Pure monomeric Fab was concentrated to approximately 20 mg/ml . Synthetic peptides comprising either the epitope II region ( residues 434–446 - NTGWLAGLFYQHK ) or a region located further downstream ( residues 610–619 - DYPYRLWHYP ) of the H77 strain were synthesized by GenScript ( >98% purity ) and dissolved in water at 10 mg/ml . A complex was formed overnight at 277 K containing 10 mg/ml Fab+0 . 9 mg/ml epitope II peptide ( HC84-1 ) , 10 mg/ml Fab+1 . 5 mg/ml epitope II peptide ( HC84-27+one peptide ) or 10 mg/ml Fab+0 . 9 mg/ml of each peptide ( HC84-27+two peptides ) . Fab crystals in complex with were grown at 293 K using the hanging-drop vapor-diffusion method in drops containing 1 µl complex solution ( 10 . 9–11 . 8 mg/ml in 10 mM TRIS pH 8 . 0 , 150 mM NaCl ) mixed with 1 µl reservoir solution containing 100 mM TRIS pH 8 . 0 , 19% PEG4000 , 170 mM Lithium Sulfate and 15% Glycerol ( HC84-1 ) or 22–24 . 6% PEG 3350 and 250–300 mM Sodium Thiocyanate ( HC84-27 ) . Diffraction quality plates ( HC84-1 ) or rock-like ( HC84-27 ) crystals appeared after one week and were flash-frozen in mother liquor with ( HC84-27 ) or without ( HC84-1 ) 22% PEG400 . Spacegroups and cell dimensions of the crystals , resolution limits , data collection details and refinement statistics are summarized in Table 1 . Data were collected at the SLS ( PX I ) and the Synchrotron Soleil ( Proxima1 ) . Data were processed with Autoproc [46] using XDS [47] and scaling and reduction was performed using Pointless [48] and programs from the CCP4 suite [49] . The crystal structures of the Fab complexes were determined by the molecular replacement method using Phaser [50] . The molecular replacement for Fab HC84-27 was performed using separate variable and constant regions of a hypothetical Fab fragment assembled from the LC of PDB accession code 2XZA ( 81% aa identity ) and the HC of PDB accession code 3QOT ( 89% aa identity ) as search model . The molecular replacement for Fab HC84-1 was performed using Fab HC84-27 as search model . Model building was performed using Coot [51] and refinement was done using AutoBuster [52] . The two peptides derived from the complexes of HC84-1 and -27 in complex with only epitope II were aligned using the MatchMaker algorithm implemented in Chimera and an iterative alignment process pruning long atom pairs until no pair exceeds 1 Å . Root mean square deviations were calculated between the two epitope II peptides either over all atoms per residue or taking into account only the main chain atoms ( N , CA , C , O ) using Chimera [53] . Buried solvent accessible surface areas for the interfaces as well as for individual residues within the peptides were calculated using the PISA server [54] . Shape complementarity was calculated using programs of the CCP4 suite [49] . Interactions were determined using the protein interactions calculator ( PIC; [55] ) . Figures were prepared with Pymol ( http://www . pymol . org ) . 6998 sequences were taken from the Los Alamos HCV sequence database and ( http://hcv . lanl . gov ) analysed using the tools of the ViPR database ( http://www . viprbrc . org ) . Secondary structure prediction was performed using all algorithms on the Network sequence analysis server ( NPS@ , Network Protein Sequence Analysis , http://pbil . ibcp . fr/NPSA; [56] ) . The atomic coordinates and structure factors for two crystal structures have been deposited in the Protein Data Bank , www . pdb . org , under the accession numbers 4JZN and 4JZO .
|
We report here the crystal structures of two neutralization-escape-resistant human monoclonal antibodies in complex with their peptide epitope . Recognition of the hepatitis C virus ( HCV ) by the humoral immune response is hampered by the high variability of the envelope glycoproteins . However , the contact site analyzed here involves residues that also are believed to interact with the HCV receptor CD81 , which the virus cannot mutate without losing viability . The structures reveal a short α-helix in the epitope projecting two hydrophobic residues into a hydrophobic pocket in the paratope , which we propose is similar to the interaction with the receptor . Our results therefore have important implications for vaccine design against this major human pathogen .
|
[
"Abstract",
"Introduction",
"Results",
"and",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"hepatitis",
"c",
"biomacromolecule-ligand",
"interactions",
"medicine",
"biochemistry",
"infectious",
"diseases",
"infectious",
"hepatitis",
"hepatitis",
"gastroenterology",
"and",
"hepatology",
"immunology",
"biology",
"viral",
"diseases",
"liver",
"diseases",
"immunoglobulins"
] |
2013
|
Structural Basis of HCV Neutralization by Human Monoclonal Antibodies Resistant to Viral Neutralization Escape
|
When deciding between alternative options , a rational agent chooses on the basis of the desirability of each outcome , including associated costs . As different options typically result in different actions , the effort associated with each action is an essential cost parameter . How do humans discount physical effort when deciding between movements ? We used an action-selection task to characterize how subjective effort depends on the parameters of arm transport movements and controlled for potential confounding factors such as delay discounting and performance . First , by repeatedly asking subjects to choose between 2 arm movements of different amplitudes or durations , performed against different levels of force , we identified parameter combinations that subjects experienced as identical in effort ( isoeffort curves ) . Movements with a long duration were judged more effortful than short-duration movements against the same force , while movement amplitudes did not influence effort . Biomechanics of the movements also affected effort , as movements towards the body midline were preferred to movements away from it . Second , by introducing movement repetitions , we further determined that the cost function for choosing between effortful movements had a quadratic relationship with force , while choices were made on the basis of the logarithm of these costs . Our results show that effort-based action selection during reaching cannot easily be explained by metabolic costs . Instead , force-loaded reaches , a widely occurring natural behavior , imposed an effort cost for decision making similar to cost functions in motor control . Our results thereby support the idea that motor control and economic choice are governed by partly overlapping optimization principles .
Should I rather bring the groceries from the car trunk to the kitchen in 1 trip or in 2 trips ? Even in a seemingly simple decision like this , multiple decision parameters are at odds . When doing a single trip , this bothersome task will certainly be finished more quickly but will require an intense physical effort . This choice might also put one at risk to drop everything on the way . On the other hand , when making 2 trips , each will be less effortful and safer but the task will take longer to complete . When examined through the prism of economics , this example shows 2 alternatives with an equal reward but different amounts and types of costs: risk , time , and effort . Utility theory [1] posits that these decision parameters are combined in a single value , the utility , which characterizes the desirability of each choice as whole . The ways in which costs affect the utility of an option have been well described for risk ( prospect theory [2] ) and delay ( hyperbolic temporal discounting [3] ) . Defining such a relationship is not straightforward for effort . Physical effort [4] , in contrast to mental effort [5] , can at least be related to an external , physically measurable variable , in the same way that reward delay is used in the example of temporal discounting . Therefore , we focus on physical effort , defined here as the subjective cost or negative utility associated with a given motor action , independent from the costs resulting from its success rate ( risk ) or delayed reward ( temporal reward discounting ) . Studies focusing on the brain circuits involved in physical effort-based decision making in humans have used handle-squeezing tasks to produce different effort levels , but they just assumed that subjective effort increases monotonically with isometric squeezing force , without further characterizing the dependency [6 , 7] . Using a similar task , Hartmann and colleagues [8] showed a quadratic discounting of monetary rewards by squeezing force , suggesting that effort for isometric force production grows proportionally to the square of the force amount . In contrast , by pitting isometric force production with different parameters directly against each other , Körding and colleagues defined effort as a function of both the duration and magnitude of force production , without the need to use an external monetary scale [9] . By using 2 parameters in a force-production task , this latter study highlighted the multifaceted nature of physical effort . The use of isometric force-production tasks to probe physical effort discounting is , however , still limiting compared to the full range of effort-related parameters one could experience when deciding between actual movements . Here we characterize the influence of duration , distance , direction , and force on subjective effort costs in actual reaching movements . From the perspective of motor control , planning and executing a movement , even towards an unambiguous goal , requires commitment to a specific motor act among an infinite amount of potential ways ( “choices” ) to acquire the goal . Decision making in this context can be seen as part of a continuum that includes motor planning and motor control , and minimizing various cost functions is a core concept of motor control: the stereotypical nature of movement trajectories and velocity profiles has been attributed to minimization of hand jerk [10] , endpoint variance [11] , and even control effort itself [12 , 13] . The potential tight link between decision making and motor control is supported by studies showing that action selection can take into account parameters that are related to movement execution , such as biomechanics [14 , 15] or motor accuracy [16] . Conversely , the vigor with which a movement is executed was shown to be explainable through delay discounting [17] . This raises the question of whether the subjective cost of an action as computed in a decision-making context ( i . e . , what we call effort here ) is comparable to potential cost functions used for optimization in motor control or , as an alternative , to the metabolic cost of the movement . Here we address this question by investigating how humans assess subjective physical effort in action-selection tasks involving binary choices between different reaching movements . In a first experiment , we varied movement duration , amplitude , and direction as well as resistive force in order to derive isoeffort curves in this duration–amplitude–direction–force space . This allowed us to independently test the sensitivity of subjects to impulse ( force × duration ) and work ( force × amplitude ) exerted during movements . In a second experiment , we pitted repeated identical movements against single movements with different resistive forces in order to obtain more precise estimates of the relationship between force and subjective effort in reaching movements .
In both experiments , subjects performed 2-alternative forced choice ( 2-AFC ) tasks in which they compared 2 different actions and were asked to choose the least effortful one ( Fig 1 ) . To make informed choices in each trial , subjects first performed both proposed actions ( sampling ) and then reported the least effortful action by executing it again ( choice ) . The need to repeat the chosen action rendered the choice relevant for the subjects , since genuine selection minimized the overall task effort . Both actions consisted of reach movements performed against different levels of resistive force . In each trial , one of the proposed actions served as a reference action , while the other served as a test action . Note that this distinction was not indicated and not relevant to the subjects but was part of our adaptive experimental design . Within each task condition , the trial-to-trial resistive force level in the test movements was selected with a staircase algorithm [18] , while the force level of the reference movements was kept constant . As a consequence , the staircases converged to the force level at which the test action was perceived as being equally effortful as the reference action ( equivalent force ) . In experiment 1 , reference and test actions consisted of single movements , differing primarily in amplitude or duration . More precisely , in each trial of the amplitude session , subjects had to choose between 2 movements that differed in amplitude , direction , and force ( after sampling both ) . Conversely , in each trial of the duration session , the choice was between movements that differed in duration , direction , and force . In both sessions , the staircase algorithm adjusted the forces of 1 of the movements , depending on the choice of the subjects , until both movements were subjectively equivalent in effort for the subject . This allowed us to construct isoeffort curves in the force–amplitude–duration movement parameter space ( Fig 1A–1D and Methods ) . In experiment 2 , the reference action consisted of 2 identical repeated movements and the test action of a single movement . This allowed us to determine the scaling of subjective effort with force ( Fig 1E and 1F ) . In experiment 1 , we asked subjects to conduct naturalistic reach movements against different force levels , either with varied durations independent of amplitude ( duration session ) or with varied amplitudes independent of duration ( amplitude session ) . As we used constant force profiles , these constraints correspond to dissociations either in impulse ( force integrated over time ) or work ( force integrated over distance ) , respectively . Fig 2A and 2B depict the average work and impulse produced by the manipulator as a function of force for the different duration and amplitude conditions in both sessions for a representative subject ( both integrated from the time of movement onset minus 100 ms to movement offset plus 400 ms ) . Impulse values were well separated in the duration session but not in the amplitude session , while work values were well separated in the amplitude session but not in the duration session . This confirms that visual instructions about reach-target location and requested movement duration together with the manipulator-controlled resistive force successfully constrained the actual movements of the subjects to the desired parameter ranges in each session ( sample trajectories and generated force profiles in S1 Fig and S1 Text ) . Importantly , the forces imposed by the manipulator had an additive effect on the torques that the subject’s arm actually needed to produce to generate the movements . Since the imposed forces were independent from arm kinematics , a simple biomechanical model of the arm ( S3 Text , S3 Fig , S4 Fig ) showed that over the duration of a movement , the torques the subjects produced to compensate the imposed forces outweighed the torques produced to compensate for the inertia of the arm . As a consequence , the total work and impulse actually produced by the subjects in the different conditions showed dissociations comparable to those observed in Fig 2A and 2B . Subjects’ choices did not systematically depend on performance differences in the various task conditions of experiment 1 , but they depended reliably on force levels ( S2 Fig , S2 Text ) . As a consequence , we could use equivalent forces to titrate the effort subjects associated with the explored movement parameters . In the amplitude session of experiment 1 , the equivalent forces did not vary significantly with movement amplitude ( linear mixed-effect model [LME] , p = 0 . 4 , effect size 0 . 3 N ) but varied significantly with reference force level ( LME , p < 0 . 001 , effect size 3 . 4 N ) ( Fig 2C ) . The result indicates that the 4-N difference between the reference forces was large enough for subjects to judge it as different in effort but that subjects were unaffected in choice by movement amplitude over the tested range when movement duration was kept constant . In other words , a movement of 120 mm against a force of 6 N was rated as effortful by the subjects as a movement of 200 mm against a force of 6 N . Since movement duration was constant in the amplitude session , the observed insensitivity to movement amplitude can also be interpreted as insensitivity to movement speed . In contrast , subjects were sensitive to movement duration when movement amplitude was kept constant in the duration session ( Fig 2D ) . Equivalent force levels were lower for long-duration movements than short-duration movements ( LME , p < 0 . 001 , effect size 3 . 8 N ) . Here , a movement in the 1 , 300–2 , 000 ms range against a force of 5 N was judged as effortful as a movement in the 0–800 ms range against a force of 9 N . This indicates that long-lasting reaches were perceived more effortful than brief reaches against the same force level . Additionally , the equivalent forces scaled with the reference force levels ( p < 0 . 001 , effect size 3 . 1 N ) without interaction between the factors force and duration ( p = 0 . 4 ) . Physical movement parameters like work or impulse , as defined above , describe the movement properties at the manipulator handle ( endpoint movement ) , irrespective of the required multijoint arm movement . Instead , effort evaluation and the resulting choice were based on subjective experience , to which the biomechanics of the movement could have contributed . In fact , biomechanics of the movement influenced effort judgment in our experiment . In both the amplitude and the duration sessions of experiment 1 , equivalent forces depended on the reference movement direction ( Fig 2C and 2D ) . Test movements performed inward ( i . e . , towards the left for right-handed subjects and vice versa ) required higher force levels to be judged as equally effortful as outward movements ( LME , amplitude session: p < 0 . 001 , effect size 1 . 5 N; duration session: p < 0 . 001 , effect size 0 . 9 N ) . This indicates that at the same force level , outward movements were considered more effortful than inward movements . This difference in equivalent force is likely linked to the use of larger muscles and the higher available strength for inward movements . After showing that duration and biomechanics but not amplitude had an influence on the effort judgment , we asked how effort would depend on the force itself . In Fig 2D , a thin dotted line represents an example isoeffort curve in the force–duration space: it connects the point representing parameters of a reference movement to the points representing parameters of equivalent-force test movements . Similar to this example curve , when averaging over movement directions in the duration session , isoeffort curves are convex for both reference force levels . This indicates that the putative effort cost function supporting the subjects’ choices was a nonlinear combination of force and movement duration . This is because if effort was a linear combination of force F and duration d , such as E ( F , d ) = αF + βd , the isoeffort curve defining the equivalent force of the test movement would have to be a straight line defined as FT=αFR+βdRα−βαdT . If , on the other hand , effort was a purely multiplicative function of force and duration—i . e . , assuming that the effort cost function is impulse E ( F , d ) = Fd—then this would lead to convex isoeffort curves shaped as the inverse function FT=FRdRdT . The isoeffort curve in Fig 2D is not straight , and the curvature does not fit the impulse model but is shallower instead . In experiment 2 , we determined the precise shape of the force–effort relationship for constant movement durations . Binary choices between 2 options only allow ranking the options in terms of preferred or nonpreferred . To describe effort as a function of force , additional information is needed to turn such a ranking into a scale with a continuous metric . This could be achieved by trying to compensate the effort cost of an action with an independent scalable benefit ( e . g . , monetary reward ) to achieve equal preference for movements of different force . But the utility function of the benefit must then be known , a task which might be as difficult to achieve as the task of determining the effort cost function itself . As an alternative , in each trial of experiment 2 , subjects chose between 2 options after having sampled both: either they opted for performing 2 similar movements in rapid succession against a reference force level FR ( the endpoint of the first movement is the starting point of the second movement ) , or they chose to perform a single movement against a test force level FT ( adjusted between trials by a staircase ) . Here we assume that an action consisting of 2 identical movements is twice as effortful as an action consisting of 1 of these movements , but both give the same benefit ( finishing the trial ) . Under this assumption , the equivalent forces FTeq ( staircase convergence point for forces FT in single test movements ) as a function of the reference movement force level FR ( fixed forces in double movements ) should follow the rule E ( FTeq ) = 2E ( FR ) , that is FTeq = E−1 ( 2E ( FR ) ) , with E ( F ) being the function linking force and subjective effort ( = cost function ) and E−1 being its inverse . As in experiment 1 , the observed decision behavior in experiment 2 was best explained by force-based choices rather than performance-based choices ( S2 Text ) . Results from experiment 2 thus allowed to test and fit models for both the cost function and its link to decisions , which we carried out using a Bayesian modeling approach ( see Methods ) . A direct observation of the equivalent force as a function of the reference force level is suited to highlight the properties required of E ( F ) . We computed equivalent forces in 2 ways: first as averages of the test-force levels at the staircase inversions ( i . e . , the asymptotic force to which the staircase procedure converged as in experiment 1 ) and second via points of subjective equality of the psychometric functions that resulted from the Bayesian model . Results of both approaches are illustrated for 2 example subjects in Fig 3A and 3B . Equivalent to the considerations regarding the isoeffort curves in experiment 1 , the simplest putative effort cost function is a linear function , E ( F ) = αF . For this , equivalent forces would have to obey the equation FTeq = 2FR ( steepest dashed red line ) , as we required E ( FTeq ) = 2E ( FR ) . However , in our data we observed that for large reference forces , the equivalent forces were smaller than predicted from the linear model . For example , for a FR of 9 N , subjects JP and MK showed equivalent forces of 12 and 14 N , respectively , instead of 18 N . This observation indicates that there was a convex nonlinear relationship between force and effort , in line with the results obtained from experiment 1 . Additionally , we observed that the equivalent forces for a FR of 0 N were larger than 0 N , confirming the intuition that a movement against no external force still has nonzero effort ( i . e . , that E ( 0 ) > 0 ) . Therefore , a power function with an offset , ( F ) = Fα + β , appears as a reasonable minimal model for the force–effort relationship ( Eq 2; see Methods ) , which we will use in the following sections . Our Bayesian modeling approach used the trial-by-trial choices of subjects as dependent data . Thereby , within the same unified framework , we simultaneously modeled ( 1 ) how forces affected effort values ( see paragraph above , Eq 2 ) and ( 2 ) how the subjects’ choices depended on these effort values ( Eq 1 ) . For the dependence of choice on effort , we answered 2 questions . Does utility show a subtractive discounting by effort ( i . e . , the difference in utilities on which decisions are based is equivalent to a difference between efforts in our task [Eqs 4 and 5] ) or a hyperbolic discounting by effort ( i . e . , the difference in utilities corresponds to a difference between effort inverses [Eqs 6 and 7] ) . Within each of these 2 alternatives , we tested whether effort was represented in a linear ( Eqs 5 and 6 ) or logarithmic scale ( Eqs 4 and 7 ) . This 2 x 2 design resulted in 4 alternative models obeying E ( FTeq ) = 2E ( FR ) , all with the same number of free parameters ( see Methods ) . Notably , all tested models had the same equation for the equivalent force curve ( Eq 3 ) ; the models only varied in the shapes of the choice curves—in particular , how the reference force FR affected their slope . We assessed model quality on the basis of 3 criteria . First , the percentage of correctly predicted choices ( binary predictions based on a comparison between the actual test force and fitted equivalent-force levels ) reflected the validity of the equivalent force curve as a decision boundary ( in red on Fig 3A and 3B ) . Second , we evaluated the fit of the model to the full choice probability curves ( in blue on Fig 3A and 3B ) by examining the corresponding residual distribution ( Fig 3F ) . Last , each fit was also tested by using the Watanabe–Akaike Information Criterion ( WAIC ) [19] , an approximation of cross-validation that allowed us to compute the relative likelihood between models . The model we ultimately selected ( and show in Fig 3A and 3B ) expressed choice probability as a function of the difference between the logarithms of reference and test efforts ( Eqs 1 , 2 and 4 ) and outperformed all other models , which we discuss below . The simplest model obeying E ( FTeq ) = 2E ( FR ) was based on a difference between test and reference efforts ( Eq 5 , no logarithms ) . The difference model predicted subjects’ choices as well ( 68 . 3% correct predictions ) as the selected logarithmic difference model ( 68 . 7% ) , meaning that the equivalent force curves were similar . But the difference model did not fit the choice probability curves nearly as well ( WAIC of 4 . 50e3 ) as the selected model ( 4 . 43e3 ) , making the difference model less likely by a factor of 6 . 3e–16 compared to the selected logarithmic difference model . Indeed , the distribution of residuals for the simplest model ( in red , Fig 3F ) , is wider than the distribution of residuals for the selected model ( in grey , Fig 3F ) . Both alternative models based on hyperbolic discounting of effort , whether computing choice probability from the difference between the inverse of efforts ( Eq 6 ) or the inverse of effort logarithms ( Eq 7 ) , showed lower prediction performances ( 66 . 9% and 63 . 8% ) , higher WAICs ( 4 . 76e3 and 5 . 09e3 ) , and wider residual distributions than the selected model and therefore had to be rejected . The results of this model-selection approach thus favor a subtractive discounting of utility by effort ( no hyperbolic discounting ) and a logarithmic internal representation of effort . By examining the posterior distributions of the selected model’s parameters ( Fig 3C–3E , Eqs 1 and 2 ) , we can interpret the equivalent force curves obtained in our subject population . Our main parameter of interest was the population average of the force exponent α in the power function described in Eq 2 , as it describes the nonlinear dependency of effort on force . The exponent α showed a narrow posterior distribution centered around 2 . This means that on average , the subjective effort rose with the square of the resistive force against a movement . Since the distribution is narrow , the confidence in this estimate is high ( 95% credible interval for the population average: 1 . 56–2 . 48 ) . For completeness , the posterior for the effort offset β ( 95% CI: 4 . 9–22 ) , reflecting the effort that subjects associated with performing a movement against no resistive force , and the posterior for γ ( 95% CI: 1 . 1–4 . 2 ) , reflecting the sensitivity of subjects to effort differences , are represented in Fig 3D and 3E , respectively . The biomechanics seemed to have played less of a role in experiment 2 . For the same reference force levels , we did not obtain different equivalent test forces between the 2 movement directions inward and outward . However , in contrast to experiment 1 , subjects never directly compared movements with different directions , as both options were in the same direction . This difference likely made experiment 2 much less sensitive in that respect .
Most studies on physical effort in human decision making operationalize effort by asking subjects to squeeze a handle that measures hand grip force [7 , 8 , 20 , 21] , a device that is easy to use and fMRI-friendly . The effort is then an isometric contraction of varying magnitude , expressed as a percentage of the maximum voluntary contraction ( %MVC ) that each subject can produce . Subjects are typically required to choose between 2 squeezes with different grip forces , each associated with different rewards or additional decision factors ( delay or risk ) . Hartmann and colleagues associated monetary rewards with grip forces and reported that among linear , hyperbolic , and quadratic effort cost functions , the quadratic cost function explained the subjects’ behavior best [8] . Klein-Flügge and colleagues used a similar task to compare effort discounting and delay discounting and reported that effort cost seemed best described as a sigmoidal function , i . e . , showed a convex dependency for lower forces , as Hartmann and colleagues did , but Klein-Flügge and colleagues found a concave relationship for forces closer to MVC because of saturation of effort cost [20] . Burke and colleagues , instead , compared the integration of physical effort and risk in a similar task and reported a sharp increase of effort cost when approaching MVC [21] . In contrast , Prevost and colleagues used rewarding erotic images instead of money , but found effort cost to fit a hyperbolic function [7] . This means that for isometric force production , the effort cost function is still uncertain or at least depends on the choice task ( reward , risk , or delay discounting ) , while for actual movements hardly any previous data exist . To answer how effort depends on force in our movement task , we first have to address the question of how choice is best linked to effort , since choice is the behavioral readout , while effort is a hidden decision variable . Apart from the study by Prevost and colleagues , the aforementioned studies rejected the idea that choice behavior takes into account physical effort in a similar fashion to delay ( i . e . , by hyperbolic discounting ) . This is not surprising since , intuitively , high physical effort cannot make the subjective utility of a choice decrease asymptotically to zero ( as hyperbolic discounting does because of the increasing denominator ) . Indeed , the subjective utility of a high-effort , low-reward action could well be negative , in which case doing nothing would be preferable . As a consequence , the cost of effort is a value that should be offset from the benefits of an action in the utility space—i . e . , the utility of each action should be computed by subtracting the associated effort . This intuition is confirmed by the results of our experiment 2: models in which the decision variable was a difference between efforts predicted the subject’s movement choices better than models in which the decision variable was a difference between the inverse of efforts . Effort studies with isometric force production modeled the probability of choosing each option by transforming the difference of efforts between the 2 alternatives with the softmax function [7 , 20] . Here we used an equivalent probit transformation but showed that using the difference of the effort logarithms yielded significantly better results than using the difference of efforts . Indeed , the difference of logarithmic effort as choice variable best captured the decrease in sensitivity we observed for higher efforts ( Fig 3A and 3B ) . How does force affect effort in transport movements ? Previous isometric contraction studies do not allow generating a good prediction for this question . The aforementioned studies modeled the subjective cost of effort as convex functions of force expressed as %MVC and titrated efforts against rewards . However , both these features of the experimental design could overemphasize the convexity of the effort cost function . First , producing a force stronger than MVC is by definition impossible . Therefore , the effort cost likely has to undergo a sharp increase when approaching this discontinuity in designs that use the full 0%–100% range of MVC as a force scale . Indeed , Hartmann and colleagues and Burke and colleagues noted that subjects always chose the effortful option when it provided more reward , except when the effort was close to MVC [8 , 21] . Second , the tendency to almost always make reward-based choices while ignoring moderate efforts also suggests that monetary rewards are too strongly motivating for typical subjects and may not be appropriate to study the cost of the moderate efforts . However , moderate efforts are essential in experimental settings to allow large numbers of trials and to stay away from the MVC discontinuity . In conclusion , a paradigm that uses moderate absolute forces instead of %MVC forces and in which effortful actions are not associated with monetary or social rewards but are compared directly seems more suited to precisely determine effort cost functions . Such a paradigm , which we partly adopted here , was introduced for isometric forces by Körding and colleagues in a study in which subjects had to resist against imposed force profiles of variable magnitudes and durations [9] . This previous study led to a different effort cost function than the one we found . When subjects had to choose between dual and single contractions with the same force profiles , but in which force and duration were varied together , a loss function of the form ( FT ) α gave the best fit for = 1 . 1 . Assuming that this fit can be generalized to constant durations , the resulting F1 . 1 relationship would indicate a quasilinear influence of isometric force on subjective effort . In contrast , in our experiment 2 , in which we extended this approach to actual effortful transport movements and isolated force dependency by keeping duration constant , we found a more convex F2 relationship . Hence , our result is closer to the results obtained in studies using %MVC despite the use of a different task , force scale , and fitting procedure ( the force exponent was a free parameter in our model , in contrast with [8] ) . Nevertheless , our use of moderate forces prevents us from generalizing our findings to movements realized against higher levels of forces ( closer to MVC ) , for which large accuracy and duration changes might bias choice preferences independent of force-dependent effort . In summary , the cost of effort as a function of isometric muscle contraction force has previously been shown to take various forms . Yet , we mainly attribute differences to the quadratic discounting that we observed here to 2 facts that were not fully considered previously . First , compensating effort with rewards is difficult because of uncertainties about the reward utility itself and the need to use large forces . Second , even when avoiding reward–effort competition and comparing effortful actions directly , interactions between force and duration need to be avoided or compensated for , since duration contributes to both effort and reward discounting and thereby may distort measured force–effort relationships , as will be discussed in the following paragraph . To properly understand physical effort in movements , it is important to disentangle the different contributions of force and duration . A previous study obtained V-shaped isoeffort curves in the duration–force space when pitting isometric contractions with force profiles of different durations and magnitudes against each other [9] . For durations below 250 ms , an increase of duration required a sharp decrease of force to maintain effort constant; for durations above 500 ms , the opposite was observed . In other words , contractions of long durations ( 1–2 s ) were considered as effortful as shorter contractions , even with slightly lower forces . This observation contradicts the intuition that longer contractions should be more effortful than shorter contractions . Moreover , performing short contractions allowed finishing the experiment more quickly since total trial duration was not controlled for; therefore , delay discounting should have additionally devalued longer movements . Körding and colleagues interpreted their result as a consequence of increased control difficulty for fast force changes: it was easier for subjects to resist against stronger force profiles when the onset and offset of the forces were slower , which was the case for long-duration force profiles . In this sense , their results marked a compound effect . In contrast , in our task we tied the onset and offset of forces to self-timed movements . This rendered force control less difficult , and , as a consequence , we observed monotonically decreasing isoeffort curves in the duration-force space ( Fig 2D ) —i . e . , effort increased monotonically with both duration and force , as intuitively expected . Other recent work argued that increasing movement durations requires smaller and smaller decreases of force to maintain effort constant ( i . e . , that perceived effort reaches an asymptote instead of growing linearly with duration in isometric force productions ) . To explain such a counterintuitive effect , the authors assume that effort costs are subject to the same temporal discounting as can typically be observed for reward in economic choice behavior [22] . This hypothetical explanation is , however , not applicable to our results , as we kept the total duration of trials constant . The isoeffort curves observed in our experiment 1 can be explained by the quadratic relationship between force and effort . In conclusion , for effortful transport movements like reaches , effort increases monotonically with movement duration , suggesting that effort is integrated over time . The observations from experiment 1 and 2 provide insight into the internal cost function used by subjects to decide between arm movements . This effort cost function for decisions could potentially be paralleled with motor control cost functions or with the actual metabolic cost of movements . In other words , we can examine whether the choice made by subjects between proposed movements with constrained parameters ( duration , speed , force , etc . ) reflect natural preferences in the execution of unconstrained movements or minimization of energy expenditure .
Subjects performed the tasks by holding and moving the spherical handle of a parallel-type haptic manipulator ( Delta . 3 , Force Dimension , Nyon , Switzerland ) with their dominant arm ( Fig 1A ) . The manipulator was connected to a computer running our own custom-written software ( C++ , OpenGL ) in charge of visual stimulus presentation , task event control , force computation , and associated data recording . The manipulator and the computer communicated bidirectionally at 2 kHz , with the manipulator sending the 3D position of the handle and the computer requesting forces to be applied at the handle for each iteration of this 0 . 5-ms haptic cycle . The movements of the manipulator handle were reproduced in real time for the subject via a spherical yellow cursor displayed in a stereoscopic augmented-reality ( 3D-AR ) environment . Display and haptic device latency were fully compensated by a forward prediction to achieve synchrony between visual cursor and handle movement ( Kalman filter with position , speed , and acceleration as state variables ) . The 3D-AR environment consisted of 2 computer monitors ( BenQ XL2720T , screen size 590 x 338 mm , 60-Hz refresh rate , distance 45 cm , Matrox DualHead2Go DisplayPort splitter ) that were placed to either side of the subject with the screens facing each other . The subject viewed the screens through a pair of semitransparent mirrors that were angled at 45° relative to the screens . This allowed for the creation of stereoscopic 3D visual stimuli that were perceived as being projected into the haptic device’s workspace . In addition to the visual cursor , which always coincided with the handle's current physical position , other visual stimuli indicated the starting points and targets of the reaching movements as well as text information . The 3D-AR haptic interface was calibrated for each subject . For this , we made the actual manipulator handle visually coincide with multiple visual targets sequentially presented in the virtual space . Since the control software selected the visual target locations , the manually adjusted handle position could be used to compute the manipulator-to-display transformation matrix for the current geometry of the setup . This calibration was then further adjusted for each subject by setting the location and projection matrix of the virtual openGL cameras according to the subject’s interpupillary distance . To allow the subjects to comfortably operate the haptic manipulator , both monitors and mirrors were tilted to lower the location of the 3D representation ( Fig 1A; angle relative to horizontal: 30° ) . For the same reason , we defined a virtual plane in front of and parallel to the monitor image plane in which all movement targets appeared ( distance to mirrors was 430 mm ) . Subjects were also encouraged to take breaks and relax their arm as frequently as desired . In order to limit the force output of the manipulator to task-relevant forces only , and to allow for natural movement trajectories , subjects could freely move the cursor around the entire spherical workspace of the haptic device . Correct depth perception of the 3D stimuli was thus required for the subjects to be able to acquire the movement targets . Before each experimental session , subjects were trained on simple versions of the tasks in order to familiarize themselves with the setup and the task requirements , notably 3D vision , resistive forces , and time constraints . The haptic manipulator produced forces that resisted the subjects' movements . Our aim was to produce a force with constant magnitude that was only present during the movements and that opposed the instantaneous movement direction , similar to a kinetic friction force . The direct definition of this friction force would thus depend on the velocity of the handle . Yet , the force command sent to the manipulator was not computed directly from online estimates of handle velocity ( which is difficult at low speeds ) to prevent sudden force onset and direction inaccuracies at low handle speeds . Instead , we implemented the friction force using a virtual point-mass ( virtual mass = 100 g ) that was connected to the handle via a virtual spring ( coefficient = 1 N . m-1 ) . In other words , subjects dragged a virtual mass with the help of a spring , and the kinetic friction force was computed according to the speed of the virtual mass and applied to it . The magnitude of this kinetic friction force ( in N ) was varied in order to produce the different resistive force levels . For each iteration of the haptic cycle , the dynamic state of this virtual mass was updated according to the forces applied to it ( = sum of the spring force and the friction force ) , and the force resulting from the virtual spring was sent to the haptic manipulator as a command . The position of the virtual point-mass was reset to the handle location , and thereby the spring force set to 0 , before the start of each movement . Additionally , the commands sent to the haptic manipulator were modulated by an envelope function ( a constant function with linear tapers of varied durations at onset and offsets ) , which allowed controlling force output outside of the defined movement periods . The course of events of a trial in experiment 1 is presented in Fig 1B ( example trial from the amplitude session ) . Each sampling subtrial started with the subject placing the cursor ( 6-mm diameter , yellow sphere ) within a fixation sphere ( 20-mm diameter , grey , brightening upon acquisition ) and holding this position for a duration randomized between 500 ms and 800 ms . The movement target sphere ( diameter 30 mm ) was displayed from the start of the subtrial; its color indicated to the subject the modalities of the movement to be executed: across both sessions , a green target indicated the need for a rapid movement ( a short-duration movement in the duration session or a large-amplitude movement in the amplitude session ) , whereas blue and red indicated medium and low speed , respectively . During the acquisition and hold stages , onscreen text announced which sampling movement was currently being performed ( “sampling 1” or “sampling 2” ) . When the fixation sphere disappeared ( “go” cue ) , the subject had to execute the required movement by placing the cursor within the target sphere within the requested time constraints . Movement duration was computed from movement onset ( determined online by a combination of speed and distance thresholds ) to target acquisition ( determined only based on cursor position relative to the target ) . Resistive forces were turned on when the fixation sphere was acquired ( on-taper: linear increase to the desired force value within 200 ms ) and were turned off when the target was acquired ( off-taper: linear decrease to 0 within 600 or 500 ms in case of successful or failed acquisition ) . Note that the actual force production by the manipulator was dependent on the subject’s movement and only started at movement onset ( see "Force generation" section ) . If the subject acquired the target faster than the minimum duration set for the movement , or if the subject did not reach the target before the maximum duration set for the movement , the subtrial was interrupted and onscreen text indicated to the subject the type of error committed ( “too fast” or “too slow” ) . Failed subtrials , which also included trials in which the subject broke fixation or left the target too early , were restarted until executed correctly . Once the target was acquired ( with movement duration dm ) , which was signaled by the target sphere becoming brighter , the subject had to hold the cursor within the sphere for a total duration ( in ms ) dh = 100 + dmmax − dm , with dmmax being the maximum potential movement duration in the session ( 2 , 000 ms in the duration session , 1 , 250 ms in the amplitude session ) . This ensured that every subtrial had the same duration across conditions within a session , thus preventing temporal discounting , here equivalent to the desire to terminate the experiment early by preferably selecting short movements . After sampling both the test movement and the reference movement by performing each sampling subtrial successfully , the subject had to indicate in the choice subtrial which movement felt less effortful . This subtrial , announced by a “choice” onscreen text , started with the subject acquiring a pre-fixation sphere . Then , the fixation spheres and targets for the 2 alternatives were displayed , and the subject indicated their choice by acquiring the fixation sphere of the chosen movement ( Fig 1B , right column ) . With acquisition of the chosen movement’s fixation sphere , the fixation and target spheres of the nonchosen movement disappeared , and the rest of the subtrial was identical to the sampling subtrial that corresponded to the chosen movement . Subjects performed experiment 1 over 2 sessions on different days , with each session lasting on average 70 minutes . In the duration session , reference and test movements differed in allowed movement duration but had the same amplitude . This allowed us to construct isoeffort curves in the force–duration space . Conversely , in the amplitude session , the reference and test movements differed in amplitude , but not in duration , which allowed us to construct isoeffort curves in the force–amplitude space . With the use of constant magnitude force profiles , the duration and amplitude session allowed us to double-dissociate total impulse ( Jx=∫tstarttstopFxdt ) and work ( Wx=∫tstarttstopFxdxdtdt ) , respectively . The reference movements had a medium duration in the duration session ( 800–1 , 300 ms ) and medium amplitude in the amplitude session ( 160 mm ) . In both sessions , reference movements were performed against either 6 N or 10 N of resistive force and could be directed either to the right or to the left . The test movements required either low or high values for the session variable of interest ( low or high duration or amplitude ) and were carried out in the direction opposite to the reference movements ( Fig 1D ) . These combinations lead to 8 conditions per session , which were presented to the subject in a randomly interleaved manner ( 2 reference movement force levels × 2 reference movement directions × 2 test movement levels of duration or amplitude ) . For each of these 8 conditions , independent pairs of staircases determined the force level against which the test movements were performed . These staircase pairs followed a one-up one-down rule with a step size of 2 N , with one staircase starting at 0 N and the other at 16 N ( the highest force the manipulator could sustainably produce ) to compensate hysteresis . In other words , when the subject chose the reference movement in a given trial , the force level of the test movement in the next trial of the same condition and staircase would be decremented by 2 N; and vice-versa , when the subject chose the test movement , the force level of the next test movement of the same condition and staircase was incremented by 2 N . Data collection for each staircase was considered complete after 7 inversions in the subject’s choices . In this subjective-choice task , the choices of the subject could sometimes lead the staircase procedure to propose force values beyond the capabilities of the manipulator ( above 16 N ) or the interest of the task ( below 0 N ) . As a consequence , the force values were clamped between 0 and 16 N , and each time the force stayed at these boundaries for 2 trials in a row , an inversion was counted in order to allow the staircase to terminate eventually . We used the average force at staircase inversions to determine isoeffort forces in experiment 1 . Because of the clamping of the staircase forces , the isoeffort forces were also bounded between 0 and 16 N , which could have caused an underestimation of the observed effects in the rare cases in which the subject stayed at the clamped force limits . Target and fixation locations were selected to avoid confounding biases . Across all 8 conditions , the targets were not placed further than 100 mm from the workspace vertical midline to prevent the effort of reaching towards large eccentricities , which would be considered a confounding factor . To achieve this , the different movement amplitudes in the amplitude session were created by offsetting the locations of the fixation spheres while keeping the targets at constant eccentricities ( Fig 1C , vertical dotted lines ) . For this reason , the 2 alternative movements ( towards left and right ) also had to be placed at different heights on the workspace ( 40-mm vertical distance ) . This made them visually more distinguishable for the subjects , especially in the choice subtrial , in which both targets and both corresponding fixation spheres are displayed . Importantly , the prefixation sphere in the choice subtrial was placed halfway between the 2 alternative fixation spheres to prevent subjects from choosing the movement starting closest to the current cursor location . Both fixation spheres were visually identical and were identified by their vertical position , which was the same as the target of the corresponding movement . While experiment 1 was designed to explore isoeffort curves in the force–duration–amplitude spaces , the similar experiment 2 was designed to provide more details about the shape of the force–effort relationship . Instead of executing a single movement in the reference action , subjects performed an identical movement twice in experiment 2 , while the amplitudes and durations of all movements were kept the same across conditions . Assuming that executing a movement twice doubles the associated effort , the experiment allowed us to determine how much force in a test movement was needed to double the effort of a single movement from the reference action . Subjects performed experiment 2 in a single session ( average duration 140 minutes ) . To repeat the reference movement , 2 targets were presented in the corresponding subtrial , and subjects performed 2 reaches in succession . The location of the first target was used as a starting point for the second movement such that no additional movements were required ( additional movements would cause more than doubling of effort ) . Targets were placed such that the 2 movements matched in reach direction and amplitude ( Fig 1E ) . In a reference action , after the movement to the first target , the subject had to maintain the cursor in its location for 500 ms , after which the first target disappeared , indicating to the subject to perform the movement to the second target . The resistive force was tapered in and out for each of these movements ( 50-ms onset taper on “go” cue and 400-ms offset taper on target acquisition ) . In all other aspects , the course of events for experiment 2 is identical to experiment 1 . In experiment 2 , individual movements had a 120-mm center-to-center amplitude and were time constrained between 800 and 1 , 300 ms ( matching the short-amplitude , mid-duration reaches of experiment 1 , Fig 1F ) , for both individual reference movements and the test movements . The total duration of each action , starting from the time the subject left the fixation point to the end of the subtrial , was maintained constant over all subtrials by adding an additional waiting time when holding the target , resulting in a total subtrial duration of 4 , 000 ms . Contrary to experiment 1 , both reference movements and the test movement were in the same direction in each trial . Four levels of reference movement force were probed ( 0 , 3 , 6 , and 9 N ) , while the forces for the test movements were determined using the same staircase procedure as in experiment 1 . Therefore , there was 1 staircase pair for each of the 8 conditions ( 4 reference movement force levels times 2 movement directions ) . Data processing and statistical analysis were carried out using Matlab and the gramm [34] toolbox for plotting . In experiment 1 , averaged staircase inversion points were analyzed using LMEs ( fitlme function in Matlab ) . For each session , we constructed mixed-effect models fitting the average force at staircase inversion points depending on the varied parameter of the session ( duration or amplitude: low , high ) , reference movement direction ( relative to subject handedness: inward , outward ) , and reference movement force ( low , high ) . All these independent variables were treated as categorical variables . The mixed-effect model included separate random intercepts and random slopes for movement duration and for amplitude across subjects . Main effect sizes were extracted from models without interaction terms . Interactions were tested in separate models and their significance was evaluated by model comparison . Choice data from experiment 2 were modeled using Stan [35] , a probabilistic programming language , through its Matlab interface . We used Stan to perform Bayesian inference , using its default implementation of a Markov chain Monte Carlo sampler ( NUTS ) . We fitted a probit hierarchical model , in which the choice of the reference movement in each trial is modeled as a Bernoulli distribution in which the associated probability P ( R|FT , FR ) is a function of the difference in utility between the test and the reference movement , and the utility for each movement depends on the corresponding movement force . Variations of the model will differ in the way utility is expressed as a function of force-dependent effort . Therefore , for subject i: P ( R|FT , FR ) i=Φ ( U ( 2Ei ( FR ) ) –U ( Ei ( FT ) ) γi ) ( 1 ) where Φ is the cumulative density function ( CDF ) of the standard normal distribution ( probit link ) , Ei ( F ) is the effort of a movement executed against the force F for subject i , and U is the utility as a function of force-dependent effort . The factor 2 reflects our assumption that repeating a movement twice should double the effort compared to a single movement and thus imposes the constraint E ( FTeq ) = 2E ( FR ) . Effort itself in all variations of the model was modeled as power-law function of force: Ei ( F ) =Fαi+βi ( 2 ) The constraint E ( FTeq ) = 2E ( FR ) , applied on Eq 2 , yields the following equation for the equivalent force curve: FTeq=2FRαi+βiαi ( 3 ) The force exponent αi , the effort offset βi , and the effort sensitivity γi for each subject were drawn from normal distributions αi ∼ N ( μα , σα ) , βi ∼ N ( μβ , σβ ) , γi ∼ N ( μγ , σγ ) . The resulting parameters of these normal distributions characterize the population-level distributions for α , β , and γ . Bayesian inference requires providing prior distributions for these parameters , which were chosen wide to not constrain the model: μα ∼ N ( 1 , 10 ) , μβ ∼ N ( 0 , 100 ) . The parameters μγ , σα , σβ , σγ were positive scale parameters and their priors each followed the same half-Cauchy distribution [36] with parameters ( location = 0; scale = 20 ) . Posterior distributions were sampled using 4 Markov chains with 1 , 000 samples each ( after a warmup of 1 , 000 samples ) . To test our model against alternative hypotheses , we varied the function of the choice probability ( Eq 1 ) . We then compared the individual model fits using the WAIC [19] , an approximation of cross-validation . In our first model , utility is the negative logarithm of effort and choice probability thus depends on the difference between effort logarithms: U ( E ) =−logE ( 4 ) As second model , we used a simpler model for the choice probability that is based on the difference of effort values and not the log-ratio ( difference of their logarithms ) : U ( E ) =−E ( 5 ) Third , we tested the hypothesis of hyperbolic effort discounting with a model in which effort is on the denominator in each utility term ( inverse effort ) : U ( E ) =1E ( 6 ) Finally , in a fourth model we modified the hyperbolic model to use logarithmic effort: U ( E ) =1logE ( 7 )
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Economic choice in humans and animals can be understood as a weighing of benefits ( e . g . , reward ) against costs ( e . g . , effort , delay , risk ) , leading to a preference for the behavioral option with highest expected utility . The costs of the action associated with a choice can thereby affect its utility: for equivalent benefits , an action that requires less physical effort will be preferred to a more effortful one . Here , we characterized how human subjects assess physical effort when choosing between arm movements . We show that the effort cost of a movement increases with its duration and with the square of the force it is performed against but not with the distance covered . Therefore , the subjective cost that determines decisions does not reflect the objective energetic cost of the actions—i . e . , the corresponding metabolic expenditure . Instead , the subjective cost has commonalities with the cost that our central nervous system is believed to minimize for controlling the motor execution of actions . Our findings thus argue in favor of action selection and action control sharing common underlying optimization principles .
|
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"Methods"
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2017
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What makes a reach movement effortful? Physical effort discounting supports common minimization principles in decision making and motor control
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Effective response to emerging infectious disease ( EID ) threats relies on health care systems that can detect and contain localised outbreaks before they reach a national or international scale . The Asia-Pacific region contains low and middle income countries in which the risk of EID outbreaks is elevated and whose health care systems may require international support to effectively detect and respond to such events . The absence of comprehensive data on populations , health care systems and disease characteristics in this region makes risk assessment and decisions about the provision of such support challenging . We describe a mathematical modelling framework that can inform this process by integrating available data sources , systematically explore the effects of uncertainty , and provide estimates of outbreak risk under a range of intervention scenarios . We illustrate the use of this framework in the context of a potential importation of Ebola Virus Disease into the Asia-Pacific region . Results suggest that , across a wide range of plausible scenarios , preemptive interventions supporting the timely detection of early cases provide substantially greater reductions in the probability of large outbreaks than interventions that support health care system capacity after an outbreak has commenced . Our study demonstrates how , in the presence of substantial uncertainty about health care system infrastructure and other relevant aspects of disease control , mathematical models can be used to assess the constraints that limited resources place upon the ability of local health care systems to detect and respond to EID outbreaks in a timely and effective fashion . Our framework can help evaluate the relative impact of these constraints to identify resourcing priorities for health care system support , in order to inform principled and quantifiable decision making .
EVD was first identified in Zaire in 1976 and there have since been at least twenty-five outbreaks in Africa . The 2014 West African outbreak—first reported in Guinea and subsequently becoming established in Liberia and Sierra Leone—is the largest to date . Symptoms of EVD include vomiting , diarrhoea and haemorrhaging , and transmission occurs via direct contact with blood and other bodily fluids . It is characterised by an incubation period of up to three weeks during which onward transmission is unlikely , followed by increasingly severe symptoms and associated infectiousness . Case fatality rates are high , and improperly buried bodies represent an ongoing source of infection [15] . In the absence of widely available pharmaceutical measures for treatment or prevention during the 2014 West African outbreak , control efforts centred around identification and isolation of cases , tracing of known contacts , and hygienic burial of people who died from EVD . Unlike previous outbreaks , which were largely confined to rural areas , the 2014 West African outbreak spread to urban regions , which contributed to the greater number of cases: official estimates are approximately 28 , 000 cases with over 11 , 000 deaths , although such numbers may have underestimated the true magnitude [16] . Health care workers were disproportionately represented among cases and the full costs of the outbreak in terms of the impact on health infrastructure are still being realised [2] . During the outbreak , there was considerable international concern about the potential for the global transmission of EVD , heightened by the appearance of cases in Spain , the United Kingdom and the United States of America [17] . Modern patterns of global transport mean that no country is isolated from the risk of disease importation , as demonstrated by the rapid worldwide spread of H1N1 influenza in 2009 [18] . The Asia-Pacific region is of particular concern , with Southeast Asia termed a ‘hotspot’ for EIDs due to social and environmental factors supporting the evolution and transmission of novel pathogens [5] . The considerable diversity—geographic , demographic , cultural and economic—of Asia-Pacific countries means that risks associated with EIDs will vary greatly across the region , both between and within countries ( Fig 1 ) . Differences in health care system funding , access and infrastructure will influence capacity to detect and respond to EID outbreaks , as evidenced by recent experience of avian influenza H5N1 , pandemic influenza H1N1 and severe acute respiratory syndrome ( SARS ) . Many countries in this region are understudied with respect to their health infrastructure and there is a poor understanding of their response capacity in the event of an EID outbreak . World Health Organization ( WHO ) regional offices in the Western Pacific ( WPRO ) and South East Asia ( SEARO ) have assessed the need to build national capacities to undertake surveillance , infection prevention and control , and public health emergency preparedness [19] . Annual assessments of these capacities are self-reported , and provide only a general statement of accomplishment [20] . The risks associated with EVD spreading to Southeast Asia were recognised during the 2014 West African outbreak [9] . In addition to global air passenger flows , specific vectors of risk included the presence of miners and aid workers in West Africa with family ties to various countries in Southeast Asia . In September 2014 , WHO regional offices undertook a rapid assessment of EVD virus preparedness across countries in the region , followed by a simulation exercise to train public health staff . A risk assessment for EVD infection in the region was undertaken using the WHO guidance for rapid risk assessment of acute public health events [14] . In addition , and of particular relevance to potential risks , forty health professionals from India and Bangladesh participated in teams supporting outbreak control in West Africa , as well as staff from Pacific Island Countries through the West Pacific Ebola Support Team [20] . Despite the ongoing efforts by WHO , the EVD preparedness review identified that all thirteen surveyed Asian countries , but only nine of thirteen surveyed Pacific Island countries , had health facilities designated to isolate suspected or confirmed cases . Only two of the Pacific Island countries surveyed reported adequate supplies of personal protective equipment ( PPE ) for EVD response and containment . In addition , EVD surveillance protocols had been developed and disseminated in all but one of thirteen Asian countries , but only two of thirteen Pacific countries [13 , 21] . In the presence of competing demands for attention and resources , there is a risk that efforts to improve health policies and systems will be reactive and transient in nature [9] . This reinforces the importance of ongoing support from international and regional organisations , such as the Association of Southeast Asian Nations ( ASEAN ) and WHO , but identifying the most effective forms of such support across this diverse region is a formidable challenge . Mathematical modelling can be a powerful tool to inform decision making in data-poor scenarios [22 , 23] . Models can incorporate data that is available from a range of quantitative and qualitative epidemiological and sociological sources . Even when precise predictions are not possible , models can provide ‘best estimates’ that enable decision makers to rapidly evaluate alternative outbreak , surveillance and response scenarios . The process of constructing a mathematical model requires assumptions about drivers of disease transmission to be made explicit , aiding transparency . Uncertainties in current knowledge can be incorporated into parameter estimates , and can help to provide estimates of the risk of various possible outcomes [24–26] . Finally , mathematical models can enable identification and prioritisation of key data requirements , providing arguments and evidence to guide future data collection efforts . Mathematical models were used extensively during the 2014 West African EVD outbreak [27] , including in the early stages when there was considerable uncertainty around disease activity . A key aim was to project the possible course of the outbreak and assess the potential effectiveness of alternative interventions within West Africa [28–33] . Models were also used to estimate the risk of global transmission [34 , 35] .
The natural history of EVD has been well characterised from previous outbreaks , and disease characteristics such as the basic reproduction number and the duration of the latent and infectious periods were therefore available from previous epidemiological studies [15] . We used a stochastic SEIR-type model ( Fig 2 ) , with the addition of compartments for the number of unburied dead bodies ( which form a significant source of transmission , if there are interactions with the dead body , as is common in various funeral rites ) and the number of safely buried dead bodies ( assumed to no longer contribute to transmission ) . All individuals are initially susceptible to infection ( S ) . Once infected , they enter a latent incubation stage ( E ) , from which they transition to become infectious , but not yet symptomatic ( I0 ) . At the point of developing symptoms ( I ) , their infectiousness increases . Post-infection , individuals either recover and are no longer infectious ( R ) or die and remain infectious ( D ) until buried ( B ) . We also introduced a compartment ( H ) for individuals who have become symptomatic and are visible to the health care system . Separating these visible ( i . e . , ascertained ) cases from the remaining , undetected cases ( I ) allows the model to incorporate actions such as case isolation ( thereby decreasing their ability to infect others ) and the provision of treatment ( thereby decreasing their risk of dying ) . Full details of the model are provided in Model description in S1 Methods . While many socio-cultural factors may influence the frequency and intensity of contact between individuals that facilitate the spread of infection , we used a simple distinction between rural and urban populations that proved to be an important determinant of EVD transmission [29] . We distinguish rural and urban populations in the model by allowing more transmission from infectious individuals in urban populations than in rural populations . Another key driver of EVD transmission is the frequency and intensity of contact between healthy individuals and infectious dead bodies as a consequence of burial practices , which may vary according to the dominant religion . For example , Islamic practices include burying the dead body as soon as possible , while in non-Islamic regions the burial may be delayed for a number of days in order to give distant family members time to visit the deceased . Other cultural traditions may also facilitate substantial transmission after death , such as the Papua New Guinean ritual of ‘haus krai’ , where the body is typically returned to the home village for burial , after which the extended family and friends gather for a wake that can continue for many days . Funerals and burials have been recognised as potential ‘super-spreading’ events [36] , which may result in a substantially greater than expected number of secondary cases [37] . The frequency of these events may therefore influence the likelihood of an outbreak occurring . In the model , we characterised the different burial practices by the mean duration of the pre-burial period ( i . e . , the average delay between death and burial ) and the daily force of infection exerted by dead bodies ( i . e . , the degree of interaction between healthy individuals and the body ) . The parameter values were informed by expert knowledge of burial customs ( where available ) , by knowledge of the dominant religions in a given region , and from estimates of the force of infection from the West African outbreak . A country’s health care system includes people and institutions responsible and resources available for disease surveillance—case ascertainment and contact tracing—and isolation and treatment of detected cases . Surveillance capacity was represented in the model by two distinct quantities: the number of transmission events that occurred prior to the first detected case; and the case ascertainment probability of subsequent symptomatic cases . Limited contact tracing was also included , allowing some contacts of identified cases to be monitored and therefore experience a higher probability of being identified should they subsequently become infected . We used the additional model compartment ( H ) to represent the isolation of identified cases in hospital isolation wards , as depicted in Fig 2 . Hospital isolation was assumed to prevent onward transmission and to increase survival probability . Hospital isolation and contact tracing were both subject to capacity constraints imposed by limited resource and workforce availability . We also stratified the model population into health care workers ( HCWs ) and the general community , to allow differential risks of exposure and case ascertainment . Prior to the first detected case , HCWs were assumed to experience a greater risk of exposure than the general community , due to close contact in medical settings and a lack of recognition of the need for special precautions . Subsequent to the first detected case , HCWs were assumed to experience a lower risk of exposure than the general community , due to the adoption of appropriate infection control measures . At this stage , any cases among HCWs were assumed to be automatically detected . This stratification also explicitly captured the impact of the availability of the health care workforce ( i . e . , uninfected HCWs , assumed to be capable of providing health services ) on health care capacity . Depletion of this workforce ( due to infection ) was assumed to reduce the provision of case ascertainment , contact tracing and monitoring , and case isolation . Specifically , only 50% of health care capacities were assumed to be available when 90% of the HCWs were available , and no health care capacities were available once 80% or less of the HCWs remained available ( see Fig 2 in S1 Methods ) . These values are in broad agreement with the observed impact on health care systems in Sierra Leone , where HCW mortality of around 20% was accompanied by substantial loss of trust in the health care system , substantial decreases in all-cause consultations and admissions and health care productivity and effectiveness was diminished amongst both employed and volunteer personnel [38] . The health care systems of Asia-Pacific countries are characterised by diversity in their level of development . Access to , and standards of , health care services can also vary substantially within a single country . While data on hospital capacity and size of the health care workforce was available , for some countries information on the geographical distribution of these resources was limited . We made two broad assumptions in calibrating our model: that health care system resources were more likely to be concentrated in urban centres , and that the remaining health care system resources were distributed within countries proportional to population density . Several strategies for boosting the existing surveillance and health care capacity were identified as practical and potentially effective: These interventions were represented by increasing the case ascertainment probability of cases in the general community , and by increasing the available capacities for contact monitoring and hospital isolation . In addition to medical interventions , changes to social behaviours and cultural practices can reduce the force of infection in the community [15 , 40 , 41] . We identified two behavioural interventions to reduce the force of infection in the community , based on evidence of success in the West African outbreak and in other infectious disease outbreaks: In response to a perceived potential EID threat , it might be possible to deliver an intervention prior to an actual outbreak occurring , while responding to an observed outbreak would necessarily involve some delay . It is therefore critical to identify how the required magnitude of an intervention to reach an “acceptable” probability of outbreak control depends upon the timing of that intervention . In our sensitivity analysis , we explored how both the magnitude and the timing of these interventions affected the population experience of disease . Intervention timing ( “delay” ) was defined as the time at which the increased capacities and/or decreased forces of infection were realised , relative to the time at which the first identified case was detected . Accordingly , a delay of zero weeks meant that the intervention was deployed prior to the first case being identified . The first identified case was defined relative to the cumulative number of infectious individuals that became symptomatic ( i . e . , transitioned to the I model compartment ) . In the absence of a health care response the distribution of outbreak sizes was bimodal , consistent with classic results from stochastic infection theory [42] . Around a quarter of the model simulations produced outbreaks of 16 cases or fewer , representing stochastic fade-out of the disease . The remaining simulations yielded outbreaks with attack rates of around 80% , representing uncontrolled outbreaks . While high , it is important to note that these attack rates correspond to the hypothetical scenario in which there is no health care system or social response to the outbreak . An attack rate of 80% is consistent with theoretical estimates for an infectious disease of equivalent transmissibility to that estimated for EVD ( i . e . , a basic reproduction number of around 2 ) , and with observed epidemic behaviour early in the West African outbreak [28] . The variety and complexity of output that a disease model provides ( such as the final size distribution ) can be both overwhelming and inappropriate in a decision support context . Accordingly , we established a qualitative measure to assess the outcome of an epidemic based on its final size ( see Fig 3 for example outcomes ) : We classified epidemics according to the above measure , as illustrated in Fig 4 . The left panel illustrates the situation in the absence of a response , where outbreaks either fade out or are uncontrolled . The right panel demonstrates how the response has little effect on outbreaks that would have faded out of their own accord , but greatly reduces the impact of a proportion of previously uncontrolled outbreaks . The distribution of outbreak sizes remained bimodal , with 96% of simulations resulting in fewer than 500 cases ( fade-out and controlled epidemics ) or attack rates of around 80% ( uncontrolled epidemics ) . Accordingly , we used a threshold of 1 , 000 cases to distinguish between controlled and uncontrolled epidemics . Since the natural history of EVD was known to be well-characterised and stable , we were able to identify appropriate parameter values for the disease characteristics ( 15 ) . For the remaining parameters , related to the proposed intervention strategies , we derived broad estimates and performed sensitivity analyses . Because disease transmission is highly stochastic in nature when there are a small number of cases , it was critical to use a stochastic transmission model . This meant that there was no single representative outbreak for a single scenario . Accordingly , for each scenario we performed 1 , 000 simulations to estimate the probability of each outcome . In each of the results figures , we use a stacked bar for each scenario to represent the percentage of these simulations that were categorised as resulting in each of the three outcomes defined above ( fade-out , controlled or uncontrolled ) . The baseline model behaviour , in the absence of any health care system response , is that all outbreaks either fade-out or are uncontrolled . A particular country or region of interest was represented by a subset of the parameter values that best represented its ( assumed ) capacities and behavioural practices . To understand how this local context affected the probability of controlling an EVD outbreak , we performed a sensitivity analysis to identify how interventions might affect the probability of controlling an EVD outbreak in that country or region . For all scenarios reported below , we also explored the effects of the first identified case being the 5th , 10th , 25th or 50th symptomatic individual . Full parameter values for all scenarios are provided in the Simulation scenarios in S1 Methods .
To estimate the impact of endogenous response capacity on control , we varied the case ascertainment probability and size of the health care system , comprising the size of the health care workforce and level of available isolation and contact tracing facilities . The most salient conclusion is the simultaneous importance of early detection and high subsequent ascertainment ( Fig 5 ) . A larger health care capacity can mitigate the failure of early detection , but only to a limited degree . Controlled outbreaks only occur more frequently than uncontrolled outbreaks when case ascertainment is 80% or higher , regardless of health care capacity . To estimate the merits of providing additional support for a health response , we considered two types of interventions: increasing case ascertainment ( i . e . , surveillance ) and increasing health care capacities . Reactively increasing case ascertainment after the first detected case , from a baseline of 20% to 100% ( Fig 6 ) demonstrates the simultaneous importance of early detection and high ascertainment; both qualities are critical for outbreak control and the provision of one is not a substitute for a lack of the other . When the first case is detected early ( e . g . , the fifth actual case , “FD = 5” ) , the probability of outbreak control is 88% when case ascertainment is perfect for the duration of the outbreak . If , however , perfect case ascertainment is only achieved four weeks after the first detected case , the probability of outbreak control falls to 35% . In contrast , where health care resources are limited , a boost in health care capacity may instead be required to increase the probability of outbreak control . As shown in Fig 7 , the importance of early detection remains paramount ( i . e . , to trigger a rapid health care response ) , but the time at which the health care capacity is boosted is less important . This is in stark contrast to boosting case ascertainment , and reflects the ability of the existing health care system to respond effectively until the outbreak reaches a critical size . As long as the additional capacity is delivered before this critical size is reached , the impact of the intervention will not be diminished Reducing the force of infection from dead bodies substantially increases the likelihood of control in all scenarios ( Fig 8 ) . However , earlier detection of the first case provides greater time in which to prepare and deliver an effective reactive intervention . The later the first detection occurs , the more critical it becomes to deliver the intervention rapidly . When the first detection is the fifth actual case ( “FD = 5” ) a delay of 4 weeks before burial practices are changed reduces the likelihood of control from 89% to 78% , but when the first detection is the twenty-fifth actual case ( “FD = 25” ) a delay of 4 weeks before burial practices are changed reduces this from 45% to 23% . As expected , reducing the force of infection from both dead bodies and from infectious individuals in the community has a dramatic effect on disease transmission and substantially increases the likelihood of control ( Fig 9 ) . However , even the impact of this intervention is substantially reduced by late detection and delayed delivery . We now demonstrate how the above results can be interpreted with respect to a specific country in the Asia Pacific region . Papua New Guinea ( PNG ) was chosen as a suitable exemplar for several reasons . The Asia Pacific Strategy for Emerging Diseases ( APSED ) data demonstrated generally lower levels of capacity among Pacific Island countries [19] . Although PNG’s Human Development Index ( HDI ) ( 0 . 505 in 2014 ) is slightly higher than that of EVD-affected West African countries ( 0 . 411 in Guinea , 0 . 413 in Sierra Leone and 0 . 43 in Liberia ) , it is the lowest ranked country in the Southeast Asia/West Pacific region , and among the lowest ranked countries globally . Therefore , estimates of health care system and population factors relevant to disease transmission are likely to be comparable . The geographic proximity of PNG to Australia and Australia’s existing engagement in PNG make it likely that Australia would be called on to support the response to any outbreak in PNG [43] . First , we divided the country into high-level administrative regions ( listed in Table 1 ) and used population sizes as reported in the 2011 census [44] . Estimates of hospital bed and health care worker numbers were provided by country experts at the Nossal Institute for Global Health ( University of Melbourne , Australia ) , who suggested that no more than 10% of beds could be used for isolation of EVD cases . We also assumed a ( modest ) national contact-tracing capacity of 100 contacts per day . We allocated national hospital beds to Port Moresby and distributed remaining beds ( regional and provincial hospitals ) among the administrative regions in proportion to their population densities , as a proxy for both population size and health care system accessibility . The health care workforce and contact-tracing capacity were allocated among regions in proportion to their designated bed capacities . From these data , we estimate that the Port Moresby region has a medium health care system ( almost 0 . 2% of the population are health care workers ) , that the Islands region has a small health care system ( almost 0 . 1% are health care workers ) , and the remaining regions have even less health care infrastructure . While Port Moresby is the largest city in Papua New Guinea and the commercial centre of the country , the vast majority of the population live elsewhere , and country experts at the Nossal Institute also advised that residents of Port Moresby frequently visit friends and relatives in rural regions upon return from international travel . Accordingly , it was judged pertinent to consider the probability of outbreak control in each of the regions . We assumed that the force of infection in the community was twice as high in Port Moresby ( highly urbanised population ) than in the other regions ( with population densities 100 times lower than Port Moresby ) , and that the average time to burial following death was 3 days , allowing for the return of bodies to the home village for burial . To estimate the case ascertainment proportion in Papua New Guinea , we consulted a variety of data sources and also referred back to the EVD outbreak in West Africa . Despite the high proportion of EVD cases that are symptomatic , early in the West African outbreak it was estimated that only about 40% of all cases sought clinical care [16] . Papua New Guinea has a low HDI ranking similar to those of the West African nations , and faces similar challenges in providing access to and quality of health care services . These challenges include: very few health professionals ( less than 1 doctor per 10 , 000 people ) , insufficient health workforce in rural areas ( more than 80% of medical officers work in urban areas , despite 87 . 5% of the population living in rural areas ) , low levels of workforce retention in rural areas ( due to remoteness , financial instability , and dangerous environments ) , limited availability of basic essential medical supplies , and lack of access to clean water in many facilities [45] . Given these issues of access and provision , we assumed that case ascertainment in Papua New Guinea was unlikely to be higher than in the West African outbreak ( 40–50% ) and , particularly in rural areas , might be substantially lower ( 10–20% ) . With clear evidence of successful behavioural interventions in Papua New Guinea during the recent 2009 cholera outbreak as reported in [41] , we anticipated that the force of infection in the community and from dead bodies could be substantially reduced once an EVD case was identified in the community . The geographic spread of the rural population ( on the order of 10 people per square kilometre ) and the inaccessibility of the Highlands region suggest that rapid delivery of additional isolation beds , health care workers , and enhanced contact tracing might be impractical outside of Port Moresby . In the densely populated urban setting of Port Moresby , controlled outbreaks are only likely under two sets of circumstances ( see Fig 10 ) . The first is when the first case is detected early , subsequent case ascertainment is high , and behavioural interventions reduce transmission in the community . The second is when case ascertainment is high and behavioural interventions reduce transmission in the community and also from dead bodies . In contrast , in the more sparsely populated rural settings , such as the Southern region , controlled outbreaks are likely when case ascertainment is high even in the absence of any behavioural interventions ( see Fig 11 ) . In these rural settings , behavioural interventions can greatly increase the likelihood of controlling outbreaks even when case ascertainment is very low , and the synergistic effects of reducing transmission in the community and also from dead bodies can avoid uncontrolled outbreaks altogether . We further considered interventions that delivered additional isolation beds , personal protective equipment , and health care workers , but the probability of outbreak control was not meaningfully affected , indicating that in these model scenarios the health care resources were not a limiting factor ( see Other interventions in Papua New Guinea in S1 Methods ) .
We have shown how the use of a stochastic model of infection and medical and social interventions can be used to support risk assessment and epidemic preparedness in the presence of limited data concerning the pathogen , the population , and available health care infrastructure . We have demonstrated how , over a range of likely country- and disease-specific scenarios , the probability of controlling an EVD outbreak is dependent on early detection and ongoing ascertainment . We have also shown that , in specific settings ( such as the Papua New Guinea case study ) , the relative merits of different resourcing strategies may shift . For example , sensitivity analyses for the rural regions of PNG indicated that interventions targeting behavioural change , such as changes to burial practices , consistently improve controllability . However , providing extra hospital beds alone is unlikely to confer substantial benefits because the limiting factor is case ascertainment rather than treatment and isolation of cases . These observations are of course specific to this population and health care system context , and a strength of this framework is the ability to tailor intervention priorities to specific local context . We can also make several more general observations . Changes in social mixing and burial practices , where the population is amenable to such interventions , can reduce transmission substantially and greatly increase the likelihood of control . This demonstrates the critical importance of effectively communicating infection control and hygiene measures to the community , and of establishing public trust in the health care system . Similarly , the provision of additional health care resources can increase the chance of control , but only if the existing infrastructure is the limiting factor in controlling an outbreak . With regard to timing of interventions , social interventions and health care strengthening can be effective even when delivered several weeks after an outbreak has been detected , when the existing health care system is sufficient to accommodate patients in those early weeks . On the other hand , reactive strengthening of surveillance systems is likely to be ineffective: case ascertainment must be high from the start of the outbreak in order to effectively improve chances of control . For future EVD outbreaks , vaccination is also likely to play a critical role in any response effort [46] . While we have not considered the effect of an EVD vaccine in this study , the model framework is amenable to such extension . Key questions to be addressed would then concern the ability of health agencies to obtain and distribute vaccines in an optimal fashion . In the event that a new infectious disease appears , however , vaccine availability cannot be expected for many months and effective responses will necessarily rely upon health care infrastructure and social interventions as modelled in this study . The benefits of an effective surveillance system are broader than merely improving detection [47] . As well as enabling a more timely response to the West African EVD outbreak , an established surveillance system would have provided earlier and more accurate information on the number , location and characteristics of cases . It is plausible to reason that an established surveillance system could also play a role in communication with affected populations , improving efforts to modify social behaviour and increasing the trust of populations in health care systems . It is instructive to compare our results with the qualitative risk assessment undertaken by WHO offices in September 2014 , which focused on Pacific Island countries [14] . The assessment identified 3 scenarios: Our mathematical modelling identified and clarified conditions for fade-out of a small cluster , and controlled and uncontrolled outbreaks . This clarifies the potential connection between what the WHO assessment refers to as ‘localized clusters’ and ‘widespread transmission’ . While the WHO assessment identifies the need for clinician awareness , case definition , triage and precautions for cases , our model also highlights the importance of secondary contact tracing and case ascertainment in limiting further spread . Our modelling demonstrates that the risk of extending to widespread transmission is not negligible , and that the presentation of cases to health facilities would not in and of itself necessarily improve control . In agreement with the APSED strategy recommendations , our results highlight the critical importance of early detection and high ascertainment for EID control [19] . Preemptive strengthening of surveillance systems in this region is therefore of paramount importance . A further use of mathematical models is to provide estimates of population and health care system impact that can serve as the basis for estimates of the economic impact of an EVD outbreak in the Asia-Pacific region [48] . Potential economic costs include not only the increased health costs and reduced labour productivity during the outbreak , but also the permanent reductions in a country’s population and labour force due to mortality , and behavioural effects induced by the outbreak such as reductions in international tourism and crowd-avoidance behaviour by a country’s residents . An estimate of these economic costs can inform the decisions that international agencies make about the benefits of intervention and health care system support . There are several limitations to the generality of our results . As recognised above , health care system data is often of variable quality in many countries . In particular , such data are typically not available at a high spatial resolution , which is likely to hide considerable geographic heterogeneity in health care system quantity , quality and access . We have dealt with this limitation by exploring a range of potential health care system resourcing levels , but the availability of more accurate data would improve the quality of model scenarios . Furthermore , our modelling approach embodies particular assumptions about disease transmission characteristics that may only partially reflect the dynamics of any specific EID outbreak . For example , increased variability ( ‘overdispersion’ ) in the number of secondary cases that a primary case generates may lead to an overestimate in the risk of an outbreak occurring [37] ( see Over-dispersion in secondary cases in S1 Methods ) . We can identify several general principles from this modelling study that can be used to inform decision making in data-poor settings . A basic understanding of the pathogen is necessary to inform the model structure ( i . e . , to identify the disease-related compartments and the flows between them ) . Where disease transmission involves a separate vector ( e . g . , mosquitoes ) or source ( e . g . , contaminated waterways ) , the model will require further compartments to capture these qualities . Model parameters may be informed by data from previous or related outbreaks , although such values should be validated as data for the novel pathogen become available . In the absence of data beyond basic population demographics , expert local knowledge is critical for estimating available health care infrastructure , relevant socio-cultural behaviours that may influence disease transmission , and subsequent behavioural changes instigated by the perceived threat or by communications ( e . g . , community hygiene promotion ) . The inherent uncertainties in these factors highlights the importance of thorough sensitivity analyses , rather than relying on ‘best available’ point estimates [49] . Once the disease model has been defined and calibrated to the target population and health care system , the next challenge is to design a range of simulation scenarios that admit interventions and resourcing levels that are realistic in both scope and timeliness . Possible sources of guidance include previous outbreaks experienced by the target population , and previous foreign-aid efforts . For comparison against these scenarios , a set of simulations with no health care response should be generated to form a baseline . Finally , it is important to determine how best to classify and communicate the epidemic outcomes generated by the model . Communication of key model outcomes to policy makers and local health care providers must be both accurate and comprehensible . Given the considerable uncertainty around model inputs in data-poor settings , it is important that specific quantitative outputs are not ‘over-interpreted’ . For example , projections of cumulative cases are unlikely to be realised given both initial uncertainty , and the evolving nature of the local and international response and intervention . We therefore advocate focusing on qualitative measures of control and burden that can inform estimates of comparative , rather than absolute , impact . Our classification of outbreaks as either controlled or uncontrolled was appropriate in the case of EVD , since there was a clear division between epidemic sizes . It is possible that further distinctions may be required in other scenarios . Despite the paucity of social , demographic and health care system data that is available for understudied countries , mathematical modelling can enable rapid assessment of risk across a range of country and intervention scenarios , to assist with prioritisation of EID preparedness and response efforts .
|
Low and middle income countries face a serious challenge when confronting emerging infectious disease ( EID ) threats . Their risk of experiencing outbreaks can be greater than in many high income countries , while their capacity to respond effectively may be constrained by competing demands on limited health care system resources . The globalised nature of health security argues for international support to improve local health care systems , but limited data makes risk assessment and decision making difficult . We propose a mathematical modelling framework that can help explore a variety of outbreak and intervention scenarios . Our framework can assist with the identification of constraints that limit the ability of local health care systems to detect and respond to EID outbreaks in a timely and effective fashion , and assess the relative importance of these constraints to help establish priorities for health care system support . We illustrate the use of our framework by considering the importation of Ebola into the Asia-Pacific region , with results emphasising the critical role played by effective surveillance in controlling localised outbreaks .
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2016
|
Model-Informed Risk Assessment and Decision Making for an Emerging Infectious Disease in the Asia-Pacific Region
|
We here report on the existence of Leber’s hereditary optic neuropathy ( LHON ) associated with peculiar combinations of individually non-pathogenic missense mitochondrial DNA ( mtDNA ) variants , affecting the MT-ND4 , MT-ND4L and MT-ND6 subunit genes of Complex I . The pathogenic potential of these mtDNA haplotypes is supported by multiple evidences: first , the LHON phenotype is strictly inherited along the maternal line in one very large family; second , the combinations of mtDNA variants are unique to the two maternal lineages that are characterized by recurrence of LHON; third , the Complex I-dependent respiratory and oxidative phosphorylation defect is co-transferred from the proband’s fibroblasts into the cybrid cell model . Finally , all but one of these missense mtDNA variants cluster along the same predicted fourth E-channel deputed to proton translocation within the transmembrane domain of Complex I , involving the ND1 , ND4L and ND6 subunits . Hence , the definition of the pathogenic role of a specific mtDNA mutation becomes blurrier than ever and only an accurate evaluation of mitogenome sequence variation data from the general population , combined with functional analyses using the cybrid cell model , may lead to final validation . Our study conclusively shows that even in the absence of a clearly established LHON primary mutation , unprecedented combinations of missense mtDNA variants , individually known as polymorphisms , may lead to reduced OXPHOS efficiency sufficient to trigger LHON . In this context , we introduce a new diagnostic perspective that implies the complete sequence analysis of mitogenomes in LHON as mandatory gold standard diagnostic approach .
Since the identification of the first causal mitochondrial DNA ( mtDNA ) point mutation [1] , the mutational landscape of Leber’s hereditary optic neuropathy ( LHON ) has become increasingly complex . In particular , LHON pathogenic mutations are frequently homoplasmic and , in some cases , their pathogenicity has not been readily recognized . [2][3] Now we know that over 90% of LHON patients are due to three common mtDNA point mutations m . 11778G>A/MT-ND4 , m . 3460G>A/MT-ND1 and m . 14484T>C/MT-ND6 [4][5] . Interestingly , the pathogenic role of the m . 14484T>C/MT-ND6 was initially not recognized because of the low phylogenetic conservation of the affected amino acid [6][7] . Later , it became also clear that some mtDNA variants , classified as secondary mutations , were associated with LHON , despite being present at high frequencies in control populations [8 , 9][10] . The debate on this issue [11 , 12] was resolved by recognizing these variants as markers of specific mtDNA haplogroups [13 , 14] , and showing that two clades of the western Eurasian haplogroup J were genetic backgrounds enhancing the pathogenic potential of the m . 14484T>C/MT-ND6 , and at a weaker extent the m . 11778G>A/MT-ND4 mutations [15 , 16] . As counterproof of this scenario , the m . 14484T>C/MT-ND6 change found on non-J mtDNA backgrounds displays a very low penetrance and has been occasionally reported in genetic surveys of control populations , thus behaving borderline and similarly to a polymorphic variant [17 , 18] . More recently , MT-ND6 and MT-ND1 have been highlighted as LHON mutational hotspots [19 , 20] , since multiple rare LHON pathogenic mutations , often preferentially associated with haplogroup J , have been reported to affect these genes [21] . Furthermore , different sets of two or more mtDNA variants have been postulated as modulators of penetrance , such as combinations of multiple private “weak” pathogenic mutations or combinations of established LHON pathogenic mutations with variants , already known as markers of specific haplogroups , but detected outside the usual haplogroup background [22 , 23] . Similar conclusions have been reached in the context of East Asian haplogroups by complete mtDNA sequencing of Asian LHON pedigrees , as compared with population-matched controls [24–27] . Thus , the identification of truly pathogenic variants , distinguished from synergistic modifying variants in various combinations , is increasingly challenging . We here present evidence that unusual combinations of otherwise polymorphic and non-pathogenic mtDNA missense mutations may be sufficient for causing low-penetrance maternally inherited optic neuropathy fitting the LHON clinical diagnosis in independent pedigrees . Our findings bridge the blurry border between “pathogenic” and “neutral” mutations in an overall continuum that truly depends on the specific and sometime unique combination of variants characterizing each mitogenome .
We observed three multigenerational pedigrees ( Families 1a , b , and c in Fig 1A ) with multiple affected individuals fitting the clinical diagnosis of LHON and with a clear maternal transmission of the phenotype . Noticeably , all three pedigrees were from the same geographical area of southern Italy ( Campania region ) . A fourth smaller pedigree ( Family 2; Fig 1B ) from northern Italy ( Emilia-Romagna region ) was observed with a single affected individual obeying the LHON clinical diagnosis . All four families tested negative for the three common LHON mutations at positions m . 11778G>A/MT-ND4 , m . 3460G>A/MT-ND1 and m . 14484T>C/MT-ND6 . Clinical histories of affected individuals are reported in detail in Supporting Information ( S1 Text , S1 and S2 Tables ) . Some examples of ophthalmological features are illustrated in Fig 2 . Histological analysis of skeletal muscle biopsies from the probands of Families 1a , 1b and 2 ( Fig 1 ) showed no overt signs of myopathy with minimal variability in fibers size , and histoenzymatic stain showed normal COX activity , but some increase of subsarcolemmal SDH reactivity ( Fig 3A ) . TEM analysis confirmed the presence of proliferated mitochondria under the sarcolemma and , occasionally , between fibers ( Fig 3B ) . Mitochondrial DNA copy number and citrate synthase ( CS ) activity were both increased in skeletal muscles of patients as compared to controls ( Fig 3C and 3D ) . Similarly , the specific oxidoreductase activities of Complex I ( CI ) , Complex II+III ( CII+III ) , Complex III ( CIII ) and Complex IV ( CIV ) were increased ( Fig 3E ) , whereas they were comparable to controls when normalized on CS activity ( S3 Table ) . Taken together these data indicate the occurrence of an activated compensatory mitochondrial biogenesis , most likely due to a compensatory response caused by a mild mitochondrial defect , as previously reported [28 , 29] . Sequencing of the entire mitogenome from each of the probands independently ascertained for Families 1a , 1b and 1c revealed the same identical sequence , indicating that they descend from the same maternal ancestor , as also suggested by their geographical proximity . They all shared the diagnostic variants for haplogroup K1a and the following private mutations: non-coding m . 2281A>G/MT-RNR2 and m . 16129G>A/MT-HV1; synonymous m . 6137T>C/MT-CO1 , m . 6329C>T/MT-CO1 , m . 8994G>A/MT-ATP6 , m . 11038A>G/MT-ND4 and m . 15253A>G/MT-CYB; and missense m . 14258G>A/MT-ND6 and m . 14582A>G/MT-ND6 . The m . 14258G>A/MT-ND6 mutation causes the amino acid substitution p . P139L , and the m . 14582A>G/MT-ND6 the amino acid substitution p . V31A . Both missense mutations affect poorly conserved positions of the ND6 subunit of CI and are not predicted to be damaging ( Fig 4 , S4 Table ) . However , the P139 position showed a higher conservation degree in mammals ( 37% ) compared to eukaryotes ( 22% ) , being highest in primates ( 66% ) . Furthermore , the P139 position in mammals sits two residues away from an invariant position ( G141 ) and , in primates is contiguous to another invariant position ( D138 ) within a moderately conserved domain ( 6 invariant positions out of 21 ) ( Fig 4 ) . The V31 position shows similar features . In eukaryotes and mammals glycine is prevalent at position 31 with a low conservation ( 49% and 46% , respectively ) . In primates , at this position valine becomes prevalent with a higher conservation ( 77% ) . Most relevantly , V31 is within a highly conserved domain ( 10 invariant positions out of 21 ) in mammals , and is even more conserved in primates ( 16 invariant positions out of 21 ) ( Fig 4 ) . Complete mtDNA sequence analysis of the proband from Family 2 showed all the variants diagnostic for haplogroup H5b and the following private mutations: synonymous m . 10248T>C/MT-ND3; missense m . 9966G>A/MT-CO3 , m . 10680G>A/MT-ND4L , m . 12033A>G/MT-ND4 and m . 14258G>A/MT-ND6 . Besides the m . 14258G>A/MT-ND6 nucleotide change , Family 2 also harbored the m . 10680G>A/MT-ND4L and the m . 12033A>G/MT-ND4 mutations that induce the amino acid changes p . A71T in ND4L and the p . N425S in ND4 subunits of CI , respectively . The p . A71T change affects a highly conserved ND4L position ( 86% in eukaryotes , 97% in mammals , invariant in primates ) , within an invariant stretch of 16 amino acids in primates ( Fig 4 , S4 Table ) . Conversely , the p . N425S affects a highly conserved ND4 position only in primates ( 41% in eukaryotes , 70% in mammals , 87% in primates ) , in a moderately conserved domain ( 9 invariant positions out of 21 ) ( Fig 4 , S4 Table ) . Both variants were considered neutral for the protein function by most of the prediction tools employed . The m . 14258G>A/MT-ND6 change , found in both Families 1 and 2 , has been previously reported according to Mitomap and HmtDB in 10 different haplogroups , being diagnostic for haplogroups U3a1a1 and H1q3 . The m . 14582A>G/MT-ND6 ( Family 1 ) variant has been previously reported in seven different haplogroups , being diagnostic for haplogroup H4a . In these databases , the sample classified as GenBank: KC878720 is from our Family 1 and it was previously published [30] without considering the recurrence of a clinical phenotype ( A . Torroni , personal communication ) . The coexistence of m . 14258G>A/MT-ND6 with the m . 14582A>G/MT-ND6 variants is , however , unique to Family 1 , when compared to all the other reported cases ( S5 Table ) . Concerning the m . 10680G>A/MT-ND4L variant , this has been found in 14 haplogroups and it has been previously reported as the only pathogenic change in three LHON families , arising as independent mutational events in haplogroups B4a1e , M13a1b and D6a1 [31 , 32] . In addition , this mutation has also been found in association with the m . 14484T>C/MT-ND6 mutation in a further LHON family with a haplogroup B4d1 background [26] . However , the m . 10680G>A/MT-ND4L change has also been recognized in ten different maternal lineages with no pathology reported ( S6 Table ) . Finally , the m . 12033A>G/MT-ND4 variant has been reported in five different haplogroups in the general population , without being associated with any pathologic phenotype . Overall , the combination of the three coexisting missense changes m . 10680G>A/MT-ND4L , m . 12033A>G/MT-ND4 and m . 14258G>A/MT-ND6 is a unique feature of Family 2 . We also screened by complete mtDNA sequencing our entire cohort of LHON probands with one of the three known primary mutations ( n = 236 ) , finding the m . 14258G>A/MT-ND6 variant in two further families , carrying the m . 11778G>A /MT-ND4 ( haplogroup T1a1 ) and m . 14484T>C/MT-ND6 ( haplogroup L2a1a1 ) LHON mutations , respectively ( Families 3 and 4; S1 and S2 Figs ) . In Families 1a-b-c all available individuals along the maternal lines ( n = 22 ) were RFLP surveyed for the m . 14258G>A/MT-ND6 and m . 14582A>G/MT-ND6 variants , which appeared always homoplasmic . In Family 2 , the proband’s mother and sister were also homoplasmic for all missense variants ( m . 10680G>A/MT-ND4L , m . 12033A>G/MT-ND4 and m . 14258G>A/MT-ND6 ) . To assess the pathogenic potential of the two peculiar combinations of missense variants found in Family 1 ( m . 14258G>A/MT-ND6 and m . 14582A>G/MT-ND6 ) and Family 2 ( m . 10680G>A/MT-ND4L , m . 12033A>G/MT-ND4 and m . 14258G>A/MT-ND6 ) we generated cybrids using enucleated fibroblasts derived from the probands of Families 1a , 1b and 2 , as cytoplast donors . As detailed in Material and Methods , different cell clones were obtained harboring each the two combinations of homoplasmic variants and used for subsequent investigations . In Fig 5 , the data obtained from each LHON cell line were pooled together and compared to control cybrids , as they proliferate at similar rates in complete medium ( 25 mM glucose ) ( S3 Fig ) . To challenge the mitochondrial oxidative phosphorylation system , we grew cybrids in a glucose-free medium containing galactose; under these conditions , the rate of glycolysis is markedly reduced and cells are forced to rely on oxidative phosphorylation for ATP production [33] . No significant differences were found in LHON cell viability compared to controls ( Fig 5A ) or between different cell clones ( S3 Fig ) . Assessment of CI redox activity displayed a non-significant reduction in LHON cells ( Fig 5B ) , indicating that the combinations of variants did not affect the CI oxidoreductase function . However , the basal and the FCCP-stimulated oxygen consumption rate ( OCR ) of LHON cells were significantly reduced ( Fig 5C ) . LHON cells also displayed a metabolic shift toward glycolysis , since they showed a higher ECAR and a lower OCR when compared to controls ( Fig 5D ) . Consistently , the CS normalized ATP synthesis , driven by CI substrates ( malate and glutamate ) , was significantly reduced in LHON cells , whereas ATP synthesis was normal when driven by CII substrates ( succinate ) ( Fig 5E ) . The OCR analysis of a further cybrids cell line carrying the m . 10680G>A/MT-ND4L variant in isolation , also displayed a defective respiration with a similar magnitude as LHON cells ( Fig 5C and S4 Fig ) . Although LHON mutations have been reported to exert their pathogenic role by increasing oxidative stress [4 , 5] , we failed to reveal any difference between LHON and control cells in terms of superoxide anion and hydrogen peroxide production ( S5 Fig ) . Overall , these data indicate that combinations of polymorphic variants in mtDNA-encoded CI genes induce a mild isolated CI defect , which was also detected in cells carrying the m . 10680G>A/MT-ND4L variant in isolation . In order to define how such peculiar combinations of variants lead to a mild Complex I defect , we took advantage of the recently released crystallographic structure of mammalian enzyme [34] . We analyzed the position of amino acids affected by the polymorphic variants , namely m . 14258G>A/MT-ND6 , m . 14582A>G/MT-ND6 , m . 10680G>A/MT-ND4L and m . 12033A>G/MT-ND4 . The variant m . 14258A>G/MT-ND6 shared by Families 1 and 2 induces the P139L amino acid change in humans , which corresponds to A140 in ovine CI . Such amino acid is located in the transversal α-helix 5 of ND6 . The variant m . 14582A>G/MT-ND6 found in Family 1 generates the amino acid substitution p . V31A in humans and corresponds to G32 in the ovine complex , affecting the transmembrane α-helix 2 ( TM2 ) of ND6 . The m . 10680G>A/MT-ND4L variant harbored by Family 2 affects the amino acid A71 of ND4L both in human and ovine CI . This amino acid lies in TM3 of the ND4L subunit . Lastly , the m . 12033A>G/MT-ND4 induces the amino acid substitution p . N425S in the loop between TM13 and TM14 of ND4 , which faces the mitochondrial matrix . Interestingly , with the only exception of the latter amino acid change , all the other variants affect positions around the putative E-channel of CI [35] , suggesting that the mild functional defect found in these patients may arise from an altered proton pumping caused by the two peculiar mtDNA combinations of variants ( Fig 6 ) .
The current study provides genetic and functional evidence that specific and previously unreported combinations of missense mtDNA variants , which individually obey the definition of population polymorphisms , may exert a sufficient pathogenic potential for being causative of low-penetrance LHON . This , as confirmed by a few other cases retrieved from the literature , now firmly establishes that LHON is a disease that may be determined by a very mild respiratory chain dysfunction , possibly close to the boundary between functional and pathological variability , which depends on the mitogenome sequence variation [36 , 37] , and is highly modulated by environmental [38] and nuclear DNA factors [39] . This scenario was best demonstrated by the cluster of Families 1a , 1b and 1c , which belong to the same maternal lineage and carry the previously unreported combination of m . 14258G>A/MT-ND6 and m . 14582A>G/MT-ND6 variants on a K1a haplogroup background ( S5 Table ) . On the clinical ground , it is worth to notice that all affected members ( n = 14 ) of this very large family are males , indicating that most likely the combination of missense mutations on a K1 mitogenome characterizing this family is not sufficient to reach and trespass the threshold for LHON in females . Furthermore , general penetrance of these 14 affected members was 13% over the total number of individuals on the maternal line , and 25% over the total number of males . This latter percentage is well below the usual quote of average 50% penetrance in males reported in literature [4 , 5] . It is also interesting to note that the mitogenomes of both Families 1 and 2 had in common m . 14258G>A/MT-ND6 , a mutation previously not recognized as associated with LHON . By screening the entire cohort of LHON families diagnosed in our Institute , we found this variant also in two LHON pedigrees carrying one of the three common LHON primary mutations ( S1 and S2 Figs ) . The other variant m . 10680G>A/MT-ND4L found in Family 2 has been either found alone in pedigrees segregating cases of LHON on the maternal line [31 , 32] , or in association with known LHON primary mutations [26] . Moreover , the mtDNA sequence variants of these previously reported cases of Chinese ancestry are found in combination with other missense changes in CI subunits genes , in particular in the ND1 subunit ( m . 3644T>C/MT-ND1; m . 3745G>A/MT-ND1; m . 3548T>C/MT-ND1 ) or in the ND6 subunit ( m . 14484T>C/MT-ND6 ) , which are closely assembled with ND4L according to the CI structure ( S6 Fig , S6 Table ) [34] . Thus , at least the m . 14258G>A/MT-ND6 and m . 10680G>A/MT-ND4L variants have been recurrently associated with LHON , either in combination with other polymorphic variants or associated with other primary mutations . However , both variants alone are reported , at very low frequencies , in the general population excluding LHON cases ( respectively 20 and 14 mitogenomes , out of 31 , 787 ) , thus with an extremely low possibility of co-occurrence by chance , and consequently further remarking their non-pathogenicity when isolated ( S5 and S6 Tables ) . To validate on the functional ground the pathogenic role of these two combinations of variants , the only recognized method is to demonstrate a biochemical defect in the cybrid cell model , where only the patient-derived mtDNA is transferred . We observed that ATP synthesis driven by CI substrates and respiration as measured by OCR were significantly defective in cybrids harboring the mitogenomes of Families 1 and 2 compared to haplogroup-matched controls . Intriguingly , a similar defect in respiration was also found in a further cybrid cell line carrying the m . 10680G>A/MT-ND4L missense variant in isolation on a I1b haplogroup , supporting its contributory role to the pathogenic potential of the Family 2 combination of variants . Unfortunately , not having available cybrids carrying the m . 14258G>A/MT-ND6 variant in isolation , we could not asses its real contribution to the respiratory defect of both Families 1 and 2 combinations of variants . However , in Family 1 the co-occurrence of the m . 14582A>G/MT-ND6 variant ultimately results in defective respiration of similar magnitude as in Family 2 and as in cybrids with the isolated m . 10680G>A/MT-ND4L variant . Remarkably , similar to the other LHON primary mutations with the exception of m . 3460G>A/MT-ND1 , the CI specific activity was not reduced in cybrids carrying the two combinations of variants [40 , 41] . Thus , even if other reports proposed that combinations of different variants might exert the equivalent pathogenic role of the single primary LHON mutation [31 , 32] , we here provide for the first time experimental evidence of the dysfunction from a functional point of view . Interestingly , the now available structure of CI revealed that the large majority of these variants , those found in the Italian Families 1 and 2 as well as those reported in Chinese families [31 , 32] , are located in close proximity to the predicted E-channel for proton translocation ( Fig 6 , S6 Fig ) , contributed by all three ND6 , ND4L and ND1 subunits . Genetic variation along this pathway may alter the efficiency of proton translocation , ultimately affecting the energy conserving function of CI . Our study has profound implications for the diagnosis of LHON , and , more in general , for the assessment of pathogenicity of mtDNA variants . In the case of the three branches of Family 1 , we performed complete mtDNA sequencing because there was a clear evidence of maternal recurrence of a phenotype undistinguishable from classic LHON despite the absence of the three common LHON mutations . However , also the sequencing of the entire mitogenome in our entire cohort of Italian LHON families revealed the presence of multiple variants potentially relevant for LHON pathogenesis , beside the known primary LHON mutations . Therefore , we propose complete mitogenome sequencing as the gold standard for LHON diagnosis , to disclose possible unique combinations of variants , or double/triple mutants . In brief , the definition of a pathogenic mtDNA mutation becomes blurrier than ever , and only the accurate consideration of population-dependent mtDNA structure , combined with functional analyses using the cybrid cell model , may lead to its final validation . A good example for such a scenario is the m . 3394T>C/MT-ND1 , which might act as an adaptive variant selected for high altitudes in Tibet , while exerting a pathogenic effect on other mtDNA backgrounds and predisposing to LHON in China [27] . Closely similar , other two adaptive variants for high altitude in Tibet , i . e . m . 3745G>A/MT-ND1 and m . 4216T>C/MT-ND1 , were also implicated in LHON [42] . The m . 3745G>A/MT-ND1 was in fact found in combination with m . 10680G>A/MT-ND4L in a Chinese LHON Family [26] , whereas the m . 4216T>C/MT-ND1 variant is at the shared root of the Western Eurasian haplogroups J and T , both possibly affecting the E-channel for proton pumping ( S6 Fig ) . In conclusion , this study highlights the complexities of mtDNA sequence variability , introducing a perspective that will change the approach for assigning the pathogenic role to peculiar combinations of mtDNA variants , and modifying the criteria [3] for diagnostics in mitochondrial human diseases .
Tibialis anterior muscle biopsy was carried out after informed consent from patients . Routine histological and histoenzymatic analyses , including cytochrome c oxidase ( COX ) and succinic dehydrogenase ( SDH ) activity staining , were performed [43] . Respiratory chain complexes and CS activities were determined on skeletal muscle homogenates as previously reported with minor modifications [44] . Skeletal muscle biopsy was also processed for transmission electron microscopy ( TEM ) using standard procedures . Total DNA was extracted by standard methods from blood cells , urinary sediment epithelium and skeletal muscle after informed consent and approval of the internal review board at University of Bologna . Direct sequence analysis of the entire mtDNA molecule was performed on total DNA extracted from skeletal muscle , by Sanger [45] or Next Generation Sequencing ( NGS ) methods . For the NGS approach , briefly , two long PCR amplicons ( 9 . 1 kb and 11 . 2 kb ) [46] were amplified using Q5 High-Fidelity DNA Polymerase ( New England Biolabs , UK ) , purified by Agencourt AMPure XP ( Beckman Coulter Life Sciences , Italy ) . The library was constructed by Nextera XT DNA Library Preparation Kit ( Illumina , San Diego , CA ) and sequenced on MiSeq System ( Illumina , San Diego , CA ) , using the 600-cycle reagent kit . All the mutations are relative to the revised Cambridge Reference Sequence ( rCRS , NC_012920 ) . The complete mtDNA sequence of the three maternally linked probands of Family 1 ( GenBank: KC878720 ) as well as that from the proband of Family 2 ( GenBank: MF039863 ) have been deposited . All variants of interest were confirmed in all their available maternal relatives by restriction fragment length polymorphism ( RFLP ) analysis ( primers and conditions are available upon request ) . Mitochondrial DNA copy number was evaluated by qRT-PCR , as previously reported [28] . Population frequencies of missense mutations and the mtDNA backgrounds on which they were observed were recovered from two public databases , Mitomap ( http://www . mitomap . org ) and HmtDB ( http://www . hmtdb . uniba . it ) [47 , 48] . Haplogroup affiliations of mitogenomes were assigned according to PhyloTree ( www . phylotree . org ) [49] . Protein conservation analysis and pathogenicity prediction were carried out applying a previously detailed in silico protocol [21] and MitImpact 2 . 7 ( mitimpact . css-mendel . it ) [35] . Positioning of amino acid changes on the 3D CI structure was performed using UCSF Chimera 1 . 11 . 2 ( www . cgl . ucsf . edu/chimera/ ) on the entire ovine respiratory Complex I ( PDB file 5LNK ) [34] . Cybrid cell lines were generated from patient’s skin fibroblasts ( individuals IV:1 from Family 1a; V:6 from Family 1b; and IV:2 from Family 2 ) and 143B . Tk- cells , as previously described [50] . A further cybrid cell line was generated from fibroblasts carrying the m . 10680G>A/MT-ND4L in isolation ( haplogroup I1b ) , identified after screening our entire fibroblast biobank from patients without mtDNA-based neurological disorders . Cybrids from control fibroblasts were previously generated ( GeneBank MF591562 , EU915473 , MF591564 ) and used in this study after the closest mtDNA haplogroup matching with LHON patients cybrids ( N1b1a , K1a2a and H1 , respectively ) . Cybrids were grown in complete medium Dulbecco’s modified Eagle medium ( DMEM ) supplemented with 10% fetal calf serum ( South America source from Gibco , Life Technologies , Italy ) , 2 mM L-glutamine , 100 U/ml penicillin , 100 μg/ml streptomycin , in an incubator with a humidified atmosphere of 5% CO2 at 37 °C . All the experiments were performed using haplogroup-matched wild type controls . For viability experiments , cells ( 4x104 cells/cm2 ) were seeded in 24 well plates and incubated for different times in complete medium or in glucose-free DMEM supplemented with 5 mmol/L galactose , 5 mmol/L Na-pyruvate and 5% FBS ( DMEM-galactose ) . Viability was determined using the colorimetric sulforhodamine B ( SRB ) assay [51] , by measuring the SRB absorbance at 570 nm with a VICTOR3 Multilabel Plate Counter ( PerkinElmer Life and Analytical Sciences , Zaventem , Belgium ) . Isolation of mitochondrial-enriched fraction and assessment of Complex I activity were carried out as previously described [52] . Rotenone sensitive specific Complex I activity was normalized on protein content and CS activity [44] . Oxygen consumption rate ( OCR ) and extracellular acidification rate ( ECAR ) in adherent cells were measured with an XFe24 Extracellular Flux Analyzer ( Seahorse Bioscience , Billerica , MA , USA ) , as previously described [53] . OCR and ECAR were measured under basal conditions and after the sequential addition of 1μM oligomycin , 0 . 2μM FCCP ( carbonylcyanide-p-trifluoromethoxyphenyl hydrazone , Sigma-Aldrich , Milan , Italy ) , 1μM rotenone and 1μM antimycin A . Data were normalized on SRB absorbance values and on non-mitochondrial residual OCR , after antimycin injection , and expressed as percentage . The rate of mitochondrial ATP synthesis was measured in digitonin-permeabilized cybrids using the previously described luciferin/luciferase assay , with minor modifications [54] . Rates were normalized to protein content and CS activity [44] . Quantification of mitochondrial superoxide and H2O2 levels were performed by flow cytometry or fluorescent microscopy using H2DCFDA and MitoSox fluorescent dies ( Life Technologies , Milan , Italy ) , as previously detailed [53] . Statistical significance was defined as p-value≤0 . 05 with Student’s t-test unless otherwise indicated .
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Leber’s hereditary optic neuropathy ( LHON ) is a common cause of maternally inherited vision loss . In the large majority of cases LHON is due to mitochondrial DNA ( mtDNA ) point mutations , clearly distinct from common polymorphisms normally found in the general population , affecting the mitochondrial function , thus defined as pathogenic . For the first time , we here demonstrate , on the genetic and functional ground , that unusual combinations of otherwise polymorphic and non-pathogenic mtDNA variants are sufficient for causing low-penetrance maternally inherited optic neuropathy in pedigrees fitting the LHON clinical diagnosis . Our findings bridge the blurry border between “pathogenic” and “neutral” mutations in an overall continuum that truly depends on the specific and sometime unique combination of variants characterizing each mitogenome . As a result , we conclude that , for an accurate diagnosis of LHON and possibly of other mitochondrial diseases , the only approach that can disclose all possible causative sources is complete mitogenome sequencing .
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2018
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Peculiar combinations of individually non-pathogenic missense mitochondrial DNA variants cause low penetrance Leber’s hereditary optic neuropathy
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NOD-like receptor protein 3 ( NLRP3 ) inflammasome activation triggers caspase-1 activation-induced maturation of interleukin ( IL ) -1β and IL-18 and therefore is important for the development of the host defense against various RNA viral diseases . However , the implication of this protein complex in human metapneumovirus ( HMPV ) disease has not been fully studied . Herein , we report that NLRP3 inflammasome plays a detrimental role during HMPV infection because NLRP3 inflammasome inhibition protected mice from mortality and reduced weight loss and inflammation without impacting viral replication . We also demonstrate that NLRP3 inflammasome exerts its deleterious effect via IL-1β production since we observed reduced mortality , weight loss and inflammation in IL-1β-deficient ( IL-1β-/- ) mice , as compared to wild-type animals during HMPV infection . Moreover , the effect on these evaluated parameters was not different in IL-1β-/- and wild-type mice treated with an NLRP3 inflammasome inhibitor . The production of IL-1β was also abrogated in bone marrow derived macrophages deficient for NLRP3 . Finally , we show that small hydrophobic protein-deleted recombinant HMPV ( HMPV ΔSH ) failed to activate caspase-1 , which is responsible for IL-1β cleavage and maturation . Furthermore , HMPV ΔSH-infected mice had less weight loss , showed no mortality and reduced inflammation , as compared to wild-type HMPV-infected mice . Thus , NLRP3 inflammasome activation seems to be triggered by HMPV SH protein in HMPV disease . In summary , once activated by the HMPV SH protein , NLRP3 inflammasome promotes the maturation of IL-1β , which exacerbates HMPV-induced inflammation . Therefore , the blockade of IL-1β production by using NLRP3 inflammasome inhibitors might be a novel potential strategy for the therapy and prevention of HMPV infection .
The inflammasomes are cytosolic multiprotein complexes responsible for caspase-1 activation [1] . Once activated , caspase-1 proteolytically cleaves interleukin ( IL ) -1β and IL-18 precursors ( pro-IL-1β and pro-IL-18 ) , leading to the release of mature forms [2 , 3] . Among identified inflammasomes , the NOD-like receptor protein 3 ( NLRP3 ) inflammasome containing NLRP3 , adapter protein apoptosis-associated speck-like protein ( ASC ) and pro-caspase-1 is the most fully studied [4] . NLRP3 inflammasome activation is a two-step process . The first step involves a priming signal provided by microbial molecules or endogenous cytokines , which upregulates the transcription of inactive NLRP3 , pro-IL-1β and pro-IL-18 . The second step is characterized by the oligomerization of NLRP3 and subsequent assembly of NLRP3 , ASC and pro-caspase-1 into a complex [5] . This signal is provided by numerous stimuli such as ATP , pore-forming toxins , viral RNA , etc . Most of them induce potassium efflux , calcium signaling , reactive oxygen species generation , mitochondrial dysfunction and lysosomal rupture [6] . The NLRP3 inflammasome has been demonstrated to be activated by many RNA viruses and could play distinct roles during viral infections [7 , 8] . NLRP3 inflammasome activation has been reported to aggravate Newcastle virus , murine hepatitis virus , coxsackievirus B3 , Dengue virus , and Zika virus infections [9–13] but exerts beneficial effects to the host response against enterovirus 71 and rabies virus diseases [14 , 15] . Surprisingly , although NLRP3 inflammasome could be activated by vesicular stomatitis and encephalomyocarditis viruses , it seemed to have no influence on the pathogenesis of these two viruses [16] . In the case of influenza A virus infection , several studies investigating the role of NLRP3 inflammasome have yielded controversial results [17–20] , leading to the conclusion that NLRP3 inflammasome might play a dual protective or detrimental role at different stages of influenza A virus infection [21] . Human metapneumovirus ( HMPV ) is a member of the Metapneumovirus genus within the new Pneumoviridae family of non-segmented , negative-stranded , enveloped RNA viruses [22] . This virus is one of the leading causes of respiratory tract disease in both children and adults . The adaptive immune response generated against HMPV is usually inefficient at protecting from reinfections , which are repeated throughout life [23] . There is currently no licensed vaccine to prevent HMPV infection and its treatment is still limited to the use of ribavirin , a weakly effective antiviral agent , and immunoglobulins [24] . Thus , highlighting the role of NLRP3 inflammasome during HMPV infection may provide a new perspective on the prevention and treatment of this viral disease . To date , only one study has reported increases in the production of IL-1β and IL-18 , accompanied by an upregulation of NLRP3 mRNA expression in HMPV-infected children , as compared to control healthy individuals [25] . However , the authors did not clarify the role of NLRP3 inflammasome during HMPV infection . In the current study , by using a pharmacological approach , small hydrophobic protein-deleted recombinant HMPV ( HMPV ΔSH ) as well as IL-1β-deficient ( IL-1β-/- ) mice , we show that NLRP3 inflammasome can be activated by HMPV SH protein . Once activated , this multiprotein complex exerts a deleterious effect during HMPV infection in mice by triggering IL-1β release . Therefore , targeting NLRP3 inflammasome as well as IL-1β may be of interest for the development of new therapeutics against HMPV infections .
MCC950 has been recently synthesized and recognized as a specific inhibitor of NLRP3 , but not NLRP1 , NLRC4 or AIM2 inflammasomes [26] . Since then , it has been preferentially used in various models of NLRP3-related diseases [27] . A recent study has reported that MCC950 did not impact the viability and proliferation of high-glucose-induced human retinal endothelial cells at a concentration of 100 μM [28] . In the current study , we also showed that this inhibitor was safe and usable for both human THP-1 ( CC50 > 250 μM ) and murine J774 . 2 ( CC50 > 125 μM ) cells ( S1 Fig ) . To determine if NLRP3 inflammasome impacts HMPV replication , THP-1 or J774 . 2 cells were treated or not with 10 μM of MCC950 because this dose has been shown to be able to block NLRP3 activation in mouse bone marrow derived macrophages , human monocyte derived macrophages and human peripheral blood mononuclear cells [26] , and then infected with HMPV . The viral loads evaluated on days 1 , 2 and 3 post-infection did not differ between MCC950-treated and control DMSO-treated groups ( Fig 1A ) . We also observed that viral titers were relatively low , but as expected since no trypsin was added during the cell culture assay . Thus , NLRP3 inflammasome had no influence on HMPV replication in vitro . To investigate if NLRP3 inflammasome is responsible for IL-1β and IL-18 production , THP-1 or J774 . 2 cells were treated or not with MCC950 and then infected or not with HMPV . We found that NLRP3 inflammasome inhibition suppressed IL-1β and IL-18 secretion in THP-1 cells and significantly decreased their concentrations in J774 . 2 cells ( Fig 1B ) . We also confirm that NLRP3 is responsible for the maturation of only IL-1β and IL-18 [29] , as evidenced by no difference in IL-6 and TNF-α levels between MCC950-treated and control groups during HMPV infection ( Fig 1C ) . Of note , we observed no IL-6 production in THP-1 cells upon HMPV inoculation . In order to confirm those results , we used wild-type ( WT ) bone marrow derived macrophages ( BMDM ) and NLRP3 KO BMDM cell lines and observed that HMPV-infected BMDM cells induced the production of IL-1β at 48 h , but not HMPVΔSH-infected BMDM ( S2 Fig ) . Conversely , no IL-1β was detected in NLRP3 KO BMDM cells following HMPV infection . Notably , TNF-α was detected in both WT and NLRP3 KO BMDM cells . To investigate if NLRP3 inflammasome is involved in the pathogenesis of HMPV , BALB/c mice were treated with MCC950 and infected with HMPV at a LD50 dose . No mortality and a less important weight loss were observed in MCC950-treated groups , as compared to controls ( Fig 2A ) . Nevertheless , the protective effect of MCC950 treatment was slightly decreased when treatment was delayed 24 h post-infection ( Fig 2B ) , in comparison with immediate treatment ( Fig 2A ) . Thus , NLRP3 inflammasome plays a detrimental role during HMPV infection and the blockade of its activation may be useful not only for the prevention but also for the therapy against HMPV disease , at least in mice . We then investigated the effect of NLRP3 inflammasome on HMPV replication by determining viral loads in the lungs . In agreement with in vitro results , mice inoculated with HMPV at sublethal or LD50 doses both showed no difference in lung viral titers between MCC950-treated and control groups ( Fig 2C ) . Therefore , it is likely that the involvement of NLRP3 inflammasome in the pathogenesis of HMPV does not occur via a direct viral replication-related pathway . Because NLRP3 inflammasome did not impact HMPV replication , we hypothesized that it possibly exerts a deleterious effect via IL-1β and/or IL-18-dependent pathways . To verify this hypothesis , we measured IL-1β , IL-18 and other cytokine levels in BAL at different time points from BALB/c mice infected with HMPV at sublethal or LD50 doses and treated or not with MCC950 . IL-18 levels were not different between MCC950-treated and DMSO-treated mice . By contrast , IL-1β levels in HMPV-infected mice were significantly decreased upon MCC950 treatment on day 1 post-infection ( Fig 3 ) . As presented above , NLRP3 inflammasome did not impact HMPV-induced IL-6 and TNF-α secretion in vitro . By contrast , interferon ( IFN ) -γ , IL-6 , and TNF-α levels in BAL were significantly decreased upon MCC950 treatment ( Fig 3 ) . In parallel , NLRP3 inflammasome inhibition also reduced the alteration of pulmonary capillary permeability and leukocyte recruitment , as evidenced by significant decreases in total protein levels and cell number in BAL from MCC950-treated mice compared to controls during HMPV infection ( Fig 4A and 4B ) . Thus , NLRP3 inflammasome inhibition protects mice against HMPV disease by exerting an anti-inflammatory effect . Moreover , this anti-inflammatory effect seems to be virus dose-dependent because NLRP3 inflammasome inhibition decreased more efficiently inflammatory parameters in the case of sublethal dose than LD50 dose of virus . Indeed , MCC950 treatment induced significant decreases in IL-6 and TNF-α levels on day 1 post-infection and total protein levels on days 3 post-infection ( sublethal dose ) and 5 post-infection ( sublethal and LD50 doses ) ( Figs 3 and 4A ) . We then investigated if NLRP3 inflammasome impacts the recruitment of particular cell type ( s ) . Only lymphocyte percentage was decreased on day 3 post-infection upon MCC950 treatment accompanied by an increase in macrophage percentage in mice inoculated with HMPV at a LD50 dose ( Fig 4C ) . Lymphocytes decrease on day 3 was characterized by a reduction in % of B and CD8 T cells ( S3 Fig ) . A time-dependent different contribution of each cell type during HMPV infection was detected , as evidenced by the predominance of polymorphonuclear neutrophils on day 1 , and then lymphocytes on days 3 and 5 post-infection . Since IL-18 levels were unaltered during in vivo infection , we further determined if this cytokine exerts some effects during HMPV disease . IL-18 was therefore inhibited in HMPV-infected BALB/c mice by using IL-18 binding protein ( IL-18BP ) , which functions as an IL-18 antagonist by binding to IL-18 and blocking its biological activities [30–32] . No difference in survival and weight loss between IL-18BP-treated and non-treated mice was observed during HMPV infection ( Fig 5A ) . Thus , the involvement of NLRP3 inflammasome in the pathogenesis of HMPV is IL-18-independent . Interestingly , we noticed that NLRP3 inflammasome inhibition always protected mice against HMPV disease even if virus was administered at a lethal dose , as evidenced by no mortality and slight weight loss ( <10% initial weight ) in MCC950-treated compared to DMSO-treated mice . This finding enables us to suggest that NLRP3 inflammasome is essential for the pathogenesis of HMPV in BALB/c mice . Because IL-18 was not required for the infectivity of HMPV , we determined if the implication of NLRP3 inflammasome in the pathogenesis of this virus could be associated with the release of IL-1β . Therefore , C57BL/6 ( IL-1β+/+ ) and IL-1β-/- mice were infected with HMPV at a LD50 dose . MCC950-treated IL-1β+/+ and untreated IL-1β-/- mice showed less weight loss and mortality , reduced IFN-γ and total protein levels , as well as leukocyte number in BAL , as compared to IL-1β+/+ mice without MCC950 treatment on day 5 post-infection ( Fig 5B–5E ) . Other parameters including IL-1β , IL-6 , TNF-α , IL-18 , leukocyte differentiation and viral replication did not differ between IL-1β+/+ mice , IL-1β-/- and IL-1β+/+ treated with MCC950 mice ( S4 Fig ) . Thus , the involvement of NLRP3 inflammasome in the pathogenesis of HMPV seems to predominantly occur via IL-1β secretion . To investigate whether HMPV SH protein is responsible for NLRP3 inflammasome activation , we first designed and generated HMPV ΔSH virus from strain C85473 . We then evaluated caspase-1 cleavage as a marker of NLRP3 inflammasome activation because caspase-1 cleavage depends on the assembly of NLRP3 , ASC and procaspase-1 to form inflammasome [5] . Western Blot analysis showed that HMPV inoculation induced caspase-1 cleavage in THP-1 cells ( Fig 6 ) . This cleavage , however , was prevented by MCC950 treatment . These results confirm the capacity of HMPV to induce NLRP3 inflammasome . In parallel , we found that HMPV ΔSH could not induce caspase-1 cleavage in THP-1 cells ( Fig 6 ) . Thus , SH protein seems to be the viral component triggering NLRP3 inflammasome activation , but other experiments are needed to determine if the mutant virus simply becomes inaccessible to pro-inflammatory danger sensors via compartmentalization or if it is physically unable to prime or activate the inflammasome . Cleaved caspase-1 was detected in both cell lysates and supernatants at 1 h but was only present in the cell supernatants at 24 h post-infection . This indicates that caspase-1 was rapidly cleaved and released into the supernatants [33] upon HMPV inoculation . We also investigated if the absence of SH protein could attenuate the infectivity of HMPV . No difference in viral replication between HMPV and HMPV ΔSH was observed in THP-1 cells ( Fig 7A ) but IL-1β production was abrogated in HMPV ΔSH-infected THP-1 cells ( Fig 7B ) . The same tendency was observed during in vivo studies . Indeed , at the image of MCC950-treated mice , no mortality was seen in HMPV ΔSH-infected mice whereas slight weight loss as well as reduced IFN-γ , IL-6 , total protein levels , leukocyte numbers in BAL and lung histopathological scores were observed , compared to HMPV-infected mice on day 5 post-infection ( Fig 7C–7G & S5A Fig ) . No difference in IL-1β and TNF-α levels as well as leukocyte differentiation was observed on day 5 between HMPV ΔSH- and HMPV-infected mice ( S5B and S5C Fig ) . However , a significant decrease of IL-1β was seen on day 1 in the HMPV ΔSH group ( Fig 3 ) . Thus , both NLRP3 inflammasome inhibition and SH protein deletion attenuated inflammation and lung injury . Moreover , SH protein did not impact on viral replication [34 , 35] , as demonstrated by no difference in the viral loads of lungs between and HMPV ΔSH- and HMPV-infected groups ( Fig 7H ) . Altogether , we conclude that in the case of HMPV infection , NLRP3 inflammasome activation is triggered by the viral SH protein .
Our study clearly shows the role of the inflammasome and in particular IL-1β in the pathogenesis of HMPV using a pharmacological approach , BMDM NLRP3 KO cells and IL-1β-/- mice . As a crucial component of the innate immune system , NLRP3 inflammasome serves an important role in host defense by recognizing RNA viral pathogens and triggering immune responses [36] . Although NLRP3 inflammasome has been reported to be implicated in many RNA viral diseases with distinct functions [7 , 8] , little is known about the involvement of this protein complex in the pathogenesis of HMPV . In such a context , this present study shows for the first time that NLRP3 inflammasome plays a detrimental role during HMPV infection and that such effect is mediated by the viral SH protein . The contribution of NLRP3 inflammasome in the pathogenesis of RNA viruses occurs through its role as a trigger of only inflammation [12 , 15 , 18 , 19] or both inflammation and viral replication [9 , 10 , 16 , 17 , 37] . Herein , we demonstrate that the involvement of NLRP3 inflammasome in the pathogenesis of HMPV only proceeds via its pro-inflammatory effect . Indeed , both in vitro and in vivo studies showed that viral replication was almost unaltered whereas inflammation was attenuated upon NLRP3 inflammasome inhibition during HMPV infection . This finding is consistent with two other studies which have also shown that NLRP3 inflammasome did not impact on viral replication during influenza and chikungunya diseases [21 , 38] . Nevertheless , the suppression of NLRP3 inflammasome has been demonstrated to decrease fulminant hepatitis and Zika virus replication [10 , 13] but increase Newcastle virus replication [9] . In other words , NLRP3 inflammasome plays distinct roles in the replication of RNA viruses . NLRP3 inflammasome , once activated , will promote caspase-1-induced IL-1β and IL-18 maturation [29] , but not other cytokines . In this study , NLRP3 inflammasome-independent secretion of IL-6 was observed in HMPV-infected J774 . 2 cells and TNF-α in THP-1 and J774 . 2 cells . This finding is consolidated by a recent in vitro study investigating RSV [39] , the closest virus related to HMPV [40] also belonging to the Pneumoviridae family [22] . The authors reported that the secretion of IL-1β , not IL-6 was triggered by RSV-induced NLRP3 activation in primary human lung epithelial cells . Although NLRP3 inflammasome is responsible for the secretion of only IL-1β and IL-18 in infected cells , the inhibition of this protein complex decreased the levels of not only IL-1β but also IL-6 , TNF-α and IFN-γ in HMPV-infected mice . Furthermore , three other inflammatory parameters including the alteration of pulmonary capillary permeability , leukocyte recruitment and lung histopathological scores were also decreased upon NLRP3 inflammasome inhibition . These data are not unique and they are consistent with several previous reports [17–19 , 21 , 26 , 38] . Thus , NLRP3 inflammasome may impact not only IL-1β and IL-18 secretion but also exert proinflammatory effects via unknown pathways [18] during RNA viral diseases in general and HMPV infection in particular . To explain the proinflammatory function of NLRP3 inflammasome , it has been suggested that its activation may occur in concert with other proinflammatory pathways such as lipotoxicity- , oxidative stress- and TLR4-related pathways [41] . We suggest that NLRP3 inflammasome exerts pro-inflammatory effect during HMPV infection through biological activities of IL-1β . Indeed , this cytokine has been identified as an important regulator of inflammation , as evidenced by its capacity to stimulate neutrophil and macrophage recruitment and infiltration in some conditions [42 , 43] and induce lung vascular permeability damage [44] . IL-1β has also been identified as an activator of IL-6 and IL-8 production [45 , 46] . Most importantly , we reported that both NLRP3 inflammasome inhibition ( BALB/c and C57BL/6 mice ) and deletion of the gene encoding IL-1β ( C57BL/6 mice ) induced less weight loss with decreased mortality and inflammation in HMPV-infected mice . Moreover , the protective effect against HMPV disease did not differ between NLRP3 inflammasome inhibition and IL-1β deletion ( C57BL/6 mice ) . Briefly , NLRP3 inflammasome-induced IL-1β release plays a crucial role during HMPV infection , at least in mice . In the case of BALB/c mice , no mortality was found in animals infected with HMPV at a LD50 dose and treated with MCC950 ( Fig 2A ) . By contrast , some mortality ( 25% ) was detected in infected C57BL/6 mice given MCC950 treatment ( Fig 5B ) . Furthermore , NLRP3 inflammasome inhibition was found to decrease IL-6 and IFN-γ levels in BAL from BALB/c mice ( Fig 3 ) but only IFN-γ levels in the case of C57BL/6 mice on day 5 post-infection ( Fig 5C ) . In parallel , IL-6 , IFN-γ and TNF-α levels in BAL from BALB/c mice were strongly higher than those from C57BL/6 mice ( Figs 3 and 5C & S4A Fig ) . All these findings indicate that HMPV-induced inflammation is more severe in BALB/c than C57BL/6 mice and that the role of NLRP3 inflammasome and IL-1β is more important in the former mice during HMPV infection . The different susceptibility of these two murine strains to HMPV [47] is a possible explanation . Although NLRP3 inflammasome activation triggers the maturation of IL-1β and IL-18 , we show that only IL-1β is involved in the pathogenesis of HMPV . Moreover , this involvement occurs at an early stage of infection process because IL-1β levels were only decreased upon NLRP3 inhibitor treatment on day 1 post-infection . This finding is not surprising since IL-1β as well as other IL-1 family cytokines are widely considered as early-response cytokines as they are released in the earliest stage of an immune response [48] . By contrast , IL-18 secretion was unaltered during infection and had no influence on the pathogenicity of HMPV in mice . This might be explained by the limited presence of macrophages during HMPV infections , which were shown to be an abundant source of IL-18 during in vitro studies [49] ( Fig 1B ) . By contrast , polymorphonuclear neutrophils were abundant on day 1 and then lymphocytes were dominant on days 3 and 5 post-infection ( Fig 4C ) . NLRP3 inflammasome activation generally employs a two-step mechanism . In general , the first signal permitting the generation of pro-IL-1β and pro-IL-18 is triggered by the recognition of viral pathogens by Toll-like receptors ( TLRs ) or retinoic acid-inducible gene-I-like receptors [5] . Herein , we did not investigate the mechanisms by which the first signal occurs . However , we think that the TLR4 receptor may be responsible for this process because a recent study has demonstrated that among various TLRs including TLR2 , TLR3 , TLR4 , TLR7 and TLR8 , only TLR4 provides the first signal of NLRP3 inflammasome activation in RSV-infected lung epithelial cells [39] . Furthermore , TLR4-/- mice induced less weight loss , decreased inflammation and no difference in viral replication , as compared to wild-type mice during HMPV infection [50] . These findings are consistent with our results when using either IL-1β-/- mice or pharmacological approach for blocking NLRP3 inflammasome activation . Recently , it has been shown that RNA viruses trigger NLRP3 inflammasome activation through a receptor interacting protein ( RIP ) 1/RIP3/dynamin-related protein 1 signaling pathway [51 , 52] . Briefly , RNA virus infection initiates the assembly of RIP1/RIP3 complex , promoting activation of dynamin-related protein 1 and its translocation to mitochondria . This results in mitochondria damage , excessive reactive oxygen species generation and subsequent NLRP3 inflammasome activation [6] . RNA viral components responsible for triggering this pathway have been identified in several viral infections such as influenza virus M2 and PB1-F2 proteins [53–55] , Measles virus V protein [56] , RSV SH protein [39] , encephalomyocarditis virus and rhinovirus 2B proteins [57 , 58] , coronavirus E protein [59] and enterovirus 71 3D protein [60] . Among these proteins , encephalomyocarditis virus and rhinovirus 2B proteins as well as RSV SH protein were recognized as viroporins . Viroporins from RNA viruses have been reported to be responsible for mitochondrial alteration [61] . Furthermore , once inserted on host cell membrane , viroporin will enable virus to tune ion permeability to stimulate a variety of viral cycle stages [62] . Taken together , we hypothesized that HMPV SH protein may be an activator of NLRP3 inflammasome during HMPV disease because it has been suggested to act as a viroporin [63] and the genomic structure of HMPV is closely related to that of RSV [40] . HMPV ΔSH viruses have been previously reported to be generated from the CAN97-83 ( group A ) or NL/1/99 ( group B ) strains [34 , 35] . Here , we generated HMPV ΔSH using C85473 strain ( group A ) to verify our hypothesis [64] . In addition to the blockade of caspase-1 cleavage , a reliable marker of NLRP3 inflammasome activation , resulting from the lack of SH protein or MCC950 treatment , we found that identically to MCC950 treatment , SH deletion had no effect on the viral replication both in vitro and in vivo . This finding is consolidated by previous studies using other HMPV ΔSH viruses [34 , 35] . We also detected that HMPV ΔSH-infected mice were protected against severe infection , as evidenced by no mortality , less weight loss and reduced inflammation . The evolution of HMPV infections was not different between HMPV ΔSH- and wild-type HMPV-infected mice receiving MCC950 treatment , but we acknowledge that no measures were taken to detect defective interfering particles in both viral preparations . In parallel , NLRP3 inflammasome inhibition had no influence on the pathogenesis of HMPV ΔSH . Taken together , we conclude that HMPV SH protein might be an activator of NLRP3 inflammasome in addition to its identified other roles to modulate type I IFN signaling pathway [65 , 66] , deteriorate cell host membrane permeability , regulate viral fusogenic function [63] and reduce CD4+ T cell activation [67] . In summary , we report for the first time a detrimental role of NLRP3 inflammasome during HMPV infection in murine models . Mechanistically , HMPV SH protein triggers NLRP3 inflammasome activation , leading to the cleavage of pro-IL-1β to form mature IL-1β . Although this cytokine is not crucial for controlling viral replication , it plays a major role in inflammatory process which is identified as an important feature for the pathogenicity of HMPV . Thus , the involvement of NLRP3 inflammasome in HMPV disease occurs via IL-1β-related inflammatory process rather than virus replication . In such a context , we believe that anti-inflammatory treatments in general and anti-IL-1β drugs in particular ( i . e . the use of NLRP3 inhibitors ) may be considered as novel potential strategies for the prevention and treatment of HMPV disease .
Six-week old female BALB/c mice with a body weight of 16 . 5–18 g were purchased from Charles River Laboratories ( Senneville , QC , Canada ) . IL-1β-/- mice were kindly provided by Dr Steve Lacroix ( Infectious Disease Research Centre , Quebec City , QC , Canada ) . Age-matched wild-type C57BL/6 mice were purchased from Charles River Laboratories . Mice were housed under pathogen-free conditions in the animal research facility of the Quebec University Health Centre ( Quebec City , QC , Canada ) and allowed to acclimatize for one week prior to the start of experiments . All experimental procedures with mice were approved by the Animal Protection Committee of the Quebec University Health Centre in accordance with guidelines of the Canadian Council on Animal Care ( Protocol number: CPAC 2017-139-1 ) . Before inoculation of substances or euthanasia , mice were anaesthetized by inhalation of isoflurane vaporized at concentrations of 3–4% and oxygen flow rate adjusted to 1 . 5 l/min . Individual body weight and clinical signs were used to monitor animal health and response to infection and were recorded daily . Mice were euthanized by CO2 inhalation upon loss of 20% of initial body weight . LLC-MK2 cells ( ATCC , Manassas , VA , USA ) were maintained in minimal essential medium ( Thermo Fisher Scientific , Burlington , ON , Canada ) supplemented with 10% fetal bovine serum ( FBS ) ( Wisent , Saint-Jean-Baptiste , QC , Canada ) and HEPES buffer ( 2 . 5 g/l ) . Murine macrophage J774 . 2 cells were kindly provided by Dr Sachiko Sato ( Infectious Disease Research Centre , Quebec City , QC , Canada ) and maintained in Dulbecco’s modified eagle medium ( Thermo Fisher Scientific ) supplemented with 10% FBS and 1% penicillin-streptomycin ( Thermo Fisher Scientific ) . Human monocyte-like THP-1 cells were generously provided by Dr Francesca Cicchetti ( Quebec University Health Centre , Quebec City , QC , Canada ) and maintained in RPMI 1640 medium ( Thermo Fisher Scientific ) supplemented with 10% FBS , 1% penicillin-streptomycin , 1% non-essential amino acids ( Thermo Fisher Scientific ) and 0 . 05 mM 2-mercaptoethanol ( Sigma Aldrich , Oakville , ON , Canada ) . Differentiation of THP-1 cells into macrophages by the addition of phorbol 12-myristate 13-acetate ( 100 ng/ml ) [68] ( Sigma Aldrich ) was carried out in all in vitro experiments . Immortalized murine bone-marrow derived macrophages WT ( BMDM iWT ) or NLRP3 -/- ( BMDM iNLRP3KO ) were kindly provided by Dr Bénédicte Py ( Centre International de Recherche en Infectiologie CIRI , Lyon , France ) and maintained in Dulbecco’s modified eagle medium ( Thermo Fisher Scientific ) high glucose , supplemented with 10% FBS and 1% penicillin-streptomycin ( Thermo Fisher Scientific ) . The HMPV strain C85473 , a clinical isolate , and the recombinant HMPV strain C85473 ΔSH were grown in LLC-MK2 cells and concentrated as previously described [69] . Viruses were concentrated by ultracentrifugation and pellets resuspended in PBS . Viral stocks were sequenced and titers were determined by immunostaining [70] and expressed as plaque-forming units ( PFU ) per milliliter . The strategy for the construction of the plasmid encoding the full-length genomic cDNA of HMPV A1/C-85473 strain ( GenBank accession number KM408076 . 1 ) and the subsequent production of recombinant viruses is described in details in [64] . Briefly , the full-length genomic cDNA of HMPV A1/C-85473 strain was generated by RT-PCR using the Superscript II reverse transcriptase ( Thermo Fisher Scientific ) and amplified by Phusion DNA polymerase ( New England Biolabs , Whitby , ON , Canada ) . A Gibson Assembly ( Cloning Kit , New England Biolabs ) was performed to integrate the genomic viral cDNA into a pSP72 plasmid ( Promega , Madison , WI , USA ) containing a T7 terminator , the hepatitis delta virus ( HDV ) ribozyme and a T7 promoter . To generate HMPV ΔSH virus , the mentioned plasmid was amplified using specific primers , designed to match before the SH gene start sequence ( 5’-GGGACAAGTAGTTATGGA-3’ ) and after the intergenic SH-G region ( 5’-ACTCTGATGTGTTTTTACTAAC-3’ ) , in order to extract completely the SH gene sequence . After amplification , linear DNA was phosphorylated and ligated with the T4 Ligase to re-circularize the shortened HMPV genome . The newly generated HMPV ΔSH genomic plasmid was validated by complete sequencing prior to transfection . BSR-T7 cells were then co-transfected ( Lipofectamin 2000 , Thermo Fisher Scientific ) with the HMPV ΔSH genomic plasmid and 4 supporting plasmids expressing the N , P , L , and M2 . 1 viral ORFs . Seven hours after transfection , the medium was replaced by Opti-MEM supplemented with 1% Non-Essential Amino Acids ( Thermo Fisher Scientific ) . Transfected cells were incubated at 37°C and 5% CO2 for four days . At this point , LLC-MK2 cells were added to the transfected BSR T7 cells and co-cultured at 37°C and 5% CO2 with the addition of fresh trypsin ( 0 . 0002% ) after two days . Two or three days after co-culture , cells were harvested , sonicated and centrifuged at 2000 x g for 5 min at room temperature . The supernatant was collected , diluted into infection medium ( Opti-MEM supplemented with 0 . 0002% trypsin ) , and inoculated onto confluent LLC-MK2 monolayers . Infected monolayers were monitored for the appearance of characteristic cytopathic effect , and the harvested virus was further amplified through serial passages in LLC-MK2 cells . The CC50 concentration of NLRP3 inhibitor MCC950 ( Tocris Bioscience , Bristol , UK ) was determined in J774 . 2 and THP-1 cells using the CellTiter 96 Aqueous One Solution Cell Proliferation Assay ( Promega ) according to the manufacturer’s instructions . J774 . 2 or THP-1 cells were treated with 10 μM of MCC950 [26] and incubated at 37°C for 1 . 5 h . Equivalent dilutions of dimethyl sulfoxide ( DMSO ) ( Sigma Aldrich ) served as control . The cells were then inoculated with wild-type HMPV or HMPV ΔSH at a MOI of 0 . 001 ( THP-1 ) or 0 . 01 ( J774 . 2 ) per well and incubated at 37°C . Cell lysates and supernatants were harvested at 1; 24; 48 and 72 h post-infection for ELISA or Western Blot analyses . In addition , the viral titers were determined by immunostaining three days post-infection and expressed as PFU per milliliter . BMDM iWT and iNLRP3KO cells in 24-well plates were washed in PBS and inoculated with Opti-MEM ( mock ) , wild-type HMPV or ΔSH HMPV at a MOI of 0 . 1 in Opti-MEM + 0 . 0002% trypsin . After 3 h adsorption at 37°C , inocula were removed and changed by fresh cell culture medium DMEM high glucose + 10% FBS and 1% penicillin-streptomycin ( Thermo Fisher Scientific ) . Cell supernatants were harvested at 1 , 24 , 48 and 72 h post-infection to perform IL-1β or TNF-α quantification by ELISA assays ( DuoSet ELISA , R&D Systems ) , according to manufacturer’s instructions , and viral titrations , as previously described [70] . A preliminary study has been carried out to determine the sublethal , LD50 and lethal doses of virus in mice . BALB/c mice were inoculated intranasally with HMPV strain C85473 ( sublethal dose = 3 x 105; LD50 = 5 x 105 or lethal dose = 106 PFU per mouse ) or HMPV ΔSH whereas IL-1β-/- and wild-type C57BL/6 mice were inoculated with 2 x 106 PFU of HMPV strain C85473 . The LD50 dose in C57BL/6 mice was four-fold higher than that of BALB/c mice because C57BL/6 mice are less susceptible to HMPV infection , as compared to BALB/c mice [47] . Equal volumes of Opti-MEM medium served as mock infection . To block NLRP3 inflammasome activation , MCC950 ( 5 mg/kg ) [21 , 71] was mixed and administered intranasally at the same time with the virus . However , MCC950 was also given 24 h post-infection in a single experiment . Equivalent dilutions of DMSO ( Sigma Aldrich ) served as control . This treatment was repeated once a day for two consecutive days . For IL-18 inhibition , immediately following inoculation of virus , mice underwent intraperitoneal injections of IL-18BP at a dose of 75 μg/kg ( R&D Systems , Minneapolis , MN , USA ) [72] . This treatment was repeated once a day for two consecutive days during infections . Control mice were given sterile saline in a similar manner . To evaluate viral titers on days 1 , 3 and 5 post-infection , mice were euthanized and whole lungs were harvested and then homogenized in PBS ( 1 ml/sample ) using TH Tissue Homogenizer ( Omni International , Kennesaw , GA , USA ) . Supernatants were collected after centrifugation at 350 x g for 10 minutes at 4°C and methylcellulose was used to determine viral titers by immunostaining and expressed as PFU per gram of lung . On days 1 , 3 and 5 post-infection , mice were euthanized and broncho-alveolar lavage ( BAL ) was performed with sterile cold phosphate-buffered saline ( PBS ) . The cells in the lavage fluid were pelleted by centrifugation at 300 x g for 5 min at 4°C , and then suspended in PBS whereas BAL supernatants were collected for evaluating other inflammatory parameters . Viable cell number was determined using a hemocytometer and expressed as number per milliliter of BAL . For differential cell counts , 100 μl of suspended cells were spun onto a slide by using a Shandon Cytospin 3 cytocentrifuge ( Thermo Fisher Scientific ) at 100 x g for 5 min at room temperature . Slides were then air-dried and stained with May-Grunewald Giemsa solutions ( Sigma Aldrich ) according to the manufacturer’s instructions . Differential cell counts were made with standard morphological criteria by counting at least 300 cells per sample . The results were expressed as differential percentage . The concentrations of IL-1β , IL-6 , TNF-α , IFN-γ and IL-18 in the cell supernatants or BAL fluids were determined using the Mouse or Human IL-1β , IL-6 , TNF-α , IFN-γ , IL-18 DuoSet ELISA ( R&D Systems ) or the Mouse IL18/IL-18 ELISA Pair Set ( Sino Biological , Beijing , China ) according to the manufacturer’s instructions . The results were expressed as picogram per milliliter of BAL . Total protein levels in the BAL supernatants were determined using Quick Start Bradford Protein Assay ( Bio-Rad Laboratories , Mississauga , ON , Canada ) according to the manufacturer’s instructions . The results were expressed as milligram per milliliter of BAL . In order to analyze lung-infiltrating immune cells , mice were deeply anesthetized and perfused intracardially with D-PBS without Ca2+ and Mg2+ prior to ( day 0 ) and on days 1 , 3 and 5 post-infection . Whole lungs were collected and digested with Liberase TL ( Roche Diagnostics , Mannheim , Germany ) . Lung homogenates were incubated for 1 h at 37°C then filtered through a 70-μm cell strainer ( BD Biosciences , Mississaugo , ON , Canada ) . The cell suspension was centrifuged at 300 x g for 10 min at room temperature . The supernatant was aspirated and cells were washed twice with D-PBS plus 2% FBS . Cells were first incubated on ice for 30 min with fixable viability stain 510 ( BD Biosciences , CA , USA ) , then washed and incubated again on ice for 30 min with purified rat anti–mouse CD16/CD32 ( Mouse Fc Block; BD Biosciences , CA , USA ) . Red blood cells were lysed with BD Pharm Lyse ( RBC Lysis Buffer 10X –BioLegend , San Diego , CA , USA ) and the recovered leukocytes were washed and resuspended in D-PBS . After the washing step , cells were incubated on ice for 40 min with a pool of antibodies ( anti-CD45 , anti-CD11b , anti-CD170 ( Siglec-F ) , anti-Ly6C , anti-Ly6G , anti-CD11c , anti-CD115 , anti-B220 , anti-CD3ε , anti-CD4 and anti-CD8a /BD Bioscience , CA , USA ) . Number of cells was determined with Precision Count Beads ( BioLegend , San Diego , CA , USA ) . Labeled cells were then washed and resuspended in DPBS . Flow cytometry analyses and data acquisition were performed by using a BD SORP LSR II and the BD FACSDiva software , respectively . The total proteins in cell supernatants were concentrated using Amicon Ultra-15 Centrifugal Filters ( Millipore Canada , Etobicoke , ON , Canada ) according to the manufacturer’s instructions . The concentrations of protein in cell lysates and supernatants were determined using Quick Start Bradford Protein Assay . Equal protein amounts were separated on 10% SDS-PAGE gels and then transferred to nitrocellulose membranes ( GE HealthCare Life Sciences , Mississauga , ON , Canada ) and blocked using 5% BSA ( Sigma Aldrich ) . Primary antibodies were used at a dilution of 1:1 , 000 goat anti-caspase-1 ( R&D Systems ) ; rabbit anti-cleaved caspase-1 ( p20 ) or mouse anti-α-tubulin ( Cell Signaling Technology , Boston , MA , USA ) . Secondary antibodies were used at a dilution of 1:1 , 000 HRP-conjugated rabbit anti-goat ( R&D systems ) or 1:5 , 000 HRP-conjugated rabbit anti-mouse or mouse anti-rabbit ( Cell Signaling Technology ) . Signal detection was carried out using the West Pico Plus Chemiluminescent Substrate ( Thermo Fisher Scientific ) . On day 5 post-infection , mice were euthanized and their lungs were removed . Tissue was fixed in 4% paraformaldehyde , embedded in paraffin , sectioned in slices of 5 μm , and stained with hematoxylin and eosin . Slides were digitalized at 40X magnification using a Nanozoomer slide scanner ( Hamamatsu , Japan ) and scored using NDP viewer 2 . 0 software ( Hamamatsu , Japan ) . The histopathological scores were determined by a pathologist and a medical biologist who were blinded to the experimental data . A semi-quantitative scale was used to score bronchial/endobronchial , peribronchial , perivascular , interstitial , pleural and intra-alveolar inflammation [73] . Scores represent consensus between the two observers . The results were expressed as lung total inflammatory scores . All statistical tests were conducted using the GraphPad Prism version 6 . 0 ( GraphPad Software , La Jolla , CA , USA ) . The results were expressed as the mean ± S . E . M for each group and 'n' referred to the sample size . Survival data were analyzed by comparing Kaplan-Meier curves using the log-rank test . Viral titers , cytokines and total protein levels , immune cell recruitment , cell differentiation as well as lung histopathological scores were analyzed using unpaired Student t-test , Mann-Whitney U-test , one-way analysis of variance ( ANOVA ) followed by Tukey post hoc or Kruskal-Wallis test followed by Dunn’s post hoc for multiple comparisons . Differences were considered statistically significant when P < 0 . 05 .
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Human metapneumovirus ( HMPV ) , a negative-stranded , enveloped RNA virus , is recognized as one of the leading causes of acute respiratory disease in children since its discovery in 2001 . Nevertheless , there is currently no licensed vaccine for the prevention of HMPV infection and treatment modalities are limited to the use of ribavirin , a weak antiviral agent or immunoglobulins . NOD-like receptor protein 3 ( NLRP3 ) inflammasome has been shown to be involved in the pathogenesis of several RNA viral diseases but its role during HMPV infection has not been fully studied . Here , we report for the first time that NLRP3 inflammasome is activated by the small hydrophobic protein of HMPV , leading to the release of IL-1β , which has the potential to exacerbate inflammation . However , NLRP3 inflammasome has no direct influence on viral replication . Thus , IL-1β-mediated inflammatory process plays an important role during HMPV infection and , therefore , anti-IL-1β strategies such as the use of NLRP3 inhibitors may be a novel potential approach for the prevention and therapy of HMPV disease .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[] |
2019
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Human metapneumovirus activates NOD-like receptor protein 3 inflammasome via its small hydrophobic protein which plays a detrimental role during infection in mice
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Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them , but also the biological relationships among those key genes . Here we describe a statistical method , Gene Relationships Among Implicated Loci ( GRAIL ) , that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250 , 000 PubMed abstracts . We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies . We then tested GRAIL , by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics . First , we took 74 nominally associated Crohn's disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes . Of these , ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive . Next , we applied GRAIL to 165 rare deletion events seen in schizophrenia cases ( less than one-third of which are contributing to disease risk ) . We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses . GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regions—that likely represent key disease pathways . An online version of this method is available for public use ( http://www . broad . mit . edu/mpg/grail/ ) .
An emerging challenge in genomics is the ability to examine multiple disease regions within the human genome , and to recognize a subset of key genes that are involved in a common cellular process or pathway . This is a key task to translate experimentally ascertained disease regions into meaningful understanding about pathogenesis . The importance of this challenge has been highlighted by advances in human genetics that are facilitating the rapid discovery of disease regions in the form of genomic regions around associated SNPs ( single nucleotide polymorphisms ) [1]–[6] or CNVs ( copy number variants ) [7]–[10] . These disease regions often overlap multiple genes – though only one is typically relevant to pathogenesis and the remaining are spuriously implicated by proximity . The difficulty of this task is heightened by the limited state of cataloged interactions , pathways , and functions for the vast majority of genes . However , undefined gene relationships might often be conjectured from the literature , even if they are not explicitly described yet . The general strategy of using function to prioritize genes in disease regions has been substantially explored [11]–[18] . However , predicted disease genes have not , in general , been easily validated . Thus far , published approaches have utilized a range of codified gene information including protein-interaction maps , gene expression data , carefully constructed gene networks based on multiple information sources , predefined gene sets and pathways , and disease-related keywords . We propose , instead , to use a flexible metric of gene relatedness that not only captures clearly established close gene relationships , but also has the ability to capture potential undocumented or distant ones . Such a metric may be a more powerful tool to approach this problem rather then relying on incomplete databases of gene functions , interactions , or relationships . To this end , we use established statistical text mining approaches to quantify relatedness between two genes – specifically , gene relatedness is the degree of similarity in the text describing them within article abstracts . The published literature represented in online PubMed abstracts encapsulates years of research on biological mechanisms . We and others have shown the great utility of statistical text mining to rapidly obtain functional information about genes , including protein-protein interactions , gene function annotation , and measuring gene-gene similarity [19]–[22] . Text is an abundant and underutilized resource in human genetics , and currently a total of 140 , 000 abstracts from articles that reference human genes are available through PubMed [23] . Additional valuable information can be seamlessly gained by including more than 100 , 000 references from orthologous genes; many important pathways have been more thoroughly explored in model systems than in humans . We have developed a novel statistical method to evaluate the degree of relatedness among genes within disease regions: Gene Relationships Among Implicated Loci ( GRAIL ) . Given only a collection of disease regions , GRAIL uses our text-based definition of relatedness ( or alternative metrics of relatedness ) to identify a subset of genes , more highly related than by chance; it also assigns a select set of keywords that suggest putative biological pathways . It uses no information about the phenotype , such as known pathways or genes , and is therefore not tethered to potentially biased pre-existing concepts about the disease . In addition to a flexible text-based metric of relatedness , GRAIL's ability to successfully connect genes also leverages a statistical framework that carefully accounts for differential gene content across regions . We assume that each region contains a single pathogenic gene; therefore narrow regions with one or just a few genes are more informative than expansive regions with many genes , since they are likely to have many irrelevant genes . To take advantage of this , we have designed GRAIL to set a lower threshold in considering relatedness for those genes in narrow regions , allowing for more distant relationships to be considered; on the other hand it sets a more stringent threshold for genes located in expansive mutligenic regions and considers only the very closest of relationships . This strategy prevents large regions with many genes from dominating the analysis . In this paper we apply GRAIL to four phenotypes . In each case GRAIL is able to identify a subsets of genes enriched for relatedness – more than expected by random chance . We demonstrate enrichment for relatedness among true disease regions rigorously based on both GRAIL's theoretically derived p-value and also based on parallel analysis of either ( 1 ) carefully selected random regions matched for gene content and size or ( 2 ) experimentally derived false positive disease regions . GRAIL is able to identify subsets of highly related genes among validated SNP associations . First we use GRAIL to identify related genes from SNPs associated with serum lipid levels; GRAIL correctly identifies genes already known to influence lipid levels within the cholesterol biosynthesis pathway . In comparison to randomly selected matched SNP sets , the set of lipid SNPs demonstrate significantly more relatedness . Second , we use GRAIL to identify significantly related genes near height-associated SNPs; these genes highlight plausible pathways involved in height . In comparison to randomly selected matched SNP sets , the set of height SNPs also demonstrate significantly more relatedness . Encouraged by GRAIL's ability to recognize biologically meaningful connections , we tested its ability to distinguish true disease regions from false positive regions in two practical applications in human genetics . First , in Crohn's disease , we start with a long list of putative SNP associations from a recent GWA ( genome-wide association ) meta-analysis [24] . We demonstrate that a substantial fraction of these SNPs contain highly related genes—far beyond what can be expected by chance . We demonstrate that many of these SNPs subsequently validate in an independent replication genotyping experiment . Second , in schizophrenia , we previously identified an over-representation of rare deletions in schizophrenia cases compared to controls [8] . Despite the statistical excess , it is challenging to identify exactly which case deletions are causal , given the relatively high background rate of rare deletions in controls . Using GRAIL however , we are able to demonstrate that a subset of case deletions contain related genes . We further demonstrate that these genes are highly and significantly enriched for central nervous system ( CNS ) expressed genes . In stark contrast , GRAIL finds no excess relatedness among genes implicated by case deletions .
GRAIL relies on two key methods: ( 1 ) a novel statistical framework that assesses the significance of relatedness between genes in disease regions ( 2 ) a text-based similarity measure that scores two genes for relatedness to each other based on text in PubMed abstracts . Details for both are presented in the Methods . The GRAIL statistical framework consists of four steps ( see Figure 1 ) . First , given a set of disease regions we identify the genes overlapping them ( Figure 1A ) ; for SNPs we use LD ( linkage disequilibrium ) characteristics to define the region . Second , for each overlapping gene we score all other human genes by their relatedness to it ( Figure 1B ) . In this paper we use a text-based similarity measure; alternative measures of relatedness , for example similarity in gene annotations or expression data , could be easily applied instead [25] , [26] . Third , for each gene we count the number of independent regions with at least one highly related gene ( Figure 1C ) ; here the threshold for relatedness varies between regions depending on the number of genes within them . We assign a p-value to that count . Fourth , for each disease region we select the single most connected gene as the key gene . We assign the disease region that key gene's p-value after adjusting for multiple hypothesis testing ( if there are multiple genes within the region ) ( Figure 1D ) . This final score is listed in this paper as pmetric where the metric is text , expression , or annotation based . Very low ptext scores for one region indicate that a gene within it is more related to genes in other disease regions through PubMed abstracts than expected by chance . Simulations on random groups of SNPs demonstrate that the ptext values approximately estimate Type I error rates , being approximately uniformly distributed under the null hypothesis ( see Figure S1 ) . However , we recommend the use of careful simulations or controls rather than actual theoretical p-values to reinforce the significance of GRAIL's findings – as we do in the examples below . The text-based similarity metric is based on standard approaches used in statistical text mining . To avoid publications that report on or are influenced by disease regions discovered in the recent scans , we use only those PubMed abstracts published prior to December 2006 , before the recent onslaught of GWA papers identifying novel associations . This approach effectively avoids the evaluation of gene relationships being confounded by papers listing genes in regions discovered as associated to these phenotypes . In addition to including primary abstract references about genes listed in Entrez Gene , we augment our text compendium with references to orthologous genes listed in Homologene [23]; this increases the number of articles available per gene from 6 to 12 ( see Table 1 ) . We note that the distribution of articles per gene is skewed toward a small number of genes with many references; 0 . 4% of genes are referenced by >500 articles , while 26% of genes are referenced by <5 . In fact 2 , 034 genes could not be connected to any abstracts at all . For each abstract we convert free text into vectors of word counts [19] . For each gene we define a word vector that consists of averaged word counts from document references to it . Pairwise gene relatedness is then the correlation between the vectors of word counts between two genes . Two genes that are referenced by abstracts using the same sorts of words will receive a high similarity score , whereas two genes that have abstract references that largely use a different vocabulary will receive a low score ( Figure 1B ) . Importantly , genes do not need to be co-cited in the same document to be identified as highly similar . After regions are scored with GRAIL , PubMed text can be used to identify keywords that may provide insight into the underlying biological pathways . We define these keywords as those words that most strongly link the significant genes in each region , that is the words with overall greatest weight across all of the text vectors from those genes . Since the GRAIL framework can be easily used with any gene relatedness metric , we also devised and tested two alternative metrics derived from Gene Ontology ( GO ) annotations [27] and an mRNA expression atlas consisting of expression measurements across multiple human tissues ( The Novartis Gene Expression Atlas ) [28] . These metrics are described in greater detail in Methods . We first applied GRAIL to a set of 19 validated SNPs associated with triglyceride , LDL , and/or HDL levels [5] , [6] . Since 14 SNPs ( out of 19 ) are near genes that are known members of lipid metabolism pathways , we hypothesized that GRAIL should be able to identify these genes accurately . A total of 87 genes were implicated by the 19 associated SNPs . Of the 14 SNPs near compelling candidate genes , 13 obtained ptext scores<0 . 01 ( Figure 2A , Table S1 ) . GRAIL correctly identified those genes implicated in lipid metabolism from each of these 14 regions . To asses the significance of these findings , we applied GRAIL to 1000 random matched SNP sets; each set consisted of 19 SNPs randomly selected from a commercial genotyping array which implicated a similar total of 87±10 genes . In contrast to lipid associated SNPs , not a single matched random set contained 13 SNPs that obtained ptext scores≤0 . 01; on average matched sets had 0 . 26 ( maximum 6 ) SNPs with ptext≤0 . 01 ( Figure 2A ) . Thus , there is substantial enrichment for highly connected genes captured by true lipid associated SNPs . Despite relatively comprehensive lipid biology annotation , GO does not identify relationships between regions as effectively as published text ( Figure 2A ) . A total of 12 out of the 19 associated SNPs obtained pannotation<0 . 01 . Relationships between highest scoring candidate genes are explained by several shared GO codes including: GO:0008203 ( ‘cholesterol metabolic process’ ) , GO:0016125 ( ‘sterol metabolic process’ ) , GO:0006629 ( ‘lipid metabolic process’ ) , GO:0008202 ( ‘steroid metabolism’ ) , and GO:0005319 ( ‘lipid transporter activity’ ) . Gene expression does not identify relationships between regions as effectively as text , either ( Figure 2A ) . A subset of 4 associated SNPs obtain pexpression<0 . 01 . The regions with the most significantly connected genes have similar tissue-specific expression profiles . The highest expression is in four samples taken from adult and fetal liver tissues , known to play a major role in cholesterol metabolism . While associated SNPs are less connected with these alternative metrics , they do seem to leverage the appropriate functional variables and provide valuable phenotypic information . We next applied GRAIL to 42 validated SNP associations to adult height in recent GWA studies [2]–[4] . This application tests GRAIL's ability to connect genes in the absence of functional literature connecting the phenotype to the relevant pathways . In contrast to lipid metabolism , all associated common SNPs were identified in 2007 and 2008 and the underlying biological pathways involved in height are still poorly understood . This insures independence between association results and the functional literature from before 2007 that is mined in this study . In most cases the key genes are not yet known . The 42 height SNPs implicated a total of 185 genes ( Table S2 ) . Of these 42 regions , 13 obtained ptext scores<0 . 01 ( Figure 2B ) . For comparison , we used GRAIL to score 1000 matched SNP sets; as before each set consisted of 42 SNPs randomly selected from a commercial array and implicated a total of 185±10 genes . Not a single random set contained 13 SNPs that obtained ptext scores≤0 . 01; on average matched sets had 0 . 77 ( maximum 10 ) SNPs with ptext scores<0 . 01 . Thus , we present clear statistical evidence that GRAIL identifies genes with non-random functional connections among associated loci . Strikingly , the top five keywords linking the genes were ‘hedgehog’ , ‘histone’ , ‘bone’ , ‘cartilage’ , and ‘growth’ ( see Table S3 for a more complete list ) . Of note , ‘height’ , does not emerge as a keyword since these genes had not been previously related to height . For comparison , the top five keywords for lipid metabolism associated SNPs were ‘lipoprotein’ , ‘cholesterol’ , ‘lipase’ , ‘apolipoprotein’ , and ‘triglyceride’ ( Table S3 ) . These results are particularly noteworthy as this analysis uses only a simple list of SNPs implicated by GWA studies—no specific biological pathways or mechanisms or phenotype details are assumed . After successfully applying GRAIL to validated associations for two phenotypes , we hypothesized that GRAIL could also be used to prospectively identify true disease regions , based on the relatedness of genes within them , from false positive regions . We tested GRAIL's ability to distinguish disease regions from a longer list of results containing a large number of false positive regions as well in two separate human genetics applications . A recent GWA meta-analysis in Crohn's disease identified 74 independent SNPs as nominally significant ( p<5×10−5 ) [24] . While the excess beyond chance suggested many of these regions were likely true positives , up to half of these regions should by necessity be unrelated to Crohn's and simply represent the tail of the null distribution . Thus we sought to explore whether GRAIL could identify a subset of these SNPs that implicate an inter-connected set of genes , and whether those represented true associations that could be validated . In a now published replication genotyping of the 74 SNPs , 30 replicated convincingly when tested in independent samples ( defined as having one-tailed association p-values<0 . 0007 in replication samples and two tailed association p-values<5×10−8 overall ) , confirming true positive associations , whereas 22 convincingly failed to replicate ( defined as overall association p-value rising to >10−4 ) ; the remaining 22 regions had intermediate levels of significance following replication ( and can be considered as yet unresolved associations ) [24] . We applied GRAIL prospectively to these 74 nominally associated SNPs . GRAIL was initially operated independent of any knowledge of the contemporaneous replication genotyping experiment . Each region contained between 1 and 34 genes , except for two regions that contained no genes and were not scored . GRAIL identified 13 regions as significant ( achieving ptext scores<0 . 01 ) , as with the previous examples far in excess of chance . Of those 13 regions , 10 were among the set that convincingly validated in subsequent replication ( Table 2 ) —the remaining three had indeterminate levels of significance . By contrast , only 20 of 63 SNPs remaining SNPs validated ( Table S4 ) . Disease regions that replicate have more significant GRAIL scores than those that failed ( p = 0 . 00064 , one-tailed rank-sum test , Figure 3A ) . As with randomly selected SNP lists , the distribution of scores for the 21 failed regions was indistinguishable from a random ( uniform ) distribution of p-values ( Figure 3B ) . Using these Crohn's results , we have compared GRAIL's performance to four other competing algorithms that also use functional information to prioritize genes , and GRAIL's performance is superior at predicting true positive associations ( see Text S1 , Figure S2 , Table S5 , Table S6 ) . As a further test of GRAIL , we then evaluated the next most significant 74 associated SNPs that emerged from the Crohn's disease GWA meta-analysis ( association p-values ranging from 5×10−5 to 2×10−4 ) . Out of the 75 regions , 8 are not near any gene , and we did not score them . The remaining 67 regions were tested with GRAIL for relationships to the 52 replicated and indeterminate regions that emerged following replication . Two emerge with highly significant GRAIL scores: rs8178556 on chromosome 21 ( IFNAR1 , ptext = 1 . 7×10−4 ) and rs12928822 on chromosome 16 ( SOCS1 , ptext = 8 . 2×10−4 ) suggesting these independent regions may lead to novel associated SNPs for Crohn's disease ( see Table S7 ) . We next applied GRAIL to recently published sets of rare deletions seen in schizophrenia cases and matched controls . Multiple groups have recently demonstrated that extremely rare deletions , many of which are likely de novo , are notably enriched in schizophrenia [8]–[10] , [29] . However , since rare deletions occur frequently in healthy individuals as well , many of these case deletions will also be non-pathogenic . In fact , we previously found that large ( >100 kb ) , gene overlapping , singleton , deletions were present in 4 . 9% of cases but also in 3 . 8% of controls , suggesting that over two-thirds of these deletions are not relevant to disease [8] . We identified 165 published de-novo or case-only deletions of >100 kb overlapping at least one gene; a total of 511 genes are deleted or disrupted by these deletions [8] , [9] , [10] . Additionally , we identified 122 regions similar control-only deletions; a total of 252 genes are deleted or disrupted by these deletions . We applied GRAIL separately to both the case and control sets of deletions . In the case deletions , we identified a subset containing highly connected genes ( Figure 4A ) . Specifically , 12 of the 165 regions obtain ptext scores<0 . 001 with text-similarity ( Table 3 ) . The top keywords suggest some common biological underlying functions: ‘phosphatase’ , ‘glutamate’ , ‘receptor’ , ‘cadherin’ , and ‘neurons’ . In contast , we did not identify any regions with significantly related genes in the corresponding list of deletions; out of a total 124 regions , none obtained ptext scores<0 . 001 ( see Table S8 ) . This represents a significant enrichment within the cases ( p = 0 . 01 , one Fisher's exact text ) . We then sought independent assessment of the biological relationship of the genes highlighted by GRAIL by examining the extent to which these genes demonstrate preferential expression in CNS tissues using a publicly available tissue atlas [30] . Here we define preferential expression as median CNS tissue expression significantly greater than in other tissues ( p<0 . 01 by one-tailed rank-sum test ) . Considering the entire set , case-deletions are not enriched for genes preferentially expressed in the CNS ( 22% are preferentially expressed in the CNS , compared to 25% of control-deletion genes ) . However , considering the subset of genes indentified by GRAIL ( ptext<0 . 01 ) , 60% ( 9 of 15 genes ) are preferentially CNS expressed . Furthermore , the fraction of genes with preferential CNS expression correlates inversely with the significance of the GRAIL score ( Figure 4B ) . Regions that GRAIL assigns non-significant scores to , do not demonstrate any compelling enrichment for CNS expressed genes .
The main strength of GRAIL is its ability to link genes through text that may not yet have an established common pathway or process . Consider the IRGM gene association to Crohn's disease – for which GRAIL found strong evidence ( uncorrected ptext = 0 . 0011 ) . GRAIL's text-based similarity metric recognize the significant connections between IRGM and four other validated or intermediate region genes: IRF1 , IL12B , IRF8 , and SP110 . IRGM is not readily connected to these genes in a well-defined pathway and , in-fact , is not referenced together with them in any abstracts; furthermore no IRGM interactions are listed in Entrez at all . Yet they all are involved in the host response to Mycobacterium and possibly other intracellular infections by macrophages . The top keywords describing the connections between IRGM and these genes were ‘macrophages’ , ‘tuberculosis’ and ‘mycobacterium’ . The IRGM gene has been shown experimentally to eliminate intracellular Mycobacterium tuberculosis via autophagy [31] . The IRF1 homolog studies in mouse have demonstrated its role in intra-cellular nitrous oxide production , necessary to fight Mycobacterium infections [32] . Individuals with loss of function IL12B mutations have been found with increased susceptibility to Mycobacterium infections [33] and knock out mice have demonstrated increased susceptibility to infection [34] , [35] . A SP110 mouse homolog has been shown to mediate innate immunity in fighting intra-cellular Mycobacterium tuberculosis infection [36] . GRAIL is able to identify this common underlying similarity between these genes , and assign a significant score to IRGM , while at the same time revealing what may be an important pathway in Inflammatory Bowel Disease . Other strategies depending on interaction networks or functional databases may struggle to detect these relationships . GRAIL systematically identifies a single gene within a disease region as the likely disease gene . We highlight two interesting examples from the height data of previously unrecognized potentially causative genes . The first example is the rs42046 SNP on chromosome 7 region implicating five genes . The genetic studies that identified this region had suggested CDK6 as the likely causative gene [2]–[4] . However , GRAIL found greatest evidence in support of PEX1 ( uncorrected ptext = 0 . 0084 ) . When we compare the most compelling of these genes , PEX1 , to candidates from the other 41 SNPs with our text-based metric , we found it to be most related to a gene in a height-associated SNP on chromosome 8 , PEX2 ( PXMP3 ) . The protein products of both PEX1 and PEX2 are involved in peroxisome biogenesis and are implicated in a genetic disease associated craniofacial and skeletal abnormalities ( Zellweger's syndrome ) [37]–[39] . While it may be a coincidence that these two closely related genes are associated by chance , it is certainly possible that peroxisome biogenesis represents a previously unrecognized height pathway . The second example is the rs10935120 SNP on chromosome 3 , implicating three genes; the genetic study that had identified this gene had suggested ANAPC13 as the likely candidate in the region [4] . However , GRAIL identified the KY gene as the most likely disease gene ( ptext = 0 . 04 ) . In fact , a mutation in the KY gene causes spinal scoliosis in a mouse model [40] , and the KY protein product interacts with sarcomeric cytoskeletal proteins [41] . While these literature-based hypotheses may be obvious to a few specialized researchers , the strength of GRAIL is that it is able to suggest these connections in a systematic and objective manner from the entirety of the published literature . We consider closely the subset of related genes identified by GRAIL from rare deletions in patients with schizophrenia . Schizophrenia is a disorder characterized by hallucinations , delusions , cognitive deficits and apathy . The molecular basis of the symptom complex associated with the disorder is largely unknown . However accumulating evidence suggest that dysregulation of synaptic activity and abnormalities in neuronal development and migration may contribute to the pathophysiology of schizophrenia [42] . Many of the highest scoring genes recovered by GRAIL within the deleted regions in cases ( Table 3 ) are localized to the postsynaptic membrane/signaling complex that propagate signals resulting in changes synapse function and downstream gene expression/transcription . The DLG2 gene product interacts at postsynaptic sites to form a multi-meric scaffold for the clustering of receptors , ion channels , and associated signaling proteins . MAGI1 and MAGI2 both encode post-synaptic scaffolding molecules involved in cell adhesion and signaling [43] , [44] . Furthermore , glutamatergic neurotransmission is implicated through the selection of GRM1 , GRM7 , and GRM8 . Many of the most significant candidate genes identified by GRAIL are involved in neuronal development , cell-cell adhesion and axon guidance . CNTN5 is an immunoglobulin super-family membrane-anchored neuronal protein that is also an adhesion molecule [45] . It may play a role in the developing nervous system [46] . The SDK1 gene expresses a synaptic adhesion protein [47] that guides axonal terminals to specific synapses in developing neurons . The PTPRM encodes a neuronally expressed protein tyrosine phosphatase that mediates cell-cell aggregation and is involved in cell-cell adhesion [48] , [49] . The most critical technical difference between GRAIL and other strategies is that it does not use any strict definitions of gene functions or interactions , but rather uses a metric of relatedness that allows for a relatively broad range of freedom with which to connect genes . While GRAIL will certainly identify relationships between genes known to be in a common pathway , it goes beyond that , and can allow less strict evidence . In fact , it is even able to identify relatedness between genes that have no established common pathways or article co-citations ! In contrast , other strategies start with static gene relationships—such as ( 1 ) pre-constructed molecular networks [12] , [16] or sets of gene with common function [11] , [15] or ( 2 ) a subset of functions identified as relevant to disease either by the user [17] or by mining the published text [14] . In a head to head match up against four other methods that we were able to obtain implemented versions of , GRAIL demonstrated superior performance in predicting Crohn's associated SNPs ( see Text S1 , Figure S2 , Table S5 , and Table S6 ) . While we have shown the promise of text-based similarity in identifying regions and the genes within them that are part of a larger biological pathway , we note that this strategy's effectiveness is wholly contingent on the completeness of the scientific text . It could be biased towards subsets of genes and pathways that are particularly well studied , and against poorly studied ones . In many of the cases that we illustrate , there are regions that could not be connected – for example , GRAIL fails to connect 5 validated Crohn's SNPs that obtain ptext scores>0 . 5 ( Figure 3B ) . These regions might have been missed since the relevant gene is either poorly studied , or even if the gene is well studied , the relevant function of that gene is not well documented in the text . An alternative possibility is that the SNP is tagging non-genic regulatory elements . Additionally , the SNP may be the first discovered representative association for a critical pathway , not represented by other SNP associations – and therefore cannot be connected to them . In this case future discoveries will clarify the significance of that association . In cases where there is no apparent published connection between associated genes , other similarity metrics based on experimentally derived data , such as gene expression , protein-protein interactions and transcription factor binding sites could also complement the text-based approaches presented here . In fact , we demonstrate how annotation-based metrics or gene expression-based metrics are able to identify a subset of the associated SNPs in lipid metabolism . As these and other metrics are optimized , they could be used in conjunction with the novel GRAIL statistical framework that we present here to help understand gene relationships .
The Gene Relationships Among Implicated Loci ( GRAIL ) has four basic steps that are outlined below . It has two input sets of disease regions: ( 1 ) a collection of NSEED seed regions ( SNPs or CNVs ) and ( 2 ) a collection of NQUERY query regions . Genes in query regions are evaluated for relationships to genes in seed regions , and query regions are then assigned a significance score . In most applications we are examining a set of regions for relationships between implicated genes , the query regions and the seed regions are identical . In other circumstances where we have a set of putative regions that are being tested against validated ones , the putative regions are defined as query regions , and the validated ones are defined as seed regions . We measure relatedness between genes using similarity in published text from gene references . We first obtain article abstracts from Pubmed . We downloaded all abstracts on December 16 , 2006 . For each gene , we identified and downloaded abstract references listed in Entrez Gene [23]; additionally , we downloaded Entrez Gene abstract references for gene orthologs listed in Homologene [53] . We removed those articles referencing more than 10 , 000 genes . Only the title ( TI ) and abstract ( AB ) fields were included for further text processing . We defined a vocabulary consisting of only those terms appearing in 40 or more abstracts , and fewer than 130 , 000; this resulted in a vocabulary of 23 , 594 terms . For each abstract j we create a vector of term frequencies , tfij , representing the number of times each term i appears within it . Term frequencies are transformed into weights , wij , according to a standard inverse document frequency scheme [54]:where NDOC is the total number of documents , and dfi ( or document frequency ) is the number of documents the term i appears in . This scheme emphasizes rare words , and de-emphasizes more common words . For every gene , we define an averaged term-vector , which is an average of weighted term vectors from gene references and homologous gene references . Abstracts are weighted according to the number of genes they reference; articles referencing many genes are down-weighted to mitigate their influence:where gik is a the weighted count of term i for gene k , j is a document reference for gene k , and document j references nref , j genes . For a given gene i these gik terms define a gene-text vector . The gene text vectors are normalized , so that their euclidean length is 1 . Pairwise gene relatedness can be calculated as the dot product between two normalized term vectors for genes . To assign keywords to a collection of query regions , we first identify the single candidate genes with the best GRAIL ptext from each region . We then eliminate those regions where the uncorrected GRAIL score for the gene is ptext>0 . 2 . We restrict keywords to those that appear in >500 documents , contain >3 letters , and have no numbers . For each term , i , we calculate a score which is the difference between averaged term frequencies among candidate genes and all genes:The top twenty highest scoring terms are selected as keywords . We defined a relatedness metric between genes based on similarity in Gene Ontology annotation terms [27] . We downloaded Gene Ontology structure and annotations on December 19 , 2006 . In addition to human gene GO annotations , we added orthologous gene annotations . Since GO is a hierarchically structured vocabulary , for each gene annotation we also added all of the more general ancestral terms . This resulted in a total of 843 , 898 annotations for 18 , 050 genes with 10 , 803 unique GO terms; this corresponds to a median of 40 terms per gene . We weighted annotations proportionally to the inverse of their frequency , so common annotations received less emphasis . We used a weighting scheme analogous to the one we used for word weighting:where gij represented the weighted code i for gene j , NG is the total number of genes , and gfi ( or GO frequency ) is the number of genes annotated with the term i . Gene relatedness was the correlation between these weighted annotation vectors . To calculate gene relatedness based on expression we downloaded the Novartis Gene Expression Atlas [28] . The data set consists of measurements for 33 , 689 probes across 158 conditions . Probes were averaged into 17 , 581 gene profiles . Gene relatedness was calculated as the correlation between expression vectors . We applied GRAIL to score 19 lipid-associated SNPs and separately to score 42 height-associated SNPs . Specific SNPs are listed in Table S1 and Table S2 . We used the SNP sets as both the seed and the query set to look for relatedness between genes across regions . We scored SNPs separately using text , annotation , and expression similarity metrics . We compiled the best candidate genes and scores for the SNP regions . Prior to replication , we had access to 74 independent SNP regions that had emerged from a meta-analysis of Crohn's Disease . All 74 SNPs were used as both the query set and as the seed set into GRAIL . We assessed whether those SNPs that replicated had different text-based significance values than those that fail to replicate . To identify additional regions of interest , we identified the next 75 most significant regions in the Crohn's disease meta-analysis – they were used in GRAIL as a query set; for the seed set included all SNPs that did not fail in replication . We identified singleton deletions or confirmed de novo deletions reported by one of three groups . We selected those deletions that were in cases only or in controls only , were at least 100 kb large , and included at least one gene . We obtained singleton deletions online published by the International Schizophrenia Consortium ( 2008 ) at [8] . We obtained de novo deletions published by Xu et al ( 2008 ) from Table 1 [10] . We obtained singleton deletions published in Walsh et al ( 2008 ) from Table 2 [9] . We identified a total of 165 case-only deletions and 122 control-only deletions . We applied the GRAIL algorithm separately to case and controls . We speculated that the case deletions might hit genes from a common pathway and GRAIL p-values may therefore be enriched for significant scores . On the other hand , we hypothesized that control deletions might be located effectively at random , and so no particular pathway or common function should necessarily be enriched in this collection . To examine genes for tissue specific expression in the CNS system , we obtained a large publicly available human tissue expression microarray panel ( GEO accession: GSE7307 ) [30] . We analyzed the data using the robust multi-array ( RMA ) method for background correction , normalization and polishing [55] . We filtered the data excluding probes with either 100% ‘absent’ calls ( MAS5 . 0 algorithm ) across tissues , expression values <20 in all samples , or an expression range <100 across all tissues . To represent each gene , we selected the corresponding probe with the greatest intensity across all samples . The data contained expression profiles for 19 , 088 genes . We included expression profiles from some 96 normal tissues and excluded disease tissues and treated cell lines . We averaged expression values from replicated tissues averaged into a single value . To assess whether genes had differential expression for CNS tissues , we compared the 27 tissue profiles that represented brain or spinal cord to the remaining 69 tissue profiles with a one-tailed Mann-Whitney rank-sum test . Genes obtaining p<0 . 01 were identified as preferentially expressed . We compared GRAIL's performance in its ability to prospectively predict Crohn's associations to five other published methods . The selection of these methods , and the evaluation is detailed in Text S1 . An online version of this method is available ( http://www . broad . mit . edu/mpg/grail/ ) .
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Modern genetic studies , including genome-wide surveys for disease-associated loci and copy number variation , provide a list of critical genomic regions that play an important role in predisposition to disease . Using these regions to understand disease pathogenesis requires the ability to first distinguish causal genes from other nearby genes spuriously contained within these regions . To do this we must identify the key pathways suggested by those causal genes . In this manuscript we describe a statistical approach , Gene Relationships Across Implicated Loci ( GRAIL ) , to achieve this task . It starts with genomic regions and identifies related subsets of genes involved in similar biological processes—these genes highlight the likely causal genes and the key pathways . GRAIL uses abstracts from the entirety of the published scientific literature about the genes to look for potential relationships between genes . We apply GRAIL to four very different phenotypes . In each case we identify a subset of highly related genes; in cases where false positive regions are present , GRAIL is able to separate out likely true positives . GRAIL therefore offers the potential to translate disease genomic regions from unbiased genomic surveys into the key processes that may be critical to the disease .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"computational",
"biology/literature",
"analysis",
"genetics",
"and",
"genomics/gene",
"discovery",
"genetics",
"and",
"genomics/complex",
"traits",
"genetics",
"and",
"genomics/bioinformatics",
"genetics",
"and",
"genomics/genetics",
"of",
"disease",
"computational",
"biology/genomics",
"immunology/autoimmunity",
"computational",
"biology/systems",
"biology"
] |
2009
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Identifying Relationships among Genomic Disease Regions: Predicting Genes at Pathogenic SNP Associations and Rare Deletions
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An understanding of the immunological footprint of Mycobacterium tuberculosis ( MTB ) CD4 T cell recognition is still incomplete . Here we report that human Th1 cells specific for MTB are largely contained in a CXCR3+CCR6+ memory subset and highly focused on three broadly immunodominant antigenic islands , all related to bacterial secretion systems . Our results refute the notion that secreted antigens act as a decoy , since both secreted proteins and proteins comprising the secretion system itself are targeted by a fully functional T cell response . In addition , several novel T cell antigens were identified which can be of potential diagnostic use , or as vaccine antigens . These results underline the power of a truly unbiased , genome-wide , analysis of CD4 MTB recognition based on the combined use of epitope predictions , high throughput ELISPOT , and T cell libraries using PBMCs from individuals latently infected with MTB .
Tuberculosis is one of the major causes of death from infectious disease . Current diagnostics do not distinguish active and latent infection , and the only available vaccine has limited efficacy . Hence , there is an urgent need for both novel vaccines and diagnostic strategies . Human T cell responses to MTB involve CD4 , CD8 , CD1 and γ∂ T cells . Seminal studies showed that human memory T helper 1 ( Th1 ) cells directed against the purified protein derivative ( PPD ) of MTB secreted IFN-γ [1] . IFN-γ has an essential role in the protective immunity to mycobacteria , as individuals with genetic defects in the IFN-γ receptor has an increased susceptibility to mycobacteria [2] . Th1 cells mainly express the chemokine receptors CCR5 and CXCR3 [3] , while Th17 cells co-express CCR6 and CCR4 and Th22 cells co-express CCR6 and CCR10 [4] , [5] . While several studies have reported the identification of MTB antigens , from abundant or easily purified proteins [6] , [7] , a truly genome-wide study to identify antigens is lacking . In only a few cases have techniques allowing ex vivo detection and/or characterization of MTB-specific T cells , prior to any in vitro expansion and manipulations , been utilized [8] , [9] , [10] . A key issue relating to MTB immunity is whether different classes of antigens elicit responses that have the same or diverse functional characteristics . MTB antigens described so far are predominantly secreted MTB proteins [11] , Some of which are not essential for bacterial survival [12] . As a result , it was hypothesized that secreted proteins might act as decoy antigens , diverting the immune response from recognizing more relevant MTB proteins [13] . In this regard , two intriguing MTB protein categories are the PE/PPE proteins , and the Esx protein family , which have been shown to elicit B and T cell responses [14] , [15] . The function ( s ) of PE/PPE proteins are not fully understood but data indicates that they influence antigen presentation and host cell apoptosis [15] . The PE/PPE genes encode almost 200 proteins ( 4% of the total open reading frames ( ORFs ) ) [16] , unique to Mycobacteria and most prevalent in pathogenic strains . While PE/PPE proteins are mainly located within the bacterial cell wall and cell surface , some are also secreted [17] , [18] . PE/PPE genes are closely related to the Esx regions [19] . These regions encode Type VII secretion systems ( T7SS ) , also known as Esx secretion systems . Five related , but functionally distinct and non cross-complementing T7SS ( Esx 1–5 ) , are present in MTB [20] . The best characterized is Esx-1 , which encodes the Rv3874 ( culture filtrate protein 10 kDa , CFP10 ) and Rv3875 ( early secretory antigenic target 6 kDa , ESAT-6 ) antigens [20] . The genes encoding the Esx proteins , are arranged in tandem pairs ( EsxA-W ) at 11 genomic loci [21] . Esx secreted proteins have been detected from Esx-1 , -3 and -5 indicating that these are functional secretion systems [22] . T cell epitopes have been described from all main MTB protein categories , indicating that protein function or cellular location per se does not determine which proteins can be recognized . Previous studies in complex pathogen systems demonstrated that immune responses are directed against a relatively large fraction of the genome [23] , [24] . However , epitope reactivity is currently described only from about 4% of the approximately 4 , 000 ORFs of the MTB genome ( [11] ( IEDB , www . iedb . org ) ) . Hence , we hypothesized that a genome-wide probe of the immunogenicity of MTB ORFs would reveal a large number of novel antigens . Defining the breadth of responses is key for the design of vaccination strategies that mirror natural immunity [25] , evaluation of disease the performance of vaccine candidates and the development of diagnostics . By combining HLA class II peptide binding predictions with modern high throughput techniques such as ex vivo ELISPOT analysis , HLA class II multimers , and the screening of T cell libraries [26] , we were able for the first time to identify and characterize the genome-wide antigen response in latently infected individuals .
Protein sequences from five complete MTB genomes ( CDC1551 , F11 , H37Ra , H37Rv and KZN 1435 ) and sixteen draft assemblies from the NCBI Protein database ( Table S1 ) were aligned . The binding capacity of all possible 15-mer peptides ( n = 1 , 568 , 148 ) was predicted for 22 HLA DR , DP and DQ class II alleles ( Figure S1 and Table S2 ) most commonly expressed in the general population [27] , to select peptides predicted to bind multiple HLA class II alleles ( promiscuous epitopes ) . This approach identifies the most dominant and prevalent responses , corresponding to approximately 50% of the total overall response [27] . A total of 20 , 610 peptides ( with a range of 2 to 10 per ORF , and an average of 5 ) , including 1 , 660 variants not totally conserved amongst the genomes considered in the analysis , were synthesized and arranged into 1 , 036 peptide pools of 20 peptides ( Figure S1 ) . The ex vivo production of IFN-γ by PBMCs from 28 LTBI donors induced by each of the 1 , 036 pools was measured utilizing ELISPOT . Pools recognized by ≥10% of donors were deconvoluted , and 369 individual MTB epitopes were identified ( Table S3 ) . Individual donors recognized , on average , 24 epitopes , underlining the large breadth of response to MTB . Epitope responses were ranked on the basis of magnitude to assess their relative dominance . The top 80 epitopes accounted for 75% of the total response and the top 175 epitopes accounted for 90% of the total response ( Figure 1A ) . Only occasional weak responses were detected in 28 TB uninfected/non-Bacille Calmette-Guérin ( BCG ) vaccinated control donors , thus demonstrating that these responses were LTBI-specific ( Figure 1A ) . The epitopes were mapped to individual MTB antigens using the H37Rv as a reference genome . A total of 82 antigens were recognized by more than 10% of LTBI donors ( Figure 1B ) . These 82 antigens accounted for approximately 80% of the total response in LTBI donors ( Figure 1C ) . Responses to the epitopes from the most frequently recognized antigens were further characterized utilizing PBMCs depleted of either CD4 or CD8 T cells . The majority ( 97% ) of these epitopes were recognized exclusively by CD4 T cells ( Table S3 ) , as expected because of their identification on the basis of predicted HLA class II binding capacity . Comparing these 82 most prevalently recognized antigens with antigens for which similar ex vivo epitope reactivity has been described ( IEDB ) , we found that the majority ( 61/82 antigens , 74% ) was novel . While a given antigen might not have been analyzed in sufficient detail to lead to the description of defined epitopes , it might nevertheless have been described as a target of T cell responses . Therefore we performed a literature search for each individual antigen to further categorized them as novel , or as targets of CD4 T cells , CD8 T cells or undefined T cell type . This revealed that 41% of the antigens we identified had not previously been described as T cell targets ( Figure S2A and Table 1 ) . The responses to novel antigens , in terms of both response frequency and magnitude , are comparable to those directed against previously known T cell targets ( Table S4 ) . Further analysis of the IEDB data revealed a limited overlap , ( 18%; 28/158 ) between antigens identified in this study and antigens known as sources of HLA class I epitopes ( Figure S2B ) . Finally , no significant correlation was found with the antigens recognized by serological responses from the MTB proteome [28] ( Figure S2C ) . Next , using the TubercuList database [16] , we determined the protein category to which the identified antigens belong ( Figure 2 ) . As expected , the identified antigens were associated with almost every category , with the exception of regulatory proteins and proteins of unknown function . The significant overrepresentation of PE/PPE proteins was notable , as well as the underrepresentation of proteins in the conserved hypotheticals , cellular metabolism and respiration categories . The localization of antigens recognized was next visualized by plotting the recognition data on a linear map of the MTB genome . Analysis of either percent of donors responding or percent of total response revealed striking clusters of reactivity within certain regions of the genome ( Figure 3A ) . When the MTB genome was parsed into 5-gene windows , significant antigenic clusters ( defined by minimum 4 proteins within the 5-gene window being recognized by 7 . 1% of LTBI donors ) could be identified using binomial distribution probability and Bonferroni correction . Three significant antigenic islands ( Figure 3B ) , encoding 0 . 55% of the total ORFs , accounted for 42% of the total response ( Table 2 ) . One of the islands ( Island 3 ) contains the well-known Rv3875 and Rv3874 antigens , which is an Esx protein pair secreted via a T7SS . Strikingly , the other two islands also contain Esx protein pairs . Moreover , two of the antigenic islands are part of the known T7SS systems Esx-1 ( Island 3 ) and Esx-3 ( Island 1 ) . It is noteworthy that the proteins recognized included not only the proteins believed to be secreted , but also the proteins forming the actual secretion apparatus ( Island 1 ) . Indeed , the antigens identified within these islands correspond to proteins from several different protein categories , mostly assigned to the cell wall and cellular processes and the PE/PPE category , which is not surprising since several of these proteins are part of the T7SS . Additionally , Rv3615c [29] , which is functionally linked to Esx-1 [30] , was also prevalently recognized . However , it stands as a single antigen and not as part of an antigenic island . To dissect whether the main determinant of immunodominance was related to a given antigen being contained within an antigenic island or belonging to PE/PPE and Esx proteins families , we calculated the percentage of the total response for different groups of proteins as well as the percentage of the MTB genome associated with these protein groups ( Table 2 ) . To compare different protein groups we calculated the ratio between % of response and % genome , as a percent enrichment . The PE/PPE proteins were responsible for 19% of the total response , and when divided into PE/PPE proteins within an island compared to non-island , the island PE/PPE were more predictive of immunogenicity than the non-island ones ( Table 2 ) . Also , in the case of Esx proteins and T7SS , proteins within the antigenic islands were more likely to be immunogenic than those outside the islands . Proteins not in the antigenic islands , and not belonging to PE/PPE and T7SS categories , were responsible for 14% of the total response ( Table 2 ) . Thus , these data show that the antigenic islands identified are highly predictive of immunogenicity , and that to be contained within the antigenic islands is the most reliable predictor of the immunodominance of PE/PPE and Esx proteins . It has been proposed that some of the responses against secreted MTB proteins act as decoys [13] , thereby supporting bacterial persistence . It has also been proposed that T cells differing in their degree of multifunctionality might differ in terms of protective potential , or have a role in pathology [31] , [32] , [33] , [34] . Definition of dominant antigens allows testing the validity of these hypotheses . To address these issues we detailed responses against PE/PPE , Esx and other proteins expressed in the three major antigenic islands , or elsewhere , by a variety of approaches , including multiparameter intracellular cytokine staining ( ICS ) assays , tetramer staining and T cell libraries . The frequency of IFN-γ , TNFα , and IL-2 expressing CD4 T cells elicited by proteins from the PE/PPE and cell wall and cell processes category , and from within an island versus non-island , induced similar cytokine expression patterns ( Figure 4A and C; gating strategy in Figure S3 ) . The vast majority of CD4+ T cells were IFN-γ+TNFα+IL-2+ or IFN-γ+TNFα+ , followed by TNFα+ single producing CD4+ T cells . To a lesser extent , TNFα+IL-2+ , single IFN-γ+ , and single IL-2+ cells were also detected ( Figure 4A and C ) . Triple cytokine producers were found in 27–40% of cytokine-expressing CD4+ T cells , 30–43% expressed any 2 cytokines , and 23–44% produced a single cytokine ( Figure 4B and D ) . We did not observe any donor- , antigen- or epitope-specific pattern of cytokine production ( Figure 4E ) . CD4+ T cells were stained with selected HLA-epitope tetramer reagents and tetramer+ cells were enriched [8] , [35] . Epitope-specific T cell responses were detected in 16 donors at frequencies 0 . 25 to 24 . 3% ( median of 3 . 8 , interquartile range 1 . 5–15 . 3 ) for seven different HLA/T cell epitope tetramer combinations ( Figure 5A ) . Only a small number of tetramer-positive cells were detected with the epitope-specific tetramers in donors with a HLA mismatch ( Figure 5A ) , which confirmed that tetramer specificity was derived from the epitope and HLA molecule combination . Epitope tetramer combinations were selected based on the number of donors responding , HLA restriction , and the availability of corresponding reagents for tetramer production . Memory subset phenotypes were determined using Abs to CD45RA and CCR7 . Similar to the multifunctionality phenotype , we did not observe any differences in memory phenotype when comparing proteins from within an island vs . non-island ( Figure 5B and C ) . Rv0129c/Rv1886/Rv3804 , Rv3418c and Rv1195 epitope-specific tetramer+ T cells predominantly consisted of CD45RA−CCR7+ central memory T cells in all donors analyzed , followed by effector memory ( CD45RA−CCR7− ) . Percentages ranged between 70 . 1 and 91 . 3% ( median 85 . 0 , interquartile range ( 77 . 7–86 . 8 ) ) for central memory T cells and 8 . 6–26 . 8% ( 13 . 3 ( 10 . 2–19 . 0 ) ) for effector memory T cells . Only a minor fraction appeared to be naïve ( CCR7+CD45RA+ ) or effector T cells ( CCR7−CD45RA+ ) . For Rv0288/Rv3019c the percentages ranged between 49 . 5 to 84 . 5% ( 56 . 8 ( 52 . 0–74 . 7 ) ) for central memory T cells , 9 . 8–37 . 1% ( 25 . 9 ( 13 . 3–33 . 8 ) ) for naïve and 4 . 8–17 . 2% ( 10 . 0 ( 7 . 4–16 . 8 ) ) for effector memory T cells . Again , a minor fraction of the tetramer+ cells appeared to be effector T cells ( Figure 5B and C ) . To measure frequency and distribution of MTB-specific T cells , we used the T cell library method [26] . The majority of epitope-specific tetramer+ cells were found to be CD45RA− . We therefore stained CD45RA−CD25− CD4 T cells from donors latently infected with TB ( LTBI ) with antibodies against chemokine receptors preferentially expressed on functionally distinct memory T cell subsets [36] . Five Th cell subsets were sorted: 1 ) CXCR3+CCR6−; 2 ) CXCR3+CCR6+ , both enriched in Th1 cells; 3 ) CCR4+CCR6− ( Th2 ) ; 4 ) CCR4+CCR6+ ( Th17 ) ; and 5 ) CCR6+CCR10+ ( Th22 ) [5] . MTB-specific T cells were almost exclusively found in the CXCR3+CCR6+ subset , while Flu-specific T cells were in the CXCR3+CCR6− and CXCR3+CCR6+ subsets , and Candida albicans-specific T cells were most prominent in the CCR4+CCR6+ subset , enriched in Th17 cells , but positive cultures were also detected in libraries from subsets enriched in Th1 , Th2 and Th22 cells ( Figure 6A and B ) . The narrow distribution of antigen-responding T cells in the CXCR3+CCR6+ subset was peculiar to MTB since Streptococcus pyogenes- or Staphylococcus aureus-specific T cells were found in both CXCR3+CCR6+ and CCR4+CCR6+ subsets ( not shown ) . Based on these results , we sorted three memory CD4 Th cell subsets ( Figure 7A and B ) : 1 ) CCR6+CXCR3− , accounting for 24 . 1% ( 21 . 8–27 . 0 ) ( median ( interquartile range ) , n = 4 ) of the memory CD4+ T cell pool; 2 ) CCR6+CXCR3+ ( 32 . 0% ( 28 . 0–32 . 4 ) ) and 3 ) CCR6− ( 37 . 0% ( 34 . 4–42 . 0 ) ) . For each donor a T cell library of 288 cultures was established . MTB-responding T cells were highly enriched in cultures derived from the CCR6+CXCR3+ T cell subset , and present at much lower frequency in the CCR6+CXCR3− and the CCR6− subsets ( Figure 7C ) . This pattern of distribution was remarkable consistent: in all 4 donors analyzed more than 80% of the MTB-reactive memory CD4 T cell response resided in the CXCR3+CCR6+ subset ( Figure 7D ) . Next , we set up T cell libraries from 4 representative donors and the CXCR3+CCR6+ subset were directly stimulated , after expansion , with 59 representative peptide pools . The results of this analysis are shown in figure 8 . Using this approach we were able to demonstrate that the results obtained with the MTB lysate also extended to responses specific for the various epitopes , and to confirm with a complementary approach the results of the ex vivo IFN-γ ELISPOT analysis utilizing the library of predicted HLA class II binding epitopes .
Individual MTB proteins have been studied to identify novel vaccine candidates , with several studies focused on culture filtrate proteins [6] , [7] . Other studies utilized bioinformatic approaches to select a subset of genes as antigen candidates [37] , [38] . However , the lack of a true genome-wide characterization has hindered a complete understanding of the mechanisms and specificity of the immune response to MTB . This study provides the first in-depth truly genome-wide description of human T cell responses to MTB . We characterized and isolated T cells directly ex vivo , thus avoiding biases introduced as a result of in vitro restimulation and expansion of T cells before analysis . This approach should be generally applicable to the study of immunity to other complex pathogens . The HLA alleles were chosen to allow coverage of the most frequent DP , DQ and DR specificities in the general population [39] . However , we readily acknowledge that this selection has potential limitations and may bias the results toward the epitopes recognized by these alleles . In terms of T cells recognizing MTB we found that the T cell response to MTB antigens in LTBI donors is strongly biased towards a subset of CXCR3+ Th1 cells that co-express CCR6 [4] . Interestingly , this narrow distribution was only seen for MTB and not other pathogens such as S . pyogenes and C . albicans within the same donor . The origin of CCR6+ Th1 cells and their differentiation requirements remains to be defined; they may represent a separate Th1 lineage , or they may differentiate from plastic CCR6− Th1 cells or CCR6+ Th17 cells [40] . Future studies will examine whether this highly focused response is key to MTB containment by examining patients who remain healthy vs . patients who progress to active disease . Striking levels of heterogeneity of responses were detected . This expands previous observations using smaller subsets of antigens [6] , [41] , and a genome-wide screen of antibody responses [28] . The observed heterogeneity might reflect differences in MTB strains , bacillary load , and metabolic state , resulting in qualitative or quantitative differences in antigen expression [42] , [43] . In any case , since natural immunity to MTB is multiepitopic and multiantigenic , and more than 80 antigens are necessary to capture 80% of the T cell response , vaccination strategies including one or a few antigens are unlikely to replicate natural immunity . Likewise , monitoring the immune response to one or a few antigens in the setting of clinical trials might yield a severely incomplete and biased picture of immune reactivity . Several antigens from the DosR regulon , as well as resuscitation- and reactivation-associated antigens have been described as preferentially recognized by individuals with latent infection using long-term T cell cultures [44] , [45] . We observed reactivity to two of these proteins , Rv2031c ( 2 donors ) and Rv2627c ( 1 donor ) , and no significant association with proteins from the DosR regulon or latency-associated antigens , similar to previous observations [46] . Numerous tuberculosis vaccine candidates are currently in clinical trials , these candidates are based on 11 MTB antigens , 7 of which were prevalently recognized in this study; Rv3804c in MVA85A [47] and Aeras-402 [48] , Rv1886c in Aeras-402 , H1 [49] and HyVac4 [50] , Rv0288 in Aeras-402 and HyVac4 , Rv3875 in H1 and H56 [51] , Rv1196 in Mtb72f/AS02A [52] , Rv2608 and Rv3619 in ID93 [53] . Of the remaining 4 antigens Rv3620c in ID93 was also recognized whereas Rv2660c in H56 , Rv0125 in Mtb72f/AS02A and Rv1813c in ID93 were not . We identified three antigenic islands within the MTB genome map as main determinants of immunodominance . Remarkably , the majority of the novel antigens identified are associated ( contained within or in close proximity to ) these islands , which all contain Esx protein pairs and PE/PPE proteins , and are part of a putative secretory system . Our analysis demonstrated that these factors synergistically contribute to determining immunodominance and confirms the importance of PE/PPE and Esx proteins , but suggests that their immunodominance is perhaps mostly determined by their location within these antigenic islands . Two main hypotheses can be put forth to explain the mechanism by which these features determine immunodominance . First , secreted proteins may act as decoys to divert the immune response from recognizing nonsecreted MTB proteins [13] , thus favoring bacterial persistence . The second hypothesis envisions that antigenic islands are dominant because they are intrinsically immunogenic , and because they perform key biological functions necessary to maintain MTB persistence . The decoy hypothesis has two predicated features; either secreted proteins result in diversion of the immune system from the bacteria itself , or the decoy effect is achieved by inducing an immune response to decoy antigens that are functionally distinct from non-decoy antigens . In the first case , we note that both secreted proteins and proteins involved in the secretion apparatus are equally recognized . Indeed , immune reactivity towards proteins involved in the secretion system apparatus has previously been described for T3SS and inflammasome activation by flagellin and the T3SS rod proteins [54] , [55] . Furthermore , we were unable to detect a functionally distinct immune response in terms of multifunctionality , memory phenotype and T cell subsets , and independent of island vs . non-island localization and secretion status of the antigen recognized . Taken together , these observations argue against the decoy hypothesis . T cells that secrete multiple cytokines are a potential correlate of protection , but have also been implicated in pathology [31] , [32] , [33] , [34] . Whatever their role might be , the majority of epitope-specific CD4+ T cell responses were multifunctional , with no differences between antigens from islands vs . non-islands , and between the PE/PPE vs . cell wall and cell processes categories . In terms of T cell phenotypes and T cell subsets a similar picture emerged , with epitope specific CD4+ T cells being predominantly CD45RA−CCR7+ central memory cells , in agreement with previous studies [26] . For some epitope specific CD4+ T cells a large fraction were CD45RA+CCR7+ , a phenotype traditionally regarded as naïve . Such T cells have previously been reported [56] , [57] , and might reflect early differentiation into antigen-specific cells . Additional studies would be required to investigate this further . The available data favors the second hypothesis , that the three antigenic islands are dominant because they perform key biological functions and are necessary to maintain MTB persistence . The most prevalently recognized island is Esx-3 , which is controlled by the iron-dependent regulator IdeR and the zinc uptake regulator Zur [58] , [59] , suggesting its involvement in fundamental biological processes such as metal iron homeostasis . In addition , Esx-3 is essential for in vitro growth , and is conserved in a wide range of mycobacterial species [20] , [60] . Furthermore , the Esx-3 system contributes to immune protection against MTB challenge in mice of the IKEPLUS strain [61] in a HLA class II dependent fashion . Genes from island 2 are , like island 1 ( Esx-3 ) , regulated by Zur [58] , providing a possible functional link between them . While island 2 is not part of an Esx secretion system per se , it is believed to originate from a duplication of the Esx-3 system [19] . Esx-1 and Esx-3 also appear to be linked , since Rv3873 interacts with Rv0288 [62] . Secretion systems similar to the T7SS associated with two of the three antigenic islands are also found in other bacteria , such as Listeria monocytogenes , S . aureus , and Bacillus anthrax [63] . Secretion of the substrates from T7SS are not dependent on interaction with host cells , unlike other bacterial secretion systems such as T3SS and T4SS , which are switched on upon host-cell contact . This suggests that T7SS , while essential for pathogenicity , may fulfill more general physiological roles than strictly host-cell oriented functions . This study was completed in a non-TB-endemic population . Ongoing studies include a larger study population from different ethnicities and geographic locations , as well as patients with different disease states and BCG vaccination status . This will provide answers for different HLA phenotypes , as well as whether patients from an endemic area or with different disease states show a different recognition pattern . In conclusion , this study describes the immunological footprint of MTB CD4 T cell recognition to an unprecedented level of detail . The high throughput cellular screens utilized here to analyze the human immune response to MTB provides information on the specificity , frequency and class of memory T cells , as well as on the individual variability in magnitude and quality of the response . As a result , 34 novel antigens and three broadly immunodominant antigenic islands were defined . The study of the class of proteins recognized , together with the phenotype of responding T cells , disproves the notion that responses against secreted antigens are a decoy utilized to favor bacterial persistence , and rather suggest that these proteins , together with those that are part of their general secretion apparatus , are targeted by fully functional T cell responses . More broadly , this study provides proof of principle of how such high throughput techniques can be applied to other complex pathogen systems . In terms of potential practical applications , the novel T cell antigens identified could be of potential use for diagnostic or vaccine purposes . Indeed , the heterogeneity of responses demonstrated herein suggests that a too narrow focus for vaccine evaluations will not replicate natural immunity . Finally , the antigens and epitopes identified can also be used as tools for identifying biomarkers to provide correlates of risk for , or protection against , tuberculosis disease .
Research conducted for this study was performed in accordance with approvals from the Institutional Review Board at the La Jolla Institute for Allergy and Immunology . All participants provided written informed consent prior to participation in the study . Leukapheresis samples from 28 adults with LTBI and 28 control donors were obtained from the University of California , San Diego Antiviral Research Center clinic ( age range 20–65 years ) . Subjects had a history of a positive tuberculin skin test ( TST ) . LTBI was confirmed by a positive QuantiFERON-TB Gold In-Tube ( Cellestis ) , as well as a physical exam and/or chest X-ray that was not consistent with active tuberculosis . None of the study subjects endorsed vaccination with BCG , or had laboratory evidence of HIV or Hepatitis B . The control donors had a negative TST , as well as a negative QuantiFERON-TB . Approval for all procedures was obtained from the Institutional Review Board ( FWA#00000032 ) and informed consent was obtained from all donors . Proteins from the 21 MTB genome projects available from the NCBI Protein database were downloaded into an in-house MySQL database . Of these , 5 were complete ( CDC1551 , F11 , H37Ra , H37Rv , KZN 1435 ) and 16 were draft assemblies ( Table S1 ) . The protein sequences were parsed into all possible 15mer peptides ( n = 1 , 568 , 148 ) , for each of which binding to 22 different HLA DR , DP and DQ class II alleles most commonly expressed in the general population ( Table S2 ) was predicted using the IEDB HLA class II ‘consensus’ prediction method [64] . The sequences of the H37Rv strain were used as a reference sequence . For each H37Rv protein , alignments were made of all orthologs identified in other genomes , as determined by a BLAST search . Because of the overall high sequence conservation among the proteins from all the 21 genomes , 1 , 220 , 829 ( 91 . 4% ) of 15mers were completely conserved among all of the strains . For each protein , the best-predicted binders , as ranked by consensus percentile , were selected for synthesis . In order to ensure coverage of each of the proteins , the number of peptides selected per protein was no less than 2 and no more than 10 , depending upon protein length ( 18 , 950 peptides ) . Any variants among the orthologs at the selected positions were also selected ( 1 , 660 ) , for a total of 20 , 610 peptides . Sets of 15-mer peptides synthesized by Mimotopes ( Victoria , Australia ) and/or A and A ( San Diego ) as crude material on a small ( 1 mg ) scale were combined into pools of 20 peptides . Peptides utilized for tetramers were synthesized as purified material ( >95% by reversed phase HPLC ) . The IEDB submission number for the peptides is 1000505 . PBMCs were obtained by density gradient centrifugation ( Ficoll-Hypaque , Amersham Biosciences ) from 100 ml of leukapheresis sample , according to manufacturer's instructions . Cell were suspended in fetal bovine serum ( Gemini Bio-products ) containing 10% dimethyl sulfoxide , and cryo-preserved in liquid nitrogen . CD4 T cells were isolated from PBMCs by positive selection with microbeads ( Miltenyi Biotec ) . Memory CD4+ T cell subsets were sorted with a FACSAria ( BD Biosciences ) to over 98% purity excluding CD45RA+ , CD25+ , CD8+ , CD19+ , and CD56+ cells . Antibodies used for positive selection were: anti-CCR6-PE or biotinylated ( 11A9; BD Biosciences ) followed by streptavidin-allophycocyanin ( APC ) ( Invitrogen ) or streptavidin-APC-cyanine7 ( APC-Cy7 ) ( BD Biosciences ) ; anti-CCR10-PE ( 314305 , R&D Systems ) , anti-CCR4-PE-Cy7 ( 1G1; BD Pharmingen ) and anti-CXCR3-APC ( 1C6; BD Pharmigen ) . Cells were cultured in RPMI 1640 medium supplemented with 2 mM glutamine , 1% ( vol/vol ) nonessential amino acids , 1% ( vol/vol ) sodium pyruvate , penicillin ( 50 U/ml ) , streptomycin ( 50 µg/ml ) ( all from Invitrogen ) and 5% heat-inactivated human serum ( Swiss Red Cross ) . T cells ( 1 , 000 cells/well ) were stimulated polyclonally with 1 µg/ml PHA ( Remel ) in the presence of irradiated ( 45 Gy ) allogeneic feeder cells ( 1 . 0×105 per well ) and IL-2 ( 500 IU/ml ) in a 96-well plate format and T cell lines were expanded as previously described [26] . Library screening was performed at day 14–21 by culturing extensively washed T cells ( ∼2 . 5×105/well ) with autologous monocytes ( 2 . 5×104 ) , either unpulsed or pulsed for 3 h with MTB whole cell lysate ( 5 µg/ml , BEI Resources ) or control antigens . In some experiments , T cells were cultured with peptide pools ( 2 µg/ml ) . Proliferation was measured on day 2–3 after 16 h incubation with 1 µCi/ml [methyl-3H]-thymidine ( Perkin Elmer ) . Precursor frequencies were calculated based on numbers of negative wells according to the Poisson distribution and expressed per million cells . PBMCs incubated at a density of 2×105 cells/well were stimulated with peptide pools ( 5 µg/ml ) or individual peptides ( 10 µg/ml ) , PHA ( 10 µg/ml ) or medium containing 0 . 25% DMSO ( corresponding to percent DMSO in the pools/peptides , as a control ) in 96-well plates ( Immobilon-P; Millipore ) coated with 10 µg/ml anti-IFN-γ ( AN18; Mabtech ) . Each peptide or pool was tested in triplicate . After 20 h incubation at 37°C , wells were washed with PBS/0 . 05% Tween 20 and incubated with 2 µg/ml biotinylated anti-IFN-γ ( R4-6A2; Mabtech ) for 2 h . The spots were developed using Vectastain ABC peroxidase ( Vector Laboratories ) and 3-amino-9-ethylcarbazole ( Sigma-Aldrich ) and counted by computer-assisted image analysis ( KS-ELISPOT reader , Zeiss ) . Responses were considered positive if the net spot-forming cells ( SFC ) per 106 were ≥20 , the stimulation index ≥2 , and p<0 . 05 ( Student's t-test , mean of triplicate values of the response against relevant pools or peptides vs . the DMSO control ) . For experiments utilizing depletion of CD4+ or CD8+ T cells , these cells were isolated by positive selection ( Miltenyi Biotec ) and effluent cells ( depleted cells ) were used for experiments . The response frequency was calculated by dividing the no . of donors responding with the no . of donors tested . The magnitude of response ( total SFC ) was calculated by summation of SFC from responding donors . PBMCs were cultured in the presence of 5 µg/ml MTB peptide and 4 µl/ml Golgiplug ( BD Biosciences ) in complete RPMI medium at 37°C in 5% CO2 . Unstimulated PBMCs were used to assess nonspecific/background cytokine production . After 6 h , cells were harvested and stained for cell surface antigens CD4 ( anti-CD4-PerCPCy5 . 5 , OKT-4 ) and CD3 ( anti-CD3-EFluor450 , UCHT1 ) . After washing , cells were fixed and permeabilized , using a Cytofix/Cytoperm kit ( BD Biosciences ) and then stained for IFN-γ ( anti-IFN-γ-APC , 4S . B3 ) , TNFα ( anti-TNFα-FITC , MAb11 ) and IL-2 ( anti-IL-2-PE , MQ1-17H12 ) . All antibodies were from eBioscience . Samples were acquired on a BD LSR II flow cytometer . The frequency of CD4+ T cells responding to each MTB peptide was quantified by determining the total number of gated CD4+ and cytokine+ cells and background values subtracted ( as determined from the medium alone control ) using FlowJo software ( Tree Star ) . A cut-off of 2 times the background was used . Combinations of cytokine producing cells were determined using Boolean gating in FlowJo software . HLA class II tetramers conjugated using PE labeled streptavidin were provided by the Tetramer Core Laboratory at Benaroya Research Institute . CD4 T cells were purified using the Miltenyi T cell isolation kit II according to manufacturer's instructions . Purified cells ( ∼10×106 ) were incubated in 0 . 5 ml PBS containing 0 . 5% BSA and 2 mM EDTA pH 8 . 0 ( MACS buffer ) with a 1∶50 dilution of class II tetramer for 2 h at room temperature . Cells were then stained for cell surface antigens using anti-CD4-FITC ( OKT-4 ) , anti-CD3-Alexa Fluor 700 ( OKT3 ) , anti-CCR7-PerCPEFluor710 ( 3D12 ) , anti-CD45RA-EFluor450 ( HI100 ) ( all from EBioscience ) and Live/Dead Yellow ( Life Technologies ) to exclude dead cells . Tetramer-specific T cell populations were enriched by incubating cells with 50 µl of anti-PE microbeads ( Miltenyi Biotech ) for 20 min at 4°C . After washing , cells were resuspended in 5 ml MACS buffer and passed through a magnetized LS column ( Miltenyi Biotec ) . The column was washed three times with 3 ml of MACS buffer , and after removal from the magnetic field , cells were collected with 5 ml of MACS buffer . Samples were acquired on an BD LSR II flow cytometer and analyzed using FlowJo software . The identified epitopes were compared for sequence homology and the weakest epitopes sharing >90% homology were eliminated . The epitopes were mapped to the H37Rv genome allowing 1 substitution per peptide , to identify antigens . IEDB queries utilized criteria matching the experimental study ( organism; MTB , host organism; human , latent disease , ex vivo , HLA class II ) . Epitopes were then mapped as above . To capture the most frequently recognized antigens the response frequency score ( no . donors responded – Square root of no . donors responded/no . donors tested ) , was utilized [65] .
|
Mycobacterium tuberculosis is one of the most life-threatening pathogens of all time , having infected one-third of the present human population . There is an urgent need for both novel vaccines and diagnostic strategies . Here , we were able to identify the targets most dominantly recognized by latently infected individual that successfully contain infection . These targets are contained in three broadly genomic antigenic islands , all related to bacterial secretion systems and composed by several distinct ORFs . Thus , our results suggest that vaccination with one or few defined antigens will fail to replicate the response associated with natural immunity . Our analysis also pinpoints that the Th1 cells dominating the response are associated with novel and well-defined phenotypic markers , suggesting that the response is molded by unique MTB associated factors . This study demonstrates further that the approach combining peptide binding predictions with modern high throughput techniques is generally applicable to the study of immunity to other complex pathogens . Together , our data provide a new angle in the worldwide fight against M . tuberculosis and could be used for diagnostic or vaccine developments .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"immune",
"cells",
"immunity",
"to",
"infections",
"immunology",
"bacterial",
"diseases",
"adaptive",
"immunity",
"immune",
"defense",
"infectious",
"diseases",
"tuberculosis",
"t",
"cells",
"biology",
"immune",
"response",
"antigen",
"processing",
"and",
"recognition",
"immunity"
] |
2013
|
Memory T Cells in Latent Mycobacterium tuberculosis Infection Are Directed against Three Antigenic Islands and Largely Contained in a CXCR3+CCR6+ Th1 Subset
|
Many species are able to share information about their environment by communicating through auditory , visual , and olfactory cues . In Drosophila melanogaster , exposure to parasitoid wasps leads to a decline in egg laying , and exposed females communicate this threat to naïve flies , which also depress egg laying . We find that species across the genus Drosophila respond to wasps by egg laying reduction , activate cleaved caspase in oocytes , and communicate the presence of wasps to naïve individuals . Communication within a species and between closely related species is efficient , while more distantly related species exhibit partial communication . Remarkably , partial communication between some species is enhanced after a cohabitation period that requires exchange of visual and olfactory signals . This interspecies “dialect learning” requires neuronal cAMP signaling in the mushroom body , suggesting neuronal plasticity facilitates dialect learning and memory . These observations establish Drosophila as genetic models for interspecies social communication and evolution of dialects .
The ability to interpret environmental information is a phenomenon found throughout all life forms . From bacteria to plants and to mammals , communication occurs within as well as between species . In some cases , information that is being shared can be highly specific , such as in the case of honeybees communicating instructions on where to find nectar[1–3] . In other cases , opportunistic bystanders can also benefit from general information . For example , predator alarm calls generated as a warning are observed , where multiple species participate in repeating the alarm throughout the community[4–8] . In all cases , the information that is shared can be dependent on local environmental cues and experiences and the manner in which information is communicated is strongly influenced by past experiences of each individual . For example , birds , which live in geographically distinct populations , manifest unique song variants or regional dialects that can last for decades , but these animals are nevertheless still able to communicate with others of their species[9–11] . Because dialects are learned and therefore influenced[12] by specific local environmental differences , it suggests that both social and non-social experiences can have dramatic effects on cognitive development[13] . It is proposed that a myriad of environmental cues , both social and non-social , are critical to animal development in determining the ability to convey and receive specific types of information . However , there are many outstanding questions as a result of this proposition: What cues are important ? When are these cues important ? How can environmental cues interact with genetically determined developmental programs ? Although social communication is most extensively documented in more derived species such as mammals and birds , insects can also display a broad range of behavioral tasks . Bees are known to be able to learn from non-natural sources in order to obtain a reward through social learning . Such information can be passed on to naïve , student bees through the use of visual cues[14 , 15] . Insect social learning extends to the genetic model system of Drosophila , where student , observer flies learn from a trained , teacher-fly , using visual cues . This has been shown in communication involving food sources and predator threats[16 , 17] . Chemical cues can serve as intra- and interspecies signals , such as fox and guinea pig urine affecting not only conspecific behavior , but also the behavior of other animals[18–20] . Sound can also be used , such as in bats and bottlenose dolphins , which are able to distinguish members of the community through the use of echolocation pitch recognition[21 , 22] . Plants have a vast arsenal of responses to pathogens[23] , including communicating a threat to neighboring plants through the use of volatile organic compounds[24] . Plant interspecies[25–31] and intraspecies[32–34] communication occurs both in laboratory settings and in the wild[30 , 35] . Drosophila melanogaster and other Drosophila species have provided insights into mechanisms of learning , memory , and complex behaviors[36 , 37] . However , these behaviors and phenotypes have been studied almost exclusively in domesticated D . melanogaster lab monocultures , while D . melanogaster wild populations are surrounded by a broad range of predators , microbes , and other Drosophilids , highlighting a communal component of the organism’s life cycle[38] . This raises the possibility of behavioral phenomenon that have yet to be discovered and analyzed in domesticated lab monocultures[39–41] . Given the vast range of environmental inputs on a wild Drosophilid , a fly must be able to discern important information from extraneous inputs , while interacting with conspecifics and a variety of other species [42–46] . Although modes of intra- and interspecies communication are likely to be genetically limited , there is also value in learning to interpret signals from variable , local environments that may provide immediate survival benefits . How do genetically constrained neurological features and variable environmental factors interact to produce context-dependent , meaningful information ? Under which environmental factors would information sharing between different species occur and be beneficial ? In this study , we sought to begin to address these questions in the Drosophila model system by using a pan-Drosophila predator known to elicit social communication [17 , 47] . D . melanogaster presented with parasitoid wasps have multiple behavioral responses , including a reduction in oviposition ( egg laying ) through an increase in ovarian apoptosis [17 , 48–51] . After removal of the wasp , a wasp-exposed “teacher” fly can instruct a naïve “student” fly about the presence of the wasp threat through the exclusive use of visual cues , such that students now reduce their own oviposition by triggering ovarian apoptosis . Using this fly-fly social communication paradigm we asked ( 1 ) whether social communication is conserved among other Drosophila species , ( 2 ) if Drosophilids engage in interspecies communication , and ( 3 ) what environmental and genetic factors are required for interspecies communication .
We utilized the fly duplex , an apparatus with two transparent acrylic compartments to test whether different species respond to seeing predators ( acute response ) and if exposed “teacher” female flies can communicate this threat to naïve unexposed “student” female flies[17] . The duplex allows flies to see other flies or wasps in the adjacent compartment , without direct contact , making all communication only visual ( Fig 1A ) . Ten female and two male flies are placed into one duplex compartment , with an adjacent compartment containing twenty female wasps . Following a 24-hour exposure , wasps are removed and acute response is measured by counting the number of eggs laid in the first 24-hour period in a blinded manner . Flies are shifted to a new duplex , with ten female and two male naïve student flies in the adjacent compartment ( Fig 1A , see Methods ) . Following a second 24-hour period , all flies are removed and the response of both teacher and student is measured by counting the number of eggs laid in a blinded manner . The 24-48-hour period measures memory of teachers having seen the wasps and students having learned from the teachers . Using wild-type D . melanogaster , we find both an acute response and a memory response to the wasp in teacher flies and a learned response in naïve student flies ( Fig 1B , S1A Fig , S1 File for all raw egg counts and p-values in this study ) [17 , 50 , 51] . We then asked whether the acute , memory , and student social learning behaviors are conserved in other Drosophila species , with varying relatedness to D . melanogaster ranging from sister species , such as D . simulans , to very distantly related species , such as D . virilis . For each species , we tested a sister species as an additional way to validate our observations . Across a broad span of the genus Drosophila , we find the conservation of both the acute and memory responses in teacher flies in addition to the ability of teachers to communicate to conspecific student flies . ( Fig 1C , S1B–S1H Fig ) . Some of these species have been previously shown to depress oviposition during wasp exposure [51] . Our experimental design allows for only visual cues to be detected from the wasps and from teachers to student flies . Thus , in all species tested , visual cues are sufficient for flies to detect wasps and for naïve flies to learn from wasp-exposed teacher flies . Conservation of these behaviors is especially impressive as the species tested are separated by millions of years of evolution , yet the basic behaviors observed in D . melanogaster are maintained . Moreover , this conservation further underscores the importance this innate behavior must have since even laboratory cultures that have not experienced wasp for many generations nevertheless exhibit a robust response . In particular , the conservation of the fly-fly communication behavior speaks to a presence of a conserved form of fly signaling and signal interpretation , which we suggest might be thought of as a “fly language” in this paradigm . Oviposition reduction is modulated in part by the effector caspase Dcp-1[17] . In D . melanogaster , we observe overlapping staining of activated Dcp-1 with a punctate pattern of DNA staining with 4’ , 6-diamidino-2-phenylindole ( DAPI ) , indicative of oocyte specific apoptotic activity ( Fig 1D–1K , S2 Fig ) . We performed immunofluorescence with antibodies specific to activated Dcp-1 across a broad range of Drosophila species , revealing cleaved caspase following wasp exposure in all 15 Drosophila species tested ( S3–S16 Figs ) . We observed an increase in positive cleaved caspase oocytes following wasp exposure ( S17 Fig ) , along with a decrease in total number of egg chambers ( S18 Fig ) , suggestive of ovarian apoptosis and elimination of oocytes[17] . Phylogenetic trees shown are adapted from previous work [52] . Following the observation that an acute response to wasps and intraspecies communication is conserved across the genus , we asked whether the wasp threat could be communicated between two different species . We utilized 15 Drosophila species that respond to wasps to answer this question ( S3–S18 Figs ) . The species were selected to span the phylogeny with different degrees of relatedness to D . melanogaster [52] . We find that D . melanogaster are able to communicate the threat to and receive communications from closely related species , such as D . simulans and D . yakuba , with oviposition of students paired with wasp-exposed teachers being ~10–30% compared to unexposed ( Fig 2A and 2B , S19A–S19F Fig ) . Interestingly , species more distantly related to D . melanogaster , such as D . ananassae and its sister species , elicit a partial communication phenotype , with oviposition depression of students paired with wasp-exposed teachers being ~50–65% of unexposed flies ( Fig 2C–2F , S19G–S19J Fig ) . A second strain isolate of D . ananassae also show partial communication with D . melanogaster ( Fig 2C–2F , S19G–S19J Fig ) . Species more distantly related to D . melanogaster , such as D . willistoni , D . equinoxialis , and D . virilis , cannot communicate with D . melanogaster ( Fig 2G–2L , S19K–S19P Fig ) . We statistically characterized these category assignments based on the criteria of mean value and statistical significance compared to unexposed in order to define efficient , partially , and lack of communication ( S2 File , Methods ) . Collectively , the data suggest that evolutionary distance contributes to the efficiency of interspecies communication . D . ananassae show varying communication phenotypes with other Drosophila species , though the pattern of communication is different . For example , D . ananassae exhibit partial communication with D . simulans ( S20A and S20B Fig ) , strong communication with its sister D . kikkawai ( S20C and S20D Fig ) , and partial communication with D . equinoxialis and D . willistoni ( S20E–S20H Fig ) . D . ananassae , in addition to D . melanogaster , are unable to communicate with the distantly related D . mojavensis and D . virilis ( Fig 2I and 2J , S20I–S20L Fig ) . Species such as D . virilis , which were unable to communicate with D . melanogaster and D . ananassae , can communicate with other species , such as its sister species D . mojavensis ( Fig 2K and 2L ) . Thus , although all species tested are capable of intraspecies communication , there is a fundamental , species-specific difference in communication mode or “fly language” when communicating wasp predator threat . We wished to assay whether the observed communication behavior is hardwired in the fly brain , or if it had a level of plasticity as a result of socialization . Known learning and memory mutants have shown defects in socialization assays [53 , 54] . Additionally , the cuticular hydrocarbon composition on flies changes as a function of social , but not sexual , experience [55] , though sexual experience is also affected by isolation [56] . Thus , we sought to assay whether socialization , which has been shown to have behavioral affects in other assays [57] including egg laying behavior [44 , 58] , has an effect on intraspecies communication . To ask this question , we collected L1 larvae and isolated each larva in a Falcon round-bottom polypropylene tube containing 1 mL standard Drosophila media . Larvae were allowed to pupate and eclose in isolation . Each tube was kept separate such that no visual information could be transferred between individuals in tubes . Following eclosion , 1 female aged 3–5 days old was used as the student , paired with one socialized female teacher ( Fig 3A ) . This 1:1 ratio was first tested with D . melanogaster where both teachers and students were previously socialized , observing typical strong communication ( Fig 3B ) . Interestingly , the flies raised in isolation presented with a partial communication phenotype , similar to when normally socialized D . melanogaster and D . ananassae are paired ( Fig 3C ) . Larval isolation has been previously shown to have effects on cooperative larval behavior , and thus , we cannot rule out the possibility that isolation of larvae translates to behavioral defects in adult flies [59] . However , given the observation of this partial communication phenotype , we suggest that while the ability to communicate is hardwired in the fly brain , there exists a degree of plasticity that is dependent on previous socialization . Given that our isolation experiments demonstrate a level of plasticity dependent on socialization , we wished to explore the possibility that partial communication between species might be alleviated as a result of socialization between two different species . Since closely related species can communicate the threat of a wasp , we postulated that environmental factors contributing to interspecies communication for distantly related species may be partially dependent on socialization . To test this idea , D . melanogaster were cohabitated with species capable of only partial communication ( e . g . D . ananassae ) ( Fig 2C and 2D ) . Cohabitation lasted for one week in a single container , allowing for frequent and multiple channels of sensory interactions . Following a weeklong cohabitation period , the two species were separated and used as students paired with teachers of the other species ( Fig 4A ) . In all experiments teachers had existed only as a monoculture , kept separate from other species monocultures , while all flies experiencing an interspecies cohabitation period were subsequently used only as students . If cohabitation of different species results in exchange of information that later facilitates communication between these two species , then we predict that species capable of only partial communication may then be capable of full or enhanced communication . We find that cohabitation can greatly enhance communication between some species , suggesting that some form of training occurs during this period . After cohabitation , D . ananassae students learn very efficiently from D . melanogaster teachers , demonstrating that cohabitation of two species yields an expanded communication repertoire ( Fig 4 , S21 Fig ) . This observation indicates that poorly communicating species are not limited by structural barriers such as wing shape or olfactory capacity . Instead this suggests that , similar to local dialects in bird songs , Drosophila species-specific cues can be learned simply by repeated exposure to the “dialect” , and provides further evidence for the role of socialization in Drosophila communication ( Fig 3 ) . Thus , there exists a variation of signal among populations of different species of Drosophila , even though there exists a conserved fly “language” to communicate the threat of a wasp . Thus , we suggest this to be analogous to “dialects” as it reflects natural variations between a common mode of communication , which can be alleviated through socialization between species . Hereafter we refer to this cohabitation as a “dialect learning” period . We observed dialect learning in two different D . ananassae strain isolates , and two additional sister species ( Fig 4B–4E , S21A–S21G Fig ) , indicating that dialect learning is likely to be a wide-spread phenomenon in Drosophila . Interestingly , some distantly related species that were unable to communicate with D . melanogaster ( i . e . D . willistoni , D . equinoxialis ) acquired the ability to partially communicate following a cohabitation-training period ( Fig 4F–4I , S21H and S21I Fig ) . This was not the case for very distantly related species ( i . e . D . virilis , D . mojavensis ) , which showed no ability to communicate with D . melanogaster even after a week-long cohabitation ( Fig 4J and 4K , S21J–S21M Fig ) . We also tested a transgenic D . melanogaster , to see if it was capable of teaching and dialect learning , and find such flies can teach their dialect to and learn the dialect from D . ananassae ( S21N and S21O Fig ) . Additionally , we tested whether D . ananassae communication could benefit from cohabitation-training with species other than D . melanogaster . We find efficient communication between D . simulans ( S22A and S22B Fig ) , D . equinoxialis ( S22C and S22D Fig ) , and D . mojavensis ( S22E and S22F Fig ) with D . ananassae following a cohabitation-training period . In contrast to the D . melanogaster results , we find communication with more distantly related species is altered after dialect training . With D . virilis and D . mojavensis , in the untrained states , we observe no ability to communicate ( S20I–S20L Fig ) , but find a partial communication phenotype following cohabitation ( S22G–S22J Fig ) . D . virilis and D . mojavensis , although capable of interspecies communication and dialect learning , cannot learn the D . melanogaster dialect , but can learn D . ananassae dialect . These results suggest that some interspecies communication barriers do exist while others can be overcome by a period of dialect training during cohabitation . Given our observation that two species can learn dialects following a cohabitation-training period , we wondered whether having more species present during the dialect training period influences dialect learning . In nature , flies encounter many different species of Drosophila , and given this knowledge , we hypothesized that neuronal plasticity exists in the fly brain to allow flies to learn multiple dialects from a given training period that includes multiple species as inputs . To probe this question , D . melanogaster were cohabitated with species capable of only partial communication or no communication in the untrained state , but show efficient and partial communication after dialect training ( i . e . D . ananassae and D . willistoni , respectively ) . These three species were cohabitated for one week in a single container . We then used the trained D . melanogaster as students with untrained D . ananassae and D . willistoni teachers ( Fig 5A ) . We find that trained D . melanogaster are able to efficiently communicate with D . ananassae and partially communicate with D . willistoni ( Fig 5B and 5C ) . These results mirror assays where these species were individually trained ( Fig 4B , 4C , 4F and 4G ) , suggesting that flies can simultaneously make use of multiple inputs from multiple species and be able to learn and remember each unique dialect they encounter . Additionally , we tested D . ananassae and D . willistoni as students that were cohabitated with D . melanogaster . We find that D . ananassae can communicate efficiently with D . melanogaster and D . willistoni ( Fig 5D and 5E ) , and that D . willistoni can partially communicate with D . melanogaster and effectively communicate with D . ananassae ( Fig 5F and 5G ) . These data also mirror individual training ( Fig 4B , 4C , 4F and 4G , S22E and S22F Fig ) . Collectively , these data demonstrate that a fly can have vast communication repertoires consisting of multiple dialects that it acquires . Given the result above with multiple species being able to learn multiple dialects , we wondered the level of specificity and the level of generalization of dialect learning as a means to provide insight into the identity of the “signal” being transferred between species . To test this , we performed cohabitation of D . melanogaster and D . kikkawai , a sister species to D . ananassae . We then assayed the communication ability of D . melanogaster with either D . ananassae or D . willistoni ( S23A Fig ) . We find that D . kikkawai trained D . melanogaster are able to effectively communicate with D . ananassae , suggesting that there is a generalizability to dialect learning ( S23B Fig ) . We tested the ability of these flies to communicate with D . willistoni , as D . ananassae has an ability to communicate with D . willistoni in the naïve state , while D . melanogaster does not , allowing further analysis into the generalizability of the signal . We find that D . kikkawai trained D . melanogaster are unable to communicate with D . willistoni , suggesting that while dialect learning is generalizable in some instances , it also has a layer of specificity ( S23C Fig ) . In order to better understand dialect learning , we tested the roles of sensory cues and genetic factors during the dialect learning period . We measured dialect learning by quantifying improvement in interspecies partial communication between D . melanogaster and D . ananassae that normally exhibit efficient communication only after cohabitation . Given that in D . melanogaster , and in other species tested , we found visual cues to be sufficient for the teacher-student dynamic ( Fig 1 ) [17] , we asked if visual cues are sufficient and/or necessary for dialect learning . We approached this question by performing the dialect training in the fly duplex , such that the two species could only see each other ( Fig 6A ) , or by performing the training in the dark , so that the two species could physically interact , but lacked visual cues ( S24A Fig ) . We find that visual cues alone are not sufficient ( Fig 6B and 6C ) , but are necessary ( S24B and S24C Fig ) for dialect learning . The observation that visual cues are necessary but not sufficient makes the dialect learning process different from the teacher-student dynamic that requires only visual cues[17] . Furthermore , we wondered if seeing another species altered the behavior of a fly to facilitate dialect learning . This hypothesis addresses the possibility that flies are passively acquiring information through eavesdropping and that the communication ability gained could be unidirectional . Blind D . melanogaster ninaB mutants do not function as students . Surprisingly , D . ananassae cohabitated with blind D . melanogaster do not learn the D . melanogaster dialect ( S24D and S24E Fig ) . This result is striking because it suggests that there is an active learning component and a bidirectional exchange of information between fly species and not simply eavesdropping or mimicry . We also performed cohabitation training under two different , monochromatic light sources , and this resulted in only a partial communication between D . melanogaster and D . ananassae , ( Fig 6D and 6E , S24F and S24G Fig ) . To exclude the possibility of a dimmer light source inhibiting dialect training under monochromatic settings , we repeated cohabitation-dialect-training in a full spectrum , lower light intensity setting , and found both species were able to learn the dialect ( S24H and S24I Fig ) . Thus , full spectrum light is essential in dialect learning . Importantly , the observation that blind D . melanogaster do not allow wild-type D . ananassae to dialect learn suggests that visual inputs are critical to altering behavioral/chemical outputs required to facilitate dialect learning . This also suggests that during the dialect learning period , transfer of information may occur bidirectionally , if the visual input that is required is indeed provided by the other species . Wing movement was shown to be required for teacher flies to instruct students in the teacher-student dynamic[17] , raising the possibility that wing movement was also important for dialect learning . Therefore , we tested flies mutant in the erect wing gene ( ewg ) , which impairs wing movement while maintaining morphologically normal wings . The allele tested has wild-type EWG protein expression in the nervous system , thus is only deficient in its non-neuronal functions , such as flight muscles [60] . We find that D . ananassae cannot dialect learn from ewgNS4 flies ( Fig 6F ) , although ewgNS4 mutants have no dialect learning impairment ( Fig 6G ) . This suggests that dialect learning by D . ananassae requires D . melanogaster to have mobile wings . To test if olfactory cues play a role in dialect learning , we utilized D . melanogaster mutants defective in chemosensory signaling . The majority of olfactory receptors require a co-receptor for wild-type function , including Orco ( Or83b ) for odorant receptors [61] and Ir8a or Ir25a for ionotropic receptors [62] . Ir8a olfactory sensory neurons ( OSNs ) primarily detect acids and Ir25a OSNs detect amines , allowing us to probe specificity of detection . We find that D . ananassae are able to learn dialect from Orco1 , Ir8a1 , Ir25a2 , single and Ir8a1;Ir25a2;Orco1 triple mutants and RNAi expressing D . melanogaster targeting each of these gene products ( Fig 6H and 6J , S25A–S25L Fig ) . By contrast only Ir25a2 mutant and RNAi knockdown D . melanogaster were able to learn the D . ananassae dialect ( Fig 6I and 6K , S25A–S25L Fig ) . These data demonstrate that Orco- and Ir8a-mediated olfactory inputs are required for dialect learning . This further suggests that multiple olfactory cues play important roles in the dialect learning period . We also find that D . melanogaster males and females are both required for dialect training D . ananassae ( Fig 6L–6M , S25M and S25N Fig ) and that the length of the training period is also critical , as 24 hours is insufficient a period for dialect learning ( S25O and S25P Fig ) . Thus , although the exact olfactory molecule ( s ) critical during a dialect learning period are yet to be identified , we speculate that dialect learning is a complex process requiring visual , olfactory and sex specific cues . To examine the possibility that dialect training involves active learning mediated by neurons of the mushroom body , we utilized the GAL4 Gene-Switch system to transiently express a transgene specifically in the mushroom body ( MB ) . Using the GAL4 Gene-Switch ligand system , RU486 [63] activates the GAL4 transcription factor , while administration of the vehicle ( methanol ) does not [63] . RU486 was administered during the cohabitation period ( or methanol for control ) , but not when flies were used as students , post-dialect training ( Fig 7A ) . Feeding of RU486 to the MB switch driver line does not impair dialect learning ( S26A Fig ) . We expressed the Tetanus toxin light chain ( UAS-TeTx ) specifically in the MB of D . melanogaster ( to inhibit synaptic transmission during dialect training ) . We find that D . ananassae are able to learn the dialect of these MB inhibited flies ( Fig 7B ) . However , D . melanogaster in which MB synaptic transmission is inhibited during the training period are unable to learn the D . ananassae dialect ( Fig 7C ) . Control methanol-only conditions ( i . e . no RU486 ligand ) with flies of identical genotypes do not show this defect ( S26B Fig ) . These data collectively indicate that visual and olfactory cues are required and possibly relayed to the MB , either directly or indirectly through a currently unknown circuit , to facilitate dialect learning . By contrast MB function does not appear to be important for D . melanogaster behavior ( s ) that enable D . ananassae to learn a dialect ( S6B Fig ) . Consistent with this idea , although Orb2ΔQ mutants cannot function as students ( Fig 7E ) [17] , D . ananassae nevertheless learns the D . melanogaster dialect from Orb2ΔQ mutants ( Fig 7D ) . Because MB function is necessary for dialect learning during dialect training , we tested the long-term memory proteins Orb2 , FMR1 , and phosphatase and tensin homolog ( PTEN ) [64 , 65] that are known to be required in the MB for memory formation . PTEN has been implicated in murine social learning models , though it has not been tested in a social learning assay in Drosophila [66] . We used the MB Gene-Switch to knockdown expression only during the cohabitation period , after which expression was allowed to resume . D . ananassae learn the dialect of each of these three knockdown lines , again suggesting that MB mediated processes in D . melanogaster are not necessary for D . ananassae dialect training ( S26C–S26G Fig ) . However , under these conditions we find that functional Orb2 and PTEN are required for dialect learning in D . melanogaster , but FMR1 is dispensable ( Fig 7F–7H ) . Orb2 and FMR1 were previously shown to be important in the teacher-student transmission of a wasp threat , and knockdown of either gene completely ablated students learning from teacher flies [17] . In this case , partial communication between D . ananassae teachers and D . melanogaster students can occur because Orb2 and PTEN expression is restored after the dialect training period , thus functioning as wild-type D . melanogaster . D . melanogaster flies having undergone knockdown of Orb2 and PTEN only during dialect training are able to function as students to wild-type D . melanogaster after the cohabitation period is completed , suggesting the partial communication phenotype observed with D . ananassae teachers is a result of gene knockdown during cohabitation and not a by-product of irreversible cellular damage or death caused by the RNAi treatments ( S26H–S26L Fig ) . Collectively , these data show critical gene products are required to function in the MB for dialect learning during the training period . Importantly , although visual inputs are necessary MB function and active learning are not necessary in D . melanogaster in order to in turn provide cues enabling dialect learning by a wild-type D . ananassae student .
In this study , we present an evolutionarily conserved response to predatory wasps across the genus Drosophila , manifesting as egg laying depression coincident with an activated effector caspase , Dcp-1 . These endoparasitoid wasps are ubiquitous keystone species in many ecosystems around the world , which prey on Drosophila larvae , with infections rates as high as 90% in natural populations [67–69] . We have shown that flies communicate a wasp threat through visual cues . We used a known generalist wasp species , Leptopilina heterotoma [70 , 71] , suggesting that the communication observed may constitute a form of “social protection” against a pan-threat . Given the geographical distribution of this generalist wasp , species tested in this study have a high likelihood of wasp encounter [72–75] . The effects of other larval and pupal generalists , in addition to specialist wasps , are currently unknown , but may provide a fruitful avenue of study . The high infection rate and prevalence of parasitoids in nature suggest to us that other wasp strains and species may also induce intra- and interspecies communication . Interspecies communication occurs to varying degrees , likely dependent on evolutionary relatedness . Closely related species , such as D . melanogaster and D . simulans , D . ananassae and D . kikkawai , and D . mojavensis and D . virilis , communicate as effectively as conspecifics . Species more distantly related to D . melanogaster exhibit only partial communication or lack the ability to confer predator information with D . melanogaster . Because of this natural variation in ability to communicate we suggest a useful analogy to language “dialects” that may hinder efficient communication between two dissimilar dialects of a common language . When two species are only able to partially communicate , they can learn each other’s dialect after a period of cohabitation , yielding interspecies communication enhanced to levels normally observed among conspecifics . Such signals benefiting two individuals has been modeled to be honest , and evolutionarily stable [76] . Although dialect learning facilitates interspecies communication across broad evolutionary distances , the ability to learn a specific dialect is dependent on relatedness of the two species ( Fig 8A ) . This observation of the role of phylogenetic distance influencing dialect learning is true in cases both utilizing D . melanogaster and D . ananassae in combination with other species tested ( Fig 8A , S27 Fig ) . The observation that different strains of the same species exhibit this partial communication that can then be enhanced by cohabitation , suggests that both social communication and dialect learning are innate behaviors conserved among all Drosophilids tested here ( Fig 8A , S27 Fig ) . Multiple strains of D . melanogaster reared in the laboratory for many decades exhibit this behavior , supporting the idea that this is an innate behavior . However , flies reared in isolation from the larval stage result in compromised communication ability , suggesting that while the ability to communicate is hardwired , or innate , there is a socialization dependent input the facilitates efficient communication , even between conspecifics . Thus , adult Drosophila neuronal plasticity allows for learning of both the communication between conspecifics and of dialects , but the specific dialect learned is dependent on social interactions specific to a communal environmental context that provides both visual and olfactory inputs . This same plasticity allows for the learning of multiple dialects in a given environment . It is remarkable that communal rearing of two species can enhance communication about a predator that is yet to be experienced by either species . Furthermore , dialect learning does not trigger Dcp-1 activation and oviposition depression , suggesting that social communication about predator presence is different from social interactions that enable dialect learning that later enhances predator presence communication . Understanding memory formation , storage and retrieval requires knowledge of the underlying neuronal circuits . In Drosophila , the mushroom body ( MB ) is the major site of learning and memory and we find that the MB is necessary for dialect learning [77 , 78] . We hypothesize that , given the large number of inputs required in dialect learning ( olfactory , ionotropic , and visual cues ) , which are then relayed to the MB , the “dialect” may be implemented in the MB via several neuronal classes that are activated and deactivated [77] . We suspect that there are increases in MB output neurons ( MBONs ) that reinforce the memory following a sufficient amount of time of stimulation ( i . e . greater than 24 hours in our assay ) . At the same time , we suspect there may be a decrease in inhibitory MBONs that may be responsible for ignoring other species . This increase/decrease would promote interactions and learning between species . Following this MBONs changing in synaptic strength , we suspect that dopaminergic neurons ( DAN ( s ) ) reinforce these signals in the appropriate MB lobes , similar to olfactory memories in other assays . We propose this given the need for olfactory reinforcement during dialect training , in addition to other necessary cues , which emulate the known MB circuitry [77] . We propose dialect learning to be a novel behavior requiring visual and olfactory inputs , perhaps integrated in and relayed through the MB , resulting in the ability to more efficiently receive information about a common predator . Without dialect learning , this information would otherwise be lost in translation or muddled , resulting in an inefficient behavioral response with significant survival disadvantages . Inhibiting synaptic transmission and knockdown of key learning and memory genes in the MB demonstrates that these inputs must be processed and consolidated in the MB , although input neuronal signaling is initiated from the visual and olfactory systems ( Fig 8B ) . Given the need for multiple sensory inputs , dialect learning is fundamentally different from the previously described teacher-student paradigm , where visual cues are necessary and sufficient for information exchange[17] . Additionally , we suggest that this study also points to previously unappreciated functions of the Drosophila MB in integrating information from multiple olfactory and visual inputs [77] . Such cognitive plasticity that allows for dialect learning from many different species hints that adult behaviors could only emerge in a manner that is dependent on previous social experiences where relevant ecological pressures are ever present and multiple species co-exist in nature . Thus , there is a real benefit to cognitive plasticity , where sharing of information directly , or by coincident bystanders , could result in behavioral immunity to pan-specific threats . The specific information shared by different species during dialect learning is not known . This study , however , provides important clues as the complex suite of sensory systems and cues that may be required for efficient dialect learning . We have presented an example of how interspecies social communication and dialect learning in Drosophila can lead to changes in germline physiology and reproductive behavior . What other ethological behaviors are modulated by MB functions and social interactions typically not revealed in laboratory monocultures ? We suggest that the Drosophila MB may integrate a myriad of social and environmental cues in order to produce ethologically relevant behavior that is responsive and useful to local environmental conditions .
The D . melanogaster strains Canton-S ( CS ) , Oregon-R ( OR ) , white1118 ( w1118 ) , and transgenic flies carrying Histone H2AvD-RFP ( His-RFP ) were used as wild-type strains . Experiments were primarily performed using CS as wild type flies except where otherwise indicated . Orco1 ( Or83b1 ) , UAS-TeTx , UAS-Orb2RNAi , UAS-FMR1RNAi , UAS-FMR1RNAi , UAS-PTENRNAi , UAS-Ir8aRNAi , UAS-Ir25aRNAi , ninaBP315 were acquired from the Bloomington Drosophila Stock Center ( stock numbers 23129 , 28838 , 27050 , 27484 , 34944 , 25841 , 25813 , 43985 , and 24776 respectively ) . Drosophila species were acquired from the Drosophila Species Stock Center ( DSSC ) at the University of California , San Diego . Flies and their respective stock numbers are listed: D . simulans ( 14021–0251 . 196 ) , D . mauritiana ( 14021–0241 . 01 ) , D . sechellia ( 14021–0248 . 25 ) , D . yakuba ( 14021–0261 . 01 ) , D . tsacasi ( 14028–0701 . 00 ) , D . kikkawai ( 14028–0561 . 00 ) , D . ananassae ( 14024–0371 . 13 and 14024–0371 . 11 ) , D . pseudoobscura ( 14011–0121 . 00 ) , D . neocordata ( 14041–0831 . 00 ) , D . equinoxialis ( 14030–0741 . 00 ) , D . willistoni ( 14030–0811 . 00 ) , D . immigrans ( 15111–1731 . 08 ) , D . mojavensis ( 15081–1352 . 22 ) , and D . virilis ( 15010–1051 . 87 ) . All experiments with D . ananassae used strain number 14024–0371 . 13 unless otherwise noted ( S1 Table ) . All stocks were kept separate to prevent visual transfer of information that could confound experiments . The ewgNS4 mutant line was kindly provided by Yashi Ahmed ( Geisel School of Medicine at Dartmouth ) . The mushroom body Gene-Switch line was kindly provided by Greg Roman ( Baylor College of Medicine ) . Ir8a1 , Ir25a2 , Ir8a>GAL4 , Ir25a>GAL4 and Ir8a1;Ir25a2;Orco1 lines were kindly provided by Greg S . B . Suh ( Skirball Institute at NYU ) . Flies aged 3–6 days post-eclosion on fresh Drosophila media were used in all experiments . Flies were maintained at room temperature with approximately 30% humidity . All species and strains used were maintained in fly bottles ( Genesse catalog number 32–130 ) containing 50 mL of standard Drosophila media . Bottles were supplemented with 3 Kimwipes rolled together and placed into the center of the food . Drosophila media was also scored to promote oviposition . Fly species stocks were kept separate to account for visual cues that could be conferred if the stocks were kept side-by-side . The Figitid larval endoparasitoid Leptopilina heterotoma ( strain Lh14 ) was used in all experiments . L . heterotoma strain Lh14 originated from a single female collected in Winters , California in 2002 . In order to propagate wasp stocks , we used adult D . virilis in batches of 40 females and 15 males per each vial ( Genesse catalog number 32–116 ) . Adult flies were allowed to lay eggs in standard Drosophila vials containing 5 mL standard Drosophila media supplemented with live yeast ( approximately 25 granules ) for 4–6 days before being replaced by adult wasps , using 15 female and 6 male wasps , for infections . These wasps deposit eggs in developing fly larvae , and we gave them access specifically to the L2 stage of D . virilis larvae . Wasp containing vials were supplemented with approximately 500 μL of a 50% honey/water solution applied to the inside of the cotton vial plugs . Organic honey was used as a supplement . Wasps aged 3–7 days post eclosion were used for all infections and experiments . Wasps were never reused for experiments . If wasps were used for an experiment , they were subsequently disposed of and not used to propagate the stock . Briefly , fly duplexes were constructed ( Desco , Norfolk , MA ) by using three standard 25mm x 75mm pieces of acrylic that were adhered between two 75mm x 50mm x 3mm pieces of acrylic . Clear acrylic sealant was used to glue these pieces together , making two compartments separated by one 3mm thick acrylic piece . Following sealant curing , each duplex was soaked in water and Sparkleen detergent ( Fisherbrand catalog number 04-320-4 ) overnight , then soaked in distilled water overnight and finally air-dried . This same cleaning protocol is used following usage of a duplex . The interior dimensions of each of the two units measured approximately 23 . 5mm ( wide ) x 25mm ( deep ) x 75mm ( tall ) . For experiments using Fly Duplexes ( teacher-student interaction ) , bead boxes ( 6 slot jewelers bead storage box watch part organizer sold by FindingKing ) were used to accommodate 12 replicates of each treatment group . Each compartment measures 32 x 114 mm with the tray in total measuring 21 x 12 x 3 . 5 mm . Each compartment holds 2 duplexes , and the tray in total holds 12 duplexes . Each bead box was soaked in water and Sparkleen detergent ( Fisherbrand catalog number 04-320-4 ) overnight , then soaked in distilled water overnight and finally air-dried every time before and after use . Empty duplexes were placed into the bead box compartments . 50 mL standard Drosophila media in a standard Drosophila bottle ( Genesse catalog number 32–130 ) was microwaved for 39 seconds . This heated media was allowed to cool for 2 minutes on ice before being dispensed . Each duplex unit was then filled with 5 mL of the media and further allowed to cool until solidification . The open end of the Fly Duplex was plugged with a cotton plug ( Genesse catalog number 51-102B ) to prevent insect escape . 10 female flies and 2 male flies were placed into one chamber of the Fly Duplex in the control , while 20 female Lh14 wasps were placed next to the flies in the experimental setting for 24 hours . After the 24-hour exposure , flies and wasps were removed by anesthetizing flies and wasps in the Fly Duplexes . Control flies underwent the same anesthetization . Wasps were removed and replaced with 10 female and two male “student” flies . All flies were placed into new clean duplexes for the second 24-hour period , containing 5 mL Drosophila media in a new bead box . For fly duplexes containing a subset of species , specifically D . mojavensis , D . immigrans , and D . virilis , 10 yeast granules were added to the standard Drosophila media after solidification of the food . This activated yeast was added to promote oviposition . Flies showed minimal oviposition in food lacking yeast . We speculate this was observed due to the fly food being optimized for D . melanogaster , which could be creating sensitized species to wasp presence . Plugs used to keep insects in the duplex were replaced every 24 hours to prevent odorant deposition on plugs that could influence behavior . The oviposition bead box from each treatment was replaced 24 hours after the start of the experiment , and the second bead box was removed 48 hours after the start of the experiment . Fly egg counts from each bead box were made at the 0–24 and 24-48-hour time points . 12 biological replicates were performed except where otherwise indicated . All experimental treatments were run at 25°C with a 12:12 light:dark cycle at light intensity 167 , using twelve replicates at 40% humidity unless otherwise noted . Light intensity was measured using a Sekonic L-308DC light meter . The light meter measures incident light and was set at shutter speed 120 , sensitivity at iso8000 , with a 1/10 step measurement value ( f-stop ) . Fly duplexes and bead boxes soaked with distilled water mixed with Sparkleen after every use for and subsequently rinsed with distilled water and air-dried in the manner described above . To avoid bias , all egg plates were coded and scoring was blind as the individual counting eggs was not aware of treatments or genotypes/species . Species were cohabitated in standard Drosophila bottles ( Genesee catalog number 32–130 ) containing 50 mL standard Drosophila media . Three Kimwipes were rolled together and placed into the center of the food . Batches of 3 bottles were made per treatment . Two species were incubated in each bottle with 100 female and 20 males of each species per bottle . Every two days , flies were placed into new bottles prepared in the identical manner . Flies were cohabitation for approximately 168 hours ( 7 days ) , unless otherwise noted . Following cohabitation , flies were anesthetized and the two species were separated . The flies were then used as students to wasp or mock exposure teachers of the opposite species . For example , we cohabitated D . melanogaster and D . ananassae for one week . Following the weeklong cohabitation , we separated the dialect trained flies . Trained D . melanogaster were placed in duplexes next to D . ananassae either mock or wasp exposed . Trained D . ananassae were placed in duplexes next to D . melanogaster either mock treated or wasp exposed . For experiments utilizing more than two species for dialect learning , species were cohabitated in standard Drosophila bottles ( Genesee catalog number 32–130 ) containing 50 mL standard Drosophila media . Three Kimwipes were rolled together and placed into the center of the food . Batches of 3 bottles were made per treatment . The three species were incubated in each bottle with 100 female and 20 males of each species per bottle . Every two days , flies were placed into new bottles prepared in the identical manner . The three-fly species were cohabitation for approximately 168 hours ( 7 days ) , unless otherwise noted . Following cohabitation , flies were anesthetized and one of the three species was tested by pairing them with teachers of the other two species . For example , we cohabitated D . melanogaster , D . ananassae , and D . willistoni for one week . Following the weeklong cohabitation , we separated the dialect trained flies . Trained D . melanogaster were placed in duplexes next to either D . ananassae or D . willistoni , mock or wasp exposed . For cohabitation experiments where two species were allowed visual only cues , the Fly Duplex was utilized . The two species were co-incubated side-by-side with 100 female and 20 males of each species per unit using the two chambers of the fly duplex such that the flies could only see each other . The fly duplex was placed into bead boxes , with each unit of the duplex containing 5 mL of standard Drosophila media . Every two days , flies were placed into new fly duplexes with fresh 5 mL standard Drosophila media . Following the weeklong co-incubation , flies were anesthetized and the two species were separated . The flies were then used as students to wasp or mock exposure teachers of the opposite species . For cohabitation experiments where the two species did not have visual cues , the two species were incubated in bottles with 100 female and 20 males of each species per bottle in complete darkness . The only difference between this method and other training sessions was the lack of light—meaning flies were subject to 25°C with 40% humidity . Every two days , flies were placed into new bottles prepared in the identical manner . Flies were exposed to light for less than 30 seconds , during which they were placed into a new bottle , and immediately returned to the dark . Following the weeklong dark-cohabitation , flies were anesthetized and the two species were separated . The flies were then used as students to wasp or mock exposure teachers of the opposite species . For cohabitation experiments under monochromatic light settings , batches of 3 bottles with 100 female and 20 males of each species were placed into 27 . 9cm x 16 . 8cm x 13 . 7cm plastic boxes ( Sterilite 1962 Medium Clip Box with Blue Aquarium Latches sold by Flikis ) . These boxes were externally wrapped with colored cellophane wrap , allowing only a certain wavelength of light to be transmitted into the boxes . Red and blue cellophane wraps were purchased from Amscam ( Amscan Party Supplies for Any Occasion Functional Cellophane Wrap , 16' x 30" , Rose Red and Spanish Blue ) . Cellophane wrapped boxes with bottles containing flies were subject to 25°C with 40% humidity under the same light intensity as previous experiments . Light intensity within the red wrapped box was 112 and within the blue wrapped box was 115 measured using the Sekonic L-308DC light meter . Every two days , flies were placed into new bottles prepared in the manner described previously . Flies were exposed to broad-spectrum light for less than 30 seconds , during which they were placed into a new bottle , and immediately returned to monochromatic light . Following the weeklong monochromatic-light-cohabitation , flies were anesthetized and the two species were separated . The flies were then used as students to wasp or mock exposure teachers of the opposite species . For the one-day cohabitation experiments , batches of 3 bottles with 100 females and 20 males of each species were placed at 25°C with 40% humidity for 24 hours . Following the 24-hour cohabitation , flies were anesthetized and the two species were separated . The flies were then used as students to wasp or mock exposure teachers of the opposite species . In order to ask whether socialization is needed for learning ability between D . melanogaster , we performed isolation experiments ( Fig 3 ) . In order to acquire isolated flies , we performed a 24-hour egg lay using approximately 100 females and 20 males of 3-5-day old Canton S at 25°C with 40% humidity on grape juice agar plates . Grape juice plates were made in aliquots of 30 plates , containing a total of 100 mL . We mixed: Dextrose ( 5 . 8 g ) , Sucrose ( 3 . 0 g ) , Agar ( 2 . 2 g ) , and Yeast ( 2 . 2 g ) . We added 86 mL distilled water and 12 mL grape juice concentrate ( welches brand ) to these solids . This solution was brought to a boil in a microwave , and allowed to pour and solidify . Plates were used immediately upon cooling . Following the 24-hour egg lay , flies were removed and the egg lay plate was placed at 25°C with 40% humidity with a 12:12 light: dark cycle for a second 24-hour period , after which , L1 larvae were collected and placed into a Falcon round-bottom polypropylene tube ( catalog number 352063 ) containing 1 mL standard Drosophila media . Larvae were allowed to pupate and eclose in isolation . Each tube was kept separate such that no visual information could be transferred between tubes . Following eclosion , 3–5 day old flies were used as students . 1 female and 1 male isolated Canton S were used as students , paired with 1 female , 1 male Canton S raised under typical socialized conditions . Social conditions were achieved by performing the same egg lay protocol as above , but 100 L1 larvae were transferred to standard Drosophila bottles ( Genesee catalog number 32–130 ) containing 50 mL standard Drosophila media and allowed to pupate and eclose at 25°C with 40% humidity . RU486 ( Mifepristone ) was used from Sigma ( Lot number SLBG0210V ) as the ligand for Gene-Switch experiments . Dialect training bottles were prepared by directly pipetting an RU486 solution onto the 3 Kimwipes in the bottle . The solution was prepared by dissolving 3 . 575 mg of RU486 in 800μL methanol ( Fisher Scientific Lot number 141313 ) . This solution was added to 15 . 2 mL of distilled water . The total solution ( 16 mL ) was thoroughly mixed and 4000 μL was pipetted onto the Kimwipe in each bottle . For bottles containing no RU486 ( methanol only ) 800μL methanol was mixed with 15 . 2 mL of distilled water . The total solution ( 16 mL ) was thoroughly mixed and 4000 μL were pipetted onto the Kimwipe in each bottle . Flies were shifted to new bottles prepared in the exact same manner every two days . Flies were cohabitated for approximately 7 days . Following cohabitation , flies were anesthetized and the two species were separated . The flies were then used as students to wasp or mock exposure teachers of the opposite species . Ovaries were collected from flies that were placed in vials along with female wasps for experimental or no wasps for control settings . Flies were placed in batches into standard vials ( Genesee catalog number 32–116 ) of 20 females , 2 males along with 20 female wasps for exposed vials , or simple placing 20 female and 2 male flies in vials for the unexposed treatments . Three vials were prepared to produce three replicates to account for batch effects . We observed no batch effects so each of the 12 ovaries imaged from each treatment were then counted as a replicate , thus providing an n of 36 . Ovaries that were prepared for immunofluorescence were fixed in 4% methanol-free formaldehyde in PBS with 0 . 001% Triton-X for approximately five minutes . The samples were then washed in PBS with 0 . 1% Triton-X , and blocked with 2% normal goat serum ( NGS ) for two hours . The primary antibody , cleaved Drosophila Dcp-1 ( Asp216 ) ( Cell Signaling number 9578 ) at a concentration of 1:100 , was used to incubate the ovaries overnight at 4° C in 2% normal goat serum ( NGS ) . The secondary antibody used was Fluorescein isothiocyanate ( FITC ) conjugated ( Jackson Immunoresearch ) , and used at a concentration of 1:200 for a two-hour incubation at room temperature . This was followed by a 10-minute nuclear stain with 4' , 6-diamidino-2-phenylindole ( DAPI ) . For confocal imaging of D . melanogaster ovaries , wheat germ agglutinin ( WGA ) was also used as a membrane marker ( Fig 1F and 1J , S2 Fig ) . All egg chambers were counted to acquire total egg chamber number and egg chambers showing Dcp-1 signal were counted as positive for Dcp-1 . All ovary quantifications were performed in a blinded manner such that the counter did not know the condition ( exposed v unexposed ) or species of the Drosophila ovaries being counted . A Nikon A1R SI Confocal microscope was used for imaging activated Dcp-1 caspase staining in D . melanogaster ( Fig 1D–1K , S2 Fig ) . Image averaging of 4x during image capture was used for all images . A Nikon E800 Epifluorescence microscope with Olympus DP software was used to image Dcp-1 caspase staining on all other Drosophila species tested ( S3–S16 Figs ) . This microscope was also used to quantify egg chambers with Dcp-1 signal and total number of egg chambers in all species tested ( S17 and S18 Figs ) . Statistical tests on exposed v unexposed/teacher v student interactions were performed in Microsoft Excel . Welch’s two-tailed t-tests were performed for data . P-values reported were calculated for comparisons between paired treatment-group and unexposed and are included in S1 File . Categorization assignments were made based on the criteria of mean value and statistical significance compared to unexposed . ‘No communication’ is assigned in instances where there was not a statistically significant decrease of the exposed group . ‘Partial communication’ , requires a statistically significant decrease of the exposed group , with an exposed mean above 50% . ‘Full communication’ , criteria are a statistically significant decrease of the exposed group , along with a mean below 50% . Direct comparisons between partial and full communication groups would require analysis of data collected at different times and between genotypes , rendering any such p-values invalid . However , to satisfy the desire for p-values associated with the partial/full threshold , one sample one tailed t tests were performed on exposed samples that were statistically less than unexposed ( S2 File ) . Corresponding p-values asses if the exposed group is statistically less than 50% . Statistical comparisons were performed in R ( version 3 . 0 . 2 “Frisbee Sailing” ) .
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In this study , we find that many different Drosophila species never having been exposed to parasitoid wasps can trigger caspase activation in the ovary and depress egg-laying when placed next to flies that had visual experience with wasps . Interestingly , when teacher flies of one species are placed with a student of a different species , communication exists , to varying degrees , which seems dependent on evolutionary relatedness . Cohabitation of two species that can partially communicate can learn each other’s “dialect” , yielding effective interspecies communication . There are various inputs involved in dialect learning , including the presence of visual and olfactory cues and memory functions , including genes implicated in social learning defects in murine models , such as PTEN . The neuroplasticity of adult Drosophila allows for learning of dialects , but the specific dialect learned is dependent on social interactions exclusive to a communal environmental context , which provides both visual and olfactory inputs . We find flies can communicate with one another about an anticipated danger , which is suggestive of a fly “language . ” The presence of a neurologically plastic system , allowing for social learning , can subsequently lead to a dramatic physiological response , requiring active learning and memory formation through integration of multiple inputs .
|
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2018
|
Drosophila species learn dialects through communal living
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The precise establishment of gene expression patterns is a crucial step in development . Formation of a sharp boundary between high and low spatial expression domains requires a genetic mechanism that exhibits sensitivity , yet is robust to fluctuations , a demand that may not be easily achieved by morphogens alone . Recently , it has been demonstrated that small RNAs ( and , in particular , microRNAs ) play many roles in embryonic development . Whereas some RNAs are essential for embryogenesis , others are limited to fine-tuning a predetermined gene expression pattern . Here , we explore the possibility that small RNAs participate in sharpening a gene expression profile that was crudely established by a morphogen . To this end , we study a model in which small RNAs interact with a target gene and diffusively move from cell to cell . Though diffusion generally smoothens spatial expression patterns , we find that intercellular mobility of small RNAs is actually critical in sharpening the interface between target expression domains in a robust manner . This sharpening occurs as small RNAs diffuse into regions of low mRNA expression and eliminate target molecules therein , but cannot affect regions of high mRNA levels . We discuss the applicability of our results , as examples , to the case of leaf polarity establishment in maize and Hox patterning in the early Drosophila embryo . Our findings point out the functional significance of some mechanistic properties , such as mobility of small RNAs and the irreversibility of their interactions . These properties are yet to be established directly for most classes of small RNAs . An indirect yet simple experimental test of the proposed mechanism is suggested in some detail .
Morphogenesis proceeds by sequential divisions of a developing embryo into domains , each expressing a distinct set of genes . Each combination of genes is associated with a particular cell identity . At advanced stages of development , most genes that define cell identity are either highly expressed ( “on” ) or strongly inhibited ( “off” ) in a given cell . For example , two adjacent domains may be differentiated by high expression of some genes in one , and low expression in the other . In such cases , it is important that cells of the two populations do not intermix . Moreover , the number of cells that show intermediate levels of expression , typically found at the interface between the two sets , should be kept to a minimum . These demands are necessary in order to unambiguously define the identity of each cell . A spatial gene expression pattern that obeys these demands is said to exhibit a sharp interface . A crucial step in setting the interfaces of gene expression patterns is often the establishment of a concentration gradient of molecules called morphogens . Some morphogens are transcription factors that regulate gene expression directly [1 , 2] . Others are ligands that bind cell-surface receptors signaling the activation of target expression [3] . Since morphogens act in a concentration-dependent manner , a morphogen gradient may be transformed into a gradient of its target messenger RNA ( mRNA ) . In principle , a single morphogen interacting cooperatively with its target enhancer can generate a sharp interface in the target transcription profile , by modulating the rate of its mRNA transcription as a function of the nuclear spatial coordinate [4] . This may be done , e . g . , by cooperative binding to a receptor or to a promoter [5] or by zero-order ultrasensitivity [6] . As an example , in Drosophila early embryonic development , Hunchback transcription depends on the cooperative binding of about five Bicoid molecules [7] . An obvious limitation in this mechanism is the need for large cooperativity factors or cascades of reactions , which make it prone to fluctuations and slow to adapt [7–10] . Recently , a role for small regulatory RNAs in establishing developmental patterning has been documented in plants [11–13] and animals [14] . In particular , it has been suggested that microRNAs ( miRNAs ) confer accuracy to developmental gene expression programs [15] . This raises the possibility that small RNAs aid morphogen gradients in establishing sharp interfaces between “on” and “off” target-gene expression . In this study , we formulate a mathematical model in which small regulatory RNAs help morphogens to determine cell identity by sharpening morphogen-induced expression patterns . For specificity , we assume here that the small RNA belongs to the miRNA family , and consider another class of small RNA in the Discussion . miRNAs constitute a major class of gene regulators that silence their targets by binding to target mRNAs . In metazoans , primary miRNA transcripts are transcribed and then processed both inside and outside of the nucleus to form mature transcripts approximately 21 nucleotides ( nt ) in length that are then loaded into the RNA-induced silencing complex ( RISC ) [16] . They are found in plants [17] and animals [18] , including human [19] , and are predicted to target a large fraction of all animal protein-coding genes [19–21] . In plants , miRNAs are known to affect morphology [11 , 12 , 22] , implying that they play an important role in determining cell identity . This is underscored by the fact that the spatiotemporal accumulation of miRNAs is under tight control in plants [23] , fly [14 , 24] , and zebrafish [25] . Our model is constructed in one spatial dimension , namely along one spatial axis . Domains of gene expression are laid out along this axis , and we assume no significant variance along other , perpendicular axes . Two key ingredients of the model are a strong interaction between miRNA and mRNA , and intercellular mobility of the miRNA . Within this framework , miRNAs generate a sharp interface between those cells expressing high levels of the target mRNA and those expressing negligible levels of mRNA . We use physical arguments to understand the range of parameters in which this sharpening occurs . Our model predicts that the spatial position of the interface is precisely determined: mobile miRNAs spatially average individual cellular fluctuations without compromising the interface sharpness . We use computer simulations to show that this is also true even with low numbers of molecules . A consequence of our model is that a local change to the transcription profiles can induce a nonlocal effect on the mRNA concentration profile; we outline an experiment to detect this nonlocal property . Finally , we consider possible applications of these ideas in plants and fruit fly .
Our theory comprises three central elements . First , miRNAs and their targets are taken to be transcribed in a space-dependent manner . Second , we assume that the interaction between miRNA and target irreversibly disable the target mRNA from being translated into proteins; this , for example , may be done by promoting the degradation of the target . Furthermore , the miRNA molecule itself may be consumed during this interaction . Last , we allow for the possibility that miRNAs move between cells . Before defining the model , let us review the available data regarding each of these processes . miRNAs and their targets are often expressed in a coordinated manner [26] . Often , the regulatory network is designed to express the miRNA and its targets in a mutually exclusive fashion . For example , the expression patterns of the miRNA miR-196 and its target Hoxb8 are largely nonoverlapping in mouse [27] and chick [28] . Similarly , the nascent transcripts of ubx ( i . e . , ubx transcripts still attached to the DNA ) are expressed in a stripe near the center of the early embryo , whereas nascent transcripts of its regulator , iab-4 , are simultaneously observed in nuclei posterior to this domain [29] . A recent large-scale study in Drosophila showed that miRNAs and their target genes are preferentially expressed in neighboring tissues [15] . Likewise , in mouse [30] and in human [31] , predicted miRNA targets were found at lower levels in tissue expressing the cognate miRNA than in other tissues . Our model assumes that the synthesis rate of the miRNA and its target are smoothly varying along a spatial axis , x . This , for example , may be the result of a common morphogen regulating ( either directly or indirectly ) the two species . The transcription profiles αμ ( x ) and αm ( x ) of the miRNA and its target are assumed to be largely anticorrelated . The detailed interaction between miRNAs and their targets is currently a topic of intense investigation [32 , 33] . miRNAs induce the formation of a ribonucleoprotein complex ( RISC ) . Targeting of a specific mRNA by a RISC is done via ( often imperfect ) base-pair complementarity to the miRNA [18] . Upon binding , protein synthesis is suppressed by either translational repression or mRNA destabilization [32 , 33] . Although it is likely that miRNA can go through a few cycles of mRNA binding [34] , the increased endonucleolytic activity conferred by the miRNA makes it plausible that the miRNA is sometimes degraded in the process . In addition , evidence suggests that mRNAs that are translationally repressed by miRNA may be colocalized to cytoplasmic foci such as stress granules [35] or processing bodies [34–36] . Stress granules are cytoplasmic aggregates that appear under stress and sequester untranslated RNA , perhaps to protect these molecules or to regulate translation [37] . Processing bodies , which are enriched with endonucleases , are believed also to be places of mRNA degradation [38] . The two types of RNA granules are also known to interact , possibly an indication that stored RNA in stress granules may be targeted for degradation [37] . In both cases , RNA granules may sequester or degrade not only the mRNA , but also its bound miRNA . Taken together , these facts make it improbable that miRNAs act in a fully catalytic manner . A pair of mRNA–miRNA reactions that describe a spectrum of plausible scenarios is where m represents the mRNA concentration and μ represents that of the miRNA . Here , θ is the average number of targets degraded by a given miRNA before it is itself lost in the process . These reactions may be realized in different ways . For example , the two species may reversibly form a complex that is then subject to degradation . Another possibility is that the two species irreversibly associate to form an inert complex . Furthermore , the reaction between the species may be reversible , as long as the typical dissociation time is much longer than the relevant biological timescale . One way in which the cell may control the dissociation time is by regulating exit of the RNA pairs from processing bodies [39] . Can miRNAs move from cell to cell ? Short interfering RNA ( siRNAs ) , another important class of small RNAs , are known to elicit non–cell-autonomous RNA silencing in plants , worms , fly , and possibly mouse ( reviewed in [40] ) . This may also be the case for trans-acting siRNA [13] . Evidence in favor of intercellular mobility of miRNA is found in pumpkin [41] . There , miRNAs have been found in the phloem sap that is transported throughout the plant by phloem tissue . In animals , many small RNAs , including many miRNAs , were found in exosomes from mouse and human mast cell lines , which can be delivered between cells [42] . In our model , we consider the possibility that miRNAs migrate from cell to cell . Mobility of the miRNA species is likely to rely on active export from the cell followed by import to neighboring cells , or perhaps on transport between neighboring cells , e . g . , via gap junctions . On the tissue scale , these transport processes are expected to result in effective diffusion . We therefore ignore the small-scale transport processes , and model miRNA mobility as pure diffusion . Finally , we combine these processes into a steady-state mean-field model given by The β terms describe independent degradation ( i . e . , by processes independent of the other RNA species ) and the k term describes coupled degradation of both RNA species . Note that the case θ > 0 ( where miRNA may go through multiple rounds of interactions with target mRNAs ) can also be brought into this form by rescaling Equation 2a [43] . Mobility of the miRNA is described by an effective diffusion constant D . The spatial coordinate x measures distance along one dimension of a tissue . All our numerical results shall be presented in units of the tissue size , i . e . , 0 ≤ x ≤ 1 . Equation 2a and Equation 2b cannot be solved analytically . In what follows , we solve these equations numerically , imposing zero-flux boundary conditions . These exact numerical solutions can be used to draw the steady-state expression profiles of both RNA species for a particular set of parameters . To gain further insight , we also develop an approximate analytical solution . As described above , a desired target protein profile comprises a domain of cells that express this protein abundantly , adjacent to a domain of cells where this protein does not accumulate . Furthermore , one requires that the number of cells with intermediate expression levels lying in between the two domains be minimized—this is our definition of a sharp interface . In this section , we discuss one scenario in which the mutual consumption of a diffusive miRNA and its target leads to such a sharp interface in the mRNA profile . We assume that some morphogen controls the transcription rate of the target . The transcription profile—namely , the transcription rate as a function of the spatial coordinate of the nucleus—is laid down as a smooth gradient , falling from one end of the developing tissue ( which , for convenience , will be called “left” ) toward the other end ( “right” ) . Motivated by a recent study that showed that miRNA and their targets are preferentially expressed in neighboring tissues [15] , we focus on the scenario in which the miRNA transcription is controlled in a fashion opposite to that of the mRNA: miRNA transcription is peaked at one end of the tissue ( where the mRNA transcription rate is minimal ) , and decreases toward the other end ( where the mRNA transcription rate is maximal ) . The kind of “mutually exclusive” transcription profiles we have in mind is depicted in Figure 1A . In this figure , and hereafter , we denote the mRNA transcription profile by αm ( x ) and the miRNA transcription profile by αμ ( x ) , explicitly noting their dependence on the spatial coordinate x . We note that , in the absence of miRNA–target interaction and of miRNA diffusion , the concentration profiles of mRNA and miRNA simply follow their transcription profiles ( Figure 1A and 1D ) . Each is rather smooth and overlaps the other near the center of the tissue . Before studying the full model , it is instructive to consider first the interacting system in the absence of miRNA diffusion . In the context of mutually exclusive transcription profiles , we expect that each cell would be dominated by one RNA species ( either the miRNA or the target mRNA ) , which we will call the majority species , and be depleted of the other , the minority species . In other words , we are making the critical assumption that the decay of the minority species in each cell is governed by the interaction with the other species ( rather than by its independent degradation ) . This assumption can be made quantitative in terms of the model parameters; see Equation S1 in Text S1 . Under this assumption , which we refer to as the strong interaction limit , it is straightforward to show ( Equation S3 in Text S1 ) that the density of the majority species in each cell is proportional to the difference between the two transcription rates in that cell , whereas the minority species is essentially absent . Consequently , in the context of mutually exclusive transcription profiles , the mRNA level becomes vanishingly small in any cell for which αm ( x ) < αμ ( x ) , namely every cell to the right of the point where the two transcription profiles are equal . The concentration profiles of the two RNA species are shown in Figure 1B and 1E , in which one can see that the mRNA and miRNA spatial expression domains are now complementary and more sharply defined . The threshold response that arises when both RNA species do not diffuse from cell to cell provides insurance against the possibility that the mRNA transcription profile is not as step-like as is required for unambiguous cell differentiation . In other words , miRNA regulation acts as a failsafe mechanism whereby incorrectly transcribed low-abundance transcripts in the region αm ( x ) < αμ ( x ) are silenced , while correctly transcribed high-abundance transcripts in the region αm ( x ) > αμ ( x ) are only mildly affected [15 , 26] . This threshold response in the target profile has been observed in the context of small RNAs—another class of posttranscriptional regulators—in bacteria [43] . We now return to our full model , which allows for diffusion of the miRNA . To simplify the analysis , let us keep the strong-interaction limit , described above ( and in Equation S1 in Text S1 ) . In general , one expects that diffusion makes the miRNA profile more homogeneous , and this is confirmed by exact numerical solution of the model , as shown in Figure 1C . Surprisingly , however , the mRNA profile does not become smoother . In fact , Figures 1C and 1F show that this profile actually develops a sharper drop from high to low mRNA levels than there was in the absence of diffusion . More specifically , miRNA diffusion creates an interface between high and negligible target expression . Increasing diffusion moves the interface deeper into the mRNA-rich region and thereby accentuates the drop in mRNA levels across the interface . Although some miRNA diffusion is required to establish a sharp interface in the mRNA profile , the diffusion constant cannot be too large . As Figure 1G demonstrates , increasing the diffusion constant may result in smoothing the interface . A corresponding increase in the interaction strength , k , can compensate for the increased diffusion , regaining the interface sharpness ( Figure 1H ) . We will quantify these observations below . Diffusing miRNAs can find themselves in one of two very different regions . In the miRNA-rich region ( including the region to the right of the point where the transcription profiles are equal ) , miRNA decay occurs mainly via processes independent of their interaction with the target . In this region , our model boils down to a simple diffusion process accompanied by linear decay . Such processes are characterized by a length scale , denoted by λ , which essentially measures how far a miRNA can travel ( due to diffusion ) before being consumed ( by independent degradation ) . It is thus an increasing function of the diffusion constant D , but a decreasing function of the independent decay rate βμ . On the other hand , in the mRNA-rich region , a miRNA decays mainly via co-degradation with its target . In this region , miRNAs decay faster , and one expects them to be able to travel over much shorter distances than in the miRNA-rich region . In fact , diffusion in this region is characterized by another , smaller , length scale , denoted by ℓ , which again increases with D , but is now a decreasing function of the interaction strength , k . Explicit expressions for the two length scales are given in Text S1 ( Equations S5 and S6 in Text S1 ) . To obtain a sharp interface in the mRNA profile , miRNAs should be able to travel from the miRNA-rich zone into the mRNA-rich zone . This means that the first length scale , λ , should be of the same order as the tissue length . This , for example , can be achieved if the diffusion constant D is large enough . On the other hand , the vicinity of the interface is governed by the other length scale , ℓ . This length scale is what determines the “width” of the interface , namely the number of cells that exhibit intermediate levels of mRNA expression ( see blue box in Figure 1C ) . A sharp interface , therefore , means a small value of ℓ , and one way to achieve a small value of ℓ is to make the diffusion constant D small enough . These two contradicting requirements on D suggest that there might be an intermediate range of values for the diffusion constant that allows for a sharp interface , but also raises the suspicion that this range may be very small and requires some fine-tuning . This , however , is not the case: the fact that λ is strongly dependent on βμ ( whereas ℓ does not depend on βμ at all ) , and that ℓ strongly depends on k ( whereas λ does not ) means that the range of allowed values of D can be set as large as needed . In Text S1 , we develop an approximate analytical expression for the mRNA profile in terms of the various parameters and the “input” profiles αm ( x ) and αμ ( x ) ( Figure S1 ) . There are two lessons to be learned from this exercise . First , the interface established by the mRNA–miRNA interaction is effectively impermeable to miRNA diffusion in the strong-interaction limit . The system thus separates into two parts which—in steady state—do not exchange molecules between them . This property allows one to calculate the position of the sharp interface in the mRNA profile . The second lesson comes from the resulting equation for the interface position . This equation takes the form of a weighted spatial average of the difference between the two transcription profiles ( Equation S11 in Text S1 ) . Before interpreting the full result , it is instructive to consider the limiting case in which miRNAs cannot be degraded independently ( βμ = 0 ) . In this case , our result ( Equation S12 in Text S1 ) implies that the interface is positioned such that total synthesis rates of mRNA and miRNA to its right are equal . Thus , it is the total production rates in that part of the system that determine the interface position , and not any particular cell by itself . In the more general case ( βμ > 0 ) , the contribution of each cell is weighted by some nontrivial function . Still , in order to determine the interface position , one needs to perform a sum over many nuclei , each contributing the difference between the local transcription rates of the two RNA species . Clearly , these rates may be influenced by many factors , and in a description that is somewhat closer to reality , one would expect this difference to be fluctuating around αμ ( x ) − αm ( x ) . However , the interface position is a sum of these fluctuating objects , and one might hope that the sum of these fluctuations—which are uncorrelated—would be close to zero . In this case , the interface position would be robust to fluctuations of this type . Indeed , a stochastic simulation of the model shows no change in the interface position ( or structure ) , as compared with the deterministic model discussed so far ( Figure S3; see Text S1 for details of our simulations ) . In a multicellular tissue , mRNA are typically not expected to be transferred from cell to cell . Therefore , most of the work presented here does not consider the possibility that mRNA can also be mobile . Nevertheless , mRNA mobility should be considered in some cases . For example , the early Drosophila embryo is a syncytial blastoderm , in which nuclei multiply in a common cytoplasmic space . In the absence of cell membranes , mRNA is likely to be mobile , although probably with a small diffusion constant [44] . In Text S1 , we generalize our model to include mRNA mobility . We find that a sharp interface can be achieved as long as the typical distance traveled by target mRNAs , even in the absence of miRNAs , is small compared with any other length scale ( such as the interface width ) . Denoting the mRNA diffusion constant by Dm , this condition can be written as . We note that this condition does not contradict any of the conditions mentioned before; see Figure S2 . In passing , let us note that the conditions required so far—namely , strong interaction between the miRNA and its target , and small ℓ—may be reached by making the mRNA completely stable ( βm → 0 ) . However , our analysis shows that in this case , the system would never relax to a steady state , since target mRNAs would accumulate at the left end of the tissue without limit . Our analysis here is , therefore , only applicable if the mRNA molecules undergo independent degradation , in addition to the miRNA-dependent degradation . Using the insight gained in the previous section , we briefly show how a stripe is formed when the miRNA transcription profile αμ ( x ) is similar to αm ( x ) but displaced from it ( Figure 2A ) . Suppose , for example , that the synthesis of an miRNA and its target are activated by the same transcription factor . In any given nucleus , the two promoters experience the same concentration of this transcription factor . However , they need not react in the same way: if the binding affinity of one promoter is stronger than that of the other , there will be intermediate concentrations of the transcription factor such that the first promoter will be activated while the other will not . Such a scenario is depicted in Figure 2A , where a common transcription factor , which exhibits a spatial gradient , activates the target gene as well as the miRNA gene . In this case , the target promoter has higher affinity to the transcription factor than the miRNA promoter . Thus , some cells in the middle of the developing tissue express the target mRNA , but not the miRNA . Unlike the case studied in the previous section , in which the transcription profiles crossed at one point , here the transcription profiles cross at two points . Let us retrace our steps in the previous section by first considering the case of no diffusion . For low values of the interaction rate k , the miRNA and mRNA profiles are qualitatively similar to their transcription profiles . As k is increased however , miRNA deplete mRNA levels at any position where αμ > αm and thus confine mRNA expression to a stripe between the two crossing points of the transcription profiles ( green curve in Figure 2B ) . Can diffusion make this profile sharper , as in the previous case ? Indeed , diffusing miRNAs that survive annihilation on the left and right diffuse into the interval between the two crossing points , and establish sharp interfaces in the mRNA concentration profile . The resulting stripe resides within this interval , but is narrower ( blue curve in Figure 2B ) . It is therefore important that parameters allow for sharp interfaces , without making the stripe too narrow ( or even disappear ) . Therefore , to sustain a well-defined stripe of gene expression , the interface width must be much smaller than the distance between the two crossing points of the transcription profiles . One can use the same analytic method mentioned earlier to calculate the new positions of the stripe boundaries ( see Figure S4 and Text S1 ) . This exemplifies how the method can be used to analyze geometries of increasing complexity . The sharp interface that we predict can be detected directly in an imaging experiment , provided the light intensity varies linearly with mRNA concentration and the spatial resolution is high enough . However , experiments often do not supply quantitative data that are faithful to the underlying concentration profile . This , for example , is the case if an experimental setup is designed to identify the presence/absence of a molecular species . The application of nonlinear filters , such as photomultipliers , may result in spurious sharp boundaries . In contrast , low spatial resolution may make a sharp interface appear smoother than it really is . Here , we address the task of making predictions that are based on quantitative analysis , yet can be tested using qualitative data . To this end , we consider a worst-case ( if somewhat artificial ) scenario in which the apparatus' readout is binary: concentrations below an apparatus-dependent threshold are not detected , whereas concentrations larger than this elicit a concentration-independent fluorescence intensity . In such scenarios , it is impossible to tell a smooth and sharp concentration profile apart as both yield a sharp interface in the binary readout ( Figure 3A and 3B ) . Fortunately , our model of miRNA-mediated morphogenic regulation possesses another signature that is visible at such coarse experimental resolution . To detect this signature , one needs to overexpress the miRNA in a small patch of cells ( hereafter denoted the “patch” ) . Our model then predicts that this patch has a qualitatively different effect depending on which side of the interface it occurs . The technique one uses to generate the patch may differ according to the stage of development under consideration . In the early blastoderm stages of Drosophila development , for example , a Gal4 driver may be used to drive expression of the miRNA in those cells in which an endogenous gene is expressed [45] . Many endogenous genes are expressed in stripes along the anterior–posterior axis during these stages and some have dedicated enhancers for single stripes [4 , 46] . As an example , the yeast FLP-FRT recombination system has been used to misexpress the gap gene knirps in a stripe by placing it under the control of the eve stripe 2 enhancer [47] . In later stages of Drosophila development , e . g . , imaginal discs , one technique is the random generation of a mosaic of mutant clones ( patches ) by mitotic recombination [45 , 48] . The patches are generated at a low rate , and one then screens for those embryos containing a single patch . We model the localized overexpression of miRNA by an effective local increase of the transcription rate ( by an amount αc = 5 ) . This increase in transcription rate occurs in a small number of cells , which in our model is about 5% of the tissue length . More specifically , we choose a position xc for the center of the patch , and for every point x that resides within a distance w/2 of xc , we change the transcription rate from αμ ( x ) to αμ ( x ) + αc . Here w is the “width” of the patch , which takes a value w ≃ 5% of the tissue length . Consider positioning the patch first in the miRNA-rich region of the developing tissue ( Figure 3C ) . One sees that , even if positioned at a distance from the expression domain of the target , the effect of the additional miRNA is to push the interface toward the left . The localized patch of cells therefore has a nonlocal effect . As mentioned earlier , the position of the interface is determined by a global comparison of the mRNA and miRNA transcription rates to the right of the interface . Ectopic expression of miRNA to the right of the interface changes this balance and displaces the boundary . Note that this displacement can only be achieved if the patch is positioned to the right of the interface , since the interface position is not influenced by transcription balance to its left . This effect is quantified in Text S1 . This experiment should be contrasted with one in which the overexpressing patch is positioned in the mRNA-rich region , as shown in Figure 3D . Such ectopic miRNA expression has a local effect , with excess miRNA creating a hole in the mRNA expression domain . The hole edges constitute two additional interfaces in the system , the sharpness of each again determined by ℓ . One can go further and make a quantitative prediction , relating the number of patches in a mosaic of patches with the lateral shift in the interface position . To first approximation , one needs to count the number of patches in the miRNA-rich region , and disregard completely the patches in the mRNA-rich region . The displacement of the interface position is then linearly proportional to this number; see Text S1 for details . Simulated experimental results that would verify this prediction are shown in Figure 4 . The distinct nonlocal effect described above does not occur when the miRNA are unable to move between cells . Also , we have checked ( for the parameters used in this study ) that it does not occur when the miRNA acts purely catalytically ( Figure S5 ) . Rather , both miRNA mobility and a strong interaction between miRNA and target are required . The presence or absence of the nonlocal effect would therefore confirm or falsify the hypotheses that miRNA are mobile and that they interact stoichiometrically with mRNA while in this mobile state .
In this study , we have analyzed a model in which miRNAs sharpen target-gene expression patterns by generating an interface between high and low target expression . This effect is due only to the strong noncatalytic interaction between the miRNA and its target , and requires no additional interactions or feedbacks . A necessary condition for a sharp interface to occur is that the miRNA and target are co-degraded; a miRNA–mRNA interaction in which miRNAs promote mRNA degradation , but in which miRNAs themselves are unaffected , is insufficient . One can , in principle , test the existence of coupled miRNA–mRNA degradation by inhibiting the transcription of mRNA and monitoring its decay rate , which in this case would be time-dependent , ( t ) = βm + k μ ( t ) . We note also that a stoichiometric interaction may complicate the interpretation of sensor transgene experiments [27] , as the transgene would then sequester miRNA and thereby alter the original expression patterns . In principle , any interaction between a pair of molecules that obeys the rules of our model , such as an irreversible noncatalytic interaction , can set up a sharp expression interface . For example , suppose that a transcription factor is deactivated by binding irreversibly to an inhibitor protein . In this case , the concentration profile of active transcription factors can exhibit a sharp interface via the mechanism described above . In common with classical reaction–diffusion models for developmental patterning [49 , 50] , an essential property here is that the inhibitor diffuses much faster than its target . The interface between low and high mRNA levels is characterized by low molecule numbers of both RNA species . In such cases , fluctuations in the molecule number of either species may have macroscopic effects . For example , a small RNA-target pair in bacteria shows enhanced fluctuations when their transcription rates become comparable ( E . Levine , M . Huang , Y . Huang , T . Kuhlman , Z . Zhang , and T . Hwa , unpublished data ) [51] . These fluctuations can in turn give rise to noise-induced bistability , which manifests itself experimentally as diversity in a population of cells ( E . Levine , M . Huang , Y . Huang , T . Kuhlman , Z . Zhang , and T . Hwa , unpublished data ) . We performed Monte Carlo simulations of our model , but found that fluctuations have no macroscopic effect , even near the transition point where molecule numbers of both species are low . This in-built robustness to fluctuations arises because the interface position is determined by an integrated transcriptional flux which averages out individual cellular fluxes . Thus spatial averaging results in high spatial precision without smoothing out the interface . Strong cooperative activation , as often occurs in morphogenetic regulation at the transcriptional level ( e . g . , Bicoid has about five binding sites in target promoters of Drosophila ) , would seem to make pattern formation by morphogens inherently susceptible to temperature variations [52 , 53] . Nevertheless , embryonic patterning appears to be quite robust to temperature variations , as has been documented for Hunchback [52] and for Eve [54] in Drosophila . The only cooperative reaction required in the model presented in this work is coupled degradation of miRNA and mRNA , suggesting the possibility that miRNAs filter fluctuations arising from temperature variations . Candidate systems in which to test the ideas put forth in this study include the establishment of dorsoventral ( adaxial/abaxial ) leaf polarity in plants , as well as the segmentation of the early Drosophila embryo . We now discuss these two systems in some detail . Leaf polarity in plants is established shortly after the emergence of the leaf primordium from the meristem . Specification of leaf polarity depends on the Sussex signal [55] , a meristem-borne signal that specifies adaxial cell fates . Members of class III of the homeodomain-leucine zipper ( HD-ZIPIII ) proteins specify adaxial fate [11 , 56] . In Arabidopsis and in maize , the polar expression pattern of these genes results from their inhibition by two miRNAs , miR165/166 , which exhibit a complementary expression pattern [11 , 12] . Recently , it has been shown that in maize , restriction of miR165/166 to the abaxial side of the developing leaf depends on the polarized expression of LBL-1 , a protein involved in the biosynthesis of trans-acting RNAs , ta-siR2141/2 [13] . Possible targets of ta-siR2141/2 include members of the arf3 gene family ( a transcription factor that is expressed abaxially ) , as well as members of the miR166 family [13] . Although miRNAs in plants are thought to act mainly cell autonomously [57] , DCL4-dependent siRNAs , such as ta-siR2141/2 , may exhibit cell-to-cell movement [40] . The following model is consistent with these data ( Figure 5A ) . The RNA transcript TAS3 is cleaved to produce ta-siR2141/2 in the meristem . These small RNAs then propagate ( diffuse ) into the adaxial side of the leaf , inhibiting the expression of miR166 either directly or through the ARF3 transcription factor . The target ( either miR166 or ARF3 ) is transcribed uniformly throughout the leaf , and is localized to the cell where it is synthesized . If one further assumes that the interaction between ta-siR2141/2 and its target is noncatalytic , then this model belongs to the class of models studied in this work , and can therefore exhibit a sharp interface between the abaxial domain of high target expression and the adaxial domain of no expression; see Figure 5 . In agreement with this model is the low abundance of ta-siR2141/2 in Arabidopsis [58 , 59] , despite their distinct phenotypic role . Early embryonic development in Drosophila proceeds via a cascade of gene activities that progressively refine expression patterns along the anterior–posterior axis of the embryo . A recent study of the expression patterns of nascent miRNA transcripts suggests that a number of miRNAs play a role in this process . The miRNAs miR-309clus , miR-10 , and iab-4 ( which all reside between annotated mRNA genes on the genome ) , and miR-11 , miR-274 , and miR-281clus ( which all reside within introns of annotated genes ) are all expressed in a graded fashion along the anterior–posterior axis of the blastoderm embryo [14 , 60] . The complementary transcription profiles of iab-4 and its target ubx at stage 5 of development make this miRNA-target system a candidate for the sharpening mechanism proposed in this study . The early ubx transcript pattern is broadly distributed over the posterior half of the embryo , becoming localized to a stripe at the center of the embryo by the completion of cell formation [29 , 61] , probably as a result of transcriptional repression by Hunchback in the anterior and posterior regions of the embryo [62] . The nascent transcript profile of its regulator , iab-4 , is broadly distributed posterior to this stripe [29] . It may be the case that iab-4 is also expressed before cell formation and that the absence of cell membranes makes iab-4 mobile . The much larger ubx mRNA , on the other hand , may be effectively stationary on the timescales of interest [7] . Furthermore , the transcription profiles of iab-4 and ubx at stage 5 do not seem to overlap [29] , suggesting that iab-4 intercellular mobility is crucial to allow it to interact with ubx at this stage of development . Assuming then that only the miRNA iab-4 is mobile , the complementary expression patterns of iab-4 and its target , ubx , measured in [29] is consistent with our model of miRNA-induced sharpening . Sample profiles predicted by the model are shown in Figure 6 . A possible difficulty with regard to applying our model to ubx/iab-4 is that the system may not have reached steady state before stage 6 , when cells begin to migrate . In particular , no ubx protein was detected at stage 5 , possibly because of the time needed to transcribe the large ubx locus [29] . Like iab-4 , the miRNA miR-10 is also expressed at stage 5 in a broad posterior region along the anterior–posterior axis [14] . The homeotic gene Scr is a predicted target of miR-10 [63] and is also expressed in the blastoderm at stage 5 [64] . The miR-10 site in the Scr 3′ UTR is likely to be functional because the pairing is well conserved in all drosophilid genomes and because the miRNA site is conserved in the Scr genes in mosquito , the flour beetle , and the silk moth [20] . Unlike ubx , the protein of Scr is detected at this stage of development in a stripe of ectodermal cells about four cells wide in the parasegment-2 region , though it may not be functional at this time as the protein ( a transcription factor ) was not localized to the nucleus [64] . This spatial expression pattern is proximal to the anterior limit of miR-10 expression [14 , 64] . Hence the interaction of miR-10 with Scr at stage 5 of Drosophila development is also a candidate for the sharpening mechanism . The sharpening mechanism is most effective when the spatial transcription profiles of miRNA and target are regulated in such a way as to be mutually exclusive . The genomic locations of the miRNAs iab-4 and miR-10 are proximal to their targets , which is certainly consistent with the possibility of coordinated regulation [65] .
To obtain the concentration profiles for the mRNA and miRNA in the different scenarios considered in this paper , we integrated numerically Equation 2 . To do this , one needs to specify the transcription profiles , αm ( x ) and αμ ( x ) , and the values of the parameters βm , βμ , k , and D . Unless mentioned otherwise in the text , we chose βm = βμ = D = 0 . 01 and k = 1 throughout . The transcription profiles of Figures 1 and 3 were where Am = 2 , Aμ = 1 , xtsx = 0 . 5 , and λtsx = 0 . 2 . In the stripe geometry ( Figure 2 ) , the transcription profile for m was as above , with xtsx = 0 . 7 . The transcription profile of the miRNA was given by with Aμ = 2 , Aμ0 = 0 . 6 , and xtsx = 0 . 3 . In the Discussion , we outline possible applications in two systems: leaf polarity in maize and segmentation in the early Drosophila embryo . Here , we did not aim to estimate parameters from experimental data ( which , in most cases , is not quantitative enough to allow for parameter inference ) . Instead , parameters were chosen arbitrarily to allow clear demonstration of possible results . In the case of leaf polarity ( Figure 5 ) , we chose αm ( x ) = Am , αs ( x ) = Aμθ ( x − xtsx ) with Am = 1 , Aμ = 50 , and xtsx = 0 . 99 . Here , θ ( x ) is the unit step function . In the Drosophila embryo ( Figure 6 ) , the transcription profile of the iab-4 miRNA was the same as in Equation 3 , whereas the ubx mRNA transcription profile was given by with xtsx = 0 . 1 , λtsx = 0 . 05 , and Am = 2 .
The GenBank ( http://www . ncbi . nlm . nih . gov/Genbank/ ) GeneIDs for the genes discussed in this paper are arf3 ( 817014 ) , eve ( 36039 ) , hb ( 41032 ) , hoxb8 ( 15416 ) , iab-4 ( 3772110 ) , lbl1 ( 100037819 ) , miR-10 ( 3772568 ) , miR-11 ( 3771987 ) , miR-196 ( 387191 ) , miR-274 ( 3771876 ) , miR-281–1 ( 3772402 ) , miR-281–2 ( 3772497 ) , miR-309 ( 3772613 ) , scr ( 40833 ) , tas3 ( 3768766 ) , and ubx ( 42034 ) .
|
Early embryonic development depends on robust patterning along the axes of the embryo . At the cellular level , neighboring segments are often identified via the concentrations of several gene products: the expression of such a gene may , for example , be high in the cells of one segment , and negligible in those of another . Recently , it has been suggested that small RNA molecules , such as microRNAs , may play a role in establishing a sharp boundary between two neighboring segments , but are not required for the overall patterning . Here , we investigate this possibility using a mathematical model , which assumes that small RNAs diffuse in the tissue . Surprisingly , we find that mobility of the small RNAs may generate a sharp interface in the expression profile of its target gene . We analyze the properties of the interaction between the two molecules that are required to achieve this function . An experimentally testable prediction is detailed , and two possible realizations in the fruit fly and in maize are discussed .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods",
"Supporting",
"Information"
] |
[
"developmental",
"biology",
"zea",
"computational",
"biology",
"biophysics",
"drosophila"
] |
2007
|
Small Regulatory RNAs May Sharpen Spatial Expression Patterns
|
A biofilm is a surface-associated population of microorganisms embedded in a matrix of extracellular polymeric substances . Biofilms are a major natural growth form of microorganisms and the cause of pervasive device-associated infection . This report focuses on the biofilm matrix of Candida albicans , the major fungal pathogen of humans . We report here that the C . albicans zinc-response transcription factor Zap1 is a negative regulator of a major matrix component , soluble β-1 , 3 glucan , in both in vitro and in vivo biofilm models . To understand the mechanistic relationship between Zap1 and matrix , we identified Zap1 target genes through expression profiling and full genome chromatin immunoprecipitation . On the basis of these results , we designed additional experiments showing that two glucoamylases , Gca1 and Gca2 , have positive roles in matrix production and may function through hydrolysis of insoluble β-1 , 3 glucan chains . We also show that a group of alcohol dehydrogenases Adh5 , Csh1 , and Ifd6 have roles in matrix production: Adh5 acts positively , and Csh1 and Ifd6 , negatively . We propose that these alcohol dehydrogenases generate quorum-sensing aryl and acyl alcohols that in turn govern multiple events in biofilm maturation . Our findings define a novel regulatory circuit and its mechanism of control of a process central to infection .
A biofilm is a community of surface-associated microorganisms embedded in a matrix of extracellular polymeric substances . Biofilms are common microbial growth forms in nature and are a leading cause of human infection [1] . These infections are seeded from biofilms present on implanted medical devices , such as intravascular catheters [2] . Biofilm formation mechanisms are thus relevant to our understanding of both microbial ecology and infectious disease . Biofilm matrix is broadly defined as an extracellular polymeric material that is maintained within a biofilm [3]–[6] . It derives from directed synthesis and secretion of matrix components as well as lysis of a fraction of biofilm cells [5] . In natural settings , matrix constituents may also come from the local environment , such as an infected host [5] . Biofilm matrix often consists predominantly of extracellular polysaccharides . For example , bacterial biofilm matrices can include cellulose , polysaccharide intercellular adhesin , and the polysaccharide polymers VPS , PEL , and PSL [6] . Other matrix components include proteins , fatty acids , and nucleic acids [6] , [7] . In general , the matrix provides support and protection of the microbial community embedded within it . Our focus is the biofilm matrix of C . albicans , the major fungal pathogen of humans . The C . albicans matrix is composed primarily of carbohydrate and includes protein , hexosamine , phosphorus , and uronic acid [8] . The primary carbohydrate is probably β-1 , 3 glucan: glucose is the major matrix sugar and biofilms are disrupted by in situ treatment with lyticase [8] , an enzyme that specifically hydrolyzes β-1 , 3 glucan . Moreover , Nett et al . have shown that elevated β-1 , 3 glucan levels are characteristic of biofilm cells as compared to planktonic free-living C . albicans cells [9] . The increased β-1 , 3 glucan content of in vitro-grown biofilms is found in both cell walls and as a secreted form [9] . Finally , soluble β-1 , 3 glucan is produced by C . albicans biofilms grown in an in vivo catheter infection model , where it can be used in diagnosis of catheter-based infection [10] . Matrix production is closely tied to biofilm formation , yet little is known about its regulation or production mechanisms . We describe here a C . albicans transcription factor , Zap1/Csr1 ( orf19 . 3794 ) , that governs matrix production . This transcription factor is closely related to the Saccharomyces cerevisiae zinc-response regulator Zap1 , and we show that expression of three zinc transporter genes depends upon C . albicans Zap1/Csr1 . This observation supports a recent report [11] indicating that the S . cerevisiae and C . albicans Zap1 both regulate zinc-responsive gene expression . However , we also show that Zap1/Csr1 controls genes that influence overall matrix levels . Our results provide a foundation for a mechanistic understanding of matrix production and its regulation .
We have described screens of C . albicans transcription factor gene insertion mutants for defects in biofilm formation [12] . In the course of these screens , we found an insertion mutant that produced a biofilm with a slimy or glistening appearance . The insertion lay in the coding region for ZAP1/CSR1 ( orf19 . 3794 ) . This phenotype was observed for several additional zap1/zap1 insertion mutants as well as a newly created zap1Δ/zap1Δ deletion mutant . This unusual phenotype was complemented by introduction of a wild-type ZAP1 construct into the zap1Δ/zap1Δ mutant , but not by the vector lacking the ZAP1 insert . Therefore , loss of ZAP1 function causes an unusual glistening appearance of in vitro-grown C . albicans biofilms . We examined overall biofilm growth and ultrastructure to explore the nature of this altered biofilm appearance . We detected no difference in biofilm biomass of zap1Δ/zap1Δ mutant and the zap1Δ/zap1Δ+pZAP1 complemented strain or the reference wild-type strain ( Figure 1A ) . Overall biofilm thickness was similar for the zap1Δ/zap1Δ mutant and the zap1Δ/zap1Δ+pZAP1 complemented strain as well ( Figure 2C , 2F ) , as visualized by confocal scanning laser microscopy ( CSLM ) . However , depth views revealed that the mutant hyphae often terminated in yeast-form cells ( Figure 2A , 2B ) . Some of these cells appeared spherical and resembled chlamydospores . Complementation with ZAP1 ( Figure 2D , 2E ) restored an appearance similar to wild-type biofilms in this system [12] . Therefore , Zap1 is required for normal hyphal morphogenesis in biofilms . A glistening appearance can be associated with accumulation of extracellular polymers , as in the case of Staphylococcus biofilms [13] . To see whether matrix might hyperaccumulate in the zap1Δ/zap1Δ strain , we measured biofilm-associated soluble β-1 , 3 glucan . The zap1Δ/zap1Δ strain produced 1 . 5- to 2-fold greater soluble β-1 , 3 glucan in biofilms than the complemented and reference strains ( Figure 1B ) . Planktonic cultures of the strains showed a similar trend but the differences were not statistically significant ( Figure 1C ) . Therefore , in in vitro-grown biofilms , Zap1 is a negative regulator of extracellular soluble β-1 , 3 glucan , a major component of extracellular matrix . In order to determine whether Zap1 may play a role in biofilm formation in vivo , we turned to a rat model for catheter-associated infection [14] . We observed that the zap1Δ/zap1Δ mutant , the zap1Δ/zap1Δ+pZAP1 complemented strain , and the wild-type reference strain all produced substantial biofilms in vivo ( Figure 3B , 3D , 3F ) , as visualized with scanning electron microscopy ( SEM ) . However , the zap1Δ/zap1Δ mutant biofilm had a striking abundance of extracellular material ( Figure 3A ) compared to the control strains ( Figure 3C , 3E ) . Quantitative measurements of serum removed from the catheters indicated that the zap1Δ/zap1Δ mutant produced over 3-fold more soluble β-1 , 3 glucan than the wild-type strain ( Figure 1D ) . Introduction of ZAP1 into the mutant reduced soluble β-1 , 3 glucan production substantially ( Figure 1D ) , as expected from the common phenomenon of partial complementation . These results indicate that Zap1 is a negative regulator of extracellular matrix production in an in vivo biofilm model . In order to understand the connections between Zap1 and matrix production , we performed expression microarrays comparing the zap1Δ/zap1Δ mutant and complemented strain , both grown as biofilms . We found 232 genes that were significantly upregulated in the mutant , and 272 genes that were significantly downregulated genes in the mutant ( Table 1; Dataset S4 , worksheet 2 ) . Several top target genes identified by the expression arrays were verified by northern or quantitative real-time PCR analysis ( Dataset S5 ) . The data indicate that C . albicans Zap1 , like its S . cerevisiae ortholog , is a regulator of zinc homeostasis as the zinc transporter genes ZRT1 , ZRT2 , and ZRT3 are downregulated in the zap1Δ/zap1Δ mutant . Indeed , we found that the zap1Δ/zap1Δ mutant is defective in growth on low-zinc medium ( Dataset S5 ) . That defect arises from reduced expression of zinc transporters , because increased expression of zinc transporter genes ZRT1 or ZRT2 improved growth of the zap1Δ/zap1Δ mutant on low-zinc medium ( Dataset S5 ) . These growth assays confirm findings reported recently by Kim et al . [11] . Several other gene classes are downregulated in the zap1Δ/zap1Δ mutant , including those related to adhesion , aldehyde metabolism , and hyphal development . The connection of adhesion and hyphal formation to biofilm formation is well established; the connection with aldehyde metabolism genes is discussed below . The classes of genes upregulated in the mutant include those related to alcohol dehydrogenase activity , carbohydrate transport , cell wall structure , ergosterol biosynthesis , and glucoamylase activity . The connection of several of these gene classes to biofilm formation is explored below . Finally , we note that the zap1Δ/zap1Δ strain has altered expression of several transcriptional regulatory genes , and these gene products may mediate indirect control of some genes by Zap1 . To identify target genes that are directly regulated by Zap1 , we used genome-wide chromatin immunoprecipitation ( ChIP ) analysis of biofilm cells ( Figure 4; Dataset S6 ) . We found that Zap1 binds directly to the promoters of ZRT1 , ZRT2 , and ZRT3 ( Figure 4A–4C; Dataset S6 ) , thus arguing that Zap1 regulates zinc homeostasis through activation of zinc transporter gene expression . The ZRT1 5′ region is shared with the divergent PRA1 gene , whose S . cerevisiae ortholog ZPS1 is a Zap1 target , so this shared regulatory region may permit Zap1 activation of both ZRT1 and PRA1 ( Figure 4B ) . We also found Zap1 associated with its own ( ZAP1 ) promoter region , as expected if C . albicans Zap1 activates its own expression ( Figure 4F ) . We note that Zap1 autoregulation is well established in S . cerevisiae [15] . Finally , we found Zap1 bound to the promoters of CSH1 and IFD6 ( Figure 4D , 4E ) , whose contribution to biofilm matrix is described below . Although S . cerevisiae Zap1 can function as a repressor [16] , we did not detect C . albicans Zap1 bound to promoter regions of genes identified by microarrays to be repressed including ADH5 , GCA1 , or GCA2 . ( ChipView plots of every significant binding event may be found in Dataset S6 , sheet 3 . ) These genes may be indirectly regulated by Zap1 . It is also formally possible that Zap1 associates with other proteins that mask the epitope in order to function as a repressor; according to this model we would fail to detect genes where Zap1 was bound as a repressor . Overall , our data clearly show that Zap1 directly activates many target genes that function in diverse biological processes . We further investigated several Zap1 target genes that may function in biofilm matrix production ( Table 1 ) . Genes that are downregulated in the zap1Δ/zap1Δ mutant could , in principle , be inhibitors of matrix production; genes that are upregulated in the zap1Δ/zap1Δ mutant could be activators of matrix production . We reasoned that overexpression of matrix inhibitors in the zap1Δ/zap1Δ mutant may cause reduced levels of soluble β-1 , 3 glucan . To test this idea , we introduced highly expressed TDH3 promoter sequences to replace promoter regions of the following target genes: ZRT2 , ZRT1 , PRA1 , CSH1 , and IFD6 . We confirmed their overexpression through qPCR assays in the zap1Δ/zap1Δ transformants ( Dataset S5 ) . We observed that both TDH3-CSH1 and TDH3-IFD6 caused a significant decrease in soluble β-1 , 3 glucan levels produced by in vitro biofilms ( Figure 5A ) , whereas the other constructs produced no significant differences . To survey candidate activators of matrix production , we overexpressed selected genes in a wild-type ( ZAP1/ZAP1 ) background . Once again , we used the TDH3 promoter to replace promoter regions of target genes YWP1 , orf19 . 3499 , HXT5 , GCA1 , GCA2 , HGT2 , and ADH5 , and used qPCR to confirm overexpression ( Dataset S5 ) . We observed that TDH3-GCA1 , TDH3-GCA2 , and TDH3-ADH5 , but not the other constructs , significantly increased soluble β-1 , 3 glucan levels produced by in vitro biofilms ( Figure 5A ) . These results support the idea that specific Zap1 target genes can modulate biofilm matrix levels in vitro . To test target gene function in vivo , we turned to the rat catheter infection model . We measured biofilm-associated soluble β-1 , 3 glucan levels after biofilm formation by the strains that had displayed altered glucan levels in vitro . The general effects on soluble β-1 , 3 glucan of each TDH3-target gene during biofilm culture in vivo paralleled those measured in vitro ( Figure 5B ) , though the magnitudes of the effects were typically greater in vivo . These findings indicate that Csh1 and Ifd6 are inhibitors of matrix production , and that Gca1 , Gca2 , and Adh5 are activators of matrix production .
C . albicans Zap1 , like its S . cerevisiae ortholog , has a critical role in zinc metabolism . Genes activated by C . albicans Zap1 include putative plasma membrane zinc transporter genes ZRT1 and ZRT2 as well as the putative vacuolar zinc transporter gene ZRT3 . Both homology and functional analysis indicates that these genes are connected to zinc acquisition ( [11] and this report ) . Thus the connection of Zap1 to zinc metabolism is clear . Interestingly , the conserved Zap1 circuit encompasses many additional genes , as indicated by comparison of Zap1-responsive genes in our dataset with their S . cerevisiae orthologs and best hits [18] . Conserved Zap1-responsive genes extend beyond zinc transporter genes ( Figure 6; Dataset S4 , worksheet 3 ) to include such Zap1-activated genes as PRA1 , DPP1 , HSP30 , LAP3 , STE23 , CSH1 , and IFD6 . Conserved Zap1-repressed genes include ADH5 and orf19 . 3352 , among many more ( Figure 6 ) . The extent of conservation may be underestimated because of the different growth conditions employed for the two organisms , and the fact that the S . cerevisiae Zap1 regulon varies with conditions of zinc limitation [19] . Some of these gene products are known or predicted to be zinc metalloenzymes , such as Ste23 , and their increased expression in zap1 mutants may reflect a homeostatic response to reduced enzyme activity . However , the relationship of many of conserved Zap1-dependent genes to zinc acquisition or metabolism is not well understood . We note in particular that the secreted metalloprotease homolog Pra1 , the ortholog of S . cerevisiae Zps1 , is also closely related to the Aspergillus fumigatus antigen ASPF2 ( 44% identity over 294 amino acid residues ) , which is induced under low zinc conditions [20] . Thus the Zap1 regulon may be broadly conserved among fungi . Genes with conserved Zap1 responsive regulation in fungi with distinct environmental niches might be considered priorities for further study in relationship to zinc metabolism . Conversely , species-specific responses may provide insight into unique features of each zinc-limited niche . MEME analysis of direct Zap1 target genes has identified two potential Zap1 binding motifs , ACCTTGGTGGTTA and TAGTGGTTAT ( motifs 1 and 2 , respectively , in Dataset S6 , worksheet 2 ) , which are similar to each other . RSAT analysis points to enriched 8-mers TAATGGTG and ATGGTGGT in these 5′ regions , which closely resemble the MEME sites . All are similar to the known S . cerevisiae Zap1 binding motif , ACCTTNAAGGT [21] , [22] , particularly because the greatest specificity is for the motif ends ACC and GGT [23] . C . albicans biofilm growth is associated with overall upregulation of ergosterol biosynthesis [24] as well as increased resistance to antifungals that target ergosterol [7] , [25] . It is striking that almost all ergosterol biosynthetic genes are regulated oppositely by Zap1 in C . albicans and S . cerevisiae ( Figure 6 [green squares]; Dataset S4 , worksheet 3 ) . ERG genes are largely downregulated in the S . cerevisiae zap1Δ mutant; in other words , ScZap1 is formally a positive regulator of ScERG genes . This relationship has functional consequences , because a S . cerevisiae zap1Δ/ZAP1 heterozygous diploid is hypersensitive to ergosterol biosynthetic inhibitors [26] . In contrast , ERG genes are largely upregulated in the C . albicans zap1Δ/zap1Δ mutant , thus CaZap1 is formally a negative regulator of CaERG genes . Zap1 may govern their expression indirectly , because they lack clear ZREs and were not bound by Zap1 in our ChIP analysis . This difference in ERG gene regulation may reflect the distinct niches sampled for microarray analysis: S . cerevisiae cells were grown aerobically [18]; our C . albicans cells were grown in biofilms , which are substantially anaerobic [27] . It is well established that ERG gene expression responds to oxygen levels [28] , a reflection of the heme requirement for ergosterol synthesis . The apparently opposite roles of Zap1 in ERG gene regulation in the two organisms may arise from the difference in growth conditions . In any event , for C . albicans biofilms , perhaps a decline in Zap1 activity during biofilm growth may be the cause of increased ergosterol biosynthetic gene expression in biofilms . In principle , Zap1 might have influenced matrix production indirectly , as a consequence of poor growth or zinc limitation . However , overexpression of ZRT1 or ZRT2 improves zinc-limited growth of the zap1Δ/zap1Δ mutant but has no effect on matrix production . These findings indicate that it is altered Zap1 target gene expression , rather than other effects of zinc limitation , that stimulates matrix production in the zap1Δ/zap1Δ mutant . Our target gene overexpression studies point to two classes of matrix biogenesis functions: Csh1 and Ifd6 inhibit matrix production; Gca1 , Gca2 , and Adh5 promote matrix production . The role of Gca1 and Gca2 in matrix production is probably direct . They are predicted extracellular glucoamylases; the extracellular localization of Gca1 has been confirmed by biochemical isolation [29] . Glucoamylases convert long-chain polysaccharides into smaller-chain polysaccharides . Therefore , we propose that Gca1 and Gca2 promote matrix production by hydrolytic release of soluble β-1 , 3 glucan fragments , perhaps from biofilm cell walls , from exported glucan polymers that are not attached to cell walls , or from debris of lysed cells . The roles of Csh1 , Ifd6 , and Adh5 may be more complex . All three are predicted alcohol dehydrogenases . One simple possibility is that they affect matrix production through their impact on carbon metabolism . For example , Adh5 may promote entry of ethanol into the TCA cycle for energy or via the glyoxylate shunt to provide hexose for β-1 , 3 glucan synthesis . Ethanol is known to accumulate in mature biofilms [30] and thus may serve as a potential source of carbon . However , this explanation does not readily account for the fact that Adh5 stimulates matrix production , whereas Csh1 and Ifd6 inhibit matrix production . A second model is based upon the roles of alcohol dehydrogenases in the Ehrlich pathway [31] . This pathway permits nitrogen assimilation from amino acids , yielding α-keto acids that must be reduced to acyl and aryl alcohols for secretion . Such alcohols have profound roles in quorum sensing and cell signaling . One aryl alcohol , tyrosol , accumulates during biofilm maturation and functions to stimulate hyphal growth [32] , [33] . The acyl alcohol farnesol also accumulates during biofilm maturation [34] and inhibits hyphal growth and biofilm formation [35]–[37] . Additional complex alcohols that inhibit hyphal growth also accumulate in C . albicans biofilms during maturation [34] . With these studies as backdrop , a simple model is that Csh1 , Ifd6 , and Adh5 catalyze the final reductive step in the biogenesis of biofilm-associated acyl and aryl alcohols , and these alcohols act as signals to govern matrix synthesis . The apparently opposite effects of these gene products on matrix production may be related to substrate specificity: Csh1 and Ifd6 may act preferentially to yield a matrix inhibitory signal; Adh5 may act preferentially to yield a matrix stimulatory signal . The idea that Zap1 governs quorum-sensing molecule synthesis explains the unexpected cell morphology observed in zap1Δ/zap1Δ mutant biofilms . Specifically , we observed an excess of yeast-form cells along with some unusually round cells that resemble chlamydospores . Consistent with the apparent accumulation of yeast-form cells , we note that the zap1Δ/zap1Δ mutant shows upregulation of yeast-specific gene YWP1 and downregulation of hyphally induced genes HWP1 , RBT1 , HYR1 , and IHD1 ( Figure 6 ) . Growth of yeast-form cells and chlamydospores is promoted by the quorum-sensing molecule farnesol [35] , [38] , [39] . However , there has been thus far no clear connection between quorum-sensing molecules and biofilm matrix . Although this connection is speculative at present , we note that it makes testable predictions; in particular , that accumulation of specific acyl and aryl alcohols will be modulated by Zap1 and by these alcohol dehydrogenases . Similarly , it predicts that other defects in biogenesis of Ehrlich pathway precursors will modulate matrix production . The unexpected connection of C . albicans Zap1 to matrix production raises the question of whether the relevant target genes are part of the conserved Zap1 regulon . We find that three of the genes are ( Figure 6 ) : C . albicans CSH1 and IFD6 share the S . cerevisiae best hit YPL088W; C . albicans ADH5 has the S . cerevisiae best hit ADH5 . All of these genes are under Zap1 control in the respective organisms . On the other hand , GCA1 and GCA2 share the S . cerevisiae best hit ROT2 , which is not significantly responsive to S . cerevisiae Zap1 under conditions examined [18] . These findings indicate that a focus limited either to conserved or novel Zap1-responsive genes would have revealed some functional targets and overlooked others . The zap1Δ/zap1Δ mutant produces a biofilm with exaggerated features of mature biofilms . We have focused here on the abundance of matrix , but there are other such features as well . For example , the mutant biofilm hyphal layer includes an apparent excess of yeast-form cells , which may be induced in mature biofilms by accumulation of quorum-sensing molecules [4] , [32] , [34] to facilitate biofilm dispersal . The upregulation of ERG genes and hexose transporter genes in the mutant are other features in common with mature biofilms [24] . A simple working hypothesis is that Zap1 functions as a negative regulator of biofilm maturation ( Figure 7 ) . We suggest that a decline in Zap1 activity during biofilm development may occur during the natural process of biofilm maturation to bring about these characteristic biological features .
C . albicans strains were grown at 30°C in either YPD ( 2% Bacto peptone , 2% dextrose , 1% yeast extract ) for Ura+ strains or in YPD+uri ( 2% Bacto peptone , 2% dextrose , 1% yeast extract , and 80 µg/ml uridine ) for Ura− strains . Transformants were selected for on synthetic medium ( 2% dextrose , 6 . 7% Difco yeast nitrogen base with ammonium sulfate and auxotrophic supplements ) or on YPD+clonNAT400 ( 2% Bacto peptone , 2% dextrose , 1% yeast extract , and 400 µg/ml nourseothricin [clonNAT , WERNER BioAgents] ) for nourseothricin-resistant isolates . Growth on low-zinc medium was assayed with synthetic medium lacking added zinc ( 2% dextrose , 1 . 7% yeast nitrogen base without ammonium sulfate and without zinc sulfate , 0 . 2% ammonium sulfate , 2 . 5 µM EDTA , and auxotrophic supplements ) . To obtain nourseothricin-sensitive isolates having flipped out the SAT1 marker , nourseothricin-resistant transformants were grown for 8–12 h in YPD liquid medium , plated at a low cell density of 200 cells/plate on YPD+clonNat25 ( 2% Bacto peptone , 2% dextrose , 1% yeast extract , and 25 µg/ml nourseothricin [clonNAT , WERNER BioAgents] ) , and allowed to grow for 24 h at 30°C as previously described [40] with the defined modifications . Biofilms for visualization were grown using Spider medium [41] . Supernatants collected for β-1 , 3 glucan measurements were grown in suspension or as biofilms in RPMI-MOPS medium for 12 h at 37°C , as described previously [10] . All C . albicans strains used in this study are listed in Dataset S1 . Reference strain DAY185 has been described [42] . Newly constructed C . albicans strains were derived from BWP17 [43] . Primer sequences are listed in Dataset S2 . All genotypes were verified by colony PCR using corresponding detection primers ( Dataset S2 ) . Construction of CJN1091 ( zap1/zap1 ) was made by PCR product-directed gene deletion [43] with 120-mer oligonucleotides CSR1null-5DR and CSR1null-3DR via consecutive rounds of transformation into BWP17 . For gene complementation , PCR was used to generate a fragment for ZAP1 from 1 , 000 bp upstream of the start codon to 500 bp downstream of the stop codon . This fragment was inserted into pGEMT-Easy ( Promega ) , digested with NgoMIV and AlwNI , and subsequently inserted by in vivo recombination in S . cerevisiae into NotI- and EcoRI-digested HIS1 vector pDDB78 [44] , yielding plasmid pCJN517 . The complemented strain CJN1193 was made by transforming CJN1091 with NruI-digested pCJN517 , directing integration to the HIS1 locus . The zap1/zap1 mutant strain was made His+ by transforming CJN1091 with NruI-digested pDDB78 to yield strain CJN1201 . The NAT1-TDH3 promoter plasmid pCJN542 [45] was used for gene overexpression . The TDH3-IFD4 overexpression strain CJN1680 was constructed by transforming CJN1201 , the zap1/zap1 mutant , using PCR products from template plasmid pCJN542 and primers IFD4-F-OE-Ag-NAT-Ag-p-CJN and IFD4-R-OE-Ag-NAT-Ag-TDH3p-CJN . These primers amplify the entire Ashbya gossypii TEF1 promoter , the C . albicans NAT1 open reading frame , the A . gossypii TEF1 terminator , and the C . albicans TDH3 promoter with 100 bp of hanging homology to 500 bp upstream into the promoter of IFD4 for the forward primer and 100 bp of hanging homology from exactly the start codon of IFD4 . The homology in these primers allows for homologous recombination of the entire cassette directly upstream of the natural locus of IFD4 so that its expression is driven by the TDH3 promoter instead of its natural promoter . By the same method , primers IFD6-F-OE-Ag-NAT-Ag-p-CJN and IFD6-R-OE-Ag-NAT-Ag-TDH3p-CJN were used for overexpression of IFD6 to produce strain CJN1631; ZRT2-F-OE-Ag-NAT-Ag-TEF1p and ZRT2-R-OE-Ag-NAT-Ag-TDH3p-CJN for overexpression of ZRT2 to produce strain CJN1655; ZRT1-F-OE-Ag-NAT-Ag-TEF1p-CJN and ZRT1-R-OE-Ag-NAT-Ag-TDH3p-CJN for overexpression of ZRT1 to produce strain CJN1651; and PRA1-F-OE-Ag-NAT-Ag-p-CJN and PRA1-R-OE-Ag-NAT-Ag-TDH3p-CJN for overexpression of PRA1 to produce strain CJN1623 . The TDH3-19 . 4899 overexpression strain CJN1638 was constructed by transforming DAY185 , the wild-type reference strain , using PCR products from template plasmid pCJN542 and primers 4899-F-OE-Ag-NAT-Ag-p-CJN and 4899-R-OE-Ag-NAT-Ag-TDH3p-CJN . By the same method , primers 999-F-OE-Ag-NAT-Ag-p-CJN and 999-R-OE-Ag-NAT-Ag-TDH3p-CJN were used for overexpression of ORF19 . 999 to produce strain CJN1675; ADH5-F-OE-Ag-NAT-Ag-p-CJN and ADH5-R-OE-Ag-NAT-Ag-TDH3p-CJN for overexpression of ADH5 to produce strain CJN1642; YWP1-F-OE-Ag-NAT-Ag-p-CJN and YWP1-R-OE-Ag-NAT-Ag-TDH3p-CJN for overexpression of YWP1 to produce strain CJN1659; 3499-F-OE-Ag-NAT-Ag-p-CJN and 3499-R-OE-Ag-NAT-Ag-TDH3p-CJN for overexpression of ORF19 . 3499 to produce strain CJN1633; 4384-F-OE-Ag-NAT-Ag-p-CJN and 4384-R-OE-Ag-NAT-Ag-TDH3p-CJN for overexpression of HXT5 to produce strain CJN1663; and HGT2-F-OE-Ag-NAT-Ag-p-CJN and HGT2-R-OE-Ag-NAT-Ag-TDH3p-CJN for overexpression of HGT2 to produce strain CJN1667 . Transformation into C . albicans strains and selection on YPD+clonNAT400 plates has been described [46] . Integration of the constructs was verified by colony PCR with a gene-specific forward detection primer ( for example primer IFD4-OE-F-det-CJN for the IFD4 gene ) , annealing to a sequence within the promoter of each gene and the reverse primer Nat-OE-R-det2-CJN annealing to a sequence found in the NAT gene . The C-terminal myc-tagging plasmid pADH34 ( Dataset S3 ) , containing a 13myc epitope tag immediately preceding the SAT1-flipper cassette ( 34-bp FLP recombination target sequence [FRT] , followed by the C . albicans MAL2 promoter , followed by a C . albicans-adapted FLP gene , followed by a C . albicans ACT1 terminator sequence , followed by the C . albicans-adapted SAT1 marker gene , followed by another 34-bp FRT sequence ) , was constructed as follows . PCR was done using template pFA6a-13myc-kanMX6 [47] and primers AHO276 and AHO277 to generate a 568-bp product containing a 13myc epitope tag and linker sequences with flanking XhoI sites . This fragment was ligated into the unique XhoI site of the SAT1-flipper cassette plasmid , pSFS2A [40] , yielding plasmid pADH34 . The C-terminal tagged nourseothricin-resistant Zap1-myc strains , CJN1684 and CJN1685 , were constructed by transforming DAY185 , the reference strain , using PCR products from template plasmid pADH34 and primers 3794MycFnostop-CJN and 3794MycRUTR-CJN . These primers amplify the entire 13myc epitope tag and complete SAT1 flipper cassette with 65 bp of hanging homology to the ZAP1 ORF minus its stop codon for the forward primer and 65 bp of hanging homology to the ZAP1 UTR precisely downstream of the stop codon for the reverse primer . The homology in these primers allows recombination of the entire 13myc epitope tag and complete SAT1 flipper cassette directly downstream of the ZAP1 ORF , lacking its natural stop codon , so that the ZAP1 ORF contains a C-terminal 13myc epitope tag translational fusion . Correct integration of the C-terminal 13myc epitope tag and SAT1 flipper was verified by colony PCR using detection primers 3794detFUpMyctag-CJN and AHO300 to check the upstream integration and 3794detRDownMyctag-CJN and AHO301 to check the downstream integration . The C-terminal tagged nourseothricin-sensitive Zap1-myc strains , CJN1688 and CJN1694 , were constructed by flipping out the SAT1 cassette from strains CJN1684 and CJN1685 , respectively , as described previously [40] . The following primer pairs were used in colony PCR to confirm the clean “flipping out” of the SAT1-flipper cassette: 3794detFUpMyctag-CJN and AHO300 , and 3794detRDownMyctag-CJN and AHO302 . The 13myc epitope tag and the region of homology to the 3′ end of ZAP1 used for integration of the SAT1-flipper cassette was confirmed by sequencing the colony PCR product generated using primers 3794detFUpMyctag-CJN and AHO283 . In vitro biofilm growth assays were carried out in Spider medium and visualized by CSLM as described previously [12] . Biomass measurements were determined for four independent silicone samples as described previously [46] . A rat central-venous-catheter infection model , as described previously [14] , was selected for our in vivo biofilm studies . We removed catheters from the rats at 24 h after C . albicans infection to determine biofilm development on the internal surface of the intravascular devices . The distal 2 cm of the catheter was cut from the entire catheter length , and biofilms were imaged by SEM at 50× and 1 , 000× magnification , as described previously [9] . Cultures were grown on silicone disks or in suspension in RPMI medium , as described above . Culture supernatants from C . albicans in vitro biofilm and planktonic cells were collected at 12 h for glucan measurements . Viable cell burdens were determined using plate counts to ensure the cultures contained similar number of cells . Supernatants were centrifuged at 3 , 000g for 10 min , and were stored at −20°C until glucan analysis . Glucan concentrations were determined using the commercially available Glucatell ( 1 , 3 ) -β-D-Glucan Detection Reagent kit ( Associates of Cape Cod ) according to manufacturer's directions . Four in vitro glucan assay replicates were performed for each sample . Statistical significance ( p-values ) was determined with a Student's t-test . After 12 h of growth in the in vivo biofilm model , serum was collected from the venous catheter . Serum samples were frozen at −20°C until glucan analysis . β-1 , 3 glucan was measured in the serum using the Fungitell ( 1 , 3 ) -β-D-Glucan Detection Reagent kit ( Associates of Cape Cod ) according to manufacturer's directions . Three in vivo glucan assay replicates were performed for each rat catheter . Statistical significance ( p-values ) was determined with a Student's t-test . Viable cell burdens were measured by harvesting kidneys at the end of the experiment as an estimation of total-body organ burden . Biofilms for expression microarray analysis were grown in Spider medium at 37°C without silicone squares . Instead , the bottom of a six-well polystyrene plate was used as a substrate for biofilm growth in order to maximize the efficiency of harvesting cells for RNA extraction . We find that one six-well plate containing biofilms for one strain yields sufficient RNA for expression microarray analysis . Similar to the silicone square method [12] , the bottom of the six-well plates were pretreated overnight in 4 ml bovine serum ( Gibco ) , and placed at 37°C with 200-rpm agitation in a thermostatic Elmi shaker . Concurrently , standard overnight cultures of the strains of interest were inoculated in YPD medium at 30°C with shaking . The following day , the six-well plates were washed with PBS , 4 ml Spider medium was added to each well , and the overnight culture was added to each well in order to obtain a starting OD600 in the 4 ml Spider well volume of 0 . 5 . Cell adherence was done for 90 min by placing the six-well plates at 37°C with 200-rpm agitation in the Elmi shaker . After the cell adherence step , the six-well plates were washed with PBS , and 4 ml of fresh Spider medium was added to the wells . Biofilms were grown for 48 h at 37°C with 200-rpm agitation in the Elmi shaker . Biofilms were harvested by scraping the bottoms of the six-well plates with a cell scraper , and combining the biofilm slurry of the same strain from each well of one six-well plate in a 50-ml conical tube . Biofilm cells were then centrifuged at 3 , 000g for 5 min , and RNA was extracted using the RiboPure-Yeast RNA kit ( Ambion , number AM1926 ) according to the manufacturer's instruction . We find that this kit yields the cleanest , most stable , and highest quality and quantity of RNA compared with the hot phenol method for extraction of RNA from a C . albicans biofilm . Northern analysis was performed as described previously [12] to verify the expression levels of ZAP1 , ZRT2 , and ZRT1 using the primers ZAP1-FNor and ZAP1-RNor for ZAP1 , ZRT2-FNor and ZRT2-RNor for ZRT2 , and ZRT1-FNor and ZRT1-RNor for ZRT1 . For quantitative real-time reverse transcription-PCR ( qPCR ) analysis , 10 µg of total RNA was DNase-treated at 37°C for 1 h using the DNA-free kit ( Ambion ) , cDNA was synthesized using the AffinityScript multiple temperature cDNA synthesis kit ( Stratagene ) , and qPCR was done using the iQ SYBR Green Supermix ( Bio-Rad ) as previously described [45] using the primers ZRT2-FqRTPCR and ZRT2-RqRTPCR for ZRT2 , ZRT1-FqRTPCR and ZRT1-RqRTPCR for ZRT1 , PRA1-FqRTPCR and PRA1-RqRTPCR for PRA1 , IFD4-FqRTPCR and IFD4-RqRTPCR for IFD4 , IFD6-FqRTPCR and IFD6-RqRTPCR for IFD6 , ZAP1-FqRTPCR and ZAP1-RqRTPCR for ZAP1 , YWP1-FqRTPCR and YWP1-RqRTPCR for YWP1 , 3499-FqRTPCR and 3499-RqRTPCR for ORF19 . 3499 , HXT5-FqRTPCR and HXT5-RqRTPCR for HXT5 , 4899-FqRTPCR and 4899-RqRTPCR for ORF19 . 4899 , 999-FqRTPCR and 999-RqRTPCR for ORF19 . 999 , HGT2-FqRTPCR and HGT2-RqRTPCR for HGT2 , and ADH5-FqRTPCR and ADH5-RqRTPCR for ADH5 . The iCycler iQ detection system ( Bio-Rad ) was used with the following program: initial denaturation at 95°C for 5 min , followed by 40 cycles of 95°C for 45 s , 58°C for 30 s , and 72°C for 30 s . Amplification specificity was determined by melting curve analysis . Bio-Rad iQ5 software was used to calculate normalized gene expression values using the ΔΔCt method , using TDH3 as a reference gene . For ease of interpretation , the reference strain expression level values were set to 1 . 0 for each gene set , and the normalized expression of each gene relative to TDH3 expression is shown . Results are the means of three determinations . Transcription expression profiling using long-oligonucleotide microarrays was performed as previously described [48] . Briefly , 10 µg of total biofilm RNA was DNase-treated at 37°C for 1 h using the DNA-free kit ( Ambion ) , and cDNA was synthesized using the AffinityScript multiple temperature cDNA synthesis kit ( Stratagene ) . We performed four individual hybridization experiments from four pairs of independently produced RNA samples of CJN1201 , the zap1/zap1 mutant strain versus CJN1193 , the zap1/zap1+pZAP1 strain . LOWESS normalization and statistical analysis of the data were conducted in GeneSpring GX version 7 . 3 ( Agilent Technologies ) . Data are reported in Dataset S4 . A volcano-plot algorithm was used to identify genes that exhibited statistical significance ( p<0 . 05 ) with a change in transcript abundance of at least 1 . 5-fold . The results of this analysis with adjusted p<0 . 05 are listed in Dataset S4 ( worksheet 2 ) . The ChIP–chip tiling arrays were designed by tiling 181 , 900 probes of 60-bp length across 14 . 3 Mb included in the C . albicans Assembly 20 genome ( http://www . candidagenome . org/ ) , as previously described [49] . The Zap1 myc-tagged strains CJN1688 and CJN1694 and the untagged reference strain DAY185 were grown under the same biofilm-inducing conditions as the strains grown for expression microarray analysis , described above . We found that one six-well plate per strain yielded sufficient starting material to complete a single ChIP–chip experiment . Biofilms were harvested by scraping the bottoms of the six-well plates with a cell scraper , and combining the biofilm slurry of the same strain from each well of one six-well plate in a 50-ml conical tube . Formaldehyde was added to the biofilm slurry to a final concentration of 1% , and the treated biofilm cultures were mixed on a platform shaker for 15 min at room temperature . Glycine was then added to a final concentration of 125 mM , and the treated cultures were mixed for another 5 min at room temperature on the platform shaker . The following cell lysis and ChIP–chip methods were adapted from previously described protocols [49] , [50] . Cells were collected by centrifugation at 4°C for 10 min at 3 , 000g , washed twice in 10 ml ice cold TBS ( 20 mM TrisHCl [pH 7 . 6] , 150 mM NaCl ) , and the pellets frozen in liquid nitrogen prior to cell lysis . Cell lysis and shearing of DNA were done by resuspending the pellets in 700 µl lysis buffer ( 50 mM HEPES/KOH [pH 7 . 5] , 140 mM NaCl , 1 mM EDTA , 1% Triton X-100 , 0 . 1% Na-Deoxycholate ) supplemented with complete protease inhibitor cocktail tablets ( Roche ) . The cell suspension was vortexed at 4°C for 4 h in the presence of 0 . 5-mm acid-washed glass beads , and the lysate was collected . Chromatin was sheared by sonication in a Bioruptor water bath sonicator ( settings: 1×15 min , 30 s on , 1 min off ) at 4°C , the sheared lysate was centrifuged at 12 , 000g for 10 min at 4°C , and the supernatant was collected . 50 µl of extract was added to 200 µl TE/1% SDS , and stored at −20°C as the ChIP input material . For chromatin IPs , 300 µl of the crude lysate was added to 200 µl lysis buffer , and 10 µl of mouse monoclonal antihuman c-myc antibody ( Biosource , number AHO0062 ) was added to the mixture . Extract plus antibody was incubated overnight at 4°C , with agitation . The following day , 50 µl of a 50% suspension of protein G-Sepharose Fast-Flow beads ( Sigma ) in lysis buffer was added and incubated 2 h at 4°C , with agitation . The beads were pelleted for 1 min at 1 , 000g , the supernatant removed , and the beads washed 5 min at room temperature with ice-cold buffers as follows: twice in lysis buffer , twice in high salt lysis buffer ( 50 mM HEPES-KOH [pH 7 . 5] , 500 mM NaCl , 1 mM EDTA , 1% Triton X-100 , 0 . 1% sodium deoxycholate ) , twice in wash buffer ( 10 mM Tris-HCl [pH 8 . 0] , 250 mM LiCl , 0 . 5% NP-40 , 0 . 5% sodium deoxycholate , 1 mM EDTA ) , and once in TE ( 10 mM Tris , 1 mM EDTA [pH 8 . 0] ) . After the last wash , 110 µl of elution buffer ( 50 mM Tris/HCl [pH 8 . 0] , 10 mM EDTA , 1% SDS ) was added to each sample , and the beads were incubated at 65°C for 10 min with periodic agitation . The beads were spun for 30 s at 10 , 000g at room temperature , and 100 µl of the supernatant was stored . A second elution was carried out with 150 µl elution buffer 2 ( TE , 0 . 67% SDS ) , and eluates from the two elution steps were pooled ( 250 µl final volume ) . Both the ChIP and input samples were incubated overnight at 65°C , and cooled at room temperature . For cleaning the IPed DNA , 250 µl proteinase K solution ( TE , 20 µg/ml glycogen , 400 µg/ml Proteinase K ) was added to each sample , and samples were incubated at 37°C for 2 h . 55 µl 4 M LiCl was added to each , and the samples were extracted once with 450 µl phenol/chloroform/isoamyl alcohol solution ( 25∶24∶1 ) . 1 ml ice cold 100% ethanol was added and the DNA was precipitated overnight at −20°C . The DNA was pelleted by centrifugation at 12 , 000g for 30 min at 4°C , washed once with ice cold 70% ethanol , and the pellets air dried . IP samples were resuspended in 25 µl TE , and input samples were resuspended in 100 µl TE+100 µg/ml RNaseA and incubated 1 h at 37°C . ChIP-enriched DNA was amplified , fluorescently labeled , hybridized , and washed as described in detail in Dataset S7 . Labeled DNA for each channel was combined and hybridized to arrays in Agilent hybridization chambers for 40 h at 65°C , according to the manufacturer's instructions ( Agilent Technologies ) . Arrays were scanned using Genepix 4000A Axon Instrument scanner . Analysis and identification of the binding events in the ChIP–chip data were determined as previously described [49] using Agilent Chip Analytics software v1 . 2 ( Agilent Technologies ) . These binding events were displayed and analyzed using ChipView v0 . 954 ( http://johnsonlab . ucsf . edu/ ) . 250 bp centered on the midpoint of the peaks in the promoter regions bound by Zap1 were submitted to MEME v3 . 5 . 7 ( http://meme . nbcr . net ) for motif analysis [51] using the following parameters: minw = 7 , maxw = 25 , nmotifs = 10 , maxsize = 50 , 000 , mod = zoops . We also analyzed bound regulatory regions with the RSAT server , http://rsat . scmbb . ulb . ac . be/rsat/ , using 1 , 500 bp of 5′ region sequence and a search for 8 bp motifs [52] .
|
A biofilm is a surface-associated population of microbes that is embedded in a cement of extracellular compounds . This cement is known as matrix . The two main functions of matrix are to protect cells from their surrounding environment , preventing drugs and other stresses from penetrating the biofilm , and to maintain the architectural stability of the biofilm , acting as a glue to hold the cells together . The presence of matrix is a contributing factor to the high degree of resistance to antimicrobial drugs observed in biofilms . Because biofilms have a major impact on human health , and because matrix is such a pivotal component of biofilms , it is important to understand how the production of matrix is regulated . We have begun to address this question in the major human fungal pathogen Candida albicans . We found that the zinc-responsive regulatory protein Zap1 controls the expression of several genes important for matrix formation in C . albicans . These target genes encode glucoamylases and alcohol dehydrogenases , enzymes that probably govern the synthesis of distinct matrix constituents . The findings here offer insight into the metabolic processes that contribute to biofilm formation and indicate that Zap1 functions broadly as a negative regulator of biofilm maturation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Material",
"and",
"Methods"
] |
[
"infectious",
"diseases/fungal",
"infections",
"genetics",
"and",
"genomics/gene",
"function",
"microbiology/microbial",
"growth",
"and",
"development"
] |
2009
|
Biofilm Matrix Regulation by Candida albicans Zap1
|
Forkhead box P3 ( Foxp3+ ) regulatory T ( Treg ) -cell function is controlled by environmental cues of which cytokine-mediated signaling is a dominant component . In vivo , interleukin-4 ( IL-4 ) -mediated signaling via IL-4 receptor alpha ( IL-4Rα ) mediates Treg cell transdifferentiation into ex-Foxp3 T helper 2 ( Th2 ) or T helper 17 ( Th17 ) cells . However , IL-4-mediated signaling also reinforces the Foxp3 Treg compartment in vitro . We generated Foxp3-specific IL-4Rα-deficient mice and demonstrated differential efficiency of IL-4Rα deletion in male ( approximately 90% ) and female ( approximately 40% ) animals , because of cyclic recombinase ( Cre ) -mediated X-linked foxp3 inactivation . Irrespective of the degree of IL-4Rα deletion within the Foxp3+ Treg cell population , mice showed exacerbation of immune effector responses with aggravated tissue pathology in tissue-dwelling helminth infections ( Schistosoma mansoni or Nippostrongylus brasiliensis ) . Mechanistically , IL-4Rα deletion in males and females led to a reduced expression of Foxp3 and subsequently an impaired accumulation of Foxp3+ Treg cells to inflamed tissues . In-depth cellular typing by flow cytometry revealed that the impairment of IL-4Rα-mediated signaling during helminth infections decreased the ability of central Treg cells to convert into effector Treg ( eTreg ) cells and caused a significant down-regulation of markers associated with Treg cell migration ( C-X-C motif chemokine receptor 3 [CXCR3] ) and accumulation in inflamed tissues ( GATA binding protein 3 [GATA3] ) as well as survival ( B cell lymphoma 2 [Bcl-2] ) . These findings unprecedentedly , to our knowledge , uncover a role for IL-4Rα signaling in the positive regulation of Foxp3+ Treg cell function in vivo . Complementing our past knowledge on a widely reported role for IL-4Rα signaling in the negative regulation and transdifferentiation of Foxp3+ Treg cells in vivo , our present findings reveal the host requirement for an intact , but not reduced or potentiated , IL-4Rα-mediated signaling on Foxp3+ Treg cells to optimally control inflammation during helminth infections .
Regulatory T ( Treg ) cells , the central component in the regulation of the immune system , play a pivotal role in the maintenance of self-tolerance and immune homeostasis [1] . Research on the molecular bases of Treg cells’ function has revealed the X-linked transcription factor forkhead box P3 ( Foxp3 ) as uniquely expressed in Treg cells . How Foxp3+ Treg cells are regulated is a critical question yet to be fully explored . Growing evidence has established that Foxp3+ Treg cell function is greatly affected by the integrity of their receptors and the cytokines available in the milieu . Our knowledge of the intricacies of such regulation has now considerably expanded . Cytokines such as interleukin-2 ( IL-2 ) , interleukin-15 ( IL-15 ) [2–4] , interferon gamma ( IFN-γ ) [5 , 6] , interleukin-12 ( IL-12 ) [7] , interleukin-6 ( IL-6 ) [8 , 9] , and interleukin-4 ( IL-4 ) [10–15] have been reported to provide critical signals in the modulation of Treg cells’ development and function . IL-4 , the canonical cytokine defining Type 2 immune responses , signals through the IL-4 receptor alpha ( IL-4Rα ) to mitigate Treg cell function during Type 2 diseases [16 , 17] . Recent reports have shown that augmentation of IL-4Rα signaling through gain-of-function mutation [14 , 15] or chronic Type 2 inflammation [18] leads to a drastic reduction in Foxp3+ Treg cell population and impairment of Treg cell suppressive function , which in turn drive their reprogramming toward T helper 2 ( Th2 ) -like or T helper 17 ( Th17 ) -like cells [14 , 15 , 18] , favoring the notion of an inhibitory role for this receptor in Treg cell function . However , treatment of cluster of differentiation 4 ( CD4 ) + cluster of differentiation 25 ( CD25 ) + Treg cells in vitro with IL-4 has been shown to have an antiapoptotic role , an augmentation of the rate of Foxp3 expression , and potentiation of Foxp3+ Treg cell suppressive function [10] , suggesting an unappreciated supporting role for IL-4Rα-mediated signaling in Foxp3+ Treg cell function in vitro yet to be validated in vivo . In the present study , we show that Foxp3+ Treg cells in secondary lymphoid organs constitutively express IL-4Rα and up-regulate the receptor expression upon S . mansoni ( Sm ) infection . We provide evidence that either 40% or 90% of deletion of the IL-4 receptor specifically within the Foxp3+ Treg cell population leads to aggravated tissue inflammation during helminth infections ( Sm and N . brasiliensis [Nb] infections ) and that this occurs as a result of a weakened Foxp3+ Treg cell compartment paralleled by an uncontrolled effector T-cell compartment . Adding to previous reports that have defined a restraining role for IL-4Rα on Foxp3+ Treg cells in vivo , we now present complementary evidence indicating that this receptor is equally needed , in full , in vivo for Foxp3+ Treg cell ability to control inflammation during helminth infections .
IL-4Rα-mediated signaling and associated factors critically mediating the function of Th2 cells were recently shown to play an important role in controlling Foxp3+ Treg cell function [10 , 12 , 14 , 15 , 18–20] . However , whether IL-4Rα-mediated signaling on Foxp3+ Treg cells promotes [10 , 19] or inhibits [14 , 15 , 18] their suppressive function ( s ) remains unclear . To address this , we examined the surface protein expression pattern of IL-4Rα on Foxp3+ Treg cells in spleen and mesenteric lymph nodes ( MLNs ) of naïve and 8-wk-Sm-infected BALB/c mice . CD4+ Foxp3+ Treg cells expressed IL-4Rα under a steady state and up-regulated their expression upon Sm infection ( Fig 1A–1C ) . These results suggest that IL-4Rα-mediated signaling might be important for Foxp3+ Treg cells to function under steady-state and inflammatory conditions . To better dissect the role of IL-4Rα-mediated signaling on Foxp3+ Treg cells , we generated a murine model , termed Foxp3cre IL-4Rα−/lox , with a specific cyclic recombinase ( Cre ) -mediated deletion of the il-4rα gene in Foxp3-expressing cells . Foxp3cre IL-4Rα−/lox mice were generated by intercrossing BALB/c mice expressing Cre under control of foxp3 gene promoter [21] with global knock-out ( IL-4Rα−/− ) BALB/c mice [22] for two generations to generate Foxp3cre IL-4Rα−/− BALB/c mice ( Figs 2A and S1 ) . These mice were further intercrossed with homozygous floxed IL-4Rα ( IL-4Rαlox/lox ) BALB/c mice ( exon 7 to 9 flanked by LoxP sites; Fig 2B ) [23] to generate a Foxp3-specific IL-4Rα-deficient mouse BALB/c strain ( Foxp3cre IL-4Rα−/lox BALB/c mice; Figs 2A and S1 ) . Foxp3cre IL-4Rα−/lox mice were identified by PCR genotyping ( Fig 2C ) . The cellular specificity of Cre-mediated IL-4Rα deletion was assessed at the genomic level by performing quantitative real-time PCR ( qPCR ) . Genomic DNA was extracted from cluster of differentiation 19 ( CD19 ) + , CD4+ Foxp3− , and CD4+ Foxp3+ sorted cells from pooled spleen and MLN cells of naïve Foxp3cre IL-4Rα−/lox , their littermate control ( IL-4Rα−/lox ) , and global knock-out ( IL-4Rα−/− ) mice ( Fig 2D ) ; and il-4rα exon 8 ( absent in IL-4Rα-deficient cells ) was quantified by qPCR and normalized to il-4rα exon 5 ( present in all cells ) . As expected , only CD4+ Foxp3+ T cells , but not CD19+ or CD4+ Foxp3− cells , from Foxp3cre IL-4Rα−/lox mice had a lower exon8:exon5 ratio when compared to their littermate controls ( Fig 2E ) . Genotypic deletion of il-4rα within CD4+ Foxp3+ Treg cells in Foxp3cre IL-4Rα−/lox mice was further confirmed at the protein level by flow cytometry analyses of IL-4Rα surface expression on spleen and MLN cells of naïve mice . In both organs , IL-4Rα was deleted specifically within CD4+ Foxp3+ Treg cell population in Foxp3cre IL-4Rα−/lox male and female mice ( Fig 2F and 2G ) . il-4rα gene deletion within the CD4+ Foxp3+ Treg cell population was more efficient in males ( efficiency of deletion [Ed] = 90 . 48% ± 5 . 45% , Fig 2H and 2I ) when compared to females ( Ed = 39 . 74% ± 5 . 776% , Fig 2H and 2I ) , enabling via the present model an assessment of the effect of partial ( female ) versus quasi-complete ( male ) impairment of IL-4Rα-mediated signaling on CD4+ Foxp3+ Treg cell in Foxp3cre IL-4Rα−/lox mice . To assess the functional impairment of IL-4Rα-mediated signaling on CD4+ Foxp3+ Treg cells in our newly generated model , pooled spleen and MLN cells of naïve male and female Foxp3cre IL-4Rα−/lox mice and their littermate controls were cultured with or without recombinant IL-4 ( rIL-4 ) for 40 hr and/or 1 hr , and then , levels of IL-4Rα surface expression and signal transducer and activator of transcription 6 ( STAT6 ) phosphorylation were measured by flow cytometry , respectively . CD19+ B cells and CD4+ Foxp3− T cells from Foxp3cre IL-4Rα−/lox mice and their littermate control had a comparable level of IL-4Rα expression , as determined by IL-4Rα geometric mean fluorescence intensity ( GMFI ) , after the addition of rIL-4 ( Fig 2J and 2K ) . In agreement , no major differences in the level of phosphorylated STAT6 ( p-STAT6 ) either at baseline ( S2A and S2B Fig ) or after rIL-4 stimulation ( S2A Fig and S2C–1E ) in both populations ( CD19+ B cells and CD4+ Foxp3− T cells ) were noted between Foxp3cre IL-4Rα−/lox mice and their littermate controls . In contrast , a proportion of rIL-4-stimulated CD4+ Foxp3+ Treg cells derived from Foxp3cre IL-4Rα−/lox mice were significantly impaired in their ability to up-regulate IL-4Rα expression compared to CD4+ Foxp3+ Treg cells derived from their littermate control ( Fig 2J and 2K ) . In support , STAT6 phosphorylation upon rIL-4 stimulation in CD4+ Foxp3+ Treg cells in IL-4Rα−/lox mice was significantly higher compared to Foxp3cre IL-4Rα−/lox mice ( S2A and S2C Fig ) , indicating that the IL-4Rα signaling pathway on CD4+ Foxp3+ Treg cells is impaired in our Foxp3cre IL-4Rα−/lox mice . Of interest , we noted that at baseline , male mice do have a higher level of p-STAT6 when compared to female mice ( S2B Fig ) . In our Foxp3cre IL-4Rα−/lox mice , even though the increase in STAT6 phosphorylation upon rIL-4 stimulation in Foxp3+ Treg cell compartment was higher in female mice than males ( S2D and S2E Fig ) because of the differential deletion of il4ra gene on Foxp3+ Treg cells , the initial higher level of p-STAT6 noticed in male mice brought the absolute final level of p-STAT6 in male and female mice to a comparable level ( S2C Fig ) . Collectively , these results reveal that IL-4Rα is specifically deleted on CD4+ Foxp3+ Treg cells in Foxp3cre IL-4Rα−/lox mice either partially ( approximately 40% in females ) or quasi-completely ( approximately 90% in males ) , resulting—in both cases—in a significant impairment of IL-4Rα-mediated signaling in the Foxp3+ Treg cell population . Equipped with the aforementioned murine model , we first interrogated the need for Foxp3+ Treg cells to express IL-4Rα expression under a steady state in vivo . Naïve Foxp3cre IL-4Rα−/lox mice and littermate control , IL-4Rα−/lox mice , were examined for alteration of Foxp3+ Treg cell compartments , overall tissue pathologies , and tissue cellularities . Foxp3cre IL-4Rα−/lox mice had similar tissue frequencies of CD4+ Foxp3+ Treg cells among cluster of differentiation 3 ( CD3 ) + T cells when compared to their littermate control ( Figs 3A and 3B and S3A ) . No aberrant changes in body weight ( Figs 3C and S3B ) , vital organs’ weight ( Figs 3D and S3C ) , or organs’ cellularities ( Figs 3E and S3D ) were noted . Foxp3cre IL-4Rα−/lox mice also displayed normal lymphocyte compartments in their primary lymphoid organ ( thymus ) , secondary lymphoid organs ( spleen and MLN ) , and peripheral tissues ( lung and liver ) ( Fig 3F–3K and S3E–2I ) . Together , our findings suggest that no major physical alterations are consequent to the impairment of IL-4Rα-mediated signaling within the Foxp3+ T-cell compartment in our Foxp3cre IL-4Rα−/lox mouse model under a steady state . Mice with a Treg cell–specific deletion of GATA3 , a transcription factor closely associated with IL-4Rα-mediated signaling [24] , have been shown to develop a spontaneous inflammatory disorder with an increased release of inflammatory soluble mediators [25] . To address whether the deletion of IL-4Rα within Foxp3+ Treg cells would also instruct a spontaneous and perhaps more subtle inflammatory response in Foxp3cre IL-4Rα−/lox mice , serum levels of soluble inflammatory mediators and liver enzymes and cytokine production by CD4+ T cells were determined . Serum levels of IL-4 , tumor necrosis factor alpha ( TNF-α ) , immunoglobulin E ( IgE; Figs 3L and S3J ) , and aspartate aminotransferase ( AST ) ( Figs 3M and S3K ) in Foxp3cre IL-4Rα−/lox mice were similar to those of littermate controls . All CD4+ T cell–derived cytokines tested were also similar between Foxp3cre IL-4Rα−/lox mice and littermate controls ( Figs 3N and 3O and S3L ) . Collectively , these results show that in vivo under a steady state , impairment of IL-4Rα-mediated signaling within the Foxp3+ T-cell compartment neither alters Foxp3+ Treg cell compartments nor results in spontaneous inflammatory disorder in Foxp3cre IL-4Rα−/lox mice . To further address the molecular basis of Foxp3+ Treg cells’ need to express IL-4Rα signaling , we assessed the in vitro Foxp3 Treg conversion and expansion capacity of CD4+ CD25−/CD4+ CD25+ cells from Foxp3cre IL-4Rα−/lox mice , respectively , in comparison with CD4+ CD25−/CD4+ CD25+ cells from IL-4Rα−/lox littermate controls . CD4+ CD25− T cells were sorted with 99 . 8% purity ( S4A Fig ) from naïve Foxp3cre IL-4Rα−/lox mice and their IL-4Rα−/lox littermate controls . Sorted cells were cultured in the presence of transforming growth factor beta 1 ( TGF-β1 ) in combination with T-cell receptor stimulation using anti-CD3 and anti-CD28 for 72 hr ( S4B and S4C Fig ) , which are known to induce conversion from CD25-negative to CD25-positive CD4+ T cells [26] . In our cultures , CD4+ CD25− T cells converted to CD4+ CD25+ Foxp3+ T cells ( induced Treg [iTreg] cells ) , with the highest rate of conversion recorded from CD4+ CD25− T-cell cultures derived from Foxp3cre IL-4Rα−/lox mice ( S4B and S4C Fig ) . This suggests that IL-4Rα signaling on CD4+ CD25− T cells might interfere with their ability to convert but is clearly not needed to promote their differentiation into Foxp3+ Treg cell in vitro . Next , we measured the effect of IL-4 stimulation on Treg cells . To do so , CD4+ CD25+ T cells , sorted from naïve Foxp3cre IL-4Rα−/lox mice and their littermate control ( S4A Fig ) , were cultured in the presence or absence of rIL-4 for 18 or 36 hr . Whereas IL-4 treatment enhanced the survival of CD4+ CD25+ T cells from control mice , the survival of CD4+ CD25+ T cells from Foxp3cre IL-4Rα−/lox mice remained unaltered following treatment with rIL-4 ( S4D Fig ) . These results suggest that IL-4/IL-4Rα signaling promotes CD25+ Treg cell survival in vitro and that this process is abrogated in CD25+ Treg cells from Foxp3cre IL-4Rα−/lox mice . Furthermore , CD4+ CD25+ Treg cells derived from IL-4Rα−/lox mice considerably expanded Foxp3+ Treg cells’ frequency ( S4E Fig ) and expression level ( S4F and S4G Fig ) in response to in vitro stimulation with rIL-4 , whereas CD4+ CD25+ Treg cells from Foxp3cre IL-4Rα−/lox mice failed to do so . Taken together , these data indicate that even though IL-4Rα-mediated signaling negatively influences the ability of naive CD4+ CD25− Foxp3− T cells to convert into Foxp3+ Treg cells , this receptor , later on , promotes the survival and enhances the Foxp3 expression of CD4+ CD25+ Treg cells in vitro . The strategy of probing subtle immune impairments , nonapparent during a steady state , under more inflammatory settings has previously proven to be efficient in unveiling hidden immune defects [5 , 27] . Moreover , the aforementioned enhancement of survival and Foxp3 expression of CD4+ CD25+ Treg cells upon induction of IL-4/IL-4Rα-mediated signaling in vitro and the striking higher expression of IL-4Rα by Foxp3+ Treg cells observed during infection warranted us to further address the possible higher need for this receptor by Foxp3+ Treg cells , in vivo , during inflammatory disease conditions . To do so , IL-4Rα−/lox , Foxp3cre IL-4Rα−/lox , and IL-4Rα−/− mice were infected with Sm cercariae and euthanized 8 wk thereafter . Deletion of il-4rα within the Foxp3+ Treg cell population was confirmed at the genomic level by qPCR ( Fig 4A ) and at the protein level by flow cytometry ( Figs 4B , S5A and S5B ) , at which specific deletion of IL-4Rα on Foxp3+ Treg cells ( more efficient in males , when compared to females ) , but not on CD19+ B cells , was observed . Flow cytometry analysis of Foxp3+ Treg cells within the Sm-diseased livers showed significant reduction of Foxp3+ Treg cell infiltration into the liver of Sm-infected Foxp3cre IL-4Rα−/lox when compared to their littermate controls ( Figs 4C , 4D and S5C ) . Furthermore , we noted that Foxp3+ Treg cells in the liver of Sm-infected Foxp3cre IL-4Rα−/lox mice had a significant reduction in the expression levels of Foxp3 ( Figs 4E and S5D ) . This suggests that IL-4Rα signaling seems to be necessary for the Foxp3+ Treg cell in order to maintain or up-regulate its expression of the suppressive marker Foxp3 in vivo during inflammation . Deletion of IL-4Rα signaling on Foxp3cre IL-4Rα−/lox mice resulted in elevated cytokine production , including Type 1 ( IFN-γ ) , Type 17 ( interleukin-17 [IL-17] ) , and Type 2 ( IL-4 , interleukin-5 [IL-5] , interleukin-10 [IL-10] , interleukin-13 [IL-13] ) cytokines in the liver of both male and female Sm-infected Foxp3cre IL-4Rα−/lox mice ( Figs 4F and S5E ) . These suggest that Foxp3+ Treg cells do require IL-4/IL-4Rα-mediated signaling in vivo to suppress overshooting inflammation . The analysis within the MLNs supported this conclusion . Even though the frequency of Foxp3+ Treg cells ( Figs 4G , 4H and S5G ) within the MLNs in Sm-infected Foxp3cre IL-4Rα−/lox mice were similar to littermate controls at 8 wk post infection , Foxp3 surface expression level on a per-cell basis was , however , dramatically reduced in Sm-infected Foxp3cre IL-4Rα−/lox mice compared to infected littermate controls ( Figs 4I and S5H ) . Reduced suppressive capacity potential was combined with increased frequency of proliferating ( CD4+ Foxp3− ki67+; Figs 4J , 4K and S5I ) and effector ( CD4+ cluster of differentiation 44 [CD44]+; Figs 4L and S5J ) T cells within the MLN of Sm-infected Foxp3cre IL-4Rα−/lox mice , accompanied by significant increase in IL-4 , IL-10 , and IL-13 production by CD4+ T cells ( Figs 4M and S5K ) . Together , these findings strongly suggest that the impairment of IL-4/IL-4Rα-mediated signaling within the Foxp3+ T-cell compartment diminishes Foxp3+ Treg cell recruitment to affected tissues during inflammation and impairs Treg cell ability to up-regulate suppressive factor , culminating into a heightened immune activation . We next questioned the nature of the heightened immune response observed during inflammation in Foxp3cre IL-4Rα−/lox mice . To do so , MLN cells from Sm-infected Foxp3cre IL-4Rα−/lox mice and littermate controls were probed for CD4+ T cell–expressing GATA3 as a marker of Th2 responses [24] , T-box transcription factor ( T-bet ) as a marker of T helper 1 ( Th1 ) responses [28] , RAR-related orphan receptor gamma ( RORγt ) as a marker of Th17 responses [29] , and B cell lymphoma 6 ( Bcl-6 ) as a marker of T follicular responses [30 , 31] . Consistent with the Th2 hegemony that is characteristic of Sm infection [32] , MLN CD4+ T cells from Sm-infected Foxp3cre IL-4Rα−/lox mice overexpressed GATA3 ( Figs 4N and S5L and S6A ) ; however , all other T-cell polarization markers remained unaltered compared to littermate control ( Figs 4N and S5L and S6A ) . Of importance , CD4+ GATA binding protein 3 ( GATA3 ) + cells from Sm-infected Foxp3cre IL-4Rα−/lox mice produced more IL-4 , IL-10 , and IL-13 compared to littermate controls ( Figs 4O and S5M and S6B ) . Together , these suggest that CD4+ GATA3+ responses likely drive the heightened immune response and the elevated cytokine production observed in Foxp3cre IL-4Rα−/lox mice during inflammation . Nevertheless , with the recent description of ex-Foxp3 T cells [14 , 15 , 18] , this observation could be confounded by the likelihood of cytokine production by newly formed ex-Foxp3+ T cells dually expressing GATA3 and Foxp3 and releasing cytokines following deletion of IL-4Rα . To address that , we traced back the source of the produced cytokines during Sm infection by co-staining of intracellular cytokines and Foxp3 in CD4+ T cells . We observed that CD4+ Foxp3+ T cells did not produce more cytokines in the MLN of Sm-infected Foxp3cre IL-4Rα−/lox mice ( Figs 4P and S5N and S6B ) , ruling out a role for Foxp3+ T cells in the heightened cytokine production observed in Sm-infected Foxp3cre IL-4Rα−/lox mice . Collectively , we conclude that the heightened immune response observed—which is due to impairment of IL-4Rα-mediated signaling within the Foxp3+ T-cell compartment in Sm-infected Foxp3cre IL-4Rα−/lox mice—is driven at least in part by CD4+ GATA3+ Foxp3− but not Foxp3+ T cells . To further appraise the consequences of the heightened immune responses observed in diseased Sm-infected Foxp3cre IL-4Rα−/lox mice , egg-driven fibrogranulomatous inflammation , as well as Foxp3+ Treg cells’ infiltration in the liver of Sm-infected Foxp3cre IL-4Rα−/lox mice , was microscopically assessed in comparison with that of Sm-infected littermate controls . We noted that Sm infection resulted in enlarged egg-driven granulomas in the liver of Foxp3cre IL-4Rα−/lox mice when compared to granulomas in the liver of their littermate control ( Fig 5A and 5B ) . In agreement with this observation , we found that the average number of Foxp3+ Treg cells within egg-driven granulomas in Foxp3cre IL-4Rα−/lox mice was significantly reduced when compared to the amount of Foxp3+ Treg cells recruited to the liver of littermate controls ( Fig 5C and 5D ) . Furthermore , collagen levels , attesting the degree of tissue fibrosis , were considerably higher in the livers of Sm-infected Foxp3cre IL-4Rα−/lox mice when compared to the levels reported in Sm-infected littermate controls ( Fig 5E ) . Indeed , colorimetric measurement of 4-hydroxyproline , a direct product of acid hydrolysis of collagen , confirmed our observed increased level of collagen in the liver of Sm-infected Foxp3cre IL-4Rα−/lox mice ( Figs 4F and S5F ) . In fact , with similar egg burdens in the guts and livers of Foxp3cre IL-4Rα−/lox mice and their littermate control ( Fig 5G ) , Sm-infected Foxp3cre IL-4Rα−/lox mice still displayed much larger coalescing granulomas ( Fig 5H ) , as indicated by hematoxylin–eosin ( HE ) ( Fig 5A ) and chromotrope aniline blue ( CAB ) staining ( Fig 5E ) . Similar to the liver , gut tissues of Sm-infected Foxp3cre IL-4Rα−/lox mice revealed elevated levels of cellular recruitment around trapped parasite eggs ( Fig 5I ) , which was associated with a more pronounced deposition of collagen ( Fig 5J ) , as confirmed by gut hydroxyproline content ( Figs 5K and S5O ) , indicating a heightened fibrogranulomatous inflammation around Sm-trapped eggs in Foxp3cre IL-4Rα−/lox mice when compared to littermate controls . Since Cre expression can generate a phenotype of its own [33–39] , we sought to address whether the uncontrolled immune responses and the exaggerated fibrogranulomatous inflammation noted in the Sm-infected Foxp3cre IL-4Rα−/lox mice were due to the specific deletion of IL-4Rα on the Foxp3+ Treg cells or were an artefact effect from the Cre transgene alone . To test that , IL-4Rα+/+ and Foxp3cre IL-4Rα+/+ mice were infected with 100 Sm cercariae , and then , Foxp3+ Treg cell compartments and fibrogranulomatous inflammation in liver and gut were investigated 8 wk post infection . We noted that IL-4Rα expression on either CD19+ B cells or Foxp3+ Treg cell compartment ( S7A Fig ) in Sm-infected Foxp3cre IL-4Rα+/+ mice was similar to littermate controls . Furthermore , in liver , the frequency of Foxp3+ Treg cell population ( S7B and S7C Fig ) and level of Foxp3 ( S7D and S7E Fig ) as well as GATA3 ( S7F and S7G Fig ) expression within the Foxp3+ Treg cell compartment in Sm-infected Foxp3cre IL-4Rα+/+ mice were similar or slightly affected when compared to their infected littermate controls . The similar frequency of Foxp3+ Treg cell population ( S7H and S7I Fig ) , as well as the comparable level of Foxp3 expression ( S7J and S7K Fig ) , was also noted in the MLN of Sm-diseased mice . In fact , Cre transgene expression in Foxp3cre IL-4Rα+/+ mice led to neither an expansion of CD4+ GATA3+ T-cell population ( S7L Fig ) nor uncontrolled Type 1 ( IFN-γ ) , Type 17 ( IL-17 ) , or Type 2 ( IL-4 , IL-5 , IL-10 , IL-13 ) cytokine production ( S7M Fig ) . In agreement with these observations , we found that Cre expression did not affect either liver granuloma size ( S8A and S8B Fig ) or hepatic fibrosis , as indicated by CAB staining ( S8C Fig ) and colorimetric measurement of 4-hydroxyproline ( S8D Fig ) . Similar to the liver , gut tissues of Sm-infected Foxp3cre IL-4Rα+/+ mice had a comparable granuloma size ( S8E Fig ) , similar collagen deposition ( S8F Fig ) , and a similar level of 4-hydroxyproline content ( S8G Fig ) when compared to their infected littermate controls , indicating that Cre transgene , in our mouse model , does not have any impact on either the immune responses or the tissue inflammation . Taken together , these observations indicate that the impairment of IL-4Rα-mediated signaling , but not the Cre transgene expression , specifically within the Foxp3+ Treg cell compartment during experimental schistosomiasis drives a poor accumulation of Foxp3+ T cells in the inflamed tissues and consequently results in elevated host fibrogranulomatous responses around the trapped parasite eggs . We next aimed to test whether this would also hold true in another inflammatory helminth disease model . We found that following subcutaneous infection of Foxp3cre IL-4Rα−/lox and IL-4Rα−/lox littermate control mice with Nb , the airways of Nb-infected Foxp3cre IL-4Rα−/lox mice showed much heavier mucus production 9 d post infection ( S9A and S9B Fig ) . Moreover , we noted that Foxp3+ Treg cells’ recruitment to the inner layer of the alveoli of the lungs of Nb-infected Foxp3cre IL-4Rα−/lox mice ( S9C and S9D Fig ) was diminished , indicating that in this model as well the impairment of IL-4Rα-mediated signaling within the Foxp3+ T-cell compartment impairs their ability to accumulate at the inflamed tissue and to control local tissue inflammation . Collectively , these results clearly suggest , in two different and major inflammatory helminth models , that impairment of IL-4Rα-mediated signaling within the Foxp3+ T-cell compartment leads to uncontrolled immune responses and exacerbated tissue ( s ) inflammation , underscoring a hitherto-unappreciated role of IL-4Rα-mediated signaling on Foxp3+ Treg cells to control inflammatory responses in vivo . Next , we investigated the mechanisms underpinning the poor ability of Foxp3+ Treg cells to accumulate in the inflamed tissues in our diseased Foxp3cre IL-4Rα−/lox mice . First , we assessed the effect of IL-4Rα deletion specifically on Foxp3+ T-cell compartment for its ability to build up the eTreg cells needed to contain the immune responses at the site of inflammation [40] . To address that , central Foxp3+ Treg ( cTreg ) cell and eTreg cell populations in hepatic lymph nodes ( hLNs ) and MLNs of Foxp3cre IL-4Rα−/lox mice infected with Sm for 8 wk were assessed in comparison to those of Sm-infected littermate controls . In both lymph nodes , deletion of IL-4Rα specifically on Foxp3+ Treg cells resulted in the accumulation of cTreg cells ( Figs 6A and 6B and S10A ) , which was associated with a significant reduction in the pool of eTreg cell population ( Figs 6A and 6C and S10B ) , indicating that IL-4Rα-mediated signaling on Foxp3+ Treg cells could be playing a role in inducing the conversion of cTreg cell to eTreg cell . Furthermore , the ability of these eTreg cells to maintain or up-regulate the expression of C-X-C motif chemokine receptor 3 ( CXCR3 ) , a chemoattractant receptor required for the migration of eTreg cells to nonlymphoid tissues ( in particular , liver [40 , 41] ) , was significantly impaired in both hLNs ( Fig 6D and 6E ) and MLNs ( S10C and S10D Fig ) of Foxp3cre IL-4Rα−/lox mice infected with Sm for 8 wk . In support , the expression level of GATA3 , a transcription factor required for Treg cell accumulation at the site of inflammation [42] , within the Foxp3+ Treg cell in the liver of Foxp3cre IL-4Rα−/lox mice infected with Sm for 8 wk was diminished when compared to littermate controls ( Fig 6F and 6G ) . Together , these results suggest that IL-4Rα-mediated signaling on Foxp3+ Treg cell is required for the maintenance or up-regulation of the markers required for migration and accumulation of Foxp3+ Treg cell in the inflamed tissue . Then , we traced back whether the reduction in the Foxp3+ Treg cell population in the liver of Foxp3cre IL-4Rα−/lox mice infected with Sm for 8 wk was due to a global defect in Foxp3+ Treg cells or in the Treg cell de novo conversion in vivo , since eTreg cell can be thymic-derived and/or peripherally induced . To address that , we analyzed the thymic-derived Foxp3+ Treg cells ( Foxp3+ Helios+ Treg cells ) and the peripherally iTreg cells ( Foxp3+ Helios− Treg cells ) in the liver of Foxp3cre IL-4Rα−/lox mice infected with Sm for 8 wk and their littermate controls . We noted that in the liver of Foxp3cre IL-4Rα−/lox mice infected with Sm for 8 wk , both Foxp3+ Helios+ and Foxp3+ Helios− Treg cells were significantly reduced ( Fig 6H and 6I ) , suggesting a global defect in the Foxp3+ Treg cell population . Finally , inasmuch as the reduction of Foxp3+ Treg cell population was independent of its proliferation as Foxp3+ Treg cells in the liver of Foxp3cre IL-4Rα−/lox mice infected with Sm for 8 wk and their littermate control had a comparable expression level of Ki-67 ( Fig 6J and 6K ) , we therefore asked whether the reduction of Foxp3+ Treg cell population in the liver could be possibly driven , in addition to their poor migration and accumulation , by the lessened ability of these Foxp3+ Treg cells to survive in the absence of IL-4Rα-mediated signaling . Indeed , we noted a diminished expression level of the pro-survival factor B cell lymphoma 2 ( Bcl-2; Fig 6L and 6M ) within the Foxp3+ Treg cell population in the liver of the Foxp3cre IL-4Rα−/lox mice infected with Sm for 8 wk when compared to their littermate control . In support , those Foxp3+ Treg cell population had a higher expression level of the apoptotic marker caspase-3 ( Fig 6N and 6O ) as well as the fixable viability stain ( Fig 6P and 6Q ) , indicating that the Foxp3+ Treg cell population in the liver has a higher propensity to undergo apoptosis in the absence of IL-4Rα-mediated signaling , which recapitulates our in vitro data mentioned earlier . Collectively , our results suggest that IL-4Rα-mediated signaling is required for the conversion of cTreg cells into eTreg cells . These eTreg cells further need the IL-4Rα-mediated signaling to maintain or up-regulate markers required for their migration , accumulation , and survival at the site of inflammation .
Studies on Foxp3+ Treg cell function have uncovered a critical regulatory role for the cytokines present in the milieu ( reviewed in [9] ) . IL-4 , the canonical cytokine of Type 2 immune responses that signals via IL-4Rα , signaling on Treg cells has been shown to promote Treg cell reprogramming toward Th17 [15] or Th2 [14 , 18] cells . As a consequence , enhanced signaling via IL-4Rα in Treg cells has resulted in impaired suppressive function and heightened inflammation , establishing the concept of a negative regulation of Treg cell activity by IL-4Rα-mediated signaling . The present study , however , shows that IL-4Rα-mediated signaling is also required by Treg cells to control inflammation in diseases ( Fig 7 ) . First , in an experimental murine model of schistosomiasis , we demonstrated that Foxp3+ Treg cells up-regulated IL-4Rα expression . Further analyses on the need for the host to up-regulate this receptor during schistosomiasis were then conducted using a murine model of specific deletion of IL-4Rα within the Foxp3+ Treg cell population , termed Foxp3cre IL-4Rα−/lox mice . Specific removal of IL-4Rα in a part or almost totally on the Foxp3+ Treg cell population exacerbated tissue inflammation during experimental Sm- and Nb-mediated diseases . Aggravated immunopathology was associated with a decline in Treg cell accumulation in the diseased tissues and the reduced expression of suppressive markers , paralleled by an augmentation of immune effector responses as translated in the Sm model in Foxp3cre IL-4Rα−/lox mice . Collectively , these findings unprecedentedly , to our knowledge , uncovered a critical need for IL-4Rα-mediated signaling on Foxp3+ Treg cells to control tissue immunopathology in helminthiases . Such a need for Foxp3+ Treg cells for this signaling axis is yet to be examined in allergic Th2 inflammation and Th1- or Th17-dominated diseases . Recently published reports have shown that augmentation of IL-4Rα-mediated signaling on Foxp3+ Treg cells leads to an impaired suppressive activity of those cells with subsequent reprogramming into ex-Foxp3 Th2 or Th17 cells [14 , 15 , 18] . Although these observations would suggest that IL-4Rα signaling might not favor Treg cell activity , our present analyses revealed that Foxp3+ Treg cells have a basal expression level of IL-4Rα under a steady state , pointing at a possible requirement for this receptor in Treg cell biology . Our assumption is in accordance with a previous attempt by other investigators that have reported the potency of IL-4 to prevent spontaneous apoptosis and reduction of Foxp3 expression in the cultures of isolated Treg cells [10] . In fact , IL-4 stimulation of isolated cultures of CD4+ CD25+ Treg cells in our study recapitulated such a need for IL-4Rα-mediated signaling to prevent cell death and to maintain or enhance Foxp3 expression , indicating a hitherto-unappreciated need for IL-4Rα-mediated signaling in Treg cell biology and activity . IL-4Rα expression by Foxp3+ Treg cells was further enhanced following Sm infection , suggesting a strong requirement for this receptor either to preserve Treg cell activity or foster their transdifferentiation into ex-Foxp3 Th2 cells . In fact , the reprogramming of Foxp3+ Treg cells into functional effector ex-Foxp3 Th2 cells has now been demonstrated during Heligmosomoides polygyrus infection [18] , during which ex-Foxp3 Th2 cells generated in an IL-4Rα-dependent manner were shown to contribute to the overall antiparasitic Th2 response [18] . Hence , it is possible that IL-4Rα up-regulation on Foxp3+ Treg cells during acute experimental schistosomiasis observed in our study could occur as an attempt for the host to rapidly mount a protective Th2 immune response during acute schistosomiasis [32] . More experiments are clearly needed at this point to address the likelihood of such a contribution of ex-Foxp3 in the host protective Th2 response during experimental schistosomiasis . IL-4Rα removal specifically from the Foxp3+ Treg cell compartment was achieved by making use of the Cre-lox system . A murine model , Foxp3cre IL-4Rα−/lox , was obtained in which IL-4Rα was deleted specifically within the Foxp3+ Treg cell compartment in a dosage-dependent manner whereby IL-4Rα is partially deleted in females and quasi-completely deleted in males . The more efficient Cre-mediated IL-4Rα deletion achieved in male when compared to female Foxp3cre IL-4Rα−/lox mice strongly fits the phenomenon of random inactivation of the X chromosome that can take place in females but not males , as previously reported [43 , 44] . Our approach herein described could therefore set a precedent for the generation of transgenic mouse models with various levels of knockdown of a target gene . We found , consistent with the literature [10] , that isolated cultures of CD25+ Treg cells tightly depended on IL-4Rα for survival and maintenance of Foxp3 expression . However , partial or quasi-complete removal of IL-4Rα from the Foxp3+ Treg cell population did not affect the Treg cell compartment during steady state . A possible explanation could be that the remnant IL-4Rα on Foxp3+ Treg cells in our Foxp3cre IL-4Rα−/lox model is sufficient to preserve the Foxp3+ Treg cell compartment and thus tolerance during a steady state in which randomly occurring inflammatory responses are not common . This is consistent with previous studies that have attempted to define the physiological importance of factors expressed by Foxp3+ Treg cells . Specifically , in these studies , Foxp3-specific GATA3- or T-bet-deficient mice were clinically indistinguishable from their littermate controls and showed no defect on the function of Foxp3+ Treg cells under a steady state in young mice [5 , 27 , 42] . In older mice ( 6 mo upwards ) , however , the targeting of GATA3 within the Foxp3+ Treg cell population led to inflammatory disease [25] . It is therefore feasible that specific deletion of IL-4Rα from the Foxp3+ Treg cell compartment might also lead to apparent physiological defects only in old mice , but this is still to be addressed experimentally . Notably , inflammation in these models of Foxp3-specific GATA3 or T-bet deletion uncovered more robustly a defect in the Foxp3+ Treg cell compartment that translated into physiological impairments [27] . Similarly , infection of our Foxp3cre IL-4Rα−/lox mice resulted in elevated inflammatory responses in helminth-mediated disease models . This was defined by increased levels of Foxp3− T-cell proliferation and activation as well as a clear augmentation of cytokine production , indicating a more potent effector response following either partial or quasi-complete deletion of IL-4Rα from the Foxp3+ Treg cell compartment during inflammation . It is also important to point out that we observed similarly heightened cytokine release and inflammation in diseased female Foxp3cre IL-4Rα−/lox mice , in which the less efficient deletion of IL-4Rα was observed when compared to Sm-infected male Foxp3cre IL-4Rα−/lox mice . The possible explanations could be that ( i ) disruption of the IL-4Rα signaling pathway on Foxp3+ Treg cells as low as 40% is enough to completely disequilibrate the inflammation–regulation balance during infection , and/or ( ii ) the functional characterization of males and females mice , by using STAT6 phosphorylation as a readout , demonstrated that the absolute final levels of STAT6 phosphorylation in cells from male and female Foxp3cre IL-4Rα−/lox mice were comparable ( S1C Fig ) , indicating that male and female Foxp3cre IL-4Rα−/lox mice do have a similar defect at the functional level of the IL-4Rα signaling pathway on Foxp3+ Treg cell population . Such observations could provide an explanation for the similar phenotype in Foxp3cre IL-4Rα−/lox female and male mice during inflammation , when elevated IL-4 is produced . As of yet , the general observation of heightened inflammatory responses in diseased Foxp3-specific IL-4Rα-impaired mice could be rooted under two opposing but not mutually exclusive explanations—i . e . , ( i ) IL-4Rα as a critical receptor in conferring to Foxp3+ Treg cells the necessary potency to control inflammatory responses in disease and/or ( ii ) the need for this IL-4Rα receptor to foster Foxp3+ Treg cells transdifferentiation into effector T cells . The former explanation does find support in our observation of a significant reduction in Foxp3 expression levels within the Foxp3+ Treg cell population following removal of IL-4Rα from the Foxp3 compartment in Sm-infected Foxp3cre IL-4Rα−/lox mice . In fact , Foxp3 expression is the defining factor that endows Treg cell with a suppressive ability , and its continuous expression is required to maintain the transcriptional and functional programs of Treg cells [45–48] . Consequently , our observation of a reduced Foxp3 expression during inflammation following IL-4Rα removal on Foxp3+ Treg cells defines a need for this receptor in stabilizing and promoting Foxp3 expression by Foxp3+ Treg cells in vivo . Although the latter explanation of a negative regulation of Foxp3+ Treg cells by IL-4Rα signaling in favor of ex-Foxp3 transdifferentiation can be appropriately dismissed by using fate-reporter mice , our present study , as it stands , convincingly indicates that the T cells responsible for the increased cytokine production reported in Foxp3cre IL-4Rα−/lox diseased mice expressed not Foxp3 but rather GATA3 , a profile inconsistent with recently reported ex-Foxp3 T cells during helminth infections [18] . This argued against Foxp3 Treg cells’ transdifferentiation into cytokine-producing effector T cells as mediating the heightened inflammation observed in diseased Foxp3cre IL-4Rα−/lox mice . Partial or quasi-complete removal of IL-4Rα within the Foxp3+ Treg cell compartment of Foxp3cre IL-4Rα−/lox diseased mice led to an impaired accumulation of Treg cells to the site of inflammation . Mechanistically , various processes can mediate such an impaired accumulation of Foxp3cre IL-4Rα−/lox Treg cells observed in our infectious settings , including defects in ( i ) the extrathymic Treg cell conversion , ( ii ) the proliferation capacity , ( iii ) the generation of eTreg cells , ( iv ) the migration and the accumulation of eTreg cells at the site of inflammation , and/or ( v ) the survival of Treg cells . We found no obvious defect of CD25− CD4+ cell precursors from Foxp3cre IL-4Rα−/lox mice in converting into Foxp3+ Treg cells in vitro , arguing against a defect in extrathymic Treg cell conversion . Ex vivo analyses of Foxp3+ Treg cells from diseased Foxp3cre IL-4Rα−/lox mice showed no signs of impaired proliferation , dismissing Foxp3+ Treg cell–defective proliferation as a possible cause of the poor accumulation reported . However , we found that cTreg cells in the lymph nodes of diseased Foxp3cre IL-4Rα−/lox mice had a poor ability to convert into eTreg cells , resulting in a significant reduction in the eTreg cell population required to populate the nonlymphoid tissues that further contain the inflammatory immune responses [40] . Furthermore , migration and accumulation of these eTreg cells were impaired , as indicated by the reduction in the expression level of CXCR3 and GATA3 , respectively . Our results are in full accordance with previous reports on the need of Foxp3+ Treg cells to express GATA3 and CXCR3 to migrate and accumulate in the inflamed tissues and in the liver , respectively [9 , 41 , 42] . In addition to the reduction in the pool of eTreg cell population and their poor ability to migrate and accumulate at the site of inflammation , Foxp3+ Treg cells in the liver of diseased Foxp3cre IL-4Rα−/lox mice had a higher propensity to undergo apoptosis , recapitulating our in vitro data , which showed that CD25+ Treg cells’ survival and stability ( as judged by Foxp3 expression ) are compromised in the absence of IL-4 . Overall , our results support the idea that an intact , rather than a potentiated or diminished , IL-4Rα-mediated signaling is optimal to endow Foxp3+ Treg cells with their most efficient ability to control inflammation in disease as illustrated here in helminthiases . As per our current findings , such an optimal response is most likely achieved by preventing Foxp3+ Treg cell death and stabilizing the expression of canonical Treg cell–suppressive and associated markers such as Foxp3 and GATA3 . In light of past reports that have defined a negative role for IL-4Rα-mediated signaling on Treg cell activity in Th2-dominated settings , our present finding of a negative role of IL-4Rα deficiency on Treg cells during inflammation further highlights the fact that the same cytokine can have both positive and negative effects on Treg cell activity and reinstates the notion that balance is key . Promoting or impairing IL-4Rα-mediated signaling yielded a similar result of Foxp3+ Treg cell impairment , therefore strongly arguing against the benefits of uninformedly modulating this cytokine receptor on Foxp3+ Treg cells to ameliorate tolerance , particularly in the current global context where helminthiasis are highly common . This is therefore particularly important in light of recent therapeutic advances for the control of highly pathogenic cases of asthma for which IL-4Rα targeting has recently been introduced and is attracting further interest for other inflammatory conditions [14 , 15] . Conclusively , in this study , a case is made for the preservation of intact levels of IL-4Rα signaling on Foxp3+ Treg cells to ensure optimal regulatory responses in vivo , and caution is therefore raised for the careful manipulation of this signaling axis in disease .
All mice were maintained in specific-pathogen-free barrier conditions in individually ventilated cages at the University of Cape Town biosafety level 2 animal facility . Experimental mice were sex- and age-matched and used between 6 and 8 wk of age . All the experimental work was in strict accordance with the recommendations of the South African national guidelines and of the University of Cape Town practice for laboratory animal procedures , as in ethics protocols 014/003 and 016/027 approved by the Animal Research Ethics Committee of the Faculty of Health Science , University of Cape Town . All efforts were made to minimize animals’ suffering . Prior to percutaneous infection with Sm cercariae , animals were anesthetized by intraperitoneal injection of a cocktail of ketamine ( 100 mg/kg ) and xylazine ( 10 mg/kg ) and monitored for 5 min to confirm deep anesthesia . Anesthesia was confirmed by the absence of pedal reflex ( toe pinch ) and eyeblink reflex amid a regular respiratory rate . The anesthesia duration was of a maximum of 30 min . During the anesthesia phase , animals were exposed to an infrared lamp to help them maintain their core body temperature . This procedure was performed and duly cared for by trained and authorized researchers . Post infection , animals were monitored until regaining of consciousness , and moistened food was added to the cage bedding . Upon reaching the study’s experimental end point and/or the protocol-defined humane end point , animals were euthanized under this study by exposure to an excess of halothane ( 4% in air ) for 5 minutes . Death was confirmed either by neck dislocation or exsanguination by cardiac puncture . Death was not a predetermined end point in any of the arms of this study . IL-4Rα+/+ , IL-4Rα−/− , and IL-4Rα−/lox mice on BALB/c background and C57BL/6 mice were previously described [22 , 23] . For Foxp3cre IL-4Rα−/lox mice , transgenic Foxp3cre mice ( a generous gift from Prof . James Wing , Osaka University ) were intercrossed for two generations with IL-4Rα−/− BALB/c mice [22] . These mice were further intercrossed with homozygous IL-4Rαlox/lox BALB/c mice [23] to generate hemizygous Foxp3cre IL-4Rα−/lox mice BALB/c strain . Hemizygous littermates ( IL-4Rα−/lox ) were used as wild-type controls in all experiments . Mice were genotyped as described previously [22 , 23] . Thymus and MLN single-cell suspensions were prepared by mechanical squeezing through a 40 μM cell strainer ( Falcon , Corning , MA , US ) . Single-cell spleen suspensions were prepared by mechanical squeezing through a 70 μM cell strainer ( Falcon ) . Liver lymphomyeloid cells were isolated following a modified version of the method of Gossen and colleagues and Hardy and colleagues [50 , 51] . Briefly , single-cell suspensions from the liver tissues were prepared by chopping them into 10 mm3 small pieces and incubating them in Iscove’s Modified Dulbecco’s Medium ( IMDM ) containing 220 U/mg Collagenase I ( Gibco , Waltham , MA , US ) , 13 U/mg DNase I ( Sigma , St . Louis , MO , US ) , and 5% inactivated fetal calf serum ( iFCS; Gibco ) ( digestion buffer ) for 30 min at 37°C under constant rotation . The resulting suspension was mechanically squeezed through a 100 μM sterile cell strainer ( Falcon ) , followed by centrifugation at 1 , 200 rpm for 10 min at 4°C . Supernatant was discarded and the cells resuspended in 36% of isotonic Percoll ( Sigma ) . This suspension was mixed thoroughly , and separation was performed at 500 g , without breaks , for 10 min at 4°C . For lungs , single-cell suspensions were prepared by chopping the lungs into 10 mm3 pieces , incubating them in digestion buffer for 30 min at 37°C , and mechanically squeezing them through a 70 μM cell strainer . Erythrocytes were lysed using RBC lysis buffer . Cells were washed; resuspended in IMDM containing 10% iFBS , 100 U/ml penicillin ( Gibco ) , and 100 μg/ml streptomycin ( Gibco ) ( IMDM culture medium ) ; and checked for viability and cell number by trypan blue staining . Antibodies used for flow cytometry analysis were as follows: IL-4Rα ( mIL4R-M1 ) , CD3ε ( 500A2 ) , CD4 ( RM4-5 ) , CD8α ( 53–6 . 7 ) , CD25 ( 7D4 ) , CD19 ( 1D3 ) , Lineage , Foxp3 ( FJK-16s ) , GATA3 ( L50-823 ) , T-bet ( eBio4B10 ) , Bcl-6 ( K112-91 ) , RoRγt ( Q31-378 ) , Helios ( 22F6 ) , IRF4 ( irf4 . 3e4 ) , Ki67 ( B56 ) , Bcl-2 , caspase-3 ( C92-605 ) , FVS dye , CXCR3 ( CXCR3-173 ) , CD44 ( IM7 ) , CD62L ( MEL-14 ) , IFN-γ ( XMG1 . 2 ) , IL-4 ( 11B11 ) , IL-10 ( JES5-16E ) , IL-13 ( eBio13A ) , and p-STAT6 ( J71-773 . 58 . 11 ) purchased from BD Biosciences ( Franklin Lakes , NJ , US ) and eBioscience ( San Diego , CA , US ) . For staining of cell-surface markers , cells ( 1 × 106 ) were labeled and washed in PBS containing 1% BSA ( Roche , Switzerland ) and 0 . 1% NAN3 ( FACS buffer ) . For detection of intracellular cytokines , cells were seeded at a density of 2 × 106 cells/well in complete IMDM culture medium and stimulated with 50 ng/ml phorbol myristate acetate ( PMA ) , 250 ng/ml Ionomycin , and 200 μM monensin ( all from Sigma ) for 8–12 hr at 37°C in a humidified atmosphere containing 5% CO2 . After the incubation period , cells were harvested , washed , fixed in 2% ( w/v ) paraformaldehyde , permeabilized with 0 . 5% saponin buffer , and then stained for cytokine production as previously described [23] . For intranuclear staining , BD Pharmingen Transcription Factor Buffer Set ( BD Biosciences ) was used as per manufacturer's instruction for detection of transcription factors . Acquisition was performed using BD LSRFortessa ( BD Biosciences ) , and data were analyzed using FlowJo software ( Treestar , Ashland , OR , US ) . Genomic DNA was isolated from CD3+ CD4+ Foxp3− , CD3+ CD4+ Foxp3+ T cells and CD19+ B cells sorted using BD FACSAria III cell sorter ( BD Biosciences ) . Cell purity determined by flow cytometer amounted to at least 99% , and NanoDrop ( ND-1000 Spectrophotometer , Thermo Fischer Scientific ) was used for measuring DNA concentration and purity . Efficiency of il-4rα gene deletion was quantified by qPCR on LightCycler 480 Instrument II ( Roche ) using the following primers; exon 5: forward 5′ AACCTGGGAAGTTGTG 3′ and reverse 5′ CACAGTTCCATCTGGTAT 3′ , exon 8: forward 5′ GTACAGCGCACATTGTTTTT 3′ and reverse 5′ CTCGGCACTGACCCATCT 3′ . PCR conditions were 94°C for 2 min , 94°C for 20 s , 45°C for 30 s , and 72°C for 20 s for 55 cycles . Pooled cells from spleen and MLN from naïve Foxp3cre IL-4Rα−/lox mice and their littermate control were cultured at 5 × 106 cells/ml in RPMI medium ( Lonza , Walkersville , MD , US ) supplemented with 10% iFBS and penicillin and streptomycin ( 100 U/ml and 100 μg/ml ) ( RPMI culture medium ) for 40 hr at 37°C in a humidified atmosphere containing 5% CO2 , in medium supplemented with 0 or 1 ng/ml rIL-4 ( BD Biosciences ) . For measuring the level of STAT6 phosphorylation , spleen and MLN cells from naïve Foxp3cre IL-4Rα−/lox mice , their littermate control , and global knock-out mice were cultured at 1 × 106 cells/ml RPMI culture medium for 1 hr at 37°C in a humidified atmosphere containing 5% CO2 , in medium supplemented with 0 or 10 ng/ml rIL-4 . After the incubation period , cells were harvested , washed in FACS buffer , and then stained for IL-4Rα and/or p-STAT6 . IL-4Rα expression and level of STAT phosphorylation were detected by flow cytometry . In other settings , sorted CD4+ CD25+ T cells from naïve Foxp3cre IL-4Rα−/lox mice and their littermate control were cultured at 1 × 106 cells/ml in RPMI medium for 18 or 36 hr , at 37°C in a humidified atmosphere containing 5% CO2 , with 0 or 10 ng/ml rIL-4; then , cells were checked for survival and Foxp3 expression by flow cytometry . CD4+ T cells were enriched from a pool of naïve spleens and MLN cells by using EasySep Mouse T Cell Isolation Kit ( Stemcell Technologies , Vancouver , Canada , Catalogue no . 19852A ) as per the manufacturer’s instruction , and then , the CD4+ CD25− population was sorted by using BD FACSAria III cell sorter ( BD Biosciences ) . Sorted CD4+ CD25− cells ( 2 . 5 × 106 cells/ml ) were cultured with plate-bound anti-CD3 ( 10 μg/ml ) in the presence of soluble anti-CD28 ( 2 μg/ml ) and different concentrations of TGFβ ( 0 , 1 , or 2 ng/ml ) ( BD Pharmingen ) in 96-well , flat-bottomed plates in triplicates . After 3 d , the iTreg cells were analyzed by flow cytometry for CD25 and Foxp3 expression . Livers were collected and homogenized in lysis buffer ( PBS [pH 7 . 1] , 0 . 1% Tween 20 [Merck] , and 1% protease inhibitor cocktail [Sigma-Aldrich , St . Louis , MO , US , catalogue no . P8340] ) . Cytokines ( IL-4 , IL-5 , IL-10 , IL-13 , IFN-γ , and IL-17 , all from BD Pharmingen ) were measured in the protein extracts by sandwich ELISA as described previously [23] . Cytokine values were normalized according to the protein content measured by Pierce BCA Protein Assay Kit ( Thermo Fisher Scientific , catalogue no . 23225 ) . Hydroxyproline content as a measure of collagen production was quantified using a modified protocol [53] . In brief , weighed liver samples were hydrolyzed overnight at 110°C in 6 M HCl and then filtered through Whatman filter papers . Filtrate was neutralized with 1% phenolphthalein and titrated against 10 M NaOH . An aliquot was mixed with isopropanol and added to a chloramine-T/citrate buffer solution ( pH 6 . 0 ) ( Sigma ) . Ehrlich’s reagent solution ( 25 g p-dimethyl-amino-benzaldehyde , 37 . 5 ml 60% perchloric acid ) was added and measured at 570 nm using a VersaMax microplate spectrophotometer ( Molecular Devices ) . Hydroxyproline levels were calculated by using 4-hydroxy-L-proline ( Calbiochem , San Diego , CA , US ) as standard , and results were expressed as μg hydroxyproline per weight of liver tissue that contained 104 eggs . Statistical analysis was conducted using GraphPad Prism 4 software ( http://www . prism-software . com ) . Data were calculated as the mean ± SD . Statistical significance was determined using the unpaired Student t test and one-way ANOVA with Bonferroni’s posttest , defining differences to IL-4Rα−/lox mice as significant ( * , P ≤ 0 . 05; ** , P ≤ 0 . 01; *** , P ≤ 0 . 001 ) .
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Host soluble mediators such as cytokines play a key role in the regulation of the immune response . Forkhead box P3 ( Foxp3+ ) regulatory T ( Treg ) cells , which are involved in maintaining self-tolerance and immune system homeostasis , are influenced by cytokines , including interleukin-4 ( IL-4 ) . However , opposing reports have emerged on the effect of this cytokine on Treg cells . Some evidence suggests IL-4 inhibits Treg cells , whereas other studies indicate a supportive role for this cytokine in Treg cell biology and function . To unambiguously address this question , we generated mice with IL-4 receptor specifically removed from the Treg cell population . Our newly generated mice did not show any sign of spontaneous inflammation during homeostasis , but when challenged with an experimental infection by parasitic worms , deletion of the IL-4 receptor from the Treg cell population led to increased inflammation and aggravated tissue pathology . Several defects such as poor activation , reduced promigratory marker expression , and reduced survival were apparent in Treg cells with impaired IL-4 responsiveness . Our evidence presents a strong case for a supportive role of IL-4 via IL-4 receptor in the biology and optimal regulatory function of Treg cells during worm infections .
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2018
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The Foxp3+ regulatory T-cell population requires IL-4Rα signaling to control inflammation during helminth infections
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Cytomegalovirus ( CMV ) is a leading infectious cause of morbidity in immune-compromised patients . γδ T cells have been involved in the response to CMV but their role in protection has not been firmly established and their dependency on other lymphocytes has not been addressed . Using C57BL/6 αβ and/or γδ T cell-deficient mice , we here show that γδ T cells are as competent as αβ T cells to protect mice from CMV-induced death . γδ T cell-mediated protection involved control of viral load and prevented organ damage . γδ T cell recovery by bone marrow transplant or adoptive transfer experiments rescued CD3ε−/− mice from CMV-induced death confirming the protective antiviral role of γδ T cells . As observed in humans , different γδ T cell subsets were induced upon CMV challenge , which differentiated into effector memory cells . This response was observed in the liver and lungs and implicated both CD27+ and CD27− γδ T cells . NK cells were the largely preponderant producers of IFNγ and cytotoxic granules throughout the infection , suggesting that the protective role of γδ T cells did not principally rely on either of these two functions . Finally , γδ T cells were strikingly sufficient to fully protect Rag−/−γc−/− mice from death , demonstrating that they can act in the absence of B and NK cells . Altogether our results uncover an autonomous protective antiviral function of γδ T cells , and open new perspectives for the characterization of a non classical mode of action which should foster the design of new γδ T cell based therapies , especially useful in αβ T cell compromised patients .
Human CMV ( HCMV ) is a universally distributed pathogen that infects 50–90% of the world's population . Asymptomatic in healthy people , HCMV infection may lead to increased morbidity and mortality in immunocompromised individuals . Overall survival following transplantation is decreased when either the donor or the recipient is HCMV-seropositive [1 , 2 , 3] . Because of drug-related adverse effects and drug resistance there is growing interest for immunotherapy as an adjunct to antiviral therapy . Understanding the mechanisms developed by the immune system to control HCMV is therefore critical to enable the design of new curative or preemptive protocols aimed at enhancing patient immune defense against this virus . Effective immune control of HCMV has been compellingly shown to rely on both conventional lymphocytes and NK cells [4] . However , as we initially reported , HCMV also induces a robust γδ T cell response in organ transplant recipients [5]; and later , γδ T cell response to HCMV was extended to several other situations not always associated to immunosuppression; such as immunodeficiencies , bone marrow transplantation , pregnancy , elderly and also in healthy individuals [6 , 7 , 8 , 9 , 10 , 11 , 12] . HCMV-mediated persistent expansion of γδ T cells in transplant recipients is associated with infection resolution [13] , and implies tissue-associated Vδ2-negative γδ T cells which acquire a terminally differentiated phenotype upon HCMV pressure [10 , 14] . When isolated in vitro , these lymphocytes were shown to kill HCMV-infected cells , limit virus propagation and produce IFNγ through recognition of opsonized viruses [15 , 16] . Several features of γδ T cells might explain their specific relationship to HCMV: ( i ) they are not MHC restricted , and thus not affected by HCMV strategies to inhibit HLA molecules , ( ii ) they recognize self-antigens on the surface of stressed cells such as virus infected cells [17 , 18] and ( iii ) they are located at external body surfaces ( eg gut and lung ) and organs ( eg liver ) involved in HCMV transmission and replication [19] . Moreover , HCMV-reactive γδ T cells exhibit dual reactivity against tumor cells , due to the recognition of stress-induced self-antigens shared by HCMV-infected and tumor cells [15 , 18 , 20] . In agreement with this , HCMV-infection and/or γδ T cell expansion have been associated with reduced cancer risk in kidney transplant recipients [21] and with graft-versus leukemia effect in bone marrow transplant recipients [22 , 23 , 24] . All these specificities are consistent with an antiviral protective role of γδ T cells against HCMV and they thus represent valuable candidates for anti-HCMV immunotherapy especially in immunocompromised patients vulnerable to neoplasia . However , their role in protection and specific contribution within the global anti-CMV immune response has not been firmly established , nor their anatomical sites of activation and intervention . The aim of the present study was therefore to take advantage of the murine model of CMV infection to address these questions and to assess the respective ability of αβ and γδ T cells alone to protect mice from CMV infection . Murine CMV ( MCMV ) has been widely used to model the immune response to HCMV in mice since it reproduces with reasonable accuracy the antiviral response of CD8 T cells and NK cells [25] . Murine γδ T cells have been implicated in MCMV infection only once [26] , and their sufficiency for protection has not yet been addressed . We show herein that γδ T cells are as competent as αβ T cells to control MCMV infection and protect mice from death encouraging the development of novel anti-viral immunotherapeutic protocols based on γδ T cell manipulation .
In mice , MCMV-specific αβ T cells control viral spread and protect infected mice from death [27] but little is known regarding the implication of γδ T cells . To evaluate the respective contribution of αβ and γδ T cells to the immune response against MCMV , mice deficient for γδ T cells ( TCRδ−/− ) , for αβ T cells ( TCRα−/− ) or for both T cell subsets ( CD3ε−/− ) were challenged with 105 plaque forming units ( PFU ) of salivary gland MCMV . This dose was reported to be sublethal for C57BL/6 mice ( as described at http://mutagenetix . utsouthwestern . edu/protocol/protocol_rec . cfm ? protocolid=5 ) . Accordingly , 100% of CD3ε+/− control mice survived MCMV infection , whereas CD3ε−/− died about 4 weeks after viral challenge ( Fig . 1A ) , confirming the critical role of T cells in controlling MCMV infection . CD3ε−/− mice were extremely sensitive to MCMV despite the presence of NK cells [28] since they died at doses of MCMV as low as 2 . 103 PFU ( Fig . 1B ) . Unexpectedly , both TCRδ−/− and TCRα−/− mice survived as long as CD3ε+/− control mice . These results reveal that the presence of either αβ or γδ T cell subset was sufficient to protect mice from MCMV infection , disclosing the potentially critical function of γδ T cells in the immune response against MCMV . To examine whether this protection against CMV by γδ T cells relies on the control of viral loads , the kinetics of MCMV spread in T cell deficient versus T cell competent mice was determined in various organs . Comparison between each mouse line is shown in Fig . 2 and comparison between different time points is shown in S1 Fig . In the absence of T cells , MCMV DNA copy numbers increased substantially from day 3 to 24 , with up to 107 copies ( /100ng DNA ) in the spleen and lungs of CD3ε−/− mice before death . Interestingly , γδ T cells alone ( in TCRα−/− mice ) were sufficient to prevent an increase of viral load in all organs , except the salivary glands which are known to support prolonged virus replication even in wild-type mice ( S1 Fig . ) . At the end of these experiments , MCMV copies were much lower in T cell bearing mice than in mice without T cells ( Fig . 2 ) , underlining the inability of C57BL/6 mice to control MCMV infection in the absence of T cells . It was of particular interest to see that in the lungs γδ T cells were as potent as αβ T cells to control the viral load except at day 14 . As a whole , these results suggest independent control of MCMV spread by the αβ and γδ T cell subsets , revealing that γδ T cells are sufficient to control viral load and can substitute for the absence of αβ T cells . Hepatitis and pneumonitis are common features of CMV pathogenesis in both humans and mice . Hepatitis can be assessed in living infected mice through the quantification of transaminase levels in the serum . As shown in Fig . 3A , aspartate aminotransferase ( AST ) and alanine aminotransferase ( ALT ) only increased in the absence of all T cells ( CD3ε−/− mice ) , reaching up to 8 fold the basal level before death of CD3ε−/− mice . Accordingly , histological analysis of livers from CD3ε−/− infected mice before death ( day 22 ) showed typical features of active hepatitis , with many large granulomas mainly composed of histiocytic cells associated with multiple apoptotic hepatocytes ( Fig . 3B ) . In contrast , only a few small granulomas were observed in TCRα−/− mice livers at that time point . Furthermore , CD3ε−/− mice presented an active pneumopathy with large granulomas and hemorrhagic foci at day 22 , while TCRα−/− lung histology was close to normal with only a slight increase of inflammatory cells in the inter-alveolar septa ( Fig . 3B ) . In conclusion , CD3ε−/− mice showed clear evidences of both liver and lung diseases 3 weeks post MCMV infection , in agreement with the high viral loads found at that time in these organs . In contrast , liver and lung disorders were not observed in TCRα−/− mice , emphasizing the ability of γδ T cells to control MCMV infection and associated organ disease . Whether γδ T cells limit organ disease only as a consequence of viral replication control or also by producing mediators of tissue repair deserves further attention . We next sought to analyze whether the control of MCMV spread was associated with an amplification of γδ T cells in infected organs . S2 Fig . shows the gating strategy used for γδ T cell flow cytometry analysis . After a slight decrease at day 3 , γδ T cell numbers increased importantly in the lungs until day 21 ( approximately 8 fold ) , and this rise persisted until the end of the experiment . A significant but more modest and transient increase was also observed in the liver ( approximately 2 fold from day 3 to 7 ) . By contrast and to our surprise given their preponderance in gut intraepithelial lymphocytes , no significant variation of γδ T cells was observed in the intestine . In the spleen , γδ T cells levels remained stable until day 21 when they decreased ( Fig . 4A ) . In conclusion , control of MCMV infection by γδ T cells in TCRα−/− mice is associated with a transient γδ T cell increase in the liver , and a delayed but strong and persistent expansion of γδ T cells in the lungs . We next asked whether γδ T cells responding to MCMV differentiate into effector-memory cells as we observed previously in humans [10 , 14] . After a transient decrease early post MCMV challenge , the proportion of effector memory ( EM , CD44+CD62L− ) γδ T cells increased in the spleen , liver and lungs concomitantly with a decrease of central memory ( CM , CD44+CD62L+ ) γδ T cells . Effector memory γδ T cells reached more than 80% in the liver and lungs at day 56 ( Fig . 4B and 4C ) . Consistent with the absence of variation in γδ T cell numbers in the intestine , no modification of γδ T cells phenotype could be observed in this organ . These results confirm that MCMV induces a marked response of γδ T cells in the lungs and liver , which is more modestly seen in the spleen and absent from the intestine . The subsets of murine γδ T lymphocytes expressing the Vγ1 or Vγ4 chains of the TCR predominate in the spleen , liver and lungs , whereas intestinal γδ T cells are almost exclusively Vγ7+ ( nomenclature of Heilig and Tonegawa [29] ) . We assessed the quantity , repertoire and memory phenotype of these γδ T lymphocyte subsets in the liver , spleen and lungs . Not surprisingly , low proportions of Vγ1+ γδ T cells were found in the intestine ( S2 Fig . ) . As observed in Fig . 5A , the expansion of γδ T cells in the lungs and liver after day 3 concerned mainly Vγ1+ but also Vγ4+ γδ T cells . Both subsets followed the kinetics of total γδ T cells ( Fig . 4A ) . Analysis of subsets also showed a response of Vγ1+ , but not Vγ4+ T cells , in the spleen ( Fig . 4A and Fig . 5A ) . The proportion of EM cells among both Vγ1+ and Vγ4+ γδ T cells increased after day 3 in the lungs , liver and spleen ( Fig . 5B ) . In contrast , Vγ7+ γδ T cell numbers/memory phenotype did not vary significantly upon MCMV infection ( Fig . 5A and Fig . 5B ) , as could be expected from the analysis of the whole γδ T cell population in the intestine ( Fig . 4A and Fig . 4C ) . The complementary-determining-region ( CDR3 ) γ1 and CDR3γ4 length profile of liver , spleen and lung-derived γδ T cells were not different between uninfected and infected mice for 14 days ( S3 Fig . and S4 Fig . ) , indicating that there were no major changes in these CDR3 repertoires after expansion . γδ T cells development in CD3ε−/− mice was reconstituted by bone marrow ( BM ) transfer experiments using TCRα−/− mice as donors ( referred to as TCRα−/− > CD3ε−/− mice ) . This method allowed the generation of the BM-derived Vγ1+ and Vγ4+ γδ T cell subsets that were increased upon MCMV infection . Control BM transplants were also performed with TCRδ−/− donors ( TCRδ−/− > CD3ε−/− mice ) and with CD3ε+/− donors ( CD3ε+/− > CD3ε−/− mice ) . γδ and/or αβ T cell reconstitution was allowed to establish for 3 months before MCMV infection of the mice . γδ T cell subset percentages were analyzed in blood from live mice throughout reconstitution ( Fig . 6A ) . Two months after grafting , the percentages of blood γδ and/or αβ T cells ( among total lymphocytes ) had reached a plateau ( Fig . 6A ) . The proportion of peripheral blood γδ T cells in CD3ε+/− > CD3ε−/− mice was lower than that found in TCRα−/− > CD3ε−/− mice ( Fig . 6A , lower panel ) , in accordance with previous findings which showed that γδ T cells in TCRα−/− outnumbered γδ T cells in C57BL/6 mice [30] . When infected with MCMV at 3 months post-graft , TCRα−/− > CD3ε−/− mice survived MCMV infection as efficiently as CD3ε+/− > CD3ε−/− and TCRδ−/− > CD3ε−/− mice , in marked contrast with CD3ε−/− > CD3ε−/− mice ( Fig . 6B ) . In a second experimental scenario γδ T cells were purified from TCRα−/− splenocytes and injected intravenously ( i . v . ) into CD3ε−/− hosts one day before MCMV infection . Surprisingly , very low protection was obtained when γδ T cells isolated from control mice were transferred , whereas γδ T cells from MCMV-infected mice conferred good protection ( Fig . 6C ) . All together our results confirm the protective anti-CMV role of BM-derived γδ T cells , and show that priming of splenic γδ T cells with MCMV in donor mice is necessary for protection against MCMV after their adoptive transfer . We next sought to gain insight into the mechanism by which γδ T cells exert their antiviral function . CD27 expression was shown to segregate γδ T cells into two functional subsets in mice: CD27+ γδ T cells being the main producers of the antiviral cytokine IFNγ and CD27− γδ T cells being prone to secrete IL-17A which is not classically considered as important in antiviral responses [31] [32] . To determine which of these subsets respond to CMV , we analyzed their evolution in organs from MCMV-infected mice . As evidenced in S5A Fig . , CD27− cells dominated the γδ T cell response in the lungs , while CD27+ and CD27− subtypes were roughly equally implicated in the liver . However , IL-17A transcripts were barely detected in these organs ( S5B Fig . ) . By contrast , IFNγ was expressed in both these organs but noticeably peaked as early as day 3 , before the rise of γδ T cell numbers and Cδ transcripts ( S5B Fig . ) . Since the presence of IFNγ transcripts in organs from TCRα−/− infected mice could be attributed to NK cells , we determined IFNγ production at the cellular level by intracellular staining of lymphocytes and using the gating strategy shown in S6 Fig . As shown in Fig . 7A , the proportion of IFNγ-producing NK cells peaked at day 3 in all organs . IFNγ-producing γδ T cells also peaked 3 to 7 days post-infection ( Fig . 7A ) , but represented a minor population when compared to IFNγ-producing NK cells at similar time points ( Fig . 7B ) . Consequently , NK cells were the largely preponderant producers of IFNγ during early acute MCMV infection ( Fig . 7B ) , accounting for 2% of lymphocytes at day 3 in the liver and lungs ( i . e . when the relative expression of IFNγ was the highest , S5B Fig . ) . Similarly , during the course of infection , the proportions of CD107a+ NK cells were higher than that of CD107a+ γδ T lymphocytes ( S7 Fig . ) . These experiments are in accord with the substantial role of NK cells in the control of early MCMV infection through IFNγ production and cytotoxicity [33] , and suggest that the antiviral role of γδ T cells might not principally rely on these two functions . Considering the above results we hypothesized that γδ T cells could exert an indirect antiviral effect by promoting NK cells accumulation as has been previously reported [34] . We therefore compared the evolution of NK cell numbers early post-MCMV infection in TCRα−/− and CD3ε−/− mice . For both mouse lines and as depicted in C57BL/6 wt mice , the overall kinetic was organ-specific with an early decrease of NK cells in the spleen in contrast to liver ( Fig . 8A ) [35][36] . In contrast to our hypothesis and despite the MCMV-induced death of CD3ε−/− mice , NK cell numbers were globally higher in CD3ε−/− mice than in TCRα−/− mice at all early time points tested ( Fig . 8A ) , showing that γδ T cells antiviral activity was not due to an early increase of NK cells . In addition , when transferred into B/NK/T cells immunodeficient Rag−/−γc−/− mice , MCMV-primed γδ T cells were also strikingly sufficient to long term protect these mice from death ( Fig . 8B ) . At day 56 , γδ T cells could easily be detected in the liver , spleen and lungs of Rag−/−γc−/− recipient mice in contrast to NK cells , demonstrating that the protective function of γδ T cells could act in the total absence of NK cells ( Fig . 8C ) .
Previous work conveys compelling evidence for the implication of human Vδ2neg γδ T cells in the immune response against HCMV infection [5 , 6 , 7 , 9] . However , key questions that cannot easily be addressed in humans remain unanswered , such as the spatial and temporal regulation of the anti-HCMV γδ T cell response and its protective role . Because of its similarity with the human CMV pathogenesis and immune response , the mouse model of MCMV infection has been extensively used and is well characterized . The goal of this study was to take advantage of this model to address these questions concerning the protective role and localization of the γδ T cell response . Herein , we show that γδ T cells are as competent as αβ T cells to protect against CMV challenge , a finding that can be of particular relevance in clinical settings , situations or diseases where αβ T lymphocytes are compromised ( hypomorphic Rag1 mutations , individuals treated with immunosuppressive drugs , foetuses or neonates , … ) and where γδ T cells have already been shown to expand [6 , 7 , 8 , 9 , 10 , 11 , 12] . This protective function of γδ T cells , under conditions of suboptimal αβ T cell response , has previously been observed earlier in mice in the context of infection by Herpes Simplex Virus type 1 ( HSV-1 ) [37] or by the gut coccidian parasite Eimeria vermiformis [38] . These results also corroborate the conserved level of protection against infection observed in patients lacking TCR αβ T cells due to a mutation in the gene coding the TCR α chain [39] . Since γδ T cells have been shown to play an important role in young mice in other infectious models , it would be interesting to evaluate this role in the context of MCMV infection [40] . In addition to extending our results to more a “natural setting” of suboptimal αβ T cells responses , it would allow analysis of the role of non BM-derived γδ T cell subtypes [41] . Finally this MCMV model could be used to evaluate the importance of γδ versus αβ T cells in the context of immunosuppression as used in transplant recipients . After administration of MCMV via the intraperitoneal route , MCMV targets the liver and spleen as cell free viruses within the first hours before dissemination to the other organs [42] . Accordingly , viral loads were the highest at day 3 in the liver and spleen but peaked at day 7 in the lungs and intestine in all mouse lines tested in the present study . In TCRα−/− mice , viral loads were the lowest at day 14 in the liver and spleen and at day 21 in the lungs ( Fig . 2 ) , i . e . after the significant increase of both Vγ1+ and Vγ4+ γδ T cell subsets in the liver and lungs ( Fig . 4A ) , and of Vγ1+ γδ T cells in the spleen ( Fig . 5A ) . Three weeks post-MCMV infection , high viral loads and liver/lung injury were evidenced in CD3ε−/− mice despite normal development and function of NK cells in these mice [28] . In contrast , liver and lung disorders were not observed in TCRα−/− mice at that time . These results are consistent with a role for γδ T cell response/expansion in these organs to control virus multiplication and associated organ damage in the absence of αβ T cells . The protective role of γδ T cells was ascertained by reconstituting γδ T cells in CD3ε−/− mice by bone marrow transplantation , or by adoptive transfer of splenic γδ T cells from TCRα−/− MCMV infected mice . However , when isolated from the spleen of TCRα−/− uninfected mice , γδ T cells were inefficient to induce protection in CD3ε−/− recipients . We can exclude the possibility that lack of protection in CD3ε−/− mice which received naïve γδ T cells was due to an absence of engraftment , because both naïve and MCMV-primed γδ T cells were found in the liver , spleen and lungs of recipient mice ( S8 Fig . ) . The absence of protection by non-primed γδ T cells purified from splenocytes may be due to a delay of reconstitution/differentiation in recipient mice that allow the virus to overwhelm the γδ T cell response . Infection of donor mice by CMV most likely prime γδ splenocytes to readily respond to CMV once transferred in CD3ε−/− mice , compensating this reconstitution limitation . The development of the anti-CMV immune response involves a complex network of cells from the innate and adaptive immunity that act sequentially to favor health over disease . Research in mice has paid a lot of attention to the early control of MCMV by NK cells , which are responsible for the enhanced resistance of the C57BL/6 mouse strain when compared to BALBc mice . In C57BL/6 mice , NK cell antiviral activity relies on both perforin and IFNγ-release that control viral loads in the liver , spleen and lungs [33 , 43] . Our ex vivo analysis of lymphocytes from C57BL/6 TCRα−/− infected organs show that the early boost ( days 3–7 ) of IFNγ expression and cytotoxic granule exocytosis is mostly due to NK cells , while γδ T cells participate only modestly to these functions ( Fig . 7 and S7 Fig . ) . Thus , although we cannot exclude that this modest contribution might help in controlling MCMV loads , these results rather raise the possibility that γδ T cells operate either by regulating other immune cells or through the production of unknown antiviral mediators . Strikingly , however , our adoptive transfer experiment into Rag−/−γc−/− immunodeficient hosts showed that γδ T cell antiviral protective function can be independent of NK/B/αβ T cells . This emphasizes their efficiency and opens interesting perspectives for their possible manipulation in clinical situations where other immune cells are defective . The kinetics of γδ T cell response was organ specific , with a progressive increase and accumulation of γδ T cells in the lungs , whereas γδ T cells quickly increased and dropped at day 21 in the liver and spleen ( Fig . 4A ) . The persistence within the lungs of memory γδ T cells contrasts with the transient increase of pulmonary γδ T cells that was observed in other murine infectious contexts [44 , 45 , 46] . However it reproduces the persistence of γδ T cell expansion in human blood during HCMV-infection which could result from persistent activation of γδ T cells in chronically infected tissues [5 , 10] . This suggests that the lungs could be an anatomical site for replication of HCMV and chronic activation of γδ T cells , consistent with the fact that HCMV is frequently found in lungs of solid organ transplant patients where it can induce tissue invasive disease [4] . The γδ T cell response to MCMV implicates bone marrow derived Vγ1+ and Vγ4+ T cells . It will be interesting in the future to determine whether these subsets play similar functions in the response to MCMV , since evidence for distinct roles of Vγ1+ and Vγ4+ T cells in the protection and/or pathogenesis during infection of mice has been reported [46 , 47 , 48] . The involvement of several subsets in the response to MCMV is in agreement with the implication of diverse Vδ2neg T cell subsets ( Vδ1 , Vδ3 , Vδ5 ) in the response to HCMV [5] . In contrast to long term HCMV-induced γδ T cells that display a restricted CDR3δ length repertoire [5] , the CDR3γ1 and γ4 length repertoire of liver , spleen and lung-derived γδ T cells was equivalent in 14-days MCMV-infected and uninfected TCRα−/− mice ( S3 Fig . and S4 Fig . ) . This could reflect a TCR-independent innate-like response of γδ T cells and/or high frequencies of MCMV-specific γδ T cells already existing in naïve mice . However , we cannot exclude the presence of a shared antigen-recognition motif in CDR3γ of different lengths ( as observed for the CDR3δ of T22-specific γδ T cells [49] ) . The number of CDR3γ1 peaks ( 4 or 5 ) confirms previous analysis of CDR3 repertoire in mice [50] . Another interesting question concerns the memory function of γδ T cells during MCMV infection , as recently described for CD44+CD27− γδ T cells in mouse models of bacterial infections [51 , 52] . Adaptive and innate like γδ T cells could both participate to memory , in light of the emerging role for innate cells in this context [53] . Previous contact with HCMV induced a rapid recall expansion of effector memory Vδ2neg γδ T cells , which coincided with better infection resolution of HCMV reactivation in transplant recipients [10] . CMV infection in mice also induces CD44+CD62L− effector memory γδ T cells that are maintained and outnumber CD44+CD62L+ central memory γδ T cells at day 56 in all organs ( Fig . 4B and Fig . 4C ) . By definition , effector memory cells are prone to exert rapid functions at the aggression site and the results shown here support the hypothesis that peripheral blood effector-memory human Vδ2neg γδ T cells are re-circulating cells that originate from CMV-targeted organs . It remains to be investigated whether murine γδ T cells recognize self-encoded stress-regulated antigens on CMV-infected cells , as demonstrated for human γδ T cells [18] . Acute infections with HCMV can result in serious disease in infected neonates and in the context of immunosuppression linked to transplantation . Inducing or enhancing the antiviral response of γδ T cells in this context is an attractive objective . Our findings open new perspectives for the use of the murine model of MCMV infection to define the precise mechanism of antiviral activity of γδ T cells and to develop new strategies to induce their activation in vivo . Their absence of MHC restriction , their combination of conventional adaptive and innate-like responses , their particular anatomical localization and their dual reactivity against infected and tumor cells , are specific features that place γδ T cells as unique effectors for clinical manipulation . In conjunction with the identification of stress antigens recognized by γδ T cells on infected cells , these results open new avenues for clinical manipulation of γδ T cells against CMV-mediated disease .
All experimental procedures involving animals were conducted according to European Union guidelines ( European Directive 2010/63/UE ) ( http://ec . europa . eu/environment/chemicals/lab_animals/home_en . htm ) and approved by the local ethics committee: Comité d'éthique pour l'expérimentation animale de Bordeaux ( CE50 ) , [project n° 50120197-A] . We used C57BL/6 mice . CD3ε−/− [54] , TCRα−/− [30] and Rag−/−γc−/− mice [55] were from the CDTA ( Centre de Distribution , Typage et Archivage Animal , Orléans , France ) . TCRδ−/− [56] were a gift from Dr Malissen ( Centre d’Immunologie de Marseille Luminy , France ) . Mice were used between 8–12 weeks of age and kept under pathogen-free conditions ( Animalerie spécialisée , Université Bordeaux Segalen , France ) . CD3ε−/− were bred to C57BL/6 mice ( C57BL/6J , Charles Rivers laboratory , Larbresle , France ) to obtain CD3ε+/− control mice . MCMV-infection was performed in an appropriate animal facility ( Animalerie A2 , Université Bordeaux Segalen , France ) . MCMV was acquired from the American Type Culture Collection ( Smith strain , ATCC VR-194 ) and propagated into BALBc mice ( BALBcBy/J , Charles Rivers laboratory , Larbresle , France ) to generate MCMV salivary gland extracts . Virus titers were defined by standard plaque assay on monolayers of mouse embryonic fibroblasts ( MEF ) . Unless indicated , infections were performed by i . p . administration of 2 . 103 PFU of the salivary gland viral stock . Mice were bled via the retroorbital sinus after anesthesia ( one eye every other week ) and the serums collected and frozen . AST and ALT were quantified using standard enzymological methods ( laboratoire de Biochimie , CHU Bordeaux , France ) . Mice were euthanized by cervical dislocation . Liver and lungs were removed , fixed for 24 h in 3 . 7% neutral-buffered formalin ( Sigma-Aldrich ) , followed by standard histological processing and paraffin embedding . Sections of 4 μm thickness were processed for Hematoxylin/Eosin/Safran ( HES ) staining ( following standard protocols ) . Genomic DNA was isolated from organs using Nucleospin tissue purification kit ( Macherey Nagel ) . Real time PCR to quantify MCMV was performed in Step one plus thermocycler ( Applied biosystem ) using GoTaq qPCR Master Mix ( Promega ) with primers specific for MCMV glycoprotein B ( gB ) ( gi330510 , forward primer: AGGCCGGTCGAGTACTTCTT and reverse primer: GCGCGGAGTATCAATAGAGC ) . Known quantities of plasmid comprising MCMV gB were used for the titration curve . Total RNA from immune cells was prepared with Nucleospin RNAII kit ( Macherey Nagel ) . Goscript reverse transcriptase ( Promega ) was used to generate cDNA . Real time PCR was performed in CFX 384 ( BioRad ) . The relative expression of transcripts was determined using the GAPDH reference gene . For spectratyping analysis , PCR ( 40 cycles ) was performed with Vγ1 and Cγ4 or with Vγ4 and Cγ1 primers , resulting in amplification of the sequences containing the CDR3γ1 or CDR3γ4 , respectively . Then a run-off reaction ( one cycle ) was performed using a fluorescently labeled Jγ4-FAM primer for CDR3γ1 and with a Jγ1-FAM primer for CDR3γ4 ( primers sequences from [50] ) . The labeled reaction products were run on a capillary sequencer ( ABI3730xl analyzer ) at ImmuneHealth ( Gosselies , Belgium ) . The fluorescence intensity was analyzed using Peak Scanner 1 . 0 ( Applied Biosystems ) . List of primer Fw ( forward ) and Rv ( Reverse ) : GAPDH ( Genbank NM_008084 ) : Fw 5’-AATGGGGTGAGGCCGGTGCT-3’ Rv 5’-CACCCTTCAAGTGGGCCCCG-3’ IFNγ ( NM_008337 . 3 ) Fw: 5’-ACTGGCAAAAGGATGGTGAC-3’ Rv 5’-TGAGCTCATTGAATGCTTGG-3’ IL17-A ( NM_010552 . 3 ) Fw 5’-TCATCTGTGTCTCTGATGCTGTT-3’ Rv 5’-TTGGACACGCTGAGCTTTGA-3’ Cδ ( X12729 . 1 ) Fw 5’-CTGTGCACTCGACTGACTTTGAACC-3’ Rv 5’-CCCAGCACCGTGAGGGACATC-3’ CDR3γ1 Fw Vγγ1 5'-CCGGCAAAAAGCAAAAAAGT-3 Rv Cγ4 5’-AAGGAGACAAAGGTAGGTCCCAGC-3’ Jγ4-FAM 5'-TACGAGCTTTGTCCCTTTG-3' CDR3γ4 Fw Vγ4 5’-CTTGCAACCCCTACCCATAT-3’ Rv Cγ1 5’-CCACCACTCGTTTCTTTAGG-3’ Jγ1-FAM 5'-CTTAGTTCCTTCTGCAAATACC-3’ We used cell strainers to mash the spleens and livers in RPMI-1640 with 8% FBS; red blood cells were lysed with NH4Cl . For the liver , immune cells were isolated by centrifugation ( 2000 rpm , 20 min ) over a 40/80% discontinuous Percoll gradient ( GE Healthcare ) . Pulmonary mononuclear cells were isolated as described [57] . Intestinal intraepithelial mononuclear cells were isolated as described elsewhere [58] . Total organ live cells ( unstained with Trypan blue ) were then counted using a hemocytometer ( Malassez chamber ) . The proportion of γδ T cells ( CD3ε+panγδ+ ) and NK cells ( NK1 . 1+NKp46+ ) among total organ live cells ( 7AAD− ) was evaluated by FACS using a large FSC/SSC gate that included all cells but debris . This proportion was then multiplied by total organ cell number to obtain the absolute number of γδ T cells and NK cells . The following monoclonal antibodies were from BD Pharmingen: anti-CD3ε ( 145–2C11 ) , anti-TCRδ ( GL3 ) , anti-CD44 ( IM7 ) , anti-CD62L ( MEL-14 ) , anti-CD27 ( LG . 3A10 ) , anti-NK1 . 1 ( PK136 ) and anti-NKp46 ( 29A1 . 4 ) . Anti-IFNγ ( XMG1 . 2 ) , anti-CD107a ( 1D4B ) and respective isotype control mAbs: Rat IgG1κ ( eBRG1 ) and Rat IgG2aκ ( eBR2a ) were purchased from eBioscience . Anti-Vγ1 ( 2 . 11 ) , anti-Vγ4 ( 49 . 2 ) and anti-Vγ7 ( F2 . 64 ) mAbs were a kind gift from P . Pereira ( Institut Pasteur , Paris ) . For flow cytometry analysis , immune cells were first incubated with anti-mouse CD16/32 ( eBioscience ) and stained with relevant antibodies and 7-AAD ( BD Pharmingen ) . Fixed cells were acquired using a LSRFortessa ( BD Biosciences ) , and analyzed using FlowJo software ( Tree Star ) . For intracellular IFNγ staining , cells were incubated in complete medium for 2h at 37°C; 10μg/ml of Brefeldin A ( Sigma-Aldrich ) was added during the last hour . Intracellular staining was performed after cell surface staining , using BD Cytofix/Cytoperm Fixation/Permeabilization Kit and according to the manufacturer’s instruction ( BD Biosciences ) . For CD107a staining , cells were incubated in complete medium for 2h at 37°C; 10μg/ml Brefeldin A ( Sigma-Aldrich ) and anti-CD107a or isotype control mAb were added during the last hour . Cells were then stained with relevant monoclonal antibodies . Mice femora and tibia from CD3ε+/− , TCRα−/− , TCRδ−/− and CD3ε−/− were isolated and the BM was flushed with 1 ml of IMDM with FBS ( 1% ) . BM cells from one donor were injected to one CD3ε−/− mice ( 8–10 per group ) , intravenously ( i . v . ) through the retrobulbar sinus in a volume of 0 . 2 mL IMDM . Mice were conditioned by i . p . injections of Busulfan 22 . 5 mg/kg ( Pierre Fabre laboratory ) two days and one day prior to transplantation [59] . 10 TCRα−/− mice were uninfected , or 14 days infected with 2 . 103 PFU of MCMV . Immune cells were prepared from spleens and pooled before γδ T cell sorting using the TCRγ/δ+ T Cell Isolation kit ( Miltenyi Biotec ) . Purity was verified by flow cytometry and 8 . 105 to 1 . 106 γδ T cells i . v . transferred into CD3ε−/− or Rag−/−γc−/− recipients . 24h after γδ T cell transfer , recipient mice were infected i . p . with 2 . 103 PFU of MCMV and followed daily . 2–3 months after infection , recipient mice were sacrificed to verify the presence of γδ/NK cells in organs . Differences were evaluated by the Mann-Whitney test and represented as follows: * = p<0 . 05 , ** = p<0 . 01 , *** = p<0 . 001 , **** = p<0 . 0001 .
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γδ T cells are unconventional T lymphocytes that play a unique role in host protection against pathogens . Human Cytomegalovirus ( HCMV ) is a widespread virus that can cause severe organ disease such as hepatitis and pneumonitis in immune-compromised patients . Our decade-long study conveys compelling evidence for the implication of human γδ T cells in the immune response against HCMV , but their protective role could not be formally demonstrated in humans . In the present study we use the murine model of CMV infection which allows the spatial and temporal analysis of viral spread and anti-viral immune responses . We show that , in the absence of αβ T cells , γδ T cells control MCMV-induced hepatitis , pneumonitis and death by restricting viral load in the liver , lungs and spleen . γδ T cells expand in these organs and display memory features that could be further incorporated into vaccination strategies . In conclusion , γδ T cells represent an important arm in the immune response against CMV infection that could be particularly important in the context of αβ T cell immune-suppression .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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γδ T Cells Confer Protection against Murine Cytomegalovirus (MCMV)
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In mammals , taste buds develop in different regions of the oral cavity . Small epithelial protrusions form fungiform papillae on the ectoderm-derived dorsum of the tongue and contain one or few taste buds , while taste buds in the soft palate develop without distinct papilla structures . In contrast , the endoderm-derived circumvallate and foliate papillae located at the back of the tongue contain a large number of taste buds . These taste buds cluster in deep epithelial trenches , which are generated by intercalating a period of epithelial growth between initial placode formation and conversion of epithelial cells into sensory cells . How epithelial trench formation is genetically regulated during development is largely unknown . Here we show that Pax9 acts upstream of Pax1 and Sox9 in the expanding taste progenitor field of the mouse circumvallate papilla . While a reduced number of taste buds develop in a growth-retarded circumvallate papilla of Pax1 mutant mice , its development arrests completely in Pax9-deficient mice . In addition , the Pax9 mutant circumvallate papilla trenches lack expression of K8 and Prox1 in the taste bud progenitor cells , and gradually differentiate into an epidermal-like epithelium . We also demonstrate that taste placodes of the soft palate develop through a Pax9-dependent induction . Unexpectedly , Pax9 is dispensable for patterning , morphogenesis and maintenance of taste buds that develop in ectoderm-derived fungiform papillae . Collectively , our data reveal an endoderm-specific developmental program for the formation of taste buds and their associated papilla structures . In this pathway , Pax9 is essential to generate a pool of taste bud progenitors and to maintain their competence towards prosensory cell fate induction .
Taste buds consist of a group of clustered sensory cells and have been identified in all vertebrates . In the mammalian tongue , taste buds develop in different types of taste papillae: in fungiform papillae ( FUP ) distributed over the anterior dorsum of the tongue , in circumvallate papillae ( CVP ) located medially at the back of the tongue , and in foliate papillae ( FOP ) located laterally at the back of the tongue ( Figure 1A ) . In addition , taste buds form locally without associated papilla structures in the epithelium of the soft palate , throat , epiglottis and upper esophagus . Despite phyletic variations and different distribution patterns of taste papillae , taste buds in the dorsal tongue epithelium develop in all vertebrates , including amphibia , reptiles , birds and mammals . In contrast , larger taste papillae with higher morphological complexity such as the CVP and FOP evolved exclusively in the mammalian lineage [1] , [2] . Embryonic induction and development of taste buds have been widely studied in amphibia and rodents ( for a recent review , see [3] ) . These investigations concentrated mainly on the FUPs of mice and rats , which contain taste buds with taste pores that open directly into the oral cavity . FUP development starts around embryonic day 12 . 5 ( E12 . 5 ) and involves the formation of an array of epithelial placodes in the anterior two thirds of the tongue . The early patterning of FUP development is regulated by complex signaling processes and involves interactions between the Wnt/β-catenin , Shh and Bmp pathways ( [4]–[9] . In mice , each of approximately a total of 90 FUP contains a single taste bud , whereas in some mouse strains the single CVP may house more than 300 taste buds [10] , which are located in epithelial trenches that begin to grow into the underlying mesenchyme at E14 . 5 . In addition , small salivary glands ( von Ebner's glands ) develop together with the CVP and FOP [11] to facilitate gustatory sensation in taste buds located deep in the trenches . Thus , while taste buds of the FUP are formed by epithelial placodes that are established early in development , the placodes of the CVP and FOP undergo substantial morphological changes and intercalate a period of extensive epithelial growth to generate increased taste bud progenitor fields prior to the induction of taste bud cells . Whereas the CVP and FOP of mammals house the vast majority of taste buds , our understanding of the genetic control of their morphogenesis is surprisingly fragmentary . A single trench was found to develop in the CVP of Tabby mice , which lack ectodysplasin A [12] , [13] . A CVP placode is missing altogether in mice lacking a functional Fgf10 gene , which is expressed in the mesenchyme at the pre-placodal stage of CVP development [14] . A malformed CVP or reduction of CVP taste bud number has been described in mice lacking Dystonin , which show insufficient innervation caused by impaired development of the glossopharyngeal cranial nerve [15] , as well as in mouse mutants that are compromised in attracting nerve endings due to missing expression of neurotrophins in the CVP epithelium [16] . A recent study revealed a role for Six1 and Six4 in CVP development , however , the morphological abnormalities may partly result from defects during cranial nerve formation , which are seen in Six1/Six4-deficient mice [17] . Thus there are considerable gaps in our knowledge about the developmental mechanisms that regulate the expansion of the early taste bud progenitor cell population in the CVP and FOP epithelium . The paralogous genes Pax9 and Pax1 evolved from a single ancestral gene in the vertebrate lineage and form a subgroup within a total of nine members of the Pax gene family . Pax9 and Pax1 regulate different aspects of thymus , skeletal and craniofacial development [18]–[22] . Pax genes encode transcription factors and regulate the morphogenesis of a wide range of organs and are key factors for the development of mammalian sensory organs such as the eye ( Pax6 , Pax2 ) , nose ( Pax6 ) and ears ( Pax2 , Pax8 ) ( for reviews , see [23] , [24] ) . Here we show that Pax9 , previously not implicated in the development of sensory organs , regulates essential steps during the development of endoderm-derived taste papillae .
Epithelial expression of Pax9 in the developing oral apparatus of mice has been documented in the anterior foregut endoderm and its derivatives , as well as in the dorsal epithelium of the tongue [18] , [25] . Whole mount X-Gal staining of a developing Pax9+/LacZ [21] mouse tongue at embryonic day 13 . 5 ( E13 . 5 ) indicated that strong Pax9 expression is associated with the localization of placodes forming the CVP and FOP , respectively ( Figure 1B ) . Immunostaining revealed Pax9 expression in the epithelium of placodes and trenches throughout the embryonic period of CVP and FOP development ( Figure 1C–J ) . Pax9 was expressed normally in the region of the developing CVP of E13 . 5 and E14 . 5 mouse embryos lacking Fgf10 ( Figure S1 ) , a growth factor secreted by the posterior tongue mesenchyme and essential inducer of CVP development [14] . In contrast to the CVP , Pax9 is also expressed in the mesenchyme underlying the FOP epithelium ( Figure 1G–J ) in cells that are part of two discrete mesenchymal Pax9 expression domains at each side of the tongue ( arrowheads in Figure 1B ) . The expression of Pax9 was down-regulated in some domains of the epithelial trenches at E18 . 5 ( Figure 1F , J ) , a stage that precedes the early phase of taste bud induction in these papillae . Interestingly , while epithelial cells of the dorsal tongue were also stained , the central regions of placodes forming the FUP were negative for Pax9 at all stages of embryonic development ( Figure 1K–N ) . A histological analysis of serial sections of the three taste papilla types developing in the mouse tongue revealed that Pax9 is required for the formation of epithelial invaginations in both CVP and FOP . In homozygous Pax9LacZ/LacZ ( for simplicity referred to as Pax9−/− hereafter ) embryos , a CVP placode forms ( Figure S2 ) but the epithelial trenches are growth retarded at E16 . 5 and E18 . 5 ( Figure 2A–D ) . Similarly , invaginations of the FOP are missing and keratinocytes of the superficial layers are aberrantly enlarged in the mutant epithelium ( Figure 2E–H ) . Moreover , the thickness of the mesenchymal cell layer was greatly reduced in the mutant FOP at E18 . 5 . In contrast , the morphology of FUP appeared normal in Pax9−/− embryos ( Fig . 2I–L ) . To address the role of Pax9 in neural crest cell-derived mesenchymal cells located adjacent to the developing FOP ( Figure 1G–J ) , we inactivated the Pax9 gene in these cells by crossing Pax9flox ( Pax9fl ) mice [26] with transgenic mice expressing Cre under the control of Wnt1 promoter ( Wnt1Cre; [27] ) . While the Pax9fl/fl alleles were efficiently recombined in Wnt1Cre;Pax9fl/fl embryos , mesenchymal cells underlying the FOP were present and epithelial trenches formed in all ( n = 5 ) mutant FOP of Wnt1Cre;Pax9fl/fl embryos ( Figure 2M , N ) . These findings indicate that Pax9 function during FOP development is primarily required in epithelial cells . Postnatal Pax9 expression continues not only in the FUP epithelium but was also found in a few taste bud cells of the fully differentiated FUP ( Figure 3A ) . Since FUP development is completed postnatally and since taste buds do not form prior to 2 days after birth we asked if Pax9 could be required at these later stages of FUP development . Because Pax9−/− embryos die at birth , we addressed this question by using transgenic mice expressing Cre under the control of Keratin 14 ( K14Cre ) promoter [28] . Previous studies showed that K14 is expressed in basal cells of the tongue epithelium and in FUP but not in actual taste bud cells . However , lineage tracing experiments identified K14-positive epithelial cells located directly adjacent to the taste bud as a niche of stem cells renewing taste bud cells in the adult mouse [29] . X-Gal staining of K14Cre;ROSAR26 embryos confirmed efficient Cre activity in the dorsal tongue epithelium from E13 . 5 onwards ( Figure S3A , B ) and Pax9 immunostaining revealed complete removal of Pax9 protein in both FUP and its associated taste buds in adult K14Cre;Pax9fl/fl mouse tongues ( Figure 3B ) . Interestingly , the size and morphology of adult FUPs was not affected and FUP taste buds in these mutants appeared normal and formed taste pores ( Figure 3C–F ) . In addition , the number of FUP visible on the dorsal aspect of K14Cre;Pax9fl/fl mouse tongues ( 30 per tongue , n = 5 ) did not differ significantly ( p>0 . 79 ) from the number of FUPs of control mice ( 31 per tongue , n = 5 ) . To characterize the differentiation of the adult , Pax9-deficient FUP epithelium , we analyzed the expression of various keratin ( K ) proteins , which form intermediate filaments in cell type-specific combinations . We found that the keratin pair K1 and K10 , which are normally expressed throughout the differentiated suprabasal layers of the epidermis , were strongly up-regulated in the K14Cre;Pax9fl/fl FUP epithelium , as well as in the interpapillary epithelium ( Figure 3G–J ) . The expression of K6 , which is often seen in hyperproliferative epidermal cells [30] , was also up-regulated in the interpapillary epithelium , but not in the FUP epithelium itself ( Figure S4A , B ) . In contrast , the expression of K14 and K5 , which are normally found in basal cells of all stratified squamous epithelia , was not changed ( Figure 3G , H; Figure S4C , D ) . Finally , we did not observe changes of the expression of K8 , which marks taste bud cells in all taste papillae , as well as of Sox2 , a marker of mature taste bud cells and critical regulator for the formation of taste sensory cell [31] , in K14Cre;Pax9fl/fl mouse tongues ( Figure 3K–N ) . Together , these results indicate that Pax9 is not functionally involved in the development of the mouse FUP . Furthermore , although the Pax9-deficient FUP epithelium shows alterations of keratin expression patterns , these changes are not associated with apparent defects of FUP maturation and FUP maintenance in the adult mouse . In contrast , Pax9 is required for the formation of filiform papillae ( FIP ) , epithelial projections of the dorsal tongue epithelium that do not contain taste buds ( Figure 3E , F; [25] ) . Unlike the epithelium of the dorsal tongue , we did not detect full K14Cre activity in the CVP and FOP epithelium during embryonic development ( Figure S3A , B ) . At perinatal stages , K14Cre activity expands to posterior regions of the tongue ( Figure S3C ) and while complete inactivation of Pax9 gradually manifests in the CVP and FOP of K14Cre;Pax9fl/fl mice , Pax9 deficiency was not associated with obvious morphological defects in these taste papillae ( Figure S3D , E ) . In summary , the data indicate that Pax9 functions are not needed in adult taste papillae and that the requirement for Pax9 is restricted to the early steps of CVP and FOP morphogenesis . While the FOP of Pax9−/− mutants does not form any epithelial trenches , the CVP exhibits rudimentary invaginations ( Figure 2 ) and we thus chose the latter to characterize the cellular and molecular defects during embryonic CVP morphogenesis . SEM of the posterior tongue region showed that newborn Pax9−/− mice lack an accumulation of accessory papillae that normally surround the central domain of the CVP ( Figure 4A , B ) . We also noted increased desquamation of the posterior tongue epithelium and diastase-controlled PAS staining revealed strongly increased levels of glycogen in the area in which the CVP trenches normally develop ( Figure 4C , D ) . This differentiation defect is reminiscent of inappropriately increased deposition of glycogen regularly observed in the benign condition glycogenic acanthosis of the esophageal epithelium [32] . Moreover , a barrier assay revealed that only the central domain of the Pax9-deficient CVP was permeable to toluidine blue solution at E18 . 5 , whereas the surrounding mutant tongue epithelium has prematurely established a full barrier ( Figure 4E , F ) . Furthermore , the mutant CVP epithelium expresses high levels of Krt1 ( Figure 4G , H ) , a keratin gene that is normally expressed in the mouse skin and not in the tongue [25] but was found to be up-regulated in oral dysplasia [33] . Together , these findings document the inappropriate differentiation of the Pax9-deficient CVP epithelium . During mouse CVP development , taste buds become morphologically distinct from the surrounding trench epithelium two days after birth . Thus , to visualize epithelial domains that have started to initiate taste bud formation in the CVP at E18 . 5 , we analyzed the expression of K8 and Prox1 , which both mark taste bud primordia at this developmental stage [34] , [35] . Both markers identified groups of cells in wild type epithelial trenches but not in the trenches of Pax9-deficient mice ( Figure 4I–L ) . The same result was found using an Ascl1 ( previously called Mash1 ) probe for in situ hybridization ( Figure S5 ) . In addition , K8 expression , normally found in loosely aligned cells in the middle of each trench ( Figure 4K ) , was strongly reduced in the mutant CVP ( Figure 4L ) . Interestingly , expression of Prox1 and K8 was also found in the apical domain of the CVP in both wild type ( Figure S6A , B ) and Pax9-deficient mice at E18 . 5 ( Figure 4J , L; Figure S6C ) . We did not further investigate these structures , which are likely to represent immature taste buds that lack taste pores [36] and are known to disappear at early postnatal stages [37] . Afferent nerve fiber endings of the glossopharyngeal nerve make contact with the CVP epithelium from E14 . 5 onwards [38] . To analyze the pattern of CVP innervation , we stained for the neural marker PGP9 . 5 [39] , which revealed a close contact of nerve fibers with the trench epithelium of the wild type CVP ( Figure 4M ) . In contrast , although branches of the glossopharyngeal nerve were present at the Pax9-deficient CVP , we did not detect any penetration of the mutant trench epithelium by nerve endings ( Figure 4N ) . The Shh signaling pathway is active in taste papillae of the developing mouse tongue [40] and its inhibition was found to increase the number of FUP in the dorsal tongue epithelium [6] , [7] . At the early stage of CVP development ( E13 . 5 ) , we found Shh expression in the epithelial placode in both control and Pax9-deficient embryos ( Figure S2 ) . At E14 . 5 , in addition to the central , dome-like structure of the CVP , a ring of accessory papillae surrounding the center of the CVP was Shh-positive in controls , but not in Pax9−/− embryos ( Figure 5A , B ) . Similar patterns were obtained with probes for the Shh pathway downstream genes Ptch1 and Gli1 , in addition to a strong down-regulation of Gli1 expression in the center of the mutant CVP ( Figure 5A , B ) . In the developing FOP , Shh expression was considerably weaker compared to that of the CVP but expression in an indistinctly delimited area was consistently identified on both sides in the posterior part of the wild type tongue ( Figure 5C ) . In Pax9−/− mutants , Shh expression levels were below the detection threshold and only very weak expression of Ptch1 and Gli1 was found ( Figure 5D ) . In contrast , consistent with unaffected FUP development , Shh was normally expressed in the dorsal tongue epithelium of Pax9−/− mutants ( Figure 5E , F ) . Since the Shh pathway is an important modulator of epithelial morphogenesis during the development of various ectodermal appendages [41]–[43] we speculated that a reduction of Shh pathway activity in the developing CVP could be related to the impaired growth of the trenches in Pax9−/− embryos . To test this , we cultured mutant embryonic tongues in the presence of purmorphamine , a Shh signaling agonist that targets the Shh pathway effector protein Smoothened [44] . Under culture conditions used in this study , embryonic tongues dissected at E13 . 5 and cultured for 48 hours in control medium either formed a small CVP or an epithelial bud . In the presence of purmorphamine , the size of the mutant CVP ( n = 4 ) was significantly increased but growth was primarily stimulated in the central , dome-like domain of the CVP ( 3 out of 4 , Figure 5H ) . A similar response was observed in Pax9-deficient tongues cultured in the presence of a Shh protein-loaded bead placed next to the CVP . However , this result was only seen when the Shh protein-loaded bead was not displaced during culture ( Figure S7A , B ) . In contrast , an enlarged CVP dome or enhanced trench formation was not observed after purmorphamine treatment of explants from wild type embryos ( Figure S7C ) . The incomplete ability of Shh pathway activation to restore epithelial growth of the Pax9-deficient CVP prompted us to search for additional developmental pathways that may be affected in the CVP of Pax9−/− mutants . To screen for early molecular defects , a genome-wide RNA expression analysis of wild type and Pax9-deficient CVP dissected at E14 . 5 was carried out . The array data suggested that two genes encoding the transcriptional regulators Sox9 and Pax1 might present early targets of Pax9 in the developing CVP . Immunostaining indeed confirmed that both transcription factors are strongly expressed at the tips of invaginating trenches of the normal CVP , but not in the CVP of Pax9−/− mutants ( Figure 6A–D ) . Sox9 and Pax1 were shown to regulate epithelial cell proliferation in various developmental systems [45]–[47] and in agreement with these functions , counting of BrdU-positive cells at the tip of the growing trenches revealed a significant reduction of the number of proliferating cells in Pax9−/− mutants ( Figure 6E–G ) . Pax1 and Pax9 are paralogous genes and while they have redundant functions during vertebral column development [22] , the absence of Pax1 expression in the Pax9-deficient CVP rules out that Pax1 may compensate for the loss of Pax9 during early CVP development . Interestingly , Pax1 itself continues to be expressed and labels most taste bud cells in the wild type CVP and FOP of adult mice ( Figure 6H; Figure S8A ) . In contrast , Pax1 is not expressed in the dorsal tongue epithelium during FUP development or in the FUP of adult mice ( Figure S8B , C ) . Analysis of mouse mutants with a targeted deletion of Pax1 [48] showed that they develop shorter CVP trenches at E18 . 5 ( 111 µm in Pax1−/− mutants , 131 µm in control littermates , n = 8 , p<0 . 01 ) , while the width of the CVP was not significantly changed ( Figure 6I , J; Table S1 ) . Histological analysis of the CVP at postnatal day 16 revealed that the CVP of Pax1-deficient mice was noticeably smaller ( n = 3; Figure 6K , L ) . Corresponding with this growth retardation , counting taste buds of a complete series of sections of one Pax1 mutant CVP indicated that the total number of taste buds was reduced by more than 50% . Thus Pax1 expression in the CVP trenches is required for epithelial growth and for the generation of the normal number of taste buds in the mouse CVP . The posterior part of the secondary palate forms the soft palate which , in contrast to the hard palate , is movable and not supported by bones . Moreover , the oral mucosa of the soft palate is part of the gustatory system and forms taste buds , however , these taste buds lack supporting papilla structures and are directly embedded in the epithelium ( Figure 7D ) . During soft palate development , Pax9 expression was detected in the mesenchyme as well as in the epithelium prior to palatal shelf elevation ( Figure 7A ) . Taste placodes of the soft palate begin to form as epithelial thickenings at E14 . 5 and express Shh [49] . Both taste placodes and soft palate epithelium are Pax9-positive , whereas Pax9 is not expressed in the epithelium of the hard palate , which lacks these placodes ( Figure 7B , C ) . In newborn Pax9−/− mice , no clusters of taste bud progenitors were found in the soft palate epithelium ( Figure 7D , E ) and complete absence of Shh expression at E14 . 5 indicates that taste placode induction is not initiated in the soft palate of Pax9−/− mutants ( Figure 7F , G ) .
Taste perception at the back of the mammalian oral cavity serves as a critically important control mechanism to discriminate nutritious ingredients from substances that are potentially toxic to the organism . The formation of epithelial trenches that are rinsed by saliva produced in associated minor salivary glands enables a high concentration of functional taste buds to form in the narrow , posterior part of the tongue . The complex architecture of the CVP and FOP , and the close vicinity of numerous taste buds in these taste papillae predict the activities of developmental programs to differ from those regulating patterning and development of the FUP on the anterior dorsal tongue . Indeed , while loss of Fgf10 signaling in the mouse tongue mesenchyme results in the absence of the CVP , the spacing and size of FUP increased in these mutants [14] . In addition , similar to the differential expression of Pax1 shown in this work , expression of a Bmp4 reporter allele was detected in taste buds of the CVP but not in taste buds of FUP [50] . These fundamental differences may be attributed to the different embryonic origins of various taste papillae . Strong support for an entirely endoderm-derived origin of the CVP and FOP was recently provided by lineage tracing of Sox17-2AiCre/R26R mouse embryos [51] , [52] . The study also indicated that the FUP on the dorsal tongue are exclusively derived from ectodermal cells . During the development of the oral epithelium , expression of Pax9 is not restricted to endoderm-derived structures but is also seen in ectoderm-derived FUP as well as in non-sensory filiform papillae ( this work; [25] ) . Our results clearly demonstrate that Pax9-deficiency does not affect patterning , development or maintenance of the mouse FUP . Although this result was unexpected , it reinforces the conclusion that endoderm-specific developmental pathways regulate the formation of the gustatory system in the posterior region of the oral cavity . The early steps of CVP morphogenesis follow a sequence that is similar to that typically seen during the development of organs which form by epithelial-mesenchymal interactions . In analogy to the formation of , for example , a mammalian tooth or hair follicle , the CVP placode forms a bud-like epithelial structure that subsequently branches to form lateral invaginations . While the initial branching of the CVP bud is not affected in Pax9 mutant embryos , subsequent invagination of the epithelial trenches is blocked . Interestingly , a characteristic ring of accessory papillae normally surrounding the central dome of the CVP was not established in Pax9-deficient embryos . Whereas the developmental role of the accessory papillae has not been studied thus far , we found that they express Shh , suggesting that they may function as transient signaling centers and thereby contribute to CVP morphogenesis . The mitogenic effect of Shh has been documented in various epithelia [53]–[55] and we here found that activation of the Shh downstream pathway by purmorphamine increased the size of the Pax9-deficient CVP in embryonic tongue cultures . However , epithelial trench formation could not be rescued in these experiments , raising the possibility that precise timing and localization of Shh secretion by accessory papilla cells are required to restrict cell proliferation to the rudimentary trenches . Inhibition of the Shh pathway in rat embryonic tongue cultures was shown to increase the number of FUP [6] . While the external morphology of the CVP was not altered by Shh pathway inhibition , formation and growth of the epithelial trenches was not analyzed in these experiments . Recently , mouse reporter strains mapping the expression of the Shh pathway and its downstream genes in embryonic and adult FUP convincingly demonstrated an association between Shh expression and proliferation in neighboring epithelial cells [29] , [56] . Thus , in vivo experiments using genetic tools suitable to inactivate or activate the Shh pathway in the CVP in an inducible manner should help to identify the specific roles of Shh for patterning and morphogenesis during CVP development . Our analyses identified Pax9 as the first developmental regulator that is directly required for the expansion of taste progenitor cells in the developing mouse CVP . This progenitor field is normally established during a period of epithelial growth between E14 . 5 and E18 . 5 and our BrdU-labeling revealed a high proportion of cells that proliferate at the tip of the CVP trenches . Proliferation is significantly reduced in the invaginating epithelial CVP trench cells of Pax9−/− embryos , and this cellular defect is associated with a drastic down-regulation of Sox9 , a known regulator of epithelial cell proliferation in other developing organs [45] , [46] , [57] . Beside this , Sox9 is necessary to establish the stem cell compartment in the hair follicle [58] , raising the possibility that Sox9 could have a similar function in the CVP . Pax1 and Pax9 exhibit similar expression patterns during embryonic development and function in a redundant manner during the formation of the vertebral column [18] , [22] . Similarly , Pax1 and Pax9 both regulate aspects during the development of the thymus , which is derived from the foregut endoderm [20] , [21] . Interestingly , while Pax1 is more critically required during vertebral column development , the role of Pax9 is more important in foregut-derived organs , to which the expression of the common Pax9/1 precursor is restricted in early chordates [59] . The moderate CVP phenotype of Pax1−/− mice identified in this work appears to support this conclusion . Together , these findings suggest that the mammalian Pax9 gene has retained the original function of the common Pax9/1 precursor gene in the foregut endoderm , while Pax1 has acquired a predominant role in the axial skeleton during vertebrate evolution . Besides their functions in taste papilla formation , the expression of Pax9 and Pax1 in taste buds of adult mice suggests additional roles in the fully matured gustatory system . The absence of isolated , Pax9-positive cells in FUP taste buds after K14Cre-mediated recombination did not cause obvious morphological defects of the taste buds . However , as K14Cre is not active in actual taste bud cells , this finding supports the conclusion that stem cells from adjacent , non-sensory FUP cells contribute to the renewal of FUP taste buds [29] . While the roles of Pax9 and Pax1 in taste buds remain to be elucidated using appropriate genetic tools , it is tempting to speculate that they could be involved in the specification of sub-populations of mature taste bud cells . Absent expression of K8 and Prox1 and lack of contact by nerve endings in the developing CVP trenches , as well as premature barrier formation indicates a highly defective differentiation program of the posterior tongue epithelium of Pax9-deficient embryos . In the mutants , the arrest of CVP morphogenesis is associated with ectopic expression of Krt1 , a keratin gene known to be strongly up-regulated in dysplasia of the oral epithelium [33] , as well as with increased levels of glycogen , a feature seen in the benign condition glycogenic acanthosis [32] . It therefore appears likely that premature and inappropriate terminal differentiation of the CVP epithelium accounts , at least in part , for the incompetence of the CVP trench cells to interact with nerve fiber endings and to generate taste bud progenitors . Our data show that epithelial trench formation in the CVP and FOP is Pax9-dependent . A primary function for Pax9 in the expansion of taste progenitor fields in taste papillae with a higher degree of architectural complexity appears to be supported by the finding that taste papillae on the dorsal tongue , which lack epithelial trenches , develop normally in Pax9-deficient mice . However , although the soft palate epithelium does normally not form any recognizeable taste papilla structures , Pax9 is required for early Shh expression and for the induction of taste progenitor cells in this part of the oral cavity . Interestingly , lack of Shh expression in the taste placodes of the soft palate was also observed in mouse mutants lacking β-Catenin in the epithelium [60] , raising the possibility that Pax9 might interact with Wnt-signalling . A complete secondary palate only evolved in the mammalian lineage , whereas the tongue is present in amphibia , reptiles , birds , and mammals [1] . While the molecular mechanisms regulated by Pax9 in the soft palate epithelium remain to be identified , it is conceivable that Pax9 may have acquired an additional , early role for taste placode formation in the soft palate epithelium at a later period during the evolution of tetrapods .
All procedures were carried out under personal and project licenses issued by the Home Office , UK and were approved by the Local Ethics Committee . Mice were housed as described previously [61] . Embryos were staged by taking mid-day on the day of vaginal plug detection as embryonic day 0 . 5 ( E0 . 5 ) . The following mouse lines were maintained on the indicated genetic background , intercrossed to produce relevant genotypes and PCR genotyped according to references: Pax9lacZ ( C57BL/6; [21] ) , Pax9flox ( C57BL/6 x 129S2/SvPas; [26] ) , Wnt1Cre ( C57BL/6; [26] ) , K14Cre ( FVB/N; [28] ) , Pax1 ( C57BL/6; [48] ) , ROSA26R ( C57BL/6; [62] ) . Mouse tissues were prepared , processed , paraffin-embedded , sectioned , stained with haematoxylin and eosin and photographically documented as described previously [61] . Diastase-controlled Periodic acid-Schiff ( D-PAS ) staining was performed as described [63] . CVP size was measured using AxioVision software v . 4 . 3 ( Carl Zeiss ) and statistically analyzed by a two-tailed t-test ( Excel software , Microsoft ) . Pax9 immunohistochemical staining on paraffin sections was performed as described previously [64] with the following modifications . Antibodies were diluted in antibody diluent ( Dako , S3022 ) and incubated in the following order: rat anti-Pax9 ( 1∶40 ) , rabbit anti-rat IgG ( Dako , Z0494; 1∶50 ) , rat APAAP ( Dako , D0488; 1∶50 ) with three TBS washes in between each step . The last two steps were repeated and alkaline phosphatase activity was visualized using Fast Red ( Sigma ) as a substrate . Other primary antibodies were detected using the Envision+ System-HRP kit ( Dako , K4008 or K4010 ) according to the manufacturer's instructions . AEC ( Dako , K4008 ) and DAB ( Dako , K4010 ) substrates stain red and brown , respectively . Primary antibodies were used at the following dilutions: rabbit anti-PGP9 . 5 ( 7863-0504 , AbD Serotec ) , 1∶200; rabbit anti-Sox2 ( C70B1 , Cell Signaling ) , 1∶100; rabbit anti-Sox9 ( O9-1 , [65] ) , 1∶1000; rat anti-Pax1 [66] , 1∶40 . Following incubation with rat anti-Pax1 antibody , HRP-conjugated rabbit anti-rat IgGs ( Dako , P0450 ) were applied at 1∶200 dilution before using the rabbit-specific Envision+ detection system . To visualize proliferating cells , BrdU labeling and detection was performed as described previously [67] . Serial sections from three wild type ( 29 sections ) and three Pax9-deficient ( 28 sections ) E15 . 5 CVPs dissected 90 minutes after BrdU injection were prepared and BrdU-positive cells counted in a defined area at the tip of epithelial trenches . Statistical significance was assessed using a two-tailed t-test . For indirect immunofluorescence analysis , 5 µm cryosections were air-dried on Superfrost ultra plus slides ( Thermo Scientific ) for 2 hours at room temperature and then fixed for 10 minutes with pre-cooled acetone at −20°C . Immunofluorescence analysis was performed as previously described [68] , using the following primary antibodies: rabbit anti-K1 ( AF109 , Covance ) , 1∶1000; mouse anti-K10 ( DE-K10 , Progen ) , 1∶160; rabbit anti-K5 ( Covance ) , 1∶5000; guinea pig anti-K14 ( GPCK14 . 2 , Progen ) , 1∶50; mouse anti-K6 ( Ks6 . Ka12 , Progen ) , 1∶10; rat anti-K8 ( TROMA-I , Developmental Studies Hybridoma Bank ) , 1∶50 . Nuclei were stained with DAPI ( Invitrogen ) and secondary antibodies were species-specific fluorochrome-conjugated goat antibodies: Cy3-conjugated anti-mouse and anti-guinea pig , both 1∶200; Alexa 594-conjugated anti-rat and Alexa 488-conjugated anti-rabbit , both 1∶400 ( Molecular Probes ) . Microscopic analysis was performed using a Leica SP2 UV confocal microscope operated through LCS 2 . 61 software ( Leica Microsystems ) . Tongue barrier assays and whole-mount X-gal staining were performed as described previously [25] , [21] . For SEM , tongues were fixed in 2% glutaraldehyde/PBS , dehydrated through a graded series of ethanol followed by carbon dioxide incubation in a Samdri 780 Critical Point Dryer . The specimens were then mounted on an aluminium stub with Acheson Silver Electrodag ( Agar Scientific ) and coated with gold using a Polaron SEM coating unit . Specimens were examined and photographed using a Stereoscan 240 scanning electron microscope . SEM images taken from flat-mounted tongues of 4 months old mice were also used to count the number of FUPs that were directly visible on the dorsal tongue surface . RNA in situ hybridization of whole embryonic specimens and of tissue sections using digoxygenin-labelled cRNA probes was performed as described previously [67] . cRNA probes were produced for Shh ( 0 . 6 kb; MGI:1327804 ) , Ptch1 ( 2 . 2 kb; MGI:3833867 ) , Gli1 ( 1 . 7 kb; MGI:12533 ) , Prox1 ( 0 . 5 kb; [69] ) , Ascl1 ( 0 . 7 kb; [69] ) , and Krt1 ( 0 . 5 kb; [25] ) . Embryonic mandibles including tongues were dissected at E13 . 0 and cultured for two days as described previously [70] , [4] . Before culture , the specimens were embedded in growth factor-reduced Matrigel ( BD Biosciences , Cat . No . 305128 ) to prevent them from flattening during culture . To activate the Hh pathway , 4 µM purmorphamine ( Calbiochem , Cat . No . 540220 ) was added to the culture medium . Alternatively , Affi-Gel Blue gel beads ( Bio Rad , Cat . No . 153-7302 ) were soaked in recombinant mouse SHH protein ( 1 . 25 mg/mL in PBS; R&D Systems , Cat . No . 461-SH ) or BSA for at least an hour and the beads were then placed onto the tongue epithelium close to the developing CVP .
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Gustatory perception is an evolutionary ancient sense , and the ability to discriminate toxic and digestible substances is vitally important for all organisms . In mammals , taste perception occurs in taste buds , groups of sensory cells that are housed in various types of taste papillae in the oral cavity . Little is known about the genetic and developmental programs that underlie the different architectures of these papillae . Using mouse models , we identified the transcription factor Pax9 as a major determinant for the development of endoderm-derived taste papillae , which develop in different locations in the back of the oral cavity . In these papillae , Pax9 regulates the expansion of the taste progenitor field , maintains the competence of these progenitors to interact with afferent nerve fibers of the glossopharyngeal nerve , and prevents their differentiation towards epidermal-like epithelial cells . In contrast , Pax9 is not required for the development of ectoderm-derived taste papillae that are distributed over the dorsum of the tongue . Our data reveal that mammals have evolved a specific developmental program to generate taste buds and associated papilla structures in different parts of the oral cavity .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology",
"growth",
"control",
"cell",
"fate",
"determination",
"embryology",
"mutation",
"anatomy",
"gene",
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"genetics",
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2014
|
The Formation of Endoderm-Derived Taste Sensory Organs Requires a Pax9-Dependent Expansion of Embryonic Taste Bud Progenitor Cells
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Severe fever with thrombocytopenia syndrome ( SFTS ) is an emerging disease that is caused by a novel bunyavirus , referred to as SFTS virus . During January 2011 to December 2011 we conducted a case-control study in Henan , Hubei and Shandong Provinces of China to determine the risk factors for SFTS . Case-patients were identified in hospitals and reported to provincial Centers for Disease Control and Prevention while being notified electronically to the National Surveillance System . Controls were randomly selected from a pool of patients admitted to the same hospital ward within one week of the inclusion of the cases . They were matched by age ( +/−5 years ) and gender . A total of 422 patients participated in the study including 134 cases and 288 matched controls . The median age of the cases was 58 . 8 years , ranging from 47 . 6 to 70 . 1 years; 54 . 5% were male . No differences in demographics were observed between cases and controls; however , farmers were frequent and more common among cases ( 88 . 8% ) than controls ( 58 . 7% ) . In multivariate analysis , the odds for SFTS was 2 . 4∼4 . 5 fold higher with patients who reported tick bites or presence of tick in the living area . Other independent risk factors included cat or cattle ownership and reported presence of weeds and shrubs in the working environment . Our findings support the hypothesis that ticks are important vectors of SFTS virus . Further investigations are warranted to understand the detailed modes of transmission of SFTS virus while vector management , education on tick bites prevention and personal hygiene management should be implemented for high-risk groups in high incidence areas .
Severe fever with thrombocytopenia syndrome ( SFTS ) is an emerging disease that is caused by a novel bunyavirus , as referred to as SFTS virus ( SFTSV ) [1] . To date , the disease has only been reported in mainland China , Japan and Korea [2] , [3] and which is characterized by high fever , thrombocytopenia , leukopenia , elevated serum hepatic enzyme levels , bleeding and multi-organ dysfunction and has an estimated case-fatality rate of 12% [4] , [5] . The clinical manifestations can barely be differentiated from hemorrhagic fever with renal syndrome caused by hantavirus or human anaplasmosis [6] , [7] . SFTSV is classified as a member of genus Phlebovirus , and thought to be transmitted by ticks as the virus has been isolated in Haemaphysalis longicornis ticks [1] . On a few account , the disease was also reported to transmit from person to person through contact with infected patient's blood or mucous [5] , [6] . Real time RT- PCR and ELISA IgM are considered the assays of choice for early detection of SFTSV [8] , [9] . In China , since 2010 SFTS has been a notifiable disease that should be reported within 24 hours as indicated by the National Notifiable Disease Surveillance System ( NNDSS ) and the national guideline for prevention and control of severe fever with thrombocytopenia syndrome ( 2010 edition ) [10] . To date , cases have been reported in rural in the east and central part of China . The largest number of reported cases were in Henan , Hubei and Shandong provinces [11] , [12] . During 2010–2011 most ( 75% ) SFTS cases in China occurred yearly between May and August . Patients aged from 1 to 90 years ( median , 58 years ) and most were farmers ( 81% ) including agricultural and forest workers from rural areas [13] , [14] . Until now , we have not found any vector competence studies performed for SFTSV . The mode of SFTSV transmission remains unclear [15]–[17] , and further investigations for risk factors are needed to effectively prevent and control the disease . Here we reported the first results of such a study which was conducted during January 2011 to December 2011 in Henan , Hubei and Shandong Provinces , China .
Informed consent was obtained from all study subjects prior to participation . All participants' personal identifiers were anonymized for confidentiality before China CDC received the dataset for pooled analysis . The study was approved by the Human Bioethics Committee , China CDC . The Chinese Center for Disease Control and Prevention ( China CDC ) collaborated with provincial CDCs of Hubei , Henan and Shandong to design and conduct a risk factors-related case control study in affected areas . Cases were detected in hospitals and reported to provincial CDCs while being reported electronically to the NNDSS . Controls were randomly selected from a pool of patients admitted in the same hospital ward within one week of the inclusion of the cases . They were matched by age ( +/−5 years ) and gender regardless of symptoms ( Tables 1 & 2 ) . When prodromal symptoms were present , the investigators of the local CDC would go to drawn the suspected case's blood . In the meanwhile , they would also search for the control for blood according to the matching requirement . Then the blood sample would be further confirmed in the labs . As stated in the National guideline for prevention and control of severe fever with thrombocytopenia syndrome ( 2010 edition ) [7] , an SFTS case is defined as a patient who presents with fever ( temperature is ≥38°C ) associated with thrombocytopenia and leukopenia and subsequently requires testing for SFTSV . In this study , case subjects were defined as SFTS patients who had positive real-time RT-PCR for SFTSV or positive for IgM ELISA [1] . Control subjects were defined as matched patients whose laboratory testing for SFTSV infection ( i . e . RT-PCR , IgM and IgG ELISA during the acute phase ) was negative . The clinically diagnosed cases and controls' sera which collected by provincial CDC were separated from blood , aliquoted and transported in a cold box ( 4°C–8°C ) to provincial CDCs' laboratories for testing . Confirmation consisted of real-time RT-PCR assay for SFTSV RNA and ELISA serology for IgM antibodies against SFTSV . All diagnostic kits were provided by the National Institute for Viral Disease Control and Prevention of China CDC in Beijing and laboratory technicians received refresher courses regarding testing techniques . Fifty professionals from China CDC , provincial and county CDCs were trained to interview and administer a standardized questionnaire to cases and controls . About 70 clinicians across primary , secondary and tertiary hospitals were also trained on case reporting . These clinicians also accepted differential diagnoses refresher courses for SFTS . Participants/patients were asked about their demographics ( age , gender , ethnic group , home address , occupation ) , living environment ( e . g . landform , environment , poultry , animal raising , house rats , wild animals ) , exposure history within the previous 2 weeks prior to fever onset ( e . g . travel history , tick bites , contact with suspected SFTS patients , contact with similar cases ) and contacts with animals ( animal species and types of vectors ) . Completed questionnaires were systematically verified by China CDC study coordinators for data completeness . Data were double-entered into an Epidata 3 . 02 ( the EpiData Association , Denmark , Europe ) database followed by consistency checking . SPSS version 18 . 0 ( Statistical Product and Service Solutions , Chicago , IL , USA ) was used for all statistical analyses . All tests were 2-tailed; statistical significance was set at P<0 . 05 , without correction for the number of statistical tests performed . We compared proportions with use of Pearson Chi-Square and Fisher's exact test . In multivariate analysis , maximum likelihood estimates for the matched odds ratios ( ORs ) were calculated using a conditional logistic regression model and the Wald test . We retained in the model the significant variables ( P<0 . 05 ) .
A total of 422 persons participated in the study including 134 cases and 288 matched controls . And 13 counties and 23 hospitals took part in the research with no refusals . The matching ratio is about 1∶3 . On PCR testing , only 46 cases had positive results . And 22 cases' IgM ELISA results were positive . The median age of the cases was 58 . 8 years ( range , 47 . 6∼70 . 1 years ) and 54 . 5% were male . No differences in demographics ( e . g . gender , ethnicity and residence ) were observed between cases and controls; however , farmers were frequent and more common among cases ( 88 . 8% ) than controls ( 58 . 7% ) . All of the cases' ethnicity were Han . As shown in the univariate analysis , potential risk factors for SFTS included those associated with ownership or contact with domestic animals , presence of rats in the households , potential exposure to wild animals , indirect or direct exposure to ticks , and contact with potentially contaminated environment . Details are presented in table 3 . In the multivariate analysis , the odds ratio for SFTS was 2 . 4 to 4 . 5 fold higher with patients who reported tick bites or presence of ticks in the living area . Other independent risk factors included cat or cattle ownership and , reported presence of weeds and shrubs in the working environment ( Table 4 ) .
This study was conducted during the early phase of the discovery of the virus and should be seen as a preliminary step within an in-depth investigation of risk factors for SFTS when it was urgent to confirm the role of ticks as the main vector of transmission . The detailed modes of transmission of SFTSV were not addressed in the study and warrants further investigations . Direct contacts with animals especially those that are free-roaming and participating in outdoor activities in dense vegetation areas increase opportunities for people to be bitten by ticks . Integrated vector management and ecosystems interventions should be implemented to reduce the density of ticks in working and living environments . Education on tick bites prevention and personal hygiene management are of utmost importance for high-risk groups in high incidence areas .
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Since 2009 , an emerging infectious disease which was identified as the severe fever with thrombocytopenia syndrome ( SFTS ) was reported in rural areas of Hubei , Shandong and Henan provinces in China . A novel bunyavirus designated severe fever with thrombocytopenia syndrome bunyavirus ( SFTSV ) had been identified to be the etiological cause of SFTS . But what risk factors lead to the disease is still not clear . Further investigations for risk factors are needed to effectively prevent and control the disease . Here we have designed case-control study to try to develop the risk factors of the spread of SFTSV . It is hoped that our research could provide epidemiological evidence for further study . Also help to determine the spread of the virus in the environment .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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2014
|
Risk Factors for Bunyavirus-Associated Severe Fever with Thrombocytopenia Syndrome, China
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Cholera is endemic in Bangladesh , with outbreaks reported annually . Currently , the majority of epidemic cholera reported globally is El Tor biotype Vibrio cholerae isolates of the serogroup O1 . However , in Bangladesh , outbreaks attributed to V . cholerae serogroup O139 isolates , which fall within the same phylogenetic lineage as the O1 serogroup isolates , were seen between 1992 and 1993 and in 2002 to 2005 . Since then , V . cholerae serogroup O139 has only been sporadically isolated in Bangladesh and is now rarely isolated elsewhere . Here , we present case histories of four cholera patients infected with V . cholerae serogroup O139 in 2013 and 2014 in Bangladesh . We comprehensively typed these isolates using conventional approaches , as well as by whole genome sequencing . Phenotypic typing and PCR confirmed all four isolates belonging to the O139 serogroup . Whole genome sequencing revealed that three of the isolates were phylogenetically closely related to previously sequenced El Tor biotype , pandemic 7 , toxigenic V . cholerae O139 isolates originating from Bangladesh and elsewhere . The fourth isolate was a non-toxigenic V . cholerae that , by conventional approaches , typed as O139 serogroup but was genetically divergent from previously sequenced pandemic 7 V . cholerae lineages belonging to the O139 or O1 serogroups . These results suggest that previously observed lineages of V . cholerae O139 persist in Bangladesh and can cause clinical disease and that a novel disease-causing non-toxigenic O139 isolate also occurs .
During 1992–93 , V . cholerae O139 was first recognized in Bangladesh , India and other countries in Southeast Asia as a causative agent of epidemic cholera [1–3] . Prior to this , the O1 serogroup was considered the sole cause of cholera epidemics [4] . The isolation of O139 from clinical cases declined quickly after the initial outbreak , with the exception of one epidemic in August 2002 in Dhaka city [5] . Following on from this , isolates of the O139 serogroup were also isolated sporadically from clinical and environmental samples from various regions of Bangladesh during 2005 , although no large-scale outbreaks of cholera attributed to O139 serogroup V . cholerae were reported during this time [5 , 6] . Since then , clinical cholera in Bangladesh has been caused entirely by the V . cholerae O1 serogroup , with an unexplained disappearance of V . cholerae O139 [5] . With the recent publication of whole genome-based phylogenies of V . cholerae , we are able to see how the isolates responsible for global cholera relate to each other [7] . It is clear from these data that the isolates causing the current ( seventh ) pandemic of cholera form a highly related monophyletic lineage dominated by isolates of the El Tor biotype and of the O1 serogroup . This phylogeny , based on whole genome sequence of clinical isolates , shows three overlapping global expansions of V . cholerae since the pandemic began , denoted wave I , II , and III . From sequencing of a limited number of O139 isolates , it has been shown that they form a single distinct phylogenetic branch that falls within wave II of the seventh pandemic El Tor lineage [7] . At one time , O139 isolates were thought to represent a new lineage of V . cholerae that would spread globally and perhaps even replace the O1 serogroup . Since the O139 serogroup of V . cholerae was first recognized , it has been included in cholera surveillance initiatives and in vaccine design efforts [1 , 8] . However , pandemic wave II O139 and O1 serogroup isolates are increasingly rare , being replaced almost exclusively by O1 serogroup wave III strains , causing disease globally . Here we report the isolation , characterization and sequence analysis of recent isolates of V . cholerae O139 recovered from stools of patients hospitalized at the icddr , b diarrheal hospital , as well as from asymptomatic members of the patients’ households . The aim of this study was to compare these new V . cholerae O139 isolates to existing O139 and O1 isolate sequence data to determine if these new cases were caused by new O139 variants , or the persistence of strains that belong to the known O139 lineage . This will inform the management of future cholera epidemics .
This study was carried out in patients presenting to the icddr , b diarrheal hospitals in the Mohakhali and Mirpur neighborhoods of Dhaka , as well as from asymptomatic household members of the cholera patients between December 2013 to March 2014 . These patients were enrolled either from the systematic surveillance system for enteric pathogens at the icddr , b Mohakhali hospital , through other ongoing cholera studies [9–11] , or through passive surveillance for cholera being conducted at these health facilities as part of a vaccination campaign with oral killed cholera vaccine Shanchol in Dhaka , Bangladesh [11] . Demographic , socioeconomic , and clinical data were obtained from all study participants . Trained study staff or hospital physicians performed a clinical examination of all study participants . Study participants were assessed for degree of dehydration according to WHO guidelines [12] and treatment was provided according to the icddr , b protocols [13] . All participants gave informed consent for collection of stool/rectal swab specimens . Rectal swabs were collected from case 1 and case 3 because fresh stool specimens were not available . Fresh stool specimens as well as stool swabs were collected from case 2 and case 4 . All rectal swabs were placed in a Cary Blair medium and transported to the icddr , b laboratory at room temperature . Two swabs were obtained from each patient . In the laboratory , the first rectal swab taken from each patient was cultured directly on to taurocholate tellurite gelatin agar ( TTGA ) and the second swab was enriched in alkaline peptone water and incubated at 37°C overnight [14] . After incubation and further culture on TTGA plates , suspected colonies resembling V . cholerae were tested by slide agglutination with monoclonal antibodies specific for V . cholerae O1 and O139 [15] , as well as by biochemical assays . Specimens that were positive for V . cholerae O139 were stored at −70°C and later examined by a multiplex PCR assay for concurrent detection of rfb sequences specific for O139/O1 genes of V . cholerae and for ctxA-specific sequences [16] . Toxigenic V . cholerae O139 ( CIRS 134B ) and V . cholerae O1 El Tor Inaba ( strain N16961 ) and classical Inaba ( strain 569B ) serotypes were used as positive controls for the multiplex PCR assay . Strains were tested for antimicrobial resistance by disk diffusion method using azithromycin , ciprofloxacin , ceftriaxone , erythromycin , mecillinam , norfloxacine , nalidixic acid , trimethoprim sulfamethoxazole , and tetracycline . The four V . cholerae O139 isolates were tested in the rabbit ileal loop assay [17] to detect fluid accumulation and enterotoxicity . V . cholerae O1 strains 569B and N16961 were used as positive controls . Detection of cholera toxin ( CT ) was performed by ganglioside GM1-specific enzyme linked immunosorbent assays ( ELISA ) [18] and differentiation of classical and El Tor biotype CT was made using MAMA PCR described previously [19] . Multiplex PCR assays were performed on a Thermo cycler C-1000 instrument ( Bio-Rad ) . Two sets of oligonucleotide primer pairs were used . The first was O139 rfb-F ( 5´- AGCCTCTTTATTACGGGTGG-3´ ) , O139 rfb-R ( 5´-GTCAAACCCGATCGTAAAGG-3´ ) , and the second one was ctxA-F ( 5´-CTCAGACGGGATTTGTTAGGC-3´ ) , ctxA-R ( 5´TCTATCTCTGTAGCCCCTATTA-3´ ) ; these pairs were used to amplify O139 rfb ( amplicon size 449 bp ) and ctxA ( amplicon size 302 bp ) genes respectively using previously described procedures [16] . The product was analysed on 1% agarose gel using Gel Red ( BioTium , USA ) stain for visualization . Genomic DNA was extracted from eight V . cholerae strains collected in Bangladesh; Strain 5 , Strain 6 , Strain 7 and Strain 8 in 1993 and Strain 9 to 12 in 2002 as well as the four V . cholerae O139 isolates collected in 2013 and 2014 . Genomic DNA was prepared by incubating a fresh V . cholerae colony from a gelatin agar plate into 5 mL of LB broth with overnight shaking at 37°C at 150 rpm . Genomic DNA was extracted with a DNA pure extraction kit ( QIAGEN , Germany ) according to the manufacturer’s recommendations . Specimen DNA was stored at -70°C and shipped in dry ice to the Wellcome Trust Sanger Institute for sequencing and whole genome analysis . Isolates were sequenced as multiplexed libraries on an Illumina MiSeq machine , producing 150 nucleotide paired-end reads . Whole genome sequence analysis on the four V . cholerae O139 isolates collected in 2013 and 2014 was carried out and compared with data from the eight strains collected in Bangladesh in 1993 and 2002 ( S1 Table ) . The data generated were combined with previously published V . cholerae genome sequence data [7] from representative O1 seventh pandemic El Tor global wave I , II and III strains , as well as three wave II O139 seventh pandemic El Tor isolates , and used to construct a whole genome single nucleotide polymorphisms ( SNP ) -based phylogeny . To achieve this , reads for all isolates were mapped to the V . cholerae O1 El Tor strain N16961 ( accession AE003852/AE003853 ) reference sequence using SMALT v0 . 7 . 4 [20] , and with GATK for indel realignment [21] . SNPs were called using a combination of SAMtools [22] mpileup and BCFtools as described previously [23] . SNPs falling in regions identified as being recombinant and so not likely to reflect the underlying phylogeny of the bacterium were excluded from this analysis as described in Croucher et al . [24] and a phylogenetic tree was drawn using the non-recombinant SNPS with RAxML [25] . Draft de novo genome assemblies were created using Velvet [26] and scaffolded using SSPACE [27] and Gap Filler [28] . The hospital surveillance activities of icddr , b were approved by the Research Review Committee ( RRC ) and Ethical Review Committee ( ERC ) of icddr , b . According to the icddr , b hospital surveillance system , we only require verbal consent from patients undergoing routine investigation for collecting stool specimens . Consent was documented in the surveillance questionnaire in the hospital surveillance system . Consent was also obtained in accordance with other ongoing studies approved by the RRC/ERC of icddr , b ( # PR-10061 , # PR-11041 ) Based on the above , verbal consent was obtained from one study participant ( case 3 ) while written informed consent was obtained from two cholera patients ( cases 1 , 2 ) and one asymptomatic household contact ( case 4 ) .
The socioeconomic status of the four cases was lower middle class and all were individuals who lived in high risk settings in urban slums in and around Dhaka city . The annual income of the adults ( and the parent of the child; case 2 ) ranged from 15 , 000–30 , 000 Taka ( ~USD 200–300 ) . Two of the participants worked in garment factories while the other two families were self-employed in small businesses . All of the cases reported that they consumed stored tap water in their homes or workplaces and shared kitchens and toilets in the community . The four V . cholerae O139 isolates ( strains 1–4 ) collected in this study , having tested strongly positive for the O139 lipopolysaccharide ( LPS ) O-antigen by the rapid dipstick assay , according to the manufacturer’s recommendations ( Span Diagnostics Ltd . , India ) , were further characterized . The serogroup was further confirmed: all four O139 isolates were found to be positive for the O139 rfb gene . PCR was used to assay for the presence of the cholera toxin gene , ctxA . Strains 2 , 3 and 4 were found to be positive for ctxA , all of which when sequenced were characteristic of the classical biotype ( see methods ) . The production and type of toxin was further confirmed by ELISA . The serogroup O139 isolates taken from case 1 ( strain 1 ) was negative for both the classical and El Tor biotype of cholera toxin by both PCR and ELISA . The rabbit ileal loop assay to detect fluid accumulation and enterotoxicity showed that three O139 strains were strongly positive for toxin production ( strains 2–4 ) , while the isolate from case 1 ( strain 1 ) failed to induce fluid accumulation and enterotoxicity in the rabbit ileal loop . All four V . cholerae O139 isolates were found to be resistant to nalidixic acid but were sensitive to all of the other antibiotics tested . To understand the detailed genetic relationships between the O139 isolates taken from these four patients , we extracted the DNA and sequenced their genomes . For comparison , we also sequenced an additional eight O139 isolates taken in Bangladesh in previous outbreaks in 1993 and 2002 . For the isolates obtained from cases 2 , 3 , and 4 , 95 . 6% of their sequence read data mapped to the genome of the V . cholerae pandemic 7 strain N16961 serogroup O1 reference sequence ( S1 Table ) . These three genomes differed by between 112–114 ( 313–316 before removing putative recombination ) single nucleotide polymorphisms ( SNPs ) from the reference sequence . When compared to the O139 strain MO10 ( accession AAKF03000000 ) mapped to the N16961 reference sequence , there were between 46–47 SNPs differentiating MO10 from these three isolates . To determine the phylogenetic relationship of the V . cholerae O139 isolates we constructed a whole genome core phylogeny from these three V . cholerae O139 isolates taken from cases 2–4 along with the O139 isolates collected in previous years , and including those previously described [7] . The sequence data are deposited in the European Nucleotide Archive with accessions ERS452533 –ERS452544 . The phylogenetic relationships of the isolates sequenced in this study , with the exception of that from case 1 , are consistent with previous data [7] . Fig 1 shows that the majority of the isolates fell in the O139 branch of the seventh pandemic El Tor phylogenetic tree , along with the previously published O139 sequences from India and Bangladesh ( accessions ERS013124 , ERS013125 , AAKF03000000 ) and the majority of isolates sequenced in this study . The new O139 sequences , with the exception of the 2013 isolate from case 1 , cluster with a strong temporal signature with isolates in the previous study [7] including the MO10 isolate from India in 1992 . Whole genome analysis of the non-toxigenic 2013 strain ( isolated from case 1 ) was distinct , with only 83 . 6% of the sequence reads mapping to the N16961 reference genome , and showing 98 , 743 and 97 , 313 ( approximately 124 , 200 and 122 , 400 before removing putative recombination ) SNP differences when compared to N16961 or MO10 using the mapping to the N16961 genome , respectively . The genome sequence data showed that the case 1 isolate ( strain 1 ) lacked the ctxAB genes but possessed the O139 specific rfb gene , confirming the PCR and phenotypic results described above . Based on the mapped genome data , this isolate was highly divergent from all other sequenced O1 and O139 isolates in this study and described previously . Although this isolate was confirmed as belonging to the O139 serogroup using traditional techniques , sequence analysis showed that the genes for the O-antigen biosynthesis genes of this isolate were different from both the O1 and other O139 isolates . To investigate this in greater detail , the 84 contigs of the previously sequenced O139 cholera isolate MO10 were ordered against the O1 N16961 reference using ABACAS [8] . The Artemis Comparison Tool [29] was used to compare the ordered MO10 genome against the case 1 genome; the contiguated sequence of one area of the LPS operon in the case 1 isolate was used to correct the ordering of one of the MO10 contigs . A search in the NCBI database using blastn [30] of the LPS operon sequence of the MO10 isolate found a hit against a 46 . 7kb sequence of Vibrio cholerae genes for O-antigen synthesis , O139 strain MO45 ( accession AB012956 . 1 ) . Comparative sequence analysis of the O139 O-antigen biosynthesis genes in the case 1 isolate showed that it was distinct from those within the O1 N16961 and O139 MO10 isolates , MO45 O-antigen biosynthesis genes , and the O-antigen biosynthesis genes from the genome obtained from case 3 in this study ( Fig 2 ) .
We report the isolation and characterization of four isolates belonging to the V . cholerae serogroup O139 in an eleven month period between December 2013 and March 2014 in Dhaka , Bangladesh . This represents the first report in Bangladesh since 2005 of clinical cases of cholera caused by V . cholerae O139 infection . This included two patients who presented with acute diarrhea who were ultimately hospitalized . To put these four isolates in context , icddr , b conducts epidemiological and ecological surveillance for cholera in different parts of Bangladesh . Between 2010–2012 , 500 clinical and environmental V . cholerae strains were isolated , 496 were confirmed as O1 and four as V . cholerae O139; all of those four previous O139 isolates were obtained from environmental samples [5] . Given the association between V . cholerae O139 and previous epidemics , the persistence and newly identified sporadic cases of both toxigenic and non-toxigenic V . cholerae O139 in the environment and in symptomatic and asymptomatic infections is notable , and may have future implications for the diagnosis and prevention of cholera in this region . Recently , a strain of V . cholerae O139 was isolated from a cholera patient in Beijing in China in May 2014 [31] highlighting the continued low level presence of this lineage in different locales . Interestingly , in two of our patients , V . cholerae O139 strains were isolated from asymptomatic household members of V . cholerae O1 infected cholera patients . In our previous studies , we have shown that household contacts of an index case of cholera are approximately three times more at risk of infection with V . cholerae [11] . However , we have previously identified non-O1/non-O139 isolates in household members of patients with O1 cholera [32] or even a different O1 Inaba or Ogawa serotype from that isolated from an index case . The V . cholerae O139 strains presented here were only resistant to nalidixic acid and therefore differ from the V . cholerae O1 that currently predominate global infections , which are also resistant to trimethoprim-sulfamethoxazole and tetracycline [31] . Whole genome sequence analysis showed that isolates from cases 2–4 fell on the O139 branch of the seventh pandemic El Tor phylogenetic tree , along with the previously published O139 sequences from India and Bangladesh ( accessions ERS013124 , ERS013125 , AAKF03000000 ) [7] . These data also highlighted the existence of one isolate , from case 1 , that was typed genotypically and phenotypically as serogroup O139 , but phylogenetically represented a distant non-El Tor pandemic 7 V . cholerae lineage . By comparing the LPS O-antigen operons it was apparent that this isolate , although highly divergent from the previously sequenced O139 isolates , possessed part of the O139 O-antigen gene cluster both targeted by the diagnostic O139 PCR test and which phenotypically appears sufficient to produce a O139 positive result by ELISA and the rapid dipstick typing methods . Further work will be required to determine fully the significance of this subtype to human health . At the time of writing this report , we had isolated two more strains of V . cholerae O139 from patients hospitalized with cholera between October and November 2014 . These strains are being further characterized at present , and preliminary data suggest that they are phenotypically and genotypically similar to the isolate from case 1 . We are at present carrying out detailed analysis of these strains using genomic techniques . In summary , our data suggest that V . cholerae O139 strains persist not only within the environment , but also are associated with occasional causes of acute watery diarrhea . Since previous infection with V . cholerae O1 does not provide protection against O139 , and vice versa , our data suggest that O139 could re-emerge as a significant cause of cholera in areas where the pathogen persists . Of note , oral killed cholera vaccine Shanchol is bivalent , and contains components of both O1 and O139 organisms , while other currently commercially available cholera vaccines are monovalent , providing protection against O1 alone . We are continuing with the surveillance of patients with acute watery diarrhea for detection of V . cholerae O139 to monitor emergence of new variants and also to detect any new and reemerging outbreaks or epidemics using microbiological and genomic analysis . This is extremely important for planning future strategies for immunoprophylactic preventive measures .
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Vibrio cholerae serogroup O1 is thought to be the sole causative agent for cholera in Bangladesh and most of the high risk developing countries . Whilst historically Vibrio cholerae serogroup O139 has been seen to cause sporadic disease , the overall numbers of reported O139 clinical cases are low , with none reported in Bangladesh since 2005 . Here we report four patients suffering from cholera attributed to serogroup O139 V . cholerae . Cases 1 and 2 were symptomatic ( isolated strains 1 , 2 ) , and cases 3 and 4 were asymptomatic ( isolated strains 3 , 4 ) . All cases were from urban Dhaka and represented a range of age groups . Cases 2–4 presented with no sign of dehydration whereas case 1 showed some signs of dehydration . Phenotypic and whole genome sequence data indicates that one of the four O139 V . cholerae isolates represents a novel O139 subtype . Since natural infection with V . cholerae O1 or vaccination with currently available licensed cholera vaccines ( e . g . , Dukoral ) provides little protection against O139 , we conclude that V . cholerae O139 remains in circulation and is still causing a low incidence of cholera . Therefore , further studies looking at the significance of these isolates towards the total burden of cholera in Bangladesh is warranted , including clinical evaluation , genome sequencing and immunobiochemistry .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
Vibrio cholerae Serogroup O139: Isolation from Cholera Patients and Asymptomatic Household Family Members in Bangladesh between 2013 and 2014
|
Within hosts , RNA viruses form populations that are genetically and phenotypically complex . Heterogeneity in RNA virus genomes arises due to error-prone replication and is reduced by stochastic and selective mechanisms that are incompletely understood . Defining how natural selection shapes RNA virus populations is critical because it can inform treatment paradigms and enhance control efforts . We allowed West Nile virus ( WNV ) to replicate in wild-caught American crows , house sparrows and American robins to assess how natural selection shapes RNA virus populations in ecologically relevant hosts that differ in susceptibility to virus-induced mortality . After five sequential passages in each bird species , we examined the phenotype and population diversity of WNV through fitness competition assays and next generation sequencing . We demonstrate that fitness gains occur in a species-specific manner , with the greatest replicative fitness gains in robin-passaged WNV and the least in WNV passaged in crows . Sequencing data revealed that intrahost WNV populations were strongly influenced by purifying selection and the overall complexity of the viral populations was similar among passaged hosts . However , the selective pressures that control WNV populations seem to be bird species-dependent . Specifically , crow-passaged WNV populations contained the most unique mutations ( ~1 . 7× more than sparrows , ~3 . 4× more than robins ) and defective genomes ( ~1 . 4× greater than sparrows , ~2 . 7× greater than robins ) , but the lowest average mutation frequency ( about equal to sparrows , ~2 . 6× lower than robins ) . Therefore , our data suggest that WNV replication in the most disease-susceptible bird species is positively associated with virus mutational tolerance , likely via complementation , and negatively associated with the strength of selection . These differences in genetic composition most likely have distinct phenotypic consequences for the virus populations . Taken together , these results reveal important insights into how different hosts may contribute to the emergence of RNA viruses .
RNA viruses pose some of the most complex , persistent and challenging problems facing public health and medicine . The ongoing outbreaks of avian influenza A ( H7N9 ) virus ( Orthomyxoviridae ) in China [1] , Ebola virus ( Filoviridae ) in West Africa [2] , and chikungunya virus ( CHIKV , Togaviridae , Alphavirus ) and West Nile virus ( WNV , Flaviviridae , Flavivirus ) in the Americas [3 , 4] highlight the health and societal impacts imposed by RNA virus-induced diseases . Several factors contribute to the emergence of these agents and the continued burdens they impose on human health . Among these is their ability to undergo rapid evolution in new and/or changing environments . Well documented examples of RNA virus evolution leading to increased virus transmission include WNV and CHIKV . In both cases , small , conservative amino acid substitutions ( residues with similar physiochemical properties ) to the viral envelope proteins resulted in more efficient transmission by mosquito vectors [5 , 6] . Adaptive changes to RNA virus genomes first arise as minority components within a genetically complex population of related but non-identical virus variants . The genetic diversity present in naturally occurring RNA virus populations has been clearly shown through a large and expanding body of observational and experimental studies to be critical to their biology . For example , several studies have demonstrated that the diversity of an intrahost viral population , rather than the fitness of individual variants , correlates with pathogenesis , disease progression and therapeutic outcome [7–9] . Moreover RNA viruses have the capacity for rapid evolutionary change because within infected hosts , all single nucleotide mutations may be generated . This has been particularly clear in the case of WNV , an arthropod-borne virus ( arbovirus ) that persists in nature in enzootic cycles between ornithophilic mosquitoes ( mainly Culex spp . ) and birds . After its initial identification in the New York City area in 1999 , WNV spread throughout the continental United States , producing the largest outbreaks of flaviviral encephalitis ever recorded in North America . The explosive spread of the virus was accompanied by the displacement of the introduced genotype by a derived strain that is more efficiently transmitted by local Culex mosquitoes [10] . Studies of intrahost population dynamics of WNV demonstrated that genetic diversity is greater in mosquitoes than in birds [11] . The selective basis for the host-specific patterns of WNV genetic diversity is that the strong purifying selection that predominates in birds is relaxed in mosquitoes [11 , 12] . In addition , the RNA interference-based antiviral response in mosquitoes creates an environment where negative frequency-dependent selection may drive rare variants to higher population frequency [13] . Moreover , WNV maintains both adaptive plasticity and high fitness by alternating between hosts that impose different selective forces on the virus population [14] . Nonetheless , important gaps remain in our understanding of how error-prone replication interacts with selective and stochastic reductions in viral genetic diversity under natural conditions . This is particularly the case for arboviruses , which tend to cause acute infection in vertebrates , with transmission occurring before the development of a neutralizing antibody response . Therefore , well-described mechanisms of immune selection such as those that occur during chronic hepatitis C and human immunodeficiency virus infections are comparatively weak during acute arbovirus infection of vertebrates . Thus , the ways that ecologically relevant , natural hosts can influence arbovirus genetic diversity remain poorly understood . WNV in particular provides an excellent experimental system to study the influences of natural vertebrate hosts on viral evolution . The virus infects a large number of wild bird species [15] with a wide-range of infection outcomes [16] . In addition , several studies have provided evidence that particular WNV variants may arise through adaptation to birds [17 , 18] . Therefore , we sought to determine whether different wild bird species may have distinct impacts on WNV population structure . Specifically , we allowed WNV to replicate in wild-caught American crows ( Corvus brachyrhynchos ) , house sparrows ( Passer domesticus ) , and American robins ( Turdus migratorius ) , bypassing the mosquito portion of the arbovirus cycle in order to focus on the impact of different vertebrate environments on virus populations during acute infection . Virus was passaged in individuals of each species five times in order to amplify host-specific patterns of selection that may remain cryptic after a single passage . Bird species were selected on the basis of ecological relevance and resistance to WNV-induced mortality . American crows experience high viremia and mortality following inoculation with WNV [19] and can directly transmit virus to roost mates without mosquito involvement [20]; house sparrows experience high viremia and intermediate mortality [21] and are frequently involved in WNV perpetuation [22]; and American robins experience intermediate viremia but very low mortality [23] and can be drivers for human WNV risk [24] . Virus populations were characterized using next generation sequencing ( NGS ) and through in vivo fitness competition studies in birds and mosquitoes . Our findings demonstrate that relevant vertebrate hosts with varying levels of disease susceptibility differentially shape WNV population structure with direct impacts on fitness during host shifts .
The WNV used in these studies was derived from an infectious clone of the NY99 genotype and is described in detail elsewhere [25] . Clone-derived WNV was passaged five times in wild-caught American crows , house sparrows and American robins . To avoid systematically selecting high- or low-replicating strains and population bottlenecks during passage , and since titers are highly variable in wild-caught birds , the sera from the individuals with the intermediate viral load were passed into the next cohort at a standard dose of 1000 plaque forming units ( PFU ) . Virus titer was variable but did not change significantly or consistently during the course of passage ( Fig 1A ) . Further , five passages in wild birds did not alter viremia production or mortality in crows and sparrows ( S1A and S1B Fig ) . WNV replication and fitness after passage was assessed using young chickens and Culex quinquefasciatus mosquitoes to directly compare the viral populations in hosts not used for passaging and to remove the variability of wild-caught birds ( e . g . age and infection history ) ( Fig 1B and 1C ) . Passaged virus ( p5 ) was similar to the WNVic ( p0 ) in peak viremia production in chickens ( i . e . at 2 and 3 dpi ) ( Fig 1B ) . Fitness assays were used to directly compare passaged viruses to a standard reference WNV in head-to-head competition . These assays can detect subtle fitness differences that are inapparent in comparative studies . Competitive fitness of all wild-bird p5 WNV was significantly enhanced in chickens . Crow-passaged virus had the smallest fitness gains and robin-passaged virus the largest ( Fig 1C ) . Fitness studies conducted in wild birds produced the same results as those in chickens ( S1C Fig ) . Competitive fitness was slightly increased in mosquitoes , but no bird-specific differences were noted ( Fig 1C , S1D Fig ) . At each passage virus was examined by NGS to determine whether the consensus sequence changed during passage and to characterize the diversity of intrahost viral populations ( S1 Table , S2 Fig ) . WNV genome coverage was variable across the genome and between samples ( S2A Fig ) , and positively correlated with viral population size ( S2C Fig ) . The lower relative WNV genome coverage from robin sera can in part be explained by smaller intrahost viral population sizes and smaller virus to host RNA ratios . Approximately 68% , 29% and 7% of NGS reads aligned to the WNV genome from crow , sparrow and robin sera , respectively . Comparatively , 20% and 0 . 5% of the NGS reads aligned to the WNV genome from chicken sera and mosquito bodies , respectively . Three nucleotide mutations that led to consensus amino acid substitutions were detected though passaging in birds , but none became fixed ( i . e . frequency = 1 ) in the population . In contrast , three consensus amino acid substitutions were detected after a single mosquito passage . All intrahost single nucleotide variants ( iSNVs ) > 0 . 02 frequency are listed in S2 Table . We estimated intrahost variation from NGS data to determine whether WNV population diversity was bird species-dependent . The mean number of unique iSNVs in each virus population was relatively constant between passages , but differences were apparent among bird species ( Fig 2A ) . WNV populations passaged in crows five times ( p5 ) had significantly more unique iSNVs than WNV passaged in sparrows and robins . In addition , the frequency of individual iSNVs increased during passage in a species-dependent manner: The mean iSNV frequency after p5 in robins was significantly higher than after p5 in crows or sparrows ( Fig 2B ) . Despite these differences , the viral populations had similar Normalized Shannon entropies ( SN ) , Hamming distances ( i . e . SNVs per coding sequence ) and amino acid substitutions per coding sequence after p5 in different species ( Fig 2C ) . We examined the ratio of viral genome equivalents ( GE ) to PFUs and intrahost single nucleotide length variants ( iLVs , including both insertions and deletions ) to assess defective viral genomes in WNV populations during passage . Crow-passaged WNV had the highest GE:PFU ratio ( Fig 3A ) and the most unique iLVs ( Fig 3B ) . In addition , a greater proportion of the iLVs in crows were found in subsequent passages compared to sparrows and robins ( Fig 3C ) . The number of iLVs per coding sequence was positively correlated with the titer of infectious virus ( Fig 3D ) . We then evaluated the possibility that greater levels of iLV carry though in crows , which can only occur via complementation ( Fig 3C ) , were due to sampling artifacts . To do this , we used a hypergeometric test implemented in R that indicated that selecting 400 common iLVs in two samples of 600 from the total pool of available single-nucleotide iLVs ( n = 51 , 490 ) was 0 . Simulation studies confirmed that it is extremely unlikely that random sampling produced the observed data . Evidence for natural selection was assessed in WNV populations using intrahost neutrality tests . The proportion of mutations in each population that were nonsynonymous ( pN ) and the ratios of nonsynonymous to synonymous variants per site ( dN/dS ) were highest in the input p0 WNV population and decreased significantly during passage in each bird species ( Table 1 ) . Separate analysis of dN and dS shows that dN did not significantly increase during passage while dS increased significantly at p5 in all bird species , a hallmark of purifying selection . The Fu and Li’s F and Fay and Wu’s H statistics were obtained from reconstructed haplotypes . The F statistic at p1 and p5 was consistently negative , indicating that the haplotypes contained excessive amounts of rare SNVs , again indicative of purifying selection ( Table 1 ) . The H statistic measures an excess of high compared to intermediate frequency SNVs . The insignificant H values suggest that the deviations from neutrality were due to natural selection rather than selective sweeps ( Table 1 ) . Analysis of reconstructed haplotypes that arose during passage and high frequency iSNVs ( i . e . frequency > 0 . 02 ) was conducted to minimize the impact of differences in sequencing coverage and to assess positive selection . 0 . 02 was selected as a cutoff for “high frequency” mutations because it includes the top 5% of a gamma distribution of all VPhaser2-accepted iSNVs . The proportion of iSNVs that were high frequency after p5 was the greatest within robin-passaged WNV populations ( 16 . 5% ) compared to sparrows ( 4 . 9% ) and crows ( 4 . 8% ) ( Fig 4A ) . Reconstructed haplotypes from high frequency iSNVs were then used to assess the selective pressures that lead to haplotype replacement during passage ( Fig 4B ) . The ancestral p0 virus population was composed of a single dominant haplotype that remained dominant after a single passage in all bird species . After p5 , the ancestral haplotype remained dominant in crows , but not in sparrows and robins . Furthermore , high frequency iSNVs from crows contributed significantly fewer amino acid substitutions per coding sequence compared to robins after p5 ( Fig 4C ) . Examination of dN/dS , amino acid diversity and high frequency nonsynonymous iSNVs across the WNV genome demonstrated that , in general , selection was the strongest in the structural protein coding regions ( Fig 4D and 4E ) . Specifically , passage in robins imposed significant selective pressures on the envelope ( E ) protein coding region that heavily targeted ectodomains ( ED ) I and II . The apparent selection of the nonstructural protein 4B ( NS4B ) from sparrow passaging is the result of a single high frequency nonsynonymous iSNV ( S2 Table ) . Individual high frequency iSNVs fluctuated in frequency through passaging and all nonsynonymous high frequency iSNVs were unique to its passage lineage ( i . e . no “signature mutations” were detected that served as markers for replication in any particular bird species , see S2 Table ) . The standardized variance in iSNV frequencies ( FST ) was then estimated from the coding sequence to determine the degree of genetic divergence among replicates within a passage and between passages ( Fig 5 ) . Viral populations from robins were more divergent compared to those from crows and sparrows . FST from WNV passaged once in young chickens was similar to wild-caught birds , but WNV passaged once in mosquitoes was much more divergent . These results are supported by analysis of haplotypes ( S3 Fig ) . The p0 haplotype was still dominant in chicken p1 populations with a small minority of haplotypes containing single iSNVs , similar to wild birds ( Fig 4B ) . In mosquitoes the ancestral haplotype became a minority after a single passage .
We examined WNV genetic diversity during the course of passage in birds that experience varying mortality due to WNV infection to assess how different hosts influence virus population structure and fitness . Passage in each host was accomplished in three concurrent biological replicates in order to control for the impact of individual wild-caught birds that may vary in several ways that could impact virus replication . Titers during passage were highly variable between individuals . However , mean titers did not significantly change during the course of passage , indicating that replication competence was retained and that overt increases in competitive fitness were not selected through our passage strategy . Wild-bird passaged virus was similar to unpassaged WNV in viremia production . Only when more sensitive in vivo competitive fitness assays ( i . e . comparative replication of the passaged and reference WNV in the same host ) were conducted were changes apparent . Note that our definition of fitness here is restricted to the specific competition environment ( within the bird or mosquito ) and does not consider the larger ecological fitness required for maintenance in a complex arbovirus transmission cycle . Passage in all birds resulted in significant competitive fitness gains during replication in chickens . Interestingly , the fitness gains were smallest after WNV was passaged in the host that experiences the most mortality ( crows ) , and largest in the most disease-resistant avian host ( robins ) . Fitness gains were far less clear when virus competition was measured in mosquitoes . A limitation to our mosquito studies is that competition was conducted via intrathoracic inoculation , which bypasses the midgut , a major physiological barrier in mosquitoes . Intrathoracic inoculation was used because the volume of blood available and the virus titers would have likely made oral infection highly inefficient . Importantly , our results on WNV replication and fitness are supported by previous observations [14] indicating that high fitness is maintained through purifying selection in vertebrates , and that no tradeoff occurs when the virus is re-introduced into mosquitoes . Moreover , replicative fitness increases occur during passage in ecologically relevant wild birds , and these gains occur in a species-specific manner . To investigate the viral genetic and population determinants of the observed fitness gains , we characterized WNV at each passage using NGS . Our data suggests that although the overall complexity of the virus population was similar among different bird species , its composition , and the selective pressures that produced it appear to be bird species-dependent . Interestingly , WNV replication in the most disease-susceptible bird species seems to be positively associated with the number of unique iSNVs ( i . e . mutational tolerance ) and negatively associated with iSNV frequency ( i . e . strength of selection ) . This observation requires further investigation using additional resistant and susceptible birds , but may provide important insights into which bird species are most likely to drive virus evolution toward fitness gains . Our data thus far suggests that more disease resistant birds such as robins would be most likely to fill this role as long as they produce sufficiently high titers to infect mosquitoes . In this study we used various neutrality tests to determine whether intrahost WNV populations from each bird species were evolving non-randomly through purifying selection . While these tests all measure slightly different aspects of genetic diversity , all clearly demonstrate purifying selection in birds . This result confirms previous studies of WNV passaged in young chickens [11] , and indicates that our approaches to sequencing and analysis , although they differ significantly from those reported previously , produce results consistent with other methods . Our studies also provide some evidence for positive selection during bird infection . We found that WNV passage in robins resulted in more amino acid substitutions that reach high frequency compared to crows . In addition , the ancestral haplotype tended to be displaced by novel mutants that arose during passage in sparrows and robins . These data suggest that positive selection within hosts is stronger in less susceptible bird species [26] . Examination of patterns of variation across the WNV genome provides additional evidence for differences in host selective environment . We found , consistent with previous reports on dengue virus populations [27] , the highest variant frequencies in ectodomains I and II of the E coding sequence of WNV passaged in robins . The mechanisms that lead to the emergence of these variants are not currently clear . Although the E protein contains most neutralizing epitopes , the earliest neutralizing antibody responses observed in birds generally occur at around 5 to 7 days post infection [23 , 28] . Other mechanisms that could impact selection on the E protein include resistance to the early antiviral states induced by type I interferon [29 , 30] and alternate methods for virus entry and uncoating of the viral RNA [31]; though these mechanisms need further investigation , especially in birds . Our results suggest that in relatively resistant hosts , novel variants may rise to high frequency within the context of purifying selection . The notion that positive selection occurs in robins is further supported by our data showing that virus diverged most during replication in them . It is , however , balanced by a lack of evidence of a selective sweep , i . e . a rapid reduction in genetic diversity as a novel variant becomes very prominent in the population . Clearly further studies are needed to confirm whether and how positive selection contributes to WNV population structure in birds . Compared to other RNA viruses , arboviruses have low long-term rates of amino acid substitution [32] . This is at least partially due to the fact that most mutations are deleterious because of evolutionary constraints on arbovirus genomes [33] . We provide evidence that accumulation of deleterious mutations , or defective viral genomes , is unequal between hosts; WNV populations replicating in wild-caught crows accumulate the most defective genomes , and WNV replicating in robins accumulate the least . Defective genomes are often found during laboratory and natural virus infections [17 , 34] and can persist through multiple rounds of transmission [35 , 36] . Using both bioassays ( i . e . GE:PFU ) and sequencing data ( i . e . iLVs per coding sequence ) , we found that the accumulation of WNV defective genomes during infection was positively correlated with viral load . This apparent density-dependent selection of deleterious mutations likely occurs via functional complementation , which becomes more efficient as effective multiplicity of infection ( MOI , i . e . intrahost viral load ) increases [37 , 38] . In addition , high MOI environments tend to tolerate neutral mutations that can become deleterious in a new environment [39] . Taken together , these studies provide a framework to understand how WNV replication in high-viremic crows leads to a broader network of potentially deleterious mutations and limited selection for adaptive amino acid substitutions , especially when compared to WNV replication in robins . The rather modest fitness gains experienced by crow-passaged WNV support this observation . The results presented here shed light on the selective forces that shape WNV populations in nature . We demonstrate that selective pressures that control WNV populations seem to occur in a species-specific manner ( Fig 6 ) . All three bird species evaluated have been suggested to be significant drivers of WNV outbreaks , with robins receiving particular attention due to findings indicating that this species is more frequently fed upon by mosquito vectors [24] . During intrahost WNV replication , our studies suggest that disease-susceptibility is positively associated with mutational tolerance and negatively associated with the strength of selection . This means that robins also may better maintain high fitness in WNV populations than do birds that are more susceptible to disease . While it is tempting to speculate that robins are significant generators of WNV genetic diversity , we also confirm herein that mosquitoes are much more efficient in generating mutational diversity in the WNV system . Moreover , these data suggest that intrahost virus evolutionary dynamics are associated with host resistance to disease in several ways and provide an important insight towards the genetic and ecological factors that influence RNA virus emergence .
Wild birds were collected from under US Fish and Wildlife Service ( #MB91672A-0 ) and Colorado Parks and Wildlife ( #13TRb2106 ) permits and with permissions from landowners . No endangered or protected species were caught or harmed during the study . Experiments involving animals were conducted in accordance with protocols approved by the Colorado State University ( CSU ) Institutional Animal Care and Use Committee ( #12-3694A ) and the recommendations set forth in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . A WNV infectious clone ( WNVic ) was previously constructed from an American crow kidney isolate collected during the 2000 outbreak in New York City [25 , 40] . The WNVic contains a naturally selected proline at amino acid site 249 in nonstructural protein 3 ( NS3 ) allowing it to replicate to high titers in wild birds [18 , 41] . Wild birds were collected in Northern Colorado from 2013 to 2014 using mist nets ( house sparrows and American robins ) and cannon nets ( American crows ) . All birds were bled prior to inoculation and serum was tested by plaque reduction neutralization test to confirm that all birds used for subsequent studies were WNV seronegative . The virus strain used to initiate the passage series was derived from a WNVic as previously described [25] . Virus was harvested from the supernatant of BHK cells transfected with linearized plasmid , stored at -80°C and used without further passage . Viruses were administered to birds by subcutaneous inoculation to the breast region with 1 , 000 WNV PFU/100 μl , a dose similar to mosquito transmission [42] , in inoculation medium ( endotoxin and cation-free phosphate buffered saline with 1% FBS ) . Birds were bled from the jugular vein at the time of peak viremia on 3 days post-infection ( dpi ) . Serum was titered by standard plaque assay on African green monkey kidney cells ( Vero , ATCC CCL-81 ) and stored at -80°C until used for subsequent passage or sequencing as described below . The first passage series utilized seven birds for each wild-caught species and the three birds with the median viral titers were used to start three independent replicate lineages , each including three naïve birds ( i . e . replicates ‘a’ , ‘b’ , and ‘c’ ) . From each group of three birds , the serum with the median viral titer was used to continue passaging to another cohort until five serial passages were completed . The WNVic derived virus was also passaged once in three young chickens for 3 dpi and two individual Cx . quinquefasciatus mosquitoes for 14 dpi to compare viral populations from commonly used laboratory vertebrate host and invertebrate vector models , respectively . See S1 Text for information about housing and care of wild-caught birds , chickens and mosquitoes . The infection phenotype of each WNV lineage after five passages ( p5 ) in wild-caught birds was compared to the unpassaged ( p0 ) WNV in the same bird species as virus passage , young chickens ( two-days old ) , and Cx . quinquefasciatus mosquitoes ( 4–7 days post emergence ) . Viremia and survival was measured from birds were inoculated with 1 , 000 PFU of p5 or p0 WNV ( n = 4–5 birds/virus ) for up to 6 dpi . As defined here , competitive fitness compares the replication of a competitor virus ( i . e . serial passaged p5 WNV ) and a standard WNV reference ( WNV-REF ) during infection of the same host . Competitive fitness is quantified by the proportion of competitor to WNV-REF genotypes using sequence chromatograms ( i . e . quantitative sequencing ) [43] . WNV-REF was generated from an infectious clone as described above and in S1 Text and is indistinguishable from the parental virus in replication in cells and relevant organisms [44] . Competitive fitness assays of co-inoculated birds and mosquitoes with equally mixed WNV-REF and p5 competitor virus was conducted as described in S1 Text . Virus libraries were prepared for RNA sequencing on the Illumina HiSeq 2000 platform ( Beckman Coulter Genomics , Danvers , MA ) using the NuGEN Ovation RNA-Seq System V2 and Ultralow Library kit ( San Carlos , CA ) ( See SI Text for more details ) . Fastq files containing read data were demultiplexed using CASAVA and custom scripts that impose high stringency ( 0 mismatches ) in the barcode region of each read . The sequence of the input WNV strain was determined from three independent biological sequencing replicates of the input virus using the Trinity assembler [45] . 100 nt paired-end reads were then aligned to this “input” sequence using MOSAIK [46] . Duplicate reads were removed using the MarkDuplicates tool within Picard to limit the influence of PCR artifacts and multiply sequenced clusters on variant calling with Vphaser2 [47] . Variants with significant strand bias were removed to reduce the potential for false-positives [48] . Variants called using Vphaser2 were used for subsequent data analysis unless otherwise specified . Analysis was limited to the protein coding sequences; and iSNVs and iLVs ( includes both insertions and deletions ) were analyzed separately . Hamming distances from the p0 “input” virus were calculated for each population by dividing the total number of polymorphisms by the average coding sequencing coverage . Mean viral population complexity was calculated by the SN at each site using the following equation [49]: SN=−pi ( Lnpi ) + ( 1−pi ) ( Ln ( 1−pi ) ) /LnN where p is the frequency of the iSNV at site i and N is the coverage at that site . At a single nucleotide position , a SN score of 0 indicates a single nucleotide was present ( i . e . no polymorphism ) while a score of 1 represents maximum complexity ( i . e . equal numbers of alternate nucleotides ) . The SN at all protein coding sequence nucleotides loci were averaged to estimate the viral population complexity . High frequency iSNVs were subjected to an additional analysis to reduce the possibility that conclusions drawn from the complete dataset were dependent on extremely rare variants . To establish a threshold for “high frequency” iSNVs , all of the Vphaser2 accepted variants detected in this study ( n = 6052 ) were log10 transformed , increased by 3 . 75 ( to make all of the values positive ) and fit to a gamma distribution , where α = μ2/s2 and β = E[μ]/s2 , using R ( data did not fit a beta distribution ) . An iSNV frequency >0 . 02 was determined to be in the upper 5% of the gamma distribution and was used to define high frequency SNVs detected through WNV passage in birds ( n = 341 individual SNVs ) . The sequencing reads from p0 , p1 and p5 were aligned to the WNV genome using mpileup from the VarScan2 software package [50] and haplotypes were reconstructed using QuasiRecomb 1 . 2 [51] with the flags ‘-r 97–10395’ , to reconstruct haplotypes from the entire coding sequence with respect to reference genome numbering , ‘-K 1–10’ , to use a bigger interval of generators and ‘-noRecomb” , to disable the recombination process because it was not expected from the viral population and to reduce the runtime . To increase haplotype specificity , the flag ‘-conservative’ was employed and analysis was restricted to haplotypes containing high frequency SNVs ( i . e . >0 . 02 ) . pN and dN/dS were used to test for intrahost selection [33] . DnaSP ( version 5 ) [52] was used to determine the number of nonsynonymous and synonymous sites to calculate dN/dS using the Nei-Gojorori method [53] with the following modifications for NGS data . Nd and Sd ( i . e . the numbers of detected nonsynonymous and synonymous mutations , respectively ) were calculated for each viral population by the sum of individual nonsynonymous and synonymous VPhaser2 accepted iSNV frequencies and the passage consensus sequence was used to determine the number of nonsynonymous and synonymous sites . The number of nonsynonymous ( 7843 . 67 ) and synonymous ( 2455 . 33 ) sites in the ancestral p0 consensus sequence were used to determine that pN prior to selection is ~ 0 . 76 . In addition , 50 most frequent haplotypes reconstructed from p1 and p5 from each bird species were analyzed using the Fu and Li’s F [54] and Fay and Wu’s H [55] statistical tests of neutrality in DnaSP with a window length of 100 , a step size of 25 and the p0 consensus sequence as an outgroup to infer the ancestral nucleotide state . FST was used to estimate the extent of interhost genetic divergence using a scale between 0 and 1 , and the extent of FST change between populations represents the degree of genetic divergence . Specifically , in-house FORTAN scripts were used to calculate FST using equations 1 , 2 and 4 by Fumagalli et al . [56] . Intrahost SNV frequencies determined by mpileup and readcounts from the VarScan2 software package [50] were used to estimate the per site heterozygosity in biological replicates compared to the total population ( e . g . all biological replicates within passage ) at a single passage ( i . e . intra-passage ) and the per site heterozygosity between passage replicates ( i . e . inter-passage ) . For estimation of the probability of resampling for the iLV data , we used the phyper command in R ( www . R-project . org ) . We calculated that a total of 51 , 490 single nucleotide iLVs were possible by multiplying the length of the coding sequence ( 10 , 299 nt ) by the 5 different kinds of iLVs that could occur at each site ( one deletion and four different nt insertions ) . We then used phyper to obtain the probability of sampling overlap of 400 iLVs out of 600 sampled ( reflecting a reasonable approximation of our observed data for crows ) given that 51 , 490 iLVs are possible . Simulation studies were conducted in R by randomly sampling 600 individuals , with replacement , from a set of 51 , 490 and comparing the sets . T-tests , Kruskal Wallis tests , and correlation statistics were obtained using R and GraphPad Prism ( La Jolla , CA ) .
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Viruses are constantly emerging into new areas and pose significant challenges to public health . Chikungunya and West Nile viruses ( WNV ) , both mosquito-borne RNA viruses , are quintessential examples of how increased globalization has facilitated the expansion of viruses into new territories . Rapid evolution of both of these agents has contributed to their rapid spread and health burden . Thus , characterizing how selection shapes zoonotic RNA viruses in their natural hosts is important to understand their emergence . As an ecological generalist able to infect hundreds of bird species , WNV is an excellent tool to study how different animal hosts can differentially drive virus evolution . We examined the genetic composition and fitness of WNV produced during replication in wild-caught American crows , house sparrows and American robins , species that range in mortality following WNV infection ( crows the highest , robins the lowest ) . We demonstrate host-dependent effects on WNV population structure and fitness . Our study provides insights on how different virus-animal interactions can influence the success of a virus in the next host and ultimately the success of virus emergence into new host systems .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Experimental Evolution of an RNA Virus in Wild Birds: Evidence for Host-Dependent Impacts on Population Structure and Competitive Fitness
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Leptospira interrogans is a bacterial zoonosis with a worldwide distribution for which rats ( Rattus spp . ) are the primary reservoir in urban settings . In order to assess , monitor , and mitigate the risk to humans , it is important to understand the ecology of this pathogen in rats . The objective of this study was to characterize the ecology of L . interrogans in Norway rats ( Rattus norvegicus ) in an impoverished inner-city neighborhood of Vancouver , Canada . Trapping was performed in 43 city blocks , and one location within the adjacent port , over a 12 month period . Kidney samples were tested for the presence of L . interrogans using PCR and sequencing . A multivariable model was built to predict L . interrogans infection status in individual rats using season and morphometric data ( e . g . , weight , sex , maturity , condition , etc . ) as independent variables . Spatial analysis was undertaken to identify clusters of high and low L . interrogans prevalence . The prevalence of L . interrogans varied remarkably among blocks ( 0–66 . 7% ) , and spatial clusters of both high and low L . interrogans prevalence were identified . In the final cluster-controlled model , characteristics associated with L . interrogans-infection in rats included weight ( OR = 1 . 14 , 95% CI = 1 . 07–1 . 20 ) , increased internal fat ( OR = 2 . 12 , 95% CI = 1 . 06–4 . 25 ) , and number of bite wounds ( OR = 1 . 20 , 95% CI = 0 . 96–1 . 49 ) . Because L . interrogans prevalence varied with weight , body fat , and bite wounds , this study suggests that social structure and interactions among rats may influence transmission . The prevalence and distribution of L . interrogans in rats was also highly variable even over a short geographic distance . These factors should be considered in future risk management efforts .
Norway rats ( Rattus norvegicus ) are the source of a number of zoonotic pathogens responsible for significant morbidity and mortality in cities around the world [1] . Additionally , the incidence and distribution of many rat-associated zoonoses appears to be increasing , likely due to increasing urbanization and urban poverty , which combine to promote urban rat infestations , close contact between rats and people , and transmission of zoonotic pathogens [1] . Leptospira interrogans , is among the most wide-spread of the urban rat-borne zoonoses , and is probably associated with the greatest human health burden , causing disease in both developing and developed nations [2]–[4] . This bacterium asymptomatically colonizes the rat kidney and is shed in the urine [3] , [4] , and direct or indirect contact with this urine can result in human infection [3] . In people , infection can cause fever with progression to jaundice , renal failure , and pulmonary hemorrhage [3] , [4] . As with other zoonotic diseases , it is important to characterize the ecology of L . interrogans in the animal reservoir in order to develop an in-depth understanding of disease risk in people , and to develop intervention strategies aimed at disease prevention [5] . For example , by studying the ecology of L . interrogans in urban Norway rats , it may be possible to identify environmental and/or population characteristics that increase or decrease the prevalence of infection in rat populations , which will , in turn , influence the probability that people living in the same geographic area will be exposed to the bacterium . This information may facilitate the development of rat control strategies aimed at zoonotic disease prevention , specifically . Previous studies have indicated that the prevalence of L . interrogans in rat populations is highly variable both among cities , and among different locations within the same city [6]–[13] . However , the factors influencing this variability in prevalence are unclear . Similarly , although some studies have found that the probability that a rat will be infected with L . interrogans increases with age [7] , [9] , [12] , [13] , and with female sex [9] , other studies have shown no association between L . interrogans infection and one or both of these variables [7] , [8] , [12] , [13] . Overall , there is a paucity of epidemiologic data regarding L . interrogans in urban rat populations . This knowledge gap is a result of the fact that the complex ecology and biology of rats are seldom taken into account when studying the pathogens they carry . For example , many studies seek only to characterize L . interrogans prevalence and not to investigate the factors influencing prevalence [6] , [10] , [11] , [14] , [15] . Frequently , the population to which the sampled rats belong is unclear or ignored altogether , making even these simple statistics of questionable value . Meanwhile those studies with a more epidemiologic focus often lack sufficient ecologic data on the rats under study to provide an in-depth analysis of L . interrogans dynamics in that population [16] . Finally , some key studies have used the presence of anti-L . interrogans antibody as a proxy for infection [9]; however , serostatus correlates poorly with infection status in rats ( i . e . , many infected rats do not develop antibodies against the infecting strain of L . interrogans ) [10] , [11] , [17] , likely because of the close evolutionary relationship between rats and L . interrogans [3] . The objectives of this study were: 1 ) to determine whether L . interrogans is present in Norway rats residing in an impoverished inner-city area of Vancouver , Canada; and 2 ) to use ecologic data on these rat populations ( collected during a year-long intensive trapping study ) to characterize the prevalence and distribution of L . interrogans and the degree to which season and population characteristics influence the ecology of this bacterium . Within the city of Vancouver , the impoverished Downtown Eastside was chosen as the study area because previous research had indicated that residents of poor , inner-city urban neighborhoods are at highest risk of urban , rat-associated leptospirosis [1] . This is because factors associated with poverty ( i . e . , infrastructural disrepair , poor hygiene , decreased health status , concurrent diseases , etc . ) may result in increased rat-human contact and/or disease transmission [1] . Although there are no known cases of autochthonous leptospirosis in this neighborhood , high rates of homelessness , HIV/AIDS , and injection drug use make fever of unknown origin a common problem . This , in combination with lack of awareness regarding urban leptospirosis among health care professionals , could lead to misdiagnosis and underdiagnosis of the disease , as has been the case in other areas of the world [1] .
This study was approved by the University of British Columbia's Animal Care Committee ( A11-0087 ) and adhered to national guidelines set out by the Canadian Council on Animal Care ( www . ccac . ca ) , including those pertaining to animal user training , euthanasia , protocol review , and wildlife ( http://www . ccac . ca/en_/standards/guidelines ) . The study area was comprised of 43 city blocks encompassing the core of Vancouver's Downtown Eastside ( DTES ) ( N49°17′/W123°6′ ) . Also included was an area within the port terminal , which is a center for international shipping that forms the northern border of the DTES . In order to adequately sample each block and capture seasonal variation in rat population and disease ecology , while avoiding anthropogenic changes caused by prolonged trapping ( e . g . , increased population turnover , disrupted population structure , rat immigration/emigration etc . ) , each block ( and the port site ) was randomly assigned to a three-week study period over the course of one year ( September 2011–August 2012 ) . Roughly equal number numbers of blocks were studied in each season , and this random assignment suggests that there should be no systematic bias regarding which blocks were trapped in which season . Within each block , approximately 20 Tomahawk Rigid Traps for rats ( Tomohawk Live Trap , Hazlelhurst , USA ) were set out along each side of the back alley that bisected the block . Traps were evenly spaced where possible , but had to be placed in a location where they did not obstruct traffic and could be secured to outdoor public property to prevent theft . At the port , traps were placed in areas where port staff had observed rats . Traps were pre-baited ( filled with bait but fixed open ) for one week to acclimatize rats to trapping equipment and bait , followed by two weeks of active trapping . Baits used included peanut butter , bacon fat , and oats . Trapped rats were anesthetized with isoflurane in a rodent Inhalation Narcosis Chamber ( Harvard Apparatus , Holliston , USA ) prior to pentobarbital euthanasia via intracardiac injection Morphometric data collected in the field included species ( based on external morphology ) , sex , weight , nose-to-rump and total length , sexual maturity ( females with an open vaginal orifice and males with scrotal testes were considered sexually mature ) , presence and number of bite wounds in the skin , and body condition on external palpation ( based on the method described by Hickman et al . [18] ) . The date and location ( block and trap ) of each rat trapped was also recorded . Rats were subsequently frozen at −30°C and sent to the Animal Health Centre ( AHC ) , British Columbia Ministry of Agriculture , Abbotsford , British Columbia for further analysis . At the AHC , rats were thawed at 4°C and underwent a full necropsy . Necropsies were conducted from May–August 2012 . During necropsy , ½ of one kidney was collected aseptically and stored at −80°C until DNA extraction ( see below ) . Additionally , sex and sexual maturity were confirmed , pregnancy and parity in females was assessed ( females that were pregnant , had visible placental scars , and/or well developed mammary tissues were considered parous ) , and each rat received a score based on the volume of internal fat stores ( poor condition ( score of 0 ) = minimal to no visible internal fat; moderate condition ( score of 1 ) = moderate internal fat; good condition ( score of 2 ) = abundant internal fat ) . A total of 701 rats were trapped . Of these , 630 were tested for L . interrogans infection by PCR . This number was arrived at by calculating the number of rats that would need to be tested within each block and the port site in order to accurately calculate the prevalence of L . interrogans within that location . This calculation was performed using the sample size for proportions function in the program Ecological Methodology ( Exeter Software , Setauket , USA ) with an expected proportion of 50 . 0% , a desired margin of error of 5% , and a fixed population correction for the size of the trapped population of the block in question . For each block , the rats to be tested were selected randomly . DNA was extracted from diluted ( 1∶5 ) and homogenized rat kidney tissues using the QiaAMP DNA Mini kit ( Qiagen Inc . , Canada ) . DNA extracts were then amplified using a real-time PCR assay which targets a 242 bp fragment of the lipL32 gene of pathogenic Leptospira species [19] . The gene encodes an outer membrane lipoprotein virulence factor . Real-time PCR ( RT-PCR ) was performed using the Agpath-ID One-Step RT-PCR Kit ( Life Technologies , Canada ) . Each 25 µl reaction contained 12 . 5 µl of 2× RT-PCR buffer , 1 µl of 25× RT-PCR enzyme , 1 µl each of forward primer ( 5′- AAG CAT TAC CGC TTG TGG TG -3′ ) , reverse primer ( 5′- GAA CTC CCA TTT CAG CGA TT -3′ ) and probe ( 5′- FAM/AA AGC CAG GAC AAG CGC CG/BHQ1-3′ ) , 3 . 5 µl nuclease-free water , and 5 µl of DNA template . Samples were run on an ABI7500 Fast PCR System . The reaction was incubated at 50°C for 2 minutes , 95°C for 10 minutes , and then amplified for 45 cycles at 95°C for 15 seconds , 60°C for 1 minute . Results were analyzed using the SDS software version 1 . 4 . To validate this assay at our laboratory , a clone of the aforementioned lipL32 fragment was ordered and diluted down to 3 copies per 5 µl . It was determined the RT-PCR could detect the clone at this concentration in three consecutive trials . All primers and the probe were made by Integrated DNA Technologies ( San Diego , USA ) and were diluted to an initial working concentration of 20 µM and 5 µM respectively . Leptospira interrogans serovar Copenhageni was used as the positive control . A subsample of 21 randomly selected RT-PCR-positive kidney samples ( approximately 1/3 of all RT-PCR-positive samples ) underwent conventional PCR with DNA sequencing to confirm the presence of L . interrogans . The conventional PCR assaytargeted a 423 bp fragment of the lipL32 gene [20] . PCR was performed using a 25 µl reaction containing an Illustra PuReTaq Ready-to-Go PCR bead ( GE Healthcare , Canada ) , 1 µl each of forward primer ( 5′- CGC TGA AAT GGG AGT TCG TAT GAT T -3′ ) and reverse primer ( 5′- CCA ACA GAT GCA ACG AAA GAT CCT TT -3′ ) , 21 µl of nuclease-free water , and 2 µl of DNA template . Samples were run with a 5 minute initial denaturation at 95°C , followed by 50 cycles of 95°C for 1 minute , 55°C for 1 minute , 72°C for 1 minute and a final incubation of 72°C for 7 minutes to produce a 423-base pair product . All PCR samples were over-laid with two drops of mineral oil and run in a Tetrad 2 thermal cycler . PCR products were purified using Amicon Ultra 4 centrifugal filters with a 30 kDa cut-off ( Fisher Scientific , Canada ) , diluted 1∶10 with nuclease-free water , and sequenced using the Big Dye Terminator version 3 . 1 Cycle Sequencing kit ( Life Technologies , Canada ) . Each reaction contained 1 µl of 5× Big Dye Terminator Sequencing buffer , 14 . 4 µl of nuclease-free water , 2 µl of Big Dye Terminator , 1 . 6 µl of primer ( diluted 1∶10 ) . One microliter of diluted template was added for a final volume of 20 µl per reaction . Each reaction was set up in duplicate to account for forward and reverse directions . Samples were run in a Tetrad 2 thermal cycler using the following program; one cycle of 96°C for 2 minutes , then 25 cycles of 95°C for 30 seconds , 50°C for 5 seconds , and 60°C for 4 minutes . After cycling , the reactions were treated with BigDye XTerminator Purification kit ( Life Technologies , Canada ) as per the manufacturer's protocol . Purified sequencing products were run on an ABI 3130 Genetic Analyzer and results were interpreted using DNASTAR Lasergene 10 SeqMan Pro program . All 21 samples were identified as Leptospira interrogans . The primary outcome variable was L . interrogans infection status ( positive vs . negative ) . Given that L . interrogans is the species of Leptospira spp . carried by rats , and given that all sequenced PCR products were identified as L . interrogans ( vs . other Leptospira spp . ) , a rat was considered to be infected with L interrogans if it was positive on the RT-PCR . Explanatory variables that were considered included season ( September–November = fall; December–February = winter; March–May = spring; June–August = summer ) , weight , length ( nose-to-rump and total body length including tail ) , sex , sexual maturity ( immature vs . mature ) , body condition as assessed by palpation in the field ( score of 0–5 ) , body condition as assessed by volume of internal fat stores on post-mortem examination ( score of 0–3 ) , presence of cutaneous bite wounds , number of cutaneous bite wounds , parity in females ( nulliparous vs . parous ) , and pregnancy in females ( see Table 1 ) . To identify characteristics associated with L . interrogans infection status , the distribution of the explanatory variables were examined among the sample as whole , as well as separately for L . interrogans-positive and -negative rats . Simple logistic regression was used to examine relationships between L . interrogans infection and each of the explanatory variables . Variables that were significantly associated with L . interrogans infection at an alpha level of ≤0 . 10 were considered for inclusion in a multiple logistic regression ( MLR ) model . Spearman's rank correlation was used to confirm that none of the variables included in the final model were strongly collinear ( rho >0 . 8 ) . For collinear variables ( e . g . , weight and length ) , models were created using each of the variables independently and compared . The final MLR model was selected using Aikake's Information Criterion ( AIC ) to balance model fit and parsimony . Subsequently , the variables included in the final logistic regression model were entered into a generalized lineal mixed ( GLM ) model to control for the effect of block , and AIC was used to select the final GLM model . By creating both MLR and GLM models , we were able to appreciate the effect of cluster-control . The dataset was then stratified and the final MLR and GLM models run in males vs . females to identify effect modification by sex . The female dataset was also used to examine the effect of parity and pregnancy in bivariable and multivariable models . All statistical analyses were conducted using R ( R Development Core Team , Vienna , Austria ) . For multivariable models , individuals with missing data for one or more of the variables under study were excluded . The location of each trap within the 43 block area of the DTES , and the number of rats caught in each trap that were L . interrogans-positive and -negative were mapped using ArcGIS 10 . 0 ( ESRI , Redlands , USA ) . This information was imported into SaTScan ( Boston , USA ) for cluster analysis using a purely spatial Bernoulli model and scanning for areas with high and low rates of L . interrogans infection using a circular window with a maximum spatial cluster size of 50% of the population at risk . Clusters identified by SaTScan were visualized in ArcGIS . The port site was excluded from this analysis because trapping took place at multiple levels within a single geographic foot-print ( which is difficult to represent in a two dimensional map ) and because trapping was somewhat more opportunistic ( vs . systematic ) compared to the blocks .
Among the 630 rats tested for L . interrogans by PCR , only 38 ( 6 . 0% ) were black rats , while the remainder were Norway rats . None of these 38 black rats were positive for L . interrogans , therefore black rats were removed from the analytic sample . The following statistics pertain only to Norway rats ( n = 592 ) , henceforth referred to as rats . The majority of rats were trapped in the spring , followed by the fall , winter , and summer ( see Table 1 ) . There were slightly more males ( 54 . 9% ) than females and over half of the rats were sexually mature ( 55 . 4% ) . The average ( median ) body weight was 123 . 7 g , and the average nose-to-rump and total length ( including the tail ) was 16 . 5 cm and 31 . 5 cm , respectively . The average body condition score as judged by palpation in the field was 2 . 5 out of 5 and 42 . 4% of rats were judged to have poor internal fat stores , while 28 . 5% and 26 . 4% had moderate and good fat stores , respectively . The average number of bite wounds per rat was 0 . 0 as the majority of rats ( 75 . 5% ) had no wounds . The overall prevalence of L . interrogans was 11 . 1% ( 66/592 ) . However , there was marked variation in the prevalence of L . interrogans by block , with prevalence ranging from 0% to 66 . 7% ( see Figure 1 ) . On bivariable analysis , the odds of being L . interrogans-positive was less in rats caught in the spring ( OR = 0 . 14 , 95% CI = 0 . 06–0 . 28 ) or winter ( OR = 0 . 47 , 95% CI = 0 . 24–0 . 89 ) compared to the fall ( see Table 2 ) . The odds of being L . interrogans positive was also less in sexually immature rats compared to mature rats ( OR = 0 . 02 , 95% CI = 0 . 001–0 . 09 ) . The odds of being L . interrogans-positive increased with increasing weight ( OR = 1 . 15 , 95% CI = 1 . 12–1 . 19 ) , nose-to-rump length ( OR = 1 . 65 , 95% CI = 1 . 46–1 . 90 ) , and total length ( OR = 1 . 32 , 95% CI = 1 . 23–1 . 43 ) . Rats with bite wounds had greater odds of being L . interrogans-positive compared to rats with no bite wounds ( OR = 4 . 94 , 95% CI = 2 . 91–8 . 44 ) , and the odds of being L . interrogans-positive increased with increasing number of bite wounds ( OR = 1 . 45 , 95% CI = 1 . 25–1 . 69 ) . Body condition score was not significantly associated with L . interrogans infection status ( OR = 1 . 04 , 95% CI = 0 . 73–1 . 49 ) , however , the odds of being L . interrogans-positive was greater in rats with a greater volume of internal fat ( OR = 5 . 12 , 95% CI = 3 . 40–8 . 13; note that fat score was entered into the multivariable models as a continuous variable for better model fit ) . In the final multivariable logistic regression model , season ( OR = 0 . 19 , 95% CI = 0 . 07–0 . 45 for spring vs . fall and OR = 0 . 31 , 95% CI = 0 . 14–0 . 67 for winter vs . fall ) , wound number ( OR = 1 . 19 , 95% CI = 0 . 99–1 . 41 ) , weight ( OR = 1 . 12 , 95% CI = 1 . 07–1 . 17 ) , and fat score ( OR = 2 . 10 , 95% CI = 1 . 20–3 . 78 ) were retained ( see Table 2 ) . The relationship between these variables and L . interrogans positivity was in the same direction but of decreased magnitude compared to bivariable analysis . After controlling for clustering by block , only weight , wound number , and fat score were retained . In the final GLM model , the odds of being L . interrogans . -positive increased with increasing weight ( OR = 1 . 14 , 95% CI = 1 . 07–1 . 20 ) , volume of internal fat ( OR = 2 . 12 , 95% CI = 1 . 06–4 . 25 ) , and number of bite wounds ( OR = 1 . 20 , 95% CI = 0 . 96–1 . 49 ) , although the last relationship was only marginally significant . Upon stratifying the models by sex , there was no apparent difference in the relationship between the explanatory variables and L . interrogans positivity in males vs . females . Among females , the odds of being L . interrogans-positive was higher in rats that were parous ( vs . non- parous ) and pregnant ( vs . non-pregnant ) . However , neither pregnancy nor parity was significantly associated with L . interrogans positivity , or improved model fit , once incorporated into a multivariable model . In the final GLM model , the estimated variance for the random effect of block was 4 . 34 , indicating that block of origin had a significant impact on L . interrogans infection status . Geographic clustering of cases was also evident on spatial analysis , which identified one cluster ( very spatially compact ) with greater than expected prevalence of L . interrogans infection and two clusters with lower than expected prevalence of L . interrogans spp . infection ( see Figure 2 ) .
Overall , this study demonstrates that L . interrogans is present in Norway rats within this inner-city neighborhood; however , the distribution of L . interrogans is not uniform . Previous studies have shown that the prevalence of L . interrogans in rats may vary among different locations within a city [12] . However , this study showed that marked clustering can take place even over a very small geographic distance within a single neighborhood . The presence of clustering is consistent with what is known about the ecology of rats in urban centers . The size of a rat's home range is determined by the availability of suitable harborage and food sources , social pressure from conspecifics or other rat species , and the presence of barriers to rat movement [21] , [22] . In urban centers , the ubiquity of resources and the barrier-effect of roadways combine to result in small home ranges that are often limited to a city block [22] , [23] . In the absence of drastic changes to the environment , long distance migration is uncommon [22] . Additionally , rats are both colonial and territorial [24] , [25]; therefore , conspecifics residing in the same geographic area are likely to be members of the same colony and interact . For these reasons it is not surprising that the presence of numerous functionally distinct rat colonies would lead to heterogeneity in pathogen distribution within an urban ecosystem . Clustering , however , has significant implications for analysis and interpretation of epidemiologic data in rats . It suggests that aggregated city-level pathogen prevalence , as is often reported [7] , [9] , [11] , is not the best measure of L . interrogans frequency . Rather , it may be more valid to measure prevalence at the level of the colony or block . Clustering must also be taken into account when attempting to identify factors that influence the prevalence L . interrogans in order to avoid bias associated with variation in distribution of disease determinants among clusters . For example , in this study , season appeared to be a predictor of L . interrogans status in the MLR model . After controlling for clustering , however , the effect of season was no longer significant . This suggests that the apparent effect of season may have been an artefact resulting from the fact that blocks with a high L . interrogans prevalence were trapped in one particular season . In the final GLM model , body weight was positively associated with L . interrogans infection status . Specifically , a 10 g increase in the weight of a rat was associated with a 14% increase in the odds of that rat of being L . interrogans-positive . This association has been noted in previous studies of L . interrogans in urban rats [9] , [12] , [13] , and was presumed to be a result of the fact that the older the animal ( as weight is a good proxy for age [22] ) , the greater the likelihood that it will become exposed to and infected with L . interrogans [12] , [13] . However , given that L . interrogans is thought to be transmitted through urine [3] , and given the colonial nature of rats and the opportunity for direct and indirect exposure to conspecifics from birth [25] , it is surprising that young rats do not become exposed earlier in life . In this study , the median weight of L . interrogans-positive rats was 302 . 5 g , which is consistent with the weight of an adult rat , compared to 96 . 2 g for L . interrogans-negative rats , which is consistent with the weight of a juvenile [22] . This suggests that the mechanism of L . interrogans infection in rats may be more complex than random environmental exposure , or else one would expect to see infection occur soon after young leave the nest . This complexity is supported by the fact that the volume of internal fat , independent of weight , was also significantly associated with L . interrogans positivity , and number of bite wounds was marginally significant . Specifically , the odds of being L . interrogans-positive were more than twice as high for a rat with higher fat score compared to a rat with a lower fat score , and increased by 20% with each bite wound . This may suggest that L . interrogans transmission has a social or behavioral aspect . For example , dominant rats have greater access to food resources and are more likely to engage in aggressive behavior compared to non-dominant rats [22] , [25] , [26] . This could result in dominant rats having greater internal fat stores and a higher incidence of bite wounds . Additionally , dominant rats are generally heavier that subordinate rats [22] . It may therefore be the case that body fat , bite wounds , and/or weight are markers of social hierarchy , and the relationship between these variables and L . interrogans infection status is , at least in part , a result of behavior . For example , dominant rats may exhibit more exploratory behavior and have more contact with conspecifics compared to subordinates [25] , both of which could increase the opportunity for exposure to L . interrogans . Some studies , however , have found that high-ranking rats actually have fewer bite wounds compared to low-ranking rats [22] , presumably because the low-ranking rats are more frequently on the ‘losing end’ of intraspecific conflicts . If this was the case then the association between number of bite wounds and L . interrogans positivity observed in this study might suggest that biting could be a method of L . interrogans transmission among rats . Leptospira interrogans has been transmitted from a rat to a human through biting [27] , and biting is an important mode of rat-to-rat transmission of Seoul hantavirus , another rat-associated pathogen [28] . The potential role of maternal antibody transfer in mediating L . interrogans infection dynamics also deserves consideration . Maternal antibody has been shown to prevent persistent infection with Seoul hantavirus in rats , and may persist for up to 5 months of age [29] . Maternal transfer of antibody could also delay infection with L . interrogans , and might partially explain why infection was uncommon in juveniles . That being said , L . interrogans are extremely well adapted to their reservoir hosts [3] , and many rats infected with L . interrogans do not have detectable circulating antibody [10] , [11] . For this reason further study is needed to determine if maternal antibody plays a role in the ecology of L . interrogans in rats . One limitation of this work is the fact that very few black rats were included in this study sample . This could be a result of the trapping methodology ( i . e . , trapping on the ground in outdoor areas ) , which may bias towards trapping Norway vs . black rats . This is because Norway rats more commonly reside in outdoor underground burrows , while black rats are more commonly found in the upper levels of man-made structures [30] . Indeed , previous studies have found that placing traps in elevated positions inside structures ( e . g . , in the roof ) increased catch success for black rats [31] . Alternatively , it could be the case that Norway rats are truly more ubiquitous in this urban environment compared to black rats . Norway rats , as a species , are larger and more aggressive compared to black rats , and tend to displace black rats where the two species coexist [22] , [24] , [30] . In this study , none of the black rats were infected with L . interrogans , which may reflect either inadequate sampling or a low prevalence of disease in this species . Interestingly , other studies of L . interrogans in Norway and black rats have also found a comparatively low prevalence of infection in the black rats [16] . This could be a result of the tendency of black rats to nest off the ground ( as opposed to the ground-burrowing Norway rat ) [30] , which could decrease their exposure to urine-borne pathogens . Given the fact that Norway and black rats differ in many aspects of their ecology [26] , [30] , it is possible that the prevalence and epidemiology of L . interrogans differs between these two species . Future studies should seek to study L . interrogans in black rats , specifically . In this study , we were able to show that the number of L . interrogans-infected rats in a block was not related to the size of the resident rat population . In other words , contrary to conventional wisdom , a larger rat infestation does not necessarily equal a larger L . interrogans-associated disease risk . Rather , it appeared that there was some block-level characteristic ( s ) that had a significant impact on L . interrogans prevalence . Although we could not identify these characteristics , it is our suspicion that they are likely features of the block environment . Rats themselves are strongly influenced by the environment in which they reside [31] , [32]; therefore it seems likely that the environment would also influence L . interrogans ecology , either directly , or indirectly through its effect on population ecology . The environment within our study area , however , is relatively uniform , being composed primarily of high-density residential and commercial properties with minimal green space . There were no obvious systematic differences between blocks with a high and low prevalence of L . interrogans . It is likely therefore , that small differences in block composition ( e . g . , availability of soil for burrowing and volume of exposed garbage ) , rather than high-level ecosystem differences , are influencing the distribution of L . interrogans in this environment . Future studies of L . interrogans in rats should seek to quantify these subtle differences and relate them to the L . interrogans ecology . The findings from this study have potential public health significance as they suggest that the risk of a person being exposed to rat-associated L . interrogans is highly heterogeneous across the urban environment and not necessarily dependent on the number of rats infesting a particular area . Additionally , the association between L . interrogans and weight seems to suggest that established populations with a high proportion of adults pose a greater risk than populations with mostly juvenile rats . Given that large , dominant rats may be preferentially removed by trapping and poisoning campaigns , due to their propensity towards exploratory behavior and competitive exclusion of subordinates [26] , [33] , it may be the case that trapping and poisoning may preferentially remove L . interrogans-infected rats . That being said , rodent control activities may also disrupt social structures , trigger long-distance rat migrations , and result in intraspecific antagonism [22] , [33] , any or all of which could have unpredictable effects on L . interrogans dynamics . Indeed in other situations , attempts to control disease in wild animals through culling have caused a paradoxical increase in disease prevalence by disrupting otherwise stable populations and thereby increasing disease transmission [34] . For this reason future studies should aim to determine the impact of rat control strategies on L . interrogans dynamics in urban rats . In conclusion , this study shows that the ecology of L . interrogans in Norway rats is inextricably intertwined with rat population ecology and that further study is needed in order to identify micro-environmental factors influencing L . interrogans prevalence in rats , to determine if the ecology of this bacterium varies among different rat species , and to determine how rat control strategies might impact L . interrogans dynamics in cities . Given the increasing incidence of urban rat-associated leptospirosis in people [1] , and given that the ecology of L . interrogans and its rat reservoir hosts have a significant impact on the risk of transmission to people [1] , it is clear that these further studies will be necessary if we are to proactively confront this public health threat .
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Urban Norway rats are the source of a number of zoonotic pathogens responsible for significant human illness . Leptospira interrogans is one of these pathogens , and although infection in rats is asymptomatic , humans infected through exposure to the bacterium in rat urine can develop fever , renal failure , and pulmonary hemorrhage . Previous studies of L . interrogans in urban rats have been of limited value because they have not taken into account the complex ecology of the rat populations under study . In this study , we found that the prevalence and distribution of L . interrogans varied greatly between blocks in an inner-city neighborhood ( reflecting that rats live in tight-knit colonies with small home ranges ) and was not related to rat population size . This suggests that the L . interrogans ‘load’ in a block does not depend on the number of resident rats , but rather on some characteristic intrinsic to that block . Additionally , increased weight , body fat , and bite wounds were found to increase the probability of L . interrogans infection , suggesting that the position of a rat within the colony's social hierarchy may also influence transmission . These factors should be considered before undertaking rat control programs .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"leptospirosis",
"medicine",
"bacterial",
"diseases",
"infectious",
"diseases",
"animal",
"types",
"urban",
"ecology",
"veterinary",
"diseases",
"veterinary",
"epidemiology",
"wildlife",
"ecology",
"zoonotic",
"diseases",
"biology",
"veterinary",
"science",
"microbial",
"ecology"
] |
2013
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Ecology of Leptospira interrogans in Norway Rats (Rattus norvegicus) in an Inner-City Neighborhood of Vancouver, Canada
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One of the most intriguing dynamics in biological systems is the emergence of clustering , in the sense that individuals self-organize into separate agglomerations in physical or behavioral space . Several theories have been developed to explain clustering in , for instance , multi-cellular organisms , ant colonies , bee hives , flocks of birds , schools of fish , and animal herds . A persistent puzzle , however , is the clustering of opinions in human populations , particularly when opinions vary continuously , such as the degree to which citizens are in favor of or against a vaccination program . Existing continuous opinion formation models predict “monoculture” in the long run , unless subsets of the population are perfectly separated from each other . Yet , social diversity is a robust empirical phenomenon , although perfect separation is hardly possible in an increasingly connected world . Considering randomness has not overcome the theoretical shortcomings so far . Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture , while larger noise disrupts opinion clusters and results in rampant individualism without any social structure . Our solution to the puzzle builds on recent empirical research , combining the integrative tendencies of social influence with the disintegrative effects of individualization . A key element of the new computational model is an adaptive kind of noise . We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible , characterized by the formation of metastable clusters with diversity between and consensus within clusters . When clusters are small , individualization tendencies are too weak to prohibit a fusion of clusters . When clusters grow too large , however , individualization increases in strength , which promotes their splitting . In summary , the new model can explain cultural clustering in human societies . Strikingly , model predictions are not only robust to “noise”—randomness is actually the central mechanism that sustains pluralism and clustering .
Many biological systems exhibit collective patterns , which emerge through simple interactions of large numbers of individuals . A typical example is agglomeration phenomena . Such clustering dynamics have been found in systems as different as bacterial colonies [1] , gregarious animals like cockroaches [2] , fish schools [3] , flocks of birds [4] , and animal groups [5] . Similar phenomena are observed in ecosystems [6] and human populations , as examples ranging from the formation of pedestrian groups [7] to the formation of urban agglomerations demonstrate [8] , [9] . Recently , numerous studies on the structure of human interaction networks [10]–[12] demonstrated that clustering is not restricted to physical or geographical space . For instance , clustering has been extensively studied in networks of email communication [13] , phone calls [12] , scientific collaboration [14] and sexual contacts [15] . It is much less understood , however , how and what conditions clustering patterns emerge in behavioral or opinion space . Empirical studies suggest that opinions differ globally [16] , [17] , while they cluster locally within geographical regions [18] , socio-demographic groups [19] , or Internet communities [20] . In addition , research on dynamics in work teams demonstrates that even groups of very small size often show high opinion diversity and can even suffer from opinion polarization [21] , [22] . Opinion clustering is defined as the co-existence of distinct subgroups ( clusters ) of individuals with similar opinions , while opinions in different subgroups are relatively large . The gaps in our theoretical understanding of opinion clustering are pressing since both local consensus and global diversity are precarious . On the one hand , cultural diversity may get lost in a world where people are increasingly exposed to influences from mass media , Internet communication , interregional migration , and mass tourism , which may promote a universal monoculture [23] , [24] , as the extinction of languages suggests [25] . On the other hand , increasing individualization threatens to disintegrate the social structures in which individuals are embedded , with the possible consequence of the loss of societal consensus [26] , [27] . This is illustrated by the recent debate on the decline of social capital binding individuals into local communities [28] . Early formal models of social influence imply that monoculture is unavoidable , unless a subset of the population is perfectly cut off from outside influences [29] . Social isolation , however , appears questionable as explanation of pluralism . In modern societies , distances in social networks are quite short on the whole , and only relatively few random links are required to dramatically reduce network distance [10] . Aiming to explain pluralism , researchers have incorporated the empirically well-supported observation of “homophily” , i . e . the tendency of “birds of a feather to flock together” [30] , [31] , into formal models of social influence [32] . These models typically assume “bounded confidence” ( BC ) in the sense that only those individuals interact , whose opinions do not differ more than a given threshold level [33] , [34] . As Fig . 1A illustrates , BC generates opinion clustering , a result that generalizes to model variants with categorical rather than continuous opinions [32] , [35] . However , clustering in the BC-model is sensitive to “interaction noise”: A small random chance that agents may interact even when their opinions are not similar , causes monoculture again ( see Fig . 1B ) . To avoid this convergence of opinions , it was suggested that individuals would separate themselves from negatively evaluated others [19] , [36] , [37] . However , recent empirical results do not support such “negative influence” [38] . Scientists also tried to avoid convergence by “opinion noise” , i . e . random influences , which lead to arbitrary opinion changes with a small probability . Assuming uniformly distributed opinion noise [39] leads to sudden , large , and unmotivated opinion changes of individuals , while theories of social integration [26] , [27] , [40] , [41] and empirical studies of individualization [42] , [43] show a tendency of incremental opinion changes rather than arbitrary opinion jumps . Incremental opinion changes , however , tend to promote monoculture , even in models with categorical rather than continuous opinions [44] . Fig . 1 demonstrates that adding a “white noise” term ( ) to an agent's current opinion in the BC model fails to explain opinion clustering . Weak opinion noise ( ) triggers convergence cascades that inevitably end in monoculture . Stronger noise restores opinion diversity , but not clustering . Instead , diversity is based on frequent individual deviations from a predominant opinion cluster ( for ) . However , additional clusters cannot form and persist , because opinion noise needs to be strong to separate enough agents from the majority cluster—so strong that randomly emerging smaller clusters cannot stabilize . In conclusion , the formation of persistent opinion clusters is such a difficult puzzle that all attempts to explain them had to make assumptions that are difficult to justify by empirical evidence . The solution proposed in the following , in contrast , aims to reconcile model assumptions with sociological and psychological research . The key innovation is to integrate another decisive feature into the model , namely the “striving for uniqueness” [42] , [43] . While individuals are influenced by their social environment , they also show a desire to increase their uniqueness when too many other members of society hold similar opinions . We incorporate this assumption as a white noise term in the model . However , in contrast to existing models we assume that noise strength is not constant but adaptive . To be precise , we assume that the impact of noise on the opinion of an individual is the stronger the less unique the individual's opinion is compared to the other members of the population . Consumer behavior regarding fashions illustrates the adaptability of opinion noise: When new clothing styles are adopted by some people , they often tend to be imitated by others with similar spirit and taste ( the “peer group” ) . However , when imitation turns the new style into a norm , people will seek to increase their uniqueness . This will sooner or later lead some individuals to invent new ways to dress differently from the new norm . Adaptive noise creates a dynamic interplay of the integrating and disintegrating forces highlighted by Durkheim's classic theory of social integration [26] . Durkheim argued that integrating forces bind individuals to society , motivating them to conform and adopt values and norms that are similar to those of others . But he also saw societal integration as being threatened by disintegrating forces that foster individualization and drive actors to differentiate from one another [27] , [40] , [41] . The “Durkheimian opinion dynamics model” proposed in the following can explain pluralistic clustering for the case of continuously varying opinions , although it incorporates all the features that have previously been found to undermine clustering: ( 1 ) a fully connected influence network , ( 2 ) absence of bounded confidence , ( 3 ) no negative influence , and ( 4 ) white opinion noise . From a methodological viewpoint , our model builds on concepts from statistical physics , namely the phenomenon of “nucleation” [45] , illustrated by the formation of water droplets in supersaturated vapor . However , by assuming adaptive noise , we move beyond conventional nucleation models . The model also resembles elements of Interacting Particle Systems [46] like the voter model and the anti-voter model [47]–[50] which have been used to study dynamics of discrete opinions ( “pro” and “contra” ) . However , we focus here on continuous opinions like the degree to which individuals are in favor of or against a political party . Computational simulation experiments reveal that , despite the continuity of opinions in our model , it generates pluralism as an intermediate phase between monoculture and individualism . When the integrating forces are too strong , the model dynamics inevitably implies monoculture , even when the individual opinions are initially distributed at random . When the disintegrating forces prevail , the result is what Durkheim called “anomie” , a state of extreme individualism without a social structure , even if there is perfect consensus in the beginning . Interestingly , there is no sharp transition between these two phases , when the relative strength of both forces is changed . Instead , we observe an additional , intermediate regime , where opinion clustering occurs , which is independent of the initial condition . In this regime , adaptive noise entails robust pluralism that is stabilized by the adaptability of cluster size . When clusters are small , individualization tendencies are too weak to prohibit a fusion of clusters . However , when clusters grow large , individualization increases in strength , which triggers a splitting into smaller clusters ( “fission” ) . In this way , our model solves the cluster formation problem of earlier models . While in BC models , white noise causes either monoculture or fragmentation ( Fig . 1C ) , in the Durkheimian opinion dynamics model proposed here , it enables clustering . Therefore , rather than endangering cluster formation , noise supports it . In the following , we describe the model and identify conditions under which pluralism can flourish .
The model has been elaborated as an agent-based model [51] addressing the opinion dynamics of interacting individuals . The simulated population consists of agents , representing individuals , each characterized by an opinion at time . The numerical value for the opinion varies between a given minimum and maximum value on a metric scale . We use the term “opinion” here , for consistency with the literature on social influence models . However , may also reflect behaviors , beliefs , norms , customs or any other cardinal cultural attribute that individuals consider relevant and that is changed by social influence . The dynamics is modeled as a sequence of events . Every event the computer randomly picks an agent and changes the opinion by the amount ( 1 ) The first term on the rhs of Eq . [1] models the integrating forces of Durkheim's theory . Technically , agents tend to adopt the weighted average of the opinions of all other members of the population . Implementing homophily , the social influence that agent has on agent is the stronger , the smaller their opinion distance is . Formally , we assume ( 2 ) The parameter represents the range of social influence of agents . For small positive values of , agents are very confident in their current opinion and are mainly influenced by individuals who hold very similar opinions , while markedly distinct opinions have little impact . The higher is , however , the more are agents influenced by individuals with considerably different opinions and the stronger are the integrating forces in our Durkheimian theory . The disintegrating forces on the opinion of agent are modeled by a noise term . Specifically , the computer adds a normally distributed random value ( “white noise” ) to the first term on the rhs of Eq . [1] . While we assume that the mean value of the random variable is zero , the standard deviation has been specified as ( 3 ) The larger the standard deviation , the stronger are the individualization tendencies of an agent . Following Durkheim's theory , equation [3] implements noise in an adaptive way: Accordingly , an agent's striving for individualization is weak , if there are only a few others with similar opinions . Under such conditions , there is no need to increase distinctiveness . However , if many others hold a similar opinion , then individuals are more motivated to differ from others . By including the focal agent in the sum of Eq . [3] , we assume that there is always some degree of opinion noise , even when agent holds a perfectly unique opinion . These fluctuations may have a variety of reasons , such as misjudgments , trial-and-error behavior , or the influence of exogenous factors on the individual opinion . Furthermore , this assumption reflects Durkheim's notion that the seeking for uniqueness is a fundamental feature of human personality , which cannot be suppressed completely [26] , [52] . We use the parameter of Eq . [3] to vary the strength of the disintegrating forces in society . The higher the value of , the higher is the standard deviation of the distribution , from which is drawn , and the stronger are the disintegrating forces . Finally , to keep the opinions of the agents within the bounds of the opinion scale , we set the value of to zero , if the bounds of the opinion space would be left otherwise .
We have studied the Durkheimian opinion dynamics model with extensive computer simulations , focusing on relatively small populations ( ) , because in this case it is reasonable to assume that all members may interact with each other . For bigger populations one would have to take into account the topology of the social interaction network as well . Such networks would most likely consist of segregated components ( “communities” ) , which are not or only loosely connected with each other [12]–[15] . Existing social influence models can explain how under such conditions each community develops its own shared opinion ( see Fig . 1A ) . However , according to these models opinion clustering is only stable when there is no interaction between communities [29] , [33] , an assumption that appears not to be empirically correct in an increasingly connected world . Therefore , we focus on a setting for which the lack of connectedness is guaranteed to be excluded as explanation of clustering and study model dynamics in relatively small and complete interaction networks . To illustrate the model dynamics , Fig . 2 shows three typical simulation runs for different strengths of disintegrating forces , while the strength of the integrating force is kept constant . In each run , all agents start with an opinion in the middle of the opinion scale ( ) , i . e . conformity . This is an initial condition for which the classical BC-model does not produce diversity . Fig . 2A shows typical opinion trajectories for a population in which the integrating forces are much stronger than the disintegrating forces . Consequently , the population develops collective consensus , i . e . the variation of opinions remains small , even though not all agents hold exactly the same opinion . Triggered by the random influences , the average opinion performs a characteristic random walk . When the disintegrating force prevails , the pattern is strikingly different . Fig . 2B shows that for large noise strengths , the initial consensus breaks up quickly , and the agents' opinions are soon scattered across the entire opinion space . Simulation scenarios A and B are characteristic for what Durkheim referred to as states of social cohesion and of anomie . Interestingly , however , pluralism arises as a third state in which several opinion clusters form and coexist . Fig . 2C shows a typical simulation run , where the adaptive noise maintains pluralism despite the antagonistic impacts of integrating and disintegrating forces—in fact because of this . In the related region of the parameter space , disintegrating forces prevent global consensus , but the integrating forces are strong enough to also prevent the population from extreme individualization . This is in pronounced contrast to what we found for the BC-model with strong noise ( Fig . 1C ) . Instead , we obtain a number of coexisting , metastable clusters of a characteristic , parameter-dependent size . Each cluster consists of a relatively small number of agents , which keeps the disintegrating forces in the cluster weak and allows clusters to persist . ( Remember that the tendency of individualization according to Eq . [3] increases , when many individuals hold similar opinions . ) However , due to opinion drift , distinct clusters may eventually merge . When this happens , the emergent cluster becomes unstable and will eventually split up into smaller clusters , because disintegrating forces increase in strength as a cluster grows . Strikingly , the state of diversity , in which several opinion clusters can coexist , is not restricted to a narrow set of conditions under which integrating and disintegrating forces are balanced exactly . Fig . 3 demonstrates that opinion clusters exist in a significant area of the parameter space , i . e . the clustering state establishes another phase , which is to be distinguished from monoculture and from anomie . To generate Fig . 3 , we conducted a simulation experiment in which we varied the influence range and the strength of the disintegrating force . For each parameter combination , we ran 100 replications and measured the average number of clusters that were present after 250 , 000 iterations . To count the number of clusters in a population , we ordered the agents according to their opinion . A cluster was defined as a set of agents in adjacent positions such that each set member was separated from the adjacent set members by a maximum of 5 scale points ( = opinion range/ ) . Fig . 3 shows that , for large social influence ranges and small noise strengths , the average number of clusters is below 1 . 5 , reflecting monoculture in the population . In the other extreme , i . e . for a small influence range and large noise strengths , the resulting distribution contains more than 31 clusters , a number of clusters that cannot be distinguished from purely random distributions . Following Durkheim , we have classified such cases as anomie , i . e . as the state of extreme individualism . Between these two phases , there are numerous parameter combinations , for which the number of clusters is higher than 1 . 5 and clearly smaller than in the anomie phase . This constitutes the clustering phase . Fig . 3 also shows that , for each parameter combination , there is a small variance in the number of clusters , which is due to a statistical equilibrium of occasional fusion and fission processes of opinion clusters ( see Fig . 2C ) . The same results were found , when starting the computer simulations with a uniform opinion distribution . This demonstrates that the simulations were run long enough ( 250 , 000 iterations ) to obtain reliable results . It also suggests that clustering is an attractor in the sense that the model generates clustering independent of the initial distribution of opinions . In addition , we performed additional statistical tests with the simulation outcomes to make sure that the existence of clusters in our model indeed indicates pluralism and not fragmentation , a state in which a population consists of one big cluster and a number of isolated agents ( see Fig . 4 ) . To illustrate , Fig . 4A plots the size of the biggest cluster in the population versus the number of clusters ( see the blue areas ) . For comparison , the yellow area depicts the corresponding distribution for randomly fragmented opinion distributions . The figure shows that the distributions hardly overlap and that the Durkheimian model generates clustering rather than fragmentation . In clear contrast , Fig . 4B reveals that the opinion distributions generated by the noisy BC-model are fragmented and not clustered . Finally , to exclude that results have been influenced by floating point inaccuracies [53] we conducted simulation experiments with the restriction that influence weights could not adopt values smaller than . All results could be replicated .
The phenomenon of self-organized clustering phenomena in biological and social systems is widespread and important . With the advent of mathematical and computer models for such phenomena , there has been an increasing interest to study them also in human populations . The work presented here focuses on resolving the long-standing puzzle of opinion clustering . The emergence and persistence of pluralism is a striking phenomenon in a world in which social networks are highly connected and social influence is an ever present force that reduces differences between those who interact . We have developed a formal theory of social influence that , besides anomie and monoculture , shows a third , pluralistic phase characterized by opinion clustering . It occurs , when all individuals interact with each other and noise prevents the convergence to a single opinion , despite homophily . Our model does not assume negative influence , and it behaves markedly different from bounded confidence models , in which white opinion noise produces fragmentation rather than clustering . Furthermore , our model does not rely on the problematic assumption of classical influence models that agents are forevermore cut-off from influence by members of distinct clusters . In order to demonstrate this , we studied model predictions in a setting where all members of the population interact with each other . However , empirical research shows that opinion clustering tends to coincide with clustered network structures [20] and spatial separation [18] . It would therefore be natural to generalize the model in a way that it also considers the structure of real social networks . Such a model is obtained by replacing the values by , where are the entries of the adjacency matrix ( i . e . , if individuals and interact , otherwise ) . Then , the resulting opinion clusters are expected to have a broad range of different sizes , similar to what is observed for the sizes of social groups . Our model highlights the functional role that “noise” ( randomness , fluctuations , or other sources of variability ) plays for the organization of social systems . It furthermore shows that the combination of two mechanisms ( deterministic integrating forces and stochastic disintegrating forces ) can give rise to new phenomena . We also believe that our results are meaningful for the analysis of the social integration of our societies . According to Durkheim's theory of the development of societies [26] , traditional human societies are characterized by “mechanical solidarity” . In these societies , individuals are strongly integrated in very homogeneous communities which exert strong influence on the behavior and opinions of individuals . According to Durkheim , however , these regulating social structures dissolve as societies turn modern . In addition , Durkheim [26] and contemporary social thinkers [27] argue that in modern and globalized societies individuals are increasingly exposed to disintegrating forces , which foster individualization [26] . As a consequence , the social forces which let individuals follow societal norms may lose their power to limit individual variation . Durkheim feared that the high diversity could disintegrate societies as they modernize [26] . That is , extreme individualization in modern societies may obstruct the social structures that traditionally provided social support and guidance to individuals . Today , modern societies are highly diverse , but at the same time they are far from a state of disintegration as foreseen by Durkheim . He argued that this is possible if societies develop what he called “organic solidarity” . In this state societies are highly diverse but at the same time the division of labor creates a dense web of dependencies which integrate individuals into society and generate sufficient moral and social binding [26] . Strikingly , our formal model of Durkheim's theory revealed another possibility which does not require additional integrating structures like the division of labor: Besides monoculture and anomie , there is a third , pluralistic clustering phase , in which individualization prevents overall consensus , but at the same time , social influence can still prevent extreme individualism . The interplay between integrating and disintegrating forces leads to a plurality of opinions , while metastable subgroups occur , within which individuals find a local consensus . Individuals may identify with such subgroups and develop long-lasting social relationships with similar others . Therefore , they are not isolated and not without support or guidance , in contrast to the state of disintegration that Durkheim was worried about . We have seen , however , that pluralism and cultural diversity require an approximate balance between integrating and disintegrating forces . If this balance is disturbed , societies may drift towards anomie or monoculture . It is , therefore , interesting to ask how the current tendency of globalization will influence society and cultural dynamics . The Internet , interregional migration , and global tourism , for example , make it easy to get in contact with members of distant and different cultures . Previous models [24] , [35] suggest that this could affect cultural diversity in favor of a monoculture . However , if the individual striving for uniqueness is sufficiently strong , formation of diverse groups ( a large variety of international social communities ) should be able to persist even in a globalizing world . In view of the alternative futures , characterized by monoculture or pluralism , further theoretical , empirical , and experimental research should be performed to expand our knowledge of the mechanisms that will determine the future of pluralistic societies .
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Modern societies are characterized by a large degree of pluralism in social , political and cultural opinions . In addition , there is evidence that humans tend to form distinct subgroups ( clusters ) , characterized by opinion consensus within the clusters and differences between them . So far , however , formal theories of social influence have difficulty explaining this coexistence of global diversity and opinion clustering . In this study , we identify a missing ingredient that helps to fill this gap: the striving for uniqueness . Besides being influenced by their social environment , individuals also show a desire to hold a unique opinion . Thus , when too many other members of the population hold a similar opinion , individuals tend to adopt an opinion that distinguishes them from others . This notion is rooted in classical sociological theory and is supported by recent empirical research . We develop a computational model of opinion dynamics in human populations and demonstrate that the new model can explain opinion clustering . We conduct simulation experiments to study the conditions of clustering . Based on our results , we discuss preconditions for the persistence of pluralistic societies in a globalizing world .
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[
"Abstract",
"Introduction",
"Model",
"Results",
"Discussion"
] |
[
"computational",
"biology"
] |
2010
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Individualization as Driving Force of Clustering Phenomena in Humans
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Mycobacterium bovis ( M . bovis ) is the main causative agent for bovine tuberculosis ( BTB ) and can also be the cause of zoonotic tuberculosis in humans . In view of its zoonotic nature , slaughterhouse surveillance , potentially resulting in total or partial condemnation of the carcasses and organs , is conducted routinely . Spoligotyping , VNTR profiling , and whole genome sequencing ( WGS ) of M . bovis isolated from tissues with tuberculosis-like lesions collected from 14 cattle at Eritrea’s largest slaughterhouse in the capital Asmara , were conducted . The 14 M . bovis isolates were classified into three different spoligotype patterns ( SB0120 , SB0134 and SB0948 ) and six VNTR profiles . WGS results matched those of the conventional genotyping methods and further discriminated the six VNTR profiles into 14 strains . Furthermore , phylogenetic analysis of the M . bovis isolates suggests two independent introductions of BTB into Eritrea possibly evolving from a common ancestral strain in Europe . This molecular study revealed the most important strains of M . bovis in Eritrea and their ( dis ) similarities with the strains generally present in East Africa and Europe , as well as potential routes of introduction of M . bovis . Though the sample size is small , the current study provides important information as well as platform for future in-depth molecular studies on isolates from both the dairy and the traditional livestock sectors in Eritrea and the region . This study provides information onthe origin of some of the M . bovis strains in Eritrea , its genetic diversity , evolution and patterns of spread between dairy herds . Such information is essential in the development and implementation of future BTB control strategy for Eritrea .
Mycobacterium bovis ( M . bovis ) is the causative agent of bovine tuberculosis ( BTB ) , achronic , infectious and contagious disease that also affects other domestic animals as well as humans [1 , 2] . Although BTB is prevalent in dairy cattle in Eritrea as shown by Omer et al . ( 2001 ) [3] and Ghebremariam et al . ( 2016 ) [4] by skin-test based survey , detection and isolation of the causative agent has never been done . Routine meat inspection at municipal slaughterhouses is performed for identifying tuberculosis-like lesions ( TBL ) that usually results in either total or partial condemnation of carcasses depending on the level of TBL dissemination , however , confirmatory testing or trace back epidemiological investigations are not conducted in Eritrea . Genotyping is a vital tool for trace back in epidemiological investigations , and according to Biek et al . ( 2012 ) [5] results from WGS alone can provide insight into TB epidemiology even in the absence of detailed contact data . Despite the usefulness of genotyping , it is rarely used in developing countries , i . e . , in Africa , Asia , and South America [6–9] . The routine use of such tool in these countries could be instrumental in complementing BTB control strategies . Spoligotyping and variable number of tandem repeat ( VNTR ) profiling have been used extensively in many countries to document the molecular epidemiology of Mycobacterium tuberculosis complex ( MTBC ) species [7 , 10–14] . For this reason , the digital MTBC molecular genotypes are predominantly stored in these two forms globally[15–18] . The recent technological advancements in molecular genetics imply that we can now more than ever understand the molecular epidemiology of MTBC at amore granular level . In the last few years , whole genome sequencing ( WGS ) for typing of pathogens has been explored and yielded important additional information on strain diversity in comparison to the classical DNA typing methods . Analysis of data from WGS also allows detection of minute differences in genetic diversity and this has contributed retrospectively to outbreak investigations [19–23] . Significantly , WGS allows for better genomic coverage withsingle nucleotide polymorphisms ( SNP ) profiling than the two classical typing methods [24 , 25] . WGS has also led to a significant growth in quantitative methodology that allows for a robust estimation of phylogenetic and temporal relationships between samples[26] . All these aspects are essential in enhancing our understanding of local and distant , recent and historical dynamics of BTB [5 , 24] . Although several reports predict that the use of WGS for genotyping will eclipse the classical MTBC typing tools [27] , this will likely take longer to occurin Africa . It is therefore important to compare their utility in resource limited settings . Although such tools have never been used in Eritrea , their use would greatly enhance our understanding of: a ) the genetic diversity of M . bovis , b ) its evolution and c ) the patterns of spread ( spatial and temporal ) between dairy herds , in the country and region . Such data ( information ) would be critical for safeguarding and further development of the dairy industry of Eritrea . In the present study , the classical MTBC typing tools ( Spoligotyping and MIRU-VNTR ) as well as WGS were used to gain insight into the spatial and temporal dynamics , genetic diversity and evolution of M . bovis strains circulating in Eritrean dairy cattle . Furthermore , to infer local and international historical phylogenetic relationships .
Pooled tissue samples ( lungs and pleura , mediastinal , bronchial , deep inguinal and lung lymph nodes ) , were collected from 15 animals that showed TBL in gross pathology , at the Asmara municipal slaughterhouse from March 2014 to May 2015 . These 15 animals were all those with TBL during the study period . The animals were slaughtered for meat purpose and processed as part of the normal work of the abattoir . Approximately 5–10 grams of pooled tissues from each sampled animal were collected in sterile specimen containers , and immediately transported on icepacks to the National Animal and Plant Health Laboratory ( NAPHL ) , Asmara , and stored at -20°C until processing for culture . Data collected from individual animals ( Table 1 ) included: source of the animal slaughtered , date of slaughter , species , breed , sex , age , pregnancy status ( pregnant/non-pregnant ) , ante mortem clinical signs , post mortem lesions , and type of the tissue samples collected . In addition , retrospective meat inspection data for the period 2010 to 2015 were retrieved from the logbook of the slaughterhouse . Samples were processed for M . bovis culture as follows: approximately 5 g of each pooled tissue sample with TBL per animal was cut into small pieces and covered with 100 ml of sterile distilled water in a biohazard cabinet ( Esco Class II BSC; Labotec , SA ) . The samples were homogenized using an Ultra-Turrax homogenizer at 17500 rpm ( Separation Scientific , SA ) . Seven millilitres of the homogenate was poured into each of two separate 15 ml falcon tubes , and the remaining homogenate was poured into individual 50 ml centrifuge tubes and stored at -20°C as reference samples . The samples were decontaminated with 7 ml of 2% HCL ( final concentration of 1% ) and 7 ml of 4% NaOH ( final concentration of 2% ) , respectively , and incubated at room temperature ( 18–25°C ) for 10 min . After subsequent centrifugation ( HeraeusLabofuge 400 ) of the samples at 3500 rpm for 10 min . , supernatants were poured off and 7 ml of sterile distilled water was added . After washing , the centrifugation step was repeated and most of the supernatant was poured off . The pellets were re-suspended in a volume of approximately 1ml using a sterile inoculation loop . Two loops of each of the pellets were spread evenly onto two Löwenstein-Jensen ( L-J ) media slants supplemented with pyruvate ( National Health Laboratory Service , SA ) and onto one L-J medium slant supplemented with glycerol ( BD Diagnostics ) , and incubated at 37°C for up to ten weeks . The slants were monitored weekly for mycobacterial growth . Ziehl-Neelsen staining was conducted andlysate ( DNA ) of acid fast bacteria was subjected to polymerase chain reaction ( PCR ) testing to identify bacteria as MTBCas previously described [28 , 29] . Subsequently , deletion analysis was performed on the isolates using PCR primers targeting the RD4 ( region of difference-4 ) as previously described for M . bovis identification [30] . The three features used to distinguish M . bovis clonal complexes were: a ) they are a derivative of most recent clonal ancestors ( MRCA ) spoligotype b ) region of difference deletion and c ) geographic restriction ( Example: African 1 is localized in West Africa ) To obtain the whole genome sequences , DNA of the 14 Eritrea M . bovis isolates was extracted ( dx . doi . org/10 . 17504/protocols . io . nsgdebw ) and sequenced on a MiSeq instrument ( Illumina , San Diego , CA ) using 2x250 paired-end chemistry and the Nextera XT library preparation kit ( Illumina , San Diego , CA ) . FASTQ files from the instrument were put through the National Veterinary Services Laboratories ( NVSL ) in-house pipeline ( see https://github . com/USDA-VS ) . Briefly , reads were aligned to the reference genome AF2122/97 , NCBI accession number NC_0002945 , using BWA and Samtools[32 , 33] . A depth of coverage of 80X was targeted . BAM files were processed using Genome Analysis Toolkit ( GATK ) ’s best practice workflow . SNPs were called using GATK’s HaplotypeCaller outputting them to variant call files ( VCF ) [34–36] . Results were filtered using a minimum QUAL score of 150 and AC = 2 . From the VCFs , SNPs gathered were outputted to three formats: an aligned FASTA file; tab-delimited files sorted by position location and by SNP groups; and a maximum likelihood phylogenetic tree created with RAxML[37] . The tree was built using a GTR-CAT model with input taken as an alignment file containing only informative and validated SNPs . SNPs were visually validated using Integrative Genomics Viewer ( IGV ) [38] . Because WGS isolates from this region of the globe are not readily available , databases from three laboratories ( United States Department of Agriculture , Centre de Recercaen Sanitat Animal ( CReSA ) —Institute de Recerca i Technologia Agroalimentáries ( IRTA ) , Spain , and Tuberculosis Research Laboratory , Department of Veterinary Public Health and Preventive Medicine , University of Ibadan , Nigeria ) that are actively sequencing M . bovis isolates were queried and field isolates that were within 150 SNPs of the Eritrea isolates were included in our analysis . Also included for perspective were widely available reference strains , AN5 , Ravenel , 95–1315 , AF2122/97 , BCG , and BZ-31150 . “FASTQ files from the isolates sequenced were uploaded into NCBI short read archive . Accession numbers Bioproject and sample numbers are listed in supplemental S1 Table .
During the period 2010 to 2015 , 78 , 820 cattle were slaughtered and 38 carcasses , originating from Maekel and Debub regions , were totally condemned due to generalized TBLs showing caseous necrosis identified in gross pathology in the lungs , livers , pleura ( chest ) , peritoneum , and lymph nodes . Besides , fore quarters of three animals , plucks , shoulders , chests and heads of six cattle were partially condemned due to the presence of TBL ( Table 2 ) . All , except one ( local breed ) , of the condemned carcasses were of the exotic HF breed or their crosses . Out of the 15 animals sampled from March 2014 to May 2015 , nine originated from Maekel and one from Debub , while the origin of the other five slaughtered animals was unknown due to lack of records . Detailed gross pathology information on the tissues collected is presented in Table 1 . During this period 26 , 603 cattle were slaughtered and nine out of the 15 carcasses sampled , were totally condemned due to generalized TBL . In addition , the entire plucks and shoulders of three animals were partially condemned ( Table 2 ) , and from three other animals , tissues with TBL were collected and the carcasses passed for consumption . Out of the 15 pooled tissue samples cultured on L-J media slants supplemented with pyruvate , 14 yielded smooth dysgonic growth , suggestive of M . bovis presence . All the 14 isolates were identified as MTBC . Subsequent examination by M . bovis specific PCR targeting the RD4 , yielded banding patterns typical of M . bovis with a 268 bp product indicating RD4 deletion .
The dominant spoligotype identified in our study was SB0120 , named BCG-like by Haddad et al . [13] and considered as parental strain for the M . bovis vaccine strain . It accounted for 64% of the isolates , whereas the other two spoligotypes SB0134 and SB0948 did so for 29% and 7% , respectively . The first two strains are widely distributed in a number of African countries , namely; Ethiopia , Algeria , Zambia , South Africa [6 , 10 , 16 , 40–43] as well as in Italy , Spain , other European countries and Mexico [13 , 44–49] . In addition to cattle , SB0120 affects wildlife and humans in Africa and Europe [50–53] . The third spoligotype ( SB0948 ) has been reported in France , Italy , and in Zambia [13 , 41 , 44] . The relatively high frequency of the spoligotype SB0120 found in the present study may indicate its predominance in Eritrean dairy cattle , though difficult to conclude with such small sample size . The second predominant spoligotype ( SB0134 ) appears to have evolved from spoligotype SB0120 by the loss of spacers 4 and 5 in addition to spacers 3 , 9 , 16 , and 39–43 that classify spoligotype SB0120 . This finding might not be surprising , in view of the past trade relations between Eritrea and Ethiopia , as both SB0120 and SB0134 spoligotypes are also present in Ethiopia . Besides , these two countries share open borders that consequently allowed the uncontrolled movement of animals as obtained in most African countries . Therefore , it might be plausible to speculate that these strains of M . bovis are shared between Eritrea and Ethiopia . On the other hand , it might also be plausible to suggest Italy as a possible source of these strains , on the following grounds: a ) long historical ties ( 1900 to 1970s ) between Eritrea and Italy existed , b ) Italian settlers initiated the establishment of dairying in Eritrea in the 19th century by importing exotic breeds ( Holstein–Friesian ) , c ) the M . bovis spoligotypes detected in our study are also wide spread in Italy . Although the reason for the apparent predominance of the two spoligotypes ( SB0120 and SB0134 ) needs further study , as this may indicate an epidemiological link between different dairy farms/regions in Eritrea , as buying and selling of cows between dairy farms is common in the country[54] without following strict sanitary rules . Since not all the slaughtered cattle with TBL had records of their farm of origin , it may also be possible to suspect that some of the slaughteredanimals might have originated from the same farm . It is noteworthy , however , that based on the WGS data there appears to be at least two introductions of M . bovis into Eritrean dairy cattle , an SB0120 strain and SB0134 strain . The SB1517 ( Ethiopian strain; Fig 2 ) is an offspring of SB0134 suggesting that the common ancestor of the cluster was SB0134 . Spoligotype SB0948 was found in only one animal . It is a descendant of spoligotype SB0120 as it differs by the absence of spacer 1 only , and deviates only by the Mtub21 locus in its VNTR profile from the other members of the SB0120 group ( Fig 1 ) . Further , the WGS data confirmed that SB0948 is a recent descendant of a sub-cluster of SB0120 isolates . Though unclear what its relevance is in neighboring Ethiopia , this spoligotype was reported in several countries in Africa and Europe [13 , 41 , 44 , 48 , 55] . The African and global comparisons of spoligotype profiles ( Fig 3and S1 Fig ) demonstrated the regional and global distribution of the spoligotype and VNTR profiles and their similarities with the Eritrean ones . These similarities could be attributed to the following two plausible reasons: a ) inter-regional and global livestock trade , b ) colonial livestock and livestock product trade within their then colonies and outside . Variable number tandem repeat ( VNTR ) profiles are considered appropriate to complement spoligotyping due to their ability to discriminate between M . bovis strains as defined by spoligotyping[15 , 55 , 56] . The three spoligotypes were clustered into six VNTR profiles ( Fig 1 ) . The diversity seen in the VNTR profiles may suggest that M . bovis has been circulating in the dairy herds of the country for quite a long time with only minor mutations as the BCG-like spoligotype ( SB0120 ) is the predominant one . Four of the VNTR profiles ( ER-2 , -3 , -4 and 6 ) may have derived from the predominant VNTR profile ER-1 , that corresponds to spoligotype SB0120 . According to Smith et al . [49] , strains bearing the same spoligotype pattern are assumed to be a set of individuals derived relatively recently by clonal replication from a single ancestral cell . On the basis of the VNTR profile , both strains , SB0948 and SB0134 , are clustered within the SB0120 group with a loss of only one locus ( Mtub12 ) in the former and two loci ( ETR-B and ETR-E ) , in the latter strain , respectively . One of the VNTR profiles within the SB0134 strain exhibited two different VNTR alleles ( 3 and 4 tandem repeats ) for locus ETR-E ( Fig 1 ) , suggesting either a mixed infection with two distinct strains or a microevolution in this strain . The VNTR profiles found in our study showed clonal variants differing at their loci as compared to what was reported in other parts of Africa ( i . e . , Zambia ) ( Fig 1 & Fig 3 ) , though they were all M . bovis strains belonging to SB0120 spoligotype . This clonal difference ( Fig 1 & Fig 3 ) seen in our study may have been attributed to the absence of active livestock ( dairy cattle ) trade between Eritrea and other parts of Africa ( Zambia ) or due to the different geographical locations and livestock management systems between the countries , that might have dictated the microevolutions ( mutations ) differently . The possible reason for having the same spoligotype ( SB0120 ) in Eritrea and other African countries ( S1 Fig ) , might be that the source of the cattle for Eritrea and the other countries was Europe , as Europe is the source for the high yielding dairy cows , like the Holstein Friesians , that are imported by most African countries with the aim of improving milk production in their countries in order to realize food security . The investigation of the 14 M . bovis isolates for clonal complex differentiation revealed that they belonged to none of the complexes identified so far i . e . , African 1 ( RDAf1 ) , African 2 ( RDAf2 ) , European 1 ( RDEu1 ) and European 2 ( RDEu2 ) [15–18] . The absence of members that belong to clonal complex African 1& 2 in our samples could suggest limited introduction of such strains from the neighboring Eastern and Western African livestock movement routes . It is noteworthy , that these two strains ( SB0120 and SB0134 ) are present in Ethiopia [16] , although most of the other strains in this country belong to Af2 . In the current study , little strain diversity is recorded ( Fig 1 ) as compared to studies conducted in other countries with similar agricultural setting like Eritrea[6 , 42] . The WGS results matched the conventional laboratory methods with better resolution . These data support two separate introductions of M . bovis into Eritrea , with subsequent localized spread . The common ancestor of these two groups is shared widely with isolates in the USA and Spain , with greater diversity found in Spain suggesting an introduction from Europe . The presence of a common ancestor in these distantly located countries may be due to the international livestock trade between these countries , geographical proximity and similar livestock production systems . Example: the origin of the high yielding dairy breed ( Holstein Friesian ) is Europe . As indicated in the spoligotyping section above , the spoligotype SB0120 , predominant in our study , is also ubiquitous in Europe , especially in France[13] , Italy [44] , Portugal[45] , and Spain[48] , most likely as a result of geographical closeness and trade relations between these countries . Therefore , our finding may not be a surprise , given the historical establishment of ‘intensive’ dairy farming by the Italian settlers in Eritrea through the importation of high yielding dairy breeds ( Holstein Friesians ) to meet the high demand for milk and dairy products . The fact that the Eritrean strains are between ( close to ) Spain samples ( Fig 2 ) may suggest two introductions or may be just one introduction; i . e . , from Europe ( Italy ) . Since we do not have information that shows historical , political or trade ties between Spain and Eritrea , we can speculate that either the strains are circulating in Italy and Spain . Or that , the Italian settlers during the establishment of dairy farms may have imported the cattle from Spain or other European countries where the same strains of M . bovis might have been circulating . A classical analogy for this speculation may be rinderpest that was brought to Sub-Saharan Africa by Italian forces in 1889 , with infected cattle they had imported from India , Aden , South Russia to feed their army that had then occupied Massawa ( Eritrea ) [57] . However , although phylogenetic comparison with Italian M . bovis isolates could not be done in our study , we cannot refute the possibility that these strains originate from Italy or via the above indicated routes from other countries . The second probable route of introduction for one of the groups of the Eritrean strains , but not for the other , may be Ethiopia considering the long and close historical relationship and uncontrolled livestock movement between these two countries . The Ethiopian and Eritrean samples have accumulated 8–16 additional SNPs since sharing a common ancestor suggesting a recent common source and regional spread . But the four Eritrean samples ( strains ) are within 5–6 SNPs from sharing a common ancestor suggesting these isolates have established and spread within Eritrea , though it might be premature to reach into conclusion with such small sample size . Eritrea , on the other hand , might have introduced this strain to Ethiopia . This is plausible because both intensive dairy farming , established 100 years ago in Eritrea and the first report of BTB ( Pirani , 1929 ) , cited by Omer et . al . [3] , occurred earlier than in Ethiopia where ‘intensive’ dairy farming started in the 1950s ( 1947 ) by importing Friesians and Brown Swiss [58] . This was followed by the detection of acid fast bacilli in a cow’s milk , in one study , and detection of what was called ‘Mycobacteria tuberculosis bovine type’ seemingly , M . bovis from 18 cattle , in another study , in Eritrea , by Sfroza in 1944[3] . The samples collected in this study are not considered representative of all strains possibly circulating in Eritrea . However , Asmara slaughterhouse , as the country’s biggest facility mostly slaughters exotic cattle breeds from various regions in Eritrea in which previously a high BTB prevalence was reported [4] . Therefore , the panel of samples still provides a valuable insight in the genetic strain composition from mostly dairy producing regions in Eritrea and a valuable basis for future investigations . The current study characterized strains of M . bovis in Eritrea and revealed their ( dis ) similarities with the strains generally present in Africa and Europe , as well as potential routes of introduction of M . bovis . Though the sample size is small , our study provides important information as well as availability of technology for future in-depth molecular studies including more samples from dairy cattle as well as cattle and goats from the traditional livestock sector . This study provides information on the origin of the M . bovis strain in Eritrea , its genetic diversity , evolution and patterns of spread ( spatial and temporal ) between dairy herds . The information obtained will be instrumental in making informed decisions in future BTB control strategy for Eritrea . Our study has some limitations . The samples were collected from one slaughterhouse and were few due to the absence of tissues with TBL during the study period . The low prevalence of BTB in the traditional livestock raising system [59] where majority of slaughtered animals come from , has limited the possibility of detecting more M . bovis strains from different geographical regions of Eritrea . Genetic profiling of M . bovis strains is a highly useful approach which can aid in the study and control of the temporal and geographical disease spread in the country and the African continent where BTB is largely uncontrolled . We recommend future studies in Eritrea to include genetic profiling of Italian isolates so as to support or negate our hypothesis with certainty than just live with speculation that the origin of the Eritrean M . bovis strains was Italy . In future studies in Eritrea , inclusion of more regional slaughterhouses including animal traceability will enable us gain greater insight into the epidemiology of BTB in the country which will allow the M . bovis genotype to be linked to the population from which it was obtained . We also recommend that simultaneous detection and strain differentiation of M . bovis isolates should become a reality in the routine of human tuberculosis reference laboratories , as well as in the routine meat inspection at municipal slaughterhouses . Therefore , using the One Health paradigm ( i . e . interdependence between the medical and veterinary fields ) , greater integration between agriculture and health sectors could be an important strategy to control M . bovis in several places in the world where the agent is disseminated between animals and humans .
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The livestock sector plays a major role in poverty and hunger reduction in the vast majority of Africa , as a source of food , cash income , manure , draught power , transportation , savings , insurance and social status . However , for livestock to play this vital role , the impact of diseases of economic and zoonotic importance need to be reduced . Bovine tuberculosis , mainly caused by Mycobacterium bovis , is such an infectious disease . Slaughterhouse ( gross pathology ) surveillance , followed by bacterial culture and genotyping , are options to identify the disease-causing agents , their distribution , and enabling trace back of the sources of infections , in order to prevent their re-introduction and spread . Unfortunately , genotyping is by far not generally introduced in the continent . In the present study , tissues with tuberculosis-like lesions were collected from the Asmara municipal slaughterhouse , the largest slaughterhouse in Eritrea , and bacterial culture , classical Mycobacterium tuberculosis complex typing ( Spoligotyping and VNTR profiling ) , as well as whole genome sequencing ( WGS ) were used to gain insight into the spatial and temporal distribution , genetic diversity and evolution of M . bovis strains circulating in Eritrean dairy cattle . The results revealed ( dis ) similarities of the Eritrean M . bovis strains with the strains generally present in Africa and Europe , potential routes of introduction to Eritrea and genetic diversity of the M . bovis strains . Future in-depth molecular studies including more samples from dairy cattle as well as cattle and goats from the traditional livestock sector are recommended .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"livestock",
"evolutionary",
"biology",
"geographical",
"locations",
"eritrea",
"molecular",
"genetics",
"molecular",
"biology",
"techniques",
"genotyping",
"bacteria",
"africa",
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"analysis",
"methods",
"artificial",
"gene",
"amplification",
"and",
"extension",
"actinobacteria",
"molecular",
"biology",
"evolutionary",
"genetics",
"agriculture",
"people",
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"places",
"polymerase",
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"europe",
"organisms",
"mycobacterium",
"bovis"
] |
2018
|
Genetic profiling of Mycobacterium bovis strains from slaughtered cattle in Eritrea
|
Nanotechnology offers great potential for molecular genetic investigations and potential control of medically important arthropods . Major advances have been made in mammalian systems to define nanoparticle ( NP ) characteristics that condition trafficking and biodistribution of NPs in the host . Such information is critical for effective delivery of therapeutics and molecules to cells and organs , but little is known about biodistribution of NPs in mosquitoes . PRINT technology was used to construct a library of fluorescently labeled hydrogel NPs of defined size , shape , and surface charge . The biodistribution ( organ , tissue , and cell tropisms and trafficking kinetics ) of positively and negatively charged 200 nm x 200 nm , 80 nm x 320 nm , and 80 nm x 5000 nm NPs was determined in adult Anopheles gambiae mosquitoes as a function of the route of challenge ( ingestion , injection or contact ) using whole body imaging and fluorescence microscopy . Mosquitoes readily ingested NPs in sugar solution . Whole body fluorescence imaging revealed substantial NP accumulation ( load ) in the alimentary tracts of the adult mosquitoes , with the greatest loads in the diverticula , cardia and foregut . Positively and negatively charged NPs differed in their biodistribution and trafficking . Following oral challenge , negatively charged NPs transited the alimentary tract more rapidly than positively charged NPs . Following contact challenge , negatively charged NPs trafficked more efficiently in alimentary tract tissues . Following parenteral challenge , positively and negatively charged NPs differed in tissue tropisms and trafficking in the hemocoel . Injected NPs were also detected in cardia/foregut , suggesting trafficking of NPs from the hemocoel into the alimentary tract . Herein we have developed a tool box of NPs with the biodistribution and tissue tropism characteristics for gene structure/function studies and for delivery of vector lethal cargoes for mosquito control .
Arthropod vectors and pest species are of enormous public health , agricultural , and economic importance . Control of these arthropods is predicated to a large extent on chemical insecticides . Ominously , many vector and pest species have developed or are developing resistance to conventional classes of insecticides . Insecticide resistance is emerging as a major threat for the control of mosquito vectors of human diseases , including Anopheles gambiae , the principal vector of malaria in Africa [1–3] . Identification of new targets and development of new approaches for control of vectors is a public health imperative . Improved and efficient techniques to investigate the molecular biology of and to characterize gene structure and function in arthropods would be of great value to identify novel targets for control . New approaches to deliver effector molecules and compounds to improve vector or pest control would also be of great value . Nanotechnology offers great potential in both of these areas . For example improved nanoparticle ( NP ) delivery of dsRNA to induce RNAi to silence and functionally characterize genes and to cause insect mortality offers exciting new potential for research as well as insect vector and pest management [4 , 5] . Physical and chemical properties of natural objects have been refined by nature to optimize biological functions and interactions [6–14] . There are many biological barriers in an organism that condition the efficacy of NP delivery to target tissues and cells [15 , 16] . In the human host , these include the vascular endothelium and walls of blood vessels , physical entrapment in organs , phagocytosis , and overall clearance of the NPs from the circulatory system . Physicochemical properties , e . g . size , shape , aspect ratio , modulus , and surface charge , are determinants of the biodistribution and trafficking of NPs in vivo in vertebrates and of internalization of NPs into cells [17–21] . The PRINT platform particle technology offers exceptional capability to mimic nature’s handiwork . Particles have been engineered to deliver siRNAs ( and other biological molecules ) to knock down target gene expression in both in vitro and in vivo systems [22–25] . The NPs containing the siRNAs are effectively delivered to target cells , where the particle is degraded in the endolysosome , and the siRNAs are then released into the cytoplasm to engage the host RNAi machinery . Major advances have been made in the development and optimization of NPs for delivery of drugs , antigens , and RNAs in vitro and in vivo in mammalian systems [26–29] . Microencapsulation techniques have been used to enhance the stability , effectiveness and environmental delivery of effector molecules , e . g . —insecticides , to control mosquitoes in nature [30] , but development of NP-delivered effector molecules , such as dsRNAs , to control mosquitoes is in its infancy . Chitosan NPs have been used to deliver dsRNA to silence chitin synthase in An . gambiae mosquitoes [31] , and chitosan-siRNA particles have been used to disrupt expression of an olfactory gene in Ae . aegypti [32] . Other types of NPs have been investigated for vector control [33–36] . The biodistribution of NP-delivered dsRNA to silence a chitinase-like gene in larval Drosophila melanogaster has been reported [37] . However , there is little information about NP physicochemical determinants of trafficking of NPs in mosquitoes following environmental ( oral or contact ) delivery . Following ingestion by adult mosquitoes , NPs would have to traffic in the alimentary tract , penetrate diverticula , cardia , foregut , or midgut barriers , disseminate into the hemocoel and then be internalized by target tissues and cells . Following contact delivery , NPs must traverse cuticular barriers and then traffic in the insect to be internalized by the appropriate tissues and organs . Determination of the optimal physicochemical characteristics of NPs to negotiate these barriers to deliver their cargoes to target cells is the goal of our research . In this and the accompanying paper [38] , we determined the biodistribution and trafficking of poly ( ethylene glycol ) ( PEG ) hydrogel particles in vivo in adult and larval An . gambiae mosquitoes following oral , parenteral or contact challenge , and the internalization potential of particles in vitro in cell cultures [38] . PRINT technology was utilized to prepare PEG NPs of defined size , shape , aspect ratio , and surface charge for mosquito challenges . In this paper , fluorescently-labeled NPs without cargoes were used to challenge adult An . gambiae mosquitoes , and the NPs with the preferred biodistribution characteristics ( e . g . organ , tissue and cell tropisms and trafficking kinetics ) for delivery of molecules to tissues and cells in mosquitoes were identified .
An . gambiae ( G3 ) strain was used in all experiments , and eggs to start the colony were kindly provided by the Malaria Research and Reference Reagent Resource Center ( MR4 ) ( http://www . mr4 . org ) . Rearing and manipulation of mosquitoes generally followed the MR4 recommendations . Briefly , mosquitoes were reared at 27°C ( ±1°C ) , 80% ( ±5% ) humidity and a light cycle of 30 min sunrise ( at 5:30 AM ) , 11 . 5h daylight , and 30 min sunset ( at 5:30 PM ) . Mosquito rearing was conducted in the insectary facilities of the Arthropod-borne and Infectious Diseases Laboratory at Colorado State University . To determine organ , tissue and cell tropisms and to estimate the abundance ( load ) of the respective NPs , alimentary tract tissues ( ventral diverticulum , dorsal diverticula , foregut , midgut , hindgut , and Malpighian tubules ) and non-alimentary tract tissues ( head , proboscis , salivary glands , thoracic muscles , ovaries , and tracheae ) were dissected from mosquitoes ( Fig 2 ) at predetermined days post challenge . Organs and tissues were mounted on slides , covered with PBS-10% glycerol mounting medium , and assayed for the presence and abundance of NPs in tissues up to 7 d post challenge using an Olympus BH2-RFCA fluorescence microscope or a Leica DM4500B fluorescence microscope . NP tropisms were determined by detection of any level of fluorescence signal ( 1 to 5+ ) in the respective organ , tissue , or cell . The intensity of the fluorescent signal was subjectively scored from 0 to 5+ . NP loads in the respective organ or tissue were assumed to be directly correlated with the relative intensity of the fluorescent signal in the organ or tissue . In some studies , to more accurately determine cell tropisms of selected NPs , alimentary tract tissues were dissected in PBS and fixed in 4% formaldehyde ( Electron Microscopy ) for at least 1 hr at room temperature ( RT ) . The fixative was then removed , the tissues were rinsed three times with PBS 5 min each at RT and then permeabilized in 1% Triton X-100 for 10 min at RT and then washed three times for 5 min each at RT . The tracts were then incubated in a 1:40 dilution of—Alexa Fluor 546 phalloidin ( high-affinity F-actin probe conjugated to bright , photo stable , orange-fluorescent Alexa Fluor 546 , lifetechnologies . com/ product A22283 ) for 15 min at RT . After rinsing with PBS ( three times for 5 min each at RT ) , alimentary tracts were placed onto slides , covered with Vectashield ( Vector Laboratories Inc . , Burlingame , CA ) , and a coverslip was sealed with nail polish on the slide . Biodistribution of NPs was determined using a Leica DM4500B fluorescence microscope .
Female mosquitoes were exposed to the respective NPs ( Fig 1 ) in 10% sucrose ( 250 μg/mL and 50 μg/mL ) for 1 d and then assayed by image analysis and immunofluorescence microscopy for NP biodistribution , trafficking , and kinetics of tissue tropisms . Nearly 100% of An . gambiae females readily ingested the NP-sucrose meals regardless of particle size and charge . NP ingestion exhibited little untoward effect on the mosquitoes; for example , in a typical experiment , the survivorship rates for mosquitoes ingesting positively ( N = 30 ) or negatively ( N = 30 ) charged 80 nm x 320 nm NPs ( 250 μg/mL ) or sucrose ( N = 28 ) were 93 , 100 , and 71% , respectively . Similarly , parenteral challenge of larval mosquitoes or in vitro challenge of mosquito cells in culture ( see Figs 6 and 7 in companion paper [38] ) caused little differences in larval survivorship or cell viability . Whole body image analysis was used to detect and quantify NPs following parenteral and oral challenges . Adults were injected with positively or negatively charged 200 nm x 200 nm NPs ( 250 μg/mL ) or sucrose . At 1 d post challenge , mosquitoes injected with the negatively charged NPs exhibited the greater fluorescent signal ( Fig 3 , Row 2 ) . The greatest Mean Fluorescence Intensity ( MFI ) values were also detected in mosquitoes challenged with negatively charged NPs ( Fig 4 ) , and the MFI values at day seven were similar to those at the day of challenge , with the exception of the 80 nm x 5000 nm positively charged NPs ( Fig 4 ) . The reasons for the dramatic differences in MFI between positively and negatively charged NPs following parenteral challenge ( Fig 4 ) may be attributable to more efficient internalization of the positively charged NPs [38] . Oral challenge of mosquitoes yielded different results . Following oral challenge with 200 nm x 200 nm negatively charged NPs for 1 d , MFI values remained very low ( Fig 5 ) . However , following oral challenge for 2 d , MFI values increased significantly to 3 d post exposure and then declined thereafter ( Fig 5 ) . These results were confirmed by oral challenge of mosquitoes with positively and negatively charged 80 nm x 5000 nm and 200 nm x 200 nm NPs ( Fig 6 ) , which also increased in abundance following ad libitum oral challenge . The MFI indices declined to essentially undetectable levels at day seven post-initial exposure . The positively charged , but not the negatively charged , 80 nm x 5000 nm NPs exhibited a similar pattern ( Fig 6 ) . Adult mosquitoes were challenged by contact with positively or negatively charged 80 nm x 320 nm NPs . A drop of the respective particle solution with NP40 ( 0 . 5% ) was placed on the head , thorax , or abdomen . Mosquitoes were dissected at 1 or 2 d post challenge and tissues were examined for fluorescence . Administration of negatively charged NPs to the head resulted in NP detection in head tissues , proboscis and alimentary tract tissues , including diverticula and foregut ) in 100% ( 5/5 ) of mosquitoes 1 d post challenge ( Fig 13A ) . Fluorescence signal was detected in midgut tissue of 60% ( 3/5 ) mosquitoes at 2 d post challenge , but minimal signal was detected in the diverticula at that time . Signal remained intense in certain tissues in the proboscis 2 d post challenge . Following contact challenge to the head with positively charged 80 nm x 320 nm NPs , fluorescence signal was detected in 40% ( 4/10 ) of mosquitoes in the alimentary tract tissues and in the proboscis; however the fluorescent signal was much less intense ( Fig 13B ) . than that detected in mosquitoes challenged with the negatively charged NPs ( Fig 13A ) . Contact challenges with positively or negatively charged NPs to the thorax or abdomen were not promising . Following administration of positively or negatively charged NPs to the thorax , very minimal fluorescent signal was detected at 1 or 2 d post challenge in the alimentary tract or proboscis of 43% ( 12/28 ) of the challenged mosquitoes . Following administration of positively or negatively charged NPs to the abdomen , very minimal fluorescent signal was detected in tissues of 22% ( 4/18 ) of the challenged mosquitoes . The fluorescence signal was typically scored as <1 ( on the scale of 0–5+ ) , and it was difficult to differentiate the mosquitoes challenged by these routes from the control mosquitoes ( Fig 13C ) . Clearly trafficking of NPs into mosquitoes following throrax or abdomen contact challenges is inefficient .
The studies provided important information for the potential use of and preferred physical characteristics of hydrogel NPs for delivery of cargoes ( e . g . dsRNA ) to silence mosquito genes for functional analyses and for mosquito control . Both adult and larval mosquitoes [38] readily ingested the NPs tested . Following 1 d oral challenge of adults positively and negatively charged NPs were detected in dorsal and ventral diverticula , cardia , foregut , and midgut at day one post ingestion ( Fig 7 ) . By day two post ingestion , signal decreased , especially for negatively charged NPs in both the number of tissues exhibiting fluorescence and in fluorescence intensity ( Fig 7 ) . When orally challenged for 1 d , there was minimal detection of the respective NPs in non-alimentary tract tissues ( Fig 7 ) . However , when mosquitoes were challenged for 2 d or more , the biodistribution of NPs changed dramatically ( Figs 5 , 6 and 7 ) . Multiple day challenges resulted in dramatic increases in MFI values , which were nearly undetectable in whole body images of mosquitoes that were orally challenged for just 1 d ( Fig 5 ) . The reason for this is unclear . The NP load is clearly increased in the mosquitoes challenged for multiple days ( Fig 5 ) , and both positively and negatively charged NPs are detected abundantly and persist in the alimentary tract ( Fig 7 ) . Multiple day challenges also results in NP dissemination to non-alimentary tract tissues ( Fig 7 ) , and the resulting biodistribution of NPs was similar to that seen with NPs following parenteral challenge where NPs were detected in or associated with tracheae and tracheoles , cardia , proboscis , etc . ( Fig 12 ) . The decline in MFI values beginning at day two ( Figs 5 and 6 ) was unexpected . Sugar pads were placed on the cages after 1 d , and perhaps mosquitoes began to feed preferentially on the sugar pads . The anatomic basis for trafficking of NPs out of the alimentary tract remains to be determined . Multiple ingestions of NPs may somehow perturb tissue barriers and promote accumulating and trafficking of NPs . However , trafficking of NPs from the hemocoel into the alimentary tract also occurs following parenteral challenge; NPs were detected in the cardia , foregut , and midgut of mosquitoes ( Fig 12B ) . The large accumulation of particles in the cardia and foregut ( Figs 8 and 12 ) following oral or parenteral challenge suggests that this organ may be involved in trafficking . Arboviruses , which must disseminate from the vector gut to infect salivary glands to be transmitted , have been detected in the cardia of infected mosquitoes . Investigators have proposed that the intussusception of the foregut and esophagus , which may be only a cell or two thick , is a likely anatomic mechanism for arbovirus dissemination [41] . The abundant accumulation of NPs in the cardia could result in trafficking of the particles between the body compartments . Arboviruses can also traffic from the midgut into the hemocoel via tracheae [42 , 43] . The association of NPs with tracheae ( Fig 12A ) is also provocative in this regard . The exact mechanism conditioning the trafficking remains to be determined . There were major differences in the biodistribution and trafficking of positively and negatively charged NPs . Following parenteral challenge , positively charged NPs seemed to coat the basal lamina of multiple organs; negatively charged NPs exhibited more punctate fluorescence associated with cells or tissues ( Fig 12B ) . The negatively charged NPs seemed to transit the alimentary tract more rapidly than positively charged NPs . Indeed , negatively charged NPs were expelled and detected on the filter papers lining the plastic containers more frequently and abundantly ( Fig 9 ) . Negatively charged NPs were also detected more frequently in proboscis and head tissues of injected mosquitoes ( Fig 10 ) , suggesting that they trafficked more in the hemolymph than positively charged NPs . Whole body imaging analyses of parenterally challenged mosquitoes ( Figs 2 and 3 ) revealed that negatively charged NPs exhibited greater MFI values and persisted longer in mosquitoes than positively charged NPs . It is noteworthy that the positively and negatively charged NPs exhibited the same phenotype in parenterally challenged larval mosquitoes ( see Fig 5 in companion paper ) [38] . In this regard , positively charged NPs are more efficiently internalized by mosquito cells ( see Fig 1 in companion paper ) [38] . Perhaps inefficient internalization of the negatively charged NPs conditions their persistence in the closed system of the hemocoel ( Figs 2 and 3 ) , which is in contrast to their rapid transit through the alimentary tract ( Fig 9 ) . The preferred charge of NPs for environmental challenge of mosquitoes remains to be determined . Positively charged particles are more efficiently internalized in vector cells [38] , but negatively charged NPs were detected abundantly in tissues in the proboscis , regardless of the mode of challenge . Cells in the labella of the proboscis of mosquitoes frequently contained or were associated with large accumulations of NPs ( Figs 10B and 13 ) . Sensory cells in the labella are of particular interest in terms of potential contact delivery of NPs . These organs are sampling the environment and could be a portal of entry of NP through oral or contact delivery of negatively charged NPs to control mosquitoes . In addition , negatively charged NPs more efficiently trafficked from the cuticle to mosquito organs than positively charged particles ( Fig 13 ) . Future studies will incorporate effector molecules in the NPs , which will then be used to challenge mosquitoes . Such studies will be most informative in selecting the optimal NPs for oral , contact , and parenteral delivery of effector molecules . The large accumulation of NPs in the diverticula of mosquitoes is potentially important in terms of environmental delivery of NPs and their cargoes for vector control . Upon emergence , adult females typically ingest sugar meals to provide energy reserves for mating , host seeking , and other behaviors . Following ingestion , the sugar meal accumulates in the diverticula and is slowly released into the alimentary tract . The large NP load in the diverticula and their subsequent release into the alimentary tract provide ongoing opportunities for NP internalization by gut cells . Importantly , the sugar meal does not induce peritrophic matrix formation , which could serve as a barrier to NP contact with target cells . Sugar baited stations [44] , which have proven to be very useful for arbovirus surveillance in mosquito populations , would thus be a potentially fruitful approach for delivering NPs and their cargoes to mosquitoes in nature . Our results provide insights into NP design that could facilitate insect gene structure and function studies . The ability to deliver effector molecules through oral or contact challenge for gene structure function studies would be of great value and would preclude confounding effects of injection on gene regulation ( e . g . induction of innate immune genes by penetration of the cuticle ) and would also minimize mortality in experimental insects due to injection . Even with parenteral challenge , optimal internalization of NPs ( e . g . positively charged particles ) and delivery of their cargoes into target cells could greatly increase efficiency of gene silencing . Our studies also provide important information for exploiting NP technology for development of new insecticides for mosquito vector control . Studies are in progress to define the preferred physicochemical properties of NPs for environmental delivery of effector molecules for gene silencing and vector lethality . The power of PRINT technology provides unparalleled capacity in this regard and for the development of a new generation of insecticides for insect vector and pest control .
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Emerging insecticide resistance in disease vectors is of great public health concern . Discovery of new targets and novel strategies for insecticidal interventions to control vector borne diseases is a public health imperative . Nanotechnology offers great potential for molecular genetic investigations and for delivery of effector molecules for control of disease vectors . We have developed a tool box of hydrogel nanoparticles ( NPs ) with the biodistribution and tissue tropism characteristics for gene structure/function studies and for delivery of vector lethal cargoes to adult mosquitoes . Nanotechnology will likely be useful for molecular investigations and potential control of the arthropod vectors of other neglected tropical diseases .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
Biodistribution and Trafficking of Hydrogel Nanoparticles in Adult Mosquitoes
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DNA double-strand breaks ( DSBs ) are a common form of cellular damage that can lead to cell death if not repaired promptly . Experimental systems have shown that DSB repair in eukaryotic cells is often imperfect and may result in the insertion of extra chromosomal DNA or the duplication of existing DNA at the breakpoint . These events are thought to be a source of genomic instability and human diseases , but it is unclear whether they have contributed significantly to genome evolution . Here we developed an innovative computational pipeline that takes advantage of the repetitive structure of genomes to detect repair-mediated duplication events ( RDs ) that occurred in the germline and created insertions of at least 50 bp of genomic DNA . Using this pipeline we identified over 1 , 000 probable RDs in the human genome . Of these , 824 were intra-chromosomal , closely linked duplications of up to 619 bp bearing the hallmarks of the synthesis-dependent strand-annealing repair pathway . This mechanism has duplicated hundreds of sequences predicted to be functional in the human genome , including exons , UTRs , intron splice sites and transcription factor binding sites . Dating of the duplication events using comparative genomics and experimental validation revealed that the mechanism has operated continuously but with decreasing intensity throughout primate evolution . The mechanism has produced species-specific duplications in all primate species surveyed and is contributing to genomic variation among humans . Finally , we show that RDs have also occurred , albeit at a lower frequency , in non-primate mammals and other vertebrates , indicating that this mechanism has been an important force shaping vertebrate genome evolution .
Environmental agents and normal cellular metabolic processes produce DNA double-strand breaks ( DSBs ) that can lead to cell death if not repaired [1] . Eukaryotic cells have evolved DSB repair mechanisms that can be classified into two broad categories: homologous recombination ( HR ) and non-homologous end joining ( NHEJ ) . The canonical HR pathway uses long stretches of homology between the flanking sequences at the site of breakage and the homologous chromosome or sister chromatid to repair DSBs perfectly , leaving no evidence that a break ever occurred . Two other forms of DSB repair , single strand annealing ( SSA ) and synthesis-dependent strand annealing ( SDSA ) , can also be classified as types of HR . NHEJ repairs the DSB without the use of a repair template and can create deletions or insertions [2] at the site of the lesion ( Figure 1 ) [1] , [3] . Previous empirical studies have provided a detailed characterization of the breakpoints produced by imperfect DSB repair mechanisms in eukaryotic cells . In vivo and ex vivo systems designed to track the fate of experimentally induced DSBs in yeast , fly , plant and mammalian cells have shown that imperfect repair is often accompanied by the insertion of extra , “captured” DNA at the breakpoint [4]–[12] . Several studies have found that this captured DNA is a duplication of sequences that have homology with the experimentally induced breakpoints such as ( 1 ) a different chromosome [13] , [14] , ( 2 ) extra chromosomal molecules such as plasmids or mitochondrial DNA [7] , [10] , [11] , [15] , ( 3 ) cDNA copies of retrotransposons [11] , [16] or ( 4 ) a nearby sequence on the same chromosome [6] , [17] . One such mechanism for “capturing , ” and thereby duplicating a sequence during DSB repair , is the SDSA pathway . SDSA occurs when nucleotides on one of the overhanging 3′ end of a DSB anneal with a complementary sequence that serves as a template for synthesis . This template may be either homologous or ectopic . Once synthesis is completed , the invading strand is displaced and anneals to the other resected 3′ end of the DSB . If an ectopic template is used , the process results in a conservative , repair-mediated duplication of the template sequence . If an homologous template is used , no duplication occurs . Additionally , both ends of the break are free to anneal with different templates , initiate repair synthesis , then re-anneal with each other . In this case , the duplication of two different templates can occur at the site of breakage ( Figure 1 ) [1] . Though studies have experimentally observed and characterized repair-mediated duplications ( RDs ) , the genome-wide scope and potential impact of these duplications upon vertebrate evolution has not been investigated . Therefore , we sought to computationally identify duplications in vertebrates whose breakpoints bear the signatures of imperfect repair events and assess their potential impact upon genome evolution . Our analysis focused on primates ( human , chimpanzee , orangutan , Rhesus macaque , marmoset ) , but also chicken , zebrafish and other mammals ( mouse , rat , dog , cow ) . We recovered 824 RDs in the human genome , 15 of which were found to be specific to the human lineage , as they are absent from the chimpanzee , orangutan , Rhesus macaque and marmoset . We confirmed experimentally that one of the human-specific RDs remains polymorphic in the general population . Lineage-specific RDs were found in all genomes for which a closely related ancestor was available as outgroup . Thus , RDs are a previously under-appreciated force shaping vertebrate genomes and generating structural genomic variation among humans .
In order to find duplications whose breakpoints bear the previously characterized hallmarks of imperfect repair events , but not those of other known duplication mechanisms ( such as retrotransposition ) , we developed a novel computational approach that capitalizes upon the repetitive nature of eukaryotic genomes . In humans and other primates , about 45% of the genome is composed of interspersed repeats that derive from the activity of a limited number of transposable element ( TE ) families [18] . Since the derived ancestral consensus sequence for any family of TEs is known , the insertion of a sequence within a TE can be found by locating fragments of annotated TEs that are separated by an intervening sequence that is not alignable with the consensus sequence ( Figure 2 ) . Drawing upon the wealth of TE annotation available , our computational pipeline began with a Perl script that parsed the human RepeatMasker ( rmsk ) annotation files ( hg18 assembly , http://genome . ucsc . edu ) to identify TEs that were interrupted by an insertion of at least 50 bp . The first pass returned over 492 , 000 such insertions , the majority of which were identified as transposon insertions . A small proportion of these insertions could be classified as processed retrogenes or LINE1 ( L1 ) -mediated transduction events and , like the nested transposon insertions , were filtered out ( see Materials and Methods ) . Next , we excluded inserted sequences not identified as any of the above types of duplications , but found at more than one other location in the genome or where a second , parental copy of the insertion could not be confidently identified in the available nuclear genome sequence . In addition , we found 113 insertions that mapped within an annotated segmental duplication ( SD ) for which we could not confidently identify the parental copy . As such , these insertions were also filtered out from the data set . Finally , we removed any cases where the inserted sequence and putative template sequence were within 50 bp of each other to exclude tandem duplications , which are typically formed by a mechanism other than DSB repair [19] . The remaining dataset included 1 , 136 interrupted TEs that had suffered the insertion of a sequence found at only one other location in the genome , each of which may represent DNA captured via SDSA at former sites of DSB . Strikingly , for 824 of the 1 , 136 duplicons , the donor sequence was located within 5 kb of the acceptor , with 753 ( 66% ) duplicons separated by less than 3 kb . The remaining 312 duplicons were separated by more than 5 kb ( n = 58 , max = 122 Mb ) or were located on different chromosomes ( n = 254 ) . A histogram of the distances between donors and acceptors located on the same chromosome demonstrated a seeming peak in the distance separating the duplicons at approximately 1 , 200 bp ( Figure 3 ) . However , we note that this peak may be an artifact of our method , as we used TEs as markers to identify acceptor sequences . Since the acceptor is located within a TE , the donor and acceptor must be separated by at least the length of the TE fragment the acceptor is located in . However , a long tail at the right side of the histogram was also apparent , as the maximum distance between donor and acceptor was 122 Mb . This clearly indicated that acceptor and donor sequences are more likely to be located within close range of each other than widely separated . For increased readability , distances between donor and acceptor of greater than 5 kb were combined into one bin ( >5000 , Figure 3 ) . We used this ad-hoc cutoff to split the duplicons into two groups: one where the donor and acceptor were within 5 kb of each other ( proximal duplications ) and the other where the donor and acceptor were separated by >5 kb or were on different chromosomes ( distant duplications ) . We noticed that the two groups were also distinguishable by the length of the duplicated ( acceptor ) sequence , which is shorter for proximal duplications ( mean = 162 bp , median = 147 bp , max . = 619 bp ) than for distant duplications ( mean = 302 bp , median = 204 bp , max . = 3 , 424 bp ) , a statistically significant difference ( Student's t-test , p<0 . 001 ) . Further examination of the acceptor sequences revealed that in 20 instances , the acceptor was a chimera of 2 different donor sequences ( Table S1 ) , as predicted by the SDSA model of DSB repair and observed previously at experimentally induced DSBs [14] . For every chimeric acceptor case , at least one of the donor sequences was located within 5 kb of the acceptor . In five cases , the second donor was within 3 . 5 kb of the first donor ( range = 289–3 , 432 bp ) , while in the other 15 cases , the second donor was located on a different chromosome . This type of chimeric duplication may be formed when the 3′ overhanging ends at the site of DSB invade different template strands and reanneal at a stretch of microhomology ( Figure 1 ) . One example of such chimeric duplication is shown in Figure 4 together with the “empty” orthologous insertion site in the chimpanzee and macaque genomes , which indicates that this particular duplication is human-specific . Note the short stretch of base complementarity ( 3 nucleotides ) at the presumed site of annealing between the two copied donor sequences , as well as the short filler DNA sequence inserted at one of the duplication breakpoints , another signature of DSB repair ( see below ) . We next focused on precisely defining the breakpoints of the potential RDs in our dataset to determine if the hallmarks of DSB repair were present ( Figure S1 ) . For this , we took advantage of the availability of draft genome sequences for four closely related primate species ( chimpanzee , orangutan , Rhesus macaque and marmoset ) and three non-primate mammals ( dog , cow and mouse ) available at the UCSC Genome Browser to perform a comparative genomic analysis . We found that 24 of the duplicons were human-specific ( present only in human , absent in all other primate species ) , 67 were hominin-specific ( present only in human and chimpanzee ) , 190 were hominid-specific ( present only in human , chimpanzee and orangutan ) , 289 were catarhinne-specific ( present only in human , chimpanzee , orangutan and Rhesus macaque ) , 513 were primate-specific ( present only in primate species ) and the remaining 53 were present in all primates and at least one other non-primate mammal ( Table S1 ) . Given the relatively recent divergence of hominids ( 18 mya ) , and thus , the short time period for substitutions to accumulate , we focused on precisely defining the breakpoints of RD that occurred in the hominid lineage ( Figure S1 ) . We aligned and individually inspected the breakpoints of all human-specific duplications for which orthologous sequences could be unambiguously identified in the other primate species ( i . e . , 18 out of 24; 14 with the donor <5 kb from the acceptor , 4 where the donor was on a different chromosome ) as well as a sample of 50 hominid-specific duplicons ( 25 randomly selected with the donor <5 kb from the acceptor and 25 randomly selected where the donor was on a different chromosome ) . We found that 51 of the 68 breakpoints ( 75% ) examined were characterized by the molecular signatures of SDSA events including deletions , “filler” sequences or stretches of microhomology between the flanking sequences of the donor and acceptor ( Table 1 ) [6] , [7] , [20] . The 17 remaining acceptor loci were characterized by the addition of a polyA or polyT tract of 5 bp or greater at one end of the insertion , indicative of the retrotransposition of processed mRNA by target-primed reverse transcription [21] , [22] . Such retrotransposition events are typically accompanied by target site duplications and , indeed , we were able to identify such duplications flanking 12 of the 17 acceptor sites terminating in polyA/T tracts ( Table 1 ) . We noticed that none of the 39 acceptor sequences from which the donor was located within 5 kb possessed polyA/T tracts ( 14 human-specific , 25 hominid-specific ) , while 17 of the 29 ( 59% ) in the other group did ( Table 1 ) . In other words , all proximal duplications ( where the donor is <5 kb from the acceptor ) bear characteristics consistent with imperfect DSB repair , while a majority of the other , more distant duplications possess characteristics of retrotransposition events . These data indicate that proximal duplications can be confidently classified as RDs , while more distant duplications cannot . Therefore , for the rest of this analysis we focus on the proximal duplication group , yielding a set of 824 probable RDs in the human genome . In order to estimate and compare the rate of repair-mediated duplication in different branches of the primate evolutionary tree , we used the same computational pipeline described above to recover chimpanzee- , orangutan- and Rhesus-specific RDs . As for human RDs , we only retained duplicons located within 5 kb of each other as manual inspection of the breakpoints of chimpanzee-specific acceptor sequences for proximal and distant duplicons gave results consistent with those obtained for human ( data not shown ) . From these data , we were able to infer the minimum rate of duplication ( i . e . , number of repair-mediated duplication events per myr ) along different branches of the primate phylogenetic tree over the past ∼40 myr ( Figure 5 ) . In the 12 myr separating the divergence of Rhesus macaque from the hominid lineage , the rate was found to be 11 . 8 RD/myr ( 142 hominid-specific RDs ) . However , in the 12 myr between the divergence of orangutan from human and chimpanzee , the rate was only 3 . 1 RD/myr . The rates in the three hominid species were almost identical ( human = 2 . 5 RD/myr , chimpanzee = 4 . 0 RD/myr , orangutan = 2 . 7 RD/myr ) , while a higher rate was found in the Rhesus macaque lineage ( 8 . 1 RD/myr ) . Thus , there seems to have been a substantial slowdown ( about 4 fold ) in the rate of repair-mediated duplication events in the hominid lineage as compared to the period predating the divergence of the hominid lineage from Old World monkeys ( Figure 5 ) . A positive correlation was observed between the average sequence divergence between donors and acceptors and the time period at which the duplication event was inferred by the comparative genomic analyses . As expected , the average divergence between donor and acceptor increased as the time since RD formation extended back from the present ( Figure 5 ) . The RD divergence values were also in good agreement with the expected sequence divergence between the related species as if the bulk of RDs had evolved at the neutral substitution rate following duplication . For example , the average pairwise divergence between donors and acceptors was 0 . 89% for human-specific and 1 . 34% for chimpanzee-specific RDs ( Figure 5 ) . Assuming a neutral substitution rate of 2 . 2×10−9 substitutions/yr [23] , the expected average divergence for RDs in the human and chimpanzee lineages should be 1 . 32% . While the average divergence for chimpanzee is almost exactly what is expected , the average divergence is slightly lower than expected for the human-specific RDs . However , the lower than expected divergence in human may be the result of a small sample size ( n = 15 ) and therefore must be viewed with caution . Interestingly , the average percent divergence of RDs in the orangutan lineage ( 1 . 33% ) is significantly lower than expected ( 3 . 96% ) assuming the same neutral substitution rate as in the human and chimpanzee lineages ( p<0 . 05 , χ2 test ) . This low percent divergence may be the result of a general slowdown of the neutral substitution rate in the orangutan lineage or of a period of relative quiescence of the mechanism responsible for RD formation early in the orangutan lineage followed by a subsequent increase . Another possible explanation is that a larger fraction of orangutan RDs have evolved under functional constraint following duplication . Identification of 7 human-specific RDs in which the donor and acceptor sequences were identical suggested that these duplications occurred in the very recent past and could still be polymorphic in the human population . To test this hypothesis , we screened 4 of these 7 RDs , along with 6 additional human-specific acceptors in 80 individuals from 4 geographic populations ( African-American , Asian , European , and South American ) for presence/absence using PCR with primers flanking the insertion . Of these 10 RDs , all but one appeared to be fixed in the human population . In addition , all 10 RDs examined were absent in the chimpanzee , gorilla and orangutan genomes analyzed ( see example in Figure 6E ) , corroborating our computational prediction that they are indeed human-specific . The insertion at chr15:31 , 987 , 740–31 , 988 , 005 in the hg18 assembly of the human genome , is apparently fixed in all European and South American populations , but remains polymorphic in African-American and Asian populations ( Figures 6A–6D ) . This acceptor sequence was also precisely absent in the Celera human genome assembly , while all other human-specific RDs were present ( data not shown ) . Next , we screened six chimpanzee-specific acceptors for polymorphism with DNA extracted from 12 unrelated common chimpanzees , but were unable to find any polymorphic RDs . These results may be due to a small chimpanzee sample size ( 12 individuals ) in comparison to the human sample size ( 80 individuals ) . Therefore , the possibility cannot be excluded that some chimpanzee-specific RDs are still polymorphic . Each chimpanzee-specific acceptor tested was absent from human , gorilla , orangutan and Rhesus macaque DNA tested ( see example in Figure 6F ) , validating that these RDs are indeed specific to chimpanzees . We next investigated whether RDs were responsible for the duplication of potentially functional sequences such as exons , predicted transcription factor binding sites and mammalian most conserved sequences ( PhastCons , 28-way; Table 2 ) . We found that two complete exons were duplicated , one within the acyl-CoA synthetase bubblegum family member 2 ( ACSBG2 ) gene ( exon 7 ) and the other in a predicted gene of unknown function ( C17orf57 , exon 20 ) . In the ACSBG2 gene , the duplicated exon inserted within an intron of the same gene , but in the opposite orientation as the donor exon . Transcriptome data indicates that this duplicated exon is transcribed in the opposite orientation relative to the donor exon and appears to form a fusion transcript with an additional non-coding exon located upstream of the ACSBG2 gene boundary ( ESTs CD687637 , BI912699 , BG573431 ) . Although the duplicated exon has preserved an intact open reading frame and high sequence identity ( ∼94% ) to the donor exon , Ka/Ks analysis revealed no evidence of selective constraint acting at the coding level on the duplicated exon since duplication ( Ka/Ks not significantly different from 1 , p>0 . 05 ) . No evidence for the transcription of the duplicated exon in the C17orf57 gene could be found , nor any evidence of selective constraint ( Ka/Ks not significantly different from 1 , p>0 . 05 ) . Of the 824 donor sequences , 22 contained sequences annotated on the UCSC Genome Browser as predicted transcription factor binding sites ( TFBS ) . In 21 instances , the same TFBS was also computationally predicted within the corresponding acceptor . Seven of the duplicated TFBS display 100% nucleotide identity between the donor and acceptor , while the other 14 display an average of 86% identity . These data suggest that RD represents a possible mechanism for locally duplicating TFBS , thereby potentially contributing to evolution of genomic regulation . Mammalian most conserved ( PhastCons ) sequences are DNA segments that are significantly more conserved between distant mammalian species than expected under a neutral model of sequence evolution , suggesting that these sequences correspond to functional elements evolving under purifying selection [24] , [25] . Of the 824 RD donors , 82 contained at least one full-length PhastCons segment . With the exception of the two aforementioned complete exons and two additional exons partially duplicated , these conserved segments map to non-coding sequences , some of which may possess regulatory functions . In most cases , the duplicated sequences have retained high identity ( >90% ) with the donor sequence , which suggests that RD is a potent mechanism for the emergence of new functional elements . In principle , RDs may arise anywhere a DSB occurs . Since DSBs can occur on any human chromosome , and assuming that the SDSA pathway can generate RD on any chromosome , we would expect to find RDs on all human chromosomes . Indeed , we were able to identify RDs on all human chromosomes , except the Y chromosome ( see Figure S2 ) . To assess whether RDs are equally distributed among chromosomes , we performed Monte Carlo simulations to determine the expected number of RDs per chromosome based upon the percentage of the total genomic DNA accounted for by each chromosome ( see Materials and Methods ) . The distribution of RDs per chromosome did not significantly differ from the expected value ( p>0 . 05 after Bonferroni correction applied ) . To ensure that these results were not an artifact of our computational method of finding RDs within TEs , we performed the same simulations as above but calculated the expected number of RDs per chromosome based upon the percentage of TE DNA on each chromosome ( see Materials and Methods ) . Using this method , we discovered a statistically significant deficit of RDs on chromosome X ( obs = 29 , exp = 53 , p<0 . 0001 ) . In an attempt to investigate the potential factors underlying this bias , we first looked at a possible inverse correlation between RD and gene densities . This observation might indicate that RDs in gene-rich regions may be deleterious , and thus more likely to be removed from the population , than those in gene-poor regions . To investigate this hypothesis , we first compared gene density within a 2-Mb window centered around each of the 824 RDs identified in the human genome to gene density within a 2-kb window centered around a set of 10 , 000 randomly sampled sequences from all chromosomes with a length of 162 bp , i . e . , the average length of the RD . There was no statistically significant difference in gene density surrounding RDs ( mean = 14 . 3 genes per 2 Mb ) and the random set of sequences ( mean = 14 . 8 per 2 Mb; Student's t-test , p>0 . 05 ) . Moreover , these densities were in good agreement with prior estimates of genome-wide gene density [18] . Therefore , RDs do not seem to accumulate in particularly gene-poor or gene-rich regions of the genome . When we calculated gene densities per chromosome , rather than genome-wide , as expected , we identified chromosome 19 as the most gene-rich chromosome with 56 . 9 genes per 2 Mb . However , chromosome X , which showed a deficit of RDs , had a gene density of 15 . 8 genes per 2 Mb , placing it as the 10th most gene dense chromosome , near the genome-wide average [18] . In sum , these analyses revealed no clear relationship between RDs and gene density and therefore the deficiency of RD on chromosome X remains largely unexplained . With strong evidence that RDs are common in primate genomes , we used our computational pipeline to screen 6 additional sequenced vertebrate genomes for the presence of RDs , using the same methodology that was used for the primate genomes . These genomes included one bird ( chicken ) , one fish ( zebrafish ) and four other mammalian species ( mouse , rat , dog , and cow ) . Although the amount and density of TEs in each genome differed significantly among these species ( from 8% in chicken to 41% in dog ) , our pipeline proved effective at uncovering RDs in all genomes surveyed ( Table 3 ) . For those species where there was sufficient genome data from a closely related species , sequence alignments were constructed between the surveyed and related species to precisely examine the breakpoints and validate the RDs ( Figure 7 ) . For those species where sequence data from a closely related species was not available , we aligned the TE in which the RD had occurred with the ancestral consensus sequence to identify the pre-integration empty site . Though this method is not as conclusive as cross-species alignment of orthologous loci , it is still effective for predicting the probable breakpoints and identifying the molecular signatures of RD such as deletions , insertions and microhomologies ( Figure 7 ) . The analysis of this group of non-primate species shows conclusively that RDs are not only shaping the genomes of primates , but also of other vertebrates . Comparison of the number of RDs within each surveyed vertebrate species revealed that the number of RDs per megabase of TE sequence ( RD density , Table 3 ) was strikingly higher in all primate species ( range = 0 . 52–0 . 65 ) than in other mammals ( range = 0 . 18–0 . 26 ) and the difference was even more pronounced between primates and non-mammalian vertebrates ( range = . 08–0 . 19 ) . These data suggest that the mechanism of RD and/or the probability of RDs becoming fixed within a population differ substantially between different branches of the vertebrate tree .
In this work , we present the first detailed analysis of duplicated DNA segments that bear the hallmarks of repair-mediated capture of other chromosomal sequences across a wide range of vertebrate species . Our investigation focused solely upon RDs that occurred within the portion of the genome derived from TEs . However , we believe that since TEs comprise at least 40% of primate genomes and are found distributed along all chromosomes , our results can be extrapolated to the rest of the genome . Indeed , RDs are , with few exceptions , randomly distributed throughout the human genome ( Figure S2 ) and were found in each of the different TE classes ( LINE , SINE , LTR , and DNA ) in rough proportion to their relative abundance in the genome ( see Table S1 ) . Computational analysis of low copy number duplications ( <10 copies ) in large vertebrate genomes has typically focused on segmental duplications ( SDs ) , which are defined as duplicated segments longer than 1 kb with more than 90% identity [26] . It has been shown that SDs account for a sizeable fraction of mammalian genomes ( e . g . , 5% in human ) and represent an abundant source of structural genomic variation within species [27]–[29] . By contrast , the frequency and impact of shorter ( <1kb ) duplications have not been systematically and thoroughly investigated . One of the challenges of analyzing shorter duplications is the computational time and power involved in identifying and characterizing such duplications , especially in large and complex genomes . Hence , the few studies that have surveyed small-scale duplications have focused on identical or nearly identical duplicons ( <100 bp ) [30]–[32] . These studies have revealed that most of these short duplications occur in tandem or in close proximity . Interestingly , Thomas et al . [30] discovered an abundant class of short local duplications , called doublets , which share many of the attributes of the RDs identified herein . The authors hypothesized that some of these doublets may have arisen via imperfect DSB repair mechanisms , although this model was not further examined . Our study provides support for this hypothesis and provides additional evidence that a substantial number of short local duplications in the human genome arose via imperfect DSB repair , as predicted initially by Thomas et al . [30] . Our approach distinguishes itself from previous studies by the fact that it provides immediate identification of the template ( donor ) and duplicated copy ( acceptor ) . Another advantage is that our pipeline significantly reduces both the time and computational resources needed to find such duplications and circumvents the cumbersome and error-prone tasks of parsing large amounts of multi-species alignment data . One obvious drawback of the method is that it is dependent on the number of TEs and on the annotation of these elements , which vary considerably between genomes and relies on the definition of accurate consensus sequences . However , for genomes such as mammals , which contain large quantities of TEs , and for which high-quality consensus libraries are available , our method provides a powerful alternative to those relying on self- or cross-species alignments . An additional drawback is that the acceptor sequences must be at least 50 bp . One key component of our algorithm is Blast [33] , which incorporates the length of the query sequence , in this case , the acceptor , to calculate the statistical significance associated with high-scoring pairs . Therefore , very short query sequences may not produce sufficiently low e-values to accurately identify donor/acceptor pairs . Our approach is also unique in that it can be tailored to identify duplications that arose by a particular mechanism . Here we focused on duplications that bear the hallmarks of SDSA-mediated DSB repair events characterized experimentally in previous studies . However , one could readily modify our computational pipeline to identify other types of duplications ( e . g . , retroposition ) or imperfect repair events leading to deletions . In fact , our data indicates that the majority of the inter-chromosomal duplications identified during the course of this study are retroposition events that would have escaped detection by methods traditionally employed to identify this type of duplications , i . e . , those which use protein-coding sequences as seeds [34] . Our results suggest that RDs are most likely formed by the SDSA repair pathway . It has been proposed that a mechanism similar to SDSA may be responsible for the formation of segmental duplications in Drosophila [35] . Our study provides several lines of evidence indicating that , in mammals and possibly in other vertebrates , SDs and RDs arise by distinct mechanisms . First , RDs are much shorter than typical SDs . The average size of the acceptor sequences was 162 bp and the largest unequivocal RD we could find was 619 bp . In contrast , SDs are , by definition , larger than 1 kb and often reach dozens of kilobases . While it is conceivable that SDSA could create duplications longer than what our pipeline was able to retrieve , these events would seem to be atypical . Thus , RDs and SDs differ markedly in terms of the size of the duplicated DNA segment . Second , in 48% of all human SDs , the duplicons are located on different chromosomes [26] . In our analysis , we found that the donor was on a different chromosome than the acceptor in only 254 of the 1 , 136 potential RDs ( 22% ) . In addition , in a sample of 29 inter-chromosomal duplications closely examined , we found that 17 instances ( 59% ) bear the hallmarks of retrotransposition rather than imperfect DSB repair ( J . K . Pace and C . Feschotte , unpublished data ) . Thus , unlike SDs , the overwhelming majority of RDs are intra-chromosomal events . Third , the genomic distribution of RDs and SDs bear little , if any resemblance . Like RD density , SD density is not uniform among human chromosomes , with some chromosomes showing either an excess ( chromosome 19 ) or deficit ( chromosome 8 ) of duplicons [36] . However , chromosome X , with a deficit in RDs , is neither enriched nor depleted in SDs . While the chromosomal content of SDs can be explained , in part , by a positive correlation between intra-chromosomal SDs and gene densities [36] , [37] , we found no clear correlation between RDs and local gene densities . The majority of intra-chromosomal SDs form complex clusters aggregated within the interstitial regions of chromosomes ( i . e . between pericentromeric and telomeric regions ) [26] . We observed no trend for the 824 intra-chromosomal RDs to form clusters or to be located within interstitial regions , but rather to be distributed across the entire length of chromosomes ( see Figure S2 ) . Collectively these data strongly suggest that RDs and SDs represent separate classes of genomic duplications that arise via distinct mechanisms , although both types of duplication must be initiated by DSBs and likely involve repair mechanisms [38] . RDs appear to follow a more uniform genomic distribution than SDs , although some chromosomal biases may be apparent . The most striking characteristic of RDs is their proximal arrangement: the average distance separating RDs is only 1 . 2 kb and scarcely exceeds 5 kb ( Figure 3 ) , while that of intra-chromosomal SDs is 3 Mb [26] . The limited distance between donor and acceptor sequences involved in repair-mediated duplication may reflect the preferred use of ectopic template ( s ) located on the homologous chromosome ( which may explain the deficiency of RDs on the X chromosome ) and biophysical constraints during the process of SDSA . The 824 RDs identified in this study have duplicated a total of 133 kb of DNA in the human genome . This is a minimal estimate since we could only recover RDs within the portion of the genome occupied by TEs ( ∼45% ) . Furthermore , our computational pipeline required the insertion to be present in a single copy elsewhere in the genome , which systematically excluded all instances where part of a TE or another repeat may have been duplicated by the process . Finally , our threshold for retaining high-scoring hits limited us to relatively recent duplication events . Indeed , out of 824 RDs in human , only 53 were found at the orthologous genomic position in a non-primate species ( Figure 5 ) . Also excluded from this count are inter-chromosomal events and duplicons located more than 5 kb apart , a fraction of which are likely to represent bonafide RD events ( an estimated 41% based on our sampling , i . e . , ∼124 events ) . Thus , the process of RD accounts for hundreds of small-scale duplication events in the human genome . We found that RD can affect virtually any sequence in the human genome , including exons , untranslated regions ( UTRs ) , predicted transcription factor binding sites ( TFBS ) and most conserved ( PhastCons ) elements ( Table 2 ) . Each of the functional elements duplicated has the potential to be re-used at the acceptor site . In addition , the duplication of TFBS can lead to changes in chromatin structure at the acceptor site and generate new transcripts by duplication of promoter sequences and splice sites . Thus , like other forms of genomic duplication , RDs have the potential to profoundly alter genome architecture . RDs offer the added originality of creating local duplications , a characteristic that might promote the functionalization of the newly duplicated segment . For example , duplicated exons are likely to be inserted , together with their flanking splice sites , in adjacent intron sequences ( see the example of RD within ACSBG2 ) , which may facilitate their incorporation into a splice variant producing a new protein isoform . The local duplication of TFBS may be particularly relevant to regulatory evolution because they are known to occur frequently , and function cooperatively , as closely spaced pairs [39] , [40] . RDs may also contribute to the rapid positional turnover observed for TFBS , which is thought to occur in part via local duplication [41]–[43] . Finally , local duplications may promote further genomic rearrangements , such as deletion or inversion of the intervening sequence mediated by ectopic recombination between the duplicated segments . Thus , RDs present a number of characteristics that provide them with a strong potential for genomic restructuring . We found substantial variations ( up to eightfold ) among different vertebrate species in RD density ( see Table 3 ) . In particular , we found two- to threefold higher RD density in primates than in non-primate mammals ( mouse , rat , dog , and cow ) , even though genome size , TE content and TE composition are similar in all these species [44] , [45] . The faster rate of DNA substitution and deletion in the rodent lineage could , in principle , account for some of the discrepancy , as it would hinder our ability to detect relatively ancient RDs in these genomes and effectively limit the evolutionary depth of our analysis as compared to the primate lineage . However , this phenomenon cannot account for the difference in the number of RDs observed in the human genome ( n = 824 ) and those in dog ( n = 192 ) , in which the dog substitution rate is only 1 . 18 times higher than that of human [45] . Another explanation could be that these discrepancies reflect intrinsic differences in the fidelity or usage of repair mechanisms in the germline of these mammals . Previous studies have shown that several proteins involved in DSB repair are under positive selection in yeast , potentially due to pressures exerted by retrotransposon activity [46] . Additionally , the repair protein Cernunnos-XLF has been shown to be under positive selection within the human lineage [47] . These observations suggest that DSB repair proteins in different species lineages might be subject to different selective pressures imposed by lineage-specific waves of TE amplification , retroviral invasions or other evolutionary forces . Thus , it is possible that the variation in the number of RDs observed in different mammalian lineages mirrors some intrinsic divergence in their repair machinery . Still another , not mutually exclusive alternative could be that species variations in RD density reflect different levels of genome instability experienced in each lineage . In other words , one would expect that genomes that have been subject to higher levels of DSBs in the past would display more instances of RD . Indeed , several lines of evidence suggest that primate genomes have been subject to particularly intense genomic instability . First , the human and chimpanzee genomes have undergone a profusion of lineage-specific segmental duplications in the recent past , with as many as 33% of the human SDs having occurred solely in the human lineage [48] . Furthermore , SDs are more abundant in primate genomes than in the genomes of mouse , rat and dog , especially interspersed ( non-tandem ) duplications [26] , [49] , [50] , that in turn likely triggered further genomic instability [26] . Secondly , primate genomes have endured large bursts of transposition over relatively short periods of time , especially during the first half of the primate radiation , leading to high copy number TE families specific to the primate lineage [18] , [44] , [51]–[53] . Such transposition bursts are likely to have been accompanied by a profusion of double-strand breaks caused either directly by the endonuclease activity of transposition enzymes or indirectly by recombination events between dispersed TE copies . Although it is clear that many TEs have been concomitantly active in other mammalian lineages , it appears that carnivores at least [45] , and potentially also artiodactyls , have experienced less explosive TE invasions and may have experienced fewer TE-induced DSBs . The latter scenario could also account for the observed slowdown in the rate of repair-mediated duplication in hominoids compared to their anthropoid ancestors ( Old and New World monkeys , see Figure 5 ) . Notably , the periods of highest repair-mediated duplication in primates coincide with the periods of most intense activity of L1 , as reflected by the copy numbers of L1 , Alu and processed pseudogenes inserted at that time , which all rely on the machinery of the autonomous L1 retrotransposon for amplification [18] , [51] , [54] . Given that the L1 machinery is also a potent source of DSBs [55] , the tremendous activity of L1 during these periods would have caused significant genomic instability , creating hundreds of thousands of opportunities for DSBs to be repaired via the SDSA pathway , thereby creating RDs . In the era between 30 and 42 Mya , when we found the most elevated rate of RD ( 18 . 3 per Myr ) , L1 generated ∼23 , 000 copies of itself ( L1PA7 , L1PA8 , L1PA8A ) [52] and ∼342 , 000 copies of AluSx elements [56] ( see http://genome . ucsc . edu for counts ) . In the subsequent period ( 30-18 Mya ) , when the rate of RD decreased to 11 . 8/Myr , ∼29 , 000 L1 ( L1PA4 , L1PA5 , L1PA6 ) [52] elements and ∼139 , 000 AluY [56] elements were added to the primate lineage . In contrast , only ∼17 , 000 L1 and ∼10 , 000 Alu elements have been added to the human genome in the past 18 myr , where we observe the lowest rate of repair-mediated duplication ( ∼3/myr ) . Thus , there is an excellent correlation between the level of activity of L1 and the rate of RD during primate evolution . A second line of evidence for varying levels of genomic instability during primate evolution lies in the analysis of nuclear mitochondrial insertions , or NUMTs , and of SDs , both of which are likely initiated by DSB [38] , [57] . Two independent studies concluded that a significant burst of NUMT integration in the primate lineage occurred between the split of New and Old World monkeys ( 30–42 Mya ) , followed by a slowdown of NUMT accumulation [58] , [59] . In addition , a significant burst of inter-chromosomal segmental duplication was observed during or shortly after the divergence of Old World monkeys from the hominoid lineage ( 25–30 mya ) [60] . These bursts of NUMT and SD coincide with the highest rate of RD formation in the primate lineage ( see Figure 5 ) . While some of these bursts might also be explained by population bottlenecks promoting the fixation of these rearrangements or by differences in generation time between species , these observations collectively suggest that a high level of genomic instability and structural variation occurred in the primate lineage between 18 and 42 Mya . Our findings that RDs occur not only in primate genomes , but also in other vertebrate genomes , indicates that this mechanism has been shaping genomes for potentially hundreds of millions of years . Since RDs are most likely created by SDSA , a form of homologous recombination , it is not surprising that RDs have occurred in a wide range of vertebrates . Although there has been a significant decrease in the formation ( or fixation ) of RDs in the human lineage , the process has nevertheless generated numerous lineage-specific duplications during hominid evolution and produced structural genomic variation among humans . Recent genome-wide analyses have revealed that non-TE insertions ranging in size from a few dozens to a few hundred nucleotides are among the most common structural variants among humans [61] , [62] . Based on our data , we can anticipate that some of these structural variants result from imperfect DSB repair processes akin to SDSA .
Genome sequences and RepeatMasker rmsk files were downloaded from the UCSC Genome Browser ( http://genome . ucsc . edu ) . The versions used were: human ( hg18 ) , chimpanzee ( panTro2 ) , Rhesus macaque ( rheMac2 ) , mouse ( mm8 ) , rat ( rn4 ) , dog ( canFam2 ) , cow ( bosTau2 ) , chicken ( galGal3 ) and zebrafish ( danRer4 ) . Potential RDs were identified by a Perl script that searched the RepeatMasker rmsk files for TEs that had been interrupted by some intervening sequence . A TE was classified as interrupted if the repeat name and orientation of the first segment ( TE-A ) matched the repeat name and orientation of the second segment ( TE-B ) , TE-A and TE-B were separated by at least 50 bp and neither TE-A nor TE-B was longer than 95% of the length of the consensus sequence . In addition , the ending consensus sequence position of TE-A was within +/− 30 bp of the starting consensus sequence position of TE-B . After the potential RDs were identified , false positives were removed . TEs separated due to nested TE insertions were removed with a Perl script and annotated retrogenes , segmental duplications or L1-mediated 3′ transduction events were manually inspected and removed from the dataset . For all remaining potential RDs , a Perl script retrieved the acceptor sequence , along with 100 bp flanking each side , and used this sequence as a Blastn query against the entire genome . In order for a Blast hit to be considered , it had to match at least 80% of the length of the query sequence with at least 50% identity . The minimum cutoff score was calculated separately for each acceptor sequence using a sliding e-value that was unique for each query sequence . The Blast output was then parsed . If the acceptor sequence minus the flanking regions was found in more than two HSPs ( high-scoring pairs ) , the RD was removed from the dataset since the donor could not be unequivocally determined . Additionally , if the acceptor sequence with the flanking regions was found more than once , the RD was discarded to avoid including potential segmental duplications or transposition of chimeric TEs . Finally , if the donor was within 50 bp of the acceptor sequence , the RD was also removed from the dataset . If all of the above criteria were successfully met , the putative donor sequence was used as a Blastn query sequence against the entire genome . This “reciprocal” Blast query then used the same criteria to determine if any sequence matched the donor . In order for the acceptor and donor sequences to be classified as a putative RD , the acceptor sequence had to be the second hit in the Blastn output generated when the donor was the query sequence and the acceptor had to meet all criteria . To verify that the computationally detected RDs existed in vivo and did not represent genome assembly errors , we designed oligonucleotide primers flanking each locus using the Primer3 web interface ( http://frodo . wi . mit . edu/ ) . PCR amplification was performed in 25-ul reactions with 10–50 ng genomic DNA , 200 nM of each oligonucleotide primer , 200 mM dNTPs in 50 mM KCl , 1 . 5 mM MgCl2 , 10 mM Tris-HCl ( pH 8 . 4 ) , and 2 . 5 units Taq DNA polymerase on an Applied Biosystems GeneAmp PCR System 9700 thermocycler . Amplification cycles were as follows: an initial denaturation step of 94°C for 4 min; followed by 32 cycles of 1 min of denaturation at 94°C , 1 min of annealing at optimal annealing temperature , and 1 min of extension at 72°C; followed by a final extension step at 72°C for 10 min . For loci with large duplications ( >2 kb ) , we used Ex Taq polymerase ( TaKaRa ) and carried out PCR in 50 ul reactions following the manufacturer's suggested protocol . PCR amplicons were separated on 2% agarose gels , stained with ethidium bromide , and visualized using UV fluorescence . To identify lineage-specific human and chimpanzee duplication loci , PCR amplification was performed on a panel of genomic DNA from five primate species , including Homo sapiens ( HeLa; cell line ATCC CCL-2 ) , Pan troglodytes ( common chimpanzee; cell line AG06939B ) , Pan paniscus ( bonobo or pygmy chimpanzee; cell line AG05253B ) , Gorilla gorilla ( western lowland gorilla; cell line AG05251 ) , and Pongo pygmaeus ( orangutan; cell line ATCC CR6301 ) . To evaluate polymorphism rates of human lineage-specific duplications , we amplified loci on a panel of genomic DNA from 80 diverse human individuals ( 20 from each of four populations: African-American , South American , European , and Asian ) that was available from previous studies in the Batzer lab at Louisiana State University ( Table S2 ) . In order to calculate the expected number of RDs per chromosome based upon the percentage of total genomic DNA accounted for by each chromosome , we used a variation on a previously published Monte Carlo simulation [63] . We used a series of PERL scripts to divide the human genome ( version hg18 ) into 10 , 000 equal size bins ( 308 , 042 bp/bin ) and calculate the number of RDs per bin , based upon the number of RDs we had previously discovered . A final PERL script performed the actual Monte Carlo simulation . This script loaded all 10 , 000 bins , along with the number of RDs in each bin , into an array and the rows were randomized . The first n rows of the array , where n is the number of bins on a given chromosome based on the chromosomes length , were examined and the total number of RDs in these bins was calculated . For example , since chromosome 1 had 803 bins based upon its length , the first 803 rows of the array were be used to calculate the expected number of RDs on that chromosome . This process was repeated 10 , 000 times for each chromosome . A similar process was used to calculate the expected number of RDs per chromosome based upon the percentage of the total amount of transposable element DNA on each chromosome . However , in this simulation , the number of bins used to calculate the expected value per chromosome was determined not by the percentage of genomic DNA occupied by the chromosome , but rather by the total amount of transposable element DNA located on the chromosome . For example , 7 . 93% of the total human transposable element DNA is located on chromosome 1 . Therefore , we used 793 of the 10 , 000 bins to derive an expected number in each replicate rather than the 803 bins used above . P-values for each chromosome were calculated using the output of the Monte Carlo simulations . For each chromosome , we calculated the number of replicates where the number of RDs was greater than or equal to the number of RDs we discovered via our computational pipeline . This number was then divided by 10 , 000 ( the total number of replicates per simulation ) to derive the p-value .
|
The repair of DNA double-strand breaks ( DSBs ) is essential for the maintenance of genome integrity . The mechanisms by which DSBs are repaired have been the subject of intense experimental investigations . It has emerged that several imperfect repair pathways exist in eukaryotes that have the potential to result in chromosomal alterations , including genomic duplications . However , it remains unclear to what extent these imperfect repair events have contributed to shaping genomes throughout evolution . Here we introduce an innovative computational approach that takes advantage of the repetitive nature of eukaryotic genomes to identify repair-mediated duplications ( RD ) that occurred during evolution . We discovered over one thousand RDs in the human genome , with two-thirds resulting from the capture of a chromosomal DNA segment located in close proximity to the presumed site of the DSB , giving rise to local genomic duplications . Comparative genomic analyses reveal that the mechanism has operated continuously , but with decreasing intensity during primate evolution , generating species-specific duplications in all primates surveyed and generating genomic variation among humans . Finally , we show that RDs have also occurred in non-primate mammals and other vertebrates , indicating that this is a previously under-appreciated force shaping vertebrate genomes .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"evolutionary",
"biology/genomics",
"genetics",
"and",
"genomics/comparative",
"genomics",
"molecular",
"biology/dna",
"repair",
"evolutionary",
"biology/evolutionary",
"and",
"comparative",
"genetics"
] |
2009
|
Repair-Mediated Duplication by Capture of Proximal Chromosomal DNA Has Shaped Vertebrate Genome Evolution
|
Noroviruses ( NoV ) are the most common cause of non-bacterial acute gastroenteritis and cause local outbreaks of illness , especially in confined situations . Despite being identified four decades ago , the correlates of protection against norovirus gastroenteritis are still being elucidated . Recent studies have shown an association of protection with NoV-specific serum histo-blood group antigen-blocking antibody and with serum IgA in patients vaccinated with NoV VLPs . Here , we describe the isolation and characterization of human monoclonal IgG and IgA antibodies against a GI . I NoV , Norwalk virus ( NV ) . A higher proportion of the IgA antibodies blocked NV VLP binding to glycans than did IgG antibodies . We generated isotype-switched variants of IgG and IgA antibodies to study the effects of the constant domain on blocking and binding activities . The IgA form of antibodies appears to be more potent than the IgG form in blocking norovirus binding to histo-blood group antigens . These studies suggest a unique role for IgA antibodies in protection from NoV infections by blocking attachment to cell receptors .
Norwalk virus , the prototype of human noroviruses ( NoVs ) , was the first virus identified in 1972 as a causative agent for acute gastroenteritis [1] . NoVs are the leading cause of epidemic acute and sporadic cases of gastroenteritis responsible for about 19–21 million cases of infection leading to >70 , 000 hospitalizations and about 800 deaths annually in the U . S . [2] . NoVs recently surpassed rotaviruses as the leading cause of pediatric non-bacterial gastroenteritis after the introduction of vaccines against rotaviruses [3] . The infection is typically self-limiting , lasts for 1–3 days , and is characterized by diarrhea , vomiting , nausea , stomach pain and fever , with more severe complications and chronic disease in the immunocompromised . Therapy involves rest and rehydration , and no specific therapeutic agent is currently available . NoVs , members of the Caliciviridae family , are non-enveloped and contain a positive-sense , non-segmented single stranded RNA genome enclosed by a protein capsid . The genome codes for three open reading frames ( ORF ) , with the first ORF coding for six non-structural proteins involved in viral transcription and replication . The second and third ORFs encode virus protein 1 ( VP1 ) and VP2 , respectively . VP1 is a major capsid ~60 kDa protein and can self-assemble into virus-like particles ( VLP ) that resemble native virions both morphologically and antigenically [4] . The viruses are classified into at least six genogroups ( GI , GII , GIII , GIV , GV and GVI ) , based upon the sequence of VP1 [5] . The genogroups are further subdivided into genotypes , with GI and GII accounting for the most diversity with 9 and 22 genotypes , respectively . GI and GII NoVs are responsible for the majority of human infections , with the genotype GII . 4 responsible for most . Human susceptibility to NoVs depends on the expression of histo-blood group antigens ( HBGAs ) on the intestinal epithelial cells [6–8] . These blood group carbohydrates are thought to play a role as receptors or co-receptors based on recent studies of correlations between susceptibility , HBGA profile and secretor status ( expression of secretor enzyme α1 , 2 fucosyltransferase ) [2 , 9 , 10] . The correlates of protection in NoV infections are not completely understood . Almost all infected persons seroconvert , but epidemiological observations and clinical studies suggest that serum antibody measurable by traditional ELISA assays may not be long-lived or is otherwise insufficient to protect individuals from re-infection . Instead , the presence of anti-NoV Abs that block binding of virus to HBGA in vitro can protect from NoV gastroenteritis in the context of experimental challenge , suggesting a potential correlate [11 , 12] . We showed previously that a serum HBGA blocking antibody titer >200 [13] or a serum hemagglutination inhibition titer of >40 [14] is associated with protection of susceptible individuals from an experimental challenge . Deeper understanding of the immune response to human norovirus infection is hampered by the lack of a robust in vitro culture model and immunological reagents .
Persons previously challenged experimentally with norovirus Hu/NoV/GI . 1/Norwalk/68/US ( Norwalk virus [NV] ) were recruited to donate peripheral blood mononuclear cell ( PBMC ) samples for study . The protocol was reviewed and approved by the Baylor College of Medicine Institutional Review Board , and informed consent was obtained from the participants . We obtained PBMCs that were isolated from heparinized blood by density gradient centrifugation using Ficoll-Histopaque from donors 1–2 years following oral challenge with a GI . 1 NV inoculum [15] . The donors from whom the panel of antibodies were isolated had been challenged 26 or 12 months prior . Infection was demonstrated in the laboratory by detection of viral genome and antigen in fecal samples , by RT-qPCR and ELISA , respectively . In addition , the donors demonstrated a greater than four-fold rise in serum antibody levels by total antibody ELISA and by HBGA blocking activity . B cells were transformed by infection with Epstein Barr virus ( obtained from supernatant of cultured B95 . 8 cotton top tamarin lymphoblastoid line ) in the presence of 2 . 5 μg/mL TLR agonist CpG ( phosphorothioate-modified oligodeoxynucleotide ZOEZOEZZZZZOEEZOEZZZT , Life Technologies ) , 10 μM Chk2 inhibitor [Chk2i] ( Sigma ) , 10 μg/mL cyclosporine A ( Sigma ) and plated in 384-well culture plates . After 7 days of culture , cells from one 384-well culture plate were expanded into four 96-well culture plates containing CpG , Chk2i and irradiated heterologous human PBMCs to serve as feeder layers for the growth of lymphoblastoid cell line ( LCL ) clusters . After an additional 3 days of culture , the supernatants were screened for binding to NV GI . 1 VLP or disruption of the NV VLP–glycan interaction ( described below ) . Briefly , 5 μL of supernatant from each well of transformed B cell cultures ( in a total assay volume of 50 μL ) were added to the wells coated with 1 μg/mL NV VLP . The bound antibodies were detected using alkaline phosphatase conjugated goat anti-human Ig ( γ and αchain specific ) ( Southern Biotech ) . In blocking assays , 50 μL of diluted supernatant as described above were mixed with NV VLP and the complexes were added to H3-PAA ( Glycotech , Rockville , MD ) immobilized on neutravidin-coated plates , as described below . Supernatants from LCL cultures ( diluted 1:10 in assay buffer ) that had been selected for rotavirus-reactive antibody were used as negative controls . Cells from wells with desired activity were subjected to electrofusion with HMMA2 . 5 myeloma cells . The fused cells then were cultured in a selective medium containing 100 μM hypoxanthine , 0 . 4 μM aminopterin , 16 μM thymidine ( HAT Media Supplement , Sigma HO262 ) , and 7 μg/mL ouabain ( Sigma O3125 ) and incubated for 14–18 days before screening hybridomas for antibody production by ELISA . Cells from the positive wells were cloned biologically by sorting single cells into 384-well plates using a FACSAria III fluorescence-activated cell sorter ( Becton Dickinson ) , cultured for about 14 days and screened for antibody production . Total RNA was extracted from hybridoma cells and used for amplification of genes coding for the variable domains of the antibody clones . First-strand cDNA synthesis and RT-PCR were done with gene-specific primers as previously described ( S1 Table ) using the OneStep RT-PCR kit ( Qiagen ) , according to the manufacturer’s protocols . The thermal cycling parameters were as follows: 50°C for 30 min , 95°C for 15 min , 39 cycles of ( 94°C for 1 min , 55°C for 1 min and 72°C for 1 min ) followed by a final extension step for 10 min at 72°C . PCR products were purified using Agencourt AMPure XP magnetic beads ( Beckman Coulter ) and sequenced directly using an ABI3700 automated DNA sequencer without cloning . Heavy chain or light chain antibody variable region sequences were analyzed using the IMGT/V-Quest program [16 , 17] . The analysis involved the identification of germline genes that were used for antibody production , location of complementary determining regions ( CDRs ) and framework regions ( FRs ) as well as the number and location of somatic mutations that occurred during affinity maturation . For expression of recombinant forms of the antibody clones , the nucleotide sequences of variable domains were optimized for mammalian expression and synthesized ( Genscript ) . The heavy chain fragments were cloned as EcoRI/HindIII fragments into pML-huCG1 or pML-huCA1 vectors for expression of γ1 or α1 chains , respectively [18] . The light chains were cloned as BglII/NotI fragments into pML-huCk or pML-huCL vectors for κ or λ chains , respectively . For expression of antibodies from hybridoma clones , cells were cultured in serum-free medium , Hybridoma SFM ( Life Technologies ) , for 21 days . Recombinant antibodies were expressed transiently in Expi293 F cells ( Life Technologies ) , according to the manufacturer’s recommendation . Equal amounts of heavy and light chain DNA were used for transfections to generate recombinant IgG or monomeric IgA antibodies . For recombinant dimeric IgA , plasmids encoding cDNAs for the heavy chain , light chain and J chain DNA were mixed at 1:1:2 ratio as described [19] . Transfection was done using ExpiFectamine 293 transfection reagent ( Life Technologies ) according to the manufacturer’s protocols . After 7 days of culture , the supernatants were clarified by centrifugation and filtered using 0 . 4-μm pore size filter devices . Antibodies were harvested from the supernatants by affinity chromatography on HiTrap KappaSelect or LambdaSelect columns ( Life Technologies ) as previously described [19] . Antibodies eluted from affinity columns were concentrated using Amicon centrifugal filters ( Millipore ) . Purified antibodies were resolved on polyacrylamide gels under reducing or non-reducing denaturing conditions and stained with Coomassie Blue reagent . We obtained polyclonal rabbit serum raised against NoV VLPs as a positive control for detection of VLPs coated on ELISA plates . This immune sera were generated by hyperimmunization of rabbits with NV VLPs as previously described [20] . We also prepared purified immunoglobulin from murine hybridoma cells secreting the mAbs 8812 or 3901 . MAbs 8812 and 3901 were included in some receptor experiments as positive and negative controls for inhibition of NV VLP binding to receptor , based on previously determined activities [8] . We also used these murine mAbs as controls for immunoblotting experiments to determine if mAbs bound to linear epitopes , since mAb 3901 , but not mAb 8812 , has been described previously to bind linear epitopes [21] . In immunoblots , mAb 3901 binds denatured VP1 but mAb 8812 does not . VLPs representing different norovirus genogroups ( GI and GII ) and genotypes ( GI . 1 , NC_001959; GI . 2 , FJ515294; GI . 4 , GQ413970; GI . 6 , KC998959; GI . 7 , JN005886; GI . 8 , GU299761; GII . 4; EU310927 ) were generated and purified as previously described [22] . Briefly , capsid proteins ( VP1 and VP2 ) were expressed in SF9 insect cells ( 2 . 75x10^6 cells/mL of Grace’s insect cell media ) from recombinant baculovirus expression vectors , and NoV VLPs were purified from culture supernatants on a cesium chloride gradient [20] . Structural integrity and purity of the VLP preparations were confirmed by electron microscopy of negatively stained VLPs ( 1 . 0% ammonium molybdenate ( Sigma-Aldrich; St . Louis , MO ) , pH 6 . 0 ) on carbon coated grids and by Western blot , respectively . We also generated a GI . 1 VLP ( designated CT303 ) in which the P domain was deleted by mutagenesis of the VP1 gene construct [23] . We prepared a second mutated GI . 1 VLP with the point mutation W375A that we previously determined ablates HBGA binding [24] . Binding characterization of purified antibodies to NoV VLPs was carried out by ELISA . NoV VLPs were suspended in PBS at 1 μg/mL and coated in microwell plates ( Nunc ) for 16 h at 4°C , and the wells were blocked with 5% skim milk and 2% goat serum in PBS-Tween . Purified antibodies were diluted serially in PBS and added to the ELISA plates . The bound antibodies were detected using alkaline phosphatase conjugated goat anti-human κ or λ chain antibodies ( Southern Biotech ) . To compare binding between different classes of antibodies , the concentrations of antibodies were adjusted to normalize for the binding sites ( Fab = 1; IgG = 2; mIgA = 2 or dIgA = 4 ) before use in ELISA . The genotype specificity of antibody binding was determined by direct ELISA , as described above , with the following modifications: VLPs were coated at 10 μg/mL and antibodies were used at a concentration of 20 μg/mL . Plates were developed using ultra-TMB reagent ( Pierce ThermoFisher; Rockford , IL ) , following the manufacturer’s protocol , and optical density as read at 450 nm using a SpectraMax M5 plate reader . We prepared purified recombinant P domain dimeric protein , as previously described [24] . Briefly , a NV P domain construct was expressed in E . coli ( Novagen ) and purified by affinity chromatography , followed by size exclusion chromatography . We tested binding of each of the mAbs to P domain dimer by direct antigen ELISA , using the same protocol as described above for the VLP binding assay . The nature of the epitopes bound by the human mAbs was determined by SDS-PAGE analysis and Western blot . NV VLPs were diluted in 5X Laemmli sample buffer and prepared for SDS-PAGE in one of the two following ways . Samples were either boiled at 100°C for 10 minutes or incubated at room temperature for 10 minutes prior to loading on separate pre-cast 14–20% polyacrylamide gels ( Criterion TGX gel , BioRad; Hercules , CA ) for electrophoresis . Electrophoresed proteins were transferred to nitrocellulose membrane for Western blot analysis . Human mAbs were diluted to 1 μg/mL in blocking solution ( 1% wt:vol , Kroger non-fat dried milk in 1X phosphate buffered saline ) . Two NV-reactive murine monoclonal antibodies ( mAb 3901 and mAb 8812 ) and a Norwalk-reactive rabbit polyclonal were used as positive controls for detection of VP1 . Blots were incubated overnight at 4°C . Bound antibodies were detected using either an anti-human Ig ( A , G , M ) -HRP , anti-mouse-HRP , or anti-rabbit-HRP conjugate antibody ( Southern Biotech; Birmingham , AL ) . Blots were developed by chemiluminescence using West Pico HRP substrate ( Pierce ThermoFisher; Rockford , IL ) following the manufacturer’s instructions . Disruption of interaction between VLP and HBGAs was used as a surrogate assay for measuring NoV neutralization by human monoclonal antibodies . Pre-existing titer of HBGA blocking antibodies is correlated with protection from NoV gastroenteritis [11 , 13] . An HBGA blocking assay was carried out as previously described [11] . Briefly , biotin-polyacryamide ( PAA ) -blood group antigen conjugates ( Glycotech , Rockville , MD ) were immobilized on neutravidin-coated plates ( Thermo Scientific ) . VLPs were mixed with serial dilutions of antibodies , and the complexes were added to the glycan-coated microtiter plates . The relative amount of VLP bound to HBGAs was determined using rabbit anti-NoV antiserum followed by horseradish peroxidase-conjugated goat anti-rabbit ( Southern Biotech ) . We tested mAbs for inhibition of binding of NoV VLPs to additional biotin-PAA-HBGA ligands , including H type 1 ( H1-PAA-biotin ) , H type 2 ( H2-PAA-biotin ) , H type 3 ( H3-PAA-biotin ) , A trisaccharide ( tri-A-PAA-biotin ) , and Lewis ( y ) ( Le ( y ) -PAA-biotin ) ( Glycotech , Rockville , MD ) . Plates were developed using ultra-TMB reagent ( Pierce ThermoFisher; Rockford , IL ) , following the manufacturer’s protocol , and optical density as read at 450 nm using a SpectraMax M5 plate reader . Hemagglutination inhibition assays were performed as described previously [14] . In brief , Human type O erythrocytes were collected from a healthy adult in Alsever’s buffer , washed twice in Dulbecco’s phosphate-buffered saline ( PBS ) without Ca2+ or Mg2+ , and pelleted by centrifugation at 500xg for 10 min at 4°C . Monoclonal antibodies ( mAb; starting concentration 60 μg/mL for human mAb and 8 . 5 μg/mL for murine 8812 ) were diluted initially 1:10 in PBS with 0 . 85% saline ( pH 5 . 5 ) , and then serially 2-fold diluted . Four hemagglutination units ( ~2 ng ) of Norwalk virus VLPs were mixed with the diluted monoclonal antibodies and incubated at room temperature for 30 min . The VLP-mAb mixture was added to an equal volume of 0 . 5% washed type O erythrocytes in 0 . 85% saline ( pH 6 . 2 ) and incubated for 2 h at 4°C . The HAI titer was determined by identifying the reciprocal of the highest dilution of mAb that inhibited hemagglutination by the VLPs . Competition-binding ELISAs were carried out to determine whether the hmAbs we generated bound distinct or shared epitopes in the NV capsid protein . Briefly , each mAb was used to coat a 96-well microtiter plate ( Greiner Bio-One; Monroe , NC ) at a concentration of 2 μg/mL in carbonate coating buffer at 4°C overnight . Norwalk VLPs ( 100 ng/mL ) were incubated with serial dilutions of each hMAb , ranging from 6 . 25 μg/mL to 250 μg/mL in assay buffer [1% non-fat dried milk ( NFDM ) in 1X PBS , w/v] , for 2 hours at 37°C . Each plate included an antigen-only control to which no mAb had been added . The assay plate was washed three times with PBS containing 0 . 05% Tween 20 ( PBS-T ) and blocked for 1 hour at 37°C with 5% NFDM in PBS . The pre-incubated VLP/mAb preparations were added to the mAb-coated microtiter plate and plates were incubated for 2 hours at 37°C . Bound VLPs were detected using a rabbit anti-NV polyclonal antibody ( 1/10 , 000 in assay buffer; 2 hours at 37°C ) followed by a commercial goat anti-rabbit-HRP conjugate antibody ( Southern Biotech; 1/7500 in assay buffer; 45 minutes at 37°C ) . Plates were developed using ultra-TMB reagent ( Pierce ThermoFisher; Rockford , IL ) , following the manufacturer’s protocol , and optical density as read at 450 nm using a SpectraMax M5 plate reader . Readings from duplicate wells were averaged . The percent competition for each competitor hMAb was calculated relative to the antigen-only control . MAbs were judged to compete for binding to the same site if maximum binding of the competing mAb was reduced to <25% of its un-competed binding . A level of 25–50% of its un-competed binding was considered intermediate competition .
Currently there is not a robust method for growing NoVs , but studies suggest that blocking the interaction of VLP with glycan moieties can be used as a surrogate for neutralization activity [11 , 25] . We sought to isolate blocking mAbs to the NoV capsid protein from volunteers challenged with NV . PBMCs isolated from two NV-immune donors were transformed with EBV , and the LCL supernatants were screened for binding to NV VLPs and separately for blocking of binding to H3-PAA glycan . The transformed B cells from cell line supernatants exhibiting IgG or IgA binding to VLPs or blocking of VLPs to the glycan , or exhibiting both activities , were expanded . The supernatants from expanded LCLs then were assayed again for binding to VLPs , and bound antibodies were detected using either polyclonal anti-IgG ( γ-specific ) or anti-IgA ( α-specific ) secondary antibodies to determine the isotype of the binding antibodies . We used polyclonal secondary antibodies , instead of monoclonal antibodies , to minimize any differences in sensitivity of the secondary antibody to gamma or alpha chains and confirmed that the affinities of secondary antibodies did not differ measurably ( S1 Fig ) . About 100 wells of the 384 wells tested were positive for NV binding . Of all the binding antibodies , a higher proportion of lines contained NV-specific antibodies that were IgG than IgA . However , the proportion of NV-binding antibodies that also exhibited blocking activity was higher for IgA antibodies than for IgG , suggesting that mAbs of the IgA isotype are highly over-represented in the repertoire of antibodies that block receptor binding ( Fig 1 ) . The cells in the positive wells were fused with a myeloma partner to generate a hybridoma clone . We were able to obtain a panel of seven IgG ( 1A8 , 2L8 , 3I23 , 4E7 , 4I23 from Donor 1 and NV1 , NV48 from Donor 2 ) and seven IgA ( 2J3 , 3I3 , 4B19 , 4C10 , 5I2 from Donor 1 and NV41 , NV56 from Donor 2 ) clones . The proper molecular assembly of IgG and dimeric IgA was confirmed by resolving antibodies on SDS-PAGE gels and staining with Coomassie Blue reagent ( S2 Fig ) . Interpretation of the curves for Ig binding to VLPs was conducted after normalizing for the differing molarity of binding sites of IgG and dimeric IgA . IgA antibodies as a class appeared to have a lower affinity for binding in the VLP binding assays when compared with IgG . Interestingly , however , this class distinction was not apparent in the assays to detect antibody mediated blocking of VLP binding to glycan . These data suggest that even lower affinity IgA antibodies can mediate potent blocking activity ( Fig 2 ) . We constructed average binding and blocking curves for IgG and IgA sets of antibodies using R software package and generated representative binding and blocking curves for IgG and IgA ( S3 Fig ) . The difference between binding of average IgG and average IgA was significant ( p < 0 . 001 ) , while the blocking was not significant ( p = 0 . 39 ) . We more fully characterized the antibodies obtained from Donor 1 in the experiments that follow . The genotype specificity of mAb binding was assessed by direct antigen ELISA . VLPs representing different human NoV genotypes were coated on an ELISA plate . Each of the mAbs isolated bound Norwalk VLPs ( GI . 1 ) and none of the mAbs detected the other GI or GII NoV genotypes tested ( Fig 3 , panel A ) . Direct antigen ELISA was performed for domain mapping of the human mAbs . All 10 hmAbs bound to wild-type NV VLPs , mediated by binding to the major capsid protein VP1 ( Fig 3 , panel B ) . The VP1 protein has two major domains , the highly conserved shell domain and the highly variable protruding ( P ) domain . Each of the 10 mAbs bound to recombinant P domain preparations , suggesting that their binding epitopes are contained within the P domain . Further support for this conclusion was provided by loss of mAb binding to VLPs assembled from a mutated VP1 ( designated CT303 ) in which the P domain had been deleted [23 , 26] . We also tested NV VLPs with ablated HBGA binding through introduction of a point mutation ( W375A ) in the HBGA binding domain . Two of the mAbs failed to bind W375A VLPs , suggesting that the residue at this position influences VP1 recognition by mAbs 3I23 IgG and 4I23 IgG ( Fig 3 , panel B ) . We tested the specificity of three representative antibodies ( 2L8 IgG , 3I23 IgG and 5I2 IgA ) to block VLP binding to diverse HBGA ligands , including H types 1 , 2 , 3 and Le ( y ) . In every case the mAbs exhibited a strong inhibitory effect , except for 2L8 IgG , which had reduced activity to block binding to H type 3 tri-A and Le ( y ) ( Fig 3 , panel C ) . To characterize the epitopes recognized by mAbs derived from Donor 1 , we tested their ability to bind the NV major capsid protein VP1 by western blot ( Fig 4 , panels A and B ) . Murine mAbs 3901 or 8812 have been described previously to bind to linear or nonlinear epitopes , respectively , and were used as controls in this experiment [21] . Each of the 10 human mAbs and the murine mAb 8812 bound to unboiled preparations of NV VLPs , suggesting that the human mAbs recognize nonlinear epitopes in the major capsid protein VP1 ( panel A ) . None of the human mAbs bound to denatured VP1 ( panel B ) . Consistent with this finding , murine mAb 3901 , but not murine mAb 8812 , bound to denatured VP1 . Epitope binning was carried out by competition-binding ELISA . MAbs were assessed in a pairwise manner for their ability to inhibit binding of each other to NoV VLPs by ELISA ( Fig 4 , panel C ) . The observed patterns of competition-binding suggest that most of the mAbs bind to one major antigenic site . However , a few mAbs ( 2L8 IgG and 3I23 IgG ) failed to inhibit capture of NV VLPs by other mAbs ( 4B19 IgA , 4C10 IgA , 4I23 IgG , 5I2 IgA ) . These observations suggest that members of the panel of mAbs bind to at least three distinct , but likely overlapping , epitopes on VP1 . Although IgA mAbs as a group appeared more potent in receptor blocking , that comparison is complicated by the fact that the IgA or IgG antibodies compared above with respect to blocking activity do not share the same variable regions . To determine if the variable domains of these antibodies contribute to the differences in activity , we analyzed the variable heavy and light chain genes of the antibodies , but did not find any unusual features in any of the antibody class in terms of gene families , mutation rate or CDR3 lengths ( S2 Table ) . To study the effects of antibody isotype on functional activity in a more defined manner , we prepared IgG or IgA versions of representative blocking antibodies using mammalian cell recombinant expression of isotype-switch variant Ig molecules . We synthesized cDNAs coding for the variable domains after optimizing the sequence of the genes computationally for expression in mammalian cells . The heavy chain antibody variable genes were cloned in expression vectors for expression as γ or α chain . The light chain antibody variable genes were cloned in expression vectors for expression as κ or λ chains . Recombinant polymeric IgA was obtained by co-expression of joining ( J ) chain along with the heavy and light chains . Electrophoresis of purified proteins on SDS-PAGE gels under non-reducing conditions confirmed the correct assembly of IgG and dimeric IgA ( S4 Fig ) . After normalizing for molarity of binding sites ( IgG = 2 , mIgA = 2 , and dIgA = 4 ) , each set of antibodies was tested in the binding and blocking assays . We calculated half-maximal effective concentrations ( EC50 ) at which binding or blocking occurred . To enable comparison between the molecular forms of each antibody , we calculated the ratio of blocking EC50 to binding EC50 for each antibody . A lower ratio of blocking to binding indicated that smaller amounts of antibodies bound to VLP were needed for blocking the VLP binding to their receptor . In the antibodies we tested , mIgA and dIgA exhibited lower blocking-to-binding ratios than IgG ( Table 1 and S5 Fig ) . Interestingly , the ratio was lower for mIgA than for IgG , despite these Igs having a similar molecular weight ( 150 kDa vs . 170 kDa ) . The activity of IgG versus IgA forms of the antibodies showed a similar trend in hemagglutination inhibition assays ( S3 Table ) . This observation suggested that the higher potency of the IgA class of antibodies for blocking stems not only from their potential to make large polymeric Ig molecules with large capacity for steric hindrance following binding , but also from structural or functional features that are found even in the monomeric form of Ig molecules of that isotype .
The molecular basis of antibody-mediated inhibition of human NoV infection is poorly understood . It has been difficult to study NoV neutralization because of the lack of a robust cell culture system for growing virus . Recent studies suggest , however , that the presence of antibodies that block NoV-HBGA interactions is associated with protection against illness [13 , 20 , 24] . In this model , antibodies that disrupt the interaction of NoV VLPs with HBGA ligands thus act as putative virus neutralizing antibodies . The structural and functional features of these putative neutralizing antibodies are not known . Blocking activity of purified , serum-derived IgA antibodies was recently described , and our group recently identified serum IgA and salivary IgA antibodies as novel correlates of protection from NoV gastroenteritis [12 , 27 , 28] . In the studies presented here , we isolated a panel of hmAbs with potent NoV-HBGA blocking activity , representing IgA and IgG isotypes , from an immune individual following experimental virus challenge . The features of these antibodies reveal new aspects of antibody-mediated NoV inhibition . The most interesting finding from these detailed studies is that naturally-occurring NoV-specific human antibodies of the IgA isotype exhibit enhanced potency for receptor blocking , compared to IgG antibodies isolated in a similar fashion . These data suggest that this enhanced potency stems from two principal factors . First , there appears to be some intrinsic structural or functional features of the IgA isotype that confer enhanced blocking activity , even in monomeric forms of IgA antibodies , compared to a matched IgG variant . It is known that IgG and IgA molecules differ in certain functional aspects , due to sequence polymorphisms in the constant domain[29 , 30] . In fact , previous studies with antibodies to other microbial agents have suggested that polymorphisms in the constant regions even of differing IgG subclasses can mediate a profound phenotypic change in the pattern binding of antibodies [31] . We did not determine the molecular basis for this effect against NV virus , but the enhancement is of interest as it has relevance to both antibody and vaccine design efforts . Second , we found that dimeric IgAs exhibited enhanced potency for blocking compared to matched monomeric IgA or IgG counterparts . Most likely , this finding is due to the large molecular weight of dimeric IgA , which probably facilitates a more profound receptor blocking capacity . It was interesting that many of the B cells we isolated from blood that encoded NoV-specific IgA secreted polymeric IgA in the naturally-occurring form . It has been noted previously that secreted IgA proteins in the serum typically are almost exclusively monomeric . However , we did not study serum antibodies here; rather we isolated NoV-specific IgA-encoding B cells from the blood , and many of these secreted dimeric IgA after recovery . It is possible that these cells are circulating in peripheral blood en route to mucosal tissues . The technique that we used predominantly isolates memory B cells , and we isolated these cells during the convalescent phase from the donor . Therefore , it is not anticipated that the cells would have been secreting dimeric IgA into the serum in the donor . We performed sequence analysis of the antibody variable genes encoding these mAbs . The data show that there is a wide diversity of antibody variable genes that encode antibodies that block receptor binding . This finding is encouraging , because it suggests that there is no genetic restriction on the ability of diverse humans to make receptor-blocking antibodies to NoV . We examined the genetic features of the antibodies to see if there were any unusual characteristics . Some especially important domains in viral surface proteins that are susceptible to recognition by potent virus-neutralizing antibodies , such as HIV envelope or influenza hemagglutinin , are associated with unusual genetic and structural features such as long heavy chain CDR3 regions or a very high level of somatic mutations [32–34] . We found that the NoV receptor-blocking antibodies did not possess any extreme genetic features . Diverse antibody variable genes were used , and the level of somatic mutation observed was typical of that found in human memory B cells [35 , 36] . The length of heavy chain CDR3 regions was average , and there was no unusual occurrence of insertions or deletions . Human NoVs cause acute gastroenteritis worldwide , and they exhibit a high degree of genetic variation in different geographical locations . Field strains of NoV evolve , and dominant novel strains emerge periodically that exhibit antigenic variation and differential glycan-binding specificities due to genetic changes that alter structure in the P domain of the NoV capsid protein [37 , 38] . HBGAs most likely function as co-receptors or cell attachment factors to NoVs , and thus they determine susceptibility to infection [10 , 37 , 39] . The structural basis for the interaction of the P domain of the NoV capsid protein with HBGAs is fairly well understood , but how particular sequence polymorphisms in this domain determine the effect on genogroup-specific biology is less well understood . We also do not understand how such sequence variations mediate binding or escape from human neutralizing antibodies . Further study of the mAbs that we isolated here should prove useful in this regard . These antibodies exhibited GI . 1 NoV specificity , consistent with the background of the virus that was used for the donor challenge and with the antigen used to screen for the NoV-specific antibodies . Structural studies of the interaction of antigen-antibody complexes with these mAbs could elucidate the critical residues in the P domain that contribute to antibody recognition in a genogroup-specific manner . Further studies also would allow us to understand the mechanism by which NoV-neutralizing antibodies block HBGA binding , whether it is by directly binding or altering the conformation of the HBGA binding site or by sterically hindering access to the HBGA binding site [40] . Such studies will shed light on additional factors that regulate protection from human NoV infection and disease .
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Human noroviruses ( HuNoV ) have become the major etiologic agent of epidemic and sporadic acute gastroenteritis . There are currently no licensed vaccines or drugs to prevent or treat NoV infection . HuNoV infects people of all ages and , even though infection is characteristically acute and self-limiting , infection can become life threatening in children , the elderly , and the immunocompromised . Human challenge studies have shown that HuNoV infection elicits a robust humoral immune response and that antibodies that block virus-like particles ( VLPs ) from binding to host attachment factors are a correlate of protection . Using high-efficiency hybridoma technology , we isolated binding and blocking human monoclonal IgA antibodies ( mAbs ) and additional human IgG mAbs specific to GI . 1 NoV . When comparing blocking efficiencies between both isotypes , we also found that human IgAs blocked GI . 1 NoV VLPs from binding to synthetic host attachment factors more effectively than did IgGs . To design a vaccine that elicits broad protective immunity , we must have a solid understanding of the NoV-mediated human antibody response to infection . This study provides valuable insight into the human humoral response to NoV infection .
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2016
|
Frequent Use of the IgA Isotype in Human B Cells Encoding Potent Norovirus-Specific Monoclonal Antibodies That Block HBGA Binding
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A deficiency in glucose-6-phosphatase-α ( G6Pase-α ) in glycogen storage disease type Ia ( GSD-Ia ) leads to impaired glucose homeostasis and metabolic manifestations including hepatomegaly caused by increased glycogen and neutral fat accumulation . A recent report showed that G6Pase-α deficiency causes impairment in autophagy , a recycling process important for cellular metabolism . However , the molecular mechanism underlying defective autophagy is unclear . Here we show that in mice , liver-specific knockout of G6Pase-α ( L-G6pc-/- ) leads to downregulation of sirtuin 1 ( SIRT1 ) signaling that activates autophagy via deacetylation of autophagy-related ( ATG ) proteins and forkhead box O ( FoxO ) family of transcriptional factors which transactivate autophagy genes . Consistently , defective autophagy in G6Pase-α-deficient liver is characterized by attenuated expressions of autophagy components , increased acetylation of ATG5 and ATG7 , decreased conjugation of ATG5 and ATG12 , and reduced autophagic flux . We further show that hepatic G6Pase-α deficiency results in activation of carbohydrate response element-binding protein , a lipogenic transcription factor , increased expression of peroxisome proliferator-activated receptor-γ ( PPAR-γ ) , a lipid regulator , and suppressed expression of PPAR-α , a master regulator of fatty acid β-oxidation , all contributing to hepatic steatosis and downregulation of SIRT1 expression . An adenovirus vector-mediated increase in hepatic SIRT1 expression corrects autophagy defects but does not rectify metabolic abnormalities associated with G6Pase-α deficiency . Importantly , a recombinant adeno-associated virus ( rAAV ) vector-mediated restoration of hepatic G6Pase-α expression corrects metabolic abnormalities , restores SIRT1-FoxO signaling , and normalizes defective autophagy . Taken together , these data show that hepatic G6Pase-α deficiency-mediated down-regulation of SIRT1 signaling underlies defective hepatic autophagy in GSD-Ia .
Glycogen storage disease type Ia ( GSD-Ia , MIM232200 ) is caused by a deficiency in glucose-6-phosphatase-α ( G6Pase-α or G6PC ) , an enzyme expressed primarily in liver , kidney , and intestine [1] . G6Pase-α catalyzes the hydrolysis of glucose-6-phosphate ( G6P ) to glucose and phosphate in the terminal step of glycogenolysis and gluconeogenesis and is a key enzyme for endogenous production of blood glucose [1] . GSD-Ia patients manifest impaired glucose homeostasis characterized by fasting hypoglycemia , hepatomegaly , hypercholesterolemia , hypertriglyceridemia , hyperuricemia , lactic acidemia , and growth retardation [1] . Hepatomegaly is caused by excessive glycogen and neutral fat accumulation [1] . Strict compliance with dietary therapies has enabled GSD-Ia patients to attain near normal growth and pubertal development [1] . However , long-term complications , including hepatocellular adenoma ( HCA ) still occur in metabolically compensated GSD-Ia patients [1] . We have previously generated a global G6pc-/- mouse line that mimics the phenotype of human GSD-Ia . However , even under intensive glucose therapy , the G6pc-/- mice rarely survive to weaning , making the follow-up study of metabolic aberrations difficult [2] . On the other hand , the liver-specific G6pc-knockout ( L-G6pc-/- ) mice survive to adulthood and develop HCA [3] , offering a suitable model to study the long-term manifestations of hepatic G6Pase-α deficiency . Macroautophagy ( or autophagy ) is a recycling mechanism that produces energy and building blocks through lysosomal degradation of intracellular proteins and organelles in times of nutrient deprivation and environmental stresses [4] . Autophagy is involved in the breakdown of lipid droplets via a selective form of autophagy called lipophagy [5] . Autophagy also functions as a cellular quality-control system by eliminating protein aggregates and defective organelles [6] . Since the liver plays essential roles in energy homeostasis , hepatic autophagy deficiency has been linked to many metabolic disorders including diabetes , obesity , non-alcoholic fatty liver disease and hepatocarcinogenesis [5] . Several energy sensing pathways , including mammalian target of rapamycin ( mTOR ) , AMP-activated protein kinase ( AMPK ) , and sirtuin 1 ( SIRT1 ) regulate autophagy pathway [7] . Autophagy occurs stepwise from initiation , vesicle nucleation , vesicle elongation , and to final fusion of the autophagosome with a lysosome for component degradation [8] . Autophagy initiation is mediated by signaling via the Unc-51-like kinase 1 ( ULK1 ) complex [8] . Under nutrient-rich conditions , mTOR plays a central role as a negative regulator of autophagy via inhibitory phosphorylation of ULK1 [9] . In contrast , AMPK , an energy sensor promotes autophagy by activating phosphorylation of ULK1 or inhibiting the mTOR pathway [7] . Autophagy can also be regulated by SIRT1 , a deacetylase that is activated by increased expression as well as by increased cellular NAD+ levels in response to nutrient starvation [7] . Studies have shown that SIRT1 regulates autophagy directly via deacetylation of autophagy-related ( ATG ) proteins and indirectly via deacetylation and activation of forkhead box O ( FoxO ) members which transactivate autophagy genes [10] . Using G6pc-deficient cell lines and young G6pc-/- mice , Farah et al . [11] have recently shown that G6Pase-α deficiency leads to autophagy impairment and suggested that mTOR signaling may play a role in autophagy deficiency seen in GSD-Ia . However , the mechanism underlying autophagy deficiency in GSD-Ia remains unclear . Using adult L-G6pc-/- mice , we now show that the G6Pase-α-deficient liver displays impaired autophagy characterized by attenuated expression of autophagy components , impaired autophagosome formation , and reduced autophagy flux . We further show that the expression of SIRT1 and FoxO3a is reduced in G6Pase-α-deficient livers . Interestingly , we show that hepatic G6Pase-α deficiency leads to activation of carbohydrate response element-binding protein ( ChREBP ) signaling , increase in peroxisome proliferator-activated receptor-γ ( PPAR-γ ) expression , and suppression in PPAR-α expression that all contribute to hepatic steatosis and downregulation of SIRT1 expression . Importantly , hepatic SIRT1 overexpression restores the expression of autophagy components and normalizes autophagic flux in G6Pase-α-deficient livers , while inhibition of mTOR signaling by rapamycin fails to correct defective hepatic autophagy . Thus , our results indicate that downregulation of SIRT1 signaling underlie autophagy deficiency in GSD-Ia . Finally , we show that restoration of hepatic G6Pase-α expression corrects metabolic abnormalities , restores SIRT1-FoxO signaling and normalizes defective autophagy .
The young global G6pc-/- mice display signs of hepatic autophagy deficiency [11] but the mice die young , making studies of long-term consequences of autophagy deficiency difficult . To delineate the mechanism underlying autophagy deficiency in GSD-Ia , we generated L-G6pc-/- mice which survived to adulthood as previously described [3] . The mice were genotyped ( S1A Fig ) and liver-specific deletion of the G6pc gene was confirmed by Western blot analysis ( S1B Fig ) . Studies have shown that autophagy-deficient livers frequently harbor morphologically abnormal and defective mitochondria [12 , 13] . Consistently , we detected many swollen and deformed mitochondria in the livers of L-G6pc-/- mice ( Fig 1A ) , suggesting impaired autophagy . Autophagy occurs stepwise from initiation , vesicle nucleation , vesicle elongation , to fusion of the autophagosome-lysosome for component degradation [8] . In the livers of L-G6pc-/- mice , impaired autophagy was evidenced by decreased expression of several components of the autophagy pathway , including initiation ( ATG101 ) , vesicle nucleation ( ATG14 ) , elongation ( LC3B or microtubule-associated protein 1 light chain 3B , and ATG3 ) , and mitophagy ( BNIP3 or BCL2/adenovirus E1B 19 kDa protein-interacting protein 3 ) ( Fig 1B and 1C ) . A key step in vesicle nucleation of autophagy is complex formation of Beclin-1 with Vps34 ( class III phosphatidylinositol 3-kinase ) and ATG14 . Interestingly , the decrease in Beclin-1 protein in the livers of L-G6pc-/- mice ( Fig 1C ) was not accompanied with a corresponding decrease in Beclin1 transcripts ( Fig 1B ) . Studies have shown that reduced expression of complex components can de-stabilize Beclin-1 [14] , raising the possibility that reduced expression of ATG14 might lead to increased Beclin-1 protein turnover in the livers of L-G6pc-/- mice . During vesicle elongation of autophagy , the non-lipidated form of LC3-I is converted to phosphatidylethanolamine-conjugated LC3-II , a marker of autophagosome formation [8] . Compared to control livers , both levels of LC3B isoform , LC3B-I and LC3B-II , were reduced in the livers of L-G6pc-/- mice ( Fig 1C ) , consistent with impaired autophagosome formation . We further showed that levels of p62 , a selective substrate for autophagy [4] were markedly increased in the livers of L-G6pc-/- mice compared to the controls ( Fig 1C ) . Furthermore , compared to the controls , the hepatocytes isolated from the livers of L-G6pc-/- mice harbored reduced numbers of autophagic vacuoles as shown by reduced staining for cyto-ID , a specific dye for autophagosomes and autophagolysosomes [15] ( Fig 1D ) . To confirm that our observations for impaired hepatic autophagy in L-G6pc-/- mice resulted from reduced autophagosome formation but not from increased lysosomal clearance of autophagosome , we examined autophagic flux in-vivo by examining hepatic LC3B-II levels in control and L-G6pc-/- mice treated with either saline or leupeptin , a lysosomal inhibitor . Our results showed that autophagic flux was significantly attenuated in the livers of L-G6pc-/- mice , compared to control livers ( Fig 1E ) . The impaired autophagy in the livers of L-G6pc-/- mice was characterized by decreased expression of many autophagy components ( Fig 1B and 1C ) . Since the FoxO factors stimulate the transcription of many Atg genes , and SIRT1 can deacetylase and activate the transcriptional activity of FoxO factors [8 , 10] , we examined the SIRT1-FoxO signaling pathway . In the livers of L-G6pc-/- mice , levels of mRNA and protein of SIRT1 and FoxO3a were decreased , compared to controls ( Fig 2A ) . The transcription of SIRT1 , a NAD+-dependent deacetylase can be stimulated by PPAR-α , and down-regulated by PPAR-γ and ChREBP [16] . Hepatic NAD+ levels , an essential cofactor of SIRT1 were similar between control and L-G6pc-/- mice ( Fig 2B ) . However , compared to controls , levels of PPAR-γ were higher in the livers of L-G6pc-/- mice whereas those of PPAR-α were lower ( Fig 2C ) . Moreover , the livers of L-G6pc-/- mice exhibited activated ChREBP signaling , demonstrated by increased nuclear-translocated ChREBP protein ( Fig 2D and S2 Fig ) and increased expression of ChREBP target lipogenic genes including acetyl-Co A carboxylase-α ( Acaca ) , fatty acid synthase ( Fasn ) , and elongation of very long chain fatty acids protein 6 ( Elovl6 ) [17] ( Fig 2E ) . These results are in good agreement with the reduced expression of SIRT1 in the livers of L-G6pc-/- mice . Taken together , these results suggest that the changes of factors that lead to hepatic steatosis contribute to down-regulation of hepatic SIRT1 in L-G6pc-/- mice . Consistent with the attenuated expression of SIRT1 , the ratios of acetylated FoxO3a ( inactive form ) to total FoxO3a in nuclear extracts of the livers of L-G6pc-/- mice were higher than those of control livers ( Fig 2F ) , demonstrating that the relative levels of active FoxO3a were reduced in the livers of L-G6pc-/- mice . Studies have shown that acetylation of ATG proteins inhibits the elongation process of autophagosome while SIRT1-mediated deacetylation of ATG proteins positively regulates autophagy [18] . We therefore examined acetylated levels of ATG proteins involved in autophagic vesicle elongation process . During autophagic vesicle elongation , ATG12 is covalently conjugated to ATG5 with the help of ATG7 and ATG10 [8] . The ATG12-ATG5 conjugate interacts with ATG16-like 1 ( ATG16L1 ) and the resulting ATG12-ATG5-ATG16L1 complex promotes another conjugation reaction involved in the conversion from LC3-I to LC3-II , a critical step in autophagosome formation [8] . Consistent with the attenuated expression of SIRT1 deacetylase , the acetylated forms of ATG5 and ATG7 were increased in the livers of L-G6pc-/- mice , compared to controls ( Fig 3A ) . While hepatic levels of mRNA for ATG5 and ATG12 were similar between control and L-G6pc-/- mice ( Fig 3B ) , hepatic levels of the ATG12-ATG5 conjugate were markedly decreased in the L-G6pc-/- mice , compared to controls ( Fig 3C ) , suggesting interference in autophagic vesicle elongation . In summary , the reduced expression of hepatic SIRT1 in L-G6pc-/- mice resulted in increased levels of acetylated ATG proteins and decreased levels of the ATG12-ATG5 conjugation that inhibit the elongation of autophagic vesicle . To demonstrate that down-regulation of SIRT1 signaling plays a major role in hepatic autophagy impairment in L-G6pc-/- mice , we examined the effect of adenovirus ( Ad ) -mediated SIRT1 overexpression on autophagy pathway along with Ad-GFP as a control vector . An increase in hepatic SIRT1 expression in L-G6pc-/- mice normalized hepatic levels of LC3B-II , ATG101 , ATG3 , and FoxO3a although the increase in ATG14 was not statistically significant ( Fig 4A ) . Since the autophagy pathway can be regulated by mTOR signaling [7] , we also examined the expression of mTOR and our results showed that hepatic levels of mTOR were unchanged in mice overexpressing SIRT1 ( Fig 4A ) . Importantly , hepatic accumulation of p62 , indicative of defective autophagy was completely normalized in Ad-SIRT1-treated L-G6pc-/- mice ( Fig 4A ) . Furthermore , an increase in SIRT1 expression efficaciously restored the attenuated autophagic flux in the livers of L-G6pc-/- mice ( Fig 4B ) . However , SIRT1 overexpression failed to normalize metabolic alterations associated with GSD-Ia including accumulation of hepatic G6P , lactate , and triglyceride in L-G6pc-/- mice ( Fig 4C ) . Taken together , down-regulation of SIRT1 signaling underlies the defective hepatic autophagy in L-G6pc-/- mice . Farah et al . [11] have recently suggested that activation of mTOR signaling plays a role in autophagy deficiency seen in GSD-Ia . We therefore examined mTOR signaling in the livers of L-G6pc-/- mice . Studies have shown that phosphorylated level of mTOR represents its activation status [19–21] . However , hepatic levels of the activated p-mTOR-S2448 and p-mTOR-S2481 were similar between control and L-G6pc-/- mice ( Fig 5A ) . mTOR pathway can regulate autophagy via phosphorylation and nuclear exclusion of transcriptional factor EB ( TFEB ) , a transcriptional factor for lysosomal and autophagy gene expression [22 , 23] . However , consistent with similar levels of activated mTOR , hepatic levels of nuclear-localized TFEB were also similar between control and L-G6pc-/- mice ( Fig 5B ) . Notably , the treatment of rapamycin , a mTOR inhibitor markedly reduced hepatic p-mTOR levels in L-G6pc-/- mice but failed to normalize hepatic levels of ATG101 , ATG14 and ATG3 , although levels of LC3B-II were slightly increased ( Fig 5C ) . The minimal role of mTOR in autophagy deficiency was further supported by similar hepatic levels of p62 between untreated and rapamycin-treated L-G6pc-/- mice ( Fig 5C ) . Finally , we showed that the attenuated hepatic autophagic flux in L-G6pc-/- mice was only marginally restored by rapamycin ( Fig 5D ) . Taken together , these results support that mTOR plays a minimal role in hepatic autophagy impairment in L-G6pc-/- mice . SIRT1 overexpression corrected impaired hepatic autophagy but failed to normalize metabolic manifestations associated with GSD-Ia , suggesting that hepatic G6Pase-α plays additional roles in maintaining liver homeostasis . We therefore treated L-G6pc-/- mice at 4 weeks post G6pc gene deletion ( WP ) with rAAV-G6PC [24] and examined phenotypic correction of the treated mice at 12 WP . Hepatic G6Pase-α activity in control , L-G6pc-/- , and rAAV-treated L-G6pc-/- mice averaged 174 . 1 ± 21 . 8 , 2 . 0 ± 0 . 21 , and 68 . 9 ± 12 . 8 nmol/min/mg , respectively ( Fig 6A ) . We showed that 40% restoration of hepatic G6Pase-α activity was sufficient to normalize liver weights ( Fig 6B ) as well as hepatic levels of triglyceride , glucose and lactate in the rAAV-treated L-G6pc-/- mice , although hepatic levels of glycogen and G6P remained elevated ( Fig 6C ) . Moreover , the rAAV-treated L-G6pc-/- mice displayed normal profile of fasting blood glucose ( Fig 6D ) . Importantly , restoration of hepatic G6Pase-α expression completely normalized hepatic levels of SIRT1 and FoxO3a along with normal levels of hepatic LC3B-I , LC3B-II and p62 ( Fig 6E ) . Finally , rAAV-G6PC treatment normalized hepatic levels of nuclear-translocated ChREBP protein and liver histology in the L-G6pc-/- mice ( Fig 6F ) . Collectively , hepatic G6Pase-α restoration not only normalizes metabolic abnormalities associated with GSD-Ia but also corrects impaired SIRT1-FoxO signaling and defective autophagy in the livers of L-G6pc-/- mice . These results demonstrate that hepatic G6Pase-α plays a critical role in autophagy pathway as well as hepatic metabolisms associated with glucose homeostasis .
GSD-Ia is a juvenile lethal disease with no curative therapy . Dietary therapies have enabled patients to attain near normal growth and pubertal development but chronic complications remain . Hepatic autophagy deficiency has been linked to many metabolic disorders , including non-alcoholic fatty liver disease and hepatocarcinogenesis . Using adult L-G6pc-/- mice , we show that the G6Pase-α-deficient liver displays defective autophagy and reduced expression of SIRT1 and FoxO3a that regulate the expression of many ATG genes . Furthermore , hepatic SIRT1 overexpression corrects defective autophagy in the livers of L-G6pc-/- mice , demonstrating that down-regulation of hepatic SIRT1 signaling underlies autophagy deficiency in GSD-Ia ( Fig 7 ) . Finally we show that hepatic G6Pase-α restoration normalizes metabolic abnormalities associated with GSD-Ia , restores SIRT1-FoxO signaling , and corrects defective autophagy . Hepatic autophagy impairment in L-G6pc-/- mice is characterized by profound changes in the autophagy system ( Fig 7 ) . Firstly , the expression of many ATG proteins involved in autophagy execution , including initiation ( ATG101 ) , vesicle nucleation ( Beclin-1 and ATG14 ) , elongation ( LC3B and ATG3 ) , and mitophagy ( BNIP3 ) was reduced in G6Pase-α-deficient livers . Secondly , autophagic vesicle elongation was defective in the livers of L-G6pc-/- mice as evident by increased hepatic levels of acetylated ATG proteins along with reduced levels of the ATG12-ATG5 conjugate . Thirdly , G6Pase-α-deficient livers express reduced levels of LC3B-II along with reduced numbers of autophagic vacuoles , consistent with impaired autophagosome formation . Fourthly , G6Pase-α-deficient livers exhibit marked accumulation of p62 , the specific autophagy substrate that plays an important role in tumorigenesis [25] . Consequently , the G6Pase-α-deficient livers display significantly impaired autophagic flux . It has been reported that levels of cellular lipids negatively regulate the autophagy system [26] . Indeed , the livers of genetically obese ( ob/ob ) and high fat diet-fed ( HFD ) mice display reduced expressions of many autophagy components [27] . We now show that the primary mechanism underlying impaired hepatic autophagy in L-G6pc-/- mice is down-regulation of SIRT1 signaling . SIRT1 activity can be regulated by its altered expression in response to the energy status of the cell as well as by the levels of the cofactor NAD+ . Indeed , the expression of SIRT1 can be suppressed by lipogenic factors such as ChREBP and PPAR-γ , and stimulated by FoxO1 and PPAR-α in response to nutrient starvation [16] . In L-G6pc-/- mice , hepatic NAD+ levels were unchanged . On the other hand , liver-specific deletion of G6Pase-α results in suppressed expression of PPAR-α , a master regulator of fatty acid β-oxidation and increased contents of hepatic G6P that activates signaling of ChREBP , a transcriptional activator and repressor [17] . Activation of ChREBP is associated with increased lipogenesis , leading to a marked increase in hepatic steatosis that is known to increase the expression of PPAR-γ [28] , a lipogenic factor capable of suppressing SIRT1 expression [16] . Moreover , aberrant PPAR-γ overexpression has been shown to aggravate hepatic steatosis [29 , 30] . The net outcome was a decrease in the expression of SIRT1 in the livers of L-G6pc-/- mice , providing a possible link between hepatic steatosis and defective autophagy in GSD-Ia ( Fig 7 ) . Studies have shown that PPAR-α positively regulates hepatic autophagy [31 , 32] , suggesting that downregulation of PPAR-α in G6Pase-α-deficient liver also contributes to defective autophagy . Autophagy can also be regulated by mTOR signaling [7] . Recently , Farah et al . [11] showed that inhibition of mTOR signaling by rapamycin increased the expression of LC3-II and autophagic vesicles in the livers of young global G6pc-/- mice and suggested that activation of mTOR signaling may underlie hepatic autophagy deficiency in GSD-Ia . However , several lines of evidence showed that mTOR pathway plays a minimal role in hepatic autophagy impairment in L-G6pc-/- mice . Firstly , hepatic levels of the activated p-mTOR-S2448 and p-mTOR-S2481 as well as hepatic levels of nuclear TFEB , a target of mTOR signaling were similar between control and L-G6pc-/- mice . Secondly , the livers of rapamycin-treated L-G6pc-/- mice continued to express reduced levels of LC3B-I , ATG101 , ATG14 , ATG3 and marked high levels of p62 similar to untreated L-G6pc-/- mice . Thirdly , rapamycin treatment marginally restored hepatic autophagic flux in L-G6pc-/- mice . The major difference between two studies is the age of the animals used: adult L-G6pc-/- mice were used in this study and 10-day-old G6pc-/- mice were used by Farah et al [11] . It has been reported that depending on developmental stages , hepatic gene expression is differentially regulated by mTOR [33] and that milk intake can activate mTOR signaling during postnatal lactation period [34] . Therefore , it is possible that mTOR signaling is activated in young G6pc-/- mice during early postnatal development . However , the inability of rapamycin to normalize the expression of ATG proteins and p62 strongly supports the lesser role of mTOR signaling in autophagy deficiency in adult L-G6pc-/- mice . While young G6pc-/- mice exhibited early signs of hepatic autophagy impairment [11] , adult L-G6pc-/- mice displayed many aspects of hepatic autophagy impairment along with a marked increase of p62 , a selective autophagy substrate that accumulates in premalignant livers and hepatic tumors [35] . Studies have shown that autophagy-deficient mice develop HCA and the sustained p62 accumulation contributes to the development of HCA/HCC [12 , 13] , the hallmark of long-term complication of GSD-Ia . Thus , the L-G6pc-/- mouse that manifests hepatic autophagy deficiency and develops HCA is an excellent model to study the etiology and therapies of HCA in GSD-Ia . Our study establishes an important role of SIRT1 in maintaining autophagy function in G6Pase-α-deficient liver ( Fig 7 ) . The transcription of SIRT1 can be stimulated by PPAR-α , and down-regulated by PPAR-γ and ChREBP [16] . Therefore , modulation of these factors in the liver may improve hepatic autophagy impairment in the L-G6pc-/- mice . Notably , the G6P-mediated activation of hepatic ChREBP signaling can be reversed by rAAV-G6PC-mediated gene therapy that restores hepatic G6Pase-α expression . On the other hand , hepatic autophagy can be stimulated by a PPAR-α agonist [31] . Therefore , pharmacological interventions using PPAR-α agonists offers another avenue to improve hepatic autophagy impairment in the L-G6pc-/- mice . We have shown that systemic administration of rAAV-G6PC to young global G6pc-/- mice delivers the G6Pase-α transgene to the liver and corrects metabolic abnormalities [24 , 36] . When followed out to 70–90 week-old , the rAAV-G6PC-treated G6pc-/- mice maintain glucose homeostasis and show no evidence of HCA/HCC [36] . We now show that rAAV-mediated G6Pase-α restoration in adult L-G6pc-/- mice corrects metabolic abnormalities associated with GSD-Ia and completely normalizes hepatic autophagy deficiency that contributes to HCA development . Taken together , our results suggest that gene therapy offers a promising therapeutic strategy to rectify impaired autophagy and to prevent HCA development in GSD-Ia .
All animal studies were conducted under an animal protocol ( ASP-16-086 ) approved by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Animal Care and Use Committee followed the guidelines ( https://oacu . oir . nih . gov/animal-research-advisory-committee-guidelines ) . The G6pc fx/fx mice containing exon 3 of the G6pc gene flanked with loxP sites [37] were crossed with the SAcreERT2/w mice expressing a tamoxifen-dependent Cre-recombinase under the control of the serum albumin promoter [38] . The liver-specific G6pc-deficient ( L-G6pc-/- ) and L-G6pc+/- mice were generated by tamoxifen-mediated excision of the G6pc exon 3 in 6-week-old G6pcfx/fx . SAcreERT2/w and G6pcfx/w . SAcreERT2/w mice , respectively , as previously described [3] . GSD-Ia is an autosomal recessive disorder and the phenotypes of L-G6pc+/+ and L-G6pc+/- were indistinguishable , therefore both mice were used as controls . To reconstitute hepatic G6Pase-α activity , rAAV-G6PC , a rAAV vector expressing human G6Pase-α [24] at 1 x 1012 viral particles/kg was infused into L-G6pc-/- mice via retro-orbital sinus at 4 WP ( weeks post G6pc gene deletion ) . Liver samples were collected from mice at 12WP following a 6-hour fast . The recombinant adenovirus vectors expressing human SIRT1 ( Ad-SIRT1 ) and GFP ( Ad-GFP ) obtained from Vigene Biosciences ( Rockville , MD ) were amplified using 293 cells and purified via CsCl gradient centrifugation , The CsCl-purified vectors were then dialyzed against a buffer containing 10 mM Tris-HCL , pH 7 . 4 , 1 mM MgCl2 , and 10% glycerol . Control and L-G6pc-/- mice at 12 WP were infused with either Ad-GFP or Ad-SIRT1 via retro-orbital sinus at 1 x 108 pfu/mice and their phenotype was analyzed at 13 WP . Ad-GFP was used as a control vector . For rapamycin treatment , control and L-G6pc-/- mice at 12 WP were injected intraperitoneally with rapamycin ( LC Laboratories ) at 5 mg/kg body weight in vehicle ( 1% polyethylene glycol , and 1% Tween-80 , Sigma-Aldrich ) for 8 consecutive days . As controls , the mice were injected with vehicle alone . Autophagic flux determination was performed as previously reported [39] . Briefly , control and L-G6pc-/- mice were fasted for 20 hours to induce autophagy pathway . Then , the mice were injected intraperitoneally with saline or leupeptin ( Sigma-Aldrich , 40 mg/kg body weight ) that blocks lysosomal degradation , and were sacrificed 4 hours later . LC3B-II and β-actin in liver lysates were analyzed by Western blots and quantified by densitometry . The protein levels of LC3B-II were normalized against β-actin . Autophagic flux was determined by the difference in normalized LC3B-II protein levels between in mice treated with saline and in mice treated with leupeptin . Liver lysates were deproteinized using 14% ( wt/vol ) perchloric acid , and then neutralized with 2 M KOH/0 . 2 M MOPS . The levels of glucose , G6P , and lactate in deproteinized lysates were determined using the respective assay kit from BioVision ( Mountain View , CA ) . Hepatic levels of NAD+ and triglyceride were determined using the EnzyChrom NAD+/NADH assay kit ( BioAssay Systems , Hayward , CA ) and a Triglyceride Quantification Kit ( Biovision ) , respectively . Hepatic glycogen levels , microsome isolation , and G6Pase-α activity assay were performed as described [24] . Hepatocytes were isolated from control and L-G6pc-/- mice at 12 WP using a two-step collagenase perfusion method . Liver was perfused via the portal vein with liver perfusion medium ( Gibco , Waltham , MA ) for 5 min at 37°C , followed by liver digest medium ( Gibco ) for 5 min at 37°C . The excised liver was incubated in liver digest medium for 30 min at 37°C , and then passed through a 100 μm cell strainer ( Falcon , Franklin Lakes , NJ ) . The hepatocytes were pelleted by centrifugation at 4°C , washed twice with hepatocyte wash medium ( Gibco ) , and purified via 20% Percoll gradients ( GE Healthcare , Waukesha , WI ) . The resulting hepatocytes were washed with Willams E medium ( Gibco ) and resuspended in HepatoZYME-SFM ( Gibco ) . To determine autophagy vacuoles , 2 X 105 hepatocytes were incubated with 1 μl Cyto-ID Green Autophagy detection reagent ( Enzo Life Sciences , Exeter , United Kingdom ) in 1 ml of HepatoZYME-SFM for 30 min at 37°C , washed , and analyzed by flow cytometry using a Guava EasyCyte Mini System ( Millipore , St Charles , MO ) . The expression of mRNA was quantified by real-time PCR using the TaqMan probes ( Life Technologies ) in an Applied Biosystems 7300 Real-Time PCR system . Data were analyzed with the SDS Version1 . 3 software ( Applied Biosystems ) and normalized to Rpl19 RNA . Western blot images were detected with the use of the LI-COR Odyssey scanner and the Image studio 3 . 1 software ( Li-Cor Biosciences , Lincoln , NE ) . The antibodies were purchased from Cell Signaling Technology: PARP ( #9542 ) , Acetylated-Lysine ( #9814 ) , FoxO3a ( #12829 ) , Beclin-1 ( #3738 ) , ATG3 ( #3415 ) , ATG101 ( #13492 ) , BNIP3 ( #12396 ) , ATG7 ( #8558 ) , mTOR ( #2983 ) , p-mTOR-S2448 ( #5536 ) , and p-mTOR-S2481 ( #2974 ) . The antibodies were purchased from Abcam: LC3B ( ab51520 ) , p62 ( ab91526 ) , ATG14 ( ab139727 ) , and TFEB ( ab122910 ) . The antibodies were purchased from Santa Cruz Biotechnology: ATG5 ( sc-515347 ) , β-actin ( sc-47778 ) , PPAR-γ ( sc-7196 ) , and PPAR-α ( sc-9000 ) . SIRT1 ( #07–131 ) antibody was purchased from Millipore . The monoclonal antibody against human G6Pase-α was raised in mice using a peptide containing amino acid residues 227 to 268 in luminal loop 3 of human G6Pase-α [40] . Antigen injection , hybridoma generation , and clone screening were performed by A&G Pharmaceutical , Inc . Hybridoma clones were screened using the enzyme-linked immunosorbent assay ( ELISA ) on the immunogen . The culture supernatant from a hybridoma clone ( 3A9 ) showing high sensitivity to the immunogen was subjected to affinity purification using the peptide coupled agarose . The specificity of the purified antibody was confirmed by ELISA . Liver tissues were homogenized with the IP lysis buffer ( 25 mM Tris-HCl , pH 7 . 4 , 150mM NaCl , 1% NP-40 , 1 mM EDTA and 5% glycerol ) containing 1 X Halt Protease and Phosphatase Inhibitor Cocktails ( Thermo Scientific ) and centrifuged at 12000 g for 20 min at 4°C . The resulting supernatants were subjected to immunoprecipitation with the indicated antibody . To detect acetylated FoxO3a , liver nuclear extracts prepared using the NE-PER Nuclear and Cytoplasmic Extraction Kit ( Thermo Scientific , Waltham , MA ) were subjected to immunoprecipitation with an antibody against FoxO3a ( Cell Signaling ) and the resulting precipitates were examined by Western blot analysis with the antibody against acetylated lysine ( Cell Signaling ) . Mouse livers were fixed in 0 . 1 M sodium cacodylate buffer ( pH 7 . 4 ) containing 2 . 5% glutaraldehyde for 1 h at room temperature . The fixed liver tissues were then treated with 1% osmium tetroxide in 0 . 1M sodium cacodylate buffer and 2% uranyl acetate for 1 h at room temperature . The liver tissues were then serially dehydrated by ethanol , and then serially infiltrated via Spurr’s resin/ethanol up to 100% resin which was then polymerized for 18 h at 70°C in a Pelco BioWave Pro microwave oven ( Ted Pella , Inc . , Redding , CA ) , and finally cut into 90 nm sections using a Reichert-Jung Ultracut-E ultramicrotome . The resulting grids were stained with uranyl acetate and lead citrate , and imaged with a JEOL-1400 transmission electron microscope operated at 80 kV . Mouse liver tissues were fixed in 10% neutral buffered formalin ( Fisher Scientific , Grand Island , NY ) , embedded in paraffin , then sectioned to 10 μm thickness , and the paraffin was removed by Xylene ( Fisher Scientific ) . Liver sections were then incubated in antigen unmasking solution ( Vector Laboratories , Burlingame , CA ) for 10 min at 100°C . Endogenous peroxidases were quenched with 0 . 9% hydrogen peroxide in methanol , and then blocked with the Avidin/Biotin Blocking Kit ( Vector Laboratories ) . The sections were then incubated with the anti-ChREBP ( NOVUS ) antibody and followed with the biotinylated secondary antibodies ( Vector Laboratories ) . The resulting complexes were detected with an ABC kit using the DAB Substrate ( Vector Laboratories ) . Sections were also counterstained with hematoxylin ( Sigma-Aldrich ) and visualized using a Zeiss Axioskop2 plus microscope equipped with 10X/0 . 45NA , 20X/0 . 5NA or 40X/0 . 75NA objectives ( Carl Zeiss , Oberkochen , Germany ) . Nuclear translocalization of ChREBP was quantified by calculating the percentages of hepatocytes containing ChREBP-positive nuclei in 10 randomly selected fields of the livers stained with ChREBP antibody at 400 x magnification . The unpaired t test was performed by using the GraphPad Prism Program , version 4 ( San Diego , CA ) . The values were considered statistically significant at P < 0 . 05 .
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GSD-Ia is an autosomal recessive metabolic disorder caused by a deficiency in G6Pase-α , a key enzyme in maintaining blood glucose levels between meals . Despite strong compliance to dietary therapies , GSD-Ia patients continue manifesting metabolic aberrations including excessive accumulation of glycogen and lipid in the liver . Recently , G6Pase-α deficiency has been linked to impairment in autophagy , a recycling process essential for cellular homeostasis . However , the underlying mechanism is unclear . In this study , we show that hepatic G6Pase-α deficiency alters the activity and/or expression of several lipid regulators , leading to hepatic steatosis and reduced expression of SIRT1 , an enzyme that regulates the activity of many proteins via deacetylation . The impaired SIRT1 signaling increases the acetylation of ATG proteins critical for autophagic vesicle elongation , and reduces the activity of FoxO factors that can induce autophagy genes . Consistently , the G6Pase-α-deficient liver exhibits autophagy impairment characterized by attenuated expression of many autophagy components , defective autophagic vesicle elongation , impaired autophagosome formation , and reduced autophagy flux . Importantly , SIRT1 overexpression in G6Pase-α-deficient liver corrects autophagy deficiency . Finally , restoration of hepatic G6Pase-α expression corrects metabolic abnormalities , restores SIRT1-FoxO signaling , and normalizes defective autophagy . Collectively , hepatic G6Pase-α deficiency-mediated down-regulation of SIRT1 signaling underlies defective hepatic autophagy in GSD-Ia .
|
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2017
|
Downregulation of SIRT1 signaling underlies hepatic autophagy impairment in glycogen storage disease type Ia
|
Intravenous challenge with Trypanosoma cruzi can be used to investigate the process and consequences of blood parasite clearance in experimental Chagas disease . One hour after intravenous challenge of chronically infected mice with 5×106 trypomastigotes , the liver constituted a major site of parasite accumulation , as revealed by PCR . Intact parasites and/or parasite remnants were visualized at this time point scattered in the liver parenchyma . Moreover , at this time , many of liver-cleared parasites were viable , as estimated by the frequency of positive cultures , which considerably diminished after 48 h . Following clearance , the number of infiltrating cells in the hepatic tissue notably increased: initially ( at 24 h ) as diffuse infiltrates affecting the whole parenchyma , and at 48 h , in the form of large focal infiltrates in both the parenchyma and perivascular spaces . Phenotypic characterization of liver-infiltrating cells 24 h after challenge revealed an increase in Mac1+ , CD8+ and CD4+ cells , followed by natural killer ( NK ) cells . As evidence that liver-infiltrating CD4+ and CD8+ cells were activated , increased frequencies of CD69+CD8+ , CD69+CD4+ and CD25+CD122+CD4+ cells were observed at 24 and 48 h after challenge , and of CD25−CD122+CD4+ cells at 48 h . The major role of CD4+ cells in liver protection was suggested by data showing a very high frequency of interferon ( IFN ) -γ-producing CD4+ cells 24 h after challenge . In contrast , liver CD8+ cells produced little IFN-γ , even though they showed an enhanced potential for secreting this cytokine , as revealed by in vitro T cell receptor ( TCR ) stimulation . Confirming the effectiveness of the liver immune response in blood parasite control during the chronic phase of infection , no live parasites were detected in this organ 7 days after challenge .
A main feature of human and murine infections by Trypanosoma cruzi , the etiological agent of Chagas disease , is the rarity of spontaneous cure . Despite the generation of a potent anti-parasite immune response , that allows the control of parasitemia at the end of the acute phase , a small number of T . cruzi persists in the tissues . From this place , and for the lifetime of the host , the parasites occasionally gain access to the blood , where they can be detected by indirect methods such as xenodiagnosis , hemoculture , subinoculation or PCR [1]–[3] . Non-sterile control of T . cruzi at the chronic phase of the infection depends on humoral and cellular mechanisms . Destruction of intracellular amastigotes strongly relies in parasite-specific CD4+ and CD8+ T cells which act by release of pro-inflammatory cytokines and chemokines and direct cytotoxicity of infected cells [4]–[7] . The clearance of extracellular trypomastigotes is optimized by the coordinated cooperation of antibodies and phagocytes , a process that results in efficient parasite-destruction when phagocytes are primed by inflammatory cytokines , notably by IFNγ [8] . Thus , at the tissues , following rupture of a pseudocyst , released trypomastigotes are opsonized by IgG and subsequently phagocytosed by resident macrophages and recruited monocytes and polymorphonuclear cells [9] . At the blood , clearance of IgG-coated tripomastigotes is supposedly mediated by resident mononuclear phagocytes at the lung , liver and spleen [10] . This process depends on an intact Fc portion of the IgG molecule [11] , and although shown to require the participation of C3 complement component , occurs independently of the lytic terminal pathway [12] . Low and continuous release of trypomastigotes to the blood ( and tissues ) contributes to maintain the high level anti-T . cruzi effector activity of chronically-infected mice . Short and long-term effects of this continuous stimulus can be mimicked in an amplified version by intravenous ( i . v . ) challenge of chronic mice with live trypomastigotes . In this respect , we previously observed that 7–12 days after i . v . challenge of chronic mice with homologous parasites , a booster of the anti-T . cruzi effector mechanisms occurs , with increase in anti-T . cruzi IgG2a and IgG1 serum antibody levels , intense brief burst in the spleen IFN-γ production , activation of B and T cells and accumulation of class II+ non-B cells in the spleen [2] . In this work , continuing our studies on the host-parasite interaction at the chronic phase , we analyzed the short-term effects of an intravenous challenge with trypomastigotes . Parasite clearance was shown to occur to a large extent at the liver , an organ with an efficient resident immunity that responds to the acute T . cruzi infection with intense inflammation and high IFN-γ production [13] .
Six- to 8-week-old female C57Bl/6 mice were bred under specific pathogen-free conditions at the Isogenic Mice Facility , Instituto de Ciências Biomédicas , Universidade de São Paulo , Brazil . Experiments were carried out in accordance to the ethical guidelines for experiments with mice , the protocols being approved by the Health Animal Committee ( CEEA ) of the University of São Paulo . T . cruzi from the Y strain was maintained by weekly passages in A/J mice . C57Bl/6 mice were infected intraperitoneally ( i . p . ) with diluted blood containing 1000 trypomastigote forms . Parasitemias were determined by microscopic examination of 5 µl blood samples obtained from the tail vein . Seven to ten months after infection , chronic mice were challenged intravenously ( i . v . ) with 5×106 tissue culture tripomastigotes of the Y strain obtained from infected LLCMK2 cultures . One hour later , challenged chronic animals or unchallenged chronic controls were sacrificed to estimate the parasite load at the lung , liver and spleen and immunohistochemical analysis of T . cruzi at the liver tissue . Moreover , 24 and 48 h after challenge other mice were sacrificed for histological examination and leukocyte population analysis at the liver . Total DNA from spleen , lung and liver tissues collected from mice at the indicated time points post-infection , were extracted using GenomicPrep Cells and Tissue DNA Isolation kit ( Amersham Biosciences ) , following the manufacturers' protocol . Each real-time PCR reaction contained 40 ng genomic DNA , 0 . 5 µM of T . cruzi 18S rRNA gene ( AF303659 ) - specific primers Tc18S-F 5′- TTGAATTGAGGGCCTCTAAGG-3′ and Tc18S-R 5′- AAAGGTACCACTCCCGTGTTT-3′ . The T . cruzi quantification reactions were performed according to the manufacturers' instructions on an ABI Prism 7900HT system . The real-time PCR reaction used Applied Biosystems' Power SYBR Green PCR Master Mix . Relative quantification , ΔΔCt method , of specific DNA was normalized for mouse GAPDH gene ( GAPDH-F 5′-TGAAGCAGGCATCTGAGGG-3′ and GAPDH-R 5′-CGAAGGTGGAAGAGTGGGAG-3′ ) . Live T . cruzi parasites in the liver of individual chronic mice were revealed by culture of liver tissue aliquots containing 1 . 6 or 0 . 4 mg of tissue homogenate ( in quadruplicate ) , at 28°C , in axenic liver infusion tryptose ( LIT ) medium . Cultures were screened twice a week , for a month , for epimastigote growth . To avoid contamination of liver samples with peripheral blood , the inferior cava vein was sectioned above the diaphragm and the animals connected to a KDS 200 Two-Syringe Infusion Pump ( KD Scientific , New Hope , PA ) which delivered sterile phosphate-buffered saline , for 5 min , at a flow rate of 2 ml/min , through the left ventricle . Liver tissue specimens were collected and fixed in 10% formalin ( Merck , La Jolla , CA ) for further processing . Paraffin-embedded tissue sections were stained with hematoxylin-eosin and analyzed by optical microscopy . The hepatic inflammatory infiltrates were photographed using an image analysis system ( Image Pro Plus Media Cybernetics , Silver Spring , MD ) . Silane-coated slides ( 5 µm ) of paraffin-embedded liver tissues from chronic mice or from control or chronic mice that had been inoculated i . v . , 1 h before , with 5×106 culture trypomastigotes were dewaxed and hydrated by routine methods before the antigen retrieval procedure . Immunostaining was done by overnight incubation at room temperature with mouse-absorbed chronic immune rat serum anti-Y strain T . cruzi parasites . Then , the sections were first incubated for 2 h with biotin-labeled secondary antibody and second with the peroxidase-conjugated biotin-avidin complex ( Elite ABC kit , Vector laboratories ) . Finally , the peroxidase was revealed by immersion in DAB ( diaminobenzidine , Sigma ) . Slides were counterstained with hematoxilin . Intrahepatic leukocytes were isolated as described [14] . Briefly , after perfusion with phosphate buffer solution ( PBS ) , the liver was removed , a cellular suspension was prepared , treated with collagenase 0 . 02% ( Invitrogen , Carlsbad , CA ) , washed , admixed with 40% metrizamide ( Sigma ) solution in PBS and gently overlaid with RPMI 1640 medium supplemented with 1% heat-inactivated fetal calf serum ( FCS ) . Culture medium and supplements were purchased from Invitrogen . After centrifugation at 1500 g and 4°C , leukocytes were harvested from the medium-metrizamide inter-phase . The phenotype of intra-hepatic leukocytes was determined using a three-color FACScalibur cytometer ( Becton-Dickinson , San José , CA ) , after staining cells with FITC- , PE- , Cy-chrome- or biotin-conjugated monoclonal antibodies ( mAbs ) to CD4 ( clone H129 . 19 ) , CD8 ( clone 53-6 . 7 ) , B220 ( clone RA3-6B2 ) , CD11b ( Mac-1; clone M1/70 ) , NK1 . 1 ( clone PK136 ) , CD69 ( clone H1 . 2F3 ) , CD25 ( clone 7D4 ) and CD122 ( clone TMβ1 ) purchased from PharMingen ( San Diego , CA ) . When using biotin-conjugated mAbs , fluorochrome-labeled streptavidin ( PharMingen ) was added as a second step reagent . The number of each cell population per liver was determined by multiplying its respective frequency among liver leukocytes by the total number of leukocytes per liver estimated in a Neubauer chamber . Intrahepatic leukocytes were cultured overnight with Golgistop at 37°C in a 5% CO2 atmosphere , according to the manufacturer's instructions , in the presence or absence of plate-bound anti-CD3 ( 10 µg/ml; clone 145-2C11 ) and soluble anti-CD28 ( 2 µg/ml; clone 37 . 51 ) mAbs . After being washed , cells were surface stained with FITC- or Cy-Chrome-conjugated mAbs to CD4 , and CD8 . Cells were then fixed with the Cytofix/Cytoperm buffer and incubated with PE-labeled mAb to IFN-γ ( XMG-1 . 2 ) diluted in Perm/Wash buffer . The analysis was done in a FACSCalibur cytometer . All reagents were purchased from PharMingen . Statistical analysis was performed by ANOVA and Tukey's multiple comparison tests , or unpaired T test , using the GraphPad PRISM 4 software . Differences between two groups were considered significant at p<0 . 05 .
To study the clearance of bloodstream forms of T . cruzi , chronic mice were inoculated i . v . with 5×106 trypomastigotes . Tissue culture forms were used because blood trypomastigotes from 7-day infected mice are coated by IgM antibodies which could interfere in parasite recognition by specific IgG [15] . As previously described [16] , parasitaemia is not detected in T . cruzi-infected chronic mice by direct microscopic examination . Similarly , when chronic mice were challenged i . v . with 5×106 trypomastigotes we did not detect parasites in the blood any time after challenge . Differently , non-infected mice injected with T . cruzi displayed high parasitemias thirty minutes after injection , and small numbers were still be seen after 24 and 48 h ( Table 1 ) . In chronic mice , clearance of circulating blood T . cruzi parasites is thought to be mediated by resident mononuclear phagocytic cells in the lung , liver and spleen . To assess the relative clearance at these organs , the tissue parasite load of chronic mice was evaluated by real time PCR for T . cruzi DNA before and 1 or 48 h after challenge . In unchallenged chronic mice we were unable to amplify T . cruzi DNA in any of the three organs ( data not shown ) . Meanwhile , one hour after i . v . challenge of chronic mice , the amounts of T . cruzi DNA were sharply increased , notably in the liver and lung and , at lower level , in the spleen ( Fig . 1A ) . Since PCR was done with same amounts of tissue DNA and the weight of the liver was 6 . 3 times that of the lungs and 12 . 7 times that of the spleen , we concluded the liver plays a major role in parasite removal . Forty eight hours after challenge the numbers of amplified copies of T . cruzi DNA were drastically reduced in these organs . This represented 98% reduction for the lung , 74% reduction for the liver and 39% reduction at the spleen . To evaluate if parasites removed by the liver were alive , liver fragments obtained 1 and 48 h after challenge of chronic mice were cultured in LIT medium . Liver cultures from unchallenged chronic mice showed no live T . cruzi ( data not shown ) . Meanwhile , in 1-h challenged chronic mice , parasites were observed in 100% of cultures containing 0 . 4 mg of liver tissue , the number of positive cultures being strongly reduced at 48 h of challenge ( Fig . 1B ) . In additional experiments , no parasite was detected in cultures containing 1 . 6 mg of liver tissue from 7-day challenged chronic mice ( data not shown ) . Differently from liver cultures , no parasite growth was observed by culturing 5 µL aliquots of blood from chronic mice , before , or 1 and 48 h after challenge , in contrast with blood cultures from challenged control mice that yielded 100% positivity ( data not shown ) . To visualize the parasites at the liver parenchyma of challenged chronic mice , the liver tissue was analyzed by immunohistochemistry using a mouse-absorbed rat antiserum specific for T . cruzi Y parasites . As shown in figure 2 , intact or damaged parasites were seen uniformly distributed along the liver parenchyma of 1-h challenged chronic mice . Contrarily , in challenged control mice and in unchallenged chronic mice , peroxidase-positive staining was not observed . Histological examination of the liver tissue in chronic mice revealed a small number of focal infiltrates in the parenchyma and few perivascular infiltrates of discrete intensity ( Figure 3A ) . Twenty four hours after challenge , a moderate increase in the number of parenchyma-scattered leukocytes , many of which grouped as tiny foci of 5–10 cells , was observed ( Figure 3B ) . At 48 h , the above picture progressed to harbor a high number of parenchyma-scattered leukocytes and large-sized focal and perivascular infiltrates ( Figure 3C ) . Viable or damaged amastigote nests were not visualized in the liver of chronic mice or challenged chronic mice , in spite that they were exhaustively sought after . In contrast to the liver , tissue pathology at the heart or striated muscle ( quadriceps ) was not modified after challenge of chronic mice ( data not shown ) . To analyze the cellular composition of liver infiltrates , intra-hepatic leukocytes from chronic mice , challenged chronic mice and controls were characterized by flow cytometry . Total number of intra-hepatic leukocytes were discretely increased in chronic mice compared to control mice ( 11 . 7±3 . 6×106 cells versus 7 . 4±0 . 4×106 cells; p<0 . 01 ) . At the chronic phase , B ( B220+ ) cells were the most numerous population , but showed no changes in relation to control mice ( Figure 4 ) . Besides , no significant changes were observed for Mac1+ ( Mac1+CD4−CD8−B220− ) cells and NK ( NK1 . 1+CD4−CD8− ) cells . CD8+ and CD4+ cells were significantly increased in relation to control mice , with predominance of CD8+ cells . In consonance with the histological analysis , a huge increase in intra-hepatic leukocytes occurred in challenged mice ( from 11 . 7±3 . 6×106 cells in chronic mice to 35 . 8±1 . 1×106 and 43 . 4±11 . 9×106 cells at 24 and 48 h after challenge , respectively ) . After challenge , Mac1+ cells became the most frequent liver leukocyte population , representing the highest cell increase in relation to chronic mice . CD8+ and CD4+ cells progressively increased after challenge , the CD4/CD8 ratio being maintained as in chronic mice . In additional experiments it was observed , for both unchallenged and challenged chronic mice , that the Mac1+ liver population included GR-1LOW and GR-1HIGH cells [17] , where GR-1HIGH cells accounted for around one third of Mac1+ cells , 48 h after challenge ( Supplementary Figure S1 ) . The activation status of intra-hepatic CD4+ and CD8+ cells was estimated by expression of CD69 , an early lymphocyte activation marker [18] . For both T cell subsets , CD69 expression was higher in chronic mice than in control mice ( Figure 4 ) . However , when chronic mice were challenged with trypomastigotes the frequency of CD4+CD69+ and CD8+CD69+ cells drastically increased after 24 h , slightly declining at 48 h . Challenge-induced augments in CD69 expression correlated with increases in the frequencies of large cells . Thus , for CD4+ cells , the percentage of large cells increased from 23% in chronic mice to around 60% at 24 and 48 h of challenge . For CD8+ cells , a notable increase was also found , from 30% in chronic mice to 55% and 64% at 24 and 48 h of challenge , respectively ( Supplementary Figure S2 ) . To further evaluate the activation status of intra-hepatic CD4+ cells we investigated the surface expression of CD25 and CD122 molecules . The CD25 molecule constitutes the IL-2 receptor ( IL-2R ) α chain , which structures the high affinity IL-2R when associated to the β ( CD122 ) and cγ ( CD132 ) chains , and the low affinity IL-2R , when associated to just the cγ chain [19] . In addition , the IL-2R β chain is also used , together with the cγ and the IL-15R α chains , to structure in the IL-15R [20] . In mice , regulatory T cells usually have a CD25+CD122LOW phenotype , while activated/effector T cells are CD25+CD122HIGH and memory cells display a CD25−CD122HIGH phenotype [21] . In chronic mice , small fractions of liver CD4+ cells bore the CD25+CD122+ and CD25+CD122LOW/NULL phenotypes , while around 30% had a CD25−CD122+ phenotype ( Figure 5A ) . Twenty-four hours after challenge , half the CD4+ cells showed a CD25+CD122+ phenotype , the expression of the CD25 molecule in this cell subset being notably higher than that of corresponding cells in chronic mice . Nonetheless , after 48 h , the frequency of CD25+CD122+CD4+ cells diminished to 30% , their level of CD25 expression being also reduced . Conversely , the frequency of CD25−CD122+CD4+ cells decreased 24 h after challenge , increasing again at 48 h . CD25+CD122+CD4+ cells in the liver of challenged mice were predominantly blasts , both at 24 and 48 h . For the CD25−CD122+CD4+ cell subset , however , the frequency of large cells in 24-h challenged chronic mice was considerably lower , similar to that in chronic mice ( around 30–40% ) , increasing to 55% by 48 h ( Figure 5B ) . When these data were expressed in terms of total cell numbers in the liver , we observed that CD25+CD122+CD4+ cells notably increased 24 h after challenge , the augment being maintained at 48 h . Differently , recruitment/differentiation of CD25−CD122+CD4+ cells was relatively delayed , a significant increase being only observed after 48 h ( Figure 5C ) . IFN-γ plays a crucial role in T cruzi infection , acting at various levels , the optimization of macrophage trypanocidal activity being decisive [22] . During the acute phase of experimental Chagas disease different cell types produce IFN-γ in the liver , contributing to parasite clearance at this organ [13] . At the chronic phase of T . cruzi infection , however , dysfunctional CD8+ cells with impaired effector functions , inclusive deficient IFN-γ production , have been described in non-lymphoid tissues [23] . To evaluate if the intra-hepatic CD4+ and CD8+ T cell subsets produced IFN-γ after trypomastigote challenge , we examined the ex vivo production of this cytokine , by intracellular staining , in liver cells of chronic mice , before and 24 or 48 h after challenge with T . cruzi . CD4+ and CD8+ liver cells from chronic mice displayed low frequencies of IFN-γ producing cells , which were not significantly modified after in vitro stimulation with anti-CD3/CD28 mAbs ( Figure 6A–B ) . Twenty-four hours after challenge , however , a huge increase in the frequency of CD4+ cells producing IFN-γ was observed . This frequency slightly decreased at 48 h of challenge , but , because of the augment in total CD4+ cell numbers , the population of IFN-γ producing CD4+ cells in the liver remained of the same size at 24 h and 48 h ( Figure 6B ) . For these cells , in vitro stimulation with anti-CD3/CD28 mAbs did not resulted in additional increase in the frequency of IFN-γ-producing cells . Differently from CD4+ cells , challenge of chronic mice resulted in discrete increases in the frequency ( Figure 6A ) and total liver number ( Figure 6B ) of IFN-γ-producing CD8+ cells . However , after in vitro stimulation with anti-CD3/CD28 mAbs , important increases in these values were observed .
In chronic host tissues , trypomastigotes released upon rupture of an amastigote nest immediately bind specific IgG facilitating their internalization by resident or recruited phagocytes [24] , a process where the production of nitric oxide and oxygen radicals by phagocytes results in destruction of the ingested parasites [22] . Yet , the uptake of opsonized trypomastigotes by tissue phagocytes is not totally effective as a fraction of locally-released parasites manage to reinvade neighboring cells or make their way to the intravascular space . Once inside blood vessels , IgG-coated trypomastigotes are quickly cleared at the lung , liver and spleen by a mechanism that depends on the Fc portion of the IgG , but not on the lytic complement pathway [25] . This was elegantly shown by Umekita and Mota [11] by observing that trypomastigotes injected i . v . into normal mice are rapidly cleared from the blood following i . v . administration of immune mouse serum or parasite-specific IgG . In this paper , by demonstrating high levels of T . cruzi DNA in the liver of challenged chronic mice we conclude this organ plays a major role for the removal of blood circulating parasites in chronic mice . Meanwhile , because trypomastigotes disappear from the blood of chronic mice soon after i . v . inoculation , but live parasites are still found in the liver after 48 h , we conclude the uptake of IgG-opsonized T . cruzi by liver phagocytes is not immediately followed by their destruction . Failure to rapidly destroy the opsonized parasites was an unexpected finding considering the extensively documented synergism of IFN-γ and specific IgG for macrophage killing of T . cruzi [8] , [24] . Since serum from chronic C57BL/6 mice contained high levels of anti-T . cruzi IgG antibodies ( data not shown ) , this failure could have occurred because of insufficient signaling of resident liver phagocytes ( Kuppfer cells ) by systemic or locally-released IFN-γ or other macrophage-activating cytokines , or because of an intrinsic resistance to priming of liver phagocytes . Independently of the reasons behind , our results indicate that , in chronic mice , resident liver phagocytes are not fully-optimized in their trypanocidal activity for IgG-coated parasites . Meanwhile , the liver trypanocidal activity seems to be increased after recruitment of lymphocytes that produce IFN-γ . This is suggested by the absence of amastigote nests at the liver in the days following challenge and by the absence of positive LIT cultures in liver samples obtained from 7-day challenged chronic mice . Yet , the possibility that T . cruzi is not destroyed at the liver , the parasitized cells leaving this organ through the bloodstream to be destroyed elsewhere , is remote due to the fact that LIT cultures in blood samples were also negative . Our observation that intra-hepatic CD4+ cells produced high levels of IFN-γ 24 h after clearance indicates that following blood parasite clearance the liver becomes an important source of this cytokine . Moreover , because IFN-γ production was induced in CD4+ cells , but only marginally in CD8+ cells , it is possible that following immune clearance successful presentation of parasite antigens was predominantly achieved through MHC class II molecules . This interpretation would imply that most cleared parasites are retained in the phagocytic vacuole of liver phagocytes with few of them escaping to the cytosol or invading hepatocytes , even after 48 h . Alternatively , the low spontaneous production of IFNγ by CD8+ cells could be explained by their commitment to cytolytic function rather than cytokine production . Interestingly , many of the CD8+ cells in the liver of challenged chronic mice were blasts that expressed the activation marker CD69 , and indication they had been signaled and might not be totally quiescent . It remains to be determined whether CD8+ cell activation had occurred through class I-peptide recognition or cytokines . In addition to IFN-γ production , CD4+ cells in the liver of challenged chronic mice presented other signs of activation , two thirds of the cells expressing the early activation marker CD69 [18] . Moreover half the CD4+ cells were large CD25+CD122+ cells , a phenotype of effector cells . Besides this population , the liver of challenged mice contained CD25−CD122+CD4+ cells , a population with reduced number of blasts , which could be memory cells that respond to IL-15 [26] . The fact that the liver of unchallenged chronic mice contains a large number of CD25−CD122+CD4+ cells , but few CD25+CD122+CD4+ cells , together with our observation that the level of CD25 expression in CD25+CD122+CD4+ cells decreases after 48 h of challenge , raises the possibility that at least part of the CD25+CD122+CD4+ population differentiates in situ to CD25−CD122+CD4+ memory cells . In spite that the IFN-γ production response to clearance seemed to be CD4+ cell-mediated , CD8+ cells predominated in the liver of challenged chronic mice . Diverse groups have reported , in humans and mice , that CD8+ cells constitute the predominant lymphocyte subset in inflammatory sites of T . cruzi-infected chronic hosts [16] , [27]–[30] . Moreover , a large fraction of CD8+ cells in chronic mice display an effector memory ( EM ) phenotype [30]–[32] , inasmuch as they do not spontaneously produce IFN-γ and other inflammatory cytokines , but they can do so after engaging T . cruzi-infected targets [30] . In consequence , CD8+ cells expanded/recruited to the liver tissue of challenged chronic mice seem to be EM cells and not anergic or dysfunctional [23] , since they could be induced to produce IFN-γ upon in vitro stimulation with anti-CD3/CD28 mAbs . By expanding/recruiting a large number of CD8+ EM cells , the liver of the chronic host is prepared for the eventual colonization of non-phagocytes by trypomastigotes , a process that seems to be of little magnitude . From the experiments shown in this work we can extrapolate that by clearing a large fraction of blood trypomastigotes and recruitment of IFNγ-producing effector T lymphocytes the liver plays an important role in the control of low level parasitaemia of chronic mice . It should be considered , however , that T . cruzi parasites are extremely diverse , exhibiting differences , not only in relation to tropism , but also in resistance to the immune effector mechanisms [33] , [34] . Therefore , because our data derive from experiments with Y strain parasites , a prototypic rethyculotropic strain , additional experiments will be necessary to ascertain the extent to which these conclusions are valid for other T . cruzi parasites .
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Chagas disease , a Latin American illness caused by the protozoan parasite Trypanosoma cruzi , has only rare spontaneous cure , and in most patients a small number of parasites persists for life in the blood and tissues , leading to chronic disorders such as cardiomyopathy . In a murine model of chronic T . cruzi infection we observed that the liver plays an important role in the clearance of blood-circulating parasites . Moreover , parasite accumulation in this organ is followed by their elimination , an effect that is not immediate but seems to depend on the recruitment of leukocytes and on the local production of IFN-γ , a cytokine known to increase the T . cruzi-killing capacity of phagocytes . Our findings contribute to the knowledge of T . cruzi-host interaction , showing the participation of a non-lymphoid organ in parasite control . In addition , they contribute to understanding the multifaceted role the liver plays in the immune response .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/protozoal",
"infections",
"immunology/immunity",
"to",
"infections",
"immunology/immune",
"response",
"immunology/leukocyte",
"activation"
] |
2010
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The Liver Plays a Major Role in Clearance and Destruction of Blood Trypomastigotes in Trypanosoma cruzi Chronically Infected Mice
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Shigella spp . are pathogenic bacteria that cause bacillary dysentery in humans by invading the colonic and rectal mucosa where they induce dramatic inflammation . Here , we have analyzed the role of the soluble PRR Pentraxin 3 ( PTX3 ) , a key component of the humoral arm of innate immunity . Mice that had been intranasally infected with S . flexneri were rescued from death by treatment with recombinant PTX3 . In vitro PTX3 exerts the antibacterial activity against Shigella , impairing epithelial cell invasion and contributing to the bactericidal activity of serum . PTX3 is produced upon LPS-TLR4 stimulation in accordance with the lipid A structure of Shigella . In the plasma of infected patients , the level of PTX3 amount only correlates strongly with symptom severity . These results signal PTX3 as a novel player in Shigella pathogenesis and its potential role in fighting shigellosis . Finally , we suggest that the plasma level of PTX3 in shigellosis patients could act as a biomarker for infection severity .
The first line of immune defense against pathogens is guaranteed by the recognition of Pathogen Associated Molecular Patterns ( PAMPs ) by Pattern Recognition Receptors ( PRRs ) . The family of PRRs includes secreted , membrane-bound and cytosolic PRRs [1] . Pathogenic organisms use sophisticated strategies to modulate PRR recognition and to control downstream signaling . Accordingly , the human enteropathogen Shigella exploits different mechanisms to hijack the innate immune response . The Shigella genus includes 4 serogroups: S . boydi , S . dysenteriae , S . flexneri and S . sonnei . and S . flexneri are the main serogroups circulating in industrialized and developing countries respectively [2] , but most studies centered on the invasion process of Shigella in vitro and in vivo have been carried out with S . flexneri . Shigella penetrates epithelial cells through a series of effectors secreted via a Type 3 Secretion System ( T3SS ) [3] encoded by a large virulence plasmid common to all Shigella serogroups . Once inside the colonic mucosa , shigellae either fuel or dampen the inflammatory response , depending on the step of the invasion process . In epithelial cells , Shigella multiplies freely within the cytoplasm [4] where the cytosolic PRR Nod1 recognizes cell-wall peptidoglycan ( PGN ) and activates NF-κB [5 , 6] . This leads to CXCL8/IL-8 production . IL-8 attracts neutrophils which are required for the clearance of shigellae but which also participate in the destruction of the epithelial barrier [7] . Within epithelial cells , S . flexneri changes its lipopolysaccharide ( LPS ) structure from a highly inflammatory hexa-acylated lipid A form to a less inflammatory tetra- and tri-acylated lipid A variant [8] . This low-inflammatory LPS is poorly recognized by the PRR Toll-Like-Receptor 4 ( TLR4 ) , making macrophages and neutrophils less able to control the infection . Furthermore , in B lymphocytes Shigella induces TLR2-mediated apoptotic death through a mechanism mediated by T3SS , independent of cell invasion [9] . These immune evasion strategies involve TLR2 and TLR4 , which are PRRs present on the surface of many cell populations , suggesting that the extracellular step could be critical for successful infection . To gain insight about this poorly explored aspect of Shigella pathogenesis we analyzed the potential role of humoral PRRs , focusing on the possible involvement of Pentraxin 3 ( PTX3 ) , which has served as a paradigm of humoral innate immunity [10] . PTX3 is a key element of the humoral arm of innate immunity , downstream of and complementary to cellular recognition and activation . Pentraxins are an evolutionarily highly conserved superfamily of proteins . PTX3 is the prototypic long pentraxin , while the short pentraxins include C-reactive protein ( CRP ) and serum amyloid P component ( SAP ) , acute-phase proteins in man and mouse respectively . PTX3 is rapidly produced and released by several cell types , e . g . mononuclear phagocytes , dendritic cells ( DCs ) and neutrophils [11] in response to primary inflammatory signals ( e . g . TLR engagement , TNF-α , IL-1β ) . PTX3 binds selected microorganisms , including Aspergillus fumigatus , Pseudomonas aeruginosa [12 , 13] and uropathogenic Escherichia coli ( UPEC ) [14] . It also promotes complement activation , thereby facilitating pathogen recognition by phagocytes [15] . All these features prompted us to investigate whether PTX3 could play a role in Shigella pathogenesis and how and to what extent this PRR is released upon Shigella infection . Our findings highlight that PTX3 is a new player in the Shigella cross-talk with the infected tissues and provide novel insights into the mechanisms of Shigella to control the production of this humoral PRR .
Firstly , we addressed the question of whether PTX3 could opsonize Shigella as reported with A . fumigatus , Salmonella typhimurium , P . aeruginosa , Neisseria meningiditis [12 , 13 , 16] and uropathogenic E . coli ( UPEC ) ( 14 ) . We observed that PTX3 ( 50 μg/mL , 1 , 1 μM ) opsonized the wild type S . flexneri 5 strain M90T ( Fig 1A and 1B ) and its plasmidless , non-invasive variant BS176 though to a lesser extent compared to P . aeruginosa ( strain PAO1 ) , used as a positive control ( 12 , 17 ) Epithelial cell invasion and macrophage death [18] are hallmarks of Shigella pathogenesis . We investigated whether PTX3 binding could affect epithelial-cell penetration by Shigella . M90T was incubated with different concentrations of recombinant PTX3 ( 0 . 05 , 0 . 5 , 5 and 50 μg/mL ) prior to infection of HeLa cells . M90T treated with bovine serum albumin ( BSA ) ( 50 μg/mL ) or with a rabbit polyclonal antibody raised against the T3SS-invasin IpaD ( 50 μg/mL ) , which is involved in bacterial internalization [19] was used in parallel . As shown in Figs 1C and S1A , PTX3 opsonization with only the concentration of 50 μg/mL significantly decreased the number of intracellular bacteria at 1 h and 2 h post-infection ( p . i . ) ( p< 0 . 001: PTX3-opsonized M90T vs . M90T plus BSA at 2h ) to levels like those induced by the anti-IpaD antibody . In human peripheral blood monocytes-derived macrophages ( MoMs ) , opsonization with recombinant PTX3 at same concentrations as above only determined a significant improvement of bacterial phagocytosis at the concentration of 50 μg/mL ( Fig 1D and 1E , S1B Fig ) ( p< 0 . 01: PTX3-opsonized M90T vs . M90T plus BSA ) . Likewise , the rate of MoMs cell death , measured through lactate dehydrogenase ( LDH ) release , ( Fig 1F and S1C Fig ) was improved by PTX3 opsonization , as also shown with the anti-IpaD antibody [19 , 20] . However , the cell death rate followed the trend as above since it was only increased with PTX3 at the concentration of 50 μg/mL ( p< 0 . 01: PTX3-opsonized-M90T vs . M90T plus BSA ) ( S1C Fig ) PTX3 is also involved in complement cascade activation and regulation [21] . There is scant and dated literature on Shigella sensitivity to the bactericidal activity of serum [22] , so we set up a bactericidal serum assay against S . flexneri M90T . In preliminary experiments using different serum concentrations ( 10%; 13%; 17%; 67% ) for 30 min at 37°C , we found that M90T was sensitive to concentrations of > 10% pooled normal human serum ( NHS ) . Exposure to 17% NHS killed around 60% of bacteria ( Fig 1G ) . Addition of low concentrations of PTX3- 5–0 . 5 μg/mL in the bactericidal serum assay ( 17% serum ) significantly increased bacterial death rate of the bacteria ( Fig 1H ) . In conclusion: PTX3-bound bacteria are partially impaired in their ability to invade epithelial cells and are better internalized by macrophages as shown with antibody-bound bacteria [23 , 24] . Low doses of PTX3 increase the bactericidal activity of serum/complement . We therefore passed to analyze a possible contribution of PTX3 in vivo , during infection . Several reports have described the therapeutic effect of recombinant PTX3 in the models of aspergillosis [25 , 26 , 27]; of P . aeruginosa acute and chronic lung infections [17 , 28 , 29]; of acute respiratory syndrome [30] and of influenza virus lung infection [31] Mice are naturally resistant to Shigella oral infection . Therefore , alternative infection models have been developed and used [32 ) . Among them , the intranasal route of infection in mice [33] has been extensively used and validated to study Shigella virulence and to analyze vaccine candidates [32 , 33] . After intranasal infection ( i . n . ) with virulent Shigella , mice develop a dramatic pneumonia and die within a few days [32 , 33] . In line with these issues , we investigated whether treating mice with recombinant PTX3 could affect the outcome of intranasal infection with M90T , as shown with the other pathogens as above . Based on previously performed pharmacokinetic analyses and therapeutic approaches in a murine model of lung infection with A . fumigatus [12 , 25 , 26 , 27] and P . aeruginosa [17 , 28 , 29] , we established a treatment schedule of daily intra-peritoneal ( i . p . ) injections with recombinant human PTX3 ( 0 . 5 mg/Kg , 11 μM ) or vehicle , starting from the day of the i . n . inoculum with 3 x 108 colony forming units ( CFU ) of M90T ( corresponding to the LD50 dose ) . The treatment with PTX3 was carried out for 48 hours ( three PTX3 injections ) . Following this experimental plan , we monitored animal survival/death ( in three independent experiments ) during 1 week . As expected [6 , 34 , 35] , during the 72 hours , 55% of mice infected with M90T died ( 12/22 ) died . By contrast , the animals infected with M90T and treated with PTX3 survived even when the treatment with PTX3 was stopped ( 19/19 ) , ( p< 0 . 0002 , two-tailed Mantel-Cox test ) ( Fig 2A ) At 72 h post-challenge , the bacterial load in lungs of M90T-infected animals was ~ 106 CFU ( per lung ) , as previously published [6 , 34 , 35] whereas in PTX3 treated animals the number of CFU ( per lung ) was ~ 104 CFU , which was significantly ( p< 0 . 0001 ) reduced with respect to that of infected , untreated animals ( Fig 2B ) . The local level of pro-inflammatory cytokines and chemokines was measured in BALs ( broncho- alveolar lavage ) ( Fig 2C ) and lung homogenates ( Fig 2D ) . We chose some chemokines/cytokines , which have been previously shown to be influenced by PTX3 treatment [12 and 17 , 29] and/or to be involved in Shigella infection [6 , 34 , 8] . CCL5 ( RANTES ) and IL-1β values were similar in BALs and lung homogenates for untreated and PTX3-treated infected animals , while those of TNF-α CXCL2/MIP-2 and CXCL1/KC were drastically decreased in both homogenates and BALs of PTX3-treated mice compared to infected-untreated mice ( for all , p <0 . 0001 , two-tailed Mann-Whitney test ) . Furthermore , we quantified the PTX3 levels in sera ( Fig 2E ) , lung homogenates ( Fig 2F ) and BALs ( Fig 2G ) . In lung homogenates of M90T-only-infected animals the PTX3 level was lower than that of PTX3-treated infected and uninfected mice ( for both , p < 0 . 0001 two-tailed Mann-Whitney test ) . Likewise , in BALs and sera the levels of PTX3 were significantly ( p < 0 . 0001 , two-tailed Mann-Whitney test ) reduced in M90T-only-infected animals with respect to those treated with PTX3 . At macroscopic examination ( S2 Fig Top ) , lungs of infected mice were enlarged , of rubbery consistency , edematous and dusky red in color due to severe hyperemia . The lungs of infected and PTX3-treated animals were macroscopically like the controls , and they appeared aerated , pinkish and spongy . In lungs of M90T-infected mice , hematoxylin-eosin staining showed acute pneumonia with severe bronchoalveolitis , alveolar edema and many damaged areas in the parenchyma . Pulmonary phlogosis was characterized by a severe and diffuse neutrophil infiltrate in peribronchial , intraluminal and interstitial areas between alveoli ( S2A , S2D and S2G Fig ) . In contrast , in PTX3-treated infected mice , lungs conserved a physiological architecture with a moderate inflammation of the aerated parenchyma and airways and a low and scattered neutrophilic exudate ( S2B , S2E and S2H Fig ) . Histopatological scores ( S1 Table ) confirmed these observations . Immunohistochemical staining of PTX3 in tissues of untreated M90T-infected mice ( S3A Fig ) revealed a diffuse production of PTX3 , due to the involvement of bronchial mucosa cells and rare interspersed neutrophils . Strong PTX3-immunostain was observed in lung sections of PTX3-treated infected mice ( S3B Fig ) . In uninfected PTX3-treated mice , PTX3 was barely detectable with only a few scattered PMNs physiologically associated with the bronchial mucus and the BALT ( S3C Fig ) . As oppose to the protective effect of recombinant PTX3 in the models of P . aeruginosa and S . fumigatus lung infection , Ptx3-deficient mice showed increased mortality and lung colonization [12 , 17] . Likewise , Ptx3 -/- mice were more susceptible than the wild type to influenza virus and to UPEC infections [31 , 14] . Hence , we assessed whether deficiency of PTX3 could affect the virulence of Shigella . With this aim Ptx3-/- mice were infected via intranasal route with M90T as above and the animals were monitored for a week . We found that Ptx3-/- mice challenged with M90T showed an accelerated death with respect to M90T-infected wild type mice ( p < 0 . 046 , two-tailed Mantel-Cox test ) as the majority ( 75%: 20/30 ) of the animals died after 48 hours p . i . ( Fig 3A ) At a same time point , only 23% ( 7/30 ) wild type infected mice died . The bacterial load in lungs of Ptx3-/- of the infected animals was around ten times more ( 9 , 3 x105 vs 1 , 54 x105 ) ( p <0 . 0001 , two-tailed Mann-Whitney test ) than that found in infected wild type animals ( Fig 3B ) . Likewise , the levels of TNF-α , CXCL-1 and CXCL-2 in BALs ( Fig 3C ) and lung homogenates ( Fig 3D ) were significantly higher ( for all , p <0 . 0001 , two-tailed Mann-Whitney test ) than those elicited in infected wild type mice . Conclusively , these findings suggest that PTX3 is involved in Shigella pathogenesis . Nevertheless , only a genetic rescue with transgene expression or recombinant Ptx3 administration to Ptx3-/- mice could consolidate this result . We then proceeded to examine whether and to what extent Shigella infection could trigger per se PTX3 release . DCs are a major source of PTX3 , released following triggers such as various inflammatory cytokines or bacterial PAMPs [10] . BMDCs from C57BL/6 mice were infected with the invasive strain M90T , or with the non-invasive isogenic strain BS176 , lacking the virulence plasmid . BMDCs were infected with shigellae at the Multiplicity of Infection ( MOI ) of 10 . PTX3 and TNF-α production was monitored in parallel at 1 , 3 , 6 and 18 h . post-infection ( p . i ) BS176 induced a significantly higher release of PTX3 than M90T ( Fig 4A ) , while TNF-α release was equivalent with both strains ( S4A Fig ) . To test if invasiveness was correlated to PTX3 release , we introduced another non-invasive strain into our assay . M90T ΔipaB lacks the T3SS-secreted invasin IpaB and is thus non-invasive in epithelial cells even if it can still construct the T3SS machinery [19] . PTX3 release induced by M90T ΔipaB was similar to that of BS176 ( Fig 4A ) . To confirm this trend , the infection protocol of BMDCs was modified to abrogate the invasive phenotype of M90T and PTX3 release was measured as above . First , BMDCs were exposed to the invasive and non-invasive strains , previously killed with gentamicin ( Fig 4B ) . M90T- and BS176-killed bacteria potentially could be phagocytized by DCs; however , the invasive ability of M90T was destroyed . The release of PTX3 did not change in BMDCs infected with killed BS176 . In contrast , the PTX3 values induced by killed M90T were significantly higher than those recorded with live M90T . Then , we prevented cell internalization of bacteria by treating the cells with cytochalasin D , which disrupts cytoskeleton organization [36] . In contrast to the previous approach , here invasive and non-invasive bacteria could not be internalized by the cells . Under this condition the PTX3 values induced by M90T were comparable to those of BS176 ( Fig 4C ) . The two different experimental approaches are aimed differently at preventing the invasive phenotype of virulent shigellae . However , under both conditions the internalization of live M90T by the cells was inhibited , leading to a significant increase of PTX3 release . Therefore , we analyzed the production of PTX3 and TNF-α in parallel in human peripheral blood MoDCs . The difference in PTX3 release observed with invasive and non-invasive Shigella strains in BMDCs was also recorded in MoDCs ( Fig 4D ) . The trend of TNF-α release was similar to that observed with PTX3 ( S4B Fig ) , in contrast to observations in BMDCs where the TNF-α production was equally induced by the two strains . These results indicate that inhibition of cell invasion—due to either bacteria killing , deficiency of virulence plasmid , or host cell cytoskeleton disruption—leads to higher PTX3 release by human or murine DC . To evaluate the signaling pathways involved in PTX3 production , we analyzed the putative roles of factors involved in downstream TLR signaling: Myd88 , Trif , Cd14 and Irf3 [37] . Infection of Myd88-/- BMDCs significantly reduced the release of PTX3 with respect to wild-type BMDCs ( Fig 4E ) . A similar trend was noted for TNF-α production ( S4C Fig ) . The absence of Trif , Irf3 or Cd14 greatly reduced the PTX3 production as shown in Fig 4F and 4G . Likewise , TNF-α measures were drastically reduced but not totally abrogated in Trif-/- , Irf3-/- and Cd14 -/- BMDCs ( S4C and S4D Fig ) . As LPS is the unique PAMP engaging the Myd88 and Trif pathways , we investigated whether LPS could trigger PTX3 release , as also shown for UPEC [14] . Shigella modifies LPS composition during intracellular residence in epithelial cells [8] . Intracellular bacteria possess a hypo-acylated lipid A characterized by a blend of lipid A forms; tetra- and tri-acylated variants are more prevalent than the hexa-acylated isoform , which is the main component present in LPS of M90T grown in laboratory media . M90T ΔmsbB1 ΔmsbB2 [38 , 8] is a M90T mutant that carries penta-acylated ( 86% ) and tetra-acylated lipid A forms . M90T ΔmsbB1 ΔmsbB2 is fully invasive . Purified LPS from this strain showed a low inflammatory potential , in accordance with the lipid A structure [8] . We checked whether LPS composition could impact PTX3 production in DCs treated with three Shigella LPS variants: that extracted from bacteria grown in laboratory medium [acellular ( a ) LPS] , that purified from intracellular bacteria [intracellular ( i ) LPS] and LPS of M90T ΔmsbB1 ΔmsbB2 . E . coli LPS was used in parallel . BMDCs stimulated with iLPS and M90T ΔmsbB1 ΔmsbB2 LPS produced a lower level of PTX3 with respect to aLPS and E . coli LPS , consistent with the degree of lipid A acylation ( Fig 4H ) . TNF-α release reflected the differences between the LPSs ( S4E Fig ) . Then , we examined whether the composition of LPS on live bacteria could affect PTX3 yield using M90T and M90T ΔmsbB1 ΔmsbB2 in an invasion assay as above . However , PTX3 and TNF-α release were similar for M90T and M90T ΔmsbB1 ΔmsbB2 , despite different lipid A composition ( Fig 4I and S4F Fig ) . MoDCs were stimulated with the three Shigella LPS forms ( aLPS , iLPS and M90T ΔmsbB1 ΔmsbB2 LPS ) following the scheme described for BMDCs . PTX3 yield drastically decreased with iLPS and LPS of M90T ΔmsbB1 ΔmsbB2 with respect to aLPS ( Fig 4J ) and TNF-α release followed the same trend ( S4G Fig ) . In contrast with results in BMDCs and in accordance with Lipid A composition , the amount of PTX3 and of TNF-α in infected MoDCs was lower with M90T ΔmsbB1 ΔmsbB2 than with M90T ( Fig 4K and S4H Fig ) . Thus , in addition to invasiveness , LPS composition plays a pivotal role in triggering PTX3 release in human DCs . The effect of acylation degree of LPS on live bacteria was not evident in murine DCs ( Fig 4I vs Fig 4K ) in line with the different TLR4 lipid A-sensitivity , as reported [39 , 40] . As macrophages are a further source of PTX3 during infections , we analyzed whether Shigella could promote PTX3 release in macrophages , as shown in DCs . In mouse BMDMs infected with M90T or BS176 , the difference in PTX3 yield between M90T and BS176 was like that observed in BMDCs ( Fig 5A ) . TNF-α release did not follow this trend as the release of this cytokine was similar between the two strains ( S5A Fig ) . However , it has been reported that Shigella-infected macrophages are poorly responsive to Shigella infection in the absence of an adequate pre-stimulation [41] . We then infected LPS-primed BMDMs as described previously [8] to evaluate the influence of LPS modification on PTX3 release . BMDMs were primed with M90T aLPS ( mainly hexa-acylated ) , M90T iLPS ( mainly tetra-acylated ) and M90T ΔmsbB1 ΔmsbB2 LPS ( mainly penta-acylated ) and were then infected with M90T at MOI 10 . Infected BMDMs primed with iLPS and M90T ΔmsbB1 ΔmsbB2 LPS ( both LPSs hypo-acylated ) released significantly less PTX3 than those primed with aLPS ( Fig 5B ) , while the amount of TNF-α was similar for all the LPSs , as already shown [8] ( S5B Fig ) . Then , we stimulated the BMDMs ( without infection ) with the three Shigella LPS ( 10 ng/mL ) as above for 6 h . PTX3 and TNF-α yields were lower with iLPS and M90T ΔmsbB1 ΔmsbB2 LPS ( both LPSs hypoacylated ) than with aLPS ( Fig 5C and S5C Fig ) . To evaluate the relative role of structural LPS on live bacteria and LPS priming , BMDMs were primed with different LPSs and then infected with M90T ΔmsbB1 ΔmsbB2 ( carrying a penta-acylated LPS ) instead of M90T ( carrying a hexa-acylated LPS ) as above . PTX3 release followed the trend observed with M90T , which was consistent with the acylation degree of the LPSs used for priming; however , M90T ΔmsbB1 ΔmsbB2 triggered a significantly lower release of PTX3 compared to M90T for each condition , in accordance with the hypo-acylation degree of its LPS ( Fig 5D ) . For TNF-α , the difference between M90T and M90T ΔmsbB1 ΔmsbB2 was maintained , while no significant difference was induced by priming with the various LPSs as for PTX3 ( S5D Fig ) . We then examined whether MoMs ( peripheral blood monocyte-derived macrophages ) respond to Shigella infection and LPS stimulation as observed with BMDMs , BMDCs and MoDCs . With this aim , MoMs were infected with either: M90T , BS176 , M90T ΔmsbB1 ΔmsbB2 or stimulated with the different LPS and both PTX3 and TNF-α production was evaluated . When infected with M90T , BS176 or M90T ΔmsbB1 ΔmsbB2 , PTX3 ( Fig 5E ) and TNF-α yields ( S5E Fig ) were significantly higher with BS176 than with M90T . This result was consistent with that seen in BMDMs , BMDC and MoDCs . Likewise , M90T ΔmsbB1 ΔmsbB2 induced the lowest PTX3 and TNF-α production in accordance with its LPS structure and as also observed in BMDMs and MoDCs . In MoMs stimulated with the four forms of LPS ( M90T iLPS and aLPS , M90T ΔmsbB1 ΔmsbB2 and E . coli LPS ) , iLPS and M90T ΔmsbB1 ΔmsbB2 LPS induced the lowest production of PTX3 ( Fig 5F ) and TNF-α , just as for BMDMs ( S5F Fig ) . Together , these experiments suggest that LPS composition is a major trigger of PTX3 production in macrophages and that PTX3 production is influenced by both structural LPS on infecting bacteria and purified LPS used for stimulation or priming . Finally , we addressed the question about the TLR4 downstream signaling leading to PTX3 release in BMDMs as shown in BMDCs . We then used Myd88-/- , Trif-/- , Irf3-/- and Cd14-/- BMDMs ( Fig 5G ) as described for BMDCs . Surprisingly , PTX3 release was abrogated in all knockout BMDMs , indicating that the MyD88-dependent and MyD88-independent pathways are synergistic in the production of PTX3 . In accordance with published results [8] we found that the MyD88 pathway was mainly involved in the release of TNF-α ( S5G and S5H Fig ) , with some contribution of the Trif pathway . In Cd14-/- BMDMs , the values of TNF-α were significantly lower than in wild-type cells , while the absence of Irf3 did not impair TNF-α release ( S5G Fig ) . These results highlight some differences in the pathways leading to TNF-α and PTX3 release . Although S . sonnei is the main serogroup circulating in high-income countries , in recent years S . sonnei has also been observed to prevail over S . flexneri in previously low- income countries where socioeconomic conditions have improved [2] . We evaluated whether S . sonnei could , like S . flexneri M90T , induce PTX3 production . BMDCs , MoDCs and BMDMs and MoMs were infected with S . sonnei as with M90T ( S6A , S6B , S6C , S6G and S6I Fig ) . Release of PTX3 induced by S . sonnei was similar to that induced by M90T in all cell populations . Likewise , TNF-α was similar with both strains under all the conditions ( S6D , S6E , S6F , S6H and S6J Fig ) . The involvement of PTX3 in shigellosis prompted us to investigate PTX3 levels in plasma of shigellosis patients . Plasma samples were collected from 31 patients in the acute stage ( 0–7 days after onset ) of culture-proven S . sonnei shigellosis and from 19 healthy subjects and PTX3 levels were measured . Mean PTX3 levels were significantly higher in the patient group ( 10 . 4 ng/mL ) compared to the control group ( 2 . 3 ng/mL ) ( p = 0 . 003 ) . The highest levels of PTX3 in patients and controls were 50 ng/mL and 11 . 75 ng/mL , respectively ( Fig 6 ) . PTX3 levels were significantly higher within 2 days of disease onset than in samples collected later and were positively associated with signs or symptoms related to the severity of shigellosis such as body temperature , number of watery stools per 24 hours and bloody stools ( S2 Table ) . Among acute cases of S . sonnei shigellosis whose maximal measured body temperature was above 39°C , the mean PTX3 level was much higher than among acute patients whose maximal measured temperature was equal or below 39°C . Similar results were found in regard to presence of blood in stool or when both signs of severity were present , albeit reaching borderline statistical significance ( p = 0 . 05 , p = 0 . 06 respectively ) .
The role of the humoral arm of the innate immunity has been poorly explored in the context of intracellular bacterial pathogens like Shigella . Here we unveil that phase fluid PRM PTX3 could play a decisive role in resolving Shigella infection as the treatment with recombinant human PTX3 rescues animals from death in the murine model of pulmonary shigellosis . As oppose to the protective effect of recombinant PTX3 Ptx3-/- infected mice showed a defective ability to clear bacteria and an accelerated kinetics of death in the same infection model . This is in line with that observed with P . aeruginosa , A . fumigatus and UPEC ( 12 , 14 , 17 ) . The therapeutic effect of PTX3 has already been reported for the extracellular pathogens P . aeruginosa and A . fumigatus and Streptococcus suis [13 , 17 , 25 , 26 , 27 28 , 29 , 42] This PRM influences pathogen phagocytosis through opsonization of microorganisms and by reinforcing complement activity [11 , 21] . In lungs of M90T-only infected animals , bacterial load was high as reported [6 , 33 , 34] while this number was significantly reduced in PTX3-treated animals . In vitro , PTX3 opsonization impairs Shigella internalization in epithelial cells , which are the replicative niche of this pathogen . Likewise , PTX3 binds human cytomegalovirus and inhibits viral-cell fusion and internalization , supposedly by crosslinking of glycoproteins on viral or cellular surface [43] . PTX3 binding to Shigella might inhibit bacteria-host cell contact by interfering sterically with the T3SS machinery thereby affecting bacterial micropinocytosis . Antibodies directed against Shigella surface structures have been shown to prevent epithelial cell internalization [23 , 24 , 44 and this study] and to promote the opsonophagocytic activity in macrophages [45] . In this light , PTX3 opsonization is reminiscent of some in vitro properties of protective antibodies against Shigella external structures , thus contributing to Shigella eradication before the adaptive immune response is mounted . These features reveal a role of PTX3 as an “ante-antibody” [16 , 44] in Shigella infections . At a local level of infection , extracellular Shigella that are no longer protected by the host cell cytoplasm , can be targeted by the complement system and easily internalized by macrophages , thus improving the bacterial clearance by the tissues as we observed in lungs of PTX3-treated mice . Indeed , Shigella is sensitive to the serum bactericidal activity ( this study ) , and low concentrations of PTX3 increase the killing activity of complement . It is unsurprising that PTX3 contributes to complement activity only at low concentrations given that it can play a double role , either by activating the three complement pathways or by negatively regulating them through various mechanisms , thereby limiting complement-mediated inflammation [21] . Moreover , the architecture in lungs of M90T-only infected animals was destroyed by dramatic inflammation mainly characterized by a massive neutrophil infiltration . In these mice , high levels of TNF-α and chemokines such as CXCL1 and CXCL2 , which act as potent neutrophil chemoattractants [46] , contribute to lung injury . In Ptx3-/- infected mice the inflammatory response seemed to be exacerbated , as the production of TNF-α , CXCL1 and CXCL2 was significantly higher than in wild type animals . In contrast , in lungs of PTX3-treated infected mice low levels of CXCL1 and CXCL2 were associated with few areas filled by a neutrophilic exudate . PTX3 can also directly contribute to local regulation of the inflammatory reaction based on neutrophil infiltrate as it binds to the adhesion molecule P-selectin and inhibits leukocyte rolling in the endothelium [47] . Although these findings sound very encouraging a definitive result could be achieved through a genetic rescue with transgene expression in Ptx3-/- infected mice or alternatively through administration of recombinant Ptx3 to these animals . In the M90T-infected wild type mice , the serum level of PTX3 was between 10 to 20 ng/mL after 72 h of infection , which was in the range of that observed in the plasma of shigellosis patients and in patients of aspergillosis ( 12 ) . Likewise , the levels of PTX3 in BAL were in the range of that recorded in BAL ( 2–10 ng/mL ) of mice infected with A . fumigatus ( 25 ) or with influenza virus ( 31 ) as both pathogens are very sensitive to the protective effect of PTX3 . These findings arise the question of whether PTX3 could play a role during natural infection in humans . In clinical trials with a S . dysenteriae 1-attenuated but still invasive vaccine , no PTX3 increase was observed in the plasma of vaccinated individuals , [48] suggesting that only invasion of the epithelial layer by Shigella is not sufficient to rise the amount of PTX3 at the systemic level . In contrast to the attenuated strains , which are likely confined to the epithelial layer , fully virulent shigellae break the integrity of the epithelial barrier and penetrate into the mucosa where they induce severe inflammation characterized by a huge amount of cytokines and inflammatory factors , which can act as signals to promote PTX3 release . In line with this issue , in plasma of patients with shigellosis ( infected with S . sonnei ) the levels of PTX3 correlate positively with the severity of symptoms , particularly with high temperature and blood in the stools being a reliable parameter of severity of shigellosis , just as in conditions like sepsis [49] and critical infections [50] . As it seemed that Shigella invasion alone poorly promotes the production of PTX3 , we analyzed PTX3 release in vitro upon Shigella infection . Epithelial cells , macrophages , DCs and neutrophils that contribute to Shigella-mediated inflammation have all been described as producers of PTX3 . In vitro intestinal cells such as Caco-2 cells do not release PTX3 and only increase their mRNA expression upon exposure to bacteria and bacterial moieties [51] . Likewise , Shigella-infected Caco-2 cells did not produce detectable levels of PTX3 ( S7A Fig ) . Moreover , bronchial epithelial cells express and produce PTX3 upon TNF-α trigger , but not following bacterial PAMP stimulation ( such as LPS ) [52] . We could suggest that in natural and experimental shigellosis , epithelial cells cannot or barely produce PTX3 upon initial bacterial contact . PTX3 is likely to be released only when inflammatory signals like TNF-α and especially IL-1β are present . Upon inflammatory activation , neutrophils release about 25% of their pre-formed PTX3 content in lactoferrin granules [53] . In lung sections of infected animals , neutrophils were strongly immunostained for PTX3 . Neutrophils recruited by inflammatory mediators could constitute a main source of PTX3 upon Shigella invasion under in vivo conditions . In contrast to epithelial cells , Shigella-infected macrophages and DCs produce PTX3 . However , virulent/invasive shigellae induce lower levels of PTX3 than do non-invasive/avirulent shigellae in these cells , suggesting that phenotypes associated with invasiveness play a major role in controlling PTX3 production . LPS is a main Shigella trigger in macrophages and DCs , eliciting PTX3 production . In contrast to UPEC-infected cells that secrete PTX3 upon LPS-TLR4/MyD88 activation , both TLR4 mediated pathways , MyD88 and Trif , participate in PTX3 production in Shigella-infected macrophages and DCs . Involvement of the TriF pathway is evident as the absence of Trif or Irf3 abrogates and massively reduces the PTX3 release in BMDMs and BMDCs , respectively . The role of IRF3 in PTX3 production has already been observed in the context of tissue repair and remodeling [54] . In Shigella-infected BMDMs , Irf3 is not involved in TNF-α production , thereby suggesting that the PTX3 and TNF-α downstream signaling pathways diverge upon LPS-TLR4 activation . The composition of LPS finely modulates PTX3 production , in accordance with the degree of acylation . Hypo-acylated LPS derived from intracellular shigellae stimulates a reduced release of PTX3 with respect to hexa-acylated LPS extracted from bacteria grown under conventional conditions , as also reported for cytokine production [8] . The impact of LPS composition present on live bacteria on PTX3 and TNF-α yield is particularly evident in human cells . Under some experimental conditions , LPS composition tuned PTX3 production more finely than TNF-α production . This result strongly links PTX3 production to LPS composition also in different physiological and pathological contexts . In conclusion , at a local level of Shigella infection , PTX3 could tip the balance toward bacterial eradication playing a double role: on the bacterial side , it helps to reduce epithelial cell invasion , to implement macrophage phagocytosis and to favor complement activity; on the host tissue side , it contributes to the prevention of the development of the destructive inflammation , which is a main feature of shigellosis . This immune evasion behavior can favor bacterial survival and proliferation , thus allowing tissue colonization during the initial phases of the disease . We suggest that PTX3 could potentially contribute to the eradication of the infection by targeting the poorly explored extracellular phase of the invasion process , which can be considered the “Achille heels” of Shigella invasion process .
M90T: wild type S . flexneri strain ( serotype 5a ) ; BS176: plasmidless , non-invasive M90T derivative [55]; M90T ΔipaB: non-invasive T3SS mutant [19]; M90T ΔmsbB1 ΔmsbB2: LPS mutant which lacks both copies of the msbB genes ( msbB1 and msbB2 ) , each of which encodes the enzyme myristolyl transferase . M90T ΔmsbB1 ΔmsbB2 carries a hypo-acylated lipid A [8 , 38] . M90T-GFP was created by transforming wild type strains with TGI pFpV25 . 1 vector [56] . The Shigella sonnei wild type strain has been described by Rossi [57] . Bacteria were routinely grown in Trypticase soy broth ( TSB ) ( BBL , Becton Dickinson and Co . , Cockeysville , MD ) or agar ( TSA ) . TSA containing 100 mg of Congo Red dye ( Cr ) per liter was used to select virulent clones of Shigella . Streptomycin ( Sm ) and ampicillin ( Ap ) were added to cultures at 100 μg/mL . For the PTX3 binding assay a Pseudomonas aeruginosa wild type laboratory strain , PAO1 was used as a positive control . The procedure was carried out as originally described with minor modifications [12] . A total of 107 CFU were incubated in 50 μl HBSS ( Hank’s Balanced Salt Solution ) with 0 . 5% BSA and biotinylated PTX3 ( 50 μg/mL ) ( 1 . 1 μM , ) [15] or biotinylated BSA ( 70 μg/mL ) . After 1 h at room temperature , samples were extensively washed with HBSS . Samples were incubated in 100 μL HBSS with 0 . 5% BSA with streptavidin-FITC anti-mouse Ig ( 1:1000 ) ( BD , Pharmingen ) . Binding was evaluated by fluorescence-activated cell sorting ( FACS ) . Normal human serum ( NHS ) was produced from buffy coats obtained by the blood bank of Sapienza University and was collected from 10 healthy adult volunteers ( blood donors ) with no history of shigellosis following written informed consent . The blood was allowed to clot , and the serum was subsequently harvested , pooled , and stored at -70°C until used . Heat-inactivated serum ( HIS ) was generated by incubating NHS for 1 h at 56°C . Exponential phase bacteria were suspended in Dulbecco's Phosphate-Buffered Saline ( DPBS ) with Mg2+ and Ca2+ and incubated at 37°C for 30 min in the presence of NHS or HIS . Bacterial survival was calculated as CFU in the presence of NHS/CFU in the presence of HIS x 100 . HeLa cells ( ATCC Cell Biology Collection ) were seeded on 6-well plates ( 8 x 104 cells/mL ) and allowed to adhere for 12 h . An amount of 108 CFU of wild type M90T in early exponential phase ( OD600 0 , 4–0 , 6 ) were incubated in either DMEM ( Gibco , Life technologies ) only or with PTX3 ( 50 μg/mL ) or anti-IpaD Ab or BSA ( 50 μg/mL ) or with PTX3 and BSA at the same time for 1 h at 37°C and then used to infect HeLa cells at MOI 50 . After 60 min , cells were washed three times with PBS and incubated for an additional 1 or 2 h . Cells were washed three more times with PBS , detached with trypsine , counted and lysed with deoxycholic acid ( 0 , 5% in H2O ) . Cell lysate was plated on Congo Red ( 0 , 1% ) containing TSB agar plates and CFU were counted after 18 h of incubation . C57BL/6 female mice from Charles River , Calco , Italy , were maintained in a specific pathogen-free animal facility of the University of Camerino and euthanized by cervical dislocation . Myd88-/- , Trif-/- , Irf3-/- or Cd14-/- were a kind gift of Maria Rescigno ( Myd88-/- ) , IFOM-IEO Campus , Milan , Italy and Francesca Granucci ( Trif-/- , Irf3-/- or Cd14-/- ) , Università degli Studi di Milano-Bicocca , Milan , Italy . Ptx3-/- were generated as described [12] Wild-type and mutant BMDMs and BMDCs were derived from bone marrow cells collected from five-week-old female mice , as already reported [8] and as detailed as follows . BMDCs ( bone barrow derived dendritic cells ) were differentiated for 7 days in RPMI 1640 ( Lonza , Italy ) containing 10% heat inactivated fetal bovine serum ( FBS ) ( Gibco , Life technologies ) , 100 μM non-essential amino acids , 1000 U/mL penicillin and 1000 U/mL streptomycin ( all from Lonza , Italy ) , supplemented with 30% R1 , containing fibroblast produced GM-CSF , as described [58] . After 7 days , BMDCs were characterized by immunostaining with CD11b , CD11c , CD80 , CD86 , MHCII monoclonal antibodies ( all from BD Pharmingen , Italy ) through a flow cytometric analysis on a FACSCalibur cytometer ( Becton Dickinson , San José , CA , USA ) . Data acquisition ( 104 events for each sample ) was performed using CellQuest software ( Becton Dickinson , San José , CA , USA ) . Analysis was performed with FlowJo software ( TreeStar Inc . , Ashland , USA ) . BMDC infections with S . flexneri strains and S . sonnei were carried out at MOI 10 . Infected BMDCs were incubated for 2 h before washing and adding gentamicin ( 60 μg/mL ) ( Gibco ) . Cells were incubated for further 1 h , 3 h , 6 h and 18 h post infection ( p . i . ) and supernatants were collected and analyzed for PTX3 and TNF-α release . When indicated , cytochalasin D was added 1 h before infection ( 0 , 4 μg/mL ) ( Invivogen ) . Alternatively , bacteria were killed by gentamicin ( 60 μg/mL ) treatment for 1 h and added to BMDCs at MOI 10 . The supernatants were then collected for ELISA at different time points ( 1 h , 3 h , 6 h and 18 h ) . For LPS stimulation BMDCs , cells were seeded on 12-well plates ( 5 x 105 cells/well ) . LPS stimulation was carried out with: LPS derived from intracellular shigellae ( iLPS ) , shigellae grown in TSB medium ( aLPS ) and M90T ΔmsbB1msbB2 LPS , as described , [8] and commercial E . coli LPS ( LPS ultrapure–EB; InvivoGen ) at the concentration of 1 and 10 ng/mL for 18 h . Supernatants were collected for ELISA analysis . BMDMs ( bone barrow derived macrophages ) were differentiated for 8 days in RPMI 1640 ( Lonza , Italy ) containing 10% heat inactivated FBS , 100 μM non-essential amino acids , 1 mM sodium pyruvate , 1000 U/mL penicillin and 1000 U/mL streptomycin ( all from Lonza , Italy ) , supplemented with 30% L929 fibroblast supernatant , containing M-CSF ( Macrophage-Colony Stimulating Factor ) . F4/80 and CD11b double-positive cells were considered as differentiated BMDMs and used in the experiments . For stimulation assay , differentiated BMDMs were seeded on 24-well plates ( 5 x 105 cells/well ) and exposed to different concentrations ( 1 , 10 , or 100 ng/mL ) of M90T iLPS , aLPS , and M90T ΔmsbB1msbB2 LPS , as described , [8] and commercial E . coli LPS ( LPS ultrapure–EB; InvivoGen ) . Stimulation was carried out for 6 h and 18 h . Cell supernatants were recovered and stored at -20°C to be used in the ELISA assay . BMDM infections assay with S . flexneri and S . sonnei strains were performed as reported [8] with minimal differences . Briefly , bacteria were used at MOI 10 on cells pre-treated or not for 4 h with Shigella iLPS , aLPS , ΔmsbB1 ΔmsbB2 LPS and E . coli LPS at the concentration of 10 ng/mL . Infected BMDMs were incubated at 37°C for 1 h , washed twice with PBS , and treated with gentamicin ( 60 μg/mL ) for 3 h . At this time , supernatants were analyzed for PTX3 and TNF-α release . PBMCs ( peripheral blood mononuclear cells ) were isolated from buffy coats obtained by the blood bank of Sapienza University from healthy adult volunteers ( blood donors ) following written informed consent . PBMCs ( peripheral blood mononuclear cells ) were obtained from blood of healthy adult volunteers ( blood donors ) , through a density gradient . CD14+ monocytes were isolated using the MACS microbead system ( Miltenyi Biotec , Bergisch Gladbach , Germany ) . The monocytes were cultured for 6 days in RPMI 1640 ( Lonza ) supplemented with 10% heat-inactivated FBS ( Euroclone Fetal Bovine Serum , GE Healthcare Life Sciences , U . S . ) , 100 μM non-essential amino acids , 1 mM sodium pyruvate , 1000 U/ml penicillin and 1000 U/mL streptomycin ( all from Lonza , Italy ) and 50 ng/mL GM-CSF ( Granulocyte-Macrophage Colony-Stimulating Factor ) ( Miltenyi Biotec ) to obtain human macrophages . Stimulation assays: MoMs ( peripheral blood monocyte-derived macrophages ) were seeded in 24-well plates ( 2 , 5 x 105 cells/well ) , exposed to 1 ng/mL of LPS derived from intracellular shigellae ( iLPS ) , shigellae grown in TSB medium ( aLPS ) , Shigella ΔmsbB1 ΔmsbB2 LPS and commercial E . coli LPS ( LPS ultrapure–EB; InvivoGen ) and incubated for 12 h . Cell supernatants were recovered and processed for ELISA . MoM infection assays with Shigella M90T strain , its derivatives BS176 and M90T ΔmsbB1 ΔmsbB2 strains , and S . sonnei strain were performed using MOI 0 , 1 on cells pretreated or not with Shigella iLPS , aLPS , ΔmsbB1msbB2 LPS and commercial E . coli LPS ( LPS ultrapure–EB; InvivoGen ) for 4 h ( 0 , 1 ng/mL ) . Infected macrophages were incubated at 37°C for 1 h , washed twice with PBS solution , and treated with gentamicin ( 60 μg/mL ) for 3 h . Supernatants were recovered and evaluated by ELISA . For infection with PTX3 treated bacteria , shigellae were incubated with PTX3 or BSA ( 50 μg/mL ) or a polyclonal rabbit anti-IpaD antibody ( 5 μL ) ( gift of Abdel Allaoui ) for 1 h at 37°C . MOI 5 was used for 2 h . MoDCs were infected with bacteria at MOI of 10 . MoM death evaluation: 108 M90T were opsonized with recombinant PTX3 ( 50 μg/mL ) , BSA ( 50 μg/mL ) or anti-IpaD Ab or nothing for 1 h at room temperature and then used to infect MoMs at MOI 5 for 2 h before evaluation of lactate dehydrogenase ( LDH ) release in supernatant . LDH was measured through the CytoTox 96 Non-Radioactive Cytotoxicity Assay kit ( Promega , USA ) , according to manufacurer’s instruction . To adjust for spontaneous lysis , % release was calculated as follows: ( Release in sample–release from non-infected cells ) / ( maximum release–release from non-infected cells ) * 100 . Phagocytosis Assay: percentage of bacterial internalization by MoMs was evaluated through cytofluorimetric analysis . CD14 was used as MoM marker , and cells positive for both GFP and CD14 were considered infected cells . Data acquisition ( 104 events for each sample ) was performed using CellQuest software ( Becton Dickinson , San José , CA , USA ) . Analysis was performed with FlowJo software ( TreeStar Inc . , Ashland , USA ) . Dendritic cells . MoDC ( peripheral blood monocyte-derived dendritic cell ) culture , stimulation and infection . PBMCs were obtained from blood of healthy adult volunteers ( blood donors ) , through a density gradient as above . CD14+ monocytes were isolated using the MACS microbead system ( Miltenyi Biotec , Bergisch Gladbach , Germany ) . The monocytes were cultured for 5 days in RPMI 1640 ( Lonza ) supplemented with 10% heat-inactivated FBS ( HyClone Fetal Bovine Serum , GE Healthcare Life Sciences , U . S . ) , 100 μM non-essential amino acids , 1000 U/mL penicillin and 1000 U/mL streptomycin ( all from Lonza , Italy ) , 20 ng/mL IL-4 and 50 ng/mL GM-CSF ( both Miltenyi Biotec ) to obtain immature human dendritic cells . MoDCs were characterized by immuno-staining with CD11c , CD14 and CD80 ( all from BD Pharmingen , Italy ) through a flow cytometric analysis . For MoDC stimulation , MoDCs were collected , seeded on 12-well plates ( 5 x 105 cells/well ) and exposed to 10 ng/mL of iLPS , aLPS , M90T ΔmsbB1 ΔmsbB2 LPS and E . coli LPS for 12 h . For MoDC infections , cells were seeded at 5 x 105 cells/well on the morning of infection . Exponential phase bacteria were added at MOI 10 directly to the wells containing MoDCs . Plates were centrifuged for 5 min at 300 x g and incubated at 37° C for 2 h . Fresh medium containing gentamycin ( 60 μg/mL ) was added , and cells were incubated for further 1 h , 3 h , 6 h and 18 h . Five-week-old ( 18–20 gr ) C57BL/6 female wild type ( Charles River , Calco , Italy ) or Ptx3-/- mice were maintained in a specific pathogen-free animal facility of the University of Camerino . For all the infections , mice were anesthetized intramuscularly with 50 μL of a solution containing Zoletil ( 1 mg ) ( Virbac , Carros , France ) and Xilor ( 2% ) ( BIO 985 , San Lazzaro , Italy ) and inoculated intranasally with 20 μL of 0 . 9% NaCl suspensions containing 3 x 108 CFU of S . flexneri M90T strain [47 , 6] . When required , infected mice ( wild type ) were treated once per day for 3 days with recombinant PTX3 ( 10 μg/mouse intraperitoneally , 0 , 5 mg/Kg , corresponding to 11 μM ) or with sterile saline and examined daily to evaluate the survival during 8 days ( n = 22 for M90T-infected-mice , n = 19 for M90T-infected and treated-mice , n = 10 for non-infected PTX3-treated mice , in three separate experiments ) , or euthanized at 3 days post-infection ( n = 10 for M90T-infected-mice and n = 11 for M90T-infected and treated-mice , n = 10 for non-infected PTX3-treated mice , in three separate experiments ) . At this time , bronchoalveolar lavages ( BAL ) were performed and BALs were used for cytokine analysis . Lungs were removed , homogenized and plated on TSA plates ( 1 lung per mice ) or analyzed for relevant cytokines or alternatively fixed in formalin . Consecutive sections from the middle of the five lung lobes were used for histological and immunohistochemical examination . In the experiments using Ptx3-/- mice survival was analyzed up to 8 days p . i . ( n = 30 , in three separate experiments ) and their lungs were processed to assess the bacterial load and cytokine production at 48 h p . i . ( n = 10 Ptx3-/-; mice n = 13 wild type ) , in three separate experiments ) . Lungs samples were fixed in 4% formaldehyde for 18 h at room temperature and treated for histopathological and immunochemistry studies as described [6] . The samples were gradually dehydrated and then embedded in paraffin . The specimens were cut in 3-μm-thick slices and stained with hematoxylin-eosin ( Carlo Erba ) or immunostained . Immunohistochemistry was performed by using the following antibodies: rabbit polyclonal anti-human PTX3 [14] . and mouse monoclonal anti-PMNs ( MA5-12607 , clone BM-2 , ThermoFisher Scientific , USA ) . The sections were incubated with the secondary antibodies ( 1:200 ) for 45 minutes and then examined blindly and scored by a pathologist . Cytokine and chemokine concentrations were determined by commercially available ELISA kits ( Duo Set R&D systems ) . The absorbance was measured on a LT-4000 Microplate reader ( Labtech ) ( Hercules , CA , USA ) . The LPSs used in this study are the same as those used by Paciello [8] . Refer to this article for relevant information about the experimental procedures for LPS extraction and purification . 31 patients in the acute stage ( 0–7 days after onset ) of culture-proven S . sonnei shigellosis were recruited for the study . They included 31 children aged 0 . 2–10 years and one adult . The control group included 19 healthy subjects , 11 adults and 8 children aged 0 . 5–14 years . Signed informed consent was obtained from the parents of all participating children and from all participating adults . Participants or their parents completed a questionnaire with personal data and details regarding symptoms and onset of disease . Blood samples were collected using EDTA tubes ( Geiner Bio-One ) . Plasma was separated and stored at -80 oC until assayed . Data was presented as mean ± S . D . , and the number of independent experiments is indicated in each legend of the figures . Statistics were performed with GraphPad Prism and data analysis was carried out as follow: Mantel-Cox test was used to compare survival curves; non-parametric Mann-Whitney U test for CFU counts and cytokine/chemokines quantification in mice; Student's t-test for PTX3 and TNF-α release in cell cultures and paired t-test for PTX3 quantification in plasma of patients . P < 0 . 05 was considered significant . Mice experiments were conducted according to the ethical requirements of the Animal Care Committee of the University of Camerino ( study protocol No 17/2012 ) upon approval of the Ministero della Salute , Direzione Generale della Sanità Animale e dei Farmaci Veterinari , Ufficio VI ( Benessere animale ) , in line with the Guidelines laid down by the European Communities Council ( 86/609/ECC ) for the care and use of laboratory animals . The study involving shigellosis patients and controls has been has been approved by the IRBs of Hillel Yaffe Medical Center and the Israel Ministry of Health ( Study protocol No . AH-382-11 ) . Written signed informed consent was obtained from the parents of all participating children and from all participating adults . PBMCs ( peripheral blood mononuclear cells ) were isolated from buffy coats obtained by the blood bank of Sapienza University from healthy adult volunteers ( blood donors ) following written informed consent .
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Soluble pattern recognition molecules , PRMs , are components of the humoral arm of innate immunity . The long pentraxin 3 , PTX3 , is a prototypic soluble PRM that is produced in response to primary inflammatory signals . Shigella spp . are human entero-pathogens which invade colonic and rectal mucosa where they cause deleterious inflammation . We show that PTX3 acts as an ante-antibody and contributes to the clearance of extracellular Shigella . As a countermeasure , Shigella uses invasiveness and low-inflammatory LPS to control PTX3 release in infected cells . This study highlights that the extracellular phase of the invasion process can be considered the “Achille heels” of Shigella pathogenesis .
|
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2018
|
Role of a fluid-phase PRR in fighting an intracellular pathogen: PTX3 in Shigella infection
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Chemokines and their receptors ( members of the GPCR super-family ) are involved in a wide variety of physiological processes and diseases; thus , understanding the specificity of the chemokine receptor family could help develop new receptor specific drugs . Here , we explore the evolutionary mechanisms that led to the emergence of the chemokine receptors . Based on GPCR hierarchical classification , we analyzed nested GPCR sets with an eigen decomposition approach of the sequence covariation matrix and determined three key residues whose mutation was crucial for the emergence of the chemokine receptors and their subsequent divergence into homeostatic and inflammatory receptors . These residues are part of the allosteric sodium binding site . Their structural and functional roles were investigated by molecular dynamics simulations of CXCR4 and CCR5 as prototypes of homeostatic and inflammatory chemokine receptors , respectively . This study indicates that the three mutations crucial for the evolution of the chemokine receptors dramatically altered the sodium binding mode . In CXCR4 , the sodium ion is tightly bound by four protein atoms and one water molecule . In CCR5 , the sodium ion is mobile within the binding pocket and moves between different sites involving from one to three protein atoms and two to five water molecules . Analysis of chemokine receptor evolution reveals that a highly constrained sodium binding site characterized most ancient receptors , and that the constraints were subsequently loosened during the divergence of this receptor family . We discuss the implications of these findings for the evolution of the chemokine receptor functions and mechanisms of action .
Directed cell migration is fundamental for life because this process is involved in key biological processes such as embryonic development , organogenesis , immune surveillance , host defense , and wound repair . Leukocyte migration and tissue localization during homeostatic and inflammatory conditions depend directly upon chemokines ( or chemotactic cytokines ) , a family of small secreted proteins . Chemokines implement their functions by acting through specific receptors belonging to the family of class A ( rhodopsin-like ) G-protein-coupled receptors ( GPCRs ) . The human chemokine-receptor system is composed of forty-five chemokines and twenty-two receptors , with complex specificity/promiscuity pattern [1] . Some chemokine-receptor pairs are highly specific but most chemokines and receptors can be involved in different pairings . This system has a highly positive developmental and protective role in physiological conditions but it is also implicated in a broad array of pathologies , including autoimmune and inflammatory diseases , allergies , cancer metastasis , and HIV infection . Therefore , the chemokine-receptor system is an attractive target for drug development [1 , 2] . Among the chemokine receptors , CXCR4 and CCR5 have been extensively studied because of their role as co-receptors of HIV for virus entry . Chemokines are structurally classified as CC , CXC , C3XC , and C chemokines , based on the arrangement of the N-terminal disulfide forming cysteines . Chemokines can also be classified according to their main function [3] . The homeostatic chemokines are involved in homing of lymphocytes in physiological conditions , whereas inflammatory chemokines are involved in attracting lymphocytes in inflammatory area ( note that some chemokines have dual functions ) . Chemokine receptors can be classified by phylogeny into two groups . The oldest group , which appeared in jawless fishes , binds mainly homeostatic chemokines while the most recent group , which appeared in jawed vertebrates , bind mainly inflammatory chemokines [3 , 4] . The “atypical” chemokine receptors with promiscuous chemokine binding are phylogenetically related to either one of these groups . Previously called decoys or scavengers , these atypical receptors usually act as β-arrestin biased receptors that do not promote migration but rather shape chemokine gradients to permit migration induced by conventional chemokine receptors [5] . Several structures of chemokine receptors , in inactive or pseudo-active forms , bound to chemical ligands or chemokines , have been resolved [6–11] and have provided invaluable information on the mechanism of action of these receptors . Details of the mechanism of chemokine binding to cognate receptors are emerging with the analysis of the recent structures of chemokine-receptor complexes [6 , 9] . The structure of these complexes corroborates the insertion of the chemokine N-terminus into the receptor helical core and the plasticity of the chemokine receptors to adapt to different ligands . Because of the wide variety of diseases in which chemokine receptors are implicated , chemokine receptors constitute very attractive targets for the pharmaceutical industry . However , despite important investments , only two drugs targeting chemokine receptors have received Food and Drug Administration approval for clinical use: maraviroc , which targets CCR5 in HIV/AIDS treatment , and plerifaxor , which targets CXCR4 for hematopoietic stem cell mobilization . Difficulties in targeting chemokine receptors for anti-inflammatory therapy may arise from inappropriate target selection and ineffective dosing or from the redundancy of the chemokine system [12] . Recent advances in the understanding of chemokine signaling have shown that this apparent redundancy hides biased signaling . The activation of the same receptor by different chemokines may induce different cellular issues [13] . This observation indicates a system more complex than initially thought . In addition , the effect of a ligand may depend on the presence of different chemokines and of the cellular system or tissue under investigation [1] . Finally , the chemokine/receptor system is species-specific and may lead to different results in mouse/rat trials compared to humans . Taken together , these additional levels of complexity make pharmacodynamics and pharmacology studies very difficult for therapeutic applications . Understanding the molecular determinants involved in functional specificity of chemokine receptors could help the rational design of drugs targeted towards this important receptor sub-family . Evolutionary information , based on analysis of multiple sequence alignment ( MSA ) can be used to gain structural and functional information on protein families . Previously , we have used evolutionary information to successfully predict the kinked structure of the transmembrane helix 2 ( TM2 ) in chemokine receptors prior to their crystallization [14] . These receptors are part of a larger sub-family , the chemotaxic ( CHEM ) sub-family in Fredriksson’s classification , which includes different chemotaxic and vasoactive receptors [15] . We have shown that the CHEM sub-family , along with the PUR sub-family of purinergic receptors , evolved by divergence from the somatostatin/opioid ( SO ) receptor sub-family in vertebrates , and that the latter sub-family evolved from the deletion of one residue in TM2 in an ancestral receptor [14 , 16] . Receptors from these three sub-families possess a characteristic P2 . 58 pattern ( Ballesteros’ numbering ) which corresponds to one of the main GPCR evolutionary pathways [16 , 17] . In the present study , we investigate the evolutionary determinants of chemokine receptors using principal component analysis of sequence covariations in nested GPCR sequence sets . This approach highlights three residues whose mutations were crucial for the emergence of chemokine receptors and their subsequent divergence into homeostatic and inflammatory receptors . These key residues are located at the binding site of a sodium ion which is thought to be a general feature amongst class A GPCRs [18 , 19] . To further define the structural/functional role of these residues , we carried out molecular dynamics ( MD ) simulations of the chemokine receptors CCR5 and CXCR4 , chosen as prototypes of homeostatic and inflammatory chemokine receptors . We show that the evolution of chemokine receptors was driven , at least in part , by dramatic changes in the sodium binding mode . Most ancient receptors , which appeared in jawless fishes , have a highly constrained sodium binding site . These constraints were subsequently loosened during the divergence of this receptor family . We discuss the implications of these findings in terms of evolution of the chemokine receptor functions and mechanisms of action .
To highlight residues characterizing chemokine receptors , we applied a hierarchical approach to search residues characteristic of the four nested sets of human sequences that lead from class A receptors to the chemokine receptor sub-family . These sets correspond to: ( 1 ) class A GPCRs , ( 2 ) the P2 . 58 receptors ( SO , CHEM and PUR sub-families ) , ( 3 ) the CHEM sub-family and ( 4 ) the chemokine receptor sub-family . Sequence sets were prepared as described in Methods . They are visualized on the Neighbor Joining ( NJ ) tree of human receptors shown in Fig 1A . In a previous study [17] , we have analyzed the sequence covariation in the multiple sequence alignment ( MSA ) of human class A GPCRs . The network representation of the top pairs with highest covariation scores highlighted the central role of position 2 . 58 as an evolutionary hub . This representation provides information on positions that covary with the P2 . 58 pattern . However , this arrangement is dependent on the number of top pairs selected . To obtain a representation of the covariation data independent of a user selected parameter , we carried out the principal component analysis ( PCA ) [20] of the double-centered covariation matrix ( specifically , an eigen-decomposition of this matrix ) , obtained from the MSA of human class A GPCRs ( S1 File ) . Fig 1B shows the positions in the MSA plotted in the plane formed by the first two components of the PCA . This analysis highlights a few positions clearly separated on the first and the second axes . The position with the highest coordinate on the first component is 2 . 58 . Next are positions 2 . 57 and 2 . 59 , then positions 1 . 46 , 3 . 35 , 4 . 46 , and 2 . 45 . These positions have the top covariation scores with position 2 . 58 [17] . On the second dimension , residues with highest coordinates are positions 7 . 49 , then 6 . 48 and 1 . 53 . These positions correspond to hallmark residues that led to the divergence of the PUR sub-family . Indeed , positions 7 . 49 and 6 . 48 are highly conserved Asn and Trp in most class A GPCRs , but are Asp and Phe in the PUR sub-family . Likewise , position 1 . 53 is usually Val in most GPCRs but Ala in PUR receptors . Proline 2 . 58 is the hallmark residue of the SO , CHEM , and PUR sub-families . This pattern results from the deletion of one residue located two positions upstream of the TM2 proline in an ancestral P2 . 59 receptor [14] . The covariation of positions 2 . 57 and 2 . 59 with position 2 . 58 is a consequence of the indel mechanism . Logo representation of amino acid distribution ( Fig 1D ) indicates an increase in the frequency of Gly and Asn at positions 1 . 46 and 2 . 45 , respectively , and a small polar residue instead of an aliphatic residue at position 4 . 46 in P2 . 58 receptors . In addition , position 3 . 35 is Asn in most P2 . 58 receptors while this amino acid is absent at this position in the complementary set . The next step was to apply the same approach to the MSA of the human CHEM sub-family ( S2 File ) . This analysis ( Fig 1C ) highlights residues associated with the divergence of chemokine receptors on the first component and the split between homeostatic and inflammatory receptors on the second component . Position 3 . 57 , at the limit between TM3 and ICL2 , is an alanine in chemokine receptors and a proline in other CHEM receptors ( Fig 1E ) . However , we can note that the presence of Pro or Ala at this position is a common feature of human class A GPCRs ( Fig 1D ) , a pattern which suggests a role in the interaction with G proteins . Most interestingly , position 7 . 45 in TM7 is either His or Arg in chemokine receptors , which is very infrequent in other human GPCRs ( 2% ) . Position 7 . 45 is preferentially Asn in class A receptors ( 67% ) . The second component highlights positions 2 . 49 and 3 . 35 . We have previously shown that position 2 . 49 differentiates homeostatic and inflammatory receptors ( A2 . 49 and S2 . 49 , respectively ) [17] . This position is strongly correlated with position 3 . 35 , which is preferentially Asn and Gly in homeostatic and inflammatory receptors , respectively ( Fig 1F ) . The position of these hallmark residues in the structure of CXCR4 and CCR5 , as prototypes of homeostatic and inflammatory chemokine receptors , is displayed in Fig 1G and 1H . Polar positions 2 . 45 and 4 . 46 are located on the external surface of the receptor at the interface with the membrane . These two positions face each other and may be involved in polar interactions . Indeed , in the crystal structure of CCR5 , S4 . 46 is involved in H-bonding with N2 . 45 . Most interestingly , positions 2 . 49 , 3 . 35 , and 7 . 45 are clustered in the receptor core and line the allosteric sodium binding pocket . Among them , positions 3 . 35 and 7 . 45 can be directly involved in the coordination of the sodium ion [18] . In the two crystal structures of sodium bound P2 . 58 receptors , the δ-opioid receptor ( OPRD , PDB entry 4N6H ) [21] and the proteinase activated receptor 1 ( PAR1 , PDB entry 3VW7 ) [22] , positions 3 . 35 and 7 . 45 participate in sodium binding , either directly ( N3 . 35 in OPRD ) or through a water molecule ( N7 . 45 in OPRD and N3 . 35/S7 . 45 in PAR1 ) . This ion acts as a negative modulator of GPCRs and stabilizes the inactive structure [18] . Mutations of N3 . 35 to smaller residues ( Ser or Ala ) in CXCR4 [23] and CXCR3 [24] yield constitutively active mutants . In the closely related angiotensin II receptor AT1 , the N3 . 35G mutant has also high constitutive activity [25] . The presence of a glycine residue at position 3 . 35 in inflammatory chemokine receptors is thus surprising , and this prompted us to investigate the history of position 3 . 35 . Covariation can result either from phylogenetic history with the correlated residues already present in the common ancestor ( or in an early step of subsequent evolution ) and maintained throughout evolution or from an epistasis mechanism in which several correlated mutations led to functional divergence in the receptor family . Differentiation between the two mechanisms requires the analysis of the GPCR repertoires from different species covering several animal phyla . The CHEM and PUR sub-families are specific to vertebrate species [14 , 16] . The N3 . 35 pattern is present in vertebrate SO receptors as exemplified by the opioid receptors . Thus , we analyzed the amino acid distribution at position 3 . 35 in the SO sub-family from different species: H . sapiens , D . rerio , B . floridae , C . elegans , N . vectensis and T . adhaerens ( S3 File ) and reported it on the NJ tree of these receptors ( Fig 2A ) . The N3 . 35 pattern is not present in the receptors from non bilaterian species ( N . vectensis and T . adhaerens ) , but polar residues ( S , T ) at this position are observed in sequences from N . vectensis . The N3 . 35 pattern is present in a few sequences from C . elegans , and in almost all chordates sequences . Interestingly , orthologs of the urotensin II receptor ( UR2R in Uniprot nomenclature ) are present in B . floridae . This is the first observation of UR2R in an invertebrate species . The small sub-family containing UR2R ( Fig 2A ) is characterized by the T3 . 35 pattern and is more closely related to invertebrate SO receptors , as an intermediate between chordate and non-chordate SO members . This analysis indicates that the N3 . 35 pattern , which strongly covaries with the P2 . 58 pattern in human GPCRs , is a hallmark of chordate SO receptors . The presence of N3 . 35 is correlated with the evolutionary drift of SO receptors observed by multidimensional scaling [16] , a pattern suggesting that this residue might have contributed to the evolution of the SO sub-family and its subsequent divergence . This residue , directly involved in the binding of the allosteric sodium ion in the δ-opioid receptor [21] , is present in most vertebrate SO , CHEM , and PUR receptors . This study strongly supports the assumption that the N3 . 35 pattern is secondary to the deletion in TM2 and might have been important for the evolutionary drift of P2 . 58 receptors in vertebrates . We also analyzed position 7 . 45 in the same set of SO receptors ( Fig 2A ) . In most receptors , position 7 . 45 is polar . This polar residue is usually Asn in chordates SO receptors ( B . floridae , D . rerio , H . sapiens ) , with a single observation of His in a sequence from D . rerio . This is not the case in sequences from non-chordate species in which position 7 . 45 is more variable with several examples of His in T . adhaerens and N . vectensis and an example of Arg in C . elegans . Finally , we analyzed positions 3 . 35 and 7 . 45 in the human CHEM sub-family ( Fig 2B ) . The H7 . 45 pattern is a hallmark of chemokine receptors , indicating that the mutation of this position may have been crucial for the emergence of chemokine receptors . H7 . 45 is found in 20 out of 23 chemokine receptors , while R7 . 45 is found in only three homeostatic receptors ( CXCR6 , CCR7 , and CCR10 ) . Among other CHEM receptors , position 7 . 45 is usually Asn ( 84% ) and the H7 . 45 pattern is observed only in the orphan GPR182 , closely related to ACKR3/CXCR7 and in C5aRL . In chemokine receptors , position 3 . 35 is Asn in 10 out of 12 homeostatic receptors and Gly in 8 out of 10 inflammatory receptors . In the other CHEM receptors , position 3 . 35 is either Asn ( 72% ) or Ser/Thr ( 24% ) and Gly is observed only in the orphan GPR33 receptor . To analyze the consequences of these mutations on the mechanism of sodium binding , we carried out molecular dynamics simulations of CXCR4 and CCR5 in the presence of a sodium ion which was initially positioned in the receptor models in the vicinity of D2 . 50 ( see Methods ) . After insertion of the models within a hydrated POPC bilayer , MD simulations were carried out for 420 ns . In both cases , the root mean square deviations ( RMSD ) of the Cα atoms of the transmembrane ( TM ) domain underwent a very fast increase of about 1 Å within the first nanosecond , followed by a slower phase that reached a plateau at about 1 . 7 Å after 20 to 40 ns ( Fig 3A ) . The root mean square fluctuations ( RMSF ) indicated similar magnitude of fluctuations for both receptors . As usual in GPCRs , the RMSF of the loops and the termini could reach 3–4 Å , whereas the residues in the central part of the TM helices had fluctuations below 1 Å ( Fig 3B ) . We can note that ( 1 ) the presence of three glycine residues in TM3 of CCR5 , at positions 3 . 30 , 3 . 35 and 3 . 39 , does not alter the fluctuations of this helix as compared to CXCR4 , and ( 2 ) the positions lining the sodium binding pocket ( residues 2 . 50 , 3 . 35 , 3 . 39 , and 7 . 45 ) have similar low fluctuations in both receptors . However , in spite of these similarities , striking differences were observed in the behavior of the sodium ion bound to CXCR4 and CCR5 during the simulations ( Fig 3C ) . In CXCR4 , after fast motion during the first nanosecond , the sodium ion remained stable with an average RMSD of 1 . 3 ± 0 . 3 Å . Similar results were seen for the three CXCR4 replicates . By contrast , in CCR5 , the RMSD of the sodium ion did not converge but indicated exchanges between ( at least ) two positions with RMSD of approximately 1 . 2 and 2 . 5 Å . These exchanges provided different RMSD patterns for the five CCR5 replicates carried out . Typical snapshots of the sodium ion bound to CXCR4 and CCR5 are displayed in Fig 4 . In CXCR4 , the ion is coordinated to four protein atoms ( D2 . 50:OD1 , N3 . 35:OD1 , S3 . 39:OG , N7 . 45:NE2 ) and to the oxygen atom of one water molecule . The position of the H7 . 45 ring is maintained by face-to-edge interaction with W6 . 48 in the g+ rotameric state . The second closest water molecule links the D2 . 50:OD2 atom to the backbone distortion of TM7 ( H7 . 45:O and N7 . 49:N ) , while the third one links the D2 . 50:OD2 atom to the N1 . 50:OD1 and N7 . 49: ND2 atoms . Two different binding modes of the sodium ion to CCR5 , obtained from classical MD simulations , are shown in Fig 4B and 4C . In Fig 4B , the sodium ion interacts with the OD1 atom of D2 . 50 , the NE2 atom of H7 . 45 in the g- conformation and four water molecules , an interaction resulting in a coordination number of six . In Fig 4C , H7 . 45 is now in the trans conformation . The sodium ion has a bivalent coordination with the OD1 and OD2 atoms of D2 . 50 , it also interacts with the OD1 atom of N7 . 49 and with two water molecules , resulting in a coordination number of five . To better characterize the environment of the sodium ion in CXCR4 and CCR5 , we measured the distances between the ion and the putative protein coordinating atoms ( Fig 5 ) . Receptor coordinating atoms include oxygen atoms from carbonyl , carboxyl , and hydroxyl groups , and the nitrogen atom with lone-pair electrons from imidazole rings . This nitrogen corresponds to the NE2 atom since histidine residues have been modeled in the most frequent tautomeric form with the hydrogen atom on the ND1 atom . In CXCR4 , the sodium ion remained within coordination distance of the D2 . 50:OD1 , N3 . 35:OD1 , S3 . 39:OG and N7 . 45:NE2 atoms for at least 98% of the trajectories ( Table 1 ) . No contact was observed with the D2 . 50:OD2 or the N7 . 49:OD1 atoms . In contrast to CXCR4 , the coordinating atoms of the sodium ion in CCR5 included the OD1 and OD2 atoms of D2 . 50 , the NE2 atom of N7 . 45 and the OD1 atom of N7 . 49 . Contacts with these residues could last several tenths of nanoseconds but were not stable on the sub-microsecond timescale . The ion moved between several sub-sites and its coordination was reorganized within and between trajectories . The sodium ion could have monovalent or bivalent coordination with the OD1 and/or the OD2 atoms of D2 . 50 . It could also be coordinated with the NE2 atom of H7 . 45 and with the OD1 atom of N7 . 49 ( these two interactions were mutually exclusive ) . In addition to the contacts displayed in Fig 4B and 4C , other modes of interaction were observed , for example , with water molecules bridging the sodium ion and the D2 . 50 side chain , but these modes usually involved at least one contact with D2 . 50 , H7 . 45 or N7 . 49 . Finally , the N3 . 35G and A2 . 49S mutations created a cavity in which the G3 . 35:O and S2 . 49:OG atoms might act as an additional binding site when S2 . 49 was in the trans orientation . However , only transient contacts with these atoms were observed in the CCR5 trajectories ( Fig 5 ) . Analysis of the contact frequencies highlights the variability in the sodium binding mode of CCR5 ( Table 1 ) . For both CXCR4 and CCR5 , during the contacts , the distances between the sodium ion and the coordinating atoms were similar to those observed in the crystal structures ( Table 2 ) . The analysis of the number of protein atoms coordinated to the sodium ion during the MD simulations ( Fig 6 ) corroborates the diversity of the sodium binding modes in CCR5 . This number usually varied between 1 and 3 with similar weights of about 30% but , in about 10% of the frames , no direct contact was observed . In contrast with CCR5 , the sodium ion in CXCR4 was coordinated to four protein atoms in 97 ± 2% of the trajectory frames . We also investigated the number of water molecules in the vicinity of the sodium ion . In approximately 85% of the CXCR4 trajectory frames , the coordination of the sodium ion was completed by the oxygen atom from a single water molecule ( Fig 4A ) . In the remaining frames , a second water molecule was present in the first coordination shell of the ion . This water molecule , which was hydrogen-bonded to N3 . 35:ND2 and L2 . 26:O upon interaction with the sodium ion , was located between TM2 , TM3 , and TM4 . For CCR5 , the number of water molecules in the first shell of the sodium ion varied from 2 to 5 . The total coordination number ( Fig 6C ) did not display such variability with an average value of 5 . 4 ± 0 . 2 for CCR5 , to be compared to 5 . 1 ± 0 . 1 for CXCR4 . These values are consistent with data mining analysis of the sodium environment in proteins [26] . Finally , to further characterize the sodium binding site , we calculated the radial distribution function of water around the sodium ion in CXCR4 and CCR5 ( Fig 6D ) . Comparison of these distribution functions highlights the differences between the CXCR4 and CCR5 sodium binding pockets . For CXCR4 , in addition to the water molecules in the first coordination shell of the ion at a distance of about 2 . 5 Å , only two water molecules could be present at a distance of about 5 and 6 . 5 Å to the sodium ion , as observed in the snapshot displayed in Fig 4A . For CCR5 , eight to nine water molecules were present in the first two shells . These differences can be explained by the difference in the sizes of the internal pocket in the vicinity of D2 . 50 in CXCR4 and CCR5 . Indeed , the size increased from 90 Å3 in CXCR4 to 236 Å3 in CCR5 , a pattern which is consistent with the changes in side chain volume upon the N3 . 35G ( 54 Å3 ) and S3 . 39G ( 29 Å3 ) mutations . The wider pocket in CCR5 can accommodate more water molecules than CXCR4 and does not constraint the sodium ion which can move by up to 3–4 Å during the simulations ( Fig 3 ) . These changes in the size of the sodium pocket result in static and dynamic sodium binding modes in CXCR4 and CCR5 , respectively . It is worth noting that , in spite of the high mobility of the sodium ion in CCR5 , an egress of the ion was not observed during the simulations . The split between homeostatic and inflammatory chemokine receptors is characterized by the A2 . 49S mutation , which lines the sodium binding pocket . In CCR5 , when S2 . 49 is in the trans rotameric state , it faces the sodium binding site at a distance of 2 . 8 Å from the carbonyl group of G3 . 35 . This geometry could provide an additional binding site to the sodium ion . However , we observed only transient escapes of the sodium ion toward this putative site ( Fig 5 ) . We extended this simulation to 1 . 0 microsecond but failed to observe stable binding of the ion to the putative site , albeit the trans orientation of S2 . 49 was stable ( Fig 7 ) . In order to obtain a larger sampling of the receptor conformational spaces , we carried out accelerated molecular dynamics ( aMD ) simulations [27] of CCR5 . In these accelerated trajectories , the RMSD of the sodium ion , 3 . 0 ± 0 . 9 Å , indicated high fluctuations of the sodium ion within the binding pocket on the nanosecond time scale . Frequent interactions of the ion with both G3 . 35:O and S2 . 49:OG were observed and could last several nanoseconds , after rotamerization of W6 . 48 to the trans conformation ( Fig 7B ) . In order to determine whether the alternative binding site reached during aMD simulations could remain stable during classical MD simulations , a snapshot of the aMD trajectory with the sodium ion interacting with the G3 . 35:O and S2 . 49:OG atoms was selected . The system was energy minimized and used as starting coordinates for subsequent classical MD simulations ( Fig 7C ) . In four out of five replicates , during several tens of nanoseconds ( from 18 to 58 ns ) , the sodium ion remained at this position , and then could experience exchanges between the alternative and canonical sites that are distant of 3–4 Å ( Fig 7C ) . In the alternative site ( Fig 4D ) , the sodium ion is coordinated to the carbonyl oxygen of G3 . 35 , the hydroxyl oxygen of S2 . 49 and three water molecules . In addition , S2 . 49 is H-bonded to S3 . 38 , providing further stability to this configuration . D2 . 50 is now located in the second coordination shell and interacts with the sodium ion through one or occasionally two water molecules . We can note that W6 . 48 , in the trans conformation , forms a trap that closes the sodium binding pocket . In this conformation , it cannot form the face-to-edge interactions with H7 . 45 that favor the interaction of the latter residue with the sodium ion . The rotameric state of W6 . 48 might explain the differences observed between the simulations restarted from the aMD snapshot and the initial MD simulations in which W6 . 48 remained in the crystal structure conformation ( Fig 7 ) .
In this article , we seek to identify the key residues that drove the evolution of chemokine receptors . Nested PCA analysis of sequence covariation matrices ( Fig 1 ) highlighted three positions ( i . e . , 3 . 35 , 7 . 45 , and 2 . 49 ) that are part of the allosteric sodium binding pocket [18] . Mutation of at least one of these positions was crucial at each hierarchical step that led from class A receptors to the split between homeostatic and inflammatory chemokine receptors . This observation prompted us to investigate the history of these positions and their structural and functional roles in prototypical chemokine receptors . Sodium has been shown to be an important regulator of a wide variety of class A GPCRs , acting as a negative allosteric modulator [18] . This allosteric role has been confirmed by the presence of a sodium ion bound in a conserved position in several high resolution structures of GPCRs [21 , 22 , 28 , 29] . The overall binding cavity is conserved within class A GPCRs and involves highly conserved residues , especially D2 . 50 ( fully conserved ) , but also S/T3 . 39 ( 80% conserved ) , and N7 . 45 ( 67% conserved ) , a pattern suggesting that sodium binding may be a general property of class A GPCRs [18] . A recent MD investigation of the free energy profiles and kinetics of sodium binding to 18 GPCRs revealed a conserved sodium binding mechanism [19] . In addition to its documented role as a negative allosteric modulator , the sodium ion might contribute to the mechanisms of receptor activation [30 , 31] , to voltage sensing [32] , and to biased signaling [21 , 33] . Moreover , presence of a sodium binding site might have contributed to the evolutionary success of class A GPCRs [18] . In view with this latter role , it is noteworthy that expansion of P2 . 58 receptors in vertebrates with the emergence of the CHEM and PUR sub-families is subsequent to the appearance of the N3 . 35 pattern in the SO receptors of chordates ( Fig 2 ) . In the sodium bound crystal structures of two P2 . 58 receptors , OPRD and PAR1 , N3 . 35 is involved in the first or in the second coordination shell of the sodium ion [21 , 22] . The divergence that led to the chemokine receptors is characterized by a specific mutation at position 7 . 45 ( Fig 1 ) . This position is preferentially an Asn residue in class A receptors ( 67% ) but a His , or in a few cases , an Arg residue , in chemokine receptors . Oldest chemokine receptors , CXCR4 and ACKR3/CXCR7 , present in the lamprey [3] , possess a histidine at this position , indicating that the divergence to chemokine receptors involved the N7 . 45H mutation . Our molecular dynamics simulations of CXCR4 and CCR5 indicate that H7 . 45 participates in sodium binding . Indeed , in the neutral state , one nitrogen atom of the imidazole ring ( usually NE2 ) has a lone-pair of electrons that allow His to act as a Lewis Base to form coordination complexes . Coordination to divalent ions ( e . g . , Fe++ , Zn++ , Ni++ , Cu++ ) is frequently found in proteins [26] . Coordination to the sodium ion is less frequent but is also observed either in model systems [34] or in proteins [26] . The distance of about 2 . 5 Å ( Table 2 ) that we observed is in agreement with statistical analysis of the Cambridge Structural Database [35] . In chemokine receptors ( Fig 2B ) , H7 . 45 can only be substituted by Arg , which allows direct salt bridge interaction with D2 . 50 to stabilize inactive structure . We and others previously noted that the split between homeostatic and inflammatory chemokine receptors is characterized by an Ala to Ser mutation at position 2 . 49 [17 , 36] . This position strongly covaries with position 3 . 35 ( second component in Fig 1C ) . Position 3 . 35 , which is a conserved Asn in 70% of P2 . 58 receptors , is Gly in the small subset of inflammatory chemokine receptors . This latter mutation is striking because of the importance of N3 . 35 in sodium binding and its role in the stability of the receptor inactive state . In the homeostatic receptors CXCR4 [23] and CXCR3 [24] , the mutation of N3 . 35 to Ser or Ala induces constitutive G protein and β-arrestin activity . Among inflammatory chemokine receptors , the direct effect of sodium ions on receptor activity has been experimentally verified on CCR3 [37] , which possesses a Gly residue at position 3 . 35 , a configuration indicating that these receptors maintain the ability to bind sodium ions . With this regard , the presence of a His residue at position 7 . 45 , involved in sodium binding , might explain the maintained sodium binding . Nevertheless , MD simulations highlight dramatic differences in the sodium binding sites of CXCR4 and CCR5 . In CXCR4 , the tightly bound sodium ion is coordinated to four protein atoms from D2 . 50 , N3 . 35 , S3 . 39 and H7 . 45 and to one or occasionally two water molecules . The contacts with these protein atoms are maintained during at least 98% of the trajectory ( Table 1 ) . Such pentameric coordination with four receptor atoms in the first coordination shell has not been observed yet in GPCR crystal structures , but examples in other protein families have been reported [38] . The stability of the sodium binding site is reinforced by the face-to-edge interactions between H7 . 45 and W6 . 48 ( Fig 4A ) . This geometry should strongly stabilize the inactive state of CXCR4 in the absence of agonists . We verified that the four residues involved in sodium coordination are conserved from P . Marinus ( Sea Lamprey , Uniprot access number: Q802H1 ) to humans . A very different pattern is observed in CCR5 . The absence of side chains at positions 3 . 35 and 3 . 39 creates a large water-filled pocket ( Fig 6D ) . Sodium is highly mobile within this pocket and experiences different binding modes that depend on the rotameric states of W6 . 48 and H7 . 45 and involve two to five water molecules ( Fig 6 ) . Different binding modes of the sodium ion within the allosteric binding pocket have also been reported in MD simulations of A2A adenosine receptor [39] , opioid receptors [30 , 40] and dopaminergic D2 receptor [41] . In these simulations , the sodium ion remains in the close vicinity of residues 2 . 50 , 3 . 39 , or 7 . 45 . Similarly , in the CCR5 simulations started from a model based on the crystal structure , the sodium ion remains in the vicinity of residues 2 . 50 , 7 . 45 and 7 . 49 ( Fig 5 ) . The alternative sodium binding site , located 3–4 Å apart , is observed only under a specific MD protocol ( Fig 7 ) . Albeit the possibility of an aMD skew cannot be ruled out , we note that the alternative site involves G3 . 35 and S2 . 49 , the two residues crucial for the emergence of the inflammatory chemokine receptors ( Fig 1 ) . Interestingly , its relative stability might be related to the rotameric orientation of W6 . 48 ( Fig 7 ) . W6 . 48 is a crucial microswitch for receptor activation following agonist binding [42] . The alternative site might thus be stabilized by ligand binding or environmental conditions . Moreover , in contrast with the sites that involve residues from TM7 and collapse upon receptor activation , this site might be maintained upon activation . The differences in the sodium binding modes ( Figs 3–6 ) prompt the question of their contribution to the physiological roles and mechanisms of action of CXCR4 and CCR5 . In addition to different physiological functions in homeostasis and inflammation , these receptors differ by several aspects of molecular and cellular regulation: ( 1 ) Ligand selectivity: CXCR4 is monogamous with a single native chemokine ligand , CXCL12 . CCR5 is highly promiscuous with ten chemokine ligands [1]; ( 2 ) Pre-coupling with G proteins: Pre-coupling of CCR5 with nucleotide free G proteins leads to two receptor populations . Pre-coupled receptors bind chemokine ligands with Kd values in the nanomolar range , close to physiological concentrations , while free receptors have a much lower affinity for chemokines , which prevent chemokine inhibition of HIV-1 entry [43] . A unique Kd in the nanomolar range is observed for CXCL12 binding to CXCR4 [44]; ( 3 ) Constitutive activity: CCR5 is partially constitutively active for both the Gαi pathway and the β-arrestin mediated internalization [45 , 46] . Wild type CXCR4 undergoes constitutive internalization by a β-arrestin pathway [47 , 48] but constitutive G protein activity of CXCR4 has been observed only upon mutation of N3 . 35 to Ser or Ala [23] . In spite of these differences , it is interesting to note that , as observed for other chemokine receptors , CXCR4 and CCR5 do not possess an ionic lock [42] between position 3 . 50 ( Arg in both receptors ) and position 6 . 30 ( Lys and Arg in CXCR4 and CCR5 , respectively ) . CXCR4 is not only involved in homing of hematopoietic stem cells but is also a major player of embryonic development , especially neuronal development [2 , 49 , 50] . Evolutionary analysis indicates that CXCR4 is the ancestor of chemokine receptors and suggests that the developmental role of CXCR4 is the initial function that has emerged in evolution [4] . Constitutive internalization , mediated by β-arrestins and related to receptor recycling , is necessary for high responsiveness of migrating cells upon stimulation [51] . A stringent control of the activation of Gαi ( related to migration ) by CXCR4 to avoid erroneous activation in the absence of CXCL12 stimulation is mandatory for the role of CXCR4 in neuronal development . Release of the ionic lock joined to tight sodium binding might have been a solution for this challenge . Interestingly , the urotensin II receptor ( UR2R ) which appeared in chordates ( Fig 2 ) has properties reminiscent of CXCR4 , including chemotaxic properties and involvement in cancer metastasis [52] , along with location in the central nervous system [53] . It possesses a polar Thr residue at position 3 . 35 , and no ionic lock from B . floridae to humans , suggesting that tightening of sodium binding and absence of ionic lock might have been mandatory for emergence of chemotaxic properties in P2 . 58 receptors . In CCR5 , the loosening of the sodium binding site results in different binding modes of the sodium ion within the sodium pocket . Such variability may be important for the functionality of CCR5 which induces biased responses upon binding to different chemokine ligands [13] . Indeed , in several receptors , altering sodium binding induced biased signaling [21 , 33 , 54] . Interestingly , in the δ-opioid receptor , the N3 . 35V mutation facilitates the mobility of the sodium ion within the allosteric binding pocket [32] and augments constitutive β-arrestin-mediated signaling [21] . In addition , the capability to maintain sodium binding at the alternative site upon activation or pre-activation might contribute to the pre-coupling of CCR5 with G proteins . Further studies will be required to investigate the putative function of this site which might be involved in biased signaling or in G protein pre-coupling . Table 3 reports the positions involved in sodium binding within the chemokine receptor family . The wide variety of sodium coordination in a small receptor sub-family with high sequence identity ( > 30% ) contrasts with the usual conservation of sodium binding mechanism within a receptor sub-family and the high conservation of the S/T3 . 39 and N7 . 45 patterns in class A GPCR ( see above ) . This high variability in the sodium binding mechanism of chemokine receptors strongly supports the assumption that the sodium ion has a major role in the mechanism of action and regulation of these receptors . We note that that only three homeostatic chemokine receptors can provide 4 protein atoms for the sodium coordination: ( 1 ) CXCR4 , ( 2 ) ACKR3/CXCR7 which is an atypical chemokine receptor that works in tandem with CXCR4 and acts as a scavenger to maintain CXCL12 gradient [55] , and ( 3 ) CXCR5 , a receptor important for secondary lymphoid tissue orchestration and lymphoid neogenesis [56] . These receptors , which bind one or two chemokines ( Table 3 ) , are among the most ancient chemokine receptors since they appeared in jawless or cartilaginous fishes [4] . In most other homeostatic receptors , position 3 . 39 is a glycine . In CXCR6 , S3 . 39 is present but position 7 . 45 has been mutated to Arg . In CCR9 with a conservative S3 . 39C mutation , the highly conserved W6 . 48 is mutated to Gln , which prevents tight packing of H7 . 45 . Thus , tight sodium binding seems related to initial functions of most ancestral chemokine receptors ( e . g . , neuronal development ) and this constraint was released with the emergence of chemokine receptors with different physiological functions . The loose sodium binding pocket observed in CCR5 may also be an extreme case . This property is related to the G3 . 35/G3 . 39 pattern which is shared only by CCR2 and CCR4 , closely related to CCR5 ( Fig 2 ) . Other inflammatory receptors possess the S3 . 39 pattern ( receptors present in fish ) , the E3 . 39 pattern ( CCR1 , CCR3 , and CCRL2 ) or the N3 . 35 pattern ( ACKR2/CCBP2 ) , which provides additional protein oxygen for sodium coordination ( Table 3 ) . Another important observation in Table 3 is the absence of the S3 . 39 pattern in promiscuous receptors . Receptors with the S3 . 39 pattern bind only one or two chemokine ligands . Promiscuous receptors have either a glycine or a glutamic acid at this position , indicating different sodium binding modes . In the chemokine/receptor system , promiscuity is linked to signaling bias . Chemokines do not induce similar response upon binding to a promiscuous receptor , but constitute an example of naturally biased ligands [13] . In several receptors , biased signaling was induced by altering residues involved in sodium binding . This has been observed , for example , in OPRD [21] and AT1 [54] . This suggests a relation between sodium binding and receptor promiscuity/biased signaling that will require experimental investigation . In conclusion , the evolutionary approach that we have developed has pointed out a key role of mutations at the sodium binding site in the evolutionary pathway that led to the emergence and diversification of chemokine receptors . Molecular dynamics simulations have highlighted the dramatic changes in the mechanism of sodium binding between homeostatic and inflammatory chemokine receptors , exemplified by CXCR4 and CCR5 , respectively . The tight binding site observed for CXCR4 is replaced by a loose binding pocket for CCR5 , in which several binding modes are possible . These findings might be related to the specific features of CCR5: pre-coupling , constitutive G protein activity , promiscuous binding and biased signaling upon chemokine binding . The sodium binding site links the orthosteric ligand binding site and the G protein/β-arrestin binding site . Careful analysis of sodium binding properties of chemokine receptors will help the understanding of the mechanisms underlying biased signaling and the subsequent design of biased drugs .
The analyzed sequences included non-redundant sets of class A GPCRs from different genomes: H . sapiens , D . rerio , B . floridae , C . elegans , N . vectensis , and T . adhaerens . All the sets were prepared , aligned , and assigned as described previously [16] . In this analysis , B . Floridae was chosen as the representative chordate because it corresponds to a reference proteome ( www . uniprot . org ) . The DARC/Duffy/ACKR1 atypical chemokine receptor was not included in the human set because of its low sequence identity with other chemokine receptors ( < 16% ) and loss of typical class A sequences patterns in TM1 , TM2 , TM3 , and TM5 , making it a remote outlier . Neighbor joining trees were obtained with the MEGA5 software [57] , using the Dayhoff matrix option and 500 bootstrap replicates . Sequence logos were obtained from the WebLogo site ( web . logo . berkeley . edu ) [58] . Covariation analysis was carried out on two sequence sets from humans: the non-redundant set of class A GPCRs ( 282 sequences ) and the CHEM sub-family subset ( 46 sequences ) [15] . The sequence analyses were performed using positions with less than 2% gap in the MSA ( extended transmembrane helices ) . The MSAs that were used for sequence analysis are available as Supporting Information ( S1 , S2 and S3 Files for , respectively , the human class A set , the human CHEM set , and the SO receptors from the six species investigated ) . The GPCR positions were numbered by reference to the most conserved position i . 50 in each helix i , according to Ballesteros’ numbering [59] . In CXCR4 , the anchor residues are: N56 , D84 , R134 , W131 , P211 , P254 , and P299 . In CCR5 , the anchor residues are: N48 , D76 , R126 , W153 , P206 , P250 , and P 294 . The covariation score between any two positions i and j in the alignment of length N was measured by the OMES method [60] which is suited to find sequence covariation related to family divergence [17] . The covariation matrix , denoted COV , was subsequently double-centered to give the matrix S according to the formula: S=[I−1N1]×COV×[I−1N1]T ( 1 ) where I denotes the N by N identity matrix , and 1 an N by N matrix of ones . The matrix S was subsequently analyzed by principal component analysis ( specifically , by an eigen-decomposition ) [20]: S=UΛUT ( 2 ) where U and Λ are , respectively , the matrix of the eigenvectors and the diagonal matrix of the eigenvalues of S . The coordinate matrix ( a . k . a . , factor scores matrix [20 , 72] ) , denoted F , gives the coordinates of each position of the alignment on the principal component axes and is computed as: F=UΛ12 . ( 3 ) The analysis was performed with functions written in the R programing language . They are available in the R package Bios2cor which can be found in the Comprehensive R Archive Network ( cran . r-project . org ) . The models of CXCR4 ( residues 28 to 319 ) and CCR5 ( residues 19 to 313 ) with a bound sodium ion were built with MODELLER version 9 . 8 [61] , using as templates the crystal structure of CXCR4 ( PDB entry 3ODU ) [11] and CCR5 ( PDB entry 4MBS ) [10] , respectively , and the high resolution ( 1 . 8 Å ) crystal structure of the δ-opioid receptor ( PDB entry 4N6H ) [21] that includes a bound sodium ion interacting with D2 . 50 and N3 . 35 . The water molecules contributing to the coordination of the sodium ion were included in the models . The three templates correspond to receptors in inactive states . The stabilizing mutations present in the crystallized CXCR4 and CCR5 receptors were reversed to the amino acids present in the human wild type receptor . The ICL3 loops that were replaced by the lysozyme and rubredoxin in the crystallized CXCR4 and CCR5 , respectively , were reversed to the human sequences of the corresponding receptors . The carboxyl group of D2 . 50 was deprotonated [62] . H7 . 45 which was completely buried from solvent was neutral . Its pKa was measured using Propka on the PDB2PQR web interface [63] , in the presence and absence of sodium , and was below 4 in any case for both receptors . The hydrogen of the pyrimidole ring was located on ND1 which corresponds to the most frequent tautomer ( HSD in the CHARMM topology file ) . Subsequently , the models were prepared for molecular dynamics simulations ( MD ) using the Charmm-gui interface [64] . The models were embedded in a palmitoyl-oleoyl-phosphatidyl-choline ( POPC ) lipid bilayer and solvated using the TIP3P model for water molecules [65] , with all atoms represented explicitly . The charges were neutralized by adding chloride ions . Molecular dynamics simulations of the CXCR4 and CCR5 models embedded in an hydrated POPC bilayer were carried out using NAMD v2 . 9 MD software [66] and the CHARMM36 parameter set [67 , 68] . They were performed using the HPC resources of IDRIS , granted by GENCI ( www . genci . fr ) . The entire assembly was subjected to energy minimization for 5000 steps to remove close contacts between atoms . Equilibration of the system was carried out with a modified version of a protocol developed elsewhere [69] . The protocol included six interlinked equilibration steps in which harmonic restraints were gradually taken off to achieve a smooth relaxation , for a total of 1 ns . Then a 20 ns equilibration step was carried out under the same conditions as the production run to achieve stable conditions . In the first two equilibration steps , the NVT ensemble at 310 K and time step of 1 fs were used . The following equilibration and production steps were carried out at constant temperature ( 310 K ) and pressure ( 1 atmosphere ) , using a 2 fs time-step for integration . The Particle Mesh Ewald method ( PME ) was used to calculate the electrostatic contribution to non-bonded interactions with a cutoff of 12 Å . The cutoff distance of the van der Waals interaction was 12 . 0 Å . The SHAKE algorithm was applied to the system . Each trajectory lasted 420 ns ( 20 ns for equilibration and 400 ns for production ) . Three and five replicates were carried out for CXCR4 and CCR5 , respectively . The initial assembled models for the different runs and the scripts used for the equilibration and production steps are available as Supporting Information ( S4 File ) A CCR5 trajectory displaying transient contacts to a putative alternative site was extended to 1 microsecond ( Fig 7A ) . To obtain a more extensive sampling of the CCR5 conformational space , we carried out accelerated molecular dynamics simulations ( aMD ) [27] . This technique , based on an extended biased potential MD approach , has been shown to be an efficient way to enhance conformational sampling . It works by adding a dihedral potential boost to all dihedral angles in the system ( dihedral boost ) and , optionally , a total potential boost to all atoms in the system ( dual boost ) when the energies are below a threshold . The threshold energies were set to the average energies , Edihed_avg and Epot_avg , computed from classical MD . The acceleration factors were calculated according to: αdihed=λ×Edihed_avg5 ( 4 ) αpot=λ×N ( 5 ) where the acceleration parameter λ was chosen to be equal to 0 . 3 and N represents the number of atoms in the system [70 , 71] . We used the 20–120 ns range of classical MD simulations to calculate the acceleration parameters . The snapshot obtained after 120 ns of classical MD simulations was used to initiate the accelerated simulation ( S5 File ) . This technique allowed obtaining snapshots with the sodium ion interacting with the carbonyl oxygen of G3 . 35 and the hydroxyl oxygen of S2 . 49 . A typical snapshot with the sodium ion in this position ( S6 File ) was used to restart the classical MD protocol to study the stability of this putative sodium site . Five replicates of 200 ns were performed and a representative run was extended to 400 ns . Trajectories were analyzed with the VMD software [72] and the Bio3D R package [73] , using in house-developed scripts . PYMOL ( DeLano Scientific LLC , San Francisco , USA ) was used for figure preparation . The frames obtained during the first 20 ns of the trajectories were not taken into account for the analysis of the coordination and hydration of the sodium ion . The R package Bios2cor , developed for covariation analysis , can be downloaded from the Comprehensive R Archive Network ( http://cran . r-project . org ) .
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The chemokine-receptor system is involved in a broad array of pathologies , including autoimmune and inflammatory diseases , allergies , cancer metastasis , and HIV infection . It is an attractive , but difficult , target for drug development and a deeper understanding of the structure-function relationships of the chemokine receptors is required to help design drugs targeted against these receptors . To gain information on the mechanism of action of the chemokine receptors , we developed an evolutionary approach based on the global analysis of co-mutations in receptor sequences . This approach drew attention to a few residues whose mutation was crucial for the evolution of the chemokine receptor family . To understand the role of these residues , we have carried out molecular dynamics simulations that revealed that these mutations dramatically modified the binding mode of a sodium ion involved in receptor regulation . These changes accompanied the divergence of chemokine receptor functions between immune surveillance and inflammation . They indicate unanticipated roles of the sodium ion in the mechanism of action of the chemokine receptors .
|
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2018
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Evolution of chemokine receptors is driven by mutations in the sodium binding site
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The in utero environment profoundly impacts childhood neurodevelopment and behaviour . A substantial proportion of pregnancies in Africa are at risk of malaria in pregnancy ( MIP ) however the impact of in utero exposure to MIP on fetal neurodevelopment is unknown . Complement activation , in particular C5a , may contribute to neuropathology and adverse outcomes during MIP . We used an experimental model of MIP and standardized neurocognitive testing , MRI , micro-CT and HPLC analysis of neurotransmitter levels , to test the hypothesis that in utero exposure to malaria alters neurodevelopment through a C5a-C5aR dependent pathway . We show that malaria-exposed offspring have persistent neurocognitive deficits in memory and affective-like behaviour compared to unexposed controls . These deficits were associated with reduced regional brain levels of major biogenic amines and BDNF that were rescued by disruption of C5a-C5aR signaling using genetic and functional approaches . Our results demonstrate that experimental MIP induces neurocognitive deficits in offspring and suggest novel targets for intervention .
Each year , an estimated 125 million pregnancies worldwide are at risk of malaria infection [1] . Plasmodium falciparum infections during pregnancy are more frequent , and associated with higher parasite burdens and worse clinical outcomes than those of non-pregnant individuals [2 , 3] . MIP has profound maternal and fetal health consequences including increased risk of maternal anemia , preterm birth , stillbirth , fetal growth restriction ( FGR ) and low birth weight infants ( LBW ) , resulting in an estimated 200 , 000 infant deaths annually [4] . MIP is characterized by the accumulation of parasitized erythrocytes ( PEs ) and monocytes/macrophages in the placenta [2 , 3] . While it is believed that this localized placental immune response contributes to adverse birth outcomes , the precise mechanism by which parasite and monocyte accumulation in the placenta results in poor pregnancy outcomes remains unknown . Recent evidence supports a role for altered angiogenesis and resulting placental vascular insufficiency [5 , 6] . The complement system is an essential component of the innate immune response to microbial pathogens [7–9] . Excessive complement activation , notably generation of the anaphylatoxin C5a , has been implicated in mediating deleterious host responses and poor clinical outcomes to infections [8 , 10] . Malaria infection is known to induce activation of the complement system through multiple pathways , and recent studies support a mechanistic role for C5a in the pathophysiology of severe malaria and malaria in pregnancy [10–14] . Complement activation has also been proposed as a common pathway mediating adverse pregnancy outcomes in the absence of infection [15 , 16] . Excessive C5a generation was implicated as a mediator of placental injury in murine models of spontaneous miscarriage and FGR [17] . Moreover , human studies have associated complement split products ( e . g . C3a , C5a ) with pregnancy complications [18 , 19] . Recent evidence has also identified an essential role for the complement system in both normal and abnormal neurodevelopmental processes [20–22] . Complement proteins and their receptors are widely expressed within the central nervous system and play a major role in regulating normal synaptic development and function [23] . Alterations in the in utero environment as a result of maternal infection may have profound and long-term implications for the developing fetus . Recent studies indicate that immunological stress at the maternal-fetal interface can alter later-life brain development and behaviour [24 , 25] . Despite the potential public health implications , little is known about the impact of in utero exposure to MIP on fetal and infant neurological development . Based on the above evidence implicating C5a in both neurodevelopment and MIP-associated adverse birth outcomes , we tested the hypothesis that in utero exposure to experimental MIP ( EMIP ) alters offspring neurodevelopment and that disruption of maternal C5a receptor ( C5aR ) signaling would rescue EMIP-induced neurocognitive injury in exposed offspring .
LBW , as a result of preterm birth or FGR , is known to be associated with impaired neurocognitive development [26 , 27] . Since MIP may cause LBW , these infants would be expected to experience an increased risk of neurocognitive impairment; however the majority of fetuses exposed to malaria in utero do not develop LBW . Therefore , in order to avoid LBW as a confounder and isolate the effects of malaria exposure alone on offspring neurodevelopment , we reduced the inoculum given to dams in a validated model of EMIP [28] from 106 to 105 PEs . This inoculum was associated with the presence of parasitized erythrocytes in the placenta and localized inflammation in the placenta ( S1 Fig and S2 Fig ) . However the 105 inoculum was associated with lower maternal peripheral parasitemia ( Fig 1A ) and less marked placental pathology than that previously reported with a dose of 106 PEs [28] . This modification eliminated the LBW phenotype in this model and resulted in equivalent birth weights ( from 1 to 20 weeks of age ) in control pups compared to offspring exposed in utero to EMIP ( Figs 1b , 5b and S3 Fig , S4 Fig and S5 Fig ) . No significant differences were observed in the length of gestation or litter size in this lower inoculum EMIP model ( S1 Table ) . Placentas from malaria-infected litters ( wild-type and C5ar-/- ) showed placental inflammation as indicated by increased expression of tumor necrosis factor ( TNF ) , interferon gamma ( IFNϒ ) , intracellular adhesion molecule-1 ( ICAM-1 ) and monocyte chemotactic protein 1 ( MCP-1 , CCL2 ) ( S2 Fig , p < 0 . 05 ) . Wild-type mice showed increased expression of ICAM and reduced expression of MCP in comparison with C5ar-/- mice in placentas from both uninfected and malaria-infected litters ( S2 Fig , p < 0 . 05 ) . Absence of congenital infection was confirmed by blood smears and PCR of fetal blood . To investigate the impact of in utero EMIP-exposure on neurocognitive performance , we compared EMIP-exposed pups to unexposed controls using a battery of standardized neurocognitive tests [29–31] . Exposed offspring showed impaired novel object recognition ( NOR ) in the NOR test of non-spatial learning and memory , and increased immobility in the tail suspension test ( TST ) , a test of depressive-like behavior . Performance in the NOR test was impaired in EMIP-exposed offspring compared with unexposed offspring ( P = 0 . 0004; Fig 1C ) . Differences observed between groups could not be attributed to other behavioral factors including differences in time of initial exploration of objects or motor behavior during testing ( Fig 1D , S3 Fig ) . Immobility in the TST was increased in EMIP-exposed offspring compared with unexposed offspring ( P = 0 . 004; Fig 1E ) . The behavioral deficits persisted to adulthood in EMIP-exposed offspring . Exposed mice tested at 20 weeks of age showed impaired performance in the NOR test ( P = 0 . 001; Fig 1F ) and increased immobility in the TST ( P = 0 . 0002; Fig 1H ) . We performed MRI to determine if the observed neurocognitive phenotype in EMIP-exposed mice was associated with changes in regional brain volumes . Prior to imaging , all mice were tested in the NOR test to confirm their behavioral phenotype . In utero exposed offspring showed impaired performance in the NOR test compared with unexposed offspring ( P = 0 . 0009; S3 Fig ) . Volumetric analysis of brain volume in 63 distinct regions revealed no differences between EMIP-exposed and control mice ( S2 Table ) . A significant correlation across all WT mice ( exposed and unexposed ) was observed between total entorhinal cortical volume ( volume of left and right cortices together ) and performance in the NOR test ( Spearman’s rho , 0 . 4912 , P = 0 . 0044; Fig 1I ) . The mouse brain atlas [32] used to define the entorhinal cortex is depicted in Fig 1J . These data confirm a role for the entorhinal cortex in performance in the NOR test as suggested by previous reports [33 , 34]; however no difference was observed between malaria-exposed and unexposed animals . Previous studies have shown that malaria in pregnancy is associated with altered placental vascular development [5] . We hypothesized that fetal cerebral vasculature may also be modified in malaria-exposed offspring , and that altered cerebrovascular development may contribute to the observed neurocognitive phenotype . Using a novel imaging approach in fetal mice , we performed micro-CT scans of fetal cerebral vasculature at G18 . To our knowledge , this is the first time micro-CT has been used to visualize fetal cerebral vasculature . Using this technique , we identified all major cerebral vessels in fetuses and determined that there were no qualitative differences in major vessel architecture ( Fig 2A–2D , S3 Table ) . In order to assess the impact of malaria–exposure on small vessel development , we further examined fetal cerebral vasculature with automated vessel tracking of the 3D images [35] . Vessel tracking analysis revealed a significant increase in the total number of vessel segments associated with in utero malaria-exposure ( Fig 3A , P < 0 . 05 ) . Malaria-exposure did not result in significant changes to total vessel length ( Fig 3B ) . Examination by MRI or micro-CT may not be sufficiently sensitive to detect subtle neurological features , such as changes in neuronal connectivity , capable of altering neurocognitive outcomes . Therefore , we next investigated levels of biogenic amine transmitters ( dopamine , norepinephrine and serotonin ) in four regions of interest ( frontal cortex , temporoparietal cortex , striatum and hippocampus ) based on their previously established involvement in the behavioral phenotypes we observed [36–38] . All tissue was harvested from animals that had been tested behaviorally to confirm their phenotype ( Fig 1C–1E ) . Wild-type malaria-exposed offspring showed decreased tissue levels of dopamine ( P < 0 . 01; Fig 4A ) and serotonin ( P < 0 . 005; Fig 4B ) in the frontal cortex , norephinephrine in the temporoparietal cortex ( P < 0 . 05; Fig 4C ) and serotonin in the striatum ( P < 0 . 05; Fig 4D ) compared with wild-type unexposed offspring . Tissue levels of the catecholamine metabolite homovanillic acid were reduced in the frontal cortex and hippocampus of wild-type exposed mice ( P < 0 . 05; S4 Table ) . Tissue levels of these analytes in each of the regions tested are reported in S4 Table . Maternal peripheral parasitemia ( ranging from 14–31% on the day of delivery; Fig 1A ) was not associated with differences in the observed levels of major biogenic amines , MRI or micro-CT imaging or neurocognitive outcomes . Based on evidence linking C5a to both neuropathology and the pathophysiology of malaria [5 , 11 , 13 , 14] , we examined the impact of genetic disruption of the C5a-C5aR signaling on neurocognitive outcomes in EMIP-exposed offspring . The deficits in NOR performance observed in WT EMIP-exposed offspring were completely rescued in C5aR deficient ( C5ar-/- ) EMIP-exposed offspring ( P < 0 . 001 ) ( one-way ANOVA and post-test , P < 0 . 004; Fig 5C ) . Again , no differences in time of initial exploration or motor behaviour were observed ( Fig 5D , S4 Fig ) . Similarly , although immobility was increased in EMIP-exposed WT offspring in the TST , these features of affective-like behaviour were absent in EMIP-exposed offspring where C5aR signaling was disrupted ( one-way ANOVA and post-test , P < 0 . 005; Fig 5E ) . Rescue of the neurocognitive deficits observed in EMIP-exposed C5ar-/- offspring persisted to adulthood ( Fig 5F–5H ) . When tested at 20 weeks of age , EMIP-exposed WT mice showed impaired performance in the NOR test compared to EMIP-exposed C5ar-/- offspring ( P < 0 . 001 ) and unexposed WT and C5ar-/- controls ( one-way ANOVA and post-test , P < 0 . 002; Fig 5F ) . Performance of exposed C5ar-/- offspring was similar to unexposed controls ( Fig 5F ) . Adult EMIP-exposed WT offspring , similar to malaria-exposed young mice , showed increased immobility in the tail suspension test compared with unexposed WT offspring ( P < 0 . 001 ) , and this effect was rescued in C5ar-/- offspring ( one-way ANOVA and post-test , P < 0 . 0001; Fig 5H ) . To provide a separate line of evidence that disruption of C5aR signaling rescues neurocognitive deficits in exposed offspring , we examined the impact of functional blockade of C5a in malaria-infected wild-type dams using C5a antisera [39] . Treatment of dams with anti-C5a antibody rescued the performance of EMIP-exposed offspring in the NOR test and TST . Offspring of dams treated with C5a antisera showed no significant difference in performance compared with unexposed offspring ( P > 0 . 05; Fig 5I ) . However , performance in the NOR test was impaired in EMIP-exposed offspring and exposed offspring of dams treated with control sera ( one-way ANOVA , P = 0 . 012; Fig 5I ) . EMIP-exposed offspring and exposed offspring of dams treated with control sera showed increased immobility in the TST compared with unexposed offspring ( P < 0 . 01 ) and EMIP-exposed offspring of dams treated with C5a antisera ( P < 0 . 001 ) ( one-way ANOVA and post-test , P < 0 . 0001; Fig 5K ) . We performed additional testing on this cohort of animals to examine the impact of the saliency of the stimuli on cognitive performance . No significant difference in freezing behavior ( a read out of contextual fear conditioning-based learning ) was observed between groups on Day 2 or Day 3 of contextual fear-conditioning ( one-way ANOVA and post-test , P > 0 . 05; S5 Fig ) . C5a has been shown to be directly neurotoxic in vitro [22] and blockade of C5aR signaling in experimental models of MIP is associated with increased placental vascular development [5] . Therefore , to begin to examine putative mechanisms by which disruption of C5aR signaling may prevent neurocognitive injury , we performed MRI and micro-CT imaging of fetal cerebral vasculature in unexposed and malaria-exposed C5ar-/- offspring . We observed no volumetric changes as determined by MRI ( S2 Table ) as a result of EMIP-exposure in C5ar-/- offspring . Although micro-CT scans of fetal cerebral vasculature ( Fig 2E–2H ) at G18 revealed a significant increase in total vessel segments in malaria-exposed wild-type offspring ( Fig 3A ) , disruption of C5a-C5aR signaling did not significantly reverse these changes . Therefore , neither changes in brain volumes as determined by MRI , nor microvascular development as assessed by micro-CT , provided an explanation for the cognitive impairments observed and their rescue by C5a-C5aR blockade . We next extended our analysis to examine the impact of EMIP-exposure on monoamine transmitter levels in adult WT and C5ar-/- mice . In contrast to EMIP-exposed WT mice , regional brain levels of biogenic amines were not significantly decreased in EMIP-exposed C5ar-/- offspring ( P>0 . 05 , Students t-test , S5 Table ) . We normalized the levels of transmitters of EMIP-exposed WT and C5ar-/- offspring to the mean of their respective unexposed controls ( Fig 6A–6F ) . Exposed C5ar-/- offspring displayed significantly higher levels of serotonin in the frontal cortex ( P = 0 . 0028; Fig 6B ) , norepinephrine in the temporoparietal cortex ( P = 0 . 012; Fig 6C ) and serotonin in the striatum ( P = 0 . 009; Fig 6D ) , compared to EMIP-exposed WT mice . Given the established role of BDNF in regulating brain monoamine levels [40 , 41] , we determined whether decreased fetal brain BNDF levels were associated with the observed decrease in biogenic amines and whether disruption of C5aR signaling would rescue these levels . We observed decreased BDNF transcript levels in EMIP-exposed WT offspring ( Fig 6G ) ; whereas BDNF levels were restored in EMIP-exposed C5ar-/- offspring ( one-way ANOVA and post-test , P <0 . 001 , Fig 6G ) .
This study provides the first evidence implicating a causal link between pre-natal exposure to malaria , C5a-C5aR signaling and subsequent neurocognitive impairment in offspring . Our findings indicate that in utero exposure to maternal malaria infection can alter the cognitive and neurological development of offspring . We observed impaired learning and memory and depressive-like behavior that persisted to adulthood in EMIP-exposed offspring that were neither congenitally infected nor LBW . These neurocognitive impairments were associated with decreased tissue levels of major biogenic amines in cortical and subcortical regions of the brain . Genetic or functional disruption of maternal C5aR signaling restored the levels of BDNF and cerebral biogenic amines and rescued the associated cognitive phenotype observed in EMIP-exposed offspring . Immunological stress at the maternal-fetal interface is associated with an increased risk of neurodevelopmental disorders in offspring [25 , 42–44] . MIP is characterized by the accumulation of parasitized erythrocytes and monocytes/macrophages in the intervillous space , creating a localized immune response in the placenta [6] . It is well established that components of the innate immune system , including complement factors , play diverse roles in angiogenesis , inflammation , neurogenesis and neurodevelopment [45 , 46] . Increased peripheral and placental levels of C5a are observed in women with MIP and are associated with adverse pregnancy outcomes [5 , 11] . C5a is a potent initiator of pro-inflammatory as well as anti-angiogenic pathways [9 , 10] . Together these observations are consistent with several potential mechanisms of impaired neurodevelopment including enhanced neuro-inflammation , altered neurovascular development , or dysregulation of complement-mediated neurodevelopmental processes [47] . Complement components are synthesized in the CNS by microglia , astrocytes and neurons and may be overexpressed in response to injury or inflammation [46 , 48] . Neurons , unlike peripheral cell types , do not express high levels of complement regulatory proteins , such as CD59 , CD46 , CD55 and CD35 , suggesting that they may be particularly susceptible to complement-mediated injury [49] . A growing body of evidence supports an important role for the complement system in normal neurodevelopment , synapse formation and synaptic pruning [20 , 21 , 23] . Complement components tag excess synapses for elimination during pruning , facilitating the formation of mature patterns of neuronal connectivity [20] . Reduced levels of complement have been associated with decreased levels of synaptic pruning in the hippocampus and neocortex , a process critical for synaptic refinement during development [20 , 21 , 50] . These findings suggest that increased complement activation during development , as occurs in MIP , could lead to excessive synapse elimination and altered neuronal connectivity [23] . Moreover in models of lipopolysaccharide ( LPS ) -induced preterm birth C5a is reported to have direct neurotoxic effects on fetal cortical neurons in vivo and in vitro [22] . These neurotoxic effects were associated with C5a-induced glutamatergic excitotoxicity [22] . Collectively these data support the hypothesis that MIP-induced complement activation at the maternal-fetal interface may alter fetal neural networks and disrupt normal brain developmental processes . While increased peripheral and placental levels of C5a are observed in women with MIP [5 , 11] , it is unclear whether fetal complement activation also occurs and whether it contributes to altered neurodevelopment . Future studies using the EMIP model could examine this question by mating heterozygote parents to generate WT , heterozygote and C5ar-/- offspring and determining the relative contribution of maternal versus fetal complement activation to neurocognitive outcome . We propose that the cognitive deficits we observed in EMIP-exposed offspring are mediated , at least in part , by a reduction in regional brain levels of biogenic amines . Biogenic amines are reported to be central to learning and memory in the NOR test and depressive-like behavior in the TST [30 , 37 , 51] . We observed reduced serotonin and dopamine in the frontal cortex , reduced norepinephrine in the temporoparietal cortex and reduced serotonin in the striatum of EMIP-exposed WT offspring . EMIP-exposed offspring do not develop reductions of biogenic amines , in these regions , when C5aR signaling is disrupted . Norepinephrine has been associated with arousal and attention; responses to novelty that facilitate object recognition [33 , 51] . Cortical monoamine function , including dopamine and serotonin , has also been linked to performance in the NOR test [36 , 38 , 52 , 53] . Previous studies have implicated altered basal ganglia and cortical monoamine levels in TST behavior [37 , 54] . Specifically , pharmacological treatment with monoamine reuptake inhibitors that increase monoamine availability induce increased mobility in the TST [30 , 54 , 55] . Based on our behavioral and HPLC data we postulate that in utero exposure to malaria induces localized and subtle changes in neuronal development . We did not observe any behavioral deficits in the CFC test , a test of learning and memory using a highly salient and aversive foot-shock stimulus [56] . This suggests that prenatal exposure to EMIP does not induce a global impairment in learning and memory but alters behavioral performance in a task-specific manner . Tight regulation of neurotrophic factors , in particular BDNF , is critical for normal neurodevelopment [40 , 57] . During embryogenesis BDNF regulates axonal and dendritic differentiation [40] . Immune responses to infections may alter BDNF levels , and disruption in BDNF-regulated processes can lead to alterations in brain monoamine levels and behavioral phenotypes in adulthood [41 , 58] . Our data , together with the above observations , support a model of pathogenesis whereby MIP-induced C5 activation impairs in utero neurodevelopment via effects on inflammation , synaptic pruning , neural network formation and regulation of BDNF , leading to reduced regional levels of monoamines and impaired cognitive performance in malaria-exposed offspring . When C5a-C5aR signaling is disrupted by genetic or functional approaches , there is reduced neurotoxicity , preserved regulation of BDNF and brain monoamine levels , and improved neurocognitive outcomes . In addition to a role in neurodevelopment and neurodegenerative disorders , C5a is a potent initiator and amplifier of anti-angiogenic pathways and could theoretically alter neurodevelopment through angiogenic pathways as has been proposed for placental vascular development and remodeling during MIP [5 , 10 , 11] . Since C5a-C5aR blockade has been show to improve placental vascular development , it is also possible that rescue of the cognitive phenotype we observed in malaria-exposed C5ar-/- offspring is the result , at least partly , of changes in placental function . Developmentally , neurogenesis and angiogenesis are tightly linked [59] . They utilize the same genetic and regulatory pathways and dysregulation in one system may alter developmental processes in the other . Therefore , we used a novel imaging approach to investigate whether the neurocognitive deficits in exposed-offspring were linked to altered neurovascular development as proposed [47] . Using micro-CT imaging , we observed an increased number of vessel segments , indicative of more vessel branching in malaria-exposed wild-type offspring . Whether this increase in cerebral vascular development represents a compensatory response to malaria-associated neurotoxicity will require further study . Overall this finding is consistent with previous observations that malaria also alters placental vascular development [5 , 10 , 60 , 61] . However , in the current study , disruption of C5a-C5aR signaling did not significantly reverse the vascular changes and did not provide a clear explanation for the cognitive phenotype observed and its rescue with C5aR blockade Inflammatory conditions during pregnancy are associated with poor neurodevelopmental outcomes [25 , 44 , 62 , 63] . For example , maternal IL-6 cytokine surges have been reported to induce an increase in the forebrain neural precursor pool via activation of the embryonic neural stem cell self-renewal pathway [64] . Such inflammation-induced changes in early neurogenesis could have a significant impact on cognitive development . We have previously shown that C5a can enhance pro-inflammatory cytokine responses , including IL-6 , to malaria-infected erythrocytes [11] . Our data do not exclude a role for neuro-inflammation in EMIP-associated adverse neurocognitive outcomes but rather suggest that both enhanced inflammation and altered neurodevelopment may be mediated through a shared pathway , C5a-C5aR signaling . In summary , we show that in utero exposure to malaria infection disrupts normal cognitive and neurological development of offspring in a model of MIP and implicate activation of C5 in the pathobiology of this phenotype . In the clinical setting , MIP is commonly associated with LBW and there is a well-established link between LBW and increased risk of developmental delay [26 , 27] . Therefore , the cognitive deficits we observed would be expected to be incrementally increased by other MIP-associated birth complications including LBW caused by fetal growth restriction and preterm birth . Collectively our observations suggest a broader potential impact of malaria exposure in utero on neurocognitive outcomes since many malaria infections in pregnancy do not result in an obvious birth phenotype . Factors that prevent normal neurological development of successive generations of children place enormous financial and social burdens on low resource countries . Persistent neurocognitive impairments as a result of MIP could have broad implications as pregnancies that occur in malaria endemic regions are at risk of MIP [65] . It is essential to identify preventable risk factors that contribute to developmental delay in children . Our data suggest that MIP is one such factor that can be targeted in order to improve cognitive development and school performance in malaria-endemic regions . A prospective study is underway to confirm these findings in children exposed to malaria in utero in sub-Saharan Africa ( NCT01669941 ) .
The EMIP model used in this study was based on a previously validated murine model of MIP , which replicates key pathogenic factors of MIP [28] . Female BALB/c mice ( wild-type or C5ar-/- ) between 6–8 weeks of age were mated with male BALB/c ( wild-type or C5ar-/- ) mice ( 8–9 weeks ) were obtained from Jackson Laboratories ( Bar Harbor , ME ) . C5ar-/- females were mated with C5ar-/- males , therefore all offspring were also C5ar-/- . Naturally mated pregnant mice were infected on G13 with 105 P . berghei ANKA-infected erythrocytes in RPMI media via injection into the lateral tail vein . A lower dose of innoculum ( 105 P . berghei ANKA-infected erythrocytes compared with 106 ) was used in this study to eliminate a low birth weight phenotype and increase the number of live births . Control pregnant females were injected on G13 with RPMI media alone . Thin blood smears were taken daily and stained with Giemsa stain ( Protocol Hema3 Stain Set , Sigma , Oakville , ON ) to monitor parasitemia . For pharmacological blockade experiments polyclonal rabbit antiserum raised against rat C5a or pre-immune control rabbit antiserum ( Sigma G9023 ) was administered via tail vein injection 2 hours prior to malaria infection ( 0 . 25mL ) and 72 hours post infection ( G16 ) ( 0 . 25mL ) . Immediately following delivery all pups were given to surrogate ( BALB/c wild-type ) dams . All mice were weighed weekly beginning at one week of age . All litters were weaned at 3 weeks of age . All experimental protocols were approved by the University Health Network Animal Care Committee ( Animal Use Protocol number 1615 5/01/2014 ) and performed in accordance with the Canadian Council of Animal Care guidelines and current University Health Network regulations . Placental tissue was collected from uninfected and malaria-infected females at gestational day 19 and whole placentas were immediately fixed in 20x volume of 10% formalin for 48 hours then transferred to 70% alcohol . Paraffin-embedded non-consecutive sections were stained for hemotoxylin-eosin ( H&E ) and examined under a light microscope ( Olympus , BX41 , Olympus Corporation ) . Behavioral testing was conducted with male offspring beginning at 4 weeks of age and terminating at 7 weeks of age in the order the tests are presented below . In some experiments , testing was performed at 20 weeks . During testing , the experimenter alternated between testing mice from each experimental group . Offspring from a minimum of 4 different litters were used in each testing cohort . All testing was done with the experimenter blinded to the testing group . A separate group of male offspring were behaviourally tested in the NOR test and TST at 5–6 weeks ( Fig 1 ) and were euthanized at 8 weeks of age for MRI . All animals were weighed prior to behavioral testing and prior to perfusion . To minimize the likelihood of neurological changes resulting from behavioral tests using aversive stimuli , as in the CFC test , offspring to be perfused for MRI were only tested in the NOR and TST . Microwave fixation of tissue was used to examine biochemical changes in biogenic amines as they relate to treatment group and performance in behavioral paradigms . All mice were tested prior to microwave fixation in the NOR test and TST . The microwave fixation procedures used here have been previously described in detail [30] . Briefly , all mice were euthanized at 8 weeks of age with a brief pulse ( ~0 . 9s ) of high intensity microwave radiation ( 8 kW , 60Hz , 56 Amp ) focused to the head and administered by a 10 KW magnetron ( model TMW-4012C , Muromachi Kikai , Tokyo , Japan ) . Microwave fixation allows for rapid heat-inactivation of enzymes in situ and avoids confounding results due to post-mortem changes . Immediately following heat-inactivation , the heat-inactivated brains were dissected regionally on ice and stored at -80°C prior to analysis . Levels of dopamine ( DA ) , norepinephrine ( NE ) , serotonin ( 5-HT ) and metabolites were assayed in perchloric acid tissue extracts with a Dionex HPLC system and electrochemical detector ( DIONEX , Sunnyvale , CA , USA ) . Biogenic amines were selected based on extensive evidence linking these neurotransmitters with learning , memory and behavioural performance . HPLC was performed only on tissue from the temporoparietal cortex , frontal cortex , striatum , hippocampus and cerebellum based on the well-established role of these specific regions in learning , memory and motor behavior which impact performance in the NOR and TST [30 , 36 , 37 , 51 , 54] . As described previously , the chromatographic conditions included a C18 reverse-phase column ( Acclaim 120 , 150 x 4 . 0 mm2 cartridge , 5 μm particle size ) at 30°C . The mobile phase consisted of sodium acetate ( 100 mM ) tetrasodium EDTA ( 0 . 125 mM ) , 1-octane sufonic acid ( 432 mg/l ) and 5 . 0% methanol ( final pH = 3 . 6 ) , delivered at a flow rate of 0 . 75 mL/min with a UltiMate 3000 pump . Samples ( 25 μl ) were injected automatically with a refrigerated autosampler ( UltiMate 3000 autosampler ) . The electrochemical detection ( ESA Coulochem III 5011A analytical cell with a 5020 guard cell ) was conducted at a working electrode potential of -400 mV . Uteri were extracted from dams at gestational day 18 and anesthetized via hypothermia ( immersion in ice-cold PBS ) . Each individual fetus is then extracted from the uterus while maintaining the vascular connection to the placenta . The embryo is briefly resuscitated via immersion in warm PBS to resume blood circulation . Embryo’s that could not be resuscitated are not perfused and were removed from the study . A catheter is then inserted into the umbilical artery and the fetus is perfused with saline ( with heparin , 100units/mL ) followed by radio-opaque silicone rubber contrast agent ( Microfil; Flow Technology , Carver , MA ) . The perfusions were performed using two different lots of Microfil . Following perfusion specimens are post-fixed with 10% Formalin and imaged using micro-computed tomography ( micro-CT ) . Specimens were scanned at 7 . 6 um resolution for 1 hour using a Bruker SkyScan1172 high resolution Micro-CT scanner . 996 views were acquitted via 180-degree rotation with an X-ray source at 54 kVp and 185 uA . Three-dimensional micro-CT data were reconstructed using SkyScan NRecon software . Each micro-CT image was manually masked to exclude extracerebral vessels using a cerebral vascular atlas as a guide [69] . The structure of the vasculature was identified automatically using a segmentation algorithm as described in detail previously [35] . Images that showed evidence of rupture of a major vessel or incomplete perfusion of Microfil were excluded from the analysis ( 9 of 38 specimens , S3 Table ) . Univariate ANCOVAs were conducted to compare the number of vessel segments and the total length of all vessel segments as a function of group , with dataset as a covariate ( to control for the variance from using different lots of Microfil ) . A linear model was used to estimate the effect of dataset and the total segments and length were adjusted accordingly . Tukey contrasts were used to test differences between the adjusted means . Analysis was performed on wild-type ( unexposed ( n = 8 ) and malaria exposed ( n = 7 ) ) and C5aR knock out mice ( unexposed ( n = 7 ) and malaria exposed ( n = 7 ) ) . RNA extraction was performed on snap-frozen fetal brain tissue and placental tissue collected at G19 . The EMIP model followed the same protocol outlined above . Dams were sacrificed at G19 , yolk sacs were dissected from uteri , fetuses were removed and weighed , and fetal brain tissue and placentas were snap frozen and stored at -80°C until analyzed . Fetal viability was determined by assessing pedal withdrawal reflex . Non-viable fetuses ( i . e . , lacking the pedal withdrawal reflex ) were considered aborted . Only viable fetuses and placentas from viable fetuses were used in the analysis . Tissue was homogenized in TRIzol ( 0 . 5mL/100mg tissue; Invitrogen , Burlington , ON ) according to the manufacturer’s protocol and RNA was extracted . Extracted RNA ( 2 μg per sample ) was then treated with DNase I ( Ambion , Streetsville , ON ) and reverse transcribed to cDNA with SuperScript III ( Invitrogen , Burlington , ON ) in the presence of oligo ( dT ) primers ( Fermentas , Burlington , ON ) with sequences listed below . Residual RNA was degraded with RNase H ( Invitrogen , Burlington , ON ) . Sample cDNA was amplified in triplicate with SYBR Green master mix ( Roche , Laval , QC ) in the presence of 1 μM both forward and reverse primers in a Light Cycler 480 ( Roche , Laval , QC ) . Transcript number was calculated based on Ct compared to the standard curve of mouse genomic DNA included on each plate by Light Cycler 480 software ( Roche , Laval , QC ) , and expression in fetal brain was normalized to geometric average of the housekeeping genes GAPDH and β-actin expression levels . Expression in placental tissue was normalized to the housekeeping genes GAPDH and HPRT . A normalization factor was generated for each sample by dividing the mean sample expression by the mean expression of the housekeeping genes . The expression of each target gene was then divided by the normalization factor for that sample to adjust for experimental variation in gene expression [70] . RPTCR Primer Sequences: ( 5’–3’ ) : GAPDH: TCAACAGCAACTCCCACTCTTCCA–TTGTCATTGAGAGCAATGCCAGCC , β-actin: GCGCCCATGAAAGAAGTAAAA–TTCGATGACGTGCTCAAAAG , HPRT: GGAGTCTGTTGATGTTGCCAGTA–GGGACGCAGCAACTGACATTTCTA , BDNF: GCGCCCATGAAAGAAGTAAA–TTCGATGACGTGCTCAAAAG . ICAM-1: CGGAAGGGAGCCAAGTAACTG–CGACGCCGCTCAGAAGAA , TNF: GACAGACATGTTTTCTGTCAAACG–AAAAGAGGAGGCAACAAGGTAGAG , IFNγ: TTCTGTCTCCTCAACTATTTCTCTTTG—CCCCACCCCCAGATACAAC , MCP: ACCACAGTCCATGCCATCAC—TTGAGGTGGTTGTGAAAAG Student’s t-test , one-way ANOVA or ANCOVA ( non-parametric Kruskal-Wallis , P < 0 . 05 ) was used to examine statistical significance between experimental groups where indicated . Post-tests on all groups were conducted using Dunn’s multiple comparison test or Tukey contrasts where indicated ( P < 0 . 05 ) .
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A growing body of evidence has established the importance of the in utero environment on neurodevelopment and long-term cognitive and behavioral outcomes . These data suggest factors that disrupt the tightly regulated in utero environment can modify normal neurodevelopmental processes . Approximately 125 million pregnancies worldwide are at risk of malaria infection every year . However the impact of in utero exposure to MIP on fetal neurodevelopment is unknown . Here we use a mouse model of malaria in pregnancy to examine the impact of maternal malaria exposure on neurocognitive outcomes in offspring . We observed impaired learning and memory and depressive-like behavior in malaria-exposed offspring that were neither congenitally infected nor low birth weight . These neurocognitive impairments were associated with decreased tissue levels of neurotransmitters in regions of the brain linked to the observed deficits . Disruption of maternal C5a complement receptor signaling restored the levels of neurotransmitters and rescued the associated cognitive phenotype observed in malaria-exposed offspring . This study provides the first evidence implicating a causal link between pre-natal exposure to malaria , complement signaling and subsequent neurocognitive impairment in offspring .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[] |
2015
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Experimental Malaria in Pregnancy Induces Neurocognitive Injury in Uninfected Offspring via a C5a-C5a Receptor Dependent Pathway
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High-throughput mRNA sequencing ( RNA-Seq ) is widely used for transcript quantification of gene isoforms . Since RNA-Seq data alone is often not sufficient to accurately identify the read origins from the isoforms for quantification , we propose to explore protein domain-domain interactions as prior knowledge for integrative analysis with RNA-Seq data . We introduce a Network-based method for RNA-Seq-based Transcript Quantification ( Net-RSTQ ) to integrate protein domain-domain interaction network with short read alignments for transcript abundance estimation . Based on our observation that the abundances of the neighboring isoforms by domain-domain interactions in the network are positively correlated , Net-RSTQ models the expression of the neighboring transcripts as Dirichlet priors on the likelihood of the observed read alignments against the transcripts in one gene . The transcript abundances of all the genes are then jointly estimated with alternating optimization of multiple EM problems . In simulation Net-RSTQ effectively improved isoform transcript quantifications when isoform co-expressions correlate with their interactions . qRT-PCR results on 25 multi-isoform genes in a stem cell line , an ovarian cancer cell line , and a breast cancer cell line also showed that Net-RSTQ estimated more consistent isoform proportions with RNA-Seq data . In the experiments on the RNA-Seq data in The Cancer Genome Atlas ( TCGA ) , the transcript abundances estimated by Net-RSTQ are more informative for patient sample classification of ovarian cancer , breast cancer and lung cancer . All experimental results collectively support that Net-RSTQ is a promising approach for isoform quantification . Net-RSTQ toolbox is available at http://compbio . cs . umn . edu/Net-RSTQ/ .
Application of next generation sequencing technologies to mRNA sequencing ( RNA-Seq ) is a widely used approach in transcriptome study [1–3] . Compared with microarray technologies , RNA-Seq provides information for expression analysis at transcript level and avoids the limitations of cross-hybridization and restricted range of the measured expression levels . Thus , RNA-Seq is particularly useful for quantification of isoform transcript expressions and identification of novel isoforms . Accurate RNA-Seq-based transcript quantification is a crucial step in other downstream transcriptome analyses such as isoform function prediction in the pioneer work in [4] , and differential gene expression analysis [5] or transcript expression analysis [6] . Detecting biomarkers from transcript quantifications by RNA-Seq is also a frequent common practice in biomedical research . However , transcript quantification is challenging since a variety of systematical sampling biases have been observed in RNA-Seq data as a result of library preparation protocols [7–10] . Moreover , in the aligned RNA-Seq short reads , most reads mapped to a gene are potentially originated by more than one transcript . The ambiguous mapping could result in hardly identifiable patterns of transcript variants [10 , 11] . A useful prior knowledge that has been largely ignored in RNA-Seq transcriptome quantification is the relation among the isoform transcripts by the interactions between their protein products . The protein products of different isoforms coded by the same gene may contain different domains interacting with the protein products of the transcripts in other genes . Previous studies suggested that alternative splicing events tend to insert or delete complete protein domains/functional motifs [12] to mediate key linkages in protein interaction networks by removal of protein domain-domain interactions [13] . The work in [4 , 14] also suggested unique patterns in isoform co-expressions . Thus , the abundance of an isoform transcript in a gene can significantly impact the quantification of the transcripts in other genes when their protein products interact with each other to accomplish a common function as illustrated by a real subnetwork in Fig 1 , which is constructed based on domain-domain interaction databases [15 , 16] and Pfam [17] . Motivated by our observation that the protein products of highly co-expressed transcripts are more likely to interact with each other by protein domain-domain binding in four TCGA RNA-Seq datasets ( see the section Results ) , we constructed two human transcript interaction networks of different sizes based on protein domain-domain interactions to improve transcript quantification . Based on the constructed transcript network , we propose a network-based transcript quantification model called Net-RSTQ to explore domain-domain interaction information for estimating transcript abundance . In the Net-RSTQ model , Dirichlet prior representing prior information in the transcript interaction network is introduced into the likelihood function of observing the short read alignments . The new likelihood function of Net-RSTQ can be alternating-optimized over each gene with expectation maximization ( EM ) . It is important to note that the Dirichlet prior from the neighboring isoforms play two possible roles . On one hand , for the isoforms in the same gene but with different interacting partners , the different prior information will help differentiate their expressions to reflect their different functional roles . On the other hand , for the isoforms in the same gene with the same interacting partners , the uniform prior assumes no difference in their functional roles and thus , promotes a smoother expression patterns across the isoforms . In both cases , the Dirichlet prior captures the functional variations/similarities across the isoforms in each gene as prior information for estimation of their abundance . The paper is organized as following . In the section Materials and Methods , we describe the procedure to construct protein domain-domain interaction networks , the mathematic description of the probabilistic model and the Net-RSTQ algorithm , qRT-PCR experiment design , and RNA-Seq data preparation . In the section Results , we first demonstrate the correlation between protein domain-domain interactions and isoform transcript co-expressions across samples in four cancer RNA-Seq datasets from The Cancer Genome Atlas ( TCGA ) to justify using domain-domain interactions as prior knowledge . We then compared the predicted isoform proportions with qRT-PCR experiments on 25 multi-isoform genes in three cell lines , H9 stem cell line , OVCAR8 ovarian cancer cell line and MCF7 breast cancer cell line . Net-RSTQ was also applied to four cancer RNA-Seq datasets to quantify isoform expressions to classify patient samples by the survival or relapse outcomes . In addition , simulations were also performed to measure the statistical robustness of Net-RSTQ over randomized networks .
Two binary transcript networks were constructed by measuring the protein domain-domain interactions ( DDI ) between the domains in each pair of transcripts in four steps . First , the translated transcript sequences of all human genes were obtained from RefSeq [18] . Second , Pfam-Scan was used to search Pfam databases for the matched Pfam domains on each transcript with 1e-5 e-value cutoff [17] . Note that only high quality , manually curated Pfam-A entries in the database were used in the search . Third , domain-domain interactions were obtained from several domain-domain interaction databases , and if any domain-domain interaction exists between a pair of transcripts , the two transcripts are connected in the transcript network . Specifically , 6634 interactions between 4346 Pfam domain families from two 3D structure-based DDI datasets ( iPfam [15] and 3did [16] ) inferred from the protein structures in Protein Data Bank ( PDB ) [19] were used in the experiments . Besides these highly confident structure-based DDIs , transcript interactions constructed from 2989 predicted high-confidence DDIs and 2537 predicted medium-confidence DDIs in DOMINE [20] were also included if the transcript interaction agrees with protein-protein interactions ( PPI ) in HPRD [21] . In the experiments , we focused on the transcripts from two cancer gene lists from the literature for better reliability in annotations . The first smaller transcript network consists of 11736 interactions constructed from the 3D structure-based DDIs and 421 interactions constructed from the predicted DDIs among the 898 transcripts in 397 genes from the first gene list [22] . The second larger transcript network contains 711 , 516 interactions constructed from the 3D structure-based DDIs among 5599 transcripts in 2551 genes in a larger gene list [23] . Since inclusion of the predicted DDIs results in a much higher density in the large network , the large network does not include predicted DDIs to prevent too many potential false positive interactions . The characteristics of the two transcript networks are summarized in Table 2 . The density of the two networks are 3 . 02% and 4 . 54% respectively , which are in similar scale with the PPI network . Both networks show high clustering coefficients , suggesting modularity of subnetworks . Note that self-interactions ( interactions between transcript ( s ) in the same gene ) are not considered since Net-RSTQ only utilizes positive correlation between the expressions of neighboring transcripts in different genes . For simplicity , Net-RSTQ assumes that self-interactions will not change the transcript quantification of an individual gene in the model . In Fig 1 ( A ) a subnetwork of the transcripts in gene CD79A and CD79B with their direct neighbors in the small transcript network is shown . The RefSeq transcript annotations of CD79A and CD79B are shown in Fig 1 ( B ) . In CD79A transcript NM_001783 contains an extra domain pfam07686 while transcript NM_021601 only contains a shorter hit pfam02189 . Note that pfam02189 also has the same hit in NM_001783 with an e-value larger than 1e-5 . In CD79B transcripts NM_001039933 and NM_000626 contain a domain pfam07686 , which is removed in alternative splicing of NM_021602 . In the transcript subnetwork shown in Fig 1 ( A ) , the transcripts in CD79A or CD79B have different interaction partners in the network . In the transcripts in CD79A , the expression of NM_021601 will correlate with the transcripts in LCK and SYK , and NM_001783 will correlate with two transcripts in CD79B . The isoform transcripts in LCK and SYK show no different DDIs suggesting there is no functional variation by protein bindings and more similar expression patterns are potentially expected as prior knowledge . We first consider the method proposed in [24 , 25] as the base model for quantification of the transcripts in a single gene . Let Ti denote the set of the transcripts in the ith gene and Tik be the kth transcript in Ti . The probability of a read being generated by the transcripts in Ti is modeled by a categorical distribution specified by parameters pik , where ∑ k = 1 | T i | p i k = 1 and 0 ≤ pik ≤ 1 . For the set of the reads ri aligned to gene i , we consider the likelihood of that each of the |ri| short reads is sampled from one of the transcripts to which the read aligns . Specifically , for each read rij aligned to transcript Tik , the probability of obtaining rij by sampling from Tik , namely Pr ( rij|Tik ) is q i j k = 1 l i k - l r + 1[8 , 26 , 27] , where lr is the length of the read . Assuming each read is independently sampled from one transcript , the uncommitted likelihood function [24] to estimate the parameters Pi from the observed read alignments against gene i is L ( P i ; r i ) = P r ( r i | P i ) = ∏ j = 1 | r i | P r ( r i j | P i ) = ∏ j = 1 | r i | ∑ k = 1 | T i | P r ( T i k | P i ) P r ( r i j | T i k ) = ∏ j = 1 | r i | ∑ k = 1 | T i | p i k q i j k . ( 1 ) This likelihood function is concave but it may contain plateau in the likelihood surface . Therefore , Expectation Maximization ( EM ) is then applied to obtain the optimal Pi . In the EM algorithm , the expectation of read assignments to transcripts were estimated in the E-step and the likelihood function with the expected assignments can be maximized in the M-step to estimate Pi . The relative abundance of the transcript Tik in gene i , ρik , can be derived from ρ i k = p i k l i k ∑ k = 1 | T i | p i k l i k , ( 2 ) and the transcript expressions in gene i , πik , can be calculated by π i k = | r i | p i k l i k . ( 3 ) The base model is applied independently to each individual gene and no relation among the transcripts is considered . In the Net-RSTQ model , the transcript interaction network S based on protein domain-domain interactions is introduced to calculate a prior distribution for estimating P jointly across all the genes and all the transcripts . The model assumes that the prior distribution of Pi is a Dirichlet distribution specified by parameters αi and each αik is proportional to the read count by average expression of the transcript Tik’s neighbors in the transcript network S . The prior read count ϕik is defined as follows , ϕ i k = l i k ( π ′ S * , ( i , k ) ∑ ( S * , ( i , k ) ) ) , ( 4 ) where S* , ( i , k ) is a binary vector represents the neighborhood of transcript Tik in transcript network S and ∑ ( S* , ( i , k ) ) is the size of the neighborhood . The calculation of each ϕik is illustrated in Fig 2 . The Dirichlet parameter αi is defined as a function of ϕik as α i k = λ ϕ i k + 1 , ( 5 ) where λ > 0 is a tuning parameter balancing the belief between the prior-read count and the aligned-read count . To obtain the optimal P jointly for all genes , we introduce a pseudo-likelihood model to estimate P iteratively in each iteration . Assuming uniform Pr ( ri ) , the pseudo-likelihood function is defined as , L ( P , α ; r ) = ∏ i = 1 N L ( P i , α i ; r i ) = ∏ i = 1 N P r ( P i | α i ) P r ( r i | P i ) P r ( r i ) ∝ ∏ i = 1 N P r ( P i | α i ) P r ( r i | P i ) . ( 6 ) Note that the pseudo-likelihood model relies on the independence assumption among the likelihood functions of each individual gene when the α parameters of the Dirichlet priors are pre-computed . Thus , the model simply takes the product of the likelihood function from each gene . Each prior distribution Pr ( Pi|αi ) follows the Dirichlet distribution , P r ( P i | α i ) = C ( α i ) ∏ k = 1 | T i | p i k α i k - 1 , where C ( α i ) = Γ ( ∑ k α i k ) ∏ k Γ ( α i k ) . ( 7 ) Integrating eqs ( 1 ) and ( 7 ) , the pseudo-likelihood function in eq ( 6 ) can be rewritten with Dirichlet prior as L ( P ; r ) = ∏ i = 1 N C ( α i ) ∏ k = 1 | T i | p i k α i k - 1 ∏ j = 1 | r i | ∑ k = 1 | T i | p i k q i j k = ∏ i = 1 N C ( λ ϕ i + 1 ) ∏ k = 1 | T i | p i k λ ϕ i k ∏ j = 1 | r i | ∑ k = 1 | T i | p i k q i j k . ( 8 ) In the pseudo-likelihood function in eq ( 8 ) , the only hyper-parameter λ balances the proportion between the Dirichlet priors and the observed read counts of each transcript . The larger the λ , the more belief put on the priors . The Net-RSTQ algorithm optimizes eq ( 8 ) by dividing the optimization into sub-optimization problems of sequentially estimating each Pi . Specifically , we fix all Pc , c ≠ i , and thus ϕi when estimating Pi with EM in each iteration and repeat the process multiple rounds throughout all the genes . In each step , the neighborhood expression ϕ is recomputed with new Pi for computing the quantification of the next gene . For each sub-optimization problem , we estimate Pi with a fixed ϕ , the part of the likelihood function in eq ( 8 ) involved with the current variables Pi is L ¯ ( P i ; r i ) = ∏ g ∈ n b ( i ) C ( λ ϕ g + 1 ) ∏ k = 1 | T g | p g k λ ϕ g k C ( λ ϕ i + 1 ) ∏ k = 1 | T i | p i k λ ϕ i k ∏ j = 1 | r i | ∑ k = 1 | T i | p i k q i j k , ( 9 ) where nb ( i ) is the set of the genes containing transcripts that are neighbors of the transcripts in gene i in the transcript network . Eq ( 9 ) consists of three terms separated by the braces . The second and the third terms are the Dirichlet prior and the likelihood of the observed counts in the data for gene i . The first term is the Dirichlet priors of the neighbor transcripts of each Tik . These prior probabilities are involved since ϕg are functions of the current variable Pi ( eqs ( 3 ) – ( 5 ) ) . Eq ( 9 ) cannot be easily solved with standard techniques . We adopt a heuristic approach to only take steps that will increase the whole pseudo-likelihood function in eq ( 8 ) . The Net-RSTQ algorithm is outlined below Algorithm 1 Net-RSTQ 1: Initialization: random initialization or base EM ( eq ( 1 ) ) estimation of P ( 0 ) 2: for round t = 1 , … do 3: P ( t ) = P ( t − 1 ) 4: for gene i = 1 , … , N do 5: compute ϕi based on P ( t ) with eqs ( 3 ) and ( 4 ) 6: estimate Pi with EM algorithm ( see next section ) 7: if L ¯ ( P i ) > L ¯ ( P i ( t ) ) then 8: P i ( t ) = P i 9: end if 10: end for 11: if max ( abs ( P ( t ) − P ( t − 1 ) ) ) <1e-6 then 12: break 13: end if 14: end for 15: return P In the algorithm , the outer for-loop between line 2–14 performs multiple passes of updating P . The inner for-loop between line 4–10 scans through each gene to update each Pi . Line 7 checks the the difference in the likelihood L ¯ of gene i before and after the estimated Pi is applied . The newly estimated Pi is kept in line 8 only if the likelihood L ¯ in eq ( 9 ) is higher . The convergence of P is checked at line 11 . In each sub-optimization problem , EM algorithm ( described in the next section ) is applied to estimate Pi . After convergence , the transcripts expression π can be learned by eq ( 3 ) with the optimal P . In line 6 of Algorithm 1 , we maximize the likelihood function of the sub-optimization problem in eq ( 9 ) to learn Pi as L ( P i ; r i ) = C ( λ ϕ i + 1 ) ∏ k = 1 | T i | p i k λ ϕ i k ∏ j = 1 | r i | ∑ k = 1 | T i | p i k q i j k . ( 10 ) Note that eq ( 10 ) is the part of eq ( 9 ) without the Dirichlet priors of the neighboring genes . In line 7 of Algorithm 1 , the ignored Dirichlet priors are combined with the likelihood in eq ( 10 ) , when L ¯ ( P i ) is computed , to evaluate the whole likelihood in eq ( 9 ) . The likelihood function in eq ( 10 ) is defined on a categorical variable with Dirichlet prior , which can be solved with EM algorithm . Following EM formulation in [26] , the expectation aijk , a soft assignment of read j to transcript k in gene i , is first estimated in the expectation step and Pi is then learned in the maximization step . When ϕi is given , by taking log of eq ( 10 ) we can write the EM steps to find Pi below . Three qRT-PCR experiments are designed to measure the isoform proportions of 25 multi-isoform genes in three cell lines , H9 stem cell line , OVCAR8 ovarian cancer cell line and MCF7 breast cancer cell line . The cell lines were selected based on the available of both RNA-Seq data and cell culture in our labs . The qRT-PCR experiments focused on the gene with most different quantification results reported by Net-RSTQ and other compared methods . Due to the limitations in time and cost of running qRT-PCR experiments , only the 25 genes in the three cell lines were tested with all the results reported in the experiments . Quantitation of the real-time PCR results was done on the data from H9 human embryonic stem cells to obtain the absolute expressions for comparing more than two transcripts and comparative Ct method was done on the data from OVCAR8 ovarian cancer cells and MCF7 breast cancer cells to obtain the ratio between a pair of transcripts . Three cell line RNA-Seq datasets were used for evaluating the accuracy of transcript quantification by comparison with qRT-PCR results . The first dataset is the H9 embryonic stem cell line data from [28] , downloaded from SRA . The second dataset is an in-house dataset from the ovarian cancer cell line OVCAR8 prepared at University of Kansas Medical Center . The third dataset is the MCF7 breast cancer cell line data from [29] , downloaded from SRA . There are 23 , 397 , 325 single-end 34bp reads in the stem cell line dataset , 19 , 892 , 473 paired-end 100bp reads in the OVCAR8 , and 21 , 855 , 632 paired-end 76bp reads in the MCF7 mapped to the human hg19 reference genome by TopHat2 . 0 . 9 [30] with up to 2 mismatches allowed . Exon coverages and read counts of exon-exon junctions were generated by SAMtools [31] to be utilized with Net-RSTQ and base EM ( eq ( 1 ) ) . Cufflinks [32] directly infers transcript expressions based on the alignment by TopHat with the min isoform fraction set to 0 for better sensitivity . TCGA RNA-Seq datasets of Ovarian serous cystadenocarcinoma ( OV ) , Breast invasive carcinoma ( BRCA ) , Lung adenocarcinoma ( LUAD ) and Lung squamous cell carcinoma ( LUSC ) were analyzed for patient outcome prediction with transcript expressions estimated by Net-RSTQ , base EM ( eq ( 1 ) ) , RSEM [33] and Cufflinks [32] . Both the gene expression and transcript expression data reported by RSEM [33] in TCGA ( level 3 data ) were utilized as two baselines for cancer outcome prediction . The raw RNA-Seq fastq files ( level 1 data ) were downloaded from Cancer Genomics Hub ( CGHub ) and processed by TopHat for use with Net-RSTQ , base EM and Cufflinks . The patient samples in each dataset were classified into cases and controls based on the survival and relapse outcomes as shown in Table 3 . The command lines for preparing the data with RSEM and Cufflinks are available in the S3 Text .
To investigate the correlation between protein domain-domain interactions and isofrom transcript co-expressions , we calculated the number of transcript pairs that are both nearby ( being neighbors or having a distance up to 2 ) in the transcript network and highly co-expressed in the TCGA samples . The transcript co-expressions were calculated by Pearson’s correlation coefficients of each pair of transcripts across all the samples in each dataset with the isoform transcript quantification by Cufflinks . The transcript pairs were then sorted by the correlation coefficients from the largest to the smallest and grouped into bins of size 1000 . The number of transcript pairs that are nearby in the transcript networks out of 1000 pairs are calculated within each bin and plotted in Fig 3 ( A ) and 3 ( B ) for the two cancer gene lists , respectively . In both Fig 3 ( A ) and 3 ( B ) , the left column shows the plots of the number of pairs that are neighbors in the transcript network , and the right column shows the plots of the number of transcript pairs with a distance up to 2 in the transcript network , among the 1000 pairs in each bin . In all the plots , similar trends are observed in all the four cancer datasets: there are more interacting isoform pairs in the bins with higher co-expressions . For example , among the 1000 transcript pairs with the highest correlation coefficients , there are 73 interactions in the transcript network in OV dataset and thus , 73 interactions ( y-axis ) for bin index 1 ( x-axis ) is plotted in the left column of Fig 3 ( A ) . In all the plots , there is a clear pattern that the numbers of matched nearby transcripts in the transcript network among the 1000 pairs in the first few bins are higher than the expected average of 30 in the small network of density 3 . 02% , 114 in the small network of density 11 . 41% ( with distance up to 2 ) , 45 in the larger network of density 4 . 54% , and 203 in the larger network of density 20 . 33% ( with distance up to 2 ) . Moreover , the 2-step walk clearly promoted the number of overlaps with the pairs of higher co-expressions in the small network . For example , the significant overlap is extended from the first 25 bins to approximately the first 50 bins or more in the four datasets . The observation suggests that higher co-expressions exist not only in the direct neighbors in the transcript network but also the nearby nodes by a small distance . By exploring the network structure with prior information through neighbors by many steps in iterations , Net-RSTQ model is expected to propagate the expression values from each transcript to its nearby nodes in the network to capture the co-expressions . Note that considering the neighboring pairs with distance up to 2 in the larger network will result in a graph of density 20 . 33% , which is likely to contain too many false relations by the two-step walk . Thus , the plots of the larger network of distance-2 pairs are only included for the completeness of the analysis . The canonical 2x2 chi-square test was also applied to compare the number of the domain-domain interactions in the first 10 , 000 transcript pairs ( first 10 bins ) with the number in the rest of the pairs . In all the four datasets in both Fig 3 ( A ) and 3 ( B ) with one exception in the LUSC dataset on the large network of distance-2 relation , there is a significant difference that the highly co-expressed transcripts are more likely to interact with each other in the transcript network , confirmed by the significant p-values . As explained previously , the exception is likely due to the large number of false-positive pairs in the dense network . The observation further support the hypothesis that protein domain-domain interactions correlate transcript co-expressions reported in previous studies [12 , 13] . To further understand the specificity of the domain-domain interactions in the highly co-expressed transcripts , we calculated the number of domain-domain pairs that construct the DDIs in the top 10 , 000 co-expressed transcript pairs . The statistics suggest high diversity of the type of DDIs . For example , there are 547 interacting transcript pairs among the 201 out of 898 transcripts in the top 10 , 000 co-expressed transcript pairs in OV dataset for small network . The 547 interacting transcript pairs represent 770 different domain-domain interactions ( There might be more than one DDIs between a pair of transcripts ) . There are 739 interacting transcript pairs among the 538 out of 5599 transcripts in the top 10 , 000 co-expressed transcript pairs in OV dataset for large network . The 739 interacting transcript pairs represent 1277 different domain-domain interactions . The statistics suggest that the correlation between protein domain-domain interactions and transcript co-expressions is not a bias due to a few highly spurious DDIs . It is a general correlation in many different DDIs and co-expressed transcripts . Very similar statistics were observed in all the datasets and both networks . To further demonstrate the co-expression relations in the transcript network , two examples are shown in S1 Fig . In S1 ( A ) Fig , WHSC1L1 contains two isoforms connected with different interactions in the transcript network . Isoform NM_017778 interacts with 12 transcripts with average correlation coefficients 0 . 22 and the other isoform NM_023034 interacts with 13 more transcripts with average correlation coefficients 0 . 30 compared with the average correlation coefficient 0 . 188 against the other unconnected isoforms across the samples in the OV dataset . In S1 ( B ) Fig , gene BRD4 contains two isoforms both of which are connected with the same 14 neighbors in the network . The average correlation coefficients between these two isoforms and the 14 neighboring isoforms are both above 0 . 26 compared with the average correlation coefficient less than 0 . 15 against the other unconnected isoforms across the samples on the BRCA dataset . In both examples , we observed high degree of agreement between co-expressions and DDIs . To further understand the transcript networks , we overlapped the DDIs between genes in the two networks with the 294 human KEGG pathways [34] . Among the 397 genes in the small network , 10 . 97% ( 17284 ) of the pairs are co-members in at least one KEGG pathway . The 10 . 97% KEGG co-member pairs covers 42 . 70% ( 2122 ) of the DDIs among the genes while the other 89 . 03% ( 140352 ) non-co-member pairs covers 57 . 30% ( 2748 ) of the DDIs . By these numbers , there is about 6-fold enrichment of DDIs in the KEGG co-member genes in the small network . Among the 2551 genes in the large network , the 5 . 15% ( 335372 ) KEGG co-member pairs covers 12 . 45% ( 40812 ) of the DDIs among genes while the other 94 . 85% ( 6172229 ) non-co-member pairs covers 87 . 55% ( 287090 ) of the DDIs . By these numbers , there is about 2 . 6-fold enrichment of DDIs in the KEGG co-member genes in the large network . We also list the KEGG pathways that are highly enriched with DDIs in the large network in S4 Table . Specifically , we consider the subnetwork of genes that are members of one KEGG pathway and calculated the density of DDIs in the subnetwork to compare to the overall density of 5 . 04% in the whole network . Interestingly , most of the enriched pathways are signaling pathways and disease pathways with very high DDI densities . In the simulations , we applied flux-simulator [35] to generate paired-end short reads simulating real RNA-Seq experiment in silico based on a ground truth transcript expression profile , using hg19 reference human genome and RefSeq annotations downloaded from UCSC Genome Browser . To generate the ground-truth expression profiles , the gene expressions were sampled from a poisson distribution and the proportions of the isoforms in each gene were derived based on a neighbor average expression in the small transcript network and an initial mixed power law expression profile with gaussian noise . A sequential updating was used to compute the proportion of each isoform by adding the neighbors’ average expressions to the initial expression . The update procedure can be found in the S2 Text . At last , flux-simulator was applied to simulate the short reads based on the ground truth transcript expression file . 15 million 76-bp paired reads were generated by Flux Simulator and mapped to the reference genome by TopHat [30] with up to two mismatches allowed . To account for the large dynamic range of abundances , the expressions were normalized by log2 ( expression+1 ) . The correlation coefficients between the transcript abundances estimated by Net-RSTQ under various λ , base EM ( eq ( 1 ) ) , Cufflinks and RSEM , and the ground truth transcript abundances are reported in Fig 4 . Furthermore , Net-RSTQ was also tested with 100 randomized networks with permuted indexes of transcripts in the transcript network . To assess the impact of the network prior , two cases are shown . Fig 4 ( A ) reports the correlation between the transcripts in which isoforms coded by the same gene are connected with different neighbors ( 109 out of 898 transcripts in 29 genes ) . Fig 4 ( B ) reports the results from all the genes with more than one isoform ( 712 out of 898 transcripts in 211 genes ) . In both comparisons , the transcript expressions estimated by Net-RSTQ achieve higher correlation with the ground truth compared with base EM , Cufflinks and RSEM . Slightly higher improvement was observed in the first case than in the second case since the network prior plays more significant role in differentiating the isoform expressions by their different neighbors . When randomized networks are used , Net-RSTQ leads to similar or worse results due to the wrong prior information . Note that since the datasets were generated to partially conform to the network prior , the isoform expressions are relatively “smooth” among the neighboring isoforms . Net-RSTQ tends to generate smoother expressions than base EM , Cufflinks and RSEM . When applying Net-RSTQ with small λs and randomized network priors , slight improvement was also observed due to the smoothness assumption on the data . To evaluate the effect of missing edges in the transcript network due to the undetected protein domain-domain interactions , we randomly removed certain percentages of the edges in the transcript network and then run Net-RSTQ with λ = 0 . 1 on the incomplete networks . The results are shown in Fig 4 ( C ) and 4 ( D ) for the 109 transcripts with different neighbors and the 712 transcripts in the gene with more than one transcript , respectively . It is intriguing to observe that only when a large percentage of the edges are removed , the performance of Net-RSTQ is affected . Intuitively , the observation can be explained by the fact that the Dirichlet prior parameter is proportional to the average of the neighbors’ expressions . As long as some of the neighbors are still connected to the target transcript in the network , the prior information is still useful . The result suggests that Net-RSTQ is relatively robust to utilize transcript networks potentially constructed with a large percentage of undetected protein domain-domain interactions . The isoform proportions estimated by Net-RSTQ , base EM , RSEM , and Cufflinks were compared to the qRT-PCR results on the three cell lines . Parameter λ = 0 . 1 was fixed in all the Net-RSTQ experiments . Among the genes that Net-RSTQ , base EM , RSEM , and Cufflinks report most different quantification results , qRT-PCR experiments were performed to test the genes with relatively higher coverage of RNA-Seq data , coding two to three isoforms , and the feasibility of designing isoform-specific primers in the qRT-PCR products ( see S1 , S2 and S3 Tables ) . Twenty-five genes in total were tested in the three cell lines: seven in H9 stem cell line , five in OVCAR8 ovarian cancer cell line , and thirteen in MCF7 breast cancer cell line . The scatter plots of the relative abundance of the first transcript in each gene estimated by Net-RSTQ , base EM , Cufflinks and RSEM were compared to the qRT-PCR results in Fig 5 ( A ) and 5 ( E ) . In the scatter plot , the estimated relative abundance by Net-RSTQ were closer to qRT-PCR results measured by the accuracy of various thresholds and Root Mean Square Errors . Net-RSTQ achieved the lowest Root Mean Square Error of 0 . 291 , which is more than 0 . 05 less than 0 . 3435 , the second best achieved by RSEM . In the 20% confidence region , Net-RSTQ puts 59 . 3% of the pairs in the region compared with 37% , 29 . 6% , and 51 . 9% by base EM , Cufflink , and RSEM , respectively . RSEM performed well by putting 37 . 0% of the pairs within 10% confidence regions but performed poorly in about half of the pairs with more than 25% error . The relative abundance of the seven genes in H9 stem cell line is shown in Figs 5 ( B ) and S2 ( A ) and S5 Table . In all seven genes tested , the relative abundance estimated by Net-RSTQ is closer to the qRT-PCR results compare to that by base EM and Cufflinks . RSEM performed similarly well on four genes and worse on the other three genes , CBLC , TCF3 and NPM1 . The same comparison on the five selected genes in OVCAR8 ovarian cancer cell line is shown in Figs 5 ( C ) and S2 ( B ) and S6 Table . Cufflinks reports very low expressions in the first transcript in four genes , three of which do not agree with the highly expressed transcript in the qRT-PCR results . While base EM performed better for two genes ( NSD1 and HNRNPA2B1 ) , Net-RSTQ performed better on the other three genes ( HRAS , TSC2 , and WHSC1L1 ) . Net-RSTQ correctly predicted the overall enrichment of isoforms of HNRNPA2B1 and NSD1 ( NM_031243 > NM_002137 in HNRNPA2B1 and NM_022455 > NM_172349 in NSD1 ) . It is possible that the expressions of NM_002137 transcript in gene HNRNPA2B1 and NM_172349 in gene NSD1 were slightly over-smoothed by network information in Net-RSTQ with the fixed λ parameter . RSEM performed slightly better on WHSC1L1 and NSD1 but much worse in the other three genes . The same comparison on the thirteen genes in MCF7 breast cancer cell line is shown in Figs 5 ( D ) and S2 ( C ) and S7 Table . Cufflinks performed poorly on 8 genes with more than 25% error while RSEM , base EM and Net-RSTQ performed poorly on 5 , 4 and 3 genes , respectively . Overall , Net-RSTQ performed better than base EM and Cufflinks and slightly better than RSEM . In summary , Net-RSTQ improved the overall isoform quantification significantly in the H9 stem cell data and predicted more consistent cases in OVCAR8 and MCF7 cancer cell lines data . Note that there could be more uncertainties in primer designs due to somatic DNA variations and cell differentiation and proliferation in cancer cell lines , potentially a larger variation in the qRT-PCR experiments on the cancer cell lines is expected than H9 stem cell line . To provide an additional evaluation of the quality of transcript quantification , we designed six cancer outcome prediction tasks by the assumption that better transcript quantification always leads to better isoform markers for cancer outcome prediction . Net-RSTQ was compared with base EM , RSEM [33] , and Cufflinks [32] by classification with the quantification of isoform transcripts in two cancer gene lists ( 397 and 2551 genes ) on four cancer datasets . Each dataset is divided into four folds with two folds for training , one fold for validation ( parameter tuning ) , and one fold for test in a four-fold cross-validation . Support Vector Machine ( SVM ) with RBF kernel [36] were chosen as the classifier . We repeated the four-fold cross-validation 100 times by each method in each dataset . The average area under the curve ( AUC ) of receiver operating characteristic of the 100 repeats are reported in Table 4 when the small gene list was used and Table 5 when the large gene list was used . The transcript expressions estimated by Net-RSTQ consistently achieved better average classification results than those by the base EM . To evaluate the statistical significance of the differences between the AUCs generated by Net-RSTQ and the base EM in the 100 repeats , we also report the p-values by a binomial test on the number of wins/loses in all the experiments between Net-RSTQ and the base EM in Tables 4 and 5 . When the small gene list was tested , three cases were significant with low p-values less than 0 . 001 and two cases were significant with p-values just below 0 . 02 while in the BRCA ( survival ) data , the p-value is only moderately significant even though the average by Net-RSTQ is higher . Overall , Net-RSTQ outperformed the base EM significantly . When the larger gene list was tested , the improvements are not as significant . The improvement was only significant in one dataset , BRCA ( survival ) , and slightly significant in two datasets , OV ( relapse ) and LUSC ( survival ) . In the other three datasets , the improvements are not significant . Net-RSTQ also outperformed Cufflinks and RSEM ( transcript or gene ) in five cases except the experiment on BRCA ( relapse ) dataset in Table 4 . In Table 5 , the improvements are less obvious . Moreover , the isoform expression features are not more informative than gene expression features . Overall , the classification performance with the small gene list in Table 4 is generally better than or similar to the large gene list in Table 5 possibly suggesting less relevance to survival and relapse in the large gene list . The parameter λ was tuned by the AUC on the validation set and the optimal λ was used to train the Net-RSTQ model to be tested on the test set . The process is repeated for each fold in 100 repeats . To show the effect of varying the λ on the classification performance in Net-RSTQ , we plotted the average AUC on the validation set across the 100 repeats on the BRCA ( survival ) dataset with small gene list in S3 ( A ) Fig . The optimal λ was 0 . 1 in this experiment . The local gradient around the optimal λ suggesting that the transcript network is playing an important role in inferring better transcript quantification from the RNA-Seq data . In S3 ( B ) Fig , the convergence of Net-RSTQ is also illustrated by each update through all the genes in each iteration . After less than 10 overall iterations across 397 genes , Net-RSTQ converged well to a local optimum . Similar convergence patterns were observed in all other TCGA samples . To understand the role of the transcript network in the transcript expression estimation , we used 100 randomized networks to learn the transcript proportion in each experiment with λ fixed to be 0 . 1 . In each randomization , the edges were shuffled among all the transcripts in the small gene list . For transcript expressions learned by each randomized network , we conducted the same four-fold cross validation to compute the average AUCs among 100 repeats . The boxplot of the AUCs learned with the 100 randomized networks is shown in Fig 6 . Compared with the classification results from the true transcript network , the result with randomized networks is always worse . Another important observation is that , the median value of the AUCs across the 100 randomized networks is lower or close to the result by the base EM , which suggests that the randomized networks play no role in improving classification and even lead to worse result . Overall , the results provide a clear evidence that the transcript network is informative for the transcript expression estimation , and supplies more discriminative features for cancer outcome prediction . To measure the scalability of Net-RSTQ , we tested the Net-RSTQ algorithm on the data of the MCF7 breast cancer cell line with three different networks , the small network ( 898 transcripts ) , the large network ( 5599 transcripts ) and an artificial huge network ( 10000 transcripts ) . Fig 7 plots the CPU seconds of running Net-RSTQ on the three networks under different λs . On the small network , the running time is at most about 100 seconds while on the large network and the huge network , the running time is in the scale of 1-e3∼1-e4 and 1-e5∼1-e6 , respectively . When λ = 0 . 1 , the CPU time for the small network is 32 . 4 seconds; for the large network is 2755 seconds; and for the artificial large network is 27806 seconds . The results suggest that Net-RSTQ might scale up to about 10000 transcripts , and thus the performance is sufficient for studies focusing on any pathway with up to several thousand genes in the pathway .
In the paper , we explored the possibility of improving short-read alignment based transcript quantification with relevant prior knowledge , protein domain-domain interactions . The observation of the correlation between isoform co-expressions and protein domain-domain interactions suggests that the approach is a well-grounded exploration . Different from previously methods [27] , Net-RSTQ is a network-based approach that directly incorporates protein domain-domain interaction information for transcript proportion estimation . The experiments suggested a great potential of exploring protein domain-domain interactions to overcome the limitations of short-read alignments and improve transcript quantification for better sample classification . The Dirichlet prior from the neighboring isoforms play two different roles: differentiating isoform expressions to reflect different functional roles or smoothing isoform expressions to reflect similar functional roles , depending on whether the isoforms of a gene share the same or different interacting partners . This principle in modeling is based on the hypothesis that isoforms playing different functional roles ( e . g . containing different protein domains ) are more likely to behavior differently than isoforms with the same or similar functional roles ( e . g . containing the same protein domains ) . When the isoforms of a gene interact with different partners , their expressions correlates with their partners’ expressions . And , when the isoforms of a gene interact with the same partners , there is no benefit on differentiating their proportions to drive the functionality . A limitation is that when the functional difference among the isoforms are not captured by domain content , the smoothing role might under-estimate the difference in their proportions . Thus , our future goal is to bring in other type of functional information to distinguish their functional roles in cancer such as preferential adoption of post-transcriptional regulations . Currently , Net-RSTQ does not directly model multi-hits reads in multiple loci . In the TCGA experiments , around 5–10% of the aligned reads in four datasets have multiple alignments reported by TopHat and only one of the best alignments is considered . To check the effect of the multiple-alignment reads in transcript quantification , we allow up to 20 best alignments by TopHat and normalized the read assignment qijk by the number of loci that the reads aligned to . The correlation coefficients between the estimated gene expressions before and after the normalization are above 0 . 98 in all the datasets . A potential rigorous solution is to add iteratively reassignment of the reads to the potential origins based on updated abundance of the involved isoforms . The modification will significantly decrease the computational efficiency and make it impractical on large RNA-Seq datasets . There is also another alternative of integrating the network information directly as a regularization term on the joint likelihood function of all the genes . We also explored this model in the S1 Text . In the preliminary experiments , we observed very similar outputs between the alternative model and the Net-RSTQ model shown in S8 Table . However , since the alternative model directly works with one large optimization problem across all the genes , the convergence is much slower as shown in S4 Fig and the optimization package used in the experiments ran into numerical issues . Thus , we believe the Net-RSTQ model is more scalable and robust in comparison . Currently , Net-RSTQ can scale on transcript network with up to around 5000 transcripts , which is sufficient for more focused analysis of several thousand genes . The running time of Net-RSTQ on such large transcript network is below 2 hours on each TCGA sample , compared with 5–8 hours needed for aligning the short reads . To further scale up Net-RSTQ , we will investigate other faster strategies of utilizing short read information , such as Sailfish [37] which directly estimates isoform expressions by counting k-mer occurrences in reads rather than reads from the alignments . This will be our future direction .
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New sequencing technologies for transcriptome-wide profiling of RNAs have greatly promoted the interest in isoform-based functional characterizations of a cellular system . Elucidation of gene expressions at the isoform resolution could lead to new molecular mechanisms such as gene-regulations and alternative splicings , and potentially better molecular signals for phenotype predictions . However , it could be overly optimistic to derive the proportion of the isoforms of a gene solely based on short read alignments . Inherently , systematical sampling biases from RNA library preparation and ambiguity of read origins in overlapping isoforms pose a problem in reliability . The work in this paper exams the possibility of using protein domain-domain interactions as prior knowledge in isoform transcript quantification . We first made the observation that protein domain-domain interactions positively correlate with isoform co-expressions in TCGA data and then designed a probabilistic EM approach to integrate domain-domain interactions with short read alignments for estimation of isoform proportions . Validated by qRT-PCR experiments on three cell lines , simulations and classifications of TCGA patient samples in several cancer types , Net-RSTQ is proven a useful tool for isoform-based analysis in functional genomes and systems biology .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
Network-Based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis
|
Clostridium botulinum is a dangerous pathogen that forms the highly potent botulinum toxin , which when ingested causes a deadly neuroparalytic disease . The closely related Clostridium sporogenes is occasionally pathogenic , frequently associated with food spoilage and regarded as the non-toxigenic equivalent of Group I C . botulinum . Both species form highly resistant spores that are ubiquitous in the environment and which , under favourable growth conditions germinate to produce vegetative cells . To improve the control of botulinum neurotoxin-forming clostridia , it is imperative to comprehend the mechanisms by which spores germinate . Germination is initiated following the recognition of small molecules ( germinants ) by a specific germinant receptor ( GR ) located in the spore inner membrane . The present study precisely defines clostridial GRs , germinants and co-germinants . Group I C . botulinum ATCC3502 contains two tricistronic and one pentacistronic GR operons , while C . sporogenes ATCC15579 has three tricistronic and one tetracistronic GR operons . Insertional knockout mutants , allied with characterisation of recombinant GRs shows for the first time that amino acid stimulated germination in C . botulinum requires two tri-cistronic encoded GRs which act in synergy and cannot function individually . Spore germination in C . sporogenes requires one tri-cistronic GR . Two other GRs form part of a complex involved in controlling the rate of amino-acid stimulated germination . The suitability of using C . sporogenes as a substitute for C . botulinum in germination studies and food challenge tests is discussed .
Clostridium botulinum and Clostridium sporogenes are closely related anaerobic spore-forming bacteria . C . botulinum is a dangerous pathogen that forms the deadly botulinum neurotoxin . This is the most potent toxin known , as little as 30–100 ng can be fatal [1] . Eight distinct types of botulinum neurotoxin ( types A to H ) , and more than thirty different neurotoxin sub-types ( e . g . sub-types A1 to A5 ) are recognised [2]–[5] . The botulinum neurotoxins are 150 kD proteins with zinc-endopeptidase activity that block acetylcholine transmission in cholinergic nerves , leading to a floppy paralysis known as botulism , that may prove fatal to both humans and animals [6] , [7] . The most frequently reported types of human botulism are foodborne botulism , infant botulism and wound botulism [1] , [8] . Foodborne botulism is an intoxication caused by consumption of neurotoxin formed by C . botulinum following spore germination and growth of vegetative cells in food . Infant and wound botulism are infections involving spore germination , growth of vegetative cells and neurotoxin formation in the gut of young infants and in deep wounds ( often associated with drug abuse ) , respectively . Botulinum neurotoxins are also important pharmaceuticals used to treat a range of localised conditions e . g . blepharospasm , hemifacial spasm , and for cosmetic purposes [9] . C . botulinum is a heterogeneous species that comprises a complex of four distinct groups of bacteria that share the common property of forming the botulinum neurotoxin [3] , [10] , [11] . Group I ( proteolytic ) C . botulinum is associated with foodborne botulism , infant botulism and wound botulism , and forms one or more neurotoxins of types A , B , F or H [3] , [5] , [10] , [11] . Strains of Group I C . botulinum that form type A1 neurotoxin have received the most attention to date because they are often associated with botulism in humans , the extreme potency of the type A1 neurotoxin , and due to the use of type A1 neurotoxin as a pharmaceutical [1] , [12]–[15] . Indeed , the first C . botulinum genome to be sequenced was that of Group I C . botulinum type A1 strain ATCC3502 [16] . C . sporogenes is occasionally pathogenic [17] , a significant cause of food spoilage [18] , and because of its strong physiological similarity to Group I C . botulinum is very widely used as a surrogate for this organism in demonstrating the effectiveness of food preservation processes [19] , [20] . Genome sequencing , whole genome analysis using DNA microarrays , and other typing methods have confirmed the close genetic relationship of C . sporogenes and Group I C . botulinum [2] , [21]–[23] . The formation of botulinum neurotoxin is used to distinguish strains of Group I C . botulinum from those of C . sporogenes [19] . Strains of Group I C . botulinum and C . sporogenes are both present in the environment as spores . This highly resistant dormant state enables survival in adverse conditions ( e . g . absence of nutrients , UV light , heat treatment , radiation , desiccation , high pressure , toxic chemicals ) that vegetative cells would not survive , and their formation by Group I C . botulinum and C . sporogenes is a primary reason why these bacteria present a significant food safety and food spoilage problem . Significantly , strains of Group I C . botulinum and C . sporogenes form spores of very high heat resistance , and the “botulinum cook” has been adopted by the canning industry as the standard minimum heat treatment ( 121°C for 3 min ) for low acid canned foods [1] . Under suitable conditions , the dormancy of bacterial spores is broken , and germination occurs . This is often initiated by a germinant receptor ( GR ) located in the spore inner membrane responding to nutrient germinants , and is followed by the release of dipicolinic acid and partial core hydration . Later , cortex-lytic enzymes degrade peptidoglycan in the spore cortex , enabling further core hydration and core expansion , and this results in the loss of spore resistance [24] . Germination involves pre-formed enzymes located in the dormant spore , and is followed by the initiation of metabolism and macromolecular synthesis , eventually leading to the emergence of a cell that is able to multiply . One approach that has interested microbiologists for many decades is to develop strategies to either prevent spore germination altogether and thereby prevent subsequent growth , or to germinate all the spores and then inactivate the emergent sensitive vegetative cells . Unfortunately the highly heterogeneous nature of spore germination ( as observed for example with Group II C . botulinum ) [25]–[27] has prevented the development of suitable processes . However , a greater understanding of spore germination in Group I C . botulinum and C . sporogenes may enable the development of novel intervention strategies to prevent or reduce disease and other adverse events such as food spoilage . Spore germination in Bacillus species generally involves a GR located in the spore inner membrane . The GR is composed of three proteins ( A , B and C ) that are encoded in a tricistronic operon . The A and B proteins are integral membrane proteins , while the C proteins are lipoproteins [24] , [28] . Spore germination in Clostridium species is not as extensively studied as that in Bacillus species , although recently significant advancements have been made with several clostridia including C . perfringens , C . difficile and C . sordellii [24] , [29]–[43] . Spore germination in clostridia often proceeds more slowly than that in Bacillus species [1] , and recent evidence suggests that although there are many similarities there are also a number of important differences in spore germination between clostridia and Bacillus species [24] , [28] , [29] . For example , spores of Bacillus species require a complete GR system to germinate effectively , and while this is also the case for some clostridia , spores of C . difficile are able to germinate effectively in the absence of what is classically understood as a GR . Such differences between clostridia probably reflect their wide genetic diversity [1] , [24] . Spores of Group I C . botulinum and C . sporogenes germinate when specific germinant nutrients such as a combination of L-alanine and L-lactate ( with less efficient germination in response to other amino acids and L-lactate or single amino acids [3] , [44] ) interact with a GR located in the clostridial spore inner membrane . GR operons are well conserved amongst strains of Group I C . botulinum . Group I C . botulinum type A strains ATCC3502 , Hall , ATCC19397 , Kyoto and NCTC2012 possess a pentacistronic GR operon ( gerXB-XA2-XB2-XC2-XB ) , two tricistronic GR operons ( gerXA1-XB1-XC1 and gerXA3-XB3-XC3 ) , and an orphan gerXB homologue [3] , [45] . Gene clusters resembling the pentacistronic GR operon and gerXA3-XB3-XC3 have been characterised in C . sporogenes strain NCIMB701792 and Group I C . botulinum type B strain NCTC7273 , respectively [16] , [46] . Strains of Group I C . botulinum type B ( Okra ) and F ( Langeland ) possess an additional tricistronic GR operon ( gerXC4-XA4-XB4 ) [3] , [45] . It is still not known , however , to which nutrient germinant ( s ) the various specific GRs are responding , or the relative importance of each of the GRs . The purpose of the present study was to dissect , at the molecular level , spore germination in Group I C . botulinum strain ATCC3502 and in C . sporogenes strain ATCC15579 . In particular , the key aims were to establish for each strain which of the multiple nutrient GRs was active in spore germination , and for the active nutrient GRs which nutrient germinant ( s ) they responded to . This was achieved using a combination of genomic , genetic and physiological approaches . The spore GRs in the two clostridia showed a number of interesting similarities , and this study provided further evidence of differences between spore germination in Clostridium and Bacillus species . Interestingly , subtle differences were also noted in spore germination between that in Group I C . botulinum strain ATCC3502 and that in C . sporogenes strain ATCC15579 . This study has provided novel insights into spore germination in these two important clostridia .
A selection of amino acids at various concentrations ( Table S1 ) were assessed for their individual effect on germination of spores of C . botulinum and C . sporogenes . The majority of the amino-acids tested have previously been reported to contribute as germinants or co-germinants for spores of Clostridium or Bacillus [1] . Initial tests showed that spore germination was similar under aerobic and anaerobic conditions ( data not shown ) . This confirmed previous reports for C . botulinum and C . sporogenes [47] , [48] . In the presence of Tris buffer ( pH 7 . 4 ) , L-lactate ( 50 mM ) and NaHCO3 ( 50 mM ) at 30°C the addition at 100 mM of either L-alanine or L-cysteine initiated spore germination in C . botulinum and C . sporogenes , although at differing rates ( Figure 1a & 1b ) . L-lactate was not essential for L-alanine or L-cysteine stimulated germination and had no effect on rate or the overall extent of germination ( data not shown ) . Three amino acids ( L-methionine , L-serine , L-phenylalanine ) each required L-lactate for inducement of germination in both species . The addition of L-lactate on its own failed to stimulate germination ( <10% fall in OD600 , equating to <1% germination ) . Spores of C . botulinum , but not those of C . sporogenes , were also germinated by glycine in combination with L-lactate ( Figure 1a ) . L-cysteine combined with L-lactate produced the most rapid germination of C . botulinum spores ( 40% of initial OD600 , approximately 90% germination after 6 h ) and C . sporogenes spores ( 40% of initial OD600 , approximately 90% germination after 4 h ) . C . sporogenes germination proceeded far more rapidly to completion with all the tested amino acids compared to C . botulinum . A number of other amino acids were tested , but failed to induce spore germination in either C . botulinum or C . sporogenes , both in the presence and absence of L-lactate ( Table S1 ) . For both species , the saturation concentration of the amino acids was 50–100 mM with l-lactate at 50 mM ( Figure 1c & 1d ) . For simplicity , L-lactate was included in all subsequent germination studies . The optimum pH range was pH 6–8 for germination with most amino acids + l-lactate . However , spore germination was also observed at pH 10 in the presence of L-serine , and L-alanine + l-lactate . The rich microbiological growth medium , TY medium , was not optimum for spore germination , with less germination observed than in the defined system , although the addition of L-lactate did increase the rate and overall extent of germination in TY medium . Spore germination measured using the Bioscreen system correlated well with direct counts of phase-dark spores by phase-contrast microscopy ( data not shown ) with an OD600 fall of 40% correlating to >90% germination of spores . The effect of sporulation medium and sporulation temperature on the subsequent germination properties of C . sporogenes spores was determined ( Figure 2 ) . Assessment of C . botulinum was precluded by frequent poor sporulation of this strain , which was less than 5% and 1% in Robertson's cooked meat broth ( CMB ) and TY respectively , compared to the optimum yield of 30% spores on RCM plus skimmed milk ( RCM+SM ) plates at 37°C . C . sporogenes spores were produced using either RCM+SM , CMB or TY broth at 37°C . Microscopic observations showed sporulation was notably lower ( ca . 40% ) using CMB and TY compared to RCM+SM . C . sporogenes spores were also produced at 15 , 20 , 28 , 30 , 37 and 42°C in CMB to evaluate the effect of temperature . Microscopic observations showed that sporulation was notably lower ( ca . 50% ) at 15°C compared to 37°C in CMB , with sporulation not observed at 42°C . Germination of the spores was then evaluated in the presence of L-alanine + L-lactate ( Figure 2 ) . Interestingly , spores produced in CMB at 37°C germinated at a faster rate compared to spores produced in the other media at 37°C . Sporulation temperature also affected germination rates , with spores produced at 37°C germinating more rapidly than spores produced at other temperatures ( Figure 2 ) . Subsequently , all spore crops used in germination studies were produced at 37°C in CMB for C . sporogenes and on RCM+SM for C . botulinum . Unlike their L-isomers , D-alanine , D-cysteine , D-methionine , D-phenylalanine and D-serine all failed to trigger spore germination in either C . sporogenes or C . botulinum . Moreover , the D-amino acids prevented spore germination ( defined as a <10% fall in OD600 , equating to <1% germination observed microscopically ) in C . botulinum and C . sporogenes induced by their equivalent L-amino acid ( Table 1 ) . To ascertain if specific D-amino acids could prevent germination by non-equivalent L-amino acids , D-serine was tested at a ten-fold excess of each of the five L-amino acids . Interestingly , D-serine prevented germination in C . sporogenes induced by L-cysteine , L-methionine , L-phenylalanine and L-serine , and to a lesser extent L-alanine . L-alanine and L-cysteine induced germination was only slightly affected by a ten-fold excess of D-serine in C . botulinum . However , when a 100-fold excess of D-alanine was added , spore germination in the presence of each of the five L-amino acids was prevented in C . botulinum . Finally , in order to assess whether the D-amino acid is acting specifically rather than being simply in excess of the L-amino acid germinant , we performed further tests using different germinants ( L-alanine , 1 mM or L-serine , 20 mM ) each combined with an excess ( 100 mM and 40 mM respectively ) of the non-germinant L-valine . The addition of excess non-germinant in each experiment had no effect on final germination levels . However , the D-amino acids ( in this case alanine or serine ) continued to be inhibitory . Homologues of Group I C . botulinum strain ATCC3502 GR sub-units ( gerXA , gerXB , gerXC ) were identified by BLASTp analyses against a draft un-assembled genome of C . sporogenes strain ATCC15579 ( Figure 3 ) . Analysis showed that the C . sporogenes strain contains three tricistronic GR operons and one tetracistronic GR operon . In comparison C . botulinum ATCC3502 has two tricistronic GR operons and one pentacistronic GR operon . Each strain has an additional orphan gerXB subunit homologue . Alignment using Clustal Omega and using Jalview to produce a tree showing the average distance based on amino acid sequence identity ( % ) , revealed homology between the GR operons ( Figure 3 ) . Each operon in C . botulinum had a closely related operon in C . sporogenes ( from 11 . 6–16 . 0% difference in identity for each gerXA ) , while the CLOSPO_02140 gerXA is most distant with regards to sequence % identity . Transmembrane helix ( TMH ) prediction analysis showed that the gerXA sub-units of C . botulinum and C . sporogenes have between three and five TMHs , and the gerXB subunits have ten TMHs . The gerXC subunits were predicted to be lipoproteins and encode a signal peptide . Interestingly , more detailed sequence analysis of the pentacistronic operon of C . botulinum reveals that although the first gene of the operon , CBO1974 , is a full-length member of the gerXB family , the 5′ end of its coding region is overlapped by a small ( 162 bp ) region of a gerXA gene , annotated as CBO1973A . Comparative analysis between C . botulinum and C . sporogenes ger homologues also revealed that the gerXA gene , CLOSPO_00838 lacks an uninterrupted region encoding 20 amino acid residues which map to residues 74–93 of the predicted translation for CBO0123 ( Figure 3b ) . A database search shows that this deletion ( with respect to C . botulinum strain ATCC3502 ) is not confined to C . sporogenes strain ATCC15579 , but can be found in 10 of a total of 19 GerA peptide sequences from proteomes of C . sporogenes ( 2 ) , Group I C . botulinum ( 4 ) and Group III C . botulinum ( 4 ) ( data not shown ) . Similar deletions were not found in any Group II C . botulinum GerA peptides . The function of this apparently conserved region remains unknown . To characterise the functionality of the putatively identified germination GRs , a series of single ( C . botulinum and C . sporogenes ) , and triple ( C . sporogenes ) insertion mutants were constructed . Furthermore , a C . sporogenes quadruple insertional knockout GR mutant ( gerXA4− ) was also generated . The current insertional knockout system does not allow multiple insertion selection , as following one insertion the single mutant is then erythromycin resistant . However , the mutant generation system was shown to be highly efficient , which negated the need for a different antibiotic selection in the multiple insertion mutants . All insertion events were tested by PCR which confirmed chromosomal integration of the intron ( Figure S1 ) . PCR using gene specific and intron specific primers confirmed insertion of the intron into the GR gene; this was further confirmed by PCR with gene specific primers flanking the insertion site producing a ∼2 kb product ( Figure S1 ) . Insertion events were verified by Southern hybridization using an intron specific probe which confirmed the correct number of insertion events in all the constructed mutants ( Figure S1c ) . To characterise the GRs and to identify their cognate germinants , single insertional knockout mutants ( gerXA1-0123− , gerXA2-1975− , gerXA3-2797− ) were created for each of the identified GR operons in C . botulinum . Spores generated from these mutants were then analysed for amino acid stimulated germination using L-alanine , L-cysteine , L-methionine , L-serine , L-phenylalanine or glycine , all in the presence of L-lactate ( Figure 4a ) . The OD600 of wild-type spores decreased ( ∼40% ) indicating efficient and complete spore germination in the presence of each amino acid . There was a ∼20% decrease in OD600 with TY medium + L-lactate . In contrast , the gerXA3-2797− mutant failed to germinate with any of the amino acids tested even after 20 h of exposure ( <1% germination observed microscopically ) . Moreover , germination was not observed with a nutrient rich broth ( TY + L-lactate ) suggesting that CBO2797 is essential for amino acid stimulated germination . The mutant gerXA1-0123− also failed to germinate to the same extent as the wild type , with a small decrease ( <10% ) in OD600 observed with L-cysteine and with nutrient rich broth ( TY + L-lactate ) . In neither case could spore germination be observed microscopically . These results suggest that CBO0123 is also essential for amino acid induced germination . Interestingly , the gerXA2-1975− mutant showed similar germination patterns to those of WT spores ( Figure 4a ) . Complementation was performed by two different approaches; using plasmid pMTL83151esp , which relies on the putative native promoter of the gene , or using pMTL83151fdx which includes the powerful promoter Pfdx of the ferredoxin gene ( fdx ) from C . sporogenes . Complementation was successful for one of the two GerXAs observed to be important for nutrient-induced germination . Introduction of the receptor CBO0123-CBO0124-CBO0125 complementation vector ( pMTL83151esp or pMTL83151fdx ) successfully restored germination to the mutant gerXA1-0123− , albeit at a different rate compared to that of the wild type ( Figure 5a ) . Introduction of the GR CBO2797-CBO2796-CBO2795 complementation vector ( pMTL83151esp or pMTL83151fdx ) drastically reduced sporulation efficiency , giving insufficient spores to allow assessment of the germination phenotype . Finally , these results were further supported by examining the number of colonies formed on TY plates after incubation for 2 days at 37°C . All spore crops were adjusted to a final concentration of ∼1×108 spores/ml , serially diluted , and plated on to TY agar . Single mutant gerXA2-1975− showed comparable numbers of colonies to the wild-type . In contrast , mutants gerXA1-0123− and gerXA3-2797− exhibited a greatly reduced colony forming efficiency ( Figure 6 ) . To characterise the C . sporogenes GRs and to identify their cognate germinants , single insertional knockout mutants ( gerXA1-00838− , gerXA2-03006− , gerXA3-02217− , gerXA4-02140− ) were created for each of the identified GR operons . The OD600 of wild-type spores decreased ( ∼40% ) indicating efficient and complete spore germination ( Figure 4b ) . Mutant gerXA3-02217− failed to germinate ( <10% fall in OD600; spore germination not observed microscopically ) with any of the amino acids tested after 20 h of exposure ( Figure 4b & 4c ) . Spore germination was not observed with a nutrient rich broth ( TY + L-lactate ) demonstrating that CLOSPO_02217 is required for amino acid stimulated germination . Germination of mutant gerXA2-03006− showed an initial delay of one hour compared to the wild type with all the amino acids tested ( e . g . Figure 4c ) . However , following this interval , germination proceeded to the same extent , albeit at a slower rate compared to the wild type ( Figure 4b & 4c ) . Similarly , gerXA4-02140− had an initial germination postponement of four hours and then proceeded to germinate fully , but also at a slower rate . No discernible phenotype was observed following insertional inactivation of the gerXA1 ( mutant gerXA1-00838− ) GR compared to the WT ( Figure 4b & 4c ) . To further understand the function of the individual GRs in germination , triple insertional knockout GerXA mutants ( gerXA3−00838+ , gerXA3−02140+ , gerXA3−02217+ , gerXA3−03006+ ) and a quadruple insertional knockout GerXA mutant gerXA4− were created . Mutation of three GerXAs resulted in one remaining potentially functional GerXA so any possible interaction between GerXAs is excluded and so enables dissection of the specific germinant recognised . As anticipated , spores from the quadruple insertional knockout mutant gerXA4− failed to germinate ( <10% fall in OD600 , germination not observed microscopically ) with any of the amino acids or in nutrient rich broth ( TY + L-lactate ) ( Figure 4b ) . Furthermore , the three triple mutants gerXA3−00838+ , gerXA3−02140+ , and gerXA3−03006+ also failed to germinate with the amino acid systems or in nutrient rich broth ( TY + L-lactate ) . Mutant gerXA3−02217+ which has only a single active GerXA present ( CLOSPO_02217 ) , displayed comparable germination rates to the wild type with all the amino acids tested and the nutrient rich broth ( TY + L-lactate ) ( Figure 4b ) . Complementation of all the GerXAs further confirmed these findings . Particularly important was the introduction of the GR CLOSPO_02217- CLOSPO_02218- CLOSPO_02219 complementation vectors ( pMTL83151esp or pMTL83151fdx ) , as these fully restored germination to the mutant gerXA3-02217− to WT levels ( Figure 5b ) . Finally , the number of colonies formed on TY plates after incubation for 2 days at 37°C was determined . All spore crops were adjusted to a final concentration of ∼1×108 spores/ml , serially diluted , and plated on to TY agar . The wild-type and single insertion mutants gerXA1-00838− , gerXA4-02140− and gerXA2-03006− formed comparable numbers of colonies . In contrast , mutant gerXA3-02217− showed a greatly reduced colony forming efficiency ( Figure 6 ) . Triple mutants gerXA3−00838+ , gerXA3−02140+ , gerXA3−03006+ and the quadruple insertional knockout mutant gerXA4− exhibited a significantly reduced colony forming efficiency compared to the WT . Importantly , the triple mutant gerXA3−02217+ , revealed comparable numbers of colonies to the wild type ( Figure 6 ) .
One important feature that has contributed to the success of botulinum neurotoxin-forming clostridia , and all other clostridia , is their ability to form highly resistant endospores . Under suitable conditions the spores germinate with associated loss in resistance properties , and cell multiplication recommences . Spore germination occurs through a number of steps that are poorly understood in clostridia . The present study has identified which nutrient germinants are able to stimulate spore germination in Group I C . botulinum ATCC3502 and in C . sporogenes ATCC15579 , has for the first time identified which of the individual GRs are responding to these nutrient germinants . A survey of the available genomes of Group I C . botulinum and its close relative , C . sporogenes reveals that although the general trend is to possess three or four operons encoding spore GR proteins , the fine detail of this organisation varies . The gerXC subunits were predicted to be lipoproteins and encode a signal peptide . In Bacillus , a lipobox consensus sequence ( GCX ) has been recognised within the first 30 residues of the GRs C subunits , where the cysteine in this motif is diacylglycerylated to facilitate cleavage of the signal peptide . In C . botulinum this lipobox was observed in gerXC gene CBO0125 and in two C . sporogenes gerXC genes CLOSPO_00836 and CLOSPO_02139 . However , diacylglycerol addition does not appear to be essential for function [29] . In addition to the existence of orphan ger genes ( such as CBO2300 in Group I C . botulinum ATCC3502 ) , there is evidence of genetic recombination at these loci , most obviously the presence of multiple gerXB genes in the pentacistronic operon of Group I C . botulinum ATCC3502 ( CBO1974-1978 ) , and in its tetracistronic equivalent in C . sporogenes ATCC15579 ( CLOSPO_03006-03003 ) . Less obvious evidence includes the small fragment of a gerXA gene apparently inserted into the beginning of the first ‘extra’ gerXB gene of the Group I C . botulinum ATCC3502 pentacistronic operon , and the extra ( or deleted ) 20 codons discovered by comparison of the coding sequences of CBO0123 and CLOSPO_00838 . Site-directed mutagenesis studies will be required to determine the functional status of these genetic differences . Spore germination in Group I C . botulinum ATCC3502 and C . sporogenes ATCC15579 was triggered by a variety of amino acids , often in combination with L-lactate . L-phenylalanine + L-lactate and L-cysteine + L-lactate were the most effective germinants for C . botulinum , while L-cysteine + L-lactate were the most effective germinant for C . sporogenes . L-lactate had no discernible effect on spore germination in the presence of L-alanine or L-cysteine , but was essential for germination induced by L-methionine , L-serine or L-phenylalanine . Previous studies have reported a variable effect of L-lactate on amino acid induced spore germination in Group I C . botulinum and C . sporogenes [1] , [44] , [46] . Germination of Group I C . botulinum and C . sporogenes with L-serine and glycine has been reported previously [44] , [49] , while germination induced by L-methionine + L-lactate in Group I C . botulinum appears to be a novel finding . L-methionine triggered germination has been previously reported in C . sporogenes [49] , B . anthracis [50] and C . tetani [51] . Germination in C . botulinum and C . sporogenes was also induced by L-phenylalanine + L-lactate , as reported previously in C . bifermentans [52] and C . sordellii [30] , whereas the GR GerI in B . cereus interacts with L-phenylalanine in combination with inosine [53] . Moreover , L-phenylalanine stimulation of C . botulinum germination was more effective than that obtained with L-alanine . It may be that L-phenylalanine and L-lactate interact before interacting with the GR or that L-lactate and L-phenylalanine may directly affect the GR together or sequentially . Any effect is unlikely to be due to the hydrophobic nature of L-phenylalanine , as L-alanine and L-cysteine also have polar side chains and induce germination efficiently . In the present study , germination was more rapid when induced by single amino acids with L-lactate than in the nutrient rich medium TY; a similar observation has been made for Group II C . botulinum [54] . However , the addition of L-lactate to TY increased the germination rate significantly . The production of spore crops is usually performed under conditions that maximise the spore yield [55] , [56] . However , mounting evidence now suggests that sporulation conditions may have a direct effect on germination efficiency in Bacillus [55]–[57] . In the present study , a greater yield of C . sporogenes spores was achieved on RCM+SM plates compared with CMB and TY broths . However , the germination rate was initially more rapid with spores produced in CMB , albeit all spore crops achieved a similar extent of germination after 16 h . B . subtilis spores produced in a liquid medium germinated more readily than spores produced on plates [58] . Similarly , germination of B . subtilis spores with dodecylamine was also highly dependent on the method used for spore preparation [59] . Although the present study shows that media composition for sporulation does have an impact on germination , the reasons for these findings remain unclear . The effect of sporulation temperature in CMB on the yield of spores and their subsequent germination was also assessed . A greater number of spores were formed at 37°C than at lower temperatures , and they also germinated more readily . Thus , on this occasion spore yield and spore germination were positively correlated . For Group II C . botulinum , sporulation temperature affected spore yield and fatty acid content , but not heat resistance or germination [60] . For B . subtilis , sporulation temperature affected resistance to wet heat and spore coat protein levels [61] . Certainly , for C . sporogenes it is apparent that sporulation conditions have a direct effect on subsequent germination with the selected amino acids . It remains to be established whether this effect is due to the number and/or state of GRs , or to as yet unknown proteins that are involved in the germination pathway . However , it is clear from these results that sporulation conditions should be considered , especially when Clostridium studies in the food industry are to be performed to evaluate processing strategies , as these typically use spores produced under conditions where the yield has been maximised . In the present study , D-amino acids failed to trigger spore germination and also prevented germination induced by their respective L-amino acid , as reported previously for other strains of Group I C . botulinum and C . sporogenes [44] , [47] , [48] , [62]–[64] . It is noted that D-alanine was previously reported to be a competitive inhibitor of L-alanine induced germination in C . sporogenes [48] . However , D-alanine did not prevent germination of spores of Group II C . botulinum types B , E and F in L-alanine + l-lactate + NaHCO3 ( pH 7·0 ) when added at ten-times the concentration of l-alanine [54] . Interestingly , in the present study , D-serine prevented germination induced by L-amino acids in C . sporogenes , and D-alanine prevented germination induced by L-amino acids in C . botulinum . These observations are consistent with those made by Montville et al . ( 1985 ) , who reported that L-cysteine triggered germination was inhibited by D-alanine as well as by D-cysteine , and that L-alanine-triggered germination was inhibited by D-cysteine as well as by D-alanine in Group I C . botulinum strains B-aphis and Ba410 [64] . Montville et al . suggested that alanine and cysteine shared a common germinant binding site in spores of these two strains [64] . However , kinetic studies ( e . g . [43] ) are required to establish if the position is the same for Group I C . botulinum ATCC3502 and C . sporogenes ATCC15579 . Studies with B . megaterium and B . subtilis suggest that the B-protein subunit of the GR presents the site for the receptor-ligand binding [65] , [66] , and although no evidence is presently available , the position may be similar in C . botulinum and C . sporogenes . Furthermore , C . botulinum ( ATCC3502 ) and C . sporogenes ( ATCC15579 ) both contain five putative alanine racemase genes . Alanine racemase is able to convert the germinant L-alanine into inhibitory D-alanine in B . cereus [67] . However , despite these clostridia containing five putative racemase genes , germination of Group I botulinum spores appeared not to be influenced by l-alanine racemase activity [44] . Molecular dissection of spore germination in Group I C . botulinum strain ATCC3502 demonstrated that two GerXAs were required for amino acid stimulated germination . The interruption of either gene CBO0123 or CBO2797 ( mutants gerXA1-0123− and gerXA3-2797− ) resulted in no observable germination . Thus , it has been shown that for amino acid stimulated germination there is a minimum requirement for the GerXAs produced by these two GRs , and while the product of gene CBO1975 appears to be inactive , it cannot be ruled out that the other products ( GerXB and GerXC ) of this operon are functional . The requirement for two GRs for germination has been previously reported in B . subtilis [68] . In this bacterium the GRs GerB and GerK interact and responded to a cocktail of L-asparagine , D-glucose , D-fructose , and K+ ( AGFK ) [68] . The B . anthracis GRs GerK and GerL also act cooperatively with alanine to stimulate the germination pathway [69] . Importantly , they can also act individually and initiate germination with proline and methionine ( GerK ) or serine and valine ( GerL ) as cogerminants in conjunction with inosine [69] . It is presently unclear how pairs of GRs come together to induce germination; potential hypotheses include: ( i ) one GR of the pair is involved in the binding of the germinant and the second GR is involved in a signalling capacity; ( ii ) both GRs together may be required to form the germinant binding site; ( iii ) one GR may physically stabilise the receptor that receives the germinant . What is clear is that more evidence is required to characterise the individual role of each GR in germinant recognition . In the present study , single C . botulinum GRs failed to induce germination , either with single or with combinations of amino acids , or with components of a rich growth medium . Complementation restored wild type levels of germination to the mutant gerXA1-0123− , albeit at a slower rate compared to that of the wild type . However restoration of germination efficiency could not be assessed for the complementation mutant gerXA3-2797− due to its poor sporulation efficiency . The failure of plasmid complemented mutants to regain wild type sporulation levels has been reported previously in C . perfringens [70] . Moreover , the use of multicopy plasmids can fail to restore the phenotype to wild type levels in clostridia [71] . It may be that in this instance inappropriately elevated levels of the GR proteins in the complementation mutant gerXA3-2797− diminished sporulation efficiency . Undoubtedly , until techniques become available for stable integration of a single chromosomal copy of the complementing DNA , complementation studies in clostridia will remain challenging . Group I C . botulinum ATCC3502 also has a pentacistronic putative GR . This third GR , CBO1975-1977 ( gerXA2-XB2-XC2 ) , is unusual as it is flanked by two additional gerXB genes ( CBO1974 and CBO1978 ) and is closely related to a GR gene cluster characterized in C . sporogenes ATCC15579 ( this work ) . Furthermore , upstream of CBO1974 there is a pseudogene , CBO1973A with a disrupted ORF which would encode the C-terminal region of a GerA protein . This pseudogene overlaps the putative start of CBO1974 ( gerXB ) . Insertion mutant ( gerXA2-1975− ) showed no attributable phenotype , with a similar germination pattern to the wild type strain . The pseudogene CBO1973A may hint at the possibility of recombinational events that have occurred at this locus that may have disrupted the normal control regions for correct GR expression . It cannot be ruled out that germination may be stimulated by suitable environmental stimuli that are not found in the nutrient rich medium , TY broth or any of the specific germinants tested in this work . C . sporogenes is often regarded as the non-toxigenic equivalent of Group I C . botulinum [2] , [19] . Comparisons of C . botulinum and C . sporogenes are important if C . sporogenes is to be used as a valid surrogate model in spore germination and other studies . There are four genes encoding GerXAs in C . sporogenes ATCC15579 , and only one of these ( CLOSPO_02217 ) was essential for amino acid induced germination . Two other GerXA proteins ( products of CLOSPO_02140 and CLOSPO_03006 ) increased the rate of germination , providing that the product of CLOSPO_02217 was also present . Therefore , one GR ( CLOSPO_02217-02219; and at least CLOSPO_02217 ) is required for amino acid stimulated spore germination . The remaining three GerXAs were not essential , but it cannot be ruled out that other products ( GerXB and GerXC ) of these operons may be functional and act synergistically with the CLOSPO_02217-02219 GR . Indeed , preliminary proteomics data from purified spores reveals that the gerXC gene CLOSPO_00836 is translated into a protein ( data not shown ) . Although in Bacillus all subunits of GRs are required for a response to amino acids , the function of each individual subunit still remains to be elucidated [72] . The finding that , in C . sporogenes ATCC15579 , some or all of the proteins from two GRs ( CLOSPO_02139-02141 and CLOSPO_03003-03006 ) contribute to increase the rate of spore germination induced by a third GR ( CLOSPO_02217-02219; or at least CLOSPO_02217 ) implies a close interaction between GR proteins . Different GRs may interact directly ( and/or compete ) with each other [73] or possibly one GR may facilitate access of the germinant to another GR . Although these two GRs were not stimulated by individual or a combination of amino acids , or by components of a rich microbiological growth medium , it is possible that they may individually respond to some other as yet unknown germinant . Interestingly , when the wild-type and various mutants containing an active CLOSPO_02217 were plated out on a rich growth medium recovery was complete ( ∼107 CFU/ml ) , while in mutants where CLOSPO_02217 was insertionally inactivated ( including in the quadruple gerXA4− mutant ) the number of colonies recovered was significantly lower ( ∼103–104 CFU/ml ) . The recovery , at a very low frequency , of any spores in the absence of CLOSPO_02217 ( including in the quadruple gerXA4− mutant ) may be due to an alternative low efficiency receptor system distinct from the ger family , or perhaps to stochastic effects ( e . g . cortex-lytic enzymes or ion/water channels ) . Similar observations have been made in Bacillus subtilis [74] . It is perhaps not surprising that this GR ( CLOSPO_02217-02219 ) was involved in germination with the selected amino acids as it shares >85% homology with the functional and now characterised C . botulinum GR ( CBO2795-2797 ) . It is interesting that this GerXA can operate independently of any other GerXA , unlike in C . botulinum . One hypothesis is that the short deletion in gerXA of CLOSPO_00838 ( when compared to its active C . botulinum homologue , CBO0123 ) is associated with loss of function . This mutational event in C . sporogenes may have brought about an evolutionary pressure which has allowed adaption of this organism to survive with only a single functional GR operon ( or at least a single functional GerXA ) . Certainly the germination mechanism of C . sporogenes ATCC15579 is different to that of C . botulinum ATCC3502 . Alignment of putative GRs with known functioning GRs appears to be problematic , as at present this is done over the whole protein in the absence of detailed knowledge of the functionality of the putative GR . However , based on comparison of the whole proteins , the GerXA of homologous GR proteins CBO2795-2797/CLOSPO_02217-02219 are functionally active , while no discernible function could be identified for the GerXA of GR proteins CBO1974-1978/CLOSPO_03003-03006 . The GerXAs of other GR proteins were either essential ( in C . botulinum ATCC3502 ) or contribute to the rate ( in C . sporogenes ATCC15579 ) . The results also call into the question the use of C . sporogenes as a suitable substitute for C . botulinum with regards to germination rates and germination substrates . More work is required to fully understand the role of each GR in clostridia and indeed why some species contain multiple GR operons and others can function with just one . The testing of additional strains would seem to be appropriate . The long term aim is that as more is understood of the complex germination systems in clostridia , it may be possible to devise specific strategies to disrupt this process . This would be of great benefit to help control pathogenic clostridia , for example in the food industry , and might also help to control spore-disseminated nosocomial infections such as those caused by C . difficile .
Homologues of C . botulinum ATCC3502 GR sub-units ( gerXA , gerXB , gerXC ) were identified by BLASTp analyses against a draft un-assembled genome of C . sporogenes strain ATCC15579 . Alignment of C . sporogenes receptors with C . botulinum was performed using Clustal Omega [75] and Jalview [76] was utilised to produce a tree showing the average distance using % identity . Protein domain analysis was performed using Pfam [77] . Transmembrane helix prediction analysis of the GR sub-units was implemented using TMHMM [78] . Proteolytic C . botulinum strain ATCC3502 ( neurotoxin subtype A1 ) and C . sporogenes ATCC15579 were grown anaerobically at 37°C in tryptone-yeast medium ( TY ) . The Escherichia coli strain Top10 ( Invitrogen ) was used for plasmid maintenance and the E . coli strain CA434 [79] was used for conjugal transfer . Both strains of E . coli were grown aerobically in Luria-Bertani medium ( LB ) at 37°C . Where appropriate , growth medium was supplemented with antibiotics at the following final concentrations; ampicillin 100 µg/ml , chloramphenicol 25 µg/ml , cycloserine 250 µg/ml , thiamphenicol 15 µg/ml , erythromycin 500 µg/ml ( E . coli ) , 20 µg/ml ( C . botulinum ) 2 . 5 µg/ml ( C . sporogenes ) , and the chromogenic substrate 5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside ( X-Gal ) 80 µg/ml . All bacterial media supplements were purchased from Sigma . Spores of C . botulinum and C . sporogenes strains were prepared in TY , Reinforced Clostridial Medium plus skimmed milk ( RCM+SM ) or Robertson's cooked meat broth ( CMB ) ( Southern Group Laboratories ) and incubated at 15 , 20 , 28 , 30 , 37 or 42°C for a period of 10 days . Spores were cleaned and stored as described previously [54] . Constructed mutants and plasmids utilised in this study are presented in Table 2 . Primers used for verification of successful insertion events and the Southern blot probes are listed in Table S2 ( supplementary material ) . PCR experiments were carried out using Phusion High-Fidelity PCR Master Mix with GC Buffer kit ( Thermo Fisher ) . Plasmid isolation and PCR purification was performed using the Wizard Plus SV Minipreps DNA Purification System and the Wizard SV Gel and PCR Clean-Up System ( Promega ) respectively , as described in the provided Technical Manual . Chromosomal DNA isolation from suspected mutants were prepared as previously described [16] . Restriction endonucleases and T4 DNA ligase were purchased from New England BioLabs and used according to the manufacturer's instructions . Southern hybridisation was performed to confirm the correct number of insertion events had occurred . The hybridisation probe was constructed by PCR to target the inserted intron using the primers Erm-F and Erm-R ( Table S2 ) . Genomic DNA ( 1 µg ) was digested overnight with HindIII restriction enzyme and the fragments separated on a 1% agarose gel . Southern blot analysis was performed with ECL detection using a commercial kit ( Amersham ECL Direct Nucleic Acid Labelling and Detection System ) according to the manufacturer's instructions . The potential germinants , including; L-alanine , L-serine , L-cysteine , L-methionine , L-phenylalanine , glycine ( 0 . 5 mM–100 mM ) and antagonists d-alanine , D-cysteine , D-methionine , D-phenylalanine , D-serine ( 10 mM–200 mM depending on solubility ) ( Sigma ) were all prepared in Tris-HCl buffer ( 20 mM , pH 7 . 4 ) with NaHCO3 ( 50 mM ) , with or without L-lactate ( 50 mM ) . NaHCO3 was a non-essential component that increases the rate and overall extent of germination by approximately 10% [54] . Germinant solutions were prepared and filter sterilised ( 0 . 45-µm syringe filter , Millipore , Bedford , MA ) . The pH of the germinant solutions was adjusted to evaluate the effect of pH on spore germination at pH 3 to pH 10 . Prior to the addition of germinants all spore suspensions were heat activated at 80°C for 10 min . Germination of spores at 30°C was measured by a decrease in optical density ( OD ) at 600 nm every 5 min using a Bioscreen C analyser system ( Labsystems , Basingstoke , UK ) under aerobic conditions . Germination was expressed in terms of measured OD600 as a percentage of the initial OD600 . To validate the OD600 measurements , at the completion of each test the proportion of germinated spores was visualised by the assessment of 200 spores in at least ten fields using phase-contrast microscopy . Typically , full germination was indicated when the OD600 fell to ∼40% of its initial value . In some tests a small fall in OD600 was observed ( <10% of initial value ) . This was attributed to settling of spores in the Bioscreen wells , and was not accompanied by microscopic observation of spore germination . Finally , the capacity of spores to germinate and form colonies was assessed . Spore suspensions were enumerated using a haemocytometer and adjusted to a final concentration of ∼1×108 spores/ml . Spores were then heat activated ( 80°C , 15 min ) , serially diluted in 0 . 85% saline , and plated in triplicate on to TY agar before incubation anaerobically ( 37°C , 48 hrs ) . Clostridium mutants were generated using the Clostron system , which inserts an erythromycin resistance cassette into the targeted gene of interest . Target sites were identified using the Pertuka method [80] and mutants were generated ( Table 2 ) as described by Heap et al . [81] . gerXA GR subunits were targeted in all germination operons . Re-targeted introns were ligated into the pMTL007C-E2 vector following restriction digest with HindIII/BsrGI . All retargeted introns were sequence verified before transformation into E . coli CA434 . Confirmed sequenced plasmids were then conjugated into their respective hosts . Finally , primers were designed and used to confirm that the intron was present and in the correct orientation in the target gene/genes of interest ( Table S2 ) . The current insertional knockout system does not allow selective isolation of clones containing a second intron insertion as following one insertion the mutant strain is then erythromycin resistant . To create the double , triple and quadruple insertional knockout mutants an alternative approach was taken in which clones containing intron insertions were identified by screening large numbers of colonies rather than by antibiotic selection . Plasmid re-targeting was carried out as above and transferred in to C . botulinum or C . sporogenes using E . coli CA434 . Confirmation of successful trans-conjugation events were screened on TY agar plates containing cycloserine ( 250 µg/ml ) and thiamphenicol ( 15 µg/ml ) . To create the multiple insertional knockout mutants the process was repeated using successive rounds of plasmid targeting and gene insertion . Successful integration of introns into the target genes was confirmed by PCR using primers flanking the target sites ( Table S2 ) . Furthermore , to confirm that the required number of insertion events had occurred , genomic DNA from the mutants was digested with HindIII and subjected to Southern analysis using an intron specific probe . For complementation , two plasmids , pMTL8315esp and pMTL8315fdx were constructed ( Figure S2 ) . Primers , with Esp3I restriction sites were designed to amplify two GR fragments; one included the 5′ noncoding region encompassing the putative promoter and was ligated into pMTL8315esp; the second fragment contained the coding operon only and was ligated into the plasmid pMTL8315-fdx which contains the strong promoter Pfdx of the ferredoxin gene ( fdx ) from C . sporogenes NCIMB 10696 . Following confirmation by sequencing , GR plasmids were then transconjugated into their respective mutants using E . coli CA434 as described earlier . Spore crops were produced as above , except with the addition of thiamphenicol ( 15 µg/ml ) to the media to maintain the plasmid .
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Clostridium botulinum is a dangerous pathogen that forms the deadly botulinum neurotoxin . Strains of C . botulinum are present in the environment as spores . Under suitable conditions , the dormancy of the bacterial spore is broken , and germination occurs . Germination is initiated following the recognition of small molecules by a specific germinant receptor ( GR ) located within spores . Currently , the identification and characterisation of these GRs remains unknown , but is critical if strategies are to be developed to either prevent spore germination altogether , or to germinate all the spores and then inactivate the emergent sensitive vegetative cells . The present study has characterised two functionally active GRs in C . botulinum which act in synergy and cannot function individually , and a related functionally active GR in C . sporogenes . These GRs respond to amino acids . Other GRs appear to form part of a complex involved in controlling the speed of germination , or are not functionally active . This study provides new insights into the mechanisms involved in germination and will allow us to develop new strategies to control this deadly pathogen .
|
[
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2014
|
Functional Characterisation of Germinant Receptors in Clostridium botulinum and Clostridium sporogenes Presents Novel Insights into Spore Germination Systems
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miRNAs are small RNAs directing many developmental processes by posttranscriptional regulation of protein-coding genes . We uncovered a new role for miR-1-1/133a-2 and miR-1-2/133a-1 clusters in the specification of embryonic cardiomyocytes allowing transition from an immature state characterized by expression of smooth muscle ( SM ) genes to a more mature fetal phenotype . Concomitant knockout of miR-1-1/133a-2 and miR-1-2/133a-1 released suppression of the transcriptional co-activator myocardin , a major regulator of SM gene expression , but not of its binding partner SRF . Overexpression of myocardin in the embryonic heart essentially recapitulated the miR-1/133a mutant phenotype at the molecular level , arresting embryonic cardiomyocytes in an immature state . Interestingly , the majority of postulated miR-1/133a targets was not altered in double mutant mice , indicating that the ability of miR-1/133a to suppress target molecules strongly depends on the cellular context . Finally , we show that myocardin positively regulates expression of miR-1/133a , thus constituting a negative feedback loop that is essential for early cardiac development .
The mammalian heart is the earliest functional organ of the embryo . Ventricular contractions continuously provide blood supply to the developing embryo despite major morphological and functional reorganization of the heart during embryogenesis [1] . Coordination of this complex task is accomplished by a tightly regulated concert of cellular and molecular interactions . An example is the maturation of cardiomyocytes in the embryonic heart , which initially express smooth muscle genes but lose this expression when heart development progresses [2]–[4] . So far , relatively little is known about regulatory mechanisms controlling the transition between immature and mature cardiomyocytes that express smooth muscle genes only under stress conditions or during dedifferentiation [5] . miRNAs have been recognized in recent years as part of the regulatory networks that govern developmental or physiological processes . Heart specific deletion of the enzyme Dicer , essential for generation of miRNAs , and of individual miRNA genes revealed critical functions of miRNA-mediated regulation at various stages of cardiac development ( for review see [6] , [7] ) . Several miRNAs , which play a role during heart development , are specifically expressed in the heart or skeletal muscle such as miR-1/133a miRNAs or the so-called myomiRs located in introns of muscle-specific genes . The function of intronic myomiRs has been addressed in a number of elegant papers suggesting functions mainly under cardiac stress and in disease conditions [8] , [9] while the exact role of miRNAs miR-1 and miR-133a is less clear , in part due to putative compensatory actions of these highly similar miRNAs . However , diseases of the heart also go along with changes of miR-1/133a expression similar to intronic myomirs , although it is often not clear whether such changes are due to an increase of non-cardiomyocytes in diseased hearts [10] . In the mammalian genome two distinct gene clusters located on two different chromosomes encode miR-1 and miR-133a: the miR-1-1/133a-2 and the miR-1-2/133a-1 cluster . Primary sequences of mature miR-1 or miR-133a are identical and both gene clusters show similar expression patterns suggesting that these miRNAs serve at least partially overlapping functions . A third miRNA cluster on mouse chromosome 1 , related to miR-1/miR133a , encodes for miR-206 and miR-133b . In contrast to the miR-1/miR133a cluster , miR-206 and miR-133b are expressed mainly in somites during skeletal muscle development [11] and later become confined to slow skeletal muscle fibers . All three loci produce bicistronic transcripts containing one miRNA from the miR-1/206 family and one from the miR-133 family essentially forming functional units [12] that are under the transcriptional control of heart and muscle specific regulatory programs [13] , [14] . Potential overlapping functions of miR-133a-1 and miR-133a-2 have been investigated by deletion of miR-133a coding regions without impairing miR-1 expression . Interestingly , concomitant deletion of both miR-133a genes causes a fetal heart phenotype of variable penetrance with ventricular septum defects ( VSD ) suggesting that miR-133a does not play a major role in early embryonic development . Surviving miR-133a mutants showed dilated cardiomyopathy with increased proliferation of cardiomyocytes and increased smooth muscle cell gene expression . The phenotype of miR-133a double mutants has been primarily ascribed to the loss of miR-133a-mediated repression of cyclinD2 and SRF [15] . In contrast to the analysis of miR-133a-1 and miR-133a-2 double mutants , only single miR-1-2 mutants have been analyzed . Deletion of miR-1-2 has been reported to cause VSDs leading to reduced survival of mutant mice [16] . In addition , defects in cell cycle regulation and cardiac conduction have been attributed to the up-regulation of the putative miR-1 target molecules Hand2 and Irx5 , as well as of the Kcnd2 potassium channel [16] . miR-1 overexpression has been shown to decrease the pool of proliferating ventricular cardiomyocytes [14] and to attenuate cardiomyocyte hypertrophy by targeting molecules involved in calcium signaling [17] . Here , we analyzed the function of the miR-1-1/133a-2 and miR-1-2/133a-1 clusters for early cardiac development by targeted gene inactivation . Deletion of single miR-1/133a clusters did not lead to major developmental defects and did not impair viability of adult mice while deletion of both miR-1/133a gene clusters caused early embryonic lethality due to severe heart malformations . Transcriptional profiling of miR-1/133a double mutant hearts revealed an up-regulation of genes characteristic for immature cardiomyocytes . Transgenic overexpression of the newly discovered miR-1 target myocardin recapitulated major aspects of the miR-1/133a phenotype . We concluded that miR-1 and miR-133a control the faithful expression of genes in a functionally redundant manner by adjustment of myocardin levels to allow specification of early cardiomyocytes with hybrid expression of cardiomyocyte and smooth muscle specific markers to more differentiated fetal cardiomyocytes .
The two miRNA miR-1/133a clusters constitute functional units at mouse chromosome 2 and chromosome 18 as both miRNAs are expressed in the heart and skeletal muscle as bi-cistronic messages . Mature miR-1-1/miR-1-2 and miR-133a-2/miR-133a-1 differ from each other indicating different target genes . In contrast , mature miR-1-1 is identical to miR-1-2 and miR-133a-2 is identical to miR-133a-1 , suggesting potentially overlapping functions . To resolve the biological function of miR-1/133a clusters in vivo , we generated knock-out mice for each individual cluster ( Suppl . Fig . S1 ) . Mice mutant for single miR-1/133a cluster were born at the expected Mendelian ratio and were viable with survival rates identical to WT littermates ( Suppl . Table S1 ) . We did not observe gross developmental defects or histological aberrations in heart and muscle . ( Fig . 1A–C , Suppl . Fig . S2A , B ) . These findings are in stark contrast to a previous study reporting ventricular septum defects , cardiomyocyte hyperplasia and increased nuclear division of cardiomyocytes after inactivation of miR-1-2 [16] . Furthermore , ECG analysis did not reveal signs of arrhythmias or alterations of the QRS-complex in either single cluster knock-out strains ( data not shown ) . Again , these findings differ from observations reported by Zhao et al . describing changes in the heart rate , shortened PR-interval , and a bundle-branch block in miR-1-2 mutants [16] . At present , the reasons for these differences are unclear although several explanations seem possible ( see discussion ) . Next , we analyzed heart functions of single miR-1/133a cluster mutants by cardiac magnetic resonance imaging ( MRI ) both under baseline condition and after pressure overload induced by transverse aortic constriction ( TAC ) . No significant changes in mean wall thickness , left ventricular mass , and ejection fraction ( EF ) were detected in single cluster mutants compared to wildtype controls under baseline conditions ( Fig . 1D–F ) . After TAC , we detected an increase in mean wall thickness and left ventricular mass and ANP expression , which did not differ between miR-1-1/133a-2 , miR-1-2/133a-1 mutants and wildtype controls ( Fig . 1D–G ) . Interestingly , we found a significant reduction of the ejection fraction in miR-1-1/133a-2 knockout mice while miR-1-2/133a-1 mutants maintained the same normal ejection fraction as wildtype controls indicating that individual miR-1/133a clusters contribute differently to cardiac remodeling in response to pressure overload ( Fig . 1F ) . Analysis of miR-1 and miR-133a concentrations in individual cluster mutants revealed no significant change of miR-1 expression after TAC compared to sham-operated mice ( Fig . 1H ) . Expression levels of miR-133a dropped slightly after TAC in both single cluster mutants suggesting that the respective remaining miR-1/133a gene cluster possesses only a limited ability to react to the loss of individual alleles by increased expression both under baseline and pathological conditions ( Fig . 1I ) . Similarly , we did not detect a compensatory increase of miR-1 and miR-133a expression in embryonic hearts of single miRNA cluster knock-out mice at E10 . 5 ( Fig . 2A ) . However , it is difficult to exclude that the lack of a single cluster already leads to increased compensatory activity of the other cluster , thereby concealing the original contribution of individual clusters in wildtype animals . Next , we generated mice that lack both clusters and hence completely fail to express miR-1 and miR-133a . Crosses of double heterozygous or compound heterozygous/homozygous animals did not yield viable double homozygous mutant animals ( dKO ) . Analysis of different developmental stages revealed that dKO animals did not survive embryonic stage E11 . 5 . A massive impairment of embryonic blood circulation and heart beating was visible in dKO embryos at E11 . 5 ( Suppl . Fig . S3 ) and no living dKO embryos were found after E11 . 5 ( Suppl . Table S2 ) . Expression analysis at E10 . 5 confirmed a complete loss of miR-1 and miR-133a expression in dKO embryos ( Fig . 2A , H , I ) . The pattern of miR-1 expression was not altered in single cluster mutants as visualized by whole mount in situ hybridization using LNA-probes ( Fig . 2B–G ) again indicating that miR-1-1 and miR-1-2 , respectively miR-133a-1 and miR-133a-2 might substitute for each other . Since the miR-1-2/133a-1 cluster is located in an intron of the mib1 ( mindbomb ) gene , a component of the Notch and Wnt pathways , we analyzed expression of mib1 in wt and dKO embryos at E10 . 5 by qRT-PCR . No significant differences in expression levels or splicing patterns were observed in dKO versus wt embryos ( Suppl . Fig . S4 ) . Morphological analysis of E10 . 5 and E11 . 5 dKO embryos revealed severe developmental defects in heart development leading to thinning of the ventricular wall of the developing heart ( Fig . 3A–F ) . Of note , we observed a striking reduction of the number of cells within the compact layer of the heart at E10 . 5 while the trabecular part was less affected . No further growth of compact and trabecular layers was apparent at E11 . 5 most probably due to a global arrest of heart development in dKO embryos ( Fig . 3D ) . A more detailed analysis of the proliferation rate revealed a reduction of EdU incorporating myocardial cells in the compact cell layer of the developing myocardium at E9 . 5 and at E10 . 5 ( Suppl . Fig . S5A–D , Fig . 3G , H ) . Similarly , we found a major reduction of pH3-positive cardiomyocytes identified by expression of myosin heavy chain in E10 . 5 dKO mutant embryos ( Suppl . Fig . S5E , F , Fig . 3I ) . We also detected a strong up-regulation of the cardiac stress marker atrial natriuretic peptide ( ANP ) in the compact layer of dKO mutant embryos at E10 . 5 by immunofluorescence staining ( Fig . 3F ) and by RT-PCR ( Fig . 3J ) but no evidence for increased apoptotic cell death as measured by staining for activated caspase 3 ( data not shown ) . In wild type hearts , expression of ANP at this developmental stage was mostly confined to the trabecular layer ( Fig . 3E ) further supporting the view that the compact layer was more severely affected than the trabecular layer by the loss of miR-1/133a although some morphological abnormalities in the trabecular layer were present as well . To get insights into the molecular processes that are affected by loss of miR-1/133a we performed a comparative RNA expression analysis of the developing heart using RNA isolated from E10 . 5 hearts ( n = 4 , dKO; n = 5 , controls ) . Data obtained by Affymetrix Genechip analysis were validated by specific quantitative RT-PCR Taqman assays using independent samples ( n = 3/3 ) . Unbiased gene ontology enrichment analysis using genes that were at least 1 . 5-fold up-regulated in miR-1/133a dKO compared to control hearts at E10 . 5 revealed that terms subsumed in the category “cell differentiation” showed the most significant enrichment . Other categories at the same level within the gene ontology hierarchy displayed significant lower p-values ( Suppl . Fig . S6 ) . Importantly , we identified a strong enrichment of terms associated with cardiomyocyte and smooth muscle cell differentiation suggesting that miR1/133a repress genes involved smooth/striated muscle differentiation . Myocardin and Kcnmb1 were the strongest up-regulated genes ( Fig . 4A , C ) together with a consistent up-regulation of several smooth muscle markers such as transgelin ( Fig . 4B ) , smooth muscle actin ( Acta2 ) ( Fig . 4D ) , myh11 ( Fig . 4E ) , caldesmon and miR-145 ( Fig . 4A ) . Increased expression of smooth muscle actin in dKO compared to wt cardiomyocytes was confirmed by immunofluorescence analysis of E10 . 5 hearts ( Suppl . Fig . S5G , H ) . Analysis of transcriptional changes in mutant hearts also revealed increased expression of trabecular markers like BMP-10 [18] and Erbb4 [19] ( Fig . 4A , F ) . Moreover , we observed changes in several genes involved in heart development , which probably reflects secondary events due to the global arrest of heart development ( Fig . 4A ) . Specifically , we detected increased expression of BMP-2 , Gata4 , Tbx18 and BMP-7 and consistent down-regulation of Msx1 and Msx2 , which are involved in epithelial to mesenchymal transition and cardiac valve formation [20] . In addition , we saw a down-regulation of the Tbx1-Six1-Eya1 axis essential for morphogenesis of the outflow tract [21] ( Fig . 4A ) . The molecular data reflected morphological alterations in dKO hearts at E10 . 5 and suggested that repression of molecules characteristic for immature cardiomyocytes might be an important function of miR-1/133 in the developing heart . In principle , loss of miRNAs should lead to increased abundance of target transcripts . Hence , we screened for predicted target sites of miR-1 and miR-133a in transcripts that were up-regulated in miR-1/133a dKO mutant hearts using Targetscan ( v6 ) and miRanda ( microrna . org ) . 27 out of 382 genes , which were up-regulated at least 1 . 5-fold , contained conserved target sites for miR-1 or miR-133a . One of the strongest up-regulated genes in that group was myocardin , which carries a conserved target site for miR-1 in the 3′-UTR ( Fig . 5C ) . Myocardin exists in different variants resulting from alternative splicing in cardiomyocytes and smooth muscle cells [22] . Analysis of the expression of different myocardin splice isoforms in E10 . 5 dKO hearts revealed that only the cardiac-specific but not the smooth muscle-specific isoform of myocardin was up-regulated in dKO hearts essentially ruling out effects of miR-1 on myocardin mRNA splicing ( Suppl . Fig . S7 ) . Furthermore , these results indicated that increased abundance of myocardin transcripts is due to miR-1 mediated repression and not caused by general up-regulation of the smooth muscle program . We also detected a conserved miR-133a target site in the 3′-UTR of Kcnmb1 [23] ( Fig . 5D ) , which is normally specifically expressed in smooth muscle cells but up-regulated in miR-1/133a dKO mutant hearts . In contrast , we did not observe transcriptional up-regulation of a number of previously described miR-1 or miR-133a target molecules like SRF , IRQ5 , Hand2 or HDAC4 in dKO hearts ( Fig . 4 ) . At the protein level , myocardin was 3-fold more abundant in dKO mutants than in wild type controls as indicated by western blot analysis of pools ( n = 3 ) of E10 . 5 WT and dKO hearts ( >4 hearts per pool ) ( Fig . 5A ) . The putative miR-133a targets SRF ( Fig . 5B , B′ ) and Hand2 ( Suppl . Fig . S8 ) were not up-regulated at the protein level , which corresponds to the transcriptional analysis . Taken together our results suggested that myocardin represents a primary target for miR-1 and Kcnmb1 for miR-133a miRNAs in vivo at E10 . 5 . To validate the regulatory interactions between miR-1 and myocardin or miR-133a and Kcnmb1 we inserted the respective miRNA binding sites as well as mutant target sites into the 3′-UTR of a luciferase reporter ( Fig . 5C , D ) . Co-transfection of either miR-1 or miR-133a together with corresponding reporter plasmids efficiently suppressed luciferase activity whereas reporter plasmids carrying mutated miRNA binding sites were not affected ( Fig . 5E , F ) confirming our assumption that myocardin and Kcnmb1 are primary targets of miR-1 and miR-133a , respectively . To further validate these findings , we transfected miR-1 , miR-133 or control miRNA into isolated embryonic cardiomyocytes . As expected , miR-1 overexpression resulted in a significant reduction of myocardin mRNA ( Fig . 5G ) and protein ( Fig . 5H ) while miR-133a overexpression caused a significant decline of Kcnmb1 mRNA ( Fig . 5I ) and protein ( Fig . 5J ) concentrations compared to miRNA controls ( Fig . 5H′ , J′ ) . Myocardin is a potent transcriptional co-activator of serum response factor ( SRF ) controlling gene expression of smooth muscle and cardiac cells . Disruption of the myocardin gene abrogates smooth muscle gene expression during embryonic development and causes programmed cell death in postnatal cardiomyocytes [24] , [25] . In addition , overexpression of myocardin in adult cardiomyocytes and other cell types leads to activation of smooth muscle cell genes [26] indicating that a tight regulation of myocardin is necessary for normal heart development . Furthermore , immature cardiomyocytes show several characteristics of smooth muscle cells , such as the expression of smooth muscle marker genes , until approximately E10 , which are only lost at later developmental stages when cardiomyocytes mature [2]–[4] . Interestingly , the adverse effects of the loss of miR-1/133a and up-regulation of myocardin became apparent at the same developmental stage when smooth muscle gene expression is normally lost in cardiomyocytes . To understand the molecular events leading to the miR-1/133a dKO phenotype and to analyze whether increased levels of myocardin induce a similar set of genes up-regulated in miR-1/133a dKO cells , we decided to overexpress myocardin in vitro in NIH3T3 cells and in vivo in embryonic hearts . Myocardin overexpressing NIH3T3 cells , marked by IRES mediated co-expression of EGFP , acquired a SM-cell like spindle shaped morphology and started to express SM-specific genes confirming previous results ( Fig . 6A–E ) 27 , 28 . Affymetrix GeneArray and quantitative RT-PCR analysis revealed an up-regulation of smooth muscle marker genes including Acta2 and Kcnmb1 , which resembled several of the transcriptional changes observed in miR-1/133a KO hearts ( Fig . 6B–E , Suppl . ) . Remarkably , overexpression of myocardin expression even stimulated expression of ANP in NIH3T3 cells ( Fig . 6E ) . Next , we generated mice overexpressing myocardin via the heart-specific α-MHC promoter ( Fig . 7A , B ) . Since overexpression of myocardin in the heart resulted in early embryonic lethality we used F0 embryos , newly generated for each individual experiment . Transgenic embryos ( n = 11 ) with similar levels of myocardin mRNA in individual embryonic hearts were used for further analysis . Hearts of myocardin-expressing transgenic embryos showed a thin compact layer and a preserved trabecular structure at E10 . 5 ( Fig . 7C , D ) strongly resembling the morphologic phenotype seen in miR-1/133a dKO embryos . We also observed reduced proliferation of cardiomyocytes at E10 . 5 ( Fig . 7E , F , K ) and ectopic expression of ANP in the remaining compact layer ( Fig . 7G , H ) . Normally , expression of ANP is confined to the trabecular layer at this developmental stage . Transcriptome analysis of myocardin transgenic hearts revealed additional similarities between miR-1/133a dKO and myocardin-transgenic hearts . Interestingly , these similarities were not only restricted to up-regulation of smooth muscle-marker genes such as Acta2 , Myh11 ( Fig . 7L , M ) but also included dysregulation of other genes involved in heart development ( Erbb4 , BMP2 , BMP-7 , Myo18b , Akap2 , Palm2 , Ppargc1a , Cacna1d , Cacnb2 ) ( Fig . 7N , Suppl . Fig . S10 ) . Most importantly , we observed a striking overlap of genes up-regulated in myocardin-transgenic and miR-1/133a dKO hearts . 90 out of 139 genes up-regulated by 1 . 5-fold in myocardin-transgenic hearts were also up-regulated in miR-1/133a dKO mutants ( Suppl . Fig . S10A ) providing a convincing molecular explanation for the similarity of miR-1/133a dKO and myocardin-transgenic heart phenotypes . While the majority of dysregulated genes in miR-1/133 KO mice and myocardin overexpressing mice showed an up-regulation ( Suppl . Fig . S10B ) we found only few genes that were down-regulated both in miR-1/133 dKO embryos and in myocardin overexpressing embryos . This observation is in line with the established function of the transcriptional coactivator myocardin suggesting that increased myocardin levels primarily stimulate transcriptional activity . In contrast , it seems likely the down-regulation of Msx1/2 [29] and Tbx1/Six1/Eya1 [21] in miR-1/133a dKO hearts occurred by secondary means independent of the up-regulation of myocardin , probably due to the loss of myocardial cells or the global arrest of heart development in miR-1/133a dKO mutants . Of note , we did not observe increased BMP-10 expression in myocardin overexpressing E10 . 5 hearts as in miR-1/133a dKO mutants ( Suppl . Fig . S10 ) . Since , we found a miR-1 binding site located within the ORF region of BMP-10 mRNA , which is able to repress BMP-10 mRNA as indicated by luciferase reporter assays in vitro , it seems likely that miR-1 directly represses BMP-10 in vivo ( Suppl . Fig . S11 ) and thereby normalizes BMP-10 levels in myocardin transgenic embryos . Our analysis suggested that the loss of miR-1 mediated repression of myocardin initiates a cascade of molecular events that is responsible for many aspects of miR-1/133a dKO phenotype . Previous studies demonstrated that miR-1 genes are direct transcriptional targets of the transcription factor SRF [14] , which depends on myocardin or MRTFs to achieve cell type specific transcriptional activity [24] . Since we demonstrated that miR-1 represses myocardin we speculated that miR-1 might be part of a negative feedback loop that restricts its own expression . Therefore , we analyzed expression of miR-1 in myocardin transgenic hearts at E10 . 5 . Interestingly , we found a strong induction of mature miR-1/133a levels ( Fig . 7O ) . Additional RT-PCR based Taqman assays designed to detect pri-miR-1-1 , pri-miR-1-2 , pri-miR-133a-2 , and pri-miR-133a-1 unveiled increased expression of all pri-miRNAs ( Fig . 8A ) indicating that both miR-1/133a clusters are activated by myocardin . To investigate whether myocardin activates the miR-1-1/133-a2 and the miR-1-2/133-a1 gene clusters via previously mapped SRF binding sites [14] , [30] , we performed chromatin immunoprecipitation ( ChIP ) experiments in C2C12 muscle cells using myocardin antibodies . We found that myocardin bound strongly to the SRF binding site up-stream of the miR-1-2/133a-1 gene cluster on chromosome 18 but not to the site up-stream of the miR-1-1/133a-2 gene ( Fig . 8B , C ) suggesting control of miR-1-2/133a-1 expression by a ternary complex composed of SRF and myocardin . In contrast , the miR-1-1/133a-2 gene might be regulated via a so far undisclosed SRF binding site or by other transcription factors such as MEF2 [10] or Tbx5 [7] that are co-activated by myocardin . Taken together , our results suggest that miR-1 mediated repression of myocardin limits transcriptional activation of both miR-1 and miR-133a clusters thereby adjusting its expression ( and of miR-133a ) in a negative feedback loop ( Fig . 7P ) .
The presence of multiple miRNAs with identical or similar mature sequences is a common and evolutionary conserved feature in several species indicating functional significance for the presence of several similar or identical miRNA genes [31] . miR-1 and miR-133a represent a particularly intriguing example since the two gene clusters , which encode mir-1-1/133a-2 and miR-1-2/133a-1 , are completely identical and apparently expressed in the same tissue: heart and skeletal muscle [6] , [7] . The lack of gross morphological abnormalities after genetic inactivation of single miR1-1/miR-133a gene cluster mutants seems to indicate redundant functions but does not rule out a differential requirement of individual miR-1/133a gene clusters under specific conditions . In fact , we found that inactivation of miR-1-1/133a-2 but not miR-1-2/133a-1 impaired the ability of the heart to maintain a physiological ejection fraction after TAC-induced pressure overload . It seems likely that other , so far unknown conditions might predominantly require activity of the miR-1-2/133a-1 gene cluster . The lack of developmental abnormalities in single miR-1/133a gene cluster mutants corroborates previous findings on miR-133a-1 and miR-133a-1 KO animals [15] . In contrast , deletion of miR-1-2 has been reported to cause incompletely penetrant developmental and electrophysiological phenotypes [16] , which do not fit to our observations . In principle , it is possible that the concomitant deletion of both miR-1-2 and miR-133a-1 rescues a potential phenotype caused by the inactivation of miR-1-2 alone but it seems more likely that deletion of miR-1-2 , which is located in an intron of the mib1 gene and close to the transcriptional start-site of RP24-66N1 , a non-coding antisense transcript , has affected regulation of neighboring genes [32] , [33] . Alternatively , the remaining miR-1-1 gene might be expressed at lower levels on the genetic background used by Zhao et al . [16] thereby compromising its compensatory activity and causing an incompletely penetrant phenotype . Deletion of both miR-1/133a clusters revealed a fundamentally new role of miR-1/133a in early heart development . The miR-1/133a dKO phenotype differs significantly from the previously described defect of miR-133a dKO mice , which becomes apparent only at later stages [15] suggesting fundamentally different mechanisms . The complete loss of miR-1/133a did not interfere with formation of the primary heart tube but affected maturation and further specification of embryonic cardiomyocytes during expansion of the compact layer of the myocardium . We observed that miR-1/133a dKO cardiomyocytes failed to get rid of their hybrid smooth muscle/cardiomyocyte phenotype and did not acquire a more mature cardiomyocyte-specific identity . Unbiased transcriptional profiling and molecular analysis of putative miR-1/133a target molecules up-regulated in miR-1/133a dKO mutants uncovered several direct targets of miR-1 and miR-133a including myocardin , Kcnmb1 and BMP-10 . We reasoned that the up-regulation of myocardin , which is a well-characterized transcriptional co-activator of SRF that serves as a major regulatory switch for smooth muscle gene expression [24] , [27] , is instrumental for mediating effects of miR-1 during early heart development . In fact , we discovered that miR-1 directly regulates myocardin mRNA in a heterologous expression system via a target site in the 3′ UTR using luciferase reporter assays and demonstrated that over-expression of miR-1 in embryonic cardiomyocytes resulted in a down-regulation of myocardin . Myocardin plays an important role for the development of visceral and vascular smooth muscle cells . Initially , its function in cardiomyocytes remained unknown due to the lack of a cardiac phenotype in constitutive myocardin knock-out mice [34] . However , more recent studies using cardiac specific deletions of myocardin demonstrated that myocardin is required for cardiomyocyte survival and maintenance of heart function after birth [25] , [35] . At E9 . 5 , myocardin mutant hearts show a pronounced reduction of cardiomyocyte proliferation , which was explained by the inability of SRF to up-regulate BMP-10 in the absence of myocardin [5] . Interestingly , ex vivo culture of myocardin mutant hearts in BMP-10 conditioned media rescues cardiomyocyte proliferation suggesting a pivotal role of BMP-10 in the control of cardiomyocyte proliferation in embryonic hearts . The reduction of cardiomyocyte proliferation in miR-1/133a dKO seems to rely on a different mechanism since BMP-10 expression was increased in miR-1/133a dKO mice but not decreased as in myocardin mutants [5] . We assume that the failure of immature miR-1/133a dKO mutant cardiomyocytes to acquire a more mature phenotype activates a cellular stress program inhibiting further proliferation , since no evidence for direct regulation of cell proliferation by miR-1/133a was found . The link between adjusted myocardin expression levels and expression of smooth muscle marker genes is evident in various pathological conditions of the heart , which are characterized by concomitant up-regulation of myocardin and smooth muscle markers [26] , [36] . To explain the fact that myocardin induces smooth muscle genes in various cells but fails to do so in cardiomyoyctes of healthy fetal and adult hearts , has been explained by the existence of putative negative regulators neutralizing myocardin or of additional cofactors required for myocardin activity in cardiomyocytes [24] . Our results suggest that miR-1 is one of the postulated negative factors restricting myocardin activity in cardiomyocytes . Down-regulation of miR-1 , which occurs under different pathological conditions [10] , and subsequent increase of myocardin activity might explain the up-regulation of smooth muscle marker genes in various diseases of the heart [5] . Initially , it was surprising to see that the increased myocardin activity in miR-1/133a dKO mutants and myocardin transgenic embryos caused up-regulation of multiple smooth muscle marker genes , since the relatively normal expression of smooth muscle genes in myocardin mutant hearts seems to suggest that smooth muscle gene expression in cardiomyocytes is not under direct control of myocardin [34] , [35] . Yet , expression of the myocardin-related genes MRTF A and B might substitute for the lack of myocardin in the heart [35] . Furthermore , increased myocardin expression might stimulate expression of smooth muscle genes even if basal activity of smooth muscle genes under physiological conditions is controlled by other means ( i . e . MRTF A and B ) . Transgenic overexpression of myocardin in the developing heart , which closely mimicked the transcriptional increase seen in miR-1/133a dKO mice , recapitulated many aspects of the miR-1/133a dKO phenotype proving the mechanistic relevance of myocardin up-regulation . Specifically , myocardin overexpression phenocopied morphological changes , reduced cardiomyocyte proliferation , and induced expression of a large set of smooth muscle marker genes all observed in miR-1/133a dKO mutants . In total , 90 out of 139 genes up-regulated by myocardin overexpression were also up-regulated in miR-1/133a dKO mutant hearts . Of course , up-regulation of myocardin does not account for all effects of miR-1/133a as illustrated by 382 genes up-regulated in miR-1/133a dKO mutants but not in myocardin overexpressing hearts . For example , expression of BMP-10 was not increased in myocardin transgenic embryos . The missing up-regulation of BMP-10 in myocardin-overexpressing embryos does not argue against the control of BMP-10 transcription by myocardin , which has been recently demonstrated using myocardin mutant embryos [5] . Rather , it supports the relevance and the efficiency of miR-1 mediated repression of BMP-10 , which seems to be able to normalize increased BMP-10 levels in myocardin overexpressing mice . Surprisingly , we did not observe up-regulation of several previously described miR-1/133 target mRNAs such as SRF , IRQ5 , Hand2 or HDAC4 in miR-1/133 dKO mutant hearts at E10 . 5 [6] , [7] . Apparently , stage-specific , context-dependent mechanisms restrict inhibitory effects of miRNAs probably by blocking access of miRNAs to certain targets or by potential secondary compensatory effects . Transgenic overexpression of myocardin in the heart resulted in a strong induction of expression of both miR-1/133 gene clusters , which together with the inhibition of myocardin by miR-1 suggests the existence of a negative regulatory loop that acts as a rheostat to regulate miR-1/133a . Intriguingly , the genetic linkage of miR-1 and miR-133a allows concomitant regulation of both genes by myocardin thereby including miR-133a into the negative feedback loop constituted by miR-1 and myocardin . It is tempting to speculate that the joint regulation of two different miRNA genes targeting different genes by myocardin is a reason for the evolutionary conservation of miR-1 and miR-133a linkage . The miR-133a target Kcnmb1 that is controlled at the transcriptional level by myocardin is another component of this regulatory network . miR-133a-mediated inhibition of Kcnmb1 and miR-1-mediated suppression of myocardin render Kcnmb1 expression dependent on the balance of miR-1/133a and myocardin concentrations in the cell , which might be important for the regulation of pathophysiologic conditions . Myocardin seems to exert its regulatory activity on miR-1-2/133a-1 via SRF since myocardin was detected by ChIP at a SRF site in the miR-1-2/133a-1 promoter . We did not detect binding of myocardin to the SRF-binding CArG box in the miR-1-1/133a-2 promoter . It is possible that additional CArG elements that have a functional impact on the expression are located further upstream or in intronic regions , which were not included in the analysis . Alternatively myocardin might also regulate the miR-1-1/133a-2 promoter via MEF-2 and Tbx5 , which are also bound and co-activated by myocardin [7] , [10] . Genome wide ChIP-seq experiments will probably solve this question in the future . Taken together our findings illustrate the complex nature of miRNA-mediated regulatory processes , which spatially and temporally restrict gene activity thereby allowing transcriptional co-activators such as myocardin and other effectors to act in a stage-specific manner .
All animal experiments were in accordance with German animal protection laws and were approved by the local governmental animal protection committee . The miR-1-1/133a-2 genomic region was deleted by homologous recombination with a targeting vector inserting an IRES-lacZ-neomycin resistance cassette into the NdeI site of pre-miR-1-1 deleting the miR-1-1 and miR-133a-2 coding regions down to the BamHI site located 140 bp 3′ of miR-133a . The vector contained 4 kb 5′ and 6 kb 3′ homologous 129 genomic sequence . The miR-1-2/133a-1 genomic region was deleted by homologous recombination with a targeting vector that replaced the genomic region coding for pre-miR-133a to pre-mir-1-2 with the IRES-LacZ-neomycin cassette . The vector contained 3 kb genomic region flanking pre-mir-1-2 at the 5′ and 3 . 5 kb genomic sequence flanking pre-miR-133a at the 3′ . Both targeting vectors contained a DTA cassette for negative selection . Targeting vectors were electroporated into MPIII 129SV embryonic stem cells . Homologous recombination was confirmed by Southern Blot analysis using appropriate restriction endonucleases ( suppl . info1 ) and probes hybridizing to genomic regions outside of the vector . Recombinant ES cells were injected into blastocysts and transferred to pseudopregnant mice . Chimeric mice were backcrossed to C57Bl/6 mice . Heterozygous animals were mated to obtain homozygous animals . For ectopic myocardin expression , the myocardin ORF representing splice form NM_145136 . 4 obtained from shuttle clone OCACo5052D0518D ( BioScience ) was inserted into the BamHI site of pIRES2-EGFP ( Clontech ) . The CMV-promoter containing pIRES2-EGFP-pA based construct was used to transfect proliferating NIH3T3 cells ( ATCC ) with Lipofectamine 2000 ( Invitrogen ) according to the manufacturer's instructions . The myocardin-IRES2-EGFP-pA cassette was inserted 3′ to 5 . 6 kb of the murine Myh6 promoter ( cardiac α-MHC ) . Transgenic embryos were newly generated for each individual experiment by pronuclear injection using the Myh6-myocardin-IRES2-EGFP-pA fragment following standard procedures . Recovered embryos were examined for GFP expression and genotyped by PCR using transgene-specific primers ( ACATTGCCAAAAGACGGCAATATGG , GGAATGGCTGGACCTCACTCCACCTAG ) using extraembryonic tissue . All transgenic animals used for further analysis ( n = 11 ) expressed similar levels of myocardin as measured by qRT-PCR . Total RNA from whole hearts of E10 . 5 embryos or NIH3T3 cells was isolated using the Trizol method ( Invitrogen ) . RNA quality was verified using the Agilent Bioanalyser and the RNA 6000 Nano Kit . RNA was labeled following the protocol of Affymetrix . Labeled samples were hybridized to Affymetrix GeneChip Mouse Gene 1 . 0 ST arrays , processed , scanned and analyzed ( RMA with Affymetrix Expression console , statistical analysis using Student's t-test with DNAStar Arraystar 5 . 0 ) . Enrichment of GO annotation and generation of Venn diagrams were accomplished using DNAStar Arraystar 5 . 0 . TaqMan Gene Expression Assays were used for quantitative RT-PCR analysis employing the Applied Biosystems StepOnePlus system . The following FAM dye TaqMan assays were used ( BMP-10: Mm01183889 , Nppa: Mm01255748_g1 , Myocd: Mm01325105_m1 , Erbb4: Mm01256793_m1 , Myh11: Mm00443013_m1 , Acta2: Mm01204962_gH , Tgln1: Mm00441661_g1; Applied Biosystems ) . For normalization , VIC labeled Gapdh assay was used ( ID 4352339E ) . Expression of miRNAs was quantified using FAM labeled TaqMan microRNA Assays ( miR-1: #002222 , miR-133a: #002246 ) . TaqMan MicroRNA Reverse Transcription Kit ( #4366596 ) was applied to convert miRNA to cDNA . VIC labeled TaqMan Assays detecting U6 snRNA ( #001973 ) were used for normalization . Relative expression was calculated using the ΔΔCt method . Kcnmb1 expression was analyzed by qRT-PCR using specific oligonucleotides ( CTGGGAGTGGCAATGGTAGTG , CCGAGTGTCTTCCGTGTGATAC , as described previously [23] . The RT-PCR was performed using a FastStart Universal SYBR-Green Mastermix ( Roche ) to allow quantification . Data were normalized to Gapdh detection ( ACCACAGTCCATGCCATCAC , CATGCCAGTGAGCTTCCCGT ) . Precursor microRNAs of miR-1-1/miR-133a-2 or miR-1-2/miR-133a-1 were detected using taqman assays specific for pri-miR-1a-1 ( m18 ) , pri-miR-1a-2 ( m19 ) , pri-miR-133a-1 ( m20 ) and pri-miR-133a-2 ( m21 ) following instructions of the manufacturer . Proliferating C2C12 cells ( ATCC ) were treated with 1% formaldehyde/PBS for 10 minutes at room temperature before termination of the reaction by addition of 125 mM glycine . Cells were washed using PBS and incubated with cell lysis buffer ( 5 mM HEPES pH 8 , 85 mM KCl , 0 . 5% NP-40 , protease inhibitor mix ) for 10 minutes . Nuclei were isolated by centrifugation ( 5000 rpm , 5 min ) and incubated with nucleus lysis buffer ( 50 mM Triscl pH 8 . 1 , 10 mM EDTA , 1% SDS , protease inhibitor mix ) at 4°C for 10 minutes . DNA was fragmented to an average fragment length of 200–500 bp using sonication ( Bioruptor , Diagenode ) . The DNA was diluted to 500 ng/µl in dilution buffer ( 0 . 01% SDS , 1 . 1% Triton X-100 , 1 . 2 mM EDTA , 16 . 7 mM TrisCl pH 8 . 1 , 167 mM NaCl ) and incubated with Protein A Agarose beads . 5% of the supernatant was kept as total input control . 1 µg of DNA were incubated with anti-myocardin antibody ( R&D systems ) or with IgG control ( Diagenode ) at 4°C overnight . 25% of antibody-binding beads ( KCH-503-008 , Diagenode ) were added to samples and incubated 2 hours at 4°C . Subsequently , beads with bound complexes were consecutively washed with low salt buffer ( 0 . 1% SDS , 1% Triton X-100 , 2 mM EDTA , 20 mM TrisCl pH 8 . 1 , 150 mM NaCl ) , high salt buffer ( 0 . 1% SDS , 1% Triton X-100 , 2 mM EDTA , 20 mM TrisCl pH 8 . 1 , 500 mM NaCl ) , LiCl buffer ( 10 mM TrisCl pH 8 , 250 mM LiCl , 1% NP-40 , 0 . 5% deoxycholic acid , 1 mM EDTA ) and TE buffer . Next , 10% Chelex ( Biorad ) was added to the beads and to the input . Samples were incubated with Proteinase K at 37°C for 30 minutes after incubation at 95°C for 10 minutes . ChiP samples were incubated again at 95°C for 5 min and centrifuged . The supernatant was used for qRT-PCR using SYBR Green Mastermix ( Roche ) with specific primers ( miR-1-2/133a-1: fwd TTGCTTTGGGATTCTTTTGG , rev TCGGGAAGAACATAGGTTGG , miR-1-2/133a-1 control: fwd CCCAGCAAATCTATAAAGA , rev GCCTGTGTGAGGTGATATAG , miR-1-1/133a-2: fwd ATACAACCCAGGTGGGAACA , rev AGAATTGCAGGTCACCTTGG , miR-1-1/133a-2 control: fwd GTGAGGACAGATTAGCCAGTAC , rev CTTCAAGCTCCTCAGAAGGC with an annealing temperature of 60°C following the manufactures instructions . Whole mount in situ hybridization for miRNAs was performed as described previously [11] using dual DIG-labeled LNA antisense probes ( Exiqon ) for mmu-miR-1 . Embryos of different developmental stages were isolated and immediately fixed in PFA . Tissues of postnatal animals were isolated after transcardial PFA perfusion . For paraffin sections , samples were dehydrated following standard protocols , embedded into paraffin and sectioned at 10 µm and H&E stained . For cryosections , tissues were equilibrated in 30% sucrose/PBS , frozen on dry ice . 10 µm sections were mounted on Superfrost slides . Pregnant mice were injected i . p . with 3 mg EdU ( 5-ethynyl-2′deoxyuridine , Click-iT EdU Imaging Kit , Invitrogen C10339 ) . Embryos were recovered at E9 . 5 and E10 . 5 , fixed with PFA and embedded for cryosections . EdU staining was performed according to the manufacturer's instructions . Staining for Phospho-Histone H3 was performed as described in the Immunohistochemistry protocol . Nuclei were stained with Dapi ( 1∶1000 ) , sections were mounted with Fluoromount and analyzed using Zeiss Axioimager ( Z1 ) . For immunohistochemistry , recovered embryos were fixed in 4% PFA for 2 h and genotyped using extra embryonic tissues . Embryos were incubated for 1 h each in PBS and 15% sucrose followed by an overnight treatment with 30% sucrose . Afterwards , embryos were embedded in TissueTek , cryosectioned , and mounted on Superfrost slides . Sections were fixed in 4% PFA , washed with PBS and incubated in blocking solution containing 5% NGS ( normal goat serum ) , 1% BSA and 0 . 3% Triton-X100 for 1 h at RT . Antibodies were incubated in blocking solution 1∶200 overnight at 4°C . After washing with PBS , secondary antibodies and DAPI was applied for 1 h at RT , followed by 3×5 min washing in PBS and embedding in Fluoromount . Pictures were taken using a Z1 axioimager ( Zeiss ) . For Western blot analysis , 10 µg total protein extracts from 3 pools of embryonic E10 . 5 hearts ( n = 4 ) were loaded on NuPAGE Novex Bis-Tris gels ( Invitrogen ) and blotted on nitrocellulose membranes . Quantification of the Western blots was performed by densitometry using the Femto-kit ( Pierce ) and Versadoc-System ( Biorad ) . The following antibodies were used according to the manufacturer's recommendations: anti-Nppa ( 1∶200 , AB 5490 , Chemicon ) , anti-α-Smooth muscle actin ( 1∶500 , Clone 1A4 , Cy3 conjugated , Sigma ) , anti-Myocardin ( 1∶200 , pAB0604 Covalab ) , anti-Tag ( CGY ) FP ( 1∶200 , AB121 Evrogen ) , anti-Myocardin ( 1∶500 , MAB4028 , R&D ) , anti-SRF ( 1∶500 , SC-335 , Santa Cruz ) , anti-Kcnmb1 ( 1∶200 , FL-191 , Santa Cruz ) , anti- Hand2 ( 1∶200 , AF3876 , R&D Systems ) , anti-Phospho-Histone H3 ( Ser-10 ) ( 1∶200 , #32219 , Upstate cell signaling solutions ) , anti-Gapdh ( 1∶1000 , 14C10 Cell signaling ) . Secondary antibodies were: anti-rabbit-Alexa594 ( 1∶1000 , A11012 , Invitrogen ) , anti-mouse-Alexa594 ( 1∶1000 , A11005 , Invitrogen ) , anti-rabbit-Alexa488 ( 1∶1000 , A11070 , Invitrogen ) , anti-rabbit-Alexa488 ( 1∶1000 , A1101 , Invitrogen ) . WT and mutated miRNA binding sites were directionally cloned in quadruplicate into the NheI and XhoI sites of the pmirGLO Dual-Luciferase Vector ( E13330 , Promega ) using oligonucleotides . ( myocd miR-1 binding site: AGAGAACGATGTCATTTAACATTCCGAGGAGAACGATGTCATTTAACATTCCGAGGAGAACGATGTCATTTAACATTCCGAGGAGAACGATGTCATTTAACATTCCGAGA; myocd mutant miR-1 binding site: AGAGAACGATGTCATTTAACAgagCGAGGAGAACGATGTCATTTAACAgagCGAGGAGAACGATGTCATTTAACAgagCGAGGAGAACGATGTCATTTAACAgagCGAGA; Kcnmb1 miR-133a-binding site: AGAAAGGCCTCCTAGGAGGACCAAGGAGAGAAAGGCCTCCTAGGAGGACCAAGGAGAGAAAGGCCTCCTAGGAGGACCAAGGAGAGAAAGGCCTCCTAGGAGGACCAAGGAG; mutant Kcnmb1 miR-133a-binding site: AGAAAGGCCTCCTCTACTAATCACGGAGAGAAAGGCCTCCTCTACTAATCACGGAGAGAAAGGCCTCCTCTACTAATCACGGAGAGAAAGGCCTCCTCTACTAATCACGGAG ) . 70%-confluent HEK293 cells were transfected with 50 ng of the respective plasmid/24-well with or without 50 pmol of miRIDIAN microRNA mimic miR-1 or miR-133a ( Thermo ) using Lipofectamine 2000 ( Invitrogen ) . Each transfection was done in triplicate . Cells were lysed 24 h after transfection . Firefly luciferase and renilla activities were determined using the Dual-Luciferase Reporter assay ( Promega ) and the Mithras LB940plate reader ( Berthold ) . Firefly luciferase intensities were normalized to Renilla activities . Cardiac MRI measurements were performed on a 7 . 0 T Bruker Pharmascan , equipped with a 300 mT/m gradient system , using a custom-built circularly polarized birdcage resonator and the IntraGateTM self-gating tool [37] . The parameters for identification of the ECG were adapted for one heart slice and transferred afterwards to the navigator signals of the remaining slices . Thus the in-phase reconstruction of all pictures is guaranteed . MRI data were analyzed using Qmass digital imaging software ( Medis ) . Mice were measured under volatile isoflurane ( 1 . 5–2 . 0% ) anesthesia . Measurements were based on the gradient echo method ( repetition time = 6 . 2 ms; echo time = 6 . 0 ms; field of view = 2 . 20×2 . 20 cm; slice thickness = 1 . 0 mm; matrix = 128×128; repetitions = 100 ) . The imaging plane was localized using scout images showing the 2- and 4-chamber view of the heart , followed by acquisition in short axis view , orthogonal on the septum in both scouts . Multiple contiguous short-axis slices consisting of 7 to 10 slices were acquired for complete coverage of the left and right ventricle . Embryonic hearts ( E11 . 5–13 . 5 , n = 254 ) were dissected and atria as well as vessels were removed . Remaining ventricles were washed with culture medium ( DMEM 4 . 5 g/ml , 10% FCS , 1× PS , 0 . 1× NEAA ) , incubated three times in predigestion buffer ( 154 . 6 mM NaCl , 11 . 1 mM Glucose , 0 . 027 mM KCl , 0 . 028 mM NaH2PO4×H2O , 11 . 9 mM NaHCO3 , 2 . 5 g/ml Pancreatin , 9 . 9 mM 2 , 3 butanedione monoxine; Sigma B0753 ) for 5 minutes at 37°C . Samples were incubated in digestion buffer ( predigestion buffer containing 0 . 25 mg/ml Liberase , Roche ) 6 to 9 times each time depending on embryonic stage followed by 5 min 1200 rpm centrifugation . Supernatants were pooled and centrifuged , cells were recovered in culture medium and plated on 1% gelatine coated 24 well plates . Medium was changed to medium without antibiotics 12 hours before transfection . Embryonic cardiomyocytes were transfected with 100 pmol miRIDIAN microRNA Mimic ( Thermo Scientific ) and 1 . 8 µl of DharmaFECT 2 transfection reagent ( Thermo Scientific ) according to manufactures instructions . Total RNA and protein was isolated 24 hours after transfection . Statistical analysis of Western blot , RT-PCR , cell proliferation and reporter genes assays was performed using Student's t-test . p-values <0 . 05 were considered to be significant . Microarray data are available via arrayexpress hosted by the EBI ( http://www . ebi . ac . uk/arrayexpress/ ) . Accession numbers are “E-MEXP-3869” and “E-MEXP-3873 . ”
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miRNAs are small non-coding RNAs involved in posttranscriptional regulation of protein-coding genes . In the mammalian genome , two distinct gene clusters code for miR-1 and miR-133a . Primary sequences of mature miR-1 or miR-133a are identical and both gene clusters show similar expression in the heart and skeletal muscle . We have generated compound mutant mice of both miR-1/133a gene clusters resulting in early arrest of heart development while single cluster mutants showed normal morphology but reacted differently to pressure overload . Compound mutant cardiomyocytes were characterized by an immature , mixed smooth muscle-heart muscle phenotype , indicating that miR1-/133a are responsible for specification of the cardiomyogenic lineage . Our search for miR1-/133a targets identified myocardin , which was strongly up-regulated in mutant hearts , while several other putative miR-1/133a targets that have been described before were not altered , indicating that miR-1/133a target control strongly depends on the cellular context . Overexpression of myocardin in embryonic hearts recapitulated major aspects of the miR-1/133a mutant phenotype , suggesting that loss of myocardin suppression is the primary reason for incorrect heart muscle specification in the mutants . In addition , we found that myocardin overexpression stimulated expression of miR-1/133a , which argues for a negative feedback loop required for adjustment of myocardin concentrations in the heart .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2013
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miR-1/133a Clusters Cooperatively Specify the Cardiomyogenic Lineage by Adjustment of Myocardin Levels during Embryonic Heart Development
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The differentiated cell types of the epithelial and mesenchymal tissue compartments of the mature ureter of the mouse arise in a precise temporal and spatial sequence from uncommitted precursor cells of the distal ureteric bud epithelium and its surrounding mesenchyme . Previous genetic efforts identified a member of the Hedgehog ( HH ) family of secreted proteins , Sonic hedgehog ( SHH ) as a crucial epithelial signal for growth and differentiation of the ureteric mesenchyme . Here , we used conditional loss- and gain-of-function experiments of the unique HH signal transducer Smoothened ( SMO ) to further characterize the cellular functions and unravel the effector genes of HH signaling in ureter development . We showed that HH signaling is not only required for proliferation and SMC differentiation of cells of the inner mesenchymal region but also for survival of cells of the outer mesenchymal region , and for epithelial proliferation and differentiation . We identified the Forkhead transcription factor gene Foxf1 as a target of HH signaling in the ureteric mesenchyme . Expression of a repressor version of FOXF1 in this tissue completely recapitulated the mesenchymal and epithelial proliferation and differentiation defects associated with loss of HH signaling while re-expression of a wildtype version of FOXF1 in the inner mesenchymal layer restored these cellular programs when HH signaling was inhibited . We further showed that expression of Bmp4 in the ureteric mesenchyme depends on HH signaling and Foxf1 , and that exogenous BMP4 rescued cell proliferation and epithelial differentiation in ureters with abrogated HH signaling or FOXF1 function . We conclude that SHH uses a FOXF1-BMP4 module to coordinate the cellular programs for ureter elongation and differentiation , and suggest that deregulation of this signaling axis occurs in human congenital anomalies of the kidney and urinary tract ( CAKUT ) .
The ureter is a pivotal component of the urinary system by warranting the efficient removal of the urine from the renal pelvis to the bladder . This task is accomplished by the compartmentalized organization of the straight tube into an outer flexible but rigid peristaltically active mesenchymal coat with contractile smooth muscle cells ( SMCs ) and surrounding fibrocytes of the inner Lamina propria and the outer Tunica adventitia , and a highly distensible yet tightly sealing specialized inner epithelial lining . This urothelium features at the luminal side large binucleate superficial ( S- ) cells that exert barrier function at least partly due to expression of uroplakins ( UPKs ) that form crystalline plaques on the surface . Underneath are two layers of smaller intermediate ( I- ) and basal ( B- ) cells that serve as precursors in injury conditions and tether the underlying fibrocytes , respectively [1–4] . Although the tissue architecture of the ureter is much less complex compared to the adjacent kidney , our knowledge on the cellular and molecular programs that drive the growth and differentiation of this organ from a simple embryonic rudiment have only recently begun to be elucidated [5] . Cell lineage and marker analyses in the mouse have shown that the different epithelial and mesenchymal cell types of the ureter arise in a highly coordinated fashion from uncommitted progenitors that are established around embryonic day ( E ) 11 . 5 from two independent precursor pools in the early metanephric field , the distal portion of the ureteric bud and its surrounding mesenchyme [4] . At E12 . 5 , the initially homogenous ureteric mesenchyme is radially subdivided into an inner layer of large cuboidal cells , and an outer layer of tangentially oriented loosely organized cells . While the latter start to differentiate into adventitial fibrocytes from E13 . 5 onwards , the first maintain a bipotential character until E15 . 5 when they differentiate into SMCs , and subepithelial fibrocytes of the Lamina propria . Urothelial differentiation starts around E14 . 5 with the establishment of a common progenitor for S- and B-cells , the I-cell that expresses ΔNP63 and low levels of UPKs . At E15 . 5 , first luminal cells downregulate ΔNP63 and express high levels of UPKs to become S-cells . KRT5+ B-cells are first recognized at E16 . 5 . They substantially expand thereafter to constitute the major cell type of the adult urothelium ( see S1 Fig for a scheme of the cellular composition of the embryonic and adult ureter ) [4] . Survival , growth and differentiation of the ureteric mesenchyme and epithelium are tightly coupled and rely on the exchange of signals between and within the two tissues [5–7] . While our knowledge of the signaling systems that underlie urothelial development has remained scarce , WNTs , BMP4 and SHH have been identified as crucial signals for SMC differentiation in the mesenchyme [8–11] . SHH is expressed in the ureteric epithelium throughout development and is thought to act in a paracrine fashion onto the adjacent mesenchyme . Global or tissue-specific deletion of Shh from the epithelium resulted in reduced mesenchymal proliferation and delayed SMC differentiation , and culminated in hydroureter , i . e . dilatation of the ureter by urinary pressure [8 , 11] . The molecular targets of SHH signaling are poorly understood . So far , expression of the genes encoding the transcription factor TSHZ3 and the signaling molecule BMP4 have been described to depend on SHH pathway activity in the ureteric mesenchyme [8 , 12] . Both genes are essential for SMC differentiation arguing that they mediate some part of SHH function [9 , 12] . Canonical WNT signaling is also required for SMC differentiation and may act in parallel to SHH in this process [10] . Here , we further explore the cellular and molecular functions of ( S ) HH signaling in the ureteric mesenchyme . We show that HH signaling is not only required for mesenchymal proliferation and differentiation but also prevents apoptosis in adventitial precursors and is essential for growth and differentiation of the ureteric epithelium . We provide evidence for a mesenchymal FOXF1-BMP4 module acting downstream of SHH in the execution of the proliferation and differentiation functions .
To investigate the functional requirement of HH signaling in ureter development , we employed a conditional gene inactivation approach using a Tbx18cre line [13] and a floxed allele of Smo ( Smofl ) [14] which encodes a unique signal transducer of this pathway [15] . As previously reported , Tbx18cre mediates recombination in the undifferentiated ureteric mesenchyme from E10 . 5 onwards , i . e . in the precursors of all differentiated cell types of the ureteric wall [10 , 16] . At E18 . 5 , urogenital systems of Tbx18cre/+;Smofl/fl ( SmoLOF ) mice displayed complete bilateral hydroureter with full penetrance in both sexes ( Fig 1A–1D , S1 Table for a list of numbers , genotypes and conditions used for this and the other experiments ) . Histological analyses revealed a reduced pelvic space in mutant kidneys . The ureter was strongly dilated and featured a mono-layered urothelium that was surrounded by fibroelastic material ( Fig 1E–1H ) . Expression of the structural components of the SMC layer ACTA2 , MYH11 and Tnnt2 as well as of the key regulator of the SMC transcriptional program Myocd was completely absent in the mutant ureter ( Fig 1I–1P ) . Differentiation of urothelial cell types was also severely compromised in the mutant ureter as indicated by a strong decrease in expression of the B- and I-cell markers KRT5 and ΔNP63 , and absence of superficial UPK1B expression ( Fig 1Q–1T ) . To test for the contiguity of the ureteric lumen and the patency of the uretero-pelvic and vesicular junctions , we injected ink into the renal pelvis . Under conditions of increased hydrostatic pressure , the ink readily drained to the bladder both in control and SmoLOF urogenital systems . Furthermore , the ureters in SmoLOF embryos terminated in the bladder neck as in the control , arguing together that physical obstruction does not cause or contribute to the hydroureter phenotype in SmoLOF urogenital systems ( Fig 1U–1X ) . Control ureters explanted at E14 . 5 and cultured for 4 days elongated and performed unidirectional peristaltic contractions within 2 days of culture . In contrast , SmoLOF ureters were strongly hypoplastic when explanted and degenerated in culture without showing any signs of contractile activity ( Fig 1Y and 1Z’ ) . Hence , lack of Smo , i . e . of HH signaling , in the ureteric mesenchyme results in tissue hypoplasia , a complete lack of differentiated mesenchymal and epithelial cell types and hydroureter formation at birth . To characterize the onset and progression of the growth and differentiation defects in SmoLOF ureters , we performed histological and molecular analysis at earlier embryonic stages ( Fig 2A–2F ) . At E12 . 5 , SmoLOF ureters appeared histologically unremarkable . The mono-layered ureteric epithelium was surrounded by up to two layers of spherical , densely packed mesenchymal cells with a clear compartment boundary to the outer spindle-shaped and radially oriented cells as in the control , indicating that initial tissue patterning of the ureteric mesenchyme was normal ( Fig 2A , left panel ) . At E14 . 5 , the urothelium of control embryos started to stratify and appeared occasionally double-layered , the compartmentalization of the ureteric mesenchyme was enhanced . In contrast , the SmoLOF urothelium remained mono-layered and the mesenchymal cell mass was sparse ( Fig 2A , middle panel ) . At E16 . 5 , the onset of substantial urine production in the embryonic kidney , SmoLOF mutants showed a strongly dilated ureter with a mono-layered urothelium surrounded by loosely packed fibrocytes ( Fig 2A , right panel ) . To characterize the initiation and progression of ureteric SMC differentiation , we analyzed the expression of the regulatory gene Myocd as well as of the SMC structural genes Myh11 and Tagln . Myocd expression was homogenously strong in the wildtype at E14 . 5 and E16 . 5 whereas Myh11 and Tagln expression was spotty at E14 . 5 and became stronger at E16 . 5 . SmoLOF ureters never expressed any of these markers , indicating that SMC differentiation was not initiated in the mutants ( Fig 2B–2D ) . Urothelial differentiation started in the wildtype at E14 . 5 with the expression of ΔNP63 and continued at E16 . 5 with the appearance of ΔNP63+KRT5+ B-cells and UPK1B+ΔNP63- S-cells . In SmoLOF mutant ureters , only few cells expressed ΔNP63 at low levels at E16 . 5 , KRT5 expression and UPK1B was not observed ( Fig 2E and 2F ) . Taken together , SmoLOF ureters develop severe mesenchymal and epithelial hypoplasia and fail to initiate the SMC and urothelial differentiation programs . To address the cellular causes for the severe tissue hypoplasia observed in SmoLOF ureters , we examined survival and proliferation in the epithelial and mesenchymal tissue compartments ( Fig 2G–2I ) . We used the terminal dUTP nick end-labeling ( TUNEL ) assay to detect apoptotic bodies . At E12 . 5 , only few apoptotic bodies were detected in control specimens whereas SmoLOF ureters showed numerous strong signals specifically in the outer mesenchymal compartment . At E14 . 5 , no signals were detected in either control or mutant ureters ( Fig 2G ) . To assess proliferation rates , we performed bromodeoxyuridine ( BrdU ) incorporation assays . At E12 . 5 , SmoLOF ureters showed significantly decreased proliferation in the inner mesenchymal compartment and the epithelium; outer mesenchymal cells proliferated at normal rates . At E14 . 5 , no changes in proliferation were observed in SmoLOF ureters ( Fig 2H and 2I ) . We conclude that Smo is required for the survival of cells of the outer mesenchymal compartment and the proliferation of inner mesenchymal and epithelial cells , specifically at E12 . 5 . The analysis of the Smo loss-of-function phenotype revealed a critical requirement of HH signaling in survival , growth and differentiation of the ureter . To test for a possible sufficiency in these cellular processes we performed a complementary gain-of-function study by conditional ( Tbx18cre-mediated ) misexpression of a constitutive active form of SMO from the Rosa26 locus ( R26SmoM2 ) [17] in the ureteric mesenchyme . Tbx18cre/+;R26SmoM2/+ ( SmoGOF ) embryos died around E12 . 5 due to cardiovascular defects [18] . To circumvent this lethality and enable an endpoint analysis of ureter differentiation , we explanted E11 . 5 kidney rudiments and cultured them for 8 days . We took advantage of a membrane-bound GFP reporter from the Rosa26mTmG reporter line [19] to visualize the descendants of the undifferentiated ureteric mesenchyme after Tbx18cre-mediated recombination . In Tbx18cre/+;R26mTmG/+ control explants , GFP+ cells initially localized to a band of mesenchymal cells that surrounded the ureter stalk and separated the metanephric mesenchyme from the nephric duct . In the following days , GFP+ cells became restricted to a condensed cell layer directly adjacent to the ureteric epithelium and to stromal cells of the medial kidney cortex as previously reported [16] . In SmoGOF ( Tbx18cre/+;R26mTmG/SmoM2 ) explants , GFP+ cells localized to these domains as well but additionally persisted in the lateral ureteric mesenchymal region to form a large ectopic cell mass after 4 and 8 days of culture ( Fig 3A and 3B ) . Histological analysis on proximal ureter sections of SmoGOF E11 . 5 + 8d explants confirmed severe mesenchymal hyperplasia ( Fig 3C and 3D ) . Coimmunofluorescence analysis of GFP and the SMC markers TAGLN and ACTA2 revealed correct mesenchymal patterning into a GFP+TAGLN-ACTA2- cell layer adjacent to the urothelium , a medial GFP+TAGLN+ACTA2+ SMC layer and an outer largely expanded coat of GFP+TAGLN-ACTA2- cells in SmoGOF explants ( Fig 3E–3H ) . Expression of Aldh1a2 identified the inner mesenchymal layer as the Lamina propria [10] . The strongly expanded outer mesenchymal cell layer expressed Fbln2 , Foxd1 and Postn , markers for adventitial fibrocytes in the wildtype ( Fig 3I–3P ) [4] . Urothelial differentiation as analyzed by ΔNP63 and UPK1B expression was unaltered ( Fig 3Q and 3R ) . We conclude that mis- and overactivation of HH signaling in the ureteric mesenchyme leads to massive hyperplasia of the adventitial cell layer but does not affect tissue patterning or cell differentiation programs . To unravel the cellular cause of tissue hyperplasia in SmoGOF ureters , we analyzed histology , cell proliferation and apoptosis at the onset of ureter development . At E12 . 5 , SmoGOF ureters were shortened and surrounded by a large mass of fibrous tissue ( Fig 4A and 4B ) . On the histological level , the subdivision of the ureteric mesenchyme into an inner region with large cuboidal cells and an outer region of more loosely organized tangentially oriented cell bodies was normal but the outer mesenchymal domain appeared strongly expanded ( Fig 4C and 4D ) . The BrdU incorporation assay revealed significantly increased proliferation in the epithelium and the inner mesenchymal domain of SmoGOF ureters at E12 . 5 ( Fig 4E–4G ) . Incorporation of Lysotracker ( DND-99 ) , a fluorogenic marker for acidified organelles [20] , into whole E11 . 5 explants after 1 day of culture indicated absence of apoptotic cells in the entire ureteric mesenchyme , with the lateral aspect of SmoGOF explants being most prominently affected ( Fig 4H and 4I ) . Moreover , mesenchyme mechanically separated from the ureteric epithelium and cultured for 6 days in the presence of 2 μM of the SMO agonist purmorphamine [21] survived while DMSO treated control explants died ( Fig 4J and 4K ) . These experiments show that tissue hyperplasia after mis- and overactivation of HH signaling in the ureteric mesenchyme is caused by a combination of reduced cell death in adventitial precursors and increased cell proliferation in SMC progenitors and the epithelial compartment . To get insight into the spectrum of genes controlled by HH signaling in the ureteric mesenchyme , we wished to determine the global transcriptional changes caused by inhibition of the pathway in the ureter . Rather than comparing mutant ( SmoLOF ) and wildtype ureters , we deemed that pharmacological inhibition of HH signaling by the SMO antagonist cyclopamine [22 , 23] in ureter explant cultures would provide a better handle to identify primary transcriptional changes . Treatment of E12 . 5 ureters with 10 μM cyclopamine led to a robust down-regulation of expression of the direct target of HH signaling Ptch1 in the ureteric mesenchyme [24] ( S2 Fig ) . Moreover , administration of 10 μM cyclopamine to E11 . 5 kidney/ureter explants for 2 days led to a complete loss of ureteric SMC differentiation after 8 days of culture while inhibition in later time intervals left this differentiation program unaffected ( S3 Fig ) . Since these findings delimited the requirement of HH signaling in the ureteric mesenchyme to E11 . 5 to E13 . 5 , we decided to treat E12 . 5 ureters with 10 μM cyclopamine for 18 h to perform microarray profiling of differential gene expression with untreated controls . Using an intensity threshold of 150 , we identified in two independent pools of treated and untreated ureters a small set of 20 genes that were consistently more than 2-fold downregulated and only one gene that was upregulated in expression in cyclopamine treated ureters ( Fig 5A and S2 Table ) . Among the downregulated transcripts were the three bona fide SHH target genes Hhip ( -11 . 9x ) , Ptch1 ( -3 . 2x ) and Gli1 ( -2 . 3x ) , confirming the specificity of our assay [24–28] . Another group of prominently downregulated transcripts comprised three members of the Forkhead transcription factor family , Foxf1 ( -5 . 3x ) , Foxl1 ( -3 . 9x ) and Foxf2 ( -3 . 3x ) , which have been reported to be primary SHH target genes in several other contexts [29–31] ( Fig 5B ) . To validate our microarray results and determine the spatial expression of selected candidates we performed in situ hybridization analysis on proximal sections of E12 . 5 control SmoLOF and SmoGOF and of E14 . 5 control and SmoLOF ureters ( Fig 5C and S4 Fig ) . Hhip expression was barely detectable at E12 . 5 and E14 . 5 in the ureteric mesenchyme of wildtype embryos but was abrogated in SmoLOF and weakly induced in SmoGOF ureters . Expression of Ptch1 and Gli1 was strong in the inner layer of the ureteric mesenchyme at E12 . 5 in the control . Expression was completely lost in SmoLOF ureters , but induced in the entire ureteric mesenchyme in SmoGOF ureters at this stage . At E14 . 5 , the expression of Ptch1 and Gli1 in the inner mesenchymal compartment was HH signaling-dependent , whereas outer mesenchymal cells maintained normal levels of Gli1 . Foxf1 expression was detectable at E14 . 5 in the inner mesenchymal compartment of wildtype embryos . Expression was completely lost in SmoLOF ureters at this stage but was not induced in SmoGOF ureters at E12 . 5 . Expression of Ddit4l ( -3 . 2x ) and Avpr1a ( -2 . 5x ) was detected in the inner mesenchymal region of controls at E12 . 5 , and was down-regulated in SmoLOF but not induced in SmoGOF ureters ( Fig 6C ) . The sensitivity of the method was not sufficient to detect expression of Foxl1 , Foxf2 , Crym , Ndp and Wif1 ( S4 Fig ) . Previous work suggested that Bmp4 and Tshz3 are targets of HH signaling [8 , 12] , and that Bmp4 , Tshz3 , Tcf21 , Tbx18 , Sox9 and canonical WNT signaling are functionally involved in SMC differentiation in the ureter or in other contexts [9 , 12 , 13 , 32 , 33] . In our microarray , expression of Bmp4 and Tcf21 was 1 . 5 fold down-regulated , expression of Tshz3 , Tbx18 and Sox9 was unchanged , and canonical WNT signaling as seen by expression of the bona fide target gene Axin2 {Jho , 2002 #36} was slightly upregulated ( S5A Fig ) . In situ hybridization analysis showed that expression of Bmp4 and Tcf21 in the ureteric mesenchyme was strongly reduced in SmoLOF ureters at E12 . 5 and E14 . 5 . Interestingly , Tcf21 expression was expanded into the entire ureteric mesenchyme in SmoGOF ureters whereas Bmp4 expression remained confined to the entire mesenchymal region albeit at increased levels . Tshz3 , Tbx18 and Sox9 exhibited slightly reduced expression in the ureteric mesenchyme in SmoLOF ureters ( possibly due to tissue hypoplasia ) , and were weakly expanded to the outer mesenchymal domain in SmoGOF ureters . In E14 . 5 SmoLOF ureters , their expression was maintained at low levels in the inner mesenchymal region . Expression of Axin2 in the inner mesenchymal cell layer appeared unaffected by loss or gain of HH signaling in the ureteric mesenchyme ( S5B Fig ) . Together , these assays identify Foxf1 , Ddit4l and Avpr1a as novel targets of HH signaling in the ureteric mesenchyme . Expression of Bmp4 and Tcf21 may indirectly depend on HH signaling whereas Tshz3 , Tbx18 , Sox9 and canonical WNT signaling are independent from this pathway . Previous work identified prominent functions for Foxf1 and Foxf2 as targets of epithelial SHH signals in SMC differentiation of the intestinal mesenchyme [30] . Given that Foxf1 is expressed in the ureteric mesenchyme at E14 . 5 , i . e . prior to the onset of SMC and S-cell differentiation , we wondered whether this transcription factor mediates part of the function of HH signaling in these programs in the ureteric mesenchyme . To test this hypothesis , we used a conditional Cre/loxP-based transgenic approach to misexpress a dominant negative version of FOXF1 in the ureteric mesenchyme in vivo . We deemed such a strategy more efficient than a conditional knockout considering the possible redundancy of Foxf1 and Foxf2 . We generated the dominant negative version of FOXF1 by fusing the open reading frame of this transcriptional activator to a cDNA fragment harboring the strong transcriptional repression domain of the Drosophila ENGRAILED ( ENG ) protein [34 , 35] . This coding region was followed by a fragment harboring an IRES-GFP sequence to allow visualization of misexpressing cells . The bicistronic transgene-cassette was integrated in the ubiquitously expressed X-chromosomal Hypoxanthine guanine phosphoribosyl transferase ( Hprt ) locus ( HprtFoxf1DN ) [36 , 37] . Transgene expression was driven by the Tbx18cre line . Due to random X-chromosome inactivation , female Tbx18cre/+;HprtFoxf1DN/+ embryos possessed a mosaic expression . Male Tbx18cre/+;HprtFoxf1DN/y ( Foxf1DN ) embryos expressed the transgene in a uniform manner and were subsequently used for phenotypic analysis . Since Foxf1DN embryos died shortly after E14 . 5 , we explanted E14 . 5 control and Foxf1DN ureters and cultured them for 6 days to assess tissue integrity and terminal differentiation . Hematoxylin and eosin staining of sections demonstrated mesenchymal hypoplasia and a reduction of the urothelium from three to two cell layers in cultured Foxf1DN ureters ( Fig 6A and 6B ) . Immunofluorescence analysis revealed a strong reduction of TAGLN and ACTA2 expression and absence of ΔNP63/UPK1B indicating severely compromised mesenchymal and epithelial cell differentiation in Foxf1DN ureters at this stage ( Fig 6C–6H ) . To characterize the onset of these phenotypical changes , we analyzed earlier embryonic stages of Foxf1DN ureters . Hematoxylin and eosin stainings at E12 . 5 and E14 . 5 revealed no dramatic effects on overall tissue size in the epithelial and mesenchymal compartments of the mutant ureter . However sub-division of the ureteric mesenchyme into inner cuboidal SMC precursors and outer spindle shaped adventitial fibrocytes appeared less clear ( Fig 6I ) . Expression of the HH target gene Ptch1 was strongly reduced in the inner mesenchymal region at E12 . 5 and E14 . 5 indicating a possible role of FOXF1 as a feed-back activator of SHH signaling ( Fig 6J ) . Strikingly , Foxf1 was required to maintain Bmp4 expression at E12 . 5 and E14 . 5 , suggesting that Foxf1 mediates Bmp4 expression downstream of HH signaling ( Fig 6K ) . Tshz3 , Tcf21 , Tbx18 , Sox9 and Axin2 were normally expressed in Foxf1DN mutants , ( S6 Fig ) . Importantly , SMC differentiation as analyzed by Myocd , Myh11 and Tagln expression was not initiated in Foxf1DN ureters at E14 . 5 ( Fig 6L–6N ) . Apoptosis in the ureter was not changed at either stage while proliferation in the inner mesenchymal region and the epithelium was reduced at E12 . 5 in Foxf1DN embryos ( Fig 6O–6Q ) . We conclude that FOXF1 acts upstream of Bmp4 , and is required to mediate the proliferation and differentiation but not the survival function of HH signaling in ureter development . To stringently test which of the various cellular functions of HH signaling in the ureter is mediated by FOXF1 , we wished to restore Foxf1 expression in ureter explants in which HH signaling was abolished by administration of cyclopamine . For this purpose , we employed the Hprt strategy again to generate an allele for conditional misexpression of Foxf1 ( HprtFoxf1 ) . Since Tbx18cre/+;HprtFoxf1/y male embryos showed early embryonic lethality prior to the onset of kidney development at E10 . 5 , we used an inducible Axin2creERT2 line that mediates recombination specifically in the inner mesenchymal domain of the ureter [4 , 38] . Axin2creERT2/+;HprtFoxf1/y ureters explanted at E12 . 5 and cultured for 3 days in the presence of 500 nM 4-Hydroxy-Tamoxifen showed robust expression of Foxf1 in the inner mesenchymal region and restored Bmp4 and Foxf1 expression after cyclopamine treatment proving the suitability of our approach ( S7 Fig ) . E12 . 5 Axin2creERT2/+;HprtFoxf1/y ureters cultured for 6 days in the presence of 500 nM 4-Hydroxy-Tamoxifen with or without 10 μM cyclopamine were morphologically indistinguishable from wildtype controls indicating that reconstitution of Foxf1 expression was not able to alleviate cyclopamine induced tissue hypoplasia in this setting ( Fig 7A ) . However , SMC differentiation as analyzed by ACTA2 and TAGLN expression and urothelial differentiation as analyzed by ΔNP63 and UPK1B expression was rescued in cyclopamine treated Axin2creERT2/+;HprtFoxf1/y explants , indicating that FOXF1 controls these differentiation programs downstream of HH signaling ( Fig 7B–7D ) . To address the role of BMP4 as a possible mediator of the HH and FOXF1 function , we performed additional pharmacological manipulation experiments in ureter explant cultures . First , we cultured E12 . 5 ureters for 6 days with or without 100 ng/ml BMP4 and 10 μM cyclopamine . Interestingly , BMP4 was able to reduce cyclopamine-induced epithelial and mesenchymal hypoplasia and to completely restore epithelial differentiation . However , it was not sufficient to induce SMC differentiation ( Fig 7E–7H ) . Similarly , BMP4 administration to E12 . 5 Tbx18cre/+;HprtFoxf1DN/y ( Foxf1DN ) explants did not rescue SMC differentiation but restored urothelial differentiation after 6 days of culture ( Fig 7I–7L ) . To test the requirement of BMP4 downstream of HH signaling and FOXF1 , we treated wildtype and Axin2creERT2/+;HprtFoxf1/y ureter explants with 10 μg/ml NOGGIN , which sequesters BMP4 from its receptor [39] or with a combination of NOGGIN and the SMO inhibitor cyclopamine . In all cases , expression of the SMC markers TAGLN and ACTA2 , and of the urothelial markers ΔNP63 and UPK1B was completely abolished ( Fig 7M–7P ) . Finally , when we co-treated wildtype ureters with the HH signaling activator puromorphamine and the BMP4 antagonist NOGGIN for 6 days , inner mesenchymal and epithelial cells were hypoplastic and did not differentiate . However , outer mesenchymal cells showed massive hyperplasia indicating that BMP4 is required downstream of HH signaling and FOXF1 for proliferation and differentiation of inner mesenchymal and epithelial cells but does not mediate the survival function in adventitial precursor cells .
The functional significance of Shh for ureter development was initially addressed by a conditional gene targeting experiment . Mice with loss of Shh from the nephric duct and its derivatives showed reduced mesenchymal proliferation and delayed and reduced SMC differentiation , and developed hydroureter with associated hydronephrosis at birth [8] . Later , mice with a complete loss of Shh were reported to display with 50% penetrance bilateral renal aplasia or hydroureter and hydronephrosis indicating a more profound role for SHH in the development of the complete upper urinary tract [11 , 40] . Targeted inactivation of HH signaling in the mesenchyme surrounding the renal pelvis and upper ureter did not compromise SMC differentiation but interfered with establishment of cells required for impulse initiation and propagation indicating an additional role for Shh in the development of ureter peristalsis [41] . Our study aimed to better understand the role of HH signaling in early ureter development by deleting its unique signaling mediator gene Smo in the ureteric mesenchyme . We observed reduced proliferation rates in the inner mesenchymal region at E12 . 5 , a failure to initiate SMC differentiation at E14 . 5 , and formation of hydroureter at birth . This confirms the previous studies that epithelial SHH is crucial for the structural architecture of the ureter by regulating in a paracrine fashion the proliferation and SMC differentiation of adjacent mesenchymal cells . The difference in the severity of SMC defects in the conditional loss-of-function models may derive from variable efficiency of cre recombination or different genetic backgrounds . Alternatively , it may indicate that other HH family members provide a minor but relevant input to SMO-mediated signaling in the ureter . A paradigm for this is found in the intestinal epithelium where SHH and IHH cooperatively signal to the underlying mesenchyme [42 , 43] . In contrast to previous studies [8 , 11] , we also analyzed the consequence of abrogation of HH signaling for epithelial development . To our surprise , we found that proliferation and differentiation of the epithelial compartment was similarly affected than that of the mesenchyme; proliferation was reduced at E12 . 5 and epithelial differentiation was not initiated at E14 . 5 resulting in epithelial hypoplasia and a complete lack of urothelial cell types at E18 . 5 . While it is possible that epithelial SHH uses paracrine and autocrine signaling pathways to regulate proliferation rates in the mesenchyme and epithelium , respectively , our approach to manipulate the signaling pathway in the mesenchyme disfavors an autocrine mode of HH signaling and rather suggests that mesenchymal HH signaling uses a relay signal to affect epithelial cell cycle progression and differentiation . Since cell density and cell number can affect cellular differentiation programs [44] , the argument may arise that epithelial and mesenchymal differentiation defects are secondary to the severe hypoplasia found in Smo-deficient ureters . However , our genetic rescue experiments showed that robust SMC and urothelial differentiation occurs despite massive tissue hypoplasia , indicating that HH controlled cyto-differentiation does not rely on cell number . Misexpression of a constitutively active form of SMO in the entire ureteric mesenchyme resulted in increased cell proliferation in the inner mesenchymal region and the epithelium indicating that the level of SHH is a limiting factor in this program . However , it did not result in ectopic or enhanced SMC differentiation in the outer mesenchymal layer . Together with our recent finding that loss of canonical WNT signaling in the ureteric mesenchyme abrogates the SMC investment of the ureter [10] , it seems plausible that initiation of SMC differentiation depends on the combinatorial input of both epithelial SHH and WNT signals and that the short range signaling activity of the latter is decisive to restrict the program to mesenchymal cells adjacent to the ureteric epithelium . WNT signals may also impinge on mesenchymal proliferation since proliferation rates were reduced but not stalled in mice with mesenchyme specific loss of both WNT or HH signaling in the ureter [10] . Our study also found that loss of HH signaling in the ureteric mesenchyme results in a massive increase of programmed cell death in the outer mesenchymal domain at E12 . 5 , and severe ureter hypoplasia from E14 . 5 onwards . Moreover , expression of a conditionally activated form of SMO completely abolished apoptosis in the lateral mesenchymal domain at E11 . 5 and led to massive tissue hyperplasia of this region from which adventitial fibrocytes normally arise . Importantly , pharmacological activation of SMO was sufficient to trigger survival of isolated ureteric mesenchyme . These findings demonstrate that HH signaling is required and sufficient to maintain cell survival in the outer region of the undifferentiated ureteric mesenchyme . The tight spatial and temporal regulation of this activity may be instrumental in defining the size of adventitial precursor pool as well as severing the ureter from the kidney . In any case , the finding that HH signaling suffices to maintain ureteric mesenchymal cells in vitro , may open avenues for easier manipulation of these progenitors in the future . All in all , our data suggest that epithelial SHH signals are crucial for the coordinated elongation of the early ureter tube by controlling the survival of tunica adventitia precursor cells and by coordinating proliferation and differentiation of the inner mesenchymal cell layer and the adjacent epithelial compartment . Previous work showed that expression of Bmp4 in the ureteric mesenchyme depends on Shh , and that loss or antagonism of BMP4 leads to mesenchymal differentiation defects [8 , 9 , 45 , 46] . However , it was unclear whether all aspects of HH signaling are mediated by BMP4 and how Bmp4 expression is regulated . Our work suggests that FOXF1 is the crucial mesenchymal effector of HH signaling that exerts its function in proliferation and differentiation of the mesenchyme and epithelium through and in concert with BMP4 . Our microarray analysis identified the three Forkhead transcription factor genes Foxf1 , Foxl1 and Foxf2 to strongly depend in their expression in the ureter on HH signaling . In situ hybridization analysis detected expression of Foxf1 but not of Foxl1 and Foxf2 in the ureteric mesenchyme suggesting that the latter two factors play a minor role in ureter development . Intriguingly , Foxf1 expression was upregulated at E14 . 5 in the inner layer of mesenchymal cells , i . e . shortly before the onset of SMC and epithelial differentiation . This contrasts with the activity of HH signaling which is present from at least E11 . 5 onwards in the inner and outer layers of the ureteric mesenchyme [8] . Together with the observation that ectopic HH signaling ( i . e . activated SMO ) is not sufficient to induce SMC differentiation and Foxf1 in the outer mesenchymal region , this argues that Foxf1 expression requires a critical second input , possibly WNTs as discussed above , from the epithelial compartment around E13 . 5 . Alternatively or in parallel , a mesenchymal activity may counteract HH activation of Foxf1 expression until that stage . We used conditional misexpression of a variant of FOXF1 encoding a strong transcriptional repressor to address the function of this transcription factor in the ureteric mesenchyme . Such an approach is not without risk since it may interfere with activity of other family members in early ureter development . However , of the more than 40 members of the Fox family of transcription factors , expression of only a few have been identified in ureter development including Foxd1 in tunica adventitia cells , Foxc1 and Foxc2 in the early ureteric mesenchyme , and Foxa1 in the ureteric epithelium [4 , 47 , 48] . Importantly , FOXF1 and FOXF2 represent an evolutionary conserved but isolated subgroup of FOX proteins , and FOX transcription factors show a high divergence of binding sites [49 , 50] arguing that FOXF1-DN only interferes with FOXF1 and FOXF2 function . Importantly , the defects we see do not phenocopy loss of any known Forkhead gene in the ureter but recapitulate the proliferation and differentiation defects of Smo loss-of-function mutants in the inner mesenchymal domain and the epithelium of the developing ureter . Moreover , mesenchymal expression of FOXF1 partially ameliorated tissue hypoplasia and completely rescued the mesenchymal and epithelial differentiation defects in cyclopamine treated ureters arguing together that FOXF1 is the crucial and unique mesenchymal mediator of inputs from SHH and other epithelial signals in the control of these cellular programs . While it is conceivable that FOXF1 directly activates the SMC program in the ureteric mesenchyme , its epithelial functions must be mediated by a diffusible factor . Our molecular analyses have shown that expression of Bmp4 in the ureteric mesenchyme strictly depends on HH signaling and FOXF1 activity in this tissue . BMP4 was sufficient to rescue the proliferation defects in both tissue compartments as well as to induce epithelial differentiation in ureter explant cultures in which HH signaling or FOXF1 function was abrogated . BMP4 did not rescue SMC differentiation in these settings arguing that FOXF1 acts upstream of and in concert with BMP4 in this program . While this study was in progress , we showed that loss of Bmp4 in the ureteric mesenchyme resulted in a complete loss of epithelial and mesenchymal proliferation and differentiation further supporting the notion that BMP4 mediates HH signaling and FOXF1 activity in the ureteric mesenchyme [51] . It is important to note that SHH , FOXF1 and BMP4 constitute a regulatory axis that has been adopted in other developmental contexts , including the morphogenesis of the developing gastrointestinal tract [30 , 31] , the establishment of left/right asymmetry in the lateral plate mesoderm [52] and vasculogenesis of the yolk sac [53] . While the presence of GLI1 binding sites in the regulatory regions of Foxf1 ( and Foxl1 ) characterized this gene as a direct target of HH signaling [31 , 54 , 55] , it remains to be seen whether Bmp4 is directly controlled by FOXF1 transcriptional activity in the ureter or in any of these contexts . Our functional experiments provided compelling evidence that FOXF1 and BMP4 mediate the proliferation and differentiation function of HH signaling in the ureter , but it seems unlikely that these factors also account for the anti-apoptotic activity of this pathway in the outer mesenchymal domain . First , Foxf1 , Foxf2 and Foxl1 were not detectably expressed in the ureteric mesenchyme at E11 . 5 to E12 . 5 when this HH activity occurs . Second , apoptosis of outer mesenchymal cells was not detected in mutants with expression of the repressor version of FOXF1 in the ureteric mesenchyme . Third , FOXF1 was not sufficient to rescue tissue hypoplasia after abrogation of HH signaling . Fourth , loss of Bmp4 in the ureteric mesenchyme does not affect cell survival in adventitial precursor cells of the ureter [51] . Finally , BMP4 antagonism did not abolish the puromorphamine induced hyperplasia of outer mesenchymal cells in ureter explants . In other developmental contexts ( e . g . the spinal cord ) it was shown that HH signaling directly regulates the expression of the anti-apoptotic gene Bcl2 [56] . Our microarray analysis showed that Bcl2 is slightly reduced upon cyclopamine treatment of ureter explants ( S2 Table ) making it a possible contributor of the pro-survival role of HH signaling . We detected strong reduction of expression of Ddit4l whose homologue DDIT4 in at least some biological contexts was reported to exert an anti-apoptotic function [57 , 58] making it another candidate for this function . Given the requirement of the SHH-FOXF1-BMP4 regulatory axis for SMC differentiation in the ureter and the severity of the hydroureter formation associated with their complete or partial loss in the mouse , it is obvious that the components of this axis represent candidate genes for human congenital anomalies of the kidney and urinary tract ( CAKUT ) . In fact , heterozygous loss-of-function mutations in BMP4 and GLI transcription factor genes have been identified in patients with ureter anomalies , and hypo- and dysplastic kidneys [59 , 60] . Since these genes are expressed and required in numerous embryonic programs , renal defects are often associated with a whole spectrum of other organ malformations . Interestingly , heterozygous inactivation of FOXF1 has been associated with the “Alveolar Capillary Dysplasia with Misalignment of Pulmonary Veins” syndrome ( ACDMPV: OMIM 265380 ) in human newborns [61 , 62] . This syndrome is characterized by failure of formation and ingrowth of alveolar capillaries and anomalously situated pulmonary veins . Affected infants present with respiratory distress resulting from pulmonary hypertension in the early postnatal period , and the disease is fatal within the newborn period [63 , 64] . Additional defects occur in the cardiovascular , gastrointestinal , musculoskeletal systems and in the urinary tract . In the latter vesico-ureteric and pelvic-ureteric junction obstructions , hydroureter and hydronephrosis have been reported [65] , pointing to haploinsufficiency of FOXF1 for ureter development . Previous work tried to find whether mutations in FOXF1 are also associated with the VATER/VACTERL combination of congenital anomalies that includes vertebral defects , anorectal malformations , cardiac defects , tracheoesophageal fistula with or without esophageal atresia , renal malformations , and limb defects . Targeted sequencing in 123 patients with VATER/VACTERL or VATER/VACTERL-like phenotype detected a FOXF1 de novo mutation in one patient . In situ hybridization analyses in mouse embryos identified Foxf1 expression in the development of most VATER/VACTERL organ systems except the urinary tract [66] , questioning the significance of mutations in FOXF1 for renal disease manifestations [67] . With our finding that Foxf1 is expressed and functionally required in ureter development in the mouse , the gene is ( back ) on the list of candidates for forms of CAKUT with additional extra-renal disease manifestations in human newborns .
All animal experiments were performed in compliance with the German animal protection law , Tierschutzgesetz ( TierSchG , BGBl . I S . 1206 , 1313 , 2006/05/18 ) . All mice were housed and handled according to good animal practice as defined by FELASA ( Federation of European Laboratory Animal Science Associations ) and the national animal welfare body GV-SOLAS ( Gesellschaft fur Versuchstierkunde/Society for Laboratory Animal Science ) . All animal experiments were approved by the Lower Saxony Committee on the Ethics of Animal Experiments as well as the responsible state office ( Lower Saxony State Office of Consumer Protection and Food Safety ) under the permit numbers 33 . 12-42502-04-13/1356 and AZ33 . 14-42502-04-13/1264 . The Foxf1 open reading frame was PCR-amplified from cDNA with primer pairs Foxf1-for ( NheI ) ATG CAC TAG TAT GTC CGC GCC CGA CAA GC and Foxf1-rev ( NdeI ) ATG CCA TAT GTC ACA TCA CAC ACG GCT TGA TG or Foxf1ΔStop-rev ( NdeI ) ATG CCA TAT GCA TCA CAC ACG GCT TGA TG with the latter introducing a mutated stop codon . A DNA fragment encoding the engrailed repressor domain ( ENG ) was PCR-amplified from the pCS2+ . Engrailed plasmid [35] with primer pairs Eng-for ( NdeI ) GAG ACA TAT GGC CCT GGA GGA TCG C and Eng+Stop-rev ( NdeI ) GAG ACA TAT GCT AGA GGC TCG AGA GGG ATC C . Restriction sites introduced via primers were used to insert PCR products into NheI-NdeI sites of a shuttle vector containing IRES-GFP to generate FOXF1-IRES-GFP ( for HprtFoxf1 ) and FOXF1ENG-IRES-GFP ( for HprtFoxf1DN ) constructs . These constructs were then subcloned into the pMP8 . CAG-Stop vector [68] using restriction enzymes SwaI and MluI . To target the Hprt locus , linearized constructs were electroporated into E14TG2a embryonic stem cells that carry a deficient Hprt locus enabling HAT selection after correct targeting and restoration of the locus [36 , 37] . Correctly targeted ES cell clones were selected with HAT medium ( Gibco ) , expanded and genotyped by PCR . Verified ES clones were microinjected into CD1 mouse blastocysts . Chimeric males were obtained and mated to NMRI females to produce heterozygous F1 females . Smotm2Amc ( synonym: Smofl ) [14] , Gt ( ROSA ) 26Sortm1 ( Smo/EYFP ) Amc ( synonym: R26SmoM2 ) [17] , Gt ( ROSA ) 26Sortm4 ( ACTB-tdTomato-EGFP ) Luo ( synonym: R26mTmG ) [19 and Axin2tm1 ( cre/ERT2 ) Rnu ( synonym: Axin2creERT2 ) {van Amerongen , 2012 #47] mouse lines were all obtained from the Jackson Lab . The Tbx18tm4 ( cre ) Akis ( synonym: Tbx18cre ) mouse line was previously generated in the lab [69] . All lines were maintained on an NMRI outbred background . Tbx18cre/+;Smofl/fl ( synonym: SmoLOF ) embryos were obtained from matings of Tbx18cre/+;Smofl/+ males and Smofl/fl females . Tbx18cre/+;R26mTmG/SmoM2 ( synonym: SmoGOF ) and Tbx18cre/+;R26mTmG/+ embryos were derived from matings of Tbx18cre/+;R26mTmG/mTmG males and R26SmoM2/SmoM2 and NMRI females , respectively . Tbx18cre/+;HprtFoxf1DN/y ( synonym: Foxf1DN ) and Tbx18cre/+;HprtFoxf1/y embryos were obtained from matings of Tbx18cre/+ males with HprtFoxf1DN/Foxf1DN and HprtFoxf1/Foxf1 females , respectively . Axin2creERT2/+;HprtFoxf1/y embryos were obtained from matings of Axin2creERT2/+ males with HprtFoxf1/Foxf1 females , respectively . For all matings cre negative littermates were used as controls . Mouse strains , genotypes , conditions and numbers for each experiment are summarized in S1 Table . For timed pregnancies , vaginal plugs were checked in the morning after mating , and noon was defined as embryonic day ( E ) 0 . 5 . Embryos and urogenital systems were dissected in PBS . Ureters for explant cultures were dissected in L-15 Leibovitz medium ( Biochrom ) . Specimens were fixed in 4% PFA/PBS , transferred to methanol and stored at -20°C prior to immunofluorescence or in situ hybridization analyses . PCR genotyping was performed on genomic DNA prepared from yolk sac or tail biopsies . All mice were bred and maintained in the central animal facility of the Medizinische Hochschule Hannover ( Hannover , Germany ) according to institutional guidelines . All experiments were performed with approval of the authorities of the State of Lower Saxony . Embryos , urogenital systems and ureters were paraffin-embedded and sectioned to 5 μm . Hematoxylin and eosin staining was performed according to standard procedures . Non-radioactive in situ hybridization analysis of gene expression was performed on whole-mount specimens or on 10-μm paraffin sections of the proximal ureter with digoxigenin-labeled antisense riboprobes [70 , 71] . For immunofluorescence analysis on 5-μm paraffin sections polyclonal rabbit-anti-TAGLN ( 1:250 , ab14106 , Abcam ) , monoclonal mouse-anti-GFP ( 1:250 , 11814460001 , Roche ) , monoclonal mouse-anti-ACTA2 ( 1:250 , A5228 , Sigma-Aldrich ) , polyclonal rabbit-anti-ΔNP63 ( 1:250 , 619001 , Biolegend ) , polyclonal rabbit-anti-KRT5 ( 1:250 , PRB-160P , Covance ) , monoclonal mouse-anti-UPK1B ( 1:250 , WH0007348M2 , Sigma-Aldrich ) , monoclonal mouse-anti-BrdU ( 1:250 , 1170376 , Roche ) or polyclonal rabbit antisera against CDH1 ( 1:250 , gift from Rolf Kemler ) and MYH11 ( 1:250 , gift from Robert Adelstein ) were used as primary antibodies . Biotinylated goat-anti-rabbit IgG ( 1:250 , 111065033 , Dianova ) , Alexa488-conjugated goat-anti-rabbit IgG ( 1:500 , A11034 , Molecular Probes ) and Alexa555-conjugated goat-anti-mouse IgG ( 1:500 , A21422 , Molecular Probes ) were used as secondary antibodies . The signal of the ΔNP63 antibody was amplified using the Tyramide Signal Amplification ( TSA ) system ( NEL702001KT , Perkin Elmer ) . Before staining , paraffin sections were deparaffinized and cooked for 15 min in antigen unmasking solution ( H-3300 , Vector Laboratories ) . Nuclei were stained with 4' , 6-diamidino-2-phenylindole ( DAPI ) . At least three specimens of each genotype were used for each of these analyses . Cell proliferation rates were analyzed by the detection of incorporated BrdU on 5 μm paraffin sections according to published protocols [72] . A minimum of 12 sections of the proximal ureter from 3 independent specimens was analyzed per genotype . The BrdU-labeling index was defined as the number of BrdU-positive nuclei relative to the total number of nuclei as detected by DAPI counterstaining in arbitrarily defined compartments of the ureter . Data were expressed as mean ± standard deviation . The two-tailed Student’s t-test was used to test for significance . P≤0 . 05 was regarded as significant , P≤0 . 005 as highly significant and P≤0 . 001 as extremely significant . Apoptosis was analyzed on 5 μm paraffin sections using the ApopTag Plus Fluorescein In Situ Apoptosis Detection Kit ( Chemicon ) . Alternatively , LysoTracker Red DND-99 ( Thermo Scientific ) was used to detect cell death in organ cultures . Briefly , E11 . 5 kidney rudiments were cultured for 1 d and incubated for 1 h with 2 . 5 μM LysoTracker prior to documentation . Kidney rudiments or ureters were dissected from the embryo , explanted on 0 . 4 μm polyester membrane Transwell supports ( Corning ) and cultured at the air-medium interface with DMEM/F12 ( Gibco ) supplemented with 10% FCS ( Biochrom ) , and 1% of concentrated stocks of Penicillin/Streptomycin , Pyruvate and Glutamax ( Gibco ) . For pharmacological manipulation of SHH signaling cyclopamine ( Selleckchem ) and purmorphamine ( Millipore ) were used at a final concentration of 10 μM and 2 μM , respectively . Recombinant mouse BMP4 ( R&D Systems ) was used at a final concentration of 100 ng/ml . BMP4 inhibitor NOGGIN ( ABIN2018288 , antikoerper-online . de ) was dissolved in water to 10 μg/ml . To induce recombination with the Axin2creERT2 line 4-Hydroxytamoxifen ( H7904 , Sigma-Aldrich ) was added to the medium at a final concentration of 500 nM for the first 24 h of culture . Culture medium was replaced every day . Contralateral kidneys/ureters were used in control groups . Two independent pools of 50 E12 . 5 left and right ureters were cultured with DMSO or 10 μM cyclopamine for 18 h . Total RNA was extracted with peqGOLD RNApure ( PeqLab ) and was sent to the Research Core Unit Transcriptomics of Hannover Medical School where RNA was Cy3-labeled and hybridized to Agilent Whole Mouse Genome Oligo v2 ( 4x44K ) Microarrays . To identify differentially expressed genes , normalized expression data was filtered using Excel based on an intensity threshold of 150 and a more than 2 fold change in both pools . Sections and organ cultures were photographed using a Leica DM5000 microscope with Leica DFC300FX digital camera or a Leica DM6000 microscope with Leica DFC350FX digital camera . Urogenital systems were documented using a Leica M420 microscope with a Fujix HC-300Z digital camera . Figures were prepared with Adobe Photoshop CS4 .
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The mammalian ureter is a simple tube with a specialized multi-layered epithelium , the urothelium , and a surrounding coat of fibroblasts and peristaltically active smooth muscle cells . Besides its important function in urinary drainage , the ureter represents a simple model system to study epithelial and mesenchymal tissue interactions in organ development . The differentiated cell types of the ureter coordinately arise from precursor cells of the distal ureteric bud and its surrounding mesenchyme . How their survival , growth and differentiation is regulated and coordinated within and between the epithelial and mesenchymal tissue compartments is largely unknown . Previous work identified Sonic hedgehog ( SHH ) as a crucial epithelial signal for growth and differentiation of the ureteric mesenchyme , but the entirety of the cellular functions and the molecular mediators of its mesenchymal signaling pathway have remained obscure . Here we showed that epithelial SHH acts in a paracrine fashion onto the ureteric mesenchyme to activate a FOXF1-BMP4 regulatory module that directs growth and differentiation of both ureteric tissue compartments . HH signaling additionally acts in outer mesenchymal cells as a survival factor . Thus , SHH is an epithelial signal that coordinates various cellular programs in early ureter development .
|
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"Results",
"Discussion",
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"and",
"methods"
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"molecular",
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2017
|
A SHH-FOXF1-BMP4 signaling axis regulating growth and differentiation of epithelial and mesenchymal tissues in ureter development
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Disruption of gene regulation by sequence variation in non-coding regions of the genome is now recognised as a significant cause of human disease and disease susceptibility . Sequence variants in cis-regulatory elements ( CREs ) , the primary determinants of spatio-temporal gene regulation , can alter transcription factor binding sites . While technological advances have led to easy identification of disease-associated CRE variants , robust methods for discerning functional CRE variants from background variation are lacking . Here we describe an efficient dual-colour reporter transgenesis approach in zebrafish , simultaneously allowing detailed in vivo comparison of spatio-temporal differences in regulatory activity between putative CRE variants and assessment of altered transcription factor binding potential of the variant . We validate the method on known disease-associated elements regulating SHH , PAX6 and IRF6 and subsequently characterise novel , ultra-long-range SOX9 enhancers implicated in the craniofacial abnormality Pierre Robin Sequence . The method provides a highly cost-effective , fast and robust approach for simultaneously unravelling in a single assay whether , where and when in embryonic development a disease-associated CRE-variant is affecting its regulatory function .
Cis-regulatory elements ( CREs ) such as enhancers are vital functional regions of the genome which determine where , when and at what levels their target genes will be expressed [1] . In keeping with their crucial role in the control of gene expression , CRE aberrations have been implicated as the cause of a variety of human diseases , genetic trait differences and predisposition to common diseases [2–3] . Modern approaches , such as next generation sequencing , now allow rapid determination of genetic variation between individuals to single nucleotide resolution . In contrast to the advancement offered by these high throughput methods for identification of sequence polymorphisms , progress towards an understanding of their precise role in disease etiology is hampered by a shortage of efficient methods for the functional characterization of observed variants . Identifying exactly which of the non-coding SNPs in a haplotype block have a regulatory function , and in what physiological context , has been complicated by some of the characteristic features of CREs: They can be located at very large distances ( in some cases over a mega base ) from their target genes; they can reside in gene deserts , or within the introns of- or even beyond- neighboring genes , making the prediction of their target genes difficult . Unlike coding mutations , the effect of non-coding sequence variation is difficult to predict . Moreover , CRE activities are often tissue- and stage-specific and highly dependent on the precise combination and stoichiometry of tissue-specific transcription factors [4] . The in vivo relevance , at the level of the whole organism , of approaches that utilize conventional assays in cell lines to test the effect of a disease-associated CRE variant is therefore highly questionable . The lack of efficient high-throughput and physiologically relevant assays for functional validation of tissue- and developmental-stage-specific CREs and identification of their target genes thus poses a real bottleneck in translating human non-coding variation into better understanding of disease mechanisms . In our search for an efficient approach for characterizing regulatory variation in a vertebrate model system , we developed a versatile , streamlined assay pipeline using zebrafish ( Danio rerio ) . Zebrafish embryos are transparent and develop rapidly and outside the mother , making it feasible to visualize specific tagged cell types in the living animal . They are well suited for transgenic manipulation since it is relatively easy to collect and inject large numbers of fertilized eggs [5] . These features make transgenic zebrafish a useful model for the characterisation of putative tissue-specific CREs in particular over the time-course of vertebrate development but also in adult tissues [6] . The use of multiple fluorescent reporters enables direct comparison between different cis-elements or different variants of the same element in the same cells of the same animal . To determine the performance of the system , we tested a set of known disease-associated CREs in dual colour zebrafish reporter transgenics and demonstrate that the method is effective in revealing differences in functional output between variants in agreement with previously reported in mouse studies of these elements . We then applied the method to investigate a set of novel putative CREs with potential disease-associated variants in the genomic region of the SOX9 gene . These variant elements , located at very long distances from SOX9 , in the large gene desert between SOX9 and KCNJ2 , were identified based on their potential involvement in the congenital craniofacial malformation Pierre Robin Sequence ( PRS ) [7] . Consistent with their possible role in PRS aetiology , we show that these elements drive specific expression patterns in the craniofacial region of zebrafish and we reveal that the variant enhancer alleles found in the PRS patients have a variety of functional effects including: complete loss of activity; partial , tissue-specific loss of enhancer activity; and failure to maintain enhancer activity through development .
Connecting a sequence variant in a non-coding genomic region to disease aetiology in the patient in whom the variant was detected , is currently a major bottleneck in human genetics . To efficiently assess genomic regions harbouring putative disease associated sequence variants , we designed a versatile , robust and cost-effective assay pipeline which combines Gateway cloning technology and Tol2-mediated transgenesis to rapidly generate multiple dual-fluorescence reporter-transgenic zebrafish lines . The assay enables direct in vivo comparisons of the spatial and temporal activities of wild-type ( Wt ) and putative SNP or mutation ( Mut ) bearing CREs within the same animal by confocal imaging ( Fig 1 ) . The first step involves cloning of the genomic fragment ( s ) containing the putative cis-regulatory element using fast and highly-efficient Gateway cloning technology ( Fig 1A and 1B ) . In cases where the disease involved is due to haplo-insufficiency of target gene expression , we were able to clone both wild-type and mutant fragments by PCR from heterozygous patient DNA . For fragments associated with quantitative traits , the phenotypic extremes of the trait will mostly segregate with homozygosity of the variant sequence . Nevertheless one can clone both variant fragments from an intermediate heterozygous individual or use a mix of the DNA of two homozygous extremes for single-step PCR cloning . Where patient DNA is not available the variant can be made via site-directed mutagenesis . The fragments of interest are inserted into an appropriate Gateway entry vector by inclusion of attB recombination sequences into the PCR cloning primers ( Fig 1A and 1B ) . Sequencing is used to confirm the presence of each allele of the element of interest in the resulting clones and to exclude the presence of additional confounding mutations introduced during cloning . Both versions of the CRE are then recombined with different flavours of fluorescent reporter cassettes by a multi-gateway reaction into a destination vector containing Tol2 transposon sites for efficient zebrafish transgenic production ( Fig 1B ) [8] . The use of Gateway cloning vectors allows high-efficiency , rapid construction of enhancer-reporter constructs . This feature is especially advantageous for scaled-up testing of the functional relevance of a large number of putative CRE-variants identified in disease-association studies . Reporter cassettes encoding eGFP or mCherry driven from a gata2 minimal promoter were generally used , but can easily be exchanged for other promoter-reporter combinations . To exclude bias in detection levels between the eGFP and mCherry fluorophores we have conducted reporter cassette swaps for some of the elements , and found highly similar outcomes in all cases . Both Tol2 constructs ( bearing the Wt and Mut versions of the CRE ) were co-injected with Tol2 mRNA into 1–2 cell stage zebrafish embryos ( Fig 1C ) . Since many of the injected embryos ( F0 ) show a variable extent of patchiness within their ( mostly tissue-specific ) expression patterns due to cellular mosaicism , the F0 founders are routinely grown to adulthood to generate stable lines . In our hands approximately 20 percent of injected embryos produce stable , dual reporter-expressing founder lines , thus yielding 7–10 independent founder lines in a single round of injection ( of ~50 oocytes ) . The F0’s ( we usually proceed with 3 to 5 independent F0’s per CRE ) are then screened for reporter gene expression driven by the Wt and Mut versions of the CRE by out-crossing with non-transgenic fish of a standard laboratory strain . Tissue-specific CRE activities of the Wt and Mut alleles are scored in F1 embryos obtained from at least 3–5 independent F0 lines to eliminate any bias arising from the influence of site of integration of the transgene on the CRE activity . Tissues where CRE ( Wt or Mut ) -driven reporter gene expression is consistently observed in the progeny of >75% of independent F0 lines are scored as constituent parts of the activity domain of the CRE being analysed ( S1 Table and S1 Fig ) . The expression pattern driven by the Wt and Mut versions of the CRE are visualised by confocal laser-scanning microscopy and compared unambiguously in the same animal through the entire time course of development of the F1 embryos ( 1–5dpf ) . Tissues and cell-types where the activities of the WT and Mut CREs completely overlap are observed as yellow in the merge channel , while the differences in CRE activities are revealed as green or red fluorescence . The assay thus provides complete and detailed spatial and temporal information about functional activity of the CRE and simultaneously reveals where and when in embryonic development this activity is affected by the presence of the disease-associated mutation . The combination of rapid cloning , high-efficiency , cost-effective transgenesis and dual-colour imaging makes the assay a very effective approach for rapid in vivo functional assessment of disease-implicated CRE-variants . Furthermore , in the case of novel CREs for which the target gene has not yet been established , comparisons can be made with the expression patterns of the zebrafish orthologs of potential candidates genes using RNA in situ hybridisation . It should however be kept in mind that subtle differences may exist between the expression of the zebrafish ortholog ( s ) and the human ( or other species ) gene the CRE is thought to regulate . The most common established mechanism by which disease-associated sequence changes affect CRE function is by alteration or disruption of binding sites for tissue-specific transcription factors . The final part of our assay pipeline contains a convenient method for testing the validity of predicted disruptions of Transcription Factor Binding Sites ( TFBS ) by the disease-associated point-mutations ( Fig 1D ) . F1 fish of selected reporter lines are bred to obtain dual-transgenic F2 embryos which are injected with morpholinos against the transcription factor whose binding is predicted to be affected by the mutation . The injected embryos are subsequently analysed for the effects of knock-down of the transcription factor on the expression pattern driven by the WT version of the CRE . The presence of the Mut CRE driving a different fluorophore within the same embryo allows unambiguous comparison of the effects produced by the transcription factor knock-down on the WT allele activity versus the effect of the altered binding site of the transcription factor as seen by the Mut-allele activity . To test the robustness of our dual-fluorescence reporter transgenic assays we selected four disease-associated CREs from the literature for which point-mutations had been firmly established as the cause of human monogenic disease ( Table 1 ) . The SBE2 element is a CRE that controls SHH ( sonic hedgehog ) expression in the developing forebrain ( Fig 2A ) . A point mutation ( C>T ) in SBE2 was reported in a patient with holoprosencephaly , and in mouse transgenic experiments the mutation was shown to abrogate the activity of SBE2 in the rostral hypothalamus [9] . We tested the human Wt ( C ) and Mut ( T ) SBE2 alleles in our dual-colour zebrafish assay . Despite the low level of sequence conservation of human SBE2 in the zebrafish genome ( Fig 2A ) , we observed activity of the Wt human SBE2 element in the developing rostral and caudal hypothalamus of transgenic fish . Simultaneous analysis of the holoprosencephaly-associated Mut allele in the same embryos unambiguously demonstrated the partial loss of activity in the rostral hypothalamus ( Fig 2B ) . Dye-swap experiments between the Wt ( C ) and Mut ( T ) SBE2 alleles consistently showed loss of expression in rostral hypothalamus from the Mut ( T ) allele irrespective of the linked reporter fluorophore used , excluding any bias in detection levels between the GFP and mCherry fluorophores ( Fig 2B ) . The Wt ( C ) allele also showed reporter signal in the rostral forebrain at 96hpf , which was lost when the Mut ( T ) allele was used ( Fig 2B ) . This observation contrasts with the study of the mouse SBE2 element [9] , where no activity of the enhancer was observed outside the hypothalamus . Some species-specific differences in CRE activity can thus be observed while employing these CRE-reporter assays . The reporter gene expression pattern driven by the Wt ( C ) SBE2 allele in the rostral and caudal hypothalamus significantly overlapped with the endogenous expression pattern of its target gene shha in the developing zebrafish embryo ( Fig 2C ) . The C>T change in the SBE2 CRE had been demonstrated to occur in a SIX3 TFBS and disrupts SIX3 binding [9–10] . We knocked down Six3 by injecting morpholinos against Six3a and Six3b [11] into F2 transgenic embryos and the extent of Six3 depletion was assessed by immunoblot ( S2 Fig ) . We observed that reporter expression driven by the Shh-SBE2 CRE Wt ( C ) allele shrunk to a more restricted domain in the caudal hypothalamus to match with the expression driven by the Mut ( T ) allele ( Fig 2D ) . The expression domain driven by the Mut ( T ) allele , bearing a disrupted Six3 binding site , was not altered upon Six3 knockdown . Expression driven by both the alleles was unaffected upon injections of control morpholinos ( Fig 2D ) . Our assay therefore demonstrates or confirms that the C>T mutation compromised Shh-SBE2 function by abrogating Six3 binding . SHH encodes a powerful morphogen whose expression at different times and places during development is controlled by multiple CREs distributed over a 1Mb regulatory domain . The most distant of these—the ZRS ( ZPA regulatory sequence ) —controls expression that is restricted to the posterior mesenchyme of the distal limb bud ( Fig 3A ) . A number of different point-mutations in the ZRS have been reported in patients with pre-axial polydactyly [12] . Among these , the Cuban mutation , a G>A change , has been shown to cause strong ectopic reporter expression in the anterior part of the limb-bud in transgenic mice [13] . Therefore this mutation appears to represent a gain of function in a CRE , rather than a loss of function as demonstrated for the SBE2 . To test whether our assay can detect this altered ZRS function , we assayed the activity of the Wt ( G ) and Mut ( A ) human ZRS alleles . The Wt ( G ) allele drove expression of both eGFP and mCherry reporters in the zone of polarising activity ( ZPA ) of the developing pectoral fins ( S3 Fig ) , at the same site where zebrafish both shha and shhb expression is normally seen ( Fig 3Ac ) . This is consistent with the expression pattern driven by this CRE in mouse experiments [13] . We observed a mutation-driven expansion of reporter expression at 72 hpf , comparable to the changes reported in the mouse forelimb bud . By 96 hpf the additional domain of mutant ZRS-eGFP expression has become stronger and more obvious , strongly lighting up the anterior edge of the growing pectoral fin ( Fig 3Ab ) . Thus our assay is able to detect a gain of function in CRE activity . We next analysed a CRE from another developmental gene locus . The SIMO element regulates the expression of PAX6 in the eye , and we have previously demonstrated that a point mutation in this CRE can cause the congenital eye malformation aniridia by disrupting an autoregulatory PAX6 binding site in the element [14] . Using dye-swap experiments we demonstrated that , in contrast to the Wt ( G ) element , and irrespective of the fluorophore used , the Mut ( T ) allele consistently fails to drive reporter gene expression in the developing lens ( Fig 3Bb ) . This observation was in complete agreement with the results obtained when the Wt and Mut elements were tested using mouse transgenic experiments [14] . The reporter gene expression driven by the Wt ( G ) allele also overlapped with the expression pattern of the zebrafish homolog of its target gene ( pax6a ) ( Fig 3Bc ) . The final known disease-associated non-coding variant we studied was a well-established polymorphic change associated with cleft lip , in an upstream regulatory element controlling the expression of Interferon Regulatory Factor 6 ( IRF6 ) [15] . The minor allele mutant site ( designated as SNP rs642961 ) has been shown to disrupt a TFAP2A binding site , but no comparative analysis had been carried out previously to show how the wild-type and variant enhancer functions differ [15] . The Wt ( G ) allele of this element drives expression in the first pharyngeal arch and in the ethmoid plate of transgenic fish , both sites where IRF6 is thought to play a key role during oral and palate development [16] . We found that expression driven by the Mut ( A ) transgene was maintained in the pharyngeal arch , but expression in the ethmoid plate was abolished ( Fig 4B ) . Endogenous expression of zebrafish irf6 was also detected in both the first pharyngeal arc and the ethmoid plate ( Fig 4C ) . Our assay is thus able to demonstrate unambiguously the in vivo effect of a common disease-associated variant on enhancer activity . Having tested our assay system with a spectrum of previously described CREs implicated in disease , we embarked on the assessment of a set of novel predicted regulatory elements from the 1 . 5 Mb “gene desert” upstream of SOX9 , in the interval between SOX9 and KCNJ2 ( Fig 5A ) . Overlapping deletions associated with isolated Pierre Robin Sequence ( PRS ) were identified in the region 1 . 2–1 . 5 Mb upstream of SOX9 , highlighting a sub-region particularly associated with PRS within the larger intergenic domain [7] . PRS is a craniofacial disorder characterized by micrognathia ( mandibular hypoplasia ) , glossoptosis , and incomplete midline fusion of the palatal shelves typically leading to a U-shaped cleft palate . These features are thought to result as a causally linked sequence of developmental malformations arising from a primary deficiency in mandibular growth in early facial development . PRS often occurs as a component of Campomelic Dysplasia ( CD;MIM114290 ) , a syndrome affecting multiple tissues including cartilage , testes , notochord , neural crest , inner ear and the central nervous system . CD is caused by heterozygous loss-of-function coding mutations in the SOX9 gene . In addition , a further group of CD cases result from disruption of regulatory control of SOX9 . PRS can be considered an endo-phenotype of CD , caused by tissue-specific loss of full gene activity [17] . Detailed genetic analysis of a small set of PRS patients had identified a locus for isolated PRS at ~1 . 2–1 . 5 Mb upstream of SOX9 [18] , which has been refined using further patient studies [7] . Putative craniofacial regulatory elements potentially relevant to PRS etiology were identified in this region through a combination of sequence conservation ( at least 70% identity over 300 bp between human , opossum and chick—the hoc elements ) , and by p300 ChIP profiling in mouse craniofacial tissue [7 , 19] . Sanger sequencing of eleven of the identified elements ( Table 2 ) in a cohort of 69 individuals , mostly with isolated PRS , identified potentially causative private variants , not present in dbSNP137 , in six of the elements studied . The genomic positions of the variant nucleotides in these elements , each showing considerable to high evolutionary conservation ( as indicated by their GERP scores ) ( except for PRS135 ) , and potential TF binding sites affected , are displayed in S2 Table . None of the identified variants could be shown to have arisen de novo in the patients; in two cases no parents were available for testing . The family pedigrees of the patients are shown in S4 Fig , with the sequenced individual arrowed and other identified carriers of the mutant allele noted . Incomplete penetrance and variable expressivity was observed in all the families studied . We analysed five of the newly identified putative PRS associated CREs ( Table 2 ) using our zebrafish assay , to establish potential enhancer function in plausible disease-related tissues that would be affected by the private SNVs in the PRS families ( Figs 5 and 6 ) . Remarkably , each of the tested CREs drives expression in specific craniofacial structures during development ( Table 2 and S1 Table ) . Each element drives a distinct pattern , significantly overlapping with the overall expression pattern of sox9 in zebrafish embryonic development ( Figs 5D , 6D and 6E ) , and also with clear overlap between some of the elements . We found that the PRS associated variants affect expression patterns in a variety of ways . Element p300-PK19 drives expression in the pharyngeal arches , midbrain , otic vesicle and ciliary margin zone of the eye . We observed the distinct tissue-specific loss of enhancer activity in pharyngeal arches 1–5 and in the midbrain of the Mut ( A ) allele of this element at 48 hpf ( Fig 5B ) . However , expression was unaffected in the otic vesicle and the ciliary margin zone . Hoc-CNE-A drives extensive expression at major sites involved in the developing craniofacial apparatus of zebrafish embryos . At two different stages of development ( 72hpf and 96hpf ) , the Wt ( C ) allele shows expression in the palatoquadrate , ceratohyals , hyposymplectic , ceratobranchials and olfactory placodes . The Mut ( T ) allele however failed to drive expression in almost all the craniofacial tissues , partly retaining expression only in the palatoquadrate and olfactory placodes ( Fig 5C ) . We also observed temporal ( and spatial ) changes in tissue-specific CRE activity due to the presence of PRS-associated variants in another of the CREs ( Fig 6A ) . P300-PK17 showed reporter expression in the first pharyngeal arch at 48 and 72 hpf . Expression driven by the mutant allele was present in the first pharyngeal arch at 48 hpf , but almost completely lost by 72 hpf . At 96 hpf reporter signal is seen in Meckel’s cartilage and the palatoquadrate in the wild-type but these sites are lost in the mutant ( Fig 6A ) . The final two CREs also revealed distinct craniofacial expression patterns in reporter transgenic embryos . However , for these elements we observed no differences in CRE activities between the wild-type and variant alleles ( Fig 6B and 6C ) . Hoc-CNE-D was shown to drive expression in the ceratobranchials at two different stages of embryonic development ( 72 and 96 hpf ) and showed additional sites of expression in the olfactory placodes and brain ( Fig 6B ) . These sites of expression were also seen with the variant allele . The p300-PK22 construct showed expression at the base of the oral cavity with both the wild-type and the variant construct ( Fig 6C ) . Thus our assay revealed craniofacial expression patterns for all five predicted CREs from the defined PRS region far upstream of SOX9 , and altered spatiotemporal expression for three of these elements when carrying a sequence variant seen in patients with Pierre Robin Sequence .
The importance of intact gene regulation for correct development and homeostasis has become increasingly recognised . As a result , research groups interested in understanding the aetiology and causative mechanisms of human disorders or disease susceptibility are now routinely looking for possible mutations or variations in CREs in patient cohorts , especially in cases where convincing causative mutations could not be found in the coding regions of genes . However , the lack of efficient and physiologically relevant assays to functionally validate the consequence of these sequence changes and to distinguish disease-linked changes from background sequence variation is hampering the translation of knowledge about human genetic variation into an understanding of disease mechanisms . CRE activity is highly dependent on the availability of the right combination and stoichiometry of specific transcription factors . Consequently , high-throughput assays for assessing the potential effects of disease-associated SNPs in cultured cells are largely uninformative as they often lack the relevant and necessary biological context for tissue or cell-type specific CRE function . In future , cell lines reflecting more closely the cell phenotypes of developing tissues may become available through emerging stem cell differentiation protocols [20] . A few high-throughput in vivo assays , such as hydrodynamic tail-vein injection and retina explant assays [21–23] have also recently been developed but their application is restricted to CREs functional only in liver or retina respectively . Therefore there is a pressing need for robust , widely applicable , relatively high-throughput , cost effective and animal-number efficient in vivo assays that enable the unambiguous comparison of putative mutant and wild-type alleles of CREs for spatial and temporal differences in activity . Such screens are vital for differentiating between common , background sequence variation and functionally active , disease-associated mutations in CREs , and will enable rapid prioritization of candidates for functional follow-up studies . The novel dual-colour zebrafish reporter transgenic assay pipeline that we have developed for investigating the functional consequences of disease- and disease-risk associated CRE mutations is designed to incorporate many of the above described merits , and thus will be a valuable tool for analysing effects of CRE mutations identified in patient cohorts and GWAS studies . While we cannot control for the number and position of transgene insertion sites in our assay , multiple independent transgenic lines bearing both the Wt and Mut version of the element driving distinct fluorescent reporters in the same animal can rapidly be constructed and tested , creating a clear consensus activity pattern and minimising the chance of bias in the analysis introduced by position effects due to site of integration of the transgenes . Other methods aimed towards targeted integration of transgenes in pre-defined docking sites in the zebrafish [24–27] or medaka [28] genomes are being developed , but the use of these techniques is more cumbersome and requires the maintenance of specialized fish stocks . Moreover , while targeted integration offers the advantage of avoiding bias from position effects , the use of dual-colour transgenesis is currently not established in these assays , complicating the possibility of simultaneous visualisation of CRE activity in the same animal , and precluding truly detailed assessment of differences in CRE activity . A comprehensive comparison of the merits and limitations of our assay with other available reporter transgenic assays for testing enhancer function is provided in S3 Table . We anticipate that it will become possible to combine advantages of the different methods in future assay designs . Characterisation of detailed expression patterns driven by particular elements allows selection of the most likely candidate sequences by virtue of their expression in the relevant anatomical structures . In combination with information on the expression patterns of the genes located within the relevant genomic region this can also help to find the likely target gene of an enhancer . This can otherwise be problematic as target genes of enhancers are often not simply the nearest one in the genome , but can be found hundreds or even thousands of kb away in either direction , beyond intervening non-target genes , and may reside within the introns of other non-target genes [29 , 30] . Most importantly our method enables the characterisation of wild-type and mutant variants of the same enhancer in the same individual animal . This is an important benefit for assessment of more subtle spatio-temporal differences as it allows a direct comparison without the need for extrapolation between separate individuals . Disruption of cis-regulatory control of gene expression can occur via a number of distinct mechanisms [31] . These range from gross changes such as CRE deletion or translocations that separate the target gene from the influence of the CRE , to single nucleotide change in CREs that abrogate TF binding , or create novel binding sites . Although our method is suitable for a rapid screening of candidate regulatory sequences located in any small- to medium-sized region of interest that has been defined by deletion or translocation breakpoint mapping , the power of our analysis pipeline lies mostly in the characterisation of single nucleotide enhancer variants . We have therefore focussed on the latter mechanism , and our results indicate that it can be further subdivided based on the functional consequences of the basepair change . We observe at least four different types of effect on enhancer activity by patient mutant alleles . The first is the change in activity in the spatial dimension; this can manifest as complete loss of expression in a specific tissue ( PAX6-SIMO , SOX9-hocCNEA ) , reduction in the extent of the expression domain ( the SHH-SBE2 element ) , or an increase in expression domain ( the SHH-ZRS ) . In the case of the SBE2 enhancer it had been shown that the reduction in expression domain size is caused by disruption of a SIX3 binding site in the element [9] and we replicated this effect by morpholino knock-down of Six3 . This experiment demonstrates the modular nature of CREs: Six3 is not essential for all of the activity of SBE2 as expression in the caudal part of the hypothalamus remains , but Six3 is essential for the expression in the rostral hypothalamus . The second mechanism we identify is a partial loss of activity in the temporal dimension , as exemplified by the p300-pk17 element in patient PRS026 which loses expression in the oral cavity only at later developmental stage . This indicates that the element functions normally when it first becomes activated , but fails to maintain its activity subsequently . The third example is the complete loss of functional activity of the element in our assay . This suggests the mutation disrupts the binding of an essential factor potentially affecting the effective formation of a TF complex , or enhanceosome [32] at the enhancer . The fourth type of outcome is an apparent lack of change , whereby the tissue-specific activity of the enhancer in the appropriate tissue is unaffected by the sequence variant . The causal connection to the disease phenotype in such cases is not obvious . The mutation could affect the precise level of transcriptional output from the element , which is not readily measured in the current fluorescent reporter assay , or it could disrupt some other function of the element not assayed here , for instance in organisation of chromatin conformation of the locus [33] . Even though not guaranteed to work for all enhancers , our results show that the dual reporter transgenic zebrafish assay is a suitable model system to test enhancer activity of many human disease-associated elements even when the element is not obviously conserved in zebrafish itself . Evolution is characterised by variable loss and gain of cis-regulatory sequences [34] . Teleost fish in particular appear to have been subject to an enhanced rate of evolutionary divergence due to the additional whole genome duplication ( 3R ) that occurred at the base of the teleost lineage [35 , 36] , and consequently the zebrafish genome lacks many of the CNEs identifiable in other vertebrate species . However , it is likely that this increased divergence has occurred primarily at the level of the cis-regulatory sequences themselves , while the transcriptional machinery involved in the reading of the elements remains largely conserved due to selection against the wide-ranging effects of changes in the pleiotropic functions of transcription factors . Our results indicate that human regulatory elements implicated in disease can be tested in zebrafish with confidence . It is remarkable that single nucleotide changes at such large genomic distance from their target gene can have such profound phenotypic effects . Most of the currently known examples of distal cis-elements involved in genetic disease act as enhancers for genes sensitive to haplo-insufficiency [31] . Our demonstration that single basepair mutations in multiple long-range cis-elements , with subtly different expression patterns , can lead to PRS highlights the sensitivity of craniofacial development to correct expression levels of SOX9 . The same is true for the other genes , SHH and IRF6 , for which enhancers were tested in this report . Several of the enhancer variants described here are either inherited or even occur as rare SNPs in the wider population . Nevertheless we present strong evidence that these variants affect the function of the regulatory element in which they occur . Mutations in enhancers may not always lead to clear , fully penetrant phenotypes , but rather could contribute partly to a phenotype in specific individuals , depending on the presence of other modifier alleles . Incomplete penetrance may be observed for a number of reasons including variation in expressivity from the enhancer , or redundancy or buffering among multiple enhancers . The mufti-faceted assay we have described here allows for the functional characterisation of disease-associated enhancer variants at the highest throughput that can currently be achieved using an in vivo animal model system . We anticipate that our strategy will facilitate the analysis of non-coding variants in genome-wide association study ( GWAS ) hits , and can also be used in studying the mechanistic basis for enhancer activity , the engineering of enhancers with desired properties , or to drive highly spatio-temporally specific expression of genetic tools .
All zebrafish experiments were approved by the University of Edinburgh ethical committee and performed under UK Home Office license number PIL 60/12763; PPL 60/4418 . CREs selected for analysis in transgenic reporter assays were cloned by PCR amplification of the fragment containing it plus flanking sequence from genomic DNA , using Phusion high fidelity polymerase ( NEB ) . attB4 and attB1r sequences were included in the PCR primers for use with the Gateway recombination cloning system ( Invitrogen ) . The amplified fragment was first cloned into the Gateway pP4P1r entry vector and sequenced using M13 forward and reverse primers for verification . In cases where a point mutation was engineered in the wildtype CRE , a site-directed mutagenesis kit ( QuikChange II XL Site-Directed Mutagenesis Kit , Agilent ) was used on the pP4P1r vector containing the wildtype CRE sequence . Test elements in the pP4P1r vector were combined with a pDONR221 construct containing either a gata2 promoter-eGFP-polyA or a gata2 promoter mCherry- polyA cassette , and recombined into a destination vector with a Gateway R4-R2 cassette flanked by Tol2 recombination sites [8 , 37] . The primer sequences used for amplification of the published CREs described in the manuscript are listed in S4 Table and images from independent lines for some of the constructs are presented in S1 Fig . Purification of genomic DNA from blood lymphocytes and Sanger sequencing of non-coding elements upstream of SOX9 was performed according to standard protocols , using the primers listed in S4 Table . Sequence conservation of disease associated CREs was assessed by multiple sequence alignment and visualised using the VISTA or ECR Browser with the human hg19 sequence as base genome [38 , 39] . Zebrafish were maintained in a recirculating water system according to standard protocol [40] . Embryos were obtained by breeding adult fish of standard stains ( AB and WIK ) and raised at 28 . 5°C as described [40] . Embryos were staged by hours post fertilization ( hpf ) as described [41] . Reporter plasmids were isolated using Qiagen miniprep columns and were given extra purification via a Qiagen PCR purification column ( Qiagen ) , and diluted to 50 ng/microliter with DNAse/RNAse free water . tol2 transposase RNA was synthesized from a NotI-linearized pCS2-TP plasmid [42] using the SP6 mMessage mMachine kit ( Ambion ) , and similarly diluted to 50 ng/microliter . Equal volumes of the reporter construct ( s ) and the transposase RNA were mixed immediately prior to injections . 1–2 nl of the solution was micro-injected per embryo of up to 200 embryos at the 1- to 2-cell stage . Embryos were screened for mosaic fluorescence at 1–5 days post-fertilization i . e . 24–120 hpf ( hours post fertilization ) and raised to adulthood . Germline transmission was identified by mating of sexually mature adults to wild-type fish and examining their progeny for fluorescence . F1 embryos from 3–5 F0 lines showing the best representative expression pattern for each construct were selected for confocal imaging . A few positive embryos were also raised to adulthood and F1 lines were maintained by outcrossing . A summary of the number of independent lines analyzed for each construct and their expression sites is included in S1 Table . Embryos for imaging were treated with 0 . 003% PTU ( 1-phenyl2-thio-urea ) from 24 hpf to prevent pigmentation . Embryos selected for imaging were anaesthetized with tricaine and mounted in 1% low-melting agarose . Images were taken on a Nikon A1R confocal microscope and processed using A1R analysis software . A zebrafish Six3 antisense morpholino oligonucleotide ( Six3AMO ) was obtained from Gene Tools , LLC , with the following sequence: 5’ GCTCTAAAGGAGACCTGAAAACCAT 3’ . This morpholino has sequence complementary to the highly conserved sequences around the translation initiation codon of both six3a and six3b , and hence inhibits the function of both zebrafish six3 genes [11] . As control we used the Gene ToolsLLC standard negative control morpholino: 5’ CCTCTTACCTCAGTTACAATTTATA 3’ . The morpholinos were injected into 1 to 2-cell stage of at least 100 embryos to deliver an approximate amount of 2 . 5 ng per embryo . RNA in situ hybridization on fish embryos was performed as previously described [43] . The sequences of primers used for synthesis of hybridization probes are listed in S5 Table . Nuclear extract was prepared from ~100 morpholino injected embryos at 48hpf using NE-PER Nuclear and Cytoplasmic Extraction Reagents ( Thermo Scientific , catalogue number 78833 ) . The extracts were boiled with 30 μL of loading buffer ( 12 . 5mM Tris at pH 6 . 8 , 2% SDS , 20% glycerol , 0 . 002% bromphenol blue , 10% 2-mercaptoethanol ) for 5min and were resolved by 10% SDS-PAGE , transferred to nitrocellulose , incubated with antibody ( anti-Six3 antibody ab139317 ) , and detected by chemiluminescence ( Thermo scientific SuperSignal West Femto Maximum Sensitivity Substrate ) . The membrane was then re-probed with anti-α-tubulin antibody ( ab44928 ) as loading control .
|
Cis-regulatory elements ( CREs ) play a vital role in gene regulation by providing spatial and temporal specificity to the expression of their target genes . Understanding how these regions of the genome work is of vital importance for human health as it has been demonstrated that genetic changes in these regions can result in incorrect gene expression , leading to a variety of human diseases . Functional characterization of putative CREs and the effects of mutations on their activity is currently a major bottleneck in many studies towards understanding the causes and mechanisms of disease and disease susceptibility . We describe a robust in-vivo approach using dual-colour reporter transgenesis in zebrafish for unambiguous assessment of the effects of disease-associated CRE mutations on CRE activity during the entire time-course of embryonic development . The highly efficient , cost-effective and modular design of the assay allows rapid analysis of several CRE-variants in parallel . We illustrate the robustness of our approach using examples of CRE-variants associated with a broad spectrum of genetic diseases including brain , limb , eye and jaw disorders . In a single assay the method can address where and when in development the CRE variant affects its activity , what potential target genes are misregulated by the change and what upstream trans-acting factors are likely to mediate this effect .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Functional Assessment of Disease-Associated Regulatory Variants In Vivo Using a Versatile Dual Colour Transgenesis Strategy in Zebrafish
|
Rabies is a uniformly fatal disease , but preventable by timely and correct use of post exposure prophylaxis ( PEP ) . Unfortunately , many health care facilities in Pakistan do not carry modern life-saving vaccines and rabies immunoglobulin ( RIG ) , assuming them to be prohibitively expensive and unsafe . Consequently , Emergency Department ( ED ) health care professionals remain untrained in its application and refer patients out to other hospitals . The conventional Essen regimen requires five vials of cell culture vaccine ( CCV ) per patient , whereas Thai Red Cross intradermal ( TRC-id ) regimen requires only one vial per patient , and gives equal seroconversion as compared with Essen regimen . This study documents the cost savings in using the Thai Red Cross intradermal regimen with cell culture vaccine instead of the customary 5-dose Essen intramuscular regimen for eligible bite victims . All patients presenting to the Indus Hospital ED between July 2013 to June 2014 with animal bites received WHO recommended PEP . WHO Category 2 bites received intradermal vaccine alone , while Category 3 victims received vaccine plus wound infiltration with Equine RIG . Patients were counseled , and subsequent doses of the vaccine administered on days 3 , 7 and 28 . Throughput of cases , consumption utilization of vaccine and ERIG and the cost per patient were recorded . Government hospitals in Pakistan are generally underfinanced and cannot afford treatment of the enormous burden of dog bite victims . Hence , patients are either not treated at all , or asked to purchase their own vaccine , which most cannot afford , resulting in neglect and high incidence of rabies deaths . TRC-id regimen reduced the cost of vaccine to 1/5th of Essen regimen and is strongly recommended for institutions with large throughput . Training ED staff would save lives through a safe , effective and affordable technique .
Rabies is a grave zoonotic infection transmitted to humans or animals by the bite of a rabid animal , usually a dog . Dog rabies is almost non-existent in Europe , North America and Australia , but it mainly exists in the poorer strata of society in the developing world . Animal and human rabies is prevalent in both urban and rural areas virtually all over Pakistan . Rabies is invariably fatal , yet completely preventable if post exposure prophylaxis ( PEP ) is applied in a timely and correct manner . WHO has prepared standard recommendations for PEP , centered upon circumstances of the biting animal and wound severity . It strongly recommends immediate and thorough wound washing with soap and water , followed by vaccine and infiltration of Rabies immune globulin ( RIG ) in severe bites[1] . Unfortunately , awareness of rabies prevention in most developing countries of the world , and especially in Pakistan , is insufficient . Most victims do not report to a health center[2 , 3]; nor do they wash the bite wound with soap and water . Instead , they apply home remedies . Even in some large health care centers , the wound severity is not assessed correctly , and hence appropriate decisions about usage of vaccines and RIG are not made , which , in the worst case , causes rabies deaths[2 , 4] . Moreover , Pakistan and Myanmar are the only two countries in the world where the obsolete nerve tissue vaccine is still produced and provided to government hospitals and clinics . In one study from Pakistan , the nerve tissue vaccine was found to have zero potency[5] . Cell or tissue culture vaccines have long replaced nerve tissue vaccine in almost all countries of the world , as they are proven to be safe and effective . Several imported culture vaccines are available in Pakistan[6–9] , yet , many institutions do not practice correct PEP either because the staff are not trained , or vaccine and RIG are not provided because they are considered “unsafe” or “unaffordable . ”[10] Since 1984 two regimens for intramuscular delivery , approved by WHO , have been in practice . However , for low income persons , the cost of the 4 or 5-dose regimen could cost their full month’s salary; hence they either forego PEP or approach government-run hospitals for treatment , which also cannot bear the cost for the large number of patients seen on any given day . In 2005 , WHO Expert Consultation on Rabies approved the low dose modified Thai Red Cross intradermal ( TRC ID ) 4-dose regimen as being safe , immunogenic and economical . Several studies have demonstrated its safety and immunogenicity . TRC ID regimen elicits equivalent immune response as the 5 dose intramuscular Essen or 4-dose Zagreb regimens[11–13] . TRC ID requires 0 . 1 ml per injection , whereas IM regimen requires 0 . 5 ml or 1 . 0 ml of the same vaccine . This practice is used in most Asian countries , and because of cost reduction , it has been instrumental in expanding delivery service so that more victims now receive PEP , and in these case rabies is averted[13 , 14] . The Indus Hospital Karachi ( TIH ) is a 150-bed free tertiary care hospital in Pakistan’s largest city Karachi . The catchment area of the hospital is approximately 2 . 5 million persons primarily of low socio-economic status . The Rabies Prevention Center ( RPC ) was established in the Emergency Department ( ED ) of the hospital in 2008 . The center policy is to use the 4-dose TRC-id regimen for vaccination of all WHO category II and III wounds , whereas equine rabies immunoglobulin ( ERIG ) is injected in WHO category III wounds in addition to the intradermal vaccine according to guidelines . [1 , 15] Our primary objective is to describe the RPC’s throughput of rabies-prone bites between 2009 and 2014 as well as to demonstrate the cost effectiveness of TRC-id as compared with the Essen five-dose intramuscular regimen in a one-year period .
This is a descriptive study of all victims of rabies- prone animal bites reported to the RPC of TIH between January 2009 and December 2014 . Information on all patients who presented to the RPC with rabies prone bite was collected on a pre-coded form by the RPC coordinator . Age , gender , the time and type of incident , site and categorization of wounds on the basis of WHO classification were documented along with a profile and circumstances of the offending animal , and its behavior as reported by the victim and/or attendant . First aid and medical care provided in the RPC was documented , as well as the type and route of administration of vaccine and infiltration of RIG in category III wounds . Patients presenting with rabies were also documented . Since there is no provision in Karachi for quarantining or testing animal brain tissue for rabies in animals , all bites were assumed to be rabies prone , and all bite victims received PEP . Each patient was interviewed about circumstances of the animal bite , condition of the animal , and assessment of the number and depth of the victim’s wound . All patients received wound cleansing for at least fifteen minutes with soap and flowing water , followed by application of chlorhexidine antiseptic . All WHO category 2 wounds were treated either with WHO pre-qualified Purified Chick Embryo Cell Vaccine ( PCECV 1 . 0 ml vial ) or Purified Verocell Rabies Vaccine ( PVRV 0 . 5 ml vial ) , both of which have proven safety and immunogenicity , and are approved for intradermal injection . Since PCEC is dispensed in 1 . 0 ml , one vial was shared among five persons; whereas PVRV is dispensed in 0 . 5 ml , hence one vial was shared between 2 . 5 persons . Since a reconstituted vial , once opened , should not be stored for more than six hours , the left- over vaccine was often wasted . Human RIG is prohibitively expensive and is not used in our RPC . Equine RIG ( ERIG ) was previously known to be associated with hypersensitivity reactions , but current productions of ERIG are highly purified and virtually free of serious reactions . ERIG , calculated for 40 IU/kg body weight was infiltrated into the wound/s as much as anatomically possible , and the remaining injected into a muscle away from the vaccine site , and the patient observed for at least an hour after injection . [16] Each patient or his/her attendant was counseled about the importance of completing the vaccine series , and to return on days 3 , 7 and 28 for the remaining injections . An appointment card with the schedule was given . TIH pharmacy dispenses vaccine and ERIG to the RPC . Audit of vaccine and ERIG consumption were obtained for July 2013 through June 2014 . The total number of patients treated , and their follow through for completion of doses were recorded . For cost effectiveness , calculations , record of vaccine and ERIG consumption , and cost of these biological were obtained through pharmacy and the finance departments for the same period .
In the past six years , 9 , 507 victims of animal bite were registered at the RPC . Majority were males ( 87% ) and mean age of victims was 25 years ( ± 16 . 3 SD ) . The numbers treated at the facility increased progressively each year as TIH’s reputation for good quality and free medical care became widespread . ( Fig 1 ) Profiles of 2983 bite patients seen between July 2013- June 2014 were analyzed ( Table 1 ) ; of which 67 did not require PEP as they had no-risk bites . Nearly 97% were Category II and III bites , and required PEP . Of those requiring vaccine , 2188 ( 73% ) completed the 4-dose vaccine series . A few bite victims ( n = 117 ) were advised to skip the third dose if the animal was reliably reported to be alive and healthy . The fourth dose on day 28 was injected , converting post exposure to pre exposure prophylaxis ( PrEP ) . In case of a bite sometime in the future , only two booster doses would be required , ie one dose of vaccine intramuscularly or intradermally at one site on both days 0 and 3 . Rabies immunoglobulin is not indicated . Vaccination was not advised for 38 patients for various reasons ( dog was reliably vaccinated , or the patient visited more than 10 days after a bite and the animal was alive and healthy ) . After one or two doses , 573 patients either defaulted or were inadvertently not recorded . Additionally , patients were excluded from ERIG if they had received a vaccine within a week before presenting to our facility , since it is not recommended to administer RIG as it blunts antibody response . 1388 ( 46 . 5% ) dog bite victims presented with Category III wounds , of whom 1108 required RIG . 280 were excluded , based on our exclusion criteria , ie . the biting animal was reliably vaccinated , the victim had received vaccine more than a week before presenting to the RPC , or the animal was known to be alive 10 days or m ore after the bite . We did not encounter any serious reaction with ERIG . The cost of a 5 ml vial of ERIG containing 1000 IU is around PKR 1 , 000 ( USD 10 ) . The dose is calculated per weight of the individual . Hence , a small child required 0 . 5 to 1 vial , and an adult 2–3 vials . The number of vials of ERIG consumed for 1108 patients was 1261 vials , and cost PKR 1 , 261 , 000 ( USD 12 , 610 ) . The number of vaccine vials consumed to treat 2300 patients with TRC id regimen was 2400 . ( Five patients brought their own vials for IM injection ) . A vial of cell culture vaccine costs PKR 547 . The total cost was PKR 1 , 312 , 800 ( USD 13 , 128 ) . The sum of treating 2300 patients with proper PEP ( 2300 required vaccine alone or vaccine plus ERIG ) was PKR 2 , 573 , 800 ( USD 25 , 738 ) or PKR 1 , 200 ( USD 12 . 00 ) per patient treated . ( Table 2 ) If Essen regimen using 5 vials per patient had been used , the cost for the same number of patients treated would have been PKR 6 , 290 , 500 ( USD 62 , 905 ) ( Table 3 ) . The total amount of money saved for vaccine was PKR 4 , 977 , 700 ( USD 49 , 777 ) . Throughout the six-year period we have encountered only two cases of rabies among patients who received PEP at our hospital; both had not returned to complete the vaccine course because of long distances from the hospital .
This study should dispel misgivings among patients and health care givers that management of dog bites is problematic and fraught with danger , and that it is prohibitively expensive . We have shown that in a large Rabies Prevention Center situated in an ED , using TRC-id regimen with quality cell culture vaccine , plus ERIG in all deep wounds is manageable as well as cost effective . We strongly recommend that HCWs obtain training in WHO recommended PEP , and that only high quality and tested cell culture vaccine and ERIG be made available in all EDs . The 5-dose IM Essen regimen may be reserved for smaller settings where only an occasional patient presents . Experience and good clinical judgment are essential in preventing human rabies .
|
Rabies is a killer disease caused by the rabies virus that is present in the saliva of rabid animals , mainly the dog . Once symptoms become apparent , death is inevitable . However , rabies can be prevented if correct post exposure prophylaxis ( PEP ) is instituted as soon as possible after a dog bite and before symptoms of rabies begin . In Pakistan , government hospitals treat 50–70 new bite victims each day . Many still dispense the free but poor quality nerve tissue vaccine that is often ineffective and fraught with serious adverse reactions . Hospital administrators consider PEP too expensive to be administered free of cost . The Indus Hospital ( TIH ) , Karachi is a private teaching hospital which provides free medical care to all . From July 2013-June 2014 , 2 , 983 new bites were seen in the ED , and rather than use the Essen regimen of five full vial intramuscular doses per patient over 28 days , we administered the WHO-approved Thai Red Cross-intradermal ( TRC-id ) 4-dose regimen . The use of the TRC-id regimen resulted in 80% cost savings over the Essen regimen . In resource-poor settings , we advocate training of ED personnel in TRC-id regimen , which , ultimately , will result in less vaccine consumption , more patient compliance and complete treatment , resulting in more lives being saved .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
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2016
|
Reducing Cost of Rabies Post Exposure Prophylaxis: Experience of a Tertiary Care Hospital in Pakistan
|
Chagas disease is a chronic parasitic infection that progresses to dilated cardiomyopathy in 30% of human cases . Public health efforts target diagnosing asymptomatic cases , as therapeutic efficacy diminishes as irreversible tissue damage progresses . Physician diagnosis of Chagas disease cases in the United States is low , partially due to lack of awareness of the potential burden in the United States . The current study tested a patient cohort of 1 , 196 Starr County , Texas residents using the Hemagen Chagas ELISA Kit as a preliminary screening assay . Samples testing positive using the Hemagen test were subjected to additional confirmatory tests . Two patients ( 0 . 17% ) without previous Chagas disease diagnosis were identified; both had evidence of acquiring disease in the United States or along the Texas-Mexico border . The Texas-Mexico border is a foci of Chagas disease human cases , with a local disease burden potentially twice the national estimate of Hispanic populations . It is imperative that physicians consider persons with residential histories along the Texas-Mexico border for Chagas disease testing .
Chagas disease is caused by infection with the protozoan parasite Trypanosoma cruzi . Primarily transmitted by infected triatomine vector species in the Americas , congenital transmission , blood transfusion , organ transplantation , or ingestion of contaminated beverage/food products are also known to contribute to human disease . The estimated global disease burden is over 6 million [1] , with up to 30% of infected patients experiencing clinical symptoms as a result of infection [2 , 3] . Over the course of decades , clinical disease manifests as progressive cardiac or gastrointestinal tissue dilation . Early identification of these clinical cases is critical , as the presence of irreversible tissue damage is inversely proportional to drug efficacy [4] and survival [5] . Eleven triatomine species exist in the United States–[6] with historical reports of these species dating back to the early 1800s [7] . Sylvatic transmission cycles , with raccoons , opossums , woodrats and dogs serving as important mammalian reservoirs have been reported in seventeen southern states [8] . Despite continual documentation of T . cruzi positive triatomines and animal reservoir species in the United States [6 , 9] , autochthonous human Chagas disease cases have been rarely described . Of the six states with published evidence of autochthonous vector-borne transmission to humans ( n = 43 total cases ) ( Arizona , California , Louisiana , Mississippi , Tennessee , and Texas ) , Texas is home to a disproportionate burden of reported cases [6 , 10–14] . Specifically , the Rio Grande Valley region has been identified as a hot-spot of positive patient populations based on historical evidence demonstrating that in 1980 , 2 . 4% of residents screened positive for Chagas [15] . This Texas-Mexico border region ( Cameron , Willacy , Hidalgo , and Starr counties ) has long been theorized to be a high-risk area for vector-borne disease due to pervasive poverty , substandard housing , barriers to healthcare access , and weaknesses in the public health infrastructure [16] . Renewed efforts of Chagas disease surveillance in the state have peaked interest in understanding the contemporary disease burden in this potentially high-risk community . A recent screening of banked sera from Cameron County , Texas revealed that 0 . 36% of residents had a confirmed Chagas disease infection [12] . With each colonia having different and unique social determinants of health [17] , our current study aimed to continue surveillance in neighboring Starr County and to further understand the Chagas disease prevalence and risk factors for infection in this local population .
In February 1981 the Starr County Health Studies program was established by investigators from the University of Texas Health Science Center at Houston with the opening of a field office in Rio Grande City , Texas . Since then and continuing today , a series of studies has been conducted to understand the genetics and epidemiology of type 2 diabetes , its complications and related conditions . In total , some 10 , 000 local residents have participated in more than 28 , 000 examinations generating more than 500 , 000 banked biological samples [18] . For the purposes of our current investigation , banked sera from 1 , 196 study participants were available for testing from study of type 2 diabetes , sleep apnea , and endothelial function [19] . All samples were initially screened by ELISA using Hemagen Chagas Kit ( Hemagen Diagnostics Inc , Columbia , MD ) . Any samples positive by Hemagen Chagas Kit were further tested using Chagas STAT-PAK assay ( Chembio Diagnostic Systems Inc , Medford , NY ) and Chagas DPP assay ( Chembio Diagnostic Systems Inc , Medford , NY ) . Lastly , any sample positive by one or more of the described tests was sent to the US Centers for Disease Control ( CDC ) Parasitic Disease Branch for confirmation testing: Weiner EIA and trypomastigote excreted-secreted antigens ( TESA ) immunoblot . Confirmed positives were defined as being positive on at least one study assay and at least one CDC confirmation assay . Confirmed positives were invited to take part in a follow-up examination , comprised of a medical chart abstraction , a contemporary health survey , and electrocardiogram ( ECG ) . Protocols were approved by institutional review boards at the University of Texas Health Science Center at Houston ( HSC-SPH-02-042 ) and Baylor College of Medicine ( H-35471 ) , respectively . Follow-up evaluation of Chagas seropositive patients was performed through enrollment under Baylor College of Medicine ( BCM ) ’s protocol . All adult subjects provided informed written consent .
From 2010 to 2014 , 1 , 196 Starr County residents were enrolled in a comprehensive examination that included anthropometric evaluations , electrocardiography ( ECG ) , echocardiography ( ECHO ) , medical and medication histories , an in-home overnight sleep evaluation , end evaluation of endothelial function and aortic stiffness ( 19 ) . Fasting plasma , serum and urine specimens were obtained from all individuals while those with no previous diagnosis of diabetes having an oral glucose tolerance test and those with type 2 diabetes having a standard meal challenge . Of the 1 , 196 , 602 were classified as having type 2 diabetes . Complete details of the sampling and disease burden are in Hanis et al . ( 2016 ) [19] . Participants ( n = 1 , 196 ) previously enrolled were tested for Chagas and eight screened positive by Hemagen Chagas Kit ( Table 1 ) . Of these eight individuals , one was positive by Chagas STAT-PAK assay , two were positive by DPP , two were positive by Weiner EIA , and one was positive by TESA immunoblot . Per our diagnosis criteria , we determined that two participants ( Sample IDs #4788 and #5070 ) were Chagas positive . The follow-up risk factor analysis , clinical assessments , and locations of importance ( Fig 1 ) are listed below . Case-patient 1 was a 76-year old Hispanic female with a 43-year history of diabetes mellitus and 20-year history of hypertension . On May 11 , 2017 , she tested positive for Chagas antibodies on Hemagen Chagas Kit , DPP and CDC Weiner EIA , and negative for Chagas antibodies on STAT-PAK and CDC TESA immunoblot . Her ECG on August 23 , 2017 indicated the presence of a 1st atrioventricular block and left ventricular hypertrophy with repolarization abnormality . She reported a history of an “enlarged heart” but was unable to provide additional clinical details at the time of assessment nor did she complete an echocardiogram . While she regarded her medical management as acceptable , her clinical complaints at the time of follow-up were continued pedal edema and inability to climb two flights of stairs . She was born in Mission , Texas where she has lived her whole life with the exception of 15 years during her early adulthood when she lived in Bartow and Winter Haven , Florida . Case-patient 1 was a mother to four children , now all adults , who were unavailable or uninterested in Chagas testing . She reported no travel to Latin American countries except for infrequent shopping day trips at the border town of Reynosa , Mexico . Her risk factors for acquiring Chagas included possible congenital transmission from her mother ( born , raised , and lived in Nuevo Leon , Mexico ) and occupational exposures . As a child , she reported frequently performing migrant work in Tennessee , west Texas , California , Iowa , and Colorado . She reported staying in “shacks” while working , but had never seen triatomine insects . Based on her discordant testing results , indicating a low antibody titer , we theorize that transmission occurred earlier in her life , in either Texas or a southern state in which she previously worked . This is not surprising since both quantitative ( decrease in the number of antibody-secreting B-cells ) and qualitative ( activity of different B-cell subsets including changes to the specificity of the antibody repertoire ) changes are associated with aging [20] . More specifically , decrease in IgG titers with specificity to vaccine antigens have been described [21] . The exact timing cannot be determined based on her lack of triatomine recognition and reported lack of triatomine exposure . Case-patient 2 was a 35-year old Hispanic male with an unremarkable health history . On May 11 , 2017 , he tested positive on all three in-house tests and both of CDC’s confirmatory tests . At his follow-up appointment on August 23 , 2017 , his ECG was normal and he had no clinical complaints . He was born in Rio Grande City , Texas , where he resided for 25 years before moving to Alabama for 2 years , and then returning back to Rio Grande City , Texas . From the ages of 17–25 , he split his time between Rio Grande City , Texas and San Vicente , Nuevo Leon , Mexico ( 74 miles away ) . His mother and maternal grandmother were both from Nuevo Leon , Mexico , posing the potential for congenital transmission . His family has had ranches in Rio Grande City and San Vicente where he has worked as his primary occupation for over 20 years . His job responsibilities have included fencing , feeding animals , clearing land , and gardening . The family ranch in Mexico has had collective animal housing ( goats , chickens , cows , lambs , and goats ) , where he reported “many times” seeing triatomines in the animal bedding . He also reported seeing triatomines in Rio Grande City on the trees outside his home . He never recalled seeing triatomines inside his home at either location . Given his extensive history of working in areas endemic to triatomines , he likely acquired infection at one of the two residential locations .
Chagas disease is a significant public health threat in numerous parts of the world . It is mainly considered a tropical disease and has received limited attention in the United States . This study adds to the growing body of work establishing Chagas disease as a considerable public health concern along the Texas-Mexico border . Owing to the significant morbidity among those infected , there should be an increased awareness in endemic triatomine areas and increased testing among those with pathologies consistent with infection such as unexplained heart failure . Historical evidence of autochthonous transmission in the state dates back to 1955 and surveillance studies have continually demonstrated high disease burdens among Hispanic foreign-born populations [22] . Despite clear evidence presented here and in our earlier screen in Cameron County [12] that Chagas continues to be present , there is no unified public health set of guidelines for its screening in either the general or specialized clinic population . Consequently , Chagas disease has long been regarded as the most neglected of the neglected tropical diseases [23] , and scientific literature suggest that this ‘neglect’ extends to some regions along the Mexico-United States border [24–26] . Lack of awareness by physicians , barriers in healthcare access , a paucity of efficacious treatment options , and substandard public health resources continue to contribute to preventable morbidity and mortality due to Chagas disease nationally [27] . It is critical we clarify the disease burden and epidemiology of transmission to improve physician awareness . An important component of developing enhanced patient profiles for physician education is identifying foci of vector-borne transmission and elevated population disease burdens . Our study demonstrated that Chagas disease infections in Starr County , Texas are higher than the estimated prevalence among foreign-born Hispanic United States residents [0 . 17% ( 2/1 , 196 ) vs . 0 . 09% ( 300 , 000/323 , 000 , 000[28] ) , respectively] . Furthermore , our study is consistent with a previous study which found 0 . 36% infection prevalence from human residents sampled from 2005–2008 in neighboring Cameron County , Texas [12] . Similarly , the border state of Nuevo Leon , Mexico has a documented history of autochthonous transmission , with a recent study in 2014 identifying a 2% seroprevalence among residents [2] and a 2017 study identifying 14 . 5% of sylvatic animals seropositive [29] . An important limitation to our study is our inability to determine the precise incident of transmission . This limitation is inherent due to our serologic diagnostic method of this life-long infection; however , based on the patients’ epidemiologic risk profiles and relatively limited travel histories , the data suggest that both patients likely acquired their infections in the United States or along the Texas-Mexico border . An implication was our finding of discordant testing results , indicating a lack of specificity of commercially available diagnostic assays for diagnosing strains of T . cruzi that evolved in North America compared to South American strains . Chagas disease diagnostics have been suboptimal [30] and our study highlights that Texas-Mexico border patient populations present similar point-of-care testing challenges . Chagas disease is a neglected tropical disease in the United States . Our research adds to the growing body of evidence that this disease is likely endemic along the Texas-Mexico border with infection prevalence higher than that of the overall foreign-born Hispanic United States resident population . However , due to limitations in the sample size for this study , it is difficult to make assumptions regarding larger populations . Physicians should be aware of the potential elevated disease risk among this geographic patient population .
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Chagas disease is a parasitic infection , which in 30% of people results in chronic dilated organomegaly over the course of decades . This progressive disease typically advances subclinically until end stage heart failure is established , at which point treatment is no longer efficacious . Thus , current public health efforts target screening of high-risk populations for early disease detection and clinical management for improved health outcomes . Although historical evidence suggests the Texas-Mexico border as a region with high Chagas disease prevalence , surveillance is nonexistent . Our study indicates this region likely has an increased risk for undiagnosed morbidity . Furthermore , occupational histories were highlighted as key risk factors for both cases in this report . Physicians should consider Chagas screening in persons with residential histories along the Texas-Mexico border .
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2018
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Continuing evidence of Chagas disease along the Texas-Mexico border
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Cutaneous leishmaniasis caused by Leishmania major is an emergent , uncontrolled public health problem and there is no vaccine . A promising prophylactic approach has been immunotherapy with Toll-like receptor ( TLR ) agonists to enhance parasite-specific immune responses . We have previously reported that vaccination of C57BL/6 mice with live L . major plus the TLR9 agonist CpG DNA prevents lesion development and confers immunity to reinfection . Our current study aims to investigate whether other TLR agonists can be used in leishmanization without induction of lesion formation . We found that live L . major plus the TLR2 agonist Pam3CSK4 reduced the pathology in both genetically resistant ( C57BL/6 ) and susceptible ( BALB/c ) mouse strains . The addition of Pam3CSK4 activated dermal dendritic cells and macrophages to produce greater amounts of proinflammatory cytokines in both mouse strains . Both Th1 and Th17 responses were enhanced by leishmanization with L . major plus Pam3CSK4 in C57BL/6 mice; however , Th17 cells were unchanged in BALB/c mice . The production of IL-17 from neutrophils was enhanced in both strains infected with L . major plus Pam3CSK4 . However , the sustained influx of neutrophils in sites of infection was only observed in BALB/c mice . Our data demonstrate that the mechanism behind leishmanization with TLR agonists may be very different depending upon the immunological background of the host . This needs to be taken into account for the rational development of successful vaccines against the disease .
The prevalence of cutaneous leishmaniasis due to Leishmania major , a chronic disease leading to disfigurement and social stigmatization , is estimated to be at 2 million new cases each year [1] . Recent data , however , demonstrate that this number is greatly underestimated [2] . Current treatments are inadequate due to toxicity , resistance , and cost . A significant amount of work focused on prophylactic vaccine approaches have been tested in mice ( Mus musculus ) , a species chosen because wild rodents are natural hosts for L . major [3] . This has included the use of attenuated parasites , parasite extracts and leishmanial antigens . Although all these vaccines have yielded promising results in rodent models [4] , they have failed when tested in primates or humans [5] . Inoculation of virulent L . major , referred to as leishmanization , has been practiced in endemic areas for millennia . This practice is the only strategy that has reproducibly provided protection in humans , possibly because it mimics a natural infection , parasite persistence , and concomitant immunity . Leishmanization was widely applied , but because of exacerbated skin disease reported in rare cases [6] , this strategy was discontinued . However , the traditional practice of leishmanization has made a comeback in certain endemic regions , given that it is the only vaccine with proven efficacy in humans . Efforts to improve the safety of leishmanization have included the addition of killed parasites or immune adjuvants to reduce the size and duration of lesions [6] . Our particular approach to a safer leishmanization has been to use Toll-like receptor ( TLR ) agonists . TLRs are a family of 11 transmembrane proteins that specifically recognize different pathogens [7] . The therapeutic effects of TLR activation in immunotherapy are associated with the expression of high levels of IL-12 and IFN-γ In particular , the use of TLR agonists as immune adjuvants in leishmaniasis have yielded promising results . As examples , the TLR7 agonist Aldara™ showed anti-leishmanial activity in experimental models and in clinical studies of cutaneous leishmaniasis in combination with conventional therapy [8 , 9] . CpG DNA , a TLR9 agonist , has been extensively tested and has shown wide prophylactic and therapeutic anti-leishmanial potential [10–13] . We have previously investigated a leishmanization approach consisting of the inoculation of live parasites along with CpG DNA ( Lm/CpG ) . We showed that Lm/CpG prevents vaccinal lesions ( an undesired effect of live vaccination ) in C57BL/6 mice while achieving parasite persistence and immunity [14 , 15] . Mechanistically , we found that Lm/CpG causes activation of dermal dendritic cells ( DCs ) to produce IL-6 [15] and IL-2 [16] , activation of NK cells [16] , and induction of Th17 response [17] . Mice have remained the major model for testing the efficacy of vaccines against cutaneous disease . Resistance or susceptibility to L . major in mice is dependent on the type of CD4+ helper T cell ( Th ) subset that is induced . Healing in resistant mice ( i . e . C57BL/6 ) is associated with the development of IFN-γ-producing Th1 cells . In contrast , susceptibility ( e . g . in BALB/c mice ) is mediated by an early IL-4 production that promotes the development and expansion of Th2 cells [18] . Contrasting with these highly polarized responses in mice , human infection data show that a mixed Th1/Th2 response is more typically observed [19] . Hence , we propose that prospective prophylactic strategies must be evaluated in both Th1 and Th2 models of disease . The aim of this study was to determine whether TLR agonists other than CpG DNA could be use in leishmanization to treat cutaneous leishmaniasis . Here , we have found that in C57BL/6 mice , L . major infection upregulates the expression of TLR2 in bone marrow-derived dendritic cells . This contrasts with our data obtained using BALB/c mice , where there is no change in the expression of TLR2 in the same cell type . Furthermore , TLR2 agonist Pam3CSK4 treatment of infected cells from both strains of mouse results in an enhanced proinflammatory response . Because TLR2 agonists have been proposed as vaccine adjuvants in other models [20–22] , we investigated the use of Pam3CSK4 as an immune adjuvant in our leishmanization model . We found that leishmanization with live L . major plus Pam3CSK4 completely prevents lesion development and decreases parasite burdens in susceptible ( BALB/c ) and resistant ( C57BL/6 ) mice . In both cases , dermal dendritic cells and macrophages express greater amounts of pro-inflammatory cytokines . Both Th1 and Th17 responses were enhanced in C57BL/6 mice; conversely , Th17 response was not enhanced in BALB/c mice in the presence of Pam3CSK4 . However , neutrophil responses were enhanced and sustained in the susceptible mice .
Six-week-old C57BL/6 and BALB/c mice were purchased from Taconic and The Jackson Laboratory , respectively . All mice were maintained in the Baker Institute for Animal Health animal care facility under specific pathogen-free conditions . Animal care was in accordance with the guidelines of the Association for Assessment and Accreditation of Laboratory Animal Care , and experiments were performed with the approval of the Institutional Animal Care and Use Committee of Cornell University ( Permit number: 2008–0177 ) . L . major clone V1 ( MHOM/IL/80/Friedlin ) promastigotes were grown at 26°C in medium 199 supplemented with 20% heat-inactivated fetal calf serum ( FCS ) ( Gemini , Sacramento , CA ) , 100 U/ml penicillin , 100 μg/ml streptomycin , 2 mM L-glutamine , 40 mM HEPES , 0 . 1 mM adenine ( in 50mM HEPES ) , and 5 mg/ml hemin ( in 50% triethanolamine ) . Infective-stage promastigotes ( metacyclics ) of L . major were isolated from stationary cultures ( 4–5 days old ) by Ficoll enrichment as described before [23] . Mice were inoculated intradermally in both ears with 104 L . major promastigotes alone or mixed with 50 μg ( in serum free DMEM ) of a single TLR2 agonist , the synthetic triacylated lipopeptide Pam3CSK4 ( InvivoGen , San Diego , CA ) , using a 27G needle in a volume of 10 μl . Parasite loads in the ears were determined as described previously [24] . Briefly , the ear sheets were separated and deposited in DMEM containing Liberase CI enzyme blend ( 0 . 5 mg/ml ) for 60 min at 37°C . The sheets were then dissociated using a handheld tissue homogenizer . The homogenates were filtered using a 70-mm cell strainer ( BD Falcon , San Jose , CA ) to produce single cell suspensions and serially diluted in 96-well flat-bottom microtiter plates containing biphasic medium prepared using 50 ml Novy-MacNeal-Nicolle ( NNN ) medium containing 20% of defibrinated rabbit blood overlaid with 100 ml M199 . The number of viable parasites in each ear was estimated by limiting dilution from the highest dilution at which promastigotes could be grown out after 7 days of incubation at 26°C . Parasite numbers were also determined in the local draining lymph node ( submandibular ) . Lymph nodes were mechanically dissociated and parasite load was determined by limiting dilution as described above . Thirty ml of stationary phase cultures ( 4–6 days old ) were collected in a 50-ml tube and centrifuged at 2800 g for 15 min at 4°C . The resulting pellets were washed three times with cold 0 . 02 M PBS ( pH 7 . 2 ) subjected to three cycles of freezing and thawing , and centrifuged at 23 , 000 g for 20 min . Supernatant was collected , and protein estimation was done by BCA assay following the manufacturer’s recommendations . Protein samples were stored at −80°C until use . Single-cell suspensions from the ear dermis were obtained as described above . For the analysis of surface markers and intracellular staining for cytokines , single cell suspensions obtained from ears and draining lymph nodes ( as described above ) were stimulated overnight with 25 μg/ml soluble Leishmania antigen , 5 ng/ml IL-2 and 10 μg/ml anti-CD28 antibody , and then cultured with brefeldin A at 10 ng/ml for 6 h and then fixed in 4% paraformaldehyde [24] . Prior to staining , cells were incubated with an anti-Fcγ III/II receptor antibody and 10% normal mouse serum in PBS containing 0 . 1% BSA , 0 . 01% NaN3 . Cells were permeabilized and stained for the surface markers CD4 ( clone RM4–5 ) , CD11c ( clone N418 ) , Ly-6G ( clone 1A8 ) and F4/80 ( clone BM8 ) , for the cytokines IL-6 ( clone MP5–20F3 ) , IL-12/IL-23p40 ( clone C17 . 8 ) , IL-4 ( clone 11B11 ) , IL-10 ( clone JES5–16E3 ) , IL-17A ( clone TC11–18H10 . 1 ) and IFN-γ ( clone XMG1 . 2 ) . Incubations were carried out for 30 min on ice . For each sample , at least 50 , 000 cells were analyzed . The data were collected and analyzed using CellQuest software and a FACSCalibur flow cytometer ( Becton Dickinson , San Jose , CA ) . Bone marrow-derived dendritic cells ( BMDDCs ) and macrophages ( BMDMs ) were generated as described [25] . In brief , bone marrow cells from C57BL/6 or BALB/c mice were isolated by flushing femurs and tibias with RPMI 1640 . After treatment with ACK buffer to lyse red blood cells , bone marrow cells were cultured in complete RPMI 1640 supplemented with 20 ng/ml recombinant murine granulocyte-macrophage colony-stimulating factor ( GM-CSF ) to generate BMDDCs . Fresh cell culture medium was added on day 3 and day 6 . After 9 days , floating cells were used as immature BMDDCs . For the generation of BMDMs , bone marrow cells were cultured in complete DMEM supplemented with 20% L-929-conditioned medium , which contains granulocyte colony-stimulating factor ( G-CSF ) . Fresh cell culture medium was added on day 5 . After 7 days , BMDMs were ready to use . Infective-stage promastigotes ( metacyclics ) of L . major from Ficoll enrichment were washed three times in PBS , resuspended at 20 × 106/ml in PBS , and incubated with 5 M 5 ( 6 ) -carboxyfluorescein diacetate succinimidyl ester ( CFSE ) for 15 min at 37°C . Depending on the experiment , BMDDCs or BMDMs were infected for 18 h with unlabeled or CFSE-labeled parasites at a cell/parasite ratio of 1:5 . Cells were also treated with 0 . 5 μg/ml of the TLR2 agonist Pam3CSK4 , either at the time of infection , or at 18 h post infection . Eighteen hours post infection , supernatants were collected for cytokine analysis and cells were harvested for surface TLR2 expression analysis . To determine surface TLR2 expression , free parasites were washed away from BMDDCs culture by washing three times with cold PBS . Cells were then harvested , incubated with an anti-Fcγ III/II receptor antibody and 10% normal mouse serum in PBS , and then stained for expression of surface markers CD11c ( clone N418 ) and TLR2 ( clone 6C2 ) . Cytokine IL-12p40/p70 in the supernatants from in vitro stimulation was measured by sandwich ELISA as described previously [24] . All antibodies were purchased from BD Bioscience . Total RNA from BMDDCs uninfected or infected with L . major was extracted using TRIzol reagent . Reverse transcription of the RNA ( 1 μg ) was performed using SuperScript III First-Strand Synthesis System ( Invitrogen , Carlsbad , CA ) . Real-time PCR was performed in the Applied Biosystems 7500 real-time PCR system . The reaction was performed using the FAST SYBR Green master mix ( Applied Biosystems , Carlsbad , CA ) . Relative quantitation values were calculated using the 2-ΔΔCt method . β-actin was used as the internal control for each sample . Fold changes of TLR2 mRNA were normalized to uninfected cells . The primers used were as follows: TLR2 forward , 5’-CTCTGTCATGTGATGCTTCTG-3’; TLR2 reverse , 5’-ATGTTACCCCCAGTGTCTGG-3’; β-actin forward , 5’- GCTCCGGCATGTGCAA-3’; β-actin reverse , 5’-AGGATCTTCATGAGGTAGT-3’ . All experiments were performed two to four times with similar results . Significant differences were determined using Student t test or one-way ANOVA with Tukey’s post hoc test for multiple means . Statistical analysis was performed with GraphPad Prism 5 ( San Diego , CA ) .
Because it has been suggested that TLR2 interacts with L . major and triggers the host immune response against the parasite [26–28] , we investigated changes in TLR2 expression in L . major-infected BMDDCs . We carried out these experiments using both resistant ( C57BL/6 ) and susceptible ( BALB/c ) mouse strains . TLR2 mRNA expression was upregulated 9-fold in infected DCs derived from C57BL/6 mice ( Fig 1A ) . However , the upregulation of TLR2 was not observed in infected DCs from BALB/c mice ( Fig 1A ) . To confirm the transcriptional results , we next determined TLR2 protein expression in both infected and uninfected BMDDCs by flow cytometry . In C57BL/6 mice , TLR2 was expressed in 43% of cells from uninfected cultures . The mean intensity of fluorescence ( MFI ) for the receptor was 145 . 1 . Upon infection , the expression of TLR2 on cell surface was increased to 76%; the MFI also increased to 280 ( Fig 1B ) . To investigate whether those changes in TLR2 expression were a direct consequence of infection , we employed CFSE-labeled parasites to directly track the infected cells . A cell/parasite ratio of 1:5 resulted in the infection of more than 60% of the cells in the culture ( Fig 2A ) . In the uninfected cells , 19% of them expressed TLR2 . However , 70% of cells containing fluorescent parasites expressed TLR2 ( Fig 2B ) . As before , the MFI for TLR2 expression also increased in the infected cells ( from 158 . 4 to 213 . 7 ) ( Fig 2B ) . Interestingly , TLR2 expression in uninfected cells from BALB/c mice was significantly higher ( >80% ) , and infection with L . major did not significantly increase the receptor expression ( Fig 1A , B ) . MFI values for TLR2 did not significantly change either . As expected , infection did not significantly change the already elevated expression of TLR2 ( Fig 2C , D ) . The results suggest that infection of L . major directly induces upregulation of TLR2 only in BMDDCs from resistant ( C57BL/6 ) mouse stain . Next we determined whether the upregulation of TLR2 expression would result in an enhanced response to TLR2 stimulation . We first infected BMDDCs from both mouse strains with L . major and treated them with the TLR2 agonist Pam3CSK4 , either at the time of infection , or 18 h post infection . The production of IL-12 was measured in culture supernatants 24 h post stimulation . As expected , BMDDCs from both mouse stains produce IL-12 in response to Pam3CSK4 . This cytokine response was significantly greater than that secreted following infection . Interestingly , IL-12 production was enhanced in L . major-infected cells treated with the TLR2 agonist , irrespective of when it was added to the cultures in both strains ( at the time or after infection ) ( Fig 3 A , C ) . We also determined the effect of agonist treatment in infected BMDMs . It is clear that L . major infection in BMDMs from BALB/c mice inhibits production of IL-12 induced by Pam3CSK4 ( Fig 3D ) [Pam3 vs Lm+Pam3 ( 18h ) ] . However , compared to Lm infected BMDMs , Pam3CSK4 treatment dramatically enhanced IL-12 production in BMDMs from both strains of mouse when added at the time of infection or 18 h post infection ( Fig 3B , D ) . These results indicate that infected cells from both mouse strains are capable of responding to the TLR2 agonist stimulation . Our in vitro data strongly suggested that the proinflammatory properties of Pam3CSK4 could enhance anti-leishmanial immunity in vivo . In order to determine the outcomes of leishmanization with Pam3CSK4 , we tested our hypothesis by using two different strains of mouse . We infected C57BL/6 mice ( Th1-biased , self-healing disease ) and BALB/c mice ( Th2 biased , progressive disease ) in the ears with a suspension of 104 L . major parasites with or without 50 μg Pam3CSK4 . We monitored the development of lesions and determined parasite burdens in ears at early ( day 2 ) and late ( days 42 for C57BL/6 mice and 70 for BALB/c mice ) time points . Surprisingly , both mouse strains inoculated with L . major and Pam3CSK4 developed either small or no lesions compared to mice infected with parasites alone ( Fig 4A , B ) . Parasite burden data from ears and lymph nodes of C57BL/6 mice revealed no differences between the two experimental groups at the early time point ( day 2 ) ( Fig 4C , D ) , suggesting that treatment with the TLR2 agonist did not interfere with parasite establishment in these mice . In contrast , parasite burden was significantly decreased in both ears and lymph nodes of C57BL/6 at day 42 ( Fig 4C , D ) . On the other hand , establishment of L . major infection in ears and draining lymph nodes of BALB/c mice was dramatically compromised at the early time point , as parasite burden was significantly decreased in both sites at day 2 ( Fig 4E , F ) . At day 70 , parasite burden was still significantly lower in the ears of mice treated with Pam3CSK4 , but no differences were detected in their lymph nodes ( Fig 4E , F ) . These results suggest that , while Pam3CSK4 prevents the development of pathology in both mouse strains , the kinetics and the mechanism whereby pathology is prevented may be quite different . We have previously shown that vaccination with L . major and CpG DNA increased the early proinflammatory cytokine production in the dermis of C57BL/6 mice [15] . To determine if this activation mechanism caused by the TLR9 agonist is shared with other TLR ligands , we investigated the expression of the proinflammatory cytokines IL-12 and IL-6 at 48 h post leishmanization , in both dermal DCs ( express CD11c ) and macrophages ( express F4/80 ) . The total number of cells positive for IL-12 and IL-6 staining were significantly increased at 48 h in all mice inoculated with parasites plus Pam3CSK4 , irrespective of the mouse strain ( Table 1 ) . This demonstrates that leishmanization with live parasites and Pam3CSK4 also induces the early initiation of a strong proinflammatory response at the sites of infection . Our results have revealed that both resistant and susceptible mouse strains are protected against the development of lesions by leishmanization with L . major plus Pam3CSK4 . Our previous work with live parasites and CpG DNA revealed that Th17 responses were required to control vaccinal pathology in C57BL/6 mice [17] . However , the immune response of the BALB/c mice to this vaccine has remained uncharacterized . To investigate whether the CpG DNA-induced Th17 cell expansion is shared with other TLR agonists , we determined the absolute number of cytokine producing CD4 T cells in ears and ear draining lymph nodes of the treated mice at early and late time points . In C57BL/6 mice , both Th17 and Th1 responses at the early time point were enhanced by leishmanization with live parasites and Pam3CSK4 ( Fig 5A ) . This enhanced CD4+ T cell response was similar to what was described in our previous work using CpG DNA [17] . In contrast , leishmanization with L . major plus Pam3CSK4 did not enhance Th17 response in the BALB/c strain , although the number of Th1 IFN-γ expressing cells was higher in the L . major plus Pam3CSK4 inoculated group ( Fig 5D ) ; the immune response in these mice was dominated by Th1 cells , as opposed of what was found in the mice infected with L . major alone . This trend continued throughout the course of the infection , as demonstrated by the data obtained in the late time point and the Th1/Th2 ratio ( Fig 5B , C , E , F ) . Notably , Th1/Th2 ratio in BALB/c mice indicated that leishmanization with L . major plus Pam3CSK4 strongly promoted the development of Th1 response . More importantly , both parasite-specific Th1 and Th17 responses were enhanced at sites of infection in C57BL/6 mice infected with L . major plus Pam3CSK4 at late time point , whereas only Th1 response was enhanced in BALB/c mice ( Fig 5G ) . These data further suggest that the mechanisms underlying protection are different between both mouse strains . We have reported that , in C57BL/6 mice , vaccination with live parasites and CpG DNA increased the influx of neutrophils to the vaccination site early after vaccination [17] . Similarly , shortly after leishmanization , the number of neutrophils was significantly increased in both C57BL/6 and BALB/c ( Fig 6A , B ) . However , neutrophil numbers were dramatically decreased at the late time point in C57BL/6 mice ( Fig 6A ) . In contrast , despite the lack of pathology , neutrophil numbers remained high in the skin of BALB/c mice received leishmanization with L . major plus Pam3CSK4 . Because other groups have reported increasing amounts of IL-17 production by neutrophils in infected BALB/c mice [29] , we assessed the ability of IL-17 production from neutrophils following leishmanization . At the early time point , there was a greater number of IL-17 producing neutrophils infiltrating sites of infection in both mouse strains after leishmanization with L . major plus Pam3CSK4 ( Fig 6C , D ) .
To date , there is no vaccine against cutaneous leishmaniasis . The failure in translating data from animal models to human disease and a lack of understanding in how protective immune responses and immunological memory are generated and maintained , have been the major impediment in vaccine design [30] . In this paper , we have discovered that leishmanization with live parasites in the presence of the TLR2 agonist Pam3CSK4 prevents the development of lesions in both susceptible and resistant mice , albeit the underlying immunological mechanisms appear to be completely different . Our work has focused on understanding how live vaccination immunity is modulated by the addition of TLR agonists . In particular , we have extensively characterized immune responses of C57BL/6 mice to vaccination with live parasites plus the TLR9 agonist CpG DNA [14–17 , 31 , 32] . We employed this mouse strain because , unlike the susceptible BALB/c mice that succumb to systemic disease by L . major , infection of C57BL/6 mice replicates all clinical features of human cutaneous leishmaniasis: self-healing lesions [33 , 34] , chronicity [35] and concomitant immunity [36] . The first objective of this study was to validate the immunological mechanism of protection behind live vaccination with CpG DNA , and to investigate whether this mechanism is shared with other TLR agonists . We chose TLR2 because this is the most promiscuous TLR receptor , being able to recognize the most diverse set of pathogen-associated molecular patterns ( PAMP ) . Furthermore , lipophosphoglycan ( LPG ) , a PAMP in Leishmania , has been shown to bind to TLR2 and activate NF-κB translocation in a TLR2-dependent manner . This ligation upregulates TLR2 expression and eventually promotes the production of IFN-γand TNF-α in NK cells [26 , 27] . Moreover , TLR2 is widely expressed among human leukocytes , which will ensure a very intense response following receptor ligation . More importantly , the higher expression of TLR2 on macrophages is associated with the better disease outcome in cutaneous leishmaniasis patients [37] , indicating the clinical relevance of using TLR2 agonists . We have shown that L . major-infected cells become more sensitive to TLR2 stimulation and increase their proinflammatory response . Our data demonstrate that leishmanization with live parasites plus the TLR2 agonist Pam3CSK4 completely protected mice against the development of lesions , suggesting that TLR2 stimulation also results in enhancing anti-leishmanial immunity . Unexpectedly , we have found that expression of TLR2 in DCs is different between the two strains of mouse . This result is similar to the previous report that showed expression levels of TLR2 , TLR4 , TLR5 and TLR6 in naïve splenic DCs are higher in BALB/c mice than in C57BL6 mice [38] . The reactivity of DCs in both strains of mouse is also different upon TLR ligand stimulation . Taken together , our data suggest that differences in both expression pattern and reactivity of TLR2 may be associated with susceptibility and resistance to L . major infection in C57BL/6 and BALB/c mice . The second objective of our work was to compare the immunological events associated with protection following vaccination of both genetically susceptible and resistant mouse strains , which are characterized by extreme Th2 or Th1 polarization , respectively . The immune responses to cutaneous leishmaniasis in humans lack the strong polarity found in mouse models . Epidemiological data from patients with localized cutaneous leishmaniasis seem to confirm the Th1/Th2 dichotomy shown in mice . Moreover , patients with diffuse cutaneous leishmaniasis display a more predominant Th2 cytokine response . Furthermore , patients with mucosal leishmaniasis show a mixture of Th1 and Th2 cytokines [39] . Thus , the comparative study of the mouse models is important to be able to predict how , and whether , vaccine efficacy studies that employ TLR2 agonists would translate to human vaccines . Our data showing that leishmanization with parasites plus Pam3CSK4 protects both C57BL/6 and BALB/c mice against lesions are very promising , and point towards the feasibility of the use of TLR2 agonists as immune adjuvants against leishmaniasis . However , our studies have also revealed that the mechanism underlying protection is very different between the two mouse strains . Firstly , in contrast to C57BL/6 mice , parasite burden was decreased in BALB/c mice that received leishmanization with parasites plus Pam3CSK4 at the early time point , indicating parasite killing in BALB/c mice was enhanced at the early time point . This is highly unlikely to be caused by the cytotoxicity of Pam3CSK4 on parasites before inoculation , as we did not observed significant difference of the viability of L . major in all our in vitro experiments . In addition , unchanged parasite burden in C57BL/6 mice at the same time point further rules out the possibility of cytotoxicity of Pam3CSK4 on parasites . We speculate that the early parasite killing enhanced by the addition of Pam3CSK4 in BALB/c mice relies on high expression of TLR2 in immune cells . Indeed , compared to C57BL/6 mice , macrophages in BALB/c mice produce more IL-12 in responding to Lm+Pam3CSK4 ( See Fig 3B and D ) . This indicates the enhanced activation of macrophages , which may lead to increase the production of nitric oxide , a toxic to L . major . Nevertheless , other effects on tissue that may be caused by inoculation of Pam3CSK4 need to be further investigated . Secondly , C57BL/6 mice , as we demonstrated before , develop a strong Th17 response following vaccination with TLR agonists . However , this effector population did not expand in treated BALB/c mice; in these animals , protection appears to be mediated by the enhanced Th1 response . The enhanced Th1 response in both strains will lead to the production of nitric oxide by activated macrophages at sites of infection , which mediates killing of parasites . A recent study by Pandey et al . showed that treating infected mice with pegylated bisacycloxypropylcysteine ( BPPcysMPEG ) , a TLR2-TLR6 ligand , is capable of conferring protection against L . major infection in BALB/c mice [40] . Importantly , administration of BPPcysMPEG after immunization with fixed L . major induced protection against challenge infection . Interestingly , this study showed that treatment of Pam3CSK4 failed to reduce parasite burden . The different outcomes compared to our results could be because of the timing of TLR2 agonist administration . After three days of infection , parasites have established the infection , which strongly suppresses the activation of TLR1-TLR2 signaling in macrophages . This is consistent with our in vitro data indicating that L . major infection in BALB/c macrophages inhibits production of IL-12 induced by Pam3CSK4 . Moreover , the different infection route ( subcutaneous vs intradermal ) and infection dose may also contribute to the outcomes of infection [34 , 41] . Another remarkable difference between the two strains was the sustained neutrophil influx in BALB/c , but not in C57BL/6 mice . The role of the neutrophil in leishmaniasis is not well understood because it varies depending on the species of Leishmania and the animal models employed . Studies in the C57BL/6 mice have shown that neutrophils may promote infection by harboring parasites [42] . Conversely , others have revealed that neutrophils contribute to parasite killing [43] . Consistent with our results , neutrophil influx has been associated with resistance in L . amazonensis murine models [44 , 45] . Finally , neutrophils appear to be required for protective responses in L . braziliensis [46] . Our data also uncovered an interesting outcome of leishmanization which is at early time point , large numbers of neutrophils infiltrate to sites of infection in both C57BL/6 and BALB/c mice that were inoculated with live parasites plus Pam3CSK4 . This may be associated with the reduced parasite burden and pathology . Moreover , neutrophil infiltration induced by the additional Pam3CSK4 is sustained in BALB/c mice , which may be due to the specific effect of Pam3CSK4 in this cell type only in the susceptible strain . Some studies have already shown the distinct phenotypes of neutrophils expressing different TLRs in both resistant and susceptible mice during L . major infection [47] . Differential expression of TLRs by neutrophils may cause the diverse responses to TLRs agonist and thus influence the development of L . major specific immune response in our leishmanization approach . Notably , leishmanization with L . major and Pam3CSK4 induces the production of IL-17 from neutrophils in both strains of mouse . The role of IL-17 in leishmaniasis is controversial . In BALB/c mice , IL-17 promotes progression of disease [29] . However , it has been associated with protection against the infection of Leishmania donovani and in our previous vaccine model [17 , 48] . In our current model , L . major plus Pam3CSK4 enhance Th1 and Th17 responses , which are associated with protection in C57BL/6 mice . In contrast , only Th1 but not Th17 response seems to be required for protection in BALB/c mice . Therefore , we speculate that the outcome of production of IL-17 depends on background of the host . Moreover , IL-17 confers protection by actively recruiting neutrophils . A recent study has revealed autocrine IL-17 activity in mouse neutrophils [49] , indicating that neutrophil-derived IL-17 may contribute to the sustained influx of neutrophils in BALB/c mice . The function of IL-17 driven from neutrophils in L . major infection requires further investigation . Several studies have shown that administration of TLR2 agonists confers protective immunity against Leishmania [40 , 50] . IL-12 has been shown to be essential to sustain the generation of memory T cells , which provides long-term protective immunity against L . major [51 , 52] . As a potent IL-12 inducer , inoculation of Pam3CSK4 stimulates large amount of IL-12 from dermal DCs and macrophages at sites of infection . Therefore , we speculate that leishmanization with L . major and Pam3CSK4 is highly likely to be able to induce protective immunity . Our findings are relevant because they reveal the complexity and the difficulty to achieve vaccine protection: by exclusively taking into account the C57BL/6 data , we would have concluded that enhancing Th17 response is necessary to protect against leishmanial challenge . However , the effectiveness of Th17 response depends on the individual . Understanding the factors that regulate parasite persistence and its role in maintenance of immunologic memory in cutaneous leishmaniasis is critical for development of effective vaccines and vaccination strategies against the disease , and may explain why vaccination strategies have not translated very well from mouse to human .
|
Cutaneous leishmaniasis is a skin infection caused by a protozoan parasite Leishmania major ( L . major ) . The only available treatment option is chemotherapy , which is toxic and expensive . Currently , there is no vaccine . Although inoculation of virulent L . major ( leishmanization ) that provides effective protection in humans was widely applied , it was discontinued due to safety concerns . To improve the safety of leishmanization , we applied agonists of Toll-like receptor in the leishmanization to induce parasite-specific immune responses . In particular , we show here that inoculation with live L . major plus a TLR2 agonist Pam3CSK4 in both resistant ( C57BL/6 ) and susceptible ( BALB/c ) mouse strains completely prevents the development of lesion and decreases parasite burden . The improved pathology is associated with enhanced production of IL-6 and IL-12 from dermal dendritic cells and macrophages . Both Th1 and Th17 responses are enhanced in C57BL/6 mice . Although only the Th1 response was enhanced in BALB/c mice in the presence of Pam3CSK4 , there is an enhanced and sustained neutrophil influx at sites of infection . Overall , our study reveals the clinical significance of TLR2 agonist in treating cutaneous leishmaniasis . However , the protective mechanism may be quite different depending upon the genetic background of the host .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
Coinjection with TLR2 Agonist Pam3CSK4 Reduces the Pathology of Leishmanization in Mice
|
Massive activation of dopamine neurons is critical for natural reward and drug abuse . In contrast , the significance of their spontaneous activity remains elusive . In Drosophila melanogaster , depolarization of the protocerebral anterior medial ( PAM ) cluster dopamine neurons en masse signals reward to the mushroom body ( MB ) and drives appetitive memory . Focusing on the functional heterogeneity of PAM cluster neurons , we identified that a single class of PAM neurons , PAM-γ3 , mediates sugar reward by suppressing their own activity . PAM-γ3 is selectively required for appetitive olfactory learning , while activation of these neurons in turn induces aversive memory . Ongoing activity of PAM-γ3 gets suppressed upon sugar ingestion . Strikingly , transient inactivation of basal PAM-γ3 activity can substitute for reward and induces appetitive memory . Furthermore , we identified the satiety-signaling neuropeptide Allatostatin A ( AstA ) as a key mediator that conveys inhibitory input onto PAM-γ3 . Our results suggest the significance of basal dopamine release in reward signaling and reveal a circuit mechanism for negative regulation .
Dopamine plays a pivotal role in a wide range of motivation and learning [1–4] . In the fruit fly Drosophila melanogaster , phasic neurotransmission from specific dopamine neuron subsets mediate the reinforcing properties of salient unconditioned stimuli in associative learning [5–14] . These dopamine neurons endow positive and negative predictive values to associated environmental cues , thereby modulating the fly’s subsequent response to the conditioned cues [5 , 6 , 11–13] . In the fly brain , the protocerebral anterior medial ( PAM ) cluster of dopamine neurons conveys reward signals to the mushroom body ( MB ) [7 , 8] . While PAM cluster neurons exist from the larva , their cellular organization in the adult is much more complex and functionally heterogeneous [7 , 15 , 16] . Distinct dopamine neurons in the adult PAM cluster , for example , mediate appetitive and aversive reinforcement [5–7] and respond to sugar reward differently [7 , 12 , 17] . Besides phasic neurotransmission , recent studies revealed that valence-coding dopamine neurons have basal activity with fluctuating Ca2+ transient at the presynaptic terminals in the MB [17–21] . Ongoing dopamine release has been shown to control state-dependent consolidation of associative memory [18–21] . Considering the functional heterogeneity of the adult PAM cluster neurons [7 , 12 , 17] , excitation and inhibition of dopamine neurons may signal appetitive and aversive values to drive bidirectional associative memories . By characterizing PAM-γ3 , a single class of dopamine neurons projecting to the γ3 region of the MB , we here show that sugar ingestion drives appetitive memory by suppressing the baseline activity of PAM-γ3 . Furthermore , we searched for feeding-related signal molecules that inhibit PAM-γ3 and identified the neurons expressing the neuropeptide Allatostatin A ( AstA ) . These results point to the importance of basal dopamine release and its negative regulation in reward processing .
PAM cluster dopamine neurons are heterogeneous both morphologically and functionally and project to the distinct domains of the MB [7 , 12 , 17 , 22 , 23] . PAM-γ3 extends their dendritic arbor in the brain area surrounding the MB medial lobes ( crepine ) and projects specifically to the γ3 compartment of the MB ( Fig 1A and 1B ) . While the majority of PAM neurons convey reward , previous studies implied that PAM-γ3 mediates aversive reinforcement [6 , 12] . However , additional GAL4 expression in other PAM neurons and nondopaminergic neurons of the driver line precluded identifying the responsible cells . We thus employed recently established split-GAL4 drivers MB441B-GAL4 and MB195B-GAL4 to specifically label 9 and 5 PAM-γ3 neurons , respectively [22] ( Fig 1A ) . To examine the role of PAM-γ3 neurons in learning , we activated them by directing the expression of dTrpA1 , a temperature-sensitive cation channel [24] , using MB441B-GAL4 and MB195B-GAL4 . Simultaneous presentation of an odor with thermoactivation of the PAM-γ3 neurons induced robust conditioned avoidance of the paired odor ( Fig 2A ) . Aversive memory established by thermoactivation of PAM-γ3 suggests their role in aversive reinforcement . As electric shock , compared to other aversive reinforcers , recruits the broadest set of dopamine neurons [6 , 10 , 14] , we examined the requirement of the PAM-γ3 neurons in shock-induced aversive olfactory memory using targeted shibirets1 ( shits1 ) expression , a temperature-sensitive dominant negative form of dynamin GFPase that inhibits vesicle endocytosis [25] . Surprisingly , thermal blockade of PAM-γ3 using MB441B and MB195B did not significantly impair electric shock–reinforced aversive memory ( Fig 2B ) . The result was same with the Shits1 blockade by another driver , R58E02-GAL4 , which strongly drives transgene expression in the majority of the PAM cluster neurons , including PAM-γ3 [7] ( S1 Fig ) . As multiple classes of adult PAM neurons contribute to reward signaling differently [7 , 12 , 17] , we examined the requirement of PAM-γ3 for sugar-induced appetitive memory . Contrary to aversive memory induced by depolarizing the PAM-γ3 neurons , thermal blockade of PAM-γ3 with MB441B-GAL4/UAS-shits1 and MB195B-GAL4/UAS-shits1 flies significantly impaired appetitive memory ( Fig 2C ) . Moreover , blocking PAM-γ3 only during the acquisition of appetitive memory revealed a similar impairment , suggesting the role of PAM-γ3 in reward processing ( Fig 2D ) . Their memory performance at a permissive temperature was not significantly different from those of the genetic controls ( Fig 2E ) . The blockade of PAM-γ3 did not impair innate sugar preference at the concentration used for the learning experiment or lower ( Figs 2F and S3A ) . These results suggest the selective requirement of PAM-γ3 for mediating sugar reward . As PAM-γ3 activation drives aversive memory [7] , inhibition of the basal activity might be important for processing sugar reward . To examine this hypothesis , we imaged the Ca2+ response of PAM-γ3 by expressing GCaMP5 [26] , a genetically encoded fluorescent calcium sensor , under the control of MB441B-GAL4 . The baseline activity was fluctuating without stimulation ( Fig 3A and 3B ) . Strikingly , sugar ingestion immediately silenced the baseline activity ( Fig 3A , 3B and 3C ) . The Ca2+ level of PAM-γ3 neurons remained suppressed even after the ingestion ( Fig 3B ) , which recovered to the baseline level approximately 20 s after the stimulus offset ( Fig 3B ) . These data are compatible with the idea that PAM-γ3 neurons mediate appetitive reinforcement by acutely suppressing their baseline activity . We hypothesized that transient inactivation of the PAM-γ3 dopamine neurons may be sufficient to signal appetitive reinforcement . Similar to the reinforcement substitution experiment with dTrpA1-mediated depolarization ( Fig 1 ) , we paired the Shits1 blockade of PAM-γ3 with one of the two odors; temperature was shifted only during the presentation of the conditioned odor ( Fig 4A ) . This protocol is different from the former Shi ts1 experiments ( Fig 2C and 2D ) , in which PAM-γ3 was blocked during both CS+ and CS- . The paired blockade of PAM-γ3 in MB441B-GAL4/UAS-shits1 flies indeed induced significant appetitive odor memory ( Fig 4B ) . To confirm this appetitive memory , we established an optogenetic silencing approach by using engineered halorhodopsin ( eNpHR ) [27] , a light-gated chloride ion pump . Transient blockade of the PAM-γ3 output by applying yellow light ( 591 nm ) during the odor presentation resulted in an induction of appetitive memory ( Fig 4C and 4D ) . We thus conclude that the suppression of PAM-γ3 baseline activity is sufficient to signal appetitive reinforcement . How does sugar ingestion suppress PAM-γ3 activity ? Many neuropeptides are known to reflect feeding states and inhibit target cells through their receptors coupled with inhibitory G proteins [28] . We thus examined the expression patterns of a series of neuropeptide-related GAL4 drivers for their potential connection with the PAM-γ3 dendrites in silico [12] . Image registration of confocal stacks of the expression of neuropeptide GAL4 lines and MB441B-GAL4 into a standard brain revealed a spatial overlap between the processes of AstA and the PAM-γ3 neurons ( Fig 5A and 5B ) . This putative connection was experimentally confirmed using reconstituted GFP signal between PAM-γ3 and AstA neurons by the GFP reconstitution across synaptic partners ( GRASP ) technique [29] ( Fig 5C ) . AstA was shown to signal satiation in Drosophila [30] and inhibits target neurons [31] . We therefore asked the involvement of the AstA neurons in mediating sugar reward . Thermoactivation of dTrpA1 with AstA-GAL4 , which exclusively labels a subset of AstA immunopositive neurons [30] , resulted in the formation of appetitive odor memory ( Fig 6A ) . The blockade of AstA neurons during learning significantly lowered appetitive memory of both sucrose ( Fig 6B ) and nonnutritive sugar arabinose ( Fig 6E ) . The sugar preference of AstA-GAL4/UAS-shits1 flies and their memory performance at a permissive temperature were unimpaired ( Figs 6C and 6D and S3B ) . Thus , AstA-expressing neurons are necessary and sufficient for mediating the reinforcement property of sugar reward , likely sweetness . To confirm that the AstA protein is the underlying modulatory signal , we generated multiple null alleles of AstA using the CRISPR/Cas9 system . Appetitive memory of these mutant flies was significantly impaired ( Fig 7A ) while leaving their innate sugar preference unaffected ( Fig 7B ) . Moreover , we also generated an RNA interference ( RNAi ) fly line against AstA based on the small hairpin RNA ( shRNA ) technique [32] . Down-regulation of AstA using AstA-GAL4 resulted in an impaired appetitive learning ( Fig 7C ) while leaving sugar preference intact ( Fig 7D ) . Given that AstA is an inhibitory neuropeptide [31] , these results suggest that the AstA release conveys sugar reward by inhibiting the PAM-γ3 dopamine neurons . In order to visualize the distribution of an AstA receptor , we inserted the GAL4 transgene into the C-terminus of the Allatostatin A receptor 1 ( DAR-1 ) coding region [33] by means of the CRISPR-Cas9 system . Confocal examination of DAR-1-GAL4 expression revealed positive labelling in the dopamine neurons projecting to the MB , including PAM-γ3 ( Figs 8A and S4 ) . If AstA/DAR-1 signaling also works in an inhibitory manner in the PAM-γ3 , down-regulation of DAR-1 may weaken the PAM-γ3 suppression . To test this , we generated RNAi fly strains against DAR-1 based on the shRNA technique . Strikingly , knocking down DAR-1 in the PAM-γ3 significantly attenuated the suppression of the baseline activity ( Fig 8B and 8C ) . Altogether , we propose that AstA provides an inhibitory signal to PAM-γ3 upon the ingestion of rewarding substances . To examine the behavioral effect of AstA/DAR-1 signaling in the PAM-γ3 , we down-regulated DAR-1 expression in the PAM-γ3 neurons and examined their appetitive memory . Consistent with our proposal , the knockdown significantly impaired sugar learning ( Fig 9A and 9B ) while leaving the innate sugar preference intact ( Fig 9C and 9D ) . AstA/DAR-1 signaling was shown to suppress neuronal activity in receiving cells through Gαi/o signaling [31 , 34] . To examine the intracellular mechanism of AstA/DAR-1 signaling in PAM-γ3 , we inhibited the Gαo subunit by expressing the pertussis toxin with MB441-GAL4 [35] . As these flies had defective sugar memory ( Fig 10A ) but unimpaired sugar preference ( Fig 10B ) , we suggest that DAR-1 inhibits PAM-γ3 activity by recruiting Gαo .
Sugar ingestion triggers multiple reward signals in the fly brain [7 , 12] . We here provided lines of evidence that part of the reward is signaled by inactivating dopamine neurons ( Figs 1–4 ) . The role of PAM-γ3 highlights the striking functional heterogeneity of PAM cluster dopamine neurons . The decrease and increase of dopamine can convey reward to the adjacent compartments of the same MB lobe—γ3 and γ4— ( Figs 3 and 4 ) [9 , 17] . The reward signal by the transient decrease of dopamine is in stark contrast to the widely acknowledged role of dopamine [36 , 37] . Midbrain dopamine neurons in mammals were shown to be suppressed upon the presentation of aversive stimuli [38] or the omission of an expected reward , implying valence coding by the bidirectional activity [39] . As depolarization of PAM-γ3 can signal aversive reinforcement ( Fig 2 ) , these neurons convey the opposite modulatory signals to the specific MB domain by the sign of their activity . Intriguingly , the presentation and cessation of electric shock act as punishment and reward , respectively [40] . Such bidirectional activity of PAM-γ3 may represent the presentation and omission of reward ( Figs 1–4 ) . While thermoactivation of PAM-γ3 induced robust aversive memory , blocking their synaptic transmission did not affect shock learning , leaving a question regarding their role in endogenous aversive memory process . PAM-γ3 may only be involved in processing aversive reinforcement different from electric shock—like heat [10] or bitter taste [11 , 41]—or respond only to the omission of a reward as pointed above [40 , 42] . However , two studies show that dopamine neurons mediating aversive reinforcement of high temperature and bitter N , N-Diethyl-3-methylbenzamide ( DEET ) are part of those for electric shock . Identification of such aversive stimuli that are signaled by PAM-γ3 activation is certainly interesting , as it is perceived as the opposite of sugar reward and thus provides the whole picture of the valence spectrum . Another scenario where sufficiency and necessity do not match is the compensation of the reinforcing effect by other dopamine cell types ( e . g . MB-M3 [6] ) . The lack of PAM-γ3 requirements for electric shock memory may be explained by a similar mechanism . How can the suppression of PAM-γ3 modulate the downstream cell and drive appetitive memory ? Optogenetic activation of the MB output neurons from the γ3 compartment induces approach behavior [43] . This suggests that the suppression of the PAM-γ3 neurons upon reward leads to local potentiation of Kenyon cell output . This model is supported by recent studies showing the depression of MB output synapses during associative learning [17 , 44–46] . A likely molecular mechanism is the de-repression of inhibitory D2-like dopamine receptors , DD2R [47] . As D2R signaling is a widely conserved mechanism [48] , it may be one of the most ancestral modes of neuromodulation . Furthermore , recent anatomical and physiological studies demonstrated that different MB-projecting dopamine neurons are connected to each other and act in coordination to respond to sugar or shock [17 , 43] . Therefore , memories induced by activation or inhibition of PAM-γ3 may well involve the activity of other dopamine cell types . Our finding that appetitive reinforcement is encoded by both activation and suppression of dopamine neurons raises the question as to the complexity of reward processing circuits ( Fig 11 ) . It is , however , reasonable to implement a component like PAM-γ3 as a target of the satiety-signaling inhibitory neuropeptide AstA . Intriguingly , the visualization of AstA receptor distribution by DAR-1-GAL4 revealed expression in two types of MB-projecting dopamine neurons: PAM-γ3 and MB-MV1 ( also named as PPL1- γ2α’1 ) . Given the roles of MB-MV1 in aversive reinforcement and locomotion arrest [6 , 10 , 17 , 19] , AstA/DAR-1 signaling may also inhibit a punishment pathway upon feeding . We thus speculate that this complex dopamine reward circuit may be configured to make use of bidirectional appetitive signals in the brain ( Fig 11 ) .
Canton-S was used as a wild-type strain . Generation and basic characterization of split-GAL4 drivers , w;MB441B-GAL4 and w;MB195B-GAL4 , is described in [22] . w;;R58E02-GAL4 and w;;AstA-GAL4 are described in [7 , 30] . UAS-PTX16 is described in [35] . AstA mutants were generated as described previously [49] . Two null alleles , AstASK1 and AstASK4 , in which the initiation methionine codon is deleted , were used throughout the present study . DAR-1-GAL4 was generated by CRISPR/Cas9-mediated targeted integration of a GAL4 transgene immediately in front of the stop codon of the DAR-1 gene . The GAL4 transgene contains a T2A peptide at the amino-terminus [50] , such that GAL4 protein is synthesized from the same transcript as DAR-1 through the ribosomal skipping mechanism . The insertion was validated with genomic PCR and sequencing . Flies were raised at 24°C except for DAR-1 and AstA knockdown experiments . Thermoactivation experiments ( Fig 1A ) used the F1 progeny of the crosses between females of w;UAS-dTrpA1 [24] or w and males of the GAL4 drivers . Synaptic blockade experiments ( Figs 2 , 4 , 6 , S1 , S2 and S3 ) used the F1 progeny of the crosses between females of w;;UAS-shits1 [51] or w and males of the GAL4 drivers . For the AstA ( Fig 7 ) and DAR-1 knockdown experiments ( Figs 8 and 9 ) , we generated a UAS-AstA-RNAi and two UAS-DAR-1-RNAi transgenes in the Vailum20 vector [52] . The 21-bp , gene-specific sequence was: ACGCAGCGACTACGACTACGA ( AstA ) , TCGGTCATTATTCAGATTATA ( DAR-1 ) , and CACGATAGGGATCTCTGTCAA ( DAR-1 ) , respectively . Females of those flies were crossed with males of the GAL4 drivers or w . The F1 progeny was raised at 24°C until 6 d after hatch , moved to 30°C , and kept for 1–14 d before experiments . For immunohistochemistry , a female reporter strain y w UAS-mCD8::GFP;UAS-mCD8::GFP;UAS-mCD8::GFP or w;58E02-LexA LexAop-mCD4::GFP11;UAS-mCD4::GFP1-10 was crossed to male GAL4 drivers , w;MB441B-GAL4 , w;;AstA-GAL4 , w;;DAR-1-GAL4 . Flies used for whole-mount immunohistochemistry were aged to 5–10 d after eclosion . For Ca2+ imaging experiments , males of w; mb247-dsRed , UAS-GCaMP5; UAS-GCaMP5 [26] or w; UAS-V20-DAR-1-RNAi; UAS-GCaMP5 were crossed to w;MB441B-GAL4 females and raised at 24°C ( Figs 3 and 8 ) . For detailed fly genotypes used for behavioral experiments , see S1 Table . Immunolabelling for the analysis of GAL4 lines was performed as previously described [5–7 , 12] . Either 97% TDE [53] or Vectashield ( VECTASHIELD® , Vector ) was used as mounding medium . The employed primary antibodies were the rabbit anti-GFP ( 1:1000; Invitrogen; A11122 ) or rat anti-N-cadherin ( DN-EX #8; 1:100; Developmental Studies Hybridoma Bank ) . The employed secondary antibodies were the cross-adsorbed secondary antibodies to IgG ( H+L ) : AlexaFluor-488 goat anti-rabbit ( 1:1000; Invitrogen; A11034 ) or Cy3 goat anti-rat ( 1:200; Jackson Labs ) . Optical sections of whole-mount brains were sampled with a confocal microscope ( Olympus FV1200 ) . Confocal stacks were analyzed with the open-source software Image-J ( National Institute of Health ) and Fiji [54] . Landmark matching–based affine and nonrigid registration of whole brains was performed as previously described [12] . Confocal images of entire brains of GAL4/UAS-mCD8::GFP flies were scanned with n-cadherin ( n-Cad ) counterstaining and registered into the standardized brain by referring the n-Cad channel . The transformations computed with the n-Cad channel were then applied to the mCD8::GFP channel . The registered images were assigned into the standardized brain and represented as different colors using ImageJ . The conditioning and testing protocol was as described previously [7 , 12] . Briefly , for sugar learning and the US substitution experiment by dTrpA1-mediated thermoactivation , a group of approximately 50 flies in a training tube alternately received octan-3-ol ( OCT; Merck ) and 4-methylcyclohexanol ( MCH; Sigma-Aldrich ) for 1 min in a constant air stream with or without dried sucrose paper or 30°C heat . For the US substitution experiment by Shits1-mediated thermoinactivation ( Fig 4 ) , a group of approximately 50 flies in a training tube alternately received OCT and MCH for 2 min in a constant air stream with or without 33°C heat . For the US substitution experiment by eNpHR3-mediated light-inactivation ( Fig 4 ) , a group of approximately 50 flies were put into a custom-made LED-embedded aluminum tube and alternately received OCT and MCH for 1 min twice in a constant air stream with or without a continuous light exposure ( 591 nm ) . The light intensity was approximately100 mW/mm2 at a distance of 10 mm from the LED , measured with the Laser Power Meter Console ( Thorlabs , PM100A ) . Flies were fed with all-trans-retinal contained food ( 2 . 5 mM ) at least for 3 d before the experiments . OCT and MCH were diluted 10% in paraffin oil ( Sigma-Aldrich ) and placed in a cup with a diameter of 3 mm or 5 mm , respectively . After a given retention time , the conditioned response of the trained flies was measured with a choice between CS+ and CS- for 2 min in a T maze . The memories were tested immediately after training unless otherwise stated . The restrictive temperature for the experiments with UAS-shits1 was 33°C and the permissive temperature was 24°C , measured with the VC-960 digital multimeter ( Voltcraft ) . For memory retention , trained flies were kept in a vial with moistened filter paper . After a given retention time , the trained flies were allowed to choose between MCH and OCT for 2 min in a T maze . A learning index was then calculated by taking the mean preference of the two reciprocally trained groups . Half of the trained groups received reinforcement together with the first presented odor and the other half with the second odor to cancel the effect of the order of reinforcement . Statistical analyses were performed with Prism5 ( GraphPad ) . Most of the data did not violate the assumption of normal distribution and homogeneity of variance . Therefore , the data were analyzed with parametric statistics: one-way analysis of variance followed by the planned pairwise multiple comparisons ( Bonferroni two-tailed test ) . Figs 2B , 2F , 6C , 6D , 7B , 9A , S1 and S2 were analyzed with nonparametric statistics: Kruskal–Wallis one-way analysis of variance followed by the planned pairwise multiple comparisons ( Dunn’s test ) . The significance level of statistical tests was set to 0 . 05 . For detailed results for statistical tests , see S1 Table . The numerical data used in all figures are included in S1 Data . The expression of GCaMP5 [26] calcium reporter was targeted to PAM-γ3 neurons by crossing MB441B-GAL4 to mb247-dsRed , UAS-GCaMP5 , or UAS-V20-DAR-1-RNAi; UAS-GCaMP5 flies . Flies that were 2 to 3 d old from the offspring were starved at 25°C for 24 h on a Kimwipe soaked with water . For DAR-1 knockdown experiments , flies were aged to 8–12 d after eclosion . Flies were then prepared for in vivo imaging by confocal microscopy as previously described [55] . Fluorescence was recorded in a transverse section of the brain . Recordings were made with a frame rate of 2 Hz in two animals , 10 Hz in two animals , and for the rest at 5 Hz , which did not alter the results . Each fly was presented with a droplet of 500 mM sucrose . The fly had access to the gustatory stimulus for 10 s . Image analysis was performed essentially as described previously [55] . Briefly , an object in each recording was stabilized by phase correlation–based image alignment using dsRed signal , then GCaMP5 signal was used as a fluorescent F value . In each animal , a region of interest in the left hemisphere was used . The baseline value of fluorescence Fmean was calculated as the average of ΔF/Fmean over 15 s before the start of the stimulation .
|
Dopamine neurons in the midbrain of mammals fire action potentials in response to rewarding stimuli , while punitive stimuli or omission of reward suppress their activity . Different signs in the activity of dopamine neurons thus can encode appetitive and aversive values; however , how these bidirectional activities directly relate to behavior has yet to be elucidated . In fruit flies Drosophila , en masse activation of dopaminergic neurons in the protocerebral anterior medial ( PAM ) cluster has been shown to signal reward . Here , we demonstrate that a specific sub-class of these dopaminergic neurons , called PAM-γ3 , mediates both aversive and appetitive reinforcement through activation and suppression of their activity , respectively . Notably , transient inactivation of the basal activity of PAM-γ3 neurons substitutes for reward and induces appetitive memory formation . Interestingly , we found that Allatostatin A , a neuropeptide that signals satiety , conveys inhibitory input onto PAM-γ3 neurons . Our results highlight the bidirectional activity of defined dopaminergic neurons , which underlies encoding of behaviorally relevant appetitive and aversive values .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
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2016
|
Suppression of Dopamine Neurons Mediates Reward
|
Mongolia is one of the endemic countries for cystic echinococcosis ( CE ) , a zoonotic disease caused by the larval stage of Echinococcus granulosus . The goal of this study is to describe the current clinical management of CE in Mongolia , to capture the distribution of cyst stages of patients treated , and to contrast current practice with WHO-IWGE expert consensus . Hospital records of CE patients treated between 2008 and 2015 at the three state hospitals and fulfilling the inclusion criterion ‘discharge diagnosis CE’ ( ICD 10 code B . 67 . 0–67 . 9 ) were reviewed . Demographical , geographical , clinical and ultrasonography ( US ) data were extracted and analyzed . The annual surgical incidence was estimated . The digital copies of US cyst images were independently staged by three international experts following the WHO CE cyst classification to determine the proportions of patients which ideally would have been assigned to the WHO recommended treatment modalities surgery , percutaneous , medical ( benzimidazole ) treatment and watch & wait . A total of 290 patient records fulfilled the inclusion criteria of the study . 45 . 7% of patients were below 15 years of age . 73 . 7% of CE cysts were located in abdominal organs , predominantly liver . US images of 84 patients were staged and assessed for interrater-agreement . The average raw agreement was 77 . 2% . Unweighted Kappa coefficient and weighted Kappa was 0 . 57 and 0 . 59 , respectively . Mean proportions of images judged as stages CE1 , CE2 , CE3a , CE3b , CE4 and CL were 0 . 59 , 0 . 01 , 0 . 19 , 0 . 08 , 0 . 03 and 0 . 11 , respectively . 40 cysts met the inclusion criteria of treatment modality analysis . The mean proportions of cases with a single cyst assigned to medical , percutaneous treatment , surgery and watch & wait were 52 . 5% ( 95% CI 42–65 ) , 25 . 8% ( 95% CI 15–30 ) , 5 . 1% ( 95% CI 0–10 ) and 3 . 3% ( 95% CI 0–10 ) , respectively . 13 . 3% ( 95% CI 5–25 ) of cysts were staged as CL and therefore assigned to further diagnostic requirement . WHO CE cyst classification and WHO-IWGE expert consensus on clinical CE management is not implemented in Mongolia . This results in exclusively surgical treatment , an unnecessary high risk approach for the majority of patients who could receive medical , percutaneous treatment or observation ( watch & wait ) . Introduction of WHO-IWGE expert consensus and training in ultrasound CE cyst staging would be highly beneficial for patients and the health care services .
Cystic echinococcosis ( CE ) is a zoonotic disease caused by the larval stage of Echinococcus granulosus . The life cycle of E . granulosus is maintained between the dog as the definitive host and various livestock as the intermediate host . Humans are considered as an aberrant intermediate host . Ingested larvae develop into cystic lesions , mostly in the liver and lung [1] . The disease is globally distributed including Central Asian countries and China [2–4] . The annual global burden of disease is estimated at 184 , 000 Disability Adjusted Life Years ( DALYs ) [5 , 6] . Due to a large proportion of asymptomatic cases and underreporting the disease burden is widely underestimated . Pastoral communities in countries with limited resources bear the greatest burden [3 , 5 , 7] . In Mongolia , one-third of the population is engaged in extensive pastoral farming . The presence of a large livestock population accompanied by watchdogs , a big number of stray dogs , unregulated private slaughtering , and lack of health education are the main reasons for the heavy human CE exposure [8 , 9] . Historically , due to strong public and veterinary action , the surgical cases decreased from 13% in 1946 to 2% in 1988 in the state hospital [10 , 11] . After the Soviet Union collapsed in 1990 , the veterinary and public health sectors weakened and many control programs for zoonotic disease , including CE , collapsed [12] . Currently , CE is not included in the national surveillance system , and official statistics are , therefore , unavailable [8 , 9 , 13] . There are few reports on the current transmission of CE in Mongolia including small scale serological surveys , hampered , however , by the sensitivity and specificity problems of serological CE testing [11 , 14–18] . CE predominantly affects rural populations with very limited access to health care [19] . Diagnosis , cyst staging , treatment and follow-up depend on imaging [20 , 21] . Ultrasonography , however , is only recently introduced in low and lower middle income countries ( LICs and LMICs ) [22–24] . Thus most endemic countries , including Mongolia , have not yet implemented the WHO Informal Working Group on Echinococcosis ( WHO-IWGE ) expert consensus [25 , 26] . The core piece of the WHO-IWGE expert consensus is to triage on the basis of ultrasound-defined cyst stages into four groups: medical , percutaneous , surgical treatment ( active cyst stage CE1 to CE3b ) and ‘watch & wait’ ( inactive cyst stages CE4 and CE5 ) [20 , 27–30] . The goal of this study is to describe the current clinical management of CE in Mongolia , to capture the distribution of cyst stages retrospectively from stored ultrasound images , to critically contrast current practice in Mongolia with WHO-IWGE expert consensus and to suggest a LIC / LMICs-adapted implementation strategy for WHO-IWGE expert consensus .
This work presented here was approved by the Medical Ethics committee of Mongolia ( July 2014 ) and WHO ERC ( 27 Nov 2015 ) . We reviewed the hospital records of patients diagnosed with CE and admitted between 2008 and 2015 to the three state hospitals conducting CE surgery in Mongolia: First Central Hospital ( FCH ) , Third Central Hospital ( TCH ) , National Center for Maternal and Child Health ( NCMCH ) . Patients identified as probable CE cases in the peripheral or secondary hospitals are , as a rule , referred to the three state hospitals for confirmation and surgery . In the archives of the state hospitals , the medical records are chronologically stored in bundles of 150–200 reports . On the front page of each record the discharge diagnosis is recorded by the surgeon , based on histopathology which is done as a routine in the national hospitals . The ‘discharge diagnosis CE’ ( ICD 10 code B . 67 . 0–67 . 9 ) was the inclusion criteria for our study . The following data were extracted from the patient records on data extraction sheets: demographic and geographic data ( specified in Table 1 ) , clinical symptoms and signs , ultrasonography ( US ) reports including number and size of cysts , US images , surgical reports and final diagnosis . US images ( photos ) were digitalized and stored . The data collected on data extraction sheets were double entered into a data base . The demographic information including age , sex , occupation , type of home , and distance from health care was presented with the relevant percentage . The distance between secondary hospital ( provincial general hospital ) and current address of the patient was calculated . The levels of the clinical care in Mongolia are provided in Fig A in S1 Appendix . The socio-economic status ( SES ) in the adult patients was stratified according to the labour force category of the National Statistical Office [31] . The current address of the patient was used to plot the geographical distribution by employing the ArcGIS 10 . 0 ( ESRI 2011 . ArcGIS Desktop: Release 10 . Redlands , CA: Environmental Systems Research Institute ) . The annual surgical incidence was estimated based on the hospital records . The frequency of the clinical signs & symptoms was calculated . The size and number of CE cysts were presented in three different categories , <5 cm , 5–10 cm , and >10 cm and single cyst , 1–3 cysts , and multiple cysts , respectively . The digital copies of US cyst images were independently reviewed by three international experts ( reviewers ) to estimate the frequency distribution of cyst stages according to WHO cyst classification ( CL , CE1 , CE2 , CE3a , CE3b , CE4 , CE5 ) in the patient population referred to the state hospitals for confirmatory assessment and treatment . The exercise was performed on the US images of abdominal lesions . The experts received no further information about the patients . Duplicate images of cysts were provided when available . If the reviewer felt unable to stage a cyst , e . g . because of poor quality of an image , the cyst was classified ‘not identifiable’ ( NI ) . After the assessment , exclusions were made on the double images . If a double image of a cyst was assessed identical by the reviewers , we selected randomly one of the images . If a double image was assessed not identical by the reviewers , the one with fewer “NI” votes was selected to represent the cyst . Interrater-agreement was calculated using the Kappa statistic . Raw agreement was calculated as the proportion of cysts where the raters noted the same stage and kappa statistics for ordered categories ( CL , CE1 , CE2 , CE3a , CE3b , CE4 , CE5 ) . We report both , unweighted and weighted kappa statistics with weights calculated as the square of the distance between the two ordinal groups . We judged agreement as poor if κ < 0 . 2; fair if 0 . 2 ≤ κ < 0 . 4; moderate if 0 . 4 ≤ κ < 0 . 6; substantial if 0 . 6 ≤ κ < 0 . 8; and good if κ ≥ 0 . 8 . The estimates represent the arithmetic mean of the 3 pair-wise comparisons . “NI” judgements were considered as missing values which have been excluded pair-wise for raw agreement and kappa estimation . Allocation of the cysts to WHO recommended treatment modalities was performed on the basis of cyst staging by the 3 reviewers and cyst size . Cases with images assessed as “NI” by all three reviewers were excluded; equally , cases with more than one cyst since completeness and ascertainment of US images was difficult retrospectively . The double images were excluded using the same algorithm as in the analysis of interrater-agreement . We calculated combinations of CE stage and cyst size for all three reviewer assessments separately and calculated the mean percentage . Based on this combination , the probability of assignment of cases to the treatment modalities as defined by the WHO-IWGE expert consensus were estimated for each case . Assignment of cysts to WHO recommended treatment modalities was performed as if all cysts were uncomplicated since the retrospective data did not allow to reliably differentiate complicated from uncomplicated cysts . Bootstrap resampling with 10 , 000 replicates was used for estimating the 95% confidence intervals for the treatment options . The analysis was conducted using the statistical package R v 3 . 4 . 0 .
A total of 290 medical records fulfilled the inclusion criterion ‘discharge diagnosis CE’ ( ICD 10 code B . 67 . 0–67 . 9 ) of the patients admitted to the three state hospitals between 2008 and 2015 , 43 records were excluded . For details see Fig 1 . The demographic data are presented in Table 1 . During the period 2008–2015 , the average annual CE surgical incidence per 100 000 was 1 . 06 ( 95% CI 0 . 7–1 . 4 ) based on the current data collection . On average 30 . 8 ( 95% CI 20 . 4–41 . 3 ) cases per annum underwent CE surgery in the central hospitals between 2008 and 2015 ( Fig B in S1 Appendix ) . The patients originated from 20 provinces corresponding to 95% ( 20/21 ) of all provinces ( Fig 2 ) . The southern provinces Omnogobi ( OG ) , Dundgobi ( DU ) , and Bayankhongor ( BH ) have the highest number of cases . Average CE surgical incidence for the survey period in these provinces was 2 . 7–6 . 1 per 100 000 inhabitants based on the medical records in the three state hospitals . The frequency of symptoms & signs in CE patients at admission to the three state hospitals are provided in Fig C in S1 Appendix . The location of CE cysts of the surgically treated patients at the three state hospitals between 2008 and 2015 are provided in Fig D in S1 Appendix . Preoperative ultrasound reports were available in 83 . 5% ( 152/182 ) of patients who had undergone abdominal surgery for CE . 26 . 3% ( 40/152 ) were explicitly recorded as hydatid cysts , 54 . 6% ( 83/152 ) as cystic lesions , and 19% ( 29/152 ) as other space occupying lesions . 99 . 3% ( 151/152 ) of the abdominal cases had the information on the cyst number in the US record . Among them , 78 . 1% ( 118/151 ) had single cysts , 20% ( 31/151 ) had 1–3 cysts and 1 . 3% ( 2/151 ) had more than 3 cysts . The information on size was available for 90 . 1% ( 137/152 ) of the abdominal cases . Among them , 48 . 9% ( 67/137 ) had cysts smaller than 5 cm , 35 . 0% ( 48/137 ) of 5–10 cm and 16 . 1% ( 22/137 ) were bigger than 10 cm . 138 US imaging photos of 84 cases with liver and abdominal cysts were available for review and CE cyst staging based on the WHO CE cyst classification by three international reviewers . Following the inclusion / exclusion procedures described in the method section images of 84 unique cysts were assessed for interrater-agreement analysis . The raw agreement was 77 . 2% . We observed substantial agreement with an average unweighted Kappa coefficient of 0 . 57 and an average weighted Kappa coefficient of 0 . 59 ( squared weights ) . The proportions of CE cyst stages are shown in Fig 3 . Mean proportion for CE stages including CE1 , CE2 , CE3a , CE3b , CE4 , and CL were 0 . 59 , 0 . 01 , 0 . 19 , 0 . 08 , 0 . 03 and 0 . 11 , respectively . No CE5 cysts were identified . Of the cysts staged by the three reviewers , 40 met the inclusion criteria for the treatment modality analysis ( selection process see methodology section ) . The mean proportion of cases assigned to medical treatment , percutaneous treatment , surgery and watch & wait was calculated as 52 . 5% ( 95% CI 42–65 ) , 25 . 8% ( 95% CI 15–30 ) , 5 . 1% ( 95% CI 0–10 ) and 3 . 3% ( 95% CI 0–10 ) , respectively . 13 . 3% ( 95% CI 5–25 ) of the cysts were staged as CL in need for further diagnostic work up ( Fig 4 ) .
To the best of our knowledge this is the first description of the clinical management of CE patients in LICs / LMICs with an attempt to critically contrast current national practice with the WHO-IWGE expert consensus [20] on the basis of interrater-agreement calculated from the retrospective cyst staging by three independent experts . Mongolia offers the unique opportunity for this exercise for two reasons . CE patients identified on the peripheral level of the health care services are exclusively referred for confirmation and treatment to the three state hospitals where patient records are carefully stored in archives with a discharge diagnosis on the front page of each patient file . The data of 290 patients with the ‘discharge diagnosis CE’ ( ICD 10 code B . 67 . 0–67 . 9 ) admitted between 2008 and 2015 were available to characterize the CE patients who currently receive treatment in Mongolia . Ultrasound photos of 46% ( 84/182 ) of patients with abdominal cysts were available for retrospective cyst staging on the basis of WHO CE cyst classification by three international experts . Based on the retrospective staging result and size , proportions of assignment to WHO-IWGE recommended treatment modalities were estimated . The socio-demographic characteristics of the study population receiving treatment at the three state hospitals show some interesting features . Around 50% of the patients are below 15 years of age . In Kazakhstan and Kyrgyzstan , countries in the same region as Mongolia and with a similar pastoral lifestyle , also reported high proportion of children among the surgical cases [3] . Equal proportions of male and female patients suggest that , understandably , the infection risk is equal with CE transmitted in a food borne dog faecal-human oral cycle . Distance to the secondary hospital is a relevant factor for access to specialized health care in all LICs and most MICs [32 , 33] . About 40% of the surgical patients had to travel at least 100 km to reach the secondary hospitals . Besides the geographic barrier other factors might contribute to underreporting but currently no data are available . 80% of the patients are living in a “yurt” which suggest that these patients are exposed to the combination of poor infrastructure , poor water and sanitation and frequent contact with watch-dogs and their faeces [34 , 35] . A significant proportion of patients presented with non-specific symptoms , around 20% with abdominal pain corresponding to 29% of the patients with abdominal cysts . Around 16 . 6% , 8 . 5% and 6 . 9% of all patients had cough , chest pain and dyspnoea , respectively . This amounts to 50% , 32% , and 14% , respectively , of patients with lung cyst . These results are in line with the clinical experience that most patients present with non-specific symptoms and signs [36] . Fever , observed in 22 . 3% of all admissions , may , however , indicate that some patients had complication such as a cysto-biliary fistula with secondary bacterial infection of the cyst or cholangitis associated with biliary obstruction due to spillage of cyst content into the biliary tree; the latter also causes abdominal pain [37] . Similarly , patients with lung cysts may have had fever due to pneumonia following bronchial compression caused by expanding cysts or secondary bacterial infection of the residual cavity after the cyst content has been expectorated via a cysto-bronchial fistula . Both complications are associated with cough and dyspnoea [38] . Care should be exercised , however , to not over interpret retrospectively non-specific signs and symptoms such as fever , documented in medical records . Most patients had only a single cyst in abdominal organs of which almost 50% had a diameter equal or smaller than 5 cm . This alone casts doubts on the indication for major surgery . If uncomplicated , these cysts would—following the WHO-IWGE expert consensus—either fall in the medical treatment group , if active ( CE1 to CE3 ) , or the watch & wait group , if inactive ( CE4 and 5 ) . Only 40 reports of the 182 abdominal cysts examined by ultrasound spelled out “hydatid cyst” as the US diagnosis , without , however , mentioning accepted US criteria and without an attempt to stage with the WHO-IWGE or Gharbi classification . The most exciting part of this data set was the unique opportunity to review and retrospectively stage 138 US imaging photos of 84 patients by three international experts to compare current practice in Mongolia with WHO recommended treatment modalities [20] . The distribution of WHO cyst stages retrospectively analysed from a subset of patients treated between 2008 and 2015 at the three state hospitals in Mongolia showed proportions of 0 . 59 , 0 . 01 , 0 . 19 , 0 . 08 , 0 . 03 and 0 . 11 for CE1 , CE2 , CE3a , CE3b , CE4 , and CL , respectively ( see Fig 3 ) . Given the relatively high number of categories , the observed raw agreement of about 80% and Kappa coefficients of close to 0 . 6 indicate that the method appears to be generally valid but with room for improvement . A similar result was found in a recent study assessing interrater-agreement of the WHO cyst classification based on 2-D US images . The authors emphasized that an improvement can be achieved when non-static imaging ( video recording etc . ) is incorporated in future studies [39] . Assignment of patients to the WHO-IWGE recommended treatment modalities takes into account cyst size in addition to cyst stage . Merging the cyst sizes with the retrospective WHO cyst staging of the study population provides an insight into deviations of current practice in Mongolia from the WHO-IWGE expert consensus . Of particular significance for patients regarding unnecessary treatment risks and for the health care services with respect to avoidable treatment costs is the fact that 3 . 3% of abdominal cysts would have not warranted any treatment at all since they were already in an inactive stage ( CE 4 ) . Following the WHO-IWGE expert consensus they would have been submitted to the watch & wait approach with a very high probability of no need for further treatment [28 , 29] . 52 . 5% of active abdominal cysts ( CE1 to CE3 ) with a diameter of 5 cm or smaller would have been submitted to medical treatment following the WHO-IWGE expert consensus [20 , 40] . This draws attention to the fact that availability of albendzole , the preferred benzimidazole for CE therapy , is hugely lacking in Mongolia . Currently , the price of albendazole is very high with approximately USD 2 per 400mg tablet . Albendazole is mostly sold in pharmacies in cities , which also limits access . Access to albendazole is a very much debated issue in the care for the neglected tropical disease echinococcosis in neglected populations [41] . In addition to albendazole cost , 10–15% of the hospital admission fee of public hospital is paid by the patients and the remaining cost is covered by the national health system in Mongolia [42] . However , there are many other costs including informal fees to clinicians and advanced diagnostics increasing the economic burden CE patients have to carry . Almost 26% of the patients assessed would have been allocated to percutaneous treatment ( PT ) . PT options are generally underused and are not carried out in Mongolia for CE management due to a lack of trained personnel . Introducing PT into Mongolia should be considered because it carries less risks for the patients , reduces treatment cost and length of hospital stay . A study in Bulgaria showed similar deviations from best practices as recommended by WHO-IWGE expert consensus[43] . There are several limitations of the study . The data were extracted retrospectively from patient files . The fact that in Mongolia CE patients are being treated exclusively at the three state hospitals with high standards of documentation and archiving compensated partly for this shortcoming . Also , cyst staging was retrospectively performed on the basis of 2-D ultrasound photos . Our interrater-agreement of retrospective cyst staging , however , gives confidence that the staging result provides an acceptable estimate of the distribution of cyst stages seen at the three national hospitals . Identifying complicated cysts is difficult in retrospective studies . In some instances we could suspect that a cyst was complicated by combining various pieces of available retrospective information ( e . g . fever , abdominal pain plus US cyst features suspicious of secondary bacterial infection of a cyst ) . This , however , is all too vague and would be an over interpretation of retrospective data . We thus did the analysis “as if” the cysts of the US images classified were uncomplicated . This may have resulted in an overestimate of the non-surgical treatment modalities . In conclusion , our study demonstrates It is recommended
|
Cystic Echinococcosis ( CE ) is a zoonotic disease , commonly known as dog tapeworm . The disease is distributed globally and predominantly affects rural populations with limited access to health care . Following the expert consensus of the WHO-Informal Working Group on Echinococcosis ( WHO—IWGE ) patients with uncomplicated cysts are assigned on the basis of WHO cyst classification to four treatment modalities: medical ( benzimidazoles ) , percutaneous , surgical treatment , and ‘watch & wait’ . In Mongolia , one third of the population practices nomadic farming . These populations are heavily affected by CE . However , cyst staging and WHO-IWGE recommendations are not implemented and patients referred to the three national treatment centres receive surgical treatment . This exposes a large proportion of patients to an unnecessary high risk approach who could be treated–depending on cyst stage—with benzimidazoles , percutaneously or observed ( watch & wait ) . We reviewed the hospital records of patients with CE and admitted between 2008 and 2015 to the three national CE treatment centres , retrospectively staged the cysts and assigned the patients to the four WHO-IWGE recommended treatment modalities . We found a high proportion of patients in the study population who would have most likely benefitted from non-surgical treatment options .
|
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"Abstract",
"Introduction",
"Materials",
"and",
"method",
"Results",
"Discussion"
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"cystic",
"echinococcosis",
"medicine",
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"mongolia",
"benzimidazoles",
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] |
2018
|
Patients with cystic echinococcosis in the three national referral centers of Mongolia: A model for CE management assessment
|
In some transmission foci of Leishmania infantum in Brazil , Lutzomyia cruzi could be considered the main vector of this pathogen . In addition , L . cruzi is a permissive vector of L . amazonensis . Its geographical distribution seems to be restricted and limited to Cerrado and Pantanal biomes , which includes some areas in Brazil and Bolivia . Considering that predicting the distribution of the species involved in transmission cycles is an effective approach for assessing human disease risk , this study aims to predict the spatial distribution of L . cruzi using a multiscale ecological niche model based in both climate and habitat variables . Ecological niche modelling was used to identify areas in South America that are environmentally suitable for this particular vector species , but its presence is not recorded . Vector occurrence records were compiled from the literature , museum collections and Brazilian Health Departments . Bioclimatic variables , altitude , and land use and cover were used as predictors in five ecological niche model algorithms: BIOCLIM , generalised linear model ( logistic regression ) , maximum entropy , random forests , and support vector machines . The vector occurs in areas where annual mean temperature values range from 21 . 76°C to 26 . 58°C , and annual total precipitation varies from 1005 mm and 2048 mm . Urban areas were most present around capture locations . The potential distribution area of L . cruzi according to the final ecological niche model spans Brazil and Bolivia in patches of suitable habitats inside a larger climatically favourable area . The bigger portion of this suitable area is located at Brazilian States of Mato Grosso do Sul and Mato Grosso . Our findings identified environmentally suitable areas for L . cruzi in regions without its known occurrence , so further field sampling of sand flies is recommended , especially in southern Goiás State , Mato Grosso do Sul ( borders with Mato Grosso , São Paulo and Minas Gerais ) ; and in Bolivian departments Santa Cruz and El Beni .
World Health Organization data show that vector-borne diseases represent more than 17% of the global burden of all infectious diseases , causing more than 1 million deaths per year [1] . The dynamics and intensity of transmission of pathogens exhibit significant spatial and temporal heterogeneity , especially in vector-borne diseases [2 , 3] . Part of this lies in the fact that vector-borne diseases are climate-sensitive , because the species involved in their complex cycles of transmission are highly dependent on climatic variables [4–6] . In addition , there is evidence that ongoing climate change is affecting , and will continue to affect the distributions and burdens of these infections [4] . Predicting the distribution of the species involved in transmission cycles is an effective approach for assessing human disease risk . The spatial distribution of a species is a reflection of its ecology and evolutionary history , influenced by specific factors depending on the spatial scale [7–9] . Species distributions are hierarchically structured in space , with climatic variables limiting distributions at coarse scales , habitat variables gaining importance as the scale narrows , and biotic interactions affecting distributions at microscales [9 , 10] . Leishmaniases are climate-sensitive diseases transmitted to humans by the bites of female sand flies ( Diptera: Psychodidae ) infected with Leishmania parasites . The distribution and behaviour of the species involved in the transmission cycle , especially of the sand fly vectors , are strongly affected by climatic variables , such as precipitation , temperature and humidity [11 , 12] . In Latin America , Lutzomyia longipalpis is the main vector of Leishmania infantum , the causative agent of visceral leishmaniasis ( VL ) [13 , 14] . Due to its great epidemiological importance and wide distribution , L . longipalpis has been the object of different studies on the effects of environmental variables and anthropogenic environmental changes on its ecology [15–20] . Some of these studies have used ecological niche modelling to estimate the geographic distribution of this vector and predict its expansion or contraction under climate change scenarios [18–20] . However , in some transmission foci of L . infantum in Brazil , the sand fly L . cruzi may be acting as the main vector of this protozoan due to absence of L . longipalpis [21–25] . Although there were suspicions that L . cruzi was the vector responsible for the transmission of L . infantum since the 1980s [21 , 22] , only recently this phlebotomine sand fly was confirmed as a proven vector of L . infantum [25] , based on the Killick-Kendrick criteria [26] , and as a permissive vector of L . amazonensis [25] . Lutzomyia cruzi can also act as an alternative vector in the location where both sand flies occur in sympatry [19] . In Brazil , the geographical distribution of L . cruzi seems to be restricted and limited to Cerrado and Pantanal biomes [23 , 24 , 27–29] . There are also reports of the presence of L . cruzi in Bolivia [30] . Recent evidences suggest introgressive hybridization between L . cruzi and L . longipalpis based on molecular analyses [31 , 32] , reinforcing the idea that they are sibling species . Even though L . cruzi has medical and epidemiological relevance , until now there are few published reports focused on the ecology and effects of environmental variables on the distribution and abundance of this sand fly [19 , 21 , 27 , 28 , 33 , 34] . A recent study applied ecological niche models to predict the distributions of L . longipalpis and L . cruzi in Brazil , but models were based on both species together , thus making it impossible to evaluate their distributions separately [19] . A further assessment of the potential distribution of L . cruzi is needed , especially for those areas where L . longipalpis does not occur . Considering that ecological niche modelling represents a tool for monitoring disease trends in natural ecosystems and identify opportunities to mitigate the impacts of climate-driven disease emergence [35] , this report aims to predict the spatial distribution of L . cruzi using a multiscale ecological niche model based in both climate and habitat variables . Besides contributing to the study of the ecological niche of L . cruzi , our goal includes the identification of specific areas in Brazil and neighbour countries that are environmentally suitable for this particular vector species , but its presence is not recorded .
We conducted a literature review to compile records of the presence of L . cruzi . On July 2016 , the online databases PubMed , ISI , Scopus and SciElo were searched for relevant studies using the terms ‘Psychodidae’ and ‘Lutzomyia’ . After removal of duplicate references , the papers were scanned for mention of L . cruzi captures , and all records compiled in a Microsoft Excel database with the available description of the capture sites ( country , state/province/department , district/municipality , and locality ) . Additionally , the sand fly distribution lists compiled by Martins et al . [36] , Young & Duncan [37] , Aguiar & Medeiros [38] and Galati [39] were also consulted to ensure known presence records were not missed . As females of L . cruzi and L . longipalpis are morphologically indistinguishable [37 , 39] , only the records with species identification based on captured males were considered as valid . The main sand fly collections in Brazil were physically visited to search for additional unpublished records of the species . These included Centro de Pesquisas René Rachou ( FIOCRUZ , Belo Horizonte , assisted by Dr J . D . Andrade-Filho ) , Instituto Butantan ( IBUT , São Paulo , assisted by Dr R . Moraes ) , Instituto Evandro Chagas ( IEC , Belém , assisted by Dr T . Vasconcelos dos Santos ) , Instituto Oswaldo Cruz ( FIOCRUZ , Rio de Janeiro , assisted by Dr J . M . Costa ) , Instituto de Pesquisas da Amazônia ( INPA , Manaus , assisted by Dr R . Freitas and Dr M . L . Oliveira ) , Universidade de São Paulo/Faculdade de Saúde Pública ( USP , São Paulo , assisted by Prof . M . A . Sallum ) , and Universidade de São Paulo/Museu de Zoologia ( USP , São Paulo , data provided by Dr A . J . Andrade ) . The online databases SpeciesLink ( http://splink . cria . org . br/ ) and GBIF ( https://www . gbif . org/ ) were also searched for presence records on February 2018 . All presence records were associated with geographical coordinates ( latitude and longitude ) and classified in three levels according to their spatial precision: High level: coordinates of the capture site were available in the original source of the record; Medium level: coordinates were obtained at Google Earth ( https://earth . google . com/ ) by visually searching for the capture site when its description was available in the source of the record; Low level: coordinates of the municipality/district centre were obtained at Google Earth when the source of the record had no information on the capture locality , but only at this administrative level . We excluded from the database those records with information only at state/province/department or country levels . The occurrence database thus contained the following information for each record: country , state/province/department , municipality/district , locality , year of capture , longitude , latitude , spatial precision , reference ( S1 Table ) . The year of capture and spatial precision were used to split the records in separate sets for model training and validation , in accordance with the spatial and temporal precision of the variables used in the ecological niche models . As some modelling algorithms require presence/absence data , we randomly sampled pseudo-absences in the space outside the environmental domain favourable for the species [40] but restricted to a maximum distance of 1000 km from the presence records . This environmental domain was estimated using the bioclimatic envelope model BIOCLIM [41] . The number of pseudo-absences was 10 times the number of presence records for each model run . We ran the pseudo-absence sampling procedure once for each modelling step ( climate and habitat models ) . These procedures were performed in R platform [42] , using the packages raster [43] and dismo [44] . We obtained historical ( 1970–2000 ) climate data for South America at WorldClim ( version 2 ) , an online database of 19 bioclimatic variables derived from monthly averages of temperature and precipitation [45] . For the climate model , we obtained the variables at the spatial resolution of 2 . 5 minutes ( approximately 5x5km per pixel ) , which is an adequate coarse resolution where climate influences species distributions [9] . We selected a subset of the original 19 variables by running a Pearson correlation matrix and retaining only the six less correlated ones ( r < 0 . 6 ) . The final set of climate variables used to run the climate model consisted of annual mean temperature ( BIO1 ) , mean diurnal range of temperature ( BIO2 ) , temperature seasonality ( BIO4 ) , annual precipitation ( BIO12 ) , precipitation seasonality ( BIO15 ) and precipitation of warmest quarter ( BIO18 ) [45] . Remote sensing variables representing vegetation and topography were used as potential habitat indicators of L . cruzi . The Enhanced Vegetation Index ( EVI ) , a product of the MODIS ( Moderate Resolution Imaging Spectroradiometer ) sensor was obtained at NASA’s EarthExplorer website ( https://earthexplorer . usgs . gov/ ) and processed with the MODIS Reproject Tool ( https://lpdaac . usgs . gov ) . Monthly EVI data for 2000–2015 was obtained for the study area at the spatial resolution of 1 km . A Principal Component Analysis ( PCA ) was performed in order to reduce collinearity in the dataset . We retained the first five components , because they represented 99% of the cumulative variance in the monthly EVI dataset . Altitude , aspect and slope variables were derived from a digital elevation model from SRTM ( Shuttle Radar Topographic Mission ) and obtained at AMBDATA , an online database of environmental layers maintained by INPE ( Instituto Nacional de Pesquisas Espaciais , http://www . dpi . inpe . br/Ambdata/ ) . The eight habitat variables were resampled to 1 km2 resolution by bilinear interpolation and cropped at the extension of the study area , which was determined by the results of the climate model . All variable processing was done using the R packages raster and RSToolbox [46] . To describe the ecological niche of L . cruzi , the values of the main bioclimatic variables and altitude in the location of each presence record were extracted . We also assessed the types of land use and cover where the vector occurs using data from MapBiomas ( http://mapbiomas . org/ ) , a high-resolution database of annual land use and cover for Brazil . Each presence record was associated with the land use and cover data of the same year of capture . We excluded the records with low spatial precision at this step , because they do not match the native resolution of the MapBiomas data layers ( 30x30m ) . The percentage of each land cover type was extracted in a 500 m buffer created on each presence record . Analyses were performed in R package raster . There are several algorithms available for developing ecological niche models , which produce different results and predictive maps even when running with the exact same input data [47–49] . There is not a consensus on the literature about one single best algorithm , thus researchers are encouraged to apply different methods to overcome this methodological uncertainty in their model predictions [50 , 51] . Therefore , we applied the same five modelling algorithms as McIntyre et al . [52] , which had satisfactory results in niche models of Brazilian sand flies: BIOCLIM , Generalised Linear Models ( GLM , logistic regression ) , Maximum Entropy ( MaxEnt ) , Random Forests ( RANFOR ) , and Support Vector Machines ( SVM ) . For a short description of the five algorithms , see McIntyre et al . [52] . To reduce spatial auto-correlation , we randomly selected a subset of species occurrences which were at least 10 km apart from the nearest record . We ran all models with their default settings on the dismo package of R platform . In order to use the whole set of unique presence/pseudo-absence records in model training , we used 10-fold cross-validation , with 10% of the records retained for internal model testing . For internal evaluation , we used the True Skill Statistic ( TSS ) , which ranges from -1 to +1 , with +1 indicating complete agreement between predicted and observed records , and values close to and below 0 representing models no better than random predictions [53] . Model outputs with TSS scores lower than 0 . 6 were discarded . Outputs with the highest TSS scores from each algorithm were overlaid and consensus areas extracted by the majority ensemble rule [54] . Final maps were produced based on the consensus between the five modelling algorithms . Uncertainty was mapped by calculating the standard deviation of pixel values from model outputs produced by each of the five algorithms . Because of the great difference in spatial precision of the species records , we ran two models with adequate settings for each spatial scale ( Table 1 ) . On a first step , we ran a climatic suitability model at the coarse spatial resolution of the climatic variables ( 2 . 5 minutes ) . For this model we used the set of L . cruzi records captured between 1970 and 2000 with the six bioclimatic variables . Model calibration area was restricted to a hypothesised accessible area of 1000 km around all known species records [55] . As we were aiming for a more conservative output for this first model , we chose the “zero omission” threshold rule [56] to convert model outputs into binary predictions . With this threshold rule , all presence records are retained inside the predicted area of occurrence , thus maximizing sensitivity ( the proportion of correctly predicted presences ) , but sacrificing specificity ( the proportion of correctly predicted absences ) . The resulting binary map of climatic suitability was then used to limit the calibration area of the habitat suitability model , which was based on the vegetation and topography variables at higher scale ( Table 1 ) . As we narrowed the spatial resolution , at this second stage we only used the presence records classified as precision levels high and medium , with capture years matching the variables ( 2004–2013 ) . The same model settings were applied , except for the threshold rule to produce binary predictions . For the final models , we chose threshold values that maximised both sensitivity and specificity [56] . With this , the final outputs become more objective , minimising both false positives and false negatives . External validation of both models was done with independent records , separated from model training ( Table 1 ) . Model significance was evaluated by binomial probabilities calculated over binary outputs , and model performance was evaluated by sensitivity ( number of correctly predicted presences divided by total number of records ) . Resulting model outputs were exported to QGIS software version 3 . 0 . 1 [57] for preparation of final maps .
The compiled database included 116 presence records of L . cruzi with associated geographical coordinates ( S1 Table ) . Most records of the vector are in Mato Grosso and Mato Grosso do Sul Brazilian states , with a single record in State of Goiás and one in Bolivia , in Santa Cruz Department ( Fig 1 ) . Most of the records have low spatial precision ( 68% ) , followed by records with medium ( 25% ) and high ( 7% ) precision levels ( Fig 1 ) . The vector occurs in areas where annual mean temperature values range from 21 . 76°C to 26 . 58°C , and annual total precipitation varies from 1005 mm and 2048 mm ( Table 2 ) . In these areas , temperatures in the coldest month of the year reach 11 . 3°C and the warmest month can reach as high as 34 . 3°C ( Table 2 ) . Extremes of monthly precipitation range from 1 mm to 157 mm ( Table 2 ) . In terms of elevation , most records of L . cruzi occur around 270 m above sea level , with a minimum of 86 m and up to 741 m ( Table 2 ) . Nine different types of land use and cover were detected around records of L . cruzi ( Fig 2 ) . Urban areas were most present around capture locations ( 64% ) , followed by open forests ( 10% ) , dense forests ( 5% ) , pasture areas ( 4% ) , and open fields ( 3% ) . The remaining land use and cover types were identified only eventually and are presented in Fig 2 . The TSS scores of the climatic suitability models ranged from 0 . 48 to 1 ( 8% were discarded with TSS < 0 . 6 ) ; and in the final models , from 0 to 1 ( 22% with TSS < 0 . 6 ) . Outputs produced by different algorithms varied considerably ( S1 Fig ) , but consensus areas showed less uncertainty ( S2 Fig ) . The climatic suitability model performed significantly better than random predictions ( binary probabilities , p = 0 . 00498 ) and had sensitivity of 0 . 92; while the final ecological niche model was also significant ( binary probabilities , p < 0 . 001 ) with a sensitivity of 0 . 72 . The coarse resolution model predicted an area of climatic suitability for L . cruzi that occupies the Central-West region of Brazil , extending westwards into Bolivia ( blue and green areas in Fig 3 ) . However , when considering the habitat variables at high resolution , the results of the final ecological niche model show that the area with suitable climate and habitat conditions for L . cruzi is much smaller , occupying 38 . 7% of the climatically suitable regions ( only green areas in Fig 3 ) . The potential distribution area of L . cruzi according to the final ecological niche model spans Brazil and Bolivia in patches of suitable habitats inside climatically favourable areas . The bigger portion of this suitable area is located at Brazilian States of Mato Grosso do Sul and Mato Grosso , where most known records of the species are located ( Fig 4 ) . Four known records of the vector fell out of the predicted area: one in Bolivia ( El Carmen ) , and three in Mato Grosso State ( Nova Canaã do Norte , Colíder and Rondolândia ) ( see arrows in Fig 4 ) . Suitable areas without known occurrence of the vector are located in Bolivian departments Santa Cruz and El Beni; southern State of Goiás in Brazil , as well as northern Mato Grosso do Sul and in border areas with São Paulo and Minas Gerais States ( see circles in Fig 4 ) .
This study represents the first report of the predicted spatial distribution of L . cruzi using a multiscale ecological niche model based on both climate and habitat variables , applying different algorithms for the same data . The final ecological niche model comprises mainly areas of the Central-West region of Brazil and some parts of East Bolivia . The low number of occurrence records and their low spatial precision were limitations of the modelling process , being the most probable reason for the low TSS scores of a minority of model outputs . We reduced these limitations by discarding outputs with TSS < 0 . 6 in the final models and subsampling the records by spatial precision , thus running models at appropriate spatial scales . Models produced by different algorithms had great spatial variability , as expected [47–51] . Uncertainty mapping provided more confidence to the areas predicted as environmentally suitable by most algorithms . Our results describe the ecological niche of L . cruzi in terms of climate , altitude and vegetation/land cover where the species occurs . The climatic values recorded at capture locations of L . cruzi are in accordance with the Köppen’s climate classification for most parts of the Central-West region of Brazil: tropical zone with monsoon period ( Am ) and with dry winter ( Aw ) [58] . Ecological studies that evaluated the linear relationship between L . cruzi abundance and climatic variables showed no significant statistical association [24 , 27 , 59] . However , it was observed that the species occurs throughout the year , with population peaks in the months with high temperature [21 , 24 , 27 , 59] . These previous studies considered both male and female specimens of L . cruzi and reported data from regions where L . longipalpis has not been detected , except in Corumbá city [60] . However , L . longipalpis was reported in Corumbá only once [60] . Successive sand fly surveys performed by different research groups were unable to confirm the presence of L . longipalpis in this area [21 , 27 , 28 , 61 , 62] . It should be noted that the occurrence sites of this vector have annual mean temperature relatively constant and annual precipitation ranging from moderate to high ( Table 1 ) . Altitude data show that most records of L . cruzi occur in the Central and Southern plateau and in the Pantanal plains of Brazil . This observation allows us to hypothesize that the distribution of L . cruzi may be limited , among other factors , by altitude , since there is no record of the species in coastal regions . Cerrado and Pantanal are the biomes where L . cruzi mostly occurs , with few observations in southern Amazon . Our results of the percentage of land use and cover types demonstrate that L . cruzi is present predominantly in urban areas . However , this does not necessarily mean that L . cruzi prefers urban areas , because most of the sand fly samplings where performed in these areas or in peri-urban localities . Nevertheless , considering that L . cruzi and L . longipalpis are sibling species [31 , 32] , the probable preference of L . cruzi for urbanized environments would not be surprising . As an example , data from the city of Corumbá , State of Mato Grosso do Sul , showed that in the 1980s the greatest abundance of L . cruzi was in native forest areas with low human interference [21] . Almost 30 years later a lower abundance was observed in the city’s peripheral forests , while in the urban area , the vector increased its abundance [27 , 28] . Similar situation was found in the city of Camapuã ( Fernandes et al . , 2017 ) , also located in Mato Grosso do Sul State . No significant association was found between the absolute frequencies of L . cruzi and percentage of vegetal coverage and three spectral indices ( normalized difference vegetation index , NDVI; normalized difference water index , NDWI; impervious surface areas , ISA ) [27] . The predicted area of occurrence from our models corroborates a previously published distribution model of L . cruzi that was restricted to the Central-West region of Brazil [34] . The predicted area of occurrence of L . cruzi cannot be determined in Andrade-Filho et al . [19] , but the general distribution of the species records used in the models is similar . Neither of the two studies give information on the spatial precision of the presence records . Positional uncertainty in species occurrence records have direct effects on ecological niche model predictions [63] and must be considered especially when developing models from secondary data . The vast majority of information available on species occurrence databases from Brazil is restricted to the municipal level . This can lead to serious bias in model predictions , as municipalities in Brazil have widely different areas , ranging from approximately 3 km2 to 160 , 000 km2 [64] . It is crucial that the spatial precision of species records match the spatial resolution of the models [65] . With our multiscale approach , we were able to develop models that incorporated the records with low spatial precision , thus reducing positional bias in our predictions . In addition , the spatial thinning process reduced the spatial auto-correlation bias . The four records that were not successfully predicted by the final models had low spatial precision , so it is not possible to determine the exact location of the species occurrence . Our models predict occurrence areas of L . cruzi in Bolivia , where the vector was found in chicken coops and pigsties in the town of El Carmen , Santa Cruz District [30] . This is the only published record from the country , and according to our predictions , L . cruzi is probably present , but so far undetected in many Bolivian regions . Both visceral and cutaneous leishmaniases are endemic in Bolivia with occurrence of L . infantum , L . braziliensis and L . amazonensis [66–69] . However , there are few reports of ecological studies of phlebotomine fauna in this country , so further field sampling of sand flies is recommended . According to the Brazilian Ministry of Health [70] , except for the southwest Minas Gerais State , in the confluence region between the Grande river and the Paranaiba river ( boundary with the states of São Paulo , Goiás and Mato Grosso do Sul ) , there are autochthonous human cases of VL reported in almost all the predicted suitable areas for L . cruzi . However , in many regions there are also the presence of L . longipalpis and/or L . cruzi [19] . A particular region , predicted as favorable to the vector , deserves to be highlighted due to the presence of autochthonous VL cases [70] and absence of L . longipalpis records according to Andrade et al . [19]: Brazil-Bolivia border in the extreme southwest Rondônia State , in the area adjacent to the municipality of Pimenteiras do Oeste . In Bolivia , few VL human cases have been reported and the disease appears to be restricted to Yungas region in the Beni department [71] . In Brazil , although the vector’s occurrence is widely known in State of Mato Grosso , some municipalities in Mato Grosso do Sul and the southern region of Goiás remain to be investigated . The border region between the states of Minas Gerais , São Paulo and Mato Grosso do Sul is also a predicted area of occurrence according to our models , but without known records of L . cruzi . This region , where the Paraná river basin divides the states , has many records of L . longipalpis , especially on the east side of the river [19] . To our knowledge , there is not a published study on the ecological interactions between L . cruzi and L . longipalpis that could justify their separation in space . Further studies on the phylogeography of both species might investigate if the Paraná river basin could have been a relevant dispersion barrier for their speciation . In conclusion , our results contribute to the study of the ecology and distribution of an important vector of VL . The disease is being increasingly reported in urban and peri-urban areas of Brazil , especially because of the geographical expansion of its main vector , L . longipalpis [72] . Given the genetic proximity of this vector with L . cruzi [31 , 32] and its absence in specific VL foci , our predictive maps also indicate potential risk areas of this disease associated with L . cruzi . It is crucial that entomological surveillance activities are performed in these areas , especially where the vector has not been detected so far .
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Leishmaniases are vector-borne diseases caused by Leishmania parasites which are transmitted to humans by the bites of infected female sand flies . The sand fly Lutzomyia cruzi is the vector of Leishmania infantum , the causative agent of visceral leishmaniasis ( VL ) , in some specific areas of Brazil . The transmission of Leishmania species is climate-sensitive and involves complex ecological interactions between parasites , vectors and hosts . Considering that the vectors are strongly sensitive to climatic and environmental conditions , studies of their geographical distribution are important for understanding the eco-epidemiology of VL , as well as for the planning of disease control actions . The ecological niche of a species is a critical determinant of its distribution . Therefore , we conducted a study to evaluate and model the ecological niche of L . cruzi and predict susceptible areas to its occurrence in South America . The potential distribution area of L . cruzi according to the final ecological niche model spans Brazil and Bolivia in patches of suitable habitats inside climatically favourable areas . Cerrado and Pantanal biomes comprise the biggest portion of this suitable area which includes three Brazilians states , and some areas in Bolivia . Our findings reinforce the importance of conducting more ecological studies on sand fly fauna .
|
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"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
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2018
|
Ecological niche modelling and predicted geographic distribution of Lutzomyia cruzi, vector of Leishmania infantum in South America
|
In Uganda , Rhodesian sleeping sickness , caused by Trypanosoma brucei rhodesiense , and animal trypanosomiasis caused by T . vivax and T . congolense , are being controlled by treating cattle with trypanocides and/or insecticides . We used a mathematical model to identify treatment coverages required to break transmission when host populations consisted of various proportions of wild and domestic mammals , and reptiles . An Ro model for trypanosomiasis was generalized to allow tsetse to feed off multiple host species . Assuming populations of cattle and humans only , pre-intervention Ro values for T . vivax , T . congolense , and T . brucei were 388 , 64 and 3 , respectively . Treating cattle with trypanocides reduced R0 for T . brucei to <1 if >65% of cattle were treated , vs 100% coverage necessary for T . vivax and T . congolense . The presence of wild mammalian hosts increased the coverage required and made control of T . vivax and T . congolense impossible . When tsetse fed only on cattle or humans , R0 for T . brucei was <1 if 20% of cattle were treated with insecticide , compared to 55% for T . congolense . If wild mammalian hosts were also present , control of the two species was impossible if proportions of non-human bloodmeals from cattle were <40% or <70% , respectively . R0 was <1 for T . vivax only when insecticide treatment led to reductions in the tsetse population . Under such circumstances R0<1 for T . brucei and T . congolense if cattle make up 30% and 55% , respectively of the non-human tsetse bloodmeals , as long as all cattle are treated with insecticide . In settled areas of Uganda with few wild hosts , control of Rhodesian sleeping sickness is likely to be much more effectively controlled by treating cattle with insecticide than with trypanocides .
Across sub-Saharan Africa , a variety of Trypanosoma spp transmitted by tsetse flies ( Glossina spp ) cause human and animal trypanosomiases . There are >10 , 000 cases/year of Human African Trypanosomiasis ( HAT ) [1] with an estimated burden of ∼1 . 3 million Disability Adjusted Life Years ( DALYs ) [2] and economic losses in excess of $1 billion due to human and animal trypanosomiasis [3] . While interventions can be directed against the vector or the parasite , emphasis has usually been on the use of drugs to treat the disease both in humans and in livestock . While the importance of treating cases , especially human ones , cannot be overstated , several advances in our understanding of tsetse biology and ecology , and improvements in the cost-effectiveness of tsetse control [4] , [5] , have revived interest in that approach to disease management . First , the use of satellite navigation as an aid to nocturnal aerial spraying , spraying much larger areas than previously , and protecting the sprayed areas with odor-baited targets , has provided impressive results , such as the eradication of G . m . centralis from Botswana [6] . Second , the demonstration of the importance of odor for host location in some species of tsetse provided a means of attracting them to insecticide-treated targets and , by killing the flies , provided control of cattle and human trypanosomiasis [7]–[10] . Third , the particularly low reproductive rate in tsetse made it possible to use as few as four such targets per square kilometer to eliminate isolated populations of G . pallidipes Austen and two sub-species of G . morsitans [9] , [11] . The method is cheaper than aerial spraying and more environmentally friendly than insecticidal ground spraying , game destruction or habitat clearance [11] . Issues of cost , logistics , government commitment , and theft of materials have meant , however , that the approach has not been used in large-scale control programs except in Zimbabwe and in the Western Province of Zambia [11] , [12] . Part of the reason for this limited use stems from the fact that , simultaneously with the development of insecticide-treated target technology , it was realized that tsetse control could be achieved equally effectively by applying insecticide to the very livestock - generally cattle - off which the tsetse were feeding . This approach has been used very successfully in areas where tsetse feed predominantly on cattle [13] , [14] , though it would be less effective in areas where – as in large parts of Zimbabwe and Tanzania – the predominant food source for the tsetse are wild mammals . Whereas insecticide-treated cattle ( ITC ) can be used in operations aimed at eliminating tsetse populations , animal trypanosomiasis can also be reduced to low levels even where tsetse populations persist [15] . It is , of course , relief from cattle disease – rather than issues of tsetse fly control versus eradication – which most interests stockholders in tsetse areas and which can be used to interest the stockholder in becoming actively involved in tsetse and trypanosomiasis control [13] . Recent advances in our understanding of the feeding behavior of tsetse on cattle have led to even cheaper methods of tsetse control where the insecticide is applied to the body regions and/or individual animals on which most tsetse feed [16] , [17] . This restricted application of pyrethroids is comparable in its cost and simplicity to the widespread use of trypanocides by farmers to prevent or cure trypanosomiasis in their livestock [16] . There are several possible reasons why these advances in affordable , low-technology tsetse control have not , as yet , played a significant role in efforts against HAT . First , there is an imperative to find and treat infected humans and livestock and this approach is thus the foundation of all efforts against the disease . Second , the odor-baited devices used so effectively in efforts against animal trypanosomiasis [10] are less effective against the important vectors of HAT [18] , [19] . This poor efficacy is probably related , in part , to the distinctions between the host relationships of the various tsetse species . The important vectors of animal trypanosomiasis , i . e . , the Morsitans-group tsetse , feed almost exclusively on mammals ( e . g . warthog , kudu , buffalo and cattle ) which they locate largely by odor , whereas the Palpalis-group species , which are the main vectors of HAT , are less responsive to odors and include reptiles and birds in their diet . For instance , between 50 and 90% of meals taken by Glossina fuscipes fuscipes are from monitor lizard [20] which themselves do not support all the trypanosome species infective to mammals [21] . In this paper , we investigate the theoretical effects of two different approaches to trypanosomiasis control , both of which have already been shown to be of interest to small-scale stockholders in resource-limited settings [22] . First we consider the effect of treating animals with trypanocides , which prevent the disease without having any insecticidal effect . Second , we consider the use of the ITC method , which has no direct trypanocidal effect but which increases mortality in the vectors . We limit our study to the situation typical of eastern and southern Africa , where Trypanosoma vivax , T . congolense and T . brucei rhodesiense occur in livestock and wildlife - and where the last-named parasite also causes “Rhodesian” sleeping sickness in humans [23] , [24] .
We generalize the Rogers [25] two-host model for trypanosomiasis to one where a single species of tsetse can feed off any finite number ( n ) of vertebrate hosts . The formal proof that Rogers' model can be generalized in this way is given in the Supporting Information ( Text S1 ) . The overall basic reproductive rate ( R0 ) of a trypanosome species is given by: ( 1 ) where D = 1 for T . vivax and T . congolense andfor T . brucei , and where the following definitions apply: R0 = overall basic reproductive rate; formally , in a completely susceptible population , the number of trypanosome-infected tsetse arising from each infected fly; c = P ( infected blood meal gives mature infection in fly ) ; u = Daily mortality rate of the flies; T = Incubation period in tsetse ( all time units are days ) ; ai = pi/d , where pi = Proportion of tsetse bloodmeals from species i , d = Duration of feeding cycle in flies; bi = P ( infected fly bite produces infection in species i ) ; mi = V/Ni , where V = Number of tsetse , Ni = Number of animals of species i , 1/ri = Duration of infection in species i . The parameter D differs between T . brucei and the other species of trypanosomiasis because it is assumed that tsetse can only be infected with T . brucei when they take their first bloodmeal . It is assumed that the probability of infection for the other species is independent of a fly's feeding history: to distinguish this situation Rogers also replaced c with c′ for T . brucei [23] . The default values for the parameters of his two-host model for Rhodesian sleeping sickness [23] are copied here for convenience , in Tables 1 and 2 . We extend the model to consider cases where , in addition to humans and domestic stock ( cattle ) , the following vertebrate species are present: ( 1 ) wild mammals; ( 2 ) monitor lizards; ( 3 ) wild mammals and monitor lizards . The interventions to be considered involve the treatment of cattle with: ( 1 ) prophylactic trypanocides that kill trypanosomes but have no effect on tsetse mortality; ( 2 ) ITC , i . e . , topical application to hosts of insecticides that kill tsetse but have no direct effect on trypanosome mortality . The use of ITC can reduce R0 in two ways . First , in common with all insecticidal techniques , it reduces the average life expectancy of tsetse , so decreasing the abundance of the flies and the proportion of the population that is old enough to harbor mature , transmissible infections . Second , and in contrast with other insecticidal techniques such as traps or insecticide-treated targets , ITC kills specifically those tsetse that become infected from the reservoir of disease in cattle . Since the Rogers model assumes that the abundance and age structure of the tsetse population is constant , it is particularly suitable for highlighting the second type of effect , and so for comparing ITC and trypanocides as means of reducing the probability that a fly will become infected . In the present paper we first use the Rogers model to address this matter under circumstances in which various levels of the use of trypanocides or insecticide treatment are applied to cattle that represent different proportions of the overall cattle population , and with host populations composed of various species . We then identify the extra benefit that ITC produces via reductions in the abundance and mean age of the tsetse population , and predict the relative merits of using ITC and trypanocides , as assessed via the model .
As a preliminary check we inserted the published default parameter values ( see Tables 1 and 2 , [25] ) into Equation ( 1 ) for the scenario where only ( untreated ) cattle and humans provided the source of tsetse bloodmeals , and obtained the published values for R0: 388 . 2 for T . vivax , 64 . 4 for T . congolense , and 2 . 65 for T . brucei . The last value is made up the sum of two components , 2 . 54 from the cattle and 0 . 11 from humans , implying that T . brucei would not survive in the absence of the cattle reservoir [25] . To control , and eventually eliminate , T . brucei the goal therefore must be to reduce the combined R0 , for human and non-human hosts , to a value less than unity . We now turn to the use of the insecticide-treated cattle ( ITC ) method of control – where the vectors , rather than the trypanosome , are targeted . In the previous sections we have assumed a fixed daily rate for adult tsetse mortality ( Table 1 ) . When considering the use of ITC , however , we need to decompose this factor into the mortality occurring at the time of feeding and that occurring between feeds . The former has generally been considered the dominant component [28] , [29] even where the host is not treated with insecticide . If the probability of surviving a feed is qf and the probability of surviving a non-feeding day is qn then a fly survives a complete feeding cycle of d days with probability qf qnd . With qf = 0 . 96 , qn = 0 . 98 , and with the assumed four-day feeding interval [25] , the probability of surviving from one feeding cycle would then be approximately 0 . 96×0 . 984 = 0 . 885 and the daily mortality rate is calculated as −ln ( 0 . 885 ) /4≈0 . 03 , as originally assumed [25] . Where some hosts are treated with insecticide we assume that flies always die if they feed off a treated animal; the probability of a given fly surviving a feed is thus the product of the probabilities that it feeds off an un-treated host and survives that meal . We assume further that flies feed off all cattle at random , particularly with respect to the animal's treatment status . If the proportion of cattle treated is pi then the probability of a fly surviving a feeding cycle is now ( 1−pi ) qf qnd . For example , with the above values for qf , qn and d , and if 10% of the cattle are treated , the survival probability will be 0 . 9×0 . 885 = 0 . 797 and the daily mortality is now approximately 0 . 057 . As a first approximation we ignore any extra mortality arising from a fly feeding off a human , rather than cattle or wildlife . Figures 1 , 2 , 3 , and 4 provide estimates of the control of trypanosomiasis , by way either of the use of trypanocidal drugs or ITC , in the situation where there is sufficient birth , of uninfected flies , to ensure that the tsetse population stays at a constant level [25] . This should be a reasonable assumption in the case where trypanocidal treatment is used to control trypanosomiasis and there is no imposed mortality on the tsetse population . When ITC is used , the population could only be kept constant if the increase in mortality is balanced by an increase in birth and/or immigration . If birth is the predominant source of replacements then Figures 3 and 4 reflect the control situation . If , however , the population is kept constant due to immigration then the replacement flies will be predominantly older flies , with above-average probability of being infected with trypanosomes , so that Figures 3 and 4 over-estimate the efficacy of ITC . However , where ITC is used , either against closed populations of tsetse or on a sufficiently large scale that immigration is limited at sites far from the boundary , the expectation is that the fly population will decrease . Inspection of Equation ( 1 ) shows that , other things being equal , R0 changes linearly with the tsetse population so that , where the use of ITC produces a decline in population levels the effect on R0 will be larger than indicated in Figure 3 . We follow Smith & McKenzie [31] in estimating that , if mortality was increased from some value u to u′ , the initial vector population ( V ) would decrease to Vu/u′ . Taking this factor into account changes the threshold value for the required percentage of cattle among non-human hosts . Thus , under the assumption of a constant tsetse population , it was impossible to force R0<1 for T . vivax ( Figures 3A , 4A , 5 ) . However , if tsetse populations are reduced as a consequence of ITC , R0<1 for T . vivax as long as cattle make up >90% of the non-human hosts ( Figure 5 ) . The proportions of cattle among non-human hosts , required to force R0<1 , declines from roughly 70% to 55% for T . congolense and 40% to 30% for T . brucei ( Figure 5 ) .
For purposes of comparing our results with previous work we have , initially , adhered closely to the design , and the parameterization , of the Rogers model – which provides a useful tool for investigating the dynamics of trypanosomiasis . It is recognized , however , that some fundamental details of the model can be improved . For example , the model makes no distinction between male and female tsetse , which are known to differ with respect to longevity , mobility , infectivity and responses to baits [32] , and does not allow that mortality changes as a function of age [33] . Moreover , advances in our knowledge over the past 23 years allow the selection of parameter values that better reflect the field situation . Thus , the feeding interval is certainly shorter than four days and where tsetse make more than one visit to a host per feeding cycle [30] , [34] this will impact on both the probability that they transmit a trypanosome , and the probability that they are killed when they alight on an animal that has been treated with insecticide . Most seriously , the model assumes that the abundance and age structure of the tsetse population is constant . This can be a reasonable assumption where no tsetse control efforts are in place , or when trypanosomiasis control consists simply of treating livestock with trypanocides that have no insecticidal effect . If cattle provide a substantial proportion of tsetse bloodmeals and if a significant proportion of these cattle are treated with insecticide , however , it may be expected that both the size of the population in the area under treatment , and its mean age , will tend to decline . On the other hand the model also ignores the problem of invasion from adjacent infected areas and this further complicates the estimation of the effect of ITC . Finally , we have not modified Rogers' implicit assumption that tsetse feed at random off the individuals of a given host species . This is known not to be the case and this consideration will complicate the modeling [17] . Nonetheless , in the limit , where some individuals provide no bloodmeals at all for tsetse , they effectively do not exist from the modeling point of view . One could thus simplify the problem by considering the “effective” number of individuals in a herd – being the numbers that do provide bloodmeals . In the same way , baboons and impala – which provide almost no bloodmeals for tsetse – do not need to be considered when modeling the dynamics of trypanosomiasis . It would not be easy to incorporate all of these details into the present model and still maintain the simplicity that allowed the model to be generalized to apply to the variety of situations considered here . The more general model can , however , be investigated using simulation models; the results of such an exercise will be reported in a separate paper . Despite the above limitations , the theoretical development presented here suggests that the use of ITC should provide a potent tool for controlling , or even eliminating , trypanosomiasis in situations where cattle provide the majority of bloodmeals for tsetse . The dynamics of transmission ensure that the requisite proportion favoring the use of ITC depends on the species of trypanosome involved; for T . vivax there is little hope of eliminating the disease unless at least 90% of the tsetse bloodmeals are from cattle – and then only if insecticide treatment is such that all tsetse feeding off cattle are killed , and if the situation is such that the increased tsetse mortality results in a decline in the fly numbers . For T . brucei the situation is very much more favorable; even if 70% of bloodmeals are being taken from wildlife , treatment with insecticide of the cattle providing the remaining meals from non-humans allows R0 to be reduced to unity . The situation for T . congolense is intermediate between these extremes . By contrast , the use of trypanocides will never allow T . vivax and T . congolense to be eliminated , even where tsetse feed only on cattle – unless all animals are kept permanently on a perfect trypanocide . T . brucei could be controlled – but only in the absence of wildlife hosts . The classical Rhodesian sleeping sickness foci are often associated with protected areas [35] , the vectors are Morsitans-group tsetse and the hosts are wild mammals such as warthog , buffalo and bushbuck . Tackling these foci is very difficult: block treatment of wild hosts with trypanocides is impossible and hence vector control is the only option . Moreover , the flies are highly mobile [36] and widely dispersed across a range of habitats and hence , to be effective , tsetse control must be applied across the entire protected area . This approach is illustrated by the use of aerial spraying and insecticide-treated targets to eliminate tsetse from the Okavango Delta ( area≈15 , 000 km2 ) of Botswana [6] . Few countries have the resources for such large-scale interventions and hence sleeping sickness persists in parts of east and southern Africa . By contrast , tackling Rhodesian sleeping sickness transmitted by G . fuscipes might be more tractable for several reasons . First , the underlying R0 of T . b . rhodesiense is likely to be low . Studies of the diet of G . f . fuscipes in Uganda and Kenya have shown that monitor lizards ( Varanus nilotica ) provide between ∼50% and >90% of bloodmeals [20] , [37]–[39] and it seems likely that poikilothermic hosts such as monitor lizards will not be competent hosts for mammalian trypanosomes . The only published study [21] confirms this for T . congolense and the results for T . brucei are equivocal but not compelling: no human-infective trypanosome has been recovered from a lizard , only one wild lizard ( N = 46 ) has been found with T . brucei s . l . , and experimental infections of captive lizards – which were not subject to the range of temperatures found in nature – produced , at most , a low and transient parasitaemia . Our results suggest that if lizards are indeed refractory to mammalian trypanosomes and form >80% of the diet of tsetse , then the R0 for T . b . rhodesiense is less than 1 . Hence we might expect that Rhodesian sleeping sickness will be associated with areas where lizards are not abundant such as away from the shores of Lake Victoria and/or in densely settled areas where wild hosts are absent . Consistent with this hypothesis , the current foci of Rhodesian sleeping sickness in Uganda are , paradoxically , not near the shores or islands of Lakes Victoria and Kyogu , where tsetse are abundant , but rather at sites further inland [40] , [41] . In areas where lizards are not important hosts , then livestock , particularly cattle , are important [20] , [38] . In the case of Uganda , the densities of cattle frequently exceed 50 head/km2 [42] and the degraded environment leads to relatively low densities of tsetse [38] . Increasing the host∶vector ratio reduces R0: for densities of 10 host/km2 and 5000 tsetse/km2 our model ( with other parameters as in Tables 1 and 2 ) suggests R0 = 13 for T . brucei; with 50 hosts and 5000 tsetse/km2 the value is 3 , and with 50 hosts and 500 tsetse/km2 it is 0 . 3 . Second , G . f . fuscipes are restricted to riverine habitats and are less mobile than Morsitans species such as G . pallidipes [36] and hence vector control can be applied on a smaller scale , focused on riverine and lacustrine habitats . Third , the abundance of cattle in settled areas , their importance as a host for tsetse and their need for water – and hence daily presence in the riverine and wetland habitats where G . f . fuscipes is concentrated – means that insecticide-treated cattle should be particularly effective baits . Hence , SE Uganda , the place where Rhodesian sleeping sickness is most serious , accounting for over half ( 2848/5086 ) of all cases across Africa [35] , is probably the easiest to tackle . Present evidence for the superior efficacy of ITC assumes greater importance due to indications over the last decade that the economy of this technique can be improved substantially , with no material loss of performance . The application of insecticide can be restricted to the legs and belly of cattle where most tsetse feed , thereby reducing the material costs of treatment by ∼90% [16] . In addition , since most tsetse feed on the larger and older animals within a herd [17] , [43] , only these animals need be treated , with further savings in cost . As a consequence , the annual material cost of ITC is reduced to <US$2 per beast per year [44] – comparable to the cost of a single dose of diminazene aceturate to cure trypanosomiasis . The restricted application of pyrethroids to older cattle allows young stock to be exposed to ticks and hence develop a natural immunity to tick-borne diseases [45] and reduces impact on dung fauna [46] , [47] which play an important role in maintaining soil fertility and , ultimately , productive pasturage . Against these favorable indications for the usefulness of ITC there is the problem that the technique can be used only in districts where cattle occur , although modeling suggests that ITC can be effective even when cattle are distributed patchily , i . e . , absent from bands of habitat up to several kilometers wide [48] . Nonetheless , for the densely-settled rural areas of central and southern Uganda where Rhodesian sleeping sickness is most acute , our findings suggest that relatively modest levels of treatment ( ∼20% even if tsetse numbers are not reduced by the intervention ) could lead to the elimination of HAT . Hence there is the exciting prospect that an important public health benefit might arise through the private actions of livestock keepers using cheap , simple and environmentally-benign methods to control vector-borne diseases in their livestock [22] .
|
In Uganda , cattle are an important reservoir for Trypanosoma brucei rhodesiense , the causative agent of Rhodesian sleeping sickness ( human African trypanosomiasis ) , transmitted by tsetse flies Glossina fuscipes fuscipes , which feed on cattle , humans , and wild vertebrates , particularly monitor lizards . Trypanosomiasis can be controlled by treating livestock with trypanocides or insecticide – killing parasites or vectors , respectively . Mathematical modeling of trypanosomiasis was used to compare the impact of drug- and insecticide-based interventions on R0 with varying densities of cattle , humans and wild hosts . Intervention impact changes with the number of cattle treated and the proportion of bloodmeals tsetse take from cattle . R0 was always reduced more by treating cattle with insecticide rather than trypanocides . In the absence of wild hosts , the model suggests that control of sleeping sickness ( R0<1 ) could be achieved by treating ∼65% of cattle with trypanocides or ∼20% with insecticide . Required coverage increases as wild mammals provide increasing proportion of tsetse bloodmeals: if 60% of non-human bloodmeals are from wild hosts then all cattle have to be treated with insecticide . Conversely , it is reduced if lizards , which do not harbor trypanosomes , are important hosts and/or if insecticides are used at a scale where tsetse numbers decline .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"veterinary",
"diseases",
"mathematics",
"theoretical",
"biology",
"pest",
"control",
"applied",
"mathematics",
"animal",
"management",
"biology",
"population",
"biology",
"veterinary",
"science",
"agriculture"
] |
2012
|
Modeling the Control of Trypanosomiasis Using Trypanocides or Insecticide-Treated Livestock
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In eukaryotes , intracellular cholesterol homeostasis and trafficking are tightly regulated . Certain bacteria , such as Anaplasma phagocytophilum , also require cholesterol; it is unknown , however , how this cholesterol-dependent obligatory intracellular bacterium of granulocytes interacts with the host cell cholesterol regulatory pathway to acquire cholesterol . Here , we report that total host cell cholesterol increased >2-fold during A . phagocytophilum infection in a human promyelocytic leukemia cell line . Cellular free cholesterol was enriched in A . phagocytophilum inclusions as detected by filipin staining . We determined that A . phagocytophilum requires cholesterol derived from low-density lipoprotein ( LDL ) , because its replication was significantly inhibited by depleting the growth medium of cholesterol-containing lipoproteins , by blocking LDL uptake with a monoclonal antibody against LDL receptor ( LDLR ) , or by treating the host cells with inhibitors that block LDL-derived cholesterol egress from late endosomes or lysosomes . However , de novo cholesterol biosynthesis is not required , since inhibition of the biosynthesis pathway did not inhibit A . phagocytophilum infection . The uptake of fluorescence-labeled LDL was enhanced in infected cells , and LDLR expression was up-regulated at both the mRNA and protein levels . A . phagocytophilum infection stabilized LDLR mRNA through the 3′ UTR region , but not through activation of the sterol regulatory element binding proteins . Extracellular signal–regulated kinase ( ERK ) was up-regulated by A . phagocytophilum infection , and inhibition of its upstream kinase , MEK , by a specific inhibitor or siRNA knockdown , reduced A . phagocytophilum infection . Up-regulation of LDLR mRNA by A . phagocytophilum was also inhibited by the MEK inhibitor; however , it was unclear whether ERK activation is required for LDLR mRNA up-regulation by A . phagocytophilum . These data reveal that A . phagocytophilum exploits the host LDL uptake pathway and LDLR mRNA regulatory system to accumulate cholesterol in inclusions to facilitate its replication .
Cholesterol is an important component of biological membranes , and it is essential for many biological functions ranging from membrane trafficking to signal transduction in eukaryotic cells [1] . However , excess cholesterol must be avoided in cells as well as in the blood stream , because it alters intracellular vesicular trafficking , deregulates cellular signaling , and initiates atherosclerosis [2] , [3] . The liver in large part regulates blood cholesterol levels by removing it from circulating blood . To maintain cellular cholesterol levels within a specified range , cholesterol levels are constantly assessed and tightly regulated in a complex manner at the transcriptional , translational , and posttranslational levels [4] . In recent years , cellular cholesterol has emerged as a significant factor , which influences outcome of infectious diseases from microbiological and cell biological studies . The cholesterol content of host cell membranes appears to be critical for microbial entry , intracellular localization , and exit by exocytosis [5] . A growing body of evidence suggests that host cellular cholesterol levels affect the replication of intracellular microbial pathogens , such as Salmonella , Mycobacterium , Brucella , and Coxiella [5] , [6] , [7] , but how cholesterol influences replication of these pathogens are not completely understood . Among the above-mentioned pathogens , infection by Salmonella or Coxiella up-regulates cellular cholesterol levels , although the mechanisms of up-regulation are not clear [7] , [8] . One of the common characteristics for these intracellular bacteria is that after internalization into their host cells the bacteria reside and proliferate in parasitophorous vacuoles . As such , cholesterol may play a role in nutrient acquisition by bacteria entrapped within vacuoles , or the accumulation of cholesterol may prevent phagolysosomal fusion [5] . Anaplasma phagocytophilum is a tick-borne obligatory intracellular bacterium that proliferates in membrane-bound inclusions in granulocytes and endothelial cells of various mammal species [9] , [10] , [11] . In humans , A . phagocytophilum causes an emerging and major tick-borne disease called human granulocytic anaplasmosis , an acute febrile disease that is potentially fatal , especially in elderly or immunocompromised individuals [12] . A . phagocytophilum is an atypical Gram-negative bacterium , because it contains substantial amounts of cholesterol in its outer membrane [13] . The bacterium lacks genes for cholesterol biosynthesis or modification; rather , it directly acquires cholesterol from its host cells or the medium [13] . Our previous data showed that cholesterol is required for A . phagocytophilum proliferation in host human promyelocytic leukemia HL-60 cells and that a high blood cholesterol level facilitates A . phagocytophilum infection in a mouse model [13] , [14] . A . phagocytophilum enters host cells through caveolae or lipid rafts , and the inclusion membrane retains caveolin-1 throughout infection , suggesting continuous infusion of the lipid raft or caveosome into growing bacterial inclusions [15] . Considering cholesterol-dependence of A . phagocytophilum membrane integrity and the importance of cholesterol for the infection process , thus survival [13] , we questioned how host cellular cholesterol uptake , trafficking , and regulatory systems are involved in A . phagocytophilum infection of human leukocytes . In this study , we present data on the intracellular cholesterol level and cholesterol distribution in A . phagocytophilum–infected HL-60 cells . We provide evidence that the source of increased level of cellular cholesterol required for A . phagocytophilum replication is extracellular low-density lipoprotein ( LDL ) rather than cholesterol synthesized by the host cells . Finally , we propose a mechanism by which the cellular LDL receptor ( LDLR ) level is increased in infected HL-60 cells to take up more LDL . The data underscore an important evolutionary adaptation of A . phagocytophilum to hijack host cell cholesterol .
We previously measured the total cholesterol level of host cell–free A . phagocytophilum and found that the level of total cholesterol per milligram of protein was higher than that of host cells [13] . Here , we further measured the total cholesterol level in A . phagocytophilum–infected HL-60 cells following infection time course . The total cellular cholesterol level progressively increased at days 2 and 3 post-infection ( p . i . ) , and the level was significantly greater than that at day 0 p . i . ( after 1 h incubation at 37°C ) . The increase in cholesterol level in infected HL-60 cells correlated with bacterial growth ( Figure 1 ) . In contrast , the cholesterol level in uninfected HL-60 cells remained unchanged during the same observation period ( data not shown ) . Most of the free ( unesterified ) cholesterol in eukaryotic cells is located in the plasma membrane [16] . Over-accumulation of free cholesterol in cells can be toxic due to the potential formation of solid crystals [17] . To determine the intracellular distribution of the observed increased cholesterol in A . phagocytophilum–infected HL-60 cells , we used a polyene antibiotic , filipin , which binds specifically to free cholesterol [18] . A specific antibody against A . phagocytophilum was used to localize bacteria by double immunofluorescence microscopy . First , the microscopy analysis clearly showed the overall filipin signal was much stronger in A . phagocytophilum-infected HL-60 cells than that in uninfected HL-60 , which supports the data shown in Figure 1 and further suggests the increased total cellular cholesterol might be free cholesterol , but not esterified cholesterol ( Figure 2A ) . Second , most of the filipin signal was confined in A . phagocytophilum–containing vacuoles ( “inclusions” ) ( Figure 2A ) . Uninfected host cells showed weak filipin signal , which was mostly localized to the plasma membrane and some unknown compartments ( assumed to be recycling endocytic compartments [19] ) . Notably , A . phagocytophilum inclusions outside of host cells also clearly displayed strong filipin signals ( Figure 2B ) , suggesting that the inclusion has intrinsic ability to retain the cholesterol . Recently , it was shown that Chlamydia release from the infected host cells occurs by two mechanisms: lysis and extrusion [20] . How the A . phagocytophilum inclusion became extracellular remains to be studied . Taken together , these results indicate that A . phagocytophilum infection alters host intracellular cholesterol homeostasis and distribution and that free cholesterol is enriched in A . phagocytophilum inclusions . Mammalian cells acquire cholesterol from two sources: receptor-mediated uptake from exogenous lipoproteins and endogenous biosynthesis in the smooth ER [4] . In leukocytes , LDL is the primary exogenous cholesterol source that is acquired via LDLR-mediated endocytosis [21] . After hydrolysis of cholesterol esters in acidic late endosomes ( enriched in acid lipases ) , the egress of free cholesterol occurs and free cholesterol is transported to the plasma membrane or delivered to the ER . Excess free cholesterol is catalyzed into cholesteryl esters by the resident ER acyl-CoA: cholesterol acyltransferase and stored as cytoplasmic lipid droplets [2] , [22] . Both undifferentiated and macrophage differentiated HL-60 cells express a regulated LDLR [23] . Cholesterol is essential for A . phagocytophilum infection in HL-60 cells [13]; thus , to better understand the source of free cholesterol required for A . phagocytophilum infection , we first examined the LDLR-mediated cholesterol uptake pathway using: 1 ) lipoprotein-deficient serum ( LPDS ) , 2 ) anti-LDLR monoclonal antibody ( mAb ) , and 3 ) pharmacological inhibitors of the LDLR-mediated cholesterol uptake pathway . LPDS was prepared from the fetal bovine serum by removing ∼95% lipoproteins using potassium bromide gradient ultracentrifugation ( data not shown ) . The fractionated lipoprotein ( LP ) was added back to LPDS in certain experiments . LPDS prevented the infection of host cells by A . phagocytophilum , and LPDS reconstituted with LP reversed this inhibition ( Figure 3A ) . Moreover , the infection rate of LPDS-conditioned HL-60 cells was decreased on day 2 p . i . compared with that on day 1; and addition of LP rescued the growth on day 2 p . i . ( Figure 3A ) , suggesting that cholesterol derived from LP is essential for A . phagocytophilum survival and proliferation in host cells . LDL enters host cells via LDLR-mediated endocytosis , which is blocked by a neutralizing antibody against LDLR [21] . We found that the infection was also significantly blocked by the LDLR mAb ( Figure 3B ) . U18886A and imipramine are hydrophobic amines that accumulate in acidic cellular compartments , such as lysosomes , and block the post-lysosomal transport of cholesterol in the LDL uptake pathway [24] , [25] . We found that both U18886A and imipramine significantly inhibited A . phagocytophilum infection and replication in HL-60 cells in a dose-dependent manner . U18886A ( 5 µM ) and imipramine ( 100 µM ) added at 1 h p . i . almost completely blocked bacterial growth ( Figure 3C ) . In contrast , lovastatin , an inhibitor of the rate-limiting enzyme 3-hydroxy-3-methylglutaryl ( HMG ) -CoA reductase in the cholesterol biosynthetic pathway [26] , did not inhibit A . phagocytophilum infection , but rather significantly enhanced it in HL-60 cells in a dose-dependent manner ( 1–5 µM; Figures 3C and D ) . 25-Hydroxycholesterol ( 25-HC ) , which inhibits both LDL uptake and biosynthesis by acting as a negative feedback regulator of cholesterol metabolism [27] , partially inhibited A . phagocytophilum infection ( Figure 3C ) . Trypan blue and Diff-Quik staining followed by light microscopy showed that although infected host cells remained viable and did not show significant changes , the morphological characteristics of A . phagocytophilum inclusions were different: bacterial inclusions remained small in U18886A- or imipramine-treated cells compared with those in untreated cells ( Figure 3D ) . The inhibitory effect of U18886A and imipramine , and the stimulatory effect of lovastatin , were observed at 1 and 2 day p . i . ( Figure 3E ) . When inhibitors were added at 1 day p . i . ( 40% of HL-60 cells were infected ) , the bacterial proliferation was still significantly blocked in U18886A- and imipramine-treated cells at optimal concentrations of 5 and 100 µM , respectively ( Figure 3F ) . Taken together , these results indicate that not only A . phagocytophilum proliferation , but also survival of the bacterium in inclusions is dependent on cholesterol derived from the LDL uptake pathway , as bacterial numbers declined upon exposure to LPDS or imipramine . Furthermore , de novo cholesterol biosynthesis is not required , and inhibition of this biosynthesis stimulated , rather than inhibited A . phagocytophilum infection in HL-60 cells . As A . phagocytophilum also infects endothelial cells [10] , [11] , we used another cell line , monkey endothelial RF/6A to perform the inhibitor studies . Our data showed that the infection of A . phagocytophilum in RF/6A was also significantly inhibited by cholesterol transport inhibitors U18666A ( 5 µM ) and imipramine ( 20 µM ) . However , no inhibitory effect was observed by lovastatin treatment ( 1 µM ) ( Figure S1 ) . Taken together , these data suggest that LDLR-dependent cholesterol uptake pathway is critical for A . phagocytophilum infection in both leukocytes and endothelial cells . Our data have shown that total cellular free cholesterol is increased in A . phagocytophilum–infected cells and that the LDL uptake pathway is required for A . phagocytophilum infection . We thus used LDL labeled with the fluorescent probe , 1 , 1′-dioctadecyl-3 , 3 , 3′ , 3′-tetramethyl indocarbocyanine ( DiI–LDL ) [28] , to compare the overall LDL uptake by A . phagocytophilum–infected and uninfected HL-60 cells . We found that LDL uptake was enhanced in A . phagocytophilum–infected cells ( Figure 4C ) . After dissociation from LDLR in early sorting endosomes , LDL is directed to late endosomes for hydrolysis of cholesterol esters [2] , [22] . By fluorescence microscopy , A . phagocytophilum inclusions were surrounded by DiI-LDL-containing small vesicles ( Figures 4A and B ) , in agreement with our previous reports that lysosomes accumulate around A . phagocytophilum inclusions [29] . We next asked whether the increased cholesterol level and enhanced LDL uptake of host cells upon A . phagocytophilum infection may involve up-regulation of LDLR expression . First , we compared mRNA levels of LDLR and other genes involved in cholesterol and fatty acid biosynthesis , including HMG-CoA reductase , HMG-CoA synthase , and fatty acid synthase [30] in infected and uninfected HL-60 cells by real-time RT-PCR . As shown in Figure 5A , LDLR mRNA level was significantly up-regulated at least 4-fold at day 2 p . i . However , the expression of cholesterol biosynthesis genes did not change significantly . The fatty acid synthase gene was significantly down-regulated upon A . phagocytophilum infection ( Figure 5A ) . The pattern of LDLR mRNA normalized to host cell TATA-box binding protein mRNA levels was very similar to that normalized to G3PDH mRNA levels . Second , we examined the LDLR protein level by western blotting . As shown in Figure 5B , LDLR was markedly up-regulated upon A . phagocytophilum infection . To evaluate whether new protein synthesis or intracellular proliferation of A . phagocytophilum is required for LDLR mRNA up-regulation , 10 µg/ml of oxytetracycline was added to cell cultures at 1 h p . i . This treatment completely blocked bacterial proliferation as confirmed by Diff-Quik staining ( data not shown ) and western blotting using mAb 5C11 against the A . phagocytophilum major surface protein , P44 ( Figure 5C inset ) . LDLR mRNA up-regulation at day 2 p . i . was abolished by oxytetracycline treatment ( Figure 5C ) , suggesting that synthesis of new A . phagocytophilum proteins and/or intracellular proliferation is required to induce LDLR mRNA up-regulation in HL-60 cells . Notably , real-time RT-PCR analysis showed that LDLR mRNA levels in A . phagocytophilum–infected HL-60 cells were significantly increased by lovastatin treatment in a dose-dependent manner ( Figure 5D ) . Western blotting also showed that the LDLR level was markedly higher in lovastatin-treated HL-60 cells at day 2 p . i . compared to DMSO–treated control cells ( Figure 5E ) , which may explain the enhanced infection level in the lovastatin-treated sample as shown in Figure 3 . Taken together , these results show that A . phagocytophilum infection enhances LDL uptake by up-regulating LDLR expression . Sterol regulatory element binding proteins ( SREBPs ) are key transcription factors for the cholesterol-mediated feedback regulation to maintain intracellular cholesterol homeostasis by regulating the LDLR gene as well as many cholesterol biosynthesis genes [3] . Three SREBP isoforms have been characterized , namely SREBP-1a , SREBP-1c and SREBP-2 [31] . SREBP-1c , the predominant isoform in adult liver , preferentially activates genes required for fatty acid synthesis , whereas SREBP-2 preferentially activates the LDLR gene and various genes required for cholesterol synthesis , such as HMG-CoA reductase [32] . Therefore , we investigated whether the up-regulation of LDLR by A . phagocytophilum infection was due to activation of SREBP-2 . SREBPs are activated by cleavage and translocation of the cleaved product from the cytoplasm to the nucleus [3] . As shown in Figures 6 , mature cleaved SREBP-2 levels remained unchanged throughout A . phagocytophilum infection . As a positive control for SREBP-2 cleavage , uninfected cells were incubated with LPDS-conditioned medium overnight , as this is known to induce SREBP-2 cleavage in different cell lines including CHO and human monoblastic leukemia cell line U937 [33] . There was no significant difference between A . phagocytophilum–infected and uninfected HL-60 cells at any post-infection time point examined , suggesting that SREBP-2 activation is not involved in the up-regulation of LDLR mRNA upon A . phagocytophilum infection in HL-60 cells . In another word , the dramatic intracellular cholesterol homeostasis up-shift by A . phagocytophilum infection cannot be sensed by the host cell key regulatory factor SREBP-2 . LDLR is regulated not only at the transcriptional level but also at the posttranscriptional level via modulation of LDLR mRNA stability [34] . Therefore , we investigated LDLR mRNA stability in A . phagocytophilum–infected HL-60 cells after treatment with actinomycin D , a eukaryotic DNA-dependent RNA polymerase inhibitor . The half-life of LDLR mRNA in infected HL-60 cells was increased by almost 2-fold as compared to uninfected cells ( Figure 7A ) . In contrast , the stability of HMG-CoA reductase mRNA did not change noticeably during A . phagocytophilum infection ( Figure 7B ) . Human LDLR mRNA contains a 2 . 5-kb 3′UTR [35] . The 3′UTR of LDLR mRNA can be stabilized by phorbol-12-myristate-13-acetate ( PMA ) and a Chinese herbal compound , berberine in the human hepatic cell line HepG2 [36] , [37] . Three AU-rich elements ( AREs ) are located in the 5′ proximal region of the 3′UTR , which have been shown to be responsible for the stabilization of LDLR mRNA by berberine , but not by PMA [37] . To investigate whether the LDLR 3′UTR containing three AREs is involved in A . phagocytophilum–induced LDLR stabilization , we transfected the luciferase fusion plasmid pLuc/LDLR 3′UTR-2 , containing three AREs of LDLR 3′UTR ( nt 2 , 677–3 , 582 ) [37] , into RF/6A cells and measured the luciferase mRNA levels in A . phagocytophilum–infected and control RF/6A cells . As shown in Figure 7C , luciferase mRNA levels normalized to the antibiotic zeocin resistance gene ( plasmid copy number ) were significantly increased in A . phagocytophilum–infected cells . Data normalized by G3PDH ( host cell number ) showed a similar pattern ( data not shown ) . These results indicate that the LDLR 3′UTR containing three AREs may be involved in enhancing LDLR mRNA stability in A . phagocytophilum–infected host cells . Accumulating evidence suggests that the extracellular signal–regulated kinase ( ERK ) signaling cascade regulates the induction of LDLR expression in HepG2 cells [34] , [38] . Moreover , berberine increases LDLR expression at the posttranscriptional level via ERK-dependent stabilization of LDLR mRNA [37] . Therefore , we asked whether and when ERK1/2 ( p44/p42 ) is activated during A . phagocytophilum infection , whether ERK1/2 activation is required for A . phagocytophilum infection , and whether ERK1/2 activation up-regulates LDLR , constituting a positive feedback loop for A . phagocytophilum replication . First , we determined whether ERK1/2 is activated by A . phagocytophilum infection in HL-60 cells by western blotting using an antibody that only recognizes activated ( phosphorylated ) ERK1/2 but not inactive ERK1/2 , as well as an antibody that recognizes both unphosphorylated and phosphorylated forms of ERK . We found that A . phagocytophilum activated ERK signaling especially during the exponential growth stage ( day 2 p . i . ) compared to day 1 p . i . or uninfected HL-60 cells ( Figure 8A ) . Second , we examined the effect of U0126 , the inhibitor of ERK upstream kinase MEK1/2 , on ERK activation upon A . phagocytophilum infection . ERK activation by A . phagocytophilum infection and A . phagocytophilum replication in HL-60 cells were also almost completely inhibited by 10 µM U0126 ( Figures 8A and B ) . This result was confirmed by western blotting for A . phagocytophilum P44 ( Figure 8C ) . To confirm ERK activation is required for A . phagocytophilum infection , MEK1/2 proteins were knocked down by RNA interference with siRNAs targeting the MEK1 and MEK2 genes . Results showed that at 4 days post transfection , the protein amount of MEK1/2 was reduced by ∼40% in MEK1/2 knockdown group , which resulted in the partial inhibition of the phosphorylation of ERK1/2 ( ∼30% ) , as well as the infection of A . phagocytophilum ( ∼50% ) ( Figure 8D ) . These data clearly demonstrate that ERK signaling is activated by and required for A . phagocytophilum infection in HL-60 cells . To determine whether ERK activation is involved in up-regulation of LDLR upon A . phagocytophilum infection , we examined the LDLR mRNA levels in U0126-pretreated HL-60 cells by real-time RT-PCR . As shown in Figure 8E , the relative LDLR mRNA level upregulated by A . phagocytophilum–infected HL-60 cells was significantly reduced by U0126 treatment starting at a concentration of 0 . 5 µM at 2 day p . i . Although the expression of LDLR mRNA was slightly reduced in uninfected HL-60 cells by MEK1/2 siRNA knockdown , there was no significant reduction of LDLR mRNA in infected HL-60 cells ( data not shown ) . Therefore , we could not draw the definitive conclusion whether MEK1/2→ERK1/2 pathway is required for up-regulation of LDLR expression in the case of A . phagocytophilum infection of HL-60 cells .
In this study , we present evidence that A . phagocytophilum is dependent on cholesterol derived from the LDLR-mediated uptake pathway of eukaryotic host cells . Several vacuole-occupying intracellular pathogens depend on host cholesterol stores or trafficking during their infection of cultured cells or mice [5] , although mechanisms vary considerably . Salmonella enterica serovar Typhimurium requires nonsterol precursors of the cholesterol biosynthetic pathway for intracellular proliferation [39] , and cholesterol accumulates in Salmonella-containing vacuoles in a Salmonella pathogenecity island-2–dependent manner [8] , [40] . The establishment of Brucella abortus infection in mice requires trafficking of plasma membrane cholesterol , which is controlled by Niemann-Pick C1 , an important cholesterol transport protein in late endosomes/lysosomes , as evidenced by resistance to B . abortus infection in Niemann-Pick C1 knockout mice [6] . Chlamydia trachomatis inclusions acquire cholesterol by selectively rerouting Golgi-derived vesicles [41] and multivesicular bodies [42] . Interestingly , cytoplasmic lipid droplets are translocated into the lumen of Chlamydia inclusions , which appears to be an alternate mechanism for acquisition of cholesterol [43] . Coxiella burnetii infection increases production of host cell cholesterol with concomitant up-regulation of host genes involved in cholesterol metabolism , including LDLR and several cholesterol biosynthesis genes [7] . Unlike any of the above described intracellular pathogens , A . phagocytophilum acquires cholesterol preferentially from the LDL uptake pathway by up-regulating LDLR expression . Toxoplasma gondii , although a eukaryotic pathogen , cannot synthesize sterols via the mevalonate pathway and appropriates cholesterol to its parasitophorous vacuole exclusively from LDL uptake [44] . Recently , an unexpected novel mechanism was demonstrated: T . gondii actively sequesters the host endocytic vesicles in its vacuolar spaces to provide its cholesterol needs [45] . Interestingly , A . phagocytophilum has an intracellular compartment somewhat similar to that of T . gondii [29] , [46] , which is segregated from both endocytic and exocytic pathways . The present study raises an intriguing question: how does A . phagocytophilum acquire cholesterol derived from the host LDL endocytic pathway ? Although A . phagocytophilum inclusions do not fuse with lysosomes , our previous data clearly demonstrate that these inclusions are surrounded by host lysosomes [29] . The physical proximity between the A . phagocytophilum inclusions and host lysosomes may facilitate cholesterol acquisition by A . phagocytophilum . Not only A . phagocytophilum enters host cells via caveolae-containing lipid rafts , but also the caveolar marker protein , caveolin-1 , co-localizes with both early and replicative A . phagocytophilum inclusions [13] . Caveolin-1 is a well-established cholesterol binding protein [47] , and caveolae/caveosomes have been proposed to be a cholesterol transporter participating in the bidirectional shuttling of free cholesterol between the plasma membrane and various intracellular compartments , including the ER , Golgi and lipid droplets [48] . Therefore , we hypothesize that the caveosome is involved in cholesterol transport to A . phagocytophilum inclusions . Another finding showed that some A . phagocytophilum inclusions co-localize with vesicle-associated membrane protein 2 ( VAMP2 ) [29] . In neutrophils , VAMP2 is believed to play a role in controlling vesicular targeting , docking , and fusion through interactions with other proteins , such as N-ethylmaleimide-sensitive factor and soluble N-ethylmaleimide-sensitive factor attachment protein [49] . The presence of VAMP2 on A . phagocytophilum inclusions may provide a mechanism to acquire cholesterol for the replicating organism through regulated vesicle trafficking . A recent report showed that A . phagocytophilum modulates lipid metabolism by increasing perilipin mRNA and protein levels to facilitate infection of HL-60 cells [50] . Perilipin is a major adipocyte lipid droplet–associated protein that plays a central role in lipolysis and cholesterol synthesis . It is unknown whether lipid droplets serve as an intermediate organelle for cholesterol acquisition by A . phagocytophilum after intracellular delivery via the LDLR pathway . Further work is required to determine the exact mechanism of cholesterol acquisition by A . phagocytophilum . Our data demonstrate that A . phagocytophilum up-regulates LDLR expression in HL-60 cells by stabilizing the LDLR mRNA via a posttranscriptional mechanism . This is the first report on modulation of LDLR mRNA stability by an infectious agent , and to our knowledge this is also the first report regarding LDLR up-regulation on leukocytes . This aspect may have clinical relevance because increasing hepatic LDLR expression is currently one of the primary strategies for hypercholesterolemia therapy . Recent data suggest that mRNA stability is the major mode of posttranscriptional regulation of LDLR expression . The stability of LDLR mRNA is known to be modulated by only a few reagents , including gemfibrozil [51] , PMA , chenodeoxycholic acid and berberine [34] . Interestingly , the stabilization of LDLR mRNA via the 3′UTR by chenodeoxycholic acid ( CDCA ) and berberine requires activation of the ERK signaling pathway . However , it is so far unclear how the ERK pathway is linked to LDLR mRNA stabilization and whether any trans-acting RNA binding proteins are involved in the stabilization process . In addition , the activity of berberine to up-regulate LDLR expression is specific to hepatocytes , as the significant increase of LDLR was found only in HepG2 cells , but not in other non-hepatic cell lines , such as CHO , HEK293 , or human primary fibroblasts [52] . The present study shows that A . phagocytophilum potently activates the ERK signaling pathway , especially at the exponential growth stage when the bacterium requires substantial amounts of cholesterol for proliferation with concomitant expansion of inclusions . The result is somewhat consistent with the recent report that A . phagocytophilum activates ERK2 ( p42 ) in host human neutrophils at 3 h p . i . [53] . For the first time , our MEK inhibitor and siRNA knock-down studies showed ERK activation is required for A . phagocytophilum infection . It has been reported that several other intracellular bacteria actively manipulate the host ERK signaling pathway to benefit microbial survival . Tapinos and Rambukkana reported a PKCε-dependent , but not MEK-dependent pathway for ERK1/2 activation by Mycobacterium leprae resulting in continuous proliferation of infected human Schwann cells , without inducing transformation [54] . Interestingly , activation of the host Ras-Raf-MEK-ERK-cPLA2 signaling cascade is required for chlamydial acquisition of host glycerophospholipids [55] . It remains to be elucidated why ERK activation is required for A . phagocytophilum infection or whether ERK involves in LDLR mRNA stabilization . Recently , the use of cholesterol biosynthesis inhibitors , such as statins , was proposed to combat certain pathogen infections because these microbes utilize the host cholesterol biosynthesis pathway . For example , lovastatin and atorvastatin reduce S . enterica serovar Typhimurium proliferation in vitro and in BABL/C mice , respectively [39] . Growth of C . burnetii can be also inhibited by lovastatin in vitro [7] . It is important to point out that unlike Salmonella and Coxiella , lovastatin enhanced , at least , did not reduce A . phagocytophilum infection in both HL-60 promyelocytic and RF/6A endothelial cells . This result is not surprising , however , because our present data show that A . phagocytophilum acquires cholesterol derived from the LDL uptake pathway and not from the biosynthesis pathway . Additionally , lovastatin-treated A . phagocytophilum–infected HL-60 cells expressed higher levels of LDLR . Thus , the question then becomes: is statin treatment beneficial , if not detrimental for A . phagocytophilum infection in vivo ? The answer to this question is very important because statin drugs are widely used in elderly patients to treat hypercholesterolemia , and A . phagocytophilum infection is more prevalent in this community . Our recent data showed that high blood cholesterol facilitates A . phagocytophilum infection in a mouse model [14] . However , our unpublished data suggest that there is a higher A . phagocytophilum level in the blood after Lipitor ( atorvastatin ) treatment of mice ( Xueqi Wang and Yasuko Rikihisa , unpublished data ) . We had originally hypothesized that statin treatment lowers blood cholesterol levels and consequently results in lower bacterial burden in the mice . This paradox could be explained as follows: statins do not reduce overall plasma cholesterol levels in mice , as they do in humans , due to very low levels of LDLs in rodents , even though they do block mouse HMG-CoA reductase and the sterol biosynthetic pathway in mice [56] . In fact , we have not found decreased blood cholesterol levels in statin-treated mice ( Xueqi Wang and Yasuko Rikihisa , unpublished data ) . Similarly , there is no significant change in serum cholesterol levels in atorvastatin-treated mice compared with vehicle-treated mice , although statins reduce S . enterica serovar Typhimurium growth in vivo [39] . Therefore , we speculate that , similar to our in vitro HL-60 cell culture model , up-regulation of LDLR in A . phagocytophilum–infected host leukocytes may result in a greater bacterial burden in statin-treated mice . Taken together , these results suggest that critical and careful consideration is required when treating granulocytic anaplasmosis patients , as statins are currently widely used to treat hypercholesterolemia in humans by lowering blood cholesterol levels . The data presented here improve our understanding of how a cholesterol-dependent bacterium exploits eukaryotic cellular cholesterol trafficking and regulatory pathways and may provide insight regarding a new therapeutic target for the treatment of human granulocytic anaplasmosis . Most information on LDLR regulation is derived from studies using hepatocytes [34]; however , as in the berberine's case [52] , in non-hepatic cells , LDLR regulation by cholesterol modulating compounds may differ from those of hepatocytes . Our study enhances our understanding of the LDLR regulation pathway in leukocytes and perhaps endothelial cells [10] , [11] , both of which are understudied , but important players in atherosclerosis .
Filipin , lovastatin , imipramine and U18666A were obtained from Sigma ( St . Louis , MO ) . 25-Hydroxycholesterol ( 25-HC ) was purchased from Steraloids , Inc . ( Newport , RI ) . MAPK inhibitor U0126 was obtained from Biomol ( Plymouth Meeting , PA ) . DiI-LDL and native LDL were purchased from Molecular Probes ( Eugene , OR ) and Intracel , Inc . ( Frederick , MD ) , respectively . The mouse mAb 5C11 recognizing the N-terminal conserved region of A . phagocytophilum major surface protein P44 has been described [57] . The anti-LDLR mAb was purified from the supernatant of hybridoma ATCC CRL-1691 ( C7 ) grown in advanced MEM ( ATCC , Manassas , VA ) by affinity chromatography using HiTrap Protein G HP ( GE Healthcare , Piscataway , NJ ) according to the manufacturer's instructions . The purity of the antibody was confirmed by SDS-PAGE followed by GelCode Blue staining ( Pierce , Rockford , IL ) . Other antibodies used include: mouse anti-SREBP-2 mAb ( BD Parmingen , San Jose , CA ) , mouse anti-phospho-ERK1/2 mAb , rabbit anti-ERK1/2 antibody , mouse anti-MEK1/2 mAb ( Cell Signaling , Danvers , MA ) , and mouse anti-α-tubulin mAb ( Santa Cruz Biotechnology , Santa Cruz , CA ) . Peroxidase-conjugated secondary antibodies were obtained from KPL ( Gaithersburg , MD ) . Normal mouse IgG were purchased from Santa Cruz Biotechnology . LPDS was prepared from fetal bovine serum ( Mediatech , Inc . , Herndon , VA ) by gradient ultracentrifugation after density adjustment by solid KBr as described [58] , [59] . LPs were used to supplement LPDS , as necessary for certain experiments . LPDS and LP fractions were dialyzed at least 36 h against buffer containing 0 . 15 M NaCl and 0 . 3 mM EDTA , pH 7 . 4 . The volume of each fraction was adjusted to be equivalent to that of the original serum , and the cholesterol concentration of each fraction was measured by Infinity™ cholesterol reagent kit ( Thermo Electron Corp . , Louisville , CO ) . A . phagocytophilum HZ strain was cultivated in human promyelocytic leukemia cell line HL-60 as described [60] . Host cell-free A . phagocytophilum was prepared by sonicating highly infected ( >90% infected cells ) HL-60 cells for 8 s twice at an output setting of 2 with an ultrasonic processor ( W-380; Heat Systems , Farmington , NY ) . After low-speed centrifugation to remove nuclei and unbroken cells , the supernatant was centrifuged at 10 , 000×g for 10 min , and the pellet enriched with host cell–free organisms was added to HL-60 or RF/6A cells . After 1 h incubation at 37°C , extracellular organisms were washed , fresh medium was added ( this time point was considered 0 h p . i . ) , and continuously incubated at 37°C . Inhibitors were added at indicated time points ( 0 h or 1 day p . i . ) , and the inhibitors were kept in the growth media throughout the incubation period or removed later as indicated . The highest final concentrations of inhibitors used were: lovastatin ( 5 µM ) , imipramine ( 100 µM ) , U18666A ( 5 µM ) , and 25-HC ( 25 µM ) . Inhibitor treatments at these concentrations did not affect host cell integrity as assessed by light microscopy or by G3PDH mRNA level . For LPDS treatment , 10% LPDS or LP-reconstituted LPDS conditioned growth medium was added at 0 h p . i . in place of the growth medium containing 10% fetal bovine serum . To block LDLR function , HL-60 cells were pretreated with anti-LDLR ( IgG2b; final concentrations:20 µg/ml ) or IgG2b isotype control antibody at 4°C for 1 h followed by addition of host cell–free bacteria , and then culture was continued at 37°C for the indicated times . The degree of bacterial infection in host cells was assessed by Diff-Quik staining ( Baxter Scientific Products , Obetz , OH ) , and the number of A . phagocytophilum cells was estimated in 100 host cells in triplicate culture wells as described [61] . Uninfected and A . phagocytophilum–infected HL-60 cells at the indicated time points ( 1 h , 1 day , 2 day and 3 day ) were collected , and total cellular cholesterol levels were measured by an Amplex Red cholesterol assay kit ( Molecular Probes ) as described [13] . The total cholesterol content was normalized by the total protein concentration as determined by bicinchoninic acid reagent ( Pierce ) . DiI-LDL uptake by infected and uninfected HL-60 cells was measured by the modified method of Teupser et al . [62] . Briefly , uninfected and approximately 40% infected HL-60 cells were incubated with LPDS-conditioned medium for 12 h to enhance LDLR expression . Then , increasing concentrations of DiI-LDL ( 2 , 5 , 10 µg protein/ml ) with or without 30-fold excess of unlabeled LDL were added to HL-60 cells and incubated for 2 h at 37°C . The cells were thoroughly washed with phosphate-buffered saline ( PBS , 137 mM NaCl , 2 . 7 mM KCl , 10 mM Na2HPO4 , and 2 mM KH2PO4 , pH 7 . 4 ) containing 0 . 4% bovine serum albumin , and lysed in the lysis reagent ( 0 . 1% SDS/0 . 1 N NaOH ) for 1 h with gentle shaking . Cellular uptake of DiI-LDL was measured in a fraction ( 200 µl ) of the lysate by fluorescence spectroscopy with excitation and emission wavelengths of 520 and 580 nm , respectively . The fluorometric data were normalized by the total protein content . Filipin staining was performed as described by Millard et al [63] . Cells were fixed in 4% paraformaldehyde at room temperature for 15 min and incubated with 50 µg/ml filipin in PBS/10% normal sheep serum for 30 min at room temperature . Then the cells were incubated with mouse anti–A . phagocytophilum antiserum in filipin/PBS/10% normal sheep serum for 60 min at 37°C followed by incubation with fluorescence-conjugated secondary antibodies for 30 min . Normal mouse antibodies were used as negative controls . Cells were then washed and observed under a Nikon Eclipse E400 fluorescence microscope with a xenon-mercury light source ( Nikon Instruments , Melville , NY ) . A . phagocytophilum–infected HL-60 and control HL-60 cells ( 2×106 ) were washed and resuspended in 100 µl PBS containing freshly added protease inhibitor cocktail set III and phosphatase inhibitor cocktail set II ( Calbiochem , San Diego , CA ) , and lysed by mixing with 100 µl of 2×Laemmli sample buffer ( 4% SDS , 135 mM Tris-HCl [pH 6 . 8] , 20% glycerol , and 10% β-mercaptoethanol ) . Samples were separated by SDS-PAGE with 7 . 5% or 10% polyacrylamide resolving gels and then transferred to a nitrocellulose membrane using a semidry blotter ( WEP , Seattle , WA ) . The membrane was blocked using 5% ( wt/vol ) skim milk ( Kroger , Cincinnati , OH ) in Tris-buffered saline ( 150 mM NaCl and 50 mM Tris at pH 7 . 5 ) containing 0 . 1% Tween-20 , incubated with primary antibodies ( 1∶500 or 1∶1 , 000 dilution ) at 4°C for 12 h , and subsequently incubated with peroxidase-conjugated secondary antibodies at 1∶1 , 000 dilution at room temperature for 1 h . Immunoreactive bands were visualized with enhanced chemiluminescence . To detect LDLR protein amount , the membrane fraction of cells was prepared according to Holla et al . [64] , and Western blotting was carried out as described [65] . Uninfected and A . phagocytophilum–infected HL-60 cells were harvested , and RNA was isolated using the RNeasy kit ( Qiagen , Valencia , CA ) . Total RNA ( 2 µg ) was reverse transcribed using SuperScript III reverse transcriptase ( Invitrogen , Carlsbad , CA ) and oligo ( dT ) 12–18 primer ( Invitrogen ) . Quantitative PCR ( 20 µl total volume ) was performed with 1 µl of cDNA ( corresponding to 0 . 2–0 . 4 µg of total RNA ) and 0 . 25 µM of each primer using a SYBR Green PCR kit ( Stratagene , La Jolla , CA ) in a Mx3000P Real-time PCR system ( Stratagene ) . All primers for cholesterol-related genes were described in Castoreno et al . [30] and G3PDH primers were described in Zhang et al . [66] . The chimeric plasmid pLuc/LDLR 3′UTR-2 has been described [37] . The constructs were sequenced , and individual clones were propagated to isolate plasmid DNA using the Endofree plasmid maxi kit ( Qiagen ) . The plasmids were transfected into endothelial cells , RF/6A , using the FuGene transfection reagent ( Roche , Indianapolis , IN ) . After 24 h , host cell–free A . phagocytophilum purified from highly infected HL-60 cells were inoculated into transfected RF/6A cells and incubated for additional 24–48 h . Samples were collected , and first-strand cDNA was synthesized as described above following DNase I ( Invitrogen ) treatment . The Luc transcripts were measured by quantitative real-time RT-PCR using specific primers: forward , TCCAACCCGGTAAGACACGACT , and reverse , TCAGCAGAGCGCAGATACCAAATA . Host cell G3PDH and the plasmid antibiotics gene zeocin ( forward , GACGACGTGACCCTGTTCATCAGC; reverse , CACTCGGCGTACAGCTCGTCCAG ) were used for normalization . HL-60 cells were transfected with double-stranded siRNA ( 3 µg/2×106 cells ) using the Amaxa nucleofection system ( kit V , program T-19; Lonza/Amaxa Inc , Walkersville , MD ) as described previously [67] . Verified human-specific siRNAs targeting the genes encoding MEK1 ( siRNA ID: s11167 ) and MEK2 ( siRNA ID: s11170 ) , or control siRNA ( # 4390843 ) not targeting any known human genes were purchased from Ambion ( Applied Biosystems/Ambion , Austin , TX ) . Two days after transfection , host cell-free A . phagocytophilum was added to cells and incubated for additional 2 days . Samples were then harvested and divided into two aliquots . One group of samples was lysed in M-PER lysis buffer ( Pierce ) supplemented with protease and phosphatase inhibitor cocktail ( Calbiochem ) , and subjected to Western blotting using antibodies against MEK1/2 , ERK1/2 , phospho-ERK1/2 and A . phagocytophilum P44 outer membrane protein [58] . Images were then captured and densitometric analysis was performed using LAS3000 image documentation system ( FUJIFILM Medical Systems USA , Stamford , CT ) . The other aliquots were stored in RNALater for further quantitative real-time RT-PCR analysis as described above . Statistical analyses were performed by unpaired , 2-tailed Student's t-test . Two-way ANOVA was used to compare mRNA decay rates . p<0 . 05 was considered to be significant .
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Maintenance of the cholesterol amount and transport within cells are essential for healthy human cell functions . Most bacteria do not need cholesterol , but certain bacteria that infect human cells are dependent on host cell cholesterol for their infection . How infected human cells deal with these cholesterol-robbing bacteria , and in turn how these bacteria hijack host cholesterol , are intriguing questions . Anaplasma phagocytophilum is a bacterium that lives inside white blood cells , and causes the disease human granulocytic anaplasmosis ( HGA ) . A . phagocytophilum needs host cholesterol to live . Here , we discovered that A . phagocytophilum infection increases the amount of cholesterol in host cells and sequesters the majority of cholesterol in A . phagocytophilum inclusions inside host cells . Human cells acquire cholesterol from two sources: receptor-mediated endocytosis of cholesterol-containing low-density lipoprotein ( LDL ) from the circulating blood , and synthesis of cholesterol inside the cells . Since A . phagocytophilum depends on cholesterol derived from LDL , it coaxes the host cell to take up more LDL by increasing LDL receptor , through inhibition of LDL receptor mRNA degradation . A . phagocytophilum infection may serve as a model to improve our understanding of the cellular cholesterol regulation in white blood cells , and may provide insight regarding new therapeutic target for treatment of HGA .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"cell",
"biology/leukocyte",
"signaling",
"and",
"gene",
"expression",
"cell",
"biology/membranes",
"and",
"sorting",
"public",
"health",
"and",
"epidemiology/infectious",
"diseases",
"infectious",
"diseases/bacterial",
"infections",
"microbiology/cellular",
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"diseases/epidemiology",
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"diseases"
] |
2009
|
Cholesterol-Dependent Anaplasma phagocytophilum Exploits the Low-Density Lipoprotein Uptake Pathway
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The Special Programme for Research and Training in Tropical Diseases ( TDR ) co-sponsored by UNICEF , UNDP , World Bank and WHO has been supporting research capacity strengthening in low- and middle-income countries for over 40 years . In order to assess and continuously optimize its capacity strengthening approaches , an evaluation of the influence of TDR training grants on research career development was undertaken . The assessment was part of a larger evaluation conducted by the European Science Foundation . A comprehensive survey questionnaire was developed and sent to a group of 117 trainees supported by TDR who had completed their degree ( masters or PhD ) between 2000 and 2012; of these , seventy seven ( 77 ) responded . Most of the respondents ( 80% ) rated TDR support as a very important factor that influenced their professional career achievements . The “brain drain” phenomenon towards high-income countries was particularly low amongst TDR grantees: the rate of return to their region of origin upon completion of their degree was 96% . A vast majority of respondents are still working in research ( 89% ) , with 81% of respondents having participated in multidisciplinary research activities; women engaged in multidisciplinary collaboration to a higher extent than men . However , only a minority of all have engaged in intersectoral collaboration , an aspect that would require further study . The post-degree career choices made by the respondents were strongly influenced by academic considerations . At the time of the survey , 92% of all respondents hold full-time positions , mainly in the public sector . Almost 25% of the respondents reported that they had influenced policy and practice changes . Some of the challenges and opportunities faced by trainees at various stages of their research career have been identified . Modalities to overcome these will require further investigation . The survey evidenced how TDR’s research capacity grant programmes made a difference on researchers’ career development and on south-south collaborations , by strengthening and localizing research capacity in lower income regions , and also showed there is more that needs to be done . The factors involved , challenges and lessons learnt may help donors and policy makers improve their future interventions with regard to designing capacity strengthening programmes and setting funding priorities .
The Special Programme for Research and Training in Tropical Diseases ( TDR ) , co-sponsored by UNICEF , UNDP , the World Bank and WHO , has a long track record in research capacity strengthening . Created in 1975 to support research and research capacity strengthening in the fight against tropical diseases , TDR’s goal is to improve health and reduce the burden of infectious diseases in low- and middle-income countries ( LMICs ) . For more than 40 years , TDR has strengthened health research capacities in these countries by: i ) supporting individuals’ education and training through fellowships , scholarships and learning-by-doing programmes for specific skills , particularly on good practice for health research and fostering mentorships; ii ) supporting institutional capacity by establishing national and international training and research centres; and iii ) developing networks and collaborative research projects [1] . Regular external reviews of its research capacity strengthening programmes have helped TDR to evolve its strategy in light of the global environment so as to remain a fit-for-purpose programme . The latest evaluation of TDR’s contribution to career development of a selected group of individuals and institutional capacity development grantees was conducted in 2010 . The main objective was to identify factors that positively influenced and improved the research capacity and career development of TDR trainees and that are of broader relevance to the objectives and goals of international development and aid agencies [2 , 3] . One of the recommendations was to better track the career development of grantees to help evaluate the influence of these early learning supports . To respond to these recommendations a career tracking survey tool was developed to study the potential links between the grants received by TDR trainees and their career development . The survey is conducted every 2–3 years to provide quantitative and qualitative data to better understand TDR’s grants impact on grantees’ careers . It provides an instant view of a trainee’s career , with performance indicators to allow monitoring and evaluation of career development . This survey tool was developed and implemented in collaboration with the European Science Foundation in France , a European structure that generates evidence to support the decision-making of countries or organizations . It was implemented in 2014 to study the contribution of TDR support on TDR training grantees’ careers between 2000 and 2012 . The survey responses have highlighted the challenges , bottlenecks and opportunities of different research career stages , which are being used to identify intervention points or specific actions needed to achieve desirable career progression .
TDR was invited to respond to a call for research support and funding organizations to join a doctorate career tracking project . The survey was launched in late 2014 by the European Science Foundation in Strasbourg , France . The aim of this call was to develop a methodology to design and implement a career tracking survey tool . Five organizations joined the study: the AXA Research Fund , Paris , France ( AXA ) ; the Fonds National de la Recherche , Luxembourg ( FNR ) ; the Goethe Graduate Academy ( GRADE ) , Frankfurt , Germany; the Paul Scherrer Institute ( PSI ) , Villingen , Switzerland and TDR . All data were disaggregated by organizations . Six hundred and thirty eight ( 638 ) trainees from the five partners responded to the survey with the following breakdown: 110 from the AXA fund , 84 from FNR , 105 from GRADE; 133 from PSI and 77 from TDR . The aggregated results from the 638 participants have been published [4] . Data were then disaggregated in 2015 and results specific to the TDR trainees are presented in this paper . A total of 304 TDR trainees who completed their doctorate or master’s degree between 2000 and 2012 with a TDR grant were identified in the TDR information and management system . These included recipients of any of the following scheme of grants: research training grants ( RTG ) ; re-entry grants ( REG ) ; the Multilateral Initiative on Malaria ( MIM ) ; research grants and institution strengthening grants ( ISG ) . RTGs were awarded to individuals in LMICs to pursue studies leading to a postgraduate degree ( MSc or PhD ) at their home country institution , in another LMIC or in a high income country . REGs were intended to facilitate the career development of young scientists returning to their home institution within 12 to 24 months , following completion of a graduate degree ( MSc or PhD ) or a post-doctoral fellowship . ISGs were designed to provide up to three years of support to an institution or research group to enhance infrastructure and the research environment . MIM grants [3] were used to provide support to core African research groups for the development of malaria control tools ( Box 1 ) . Information on all individuals and institutions that received grants between 2000 and 2012 was extracted from the TDR information management system and tabulated for range and scope of research topics . Trainees were contacted individually , through e-mail , to ascertain their willingness to participate in the career tracking survey and to update their personal information . From a total of 304 trainees identified , 117 trainees ( 39% ) responded positively while 187 did not respond , either due to out of date e-mail addresses or possible lack of interest . The questionnaire design was based on existing surveys of doctorate graduates conducted by the Organization for Economic Cooperation and Development ( OECD ) , Eurostat , the European Commission Marie Sklodowska-Curie actions , Wellcome Trust , UNESCO and the US National Science Foundation . The range of topics covered by the survey included demographics , mobility ( virtual , physical and sectoral ) , research outcomes , roles and responsibilities , competence development and skills utilization . Several drafts of the questionnaire were reviewed by the five participating organizations and pre-tested in-house by ESF staff members , with the final questionnaire peer-reviewed by two independent international experts . The resulting questionnaire contained 52 questions , written in English . Participants were informed about the detailed data protection and confidentiality arrangements that were in place for the survey such as the anonymization of replies before analysis . This included destroying all contact details before conducting any survey analysis and avoidance of any questions likely to collect sensitive or identifying information of any kind ( date of birth , thesis title , disciplinary field , institution name , etc . ) . Written assurance was also given that contact details would only be used for the purpose of contacting the trainees during the data collection phase . Since ESF is located in Strasbourg , France , the modalities of the survey were declared to the Commission Nationale de l’Informatique et des Libertés ( CNIL ) , the independent French authority protecting privacy and personal data . The list of TDR trainees and their contact details were shared with ESF and names and e-mail addresses entered into an online survey database . The survey was launched with an explanatory cover note from ESF in September 2014 . The questionnaire and an introductory message were sent to each of the 117 participants . Any queries received by the ESF team from participants were dealt with on an individual basis , including practical questions regarding completion of the questionnaire . The number of respondents was logged on a daily basis and the percentage of responses on a weekly basis . A total of five reminders to participate in the survey were sent . The survey was closed in November 2014 and all respondents were thanked for their participation . The survey data were imported into the Statistical Package for the Social Sciences ( SPSS ) for analysis by ESF .
Among the 304 TDR trainees identified , 117 trainees expressed availability to participate and were included in the survey . These included 54 RTG , 29 REG , 18 MIM and 16 ISG grants . Ultimately , 77 trainees responded to the survey ( 66% of those included ) . Unfortunately it was not possible to break down the analysis by grant as 68% responded to the question “Do you know the type of grant you received from TDR ? ” with “don’t know” and the survey was anonymous . WHO Member States are grouped into six regions: Africa ( AFR ) , the Americas ( AMR ) , South-East Asia ( SEAR ) , Europe ( EUR ) , Eastern Mediterranean ( EMR ) , and Western Pacific ( WPR ) . Profiles of the TDR trainees who responded to the survey are shown in Fig 1A . The majority of respondents came from AFR ( 53% ) ; 21% originated from AMR , mainly from Brazil ( 59% ) and Argentina ( 25% ) ; 11% were from SEAR , 11% from EMR and 4% from WPR . Of the 77 respondents , 58% were men and 42% were women ( Fig 1B ) . Representation of women was slightly higher than in the group of 304 initially contacted ( 62% men , 38% women ) . As shown in Fig 1C , women are well represented in all WHO regions except AFR where men are more represented ( 77% ) than women ( 23% ) . In EMR , women are more represented ( 70% ) than men ( 30% ) . In terms of age , the majority of respondents were between 35 and 45 ( 51% ) . Women were slightly older than men: 34% of women were above 50 years of age as compared to 18% of men . In all WHO regions , except AMR , the vast majority of women have children ( 92% ) but only 29% of women had children in AMR . Further investigation would be needed to understand any potential barrier for AMR women with children to access TDR training grants . Fifty-eight percent of men and 42% of women had other caring responsibilities such as care of an elderly person or an adult with a disability . In AFR , the majority of respondents were from English speaking countries ( 64% ) followed by French ( 33% ) and Portuguese ( 3% ) ( Fig 1D ) . The response rate ( number of trainees who responded to the questionnaire / number of trainees who received the questionnaire ) was higher in Francophone ( 87% ) than in Anglophone ( 55% ) trainee sub-groups . When aiming at enhancing support to Francophone and Lusophone countries , further study may be needed to better understand the factors involved . The 77 respondents were supported by TDR to obtain either a MSc ( 14 respondents ) , a medical doctorate ( MD ) ( 5 respondents ) or a PhD ( 58 respondents ) . All trainees studying for a master’s degree obtained their degree through structured means , involving a combination of defined courses and independent research . For trainees studying for a PhD , the majority of respondents ( 86% ) achieved their degree through the traditional means of an independent research study under the guidance of a supervisor and only 14% through structured means . There was no relationship between the time taken to complete the degree and the structure followed . There was also no difference in the time taken and the structure followed to complete their degree between men and women . The median time taken by respondents to complete their PhD was four years . Support provided by TDR did not always cover the full duration of the degree and ranged from one year ( 28% ) or less ( 6% ) to two years ( 20% ) , three years ( 25% ) , or more ( 21% ) . More men were supported for three years ( 30% ) as compared to women ( 19% ) , and more women were supported for one year or less ( 39% ) as compared to men ( 30% ) . The reasons for the variation of length of support are not clear . It would be important to better understand why duration of support was shorter for women than for men and what the implications were . Indeed early career support to acquire a degree is known to be a key factor for career development and a potential future leadership role [5] . Eight respondents ( seven men from AFR and one woman from AMR ) took a career break for one year or more . Of the seven men , only one found it very difficult to return to their previous position . The only woman who took a study break found it relatively easy to return to her position . However , the reasons for having taken a study break were not clearly explained; a more explicit question will be added in the next survey . A proportion of respondents ( 35% overall ) moved outside of their country of origin to complete their degree , the majority from AFR . Forty-one percent of AFR respondents who moved abroad went to high-income countries , mainly in North America and Europe . Overall , 65% of respondents completed their degree in their region of origin . Seventy-nine percent of TDR grantees from AFR who completed their degree in their region of origin were trained in three countries: Kenya , Nigeria and South Africa . Sixty-nine percent of TDR grantees from AMR who completed their degree in their region of origin were trained in Argentina and Brazil . All of the countries where training took place have a relatively high national gross domestic income , with a well-developed health research structure and capabilities [6] . Thus , the survey showed the great benefit of TDR and other agencies supporting capacity strengthening programmes to promote collaboration between scientists in countries with more advanced health research capacities and countries with lower health research capacities within the same region . The gain of south-south collaboration as compared to north-south collaboration in term of career development was analysed based on the 41 trainees from AFR . Fifteen ( 15 ) studied in high-income countries ( north-south collaboration ) , 20 studied in three other African countries ( Kenya , Nigeria and South Africa ) ( south-south collaboration ) while six studied in their own country . There was no difference in response to the different questions between trainees who studied in high-income countries and those who studied regionally . This may suggest that south-south collaborations are as effective and at a lower cost than north-south collaborations . All of the TDR trainees who responded to this survey were employed , with 95% holding a position at a university or research institution and 89% working as academic researchers . Fig 1E provides details of TDR trainees’ current employment . Most of the respondents held a full-time position with more than 30 hours per week ( 92% ) in either a permanent ( 83% ) or temporary position ( 9% ) . Women were more often in permanent full time positions ( 91% ) than men ( 78% ) . While the number is small , only men were self-employed ( 2% ) . The vast majority of respondents worked in the public sector ( 83% ) in non-profit ( 79% ) or for-profit ( 4% ) institutions , followed by the private sector ( 12% ) and others , including public-private partnerships ( 2% ) . Twenty eight ( 28% ) were directly funded by their employer , while 72% were employed on grants funded by some other external party . Table 1 presents TDR respondents working as academic researchers ( 89% ) by career stages as per the Frascati definition [7 , 8] . The only difference between men and women was that a higher proportion of women described themselves as R1 researchers ( first stage ) and more often they held positions as junior researchers . This was the case for all WHO regions . The minority not working as researchers ( 11% ) were asked to indicate the reason ( s ) for this . The most common reasons cited were the difficulty of obtaining a suitable academic research position ( 100% ) , the difficulty to secure a tenured post ( 100% ) , the lack of research career opportunities ( 80% ) and the low remuneration in research positions ( 75% ) . In terms of occupational areas , the highest proportion of respondents worked in life sciences ( 47% ) , followed by education ( 34% ) , training ( 31% ) , healthcare ( 31% ) that included healthcare practitioners and healthcare support occupations , social sciences ( 5% ) and administrative support . Table 2 clearly shows that a higher proportion of men were involved in management . However , similar proportions of women and men worked in life sciences , education , healthcare , social sciences and administrative support . There was no difference based on country of origin , country of study , country of work and their career stages . In general , it is quite difficult to compare salaries across the geographical spread of the various WHO regions . However , some gender differences in salary levels were evident , since a higher proportion of women earned less than €20 000 per year ( 55% women versus 44% men ) regardless of the region of origin . This is perhaps due to the fact that women more often held positions of junior researchers ( Table 1 ) . It could also reflect the worldwide issue of the gender pay gap . The survey asked respondents to indicate in how many different countries they had physically studied or worked for a period of more than three months during and after TDR support ( physical mobility ) . The majority of respondents had studied and worked solely in their own country ( 72% ) while 28% percent had studied or worked in other countries . It is worth noting that international physical mobility was higher for AFR respondents ( 48% ) . In general the survey showed a strong mobility to countries with more advanced health research capacities . The highest international physical mobility was to Europe ( 60% ) and North America ( 38% ) then Argentina and Brazil ( 11% each ) and Australia ( 7% ) . Virtual mobility , or collaboration via information and communication technology platforms , was also considered . The majority of respondents ( 75% ) acknowledged virtual mobility had taken place solely within their own countries . From the 25% remaining respondents , the highest international virtual mobility was to countries in Europe ( 46% ) and North America ( 31% ) . As was the case with physical mobility , virtual mobility was higher for AFR respondents ( 42% ) . Interestingly , international physical mobility to Europe was higher than virtual mobility . The survey showed that 58% of respondents conducted research in collaboration with researchers based in another country , mainly in Africa , Europe and North America , through a joint publication ( 55% ) and/or a joint project ( 52% ) , in line with the mobility trends described above . There was a considerable proportion of respondents who reported having engaged in multidisciplinary research activities ( 81% ) . Multidisciplinary collaboration was reflected through either joint publications ( 81% ) , collaborating at distance with occasional face-to-face ( 67% ) or through web-based technologies ( 52% ) . Women seemed to engage in multidisciplinary approaches to a higher extent than men . Indeed , a higher proportion of women worked with researchers from a different field of expertise , either through joint publications ( 89% for women versus 74% for men ) or virtual collaborations ( 63% for women versus 44% for men ) . This could be due to the fact that more women work in the field of social sciences than men . In a previous study analysing TDR support of 116 research training grants , 11/36 ( 30 . 50% ) women and 11/80 ( 13 . 75% ) men worked in the domain of social sciences . However in a recent study analazing gender differences in scientific collaborations , it is clear that women in the natural sciences domain have more collaboration in other fields than men [9] . Further research would be needed to better understand why TDR women trainees tend to engage in multidisciplinary approaches more often than men . Intersectoral collaboration , in terms of joint activities between research institutions , industry or commercial ventures , was limited: 23% worked on a joint publication and 19% collaborated on a joint research project with industry . Men collaborated only slightly more frequently with industry ( 33% ) than women ( 26% ) . There is a clear need to encourage intersectoral collaboration . This could be done though promoting and fostering mobility between research institutions , government and nongovernmental agencies , and the public and private sectors . It would help to make the career perspective after graduation more attractive and to reduce existing barriers to collaborative work between these sectors . Some of these barriers to career development are attitudinal , reflecting a lack of knowledge and sometimes a negative perception that academic staff may have about a career outside the university’s walls . The quality of career mentorship provided at the doctoral level could be an essential element to help overcome these concerns . Other barriers could be structural and institutional , bringing into question the reliance on publication output as the sole or main criterion for scientific recognition and career development . Respondents , regardless of the region they came from , reported that they regularly used their doctoral skills in their current position ( 92% ) . They most often used these skills in managing research activities ( 74% of respondents dedicated more than 20% of their time to these activities ) . This was followed by staff management activities ( 47% ) , which included supervising students either at undergraduate and master levels ( 82% ) and/or PhD level ( 65% ) or supervising their peers’ work ( 75% ) ; teaching activities ( 46% dedicated more than 20% of their time ) and administrative activities ( 37% dedicated more than 20% of their time ) . Some dedicated time to transferring technology to industry ( 21% ) . There was no significant difference between genders in any of these activities . Respondents reported having made presentations at national ( 73% ) and international conferences ( 72% ) and women were more active than men in international presentations ( 75% for women versus 66% for men ) . Over 70% of respondents had been either lead authors ( 65% ) or co-authors ( 70% ) on peer-reviewed publications in the last 12 months . Similar proportions of men and women had been lead authors ( 69% for women versus 62% for men ) but a higher proportion of men were co-authors ( 55% for men versus 45% for women ) on peer-reviewed publications . In terms of research and development , 20% of respondents had produced new research software resources and 9% of them had filled a patent . None of them had registered or licenced a product in the last 12 months . Almost 25% of respondents claimed that their work had made a significant impact on influencing changes in policy and practice . This relatively low percentage could be due to the fact that respondents come from a largely academia-based group ( 98% held a position in university or in research institutions and 89% worked as academic researchers ) which usually report impact more through publications , conference presentations and research awards . All trainee contact details or other identifying information of any kind ( date of birth , thesis title , disciplinary field , institutional name , etc . ) were destroyed before conducting any analysis . As a consequence , there was no possibility to verify if the work of the trainee had an impact on policy and practice . However , this percentage suggests the need to maintain and enhance efforts to bridge the gap between health research and policy-making and practice , as well as the need to capture such evidence in a systematic way . Indeed , the lack of evidence on translating research results into health policies , interventions or new tools has been identified for decades as a weakness in the evaluation of research capacity strengthening organizations [10] . Activities to communicate results to the public had been undertaken by 30% of respondents and media coverage was achieved by 22% of respondents . Men were more likely than women to claim impact on policy and practice changes ( 29% versus 19% ) , to communicate to the public ( 40% versus 16% ) and to receive media coverage ( 27% versus 16% ) . Respondents were asked to rate the importance of TDR support on achieving their professional career goals . Eighty ( 80 ) percent rated TDR support as very important , and 91% of respondents rated the TDR support as very or fairly important; no difference was observed between genders . This outcome is substantially higher when compared to the other four organizations involved in this survey , which scored an average of 54% of importance with the support received . These results confirm the need for research capacity strengthening in low-and middle-income countries and the catalytic role that TDR has played in research career development . Two additional elements , the first post-doctorate employer and the academic advisor , were rated as important for career progression by 64% and 63% of the respondents , respectively . The post-degree career choices made by the respondents were strongly influenced by academic considerations . The most important reason influencing the decision to accept a post-doctorate position was the willingness to get additional training in the same area of their degree ( 70% ) . This was seen as a necessary step towards the employment they aspired to ( 67% ) . This is an important result to be taken into consideration when implementing future research capacity strengthening programmes for development . Increasingly , countries have identified the need for building capacity in research for implementation in order to enhance health care delivery and reach vulnerable populations . Research for implementation helps solve implementation bottlenecks , identify optimal approaches for real life settings and speed up the bench-to-bedside translation . TDR has recently shifted its strategic focus toward research for implementation , and is building upon capacity already developed with previous trainees .
The survey generated valuable information that highlighted the positive impact of TDR training grants on the research career development of its trainees . The response rate ( 68% of all TDR trainees contacted ) was high in comparison to average online surveys ( 30% ) [11] . However , this study presents two main limitations . Fist the population of TDR grantees who responded is small , i . e . 77 respondents from the 117 TDR trainees who had a valid e-mail ( 66% ) and from the total of 304 TDR trainees ( 25% ) who had initially been contacted . This illustrates the challenges to maintain contact with past trainees , as identified in previous evaluations of TDR’s capacity building activities [2] . In order to help keep track of former trainees , TDR launched the TDR Global initiative in 2016 . The TDR Global platform , is an efficient and flexible web-based platform based on an existing open access “research networking tool” . It builds profiles of researchers affiliated to TDR and maps their expertise , their research activity and academic networks based mainly on their publications and co-authorship . The platform also helps track their career and professional achievements based on data they provide . This platform was launched publicly in November 2016 and data on its use and utility are being collected [12] . In addition , influence of the trainee’s selection on the training intervention outcome is difficult to assess . The current survey was not designed to analyse this element . Heads of institutions supported by TDR expressed in a previous survey [2] that TDR supported training had a high impact on the ability to develop research project . This , suggests that at least TDR supported training made a difference in some research skills . The results presented in this paper highlight the important link perceived by respondents between TDR support and their career advancement . Most of the trainee respondents ( 80% ) rated TDR support as a very important factor that influenced their professional career achievements . In order to address the potential social desirability bias ( i . e . respondent giving a positive answer to please the questioner ) a multiple choice questionnaire was included asking the importance of: ( 1 ) sponsoring organization; ( 2 ) the PhD supervisor/ mentor; and ( 3 ) the employer . A high proportion of respondents ( 89% ) remained in the field of research . The return rate to their region of origin ( 96% ) is high with a very limited ‘brain drain’ rate to high-income countries ( 4% ) . These results do not take into account the 75% of trainees who could not be followed up . The TDR Global platform should potentially allow for a more comprehensive analysis . In the meantime , in order to assess the level of trainees who remained in the field of research , TDR developed a short survey on 212 trainees supported by TDR in Brazil . Brazil has a national research information system called Lattes which is coordinated by the Brazilian National Council for Scientific and Technological Development ( CNPq ) . It is mandatory for researchers to fill in their profile on Lattes in order to apply for grants , faculty positions or staff appraisal . A search in the public interface of Lattes ( http://lattes . cnpq . br/ ) showed that 86% of the 212 Brazilian TDR trainees had updated their profile in Lattes in the past two years and were still involved in research . Although Brazil is merely an illustrative example , this result reinforces the role of TDR on developing research capacity in low- and middle-income countries . For decades , research capacity strengthening programmes targeting scientists in LMICs focused on north-south collaboration . According to the UNESCO Science Report 2015 , from 2008 to 2014 , the top three partners for the Economic Community of West African States ( ECOWAS ) came from France , the United States of America , and the United Kingdom , in that order [13 , 14] . During this period , efforts increased research productivity in LMICs to a small extent . For example , in Sub-Saharan Africa the number of researchers rose from 0 . 9% to 1 . 1% ( 58 800 to 82 000 ) while in South Africa the number of researchers remained stable ( 0 . 3% ) . According to the same report , between 2008 and 2014 , the percentage of worldwide scientific articles from Sub-Saharan Africa rose from 1 . 2 to 1 . 4 and from 0 . 5 to 0 . 7 in South Africa . Some programmes have promoted a south-south collaboration approach to effectively address local health research problems and needs . An example is the Consortium for Advanced Research Training in Africa ( CARTA ) which is part of the African Institutions Initiative supported by the Wellcome Trust . CARTA aims to make a difference by rebuilding and strengthening the capacity of African universities to train locally skilled researchers [15] . A real time evaluation of the first four years of the CARTA programme [16] shows that although a critical mass of PhD and MSc graduates has been created , the long term impact , as for all the capacity building programmes , is still to be demonstrated . Indeed , although south-south collaboration should offer the possibility of facilitating the transfer of knowledge and best practices across the institutions [15] , the effectiveness of this approach has to be carefully analysed [17] . The results presented in this article do not show any difference for a respondent from AFR , whether they studied in an LMIC or a HIC . This highlights the potential cost effectiveness of south-south collaboration . Collaboration across regions encourages mobility which is an important factor to develop independence following a post-doctoral position and gain leadership skills . Interestingly , most of the TDR trainee respondents worked in their own region during the period following their TDR grant . It would be important in a future study to analyse the factors involved in this low level of mobility and the level of south-south collaboration as well as north-south-south collaboration . The survey also identified the challenges , bottlenecks and opportunities that trainees faced at various stages of their research careers . Although women are well represented in most WHO regions ( except AFR ) , they do not always reach the same level and salary as men do . As a result of this survey , TDR initiated a new Women in Science programme to explore how to help more women enter and stay in science careers . Factors influencing access to TDR training grants from non-English speaking countries have not been identified properly and would need to be studied in future surveys . The lessons learnt from this study are summarized below: The results of this study help highlight some factors influencing the effectiveness of TDR’s capacity strengthening programmes from 2000 to 2012 . Lessons learnt could also help donors and policy-makers when setting programmes and funding priorities .
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The Special Programme for Research and Training in Tropical Diseases ( TDR ) co-sponsored by UNICEF , UNDP , World Bank and WHO has been providing training grants to strengthen research capacity in low- and middle-income countries for over 40 years . In order to assess to what extent TDR’s grants made a difference on the career development of these grantees , a survey tool was developed and implemented in collaboration with the European Science Foundation . The survey was answered by 77 individual trainees who completed their degree ( masters or PhD ) with support from TDR between 2000 and 2012 . The study provided valuable information on factors involved in the career development of the trainees and influencing the local retention of the capacity that has been built , to prevent “brain drain” . Encouraging aspects , such as a 96% of the capacity being retained locally , a 92% full-time employment rate at the time of the survey , or 89% of the respondents still working in research showed the positive influence of TDR’s capacity strengthening grants on researchers’ career development . This was in line with 80% of the respondents rating TDR’s support as “very important” . The challenges , lessons learnt and further opportunities identified may be helpful to donors and policy-makers when designing research capacity programmes , fostering south-south collaboration , and setting funding priorities .
|
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2017
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Tracking the career development of scientists in low- and middle-income countries trained through TDR’s research capacity strengthening programmes: Learning from monitoring and impact evaluation
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Despite World Health Organization ( WHO ) prequalification of two safe and effective oral cholera vaccines ( OCV ) , concerns about the acceptability , potential diversion of resources , cost and feasibility of implementing timely campaigns has discouraged their use . In 2012 , the Ministry of Health of Guinea , with the support of Médecins Sans Frontières organized the first mass vaccination campaign using a two-dose OCV ( Shanchol ) as an additional control measure to respond to the on-going nationwide epidemic . Overall , 316 , 250 vaccines were delivered . Here , we present the results of vaccination coverage , acceptability and surveillance of adverse events . We performed a cross-sectional cluster survey and implemented adverse event surveillance . The study population included individuals older than 12 months , eligible for vaccination , and residing in the areas targeted for vaccination ( Forécariah and Boffa , Guinea ) . Data sources were household interviews with verification by vaccination card and notifications of adverse events from surveillance at vaccination posts and health centres . In total 5 , 248 people were included in the survey , 3 , 993 in Boffa and 1 , 255 in Forécariah . Overall , 89 . 4% [95%CI:86 . 4–91 . 8%] and 87 . 7% [95%CI:84 . 2–90 . 6%] were vaccinated during the first round and 79 . 8% [95%CI:75 . 6–83 . 4%] and 82 . 9% [95%CI:76 . 6–87 . 7%] during the second round in Boffa and Forécariah respectively . The two dose vaccine coverage ( including card and oral reporting ) was 75 . 8% [95%CI: 71 . 2–75 . 9%] in Boffa and 75 . 9% [95%CI: 69 . 8–80 . 9%] in Forécariah respectively . Vaccination coverage was higher in children . The main reason for non-vaccination was absence . No severe adverse events were notified . The well-accepted mass vaccination campaign reached high coverage in a remote area with a mobile population . Although OCV should not be foreseen as the long-term solution for global cholera control , they should be integrated as an additional tool into the response .
Provision of safe water and proper sanitation are without doubt the long-term and only solution for cholera control [1] , [2] . However , controlling cholera globally is far from being achieved; the disease burden is increasing with large-scale outbreaks reported in the past several years , such as those in Haiti and Zimbabwe [3] . Current outbreak response interventions focus on case management and access to health care , as well as the immediate provision of safe water and hygiene promotion [1] . However , current outbreak control activities have proven insufficient to avoid massive numbers of cases and deaths in recent large-scale outbreaks . The adequate treatment of cases for example , although crucial to decrease mortality , has a limited impact in controlling disease spread [1] , [3] . Oral cholera vaccines ( OCV ) , which have the potential to reduce the number of cases and minimize the spread of disease [4] , [5] , could be an important addition to the cholera response arsenal [1] , [6] , [7] . The World Health Organization ( WHO ) prequalifies the OCV Dukoral ( SBL Vaccine/Crucell , Sweden ) and Shanchol ( ShantaBiotechnics , Hyderabad , India ) . Both are killed whole cell V . cholerae O1 vaccines; Shanchol also contains V . cholerae O139 and Dukoral the recombinant cholera toxin B subunit . The two vaccines share a good safety and efficacy profile with an estimated protection of 60–85% for 2–3 years [1] . Although , recommended by WHO ( including in response to outbreaks since 2010 ) [8] , their use as public health tools has been limited . Specifically , questions about the acceptability , feasibility , cost and potential diversion of resources have discouraged the use of OCV for outbreak control [9] . In 2012 , the Ministry of Health ( MoH ) of Guinea , with the support of Médecins Sans Frontières-Operational Centre Geneva ( MSF ) organized the first cholera outbreak response in Africa using an OCV in the Republic of Guinea ( Guinea ) . This was also the first time that Shanchol was used in a mass vaccination campaign on the African continent . Cholera has been reported in Guinea since 1970 . The largest outbreak was in 1994 with more than 30 , 000 cases and 670 deaths reported . The most affected areas were the coastal prefectures and the islands ( Maritime Guinea , where the capital Conakry is located ) [10] . From 2003 to 2007 , cholera outbreaks were reported each year during the rainy season ( July–August ) throughout the country with Maritime Guinea remaining the most affected area . From 2008 to 2011 , only sporadic cases were reported [11] . In 2012 , the first cholera cases were reported in Forécariah ( Maritime Guinea ) before the rainy season . From February 2 to March 8 , a total of 147 cases and 13 deaths were reported . On March 3 , the first case was reported and confirmed in Conakry . A cholera outbreak was also on going in neighbouring Sierra Leone , with 13 , 934 cases and 232 deaths reported countrywide between January and August 2012 [12] . The regional nature of the epidemic , the early notification of cases before the peak of the rainy season and the long interval without outbreaks , thereby increasing the number of susceptible individuals due to lack of prior exposure , all suggested the possibility of a large epidemic in Guinea in 2012 . Case management , water , health education , hygiene and sanitation interventions were implemented in response to the outbreak . Non-selective mass vaccination campaigns were implemented in the prefectures of Boffa and Forécariah ( Figure 1 ) . Two doses of Shanchol , two weeks apart were offered from April 18 to May 14 , 2012 in Boffa and from May 27 to June 15 , 2012 in Forécariah ( Figure 2 ) . Overall , 316 , 250 vaccines were delivered by 43 teams ( of 9 members in Boffa and 5 in Forécariah ) in 287 vaccination sites ( one per village or settlement ) . All individuals older than 12 months were eligible for vaccination in both rounds . Pregnant women were offered vaccine after a careful examination of the risk and benefits ( an on-going outbreak in a remote rural place with limited access to health care and high cholera associated mortality in the past ) following the manufacture and WHO recommendations [8] . Vaccines were stored under cold chain , but were transported and used at ambient temperature on vaccination days . Before administration , vaccine vial temperature monitor was checked for stability and all remained valid . Here , we present the results of household-based vaccination coverage and acceptability surveys and surveillance of adverse events .
All individuals older than 12 months , resident in the six sub-prefectures bordering the sea in Boffa prefecture ( Koba , Boffa-centre , Douprou , Tougnifily , and part of Mankountan and Tamita ) and in the sub-prefectures of Kaback and Kakossa in Forécariah prefecture were targeted for vaccination and were eligible for inclusion in the survey ( Figure 1 ) . The coastal area of Boffa combines both inland areas and several islands . Kaback and Kakossa are two separate islands . Residents were defined as persons living ( sleeping and eating ) in the area for at least the previous two weeks . The adult population is mobile with men in particular , leaving and returning to the area for fishing , agriculture and trade . A representative sample of the population in each survey site ( Boffa and Forécariah ) was selected using cluster-based sampling with population proportional to size [13] . To sample households within the selected sectors , all households were enumerated . The first household was selected with the aid of a random number table and subsequent households were selected by proximity ( first household to the left ) . In the urban area of Boffa and in Kaback Island in Forécariah , satellite-map based sampling was used to select randomly the starting point of the cluster [14] . This methodology was used in urban Boffa because of the large number of households to enumerate and in Kaback Island because of the absence of accurate population data per sector . The sample size was calculated to obtain a representative estimate of the proportion of residents who received two doses of OCV by age group ( 1–4 , 5–14 , 15 years and older ) . Sample size was calculated to ensure a sufficiently precise estimate for children aged 1 to 4 years as this group was the smallest . We considered the following assumptions: 70% of children would receive two doses of vaccine , alpha error of 5% , absolute precision of 7% for Boffa and 10% for Forécariah , design effect ( deff ) of 3 . 0 for Boffa and 1 . 5 for Forécariah ( coverage was expected to be more homogenous in the islands ) . Taking into account the results of the 2005 Demographic and Health Survey [15] , we expected 0 . 7 children 1–4 year old per household ( average of 6 . 1 individuals per household and 12% of the population between 1 and 4 years ) . Assuming 10% of missing data , we planned to visit 780 households ( 60 clusters of 13 households ) in Boffa and 180 households ( 30 clusters of 6 households ) in Forécariah . A household was defined as a group of people sleeping under the same roof and sharing meals every day for at least the previous two weeks . All surveyors and supervisors were recruited locally and received a theoretical and practical training . Training consisted of survey and interview methodology and a pilot implementation of the questionnaire . Teams conducted face-to-face interviews after consent . Survey teams asked for the help of neighbours to trace absentees and re-visit empty ( but not abandoned ) households later in the day . If during the second visit the occupants could not be found or if they refused to participate , that household was skipped . A standardized pre-piloted questionnaire was used to collect the following information: demographic data ( age , sex , and household size ) , vaccination status ( card-confirmed and orally reported ) , reasons for non-vaccination ( open question ) , and acceptability data ( adverse events , taste and beliefs about the vaccine ) . Questions concerning acceptability were only collected in Boffa ( first site of vaccination ) in participants older than 15 years . Interviews were conducted in the local language . Surveillance of adverse events following immunization ( AEFI ) was implemented at vaccination sites , health centres and health posts in the target areas . An AEFI was defined as a medical occurrence detected by the vaccination site supervisor or a physician with an onset up to 14 days after receipt of a dose of vaccine . During the awareness campaign and at the time of vaccination , participants were told to report to a vaccination site or a health centre if they felt ill after receiving the vaccine . The following data were collected using a standardized form: age , sex , pregnancy , history of allergies , vaccination date , consultation date , date of onset of the symptoms , type of symptoms , and clinical outcome ( recovery , transfer or death ) . Our main outcome was the OCV coverage ( single dose and full course ) in each of the target locations . Vaccine coverage was calculated dividing the number of individuals reporting being vaccinated by the survey population and expressed as a percentage . Vaccination coverage estimates include both card-confirmed and oral reporting . Secondary outcomes included vaccine coverage by age group , sex and reasons for non-vaccination . Crude vaccination coverage estimates and 95% confidence intervals ( 95% CI ) were obtained considering the survey design . The design effect was calculated to estimate the loss of precision due to the cluster based sampling strategy . Sampling weights were calculated to account for differences in the cluster size . Data entry was performed using EpiData 3 . 1 ( EpiData Association , Denmark ) and data analysis was performed using Stata 12 . 0 ( College Station , USA ) . The Ethical Review Board of Guinea and the MSF Ethical Review Board approved the study protocol . Oral informed consent was obtained from participants in all instances . All children had consent given from a parent/guardian and all adult participants provided their own consent . Oral informed consent was requested since the study did not present any risk of harm to subjects and did not involve procedures for which written consent is normally required outside the research context . The procedure was approved by the ethical review boards . The request of consent was registered in a log-book . Privacy and confidentiality of the data collected from participants was ensured both during and after the conduct of the surveys . All treatment was provided free of charge and participation was voluntary .
Vaccination card retention was higher for children ( 81 . 7% ) than adults ( 74 . 8% ) , and higher for females ( 82 . 4% ) than males ( 73 . 2% ) . Overall , 89 . 4% [95%CI: 86 . 4–91 . 8%] and 87 . 7% [95%CI: 84 . 2–90 . 6%] were vaccinated during the first round and 79 . 8% [95%CI: 75 . 6–83 . 4%] and 82 . 9% [95%CI: 76 . 6–87 . 7%] during the second round in Boffa and Forécariah respectively . The two dose ( fully vaccinated ) vaccine coverage ( including card and oral reporting ) was 75 . 8% [95%CI: 71 . 2–79 . 9% , deff = 10 . 1] in Boffa and 75 . 9% [95%CI: 69 . 8–80 . 9% , deff = 5 . 0] in Forécariah . Considering incomplete vaccination , 93 . 3% [95%CI: 91 . 1–95 . 0% , deff = 5 . 9] received at least one dose in Boffa and 94 . 9% [95%CI: 91 . 8–96 . 9% , deff = 3 . 7] in Forécariah . The dropout rate between the first and second dose was 15 . 2% [95%CI: 12 . 2–18 . 7%] and 13 . 6% [95%CI: 9 . 7–18 . 7%] in each site respectively . Vaccine coverage was lowest among adults in both prefectures ( Figure 4 ) . Vaccine coverage with two doses was similar among females and males in Boffa ( 76 . 6% [95%CI: 71 . 9–80 . 7%] vs . 75 . 0% [95%CI: 69 . 8–79 . 4%] ) , but higher among females in Forécariah ( 79 . 4% [95%CI: 74 . 4–83 . 6%] vs . 71 . 4% [95%CI: 63 . 3–78 . 3%] ) . Vaccine coverage among women in childbearing age ( 15–49 years old ) was statistically higher than among men of same age in Forécariah ( 72 . 6% [95%CI: 65 . 4–78 . 8%] vs . 53 . 4% [95%CI: 41 . 6–64 . 8%] , p<0 . 001 ) , but not in Boffa ( 70 . 1% [95%CI: 63 . 8–75 . 7%] vs . 64 . 3% [95%CI: 56 . 1–71 . 7%] , p = 0 . 1 ) . No major differences were observed in vaccination coverage by sub-prefecture ( Table 1 ) . Regarding the awareness campaign , 95 . 7% of survey participants [95%CI: 94 . 2–96 . 8%] reported being aware of the campaign . Among individuals not vaccinated , the main reason was “absence during the campaign” for both the first and second rounds . The second most reported reason was “not having time to go for the vaccination” and the third , “sick during the campaign” ( Table 2 ) . AEFI was reported as the reason for non-vaccination by 0 . 9% of non-vaccinated individuals during the second round . A small percentage of participants considered that the vaccine made them feel sick ( 3 . 9% [95%CI 2 . 4–4 . 7%] ) . A large proportion of participants reported that the taste of the vaccine was bad ( 77 . 6% [95%CI 69 . 5–84 . 1%] ) . Among those vaccinated 1 . 4% [95%CI: 0 . 8–2 . 2%] reported spitting out or vomiting the vaccine . However , 98 . 9% [95%CI 97 . 8–99 . 5%] reported that they would be vaccinated again in a future cholera campaign . Overall , 48 patients ( 15 per 100 , 000 vaccinated ) spontaneously reported symptoms that were linked with the vaccine by the health personnel and considered as AEFI with 35 ( 20 per 100 , 000 vaccinated ) after the first round and 13 ( 9 per 100 , 000 vaccinated ) after the second round . In total , 29 were women ( 60% ) and the median age was 27 years ( IQR: 16–36 years ) ; 8 ( 17% ) were children 1 to 4 years . Seven patients reported having a history of allergies ( 15% ) . The cause of the allergy was specified for two patients ( quinine and chloroquine ) . The average delay between vaccination and symptom onset was 24 hours with a median delay of 7 hours ( IQR: 1–24 hours ) . One quarter reported the symptoms in the following hour after vaccination . Symptoms reported ( n = 139 ) were mainly gastro-intestinal: 28 ( 20% ) diarrhea , 22 ( 16% ) vomiting , 14 ( 10% ) stomachache and 12 ( 9% ) nausea . In addition , 15 patients ( 11% ) reported fever and general weakness . No patient was transferred to a hospital and no deaths were reported .
The high coverage and good acceptability of the campaigns , conducted in a rural mobile population in Guinea , is encouraging . The percentage of people reporting AEFIs was low and almost all participants reported that they would be vaccinated in a future campaign . However , more evidence is needed about the feasibility of reactive campaigns from densely populated urban scenarios where cholera burden is high and cholera outbreaks evolve faster [16]–[20] . Also the acceptability of target campaigns in such a context should be assessed from a political , public health and community point of view . Determining the short-term protection given by the first dose is a clear priority as an effective one-dose regimen would facilitate the ease and timeliness of reactive campaigns in all contexts . There are several key limitations of note . Despite the short time span between the vaccination campaign and the data collection for the surveys , we were not able to card-confirm vaccination status for 25% of participants and as a result some information bias may be present . Considering those individuals as not-vaccinated ( worst-case scenario ) , two-dose coverage would decrease to 61% in Boffa and 64% in Forécariah . Second , the precision of estimates was better than expected because the number of participants recruited was higher ( linked with the household size composition ) than originally planned . However , population estimates in the surveyed areas are likely to be inaccurate . In most areas , no major differences were observed between administrative and survey coverage , but in Kaback an important deviation was observed . Inaccuracies in the population data could have caused some imbalances in the allocations of clusters; as described , we tried to avoid this problem using spatial sampling in Kaback . An additional limitation concerns the use of a quantitative approach to explore campaign acceptability . Although reasons for non-vaccination were specifically collected using an open question , we cannot exclude the possibility that the population may not have understood certain awareness and education messages . A qualitative assessment would aid in understanding better reasons for non-vaccination , elucidate possible solutions and provide a better understanding of the perception of the vaccination campaigns by the population . There are few examples where OCVs have been used as public health tools . Dukoral was used pre-emptively in refugee camps in Uganda and Darfur [21] , [22] and in endemic areas ( Zanzibar and Mozambique ) [23] , [24] . Shanchol has been recently used in Haiti in a pilot campaign [25] . To our knowledge there are only two published examples of reactive campaigns using OCV , and both were conducted in Asia [26] , [27] using vaccines not prequalified by the WHO . The coverage and acceptability of these campaigns varied depending on the setting and the approach ( pre-emptive vs . reactive ) . High coverage was obtained in Uganda , Darfur and Micronesia [21] , [22] , [26] and lower coverage was obtained in Mozambique , Zanzibar and Vietnam [23] , [24] , [27] . In Guinea we obtained 76% coverage for two doses and 93% of the population received at least one dose , which represents , to our knowledge , one of the highest coverage reached [21]–[24] , [26] , [27] . The high coverage obtained is a promising outcome considering that this was one of the largest campaigns conducted in terms of number of doses administered , the specificities of the population ( rural and mobile ) , and the short time available for preparation of the campaign , which has been one of the major arguments against outbreak response with OCV . There are several factors that likely influenced the population to participate in the campaign: first , the campaign was conducted in response to an outbreak and the possibility of even partial protection against a frightening disease was motivating . Second , the population may have been reassured by the involvement of the MoH , public health authorities and MSF; as an example , the vaccination campaign was inaugurated in Boffa with the presence of the Minister of Health . This involvement was also crucial to mobilize human resources and to organize the campaign considering the local specificities . Finally , both the awareness campaign and the vaccination strategy itself ( decentralized with sites organized in each village or settlement ) involved the communities . This aimed to ensure awareness and provide vaccination opportunities to remote places and difficult to reach population which likely contributed to this high coverage . Vaccination activities started early in the morning and finished late in the afternoon to maximize the opportunities for workers in the main fishing ports . Despite these efforts , the lowest coverage was obtained in adult males . Significant differences where observed by sex in Forécariah , especially in individuals between 15–49 years old . The vaccination campaign in Forécariah coincided with an intense period in agriculture activities , which was a barrier for the participation in the campaign , especially for the male adults . In addition , the Red Cross Society of Guinea distributed soap and a bottle of chlorine solution to women of childbearing age in Forécariah during the second round of vaccination , which likely increased the coverage in this group . Distribution of soap and chlorine was one of the control measures implemented by the MoH in response to the outbreak in the affected places , but this activity was successfully integrated in Forécariah within the vaccination sites . This suggests that synergies among different preventive approaches is an element to consider in future campaigns both to provide a more comprehensive message on cholera prevention and to improve the vaccine coverage itself . The number of AEFI reported through the surveillance system was low , without severe AEFI reported . Only a small proportion of non-vaccinated individuals during the second round of vaccination reported AEFI as a cause of non-vaccination . This result is coherent with previous publications on vaccine safety where mild symptoms ( mostly not requiring medical attention ) have been reported [28] , [29] . The proportion of vaccinated individuals reporting AEFIs was lower in our study than in the cluster randomized clinical trial conducted in Kolkata ( 15 vs . 76 per 100 , 000 ) [28] . This difference is probably explained by: first , our surveillance system was passive compared with the active case finding implemented in Kolkata; and second , access to health care was likely more difficult in the vaccinated area in Guinea ( remote rural area ) than in the urban context of Kolkata . With respect to the proportion of vaccinees vomiting or spitting out the vaccine after intake , we found a higher percentage than previously documented with Dukoral ( no data available for Shanchol ) [23] . For administration of Dukoral , the vaccine has to be diluted in water containing a buffer solution . Although administration with water is not necessary for Shanchol , we offered water after vaccine intake . Most vaccinated individuals did not like the taste of the vaccine and offering water may have contributed to fewer incomplete vaccine courses . Additional information should be collected in future campaigns using Shanchol , considering that providing water considerably increased the logistic complexity of the campaign . In order to facilitate the use of OCV as an additional tool , WHO and partners are in the process of creating a vaccine stockpile dedicated to outbreak response [30] . Here , we showed that high coverage can be reached within a few weeks , even in rural areas , and that the campaigns were well accepted by the population . Good documentation of these interventions is essential to elucidate the strategies leading to successful outcomes as well as key implementation barriers . Synergies between different axes in cholera control interventions should be pursued and other examples of integrated cholera response than the one presented here should serve also to determine the best use of vaccines for cholera prevention and control .
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Two safe and effective oral cholera vaccines are recommended by the World Health Organization for cholera prevention and control; however , concerns about the acceptability , potential diversion of resources , cost and feasibility of implementing timely campaigns has discouraged their use . In 2012 , the Ministry of Health of Guinea , with the support of Médecins Sans Frontières , organized the first mass vaccination campaign using a two-dose oral cholera vaccine ( Shanchol ) as an additional control measure to respond to an on-going nationwide epidemic . This was also the first time that Shanchol was used in a mass vaccination campaign on the African continent . High coverage was reached within a few weeks , and the campaigns were well accepted by the population . Synergies between different axes in cholera control interventions should be pursued as described here , and although oral cholera vaccines should not be foreseen as the long-term solution for global cholera control , they should be integrated as an additional tool into the outbreak response strategies .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2013
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First Outbreak Response Using an Oral Cholera Vaccine in Africa: Vaccine Coverage, Acceptability and Surveillance of Adverse Events, Guinea, 2012
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Complex diseases and traits are likely influenced by many common and rare genetic variants and environmental factors . Detecting disease susceptibility variants is a challenging task , especially when their frequencies are low and/or their effects are small or moderate . We propose here a comprehensive hierarchical generalized linear model framework for simultaneously analyzing multiple groups of rare and common variants and relevant covariates . The proposed hierarchical generalized linear models introduce a group effect and a genetic score ( i . e . , a linear combination of main-effect predictors for genetic variants ) for each group of variants , and jointly they estimate the group effects and the weights of the genetic scores . This framework includes various previous methods as special cases , and it can effectively deal with both risk and protective variants in a group and can simultaneously estimate the cumulative contribution of multiple variants and their relative importance . Our computational strategy is based on extending the standard procedure for fitting generalized linear models in the statistical software R to the proposed hierarchical models , leading to the development of stable and flexible tools . The methods are illustrated with sequence data in gene ANGPTL4 from the Dallas Heart Study . The performance of the proposed procedures is further assessed via simulation studies . The methods are implemented in a freely available R package BhGLM ( http://www . ssg . uab . edu/bhglm/ ) .
Many common human diseases and complex traits are highly heritable and are believed to be influenced by multiple genetic and environmental factors . Genome-wide association studies ( GWAS ) represent a powerful way for discovering disease-associated factors and investigating the genetic architecture of complex diseases [1] . In the past few years , these studies have identified hundreds of common variants ( i . e . , genetic variants with minor allele frequency ( MAF ) >∼5% ) associated with complex diseases [2] . However , the estimated effect sizes for the identified variants are small ( most odds ratios are below 1 . 5 ) and explain only a small proportion of the heritability of complex diseases [2] , [3] , motivating research interest in finding ‘missing’ genetic factors that contribute to the remaining heritability [4] , [5] . Many explanations for the missing heritability have been suggested [4] , [5]; one is that many common variants with much smaller effects are yet to be detected , and another is the possible contribution of rare variants ( MAF <0 . 5% or 1% ) that are poorly captured by previous GWA genotyping arrays . Empirical studies and population genetics theory support the potentially important role of both rare variants and common variants of very small effects [6]–[10] . Several current studies have implicated association of rare variants with complex diseases and traits [11]–[18] . Next-generation sequencing technologies have provided unparalleled tools to sequence a large number of individuals in candidate genes , exomes , or even the entire genome , allowing for comprehensive studies of both common and rare variants . In addition to the common problems of handling large numbers of variants , however , detecting disease-associated rare variants and common variants of small effects poses unique statistical challenges [19] , [20] . As such variants individually contain little variation , statistical methods that detect association between a single variant and disease phenotype provide low power with realistic sample sizes . Therefore , it is necessary to develop sophisticated methods that can effectively combine information across variants and assess the collective effect of multiple variants [4] . Several approaches along this line have been proposed [19] , [20] . The basic procedure of these methods is to construct a linear combination of multiple variants with fixed weights to summarize the information across the variants and then estimate its association with the phenotype [21]–[25] . Different weights yield different summaries of the variants and implicate different assumptions about the relative importance of individual variants [24] , [26] . Further , they implicitly assume that all variants affect phenotype in the same direction . However , there are many examples in which numerous rare variants detected in a gene or region may have disparate or even opposite effects on phenotype [4] , [11] . Thus , these methods can be suboptimal if the data do not follow the underlying assumptions . Recently , several methods have been proposed to deal with variants with opposite effects [26]–[32] , and to summarize the information across variants using non-linear functions [33] , [34] . All the existing methods have been developed to assess only one group of variants at a time . Since common diseases are likely caused by a complex interplay among many genes and environmental factors , however , it is more appropriate to simultaneously model multiple groups of variants and covariates [19] . The joint analyses would improve the power of detecting causal effects and hence lead to increased understanding about the genetic architecture of diseases . Such methods are also advantageous for studies involving only one candidate gene , because numerous variants detected within a gene can be divided into multiple groups based on their allelic frequencies ( common or rare ) and functional annotations of the genomic regions they reside in ( for example , non-synonymous or synonymous ) . It has been found in GWAS that the vast majority ( 80% ) of associated variants fall outside coding regions , emphasizing the importance of including both coding and non-coding regions in the search for disease-associated variants [2] . We propose here a comprehensive hierarchical generalized linear model ( GLM ) framework for simultaneously analyzing multiple groups of rare and common variants and relevant covariates . The proposed hierarchical GLMs introduce a group effect and a genetic score ( i . e . , a linear combination of main-effect predictors for genetic variants ) for each group of variants , and jointly estimate the group effects and the weights of the genetic scores . This framework includes various previous methods as special cases , and can effectively deal with both risk and protective variants in a group and can simultaneously estimate the cumulative contribution of multiple variants and their relative importance . The methods are illustrated with sequence data in gene ANGPTL4 from the Dallas Heart Study , and are further assessed via simulation studies . Finally , we conclude this article by highlighting some areas of future research .
Suppose that a population-based association study consists of n unrelated individuals , phenotyped for a continuous or discrete disease trait and genotyped for a number of rare and/or common genetic variants in one or multiple candidate genes or genomic regions . The observed values of the response variable are denoted by y = ( y1 , ··· , yn ) . We assume that the genetic variants can be divided into K groups , Gk , k = 1 , ··· , K , and the k-th group Gk contains Jk variants , where K≥1 and Jk>1 . The groups can be constructed based on candidate genes in which the variants are located and the types of the variants ( e . g . , common variants , rare non-synonymous or synonymous coding variants ) . We assume that some non-genetic variables ( e . g . , gender indicator , age , etc . ) are also measured for each individual and will be included as covariates in the model to control for possible confounding effects . We extend the hierarchical generalized linear model ( GLM ) of Yi and Zhi [26] to simultaneously fit covariates and multiple groups of rare and common variants . A generalized linear model consists of three components: the linear predictor η , the link function h , and the data distribution p [35] , [36] . The linear predictor of individual i is expressed as the multiplicative form: ( 1 ) where β0 is the intercept , xij and βj represent covariate j and its coefficient , respectively , zij is the main-effect predictor for individual i at genetic variant j in group Gk , equaling to the number of minor alleles for an additive coding ( for a rare variant , the additive coding is approximately equivalent to a dominant coding because the frequency of the minor allele is very low ) , the common coefficient represents the group effect for Jk variants in the k-th group , and the individual coefficients can be interpreted as the weights or relative effects of individual variants . The common coefficient represents the association between the phenotype and the linear combination of Jk individual main-effect predictors for variants in group Gk . The linear combination provides a way to combine the genetic variation across the Jk individual variants , referred to as genetic score . Therefore , the common coefficient represents the cumulative importance of the Jk individual variants in the k-th group , hence referred to as the group effect , and the weights , , give the relative importance of the individual variants in group Gk . The mean of the response variable is related to the linear predictor via a link function h: ( 2 ) The data distribution ( likelihood ) is expressed as ( 3 ) where is a dispersion ( or variance ) parameter , and the distribution can take various forms , including Normal , Gamma , Binomial , and Poisson distributions . Our main goal is to estimate the group effects and to test the hypotheses gk = 0 , k = 1 , ··· , K . We treat the weights 's as unknown parameters and estimate them along with the group effects and other parameters from the data . But we cannot simply use classical framework ( equivalent to setting uniform distributions on the 's from a Bayesian perspective ) , since this would result in a nonidentifiable model [37] , [38] . An approach to overcoming the problem is to use an informative prior for . We use the following hierarchical prior distribution: ( 4 ) where the prior means are prefixed and will be discussed in detail later , and the subscript k[j] indexes the group k that variant j belongs to . The above hierarchical prior assumes that follows a scale mixture of normals with unknown variable-specific variance . The prior distribution for is a hierarchical formulation of the half-Cauchy distribution , which has desirable properties , such as an infinite spike at the prior mean and very heavy tails , and also facilitates efficient computation [39] , [40] . An attractive feature of our hierarchical prior is that it is free of user-chosen tuning parameters and introduces group-specific parameters and variable-specific parameters and . The group-specific parameters provide a way to pool the information among variables within a group and also to induce different shrinkage for different groups , while the variable-specific parameters allow different shrinkage for different variables . Yi and Zhi [26] set the scale parameters to a known value for all the weight parameters and recommended = 0 . 5 as default . However , it would be more reasonable to estimate the scale parameters from the data . If the number of groups is not large , the group effects usually can be estimated classically . However , low allelic frequencies can yield very small variances for the predictors of , i . e . , , and as a result the classical procedure can result in numerically instable estimates for the group effects . To overcome this problem , we can place a weakly informative prior on that constrains to a reasonable range [41] . We use the following hierarchical prior distribution: ( 5 ) This hierarchical prior distribution includes group-specific parameters , which can induce different shrinkage for different group effects . The group-specific parameters are assumed to follow a weakly informative prior Gamma ( 0 . 5 , 0 . 5 ) . This weakly informative prior does not strongly shrink towards zero , but can constrain to lie in a reasonable range [41] . For the covariate effects , we also use the above weakly informative prior ( 5 ) , i . e . , . For the intercept and the dispersion parameter , we can use any reasonable non-informative prior distributions; for example , with set to a large value , and . Our hierarchical GLMs include multiplicative parameters , a common coefficient for a group of variants and a weight parameter for each variant . As explained earlier , the common coefficient represents the overall association of the Jk individual variants in group k with the disease . In our hierarchical model , the multiplicative term can be expressed as , and thus the predictor zij ultimately gets the coefficient , which represents the main effect of that variant . The coefficient is affected by the prior mean of . Therefore , we define the adjusted main effects as , which represent the effects of individual variants . For the multiplicative model to be useful , we need informative prior distributions on the multiplicative parameters that allow us to distinguish between the group effects and the individual weights . The prior means and the variances in the normal prior distributions of the weights ( i . e . , ) are the key components to interpret our hierarchical model . The variances directly control the amount of shrinkage for . If = 0 , the coefficient equals the prior mean . If = ∞ , is actually estimated using least squares and the parameters and cannot be distinguished . If is finite , the coefficient is shrunk towards but not identical to the prior mean . Therefore , the prior distributions bridge the gap between the two extremes of simply using the fixed weighted sum of the Jk variants as a predictor ( = 0 ) , and including them as Jk independent predictors ( = ∞ ) [37] , [38] . This interpretation can be more explicitly understood by the identity ( 6 ) where . The second term in the right side is controlled by the variances , and represents the deviation from the fixed weighted sum . Most of existing methods for analyzing rare variants proceed to construct a linear combination ( genetic score ) of rare variants with fixed weights [21]–[25] , and thus can be viewed as special cases of our model . The prior means represent the prior relative importance of the individual variants and can be specified in various ways . The weights proposed by previous methods [21]–[25] can be used as the prior means in our hierarchical model . The simplest way is to set all = 1 , resulting in the simple sum , and incorporating no prior information about the relative importance of rare variants into the model . But our method can estimate the weights from data and produce different weights to different variants based on their contributions to the phenotype . Therefore , our model uses a previous score ( i . e . , ) as the baseline , and improves the fit by accounting for the variation among individual variants . An alternative choice of the prior means is to set all = 0 . With this choice , the weights are shrunk towards zero , and variants with small effects can be essentially removed from the model . This seems to be reasonable , especially for the situations with non-functional variants . However , we don't recommend this approach for rare variants for several reasons . First , most of rare and common variants have small effects , but they can be cumulatively important . In order to detect the cumulative effect , therefore , it would be better to include all the small effects in the model . Second , the estimated group effect can be less interpretable and accurate , if only one or a few variants are included in the model . Third , our hierarchical model can estimate the weights of individual variants from the data , and thus can deal with non-functional variants and disparate effects . Our Bayesian hierarchical GLMs can be fitted using Markov chain Monte Carlo ( MCMC ) algorithms that fully explore the joint posterior distribution by alternately sampling each parameter from its conditional posterior distribution [36] . However , it is desirable to have a faster computation that provides a point estimate ( i . e . , the posterior mode ) of the coefficients and their standard errors ( and thus the p-values ) . Such an approximate calculation has been routinely applied in statistical practice [41] . We develop our mode-finding algorithm by modifying the standard iterative weighted least squares ( IWLS ) for fitting classical generalized linear models [42] , [43] . Our algorithm updates the coefficients and using an iterative procedure . Conditional on the current estimates , we update by running the generalized linear model with the proposed prior distributions for and other corresponding parameters: ( 7 ) where , and then conditional on the current estimates , we update by running the generalized linear model with the proposed prior distributions for and other corresponding parameters: ( 8 ) where . We fit these two hierarchical generalized linear models by incorporating a flexible expectation-maximization ( EM ) algorithm into the iteratively weighted least squares ( IWLS ) for fitting classical generalized linear models . We describe our EM-IWLS algorithm in detail in Text S1 . We initialize our iterative algorithm by setting the parameters ( ) with some plausible values . For example , we can start with = 0 , = , = 1 , = 1 , = 0 . 5 , = = 0 . 5 , and = = = = 1 . We then update the parameters by iteratively running the hierarchical generalized linear models ( 7 ) and ( 8 ) until convergence . Instead of doing a nested converged EM-IWLS for each of the two models , we can run one step of the EM-IWLS at each iteration , thus taking less computing time to ultimately achieve convergence by not wasting time running many steps of the EM-IWLS within each iteration . To assess convergence , we use the standard criterion for analysis of classical generalized linear models ( as implemented in the R function glm ) , i . e . , , where is the estimate of deviance ( i . e . , ) at the tth iteration , and is a small value ( say 10−5 ) . At convergence of the algorithm , we summarize the inferences using the latest estimates of the coefficients and their standard errors . Based on these outputs , we can calculate approximate p-values as in the classical framework for testing whether a coefficient is significantly different from zero , for example , the hypothesis = 0 . The adjusted main effects are then estimated as , and the approximate standard error for can be obtained by using the delta technique: ( 9 ) Therefore , we can calculate the approximate p-value for testing the hypothesis = 0 . Our model fitting strategy is based on extending the well-developed IWLS algorithm for fitting classical GLMs to our Bayesian hierarchical GLMs . The IWLS algorithm is executed in the glm function in R ( http://www . r-project . org/ ) . We have implemented the EM-IWLS algorithm by inserting the E-step for updating the missing values ( i . e . , the variances and the hyperparameters and ) and the steps for calculating the augmented data and the dispersion parameter into the IWLS procedure ( see Text S1 ) . We have created a new R function bglm by modifying the glm function to implement our EM-IWLS algorithm that estimates posterior modes and standard deviations for hierarchical GLMs with the prior distributions proposed here ( see Text S1 ) and some other hierarchical priors [44] , [45] . We have also developed an R function bglm . ex that implements the iterative algorithm described above for fitting our hierarchical multiplicative GLMs . Although described in the context of genetic variants in this paper , the functions bglm and bglm . ex can be used as general tools for routine data analysis using hierarchical GLMs . We have incorporated the functions bglm and bglm . ex into the freely available R package BhGLM ( http://www . ssg . uab . edu/bhglm/ ) that is an extensible and interactive environment for genetic association analysis of common and rare variants and gene-gene and gene-environment interactions . Our hierarchical multiplicative GLMs include various models as special cases . Although less comprehensive , these reduced models can be useful in some situations , and thus can be used as alternative approaches to analysis of multiple groups of rare and common variants . We here consider two types of reduced models . The first ignores the group effects and directly models the main effects of individual variants . Thus , the linear predictor ( 1 ) is reduced to ( 10 ) and the mean and the distribution of the response variable take the same form of the expressions ( 2 ) and ( 3 ) . In this model , the coefficient represents the main effect of genetic variant j , and follows the hierarchical prior distribution ( 4 ) with the prior mean = 0 . This approach can only detect individual variants with strong effects , and is less powerful in situations where the effects of all individual variants are small but they are cumulatively significant . The second alternative approach is to preset the weights of individual variants using the previous methods [21]–[25] . Thus , the linear predictor ( 1 ) becomes ( 11 ) where with fixed weights . This model is equivalent to setting the priors as ( i . e . , ) and thus is a special case of our hierarchical model . The performance of this method heavily depends on the quality of the fixed weights .
We have proposed here a Bayesian hierarchical generalized linear model framework for simultaneously analyzing multiple groups of rare and common variants and relevant covariates . Since complex diseases and traits are likely influenced by multiple genetic variants and environmental factors , the joint analyses of multiple groups of genetic variants can improve the power of detecting causal effects and lead to increased understanding about the genetic architecture of diseases . The proposed hierarchical generalized linear models introduce a group effect and a genetic score for each group of variants , and jointly estimate the group effects and the weights of the genetic scores . This can produce ‘optimal’ weights to different variants based on their contributions to the phenotype , yielding an effective summary of the information across variants . The simulation studies show that the proposed method can consistently provide reasonable power even in the presence of both risk and protective variants in a group , and has better power than existing approaches even when all variants act in the same direction . Application of the method to a large published dataset on resequencing of the gene ANGPTL4 and triglycerides not only confirmed the original findings but also detected new associations . In addition to the properties described above , our method has several remarkable features . First , the proposed method can simultaneously estimate the group effects of multiple groups of variants and the individual effects of the variants , allowing us to not only identify significant genes ( or groups of variants ) but also assess the relative importance of single variants . Second , our hierarchical model includes various existing methods for rare variants as special cases . This shows that the proposed method is theoretically more advantageous than the existing methods , and allows us to conveniently analyze data using different ways . Third , any external information about variants , for example , the functional prediction , can be easily incorporated into our hierarchical model by specifying the prior means of the weights for variants . By doing so , our approach has the additional advantage of accounting for uncertainties about the prior assumptions . Fourth , our approach is based on the generalized linear model framework and thus can deal with various types of continuous and discrete phenotypes and covariates , and can fit any generalized linear models . Finally , the proposed algorithm extends the standard procedure for fitting classical generalized linear models in the general statistical package R to our Bayesian model , leading to the development of stable and flexible software . Our approach is highly extensible; we have planned several extensions to the proposed method , some of which have been initially implemented in our software BhGLM . The key to our approach is the use of hierarchical prior distributions for the weights and the group effects , so that these multiplicative parameters are identifiable and can be simultaneously estimated from the data . We have proposed to use the hierarchical expression of the half-Cauchy distribution with the innovation of introducing both group- and variable-specific parameters . The half-Cauchy prior is an excellent default choice for many problems [39] , [40] , and has been shown to perform well for our purposes . However , other hierarchical priors or penalized likelihood methods have been developed for high-dimensional data analysis , including lasso [48] , [49] , adaptive Lasso [50] , and the elastic net [51] . These methods can be expressed as hierarchical models by assigning certain priors on the variances and other hyperparameters [45] , [48] , [52] , and can be incorporated into our framework . Although demonstrated with only several groups of variants , our method can be adapted to deal with large-scale sequencing data involving thousands of exomes or candidate genes . For these high-dimensional settings , we need to modify the prior distributions of the group effects and the computational algorithm . We can place a shrinkage prior on the inverse scale in the gamma prior of and estimate the inverse scale from the data . We can further group the group effects based on pathways that candidate genes belong to , and specify the shrinkage priors by incorporating the second-level hierarchical structure , similar to the hierarchical priors of the weights . We describe our algorithm by simultaneously estimating all weights . This method can be very fast when the number of variables is not very large ( say <2000 ) and has the advantage of accommodating the correlations among all the variables . However , it can be slow or even cannot be implemented when the number of variables is large due to memory storage and convergence problems . We can extend the algorithm to update coefficients group by group; at each of the iteration , the group-at-time algorithm proceeds by cycling through all the groups of parameters and treats the linear predictor of all other groups as an offset in the model . This method updates coefficients in a conditional manner , significantly reducing the number of parameters in each M-step of the EM-IWLS algorithm , and thus can deal with large number of variables . Our third extension could incorporate external gene or pathway level information into the hierarchical model . Candidate genes or pathways studies usually consist of data at different levels , i . e . , genetic variants within multiple candidate genes or pathways which may be functionally related [53] . Most of statistical methods for association studies consider only individual-level predictors ( i . e . , SNPs and covariates ) and ignore the hierarchical structure of the data and gene or pathway-level information . Often , rich gene or pathway-level information is available [54] , including genomic annotation or pathway ontologies , functional assays , in silico predictions of function or evolutionary conservation [55] . Therefore , there is a growing need to develop sophisticated approaches that model the multilevel variation simultaneously and incorporate gene or pathway-level data into the model [56] , [57] . Our hierarchical models provide a natural and efficient way to incorporate the external information about candidate genes into the analysis . One way to include the gene-level information in the hierarchical models is to model the prior means of weights and group effects using gene or pathway level predictors [38] . This would allow us to pool the information in the same genes or pathways and thus would provide more effective inference about the genetic effects . Our fourth extension could incorporate genetic interactions ( gene-gene and gene-environment interactions ) into the model . Just as interactions must be considered in standard GWA studies [57]–[59] , they are also likely to be important in association studies involving rare variants [19] . In principle , we can extend the proposed model to include additional groups for interactions for each pair of groups of main effects and to define an overall effect and a genetic score for each interaction group . However , it would be necessary to investigate statistical power for detecting interactions for rare variants . Finally , we have planned to extend our method to family-based matched case-control association studies . So far the existing methods for rare variants have focused on population-based studies . However , for rare variants , family-based designs may prove very useful [60] . Not only are they robust against population stratification , but they may also offer increased power due to the increased likelihood of affected relatives to share the same rare disease variants . As the conditional logistic regression commonly used for matched case-control studies can be formulated as a Poisson regression [36] , our hierarchical generalized linear models can be applied . The proposed hierarchical generalized linear models may provide efficient tools for disease risk prediction and personalized medicine . GWA studies have raised expectations for predicting individual susceptibility to common diseases using genetic variants [61] , [62] . Previous methods using only a limited number of significant variants have typically failed to achieve satisfactory prediction performance [63] , [64] . Recent studies show that joint analysis of a large number of genetic variants can improve the prediction of complex traits [65]–[67] . It is understood that a model including as many predictors as possible and fitted appropriately could provide better prediction . Although the previous studies have included many genetic variants in a predictive model , they treat these variants individually and hence could be suboptimal to efficiently use information of genetic variants with small effects and low frequencies . The proposed hierarchical models can better deal with such variants and can integrate external biological knowledge , and therefore may be able to improve the accuracy of prediction .
|
Complex diseases and traits are likely influenced by many common and rare genetic variants and environmental factors . Next-generation sequencing technologies have provided unparalleled tools to sequence a large number of individuals , allowing for comprehensive studies of both common and rare variants . However , detecting disease-associated rare variants and common variants of small effects poses unique statistical challenges . We propose here a comprehensive hierarchical generalized linear model framework for simultaneously analyzing multiple groups of rare and common variants and relevant covariates . The proposed hierarchical generalized linear models introduce a group effect and a genetic score for each group of variants , and jointly they estimate the group effects and the weights of the genetic scores . This framework includes various previous methods as special cases , and it can effectively deal with both risk and protective variants in a group and can simultaneously estimate the cumulative contribution of multiple variants and their relative importance . The methods are illustrated with sequence data in gene ANGPTL4 from the Dallas Heart Study and are further assessed via simulation studies . The methods have been implemented in a freely available R package BhGLM ( http://www . ssg . uab . edu/bhglm/ ) .
|
[
"Abstract",
"Introduction",
"Methods",
"Discussion"
] |
[
"medicine",
"computer",
"science",
"mathematics",
"genetics",
"biology",
"genetics",
"and",
"genomics"
] |
2011
|
Hierarchical Generalized Linear Models for Multiple Groups of Rare and Common Variants: Jointly Estimating Group and Individual-Variant Effects
|
Nigeria is one of the countries endemic for Buruli ulcer ( BU ) in West Africa but did not have a control programme until recently . As a result , BU patients often access treatment services in neighbouring Benin where dedicated health facilities have been established to provide treatment free of charge for BU patients . This study aimed to describe the epidemiological , clinical , biological and therapeutic characteristics of cases from Nigeria treated in three of the four treatment centers in Benin . A series of 82 BU cases from Nigeria were treated in three centres in Benin during 2006–2016 and are retrospectively described . The majority of these patients came from Ogun and Lagos States which border Benin . Most of the cases were diagnosed with ulcerative lesions ( 80 . 5% ) and WHO category III lesions ( 82 . 9% ) ; 97 . 5% were healed after a median hospital stay of 46 days ( interquartile range [IQR]: 32–176 days ) . This report adds to the epidemiological understanding of BU in Nigeria in the hope that the programme will intensify efforts aimed at early case detection and treatment .
Buruli ulcer ( BU ) is a neglected tropical disease that mainly affects the skin . The disease results from infection with Mycobacterium ulcerans , an environmental bacterium . BU is found in often swampy and humid areas . The mode of transmission remains obscure to this day , although several hypotheses have been proposed . Many authors have discussed potential reservoirs as well as vectors and transmission mechanisms that vary from region to region depending on the epidemiological , social and local environmental context . Direct human to human transmission of M . ulcerans is a rare possibility [1] . The main hypothesis is that the surface of the patient’s skin was contaminated by bacteria from an environmental source ( e . g . swamps ) and introduced into the skin by trauma . It is assumed that insects ( aquatic bugs and mosquitoes ) are the host and vector of M . ulcerans . Several experimental and environmental studies have demonstrated the implication of aquatic bugs in transmission of the disease [2–4] . DNA of M . ulcerans was detected in mosquitoes collected in Australia but a field study conducted in Benin suggested that mosquitoes do not play a central role in the ecology and transmission of M . ulcerans [5] . Fish has also been identified as a passive reservoir of M . ulcerans but generally not responsible for direct transmission of the disease [6] . Acanthamoeba species have also been identified as natural hosts of M . ulcerans and have been suggested as responsible for transmission of the disease [7] . No definitive conclusion has yet been drawn about how the disease is transmitted . The World Health Organization ( WHO ) has classified BU as a neglected tropical disease [8–11] . BU is the third most common mycobacterial infection in the world among immunocompetent individuals after tuberculosis and leprosy [12] . BU is characterized by a chronic necrosis of subcutaneous tissues , ranging from a simple nodule to a large cutaneous ulceration . Sometimes the bone is affected and the resulting damage can impair the functional mobility of the affected limb . Without early and effective treatment , the disease can progress and cause cosmetic complications and sequelae or functional limitations [13] with attendant stigma and social problems [14 , 15] . It can even lead to limb amputation . WHO classifies BU lesions into three categories according to severity [16 , 17] . Category I lesions are single small lesions ( e . g . nodules , papules , plaques and ulcers < 5 cm in diameter ) . Category II lesions consist of non-ulcerative or ulcerative plaques , oedematous forms and single large ulcerative lesions of 5–15 cm in cross-sectional diameter , while lesions in the head and neck regions and the face , disseminated and mixed forms including osteomyelitis , and extensive lesions of more than 15 cm are considered as Category III . BU mostly affects poor people in rural areas with limited access to health care [11 , 18–20] . Children aged < 15 years are most commonly affected by the disease [21] . Worldwide , BU has been reported in > 33 countries , mostly within the tropical areas [22] . The majority of BU cases occur in Africa; however , cases have been reported in Australia , French Guiana , Peru and Papua New Guinea [23] . Recognizing that BU constitutes an emerging public health threat , in 1998 WHO established the Global Buruli Ulcer Initiative ( GBUI ) to coordinate control and research activities worldwide [9 , 18 , 22–24] . Up until 2004 , the only curative treatment for BU was surgery , which consisted of wide excision to remove all infected tissues including some of the adjacent healthy tissues . Large lesions require skin grafting [18 , 21 , 23] . Scientific studies have shown the effectiveness of using different combinations of antibiotics to treat BU [25–27] . The standard treatment since 2004 has been the combination of rifampicin and streptomycin [16] . WHO has issued a provisional recommendation to use the new combination full oral therapy [28] . The introduction of antibiotic therapy has reduced the number of surgical procedures and recurrence rates . Almost all Category I and some Category II lesions can be cured without surgery [29] . In Benin , the BU control programme is known as the Programme National de Lutte contre la Lèpre et l’UB ( PNLLUB ) . It coordinates BU control activities through four care facilities known as Centres de Dépistage et de Traitement de l’Ulcère de Buruli ( CDTUB ) , located in the southern departments where BU is endemic [30] . During the course of their activities , the CDTUBs also receive patients from Nigeria . BU cases were officially reported in Nigeria in 1967 [31] and in 1976 [32] in different Nigerian states . Between 1998 and 2000 , BU cases at the Leprosy and Tuberculosis Hospital in Moniaya-Ogoja were confirmed by the Institute of Tropical Medicine , Antwerp , Belgium . In 2006 , the Nigerian authorities , in collaboration with a team from Benin and WHO , conducted an assessment of the BU situation in order to identify the endemic areas in Nigeria . The assessment covered only 5 states and therefore could not identify all the endemic regions as originally planned [33] . That was the first time in 2006 when Nigeria notified 9 BU cases to WHO . During 2009–2016 , Nigeria reported 511 cases to WHO with increasing numbers of cases each year [34] . BU is known to be endemic in the south of Nigeria mainly in states such as Akwa Ibom , Anambra , Benue , Cross River , Ebonyi , Enugu , Ogun and Oyo [33 , 35] . Ogun State is divided by two drainage basins , the Yewa and the Ogun rivers , which discharge in separate lagoons . South-west Nigeria is characterized by tropical rainforest , similar to the environments where BU occurs in endemic areas of West Africa [35 , 36] . In order to establish an effective BU control system in Nigeria , it is imperative that all endemic areas are identified; hence the necessity of providing data on the states where Nigerian BU patients treated in Benin have come from . In 2014 , a study from CDTUB in Pobè , Benin reported 127 PCR-confirmed cases of Nigerian BU patients treated in the facility [35] . Pobè is a town on the border with south-western Nigeria , making it the first facility of contact by patients from Nigeria . The objective of our study therefore is to describe the epidemiological , clinical , biological and therapeutic characteristics of BU cases from Nigeria treated in the other three CDTUBs and contribute data to the health authorities in that country .
This is a retrospective descriptive study of a series of 82 BU cases from Nigeria who were treated in three of the four CDTUBs , namely the CDTUB of Allada , the CDTUB of Lalo and the Centre Nutritionel et Sanitaire Gbemonten ( CNSG ) of Zagnanado from 1 January 2006 to 31 December 2016 . This was a comprehensive sampling . All the cases from Nigeria , who were clinically suspect for BU and treated in the CDTUBs of Allada , Lalo and Zagnanado during the study period and for whom data were available , were included in this study . For each patient the following information was collected from their medical records and analysed: The data on the BU cases from Nigeria treated in the three CDTUBs were taken from the PNLLUB’s Register BU 01 , which is used to collect standard information for each BU patient . The data were supplemented with additional information from the patients’ medical records kept in each CDTUB . The complete data were recorded with the software Microsoft Excel 2010 and then analysed with the statistical software IBM SPSS Statistics version 20 . We only performed a descriptive analysis of the epidemiological , clinical , biological and therapeutic variables of the cases . The maps were drawn from free-access shapefiles obtained from DIVA-GIS ( http://www . diva-gis . org/ ) with QGIS 1 . 8 . 0 and ArcView 3 . 2 software . This retrospective study was conducted after the approval and with the authorization of the Ministry of Health of Benin . The case data in the PNLLUB database used by the authors for this study were anonymized .
A total of 82 new patients from Nigeria suspected of having BU were treated in the three Beninese CDTUB from 1 January 2006 to 31 December 2016 , with an annual average of 7 patients . Table 1 shows details of the socio-demographic , epidemiological characteristics and states of origin of the patients . Of the 82 patients , 45 ( 54 . 9% ) were male . The median age of the patients was 20 years ( IQR: 13 . 5–42 . 5 years ) . The State of residence in Nigeria was available for 66 patients , of whom 39 ( 59 . 1% ) were from Ogun State; 25 ( 37 . 9% ) from Lagos State and 2 ( 3 . 0% ) from Oyo State . Some 55 patients ( 67 . 1% ) were treated in the CDTUB of Zagnanado; 15 ( 18 . 3% ) in the CDTUB of Lalo and 12 ( 14 . 6% ) in the CDTUB of Allada . Patients from Lagos State were mostly treated in the CDTUB of Zagnanado while those from Ogun State were equally treated in the three centres ( Fig 1 ) . The person who referred the patient to the CDTUB was specified for 79 patients; 62 ( 78 . 5% ) were referred by former BU patients from Nigeria who had been treated in Benin . The other patients were either referred by health agents or by family members . The median delay before seeking medical assistance was 203 days ( IQR: 87 . 5–1638 ) . Clinically , 66 ( 80 . 5% ) patients had ulcerative lesions; 11 ( 13 . 4% ) had nonulcerative lesions ( plaque , nodule , oedema ) and 5 ( 6 . 1% ) had osteomyelitis . Of the 82 patients , 53 ( 64 . 6% ) had lesions on their lower limbs; 22 ( 26 . 8% ) had lesions on their upper limbs; 3 ( 3 . 6% ) had lesions on other parts of their body ( abdomen , back , head/neck ) ; and 4 ( 4 . 9% ) had lesions on multiple parts of their body . Some 68 patients ( 82 . 9% ) had Category III lesions ( multiple lesions or lesions > 15 cm in diameter ) ( Fig 2 ) , 13 ( 15 . 9% ) had Category II lesions ( lesions 5–15 cm in diameter or on their faces/breast/genitalia ) ; only one patient ( 1 . 2% ) had a Category I lesion ( lesion < 5 cm in diameter ) . For 78 patients , the medical records of 78 patients mentioned whether or not the movements of the affected part were limited at the time of diagnosis; 24 ( 30 . 8% ) had restricted joint movements . Samples were taken from 12 patients ( 100 . 0% ) in Allada , 12 patients ( 80 . 0% ) in Lalo and 23 patients ( 41 . 8% ) in Zagnanado giving a total of 47 out of the 82 patients ( 57 . 3% ) for PCR confirmation; 36 out of 47 tested positive . All the 82 patients received treatment free of charge including specific antibiotic therapy of combined rifampicin with streptomycin for 8 weeks as recommended by WHO as well as surgery and physiotherapy as required . However , 80 patients ( 97 . 6% ) received surgery . The median length of hospital stay was 46 days ( IQR: 32–176 days ) . The length of hospital stay was relatively longer for the patients treated in the CDTUB of Allada with a median of 197 days ( IQR: 184-318 ) and the CDTUB Lalo with a median of 256 days ( IQR: 170–340 ) , while the median length of hospital stay was 35 days ( IQR: 27–48 ) in Zagnanado . Some 78 patients ( 97 . 5% ) were healed among whom two patients ( 2 . 4% ) healed without surgery; one patient ( 1 . 2% ) died during his hospital stay and one patient ( 1 . 2% ) was lost to follow up . Treatment outcome data were missed for two patients . The epidemiological , clinical , biological and therapeutic characteristics of the patients are summarized in Table 1 .
In addition to local BU cases , the CDTUB of Benin receive BU cases from Nigeria , most of whom are advanced Category III lesions whose care requires more time as well as more material and financial resources and have a socioeconomic impact on both the patients and their caregivers . However , all the treatment was provided for free . These patients mainly come from Nigerian states that border Benin and are referred by former patients who received care from one of the CDTUBs . It is therefore important that BU control activities be intensified in these different states in order to detect cases early and reduce the severity of the disease .
|
Buruli ulcer ( BU ) is a neglected tropical disease that mainly affects the skin . The disease results from infection with Mycobacterium ulcerans , an environmental bacterium . In Benin , the BU treatment centres usually receive patients from Nigeria . In 2014 , a study from one of the treatment centres ( CDTUB , Pobe ) which borders south-western Nigeria reported on a cohort of 127 PCR-confirmed cases between 2005 and 2013 . We describe the epidemiological , clinical , biological and therapeutic characteristics of BU cases from Nigeria treated in the three other CDTUBs .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"and",
"health",
"sciences",
"pathology",
"and",
"laboratory",
"medicine",
"tropical",
"diseases",
"geographical",
"locations",
"surgical",
"and",
"invasive",
"medical",
"procedures",
"health",
"care",
"bacterial",
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"signs",
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"benin",
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"patients",
"bacteria",
"africa",
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"buruli",
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"biology",
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"organisms"
] |
2018
|
Report of a series of 82 cases of Buruli ulcer from Nigeria treated in Benin, from 2006 to 2016
|
With relatively low efficiency , differentiated cells can be reprogrammed to a pluripotent state by ectopic expression of a few transcription factors . An understanding of the mechanisms that underlie data emerging from such experiments can help design optimal strategies for creating pluripotent cells for patient-specific regenerative medicine . We have developed a computational model for the architecture of the epigenetic and genetic regulatory networks which describes transformations resulting from expression of reprogramming factors . Importantly , our studies identify the rare temporal pathways that result in induced pluripotent cells . Further experimental tests of predictions emerging from our model should lead to fundamental advances in our understanding of how cellular identity is maintained and transformed .
Cellular states are plastic , and even terminally differentiated cells ( e . g . , B-cells ) can be reprogrammed to pluripotency by ectopic expression of selected transcription factors [1] , [2] , [3] , [4] , [5] , [6] , [7] . This finding raises the possibility of creating patient-specific stem cells for regenerative medicine [8] . However , reprogramming efficiencies range from 0 . 0001% to 29% [5] , [6] , [9] , [10] , with most reports showing that successful induction of the pluripotent state is rare even if all required factors are present [11] , [12] . The genetic and epigenetic regulatory mechanisms that make reprogramming possible , and determine its efficiency , are poorly understood [2] . Elucidating these mechanistic principles can help define optimal strategies for reprogramming differentiated cells , and answer fundamental questions regarding how cellular identity is maintained and transformed . In spite of recent progress , our knowledge of the identities and functions of the genes and proteins involved in regulating the transformation of cellular identity is grossly incomplete [2] , [13] , [14] . Thus , it is not yet possible to construct a detailed molecular mechanistic description of how epigenetic modifications and expression of master regulatory genes are controlled . However , ectopic expression of the same transcription factors can reprogram different cell types [1] , [6] , [12] , and the genetic and epigenetic transformations observed during reprogramming of diverse differentiated cells share many common features [2] , [11] , [15] , [16] , [17] , [18] , [19] . These common observations can be the basis for developing a conceptual understanding of the general architecture of the genetic and epigenetic networks that regulate transcription factor induced reprogramming and establish cellular identity during differentiation . We have taken a step toward this goal by developing a computational model that is consistent with , and suggests general mechanistic explanations for , empirical observations of transcription factor induced reprogramming . The model makes experimentally-testable predictions . If validated , descendents of this model could also provide insights into the aberrant de-differentiation events which characterize some of the most malignant cancers .
Elegant theoretical models for the molecular regulatory networks responsible for stem cell renewal and differentiation and the population dynamics of these processes have been created [20] , [21] , [22] , [23] , [24] . Our goal is different . We aim to develop a model for the architecture of coupled epigenetic and genetic networks which describes large changes in cellular identity ( e . g . , induction of pluripotency by reprogramming factors ) . Although the general principles of interactions between genetic and epigenetic layers of regulation have been described [25] , [26] , no computational model has been developed to study the outcomes of such interactions and their biological consequences . Such a computational model would be a useful complement to experiments in understanding the processes that occur during reprogramming of differentiated cells , and why reprogramming is rare . Here , we propose , to our knowledge , the first computational model that describes how cellular identity changes by creating a mathematical description of interactions between epigenetic and genetic networks . Our goal is not to describe the details of how specific regulatory proteins interact , but rather , to understand general principles underlying how cellular states evolve upon ectopic expression of certain types of genes . The concise model we have developed explains why reprogramming probability is low , and makes experimentally testable predictions . Almost all cells in a multi-cellular organism share the same DNA sequence . Yet , different cell types express distinct genes and perform different functions . Epigenetic modifications are major regulators of cell-type specific gene expression . They function by packaging DNA into configurations that allow only some genes to be expressed , while other genes are tightly packed into heterochromatin structures that hinder access of most transcription factors [27] . Changes in cellular identity during developmental differentiation or transcription factor induced reprogramming require modification of the epigenetic state of the cell . The maintenance and alteration of cellular identity is regulated by a complex set of interactions between developmentally important genes , chromatin modifiers , transcription factors etc . , the details of which remain unknown . Toward developing a model for the architecture of these complex regulatory networks we consider only the developmentally important genes . For simplicity , each ensemble of genes responsible for maintenance of a particular cellular identity ( e . g . , Oct4 , Sox2 , etc . , for pluripotency ) is described as a single module ( Fig . 1a ) . Theoretical justification for treating genes that control the embryonic stem ( ES ) cell state as a collective unit exists [28] . We also carried out some studies with each module consisting of a small number of genes ( see corresponding discussion below ) . ES cells can differentiate into various lineages . Upon further differentiation , cells become more restricted . For example , hematopoetic stem cells can differentiate into T and B-lymphocytes , but not neural cells . Therefore , in our model , we arrange gene modules in a hierarchy ( Fig . 1a ) . Although each cell state can potentially differentiate into many branches , without loss of generality , we consider two branches to emanate from each cell state . Thus , the cellular states are arranged on a Cayley tree . In our model , a cell state ( Fig . 1b ) is specified by: i] the state of the epigenome , and ii] the expression levels of master regulatory genes . ES cells are cultured in specific media ( e . g . , containing LIF/BMP4 for mouse ES cells ) to prevent differentiation [43] . The medium inhibits a self-induced differentiation pathway . We represent this feature by assuming that proteins expressed by the module regulating the ES state favor putting positive chromatin marks on gene modules regulating immediate progenies if LIF , etc . are absent . Simulations of this situation show ( Fig . 4 ) that , as in experiments [2] , ES cells differentiate randomly to one of their progeny . Our model exhibits robust differentiation ( forward programming ) to specific cell states when the appropriate cues are delivered . Appropriate cues are expression of proteins ( e . g . , signaling products ) that become available during interphase . In the next telophase , these proteins favor putting positive histone marks on the gene module regulating the appropriate progeny of the current cellular state ( rule 1 ) . Results from our computer simulations ( Fig . 4 in Text S1 ) demonstrate that our model exhibits high-fidelity responses to such differentiation cues . This is consistent with the experimental observation that overexpression of the master-regulatory genes of desired lineage leads to predominant differentiation in that direction [44] , [45] . This result is relevant because practical use of induced pluripotent cells will involve differentiating them to desired cell types . We also find an exponential decay of the number of progenitor cells ( with a signal strength-dependent lifetime ) , as has been noted before [46] . We simulate reprogramming experiments by starting with a terminally differentiated cell state where genes from other lineages , etc . , have been epigenetically silenced . Our basic premise is that terminally differentiated cells can reprogram because protein products of the ectopically expressed genes can potentially alter the epigenetic state of the cell as a cell progresses through the telophase . In our low resolution model , we identify genes not by names , but rather by their functional properties . We presume that Klf4 and c-Myc are important ingredients of the reprogramming “cocktail” because they promote progression through the cell cycle , and this provides more opportunities for the other reprogramming factors to perturb the epigenome during telophase . This functional identification of Klf4 and c-Myc makes our model general , and is validated by experiments showing that shutting down p53 abrogates the need for Klf4 and c-Myc for reprogramming ( only Oct4 and Sox2 required ) precisely because this also allows faster progression through the cell cycle [47] , [48] , [49] , [50] , [51] . ( Interestingly , simulataneous action of c-Myc and p53 knock-down decreases the efficiency of reprogramming indicating existence of the optimum ) . Oct4 and Sox2 have an enormous number of binding targets on the DNA , and are responsible for maintenance of the ES state which likely implies multiple interactions with master-regulatory genes . We therefore identify the ectopic expression of these genes with the function of being highly likely to perturb the epigenome during telophase . Each gene module in our model corresponds to an ensemble of carefully tuned mutually interacting master-regulatory genes that govern a particular cellular identity . At the moment , not all of the master-regulatory genes of cellular states are experimentally identified , thus we use gene modules to represent these ensembles in a general way . Even though products of ectopically expressed Oct4 and Sox2 have numerous targets [52] , it is unlikely that the epigenetic state of many such sets of genes will be simultaneously altered . Thus , in order to mimic the effect of reprogramming factors , we randomly pick one epigenetically silenced gene module and change its state to correspond to open chromatin . To examine the effects of overexpression of ectopic genes , we also study the consequences of multiple epigenetic transformations at a time ( see discussions below ) . Starting with a terminally differentiated state we perturb the epigenome as described above , and then simulate the next gene expression phase where both the module regulating the terminally differentiated state and the one which was transformed to open chromatin status can express proteins according to rules 1′–2′ ( or Eq . 3 ) . The protein atmosphere thus generated becomes the input to simulation of the next telophase according to rules 1–4 ( or Eq . 2 ) . This can then potentially establish a new epigenetic state which becomes input to simulation of the next gene expression phase; i . e . , the genetic and epigenetic states are allowed to come to a new balance . Then , the epigenetic state of another randomly picked silent gene module is changed to open chromatin because of the effects of reprogramming factors . This procedure is continued until a fully reprogrammed or a dead/arrested state is achieved ( see below ) . We carried out 10 , 000 independent replicate simulations of the effects of ectopic expression of reprogramming factors on a differentiated cell in a model with four levels in the hierarchy of cellular states . Results from each simulation describe the fate of a single cell in a population . Only 3 out of 10 , 000 “cells” successfully reprogrammed; i . e , as in experiments , reprogramming is rare . The percentage of cells that reprogram depends upon the number of levels in the hierarchy ( 0 . 0001% and 2% of the cells reprogram successfully for a five-level and three-level hierarchy , respectively ) . This suggests that reprogramming efficiency should improve for less differentiated cells . This has been demonstrated directly in a well-defined lineage such as the hematopoietic system [53] . Additionally , Hanna et al . demonstrated a notable increase in the efficiency of reprogramming B cells upon Pax5 knockdown [12] . Loss of Pax5 had been previously shown to cause dedifferentiation of B cells to a common progenitor that upon transplantation allowed T cell development [54] . We report results for models consisting of 3- , 4- and 5-levels in the hierarchy of gene modules , but in real organisms the depth of the differentiation tree could be as large as tens of levels [55] . Since our results indicate that reprogramming efficiency decreases quickly with the increase in the depth of the hierarchy , it is natural to ask why reprogramming is at all feasible . The reason is that master-regulatory genes that regulate closely related states are not mutually exclusive sets of genes . The difference between genes that regulate closely related cellular states can be as small as one or two genes [54] . However , genes that regulate cellular states distal in the hierarchy are not correlated in this way . As our model does not treat correlations between genes that regulate closely related states , in effect , each gene module in our model represents master regulatory genes that control the identity of a number of cellular states that have many master regulatory genes in common . Thus , a 5-level hierarchy in our model might represent a 50-level depth of differentiation in a real organism . The results reported above were obtained for specific values of parameters ( Table 2 ) which represent rules 1–4 and 1′–2′ ( Eqs . , 2–3 in Methods ) . Our simulation results are consistent with diverse experimental observations ( see Table 3 and discussion below ) only if the methylation constraints ( rule 4 ) and mutual repression of expression of gene modules ( rule 2′ ) are relatively strong effects ( i . e . H>G and J>F , see Table 2 , Eqns ( 2–3 ) , and parameter sensitivity in SI for further details ) . As long as these two conditions are met , the specific choice of parameter values only alters the quantitative value of the number of successfully reprogrammed cells , but reprogramming to the ES state remains rare . Our simulation results suggest a mechanistic explanation for why reprogramming is so rare . When reprogramming factors attempt to change cellular identity by altering the epigenetic state of a previously silenced gene module , the probability of success depends upon the position of this module relative to the one that regulates the terminally differentiated state . We find that the position of the module whose epigenetic state is altered can belong to one of three categories ( Fig . 5a ) . Suppose this gene module regulates a cellular identity in a different lineage from the terminally differentiated state . In the next interphase , both modules can express proteins as there are no mutually repressive interactions between them . In the subsequent telophase , proteins expressed by each module would favor epigenetic silencing of the other ( rule 4 ) . Expression of proteins characteristic of a cell type from a different lineage does not favor reprogramming because it leads to cell death or arrest in our model . Cell death could be mediated by various mechanisms including genetic instabilities if the two open gene modules send conflicting instructions to housekeeping genes . Of course , there is also the chance that the cell will be rescued by stochastic expression of some master-regulatory gene , or that the cell will assume an “intermediate” cell state without master regulation that could be viable , but does not reprogram , such as some arrested states [18]; finally , there is a possibility that two master regulators will not repress each other in full , but some minuscule amount of expression of both will remain thus , arresting the cell . Within the framework of our model we do not distinguish between these possibilities , and classify cells in all these unusual , dead , or arrested states to be dead/arrested . The gene module whose epigenetic state is altered by reprogramming factors could be in the same lineage as the differentiated cell , but not be its sibling or progenitor . In the following interphase , this module and the one that regulates the terminally differentiated state can both express proteins . In the subsequent telophase , according to our model , protein products of the gene module regulating the terminally differentiated state will favor epigenetic silencing of the module that was turned on by the action of reprogramming factors ( rule 4 ) . But , the opposite is not true because the cellular state regulated by the gene module whose epigenetic state was altered by reprogramming factors could potentially differentiate to the terminally differentiated cell type . Thus , the altered gene module will be silenced again , and the cell remains terminally differentiated . Reprogramming factors could also change the epigenetic state of a previously silenced gene module which regulates an immediate sibling or the progenitor of the terminally differentiated state . In the subsequent interphase , these two gene modules with open chromatin status will not simultaneously express proteins at high levels . This is because gene modules that are “nearest neighbors” in the hierarchy mutually repress each other ( rule 2′ ) . If the dominantly expressed gene module ( determined stochastically ) is the one which regulates a sibling or the progenitor of the terminally differentiated state , then during the next telophase its products will establish epigenetic marks consistent with a new identity ( rule 1 ) . Thus , with a probability determined by stochastic effects , a step toward reprogramming can occur via trans-differentiation or de-differentiation . These arguments suggest that a step toward reprogramming occurs with significant probability only if the epigenetic state of a gene module regulating a sibling or progenitor of the differentiated cell is changed to open chromatin status by reprogramming factors . This is a rare event in our simulations where the set of master regulator genes that determine a cellular identity are considered to be one gene module . In reality , this is even less likely because it requires reprogramming factors to orchestrate changes to a set of master regulator genes synchronously . For successful reprogramming to the ES state , a sequence of such rare events must occur in a particular cell . This is because after a step toward reprogramming occurs , the partially reprogrammed cell is subject to all the constraints discussed above . Therefore , although cellular identity is plastic , reprogramming a terminally differentiated cell to the ES state is rare and requires many cell cycles . Two examples of how states evolve under the influence of reprogramming factors in our simulations are shown in Fig . 5b . The first example shows a “cell” that does not successfully reprogram , as after a successful trans-differentiation , ultimately the cell is arrested/dead . In the second example reprogramming to the ES state occurs successfully , and it shows an interesting feature . At an intermediate time point , before the ES state is realized , reprogramming factors have turned on expression of the endogenous gene module that regulates the ES state . But this is transient , as this module is quickly silenced . We find that , unless proteins expressed by each gene module can stably repress genes that are distal in the hierarchy of states ( rule 4 , realized presumably through DNA methylation ) , expression of endogenous genes that regulate the ES state can occur early and prior to the temporal increase in the number of bivalently marked genes observed during reprogramming . In other words , our model recapitulates the observation that endogenous expression of Oct4 and Sox2 is the last step toward reprogramming only if the “DNA methylation” constraint is long-ranged . Thus , the model suggests that transient blocking of methylation machinery might allow endogenous expression of Oct 4 , Sox2 , etc . , at intermediate time points . This is consistent with the observation that DNA methyltransferase and histone deacetylase ( HDAC ) inhibitors , such as valproic acid ( VPA ) , an HDAC inhibitor , improve reprogramming efficiency [9] . Our model predicts that reprogramming occurs via a sequence of trans-differentiations to immediate siblings or de-differentiations to immediate progenitors in the hierarchy of cellular states . Note , however , that our results do not imply that pure differentiated states will be observed as reprogramming occurs . Oct4 , Sox2 , etc . , have numerous targets , and so genes from unrelated lineages will transiently be expressed during reprogramming to the ES state ( 22 ) . But , the entire set of master regulatory genes for a cellular state from a different lineage will not be expressed . We illustrate this point by showing computer simulation results from a model where we consider each gene module to be comprised of three individual genes ( Fig . 6 ) . Reprogramming factors can attempt to change the epigenetic state of the individual genes randomly as before . However , in this more complex model , if we allow only one gene's epigenetic state to be modified in every telophase , reprogramming becomes so rare that we cannot observe it in a realistic computer simulation time . So , we allowed a larger number of transformations per cycle . Choosing this number to be too large corresponds to overexpression of reprogramming factors , and this severely hinders reprogramming ( Text S1 , section 2 ) . For the results shown in Fig . 6 , we randomly pick 12 genes and change their epigenetic states during each simulated telophase . We assume that the entire set of genes comprising a module must be expressed for its products to regulate the epigenetic or genetic network . This is consistent with combinatorial control of regulation . Fig . 6a shows two examples of in silico cells that successfully reprogram to the ES state . Reprogramming takes place via a sequence of trans-differentiation and de-differentiation events wherein the entire set of genes that regulate a progenitor or sibling of the previous cellular state is expressed . But , the intermediate states are not pure differentiated states as some genes from unrelated lineages are also turned on at the same time ( as observed in experiments [18] ) . If the terminally differentiated state in our simulations is analogous to a B cell , our simulations predict that all successfully reprogrammed cells must transit through an impure state where all the genes regulating the hematopoetic stem cell state are turned on ( as in Fig . 6a ) . Although beyond the scope of this work , it would be reasonable to test this prediction by applying a cre-lox based lineage-tracing approach . Using one or more stem/progenitor specific promoters that are inactive in the terminal state ( e . g . , B cell ) , in combination with a lox-STOP-lox reporter , one could retrospectively determine whether all the resulting iPS cells are labeled and hence have transiently expressed markers of earlier stages within the same lineage . An unrelated cell type , such as fibroblasts , should generate unlabeled iPS cells because it would not be expected to transition through hematopoietic progenitor stages and hence serve as an appropriate control . The results depicted in Fig . 6 could also potentially be assessed quantitatively in experiments where the temporal evolution of the gene expression patterns of a number of successfully reprogrammed cells is observed . Consider a state where the master regulator genes corresponding to a particular cellular identity are all expressed . One could then ask: when these genes are subsequently silenced during reprogramming , which complete set of master regulatory genes start expressing proteins ? One could ask this question at various times during reprogramming and in various successfully reprogrammed cells . This would enable calculation of the following four point correlation function ( C ) : ( 1 ) where δ is the Kroenecker delta , t is time , t+Δt is a later instant in time during reprogramming ( a cycle in our simulations ) , i and j are labels of two genes , and Si is either 1 or 0 depending upon whether the ith gene is expressing proteins or turned off . Our computer simulations predict ( Fig . 6b ) that , at each stage of reprogramming , the correlation function would have high values for genes from lineages related to the terminally differentiated starting point and low values for genes of unrelated lineages . We hope that this prediction can also be assessed in future experiments . This could involve permanent labeling as mentioned above , or possibly , in the long-term , real-time monitoring of cell state transitions .
To the best of our knowledge , we have developed the first computational model that describes how terminally differentiated cells may be reprogrammed by expression of ectopic genes . This is achieved by a mathematical description of interactions between epigenetic and genetic networks of master-regulatory genes that govern specific cell states . The model also describes differentiation in accord with experiments . Our model describes cellular states as attractors on a generalized landscape of all possible genetic/epigenetic configurations . Cellular states are stable , self-renewing states unless a perturbing signal ( either differentiation cue or reprogramming factors are introduced ) . As summarized in the table 3 , major features of the reprogramming process are explained by our results and the mechanism of reprogramming it suggests . For instance , different cell types can be reprogrammed with the help of the same set of factors [1] , [12] , [16] because ectopic expression of genes that have many targets ( e . g . , Oct4 and Sox2 ) can perturb the epigenetic state regardless of the identity of the starting differentiated cell type . The importance of fast progression through the cell cycle ( due to cMyc , Klf4 , or p53 knockdown ) is because this offers more opportunities for epigenetic transformations during telophase . The important experimental observation that endogenous Oct4 and Nanog expression [2] occurs just prior to complete reprogramming is also recapitulated by our model . The stochastic nature of the reprogramming process [56] and its low yield [2] are because only a few types of trajectories can lead to successful reprogramming , and they are realized rarely by stochastic perturbation of the epigenome by the reprogramming factors . Our model predicts the nature of these rare trajectories to be those that progress through reprogramming via de-differentiation to closely related cell types ( immediate progenitors or siblings in the hierarchy ) . Ways to directly test this prediction are suggested . However , any feature that involves a specific molecular interaction between specific molecules is not described by our model . In our current model , we consider states with genes that express proteins with conflicting demands to die/arrest . In reality , some of these situations can give rise to steady states that do not arrest or reprogram ( such as the recently studied BIV1 , MCV8 , etc . , cell lines ) [18] . The ideas emerging from our model are consistent with observations made by manipulating these trapped states . For example , consider the observation that removing reprogramming factors allows cells from the BIV1 cell line ( isolated during reprogramming of B lymphocytes ) [18] to reprogram to the ES state . This suggests that overexpression of reprogramming factors prevents these cells from reprogramming to the ES state . Our model suggests that this could be due to two reasons . First , over expression of reprogramming factors ( which have many targets ) could simultaneously change the epigenetic states of a number of silenced genes to permissive chromatin status . Our simulations of the model shown in Fig . 6 with a large number of such simultaneous transformations ( e . g . , 22 at a time , rather than 12 at a time used for Fig . 5 ) prevents successful reprogramming because of the large probability of obtaining dead or arrested states . As noted above , one of these states that cannot reprogram could correspond to the BIV1 cells . Secondly , our model describes how lowering expression of reprogramming factors in BIV1 cells could enable reprogramming . In our simulations , we consider proteins expressed during each interphase to act on the epigenome to reach a new balance which then leads to a corresponding protein expression pattern before another epigenetic transformation can occur due to the action of reprogramming factors . This is analogous to assuming that the reprogramming factors can act to change the epigenetic state of a set of master regulator genes rarely . If reprogramming factors are grossly overexpressed , this would not be true . So , before a new protein expression pattern could be expressed consistent with a newly acquired epigenome ( say , de-differentiation to a progenitor ) , another epigenetic transformation would occur , and the whole cycle would start again . Simulation results showing this effect upon overexpression of reprogramming factors are depicted in Fig . 3B in Text S1 . Removing reprogramming factors could potentially allow reprogramming of cells trapped in such an infinite loop . Our low-resolution model for the architecture of genetic and epigenetic regulatory networks that determine how cellular identities change is consistent with diverse observations ( Table 3 ) . In formulating this model , we ruled out many models that were inconsistent with known experimental results , but we cannot rule out all other possible models . Therefore , the predictions of the model ( noted earlier ) need to be experimentally tested ( perhaps in ways that we have suggested ) to either falsify it or encourage studying it further . If tested positively , the suggestions emerging from our model regarding ways to enhance reprogramming yields should be further explored . It would also be interesting to study other transcription factor induced cell state conversions [57] , [58] within the conceptual and computational framework we have developed for how cellular identity is transformed . In particular , recent results of direct conversion between exocrine and endocrine cells through ectopic expression of three alternative transcription factors [59] should be examined . It would be interesting to further investigate several assumptions adopted in the model for the lack of specific information about individual master-regulatory modules . For example , maximum expression levels of different master-proteins within different modules could differ , as well as coupling between genetic and epigenetic networks could be different for different modules . Also , we assumed that every simulated cell ( as represented by a simulated trajectory ) has the same level of expression of reprogramming factors while in reality cells can be transfected in a heterogeneous fashion . Also , the difference in viral integration sites in different cells could lead to the different expression levels of exogeneous genes thus making effect of reprogramming factors heterogeneous across the population . In a sense then , we have studied those cells which have expressed reprogramming factors at levels above a threshold . It would be interesting to further explore the consequences of such heterogeneity . Another avenue for further exploration lies in defining the notion of time during the reprogramming process , in this work cell cycling has been adopted as a measure of time required for reprogramming while in reality cells cycle with non-equal rates determined from some form of cell division rate distribution ( simplest form would be an exponential distribution ) . It would be interesting to see applicability of the 4-point correlation function based analysis for the situation when cell cycling rates are not identical . Finally , de-silencing action of reprogramming factors is assumed to be distributed randomly . It would be interesting to consider situations when de-silencing distribution is not uniform across the hierarchy . It is possible that non-uniform distributions can improve the reprogramming efficiency . From the standpoint of statistical physics , our model couples a Potts model with short and long-ranged interactions in external fields ( Eq . 2 ) with an Ising model with short-ranged interactions in an external field ( Eq . 3 ) . It may be fruitful to develop a deeper field-theoretic understanding of such models .
All simulations are carried out with the help of two hierarchical lattices because two lattices are required to properly describe the cell state as shown in Fig . 1b . In the simulation code provided in Text S2 , we consider 4 levels in the hierarchy ( such as the one in Fig . 1b ) . Other possibilities ( 3 and 5 levels ) have been considered also . The epigenetic lattice has a discrete epigenetic state associated with each node ( −1 , 0 , +1 ) . Sepigen = −1 corresponds to closed chromatin , Sepigen = 0 corresponds to bivalent chromatin and Sepigen = +1 corresponds to open chromatin . Genetic lattice describes expression of proteins from master-regulatory modules . It has discrete gene expression states associated with each node ( 0 , +1 ) . Sgen = 0 corresponds to the absence of any protein expression from the given gene , Sgen = +1 corresponds to the maximum protein expression from the gene . In the course of simulation , cell states change in response to random epigenetic perturbations according to the rules described above ( see Table 1 for summary ) . There are two possible endpoints for the simulation procedure: either the cell will assume a dead/arrested state , in which case the simulation stops; or it will , as a consequence of a random sequence of epigenetic transformations , be reprogrammed to the ES-state , which is indicated by the stable turning on proteins expressed by the of ES-regulatory module . In the latter case we stop the simulation procedure manually because , according to experimental observations [2] , stable expression of endogenous Oct4 suppresses expression from the exogenous locus , thus preventing future action of reprogramming factors . In order to initialize simulations one has to specify either the epigenetic or genetic state of the lattice ( see Fig . 7 ) . If we start by specifying the protein expression pattern , computer simulations are carried out to determine the epigenetic state that is realized in telophase . A Monte-Carlo simulation algorithm is used in accord with the following Hamiltonian , with its four terms representing rules 1–4 ( see Model development ) , respectively: ( 2 ) Siep denotes the epigenetic spin state of the ith module , and Sigen specifies the protein expression level of the ith module . The angular brackets denote the average expression level of the jth module obtained during the preceding interphase , and could include protein products of ectopic genes or signaling events . |Siep| represents the absolute value of Siep . The quantity G is a positive parameter that represents the strength with which the protein atmosphere can modify the epigenetic state by altering histone marks . H is a positive parameter that represents the strength of the DNA methylation constraint . The quantity , a , is a positive constant that favors values of Siep<a if proteins expressed by gene , j , are present . As detailed in the Text S1 ( see section 2 ) , the results of our simulations are inconsistent with experimental results if H is not greater than G . As long as H>G , our qualitative results do not depend upon the specific values of these parameters . The specific value of a does not affect qualitative results . Results presented in the main text are for a = 0 , and G = 25 , H = 40 ( in units described below ) . During simulation of the telophase , the epigenetic state Sepigen of each module fluctuates . The output of the telophase simulation is <Sepigen> , an average of these fluctuating values for each node of the lattice ( i . e . for each module ) . Because we have a discrete representation for the epigenetic marks ( +1 , 0 , or −1 ) while actually each gene bears multiple marks , using the average allows us to reflect intermediate levels of positive and negative histone marks on a gene . For example , an average value near zero for the epigenetic state of a gene module implies that both positive and negative marks are present on histones associated with it , a value close to one represents an open chromatin state , etc . Average values of epigenetic state serve as input for simulation of interphase . If <Sepigen>∼1 ( gene is epigenetically available ) , than it will favor protein expression during the interphase in accord with the rules depicted on Fig . 3a . Similarly , if two neighboring states are epigenetically available , only one protein will be expressed due to mutual repression of neighboring master-regulators . Separate Monte Carlo simulations are carried out to establish gene expression patterns during interphase . The following Hamiltonian , with the two terms in it corresponding to rules 1′ and 2′ ( see Model development ) , respectively , is used: ( 3 ) The angular brackets denote the average value of epigenetic state of the ith module obtained during the preceding telophase . F is a positive constant that represents how strongly a protein is expressed or repressed if it is in open chromatin state or in heterochromatin , respectively . The parameter , b , is a positive constant; protein expression is favored if <Siep>>b . Note that the form of the first term in Eq . 3 implies that protein expression is more strongly repressed if a gene is packaged in heterochromatin compared to if it is bivalently marked . J represents the strength of mutual repression by other proteins . As detailed in the Text S1 ( section 2 ) , our results are inconsistent with experiments if J is not greater than F . As long as J>F , the specific values do not affect qualitative results . As long as the parameter b is larger than the typical size of fluctuations in <Siep> ( ∼0 . 1 ) , the specific value of b does not affect qualitative results . Results presented in the main text correspond to b = 0 . 3 , and F = 2000 , J = 3000 ( for units , see below ) . Values of Sigen fluctuate during this Monte-Carlo procedure . The output of the simulation of the interphase is <Sigen> , which represents the average expression level of the regulatory protein in the interphase . These averages are further used in the next telophase simulation , thus , completing the cycle . The Monte-Carlo algorithm is standard [60]: the lattice spins ( +1/0/−1 on epigenetic lattice; +1/0 on genetic lattice ) are initialized randomly . The move consists of 1 ) randomly choosing the node on the lattice; 2 ) randomly deciding on the choice of new value of Si for this node ( i . e . if Siepigen was 0 then it can become −1 or +1 with equal probability ) ; 3 ) energy for this configuration is computed according to the appropriate Hamiltonian; 4 ) attempted changes in state are accepted with probability equal to min [1 , exp {] . The parameter , β , is analogous to inverse temperature used in simulation of thermal systems , and sets the scale for the parameters , F , G , H and J . If we pick this effective temperature to be too high ( β≪F , G , H , J ) , the system is disordered; specific cellular identities are not established and the model has no biological significance . We use β = 1 for results reported in the main text . During each phase , the Monte-Carlo procedure is carried out until running average values of <Siep/gen> stop changing along the trajectory; i . e . , they converge to a single well-defined value . For the reported parameters ( Table 2 ) , 50 , 000 updates are sufficient for accurate averaging during each phase . A computer code written using the C++ language is provided as Text S2 allows calculation of all the results we report . For details regarding the output and input formats see the Text S1 .
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Most cells in an organism have the same DNA . Yet , different cell types express different proteins and carry out different functions . These differences are reflected by cell epigenetics; i . e . , DNA in different cell types is packaged distinctly , making it hard to express certain genes while facilitating the expression of others . During development , upon receipt of appropriate cues , pluripotent embryonic stem cells differentiate into diverse cell types that make up the organism ( e . g . , a human ) . There has long been an effort to make this process go backward— i . e . , reprogram a differentiated cell ( e . g . , a skin cell ) to pluripotent status . Recently , this has been achieved by overexpressing specific transcription factors in differentiated cells . This method does not use embryonic material and promises the development of patient-specific regenerative medicine . The mechanisms that make reprogramming rare , or even possible , are poorly understood . We have developed the first computational model of transcription factor-induced reprogramming . Results obtained from the model are consistent with diverse observations , and identify the rare pathways that allow reprogramming to occur . If validated by further experiments , our model could be further developed to design optimal strategies for reprogramming and shed light on basic questions in biology .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"biophysics/theory",
"and",
"simulation"
] |
2010
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A Model for Genetic and Epigenetic Regulatory Networks Identifies Rare Pathways for Transcription Factor Induced Pluripotency
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Chagas Disease is the leading cause of heart failure in Latin America . Current drug therapy is limited by issues of both efficacy and severe side effects . Trypansoma cruzi , the protozoan agent of Chagas Disease , is closely related to two other major global pathogens , Leishmania spp . , responsible for leishmaniasis , and Trypansoma brucei , the causative agent of African Sleeping Sickness . Both T . cruzi and Leishmania parasites have an essential requirement for ergosterol , and are thus vulnerable to inhibitors of sterol 14α-demethylase ( CYP51 ) , which catalyzes the conversion of lanosterol to ergosterol . Clinically employed anti-fungal azoles inhibit ergosterol biosynthesis in fungi , and specific azoles are also effective against both Trypanosoma and Leishmania parasites . However , modification of azoles to enhance efficacy and circumvent potential drug resistance has been problematic for both parasitic and fungal infections due to the lack of structural insights into drug binding . We have determined the crystal structures for CYP51 from T . cruzi ( resolutions of 2 . 35 Å and 2 . 27 Å ) , and from the related pathogen T . brucei ( resolutions of 2 . 7 Å and 2 . 6 Å ) , co-crystallized with the antifungal drugs fluconazole and posaconazole . Remarkably , both drugs adopt multiple conformations when binding the target . The fluconazole 2 , 4-difluorophenyl ring flips 180° depending on the H-bonding interactions with the BC-loop . The terminus of the long functional tail group of posaconazole is bound loosely in the mouth of the hydrophobic substrate binding tunnel , suggesting that the major contribution of the tail to drug efficacy is for pharmacokinetics rather than in interactions with the target . The structures provide new insights into binding of azoles to CYP51 and mechanisms of potential drug resistance . Our studies define in structural detail the CYP51 therapeutic target in T . cruzi , and offer a starting point for rationally designed anti-Chagasic drugs with improved efficacy and reduced toxicity .
Chagas Disease , a potentially lethal tropical infection , is caused by the kinetoplastid protozoan Trypanosoma cruzi , which is spread by blood-sucking reduviid insects [1] . It is the leading cause of heart failure in Latin America , with an estimated to 8–10 million people infected [2] . The parasite invades and reproduces in a variety of host cells , including macrophages , smooth and striated muscle , fibroblasts and neurons . Disease progression is marked by an initial acute phase , which typically occurs in children , followed by a symptom-free intermediate phase . A chronic phase leading to GI tract lesions and heart failure often ensues . Current chemotherapy options are limited to nifurtimox and benznidazole , which have been in use since the late 1960s and are compromised by adverse side reactions and low efficacy in chronic disease [3] , [4] . A need for drugs with more consistent efficacy and less toxicity is manifest . With an essential requirement for ergosterol [5] and an inability to survive solely on cholesterol salvaged from the host , T . cruzi is vulnerable to inhibitors of the sterol biosynthesis enzyme 14α-demethylase ( CYP51 ) [6] , [7] . Disruption of CYP51 results in alteration in the ultrastructure of several organelles , decline of endogenous sterols in the parasites , and an accumulation of various 14α-methyl sterols with cytostatic and cytotoxic consequences [8] . The broad spectrum antifungal drug posaconazole ( Noxafil; Schering-Plough ) [9] , which targets CYP51 , is poised for clinical trials against T . cruzi [6] , [10] , [11] . Posaconazole is capable of inducing parasitological cure in a murine model of both acute and chronic Chagas Disease , curing between 50–100% of animals in the acute phase of infection , and 50–60% of animals chronically infected [7] , [11] . However , the high manufacturing cost of posaconazole and the requirement for administration via oral suspension simultaneously with a fatty meal or nutritional supplement to enhance absorption may limit its use in treating chronic T . cruzi infections [12] . The search for CYP51-specific compounds that are easier to synthesize and better absorbed upon oral administration continues [13]–[17] . To rationalize protein-ligand interactions for new inhibitors in T . cruzi , homology modeling based on the x-ray structure of CYP51 from Mycobacterium tuberculosis ( CYP51Mt ) [18]–[20] has been used [14] , [15] , [17] . But CYP51Mt has only 27% sequence identity to the T . cruzi enzyme and is unusually exposed to the bulk solvent at the substrate binding site . This structural peculiarity largely excludes the functionally important BC-loop from protein-inhibitor interactions and thus limits the utility of CYP51Mt as a model for a Chagas Disease target . The CYP51 BC-loop residue 105 ( numbering according to T . cruzi and T . brucei CYP51 ) is indispensable in the discrimination of the species-specific sterol substrates in T . cruzi and T . brucei [19] , [21] . Also , a critical mutation hot spot [22] , the well conserved BC-loop residue Y116 was reported to be involved in fungal drug resistance , inhibitor binding , and the catalytic function of CYP51 in Candida albicans ( Y132 , according to C . albicans numbering ) [22]–[27] , Histoplasma capsulatum ( Y136 , according to H . capsulatum numbering ) [28] , and in the causative agents of zygomycosis in humans , Rhizopus oryzae and Absidia corymbifera [29] . It may therefore play a similar role in T . cruzi . Here we report the crystal structures for the CYP51 target in T . cruzi ( CYP51Tc ) ( resolutions 2 . 35 Å and 2 . 27 Å ) and that of the closely related CYP51 ortholog from Trypanosoma brucei ( CYP51Tb ) ( resolutions 2 . 7 Å and 2 . 6 Å ) , each bound to an anti-fungal triazole drug , either fluconazole or posaconazole . T . brucei is a protozoan parasite closely related to T . cruzi [30] and the agent of another lethal tropical disease , African Sleeping Sickness . In contrast to T . cruzi and Leishmania spp . , it is not clear if the sterol biosynthesis pathway can be targeted in T . brucei . Each parasite has a different life-cycle and different sterol requirements . Although the insect ( procyclic ) form of T . brucei can undertake de novo sterol biosynthesis , the latter is apparently suppressed in the bloodstream form in the mammalian host , which is supported by receptor-mediated endocytosis of host low-density lipoproteins that carry phospholipids and cholesterol esters [31] . Nevertheless , CYP51Tc and CYP51Tb do share 83% sequence identity , a fact which has been crucial for successfully determining their crystal structures and makes it possible to extrapolate structural features learned from one enzyme toward the other . Furthermore , the Leishmania CYP51 are 72–78% identical to that of T . cruzi and T . brucei , so they too can now be modeled to facilitate drug discovery and development .
By trial-and-error we empirically identified the protein N-terminal modification that eventually led to CYP51 crystals of sufficient quality to determine the x-ray structure . To improve our chances for success , we did the work in parallel on CYP51 proteins from Trypanosoma cruzi and Trypanosoma brucei . Five different expression vectors were designed in this work for each CYP51 ortholog to eliminate a stretch of hydrophobic residues which presumably mediate association of the proteins with the endoplasmic reticulum ( ER ) . In their place we introduced hydrophilic or charged sequences at the N-terminus ( Table 1 ) . His6-tag ( CYP51Tc ) or His8-tag ( CYP51Tb ) was introduced at the C-terminus to facilitate purification . Coding sequences were sub-cloned between the NdeI and HindIII restriction cloning sites of the pCWori vector [32] and in this form used to transform Escherichia coli strain HMS174 ( DE3 ) . The original coding sequence for CYP51Tb contained an internal NdeI site at 345 bp which was silenced by QuickChange site-directed mutagenesis ( Stratagene ) using forward GGGGTTGCCTATGCTGCC and reverse CCCCAACGGATACGACGG PCR primers . DNA amplification reaction: 5 min at 94°C , annealing for 1 min at 50–60°C , extension for 1 . 5 min at 72°C , for 30 cycles , followed by extension for 10 min at 72°C . The highest expression levels were achieved and the best crystals were obtained from the expression constructs modified by replacing the first 21 residues upstream of K22 with the fragment MAKKKKK . Subsequently , based on the analysis of the packing interactions in the crystal , three consecutive glutamate residues , E249-E251 , were replaced in CYP51Tb with alanine by site-directed mutagenesis ( Stratagene ) using forward GCGCGGCTGCTGCTGTCAACAAGGACAGC and reverse GCGCGAGCAGCAGCCTTTCGAGCAATGAT PCR primers . DNA amplification reaction: 5 min at 94°C , annealing for 1 min at 45–65°C , extension for 1 . 5 min at 72°C , for 35 cycles , followed by extension for 10 min at 72°C . This CYP51Tb variant was used to generate the CYP51Tb-posaconazole crystals . The identity of all resulting vectors was confirmed by DNA sequencing . Screening of crystallization conditions was routinely performed following purification of protein variants using commercial screening kits available in high throughput screening format ( Hampton Research ) , a nanoliter drop-setting Mosquito robot ( TTP Labtech ) operating with 96-well plates , and a hanging drop crystallization protocol . Optimization of crystallization conditions , if required , was carried out manually in 24-well plates at 23°C . Proteins were from 1 . 0–1 . 8 mM frozen stocks in 20 mM Tris-HCl , pH 7 . 2 ( CYP51Tb ) or pH 8 . 0 ( CYP51Tc ) , 10% glycerol , 0 . 5 mM EDTA , and 1 mM DDT . The CYP51Tb triple mutant E249A/E250A/E251A was used to obtain CYP51Tb-posaconazole crystals . Prior to crystallization proteins were diluted to 0 . 1–0 . 2 mM by mixing with 50 mM potassium phosphate at appropriate pH , supplemented with 0 . 5 mM ( CYP51Tb ) or 0 . 1 mM ( CYP51Tc ) fluconazole . Dilution in the absence of fluconazole or phosphate caused fast precipitation of protein samples . Posaconazole was prepared as 10 mM stock solution in DMSO and has been used at final concentration of 0 . 2 mM . Protein-posaconazole mix was incubated at 4°C for one hour prior to crystallization . Crystals of CYP51Tb–fluconazole complex grew from 15% ethylene glycol and 0–3% acetonitrile . Crystals of CYP51Tb–posaconazole complex grew from 6% PEG 4000 , 2% tacsimate , pH 8 . 0 , and 2% DMSO . Crystals of CYP51Tc–fluconazole grew either from 40% polypropylene glycol 400 and 0 . 1 M Tris-HCl , pH 6 . 0 ( PDB ID 2WUZ ) , or from 25% PEG 4000 and 0 . 1 M Bis-Tris , pH 5 . 5 ( PDB ID 2WX2 ) , the latter being harvested directly from the Mosquito 200-nl drop . Prior to data collection , the crystals were cryo-protected by plunging them into a drop of reservoir solution supplemented with 20–24% ethylene glycol or 20% glycerol , and flash-frozen in liquid nitrogen . All native and two-wavelength anomalous dispersion x-ray diffraction data were collected at 100–110 K at beamline 8 . 3 . 1 , Advanced Light Source , Lawrence Berkeley National Laboratory , USA . Anomalous diffraction data were collected from one CYP51Tb crystal at two wavelengths , one corresponding to the median between the Fe peak and the inflection point and the other at 375 eV higher ( Table 2 ) . Data indexing , integration , scaling , phasing , and density modification were conducted using the ELVES automated software suite [34] ( Tables 2 and 3 ) . CYP51Tb–fluconazole data processed in P3121 with Rmerge of 6 . 5% allowed for location of a single Fe atom . Initial phases with an overall figure of merit of 0 . 26 were improved by solvent flattening ( mean figure of merit 0 . 85 after solvent flattening ) to provide an interpretable electron density map ( Table 2 ) . Automated model building using BUCCANEER [35] placed the polyalanine backbone for 84% of the residues in the asymmetric unit . The remaining residues were built manually with COOT [36] , alternated with TLS and positional refinement using REFMAC [37] , [38] . The structure was refined to 3 . 2 Å with the R and Rfree values of 32 . 0% and 38 . 0% , respectively . Although showing up largely as a polypeptide backbone at low resolution , this T . brucei structure served as a search model for molecular replacement in determining the x-ray structure for CYP51Tc using 2 . 35 Å native data processed as P21 with Rmerge of 11% . Two CYP51Tc molecules were placed in an asymmetric unit . Manual model building with COOT [36] alternated with TLS and positional refinement using REFMAC [37] , [38] resulted in the final CYP51Tc structure with the R and Rfree = values of 21 . 7% and 27 . 5% and the Ramachandran statistics of 93 . 8% residues in preferred regions , 5 . 2% in allowed regions , and 1% ( 9 residues ) outliers , as calculated by COOT . NCS restrains were applied at all stages of the refinement . The refined CYP51Tc structure was used as a starting model against both the 2 . 27 Å native data for CYP51Tc and 2 . 7 Å native data for CYP51Tb , which allowed the majority of the CYP51Tb side chains to be built in . At that time , refinement of CYP51Tb converged with R and Rfree of 21 . 0% and 27 . 4% , respectively . Ramachandran statistics indicate 91 . 2% residues in preferred regions , 5 . 9% in allowed regions , and 2 . 9% ( 13 residues ) outliers . Refinement of 2 . 27 Å CYP51Tc data converged with R and Rfree of 19 . 3% and 27 . 3% , respectively , and the Ramachandran statistics of 95 . 6% residues in preferred regions , 3 . 5% in allowed regions , and 0 . 9% ( 9 residues ) outliers . Analysis of the crystallographic symmetry packing interactions in the CYP51Tb-fluconazole complex revealed contacts between the triplets of glutamate residues D249-D251 situated in the GH-loop . To reduce electrostatic repulsion , all three residues were replaced with alanine . Although this modification did not improve resolution of the CYP51Tb-fluconazole crystals , the triple mutant was more amenable to co-crystallization with posaconazole . The CYP51Tb coordinates refined to 2 . 7 Å served as a search model to determine CYP51Tb-posaconazole structure using 2 . 6 Å native data processed as C2 with Rmerge of 8 . 5% . Four protein molecules were placed in an asymmetric unit . Refinement converged with R and Rfree of 19 . 1% and 26 . 4% , respectively and the Ramachandran statistics of 95 . 3% residues in preferred regions , 4 . 0% in allowed regions , and 0 . 7% ( 13 residues ) outliers . In all structures , side chains not visible in the density were modeled as alanine ( Table 3 ) . Binding of posaconazole to CYP51Tc was predicted by molecular docking using the 2WUZ structure . Docking was carried out using GLIDE ( version 5 . 0 ) [39] . The docking protocol was validated by re-docking of fluconazole , which reproduced the binding mode observed in the crystal structure . The protein was initially prepared by the Protein Preparation Wizard module using default options . Hydrogen atoms were added to the complex structure , followed by a restrained minimization using the OPLS2005 force field . The Receptor Grid Generation module was then employed to prepare a rigid receptor grid centered at M360 , which contains the entire binding tunnel of the energy minimized complex , for subsequent docking . The three-dimensional structure of posaconazole was generated by the Ligprep module with the OPLS2005 force field . Computational docking was performed using GLIDE in standard precision ( SP ) mode , and binding affinities were estimated as GLIDE score . The characteristic coordination between the heme group and the ligand was modeled by applying a constraint at the Fe3+ ion of the heme group that imposed interaction with one of the nitrogen atoms from the ligand's triazolyl ring . Since posaconazole ( molecular weight = 700 . 8 g/mol ) is significantly larger and longer than fluconazole ( molecular weight = 306 . 3 g/mol ) ( Fig . 1 ) , the van der Waals radii of the ligand were softened by a scaling factor of 0 . 6 in the initial docking calculation , which predicted two binding poses with similar Glide scores of −9 . 23 and −9 . 60 . The binding model was further refined by relaxing the binding tunnel in the presence of posaconazole . Side chains of residues within 4 Å from the docked posaconazole were optimized by performing side-chain refinement with Prime ( version 2 . 0 ) [40] . The resulting complex was used to re-dock posaconazole with van der Waals radii scaled by the default value of 0 . 8 . Consistent with the initial calculations , the second-round docking also predicted the same binding orientations with favorable and similar GLIDE scores ( pose 1 = −11 . 07; pose 2 = −10 . 70 ) . Protein Data Bank: coordinates and structure factors have been deposited with accession codes 2WUZ , 2WX2 , 2WV2 and 2X2N .
By trial-and-error , the highest expression levels and best crystals for both CYP51Tc and CYP51Tb were obtained from the expression constructs modified by replacing the first 21 residues upstream of K22 with the highly positively charged fragment MAKKKKK ( Table 1 ) . The triple E249A/E250A/E251A CYP51Tb mutant was based upon this N-terminally modified construct . The UV-vis spectra of purified proteins revealed features characteristic for homogeneous and normally folded P450 ( Fig . 2 ) . We first determined the crystal structure for CYP51Tb using anomalous dispersion of the heme iron . Although largely a backbone trace at 3 . 2 Å resolution , this structure served as a search model for molecular replacement in determining the CYP51Tc–fluconazole structure at 2 . 35 Å , which was used as a search model against the 2 . 27 Å CYP51Tc–fluconazole data to reveal an alternative conformation of fluconazole bound in the active site . This same CYP51Tc structure was used as a model against the 2 . 7 Å CYP51Tb–fluconazole data . Refined to 2 . 7 Å CYP51Tb coordinates subsequently served as a search model for determining the 2 . 6 Å CYP51Tb–posaconazole structure . CYP51Tc and CYP51Tb have a common P450 protein fold characterized by the sets of the α-helices and β-sheets highlighted in Fig . 3A , B . The T . cruzi and T . brucei structures superimpose with r . m . s . d . of 0 . 89 Å for Cα atoms , with the most pronounced differences in the region encompassing the F and G helices and the loop between them ( Fig . 4A ) . By contrast , Trypanosoma CYP51 enzymes do not superimpose nearly as well with bacterial CYP51Mt ( r . m . s . d . of 1 . 83 Å ) ( Fig . 4B ) , being more similar to their human counterpart ( CYP51h ) , based on both backbone similarity ( r . m . s . d . of 1 . 45 Å ) and solvent exposure at the active site ( Fig . 4C ) . All three eukaryotic enzymes lack the extreme bending of the I-helix that is associated with CYP51Mt , resulting in their active sites being more isolated from the bulk solvent . The structured BC-region in Trypanosoma CYP51 includes the B'-helix encompassed by the short η-helices blocking access to the active site from the bulk solvent . Seven residues from the BC-region , V102 , Y103 , I105 , M106 , F110 , A115 and Y116 , are part of the active site in CYP51Tc and CYP51Tb , which is consistent with our previous observation that a series of CYP51 inhibitors reported elsewhere [16] have higher binding affinities toward Trypanosoma CYP51 compared to CYP51Mt , where these residues do not participate in the active site due to the “open” conformation of the loop . The two CYP51Tc–fluconazole structures reported here superimpose with r . m . s . d of 0 . 68 Å , revealing some conformational differences in the F-helix and the BC-loop , which may account for the distinct fluconazole binding modes and result in re-packing of protein molecules in the crystal lattice ( Table 3 ) . In the CYP51Tb-posaconazole structure , four protein molecules in the asymmetric unit superimpose with the r . m . s . d . within of 0 . 5 Å , revealing virtually no conformational variations . However , posaconazole samples two distinct conformations due to the long tail swinging ∼7–8 Å in the hydrophobic mouth of the substrate binding tunnel ( Fig . 3B ) . The entrance to the tunnel is marked by a patch of the hydrophobic residues ( colored yellow in Fig . 3B ) , which apparently guide access of the sterol substrates to the active site . As expected , fluconazole is bound in the active site by coordination to the heme iron via the aromatic nitrogen atom of a triazole ring and by multiple van der Waals and aromatic stacking interactions ( Fig . 5 ) . All residues within 7 Å of fluconazole ( Fig . 6A ) are labeled with blue triangles in Fig . 7 . The 2 , 4-difluorophenyl moiety is enclosed in the pocket formed by the heme macrocycle , the aromatic side chains of Y103 , F110 , Y116 ( BC-loop ) and F290 ( I-helix ) , and aliphatic side chains M106 , A287 and A291 . Although fluconazole occupies the same pocket in both CYP51Tc structures , it adopts two conformations that differ by the 180° flipping of the 2 , 4-difluorophenyl moiety . Orientation 1 is observed both in the 2 . 27 Å CYP51Tc–fluconazole structure reported in this work ( PDB ID 2WX2 ) ( Fig . 5A ) and in the CYP51Mt-fluconazole complex reported elsewhere ( PDB ID 1EA1 ) [18] . The same conformation is adopted by the 2 , 4-difluorophenyl ring of posaconazole in the CYP51Tb-posaconazole complex in all four molecules in the asymmetric unit . In orientation 1 , Y103 makes a 2 . 7 Å H-bonding contact to the main chain amide group of M360 . A 180° flipped orientation of the ring , orientation 2 , is observed in the 2 . 35 Å CYP51Tc–fluconazole structure ( PDB ID 2WUZ ) ( Fig . 5B ) . As evidenced by the residual Fo-Fc electron density map calculated for the orientation 1 ( pink mesh in Fig . 5B ) , the 2-fluoro substituent of the fluconazole difluorophenyl ring in 2WUZ must point toward the heme macrocycle . A 2 . 6 Å H-bonding contact between the 2-fluoro substituent and the hydroxyl group of Y103 may help to stabilize orientation 2 , which appears to be less sterically favorable than orientation 1 . Perhaps both ring conformations co-exist in the CYP51Tc-fluconazole complex , possibly correlated with the conformation of the BC-loop which affects H-bonding pattern of Y103 . In orientation 1 , the H-bond between the 2-fluoro substituent and Y103 is broken due to the 3 . 5 Å reorientation of Y103 toward M360 resulting in the 2 . 7 Å H-bond to its amide nitrogen and in the flipping of the 2 , 4-difluorophenyl ring into a sterically more favorable orientation with the fluorinated edge facing away from the heme macrocycle ( Fig . 5B ) . Crystallization conditions may have served to shift the equilibrium by stabilizing one of these states . The entire fluconazole molecule is shifted about 1 . 5 Å between the two CYP51Tc structures , which may be related to the low efficacy of this drug against T . cruzi . Given that the CYP51Tb active site is virtually identical to that of T . cruzi , the same equilibrium would be expected to occur in T . brucei . However , we could not observe this phenomenon as CYP51Tb-fluconazole complex has been co-crystallized under a single set of conditions with one molecule in the asymmetric unit . The CYP51Tc structures revealed a 42 residue-long hydrophobic tunnel connecting the chamber adjacent to the heme with the protein surface ( Fig . 6B ) . Residues constituting the tunnel in addition to those interacting with fluconazole are labeled with green triangles in Fig . 7 . The mouth of the channel is surrounded by residues I45 , I46 , G49 , K50 , I209 , P210 , H458 , and M460 , which may delineate the substrate/inhibitor entry site in eukaryotic CYP51 ( Fig . 8 ) . This entry mode would be in contrast to that in CYP51Mt , where it most likely occurs through the open BC-loop . The tunnel-forming residues are invariant between CYP51Tc and CYP51Tb with the exception of four conservative substitutions at positions 46 , 105 , 215 and 359 . The residue at position 105 ( highlighted cyan in Fig . 7 ) is known to dominate substrate specificity with respect to the methylation status of the C-4 atom in CYP51 sterol substrates . I105 in T . cruzi allows efficient conversion of C4-dimethylated 24-methylenedihydrolanosterol while the bulkier F105 in T . brucei favors C4-monomethylated norlanosterol [19] , [21] . Phenylalanine in CYP51Tb protrudes further into the active site than isoleucine in CYP51Tc ( Fig . 6A ) , potentially resulting in interference with the 4β-methyl group of the sterol substrate . However , F105 does not interfere with either posaconazole or fluconazole binding . Comparison of the residues constituting the tunnel in CYP51Tc with the human counterpart , CYP51h , indicates that two residues , H236 and H489 ( numbered according to the human sequence and highlighted yellow in Fig . 7 ) , protrude into the tunnel near the opening , reducing both its size and hydrophobicity . As they are present exclusively in mammalian orthologues [41] , H236 and H489 may partly account for the selectivity of azole drugs toward pathogenic fungi and protozoa . In accord with this hypothesis , proline corresponding to H236 in pathogenic fungi is among hot spots that confer resistance to posaconazole in Aspergillus fumigatus ( P216 ) [42] and Candida albicans ( P230 ) [43] . The hydrophobic tunnel in CYP51Tb accommodates the antifungal drug posaconazole in either extended or bent conformations . The 2 . 6 Å structure of the CYP51Tb-posaconazole complex revealed four protein monomers in an asymmetric unit with posaconazole coordinating to the heme iron in a manner similar to that of fluconazole with the fluorinated edge of the 2 , 4-difluorophenyl ring facing away from the heme macrocycle , and the long substituent tail extending into the hydrophobic tunnel . Electron density is well defined for the Fe-coordinating head of the posaconazole molecule in all four monomers but somewhat fades out toward its long tail ( Fig . 8A ) . Thus , the terminal 2-hydroxypentan group is defined in none of four monomers . Three from the four monomers ( chains A , B , and C ) accommodate posaconazole in bent conformation while in the monomer D posaconazole is in extended conformation . Conformational variability of posaconazole is enabled by the interconversion of the piperazine six-membered ring between the chair and twisted boat conformations . The latter serves to accommodate the bend . Electron density is best defined in monomer B , where the terminal phenyl-2-hydroxypentan-triazolone group of posaconazole lies within 6 Å of protein residues I209-P210-A211 and V213-F214 which are invariant between CYP51Tc and CYP51Tb . P210 , the mutation hot spot in fungi , is situated right in the bend of the posaconazole molecule ( Fig . 9A ) . In the extended conformation in monomer D , the phenyl-2-hydroxypentan-triazolone group swings toward residues I45-I46 ( Fig . 9B ) . Remarkably , points of posaconazole contact in the tunnel mouth are among mutation hot spots in azole resistant isolates of pathogenic fungi A . fumigatus [42] , [44]–[48] and C . albicans [43] , [49] ( Fig . 8B and C ) . The scattered Fo-Fc electron density map in the monomers A and D ( Fig . 8A ) suggests possible interconversion of the posaconazole conformers in dynamic equilibrium , meaning that the phenyl-2-hydroxypentan-triazolone group dangles in space within the tunnel mouth ( Fig . 3D ) . Given the high sequence and structural similarities between CYP51Tc and CYP51Tb , similar dynamics would be expected in the CYP51Tc-posaconazole complex . The x-ray structures of the CYP51 therapeutic targets determined in this work are intended for use in rational drug design . We also apply computational methods to explore binding modes of known chemical structures as well as to generate new scaffolds based on the configuration of the CYP51 binding sites . Considering the differential geometries of the host and pathogen binding sites , we aim to develop a pool of highly selective molecules with no cross-reactivity to human CYP51 . As a first step , we docked posaconazole into the CYP51Tc active site and compared the docking poses with the experimental structure of CYP51Tb-posaconazole complex . Two poses with similar docking scores were identified for posaconazole by GLIDE [39] , differing primarily in the orientation of the 2 , 4-difluorophenyl ring ( Fig . 10 ) . Interestingly , the long posaconazole tail docks in a mode more similar to the CYP51Tb-posaconazole complex defined in this work rather than that in the recently deposited T . cruzi structure ( PDB ID Code: 3K1O ) . Given that the protein-posaconazole interactions in the tunnel are of hydrophobic/aromatic stacking nature ( Fig . 9 ) , this ambiguity is not surprising . Another source of docking ambiguity arises from the binding predicted for the 2 , 4-difluorophenyl substituent . In the better scoring pose 1 ( highlighted yellow in Fig . 10 ) , the 2 , 4-difluorophenyl ring binds in the experimentally observed orientation 1 . In the slightly lower scoring pose 2 ( highlighted pink ) , the 2 , 4-difluorophenyl ring is bound in a different pocket formed by the residues M106 , E205 , L208 , F290 , T295 , L358 and M460 , suggesting an additional cavity in the CYP51 active site suitable for drug targeting . This pose is achieved via flipping of the central furan ring to which all the substituents are attached . Thus , in addition to the experimentally observed binding ambiguity of the long substituent tail , conformational ambiguity of the difluorophenyl ring is predicted by the docking calculations and perhaps will be observed in future structures of CYP51 in complex with inhibitors similar to posaconazole . The rapid development of azole resistance in T . cruzi observed in vitro suggests that the same may occur in patients [50] . Although no data are available on the development of posaconazole resistance in Chagas Disease patients , studies conducted on fungal infections indicate that posaconazole resistance occurs mainly by a mechanism involving mutation of the cyp51 gene [42] , [51] , [52] . Posaconazole appears to be less susceptible to the efflux pumps that confer resistance to some other azoles [43] , [51] , [53] . Mapping mutations in cyp51 genes in clinical posaconazole resistant isolates on the CYP51 structure , points to the tunnel entrance as a mutation hot spot . Mutations of G54 , P216 and M220 in clinical isolates of A . fumigatus [42] , [44]–[48] ( corresponding to G49 , P210 and F214 , respectively , in CYP51Tc and CYP51Tb ) and of A61 [49] and P230 [43] in clinical isolates of C . albicans ( I45 and P210 , respectively , in CYP51Tc and CYP51Tb ) map directly to the tunnel mouth ( Fig . 8B and C ) . Mutations of G54 in A . fumigatus to arginine or tryptophan associate with moderate and high levels of resistance , respectively , and confer cross-resistance between itraconazole and posaconazole [44] . Mutations of M220 confer cross-resistance to all azole drugs tested , including itraconazole , voriconazole , ravuconazole and posaconazole [54] , [55] and therefore may interfere with the entry of the drugs . In accord with this assumption , posaconazole is reported to induce resistance to all azole drugs in Candida parapsilosis in vitro [51] . The alarming perspective emerging from antifungal therapy efforts must be taken into consideration when designing anti-Chagasic drugs targeting CYP51Tc . Thus , the terminal phenyl-2-hydroxypentan-triazolone group in posaconazole may play an important role in pharmacokinetics rather than in the interactions with the target , and yet these interactions seem to induce resistance which otherwise could probably be avoided . In summary , the x-ray structures of Trypanosoma CYP51 enzymes reported here open new opportunities for rationally designed inhibitors against therapeutic targets in important human pathogens . The structures provide templates for developing CYP51 inhibitors with improved efficacy and resistance properties that are structurally and synthetically simpler than posaconazole . By utilizing the differential geometries between host and pathogen CYP51 binding sites , it maybe possible to create new drugs with minimized toxicity and host-pathogen cross-reactivity . In addition , the posaconazole binding mode offers insights into the development of drug resistance in pathogenic fungi , implying that an analogous mechanism may be implicated in protozoan pathogens . The reported structures also provide a good template for drug design targeting Leishmania CYP51 . However , drug development must take into account the properties and accessibility of the compartment where these parasites reside . Unlike T . cruzi , Leishmania amastigotes replicate in the acidic environment ( pH ∼5 ) of the phagolysosomal vacuoles in macrophage cells [56] , [57] , imposing different requirements on the physicochemical properties of CYP51 inhibitors targeting leishmaniasis .
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Chagas Disease is caused by kinetoplastid protozoa Trypanosoma cruzi , whose sterols resemble those of fungi , in both composition and biosynthetic pathway . Azole inhibitors of sterol 14α-demethylase ( CYP51 ) , such as fluconazole , itraconazole , voriconazole , and posaconazole , successfully treat fungal infections in humans . Efforts have been made to translate anti-fungal azoles into a second-use application for Chagas Disease . Ravuconazole and posaconazole have been recently proposed as candidates for clinical trials with Chagas Disease patients . However , the widespread use of posaconazole for long-term treatment of chronic infections may be limited by hepatic and renal toxicity , a requirement for simultaneous intake of a fatty meal or nutritional supplement to enhance absorption , and cost . To aid our search for structurally and synthetically simple CYP51 inhibitors , we have determined the crystal structures of the CYP51 targets in T . cruzi and T . brucei , both bound to the anti-fungal drugs fluconazole or posaconazole . The structures provide a basis for a design of new drugs targeting Chagas Disease , and also make it possible to model the active site characteristics of the highly homologous Leishmania CYP51 . This work provides a foundation for rational synthesis of new therapeutic agents targeting the three kinetoplastid parasites .
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[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"and",
"Discussion"
] |
[
"biochemistry/structural",
"genomics",
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"biochemistry/biomacromolecule-ligand",
"interactions",
"biochemistry/drug",
"discovery"
] |
2010
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Structural Characterization of CYP51 from Trypanosoma cruzi and Trypanosoma brucei Bound to the Antifungal Drugs Posaconazole and Fluconazole
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Many bacteria inhibit motility concomitant with the synthesis of an extracellular polysaccharide matrix and the formation of biofilm aggregates . In Bacillus subtilis biofilms , motility is inhibited by EpsE , which acts as a clutch on the flagella rotor to inhibit motility , and which is encoded within the 15 gene eps operon required for EPS production . EpsE shows sequence similarity to the glycosyltransferase family of enzymes , and we demonstrate that the conserved active site motif is required for EPS biosynthesis . We also screen for residues specifically required for either clutch or enzymatic activity and demonstrate that the two functions are genetically separable . Finally , we show that , whereas EPS synthesis activity is dominant for biofilm formation , both functions of EpsE synergize to stabilize cell aggregates and relieve selective pressure to abolish motility by genetic mutation . Thus , the transition from motility to biofilm formation may be governed by a single bifunctional enzyme .
In the environment , bacteria alternatively exist as planktonic individual cells or in cell aggregates known as biofilms [1] , [2] . Planktonic cells can be either non-motile or motile by assembly and rotation of flagella . Cell motility often promotes initial biofilm formation but ultimately motility is inhibited during the transition to sessile cell aggregates [3]–[8] . Mature biofilms contain non-motile cells that are encapsulated in an extracellular matrix composed of polysaccharides , proteins , and DNA [9] . The mechanism of motility inhibition during biofilm formation is poorly understood and the underlying purpose for motility inhibition in biofilms is unknown . The Gram positive soil bacterium Bacillus subtilis is a model organism for biofilm formation . B . subtilis biofilms manifest either as floating pellicles or as colonies with complex architecture . Both types of biofilms are stabilized by an extracellular polysaccharide matrix ( EPS ) and the amyloid protein TasA [10]–[12] . Production of both matrix components is tightly repressed by the DNA binding transcription factor SinR and a complex series of upstream regulators [13]–[16] . Notably , the 15 gene eps operon is directly repressed by SinR and encodes putative glycosyltransferases , presumably for EPS biosynthesis , as well as EpsE , a protein that inhibits flagellar rotation [17] . Flagella structure and function is best understood in the Gram negative bacteria Escherichia coli and Salmonella enterica [18] , [19] . The flagellar basal body is anchored in the cell membrane and serves as a scaffold for the hook and the external , helical filament . Flagellar rotation occurs when an influx of protons through the MotA/MotB proton channel induces a conformational change in the motor protein MotA [20]–[22] . The conformation change in MotA is transduced into flagellar rotation by interaction with the ring of FliG rotor proteins that sits underneath the flagellar basal body [23]–[25] . EpsE is thought to directly interact with FliG to distort the MotA-FliG interaction and cut power to the flagellum like a molecular clutch [17] . The specific region of the EpsE protein that interacts with FliG is unknown . EpsE also shows sequence similarity to the Type 2 family of glycosyltransferases and encodes the highly conserved DXDD active site motif [26] , [27] . Here we demonstrate that EpsE has two genetically separable functions , acting both as an enzyme for EPS biosynthesis and acting as a clutch by protein-protein interaction . We further show that both functions of EpsE synergize to promote biofilm formation . Thus , an “ordinary” looking enzyme common to eps operons in diverse bacteria has an extraordinary additional function . Furthermore , the transition from motility to biofilm formation may be governed by a single protein .
In B . subtilis , SinR represses the eps and yqxM operons , which are responsible for synthesizing the extracellular polysaccharide ( EPS ) and protein components of the extracellular matrix , respectively [10]–[12] . Consequently , a sinR mutant forms a colony with a more complex architecture and a thicker , more robust pellicle compared to wild type ( Figure 1A and 1B ) . Mutation of either the EpsE or EpsH putative glycosyltransferases encoded within the eps operon disrupted complex colony architecture in the sinR background ( Figure 1C and 1D ) . In pellicle assays a sinR epsH double mutant formed shattered sunken aggregates , but a sinR epsE double mutant completely abolished biofilm formation and aggregates did not accumulate ( Figure 1C and 1D ) . We conclude that both glycosyltransferase homologs are required for biofilm formation , but that the absence of EpsE results in a more severe biofilm defect than the absence of EpsH . To confirm that the severe biofilm defect in the sinR epsE double mutant was a direct consequence of the loss of epsE , the epsE gene was complemented at an ectopic site in the chromosome . To generate the complementation construct , the epsE gene was cloned downstream of the promoter of the eps operon ( Peps ) and inserted into the ectopic amyE site ( amyE::Peps-epsE ) . Introduction of the Peps-epsE complementation construct rescued both complex colony architecture and pellicle formation to the sinR epsE double mutant ( Figure 1E ) . EpsE encodes a highly conserved DXDD glycosyltransferase enzymatic active site motif ( D94G95D96D97 ) . To determine the contribution of the EpsE putative enzymatic active site to biofilm formation , aspartate94 ( D94 ) was changed to an alanine residue ( D94A ) by site-directed mutagenesis of the epsE complementation construct ( amyE::Peps-epsED94A ) . A sinR epsE mutant complemented with epsED94A was severely reduced for both complex colony architecture and pellicle formation ( Figure 1F ) . We conclude that the putative active site of EpsE is required for biofilms . One way in which the EpsE putative enzymatic activity could contribute to biofilm formation is by the synthesis of the EPS matrix component . To determine whether EPS was being synthesized , EPS was first isolated and purified from cells wild type for EpsE . To improve EPS recovery , EPS synthesis was enhanced by mutation of SinR , and EPS was liberated from the cell surface by mutation of the EPS extracellular organizing protein TasA . When spent media was harvested from dense cultures of a sinR tasA double mutant and mixed with ethanol , a threadlike substance precipitated ( Figure 2A ) . When the precipitate was resolved by SDS-polyacrylamide gel electrophoresis ( PAGE ) and stained with Stains-All , a band that did not leave the stacking gel was present , consistent with a high molecular weight substance ( Figure 2A ) [28] . This precipitate was insensitive to treatment with Proteinase K , DNase , and RNase , indicating that the substance was not composed of protein , DNA , or RNA ( Figure 2B ) . Mutation of either EpsE or EpsH abolished the production of the threadlike precipitate and abolished the high molecular weight Stains-All-reactive material ( Figure 2A ) . The precipitate and Stains-All-reactive material was restored to the sinR tasA epsE triple mutant when complemented with wild type epsE , but not when complemented with the EpsE glycosyltransferase active site mutant allele epsED94A ( Figure 2A ) . The active site allele mutant protein was produced in amounts similar to wild type and thus the loss of precipitate was not due to a loss of EpsE protein ( Figure 3 ) . We infer that the precipitate and high molecular weight Stains-all-reactive material is the EPS that constitutes the biofilm matrix and that EpsE is required for its synthesis . Furthermore , the putative EpsE active site is essential for EPS synthesis and we infer that EpsE acts as a glycosyltransferase enzyme to promote biofilm formation . Here we show that EpsE likely acts as an enzyme to synthesize EPS , but EpsE has also been reported to interact with the flagellar rotor component FliG and act as a clutch to inhibit flagellar rotation [17] . The epsED94A active site mutant allele restored motility inhibition to a sinR epsE double mutant , even though it lacked EPS biosynthesis ( Figure 1D and 1F ) . We conclude that the EpsE putative enzymatic activity is unrelated to clutch function and we hypothesize that EpsE is bifunctional . To further demonstrate genetic separability of the two functions we randomly mutagenized EpsE and screened for loss-of-extracellular polysaccharide ( lox ) alleles that only abolished EPS production , and loss-of-clutch ( loc ) alleles that only abolished motility inhibition . To support genetic screens involving EpsE , a random pool of mutations ( epsEmut ) was generated by amplifying the epsE gene by low fidelity polymerase chain reaction ( PCR ) , cloned downstream of the native Peps promoter , and inserted into a plasmid between the arms of the amyE gene ( amyE::Peps-epsEmut ) . The plasmid library was then integrated into the B . subtilis amyE locus as a pool of mutants . Thus , the mutated copies of epsE were incorporated in a manner analogous to the epsE complementation construct , and epsE mutant alleles could be screened for either the ability or inability to complement an epsE deletion . The screen for loss of extracellular polysaccharide ( lox ) mutant alleles of epsE was conducted in two sequential stages . The first stage of the screen isolated epsE mutants defective in EPS production . The epsEmut mutant pool was introduced into a sinR epsE double mutant and colony morphology was analyzed . Colonies containing epsE alleles that had the ability to produce EPS had a rough colony phenotype and were excluded from further screening [29] , [10] . Colonies containing epsE mutants that did not have the ability to produce EPS had a smooth colony phenotype and were chosen for the second stage of the screen . Each smooth epsE colony was individually inoculated onto swarm agar plates to determine if the allele of EpsE was proficient for clutch function and motility inhibition . Motile strains , which lost clutch function , were excluded from further study to avoid EpsE null mutants . Thirty mutants that were inhibited for motility and had a smooth colony phenotype were isolated as lox alleles . Sequencing of the lox mutants revealed three classes of mutations within the epsE gene after discarding siblings ( Table S1 ) . Class 1 mutations were located within the conserved DXDD glycosyltransferase active site motif ( Figure 3 , Table S1 ) . Class 2 mutations were located outside of the conserved DXDD motif but were presumably important in either substrate recognition or substrate specificity ( Figure 3 , Table S1 ) . For example , one particular class 2 mutant changed the conserved asparate182 to a glycine ( EpsED182G ) , and the homologous aspartate was found to be important for nucleotide binding in ExoM of Sinorhizobium meliloti [27] . Another class 2 mutant altered histidine155 that was highly conserved among other glycosyltransferases [30] . The residues glycine12 and cysteine154 were not conserved in other glycosyltransferases , but the substitutions at these positions may either confer substrate specificity or interfere with the conserved residues adjacent to them ( Figure S1A ) . Consistent with a defect in glycosyltransferase function , no EPS was isolated from supernatants of cells containing either lox class 1 or class 2 mutations ( Figure 2A ) . Similar to the EpsED94A active site mutation , Class 1 and 2 mutants synthesized wild type amounts of EpsE protein ( Figure 3 ) . Class 3 mutations contained more than one substitution within the EpsE coding region . We note however , that each Class 3 mutation contained a substitution corresponding to a position already identified in either Class 1 or Class 2 alleles . We infer that only one of the substitutions in Class 3 mutants actually accounts for the loss of EPS phenotype . Mutants in all lox classes abolished EPS biosynthesis but retained clutch activity . The EpsE loss-of-clutch ( loc ) screen was conducted in three sequential stages to isolate alleles of epsE that were defective in motility inhibition , retained EPS biosynthetic capacity , and produced EpsE protein levels comparable to wild type . In the first stage , epsE mutants were isolated that were defective in motility inhibition . The pool of epsEmut alleles were introduced to a sinR mutant deleted for the entire eps operon , pooled , and inoculated in the center of a swarm agar plate . Deletion of the entire eps operon ensured that EPS biosynthesis could not be restored regardless of the epsE allele introduced . Alleles of epsE that were functional for the clutch inhibited motility , remained at the site of inoculation , and were excluded from further screening . In contrast , alleles of epsE that were defective for the clutch remained motile , spread from the site of inoculation , and were harvested . In the second stage , epsE alleles from the first stage were screened for those that retained EPS biosynthetic capacity by introduction to a sinR epsE double mutant and plating for discrete colony forming units . Alleles of epsE non-functional for EPS biosynthesis exhibited a smooth colony morphology and were excluded from further screening . In contrast , alleles of epsE that were functional for EPS biosynthesis restored rough colony architecture and were individually isolated . In this particular genetic background , motility was inhibited due to the dominance of EPS production and therefore the EPS proficient epsE alleles were backcrossed into a sinR epsE epsH triple mutant to ensure that motility inhibition was still abolished ( representative epsE allele Figure 1H and 1I ) . Ultimately , after two stages of screening we had retained a set of sixty epsE alleles that were deficient for motility inhibition but proficient for EPS synthesis . Sequencing of these mutants revealed a variety of mutations in the epsE gene as well as in the ribosome binding site ( RBS ) . Some alleles contained multiple mutations and were discarded from further analysis , while others contained the same mutation ( siblings ) and only one of each sibling was retained for further study . The remaining alleles were advanced to the third stage of the screen in which EpsE protein levels were assayed ( Figure S2 ) . To establish a “wild type” standard for EpsE protein comparison , whole cell lysates of cells mutated for sinR ( to increase eps operon expression ) and epsH ( to prevent cell aggregation ) , were resolved by SDS-PAGE , electroblotted , and probed with an anti-EpsE antibody . A high level of EpsE was produced in the sinR epsH double mutant and this established the baseline for EpsE comparison ( lane “Native” ) ( Figure 4A ) . Cells triply mutated for sinR , epsH , and epsE did not produce EpsE , but ectopic complementation restored EpsE levels comparable to wild type ( +WT ) ( Figure 4A ) . We conclude that ectopic complementation restored native levels of EpsE . To assay the amount of EpsE produced by the mutant alleles , we used the sinR epsH epsE triple mutant and complemented the strain with the various epsE mutants ( amyE::Peps-epsEmut ) . Many of the screened clutch-defective mutant alleles , including mutations in the epsE RBS , resulted in a reduced amount of EpsE relative to the wild type standard ( Figure 4A ) . Four alleles ( K106E , F110L , F110V , and K113E ) near the DXDD enzymatic active site sequence , and one allele in the C terminal region of EpsE ( Y197C ) , however , produced EpsE levels comparable to the wild type ( Figure 4A ) . Whereas many alleles abolished motility inhibition while retaining EPS synthesis , only these latter 5 alleles met the definition of the loss-of-clutch ( loc ) genotype as their phenotype was not due to a reduction in protein levels ( Figure 2 , Figure 4A ) . We hypothesize that the loc alleles represent residues likely required for interaction with FliG . Clutch function is correlated with a punctate localization of EpsE-GFP to the cell membrane that can be abolished by mutations of FliG that renders FliG clutch-insusceptible ( e . g . FliGV338A ) [17] ( Figure 4B , Figure S3 ) . To determine the cellular localization pattern of the loc alleles , translational fusions were constructed between each allele and GFP , and placed at an ectopic locus ( thrC:: Peps-epsEloc-GFP ) . In each case , the EpsEloc-GFP fusions displayed a diffuse membrane-associated pattern of localization reminiscent of the localization of EpsE-GFP in the FliG clutch-insusceptible background ( Figure 4B ) . Thus , punctate localization of EpsE is tightly correlated with clutch activity and either loc mutations in EpsE or clutch-insusceptible mutations in FliG mislocalize EpsE and render the cells motile . We conclude that the residues mutated in the loc alleles are required for interaction with FliG . EPS biosynthesis has been shown to be required for biofilm formation and the inhibition of motility has been speculated to stabilize cell aggregates [29] , [17] . To determine the relative contribution of the EPS synthesis and clutch activities of EpsE to biofilm formation , we constructed strains that were disrupted for one or the other function . All strains were mutated for sinR to alleviate repression on the eps operon , the native copy of epsE was deleted , and alleles of epsE were complemented at the amyE locus ( amyE::Peps-epsE ) . Whereas the EpsElox mutant ( D94A ) was specifically defective for EPS biosynthesis and formed a crippled pellicle that shattered and sank to the bottom of the tank , the EpsEloc mutant ( K106E ) formed a pellicle indistinguishable from a sinR mutant ( Figure 1F and 1H ) . We conclude that the contribution of EpsE to EPS biosynthesis is more significant than the contribution of clutch function for pellicle formation . We next attempted to determine the consequence of disrupting both EPS biosynthesis and clutch function simultaneously and in a manner that did not depend on the allele of EpsE . For example , a sinR epsH double mutant formed a shattered pellicle reminiscent of a sinR mutant containing an EpsElox allele ( Figure 1C and 1F or 1G ) . Also , a sinR mutant containing a fliGV338A clutch-insusceptible allele formed a robust pellicle reminiscent of a sinR mutant containing an EpsEloc allele ( Figure 1J and 1H ) . When a fliGV338A mutation and an epsH mutation were simultaneously introduced into a sinR mutant , only small flecks of biomass accumulated in the well and the phenotype was more severe than either mutation alone ( Figure 1K ) . A similar phenotype resulted when a sinR mutant was simultaneously mutated for fliGV338A and epsED94A ( Figure S4B ) . Thus , different methods of simultaneously disrupting EPS biosynthesis and clutch function produced a severe defect in pellicle formation reminiscent of a sinR mutant that lacks both functions due to a complete deletion of the epsE gene ( Figure 1D ) . We conclude that both functions of EpsE synergize to promote pellicle formation . Upon prolonged incubation , the sinR epsH fliGV338A mutant developed saf suppressors ( suppressors of aggregate formation ) that restored biomass reminiscent of a sinR epsH mutant ( Figure 5A ) . One way in which large aggregates could be restored was if the suppressor mutations had somehow abolished flagellar motility . To determine whether the suppressors were motile , we grew pellicles of a sinR epsH and a sinR epsH fliGV338A mutant , harvested the pellicles from both strains at day 4 , dilution plated , and inoculated individual colonies onto swarm agar ( Figure 5A ) . The sinR epsH population was initially non-motile , but we found that a small percentage of isolated colonies had gained motility upon prolonged incubation in the pellicle assay , likely through loss of EpsE or EpsE activators [17] , [16] ( Figure 5B ) . Whereas the sinR epsH fliGV338A triple mutant population was initially motile , a large percentage of isolated colonies had lost motility concomitant with aggregate formation ( Figure 5B ) . We infer that there is strong selective pressure to form aggregates and that loss of motility is necessary for aggregate formation . One way in which motility could be abolished in the absence of the flagellar clutch was by mutation of a gene required for flagellar assembly . To determine whether the saf suppressors of the sinR epsH fliGV338A triple mutant were defective for flagella , we introduced a modified version of the flagella filament that can be fluorescently labeled ( amyE::Phag-hagT209C ) [17] . Whereas the sinR epsH fliGV338A parent strain was motile , the saf mutants had a severely decreased number of flagella that were not sufficient for motility ( Figure 5C ) . In comparison , the clutch proficient sinR epsH strain did not lose the ability to assemble flagella after prolonged incubation ( Figure 5C ) . We infer that the non-motile saf suppressors of sinR epsH fliGV338A triple mutant have a mutation in an essential gene for flagellar synthesis and/or function , and that the severe decrease in the number of functional flagella restored aggregate formation . Thus , motility is detrimental to aggregate and pellicle formation , and the clutch relieves genetic selective pressure for motility loss that could otherwise result in mutation of any of the 40 genes required for flagella biosynthesis .
In many bacteria , the motility-to-biofilm transition is thought to be complex [2] . Here we demonstrate in B . subtilis that the motility-to-biofilm transition may be potentially reduced not only to the regulation of a single eps operon , but to a single protein within the operon , EpsE , that is bifunctional . EpsE is a glycosyltransferase that participates as an enzyme to synthesize the biofilm EPS . Furthermore , EpsE acts as a flagellar clutch to inhibit motility through interaction with the flagellar rotor . The two functions of EpsE are genetically separable , and through separate and distinct mechanisms , EpsE promotes matrix synthesis and inhibits motility to synergistically stabilize the biofilm . The two functions of EpsE are mechanistically separable as indicated by the phenotype of mutations in the EpsE ribosome binding site ( RBS ) ( Figure 4A ) . The RBS mutants reduced the level of EpsE protein below the limit of detection , but nonetheless retained the ability to produce EPS and form colonies with complex architecture ( Figure 2C , Figure 4A ) . We infer the mechanism of EPS biosynthesis is independent of protein levels and therefore EpsE acts sub-stoichiometrically like an enzyme . The RBS mutants and other mutations that reduced EpsE protein levels , however , resulted in a loss of motility inhibition . We infer that the mechanism of clutch function is dependent on protein levels and therefore EpsE acts stoichiometrically , via a protein-protein interaction . EpsE is thought to interact directly with FliG , and for each basal body , approximately 26 FliG subunits polymerize into a wheel-like rotor [31]–[33] . The number of EpsE molecules that must interact with the rotor to inhibit rotation of a flagellum is finite but unknown . The two mechanisms of EpsE may also be distinguished by subcellular localization patterns . EpsE localized both as membrane associated-puncta as well as a diffuse membrane-associated haze ( Figure 6A–6C ) . Punctate localization is associated with clutch activity as clutch-insusceptible mutations in FliG or loss-of-clutch alleles in EpsE abolished puncta formation . While it is unknown whether EpsE in puncta participate in enzymatic reactions , punctate localization was not required for EPS biosynthesis . EPS biosynthesis occurs at the cytoplasmic membrane and we hypothesize that the diffuse membrane localization may represent interactions with other EPS enzymes or substrates [34] . The two mechanisms of EpsE may be further distinguished by mapping the location of the residues required for each activity in the tertiary structure . EpsE is an insoluble protein and has proven difficult to purify for structural analysis . Instead , we generated a predicted three dimensional structure of EpsE by threading the primary sequence through known glycosyltransferase structures , and the lox and loc residues were mapped onto the model ( Figure 6D–6E ) . In partial validation of the predicted structure , the DXDD motif and lox residues were located in a pocket consistent with the active site found in other glycosyltransferases ( Figure 6D ) [26] , [35] . Three of the four loc residues , however , localized to the same face of a predicted alpha helix within a groove on the exterior of the protein ( Figure 6E ) . While the fourth loc residue was not contained within the homology model , we hypothesize that the remaining residues constitute the site of contact with FliG . EpsE is part of a growing list of enzymes that regulate other functions in the cell by direct protein-protein interaction . For example , GlnA acts enzymatically as glutamine synthetase in B . subtilis , and also controls transcriptional regulators of nitrogen metabolism by direct protein-protein interaction [36] , [37] . Glycosyltransferases are becoming increasingly identified as having additional regulatory functions . In B . subtilis , UgtP acts as a glucosyltransferase for glucolipid synthesis and also inhibits polymerization of the cell division protein FtsZ by protein interaction [38] , [39] . In Listeria monocytogenes , GmaR enzymatically glycosylates the flagellum and directly interacts with the transcription factor MogR to derepress flagellar gene expression [40]–[42] . We note that many bacteria encode EPS operons that are rich in glycosyltransferase homologs , and that pleiotropic effects often observed in biofilm regulatory mutants may be due to as-yet-unidentified bifunctional enzymes . Bifunctional enzymes are important proteins that couple metabolism to related physiological functions . Here we show that EpsE couples EPS biosynthesis and functional control of the flagellum during biofilm formation . Functional control of the flagellum has been implicated in the biofilm formation of bacteria besides B . subtilis . In Escherichia coli , the protein YcgR is a c-di-GMP dependent inhibitor of swimming speed and chemotaxis [43]–[45] . Like EpsE , YcgR may be involved in the biofilm transition because c-di-GMP is a ubiquitous transition regulator that inhibits motility and promotes biofilm formation [46] , [7] . In Pseudomonas aeruginosa , SadC is a putative c-di-GMP synthase and positive regulator of biofilm formation by promoting EPS production . Mutation of SadC results in an increase in flagellar rotation reversal frequency that has been associated with surface attachment [47] , [48] . Thus , inhibition of flagellar function may play an important role in the transition from motility to biofilm formation , as the pre-existent flagella are regulated faster than can be accomplished by transcriptional control . Here we show that functional inhibition of the flagellum is critical for aggregate formation of cells crippled for EPS biosynthesis . The clutch may be most relevant in the natural environment , during early biofilm formation , or when biofilm formation is otherwise impaired . We demonstrate the synergy of the clutch and EPS enzymatic activity in a sinR mutant that produces a uniform population of cells that express flagellar genes [49] . In the wild type , however , mutation of the clutch function , either by deletion of epsE or introduction of a clutch insusceptible allele of FliG , does not show the severe synergistic effect on the biofilm ( Figure S4A ) . Wild type planktonic populations are mixtures of cells that are on and off for flagellar gene expression and we infer that in the wild type , a population of non-motile cells is pre-existent and therefore does not need to make the motility-to-biofilm transition [50] . We further infer that the clutch is still relevant and important for the motile subpopulation to be included in the aggregates . In support of this assumption , we find that there is strong genetic selective pressure to abolish motility concomitant with aggregate formation ( Figure 5 ) . Thus , the clutch may not only inhibit motility to form the biofilm but may also relieve selective pressure on mutation of any of approximately 40 genes required for flagellar synthesis . EpsE is the first clutch protein discovered for the bacterial flagellum and other flagellar clutches may be difficult to identify [17] . For example , the EpsE protein does not contain a conserved domain commonly associated with protein-protein interactions nor would one predict from the primary sequence that the EpsE protein was related to the flagellum . Rather , much of the protein sequence is conserved among other glycosyltransferases , including some of the residues we identify as required for clutch function ( Figure S1A ) . Interestingly , three of the four residues that render FliG susceptible to the clutch are conserved in most other bacteria but not in B . subtilis [17] ( Figure S1B ) . We infer that , at least in the case of B . subtilis , the FliG protein may have evolved to accommodate inhibition by a protein present during biofilm formation ( i . e . EpsE ) . Perhaps the FliG in each bacterium evolved separately to modify different sites such that each clutch protein is uniquely suited to disable the rotor under specific conditions . Taken together , we conclude that it will be difficult to find functional inhibitors of the flagellum using bioformatic analyses alone and that clutch proteins may be best discovered by classical genetic approaches .
B . subtilis strains were grown in Luria-Bertani ( LB ) ( 10 g tryptone , 5 g yeast extract , 5 g NaCl per L ) broth or on LB plates fortified with 1 . 5% Bacto agar at 37°C . When appropriate , antibiotics were included at the following concentrations: 10 µg/ml tetracycline , 100 µg/ml spectinomycin , 5 µg/ml chloramphenicol , 5 µg/ml kanamycin , and 1 µg/ml erythromycin plus 25 µg/ml lincomycin ( mls ) . For pellicle formation experiments , 10 µl of culture grown overnight at room temperature in LB medium was inoculated into 10 ml minimal MSgg medium ( 5 mM potassium phosphate ( pH 7 ) , 100 mM MOPS ( pH 7 ) , 2 mM MgCl2 , 700 µM CaCl2 , 50 µM MnCl2 , 50 µM FeCl3 , 1 µM ZnCl2 , 2 µM thiamine , 0 . 5% glycerol , 0 . 5% glutamate , 50 µg/ml tryptophan , 50 µg/ml phenylalanine , and 50 µg/ml threonine ) in 6-well microtiter plates and incubated at 25°C for 2 days [29] . For colony architecture analysis , colonies were toothpick inoculated onto minimal MSgg medium fortified with 1 . 5% Bacto agar and incubated for 3 days at 25°C . For the motility assay , swarm agar plates containing 25 ml LB fortified with 0 . 7% Bacto agar were prepared fresh and the following day were dried for 20 minutes in a laminar flow hood . Each plate was toothpick inoculated from an overnight colony and scored for motility after 18 hours incubation at 37°C [51] . Plates were visualized with a BioRad Geldoc system and digitally captured using BioRad Quantity One software . Cells were grown for 24 hours in TY Broth ( LB broth supplemented after autoclaving with 10 mM MgSO4 and 100 µM MnSO4 ) , pelleted , and the supernatant was put on ice . The chilled supernatant was mixed with ice cold 75% ethanol . For imaging in 12-well microtiter plates , the precipitate was mixed with glycerol to a final concentration of 17% and images were taken with a Canon Powershot A620 digital camera . For staining samples using Stains-All , the precipitate was spun down at 14 , 000 RPM for 3 minutes . The supernatant was discarded and the residual ethanol was allowed to evaporate . Each sample was mixed with 100µl of 1× SDS Sample Buffer and 10 µl was loaded onto a SDS-12% polyacrylamide gel . Samples were run for 30 minutes at 200 V . The stacking and resolving gel was fixed for 24 hours ( 25% isopropanol , 3% acetic acid ) and stained overnight with 100 ml of Stains-All Reactive Solution ( 5 ml of 1 mg/ml Stains-All [Sigma] in formamide , 50 µl 2-mercaptoethanol , and 95 ml Stains All Base Solution [16 . 6% isopropanol , 5 . 5% formamide , and 0 . 5% 3 . 0M Tris-HCl ( pH 8 . 8 ) ] ) [52] . The stacking gel was scanned using an HP Scanjet 4370 . For treatment with Proteinase K , 300 µl of supernatant was mixed with a final concentration of 400 µg/ml of Proteinase K ( Fisher ) for 1 hr at 55°C . For treatment with DNase and RNase , 300 µl of supernatant was mixed with a final concentration of 67 µg/ml DNase I ( Roche ) and 330 µg/ml Ribonuclease A ( Sigma ) for 30 minutes at 37°C . Both treated supernatants were then treated as described above to precipitate EPS . To generate a pool of epsE mutants , primer pair 1386/1260 was used to amplify the epsE reading frame using 3610 chromosomal DNA as a template and Expand polymerase with Expand Buffer 1 ( Roche ) . This fragment was digested with NheI and BamHI and ligated into the NheI and BamHI sites of pDP232 containing the Peps promoter region and a chloramphenical resistance cassette between the two arms of the amyE gene . Multiple ligations were transformed into E . coli and all of the resulting colonies were pooled to generate a plasmid library of epsEmut complementation constructs ( pSG4 ) . The plasmid library was transformed into naturally competent B . subtilis PY79 and phage lysates were generated . The phage lysates were used to transduce strains of B . subtilis for screening of enzymatic and clutch mutants of epsE . The epsEmut pool of lysates were transduced into a sinR epsE mutant ( DS2174 ) . The resulting smooth colonies were inoculated onto 0 . 7% LB agar plates and incubated at 37°C . Smooth colonies that were also inhibited for motility were isolated . The epsEmutpool of lysates were transduced into a sinR eps mutant ( DS1722 ) . All of the resulting colonies were pooled , spotted onto the center of 0 . 7% LB agar plates , and incubated at 37°C for approximately 6 hours . Motile cells were pooled from the edge of the swarm radius and phage lysates were generated . These phage lysates were transduced into a sinR epsE double mutant ( DS2174 ) . The rough colonies were isolated and a phage lysate was generated from each colony . These lysates were transduced into a sinR ΔepsE epsH::tet mutant ( DS2946 ) to verify that each mutant epsEmut allele abolished clutch function . The epsE mutants were sequenced by amplifying DNA from the appropriate strain using primer pair 953/345 . The PCR product generated was sequenced using primers 732 and 733 individually . 1 µg of purified EpsE protein was submitted to Cocalico Biologicals for serial injection into a rabbit host for antibody generation . Anti-EpsE serum was mixed with EpsE-conjugated Affigel-10 beads and incubated overnight at 4°C . Beads were packed onto a 1 cm column ( Bio-Rad ) and then washed with 100 mM glycine ( pH 2 . 5 ) to release the antibody and immediately neutralized with 2M unbuffered Tris . Affinity purification of the antibody was verified by SDS-PAGE . Purified antibody was dialyzed into 1× PBS , 50% glycerol and stored at -80°C . B . subtilis strains were grown in LB to OD600 ∼0 . 8 , 10 ml were harvested by centrifugation , resuspended to 10 OD600 in Lysis buffer ( 20 mM Tris pH 7 . 0 , 10 mM EDTA , 1 mg/ml lysozyme , 10 µg/ml DNAse I , 100 µg/ml RNAse I , 1 mM PMSF ) , and incubated for 30 minutes at 37°C . 10 µl of lysate was mixed with 2 µl 6× SDS loading dye . Samples were separated by 12% Sodium dodecyl sulfate-polyacrylamide gel electrophoresis ( SDS-PAGE ) . The proteins were electroblotted onto nitrocellulose and developed with a 1∶10 , 000 dilution of primary antibody for anti-EpsE and a 1∶10 , 000 dilution of secondary antibody ( horseradish peroxidase-conjugated goat anti-rabbit immunoglobulin G ) . Immunoblot was developed using the Immun-Star HRP developer kit ( Bio-Rad ) . For blots probed with anti-SigA antibody , the samples used for the anti-EpsE western blot were diluted 1∶100 and a 1∶20 , 000 dilution of anti-SigA was used . Anti-SigA was a gift from Masaya Fujita ( University of Houston ) . Fluorescence microscopy was performed with a Nikon 80i microscope with a phase contrast objective Nikon Plan Apo 100× and an Excite 120 metal halide lamp . FM4-64 was visualized with a C-FL HYQ Texas Red Filter Cube ( excitation filter 532–587 nm , barrier filter >590 nm ) . GFP and Alexa Fluor 488 C5 maleimide fluorescent signals were visualized using a C-FL HYQ FITC Filter Cube ( FITC , excitation filter 460–500 nm , barrier filter 515–550 nm ) . Images were captured with a Photometrics Coolsnap HQ2 camera in black and white , false colored , and superimposed using Metamorph image software . For GFP microscopy , cells were grown overnight at 22°C in LB broth and 0 . 5 ml was pelleted and resuspended in 0 . 1 ml PBS . Membranes were stained by resuspension in 50 µl of PBS containing 5 µg/ml FM4-64 and incubated for 10 min at room temperature . Samples were observed by spotting 3 µl of the suspension on a glass microscope slide and were immobilized with a poly-L-lysine-treated glass coverslip . For fluorescent microscopy of flagella , 0 . 5 ml of broth culture was harvested at 0 . 5–2 . 0 OD600 , and washed once in 1 . 0 ml of T-Base Buffer ( 15 mM ( NH4 ) 2SO4 , 80 mM K2HPO4 , 44 mM KH2PO4 , 3 . 4 mM sodium citrate , and 3 . 0 mM MgSO4·6H20 ) . The suspension was pelleted , resuspended in 50 µl of T-Base buffer containing 5µg/ml Alexa Fluor 488 C5 maleimide ( Molecular Probes ) , and incubated for 5 min at room temperature [17] . Cells were then washed twice with 500 µl T-Base buffer . Membranes were stained by resuspension in 50 µl of T-Base buffer containing 5 µg/ml FM4-64 ( Molecular Probes ) and incubated for 5 min at room temperature . Three microliters of suspension were placed on a microscope slide and immobilized with a poly-L-lysine-treated coverslip . Three replicates of strains DS1674 and DS4532 were inoculated into MSgg , grown at 25°C , and images were taken every 24 hours for 4 days . The pellicles were harvested and dilution plated for discrete colony forming units . Three hundred colonies of each replicate were inoculated onto 0 . 7% swarm agar and incubated at 37°C . After 5 hours , the number of colonies that were non-motile were counted . The amino acid sequence of EpsE from B . subtilis strain 3610 was submitted to 3D-JIGSAW ( version 2 . 0 ) [53]–[55] . All constructs were first introduced into the domesticated strain PY79 by natural competence and then transferred to the 3610 background using SPP1-mediated generalized phage transduction [56] . All strains used in this study are listed in Table S2 . All plasmids used in this study are listed in Table S3 . All primers used in this study are listed in Table S4 .
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Bacteria form persistent and antibiotic-resistant cell aggregates known as biofilms . Biofilms can form in environmental settings on plant and animal tissues , in industrial settings on pipes and the hulls of ships , and in clinical settings on catheters and medical devices . Biofilms are characterized by two features: the cells within the aggregates are non-motile , and they produce an extracellular polysaccharide ( EPS ) matrix . We have found a bifunctional enzyme EpsE that contributes to both features of biofilm formation in Bacillus subtilis . EpsE interacts with the flagella rotor to inhibit motility and also cooperates with other enzymes to synthesize the EPS matrix . Thus , the transition from motility to biofilm formation may be governed by a single bifunctional protein . In the past decade , research on biofilms has been focused on biofilm eradication . Understanding how cells transition into the biofilm state may provide additional approaches of preventing the formation of a biofilm in the first place .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"microbiology/environmental",
"microbiology",
"microbiology/microbial",
"growth",
"and",
"development"
] |
2010
|
The EpsE Flagellar Clutch Is Bifunctional and Synergizes with EPS Biosynthesis to Promote Bacillus subtilis Biofilm Formation
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Innate immune responses are essential for controlling poxvirus infection . The threat of a bioterrorist attack using Variola major , the smallpox virus , or zoonotic transmission of other poxviruses has renewed interest in understanding interactions between these viruses and their hosts . We recently determined that TLR3 regulates a detrimental innate immune response that enhances replication , morbidity , and mortality in mice in response to vaccinia virus , a model pathogen for studies of poxviruses . To further investigate Toll-like receptor signaling in vaccinia infection , we first focused on TRIF , the only known adapter protein for TLR3 . Unexpectedly , bioluminescence imaging showed that mice lacking TRIF are more susceptible to vaccinia infection than wild-type mice . We then focused on TLR4 , the other Toll-like receptor that signals through TRIF . Following respiratory infection with vaccinia , mice lacking TLR4 signaling had greater viral replication , hypothermia , and mortality than control animals . The mechanism of TLR4-mediated protection was not due to increased release of proinflammatory cytokines or changes in total numbers of immune cells recruited to the lung . Challenge of primary bone marrow macrophages isolated from TLR4 mutant and control mice suggested that TLR4 recognizes a viral ligand rather than an endogenous ligand . These data establish that TLR4 mediates a protective innate immune response against vaccinia virus , which informs development of new vaccines and therapeutic agents targeted against poxviruses .
In 1980 , the World Health Organization declared that smallpox had been eliminated as a human disease [1] . Nevertheless , potential bioterrorist release of Variola major , the causative agent for smallpox , and human infection with monkeypox or other zoonotic orthopoxviruses has heightened interest in this family of viruses [2] . Variola major is particularly feared as a bioterrorism agent because of the high rate of transmission and up to 30% mortality caused by smallpox [3] . Fatal cases of smallpox were characterized by clinical findings similar to septic shock , likely mediated by the host inflammatory response to infection . However , molecules and signaling pathways that initiate and control protective and detrimental immune responses to Variola major remain poorly defined . Identifying molecular determinants of the innate immune response to poxviruses is critical to understanding pathogenesis of poxvirus infections and developing better therapies to prevent or ameliorate the sepsis-like disease manifestations . This knowledge also may lead to development of a safer smallpox vaccine that eliminates the high risk of severe , life-threatening complications associated with the current live , attenuated vaccinia virus vaccine . Improved understanding of the innate immune response to poxviruses will have benefits beyond advancing new vaccines and therapies to prevent and treat infection . Vaccinia virus is being investigated as a gene delivery , oncolytic , or immunizing vector for a wide variety of diseases , including cancer , HIV and malaria [4]–[8] . Greater knowledge of normal host-pathogen interactions will enable more efficient targeting and efficacy of these vectors in patients . Finally , insights gained from studying pulmonary infection with poxviruses are expected to inform research on protective and harmful aspects of host immunity to other respiratory pathogens . Toll-like receptors ( TLRs ) have emerged as key molecules in initiating innate immune responses to a variety of different pathogens , and these receptors also regulate subsequent adaptive immune responses to infection . TLRs recognize defined molecular patterns associated with various pathogens , including bacteria , fungi , and viruses . In vitro studies have identified canonical ligands for different TLR family members , such as double-stranded RNA for TLR3 and bacterial lipopolysaccharide ( LPS ) for TLR4 . However , recent studies suggest that TLRs may respond to a broader range of molecular patterns . For example , while TLR4-dependent recognition of LPS is well-established as a central regulator of effective host immunity to bacterial pathogens , TLR4 also may signal in response to a wide variety of endogenous ligands , such as heat shock proteins [9] , [10] . TLR4 also may respond to some viral proteins , and TLR4-dependent signaling may be necessary to limit viral replication and disease morbidity in vivo [11] , [12] . These studies emphasize that functions of TLRs in host immunity may extend to pathogens that do not carry known ligands for specific receptors , particularly as TLRs respond to infections in living animals . We recently established that TLR3 controls a detrimental innate immune response to pulmonary infection with vaccinia virus , a model virus for studies of orthopoxviruses [13] . Compared with wild-type mice , mice lacking TLR3 ( TLR3−/− ) had reduced viral replication and were protected against disease morbidity and mortality . Adverse effects of TLR3 signaling were caused in part by an excessive inflammatory response to infection . To further investigate TLR3 in poxvirus infection , we initially focused on functions of TIR domain-containing adapter inducing interferon-β ( TRIF ) , the only known downstream adapter molecule for TLR3 . Unexpectedly , mice lacking TRIF ( TRIF−/− ) did not reproduce protective effects of deleting TLR3 , but TRIF−/− was more susceptible to vaccinia infection . These data prompted us to analyze functions of TLR4 , the only other TLR known to signal through TRIF , in response to respiratory infection with vaccinia virus . We determined that TLR4 signaling protects mice against vaccinia infection , limiting viral replication and local inflammation .
We recently reported that TLR3−/− mice are protected from pulmonary vaccinia infection compared to wild type C57BL/6 controls [13] . The only known adaptor molecule for TLR3 is TRIF , so TLR3 is thought to signal exclusively through TRIF to control secretion of type I interferons and pro-inflammatory cytokines [14] . Because of this direct TLR3 to TRIF signaling pathway , we hypothesized that TRIF−/− mice would be protected against vaccinia infection , similar to TLR3−/− mice . We infected TRIF−/− and wild-type C57BL/6 mice with 1×104 pfu Vac-GFL intransally ( i . n . ) to reproduce the natural respiratory route of infection with Variola major . Vac-GFL is a recombinant vaccinia virus that expresses a reporter protein comprised of GFP fused to firefly luciferase [13] , which allows viral replication and dissemination to be quantified in living mice using bioluminescence imaging . We previously established that in vivo measurements of bioluminescence from Vac-GFL correlate directly with viral titers in a defined organ or tissue [15] . Bioluminescence imaging was performed daily to monitor replication of vaccinia virus , and weight loss was used as marker for systemic severity of disease . Unexpectedly , susceptibility of TRIF−/− mice to vaccinia infection was distinct from that of the TLR3−/− mice . TRIF−/− mice had less weight loss than wild-type mice on days 1–4 post-infection ( p<0 . 05 ) , which is similar to our published results for TLR3−/− versus wild-type mice , ( Figure 1A ) . However , TRIF−/− mice differed from TLR3−/− animals in that replication of Vac-GFL was greater in mice lacking TRIF , as quantified by region of interest analysis of head , chest , and abdomen sites on bioluminescence images . By area under the curve ( AUC ) analysis , TRIF−/− mice had significantly greater luminescence in their chests ( from lung infection ) than wild-type mice ( Figure 1B; p<0 . 01 ) . These data indicate that a different and/or additional host molecule ( s ) controls responses to vaccinia in TRIF−/− mice relative to those mediated solely by TLR3 . This experiment continued until day 7 post-infection , when the animals were euthanized to obtain plasma and bronchoalveolar ( BAL ) fluid for quantification of cytokines . Levels of IL-6 , IL-4 , IFN-γ , MCP-1 , TNF-α , and TGF-β were measured in these samples , but no significant differences were seen between the TRIF−/− and WT mice ( data not shown ) . We hypothesized that TLR4 , the only other Toll-like receptor known to signal through TRIF , may control differing host responses to vaccinia in TLR3−/− versus TRIF−/− mice . TLR4 is reported to limit replication of a limited number of viruses [11] , [16] , although functions of this receptor in vaccinia infection have not been established . To investigate TLR4 in host defense against vaccinia virus , we used C3H/HeJ mice , which have a point mutation in the cytoplasmic region of TLR4 that renders them unresponsive to LPS [17] . As controls , we used C3HeB/FeJ mice , which have normal , functional TLR4 . C3HeB/FeJ mice are genetically similar to C3H/HeJ mice and are well-established as a control strain for experiments using C3H/HeJ animals [18]–[20] . We infected C3H/HeJ and C3HeB/FeJ mice with 1×104 pfu Vac-GFL . Systemic effects of disease were monitored by weight loss and rectal temperature , while viral replication and spread were assessed with bioluminescence imaging . While both strains of mice lost body temperature in response to vaccinia infection [21] , temperatures decreased to a greater extent over the course of the infection in C3H/HeJ ( TLR4 mutant ) mice relative to C3HeB/FeJ ( Figure 2A ) . C3H/HeJ mice had a slightly lower temperature than the controls prior to infection , but there were no differences between strains on days 1 , 2 , and 3 post-infection . Beginning on day 4 , however , rectal temperatures were significantly lower in C3H/HeJ mice , reaching a mean temperature of 33°C on day 6 post-infection ( p<0 . 05 ) . In contrast , the lowest mean temperature recorded in C3HeB/FeJ mice was 34 . 7°C on day 7 . C3H/HeJ mice had significantly lower temperatures than control C3HeB/FeJ mice on days 4–7 ( p<0 . 05 ) . As a second marker of disease severity , weight loss was monitored over the course of the disease ( Figure 2B ) . Surprisingly , the TLR4 mutant mice lost slightly less weight than the controls with significant differences on days 1–3 and 7–8 post-infection ( p<0 . 05 ) . Although the pattern of the weight loss difference is opposite that of the body temperature , it is consistent with the reduced weight loss observed in TLR3−/− and TRIF−/− mice compared with wild-type controls . Bioluminescence imaging showed that C3H/HeJ ( TLR4 mutant ) mice had significantly greater viral replication in the chest region on days 1 , 4 , and 5 post-infection ( p<0 . 05; Figure 2C ) . Light measured in the chest region of interest predominantly represents viral replication in the lung . C3H/HeJ mice also had significantly more Vac-GFL bioluminescence in the chest over the full course of the experiment as determined by AUC analysis . AUC values for bioluminescence were 1 . 61×108 vs . 3 . 18×107 for C3H/HeJ and C3HeB/FeJ mice , respectively ( p<0 . 01 ) . C3H/HeJ mice also had increased abdominal luminescence compared to control animals on day 4 ( p<0 . 05 ) and over the course of the experiment by AUC analysis ( Figure 2D ) . AUC values for photons produced in abdominal regions were 1 . 68×107 and 5 . 21×106 for C3H/HeJ and control C3HeB/FeJ mice , respectively ( p<0 . 05 ) . Bioluminescence in the head region did not differ between groups , and all mice recovered from infection ( data not shown ) . Collectively , these data suggest that TLR4 limits respiratory infection and systemic spread of vaccinia virus . To establish effects of TLR4 on survival , we infected C3H/HeJ and control C3HeB/FeJ mice with 5×105 pfu Vac-GFL , a dose 1 . 5 logs higher than used previously . Using this inoculum , TLR4 mutant mice were clearly more susceptible to vaccinia infection . By day 10 post-infection , 70% of C3H/HeJ mice had died , while all control mice recovered from infection ( Figure 3A ) . As in the previous experiment , loss of body temperature was measured as a sign of morbidity . C3H/HeJ mice were significantly more hypothermic than control C3HeB/FeJ mice on days 2 and 5–9 post-infection ( p<0 . 05; Figure 3B ) . The rapid recovery of mean temperature in C3H/HeJ mice between days 9 and 10 is caused by death of the most hypothermic mice , while the surviving animals recovered temperature comparable to control C3HeB/FeJ mice . These data were consistent over 5 independent experiments . Weight loss also was monitored over the course of the disease . C3H/HeJ mice exhibited less weight loss than control C3HeB/FeJ animals over the first 7 d post-infection , and these differences were significant on days 2–4 and 6 ( p<0 . 05; Figure 3C ) . The same trend was observed in two subsequent experiments . However , C3H/HeJ mice recovered weight more quickly than control C3HeB/FeJ animals on days 8–13 , with significant differences observed on days 12 and 13 ( p<0 . 05 ) . Both body temperature and weight loss are reported to be regulated by cytokines , including IL-1 , IL-6 , and TNF-α , as part of the “sickness response” [22] . The discrepancy between these parameters during vaccinia infection suggests underlying differences in mechanisms and pathways that regulate these two global measures of disease . These data highlight limitations of using weight loss alone as a measure of disease severity in vaccinia infection . With an inoculum of 5×105 pfu Vac-GFL , differences in viral replication between genotypes were even more pronounced than in the earlier experiment . Bioluminescence from Vac-GFL was greater in the head region of C3H/HeJ mice compared with controls . Differences between strains were statistically significant over the latter part of infection on days 5 and 7–10 ( p<0 . 05; Figure 4A ) . Over the course of the experiment , there was a trend for higher head bioluminescence in C3H/HeJ mice as determined by AUC analysis , although this difference was not statistically significant . Similarly , bioluminescence in the chests of TLR4 mutant mice was significantly increased over the controls ( p<0 . 05 ) on days 3–7 and 10 post-infection ( Figure 4B , C ) . At the peak of infection on day 6 , the chest luminescence of the TLR4 mutant mice was 8-fold higher than that of the control mice . Moreover , the AUC for bioluminescence in C3H/HeJ TLR4 mutant mice was significantly greater than that for controls ( 7 . 22×108 vs . 8 . 20×107 , respectively; p<0 . 05 ) . Increased viral replication in lungs of C3H/HeJ was also confirmed by plaque assay ( Figure 5 ) . Finally , C3H/HeJ mice had greater systemic spread of the virus to the abdomen ( Figure 6A and 6B ) . At the peak on day 5 , the TLR4 mutant mice had 4 . 7-fold higher luminescence in the abdomen than wild-type controls . Differences between the two genotypes were significant on days 3–8 post-infection . The AUC of the abdominal luminescence in the C3H/HeJ mice was 4 . 39×107 compared with 9 . 39×106 in the control C3HeB/FeJ mice , respectively ( p<0 . 05 ) . These data extend our initial observations of increased viral replication and dissemination in mice lacking functional TLR4 . Taken together , loss of functional TLR4 renders C3H mice more susceptible to pulmonary vaccinia infection , as measured by multiple parameters . Therefore , TLR4 must recognize some exogenous or endogenous ligand present in vaccinia infection . To exclude the possibility of our results being affected by endotoxin contamination of our viral preparation , we infected RAW cells with Vac-GFL in the presence or absence of 10 µg/mL polymyxin B [23] . Levels of IL-6 , TNF-α , and MCP-1 in the cell culture supernatants were assayed by ELISA . Adding polymyxin B did not affect levels of IL-6 , MCP-1 , or TNF-α in the supernatants of infected cells ( data not shown ) , establishing that contaminating endotoxin did not affect our in vivo studies . Type I interferons are essential to effective host defense against vaccinia infection [24] . TLR4 signaling results in production of Type I interferons through activation of transcription factors interferon regulatory factor 3 ( IRF3 ) and NF-κB . To determine to what extent TLR4 regulates secretion of type I interferons during vaccinia infection , we measured concentrations of interferon-β ( IFN-β ) in lung tissue of C3H/HeJ and control mice . Mice were infected i . n . with 5×105 pfu Vac-GFL , and lungs were harvested on days 3 and 5 post-infection . The day 3 time point is early in the course of infection , at the beginning , or just before , differences in luminescence and body temperature appear . Day 5 is near the peak of the infection where differences between TLR4 mutant and control mice are most pronounced . Lungs were homogenized and concentrations of IFN-β in supernatants were measured by ELISA . Levels of IFN-β were below the limit of reliable detection on day 3 in both groups of mice . On day 5 post-infection , IFN-β levels in 8 of 9 control mice remained below the limit of detection . On the other hand , six of 9 C3H/HeJ mice had IFN-β above the limit of reliable detection on day 5 ( Figure 7 ) . Therefore , C3H/HeJ mice are capable of producing IFN-β despite the lack of TLR4 signaling , showing redundancy in signaling pathways that activate a type I interferon response to vaccinia . We hypothesized that protective effects of TLR4 may be mediated by pro-inflammatory cytokine responses , limiting viral replication and spread directly , or indirectly through recruitment of immune cells . To test this hypothesis , we infected C3H/HeJ and control mice with 5×105 pfu Vac-GFL i . n . and harvested lungs on days 3 and 5 post-infection . Supernatants from homogenized lungs were analyzed by ELISA for IL-6 , TNF-α , and MCP-1 . There were no significant differences in levels of any of these cytokines between groups of mice on day 3 . On day 5 , TNF-α and MCP-1 levels were the same in TLR4 mutant and control mice , but IL-6 levels were significantly higher in C3H/HeJ lungs ( Figure 8 ) . No significant differences were detected in the plasma at either time ( data not shown ) ( p>0 . 4 ) . As with type I interferon , redundant signaling pathways are able to elicit NF-κB-dependent cytokine production in response to vaccinia infection . To analyze the degree and composition of leukocyte infiltrates in the lung , immune cells were isolated from uninfected mice and mice on days 3 and 5 post-infection . Numbers and types of cells were analyzed by flow cytometry . At day 3 , there was a trend towards higher total CD45+ cells in the C3H/HeJ cell , but these differences were not significant . We also measured subsets of immune cells in the lung , including B lymphocytes , CD4 and CD8 lymphocytes , macrophages , dendritic cells , and neutrophils . However , there were no consistent differences in cell types recruited to lungs of infected C3H/HeJ and control C3HeB/FeJ mice ( data not shown ) . To further assess the pattern of inflammation and tissue damage in TLR4 mutant lungs , we examined the lungs of vaccinia-infected mice by histology . Hematoxylin and eosin–stained sections showed foci of mixed and lymphocytic peribronchial and perivascular infiltrate ( Figure 9A and 9B ) . Occasionally , infiltrating cells could be seen in alveoli separate from any peribronchial or perivascular focus . In foci of severe inflammation , epithelial cell necrosis was observed , and some inflammatory cells had apoptotic morphology . As a quantitative measure of inflammation , numbers of foci in each section were counted . On day 3 post-infection , the beginning of the interval when increased levels of virus could be discerned in lungs of TLR4 mutant mice , C3H/HeJ TLR4 mutant mice had significantly more foci of inflammation than controls ( p<0 . 05; Figure 10 ) . No consistent differences were detected on day 5 . These data indicate that TLR4 is not required for producing an early local inflammatory response to vaccinia infection . To investigate the cell type ( s ) involved in the propagation of infection in the lungs , we performed immunohistochemical staining on paraffin-embedded lung sections with anti-GFP . Mice were infected with 5×105 pfu Vac-GFL , and lungs were harvested on days 3 and 5 post-infection . In all samples , intense anti-GFP staining was localized to bronchial epithelial cells with less extensive infection detected in alveolar epithelial cells ( Figure 11A and 11B ) . Samples of both genotypes also showed some staining of cells among the inflammatory infiltrate , possibly macrophages , although firm identification could not be made . In all samples , the regions of positive anti-GFP antibody staining were associated with foci of inflammation , but many foci of inflammation had no regions of anti-GFP antibody staining . The distribution and types of infected cells did not differ between strains of mice . These findings suggest that in the lungs , vaccinia primarily replicates and spreads through epithelial cells . In order to determine whether TLR4 was signaling in response to an endogenous or a viral ligand , we treated bone marrow macrophages isolated from C3H/HeJ and control mice with live or UV-inactivated virus ( MOI = 5 ) , and measured levels of TNF-α and IL-6 in the supernatant . The undiluted stock of UV-inactivated Vac-GFL ( 9 . 0×107 pfu/mL ) produced no plaques or cytopathic effect in cultured Vero cells ( data not shown ) . TLR4 mutant and control macrophages were equally resistant to viral replication , even when challenged with live virus at a high MOI ( Figure 12A ) . TLR4 mutant and control macrophages treated with UV-inactivated virus produced significantly ( p<0 . 05 ) higher levels of IL-6 and TNF-α than cells of the same genotype treated with live virus ( Figure 12B and 12C ) . This is likely due to the absence vaccinia-encoded inhibitors of TLR and other signaling pathways , such as N1L , A46R , and A52R [25]–[27] , produced by replicating vaccinia virus . TLR4 mutant macrophages produced significantly higher levels of both IL-6 and TNF-α than control cells ( p<0 . 05; both live and UV-inactivated virus ) . This shows that TLR4 not only is unnecessary for the cytokine response of bone marrow macrophages to vaccinia virus , but it actually dampens that response . C3H/HeJ ( TLR4 mutant ) cells treated with UV-inactivated virus produced by far the highest levels of any condition , rising above IL-6 levels in C3H/HeJ-with-live virus cultures by 6- to 7-fold and 2- to 3-fold for TNF-α in the same cells . Cytokine levels in UV-inactivated C3H/HeJ cultures were approximately 6- to 10-fold higher than those in UV-inactivated C3HeB/FeJ cultures . The fact that macrophages were able to produce TNF-α and IL-6 in response to UV-inactivated virus , and that TLR4-intact macrophages produce significantly less of these cytokines , indicates that neither viral replication nor cell death is necessary for TLR4 recognition of vaccinia virus . This suggests that TLR4 recognizes a component of the viral particle rather than an endogenous ligand released from infected host cells .
The innate immune system is vital for host defense against poxviruses , but molecular mechanisms of virus recognition and host defense are incompletely understood . While a robust Th1 immune response is necessary to eliminate vaccinia and other poxviruses , an exaggerated innate immune response also may threaten the life of the host . In septic shock , a systemic “cytokine storm” causes blood vessel dilation and activation of the clotting cascade , leading to hypotension , hemolysis , and multi-organ failure . Severe and fatal cases of smallpox are characterized by fever , hypotension , coagulopathy , blood vessel dilatation , and leukocyte extravasation , all of which are resemble the pathophysiology of septic shock [3] . These observations , coupled with the absence of lesions from any location except the skin , suggest that an uncontrolled systemic immune response is the most dangerous aspect of poxvirus infection . As one mechanism through which immunity contributes to disease manifestations of poxviruses , we recently reported that TLR3 has a detrimental effect in vaccinia infection [13] . Specifically , mice lacking TLR3 had decreased viral replication , morbidity , and mortality following infection with vaccinia virus . These data established TLR3 as a key determinant of poxvirus pathogenesis and highlight the critical balance between effective and excessive innate immune responses during poxvirus infection . To further investigate signaling pathways by which TLR3 exacerbates poxvirus disease , we first analyzed vaccinia infection in mice lacking TRIF , the only known adapter protein for TLR3 . Unlike TLR3−/− mice , viral replication was significantly greater in TRIF−/− mice relative to wild-type animals . These data suggested the possibility that protective effects of TRIF against vaccinia infection were mediated through TLR4 . Besides TLR3 , TLR4 is the only other TLR known to use TRIF as a signaling adaptor . Although TLR4 canonically recognizes bacterial LPS , this receptor also has been implicated in host defense against some viruses . For example , TLR4 is reported to recognize respiratory syncytial virus ( RSV ) protein F or vesicular stomatitis virus ( VSV ) glycoprotein G , thereby initiating protective innate immune responses [11] , [16] . Unlike TLR3 , TLR4 does not rely on TRIF exclusively , but also can signal through the adaptor myeloid differentiation factor 88 ( MyD88 ) . We hypothesized that in TLR3−/− mice , the normal inflammatory response was attenuated sufficiently to minimize injury to the host while still eliminating vaccinia virus . In TRIF−/− mice , we reasoned that signaling inputs from TLR3 and TLR4 were both blocked , thus decreasing the inflammatory response to such a degree that the host was not able to make an effective defense against the virus . Consistent with this hypothesis , we demonstrated a protective effect for TLR4 in pulmonary vaccinia infection . Mice with an inactivating mutation in TLR4 suffered increased mortality , more severe hypothermia , and increased viral replication in the head , chest , and abdomen . Further investigation into the mechanism of this protection , however , revealed a more complicated picture . The TLR4 signaling pathway results in activation of NF-κB and interferon regulatory factor 3 , suggesting that TLR4-deficient mice would have increased viral replication because of impaired cytokine production and recruitment of immune cells to the lung and other sites of infection . However , levels of TNF-α , MCP-1 , IL-6 , and IFN-β in TLR4 mutant mice were equal to or even greater than those of the controls . Moreover , histological examination of infected lungs showed that TLR4 mutant mice had significantly more foci of inflammation in their lungs than did controls as early as day 3 post-infection . The results suggest either that TLR4 does not function in these aspects of host immunity to vaccinia virus or that other pattern recognition receptors compensate for loss of TLR4 . For example , recent studies suggest protective functions of TLR2 and TLR9 in poxvirus infection [28] , [29] . The fact that the TLR4 mutant mice are still more susceptible to disease indicates that other pattern recognition receptors are not fully redundant to TLR4 in poxvirus infection . Immunohistochemical staining revealed vaccinia infection predominantly in bronchiolar epithelium with lesser amounts of viral GFP in alveolar epithelial cells . These data are consistent with previous studies showing that respiratory infection with poxviruses causes a necrotizing bronchopneumonia [30] . We also identified viral GFP antigen in immune cells in the lung , likely macrophages . Previous studies suggest that monocyte/ macrophage cell types are responsible for systemic spread of poxviruses [30] . While we cannot exclude the possibility that GFP is present in these cells because of phagocytosis rather than infection , our data are compatible with a model in which cells in the monocyte lineage are responsible for systemic dissemination of virus . The observation that both genotypes exhibited a similar repertoire of infected cells suggests that a difference in susceptibility of specific cell types does not account for increased susceptibility of the TLR4 mutant mice . Increased IL-6 and TNF-α levels in TLR4 mutant macrophages treated with UV-inactivated virus show that viral replication and cell damage are dispensable for TLR4 recognition of vaccinia . This suggests that TLR4 recognizes a component of the viral particle rather than a host ligand . In our model , the ligand recognized by TLR4 likely would be located in/on the intracellular mature virion ( IMV ) particle , the predominant form of virus isolated by standard purification procedures such as those used in this research . TLR4 predominantly localizes to the cell membrane , so candidate TLR4 ligands likely would be on the surface of the intracellular mature virion . However , crosslinking DNA in the viral genome with UV/psoralen treatment does not prevent vaccinia from entering the cell and uncoating , so the TLR4 ligand also could be a capsid protein or another protein present in the viral particle . Increased inflammation in TLR4 mutant mice may be secondary to increased viral burden or a primary effect of the loss of TLR4 . Because TLR4 mutant macrophages secrete increased levels of IL-6 and TNF-α even when challenged with UV-inactivated virus , we propose that lack of TLR4 signaling causes increased inflammation . This interpretation also is supported by our data showing equal viral titers in TLR4 mutant and control macrophage cultures infected with live virus despite the higher cytokine levels in TLR4 mutant cell cultures . Consistent with our observations in TLR3−/− mice , TLR4 may provide its protection by dampening the inflammatory response elicited in response to vaccinia infection . In conclusion , this study demonstrates that TLR4 mediates a protective immune response to vaccinia virus . To our knowledge , it is the first to demonstrate such a role in the context of vaccinia infection , adding to a growing body of literature showing that TLR4 may respond to non-bacterial ligands and mediate protective effects against viruses . These data also highlight the complexity of TLR signaling in vivo in determining overall outcomes of infection . As the TLR4 mutant mice had equal or greater levels of interferon and proinflammatory cytokines in their lungs , we cannot attribute their increased susceptibility to impairment of TLR4-dependent interferon or cytokine production . Protective effects of TLR4 also cannot be attributed to altered or impaired effector cell recruitment or to increased susceptibility of a specific lung cell population to vaccinia infection . However , TLR4 differentially activates an aspect ( s ) of antiviral defense that is essential for early control of vaccinia replication and spread . Understanding details of this differential regulation will reveal strategies to enhance beneficial immunity to poxviruses and suppress detrimental host responses .
TRIF−/− mice backcrossed to a C57BL/6 background were originally developed by the S . Akira laboratory and were bred at the University of Michigan . Wild-type ( WT ) C57BL/6J control mice were obtained from The Jackson Laboratory . Adult male and female mice ages 7 to 9 wk old were used for experiments . C3HeB/FeJ and C3H/HeJ mice were obtained from The Jackson Laboratory . Adult male mice ages 6 to 10 wk old were used for experiments . 17-wk-old mice were used as uninfected controls for histological studies . We prepared stocks of Vac-GFL , a recombinant Western Reserve ( WR ) vaccinia virus that expresses firefly luciferase and GFP , and determined viral titers as described previously [13] . Viral titers in excised organs were analyzed by serial dilution on Vero cells [15] . Vero cells were maintained as we previously have described [15] . Primary bone marrow macrophages were obtained by flushing the femurs and tibiae of mice with cold PBS . This suspension was filtered through a 100 µm filter and a 40 µm filter . Macrophages were cultured in Dulbecco's modified Eagle medium supplemented with 20% L929-cell-conditioned media , 10% heat-inactivated fetal bovine serum , 1% L-glutamine , and 0 . 1% penicillin-streptomycin . Macrophages were cultured 1 wk in this media before performing experiments with them . All animal procedures were approved by the University of Michigan Committee on the Use and Care of Animals . Mice were infected i . n . with vaccinia virus as described previously [15] . Weights and rectal temperatures ( Physitemp Instruments ) were recorded on conscious mice immediately before infection and on each day throughout experiments . Bioluminescence imaging was performed on each day after infection using an IVIS 200 system ( Caliper ) . Imaging and data analysis were performed as described previously [15] . To prepare lungs for histology , mice were euthanized on days 3 and 5 post-infection , and lungs were inflated with 1 mL of 10% formalin in PBS . Lungs were excised , preserved in 10% formalin overnight or longer , and then transferred to 70% ethanol solution . Fixed tissues were paraffin embedded and sectioned by the Morphology Core Facility at the University of Michigan . Tissue sections were stained with Gill's hematoxylin and counterstained with eosin . Sites of viral replication in the lungs were identified by immunohistochemistry , based on detection of GFP from Vac-GFL . Paraffin-embedded lung sections were stained using the Vector Laboratories ABC staining kit . Tissue sections were stained with rabbit polyclonal anti-GFP antibody ( 1/500 dilution ) ( Invitrogen ) and goat anti-rabbit secondary antibody ( 1/200 dilution; Vector Laboratories ) . Blocking solution consisted a 1/67 dilution of goat serum in PBS with 250 mM total NaCl . To quantify foci of inflammation in lung sections , we analyzed transverse lung sections through comparable portions of the upper and lower lobes of each lung . Sections were viewed under a 4× objective , and numbers of inflammatory foci were counted . Mean values for numbers of foci and SEM were calculated . Blood was obtained from the abdominal aorta of euthanized mice and collected into heparinized tubes . Plasma was separated from cells by centrifugation . Bronchoalveolar lavage of TRIF−/− mice was performed by intratracheal instillation and withdrawal of 1 mL PBS in lungs of euthanized mice . Plasma and bronchoalveolar lavage fluid concentrations of TNF-α , IL-6 , and MCP-1 were determined by ELISA performed by the University of Michigan Cancer Center Cellular Immunology Core Facility . Concentrations of IFN-β were measured by ELISA ( PBL Biomedical Laboratories ) according to the manufacturer's instructions . Lungs were harvested on day 3 or 5 post-infection and homogenized in 5 mL PBS with a Polytron tissue homogenizer ( Brinkmann ) . Lung homogenates were centrifuged at 2111×g for 10 minutes at 4°C . Supernatants were removed and concentrations of TNF-α , IL-6 , and MCP-1 measured by ELISA as described above . Lungs were excised on day 3 or 5 post-infection and disaggregated by mechanical disruption in a blender ( VWR ) . Cells were counted and analyzed by flow cytometry as described previously [31] . The following mAbs obtained from BD Pharmingen were used: RM4-4 ( anti-murine CD4 , rat IgG2b ) , 53-6 . 72 ( anti-murine CD8 , rat IgG2b ) , 1D3 ( anti-murine CD19 , rat IgG2a ) , M1/70 ( anti-murine CD11b , rat IgG2b ) , HL3 ( antimurine CD11c , hamster IgG1 ) , 2 . 4G2 ( anti-murine CD16/CD32 Fc block , rat IgG2b ) , 30-F11 ( anti-murine CD45 , rat IgG2b ) , and RB6-8C5 ( anti-murine Ly6G Gr-1 , rat IgG2b ) . Monoclonal Abs were primarily conjugated with FITC , PE , APC and APC-Cy7; biotinylated Abs were visualized using streptavidin-PerCP-Cy5 . 5 ( BD Pharmingen ) . Isotype matched control mAbs ( BD Pharmingen or eBioscience ) were tested simultaneously in all experiments . All samples were analyzed on the BD LSR II flow cytometer with 3 lasers ( 488 nm blue , 405 nm violet and 633 nm HeNe red ) . CD45 APC-Cy7 and Invitrogen LIVE/DEAD Fixable Violet Dead Cell Stain were added to all lung mince samples . Subset analysis was performed on gated CD45-positive live cells . A minimum of 10 , 000 cells were analyzed for each sample . For all analyses , percentages for matched isotype control Abs were subtracted from values obtained for staining with specific Abs for individual markers . Vac-GFL was UV-inactivated by irradiation for 90 s on “sterilize” setting in a GS Genelinker UV-chamber ( BioRad ) following incubation in a Hank's Balanced Salt Solution ( HBSS ) solution containing 1 . 0 µg Psoralen according to the protocol of Puhlmann and colleagues [32] . Data were analyzed by t test for pairwise comparisons , using Microsoft Excel or GraphPad Prism software . Differences with p<0 . 05 were regarded as statistically significant .
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Toll-like receptors are a class of transmembrane proteins that detect the presence of infectious organisms and activate host innate and adaptive immune responses . Vaccinia virus is the prototypic poxvirus , and it is used as both a model and a vaccine for the virus that causes smallpox . We recently reported that Toll-like receptor 3 ( TLR3 ) , which recognizes double-stranded RNA , acts in vaccinia infection in a way that is detrimental to the host . TLR3 relays its signal to the nucleus using the adaptor protein TRIF . In this paper , we report that mice lacking TRIF are more susceptible to vaccinia infection than wild-type controls . TLR4 also uses TRIF to relay its signals . We report our findings that TLR4 has a protective effect in vaccinia infection . Mice with a nonfunctional mutant version of TLR4 are more susceptible to vaccinia infection than wild-type controls . The protection that TLR4 affords is not due to effects on secretion of proinflammatory cytokines or type I interferon , and the receptor also does not uniquely regulate recruitment of white blood cells to the site of infection . Rather , TLR4 recognizes a molecule in or on vaccinia virus to bring about a protective response that may be due to an ability to diminish the degree of inflammation caused by vaccinia infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biotechnology",
"immunology/immunity",
"to",
"infections",
"virology/animal",
"models",
"of",
"infection"
] |
2008
|
Protective Effect of Toll-like Receptor 4 in Pulmonary Vaccinia Infection
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Morbidity due to Schistosoma haematobium and hookworm infections is marked in those with intense co-infections by these parasites . The development of a spatial predictive decision-support tool is crucial for targeting the delivery of integrated mass drug administration ( MDA ) to those most in need . We investigated the co-distribution of S . haematobium and hookworm infection , plus the spatial overlap of infection intensity of both parasites , in Ghana . The aim was to produce maps to assist the planning and evaluation of national parasitic disease control programs . A national cross-sectional school-based parasitological survey was conducted in Ghana in 2008 , using standardized sampling and parasitological methods . Bayesian geostatistical models were built , including a multinomial regression model for S . haematobium and hookworm mono- and co-infections and zero-inflated Poisson regression models for S . haematobium and hookworm infection intensity as measured by egg counts in urine and stool respectively . The resulting infection intensity maps were overlaid to determine the extent of geographical overlap of S . haematobium and hookworm infection intensity . In Ghana , prevalence of S . haematobium mono-infection was 14 . 4% , hookworm mono-infection was 3 . 2% , and S . haematobium and hookworm co-infection was 0 . 7% . Distance to water bodies was negatively associated with S . haematobium and hookworm co-infections , hookworm mono-infections and S . haematobium infection intensity . Land surface temperature was positively associated with hookworm mono-infections and S . haematobium infection intensity . While high-risk ( prevalence >10–20% ) of co-infection was predicted in an area around Lake Volta , co-intensity was predicted to be highest in foci within that area . Our approach , based on the combination of co-infection and co-intensity maps allows the identification of communities at increased risk of severe morbidity and environmental contamination and provides a platform to evaluate progress of control efforts .
Parasitic infections caused by Schistosoma haematobium ( the aetiological agent of urinary schistosomiasis ) and hookworm ( a soil-transmitted helminth; STH ) are widely endemic among human populations in sub-Saharan Africa ( SSA ) [1] , [2] . The geographical distribution of these infections is known to be driven by environmental and climatic factors that influence parasite populations and those of the snail intermediate host of schistosomes [3] . Additionally , socioeconomic inequalities in human populations at risk , particularly in access to clean water and sanitation , housing , and the access to treatment impact on the observed distribution of these parasitic infections [2] , [4] . Control efforts rely on accurate geographical identification and enumeration of populations most at risk of morbidity ( i . e . co-infected and/or with intense infections ) [5] , [6] . Morbidity , including iron-deficiency anaemia , reduced growth and impaired cognition , is exacerbated by multiple species infections ( co-infection ) and high parasite burden ( i . e . high infection intensity ) [7] . Although co-infection and infection intensity are the indirect morbidity indicators most sensitive to changes in parasite transmission , contemporary control programs based on mass drug administration ( MDA ) are planned according to the identification of communities above established single-species prevalence of infection thresholds [8] , [9] . The number of adult worms is particularly difficult to measure and a proxy for infection intensity is often used such as the egg concentration in urine ( in the case of S . haematobium ) or in stool ( in the case of intestinal schistosomiasis and STHs ) . The number of eggs that are passed in the urine or stool is determined by important non-linearities in worm life-cycles such as fecundity of female worms and density-dependent development [10] , [11] . In endemic populations , the occurrence of infections that lead to high egg output determines the level of environmental contamination which partly contributes to transmission . Therefore , targeting treatment delivery to communities with a high proportion of co-infected and/or to those with high egg output could lead to more efficient reduction of transmission and severe morbidity compared to targeting treatment based on prevalence of single infections . With the aim of assisting the planning and implementation of MDA , model-based geostatistics ( MBG ) has been used to produce predictive empirical maps of prevalence of infection at different spatial scales [12]–[16] . The MBG approach provides an extensive set of spatial modeling tools for assessing the geographical overlap of multiple parasite infections [17] . One approach is overlaying prevalence of infection maps for multiple parasites ( i . e . co-endemicity mapping ) [18]; alternatively , spatial multinomial models can be used to predict the prevalence of mono- and co-infection [3] , [19] . Recently , Brooker et al . [3] have mapped S . mansoni and hookworm mono- and co-infection in the East African region; thus far no studies have been reported at the national or regional scale in West Africa . Examples of MBG studies that have analysed the spatial distribution of single-species intensity of infection are available in the literature [13] , [20] , [21] . We have recently suggested extending this approach to the overlay of predictive maps of intensity of infection ( i . e . mapping co-intensity ) to allow the identification of common areas of high transmission of multiple parasite species where integrated treatment could be prioritized [17] . To date there are no reported studies in the literature that have mapped co-intensity profiles . Recently , with financial and technical support from the Schistosomiasis Control Initiative ( SCI ) , three contiguous countries in the Sahelian zone of West Africa ( Burkina Faso , Mali and Niger ) conducted coordinated national cross-sectional school-based parasitological surveys [22] . Based on these surveys , Bayesian geostatistical analyses were conducted for estimating the geographical distribution of S . haematobium and S . mansoni infection metrics in these countries [13] , [14] , [23] . An important country in the region with respect to helminth transmission is Ghana . The construction of the Akosombo dam from 1962 to 1967 , created a vast area now known as Lake Volta ( approximately 8 , 500 km2 ) suitable for the breeding of freshwater snails that serve as intermediate hosts of schistosomiasis . Since then , schistosomiasis in Ghana assumed major importance as a public health problem in the country , and the prevalence of S . haematobium rose from 5–10% before the construction of the dam to >90% in most communities along lake Volta [24]–[28] . Similarly , the construction of numerous agricultural dams throughout the Upper East Region between 1958 and 1964 resulted in a rise in prevalence of S . haematobium from 17% to 51% [29] . Studies in children 15–19 years of age in the North Western Region [30] and in the Southern Region of Ghana [31] , [32] , [33] have yielded prevalence estimates of 34% and 60–83 . 9% , respectively . In a study in infants ( 1–5 years of age ) in the Central region the prevalence of urinary schistosomiasis was estimated to be 11% [34] . Prior to the commencement of the Ghana Health Service Neglected Tropical Disease ( GHS NTD ) program in five regions ( Upper West , Upper East , Northern , Western , and Central ) in 2008 , national teams collected data for the national mapping of schistosomiasis and STHs with technical assistance of SCI . Before the inception of the GHS NTD program , limited effort had been carried out in a few areas around Lake Volta and no sizeable MDA of schistosomiasis had been implemented in the country . Incidentally for STHs , the Global Program to Eliminate Lymphatic Filariasis ( GPELF ) was ongoing in lymphatic filariasis ( LF ) -endemic areas ( mainly in the west and north of the country ) , distributing ivermectin plus albendazole . Therefore the data collected truly represent the burden of schistosomiasis and STH infections before the implementation of the nationwide program . In this paper , we describe data from the 2008 pre-intervention national helminth survey in Ghana and predict for the first time the prevalence of S . haematobium and hookworm mono- and co-infections and intensity of infection , as measured by egg counts , in Ghana . We hypothesize that the combined use of co-infection and co-intensity maps has the potential to further broaden the range of spatial predictive decision-support tools to aid targeting the delivery of integrated MDA and may constitute an important cartographic resource to evaluate progress in morbidity control . The aims are to identify communities in Ghana where the integrated distribution of praziquantel and albendazole could be prioritized to maximize the impact on morbidity and generate output maps which can constitute an evidence base to be used by GHS NTD program managers for the evaluation of ongoing interventions .
Ethical approval for these surveys was obtained from Imperial College Research Ethics Committee UK and the Ghana Health Service Ethical Review Committee in Ghana . The official letters were sent by the Ghana Health Service to the Regional and District health and educational authorities in advance . All data collection activities were carefully explained to , and oral consent was obtained from traditional authorities and other opinion leaders in the village ( the village head , elders and political leaders ) , the school headmasters , the parent-teachers association , the representative of the pupils' parents and the local health authorities . All parents/guardians of all children involved in the study provided consent; parents/guardians who did not want their children to participate informed the school authorities . Child participants were given an explanation of the data collection activities and were free not to participate if they so chose . Written consent was not obtained and oral consent was approved by the ethics committee involved because the survey was considered by the UK and Ghanaian ethical committees as part of the monitoring and evaluation of routine health activities carried out by the GHS NTD control program . Representatives of parent-teacher associations were invited to be present during the sample collection process . Most of the parents who showed up at the school were there to ensure that their children had the opportunity to participate . They were also given the opportunity to have a look at microscope slides that had the parasite eggs present . The parasitological data for this study were collated from national , school-based parasitological surveys conducted in Ghana in 2008 with the support from the SCI [9] . These surveys were originally designed and implemented with the objective of mapping urinary schistosomiasis , which is the most prevalent form of schistosomiasis in West Africa [22] , [35] . As the geographical coordinates of the schools were not known , but the district and locality ( rural or urban ) of each school is known , a stratification procedure was used to select the schools such that schools in rural communities or districts that were adjacent to Lake Volta were twice as likely to be sampled as schools in urban communities or districts that were not adjacent to Lake Volta . Districts were stratified into 4 strata: a ) those adjacent to Lake Volta ( stratum 1 ) ; b ) districts not adjacent to the lake ( stratum 2 ) ; c ) schools which are located in rural areas ( stratum 3 ) ; and d ) schools which are located in urban areas ( stratum 4 ) . The stratum that is adjacent to the lake ( stratum 1 ) was sampled twice as densely as the stratum away from the lake ( stratum 2 ) to ensure that accurate estimates of schistosomiasis are obtained . The rural stratum was sampled more densely than the urban stratum to ensure there were enough data for rural areas which are expected to have higher prevalence of both schistosomiasis and soil-transmitted helminths . To ensure good geographical coverage of the survey area the number of schools to be selected from each district was calculated proportional to the size of the district . The area of each district was calculated using a geographical information system ( GIS ) . The sample size was calculated to give the same spatial density of schools as for similar surveys from neighbouring West African countries also supported by SCI ( i . e . Burkina Faso , Mali and Niger ) [13] , [14] . It was decided to survey 77 schools and select at random 60 children ( 30 boys and 30 girls ) in each school when possible . The sampling frame for school selection consisted of a list of all schools in the country , stored in a Microsoft Excel 2007spreadsheet . Children were selected from within the selected schools using systematic random sampling of class lists . Selected children were assembled and asked to provide a stool and urine sample . A total of 4 , 577 children aged 2–19 year old were tested; these correspond to 43 fewer children than expected because fewer children were sampled in some schools; these schools were evenly distributed across the country . Stool samples provided by each child were used to make two slides which were examined microscopically using the semi-quantitative Kato-Katz technique for the eggs of STHs ( Ascaris lumbricoides , Trichuris trichiura and hookworm ) and Schistosoma mansoni . After collection of stool samples these were processed immediately and slides were prepared and examined in the field laboratory by experienced microscopists in diagnosing schistosomiasis and STHs , within 2 hours of preparation to increase detection of the more labile hookworm eggs , by the Kato-Katz thick smear technique using a 41 . 7 mg template [36] . The concentration of eggs was expressed as eggs per gram of faeces ( epg ) . From urine samples , up to 10 mL were filtered through a polycarbonate membrane and the number of eggs of S . haematobium were counted and expressed as eggs per 10 mL of urine . The geographic location of the school was determined using a handheld global positioning system device . The dataset for analysis included data from 4 , 445 children aged 5–19 years located in 77 schools from which complete demographic and parasitological information was available . A summary of the prevalence of each parasite for the study area is presented in Table 1 , showing that T . trichiura was a rare STH infection in the study area . The prevalence of S . mansoni was also very low in comparison to that of S . haematobium . In our analyses we considered the data for S . haematobium and hookworm only because multiple infections with these parasites are known to be associated with pronounced morbidity , including anaemia [21] . The survey data were summarized by prevalence of mono- and co-infections and arithmetic mean infection intensity , by survey location . These summary data were plotted in ArcGIS version 10 ( ESRI , Inc ) . To provide robust confidence intervals around the mean prevalence in Ghana prevalence estimation took into account the clustered design of the sampling , using the school as a primary sampling unit and including adjustments for the probability of sampling and finite population corrections for sampling without replacement in the Stata/SE 11 . 0 statistical package ( StataCorp , College Station , Texas , USA ) . This was based on the assumption that children attending the same school would be more likely to have more similar exposures than children attending other schools . Electronic data for land surface temperature ( LST ) and normalised difference vegetation index ( NDVI ) were obtained from the National Oceanographic and Atmospheric Administration's ( NOAA ) Advanced Very High Radiometer ( AVHRR; see Hay et al . [37] for details on these datasets ) and the location of large perennial inland water bodies was obtained from the Food and Agriculture Organization of the United Nations ( http://www . fao . org/geonetwork/srv/en/main . home ) . Values for LST , NDVI and distance to the nearest perennial inland water body ( PIWB ) were extracted in ArcGIS version 10 . 0 ( ESRI , Inc ) for each survey location . The initial set of variables included the individual-level variables of sex and age ( categorized into 5–9 , 10–14 years and 15–19 years ) and the school-level variables of NDVI , LST and distance to PIWB . Fixed-effects multinomial regression models of S . haematobium/hookworm co-infections were developed in a frequentist statistical software package ( Stata version 10 . 1 , Stata Corporation , College Station , TX ) . A quadratic association between LST and prevalence was assessed and was not found to improve model fit ( using Akaike's Information Criterion [38] ) ; distance to PIWB was significantly and negatively associated with prevalence of co-infection . NDVI was not found to be significantly associated with prevalence of co-infection in the preliminary multivariable models and was excluded from further analysis ( Wald's P>0 . 2 ) . Therefore , it was decided to enter LST and distance to PIWB as covariates into the final spatial models in WinBUGS . In the MBG co-infection model , individual raw survey data were aggregated into groups according to age group , sex and location and using four infection outcomes ( i . e . 1 = Without infection; 2 = S . haematobium mono-infection; 3 = hookworm mono-infection and 4 = S . haematobium-hookworm co-infection ) . In this model the baseline category was “Without infection” . Statistical notation of Bayesian geostatistical models is presented in Text S1 . Individual egg count data were used as a proxy of worm burden in the models of infection intensity . Infection intensity can be modeled by transforming parasite egg counts into an ordinal or nominal categorical variable based on World Health Organization ( WHO ) cut-offs ( not infected , light-intensity infection , moderate and high-intensity infection ) [39] and using a multinomial distribution for the stratified intensity outcomes . However , the multinomial approach involves stratifying egg counts , leading to a loss of information whereas the Poisson or the negative binomial approach make full use of infection intensity data on a continuous scale ( as measured by number of eggs found in both slides per individual ) [40] . Usually , only a small proportion of the infected population excretes large numbers of parasite eggs . Therefore , infection intensity data typically contain many zero egg counts due to the aggregation of parasite distribution among hosts ( also referred to as over dispersion ) [41] and the presence of false negatives [42] . The large number of zero counts suggests the data are over dispersed relative to the Poisson distribution , the usual discrete probability distribution used for count data . To address this problem , the zero-inflated Poisson ( ZIP ) or the zero-inflated negative binomial ( ZINB ) regression models could be used [21] , [43] , [44] . The best fitting distributional form of parasite egg counts was investigated using the nbvargr command in Stata version 11 ( Stata Corporation , College Station , TX ) ; this assessment provided statistical support to consider the ZIP distribution as the best possible fit to the data for both parasites . We then developed univariate and multivariate models of parasite egg counts using ZIP models for each parasite species in Stata version 11 . The variable screening approach was similar to that outlined above for models of co-infection and for S . haematobium and hookworm it was decided to enter untransformed LST and distance to PIWB as environmental covariates into the final spatial models in WinBUGS . We have applied a MBG ZIP model following an approach which is similar for prediction of prevalence , using the same candidate set of predictor variables and geostatistical random effects as the ones used in the co-infection model . The main difference was that the outcome , rather than being binary ( infected/not infected ) , was a count [epg ( for hookworm ) or eggs per 10 mL of urine ( for S . haematobium ) ] modeled using a Poisson distribution for the mean intensity models . With a ZIP model there are two processes that have to be considered , 1 ) the zero inflation model and 2 ) the ( positive ) expectation of the response for the distribution of the Poisson ( or other distribution ) part of the model . The marginal ( or overall ) expected value of the response is the expected value of the Poisson part shrunken by an amount proportional to the zero inflation probability [45] . Statistical notation of MGB ZIP models is presented in Text S2 . The spatial models were fitted in WinBUGS version 1 . 4 statistical software ( Medical Research Council Biostatistics Unit , Cambridge , United Kingdom and Imperial College London , United Kingdom ) and were based on MBG [46] . For each model ( i . e . single infection intensity models and the multinomial model of co-infection ) a burn-in of 5 , 000 iterations was used followed by 5 , 000 iteration intervals after which convergence was assessed using visualization of history and density plots of the series of posterior values . Bayesian model outputs for parameters of interest and for predictions at unsampled locations are probability distributions , termed posterior distributions , which represent the probability of a variable of interest taking each of a range of plausible values . The posterior distributions can be summarized by statistics such as the posterior mean and 95% Bayesian credible interval ( BCI ) . For model coefficients , significance at the 5% level is defined by a 95% BCI that excludes zero . In all models , convergence of model parameters was successfully achieved after 20 , 000 iterations and the model was run for a further 10 , 000 iterations , after which the predicted prevalence for each outcome group at unsampled locations was stored for boys of 15–19 years of age . The models developed allow production of predictive maps of co-infection and infection intensity for all age groups and sexes – for mapping purposes we chose to map boys aged 15–19 years , as this was the group with the highest risk of co-infection and the highest hookworm intensities of infection . Predictions were made at the nodes of a 0 . 1×0 . 1 decimal degree grid ( approximately 12 km2 ) by adding ( on the logit scale ) the following: 1 ) the sum of the products of the coefficients for the fixed effects and the values of the fixed effects at each prediction locations , and 2 ) the interpolated random effect . The latter was achieved using the spatial . unipred command in WinBUGS [47] , which implements Bayesian kriging . This function implements independent simulations that do not consider neighboring values , as opposed to joint prediction which is conditional on the values of neighboring locations . While joint prediction yields more accurate measures of prediction uncertainty , it was not considered feasible in this study due to having extremely demanding computational requirements . The area under the curve ( AUC ) of the receiver operating characteristic was used to determine discriminatory performance of the model predictions relative to observed co-infection prevalence thresholds of 5% and 10% [48] . Following the same procedure , the predicted infection intensity was compared to the observed intensity of infection , dichotomised at 50 eggs/10 mL , for S . haematobium and at 1 epg of stool for hookworm . An AUC value of 0 . 7 was taken to indicate acceptable predictive performance [48] . The S . haematobium and hookworm co-intensity map for Ghana was constructed by overlaying the predicted posterior mean intensity maps of S . haematobium and hookworm in ArcGIS version 10 . 0 ( ESRI , Inc . ) . WHO classifies infection intensity based on eggs count thresholds [39]: for S . haematobium light infections are 1–50 eggs/10 mL of urine and heavy infections are >50 eggs/10 mL of urine , and for hookworm light infection are 1–1 , 999epg , moderate infection was 2 , 000–3 , 999epg , heavy infection was >4 , 000epg . For mapping purposes the predicted intensity of S . haematobium was defined as <25 eggs/10 mL of urine , >25–50 eggs/10 mL of urine and >50 eggs/10 mL of urine . Due to the low mean hookworm infection intensity in Ghana , the predicted intensity of infection for this parasite was dichotomized according to <1 and ≥1 epg .
The prevalence of S . haematobium and hookworm mono- and co-infection is presented stratified by sex and age ( Table 2 ) ; our results show that males are significantly more co-infected than females and children of 15–19 years of age were significantly more co-infected than children of 5–9 years of age . The frequency distribution and spatial distribution of the raw prevalence of S . haematobium and hookworm mono- and co-infections for Ghana is presented in Figure 1 . The bar chart in Figure 1A shows that the distribution of the school prevalence mono- and co-infection is markedly skewed; the map in Figure 1B shows that there is a distinct spatial heterogeneity of S . haematobium and hookworm co-infections in Ghana where most co-infections are distributed near the western bank of the Lake Volta in central Ghana . Based on WHO classification guidelines [39] , our results show that all hookworm infections in Ghana are of light intensity ( 1–1 , 999 epg ) whereas 42% of the S . haematobium infections are of heavy intensity ( >50 eggs/10 mL of urine ) ( Table 1 ) . The spatial distribution of the raw intensity of S . haematobium and hookworm infections , as measured , respectively by the mean number of eggs per 10 mL of urine or epg in each location in 4 , 527 ( for S . haematobium ) and 4 , 538 ( for hookworm ) school children aged 5–19 at 77 locations in Ghana is presented in Figure 2 . The map in Figure 2A suggests that S . haematobium heavy-intensity infections are distributed along the Lake Volta . Figure 2B suggests that the most intense hookworm infections are not localized around the Lake Volta but distributed across a wider area in central Ghana . Parameters in Table 3 represent the logarithm of the relative risk ratio of mono- and co-infections; inspection of the 95% BCI shows that males had a significantly higher prevalence of co-infection and mono-infections than females . In addition , the prevalence of S . haematobium-hookworm co-infections in children aged 15–19 years was significantly higher than in those of age 5–9 years . Furthermore , children aged 10–14 had significantly higher S . haematobium mono-infections than children aged 5–9 years . Distance to PIWB was significantly and negatively associated with S . haematobium-hookworm co-infections and hookworm mono-infection . The variable for LST was positively and significantly associated with hookworm mono-infections . Phi ( φ ) indicates the rate of spatial decay of spatial autocorrelation and varied from 50 . 3 , 19 . 8 and 59 . 8 for S . haematobium-hookworm co-infection , S . haematobium mono-infection and hookworm mono-infections ( Table 3 ) . This indicates that , after accounting for the effect of covariates , the radii of the clusters were approximately 7 km , 18 km and 6 km for S . haematobium-hookworm co-infection , S . haematobium mono-infection and hookworm mono-infections ( note , φ is measured in decimal degrees and 3/φ determines the cluster size; one decimal degree is approximately 111 km at the Equator ) . The tendency for spatial clustering was the weakest for hookworm mono-infections ( the higher value the spatial variance parameter the higher the tendency for spatial clustering ) ( Table 3 ) . The geographical distribution of the risk of S . haematobium mono-infection ( Figure 3A ) is widespread and heterogeneous across Ghana , while the distribution of the risk of hookworm mono-infection ( Figure 3B ) is also geographically heterogeneous but much more focal . In Figure 3A , the risk of S . haematobium mono-infections is highest ( >30% ) in areas adjacent to the Lake Volta as well as in areas not associated with the Lake Volta in the south of the country . In contrast , the risk of hookworm mono-infection is highest ( >5% ) in areas in the eastern bank of the Lake Volta and areas located in a mid-latitudinal band across Ghana , not directly associated with the Lake Volta . In Figure 3C , the risk of S . haematobium and hookworm co-infections is quite focal and associated with areas adjacent to the Lake Volta and is highest ( >5% ) in the East Bank and in the South West of the lake . This model was able to predict with an AUC of 0 . 78 ( 0 . 70 , 0 . 85 ) and 0 . 75 ( 0 . 68 , 0 . 81 ) using a cut off of 5% and 10% prevalence , respectively . Estimates presented in Figure 4 are the mean ( marginal ) posterior predicted intensity values ( A and B ) , the standard deviation of the predicted mean egg counts ( C and D ) , mean probability of intensity being non-zero ( E and F ) , and the predicted mean non-zero counts ( G and H ) , from Bayesian geostatistical models . Males and children aged 10–14 years had the highest intensity of S . haematobium infections , whereas children aged 15–19 years had the highest intensity of hookworm infections ( Table 4 ) . Distance to PIWB was negatively associated and LST was positively associated with S . haematobium infection intensity . None of the environmental variables were significantly associated with hookworm infection intensity . After accounting for the effect of covariates , intensity of infection was clustered with a radius of approximately 17 km and 6 km for S . haematobium and hookworm respectively . The tendency for spatial clustering was the strongest for hookworm infection intensity ( Table 4 ) . The models of S . haematobium and hookworm infection intensity were able to predict the geographical distribution of infection intensity with an AUC 0 . 82 ( 95% CI: 0 . 75 , 0 . 88 ) and 0 . 78 ( 95% CI: 0 . 73 , 0 . 85 ) using a cut-off of 50 eggs per 10 mL of urine and 1 epg , respectively . A map showing the geographical distribution of the mean co-intensity profile for boys aged 15–19 years in Ghana is shown in Figure 5 . This map indicates that the areas where high intensity S . haematobium infection co-exists with areas where intensity of hookworm infection was predicted to be ≥1 eggs per gram are localised to small areas adjacent to the Lake Volta . These areas are surrounded by areas where light to moderate S . haematobium infections co-exist with hookworm infections of ≥1 epg . Visual inspection of Figure 3C and Figure 5 suggests that the risk of S . haematobium and hookworm co-infections is highest ( >10–20% ) in areas where S . haematobium infections co-exist with hookworm infections of ≥1 epg . In addition , the area in the eastern bank of the Lake Volta where the highest prevalence of co-infection was predicted ( Figure 3C ) coincides with an area where S . haematobium and hookworm co-intensity is predicted to be >25–50 eggs/10 mL and ≥1 epg . However , the area where co-infection is >15% is located in a different area where co-intensity is predicted to be highest ( 50 eggs/10 mL and ≥1 epg ) .
All existing studies of the spatial epidemiology of mono- and co-infection focus on S . mansoni and hookworm and highlight the marked spatial heterogeneity in patterns of infection [3] , [19] , [49] . Our modeling shows that it is also possible to predict spatial patterns of S . haematobium–hookworm co-infection at the national scale in Ghana . The observed risk factors ( i . e . distance to water bodies and land surface temperature ) are already well established and are consistent with the known epidemiology of S . haematobium and hookworm infection [3] . We demonstrated that the distribution of hookworm mono- and co-infection in Ghana is highly focal , exhibiting a highly skewed frequency distribution and a marked spatial dependency . In contrast , the distribution of S . haematobium is geographically heterogeneous and is more widespread . The generally similar patterns of hookworm mono- and co-infection suggest that the localized spatial distribution of co-infection in Ghana is influenced by the distribution of hookworm , rather than the distribution of S . haematobium . This finding is not consistent with those from East African countries where the geographical distribution of co-infection was found to be generally influenced by the distribution of S . mansoni rather than hookworm [3] . This reflects the fact that , in East Africa , schistosomiasis is focal and hookworm is ubiquitous , whereas in West Africa , schistosomiasis is more widely distributed and hookworm is relatively rare . The relative focality and low level of hookworm infection in Ghana may be driven by the MDA of anthelmintics for the control of other parasitic infections . The Global Program to Eliminate Lymphatic Filariasis ( GPELF ) distributes ivermectin and albendazole for LF across the region [24]–[28] and it is possible that the administration of albendazole for LF control in parts of Ghana may have had an important impact on STH prevalence and associated geographical distribution . The transmission dynamics of hookworm depends on microclimatic suitability for infective larvae survival ( primarily temperature and humidity ) and exposure opportunities to environments contaminated with human excreta . However , in our analyses we did not find statistical support for the inclusion of remotely sensed rainfall data ( as measured by NDVI ) as an environmental covariate in any of our models . It is possible that the effect of these programs have confounded substantially the relationship between environmental determinants known to influence the geographical distribution of hookworm . We have also predicted for Ghana the spatial distribution of S . haematobium and hookworm infection intensity . While the predictive infection intensity for hookworm was low across most of the country , our approach generated local estimates of infection intensity for both parasites that highlighted the role of geographical heterogeneity in intensity of infection on parasite co-infection profiles . When combining the predictive intensity of infection maps for S . haematobium and hookworm , we found similarities between the distribution of co-infections ( Figure 3C ) and co-intensity ( Figure 5 ) , which is consistent with recent evidence suggesting that multiple helminth infections tend to cluster more with increasing levels of intensity of transmission [5] , [6] . However , there were subtle differences that suggest it might be worth using both co-infection and co-intensity mapping approaches when planning integrated control programs over those that use crude prevalence or intensity maps alone . Considering that intensity of infection is both an important epidemiological driver of morbidity and very sensitive to intervention efforts , the maximal effect of integrated morbidity control and evaluation could be achieved by geographically targeting areas where S . haematobium intensity co-exist with areas of hookworm intensity . In addition , targeting these areas would provide adequate transmission control by contributing to the reduction of the level of environmental contamination . While an empirical map of co-infection would allow the enumeration of population that are in need of treatment for multiple infections , its combined use with a co-intensity map constitutes an important cartographic resource by allowing the evaluation of the impact of control programs with the aim of reducing population-level morbidity [17] . This could be objectively achieved by conducting follow up surveys targeted to areas predicted to have the highest combined co-infection/co-intensity and assessing the degree of spatial contraction ( or expansion ) in the co-intensity surface following MDA . Important uncertainties should be noted from the Ghanaian dataset and the predictions surfaces for parasite infection used in our models , which are likely to be propagated throughout the modeling framework . First , we used threshold egg counts to classify light , moderate and heavy intensity infections for each species [39] . In the case of hookworm it has been shown that the relationship between worm burden and egg output is non-linear , i . e . density-dependent , and differing between communities [50] . These non-linear phenomena influence the validity of infection intensity as measured by egg concentration in urine or in faeces and detection of parasite eggs simply indicates the presence of at least one sexually mature and mated female worm . However , egg counts for hookworm infections were consistently low and for that reason these may actually reflect low adult parasite burdens although heavy infections of asexual female or male worms may also be possible . Furthermore , the egg counts were based on a single sample which limits the Kato-Katz test performance for detecting low infection intensities such as the ones identified in our surveys [51] . Stool processing times greater than 30 minutes are also likely to result in low hookworm intensities being detected due to egg lysis . While the effect of the latter was minimized by prompt field processing of samples , the former is likely to be a limitation of the study as it may lead to greater variability of the estimates of infection intensity and therefore less precision in the mean prediction estimates shown in our maps . Second , all hookworm infections were of low intensity and for that reason we chose to categorize our intensity map for hookworm into <1 epg and ≥1 epg for the generation of the co-intensity map outputs . Whilst the data used are a pre-intervention dataset , the degree to which the observed level of hookworm infection would be obscured by ongoing , small scale and spatially variable interventions efforts as mentioned above is difficult to quantify ( there was some LF control with anthelmintics prior to 2008 ) . However , based on the stratified design of the sampling protocol , we think that the data collected should be a good representation of both schistosomiasis and STHs before the GHS NTD control program was implemented , although some bias may be present in districts not adjacent to Lake Volta as some high hookworm transmission areas may have been missed . While the stratified approach to sampling adopted in our survey is adequate to estimate prevalence of schistosome infections and co-infections , future work should consider balanced spatial sampling schemes which account for geographical differences in other helminth species distributions . The surveys targeted children 5–19 years but the age-intensity profile for both helminth infections are different , with maximum intensity occurring at 10–14 years for schistosomiasis and 20–25 years for hookworm [52] , [53] . In our modeling approach we found statistical support to generate co-infection and co-intensity maps for the 15–19 age group . While this may have been adequate for S . haematobium infection , it may not have been the case for hookworm , and predictive surfaces for this parasite are likely to represent under estimates . However data for the older age groups ( i . e . 20–25 year of age ) were not available . Nevertheless , given that low-intensity infections are not trivial and have been shown to cause significant morbidity , particularly when occurring as co-infections with other parasites [54] , [55] , the resulting predictive co-intensity map when combined with the co-infection map represents a rich source of information for decision makers with the aim of integrated morbidity control in Ghana . A number of potential improvements to the geostatistical approach to modeling co-infection and co-intensity could be adopted in the following ways . First , it has been shown that the diagnostic sensitivity of a single Kato-Katz thick smear or urine slide examination is low due to significant day-to-day and intra-specimen variation [42] and low infection intensities are likely to be missed unless multiple samples over consecutive days are collected [56] , [57] . The predictive ability of our co-infection and intensity models could be improved in future iterations of these maps by modeling diagnostic uncertainty within the MBG framework [58] . Second , the fact that parasite infections and co-infections occur at particular locations in Ghana may partly be due to unmeasured covariates , such as poverty indicators ( e . g . socio-economic status , access to clean water and sanitation ) . While a quarter of the variability in multiple-parasite associations can be explained by factors associated with the domestic environment , environmental factors have been shown to have an important role in driving these associations [59] . However , for remotely-sensed environmental factors included in our models the mean value was used as a proxy for the true environmental exposure distribution of pre-school children included in the analysis . This approach provides a somewhat imprecise measurement of exposure and therefore may result in regression dilution bias arising from imprecise exposure measurement which is most likely to lead to underestimation of the observed environmental effects [60] . Our ecological modeling approach could also be improved by including socio-economic status ( a well known risk factor for infection at small spatial scales [19] ) as a contextual covariate but a high-resolution poverty map for the study area was not available . Alternatively , a better understanding of sub-national variation in co-infection and co-intensity could be achieved in future iterations of our maps by adopting an individual level modeling approach and extending our models to include factors associated with the domestic environment of each child . Finally , although the combined use of the resulting co-infection and co-intensity maps allows delineating areas where highest morbidity could be present , it does not allow estimating the number coinfected with high infection intensity profiles [17] . This feature would be important for resource planning and allocation . This could be achieved by categorizing species infection profiles ( e . g . S . haematobium; hookworm ) by intensity of infection ( high , moderate , low; or by its percentiles ) and combining for each individual the parasite-intensity for one parasite with parasite-intensity with the other parasite . In doing so , the present model could be extended to its multivariate analogue taking into account a multivariate spatial process [61] . The resulting maps would then allow evaluation of the geographical variation of multiple infections of differing intensities , including the estimation of the number of individuals co-infected with different intensities . The combination of co-infection and co-intensity maps allows the identification of sub-groups of the population which play an important role in environmental contamination ( due to high egg ouput ) and are at increased risk of severe morbidity ( due to multiple species , heavy intensity parasite infections [54] , [62] ) . The maps produced by our approach could be used by national program managers as decision-support tools for targeting the geographical delivery of integrated MDA to areas where intense transmission may be occurring and evaluate the progress of the national program . In the future , these maps could be updated in subsequent methodological iterations to incorporate further modeling refinements .
|
Urinary schistosomiasis and hookworm infections cause considerable morbidity in school age children in West Africa . Severe morbidity is predominantly observed in individuals infected with both parasite types and , in particular , with heavy infections . We investigated for the first time the distribution of S . haematobium and hookworm co-infections and distribution of co-intensity of these parasites in Ghana . Bayesian geostatistical models were developed to generate a national co-infection map and national intensity maps for each parasite , using data on S . haematobium and hookworm prevalence and egg concentration ( expressed as eggs per 10 mL of urine for S . haematobium and expressed as eggs per gram of faeces for hookworm ) , collected during a pre-intervention baseline survey in Ghana , 2008 . In contrast with previous findings from the East Africa region , we found that both S . haematobium and hookworm infections are highly focal , resulting in small , localized clusters of co-infection and areas of high co-intensity . Overlaying on a single map the co-infection and the intensity of multiple parasite infections allows identification of areas where parasite environmental contamination and morbidity are at its highest , while providing an evidence base for the assessment of the progress of successive rounds of mass drug administration ( MDA ) in integrated parasitic disease control programs .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
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[
"medicine",
"disease",
"mapping",
"infectious",
"diseases",
"environmental",
"health",
"public",
"health",
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"epidemiology",
"pediatric",
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] |
2011
|
Mapping Helminth Co-Infection and Co-Intensity: Geostatistical Prediction in Ghana
|
Buruli Ulcer ( BU ) is a neglected infectious disease caused by Mycobacterium ulcerans that is responsible for severe necrotizing cutaneous lesions that may be associated with bone involvement . Clinical presentations of BU lesions are classically classified as papules , nodules , plaques and edematous infiltration , ulcer or osteomyelitis . Within these different clinical forms , lesions can be further classified as severe forms based on focality ( multiple lesions ) , lesions’ size ( >15cm diameter ) or WHO Category ( WHO Category 3 lesions ) . There are studies reporting an association between delay in seeking medical care and the development of ulcerative forms of BU or osteomyelitis , but the effect of time-delay on the emergence of lesions classified as severe has not been addressed . To address both issues , and in a cohort of laboratory-confirmed BU cases , 476 patients from a medical center in Allada , Benin , were studied . In this laboratory-confirmed cohort , we validated previous observations , demonstrating that time-delay is statistically related to the clinical form of BU . Indeed , for non-ulcerated forms ( nodule , edema , and plaque ) the median time-delay was 32 . 5 days ( IQR 30 . 0–67 . 5 ) , while for ulcerated forms it was 60 days ( IQR 20 . 0–120 . 0 ) ( p = 0 . 009 ) , and for bone lesions , 365 days ( IQR 228 . 0–548 . 0 ) . On the other hand , we show here that time-delay is not associated with the more severe phenotypes of BU , such as multi-focal lesions ( median 90 days; IQR 56–217 . 5; p = 0 . 09 ) , larger lesions ( diameter >15cm ) ( median 60 days; IQR 30–120; p = 0 . 92 ) or category 3 WHO classification ( median 60 days; IQR 30–150; p = 0 . 20 ) , when compared with unifocal ( median 60 days; IQR 30–90 ) , small lesions ( diameter ≤15cm ) ( median 60 days; IQR 30–90 ) , or WHO category 1+2 lesions ( median 60 days; IQR 30–90 ) , respectively . Our results demonstrate that after an initial period of progression towards ulceration or bone involvement , BU lesions become stable regarding size and focal/multi-focal progression . Therefore , in future studies on BU epidemiology , severe clinical forms should be systematically considered as distinct phenotypes of the same disease and thus subjected to specific risk factor investigation .
Buruli ulcer ( BU ) , caused by Mycobacterium ulcerans , is the third most common mycobacteriosis worldwide , after tuberculosis and leprosy [1] . BU pathogenesis is mediated by mycolactone , a potent polyketide-derived macrolide that triggers apoptotic cell death [2] and is associated with the necrotic nature of the disease [3] . BU mostly affects people in tropical countries in Africa [4] , America [5] , Asia [6] and Australia [7] . Although no official estimate of global incidence is available at present , West Africa is the main endemic area , with 1967 new cases reported by Côte d'Ivoire , Ghana , and Benin in 2013[8] . BU is a devastating necrotising skin infection characterised by pre-ulcerative lesions ( papules , nodules , plaques and edematous infiltration ) , which commonly develop into ulcers with undermined edges and can spread to an entire limb [9] and can also affect the bone ( osteomyelitis ) [10] . Moreover , within these clinical presentations , more aggressive severe forms of BU , such as multiple lesions , larger lesions or higher World Health Organization ( WHO ) categories have been described [11] , although underreported and less understood . Epidemiological studies on M . ulcerans transmission , on BU risk factors and on the host immune status , suggest that the variable frequency of BU and its distinct clinical forms are related to: i ) age; ii ) gender; iii ) preferential anatomical site; iv ) water contact; and v ) regional occurrences [12 , 13 , 14 , 15 , 16] . To date , a reduced number of risk factors underlying the severe BU phenotypes had been reported . HIV co-infection is one of the few examples . Some studies revealed an increased BU prevalence among HIV patients , especially those presenting large lesions and osteomyelitis [17 , 18] . Specifically , low CD4 cell counts were significantly associated with larger lesions and patients with a CD4 cell count below 500 cell/mm3 took twice as long to recover from BU when compared with individuals with a normal CD4 cell count [19] . Other risk factors , such as hypoproteinemia [11] and anemia [20] were also identified to be associated with severe forms of BU disease . In addition , the delay in seeking medical care and the late medical diagnosis of BU have been proposed to account for the disease presentation [21 , 22 , 23 , 24] . In fact , in BU endemic regions the culture and beliefs are powerful factors that affect proper medical intervention , as patients preferentially seek treatment from traditional practitioners , or herbalists [22] . On top of this , the lack of knowledge on the available treatments and their effectiveness , the financial constraints during hospitalisation , fear of treatment , and poor access to health facilities are also important aspects delaying the pursuit of proper treatment [25 , 26] . Indeed , delay in seeking medical care has been previously associated with the distinct BU clinical forms . Taking into consideration that the time from progression of a pre-ulcer to an ulcer is variable and can range from a few weeks to several months ( e . g . estimated average time of 30–90 days ) [27] , it was established that individuals with non-ulcerated forms had a median delay of 30 to 45 days , while individuals with ulcers presented a 60-day delay and patients with osteomyelitis up to 90 days [28] . Thus , the more advanced and destructive ulcerated forms and osteomyelitis are associated with longer delay-periods , while non-ulcerated forms are more common in patients with recent infection [28] , justifying the importance of early diagnosis and treatment for the disease . Nonetheless , more aggressive , severe clinical presentations of BU , such as large lesions ( >15cm in diameter ) and multifocal lesions , have also been described [11] , although the underlying pathological mechanisms are yet unclear [29] . While this can be associated with characteristics of the patient itself ( genetic susceptibility/health status ) or with the virulence of the infecting strain , it is also rational to question the influence of the delay in health seeking on the appearance of the more severe forms of BU . To our knowledge , the latter aspect is yet to be studied . Therefore , to uncover whether the time-lapse between the first remembered symptoms and clinical diagnosis is associated to disease severity , we retrospectively analysed a cohort of 476 laboratory-confirmed BU treated cases discovered in a highly endemic area in Allada , Benin , between 2005 and 2013 .
Ethical approval ( clearance Nu 018 , 20/OCT/2011 ) for integrating studies on BU was obtained from the National Ethical Review Board of the Ministry of Health in Benin , registered under the Number IRB0006860 . The Centre de Dépistage et de Traitement de l'Ulcère de Buruli ( CDTUB ) —Allada and the national BU control program authorities approved access to the registry . All data analyzed in this study was anonymized . We retrospectively collected clinical data from 476 laboratory-confirmed BU patients of CDTUB in Allada , Benin—between January 2005 and December 2013 . At the moment of diagnosis , parameters such as age , gender , major clinical form ( nodule , plaque , edema , ulcer or osteomyelitis ) and multifocal presentations were registered . For mixed clinical forms , the most severe lesion was considered the major clinical form . Additionally , lesion size ( cm , considering major diameter ) , WHO category [30] ( Category 1: maximum lesion diameter <5cm; Category 2: maximum lesion diameter 5–15cm; and Category 3: minimum lesion diameter >15cm associated or not with osteomyelitis and/or multifocal lesions and/or at a critical site ) , lesion site ( upper or lower limb , trunk , head and/or neck ) and laboratory confirmation tests ( culture of M . ulcerans from the lesion , histopathology with the presence of acid-fast bacilli , or highly specific IS2404 real-time PCR ) were taken into consideration . The HIV status was also retained for the present study and excluded from analysis if positive . Delay in seeking medical care ( time between first symptoms or signs remembered and medical attendance ) was also recorded . The time of seeking medical care was defined as the moment of diagnosis and treatment initiation . All included patients completed antibiotherapy according to the WHO recommendations and were treated with surgical procedures [30] . Explanatory and descriptive analysis of the study cohort was performed based on the following variables: age at the moment of the BU diagnosis; gender; clinical form ( ulcer , plaque , edema , nodule and osteomyelitis ) ; lesion site; and lesion severity . Severe phenotypes were defined as multifocal lesions ( more than one lesion ) ; large lesions ( diameter >15cm ) or Category 3 lesions ( minimum lesion diameter >15cm associated or not with osteomyelitis , multifocal lesions and/or at a critical site ) as classified by the WHO recommendations . Median comparisons were performed through one-way ANOVA’s ( Brown-Forsythe and Welch , when applicable ) using age , gender , site of lesion , clinical BU form; and lesion severity as explanatory variables and time-delay seeking medical care ( days , using means and medians distribution in each group ) as a dependent variable . Unadjusted and adjusted ( for age-cutoff value 15 years of age- and gender binary or linear logistic regression models ) odds ratios were then calculated to explore the effects of time-delay in diagnosis into the clinical form of BU lesions , and particularly into severe phenotypes of BU . We systematically fit the model , controlling age ( dichotomized or ordinal ) and gender with the considered time-delay ( to seek medical attendance ) as explanatory variables for each of the clinical lesions and severe phenotypes defined for BU . All the described analyses were obtained using IBM SPSS Statistic v . 22 . A result was considered significant for p<0 . 05 .
The BU cohort ( CDTUB , Allada , Benin ) , comprising 476 cases , had laboratory BU confirmation by at least one laboratory diagnostic test , as recommended by the WHO . Results were positive for IS2404 RT-PCR in 430 ( 90 . 3% ) cases and Ziehl-Neelsen staining in 327 ( 68 . 7% ) cases . All cases were HIV negative . The median age at diagnosis was 12 years ( IQR: 7–24 years; mean 17 . 9 ± 16 . 3 years ) , with 321 ( 67 . 4% ) patients 15 years old or under . Although the overall gender ratio of the patients was balanced ( 245 [51 . 5%] male ) ( Table 1 ) , a major distortion of this ratio was recorded as a function of age , with males being predominant in younger patients and females in older patients ( OR 2 . 99 , 95%CI 2 . 00–4 . 46 , p = 0 . 0001 ) . Specifically , male patients accounted for 193 ( 60 . 1% ) of the patients younger than 15 , but only 52 ( 33 . 5% ) of those were over 15 ( Table 1 ) . Considering the dominant clinical BU form per patient , 4 ( 0 . 8% ) presented nodules ( Fig 1A and 1F and Table 1 ) , 24 ( 5 . 0% ) presented edema ( Fig 1B and 1F and Table 1 ) , 125 ( 26 . 3% ) presented plaques ( Fig 1C and 1F and Table 1 ) , and 320 ( 67 . 2% ) presented ulcers ( Fig 1E and 1F and Table 1 ) . Osteomyelitis was diagnosed in 5 patients ( 1 . 1% ) , and was considered the most relevant form in 3 of the patients ( 0 . 6% ) ( Fig 1E and 1F and Table 1 ) . Concerning the site of lesions , 256 ( 53 . 8% ) patients presented lesions on the lower limbs , while 171 ( 35 . 9% ) had lesions on the upper limbs ( Fig 2 and Table 1 ) . Atypical sites ( head , neck and/or trunk ) accounted for 49 ( 10 . 3% ) patients ( Fig 2 and Table 1 ) . Site of the lesion and relative age , gender and dominant clinical form distribution are represented in Fig 2 . Regarding the observed severe forms of BU , 22 ( 4 . 6% ) patients presented lesions in more than one localization ( Fig 3A and Table 1 ) , while 142 ( 29 . 8% ) patients presented lesions larger than 15cm in major diameter ( Fig 3B and Table 1 ) . The WHO category 3 is a broader classification given that it comprises patients with multiple lesions , lesions with a diameter >15cm associated or not with osteomyelitis and/or lesions at a critical site . Taking into account these criteria , we recorded 315 ( 66 . 2% ) patients in category 1+2 and 161 ( 33 . 8% ) in category 3 ( Fig 3C and Table 1 ) . The different clinical presentations , as well as the severe forms of these lesions , were subjected to age and gender adjustments ( Tables 2 and 3 , respectively ) . No significant interference was recorded in the binary logistic regression , except for upper body lesions ( upper limb , head or neck ) , for which there was an overrepresentation of younger ages ( OR 0 . 986 , 95%CI 0 . 974–0 . 998 , p = 0 . 018 ) ( Table 2 ) . The overall mean time-delay to seek medical care was 101 . 1 days ( 95%CI 86 . 3–117 . 0 ) ( S1 Table ) . Since the variable time-delay does not follow a normal distribution ( Kurtosis = 48 . 2; Skewness = 6 . 4 ) , median variations were considered to compare the distinct behavior of dependent variables . Time-delay to seek medical care was indistinct for male and female gender ( p = 0 . 538 ) ( Fig 4A and S1 Table ) : median was 60 days [IQR 30–90] for both genders . However , age was associated with significantly different delay times ( p = 0 . 004 ) ( Fig 4B and S1 Table ) . Median was 60 days [IQR 30–120] for patients over 15 years old at the moment of the diagnosis; while time-delay was 45 days [IQR 30–90] for patients with 15 years of age or under . Time-delay was also related to the clinical form of the disease ( Fig 5 ) . Median was 32 . 5 days [IQR 30–67 . 5] for non-ulcerated forms ( nodule , edema , and plaque ) ; 60 days [IQR 20 . 0–120 . 0] for ulcerated forms; and 365 days [IQR 228–548] for bone lesions . When the time-delay among patients with non-ulcerated versus ulcerated forms was compared , we confirmed significant discrepancies ( p = 0 . 009 ) ( Fig 5B and S1 Table ) . In addition , among the non-ulcerated clinical forms , edema was significantly associated with longer time-delays when compared with others non-ulcerated forms ( median 45 days , IQR 30–105 versus 30 days , IQR 30–60 , respectively , with p = 0 . 03 ) ( S1 Table ) . Even when age and gender were adjusted in binary logistic regression , we observed an increased risk of developing ulcerative lesions as each day/month passed ( Table 4 ) . Considering severe forms of BU , none of the aggressive phenotypes were considered related to significantly different delay times to seek medical care: multifocal lesions ( median 90 days , IQR 56 . 3–217 . 5 , p = 0 . 09 ) ( Fig 6A and S2 Table ) , larger lesions with diameter >15cm ( median 60 days , IQR 30–120 , p = 0 . 92 ) ( Fig 6B and S2 Table ) or category 3 WHO classification ( median 60 days , IQR 30–150 , p = 0 . 20 ) ( Fig 6C and S2 Table ) , when compared with unifocal ( median 60 days , IQR: 30–90 ) , small lesions ( diameter ≤15cm ) ( median 60 days , IQR 30–90 ) or WHO category 1+2 lesions ( median 60 days , IQR 30–90 ) , respectively ( Fig 6A–6C and S2 Table ) . Finally , when systematically fit within binary ( dichotomized variables ) ( Table 5 ) or linear ( Table 6 ) logistic regression models controlling for age and gender , time-delay to seek medical care remained statistically insignificant with respect to the occurrence of the most aggressive severe clinical forms .
BU pathogenesis is related with necrosis of the subcutaneous tissue associated with mycolactone , the potent cytotoxic/immunosuppressive toxin produced by M . ulcerans [3] . Initial pre-ulcerative lesions ( papules , nodules , plaques and edematous infiltration ) can evolve into ulcers and progressively spread over significant extensions of the body [9] or even affect the bone [10] . Large national studies in West African countries , namely Ghana [31] , Benin [28 , 29 , 32] and Côte D`Ivoire [33] , included the largest BU cohorts studied thus far and provided information about the age and gender of patients , site of lesions and the major clinical forms—providing further clues on the evolution of BU pathology . The majority of these studies used distinct methodologies ( retrospective and/or prospective cohorts; cross-sectional ) and a descriptive approach , with a large proportion of diagnoses being retrospective and scar-based . Here , we strictly consider laboratory-confirmed BU patients . Concerning the BU clinical forms ( papules , nodules , plaques , edematous infiltration , ulcers and osteomyelitis ) , the observations of our study globally fit the variances reported in those larger cohorts . Specifically , we confirm that BU is mainly a paediatric disease ( median age of diagnosis 12 years with IQR: 7–24 years and mean of 19 . 7 years ) ; with a predominance of lesions on the lower limbs ( 53 . 8% ) ; a predominance of ulcerative forms ( 67 . 2% ) ; and with an equilibrium between genders . In addition , there is a distinct distribution of gender when age is considered , with males being overrepresented in younger patients , reproducing data from previous studies [15 , 29] . Osteomyelitis and edematous forms are classified as belonging to the spectrum of BU presentations , although some authors consider them to be more severe clinical forms [32 , 34 , 35 , 36] . Regarding osteomyelitis , a great variance in prevalence is described and further complexity is added when suspected non-confirmed cases of bone involvement are included in the analysis . Indeed , reported prevalence values of bone disease related to BU were as high as 29 . 5% [37] and 36 . 1% [38] . However , when only confirmed osteomyelitis cases were considered , prevalence decreased with values ranging between 6% [29] and 20% [39] in Africa and only 1% in Australia [40] . Moreover , HIV infection seems to favour the occurrence of osteomyelitis [17] . In the present study , osteomyelitis lesions only occurred in 1 . 1% of the at-risk population , which could be related to the fulfillment of confirmed diagnosis criteria ( e . g . x-ray or surgical evidence ) and the absence of the HIV co-infection selection criteria . Eedematous lesions manifest as diffuse , extensive , usually non-pitting swelling with ill-defined margins involving part or all of a limb or other part of the body [41] . Cases of edematous M . ulcerans infection can be misdiagnosed as bacterial cellulitis leading to delays in diagnosis , progression of disease , increased morbidity and increased complexity and cost of treatment . Additionally , edema is often self-perceived as not being a relevant health problem , therefore delaying seeking medical attention . In previous studies , prevalence was determined to be between 2 . 5% [42] and 12 . 5% [31] . In our study , edematous forms accounted for 5% of the studied population , fitting with the prevalence reported in similar cohorts [31 , 34 , 35 , 36 , 42] . Within to the above described clinical BU presentations , more aggressive , severe clinical presentations have been described [11] , although the underlying pathological mechanisms are yet unclear [29] . In our study , within the severe phenotypes , 33 . 8% of the patients were in WHO category 3; 4 . 5% presented multifocal forms; and 29 . 8% of the patients presented lesions >15cm in major diameter . Regarding multifocal lesions , previous studies describe highly variable prevalences ( e . g . 2 . 0% -11 . 1% ) [40 , 42 , 43 , 44 , 45 , 46] . Moreover , in our African cohort , we verify that age does not associate with multifocal lesions , conversely to an Australian cohort [40] . Regarding lesion size , only a few studies report large lesions as a specified studied variable , since these lesions are usually included in category 3 lesions . However , when considered separately , their prevalence ranged between 11 . 1% [47] and 36 . 0% [29] , while category 3 lesions have been reported to range between 19 . 7% [48] and 60 . 0% [39]–values replicated in the present study . The effect of time-delay in seeking medical care for BU patients is a relevant issue for public health and patient management . Our observations in a cohort of laboratory-confirmed cases of BU show that gender was not related with distinct behavior in seeking specific medical care and that younger patients , mainly through their parents/legal tutors , spent less time seeking medical attention prior to diagnosis ( median 45 versus 60 days , for the group ≤15 years old versus >15 years old respectively , p = 0 . 004 ) . In line with previous African studies , we found that more advanced ulcerative forms were related to the delay in seeking medical care . Remarkably , and contrary to what one would expect , we found that multifocal lesions , larger lesions or WHO category 3 lesions may be considered distinct clinical entities since the time-delay in seeking medical attention had no significant role in disease progression . As a matter of fact , in Africa , time-delay was seen as a marker of accessibility to medical care and , in fact , some studies compare time-lapse before and after interventional politics on health care improvement . In West Africa , studies reported a time-delay between 42 [38] and 84 days [44 , 49] , taking into consideration all clinical forms . Specifically , a Beninese study reported distinct clinical forms relating to time-lapse since first symptoms were remembered [28] . Time-delay was shorter for non-ulcerated clinical forms ( median 30 to 46 days ) , than for ulcerated forms ( median 61 days ) and larger for osteomyelitis ( median 91 days ) . In Australian studies , time-lapse until medical care was reported to be much shorter—between 14 days ( IQR 0–6 weeks ) [40] and 42 days ( ranging from 2 and 270 days ) [50] . In this distinct health-care reality , determinants for delay in seeking medical care were related to atypical sites of lesions , associated with an increased complexity in medical BU diagnosis . Interestingly , in Australian patients , ulcerated versus non-ulcerated clinical forms did not experience significantly different time lapses . Moreover , independently of the advances in diagnosis and clinical management , there was no variation in time-delay between 1998–2004 and 2005–2011 . In Southern America , the time-delay reported among Peruvian BU patients was between 1 and 8 months [51] . Overall , our observations in a cohort of laboratory-confirmed cases of BU , strengthening previous observations and show that the time-delay in seeking medical care is related to the more advanced ulcerative forms , further justifying early diagnosis and treatment . Notably , we additionally show that time-delay was not significantly associated with more severe phenotypes of BU , such as multifocal lesions , larger lesions or WHO category 3 lesions . Indeed , our results demonstrate that after initial progression lesions become stable regarding size and focal/multifocal progression . Therefore , in future studies on BU epidemiology , severe clinical forms should be systematically considered as distinct phenotypes of the same disease and therefore subjected to specific risk factor investigation . These results further highlight that intrinsic regulatory mechanisms , such as the host immune response and local biochemical and physical factors , most likely have relevant roles in determining severe phenotypes , justifying more structural immune-related and bacterial genetic studies .
|
Buruli Ulcer ( BU ) is a neglected disease caused by Mycobacterium ulcerans . Clinical presentations of BU lesions are classically classified as papules , nodules , plaques and edematous infiltration , ulcer or osteomyelitis . Within these different clinical forms , lesions can be further classified as severe forms based on focality ( multiple lesions ) , lesions’ size ( >15cm diameter ) or WHO Category ( WHO Category 3 lesions ) . There are studies reporting an association between delay in seeking medical care and the development of ulcerative forms of BU or osteomyelitis , but the effect of time-delay on the emergence of lesions classified as severe has not been addressed . To address both issues , and in a cohort of laboratory-confirmed BU cases , 476 patients from a medical center in Allada , Benin , were studied . In our cohort , we validated previous observations , demonstrating that time-delay is statistically related to the clinical form of BU , namely ulcers and osteomyelitis . However , time-delay is not related with more severe phenotypes , implying that severe clinical forms of BU should be considered as distinct phenotypes of the same disease and subjected to specific risk factor investigation .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
Clinical Epidemiology of Buruli Ulcer from Benin (2005-2013): Effect of Time-Delay to Diagnosis on Clinical Forms and Severe Phenotypes
|
Trypanosoma vivax is one of the causative agents of Animal African Trypanosomosis in cattle , which is endemic in sub-Saharan Africa and transmitted primarily by the bite of the tsetse fly vector . The parasite can also be mechanically transmitted , and this has allowed its spread to South America . Diagnostics are limited for this parasite and in farm settings diagnosis is mainly symptom-based . We set out to identify , using a proteomic approach , candidate diagnostic antigens to develop into an easy to use pen-side lateral flow test device . Two related members the invariant surface glycoprotein family , TvY486_0045500 and TvY486_0019690 , were selected . Segments of these antigens , lacking N-terminal signal peptides and C-terminal transmembrane domains , were expressed in E . coli . Both were developed into ELISA tests and one of them , TvY486_0045500 , was developed into a lateral flow test prototype . The tests were all evaluated blind with 113 randomised serum samples , taken from 37 calves before and after infection with T . vivax or T . congolense . The TvY486_0045500 and TvY486_0019690 ELISA tests gave identical sensitivity and specificity values for T . vivax infection of 94 . 5% ( 95% CI , 86 . 5% to 98 . 5% ) and 88 . 0% ( 95% CI , 75 . 7% to 95 . 5% ) , respectively , and the TvY486_0045500 lateral flow test prototype a sensitivity and specificity of 92 . 0% ( 95% CI , 83 . 4% to 97 . 0% ) and 89 . 8% ( 95% CI , 77 . 8% to 96 . 6% ) , respectively . These data suggest that recombinant TvY486_0045500 shows promise for the development of a pen-side lateral flow test for the diagnosis of T . vivax animal African trypanosomosis .
Trypanosoma vivax is a protozoan parasite of the genus trypanosomatidae spread primarily by biting insects . Together with T . brucei and T . congolense , it is a causative agent of Animal African Trypanosomosis ( AAT ) in cattle . T . vivax causes a severe version of AAT , often characterised by hemorrhagic fever as well as the more typical weight loss , fatigue and anaemia [1] . As T . vivax does not require midgut gestation within the vector it can be can be transmitted mechanically by body fluid contamination and hematophagous flies [2 , 3] . This has allowed the spread of the disease in South America , an area previously free from T . vivax . Over eleven million cattle are estimated to be at risk in this region [4] in addition to the 46 million cattle at risk in sub-Saharan Africa [5] . Diagnostics are limited for this parasite , relying principally on microscopy , specific antibody detection using whole parasite lysates as target antigen [6] or PCR that requires specialised equipment [7 , 8] . Recently , the use of heterologous soluble form variant surface glycoproteins ( VSGs ) , such as T . evansi RoTat1 . 2 and T . equiperdum p64 , as cross-reactive diagnostic antigens for T . vivax cattle infections has been described [9] and these may lead to new diagnostic tools . Nevertheless , at the moment , farmers mostly rely upon symptom-based diagnosis , which is complicated by the numerous other diseases with similar manifestations in the endemic regions . With this in mind , we set out to develop a low-cost pen-side diagnostic test for T . vivax infections in cattle using lateral flow test ( LFT ) technology . We used the approach of identifying parasite antigens selectively recognised by cattle infection sera by proteomics , followed by recombinant protein expression in E . coli and antigen assessment by ELISA to select an antigen for LFT prototyping . This general approach has been successful for selecting diagnostic antigens for human T . brucei gambiense and cattle T . congolense infections [10–12] . One of these antigens , a recombinant invariant surface glycoprotein ( rISG65-1 ) , has been selected by the Foundation for Innovative New Diagnostics ( FIND ) for development of a next-generation ‘all recombinant’ LFT for human African trypanosomiasis . Here , we report the identification , recombinant production and evaluation by ELISA of segments of two related invariant surface glycoprotein ( ISG ) diagnostic antigens for AAT caused by T . vivax , and the generation and evaluation of a prototype LFT with one of them .
Rodents were used to propagate sufficient T . vivax parasites to make the detergent lysates for immunoaffinity chromatography and proteomics . The animal procedures were carried out according the United Kingdom Animals ( Scientific Procedures ) Act 1986 and according to specific protocols approved by The University of Dundee Ethics Committee and as defined and approved in the UK Home Office Project License PPL 60/3836 held by MAJF . Cattle studies were approved by the ClinVet IACUC which complies with The South African National Standard: SANS 10386:2008: The care and use of animals for scientific purposes . All sera were provided by GALVmed . The sera used for the antigen identification by immunoprecipitation and proteomics were from four animals obtained commercially in Burkina Faso and treated prophylactically for T . vivax infections before experimental infection with T . vivax . Further sera , including 113 samples for ELISA and LFT blind testing , were obtained from Burkina Faso , Mozambique and South Africa , the latter were all from cattle raised under fly-nets . Of the 113 sera for blind testing: The Burkina Faso samples ( 21 sera ) were from 4 calves and consisted of 4 pre-infection and 17 T . vivax post-infection sera . The Mozambique samples ( 20 sera ) were from 2 calves and consisted of 20 T . vivax post-infection sera . The South Africa ( ClinVet ) samples ( 72 sera ) were from 31 calves and consisted of 27 pre-infection and 32 T . vivax post-infection sera and 13 T . congolense post-infection sera . Strains used to infect cattle ( one isolate per calf ) were: In Mozambique , Y486 and IL700 . In Burkina Faso , Sokoroni 18 , Napie22 , Komborodougou and Gondo Bengaly . At ClinVet , ILRAD560 . Sera were collected in Burkina Faso from four calves before and 28 days after experimental infection with T . vivax . Aliquots ( 250 μl ) of the pre- and post-infection sera were pooled and IgG fractions were purified on protein-G Sepharose , as previously described [11 , 13] . Purified IgG was coupled to CNBr-activated Sepharose 4B ( GE Healthcare ) at 4 mg IgG per milliliter of packed gel , according the manufacturer’s instructions . Three BALB/c mice were injected with one stabilate of T . vivax ILRAD V34 . After five days , infected mouse blood was harvested with citrate anticoagulant , adjusted to 5×104 parasites per ml with phosphate-buffered saline ( PBS ) and aliquots of 0 . 2 ml were injected into the peritoneal cavity of 45 NMR1 mice . The mouse blood was harvested after 7 days and the parasites were purified by centrifugation , to yield a buffy coat enriched in trypanosomes , followed by DE52 ion exchange chromatography to remove white blood cells and residual erythrocytes , as described in [11 , 13] . The purified trypanosomes were dissolved at 1 x 109 cells . mL-1 in 50 mM sodium phosphate buffer , pH 7 . 2 , 2% n-octyl-β-D-glucopyranoside ( nOG ) detergent containing 1X Roche protease cocktail minus EDTA as well as 1 mM phenylmethylsulfonyl fluoride ( PMSF ) , 0 . 1 mM N-p-tosyl-L-lysine chloromethyl ketone ( TLCK ) , 1 μg . mL-1 leupeptin and aprotinin . The latter protease inhibitor cocktail is efficient in protecting trypanosome proteins from proteolysis in detergent lysates for immunoprecipitation [14] . The lysate was incubated for 30 min on ice and then centrifuged at 100 , 000 g for 1 h at 4°C . Aliquots of T . vivax detergent lysate ( 10 ml ) were incubated with 0 . 75 ml packed volume of each of the 4 mg . ml-1 Sepharose-IgG ( infection and non-infection/control ) gels , rotating for 3 h at 4°C . The gels were then packed into disposable 10 ml columns and washed with 10 ml of 10 mM Na2PO4 , pH 7 . 2 , 200 mM NaCl , 1% nOG , followed by 10 ml of 5 mM Na2PO4 pH 7 . 2 , 1% nOG . The trypanosome proteins were eluted with 500 μl of 50 mM sodium citrate , pH 2 . 8 , 1% nOG into tubes containing 100 μl of 1 M Tris pH 8 . 5 for neutralization . The eluates were further concentrated to 270 μl using a centrifugal concentrator ( Millipore , 0 . 5 ml capacity with 10 kDa MW cut off membrane ) . The concentrates containing the trypanosome proteins were then transferred to low binding Eppendorf tubes and the proteins precipitated by adding 1 ml ice-cold ethanol and incubation for 24 h at −20°C . Following ethanol precipitation , the proteins eluted from the post-infection IgG and pre-infection IgG columns were dissolved in SDS sample buffer , reduced with DTT and run on a precast 4–12% Bis-Tris gradient SDS-PAGE ( Invitrogen ) using the MES running system . The gel was stained with colloidal Coomassie blue and equivalent regions of the infection and control lanes were cut out , reduced and alkylated with iodoacetamide and digested in-gel with trypsin . The tryptic peptides were analysed by LC-MS/MS on a Thermo Orbitrap Velos system and MaxQuant 1 . 4 software was used to match peptides to the predicted trypanosome protein databases [15] . Where possible , annotated gene names , or the names of homologues identified using BLASTp [16] or the protein fold/family identified with Pfam [17] , were used ( S1 Table ) . The program MaxQuant 1 . 4 was also used to obtain relative intensity data of the peptides recovered from the post-infection and pre-infection ( control ) IgG columns . A DNA construct encoding residues 42–363 of TvY486_0019690 was amplified from T . vivax ( strain ILRAD V34 ) genomic DNA using the forward and reverse primers 5’-CATATGGAGAATGAGATTGCTCGGG-3’ and 5’-GGATCCAATGCTGAGTTTGCTATTGTTAGCTGA-3’ , respectively , where the underlined bases are the Nde1 and BamH1 cloning restriction sites . The gene TvY486__0045500 , which is very similar in sequence to TvY486_0019690 , could not be selectively amplified and a construct encoding residues 40–363 was instead synthesised by GenScript and optimised to avoid rare codon combinations in E . coli , unfavourable mRNA structures for protein expression and cis elements . The gene was obtained in a pUC vector with restriction sites ( Nde1 and BamH1 ) in place for downstream cloning . Both constructs were ligated into pCR2 . 1-TOPO using the TOPO TA Cloning Kit ( Invitrogen ) and then inserted into a pET15b-derived plasmid ( Novagen ) modified to include a tobacco etch virus ( TEV ) protease cleavage site between the N-terminal hexahistidine affinity tag and the protein sequence of interest . Recombinant gene expression of the TvY486_0045500 construct was achieved with E . coli BL21-CodonPlus ( DE3 ) RIPL cells ( Stratagene ) in autoinduction medium [18] containing 50 μg mL-1 ampicillin and 12 μg mL-1 chloramphenicol . The construct for TvY486_0019690 was expressed in BL21 ( DE3 ) Gold cells ( Stratagene ) in autoinduction medium containing 50 μg mL-1 ampicillian . Cells were cultured for 24 h at 22°C before harvesting by centrifugation ( 3 , 500 x g , 30 min , 4°C ) the bacterial pellet was resuspended in buffer A ( 50 mM Tris-HCl , pH 7 . 5 , 250 mM NaCl ) containing an EDTA-free protease inhibitor cocktail ( Roche ) . Purification was achieved using the methods described in [19] . Briefly , E . coli cells were mechanically lysed in the presence of DNAse than clarified by centrifugation ( 4°C , 40 min , 30 , 000 g ) . The proteins were captured using a 5 ml immobilised metal affinity chromatography ( IMAC ) ( HisTrap GE Healthcare ) and eluted with an imidazole gradient . Affinity tags were removed , via proteolytic cleavage ( 1 mg His6-TEV protease per 20 mg protein , 4 ˚C , 16 h ) and the protein dialysed into buffer A ( 50 mM Tris-HCl , pH 7 . 5 , 250 mM NaCl ) . The protease , uncleaved protein and affinity tag contaminants were removed with a further subtractive IMAC step . Final purification was achieved by size exclusion chromatography ( Superdex 200 26/60 ) eluted with buffer A . Finally , proteins were dialysed into PBS and adjusted to at least 1 mg . ml-1 using 10 kDa cut-off centrifugal concentrators . All proteins were >95% pure , as judged by sodium dodecyl sulphate polyacrylamide gel electrophoresis ( SDS PAGE ) and Coomassie blue staining . White polystyrene Costar untreated 96 well plates were coated with 50 μl per well of target protein at a concentration of 2μg mL-1 in plating buffer ( 0 . 05 M NaHCO3 , pH 9 . 6 ) then blocked with 200 μl of PBS containing 5% bovine serum albumin ( BSA ) and 0 . 1% Tween-20 overnight at 4°C . Calf sera were diluted 1:2500 in PBS containing 5% BSA , 0 . 1% Tween-20 and transferred in triplicate by a liquid handling device ( Bio-Tek , Precision ) to the ELISA plates and incubated for 1h at room temperature . After 1 h the diluted sera were aspirated and the wells were washed with PBS containing 0 . 1% BSA with the liquid handling device . This wash cycle was repeated 5 times . Biotinylated anti-bovine-IgG ( Jackson labs ) was added at dilution of 1:4000 ( 50 μl per well ) and incubated for 1 h . Excess anti-bovine-IgG antibody was washed away ( as described before ) and 50 μl per well of ExtrAvidin-Horse Radish Peroxidase ( HRP ) at a dilution of 1:4000 was added to the plates and incubated for 1 h . The solution was aspirated and the wash steps were repeated . Finally , chemiluminescent super signal Femto substrate ( Pierce ) diluted 1:5 ( i . e . , 0 . 5 ml solution A , 0 . 5 ml solution B with 4 ml PBS ) was applied to the wells at 50 μl per well and plates were read using an Envision plate reader within 5 minutes of addition of the substrate . Purified recombinant TvY486_0045500 residues 40–363 ( 7 . 5 mg ) were provided to BBI-Solutions , an immunoassay development and manufacturing company that has completed more than 250 lateral flow projects over the last 25 years , with manufacturing sites in Europe , USA and South Africa , and 2400 prototype LFT devices were manufactured . The LFT is comprised of a sample pad , conjugate pad , nitrocellulose strip and top pad all attached to a backing card and housed within a plastic cassette . The sample is applied to the sample pad ( followed by a chase buffer ) that then flows onto the conjugate pad which contains 2 gold conjugates , a test conjugate that has p310 antigens bound to gold colloid , and a control conjugate that has an irrelevant ( for the p310 detection system ) antibody bound to gold colloid . The sample flows up the test strip and solubilizes the gold conjugates which then flow up the assay on to a nitrocellulose strip that has a p310 antigen line striped at the test line position . If it is a positive sample , anti-p310 antibodies within the sample will bind the p310 antigen test line and will have also bound the p310 antigen gold conjugate . This results in the p310 antigen gold conjugate being localized at the test line , due to a p310 antigen-anti p310 antibody-p310 antigen “sandwich” binding reaction . The accumulation of the gold conjugate will eventually become visible to the end user if the sample contains sufficient anti-p310 antibodies . If the sample is negative there will be no anti-p310 antibodies present and so no accumulation of gold colloid at the test line and so a test line will not appear . The sample/conjugate solution will flow past the test line and the irrelevant gold conjugate will bind at a control line and form a visible line , which is specific to the irrelevant gold conjugate , thus demonstrating successful flow of the sample and conjugates up the lateral flow assay . The sample/conjugates will then move in to the top pad of the lateral flow assay that ensures the solution flows unidirectionally along the assay . Triplicate aliquots of 5 μl of calf sera diluted with 15 μl of PBS were added to the LFTs followed by an 80 μl of chase-buffer ( PBS containing 0 . 05% Tween 20 ) . Tests were discarded if upper control line was not clearly visible . After 30 min , scoring of the test bands was performed by visual comparison of freshly completed tests with a scoring card [20] ( S2 Fig ) and the consensus score from three devices for each serum was recorded . After reading , the nitrocellulose test strips were taken out their cases for photography .
An immunoprecipitation experiment was carried out to identify candidate diagnostic antigens for T . vivax . Pooled pre-infection ( day -7 ) and post-infection ( day +28 ) calf sera from four animals from Burkina Faso were used to generate IgG antibody columns . Detergent lysate of bloodstream form T . vivax cells was generated from parasites recovered from mice infected with T . vivax strain ILRAD V34 . Identical amounts of parasite detergent lysate were mixed with the pre-infection and post-infection Sepharose-IgG beads and proteins bound to the washed beads were eluted with low pH to break antibody-antigen interactions . The eluted samples from the pre-infection and post-infection columns were concentrated and subjected to SDS-PAGE gels for antigen separation . The pre-infection and post-infection eluates were run on separate SDS-PAGE gels to reduce potential antigen cross-contamination . The Coomassie blue stained gel lanes were cut into ten segments and each subjected to in-gel reduction and alkylation and trypsin digestion . The peptides from each gel slice were separately analysed by LC-MS/MS and the data concatenated for the pre-infection and post-infection eluate samples , respectively . These concatenated data sets were used to search the predicted protein database for T . vivax ( Y486 ) using MaxQuant 1 . 4 . Many proteins ( >1300 ) were identified in the combined data from each of the Sepharose-IgG eluates . However , the protein identification lists were sorted to select for proteins found either uniquely in the post-infection Sepharose-IgG eluate or that were >10 fold enriched in the post-infection Sepharose-IgG column eluate , as judged using the label-free quantification function in MaxQuant 1 . 4 [21] , ( S1 Table ) . Of the twenty-three proteins unique to the post-infection IgG eluate , all had low LC-MS/MS intensities suggesting that the immune response to these antigens , while specific , was low [10 , 11] . Eleven proteins had infection: control intensity ratios >10 . Two of these stood out as possible immunodiagnostic antigens , TvY486_0045500 and TvY486_0019690 . These are two closely related proteins sharing 91% and 80% amino acid sequence similarity and identity , respectively . These proteins have a typical ISG domain structure , consisting of an N-terminal signal peptide , an ISG domain , a transmembrane domain and a small intracellular domain [22] . We chose to investigate these antigens because ISGs have previously proved to be good diagnostics antigens for T . brucei , T . congolonse and T . evansi [10–12] . Similar segments of TvY486_0045500 ( amino acid residues 40–363 ) and TvY486_0019690 ( amino acid residues 42–363 ) , avoiding the N-terminal signal peptides and C-terminal transmembrane domains , were cloned and expressed with cleavable hexa-histidine tags in E . coli . Following nickel affinity purification and proteolytic cleavage of the hexa-histidine tags , monodisperse forms of both proteins collected from a subsequent gel-filtration purification step ( and separated from aggregated material appearing at the void volume ) with a final yield of 0 . 6 mg . L-1 for TvY486_0019690 and 4 mg . L-1 for TvY486_0045500 . The predicted amino acid sequences of the two recombinant proteins are shown in ( S1 Fig ) . The two purified recombinant proteins were used to coat ELISA plates and tested with the sera of 14 calves that had been collected pre- ( day -7 ) and post- ( day +28 ) experimental infection with T . vivax at the ClinVet site . These data ( Fig 1 ) indicated that both recombinant TvY486_0045500 and TvY486_0019690 coated ELISA plates could discriminate infected from uninfected sera . TvY486_0045500 ( residues 40–363 ) was selected for the manufacture of a prototype lateral flow device , because of its relative ease of protein expression , and was supplied to BBI Solutions ( Dundee , http://www . bbisolutions . com/ ) . Both the TvY486_0045500 and TvY486_0019690 coated ELISA plates , and the TvY486_0045500 LFT prototype , were tested in triplicate with 113 randomised cattle sera provided by GALVmed . After data collection , the sera codes were broken and the data are collated in ( S2 Table ) . Sera were classified as being either from uninfected animals or from animals that had been exposed to experimental T . vivax infection . Based on this classification , there were 69 infection ( positive ) and 44 control ( negative ) sera . Cut-off values for maximum positive/negative discrimination were determined ( 600 , 000 and 1 , 100 , 000 units for the TvY486_0045500 and TvY486_0019690 ELISA plates , respectively , and > = 2 units for the LFT ) and , using these cut-offs , the sensitivity and specificity data were determined ( Table 1 ) . Representative LFT data are shown in ( Fig 2 ) and the results of all 113 tests are shown in ( S2 Fig ) .
In this study , we used quantitative proteomics to identify candidate diagnostic antigens , i . e . , those proteins in whole T . vivax detergent lysate that bound selectively ( >10 fold more ) to the immobilised IgG from calves experimentally infected for 28 days with T . vivax versus immobilised IgG from the same animals collected 7 days prior to experimental infection . In total , we found 34 candidate protein groups but rejected most of these based on the low intensities of their combined peptide ions in the LC-MS/MS analyses ( we interpret low peptide intensities as an indication that only a small proportion of infection-specific IgG is directed towards their parent antigens [10 , 11] ) . The two proteins that produced the most intense peptides , and significant ( around 30-fold ) enrichment , were two related ISGs . We therefore focussed on these proteins and made recombinant versions in E . coli that lack the predicted cleavable N-terminal signal peptides and the predicted C-terminal transmembrane and short cytoplasmic domains . Both recombinant proteins were immunoreactive with pooled T . vivax infection sera and both antigens were subsequently tested in ELISA format against 113 randomised calf sera and found to have identical overall performance in terms of sensitivity and specificity ( Table 1 ) . Further , the Pearson coefficient between the two ELISA data sets was 0 . 9876 , indicating that there is nothing to choose between the two antigens with respect to immunodiagnostic potential . The antigen that expressed most efficiently in E . coli ( TvY486_0045500 ) was used to make a prototype LFT device and this was also tested blind with the same 113 randomised sera . Upon breaking the code , it became clear that we could obtain maximum discrimination between T . vivax positive and negative sera by setting the visual score cut-off at > = 2 ( Fig 2 ) and , using these criteria , the sensitivity and specificity of the prototype LFT was similar to that of the ELISA ( Table 1 ) . These are promising performance results considering that the prototype LFT was not optimised with respect to antigen density on the test strip , antigen-gold conjugation or chase-buffer composition which , individually or collectively , should allow a reduction in background ( false positive ) scores of 0 . 5 and 1 for some sera . Of note is that 13 of the T . vivax negative sera were from calves experimentally infected with T . congolense . None of these 13 sera gave a positive reaction with the T . vivax ISGs , either by ELISA or LFT , suggesting that the T . vivax ISGs do not routinely cross-react with T . congolense infection sera . This lack of cross-reactivity with T . congolense ( and likely with other trypanosome species such as T . b . brucei ) is expected , given that BLASTp [15] searches with the TvY486_0045500 predicted amino acid sequence does not return any significant hits against trypansomatid predicted protein databases , other than for T . vivax , [15 , 22] . This is in contrast to , for example , the GM6 antigen ( also recently developed into an LFT ) that cross-reacts with the sera from cattle infected with multiple trypanosome species [23 , 24] . Both of these properties are useful , the latter with respect to making a pan-specific cattle AAT diagnostic and the former as a component of a pathogen-identifying diagnostic . It is also worth noting that BLASTp searches with the TvY486_0045500 predicted amino acid sequence does not return significant hits against any predicted protein databases , other than for T . vivax , suggesting that cross-reactivity with other non-trypanosomatid cattle pathogens is also unlikely .
|
African Animal Trypanosomosis presents a significant problem for agricultural development in sub-Saharan Africa and leads to large economic losses . One of the main parasites responsible is Trypanosoma vivax . Current diagnostic methods are either symptom-based or too costly and technologically demanding for use in endemic regions . Here , we identified T . vivax proteins selectively recognized by infected cattle sera and developed two related proteins into ELISA tests and one of these into a lateral flow test prototype . All three tests performed well when tested against randomised calf sera , suggesting good potential for the development of a pen-side T . vivax animal African trypanosomosis diagnostic device for use in endemic regions .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"livestock",
"medicine",
"and",
"health",
"sciences",
"enzyme-linked",
"immunoassays",
"ruminants",
"engineering",
"and",
"technology",
"vertebrates",
"parasitic",
"diseases",
"animals",
"mammals",
"veterinary",
"diagnostics",
"immunologic",
"techniques",
"veterinary",
"science",
"veterinary",
"medicine",
"research",
"and",
"analysis",
"methods",
"prototypes",
"technology",
"development",
"proteins",
"immunoassays",
"recombinant",
"proteins",
"proteomics",
"agriculture",
"biochemistry",
"diagnostic",
"medicine",
"biology",
"and",
"life",
"sciences",
"cattle",
"amniotes",
"bovines",
"organisms"
] |
2016
|
Proteomic Identification of Immunodiagnostic Antigens for Trypanosoma vivax Infections in Cattle and Generation of a Proof-of-Concept Lateral Flow Test Diagnostic Device
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We have identified a large expansion of an ATTCT repeat within intron 9 of ATXN10 on chromosome 22q13 . 31 as the genetic mutation of spinocerebellar ataxia type 10 ( SCA10 ) . Our subsequent studies indicated that neither a gain nor a loss of function of ataxin 10 is likely the major pathogenic mechanism of SCA10 . Here , using SCA10 cells , and transfected cells and transgenic mouse brain expressing expanded intronic AUUCU repeats as disease models , we show evidence for a key pathogenic molecular mechanism of SCA10 . First , we studied the fate of the mutant repeat RNA by in situ hybridization . A Cy3- ( AGAAU ) 10 riboprobe detected expanded AUUCU repeats aggregated in foci in SCA10 cells . Pull-down and co-immunoprecipitation data suggested that expanded AUUCU repeats within the spliced intronic sequence strongly bind to hnRNP K . Co-localization of hnRNP K and the AUUCU repeat aggregates in the transgenic mouse brain and transfected cells confirmed this interaction . To examine the impact of this interaction on hnRNP K function , we performed RT–PCR analysis of a splicing-regulatory target of hnRNP K , and found diminished hnRNP K activity in SCA10 cells . Cells expressing expanded AUUCU repeats underwent apoptosis , which accompanied massive translocation of PKCδ to mitochondria and activation of caspase 3 . Importantly , siRNA–mediated hnRNP K deficiency also caused the same apoptotic event in otherwise normal cells , and over-expression of hnRNP K rescued cells expressing expanded AUUCU repeats from apoptosis , suggesting that the loss of function of hnRNP K plays a key role in cell death of SCA10 . These results suggest that the expanded AUUCU–repeat in the intronic RNA undergoes normal transcription and splicing , but causes apoptosis via an activation cascade involving a loss of hnRNP K activities , massive translocation of PKCδ to mitochondria , and caspase 3 activation .
Spinocerebellar ataxia type 10 ( SCA10 ) is an autosomal dominant neurodegenerative disease presented with progressive pancerebellar ataxia , leading to total disability [1]–[4] . Approximately 60% of the SCA10 patients also suffer from epilepsy with complex partial seizures and generalized tonic-clonic seizures , which become life-threatening due to development of status epilepticus [3]–[5] . The disease-causing genetic mutation is a large ( up to 22 . 5 kb ) expansion of a pentanucleotide , ATTCT , repeat present within the ninth intron of the ATXN10 gene on chromosome 22q13 . 31 [6] . In the last two decades , investigators identified a group of diseases caused by expansions of short tandem repeats , also known as microsatellite repeats . Most of these mutations involve unstable trinucleotide repeats located in different regions of respective genes . The roles of repeat expansion mutations in the pathogenic mechanism of these diseases are diverse and complex [7] , [8] . However , in a simplistic view an expanded repeat in the coding region produces an elongated tract of repetitive amino acid residues with a gain of toxic function at the protein level , whereas a triplet repeat expansion in 5′- and 3′-untranslated regions ( UTR ) may result in an altered transcription level of the gene or a production of toxic RNA transcript containing expanded ribonucleotide triplets . Friedreich's ataxia ( FRDA ) is the only known disease caused by an expansion of an intronic trinucleotide repeat . Typical FRDA mutations are large GAA repeats located in intron 1 of the FXN gene , which severely hinders the transcription of the FXN gene , leading to the autosomal recessive phenotype [9] . SCA10 and myotonic dystrophy type 2 ( DM2 ) are only human diseases caused by non-trinucleotide microsatellite expansion mutations although an insertion of a large pentanucleotide repeat has recently been reported to be associated with SCA31 [10] . In DM2 the mutation is a large ( up to 44 kb ) expansion of CCTG tetranucleotide repeat in intron 1 of the ZNF9 gene . Thus , it is an interesting coincidence that non-trinucleotide mutations in DM2 and SCA10 are both large expansions located in an intron and causing autosomal dominant phenotypes . In DM2 , expanded CCUG tetranucleotide repeat transcripts accumulate mostly in nuclear foci , and sequestrate the muscleblind like 1 ( MBNL1 ) protein into the RNA foci [11] , [12] . The resultant depletion of MBNL1 causes splicing dysregulation of a variety of RNA transcritpts similar to DM1 . Splicing misregulation is thought to be the primary pathogenic mechanism in DM1 and DM2 . In SCA10 the number of ATTCT repeats ranges from 10 to 29 in normal individuals , and increases up to 4 , 500 in patients [13] , [14] . The ATXN10 gene consists of 12 exons spanning 172 . 8 kb , and encodes ataxin 10 , which contains two armadillo repeats known to mediate protein-protein interaction . Knock-down of ATXN10 by RNAi induces cell death in primary cerebellar neurons [15] , whereas over-expression of ATXN10 activates the mitogen-activated protein kinase cascade and promotes neurite extension in PC12 cells [16] . While ATXN10 is expressed in a wide variety of tissues , expression is especially strong in brain , heart and muscle . Although these data suggest that ataxin 10 plays a role in neuronal survival and differentiation , the exact function of ataxin 10 remains unknown . Thus , it is plausible that a large expansion of the ATTCT repeat may interfere with the transcription , like the GAA repeat expansion does in FRDA , leading to a loss of function of ataxin 10 . However , we recently demonstrated that neither a gain nor a loss of the function of ATXN10 is the primary pathogenic mechanism of SCA10 [17] . Analyses of SCA10 fibroblasts showed that the ATXN10 mRNA levels remain unaltered in spite of the repeat expansion [6] , [17] . In addition , transcription of the mutant alleles and post-transcriptional splicing of the mutant ATXN10 transcript remain largely unaltered in SCA10 patients [17] . Furthermore , homozygous Atxn10 knockout ( Atxn10−/− ) mice showed embryonic lethality while heterozygous ( Atxn10+/− ) mice showed no phenotype [17] . Finally , a recent report described patients with balanced translocation t ( 2;22 ) ( p25 . 3:q13 . 31 ) , in which the breakpoint of chromosome 22q13 . 31 disrupted intron 2 of ATXN10 [18] . These patients were totally asymptomatic , suggesting that haploinsufficiency of ATXN10 does not cause SCA10 . In the present study , we examine whether the expanded AUUCU RNA repeat in the mutant ATXN10 transcript is the principal pathogenic molecule capable of triggering neuronal death in SCA10 . We demonstrate that the expanded AUUCU repeat within the spliced intron interacts with hnRNP K , and this RNA-protein interaction results in loss of hnRNP K function , translocation of Protein Kinase C δ ( PKCδ ) to mitochondria and activation of apoptosis in SCA10 cells . Furthermore , we observe that targeted inactivation of the mutant ATXN10 transcripts in SCA10 cells significantly reduces mitochondrial translocation of PKCδ . Together , these results define a key pathogenic mechanism of SCA10 and provide clues for potential therapeutic strategies .
We propose that the mutant ATXN10 transcripts containing expanded AUUCU repeats contribute towards the SCA10 phenotype . To investigate whether the sub-cellular distribution and fate of the mutant ATXN10 transcripts are altered , RNA FISH analysis with a Cy3- ( AGAAU ) 10 riboprobe was performed on SCA10 fibroblasts containing ∼2000 or ∼1 , 000 ATTCT repeats and on normal fibroblasts expressing the wild type ATXN10 transcripts containing 12 AUUCU repeats . The ( AGAAU ) 10 riboprobe detected the presence of nuclear and cytoplasmic aggregates in SCA10 fibroblasts ( Figure 1A; arrows , also Figure S1A; arrow ) , but not in normal fibroblasts ( Figure 1B ) . These aggregates observed in this and other Figures were resistant to DNAse and disappear after RNAse treatment . Since our previous study showed that the 9th intron of the ATXN10 gene ( 66 , 421 bp ) encoding the expanded AUUCU repeats is spliced normally [17] , our present results imply that the intron 9 sequences are spliced and partly translocated to the cytoplasm in SCA10 fibroblasts . FISH with an anti-sense probe specific for exon 9 of the ATXN10 gene showed no significant binding in the same SCA10 fibroblasts ( data not shown ) , confirming that the aggregated AUUCU repeat sequences are spliced from the mutant ATXN10 transcripts . These findings suggest that intron 9 containing the expanded AUUCU repeat is spliced out of the mutant ATXN10 transcripts , but expanded AUUCU repeats within the spliced intron 9 are resistant to degradation , and deposited as aggregates in nuclei and in cytoplasm in SCA10 cells . We determined whether expanded AUUCU repeats alone are sufficient to form aggregates . Untranslated ∼500 AUUCU repeats from a transgene ( Figure 1C ) were expressed in human neuroblastoma Sy5y cells . The transgene is designed to express an expanded ATTCT repeat within the rabbit β-globin intron downstream of the human α-enolase promoter and upstream of the LacZ reporter . Using RT-PCR analysis , we confirmed that the AUUCU-repeat-containing the rabbit β-globin intron is spliced from the transcript when the transgene is expressed in Sy5y cells ( data not shown ) . FISH analysis of the Sy5y cells expressing ∼500 AUUCU repeats showed SCA10-like nuclear and cytoplasmic aggregates ( Figure 1D ) . However , under identical conditions , aggregates were not detected in Sy5y cells expressing the lacZ transcripts encoding shorter repeats ( 12 or 25 repeats ) ( data not shown ) . FISH analysis of transfected normal human fibroblasts expressing ∼500 AUUCU repeats also showed SCA10-like nuclear and cytoplasmic aggregates ( Figure S1B; arrow ) . These data indicate that even when the expanded AUUCU repeat is ectopically expressed , the intronic sequence is spliced from the transcript of the transgene , becomes resistant to degradation , and aggregates in nuclear and cytoplasmic foci in Sy5y cells . We also determined whether transcripts with expanded AUUCU sequences form similar aggregates in mouse brain . Transgenic mouse lines using the construct described in Figure 1C were generated . Repeat-primed PCR ( RP-PCR ) analyses of genomic DNA from these mice showed the presence of expanded ATTCT repeats ( Figure 1E ) , and Southern analyses confirmed the presence and integrity of ∼500 ATTCT repeats ( Figure 1F ) . The ( AGAAU ) 10 riboprobe detected distinct intracellular aggregates in brains from 6-month-old ( Figure 1G ) and 3-month-old ( Figure S1C ) transgenic mice , but not in control mouse brains . Importantly , similar to the SCA10 cells , we observed a large number of aggregates not only in the nucleus but also in the cytoplasm , and they were more abundant in 6-month-old than 3-month-old mice ( Figure 1G and Figure S1C ) . The formation of SCA10-like aggregates in these cells and transgenic mouse brains confirms that the expanded AUUCU repeats are necessary and sufficient to form nuclear and cytoplasmic aggregates . Moreover , these large foci suggest that the expanded AUUCU-RNA repeats may aggregate as insoluble RNA-protein complexes , as described in other repeat expansion disorders [7] , [8] . Light-microscopic analysis of the Sy5y cells expressing the ∼500 AUUCU repeats showed a dramatic increase in cell death ( Figure 2A ) , whereas cells expressing normal-size repeats showed virtually no cell death ( Figure 2B ) . A TUNEL assay revealed that more than 70% of cells expressing the ∼500 AUUCU repeats underwent apoptosis 48 hours after transfection ( Figure 2A and 2C ) , while cells expressing 12 AUUCU repeats did not undergo apoptosis ( Figure 2B and 2C ) ( p<0 . 0001 ) . Furthermore , caspase-3 activity was significantly higher in cells expressing ∼500 AUUCU repeats than in control cells ( p<0 . 0001 ) ( Figure 2D ) , suggesting that the expanded AUUCU repeats activate caspase-3-mediated apoptosis . We also observed that expression of ∼500 AUUCU repeats cause apoptosis in PC12 cells ( Figure S2 ) . The distinct aggregates in SCA10 cells and transgenic mouse brains led us to hypothesize that the expanded AUUCU repeat RNA may interact with proteins , and that such interactions may have pathogenic significance . We pulled down proteins from mouse brain extracts using biotin-labeled expanded AUUCU RNA repeats and analyzed them by SDS-PAGE ( Figure 3A ) . The unique protein that was reproducibly and repeatedly pulled down ( n = 6 ) was identified by mass spectrometry as hnRNP K ( Figure 3A; arrow ) . hnRNP K contains three K-homology ( KH ) domains that mediate its interactions with RNA and a K interactive ( KI ) region with proline-rich docking sites important for src homology domain binding . To establish the specificity of the interaction of hnRNP K with AUUCU RNA , purified hnRNP K was incubated with single-stranded ( AUUCU ) 15 RNA and extracted with buffers containing increasing salt concentrations . The data show a significant affinity of hnRNP K with ( AUUCU ) 15 RNA even in the presence of 250 mM NaCl; in contrast hnRNP K is completely dissociated from the control RNA at significantly lower ( ≤100 mM ) salt concentrations ( Figure 3B ) . Thus , hnRNP K can bind tightly to AUUCU repeats , in addition to the consensus sequence , U ( C3-4 ) U/A [19] . We next immuno-precipitated ( IP ) hnRNP K from SCA10 and normal fibroblasts and determined the presence of intron 9 of the ATNX10 transcript in the IP pellets . RT-PCR analysis of the IP pellets showed the presence of the intron 9 sequence of the ATXN10 transcript when hnRNP K was precipitated from SCA10 fibroblasts but not from normal fibroblasts ( Figure 3C ) . We did not detect the presence of exon 9 or exon 10 in the pellets , further corroborating the idea that intron 9 containing the expanded AUUCU repeat is spliced from the ATXN10 transcript . These data indicate that hnRNP K is tightly associated with the expanded AUUCU repeat within the intron 9 sequence in SCA10 cells . To demonstrate the in vivo interaction of the expanded repeat with hnRNP K , we investigated the co-localization of hnRNP K with AUUCU RNA in transgenic mouse brain . The expanded AUUCU repeat aggregates were visualized by FISH , and hnRNP K was detected with anti-hnRNP K antibody by immunofluorescence . Sagittal sections of hippocampus CA1 ( Figure 3E ) and cerebral cortex ( Figure S3 ) from the 6-month-old transgenic mice showed distinct co-localization of ∼500 AUUCU aggregates with endogenous hnRNP K . In contrast , control mouse brains showed no foci ( Figure 3D ) . We next transfected Sy5y cells with two plasmids: one to express the ∼500 AUUCU repeat ( Figure 1C ) and the other to express GFP-tagged hnRNP K . FISH analysis of the double-transfected cells revealed significant co-localization of the red fluorescence from the AUUCU RNA repeat and the green fluorescence from the GFP-hnRNP K ( Figure 3F; arrow ) , indicating that hnRNP K exists as a RNA-protein complex with AUUCU RNA in vivo . We assessed whether binding of hnRNP K with the expanded AUUCU RNA interferes with hnRNP K activity by studying hnRNP K-regulated alternative splicing of transcripts . hnRNP K is known to regulate alternative splicing of exon 6A and 6B , the mutually exclusive exons of the β-tropomyosin gene in vertebrates , and decreased hnRNP K activity has been shown to increase the inclusion of exon 6A and the exclusion of exon 6B [20] , [21] . RT-PCR analysis showed that exon 6A is predominantly included in the mature β-tropomyosin transcripts in SCA10 cells compared to normal control cells ( Figure 3G ) , suggesting that the hnRNP K activity is decreased in SCA10 cells . Consistent with these results , splicing of β-tropomyosin was also markedly altered in normal fibroblasts ectopically expressing expanded AUUCU repeats ( data not shown ) . To understand the possible pathogenicity of a loss of hnRNP K function in SCA10 , we treated Sy5y cells with four different hnRNP K siRNA duplexes . The sequence that most significantly and reproducibly decreased hnRNP K protein level was used at titrating concentrations to knockdown hnRNP K in Sy5y cells . Western blot analysis showed that cells treated with 100 pM hnRNP K siRNA had >50% reduction in hnRNP K protein level , compared to that in cells treated with control siRNA ( Figure 4A ) . We detected no significant cell death up to 48 hours after siRNA treatment , in accordance with previous studies [22] , [23] . However , we observed a large number of dying cells 72 hours after transfection with the hnRNP K siRNA; in contrast , cells treated with control siRNA did not show significant cell death . Activation of cell death pathways in Sy5y cells transfected with hnRNP K siRNA was verified by significant caspase-3 activity ( n = 3 , p<0 . 001 ) ( Figure 4B ) , and increased TUNEL-positive cells ( n = 6 , p<0 . 0001 ) ( Figure 4C ) , 72 hours post-transfection . The concentration of hnRNP K siRNA sufficient to activate caspase-3-mediated apoptosis at 72 hours was 100 pM ( n = 3 , p = 0 . 0001 ) ( Figure 4D ) . Thus , down-regulation of hnRNP K activates caspase-3-mediated apoptosis similar to that observed in cells expressing expanded AUUCU repeats . Based on our data we postulated that an interaction of hnRNP K with the AUUCU repeat results in a loss of function of hnRNP K , leading to apoptotic cell death . We studied whether hnRNP K over-expression rescues cells from apoptosis induced by expanded AUUCU repeats . We established stably transfected Sy5y cell lines over-expressing hnRNP K , and then transiently transfected them with the plasmid shown in Figure 1C . Sy5y cells stably expressing a control plasmid in lieu of hnRNP K underwent massive cell death when expanded AUUCU repeats were expressed . In contrast , ∼50% over-expression of hnRNP K ( Figure 4E ) decreased the expanded AUUCU repeat-induced apoptosis by ∼30% , and this decrease in apoptosis is accompanied by reduced caspase-3 activity ( n = 3 , p<0 . 05 ) ( Figure 4E ) . These data confirm our hypothesis that expanded AUUCU repeats activate apoptosis by suppressing hnRNP K function . In vivo studies have shown that hnRNP K and PKCδ remain constitutively bound together within the cell [24]–[27] . Studies also showed that hnRNP K , when bound to nucleic acids , cannot be phosphorylated and cannot interact with PKCδ [25] . PKCδ has been implicated as an activator of apoptosis in many cell types , including neurons [28] , [29] . Over-expression of PKCδ has been shown to activate apoptosis through a positive regulatory loop , in which caspase-3 activates PKCδ and activated PKCδ cleaves caspase-3 [30] . PKCδ over-expression results in its translocation to mitochondria , release of cytochrome c , and activation of caspase-3 [30]–[32] . Since binding of hnRNP K to the expanded AUUCU repeat is expected to reduce the formation of the hetero-dimeric complexes between hnRNP K and PKCδ , and mimic PKCδ over-expression , we investigated the ramifications of hnRNP K inactivation on sub-cellular localization of PKCδ in SCA10 fibroblasts and transgenic mouse expressing ∼500 AUUCU repeats in brain . We first investigated whether cellular localization of PKCδ is altered in SCA10 cells . PKCδ was immunostained with green fluorescence and mitochondria were identified using mitotracker deep red 633 . Immunostaining of the normal fibroblasts for PKCδ showed that PKCδ is present in the cytoplasm and the nucleus , but no significant PKCδ localization in mitochondria ( Figure 5A ) . In contrast , PKCδ significantly overlaps with mitochondria in SCA10 fibroblasts as punctate staining around the nucleus , suggesting that a significant portion of PKCδ is translocated into the mitochondria ( Figure 5B ) . To further verify that the interaction between hnRNP K and PKCδ is diminished in SCA10 fibroblasts , we immunoprecipitated hnRNP K from normal and SCA10 fibroblasts and analyzed the relative abundance of hnRNP K and PKCδ in the IP by Western blot analysis . The Western blot data show a significantly lesser amount of PKCδ in the IP from the SCA10 fibroblasts compared to normal fibroblast ( Figure S4A ) . These data support our hypothesis that expanded AUUCU RNA interacts with hnRNP K and this binding results in the release of PKCδ , facilitating translocation of PKCδ to mitochondria in SCA10 . To test that PKCδ is translocated to the mitochondria in SCA10 cells , we analyzed the mitochondrial protein fractions from SCA10 and control fibroblasts by Western blotting . Consistent with the immuno-histochemical data , the Western blot data showed elevated PKCδ level in SCA10 mitochondria ( 4B ) . Moreover , sagittal sections of transgenic mouse brain showed similar mitochondrial localization of PKCδ while negligible mitochondrial localization of PKCδ was seen in age-matched wild-type mice ( Figure 5C and 5D ) . We also analyzed fibroblasts derived from patients with ataxia telangiectasia , and unlike SCA10 fibroblasts , these fibroblasts did not show presence of any detectable level of PKCδ in mitochondria ( data not shown ) , suggesting the disease specificity of this mechanism in SCA10 . These results suggest that PKCδ is translocated into the mitochondria of SCA10 cells . To test the hypothesis that the interaction of AUUCU RNA with hnRNP K leads to a loss function of hnRNP K , which then results in translocation of PKCδ into mitochondria , we transfected normal fibroblasts with hnRNP K siRNA and studied the cellular localization of endogenous PKCδ . When hnRNP K is downregulated , a majority of PKCδ was translocated to mitochondria and a negligible amount of PKCδ was detected outside mitochondria ( Figure 6A ) . In normal fibroblasts , or in fibroblasts treated with control siRNA , most of the PKCδ was detected within cytoplasm and nuclei , with no detectable translocation to mitochondria ( Figure 6B ) . Importantly , downregulation of hnRNP K in normal fibroblasts did not alter the steady state level of PKCδ ( Figure S4C ) . We also expressed ∼500 AUUCU repeats in primary human fibroblasts and studied the expression and cellular localization of PKCδ in these cells to investigate whether AUUCU RNA interferes with the expression and/or subcellular localization of PKCδ . We found that the expression of PKCδ remained unaltered in cells expressing expanded AUUCU repeats and the red fluorescence from mitochondria significantly overlaps with the green fluorescence from PKCδ in fibroblasts expressing ∼500 AUUCU repeats ( Figure 6C and Figure S4D ) or in those cells expressing ∼200 AUUCU repeats ( Figure S5 ) , suggesting that PKCδ translocates to mitochondria in response to the expression of expanded AUUCU repeats . In contrast , a negligible translocation of PKCδ was observed when 12 AUUCU repeats were expressed in fibroblasts ( Figure 6D ) . Together , these data corroborate our hypothesis that the expanded AUUCU repeat interacts with hnRNP K , suppresses its function , resulting in mitochondrial translocation of PKCδ and activation of apoptosis . To test whether mitochondrial localization of PKCδ can be decreased by reducing the mutant ATXN10 transcript , we targeted the ATXN10 transcript in SCA10 fibroblasts with two different ATXN10 siRNA and studied the cellular localization of PKCδ . This resulted in significant decrease in the number of both nuclear and cytoplasmic AUUCU RNA aggregates ( Figure 7A; left panel ) , whereas control siRNA did not reduce the number of AUUCU RNA foci in SCA10 fibroblasts ( Figure 7A; right panel ) . Treatment of SCA10 fibroblasts with ATXN10 siRNA substantially restored normal PKCδ subcellular localization , with decreased amount in mitochondria ( Figure 7B; top panel ) . As expected , Control siRNA had no significant effects on the distribution or amount of PKCδ in SCA10 cells ( Figure 7B; center panel ) . Treatment of normal fibroblasts with ATXN10 siRNA did not have any effect on PKCδ cellular localization ( Figure 7B; bottom panel ) . We conclude that by disrupting the hnRNP K-AUUCU complexes , hnRNP K can re-establish its normal function within the cell , alleviating the pathogenic mechanisms leading to apoptosis . These findings support our hypothesis that expanded AUUCU repeats are toxic and are sufficient to trigger PKCδ translocation to mitochondria and apoptosis .
Multiple inherited human neurological disorders are now attributed to expansion of short tandem repeats either in coding or non-coding regions of genes [2] , [7] , [8] . Genetic and molecular analysis of these disorders have revealed that the repeat expansion can result in either a loss of function of the gene ( Fragile-X syndrome and Friedreich's ataxia ) or a gain of function of the encoded protein ( SCA1 , SCA2 , SCA3 , SCA6 , SCA7 , SCA17 , Huntington's disease , DRPLA , and oculopharyngeal muscular dystrophy ) [7] , [8] . RNA-mediated pathogenesis is believed to play a critical role in several other repeat expansion disorders , including Myotonic Dystrophy Type 1 ( DM1 ) and Type 2 ( DM2 ) , SCA8 , SCA12 , Huntington's disease like 2 ( HDL2 ) , and fragile X tremor ataxias syndrome ( FXTAS ) [7] , [8] . However , the pathogenic mechanism of DM1 , SCA8 , SCA12 , HDL2 and FXTAS , which are caused by trinucleotide repeat expansions , may also involve qualitative or quantitative alterations of the protein products of the respective genes or genes on the opposite strand [33]–[35] . In contrast , SCA10 is the only human disorder proven to be caused by an expansion of a pentanucleotide repeat . Like the DM2 CCTG tetranucleotide repeat , the SCA10 ATTCT repeat shows repeat-number polymorphism , which makes these non-trinucleotide repeat highly unlikely to encode protein sequences from either strand . Furthermore , we have shown that the intronic repeat expansion does not alter ATXN10 transcripts [17] . Thus , SCA10 is likely to be a disorder solely caused by RNA-based mechanism , unlike most disorders that are caused by trinucleotide repeat expansions . In the present study we provide evidence that SCA10 pathogenesis results from a trans-dominant gain-of-function of AUUCU repeats . First , transcription of the mutant allele produces transcripts that form aggregates in the nucleus and cytoplasm of the SCA10 cells and in transgenic mouse brain . Second: the expanded AUUCU repeat complexes with hnRNP K , leading to the loss of function of hnRNP K . Third , expression of expanded AUUCU repeat results in the accumulation of PKCδ in the mitochondria and caspase-3 mediated activation of apoptosis . Fourth , diminished hnRNP K activity recapitulates these events caused by expanded AUUCU repeats . And finally , over-expression of hnRNP K , as well as down-regulation of transcripts of expanded ATTCT repeat , rescues cells from apoptosis caused by expanded AUUCU repeats . Based on these findings , we conclude that the AUUCU RNA binds to and inactivates hnRNP K , triggering caspase-3-mediated apoptosis via translocation of PKCδ to mitochondria . Previous reports suggest that the presence of PKCδ in the mitochondria results in decreased membrane potential , release of cytochrome C , and activation of caspase-3 [30]–[32] , further supporting our conclusion . Moreover , caspase-3 activates PKCδ and activated PKCδ further activates caspase-3 [30] , and proteolytically activated PKCδ down-regulates hnRNP K protein in a proteasome-dependent manner [36] . Hence , positive feedback loops involving hnRNP K , PKCδ and caspase-3 may enhance this pathogenic pathway in SCA10 . Since apoptosis is considered to be a major mechanism of cell death in a variety of human neurodegenerative disorders [37] , the novel pathway of apoptosis induced by the mutant ATXN10 RNA is relevant to the neurodegenerative phenotype of SCA10 . Our results provide strong evidence that this novel mechanism of trans-dominant RNA gain of function contributes to the pathogenic mechanism in SCA10 . The formation of aggregates may not necessarily be a required event for the mutant RNA to exert its toxicity . Binding of the soluble form of the mutant RNA to hnRNP K may be sufficient to cause the loss of function of hnRNP K with a release of PKCδ , and the aggregate formation could be a secondary phenomenon . We hypothesize that expanded AUUCU RNA pathologically binds to hnRNP K and prevents PKCδ from binding to the hnRNP K , mimicking over-expression of PKCδ within the cell . Previous studies have shown that hnRNP K is constitutively bound to PKCδ , but upon binding to nucleic acids , hnRNP K can no longer interact with PKCδ [25] , [30] . Translocation of PKCδ to mitochondria in SCA10 cells , fibroblasts expressing expanded AUUCU repeat , and fibroblasts treated with hnRNP K siRNA argues for this mechanism . Studies have shown multiple apoptotic activators , including oxidative stress and over-expression of PKCδ , induce PKCδ translocation to the mitochondria , [32] . The mitochondrial translocation of PKCδ has been shown to cause an alteration in calcium signaling events and mediates the H2O2-mediated loss of membrane potential , release of cytochrome c , and activation of caspase-3 [38] . While it is possible that the expanded AUUCU repeat causes PKCδ translocation via other mechanisms , our data showing that over-expression of hnRNP K rescues AUUCU-mediated apoptosis argue for the mechanism mediated by a loss of function of hnRNP K . Our present data do not rule out the possibility that additional proteins interact with the mutant ATXN10 transcripts . Also , expression of hnRNP K is ubiquitous within the cell , and diminished hnRNP K could lead to altered regulation of transcription , splicing and cell signaling , which may account for the phenotypic variability in SCA10 as illustrated in Figure 7C . We are investigating these mechanisms . However , our current data convincingly show that the hnRNP K inactivation and PKCδ mitochondrial translocation are a key pathogenic pathway mediating the RNA gain of toxic function in SCA10 .
SCA10 fibroblasts were isolated from skin biopsy from a Mexican-American SCA10 patient with ∼2000 repeats and a Brazilian SCA10 patient with ∼1000 repeats under signed informed consent approved by IRB at UTMB and the Ethics Committee at Federal University of Parana . These human fibroblasts Cells were cultured in MEM with Eagle-Earle salt and 2 mM L-glutamine containing 15% fetal bovine serum and antibiotic in 5% CO2 at 37°C in 75 cm2 flasks . Human neuroblastoma Sy5y cells were cultured at Ham's F12K medium with 2 mM L-glutamine adjusted to contain 1 . 5 g/L sodium bicarbonate , 15% horse serum , 2 . 5% fetal bovine serum in 5% CO2 at 37°C in 75 cm2 flasks . The cytomegalo virus ( CMV ) promoter sequences in plasmid pCDNA3 . 1-hygro-lacZ ( Invitrogen ) were replaced with the MfeI/BamHI fragment of the human α-enolase promoter sequences ( ∼5 . 0 kb ) . The 2nd intron of rabbit β-globin intron was cloned downstream of the enolase promoter and upstream of the lacZ . Expanded ATTCT repeats from the SCA10 hybrid cells [17] were PCR amplified with forward primer 5′-CCAAGGATGCAGGTGCCACAGCATCTC-3′ and reverse primer: 5′-ATATGCATCCAGCTTCTGATTACATGGACT-3′ . A polylinker containing SwaI site was cloned into the MfeI site within the β-globin intron . Subsequently , the DNA fragment containing the ATTCT duplex was cloned into the SwaI site within the intron . Presence of the expanded ATTCT sequences in the transgenic plasmid was confirmed by digesting the plasmid DNA with NheI and HindIII sites that flank the SwaI site , and by sequencing . Plasmids encoding the expanded ATTCT repeats were grown in E . coli SURE bacteria at 16°C to minimize the deletion of the repeat sequences [39] . The transgenic plasmid DNA containing the LacZ and ∼500 ATTCT repeats was digested with MfeI and NaeI , and digested DNA was electrophoresed on agarose gel . The ∼10 kb DNA fragment containing the transgene was purified from agarose gel using gel extraction kit ( Qiagen ) . The cloned ATTCT repeats under enolase promoter contain 650 bp of upstream and 500 bp of downstream ATXN10 sequence in addition to the ATTCT repeats . The control plasmids containing the same ATXN10 flanking regions and 12 ATTCT repeats were PCR amplified from a normal subject . The cDNA clones of human hnRNP K was purchased from Open Biosystems , USA and cloned in-frame into pCGFP-C1 ( BD Biosciences , USA ) . For construction of plasmid for stable expression of hnRNP K , the ORF of the human hnRNP K was PCR-amplified from the pool of human cDNA ( Clonetech ) with the following primer sets: forward: 5′-CTGATTGGTGTGCCCGTTTAATAA-3′ and reverse: 5′-CTCCTTCAGTTCTTCACTAGTC-3′ . The 1507 bp PCR product was purified from agarose gel using gel extraction kit ( Qiagen ) and the blunt-ended PCR product was cloned into the EcoRV site in the mammalian expression vector pcDNA3 . 1-Hygro ( + ) ( Invitrogen ) to generate recombinant plasmid pcDNA-hnRNP K . The coding sequence of hnRNP K in recombinant plasmid pcDNA-hnRNP K was sequenced to verify the proper orientation and sequence integrity of hnRNP K . The transgene containing 500 ATTCT repeats within an intron ( Illustrated in Figure 1C ) was microinjected into the fertilized eggs and transplanted into the uterus of pseudo-pregnant surrogate mothers to obtain founder transgenic mice using standard procedure at the UTMB transgenic core facility . Presence of the transgene and the repeat in the transgenic founder mice were confirmed by both Southern blot as well as repeat primed PCR analyses . Animal experiments were performed under a protocol approved by IACUC at UTMB . Mouse genomic DNA was collected from tail samples , and repeat-primed PCR and Southern blot analyses were performed as previously described [40] . Plasmid pcDNA3 . 1 control as well as pcDNA- ( ATTCT ) n ( n = 500 ) were first linearized with Bam HI and the linear plasmid was in vitro transcribed with T7 RNA polymerase ( Promega ) . Biotinylated rCTP was mixed with other rNTPs during transcription to incorporate the biotin-labeled rCTP into ( AUUCU ) n RNA . Nuclear extracts from brain were made from a 2 month old B6 mouse using NE-PER Nuclear and Cytoplasmic Extract Reagent ( Pierce ) according to vendors specification . The total protein mixture was incubated with ( AUUCU ) n RNA at 4°C overnight , and the unbound proteins were washed by using RNA washing buffer ( 0 . 5% NP- 40 , 100 mM NaCl , 50 mM Tris-HCl ) four times . The proteins that remain bound to the magnetic beads after extensive washing were extracted by boiling the magnetic beads in 1X SDS-PAGE loading buffer . The extracted proteins were electrophoresed on 5–12% PAGE and proteins that appear as unique bands were excised , digested with trypsin and then analyzed by MALDITOF assay at Biomolecular Resource Facility Core at UTMB and the sequence was identified by searching the rodent protein database . The SCA10 and control normal fibroblasts were harvested and washed with 1X PBS , lysed in 20 mM HEPES pH 7 . 4 , 1 mM EDTA , 100 mM NaCl , 1% NP-40 , Leupeptin ( 10 µg/ml ) , aprotinin ( 10 µg/ml ) , 20 mM β-glycero-phosphate , 20 mM NaF and 1 mM Na Vanadate . hnRNP K was immuno-precipitated using anti-hnRNP K antibody and the IP pellet was washed three times in the lysis buffer , and bound proteins were eluted in SDS-containing sample buffer and separated on SDS-PAGE . The membrane was first immunoblotted with anti-hnRNP K antibody and then with PKCδ antibody . To detect the intron 9 sequences of ATXN10 in the IP pellet , total RNA was extracted from the IP pellets by phenol-chloroform extraction , and DNA contamination was removed with TURBO DNAse Kit ( Ambion ) . The cDNA synthesis was carried out using 1 µg of total RNA using a RT-PCR kit ( BD Biosciences ) . The cDNA aliquots were quantified and cDNA were used to detect the presence of intron 9 sequences of ATXN10 transcripts by PCR , using the forward primer 5′-AAGGATCAGAATCCCTGGAA-3 and the reverse primer 5′-TCATTCTGCCATCTGTTTTC-3′ . Splice isoforms of β-tropomyosin mRNA were analyzed using RT-PCR as previously described [20] , [21] with a set of three primers; E5: 5′-GCCATGAAGGATGAGGAGAA-3′ ( forward primer ) , E6a: 5′-CTGAGGTGGCCGAGAGGTAA-3′ ( reverse primer to detect exon E6a ) and E6b: 5′-TAAATGTGGGGACCTAGAGG-3′ ( reverse primer to detect exon E6b ) . 1 mg of the Streptavidin-conjugated Dynabeads ( Invitrogen ) was washed once with Solution A ( 100 mM NaOH , and 50 mM NaCl ) and twice with Solution B ( 100 mM NaCl ) . The magnetic beads were next incubated in 50 µl of 2X incubation buffer ( 10 mM Tris , pH 7 . 5; 1 mM EDTA; 2 M NaCl , ) for 15 minutes . 1000 pmoles ( 50 µl ) of biotinylated RNA [either ( AUUCU ) 15 or control RNA: ( UUUCC ) 3 ( CCCUU ) 3 ( UUUUC ) 3 . ] were added to the magnetic beads , incubated at room temperature for 1 hour , and washed twice with 1X incubation buffer . Five mg of purified hnRNP K were added to the magnetic bead-RNA mixture and incubated in a binding buffer ( 20 mM HEPES , pH 7 . 5; 10% glycerol; 1 mM DTT; 0 . 1 mM EDTA ) at 4°C for overnight . The supernatant was discarded and the magnetic beads were resuspended in binding buffer ( 25 mM Tris , pH 7 . 5; 0 . 1 mM EDTA; 10 mM NaCl ) . RNA-bound hnRNP K was next sequentially eluted with buffers containing increasing NaCl concentrations . The eluted hnRNP K protein fractions were analyzed on PAGE by Coomasie staining and Western blotting . Mouse monoclonal anti-hnRNP K was obtained from Acris Antibodies GmbH . Monoclonal anti-PKCδ ( G-9 ) and Cytochrome C Oxidase ( COXII ) antibodies were purchased from Santa-Cruz Biotechnology . The Western blotting experiments were done according to standard procedure and the target proteins were detected using ECL Western kit ( Amersham ) . Expression levels of β-actin ( Abcam ) were used as controls for protein loading . Cells were grown in chamber slides overnight prior to TUNEL assay . TUNEL assay was performed according to vendor instructions ( Roche ) . Student's t-test was used to calculate statistical significance . Caspase-3 assay was performed according to instructions supplied by vendor ( Calbiochem ) . P values were calculated using student's t-test . Sy5y cells were transfected with plasmids or siRNA by Lipofectamine 2000 reagent ( Invitrogen ) . For the targeted inactivation of hnRNP K , the On-target-Plus siRNA duplexes were purchased from Dharmacon . The control non-targeting siRNA from Dharmacon was used as a negative control for all siRNA experiments . Approximately 100 and 200 nmoles of the siRNA pools were used for the targeted down-regulation of hnRNP K , and different assays were applied 72 hours after the transfection . Fibroblasts were transfected using the human dermal fibroblast nucleofector kit for electroporation ( Amaxa Corporation ) . Plasmids expressing either 12 or 500 ATTCT repeats were transfected at 3 µg according to kit instructions , and siRNA ( both hnRNP K and ataxin 10 ) was transfected according to kit instructions . For stable over-expression of hnRNP K in Sy5y cells , pcDNA-hnRNP K was digested with MfeI and the linear plasmid DNA was tranefected into Sy5y cells using Lipofectamin 2000 reagent ( Invitrogen ) , and the stable clones were selected with hygromycin ( 300 mg/ml ) . Total protein was isolated from the stably transfected cells and the hnRNP K expression level was analyzed by Western blotting with the anti-hnRNP K antibody . RNA foci were detected using a Cy3-labeled ( AGAAU ) 10 RNA riboprobe . Slides were pre-hybridized at 65°C in RNA hybridization buffer for 1 . 5 hours . Slides were then hybridized overnight in 250 ng ( AGAAU ) 10/1 ml hybridization solution at 45°C . Slides were rinsed with PBS three times and then extensively washed 4 times 5 minutes each to remove all non-specific binding probes . Slides were then mounted with DAPI mounting medium . Transgenic mice anesthetized with Avertin were perfused through the aorta , first rinsing for 15 minutes with PBS and then 60 ml of fresh 4% Paraformaldehyde ( PFA ) in DEPC water . The brain was carefully removed and stored in 4% PFA at 4°C with gentle agitation overnight . Brain tissue was then placed in 30% sucrose overnight . Mouse brains were fixed in paraffin and sectioned sagittally . RNA foci were stained using a Cy3-labeled ( AGAAU ) 10 riboprobe . First , paraffin was removed from the brain sections and slides were dehydrated with 70% , 95% and 100% Ethanol in DEPC water , and washed using DEPC PBS . Following FISH , hnRNP K was immunodetected . Sections were blocked with DAKO antibody blocking solution ( serum-free ) and later double stained with anti-hnRNP K 1∶1000 in DAKO antibody diluent . Goat anti-mouse 488 was used to identify hnRNP K and slides were visualized using a Hamamatsu Camera Controller using DP controller software in histopathology lab at UTMB . Fibroblasts were transfected with plasmids pcDNA- ( ATTCT ) 12 , pcDNA- ( ATTCT ) 500 , hnRNP K siRNA or control siRNA through electroporation . Transfections were conducted in chamber slides . Thirty-six hours after repeat transfection and 72 hours after RNAi transfection , the cells were treated with mitotracker deep red 633 ( Invitrogen ) at a concentration of 250 nM in cell culture medium . Cells were incubated at 37°C for 30 minutes . After washing the cells three times with PBS , cells were then fixed with 4% PFA for 30 minutes at room temperature . Cells were washed 3 times with PBS and stored in 70% Ethanol for up to 24 hours . Cells were blocked with DAKO antibody blocking solution ( serum-free ) and later double stained with anti-PKCδ 1∶500 in DAKO antibody diluent . Goat anti-mouse 488 was used to identify PKCδ . Fluorescent photomicrographs were taken using a Hamamatsu Camera Controller using DP controller software in the histopathology core lab at UTMB . The sagittal section of the transgenic brain was processed according to the procedure described above and immuno-stained with anti-PKCδ and Cox II antibodies to detect mitochnodria and PKCδ respectively . The cytoplasmic , nuclear and mitochondrial protein fractions from normal and SCA10 cells were isolated using the mitochondria isolation kit and Sub-cellular Protein Fractionation kits ( Thermo Scientific-Pierce ) . The isolated proteins were analyzed by Western blotting using anti-PKCδ antibody .
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In an earlier study , we showed that the mutation of spinocerebellar ataxia 10 ( SCA10 ) is an enormous expansion of a gene segment , which contains a tandemly repeated 5-base ( ATTCT ) unit . Since SCA10 is the only known human disease that is proven to be caused by 5-base repeat expansion , it is important to learn how this novel class of mutation causes the disease . We found that the mutation produces an expanded RNA repeat , which aberrantly accumulates in SCA10 cells and interacts with a major RNA–binding protein . When we expressed expanded RNA repeats or decreased the RNA–binding protein level in cultured cells , either of these manipulations produced a specific type of cell death that is associated with a massive transfer of a key enzyme called protein kinase C delta to mitochondria . We also showed that either blocking the expanded AUUCU repeat or replenishing hnRNP K rescues cells from the cell death induced by the SCA10 mutation . Together , we conclude that the mutant RNA inactivates hnRNP K and kills cells by triggering the specific cell-death mechanism . Our data provide important clues for therapeutic intervention in SCA10 .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"genetics",
"and",
"genomics/genetics",
"of",
"disease",
"neurological",
"disorders/neurogenetics",
"neurological",
"disorders/movement",
"disorders",
"neuroscience/neurobiology",
"of",
"disease",
"and",
"regeneration"
] |
2010
|
Inactivation of hnRNP K by Expanded Intronic AUUCU Repeat Induces Apoptosis Via Translocation of PKCδ to Mitochondria in Spinocerebellar Ataxia 10
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In budding yeast meiosis , the formation of class I interference-sensitive crossovers requires the ZMM proteins . These ZMM proteins are essential in forming a mature synaptonemal complex , and a subset of these ( Zip2 , Zip3 , and Zip4 ) has been proposed to compose the core of synapsis initiation complexes ( SICs ) . Zip4/Spo22 functions with Zip2 to promote polymerization of Zip1 along chromosomes , making it a crucial SIC component . In higher eukaryotes , synapsis and recombination have often been correlated , but it is totally unknown how these two processes are linked . In this study , we present the characterization of a higher eukaryote SIC component homologue: Arabidopsis AtZIP4 . We show that mutations in AtZIP4 belong to the same epistasis group as Atmsh4 and eliminate approximately 85% of crossovers ( COs ) . Furthermore , genetic analyses on two adjacent intervals of Chromosome I established that the remaining COs in Atzip4 do not show interference . Lastly , immunolocalization studies showed that polymerization of the central element of the synaptonemal complex is not affected in Atzip4 background , even if it may proceed from fewer sites compared to wild type . These results reveal that Zip4 function in class I CO formation is conserved from budding yeast to Arabidopsis . On the other hand , and contrary to the situation in yeast , mutation in AtZIP4 does not prevent synapsis , showing that both aspects of the Zip4 function ( i . e . , class I CO maturation and synapsis ) can be uncoupled .
During meiosis two successive chromosomal divisions follow a single S phase , allowing the transition from the sporophytic to the gametophytic state . This ploidy reduction occurs during the first meiotic division , when homologous chromosomes are separated from each other . For this to happen , homologous chromosomes must first associate in bivalents , linked by chiasmata—the cytological reflection of crossovers—that are established during meiotic prophase . Meiotic recombination is initiated by the induction of DNA double-strand breaks ( DSBs ) subsequently resected to generate 3′ single-stranded tails that invade the intact DNA duplexes that are used for DNA repair . Most of these events happen using the homologous chromosome as the template for DNA repair , to yield either crossover ( CO ) or noncrossover recombinant products [1] . In most organisms , the occurrence of a CO inhibits the occurrence of another event in a distance-dependent manner , resulting in COs more evenly spaced than would be expected if they occurred randomly . This phenomenon is known as interference [2] . At least two kinds of COs can coexist . In Saccharomyces cerevisiae , class I COs are interference-sensitive and their formation is dependent on the ZMM proteins ( Zip1 , Zip2 , Zip3 , Zip4 , Msh4 , 5 , and Mer3 ) [3] . Class II COs , however , are interference-insensitive and lead to randomly distributed COs requiring the Mus81 and Mms4 proteins [4] . While several of the recombination intermediates produced during the recombination processes have been described , our understanding of the mechanisms governing the different pathways , as well as their putative interconnections , remain largely unraveled . A detailed study of a set of five S . cerevisiae zmm mutants ( mer3 , msh5 , zip1 , zip2 , and zip3 ) demonstrated that the corresponding ZMM proteins are necessary for the correct progression from DSBs to stable single-end invasion ( SEI ) intermediates [5] . The biochemical functions of most of the actors are still under question , but recent data obtained on the Mer3 helicase [6] and on the Msh4/5 heterodimer [7] support the idea that the ZMM proteins bind to some early recombination intermediate to allow the formation of stable SEI intermediates , committing these to the interfering pathway . These multiple CO formation pathways do not coexist in all species [8] , but the recent characterization of Atmsh4 and Atmer3 mutants showed the existence of two CO classes in Arabidopsis , with a major type being sensitive to interference and a minor interference-insensitive type [9–11] . Another important feature of the first meiotic prophase observed in the vast majority of organisms is the transitory setup , between homologous chromosomes , of a structure called the synaptonemal complex ( SC ) [12] . SC assembly starts with the formation of a single protein axis ( called the axial element , AE ) along each pair of sister chromatids . Then , while homologue recognition and recombination take place , the AEs of homologous chromosomes ( then called the lateral element , LE ) are closely connected together in a process called synapsis . The central element ( CE ) of the SC is polymerized creating a ladder-like structure holding each chromosome close to its homologue ( for a review see [12–14] ) . A major component of the CE is a long coiled-coil protein ( Zip1 in budding yeast , ZYP1 in Arabidopsis , SYCP1 in mammals , see [14] ) , whose polymerization forms the transverse filament . The way the mature SC actually forms is still unknown . A considerable amount of descriptive cytogenetic studies , however , has shown that there is a general tendency for early synapsis to occur at or near chromosome ends . Subsequently , additional synaptic initiation sites may occur interstitially , with the number of these sites being highly variable . For example , animals are known to have few of these , whereas higher plants have many [13] . Recent molecular data from budding yeast studies showed that the formation of a mature SC ( i . e . , polymerization of Zip1 , formation of the CE ) depends on a protein complex called the “synapsis initiation complex” ( SIC ) [15] . There are now several known components of the SIC [16–18] that all belong to the ZMM group of proteins . It appears that binding of Zip3 onto chromatin recruits both Zip2 and Zip4 , which , in turn , induces Zip1 polymerization [17 , 18] . The biological function of these proteins is still poorly understood , but recent evidence suggests that they act on Zip1 polymerization through a pathway involving protein conjugation [19–21] . The fact that all the SIC components are necessary for class I COs , and that the number of SICs corresponds with the number of COs ( see Discussion ) , strongly suggests that , at least in S . cerevisiae , synapsis proceeds from class I CO sites [22 , 23] . The existence of such SICs in other eukaryotes , as well as their possible link with CO precursors remains to be elucidated . Furthermore , unlike other ZMM proteins , Zip proteins are poorly conserved among species [21] . In this article , we report the characterization of a putative higher eukaryote SIC component: the Arabidopsis ZIP4 protein . Our data clearly indicate that AtZIP4 belongs to the ZMM pathway because it is necessary for class I CO setup . However , its requirement for CE polymerization is not observed since complete synapsis is achieved in Atzip4 background .
In a screen for A . thaliana T-DNA ( Agrobacterium tumefaciens-transferred DNA ) insertions that generate meiotic mutants ( see Materials and Methods ) , we have isolated three allelic mutations corresponding to disruption of a predicted open reading frame of the Arabidopsis genome , At5g48390 , annotated as a putative tetratricopeptide repeat–containing protein . The first two mutations correspond to insertion alleles ( Figures 1 and S1 ) , whereas the third mutation corresponds to a deletion allele in which no amplification of any part of At5g48390 could be detected ( see Figure S1 ) . We isolated and sequenced the full-length At5g48390 cDNA from flower buds and found it encodes a 936-amino acid ( aa ) protein . Database searches using the BLASTP program ( Blosum 45 ) for proteins similar to that encoded by At5g48390 produced the highest scores ( outside the plant kingdom ) with several mammalian sequences similar to a testis-specific expressed sequence ( TEX11 , 18% identity and 38% similarity over 894 aas ) [24] . A second round of homology searches using TEX11 as the query revealed a significant similarity with the budding yeast Zip4/Spo22 protein ( 15% identity and 35% similarity over 532 aas , BLASTP , Blosum 45 ) . A multiple sequence alignment of putative ScSpo22/Zip4 orthologues revealed an overall conservation of this protein between S . cerevisiae , vertebrates , and plants , with conserved residues throughout the entire length of the protein ( Figure 1B ) and largely exceeding the putative tetratricopeptide repeat domains ( aa 134–167 and 443–517 found in PROSITE and Pfam databases ) . Reciprocally , iterate searches for putative ScZip4 homologues within the Arabidopsis genome using the PSI-BLAST program only picked up At5g48390 ( 19% identity and 35% similarity over 267 aas ) . These results led us to call the newly isolated gene AtZIP4 and the corresponding mutations Atzip4-1 and Atzip4-2 ( Figure 1A and 1B ) . The deletion allele ( Figure S1 ) was called Atzip4-3 . Reverse-transcriptase PCR ( RT-PCR ) studies showed that AtZIP4 , as with many Arabidopsis meiotic genes , is expressed at low level in roots and flower buds but not in leaves ( unpublished data ) . Furthermore , RT-PCR studies on flower bud cDNA from mutant plants showed that wild-type transcript is not detected in Atzip4-2 , and that a truncated form is expressed in Atzip4-1 ( Figure S1 ) . Nevertheless , no phenotypic difference could be detected between both alleles , either between these two insertion mutants and the deletion allele Atzip4-3 , suggesting that all of the three alleles correspond to null mutations , and that the partial AtZIP4 cDNA expressed in Atzip4-1 is not functional . All three Atzip4 mutants displayed the same phenotype: normal vegetative growth ( Figure 2 ) but short siliques ( Figure 2 , arrows ) suggesting fertility defects . The mean seed number per silique was 3 . 4 for Atzip4-1 ( n = 1 , 000 ) and 4 . 3 for Atzip4-2 ( n = 1 , 000 ) , whereas wild-type siliques contained on average 63 and 71 seeds per silique for Ws ( Atzip4-1 ecotype ) and Col-0 ( Atzip4-2 ecotype ) , respectively ( n = 50 ) . We examined the reproductive development of these mutants and found that Atzip4 are sterile due to abortion of male and female gametophytes ( unpublished data ) . Comparison of the early stages of microsporogenesis revealed no difference between wild-type and mutant plants ( Figure 2B and 2D ) : round pollen mother cells ( PMCs ) were found within the anther locules . In wild-type anthers , these cells underwent two meiotic divisions to produce a characteristic tetrad of microspores ( Figure 2C ) . Meiosis products were also detected in mutant plants , but they lacked the regular tetrahedral structure and were either asymmetric tetrads or “polyads” containing more than four products ( Figure 2E ) , suggesting that the meiotic program is disturbed in Atzip4 mutants . We therefore investigated male meiosis by staining chromosomes with 4′ , 6-diamidino-2-phenylindole ( DAPI ) . Wild-type Arabidopsis meiosis has been described in detail in [25] , and the major stages are summarized in Figure 3 . During prophase I ( Figure 3A–3D ) , meiotic chromosomes condense , recombine , and undergo synapsis , resulting in the formation of five bivalents , each consisting of two homologous chromosomes attached to each other by sister chromatid cohesion and chiasmata , which become visible at diakinesis ( Figure 3D ) . Synapsis ( the close association of two chromosomes via an SC ) begins at zygotene ( Figure 3B ) and is complete by pachytene , by which point the SC has polymerized along the whole length of the bivalents ( Figure 3C ) . At metaphase I , the five bivalents are easily distinguishable ( Figure 3E ) . During anaphase I , each chromosome separates from its homologue ( Figure 3F ) , leading to the formation of dyads corresponding to two pools of five chromosomes ( Figure 3G ) . The second meiotic division then separates the sister chromatids , generating four pools of five chromosomes ( Figure 3H and 3I ) , which gives rise to tetrads of four microspores ( Figure 2C ) . In Atzip4 mutants , the early stages of meiosis could not be distinguished from wild type: chromosomes appeared as threads at leptotene ( Figure 4A ) , condensed and synapsed ( Figure 4B ) until pachytene ( Figure 4C ) . Aberrations , however , appeared at early diakinesis in Atzip4 mutants , with cells showing a mixture of bivalents and univalents ( Figure 4D ) . At metaphase I , this defect became even more obvious with mutant cells showing a variable number of bivalents ( from 0 to 4 , Figure 4E–4H ) . During subsequent anaphase I , random segregation of the chromosomes was observed in the mutant ( Figure 4I and 4J ) . Then , in the second meiotic division , sister chromatids segregated normally ( Figure 4K ) , giving rise to a variable number of daughter cells containing aberrant numbers of chromosomes ( compare 3I to 4L ) . An analysis of female meiosis in Atzip4 identified defects similar to those seen during male meiosis ( unpublished data ) . Thus , AtZIP4 is involved in both male and female meiosis , and its disruption leads to a decrease in the number of bivalents . The level of meiotic recombination in Atzip4 mutants was estimated by two independent methods . First , the overall level of meiotic recombination was estimated by measuring the mean number of chiasmata at metaphase I on spread PMC chromosomes , as described in [26] . The Atzip4 alleles are in two different ecotypes ( Ws for Atzip4-1 and Atzip4-3 and Col-0 for Atzip4-2 ) , and because this measurement is known to vary among genotypes [27] , we compared chiasma frequency in all Atzip4 mutants to their respective wild type . As shown in Table 1 , we observed a strong decrease in chiasma formation in every mutant in comparison to wild types: 7 . 7 times less in Atzip4-1 , 5 . 6 times less in Atzip4-2 , and 9 times less in Atzip4-3 , corresponding to a residual level of chiasma of 12 . 9% for Atzip4-1 , 17 . 7% for Atzip4-2 , and 10 . 8% for Atzip4-3 , respectively . Statistical analyses on these data showed that if the mean chiasma number is different between Ws and Col-0 ( t test , p = 3 . 93216 10−15 ) and between all mutant and their respective wild types , there is no difference between the two Atzip4 alleles in Ws ecotype ( Atzip4-1 and Atzip4-3 , p = 0 . 40 , t test ) . Secondly , the level of recombination was calculated genetically on several intervals of Chromosome I ( Table 2 ) . Taking advantage of the mutants' different backgrounds , we crossed a heterozygous Atzip4-1+/− ( Ws ) plant with an Atzip4-2+/− ( Col-0 ) plant and in the F1 generation selected either Atzip4 mutants ( Atzip4-1Atzip4-2 ) or homozygous wild-type plants . In order to measure male meiosis recombination rates in wild-type and Atzip4 backgrounds , we then performed backcrosses between these lines and the Col-0 ecotype used as female . We chose microsatellite markers polymorphic between the two ecotypes to measure the percentage of recombination in the two genotypes ( wild type or Atzip4 mutant ) in this hybrid background Ws/Col-0 ( Table 2 ) . For the three intervals tested , we found that the level of meiotic recombination decreased by a factor of approximately 5 ( from 4 to 6 ) in the mutant background compared to wild type . Chiasma frequency in this hybrid background was also measured and found to be identical to the observed frequency in Ws background ( 7 . 6 ± 0 . 9 , n = 37 ) for the wild-type Ws/Col-0 and 0 . 92 ± 0 . 8 ( n = 105 ) for the Atzip4 mutant . These experiments demonstrate that the shortage of bivalents observed at metaphase I in Atzip4 mutants reflects a general reduction in CO formation . The decrease in recombination frequency varied from 5- to 9-fold depending on the method used , the allele tested , or the genetic background ( Tables 1 and 2 ) . The phenotype of Atzip4 mutants is similar to that of other recently described zmm Arabidopsis mutants , and specifically , Atzip4 mutants show a reduction in CO frequency comparable to that of the Atmsh4 mutant ( Table 1 ) . Thus , in order to check whether these genes belong to the same epistasis group , we quantified the level of remaining COs in the Atmsh4Atzip4 double mutant ( see Materials and Methods ) . We did not observe a significant decrease in the mean number of chiasmata per PMCs between Atzip4 and double Atmsh4Atzip4 ( t test , p > 0 . 05 ) , showing that these two genes function in the same pathway of CO formation . Because Atzip4 mutants display a strong decrease in CO frequency , we wondered whether the early stages of meiotic recombination were disrupted . We therefore analyzed the nuclear distribution of the DMC1 protein , which is an essential component of the recombination machinery . Its appearance on meiotic chromosomes during prophase is thought to reflect the progression of recombination repair . To date , DMC1 staining on meiotic chromosomes in plant cells has not been described . We therefore designed an antibody directed against a synthetic peptide specific to the DMC1 protein ( no signal in a dmc1 background , see Materials and Methods ) . To accurately define the temporal distribution of DMC1 throughout meiosis , immunolocalization studies were carried out by double-labeling wild-type and mutant PMCs with anti-DMC1 and anti-ASY1 ( a protein associated with the AE of the SC , [28] ) antibodies . In wild-type cells , DMC1 foci appeared at mid-leptotene , when ASY1 was detectable as continuous stretches ( Figure 5A ) and persisted during zygotene when ASY1 localized to full-length chromosome axes and the chromosomes started to synapse ( Figure 5B ) . Quantification of the number of foci observed at these stages showed a mean number of foci in Ws PMCs of 235 ± 84 ( n = 43 ) . DMC1 staining then tended to disappear , and only a few residual DMC1 foci could be seen by the pachytene stage ( Figure 5C ) . A similar pattern of DMC1 labeling was observed in Atzip4-1 , with strong fluorescence from mid-leptotene to zygotene , and reduction in the number of foci while synapsis proceeded , until finally at pachytene fluorescent foci were no longer visible ( Figure 5D–5F ) . Nevertheless , quantification of the DMC1 signal ( all stages taken together ) showed that the mean number of foci observed in the mutant background was slightly but significantly ( t test , p = 0 . 002 ) higher than in wild type , with a mean number of foci of approximately 294 ± 75 ( n = 46 ) . This suggests that in Atzip4 the dynamics of DSB formation and/or repair may be slightly modified , but excludes the possibility that the shortage in chiasmata is a consequence of an overall decrease in meiotic recombination events . We tested for interference by comparing the number of single and double COs in two adjacent intervals of Chromosome I ( Table 3 ) . In wild type , chromosomes that recombined in interval I showed a strong decrease in the frequency of COs in adjacent interval II ( 7 . 2% recombination in II when COs have occurred in I to be compared to 19 . 3% without preselection of recombinants in interval I ) and vice versa ( 12 . 5% compared to 33 . 45% ) . This can be expressed by the coefficient of coincidence ( CC ) defined as the proportion of observed double COs divided by the expected proportion of double COs if they were independent ( that is , the product of each individual CO frequency ) [2] . When COs in the two intervals are independent the CC is 1 , whereas the stronger the interference between two adjacent COs , the lower the CC . As shown in Table 3 , the wild-type CC for the two intervals was 0 . 37 . Statistics performed on this data showed that in wild type the proportion of single and double COs deviates highly significantly from that expected without interference ( χ2 = 25 . 4 , p < 0 . 001 ) . In the Atzip4 background , we found a CC close to 1 ( Table 3 ) , and statistical analyses of these results confirmed that the proportion of double CO was very close to that predicted without interference ( χ ( 1 ) 2 = 0 . 046 , p > 0 . 1 ) . On the contrary , we found that the results obtained in Atzip4 are significantly different ( χ ( 1 ) 2 = 5 . 79 , p < 0 . 025 ) from the expected distribution obtained by applying the wild-type CC of 0 . 37 . Thus , the COs occurring in these two adjacent intervals in Atzip4 are not sensitive to interference . From observations of DAPI-stained preparations , chromosomes in Atzip4 mutants appeared to be able to synapse ( compare Figure 3C to 4C ) . To fully understand the effect of the Atzip4 mutations on SC formation , meiotic chromosomes were immunolabeled with antibodies against ASY1 and ZYP1 ( a major component of the CE of the SC , [29] ) . There was no obvious difference in mutant compared to wild-type cells ( Figure 6 ) . Briefly , we observed axial staining with ASY1 that commenced during early prophase and became visible as threads while leptotene progressed ( Ws , Figure 6A; Atzip4-1 , Figure 6M ) . ZYP1 appeared very early on chromosomes ( defining the beginning of zygotene stage , that is , the beginning of synapsis ) as foci that quickly elongated yielding a mixture of foci and short stretches of ZYP1 labeling ( Figure 6B–6H for wild type; Figure 6N–6T for Atzip4-1 ) . The number of these first ZYP1 sites varied from one to more than 20 . Synapsis then progressed very asynchronously with some bivalents completing synapsis before others had hardly started ( Figure 6I and 6J for wild type and Figure 6U and 6V for Atzip4-1 ) . Finally , complete synapsis was observed in both genotypes ( Figure 6K and 6L for wild type and Figure 6W and 6X for Atzip4-1 ) . In order to detect possible differences in synapsis efficiency between mutant and wild type , we measured the proportion of cells showing full synapsis ( pachytene stage , Figure 6K–6L and 6W–6X ) among the group of cells that were immunolabeled by anti-ZYP1 in wild type and mutant . These proportions were found not to be statistically different ( χ ( 1 ) 2 = 2 . 15 , p > 0 . 14 ) with 44 . 8% of full pachytene for wild type ( Ws , n = 174 ) versus 37 . 8% for mutant cells ( Atzip4-3 , n = 262 ) . We also measured the total length of the SC at pachytene and found that it was the same in both genotypes: 154 ± 31 μm in wild type ( Ws , n = 15 ) and 153 ± 23 μm in Atzip4-1 ( n = 23 ) . Therefore , AtZIP4 is not required for synapsis to proceed . We quantified early synapsis events by counting the number of ZYP1 stretches in early to mid-zygotene , that is , as soon as ZYP1 labeling can be detected on chromosomes and until it covers less than 40% of the nuclei that correspond to nuclei of Figure 6B–6H and 6N–6T . We found that the mean number of synapsis sites per nucleus was significantly different between Atzip4-1 and wild-type ecotype Ws ( t test , p < 0 . 001 ) . For the wild type the mean number of ZYP1 stretches was 7 . 6 ± 3 . 2 ( mean ± SD , n = 43 ) , whereas it was only 4 . 9 ± 2 . 8 ( n = 39 ) for Atzip4-1 . Therefore , the Atzip4 mutation may not prevent full synapsis from occurring , but it can modify synapsis initiation and/or synapsis dynamics .
Recent studies suggest that like S . cerevisiae , Arabidopsis possesses at least two CO pathways . The major ( class I ) pathway depends on AtMSH4 [9] , AtMSH5 ( F . C . H . Franklin and R . Mercier , personal communication ) , AtMER3 [10 , 11] , and possibly a newly identified gene called PTD [30] . We show here that AtZIP4 is likely to be another key player in this pathway . First , we showed that the AtZIP4 protein is necessary for 85% of the meiotic COs in Arabidopsis , as are AtMSH4 [9] and AtMSH5 ( F . C . H . Franklin and R . Mercier , personal communication ) , and we demonstrated that AtMSH4 and AtZIP4 belong to the same epistasis group , with regards to their effect on CO level . Secondly , the ZMM proteins are thought to specifically drive the formation of class I but not class II COs . Accordingly , the remaining COs observed in the zip1 , mer3 , and msh4 budding yeast mutants no longer display interference [18 , 31–33] and those in zip4 display negative interference [18] . In the case of Atzip4 , genetic analysis using two sets of adjacent markers on Chromosome I showed that the occurrence of remaining COs in this part of the genome was not subjected to interference . This situation seems to be the same for the other Arabidopsis ZMM proteins identified so far: the remaining COs in ptd and Atmsh4 are randomly distributed among cells , consistent with an absence of interference by one CO on another [9 , 30] , and genetic analysis showed that the occurrence of remaining COs in Atmer3 did not display interference [10] . Lastly , the study of early recombination events in Atzip4 , by immunolabeling with anti-DMC1 , demonstrated that even if the dynamics of DSB repair are modified in the Atzip4 background , the CO defects observed do not reflect an overall decrease in recombination events . The same results have been reported for Atmer3 [10] and Atmsh4 [9] , showing that all these mutants are defective in the maturation of recombination events leading to class I CO formation . Therefore , we can conclude that AtZIP4 possesses all the characteristics of a ZMM protein . As suggested by our observations of DMC1 foci , it seems highly likely that in the zmm mutant backgrounds , recombination is initiated at the wild-type level , but that CO maturation is prevented . Because chromosome fragmentation was never observed in any of the Arabidopsis zmm mutants ( this study or [9 , 10] , for example ) , DSB repair appears to still take place . Unfortunately , we cannot decipher which repair pathway is in use ( repair onto the homologous chromosomes yielding noncrossover products or onto the sister chromatid , for example ) . These data are consistent with data from budding yeast zmm mutants in which no modification in DSB levels was observed [5 , 32] , but DSB repair was affected at steps yielding stable SEI molecules [5] . zmm mutants ( and zip4 in particular ) show decreased CO formation without noncrossover increase [5 , 16 , 18] , and most DSBs disappeared because they were either degraded or repaired through nonconventional pathways [5] . In budding yeast , formation of the SC depends on a protein complex called the SIC [15] . So far , Zip2 , Zip3 , and Zip4 are the known key components of the SIC . These three proteins are not necessary for initial binding of Zip1 to chromosomes but are necessary for the progression of synapsis [18] . Zip2/Zip4 are thought to play vital roles in synapsis initiation [18] , whereas the function of Zip3 might be to stabilize the Zip2/Zip4 complex onto chromosomes . The Zip proteins are poorly conserved among eukaryotes [21] , but a Caenorhabditis elegans Zip3 orthologue was described recently [34] . Synapsis proceeded normally in the C . elegans zhp-3 mutant even though CO formation was defective . Nevertheless , unlike meiosis in most organisms ( see below ) , synapsis in C . elegans is totally uncoupled from recombination; therefore , generalizations regarding this apparent divergence in SIC function as it may apply to other higher eukaryotes are hard to make . Our results on another core component of the SICs ( Zip4 ) show that in A . thaliana the role of Zip proteins as SIC components is also not conserved ( not only normal pachytene stages are achieved in Atzip4 mutants , but these occur at wild-type frequency ) , while synapsis is indeed dependent on recombination in Arabidopsis [35] . Therefore , the two aspects of Zip4 function , recombination control and synapsis setup , can be uncoupled . Nevertheless , we cannot exclude a role , direct or not , of AtZIP4 in early synapsis since we observed a 35% decrease of early ZYP1 foci number in Atzip4 mutants . This diminution could reflect either a global diminution of the numbers of sites from which Zip1 polymerization proceeds , or , alternatively , it might reflect a perturbation of synapsis dynamic in Atzip4 mutants . Data obtained in budding yeast suggest that most , if not all , SC initiation sites correspond to CO sites . Indeed , good correlations were observed between the number of COs and the number of Zip3 foci . For example , when the CO frequency decreased in leaky spo11 mutants , [36] observed a correlation between the amount of Zip3 foci , SC formation , and CO level . Reciprocally , the increased CO frequency observed in a sgs1 mutant was accompanied by an increase in Zip3 foci [37] . Therefore , the idea emerged that CO intermediates ( and only those leading to class I COs ) provide the sites for Zip1 nucleation [1 , 22 , 23] . The situation is less clear in other organisms . In many species synapsis progression was investigated by counting SC stretches on silver-stained early zygotene chromosomes . Even if this technique probably underestimates the number of SC initiation sites , it gives an idea of the synapsis initiation pattern . Synapsis appears to commonly take place at least at the terminal or subterminal region of chromosomes . Furthermore , a variable number of interstitial initiation sites has also been observed [13 , 38] . Plants are known to have high numbers of such synapsis initiation sites ( for example , 76 SC segments/nucleus in rye [39] , up to 300 in Tradescantia [40] , and up to 36 for a single lily bivalent [41] ) . The average chiasmata number per bivalent , however , is much lower and hardly varies , at around 1–3 per bivalent ( 2 . 45 per bivalent for the lily , for example ) . Animals have much lower numbers of interstitial pairing sites [42] , but even so , the ratio between synapsis initiation sites and chiasmata can be higher than 1 [43] . Lastly , immunocytology studies on mouse showed that in mammals , synapsis can proceed from sites different than CO sites ( cited in [14] ) . In this study , we show that when 85% of COs ( which probably represent all the class I COs ) are suppressed in Arabidopsis , synapsis is not prevented . More precisely , in Atzip4 mutants we observed an average of one chiasma per meiocyte , whereas the five chromosome pairs still synapsed at pachytene , showing that the absence of CO within a bivalent does not prevent synapsis from occurring . More generally , only mild synapsis defects were reported for the other Arabidopsis zmm mutants [10 , 11 , 30] . In the case of Atmsh4 , it has been shown that prophase I is delayed compared to wild type ( from 30 to 38 h ) suggesting that the timing of synapsis could be modified when an Arabidopsis ZMM is not functional [9] . In the case of Atzip4 mutants , the observation that the average number of synapsis tracks was significantly lower than in wild type suggests that if CO I intermediates are not absolutely required for synapsis in plants they may correspond to some of the synapsis initiation sites . This could explain why examples of correlation between synapsis initiation sites and CO sites were reported in plants , such as in chromosomal inversions of maize ( see [44] , for example ) . In conclusion , our results show that , in Arabidopsis , synapsis either does not depend on CO I , or depends upon CO I precursors upstream of the ZMM proteins . Furthermore , in Arabidopsis , synapsis initiation sites may coincide with sites of future CO formation , but this does not appear to be a unique or indispensable relationship . We have shown that CO I intermediates are not necessary for synapsis in Arabidopsis; nevertheless , it is clear that recombination and synapsis remain strongly connected in most higher eukaryotes . Drosophila melanogaster and C . elegans are the only organisms in which the two processes are uncoupled since both can form normal SCs in the absence of any recombination [45 , 46] . To date , these appear to be exceptions since all the other organisms studied ( A . thaliana , mouse , yeast , coprinus ) are asynaptic when DSBs are prevented [47] . Ultrastructural studies performed on different plant species showed that synapsis proceeded from sites of AE interaction ( axial associations ) that load early recombination nodules ( RAD51-containing nodules ) , establishing the link between recombination and synapsis [48–51] . In Arabidopsis , these nodules have not been described because of the difficulties involved in preparing chromosomes for electron microscopy in this species . Nevertheless , in Arabidopsis , the early association of ZYP1 with chromosomes in foci and its subsequent extension was shown to depend on AtSPO11–1 and AtDMC1 , respectively [29] , showing that normal synapsis is dependent upon early recombination intermediates as in other species . Nevertheless , close to 250 early recombination intermediates can be observed in Arabidopsis ( as estimated by the number of RAD51/DMC1 foci ) , whereas the number of ZYP1 initial foci does not exceed 20 ( this study and [29] ) . Thus , it appears that only a minority of these early recombination intermediates are actually acting as synapsis initiation sites . The way these are selected , as well as the specific components of synapsis initiation complexes in higher eukaryote , remains to be elucidated .
The Atzip4-1 mutant ( EJD21 line ) and Atzip4-3 ( EFS349 line ) were obtained from the Versailles Arabidopsis T-DNA transformant collection [52] . Mutant screening was performed as described in [53] . The Atzip4-2 mutant , line Salk_068052 , was obtained from the collection of T-DNA mutants at the Salk Institute Genomic Analysis Laboratory ( SIGnAL , http://signal . salk . edu/cgi-bin/tdnaexpress ) [54] and provided by the Nottingham Arabidopsis Stock Centre ( NASC ) ( http://nasc . nott . ac . uk ) . The Atmsh4 mutant corresponds to line Salk_136296 and was described in [9] . Arabidopsis plants were cultivated in a greenhouse or growth chamber under the following conditions: photoperiod 16 h/day and 8 h/night; temperature 20 °C day and night; humidity 70% . Isolation of Atzip4-1: the EJD21 line segregated 3:1 for the meiotic mutation ( revealing the presence of a single recessive mutation ) and 15:1 for kanamycin resistance ( one of the T-DNA markers ) , suggesting the presence of at least two inserts . After crossing to wild type , linkage between a single T-DNA insert and the meiotic phenotype was checked as described in [35] . We tested for allelism between the Atzip4-1 and Atzip4-2 mutations by crossing Atzip4-1−/+ and Atzip4-2−/+ . Among the F1 plants , one-fourth was semi-sterile and possessed each of the mutant alleles . Double mutants for Atmsh4 and Atzip4-2 were obtained by crossing plants heterozygous for each mutation . The resulting hybrids were self-pollinated . We used PCR screening to select the sterile plants in the F2 progeny homozygous for both mutations . Recombination rates and interference study: Plants heterozygous for Atzip4-1 mutation ( Ws ecotype ) were crossed to heterozygous plants for Atzip4-2 ( Col-0 ecotype ) . F1 plants , either homozygous semi-sterile Atzip4-1/Atzip4-2 or homozygous fertile AtZIP4+/+ , were selected after PCR genotyping and crossed onto a wild-type Col-0 plant . Progeny were sown in vitro and genotyped for several loci on Chromosome I with microsatellite markers showing polymorphisms between the two ecotypes Ws and Col-0: msat1 . 55 , msat1 . 12 , F5I14 , and nga280 ( [55] and http://www . inra . fr/vast/msat . php ) . For interference studies , plants showing recombined chromosomes in interval I ( msat1 . 55 and msat1 . 12 ) and/or in adjacent interval II ( msat1 . 12 and nga280 ) were scored as well as the plants that have not recombined in one or the other of the interval . We tested for deviation from an expected repartition with or without interference by means of a Chi-squared ( χ2 ) test , applying a degree of freedom of 1 . Isolation of plant T-DNA flanking sequences: The right border of the T-DNA insert of Atzip4-1 was isolated using kanamycin rescue experiments , according to [56] . The left border of T-DNA insert in Atzip4-1 was PCR amplified ( P4 and LbBar2 ) and subsequently sequenced , showing the T-DNA was inserted in a predicted open reading frame of the Arabidopsis genome , At5g48390 . Sequencing of AtZIP4 cDNA: cDNA synthesis was performed with Superscript RT ( Invitrogen , http://www . invitrogen . com ) from total RNA ( 3 μg ) extracted from Ws young flower buds . 3′ RACE experiments were performed using Invitrogen system for Rapid Amplification of cDNA Ends , version 2 . 0 . For 3′ RACE experiments specific primers used were P3: GGGTCAAGGTGTGGGAAGGA and P8: GTGGTGAATTCTTGAGGCTGGC . RACE products were cloned into pCR2 . 1-TOPO ( Invitrogen ) and sequenced . Oligonucleotides for PCR genotyping: The right border of the Atzip4-1 T-DNA was amplified by PCR with primers P4: CCGTGTATGTCATACGCAAGT and TAG3:CTGATACCAGACGTTGCCCGCATAA; the left border was amplified with P3: GGGTCAAGGTGTGGGAAGGA and LbBar2: CGTGTGCCAGGTGCCCACGGAATAG . Wild-type AtZIP4 was amplified with primers P3 and P10: CCAACCCGATGCTCAGCCA . For Atzip4-2 , oligonucleotides P3R: TCCTTCCCACACCTTGACCC and P5: GACTGCTGGAGCAGAAACT were used for the wild-type allele and P3R with LbSALK2: GCTTTCTTCCCTTCCTTTCTC for the mutant allele . AtMSH4 wild-type allele was amplified using primers 636296U: CTTCTTGCAGGTTGTGTTTG and 636296L: GCCAGCTGTTTTTGTTGTC and mutant allele using 636296L and LbSalk2 . Protein sequence similarity searches were performed at the National Center for Biotechnology Information ( http://www . ncbi . nlm . nih . gov/BLAST ) and at the Arabidopsis Information Resource ( TAIR , http://www . arabidopsis . org/Blast ) , using BLOSUM45 matrix and default parameters . Sequence analyses were performed with BioEdit software ( http://www . mbio . ncsu . edu/BioEdit/bioedit . html ) . The anti-ASY1 polyclonal antibody has been described elsewhere [28] . It was used at a dilution of 1:500 . The anti-ZYP1 polyclonal antibody was described by [9] . It was used at a dilution of 1:500 . The anti-DMC1 antibody was obtained by immunizing a rabbit with a synthetic peptide conjugated with KLH ( Eurogentec , http://www . eurogentec . com ) . The synthetic peptide consisted of 18-aa residues from positions 1 to 18 of the Arabidopsis DMC1 protein ( mmaslkaeetsqmqlver ) and was designed so that the anti-DMC1 antibodies would specifically recognize AtDMC1 and not cross-hybridize with AtRAD51 . Rabbit anti-DMC1 antibodies were purified as described in [57] . Specificity of the purified anti-DMC1 antibodies was checked by including the dmc1 mutant [58] as a negative control in immunolocalization experiments . The working dilution of the purified serum for cytology was 1:20 . Comparison of early stages of microsporogenesis and the development of PMCs was carried out as described in [35] . Preparation of prophase stage spreads for immunocytology was performed according to [28] with the modifications described in [59] . All observations were made using a Leica ( http://www . leica . com ) DM RXA2 microscope; photographs were taken using a CoolSNAP HQ ( Roper , http://www . roperscientific . com ) camera driven by OpenLAB 4 . 0 . 4 software; all images were further processed with OpenLAB 4 . 0 . 4 or AdobePhotoshop 7 . 0 ( http://www . adobe . com ) . SC length measurement was performed using Optimas ( Bioscan Incorporated , http://www . bioscan . com ) software .
GenBank ( http://www . ncbi . nlm . nih . gov/Genbank ) accession number for AtZIP4 cDNA is EF176583 . The accession number for HsTEX11 is AAH36016 , Rice NP_915110 , and Zebrafish XP_692604 . The accession number for the budding yeast Zip4/Spo22 protein is NP_012192 .
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During meiosis two successive chromosomal divisions follow a single S phase , resulting in the formation of four haploid cells , each with half of the parental genetic material . This ploidy reduction occurs during the first meiotic division , when homologous chromosomes ( paternal and maternal ) are separated from each other . For this to happen , homologous chromosomes associate in bivalents , where each chromosome is linked to its homologue by chiasmata . These chiasmata reflect the formation of crossovers , one of the manifestations of the exchange of genetic material occurring during homologous recombination . Another important feature of the meiotic prophase is the transitory setup ( synapsis ) , between homologous chromosomes , of a tripartite protein structure called the synaptonemal complex , amazingly conserved among species , but which function remains a puzzle despite half of a century of extensive survey . In this study , we investigate the relationships between these two crucial meiotic events using the model plant Arabidopsis thaliana . We show that in this plant , crossover formation and synapsis completion can largely be uncoupled .
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"cell",
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2007
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Zip4/Spo22 Is Required for Class I CO Formation but Not for Synapsis Completion in Arabidopsis thaliana
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It has come to light that Zika virus ( ZIKV ) infection during pregnancy can result in trans-placental transmission to the fetus along with fetal death , congenital microcephaly , and/or Central Nervous System ( CNS ) malformations . There are projected to be >9 , 200 , 000 births annually in countries with ongoing ZIKV transmission . In response to the ZIKV threat , the World Health Organization ( WHO ) is strategically targeting prevention of infection in pregnant women and funding contraception in epidemic regions . I propose that the damaging effects of ZIKV can be reduced using a seasonal window of opportunity for conception that may minimize maternal exposure . Like other acute viral infections—including the related flavivirus , dengue virus ( DENV ) —the transmission of ZIKV is anticipated to be seasonal . By seasonally planning pregnancy , this aspect of pathogen ecology can be leveraged to align sensitive periods of gestation with the low-transmission season .
The Zika virus ( ZIKV ) is a mosquito-transmitted virus—vectored by Aedes aegypti—spreading rapidly across the globe [1] . Pregnant women infected with ZIKV risk severe fetal outcomes , including brain abnormalities—believed to be due to disruption of brain development caused by intrauterine infection—and death [2 , 3] . ZIKV was the suspected cause of the 2015/2016 outbreak of microcephaly in Brazil [4] , and scientific consensus has now been reached that prenatal ZIKV infection causes microcephaly and other forms of brain abnormalities . Upon maternal infection , however , the risk of such fetal outcomes remains unknown [5] . In April 2016 , the causal link between ZIKV and microcephaly was inferred via several independent lines of evidence , including ( 1 ) microcephaly and brain abnormalities in infants born to mothers with suspected or confirmed ZIKV infection during the first or second trimester of pregnancy , ( 2 ) the rare form of microcephaly in infants with congenital Zika syndrome ( CZS ) , distinguishing it from microcephaly resulting from other causes , and ( 3 ) birth defects occurring in women with travel-acquired ZIKV , coupled with the low probability that these events were coincident and not causal [5] . Several reports from February to May 2016 have now provided strong evidence for the causal link . A retrospective study of the 2013/2014 ZIKV outbreak in French Polynesia found a 14-fold increase in severe microcephaly in newborns and fetuses following the epidemic; amniotic fluid tested positive for ZIKV in 4 of 7 women sampled after identification of fetal abnormalities [6] . In addition , in Brazil , 42 ZIKV-positive pregnant women were tested for fetal abnormalities . Adverse findings—including fetal death , microcephaly , and central nervous system ( CNS ) damage—were observed in 12 of the women . There were no abnormalities in ZIKV-negative women [2] . Lastly , the complete ZIKV genome was recovered from the brain of a fetus with microcephaly aborted by an expectant mother infected during the 13th week of gestation [7] , and the Centers for Disease Control ( CDC ) reported on two newborns from Brazil with microcephaly who died shortly after birth , as well as two miscarriages; all tested positive for ZIKV [8] . In addition to the epidemiological evidence , newly developed mouse models of ZIKV have demonstrated that ZIKV strains from French Polynesia and Brazil can infect the fetus via the placenta and cause intrauterine growth restrictions and/or fetal loss [9 , 10] . Culture models of early brain development have also shown ZIKV can cause neural cell death [10 , 11] . Recognizing the incomplete picture of ZIKV in utero pathology , in February 2016 , the WHO declared the cluster of microcephaly in Brazil to be a Public Health Emergency of International Concern , and the International Health Regulations Emergency Committee issued recommendations to reduce ZIKV infections in pregnant women [4] . In the United States , $1 . 9 billion has been requested of congress to respond to ZIKV domestically and internationally [12] . Maternally transmitted viral infections , such as ZIKV , can be prevented by protecting pregnant women from infection , but it is likely to be many years before a ZIKV vaccine or treatment is developed . Alternative preventative measures are therefore needed to protect women and their children from this emerging pathogen . Two key components of the ZIKV response by governments and health agencies are ( 1 ) vector control and ( 2 ) preventing infection in pregnant women . The WHO’s ZIKV operational response plan includes control of Aedes aegypti mosquitoes and financing contraceptive services in affected areas to manage pregnancy and mitigate the impact of ZIKV [4] . At the CDC’s April 2016 Zika Action Plan Summit , the CDC Director acknowledged “the control of Aedes aegypti is challenging” and declared that decreasing the risk of ZIKV to pregnant women and women of childbearing age is a key priority [13] . Government officials in El Salvador , Colombia , and Ecuador have recommended women delay pregnancy while uncertainty surrounding ZIKV remains . The WHO ZIKV Q&A website ( updated regularly ) states , “Women wanting to postpone pregnancy should have access to a comprehensive range of reversible , long- or short-acting contraceptive options to the full extent of the law” [14] . The CDC has issued recommendations for ZIKV-exposed couples to delay pregnancy . Exposed women and exposed asymptomatic men are recommended to wait 8 weeks , and men with symptoms are recommended to wait 6 months [15] . No official stance on delaying pregnancy has been taken for unexposed women . Problematically , the public is receiving a mixed message highlighted by media coverage [16–18] . Given that extended delays of pregnancy may not be a viable option for millions of women living in ZIKV-epidemic regions , I propose a strategy that will reduce intrauterine ZIKV infection risk without requiring long-term delays of pregnancy . Specifically , I recommend that public health and research communities focus on three current ZIKV knowledge gaps: These aspects of ZIKV biology can be integrated with incidence data and mathematical models to inform interventions , including reducing transmission ( i . e . , vector-to-human and sexual ) via vector control and behavioral changes , planning pregnancy to avoid the high-transmission season , launching vaccines once developed , and reducing intrauterine transmission and pathology . Knowledge gap 3 ( immunity ) will be particularly important for understanding the recurrent epidemic dynamics of ZIKV and CZS . If ZIKV antibodies either wane or do not fully protect from infection , then we could expect women of childbearing age to be susceptible to ZIKV after their primary infection ( which might occur during the first epidemic wave ) .
Seasonality is a common feature of acute infectious diseases [19–24] , including flaviviruses like dengue virus ( DENV ) , West Nile virus ( WNV ) , yellow fever virus ( YFV ) , and other arboviruses vectored by Aedes aegypti ( i . e . , chikungunya virus [CHIKV] ) [25–29] . Although infectious diseases are seasonal , the timing of the high-transmission season can ( 1 ) vary among pathogens within a country and ( 2 ) vary among countries/regions for a given pathogen [30] . The drivers of DENV , WNV , YFV , and CHIKV seasonality are likely some combination of vector phenology , climate conditions , and additional host or environmental factors . In general , climatic , physiological , and behavioral factors that influence transmission seasonality include those that impact host and/or vector susceptibility to infection , host/vector infectiousness , virus viability , the transmission-relevant contact rate among hosts/vectors , the density of hosts , and vector abundance [19 , 24 , 30] . Aedes aegypti has seasonal variation in its ability to facilitate flavivirus transmission because its abundance and competence as a vector are affected by temperature and rainfall [31 , 32] . Using data from Puerto Rico—one of the US locations with ongoing ZIKV transmission—Fig 1A demonstrates the seasonal abundance of blood-fed female Aedes aegypti , which transmit ZIKV . Aedes aegypti seasonality affects seasonal transmission of DENV and CHIKV [31 , 33] and it is likely to impact seasonal ZIKV transmission . In regions with strong seasonal fluctuations in Aedes aegypti , seasonal changes in abundance and vector competence should be characterized and used to estimate the local timing of the high-transmission season . A key reason for characterizing transmission seasonality and pinpointing the high transmission season is because its timing will affect the risk of microcephaly in birth cohorts . This is because births are seasonal across human populations , and there is a distinct birth pulse in most countries/regions that varies geographically in its seasonal timing [34 , 35] . Fig 1B shows the birth seasonality in Puerto Rico , with the birth peak from August–October . Due to birth seasonality , the percent of pregnancies experiencing a specific trimester is not evenly distributed throughout the year ( Fig 1D ) . For any given country , the timing of the seasonal birth pulse relative to the ZIKV transmission season will therefore determine the fraction of pregnancies at risk for maternal infection and congenital ZIKV . For example , if a country has a birth pulse in which sensitive gestational periods coincide with the ZIKV season , more pregnancies in that country will be at risk than elsewhere . Fortunately , if access to contraceptives and family planning practices are proactively targeted for intervention , then the birth pulse could be intentionally shifted and amplified regionally to minimize the risk of intrauterine ZIKV infection for entire birth cohorts .
At this time , there are insufficient data to predict the seasonal timing and frequency ( i . e . , annual , biennial , triennial , etc . ) at which ZIKV epidemics will occur . The ZIKV outbreak in Brazil peaked between July 12–18 , 2015 [39] , which is out-of-phase with DENV epidemics in Brazil , which consistently peak around March [40] . This suggests the seasonal timing of DENV epidemics might not be useful in predicting the timing of ZIKV . Importantly , however , the first epidemic wave of ZIKV may not reflect ZIKV’s future recurrent epidemic timing . The first wave of the epidemic may differ from future recurrent epidemics because ( 1 ) clinical recognition and reporting of cases may lag far behind pathogen introduction , ( 2 ) the first wave occurs in a fully susceptible population , which will alter the epidemic growth curve and the time until susceptible depletion , and ( 3 ) the timing of epidemic onset will be influenced by pathogen introduction as opposed to recurrent epidemics in locations with unbroken transmission chains , the onset of which is influenced by the build-up of the susceptible population and seasonal transmission [20] . As ZIKV incidence data become available , the annual transmission “high-season” and “low-season” should be characterized so pregnancy may be planned such that sensitive periods of gestation are aligned with the low-season window of opportunity . After the initial wave of the epidemic , ZIKV transmission models can be fitted and transmission parameters estimated using time series data from ZIKV surveillance . Fig 2 provides a potential ZIKV Susceptible-Infected-Recovered transmission model developed with a focus on the demography relevant to congenital ZIKV . To estimate seasonal transmission parameters , this model would require extensive time series data on reported ZIKV cases either weekly or monthly . To overcome data limitations , data from other ZIKV surveillance systems could be used in parallel to parameterize such a model . Surveillance data that could be used to study ZIKV transmission and pathology include reported cases , registries of miscarriage and CZS , ZIKV serology data , and mosquito surveillance data . Models with similar levels of complexity in transmission , pathology , and demography have been parameterized for poliovirus and measles [35 , 41]; see [42] for statistical inference methods . By combining transmission models with reported ZIKV cases , data on vector abundance , and other covariates that could influence transmission ( e . g . , temperature , humidity , and human movement ) , the underlying mechanistic drivers of ZIKV transmission seasonality could be revealed ( knowledge gap 1 ) . Assuming vector abundance is an important driver of ZIKV seasonal transmission , based on the Aedes aegypti data from Puerto Rico , the high-transmission season in Puerto Rico would occur between October–December and the trough would be April–June ( Fig 1A ) . The impact of vector abundance on flavivirus transmission is indicated by the 2013 DENV epidemic in Puerto Rico , which had a trough in April ( Fig 1C ) , as would be predicted based on vector seasonality . Importantly , the high and low transmission seasons are tied to local climate conditions and will therefore be region-specific . With knowledge of regional transmission seasonality , initiating pregnancy during the seasonal window of opportunity for conception would minimize risk of maternal infection and subsequent damage to the fetus . Birth defects resulting from in utero infection with CMV , herpes simplex , and rubella virus are reported to be highest when maternal infection occurs within the first 20 weeks of gestation [43–45] . Miscarriages of known ZIKV-positive fetuses have been reported at 11 and 13 weeks gestation [8] . Preliminary data suggest miscarriage and CZS are most likely when maternal infection occurs during the first or second trimester [5 , 6 , 46 , 47] , but fetal abnormalities have been found in women infected with ZIKV during weeks 8–35 of gestation [2] , indicating all three trimesters are vulnerable to some extent . The critical window of susceptibility for ZIKV-induced miscarriage and CZS needs to be identified and taken into account when determining the seasonal window of opportunity for conception . Identifying the period of susceptibility for the fetus and using planned seasonal conception to redistribute births—i . e . , to take advantage of the transmission low season and ensure sensitive gestation occurs during the ZIKV low season—would reduce risk to the fetus by minimizing maternal exposure . Based on the size of the 2014 birth cohort in Puerto Rico , redistributing births even by a small amount , for example with as little as 3% fewer births experiencing a susceptible trimester during the high transmission season , would translate to reducing risk for approximately 1 , 000 births annually . In a large country like Brazil , which had a birth cohort of approximately 3 million in 2015 [48] , planned seasonal conception for 3% of births could reduce risk in >88 , 000 pregnancies . The absolute reduction in risk , however , is unknown , as it will depend on the incidence of ZIKV infection in the population and the subsequent risk of trans-placental transmission and fetal abnormalities . Fig 3A shows the window of opportunity for conception when the high transmission season lasts 13 weeks and the fetus is susceptible during various periods of gestation . The window of opportunity depends on three key factors: ( 1 ) the timing of the transmission trough ( i . e . , the week ( s ) or month of the year when transmission is at a minimum ) , ( 2 ) the susceptible period of gestation , and ( 3 ) whether the severity of congenital ZIKV infection varies during the susceptible period of gestation . For example , it may be that the first two trimesters are susceptible to fetal abnormalities , but the first trimester is the most vulnerable . Knowing the distribution of susceptibility throughout the gestational weeks would impact the timing of planned conception . Assuming the period of susceptibility spans gestation weeks 1–20 , with the first trimester being highly susceptible and therefore given high priority for protection , Fig 3B and 3C show how the seasonal distribution of conception could be shifted and amplified to reduce ZIKV risk in Puerto Rico . In general , although tailoring conception seasonally will not alleviate risk of maternal exposure to ZIKV , it could reduce risk and provide an option for women as they wait for a ZIKV vaccine and/or clinical interventions . Planned seasonal conception would be an effective low-cost means of empowering women to protect themselves and their children . The feasibility and implementation of this strategy would require collaboration among vector ecologists , epidemiologists , and social scientists . In order to seasonally time pregnancy , A key unknown is the susceptible period of gestation; when this period is determined , then seasonally planning pregnancy could be integrated into the growing portfolio of ZIKV interventions . The feasibility and acceptability of planning conception seasonally will need to be addressed regionally with careful consideration of women’s reproductive rights and personal values . An R-package including data used in this manuscript and a conception planning calendar is provided in S4 Data . The conception planner requires user-defined ( 1 ) timing of the transmission trough , ( 2 ) susceptible weeks of gestation , and ( 3 ) a statement of whether the first trimester is particularly vulnerable . To increase the effectiveness of seasonally planning conception , vector control campaigns could be used to restrict the mosquito season , minimize the duration of the high-transmission season , and expand the window of opportunity for “safe gestation . ” The integration of epidemiology and family planning can be an effective tool for seasonally timing conception to reduce women’s risk of ZIKV infection during pregnancy .
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Scientific consensus has now been reached that intrauterine Zika virus ( ZIKV ) infection can result in infection of the fetus and subsequent fetal death , congenital microcephaly , and/or Central Nervous System ( CNS ) malformations . Preliminary data suggest miscarriage and congenital Zika syndrome ( CZS ) are most likely when maternal infection occurs early in pregnancy , but fetal abnormalities have been found in women infected with ZIKV during all three trimesters , indicating all trimesters are vulnerable . Like related flavivirus infections , ZIKV transmission is likely to be seasonal . I propose that the risk of ZIKV infection to pregnant women can be reduced using a window of opportunity for conception that will align sensitive periods of gestation with the low-transmission season for ZIKV .
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2016
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Preventing Zika Virus Infection during Pregnancy Using a Seasonal Window of Opportunity for Conception
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Lethal mutagenesis is a promising new antiviral therapy that kills a virus by raising its mutation rate . One potential shortcoming of lethal mutagenesis is that viruses may resist the treatment by evolving genomes with increased robustness to mutations . Here , we investigate to what extent mutational robustness can inhibit extinction by lethal mutagenesis in viruses , using both simple toy models and more biophysically realistic models based on RNA secondary-structure folding . We show that although the evolution of greater robustness may be promoted by increasing the mutation rate of a viral population , such evolution is unlikely to greatly increase the mutation rate required for certain extinction . Using an analytic multi-type branching process model , we investigate whether the evolution of robustness can be relevant on the time scales on which extinction takes place . We find that the evolution of robustness matters only when initial viral population sizes are small and deleterious mutation rates are only slightly above the level at which extinction can occur . The stochastic calculations are in good agreement with simulations of self-replicating RNA sequences that have to fold into a specific secondary structure to reproduce . We conclude that the evolution of mutational robustness is in most cases unlikely to prevent the extinction of viruses by lethal mutagenesis .
Lethal mutagenesis is a proposed therapy for patients with viral infections . The general approach is to increase the deleterious viral mutation rate enough so that the viral population will go extinct [1] . Here , we analyze the risk that lethal mutagenesis therapy will fail as a result of the virus population evolving mutational robustness . Research on lethal mutagenesis and the question of how much mutational robustness can affect mutagenesis are of practical importance . In support of the promise of lethal mutagenesis as a treatment for many human and agricultural viruses , there are reports of the addition of a mutagen severely reducing or extinguishing populations of coxsackievirus B3 [2] , foot-and-mouth disease virus [3]–[6] , Hantaan virus [7] , [8] , hepatitus C virus [9] , human immunodeficiency virus type 1 ( HIV-1 ) [10] , lymphocytic choriomeningitis virus ( LCMV ) [11]–[14] , poliovirus [2] , [15] , [16] , and vesicular stomatitis virus ( VSV ) [15] , [17] . Several recent works have started to develop a theoretical framework to describe lethal mutagenesis [18]–[22] . Theoretical work has led to the prediction that lethal mutagenesis could also be a viable treatment for bacterial infections [20] , [22] . An important limitation to any pathogen treatment is the ability of the pathogen to develop resistance . Since lethal mutagenesis introduces deleterious mutations throughout the genome of viruses , it seems that there are only two types of effective resistance mechanisms . First , the virus could evolve a mechanism to reduce the number of mutations that the therapeutic mutagen introduces . Ref . [23] described such resistant mutations in poliovirus being treated with ribavirin and Ref . [24] described them for foot-and-mouth disease virus . Second , the virus could evolve so that the mutations introduced become , on average , less deleterious . In other words , it could evolve to have greater sequence neutrality or mutational robustness . Empirical studies of lethal mutagenesis appear to yield conflicting results . While Ref . [25] has provided evidence that two strains of VSV differed in mutational robustness during mutagenesis treatment , Ref . [14] later concluded from work with LCMV that lethal mutagenesis does not lead to the evolution of greater mutational robustness . Here , we explain how these apparently contradictory results are both consistent with a simple model of lethal mutagenesis . The organization of this paper parallels our line of inquiry . First we ask , when will a population at equilibrium go extinct ? We find with a deterministic model that an approximation for the critical mutation rate , i . e . the mutation rate beyond which the population goes extinct , is the log of reproductive capacity divided by the non-neutrality of the population at equilibrium . The implication is that small increase in the mutation rate can compensate for relatively large increases in neutrality . Next , we ask , how will elevating the mutation rate increase the rate at which populations move to areas of a neutral network with higher equilibrium neutrality ? We find with a semi-deterministic model that the time it takes for a population undergoing mutagenesis to find the optimal area of the network grows exponentially with the size of the barrier to it . The implication is that we can usually disregard these shifts of the virus population , since the population will quickly shift to the optimal area if the barrier is small and the population will stay where it begins if the barrier is large . Finally , we ask , when will a population that is not at equilibrium go extinct ? We show with a stochastic analytical model and simulations based on RNA-secondary structure networks both the critical mutation rate in these more complex models and the probability of stochastic extinction at mutation rates below the critical mutation rate . The implication is that the initial robustness of the population can be important in some cases , but not when the mutation rate exceeds the critical mutation rate .
First , we consider the effects of mutational robustness in a deterministic model of lethal mutagenesis . In general , virus extinction is guaranteed if [18] ( 1 ) is the basic reproductive ratio known from epidemiology . In the context of lethal mutagenesis , it measures the mean number of offspring virions ( per infecting virion ) that successfully infect a susceptible cell . combines the effects of both virus reproduction and virus death . Offspring virions that die before having the chance to infect a susceptible cell do not contribute to . We can write as [18] . is the basic reproductive capacity of the best genotype in the viral fitness landscape and is the mean fitness of the viral population , measured in units of . We use the term reproductive capacity for since no individual of any genotype can have a greater expected number of reproductive offspring . We assume that changes in the mutation rate affect only and leave unchanged . Under the fairly weak assumptions that populations are large , recombination is absent , and mutations are Poisson-distributed [18] , we have . Thus , we can rewrite Equation ( 1 ) as ( 2 ) where is the deleterious genomic mutation rate . Equation ( 2 ) allows us to solve for the deleterious mutation rate beyond which extinction is guaranteed . We find that leads to extinction . In general , we can write the deleterious mutation rate as , where is the overall genomic mutation rate and is the probability that a random mutation is deleterious . Equation ( 2 ) then becomes ( 3 ) Mutagenesis will increase . The evolution of mutational robustness will decrease . Throughout the remainder of this paper , we consider populations evolving on neutral networks . All sequences on the neutral network have the same reproductive capacity , and sequences off the neutral network are inviable . The neutral-network metaphor is a reasonable approximation for populations near the top of their fitness peak in more general fitness landscapes . Strongly deleterious mutations will generally be purged from the population quickly and thus can be considered lethal . Weakly deleterious mutations will have a minor effect on population fitness and can—to first order—be considered as neutral mutations . In the case where neutral sequences are distributed at equal density throughout the mutational network , is a constant and corresponds to the fraction of non-neutral mutational neighbors at each node in the network . More generally , is determined approximately by the average population neutrality at equilibrium . This approximation has lead to good predictions for fitness landscapes based on RNA secondary-structure folding [26] . To first order , is independent of the mutation rate , because the average neutrality of a population depends primarily on the structure of the neutral network [27] , [28] . However , for very large mutation rates , will depend on [29] . For example , for , the number of a sequence's neutral two-point mutants will have a larger effect on the average neutrality than the number of neutral one-point mutants . Under the assumption that is independent of , we can rearrange Equation ( 3 ) and solve for the value of that must be exceeded for the population size to deterministically decrease . Throughout this paper , we denote this value of as and for this deterministic model we find that ( 4 ) As long as the critical mutation rate is close to unity and we use a value measured at equilibrium , this expression will give a reasonable approximation for the critical mutation rate . Figure 1 shows how an increase in mutational robustness , i . e . , a decrease in , extends the regime in which a viral population can survive mutagenesis treatment . Of course , the critical mutation rate may be far above unity and the assumption that is independent of may not be valid in that regime . The stochastic models we analyze below indicate a way to make an analogous measurement in this case for the purpose of calculating . Before presenting that result , however , we next consider a more troubling possibility: Will the elevation of the mutation rate during lethal mutagenesis increase the rate at which the virus population evolves to a higher equilibrium level of robustness ? In general , a neutral network may be broken into separate areas of differing neutrality and separated by entropic barriers . ( The term entropic barrier means that the probability to jump from one network to another with one mutational event is low . ) In other words , there may be few possible paths in the network from one area to another . In this case , there is the risk that increasing mutation rates will increase the rate at which virus populations find rare paths to other areas of the neutral network in which it is possible to evolve greater neutrality . This process is comparable to that of demes drifting between equilibria ( adaptive peaks ) in the context of shifting-balance theory [30] . Depending on how great a barrier is in comparison to the mutation rate , the evolution of greater neutrality during lethal mutagenesis will be either inevitable or extremely unlikely . The barriers between areas of the neutral network at high mutation rates will often be so small that they can be neglected . In this case , the separate areas form one large , connected neutral network . Alternatively , the barriers will be so large that we may disregard the undiscovered areas of the neutral network . We next illustrate this concept with a specific example . We consider the neutral-staircase landscape [29] , a fitness landscape consisting of multiple nested neutral networks . Networks with relatively low connection density are embedded into larger networks with increasingly higher connection density . To discover the next larger network , a population has to cross an entropic barrier . Sequences in the neutral-staircase landscape consist of zeros and ones ( bits ) . The bits are organized into blocks of pairs of bits . Each block is separated by an additional bits . The total sequence length is thus . Blocks can be either active or inactive . Sequences are viable if and only if all bits in inactive blocks are set to zero and no pairs of bits in active blocks are both set to one . Viable sequences with minimal neutrality contain one active block at one end of the sequence and sequence neutrality increases when the inactive block adjacent to an active block becomes active . The inactive block adjacent to an active block becomes active when the bits between the adjacent inactive and active blocks are all set to one at the same time . Thus , the bits between blocks form an entropic barrier . The larger , the harder it is to discover the more-densely connected areas of the neutral network . The neutral-staircase landscape can be solved analytically , and the full derivation can be found in Ref . [29] . We express the solution in terms of the bit-copying–fidelity rate and the reduced mutation rate . The average fitness of a population at equilibrium is given by ( 5 ) under the assumption that the dominant sequence in the population has active blocks . To increase the number of active blocks , the population has first to generate a mutant with active blocks , and then this mutant has to go to fixation . The probability that at least one offspring sequence in one time step will have active blocks is ( 6 ) where is the population size . A sequence with active blocks will become fixed with probability . We obtain from the classic expression for the probability of fixation , [31] . We can combine and to estimate , the expected number of generations until the dominant sequence changes from having active blocks to having active blocks [29]: ( 7 ) ( This expression assumes that the time to fixation is negligible compared to the time to discovery . ) If we sum over all possible values of , we obtain the convergence time , i . e . , the expected time for the population to move from having one active block to the maximum number of active blocks , : ( 8 ) Figure 2 shows convergence times as a function of mutation rate . The curves in Figure 2 are only plotted for , where Equation ( 8 ) has previously been found to be in good agreement with simulations [29] . When barriers are large , there is a log-log relationship between convergence time and the genomic mutation rate . So convergence times may decline quickly as the mutation rate increases . However , there is a log-linear relationship between the convergence time and the size of the barrier . Therefore , even at high mutation rates , the time to convergence may be an astronomical number of generations if the barrier is large ( Figure 2 ) . This is true even for large populations . The prospect of the equilibrium neutrality increasing raises the question of how much increases in equilibrium neutrality may increase . Although the calculation of convergence times assumed that that the population size was constant , we can answer this question by considering Equation ( 5 ) as a measure of absolute fitness . Then we find that an increase in the number of active blocks does not greatly increase the critical mutation rate ( Figure 3 ) . When barriers are small , we can expect that the area of the neutral network with the greatest connection density can be found in a reasonable number of generations . In this case , the main question is whether the population can find areas with high connection density before it goes extinct under mutagenesis . In the following subsections , we will address this question using fully stochastic models . According to Equation ( 1 ) , extinction is guaranteed if the mutation rate is so high that the equilibrium mean fitness of the population is less than 1 . But lethal mutagenesis is not an equilibrium process . Therefore , we next explore how extinction occurs in a population out of equilibrium , using the mathematical framework of multi-type branching processes . Because this approach is a stochastic one , we calculate not only the mutation rate at which extinction is guaranteed but more generally the probability that extinction happens at any given mutation rate . Our main question here is how the extinction probability changes if the population resides initially in regions of the neutral network with particularly low or high connection density . The mathematical framework we use to calculate the extinction probability under lethal mutagenesis is that of multi-type branching processes . This framework has been used previously to calculate the fixation probability of a rapidly mutating virus on a neutral network [32] , [33] . The next two paragraphs offer a brief introduction . Consider a population where all offspring are identical to their parents . A sequence produces a random number of offspring in the next generation . All these offspring sequences produce their own random number of offspring according to the same probability distribution . The number of progeny that a sequence has in two generations , then , is the sum of these random variables . The use of a probability generating function ( p . g . f . ) allows for convenient expression of these sums . We use ( 9 ) where is the probability that the number of offspring equals . The convenience of using p . g . f . s is that we obtain the p . g . f . for the distribution of sizes for the second , third , and all following generations by iteratively substituting the p . g . f . into itself two , three , or more times . The theory of branching processes [34] shows that the probability of extinction , the condition in which all sequences stop producing offspring , is the value of that satisfies the simple expression ( 10 ) so long as the expected number of offspring but finite . The theory also shows that the condition guarantees extinction . When there is a finite number of distinct genotypes , we use multivariate offspring distributions . In this case , the p . g . f . is a vector-valued function and takes a vector as its argument . Component of the p . g . f . has the form ( 11 ) Here , is the joint probability that genotype has offspring of type 1 , offspring of type 2 , and so on . As in the one-dimensional case , the extinction probability follows from the fixed-point equation ( 12 ) Component of the fixed point gives the probability that the branching process goes extinct if it was started with a single particle of type , as long as the following assumptions are met [34]: The expectation and variance of the offspring of each type are finite; all types do not have exactly one offspring; each type can have a descendant of any other type; and the dominant eigenvalue of the matrix of means is greater than one . The matrix of means , here denoted , in a multi-type branching process is comparable to the expected number of offspring in a single-type branching process and has elements ( 13 ) If the above assumptions are satisfied except that , extinction is guaranteed . Extinction probabilities can easily be found numerically from Equation ( 12 ) , but we next present two approximations to illuminate how extinction probabilities follow from offspring distributions . First , we need an explicit expression for the multivariate p . g . f . s in the fixed-point equation . If the number of offspring of type produced by a type- sequence is Poisson-distributed with mean , then Equation ( 9 ) defines the corresponding p . g . f . as . The p . g . f . for a sum of independent random variables is the product of the p . g . f . s of all the variables . Assuming independence of the number of offspring of each type , then , our multivariate p . g . f . s are ( 14 ) When extinction probabilities are close to one , we can approximate them by taking the log on both sides of Equation ( 12 ) , expanding to second order , and performing some algebra to obtain ( 15 ) Equation ( 15 ) says that the probability of extinction of a type- sequence is approximately if this sequence does not produce any other types of sequences . This is natural since is a measure of how much the replication rate of type- sequences exceeds the replacement rate . If we equate with the selective advantage in a constant–population-size model , we see the classic result [31] . We also see in Equation ( 15 ) how the probabilities that other types of sequences do not go extinct weight the contribution of the rates in reducing the extinction probability . When extinction probabilities are close to zero , we can express using the linear approximation of Equation ( 14 ) at zero: ( 16 ) Equation ( 16 ) says that is at least the probability that a type- sequence produces no offspring . The equation also shows how further increases as the fraction of offspring that will go extinct , , increases . Solving Equation ( 16 ) gives ( 17 ) where is the identity matrix and is the diagonal matrix whose diagonal elements are the elements of the vector . The previous subsection developed the general theory of stochastic extinction under lethal mutagenesis . We will now apply this theory to the special case of a neutral network of RNA sequences . To this end , we will first describe a model that links a sequence's location in a neutral network with the sequence's neutrality . This model yields the rates at which sequences produce offspring sequences with different levels of neutrality . We then present both analytic and simulation results that show how the initial location of a population affects its extinction probability . Consider how the probability-density function of the offspring distribution , the probability that a sequence will produce any number of offspring with any combination of neutralities , depends on a sequence's location in a neutral network . The sequence's location determines how many mutations can push sequences off of the neutral network . The sequence's location also determines how mutations can change the fraction of a sequence's neighbors that are neutral ( i . e . change the sequence's neutrality or robustness ) . In theory , we could determine the graph that connects all sequences in a neutral network , and read off from this graph . But in practice , this graph is so large for RNA sequences of even modest length that this approach is not feasible . A more feasible , but still computationally intensive , approach would be to group sequences into classes of various levels of neutrality and then estimate a matrix of means from a sample of sequences from each class . The principle eigenvalue of this matrix of means would indicate if extinction was guaranteed . Instead , we here describe a sequence simply by two parameters and . The parameter measures the probability that mutant offspring are neutral , and the parameter determines whether this probability stays constant ( no epistasis ) , increases ( antagonistic epistasis ) , or decreases ( synergistic epistasis ) as the number of mutations increases . We define such that the larger it is , the smaller the probability that offspring are neutral ( see next paragraph ) . Instead of , we also use the fraction of deleterious mutations , which satisfies ( 18 ) The larger , the smaller the probability that offspring are neutral . As in the deterministic model , means that all offspring are neutral and means that no offspring is neutral . Our approach is inspired by Ref . [35] , which showed that the fraction of neutral sequences at a distance from a reference sequence decays approximately as ( 19 ) Ref . [35] also showed that and are not independent from each other , but that either parameter determines the other . The relationship between and arises because the total number of neutral sequences in a given neutral network is a constant , . We can express in terms of as ( 20 ) where is the sequence length and 3 represents the number of RNA bases to which an existing base can mutate . Using Equation ( 19 ) for and given either or , we can solve Equation ( 20 ) for the other parameter . Equations ( 19 ) and ( 20 ) say that , since there are only so many neutral sequences , if a sequence is in an area of the neutral network with a high connection density , then the connection density of neutral sequences must generally decline as we move away from it , and vice versa . This reasoning implies that and are negatively correlated , and we found here that ( Figure S1 ) . We can use this framework to determine the and of an offspring sequence , given that we know and of the parent sequence . Equation ( 19 ) describes the expected density of neutral sequences as we move away from the parent sequence . The fraction is the factor by which the probability of an offspring being neutral is reduced as the number of mutations goes from to . We take this fraction as the neutrality of an offspring with mutations . Then , . Note that this approach neglects back mutations , which generally are highly unlikely for sufficiently long sequences . Once we have the offspring's , we can solve for the offspring's using Equations ( 19 ) and ( 20 ) . We close this system by evenly dividing the range of the continuous variable into bins . Sequences with a in the range of a bin are given the value of the upper boundary of the bin . The bins are indexed so that the of type- sequences . Putting everything together , the probability that any one offspring of a parent of type is of type is ( 21 ) where is the probability of having mutations , and if is in and otherwise . To fully specify , we assume that the distribution of mutations is Poisson with mean . As explained in the previous subsection , if the number of offspring of each type are independent and Poisson-distributed , the p . g . f . s for the fixed-point equation used to calculate extinction probabilities are products of Poisson p . g . f . s . See Text S1 for a more detailed derivation . The matrix defined in Equation ( 21 ) , multiplied with the reproductive capacity , corresponds to the matrix of means discussed in the previous subsection . Therefore , the critical mutation rate is the mutation rate at which the dominant eigenvalue of equals one . Here , is determined by the parameters sequence length , neutral-network size , and reproductive capacity according to ( 22 ) where is the dominant eigenvalue of and represents the fraction of offspring produced at equilibrium that are neutral . is an exponentially decaying function of ( Figure 4 ) . Since when , we can derive the rate of decay of with by measuring at a positive mutation rate : ( 23 ) This is an effective value of the probability of neutrality from the deterministic model subsection , and allows us to calculate critical mutation rates that are far above one as ( 24 ) , and thus , is largely determined by and ( Figure 4 ) . The relationship between and in Equation ( 24 ) is the same as in the deterministic model ( Equation ( 4 ) ) . We next present results directly showing the relationships between , , and . First , we present results based on the assumption that populations initially consist of a single sequence . This case is relevant to a scenario in which a patient is inoculated with a small dose of virus while on lethal mutagenesis therapy or a virus is establishing itself in a new tissue of a patient's body . With this assumption , we found that the probability of extinction declined with the initial sequence's neutrality , but also that the gradient in extinction probabilities rapidly leveled as the mutation rate increased ( Figure 5 ) . In agreement with the theory of branching processes , the critical mutation rate at which extinction is guaranteed was independent of the initial sequence's robustness . Next we used the analytic calculations to study the effect of the size of the neutral network . When going from a smaller neutral network to a larger neutral network , the extinction threshold slowly moves towards larger values ( Figure 6 ) . Extinction probabilities decline faster with increasing for populations that initially are highly robust ( is small ) compared to populations that initially are not very robust ( is large ) . Consequently , the larger the neutral network , the stronger is the extinction probability affected by the robustness of the sequence seeding the population ( Figure 6 ) . Since lethal mutagenesis is intended to eliminate virus populations that have grown to high levels , we also considered the effect of the initial population size . We considered an initial population that was uniformly composed of sequences with a given initial robustness . When going from a smaller initial population to a larger initial population , only the extinction probabilities for mutations rates below the extinction threshold changed ( Figure 7 ) . The gradient of extinction probabilities receded into a region in which sequence neutrality was low and mutation rates were just below the threshold . As in Figure 1A , the extinction threshold with was the mutation rate where the expected number of offspring without any mutations was one , i . e . . When the initial population was large and had at least a small amount of neutrality ( ) , the extinction threshold was the mutation rate where , at equilibrium , the expected number of offspring without any mutations was one , i . e . such that the eigenvalue of was one ( Figure 7C ) . We verified our branching-process model by carrying out simulations with individual RNA sequences ( see Methods for details ) . The simulations used an RNA-folding algorithm to obtain a computationally tractable genotype-to-phenotype mapping that did not make the simplifying assumption that a sequence is fully described by just the two parameters and . The simulations were initiated with sequences having a wide range of neutralities , as measured from the fraction of point mutations that maintained the neutral phenotype . In each generation of the simulations , sequences with the neutral phenotype reproduced , their offspring received a random set of mutations , and the phenotypes of these offspring were then determined . Simulations were continued until each population exploded or went extinct . The length of the sequences was 40 . We found that the analytic calculations and the RNA secondary-structure simulation results were in broad agreement ( Figures 5 and S2 ) . The main difference was that the analytic calculations had a of roughly one to two mutations per replication above the in the simulations .
We have studied how the evolution of mutational robustness affects lethal mutagenesis . Using a simple deterministic theory , we found that extinction was guaranteed past a critical mutation rate given by the log of reproductive capacity divided by the probability that a random mutation is deleterious . Thus , a reasonable change in mutational robustness ( say , 10–30% ) will result only in a minor change to . For neutral networks composed of subunits divided by barriers , we argued that barriers will in practice either be negligible or unsurmountable . In either case , a theory describing only a single neutral network is sufficient to explain how robustness affects lethal mutagenesis . We determined whether and to what extent robustness could evolve while mutagenesis was ongoing using a stochastic branching-process model of lethal mutagenesis . We found that when the initial population was small and mutation rates were high enough to be able to cause extinction , but not so high that extinction was assured , the initial neutrality of a population could affect the probability of extinction . When mutation rates were more extreme , the neutral network small , or the initial population size large , initial neutrality had little effect on the probability of extinction . In our model of replicating RNA sequences , we found that the critical mutation rate increased with increasing neutral-network size . The larger the neutral network , the larger . This result follows immediately from the relationship between and . The larger , the smaller for the same . Thus , larger neutral networks are in general composed of more robust sequences that can withstand a higher mutation rate . Yet the relationship between and was rather weak . Increasing the neutral network size by over -fold ( from to ) changed by less than a factor of 3 ( Figure 6 ) . We found that the stochastic model behaved nearly deterministically when the initial population size was 100 , 000 , which is not a large population for viruses . This result assumed a completely homogeneous initial population . If the initial population were heterogeneous , we would likely see nearly deterministic behavior at even lower initial population sizes . At high heterogeneity , the population might contain a single individual with high neutrality . This individual would have a low extinction probability unless was close to . The extinction probability of the entire population would then be dominated by the extinction probability of this one individual , since the extinction probability of the entire population can only be as high as the extinction probability of any one of its members . What are reasonable values for the fraction of deleterious mutations ? Estimates for the fraction of lethal mutations for various viruses ( VSV , poliovirus , bacteriophages ) range from between 20% to 40% [18] , [36] , [37] . For the same viruses , between 30% and 60% of random mutations are deleterious but non-lethal [36] , [37] , and there seems to be a tendency for those viruses that have a higher fraction of lethal mutations to have fewer non-lethal deleterious mutations . Together , approximately 70% to 80% of random mutations are deleterious . These measurements do not provide , however , an estimate of for a robust and a non-robust strain of the same virus . While such estimates are not available for entire virus genomes , several exist for individual proteins . Neutralities of less-robust variants of a protein tend to be 15% to 50% lower than neutralities of more-robust variants of the same protein [38]–[40] . If we accept an increase in robustness by a factor of two as a worst case scenario for a real-world virus , then likewise the critical mutation rate will at most double ( Figure 1 ) . Yet mutational robustness can only increase to the extent to which it is not already present . Theory predicts that populations evolve robustness if the product of mutation rate and population size exceeds one , and that the level of robustness achieved is largely independent of the actual mutation rate [27]–[29] . For RNA viruses , whose mutation rates alone are on the order of one per genome and generation [41] , we would therefore expect that their wild types have already evolved most of the robustness their genome architectures are capable of . Artificial mutagenesis should therefore not result in major additional gains in robustness for these viruses . The reproductive capacity is difficult to relate to data , because it depends not only on the virus burst size but also on the number of offspring particles that go on to establish a successful infection . Burst sizes range from values in the double digits ( e . g . , 76 for bacteriophage [42] ) to many thousand ( e . g . , up to 10 , 000 for poliovirus [43] ) . Which percentage of these offspring viruses die before infecting a cell in vivo is unclear . More importantly , interacts with the neutral-network size to determine extinction probabilities in our stochastic models . Since we know of no precise and accurate estimates for the neutral-network size , a precise and accurate value for would not make the final results more meaningful . At any rate , the log-linear relationship between and ( Equation ( 24 ) ) means that the change in due to the evolution of robustness is not highly sensitive to the exact value of . The sequence lengths of 40 and 400 used in the stochastic models are short in comparison to the genomes of RNA viruses , which are about 10 , 000 base pairs long . Since the relationship between and remains similar for sequences up to lengths of 10 , 000 ( Figure S1 ) , we expect that our analytical branching-process model gives reasonable results even when extrapolated to sequences of realistic lengths . For our model of replicating RNA sequences under mutagenesis , we found that the critical mutation rate in the analytic model was slightly higher than the one in the simulations . This observation suggests that our estimates of neutral-network size are too large . We would have overestimated if the neutral networks for the RNA shapes chosen have multiple components , which has been observed for many RNA secondary-structure neutral networks [44] . In this case , should be the size of the component , rather than the size of the entire neutral network . Alternatively , the difference in may be the result of Equation ( 19 ) not exactly matching the true fitness landscape . The bulk of our results implies that the evolution of mutational robustness during lethal mutagenesis is not a serious threat to the efficacy of lethal mutagenesis . As long as lethal-mutagenesis treatment aims to increase substantially beyond ( say , to or more ) , the population will not be capable of compensating this increase in mutation rate by evolving a commensurate increase in robustness . This implication is consistent with the report that lymphocytic choriomeningitis virus ( LCMV ) passaged with a sub-lethal dose of 20 5-flourouracil ( 5-FU ) went extinct without exception when a lethal dose of 100 5-FU was later used [14] . Additionally , our results are not a contradiction to the report that a mutationally robust strain of vesicular stomatitis virus ( VSV ) prevailed in competition against a strain that was more fit in the absence of a mutagen when 5-FU doses were 20 , 40 , 60 , and 80 [25] . When two strains are in direct competition , relatively minor differences in robustness can favor the more robust strain over the less robust one at sub-lethal concentrations of mutagen [26] , [45] . Yet both strains would likely go extinct at higher doses of mutagen . While our models do show that the initial neutrality of a population can affect its probability of extinction , this relationship may be overshadowed in practice . For example , the models neglect the effect of defective interfering particles , which may contribute to extinction by lethal mutagenesis [13] . The defense systems of host cells or the abundance and distribution of susceptible cells could also be more important than initial population neutrality . Finally , we have not addressed the potential for resistance to the mutagen , observed in some experimental systems [23] , [24] . This work has provided quantitative support for the statement that the evolution of mutational robustness will have only a minor effect on lethal mutagenesis . In an extreme case , half of all non-beneficial mutations could evolve to become neutral . In this case , doubling the mutation rate will be sufficient to cause extinction ( Figure 1 ) . For less extreme cases of robustness , less extreme increases in mutation rates would suffice . If entropic barriers to higher levels of robustness are substantial , increasing mutation rates to critical levels will not make the epochal evolution of this greater robustness appreciably more likely . If the entropic barriers are small and virus population sizes are appreciable , we generally need to treat the population as if it consisted of viruses with the mutation-selection–equilibrium level of robustness . So while natural selection may increase the sequence neutrality of viruses during lethal mutagenesis , by itself , this effect is unlikely to affect the course of treatment . The analysis of the potential effects of increased sequence neutrality combined with the evolution of higher-fidelity polymerases and other compensatory mutations remains a topic for future work .
We evaluated the convergence times given by Equation ( 8 ) , numerically derived from Equation ( 5 ) , and implemented a bisection root finding algorithm to solve Equations ( 19 ) and ( 20 ) for , given all other parameters , using the Sage [46] computing environment . Specific components of Sage used included the multiple-precision library MPFR [47] , SciPy [48] , and the computer algebra system Maxima [49] . The scripts used are included in Dataset S1 . We obtained the fixed point in Eq . 12 by iterating the p . g . f . s until the total difference between the input vector and the resulting vector was less than . Component of gives the extinction probability of a population that begins with a single sequence of type . To calculate the extinction probabilities of populations of size where , we assumed independence of the extinction of each lineage in the initial population ( consistently with the branching process ) and used the probability that all of the lineages went extinct , . Sequences that folded into a target shape were considered neutral , and all others were considered inviable . The neutrality of a sequence was the fraction of neighbors at a Hamming distance of one that also had the target phenotype . The RNAfold function in the Vienna package [50] version 1 . 7 was used for the folding . Unpaired bases were allowed to participate in at most one dangling end ( the default option -d1 ) . The size of the neutral network was determined by randomly sampling the sequence space and seeing what proportion was neutral , and then multiplying this proportion by the size of the sequence space . We chose target shapes that were relatively common and limited the sequence length to 40 . This limit reduced the number of random sequences that needed to be sampled to estimate the neutral-network size without introducing any obvious biases in the results . We used the following targets: Here , positions that form base pairs are indicated with matching parentheses , and unpaired positions are indicated with dots . For the first target , which was used to generate the results in Figure 5A , we sampled two hundred million sequences and found 88 , 840 to be neutral . Therefore , . For the second target , which was used to generate the results in Figure S2A , we sampled one hundred billion sequences and found 19 , 782 to be neutral . Therefore , . The extinction probability of a sequence was determined by simulation of a branching process on the RNA secondary-structure neutral network . Simulations began with a single neutral sequence . These sequences were selected from the sample of sequences used to estimate the size of the neutral network so as to get the full range of initial neutralities . At each iteration , each sequence in the population had a Poisson distributed number of offspring . Each letter of the sequence changed to any of the other three possible letters with a probability equal to the genomic mutation rate divided by the sequence length . Mutation rates ranged from zero to fifteen . Each sequence was tested to see if it folded into the target , and sequences that did not were removed . Simulation was continued until the population size reached zero or 10 , 000 . Simulations were replicated 100 times for each of 500 initial sequences and the extinction probability was the number of simulations in which extinction occurred divided by the total number of simulations . A local polynomial fitting function ( the loess function in R [51] ) was used to produce smooth curves from the extinction probability data . In Figure 5A , the maximum mutation rate used in simulation runs was 15 . The extinction probability for larger mutation rates is an extrapolation of the observed pattern . We have no reason to expect that this extrapolation is incorrect . The code written for these analyses is in Dataset S1 .
|
The high mutation rate of RNA viruses , such as HIV , allows them to rapidly evolve resistance to host defenses and antiviral drugs . A new approach to treating these viruses—lethal mutagenesis—turns the mutation rate of these viruses against them . It uses mutagens to increase the viruses' mutation rates so much that the accumulation of harmful mutations drives viral populations to extinction . Is there any way that a virus could adapt to a drug that increases its mutation rate ? One way is that the virus could evolve so that mutations tend to be less harmful . In previous experimental work , there have been reports that virus populations can differ in robustness . Yet , the evolution of mutational robustness did not seem to inhibit extinction by lethal mutagenesis . In this work , we model viral populations under lethal mutagenesis in order to see when viruses might escape extinction by evolving robustness to mutations . We find that viruses can benefit from robustness only at relatively low mutation rates because the extent to which robustness increases fitness is rapidly drowned out by the extent to which higher mutation rates decrease fitness . The implication is that the evolution of mutational robustness is not a fundamental impediment to lethal mutagenesis therapy .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"virology/virus",
"evolution",
"and",
"symbiosis",
"virology/new",
"therapies,",
"including",
"antivirals",
"and",
"immunotherapy"
] |
2010
|
Does Mutational Robustness Inhibit Extinction by Lethal Mutagenesis in Viral Populations?
|
In mass vaccination campaigns , large volumes of data must be managed efficiently and accurately . In a reactive oral cholera vaccination ( OCV ) campaign in rural Haiti during an ongoing epidemic , we used a mobile health ( mHealth ) system to manage data on 50 , 000 participants in two isolated communities . Data were collected using 7-inch tablets . Teams pre-registered and distributed vaccine cards with unique barcodes to vaccine-eligible residents during a census in February 2012 . First stored on devices , data were uploaded nightly via Wi-fi to a web-hosted database . During the vaccination campaign between April and June 2012 , residents presented their cards at vaccination posts and their barcodes were scanned . Vaccinee data from the census were pre-loaded on tablets to autopopulate the electronic form . Nightly analysis of the day's community coverage informed the following day's vaccination strategy . We generated case-finding reports allowing us to identify those who had not yet been vaccinated . During 40 days of vaccination , we collected approximately 1 . 9 million pieces of data . A total of 45 , 417 people received at least one OCV dose; of those , 90 . 8% were documented to have received 2 doses . Though mHealth required up-front financial investment and training , it reduced the need for paper registries and manual data entry , which would have been costly , time-consuming , and is known to increase error . Using Global Positioning System coordinates , we mapped vaccine posts , population size , and vaccine coverage to understand the reach of the campaign . The hardware and software were usable by high school-educated staff . The use of mHealth technology in an OCV campaign in rural Haiti allowed timely creation of an electronic registry with population-level census data , and a targeted vaccination strategy in a dispersed rural population receiving a two-dose vaccine regimen . The use of mHealth should be strongly considered in mass vaccination campaigns in future initiatives .
In mass vaccination campaigns and other large-scale health interventions , healthcare providers are challenged to find a data collection system that allows timely , accurate , and efficient management of large volumes of data . Traditional paper-based data collection systems have been used effectively in health programs for generations , and can result in high quality data . However , public health programs that use paper-based data systems and wish to analyze data must compensate for staff , paper records , time , and funding to digitize data , potentially adding vulnerability to human-introduced error [1]–[3] . With continuously expanding mobile networks [4] , [5] , mobile health ( mHealth ) solutions are an increasingly attractive and acceptable way to collect , manage , and analyze information [6] , [7] . Direct electronic data collection can result in higher quality data [3] , [8]–[13] and can produce a cleaner database more rapidly [3] , [8] , [10] , [14] , [15] . Direct data entry has also been shown to be faster and less expensive when compared to paper-based data collection [3] . Though employed in various health and research settings , the use of mHealth has not been extensively documented in mass vaccination campaigns in resource-limited settings . The worst cholera outbreak in recent history has been ongoing in Haiti since October 2010 , which began only ten months after a devastating earthquake struck near Port-au-Prince , the country's capital . As of October 2013 , the Haitian Ministry of Health has reported over 8 , 360 cholera-related deaths and over 684 , 000 cases of cholera [16] . In December 2011 , Haiti's Ministry of Health , and implementing partners Groupe Haïtien d'Étude du Sarcome de Kaposi et des Infectieuses Opportunistes ( GHESKIO ) and Partners In Health , initiated a plan to vaccinate 100 , 000 residents with oral cholera vaccine in two areas—50 , 000 in Port-au-Prince , and 50 , 000 in two rural communities in the Artibonite Valley . The context , strategies used , acceptability , feasibility , and vaccine coverage rates of these oral cholera vaccination ( OCV ) campaigns are described in detail elsewhere [17] . Fueled by an ongoing epidemic that continued to claim lives , there was urgency to complete vaccination prior to the forthcoming rainy season . We sought to demonstrate that a mass OCV campaign was possible in an epidemic , rural , resource-limited setting [18] . As a result , we documented individual-level information with greater detail than is typical in mass vaccination campaigns to understand granular-level coverage , uptake of the vaccine , trace vaccination adverse reactions , and evaluate vaccine effectiveness after the campaign [19] . We also wanted to ensure as complete vaccination coverage as possible to leverage the herd-immunity effect of the vaccine [20]–[22] . In order to collect the depth of information needed within a short period of time , we used an electronic mHealth solution with the primary aims of ( 1 ) providing a timely , efficient data management system , and ( 2 ) mapping and documenting detailed information on campaign community coverage and vaccine uptake for 50 , 000 vaccinees in two isolated communities in rural Haiti .
Ethics approval was obtained from Partners Institutional Review Board ( Boston , MA ) for secondary analysis of the data collected during the census and campaign . All data were collected as part of a public health campaign ( approved by the Haitian National Bioethics Committee ) ; informed consent was not required during the campaign . The vaccination campaign was conducted in Bocozel and Grand Saline , two sections in the Artibonite Valley of Haiti [17] . Bocozel was initially the targeted section for the campaign , but after census showed fewer than expected residents , the vaccination campaign area was extended to Grand Saline . Both of these agricultural communities are isolated and have poor road infrastructure , making access and travel to and within the areas difficult . A census was conducted in Bocozel in February 2012 to pre-register eligible residents and to deliver an education campaign on hygiene and sanitation messages [17] , [23] . All non-pregnant residents over 1 year old living in the section were invited to be vaccinated . A unique number was assigned to each house within each locality , and was marked on the door or wall of the house and recorded in the census database . Other variables recorded at the time of census were full name , gender , age , and locality ( neighborhood ) of residence . A census was not conducted in Grand Saline . The vaccination campaign followed from April to June 2012 in two phases to avoid a schedule conflict with an oral polio vaccination campaign . Phase 1 targeted adults and children aged 10 years and older from Bocozel , and Phase 2 targeted children 1–9 years old from Bocozel , as well as all Grand Saline residents [17] . A three-tiered campaign strategy was used: community centers , schools , churches , and communal areas throughout the area were designated as fixed vaccination posts—44 in Bocozel and 11 in Grand Saline . When data demonstrated that attendance at the fixed vaccination posts began to wane , the supervisor and project managers moved to mobile posts , and subsequently to a door-to-door strategy . Data were collected using handheld Samsung ( Seoul , South Korea ) Galaxy Tabs with a 7-inch display running Android operating system; 50 tablets were used during the census , and 40 during the vaccination campaign . The software platform was built by a contracted partner ( Majella Global Technologies , Portland , ME , USA ) on Open Data Kit . External battery packs with dual USB charging ports provided a portable , backup power supply . Data records were first stored locally on devices in the field , and uploaded nightly via office Wi-Fi to a secure , web-hosted database . Online registries were subsequently downloaded nightly for analysis . All tablets and computers were password-protected and encrypted [24] , [25] . Those interested in being vaccinated received a vaccine card either during the census , or at the vaccination post if they had not been included in the census for some reason . The vaccine card included a unique numeric barcode , full name , gender , age , locality ( neighborhood ) of residence , and spaces to record the date of each vaccination . We retrieved and input resident information by using the tablets' barcode-scanning function . Manual entry of the barcode number was possible if scanning failed . Receipt of each of two OCV doses was confirmed on the card with custom-made rubber stamps . Locally recruited Haitians staffed 50 teams during the census and 40 teams during the vaccination campaign . Census teams of two had one enumerator and one community guide , and were managed by a total of 10 supervisors; vaccination teams consisted of one enumerator , two vaccinators , and one community guide , and were managed by a total of 20 supervisors . All enumerators were high school-educated . Two-day trainings were conducted prior to the census and the vaccination campaign , covering use of hardware and software , in-depth review of the data collection forms , communication style , and role-play . We also conducted refresher trainings before each new dose throughout the campaign to review software functions , updates to data collection forms , feedback from the previous dose for improved data quality , and practice scenarios . Each night , data records collected in the field were uploaded from each tablet and merged into a web-hosted database . At the end of census , population data were downloaded from the web-hosted electronic database and formatted in Microsoft Excel to become a dataset , or a “lookup table” . The lookup table was loaded back on to all tablets and embedded within the electronic forms , and served as a locally stored database from which previously collected population data could be retrieved . From April to June 2012 , residents presented their cards at vaccination posts to receive OCV . Residents could go to any post , since census data was available on all tablets . Residents' barcodes were scanned and their personal census information automatically populated form fields ( name , age , gender , locality of residence ) . We then added information at each encounter including enumerator and supervisor names , vaccination date , dose , and manufacturing batch number . The datasets were cleaned and newly updated lookup tables were loaded onto tablets between each vaccine phase . Each tablet had multiple data collection forms to provide appropriate ways to record information . The main two forms were autopopulated with vaccinee information by barcode , or by looking up the family name if a resident lost her/his vaccine card or if the barcode did not function . For those whose records could not be located on a tablet by barcode or family name , an office-based team could search any combination of identifiers in the database by desktop computer; we were then able to retrieve the original barcode number linked with the individual . If her/his record could not be located in the computer database , a new vaccine card was issued and a new registration form was completed to collect her/his information ( see Figure 1 ) . After initial days of vaccination at fixed and mobile posts , we used our electronic databases and a custom-built analysis tool to generate case-finding reports of all residents who were expected to be vaccinated , but had still not received dose 1 ( or who had received dose 1 , but had not come for his/her second follow-up dose ) [17] . For example , during phase 1 , after vaccination records from the tablets were uploaded to the electronic registry database , we could compare the current vaccination registry with the original census database to identify individuals who had registered for OCV during the census , but still needed their first OCV dose . Our teams went door-to-door , locating individuals by the unique numbers assigned to each household during the census . There was no case-finding in Grand Saline because no census was performed there . The software included automatic check features , such as logic branching and requiring a response , to ensure accuracy and completeness before being saved . During data collection , team supervisors accompanied enumerators and did spot checks to ensure that enumerators were filling in forms correctly . If any errors were found , they were corrected on the tablet if possible , or else recorded in an error log and reported to the Data Manager for resolution in the electronic database daily or at the end of each phase . During vaccination , data collected on vaccine recipients for the vaccine registries were linked directly with census data in the tablet records , allowing for accurate data linking at the point of vaccination . The registries were reviewed nightly or every two nights , and cleaned at the end of each vaccination phase . Enumerators were trained how to take Global Positioning System ( GPS ) coordinates during staff training . Each morning of vaccination , they recorded the location of the fixed vaccination posts with the tablets' built-in GPS functionality . We mapped locality coordinates in Google Earth , verifying them with local collaborators and against existing databases [26] . We used ArcGIS 10 ( ESRI , Redlands , California , USA ) to compile this information and generate summary maps of localities , vaccination posts , regional health centers and cold chain storage locations , and population coverage rates . Because localities were recorded as point locations ( rather than areas ) , we visualized community vaccination coverage ( Figure 2 ) and follow-up rates ( Figure 3 ) using population-proportionate bubbles centered over locality point locations . We shifted some locality points that were clustered together to reduce overlapping of the population bubbles and to improve visualization of the data . Additional roads , canals , and water bodies were geocoded from Google Earth to produce a background reference layer . Locality-level vaccination coverage data was not available in Grand Saline because we did not conduct a census there , so aggregated data were visualized . The costs of hardware , software , and training were included in the calculations for determining the cost of implementing mHealth in the census and vaccination campaign in Bocozel and Grand Saline . Hardware costs included tablet computer purchase and rentals , and surge protectors . The cost of external battery packs and tablet accessories were excluded . Software costs included a data-hosting contract and mobile licenses for each tablet computer for the duration of the census and vaccination campaign , and the custom-built analysis tool for generating case-finding reports . Training costs included technology-related on-site training , support , and travel for two 1-week periods , which were estimated to be 40% of total training costs incurred by our contracted software platform partner .
During a 13-day census in Bocozel , we collected over one million pieces of data . Our teams enumerated an average of 14 . 6 households , or 53 individuals , per enumerator per day . We enumerated 34 , 767 individuals in 9 , 517 households . Of these , 33 , 441 eligible individuals pre-registered for OCV . During 40 vaccination campaign days in Bocozel and Grand Saline , we collected approximately 1 . 9 million pieces of data while distributing 86 , 659 vaccines to 45 , 417 individuals . On the first vaccination day , when our vaccination posts were busiest , we documented administering OCV to 6 , 200 individuals , or 155 vaccinations per enumerator per day . Of those who received at least one dose during the campaign , 90 . 8% were also documented to receive two doses [17] . Case-finding reports were generated after initial days vaccinating at fixed and mobile posts during all phases of vaccine administration in Bocozel . When attendance at vaccination posts slowed and vaccination coverage based on census information plateaued , we created a case-generating report with address information of over 11 , 000 residents ( approximately 20% of the target population for the campaign ) of Bocozel who had registered for OCV , but had not yet received OCV . Following the vaccination campaign , we mapped 55 vaccination posts and 4 health centers used as cold chain staging areas . We also mapped 53 localities in Bocozel , plus an additional point for Grand Saline . These data were used to generate maps of vaccination post locations [17] , community coverage ( Figure 2 ) , and second-dose follow up ( Figure 3 ) . The total cost of deploying mHealth during the campaign ( including census in Bocozel , and vaccination in Bocozel and Grand Saline ) was $29 , 129 . Technology-related training cost $6 , 624; software and development totaled $7 , 900 . Hardware purchase/rentals and surge protectors totaled $14 , 605 , but the cost for hardware is flexible depending on negotiations , demand , and the regularly changing cost of technology .
The use of mobile health technology in a reactive OCV campaign in Haiti allowed timely creation of an electronic vaccination registry with population-level census data , and a targeted vaccination strategy in a dispersed rural population receiving a two-dose vaccine regimen . Direct-entry electronic registries allowed us to evaluate community coverage in near real-time , and to generate case-finding reports that resulted in greater than had occurred with fixed vaccination posts . The collection of GPS coordinates for geospatial mapping allowed us to calculate , plot and visualize community coverage and vaccination follow-up rates , which were important programmatic results in the setting of an epidemic and humanitarian crisis . The use of mHealth should be strongly considered in future mass vaccination campaigns , including during epidemics and situations in which timely access to vaccination coverage data is required .
|
The World Health Organization ( WHO ) recently endorsed the creation of a global oral cholera vaccine ( OCV ) stockpile as part of an integrated , strategic framework to address the re-emerging threat that cholera causes worldwide . In conjunction , the WHO also called for continued monitoring and evaluation around the use of OCV in different settings . In response to the cholera epidemic in Haiti that began in October 2010 , Partners In Health , an implementing partner of Haiti's Ministry of Health , vaccinated 50 , 000 Haitians in two rural communities in the Artibonite Valley in 2012 . In this paper , the authors describe the use of mobile health ( mHealth ) technology for data collection and geospatial mapping to document this rural OCV campaign , focusing on the utility , benefits , and challenges of mHealth in a reactive campaign in the midst of the ongoing epidemic .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"public",
"and",
"occupational",
"health",
"bacterial",
"diseases",
"infectious",
"diseases",
"medicine",
"and",
"health",
"sciences",
"behavioral",
"and",
"social",
"aspects",
"of",
"health",
"global",
"health",
"biology",
"and",
"life",
"sciences",
"immunology",
"infectious",
"disease",
"control",
"vaccination",
"and",
"immunization"
] |
2014
|
Using Mobile Health (mHealth) and Geospatial Mapping Technology in a Mass Campaign for Reactive Oral Cholera Vaccination in Rural Haiti
|
Replicative DNA polymerases are stalled by damaged DNA while the newly discovered Y-family DNA polymerases are recruited to rescue these stalled replication forks , thereby enhancing cell survival . The Y-family DNA polymerases , characterized by low fidelity and processivity , are able to bypass different classes of DNA lesions . A variety of kinetic and structural studies have established a minimal reaction pathway common to all DNA polymerases , although the conformational intermediates are not well defined . Furthermore , the identification of the rate-limiting step of nucleotide incorporation catalyzed by any DNA polymerase has been a matter of long debate . By monitoring time-dependent fluorescence resonance energy transfer ( FRET ) signal changes at multiple sites in each domain and DNA during catalysis , we present here a real-time picture of the global conformational transitions of a model Y-family enzyme: DNA polymerase IV ( Dpo4 ) from Sulfolobus solfataricus . Our results provide evidence for a hypothetical DNA translocation event followed by a rapid protein conformational change prior to catalysis and a subsequent slow , post-chemistry protein conformational change . Surprisingly , the DNA translocation step was induced by the binding of a correct nucleotide . Moreover , we have determined the directions , rates , and activation energy barriers of the protein conformational transitions , which indicated that the four domains of Dpo4 moved in a synchronized manner . These results showed conclusively that a pre-chemistry conformational change associated with domain movements was too fast to be the rate-limiting step . Rather , the rearrangement of active site residues limited the rate of correct nucleotide incorporation . Collectively , the conformational dynamics of Dpo4 offer insights into how the inter-domain movements are related to enzymatic function and their concerted interactions with other proteins at the replication fork .
Elucidating the mechanism of enzyme catalysis encompasses the identification and characterization of each chemical and conformational intermediate occurring along the reaction pathway [1] . Among the six families ( A , B , C , D , X , and Y ) of DNA polymerases , crystallographic studies have captured these enzymes , which exhibit a similar three-dimensional right hand shape composed of the finger , palm , and thumb domains , in various states . By superimposing these structural snapshots during a catalytic cycle , conformational changes have been revealed as the polymerase sequentially binds the DNA and nucleotide substrates . In general , nucleotide binding induces a significant structural change involving an open-to-close transition of the finger domain for the A- , B- , and some X-family DNA polymerases [2]–[6] while ternary complex formation for the Y- and some X-family members [7] , [8] leads to the subtle repositioning of select active site residues . The open-to-close finger domain transition induced by nucleotide binding provides the basis for an induced-fit model , which has been proposed to correspond to the rate-limiting step of correct nucleotide incorporation . Numerous stopped-flow studies monitoring a single fluorophore , either on DNA ( e . g . , 2-aminopurine ) [9]–[13] or on the finger domain ( tryptophan or fluorescent dye ) of a DNA polymerase [14] , [15] , have generated interesting but contradictory evidence for this assignment because the fluorescence intensity of a fluorophore can be affected by many factors , thereby complicating data interpretation . Recently , this assignment of the rate-limiting step has been forcefully questioned due to fluorescence resonance energy transfer ( FRET ) -based evidence for two A-family DNA polymerases [16]–[18] , which shows that the closure rate of the finger domain is too fast to limit correct nucleotide incorporation . Therefore , it has been hypothesized by us [19] , [20] and others [16]–[18] , [21] that the rate-limiting step corresponds to the subtle repositioning of active site residues , which are critical for properly aligning two magnesium ions , the 3′-hydroxyl of the primer terminus , the α-phosphate of the incoming dNTP , and the conserved carboxylate residues in the active site . To the best of our knowledge , no studies have characterized the global conformational dynamics of a DNA polymerase undergoing catalysis . Besides the finger domain , other core domains of a DNA polymerase may undergo significant structural changes and movements during nucleotide incorporation . To establish a better understanding of the interrelationship between protein conformational dynamics and nucleotide incorporation , we chose to investigate Dpo4 , a 40 kDa Y-family DNA polymerase containing no tryptophan residues and a single cysteine . In addition to the three aforementioned polymerase core domains , Dpo4 also possesses a little finger ( LF ) domain that is unique to the Y-family DNA polymerases ( Figure 1 ) [22]–[24] . After generating two FRET systems ( i . e . , donor on DNA/acceptor on each domain of Dpo4 and donor on the LF domain/acceptor on the finger domain ) using protein engineering methods , we monitored time-dependent FRET signal changes during a single , correct nucleotide incorporation in order to probe how each domain of Dpo4 moved relative to either DNA or LF in real time . We observed a surprising DNA translocation event induced by nucleotide binding and concerted motions of all four of Dpo4's domains during catalysis . We also conclusively excluded rapid domain closure as the rate-limiting step of the kinetic mechanism for correct nucleotide incorporation .
Recently , our crystallographic study of Dpo4 reports that , upon nucleotide binding , no large-scale domain movements are observed , but local conformational changes occur for active site residues ( Y10 , Y48 , R51 , and K159 ) near the nucleotide binding pocket [8] . To examine if these crystallographic observations are true in solution , we investigated the conformational changes of Dpo4 during a single , correct nucleotide incorporation by monitoring the real-time FRET changes with a stopped-flow apparatus . Conformational changes were detected using two FRET systems , which monitored ( i ) the motions of specific residues on each domain relative to the enzyme-bound DNA substrate and ( ii ) the motions of the finger domain relative to the LF domain . For system ( i ) , the FRET pair consisted of an Alexa488 donor fluorophore covalently linked to the ninth primer base [22] from the primer 3′-terminus in S-1 or S-2 DNA ( Table 1 ) and an Alexa594 acceptor fluorophore on a site-specific , substituted cysteine , which was not a functionally conserved residue in Dpo4 ( Figure 1 and Table S1 ) . At least one α helix residue and one loop residue in each domain were selected for attaching Alexa594 ( Table S1 ) in order to exclude the effect of protein secondary structure on the observed real-time FRET . For system ( ii ) , an intrinsic tryptophan donor ( Y274W ) was engineered into the LF and the 7-diethylamino-3- ( 4′-maleimidylphenyl ) -4-methylcoumarin ( CPM ) acceptor fluorophore was attached to a single cysteine mutation in a loop of the finger domain ( Table S2 ) . The Förster radii ( R0 ) of the FRET pairs of Alexa488/Alexa594 and tryptophan/CPM are 60 and 30 Å , respectively [25] . Notably , the reason why these two FRET systems can be established through protein engineering methods is because Dpo4 contains no native tryptophan residues and only one native cysteine residue . This native cysteine residue was mutated to serine so that only a single cysteine was labeled with either Alexa594 or CPM ( Materials and Methods ) . DNA polymerase activity of each fluorophore-labeled and unlabeled Dpo4 mutant was measured under single-turnover conditions using radioactive chemical-quench techniques; these rates were determined at both 20°C and 37°C ( Table S3 ) . Relative to wild-type Dpo4 , the observed rate constants ( kobs ) indicated that the mutants , with or without the dye , were catalytically active . Furthermore , the circular dichroism spectra of unlabeled mutants were nearly identical to wild-type Dpo4 ( Figure S1 ) , thereby indicating these point mutations did not significantly alter the enzyme's secondary structure . To verify the conformational changes were related to a FRET signal , steady-state fluorescent assays were employed using Dpo4 mutants labeled with Alexa594 , either S-1 or S-2 DNA substrates attached to Alexa488 , and the correct nucleotide , dTTP . First , control experiments were performed with either labeled protein binding to unlabeled DNA or unlabeled protein binding to labeled DNA in the presence or absence of dTTP at 20°C . Although Dpo4 binds to DNA tightly with an affinity of 3–10 nM [19] , [26] , the emission spectra for these control experiments did not show any significant fluorescence changes of FRET ( Figure S2A and S2B ) . In contrast , addition of the labeled Dpo4 N70C mutant to the labeled DNA alone ( black trace ) resulted in a large reduction in donor ( Alexa488 ) fluorescence accompanied by a concomitant increase in acceptor ( Alexa594 ) fluorescence ( red trace ) upon exciting at the donor excitation wavelength of 493 nm ( Figure 2 ) . The dramatic acceptor fluorescence increase was likely due to efficient FRET between donor and acceptor . After the addition of 1 mM correct incoming nucleotide dTTP to the Dpo4•DNA ( S-1 or S-2 ) complex , a decrease in FRET ( green trace ) was observed ( Figure 2 ) as indicated by an increase in donor fluorescence and a decrease in acceptor fluorescence . The changes in both donor and acceptor fluorescence were slightly larger with S-1 than with S-2 when superimposing their steady-state fluorescence spectra ( unpublished data ) . Although the amplitude of the FRET change induced by dTTP addition was relatively small , the experimental result was reproducible . Similar phenomena were observed for the LF , palm , and thumb domain mutants ( unpublished data ) . The FRET signal represented conformational changes that may be predominantly pre-catalytic , since a similar trend was detected with dideoxy-terminated S-2 DNA ( Figure 2B ) . Overall , these results confirmed that this FRET system indeed monitored Dpo4's conformational transitions during the nucleotide incorporation cycle . Real-time kinetic FRET experiments were performed to further dissect the FRET change in Figure 2 and to measure the conformational transition rates of the nucleotide-induced domain movements for the binary Dpo4•DNA ( S-1 or S-2 ) complex at 20°C and 37°C . First , domain motions relative to DNA were investigated . No time-dependent fluorescence change was detected in control experiments , which were performed as stated above ( Figure S2C ) . Upon the addition of dTTP to the labeled Dpo4•S-1 complex , certain residues on the finger ( N70C ) and palm ( S112C and N130C ) domains exhibited three FRET phases while all other mutants showed two phases ( Figure 3 and Figure S3 ) . As expected , the time-dependent FRET signal changes of acceptor were correlated with the fluorescence signal changes of the donor , and hereafter only the acceptor signal is discussed . For the finger ( N70C ) and palm ( S112C and N130C ) domain mutants , the three phases were defined by an initial , rapid FRET decrease phase ( P0 ) followed by a second , fast increase phase ( P1 ) and a third , slow decrease phase ( P2 ) ( Figure 3A , 3B , and Figure S3C ) . Any change in FRET represents a change in the distance between two fluorophores , which subsequently indicates the motion of a Dpo4 domain relative to DNA . Thus , the above-mentioned FRET changes indicated a rapid DNA translocation event during P0 ( see below ) , closure of the finger and palm domains to grip the DNA substrate during P1 , and reopening of these two domains during P2 ( Figure 1 ) . Meanwhile , the remaining mutants showed two phases that were similar to the aforementioned P1 and P2 phases ( Figure 3C , 3D , and Figure S3 ) . However , depending upon the mutant , the directionality of these two phases' FRET signals varied . The FRET traces for the thumb mutants ( K172C and S207C ) exhibited a “gripping-reopening” motion analogous to P1 and P2 for N70C , S112C , and N130C ( Figure 3 and Figure S3 ) . In contrast , residues in the LF ( R267C and K329C ) , finger ( E49C ) , and palm ( S96C ) domains moved away and then towards the DNA ( Figure 3D and Figure S3 ) . To determine whether these domain movements for each phase were synchronized , we fit each individual phase to a single-exponential equation in order to extract the rates of the conformational transitions ( Table S4 ) . Interestingly , an initial , rapid FRET decrease , P0 , for the finger ( N70C ) and palm ( S112C and N130C ) residues was detected , which suggested a DNA translocation event that increased the distance between the FRET pair . This event was likely through the rotation of the DNA duplex and can also be inferred from the superimposition of our published binary and ternary crystal structures of Dpo4 [8] . Interestingly , a stopped-flow study of S . acidocaldarius DinB homolog ( Dbh ) , a Y-family homolog of Dpo4 , has also inferred a similar DNA translocation event based on real-time fluorescence changes of a single fluorophore ( 2-aminopurine ) in DNA [9] , although the evidence is indirect and questionable . Unfortunately , the rate of P0 occurred too fast to be determined accurately and is not reported here . Since this P0 phase occurred near the time resolution of our instrument , the corresponding FRET decrease could not be distinguished when P1 also resulted in a FRET decrease as with residues on the LF , E49C on the finger , and S96C on the palm . Additionally , the distances between the residues on the thumb domain and the labeled DNA base were approximately perpendicular to the direction of DNA translocation in P0 . Therefore , the change in distance for each of these events likely produced a change in fluorescence below the level of sensitivity of our system . Interestingly , the rates for each domain during P1 and P2 were similar at each reaction temperature for both the donor and acceptor fluorescence traces , and so the average rates of P1 and P2 are used to simplify the discussion in the later section . However , the average P2 rate was approximately 25- or 5-fold slower at 20°C and 37°C , respectively , than that of P1 ( Table S4 ) . The similar rates of the donor and acceptor further confirmed that the observed fluorescence changes were due to a time-dependent FRET process . Based on the sites tested herein , the domains of Dpo4 moved in a concerted motion upon binding a correct nucleotide . However , the relative direction of residues within each domain was not always identical , which likely reflects the rotational nature of the polymerase core domains assembling the active site for catalysis . Consistently , neutron spin-echo spectroscopic studies of Thermus aquaticus DNA polymerase reveal that this A-family enzyme does not function as a rigid body in solution but uses coupled inter-domain motions and intra-domain rotations to coordinate catalysis [27] . After examining the ternary crystal structure of Dpo4 [22] , a rotational axis in the palm domain between β-sheets 5 and 6 , where the active site is in closer proximity to the bound DNA and dNTP , would be consistent with an inward motion of residues S112C and N130C and an outward motion of residue S96C . Similarly , for the finger mutants N70C and E49C , a rotational motion about an axis between α-helixes B and C would allow the finger domain to be in greater contact with the substrates despite the anomalous directionality of the FRET traces . The LF and thumb domains may rotate upon formation of a ternary complex , although the locations examined in this study did not confirm this possibility . Our next objective was to discern if these conformational changes were occurring before or after the chemistry step . Using a non-extendable S-2 DNA substrate , we observed that P2 for all mutants was absent while the other phases remained unchanged ( Figure 4 and Figure S4 ) . The apparent disappearance of P2 indicated that P0 and P1 represented pre-chemistry conformational changes while P2 represented either the chemistry step or a post-chemistry event . Based on the varying temperature dependencies for the P1 and P2 rates at 20°C and 37°C , these data suggested that the free energy profile was different for these pre- and post-chemistry conformational transitions . Thus , parallel stopped-flow experiments were performed at 17°C , 24°C , and 32°C in order to determine the activation energy ( Ea ) barriers for P1 and P2 ( Table 2 and Figure S5 ) . The rates for each phase were plotted as a function of temperature so that the Ea value could be extrapolated ( Figure 5 ) . Although the domain movements occurred at similar rates , the activation energy barriers showed a wider range: 13–18 kcal/mol for P1 and 20–25 . 4 kcal/mol for P2 ( Table 2 ) . The average Ea values were 15±2 and 23±2 kcal/mol for P1 and P2 , respectively . Both of these Ea barriers were less than the Ea value of 32 . 9 kcal/mol , which has been determined previously as the rate-limiting conformational change prior to phosphodiester bond formation using a radioactive chemical-quench technique [20] . Therefore , neither of these fluorescent phases was directly related to the rate-limiting conformational change . Moreover , the Ea barrier for uncatalyzed phosphodiester bond formation in solution is estimated to be 21 . 1 kcal/mol [28] . The Ea should be lower than 21 . 1 kcal/mol if this reaction was catalyzed by an enzyme like Dpo4 based on Pauling's transition state theory [29] . Consistently , Florián et al . have used computer simulation to conclude that for T7 DNA polymerase , a rate-limiting phosphodiester bond formation step involving the transfer of a proton to activate the 3′-hydroxyl nucleophile accounts for an activation energy of 12 . 3 kcal/mol [28] . Radhakrishnan and Schlick have used quantum mechanics/molecular mechanics dynamics simulations and quasi-harmonic free energy calculations to show that the rate-limiting phosphodiester bond formation step for correct nucleotide incorporation catalyzed by DNA polymerase β occurs with a free energy of activation of 17 kcal/mol [30] . Thus , P2 likely represented a post-chemistry event rather than the chemistry step , because the average Ea of P2 was higher than that of uncatalyzed phosphodiester bond formation in solution . Also noteworthy , we focused on the FRET data collected at 20°C and 37°C , both sub-optimal temperatures for the thermostable Dpo4 , since data collected at temperatures exceeding 37°C did not capture as many FRET phases due to the faster rates . Nonetheless , Dpo4 remained active , dynamic , and flexible at both 20°C and 37°C [20] . To support and expand upon the above work , the motions of the finger domain ( Table S2 ) relative to the LF domain ( Y274W ) were investigated . For the two CPM-labeled Dpo4 mutants with S-3 ( Table 1 ) , the nucleotide binding and incorporation steps produced an acceptor fluorescence trace consisting of two phases: an initial , fast decrease phase followed by a slow increase phase ( Figure 6 , black trace ) . The similar kinetic rates , obtained after fitting each phase with a single-exponential equation , suggested that these two phases were correlated to P1 and P2 as identified from the above domain-DNA studies . Using dideoxy-terminated S-4 DNA , the second , slow phase was not detected ( Figure 6 , red trace ) . Together , these results demonstrated that the finger domain initially moved away from the LF domain before catalysis and then reopened following nucleotidyl transfer ( Figure S6 ) . Currently , we are investigating how the palm and thumb domains move relative the LF domain during correct nucleotide incorporation by using the real-time FRET methodology with the tryptophan/CPM as the FRET pair . The overall picture emerging from our data suggested that the conserved polymerase core , composed of the finger , palm , and thumb domains , moved inward to tighten its grip on the DNA ( Figures 1 and 3 ) , which was important in aligning the substrates for formation of an active ternary complex ( P1 ) . In the meantime , the LF domain , a non-polymerase core domain , moved away from the DNA ( Figures 1 and 3 ) . After nucleotide incorporation , the domains slowly returned to a relaxed conformation ( P2 ) . The opposing directional movement of the LF domain may play a role in translesion synthesis . Functionally important domain rearrangements have been observed in many proteins [31] . By moving away from the DNA , the additional space at the polymerase active site may accommodate a distorted DNA structure , especially those containing bulky DNA lesions . Since this movement was observed with undamaged DNA , it is possible that the dynamic conformational motions of the LF domain have evolved to confer the lesion bypass abilities unique to Dpo4 and other Y-family DNA polymerases . Furthermore , the interactions between Dpo4 and the proliferating cell nuclear antigen have been mapped to the LF domain [32] . Therefore , this domain motion may be important during protein-protein interactions at the replication fork . Lastly , the inward movement of the LF domain during the post-chemistry relaxation ( reopening ) stage may inhibit the translocation of DNA and prevent processive nucleotide incorporation . This hypothesis is supported by the low polymerization processivity of Dpo4 , which has been shown to be about one nucleotide incorporation per DNA binding event by us ( K . A . Fiala and Z . Suo , unpublished data ) and others [33] . On the basis of our data , the minimal kinetic pathway catalyzed by Dpo4 [19] has been expanded as shown in Figure 7 . In Step 1 , the Dpo4•DNA binary complex was formed and existed mainly as a complex where the primer terminus occupied the dNTP binding pocket ( DNA* ) so that nucleotide incorporation could not occur until DNA translocated [8] . Notably , the structure of Dpo4 undergoes significant conformational changes from its apo form ( Eapo ) to its binary form based on our published structural studies [8] . Step 2 , which corresponded to the FRET signal change of P0 , demonstrated the DNA translocation event induced by nucleotide binding [8] , [9] . Once the ternary complex has formed , Dpo4 tightened its grip ( E′ ) as evident by the domain motions representing P1 ( Step 3 ) . Superimposing the crystal structures of Dpo4's binary and ternary complexes has revealed that some active site residues are re-positioned ( E″ ) to properly align all substrates ( Step 4 ) , and this process corresponded to the rate-limiting step during nucleotide incorporation as determined by our previous work ( see discussion below ) [8] , [19] , [20] . Following phosphodiester bond formation ( Step 5 ) , the active site isomerisation step must be reversed ( Step 6 ) as well as the “grip” conformational change ( Step 7 ) , i . e . , the conformational transition related to the fluorescence change observed in P2 . Lastly , the reopening of the domains allowed pyrophosphate ( PPi ) to be released ( Step 8 ) so that the binary complex can either undergo another catalytic cycle or dissociate [19] , [20] . The assignment of the rate-limiting step during nucleotide incorporation has been controversial in the DNA polymerase field for a long time [21] . We propose that Step 4 represents the rate-limiting event ( Figure 7 ) for the following reasons: ( i ) at 20°C , the collapse of the polymerase core domains ( Step 3 ) was much faster ( average P1 = 15 . 3 s−1 in Table S4 ) than the rates determined using radioactive chemical-quench techniques ( average kobs = 0 . 66 s−1 ) , which is consistent with the fast closure rate of the finger domain of other DNA polymerases [16]–[18]; ( ii ) the rate of phosphodiester bond formation is estimated to be 9 , 000 s−1 at 20°C [34]; and ( iii ) the activation energy barriers of the P1 and P2 conformational transitions did not coincide with the Ea of 32 . 9 kcal/mol obtained for nucleotide incorporation ( see above discussion ) [20] . The evidence in ( i ) and ( iii ) exclude Step 3 as rate limiting while both ( ii ) and ( iii ) eliminated Step 5 in our consideration . These differences in rate and Ea barriers along with three independent lines of kinetic evidence ( about 25% more products can be formed if the reaction is chased with a large excess of unlabeled , correct dTTP , rather than quenched with strong acid; E″•DNAn•dNTP has a ∼100-fold slower dissociation rate than E•DNAn•dNTP; and there is an insignificant elemental effect between the incorporation of correct dTTP and its α-thio analog , Sp-dTTPαS [19] , [20] ) suggested that the pre-chemistry isomerisation step ( Step 4 ) limited the rate of a correct nucleotide incorporation determined using radioactive chemical-quench techniques . Thus , Step 4 occurred at an average rate of 0 . 66 s−1 at 20°C . However , this rate-limiting step was not probed here because the subtle active site rearrangements would not alter the distance between the FRET pair , thereby yielding no detectable FRET signal changes . Currently , the nature of Step 4 is unclear . It may involve repositioning of the side chains of active site residues [8] , binding of metal ion ( s ) [12] , and/or realignment of the 3′-hydroxyl of the primer terminus and the α-phosphate of an incoming nucleotide for an in-line phosphodiester bond formation [35] . Notably , the rates of P2 at 20°C ( average P2 = 0 . 57 s−1 ) were similar to the rapid-chemical quench rates ( average kobs = 0 . 66 s−1 ) . This is because the P2 fluorescence signal likely originated from the rapid domain movements that occurred during Step 7 . However , the rate was limited by the slow , preceding isomerisation process ( Step 6 ) . Although we do not know the rate of Step 6 , we assume that it was comparable to the rate of Step 4 , since Step 6 was the reverse isomerisation process . To determine the magnitudes of the protein conformational changes in Figure 7 , we quantitatively estimated the distances between the donor and acceptor fluorophores in FRET system ( i ) ( see above ) using the measurements of steady-state FRET efficiency at 20°C as in Figure 2 ( unpublished data ) . Distances were calculated for each of the two states ( Table S5 ) : the initial binary complex of Dpo4 and S-1 ( i . e . , E•DNAn* in Figure 7 ) and the ternary complex of Dpo4 , S-2 , and dTTP ( i . e . , E″•DNAn•dNTP in Figure 7 ) . Accordingly , the net movements for nine of Dpo4's residues during Steps 2 through 4 in Figure 7 vary from residue to residue and were in the range of −0 . 02 to 1 . 52 Å ( Table S5 , positive values indicate that the Dpo4 residues moved away from DNA ) . Consistently , if the residue moved away from the DNA during Step 3 as suggested by the above real-time FRET during P1 , e . g . , E49 , K329 , and R267 , then the net movement value in Table S5 is positive and relatively large since both the DNA translocation event in Step 2 and the conformational change in Step 3 increased the distance between the FRET pair . Interestingly , these steady-state FRET efficiency-based values were close to the predicted net movements ( −0 . 59 to 3 . 95 Å ) of the corresponding Dpo4 residues during correct nucleotide binding based on the binary [8] and ternary [36] crystal structures of Dpo4 ( Table S6 ) . If DNA slides by one base pair in Step 2 as suggested by the crystal structures of Dpo4 [8] , then the changes in distance between the nine FRET pairs due to movement of the DNA were predicted to be in the range of −1 . 35 to 5 . 21 Å ( Table S6 ) . Moreover , the motion distances of these nine Dpo4 residues from Steps 3 to 4 , which were likely dominated by Step 3 , were predicted to be in the range of either −3 . 69 to 1 . 86 Å ( Table S5 ) or −1 . 51 to 0 . 93 Å ( Table S6 ) . Together , these measured and predicted data suggest that the motions of Dpo4's residues and domains as induced by the binding of a correct dTTP were not dramatic and occurred within a few angstroms . Although trends of residue motions derived from Tables S5 and S6 were similar , the structurally predicted net movements during Steps 2 to 4 are larger . These differences are not surprising since the crystal structures that are often influenced by crystal packing may not reflect the exact structures in solution . Furthermore , the flexibility of the long linker for fluorophore attachment to a cysteine residue or a DNA base may induce uncertainty in the estimated distances between FRET pairs based on the steady-state FRET efficiencies . Lastly , distance calculations in Table S5 assumed that both the donor and acceptor fluorophores can undergo unrestricted isotropic motions , which may not be true for the various conformations sampled by each measured residue in Dpo4 . The combined dynamic and kinetic studies allow us to draw four conclusions that improve our current understanding about the kinetic mechanism of DNA synthesis ( Figure 7 ) . First , there was a rapid DNA translocation event induced by the binding of a correct nucleotide . Second , the four domains of Dpo4 moved in a synchronized manner during correct nucleotide incorporation . The LF domain and the polymerase core moved in opposite directions . The palm and finger domains did not move as rigid bodies due to the presence of intra-domain rotational movements . Third , the motions of the amino acid residues and domains of Dpo4 induced by correct nucleotide binding are within a few angstroms . Fourth , the active site rearrangement process ( Step 4 ) , rather than the pre-chemistry conformational change associated with domain movements ( Step 3 ) and phosphodiester bond formation ( Step 5 ) , limited the rate of correct nucleotide incorporation in the reaction pathway . Moreover , Step 3 ( 15 kcal/mol ) , Step 4 ( 32 . 9 kcal/mol ) , Step 5 ( <21 . 1 kcal/mol ) , and Step 6 ( 23 kcal/mol ) were thermodynamically distinguished in this paper . In addition to the invaluable information gathered on the protein dynamics of Dpo4 , our study illustrated the limitations of monitoring the motions of only a single residue relative to DNA by stopped-flow FRET [16]–[18] as seen by the contrasting results observed for residues on the finger and palm domains of Dpo4 in this paper . By monitoring multiple residues , we were able to reveal the proposed rotational nature of the domain movements . It is possible that further rotations or semi-rigid domain motions could be determined by monitoring more sites on the protein or DNA . These measurements are more meaningful if amino acid residues in each domain of Dpo4 move with slightly different rates and/or directions in each of the protein conformational change steps ( Step 3 , Step 4 , Step 6 , and Step 7 ) as the slightly different P1 and P2 rates in Table S4 have suggested ( Figure 7 ) . Thus , by using the real-time FRET methodology , this study presents a powerful system for monitoring the global dynamics of protein motions at multiple sites , which is necessary to gain a better understanding of enzyme catalysis . At present , we are using this system to investigate protein dynamics during incorrect nucleotide incorporation . It will be interesting to see whether DNA also translocates in order to free space for the binding of an incorrect nucleotide , whether Dpo4 undergoes similar global conformational dynamics as described above , whether Dpo4 uses a similar kinetic mechanism as shown in Figure 7 , and whether Step 4 is rate-limiting during misincorporation . Differences in the kinetic mechanisms for correct and incorrect nucleotide incorporations will reveal which steps serve as kinetic checkpoints and help Dpo4 to achieve its fidelity [21] . Moreover , since Dpo4 functions as a lesion bypass DNA polymerase in vivo , we are employing our FRET systems to explore Dpo4's protein dynamics during the bypass of DNA lesions , including an abasic site [37] , a N- ( deoxyguanosin-8-yl ) -1-aminopyrene adduct [26] , and a cisplatin-DNA adduct [38] . These studies will reveal how a lesion in the DNA template affects concerted domain motions within Dpo4 during DNA synthesis .
The plasmid [39] encoding the dpo4 gene from S . solfataricus P2 was mutated using the Stratagene QuikChange kit . To avoid ambiguity of labeling , the sole native cysteine was replaced with a serine ( C31S ) . Using the C31S mutant as a template , single cysteine substitutions were introduced individually into each domain ( Table S1 ) . Separately , an endogenous tryptophan FRET donor was substituted into the LF domain by generating a Y274W mutant ( Table S2 ) . All mutants summarized in Tables S1 and S2 contain the C31S substitution . Mutations were confirmed by DNA sequencing ( OSU Plant-Microbe Genomics Facility ) . Purification of the mutant proteins was performed as described for wild-type Dpo4 [39] . Dpo4 mutants were labeled with either Alexa594 or CPM ( Molecular Probes , Invitrogen ) by incubating the mixture at 4°C for 12 h with a 10-fold molar excess of dye , according to the manufacturer's protocol . After labeling , each Dpo4 mutant was separated from the unbound fraction of dye by both size-exclusion chromatography ( G-25 resin ) and extensive dialysis . The labeling efficiencies were typically 95% or greater as determined by the Bradford protein assay ( Bio-Rad ) . The protein concentration of each dye-labeled Dpo4 mutant was determined by a spectrometric Bradford protein assay ( Bio-Rad ) by using the corresponding unlabeled Dpo4 mutant as a protein standard . The concentration of each unlabeled protein was determined by UV spectroscopy at 280 nm using the calculated molar extinction coefficient of 28 , 068 M−1 cm−1 . All oligonucleotides ( Table 1 ) were purchased from Integrated DNA Technologies . Alexa488 ( Molecular Probes , Invitrogen ) was attached to a 5-C6-Amino-2′-deoxythymidine on the ninth primer base from the 3′-end of the DNA substrates . Alexa488-labeled DNA was purified according to the manufacturer's protocol and annealed as described previously [39] . Steady-state fluorescent assays ( Fluoromax-3 , Jobin Yvon Horiba ) , stopped-flow kinetic assays ( Applied Photophysics SX20 , UK ) , and rapid chemical-quench kinetic assays ( KinTek ) were carried out under the same conditions in buffer R , which contained 50 mM HEPES , pH 7 . 5 at desired temperature , 50 mM NaCl , 6 mM MgCl2 , 0 . 1 mM EDTA , and 10% glycerol . For domain motions relative to DNA , 600 nM Dpo4 mutant , 100 nM DNA , and 1 mM dTTP were used . For stopped-flow experiments , with excitation of donor Alexa488 at 493 nm , both donor and acceptor fluorescence signals were recorded separately by using band pass filters XF3084 for Alexa488 ( band pass range: 510–570 nm , Omega Optical , USA ) and XF3028 for Alexa594 ( band pass range: 615–650 nm , Omega Optical , USA ) over time . For finger domain motions relative to the LF , 200 nM Dpo4 mutant , 300 nM DNA , and 1 mM dTTP were reacted . The CPM fluorescence was monitored by using a 420-nm cut-off filter when the tryptophan donor was excited at 290 nm . In both steady-state and stopped-flow kinetic experiments , slits were set at 5 nm for both excitation and emission . Fluorescence traces were fit to a single-exponential equation , ΔF = A[exp ( −kt ) ]+constant . Rapid chemical-quench reactions [39] were performed as described previously . For each reaction time course , a single-exponential equation , [Product] = A[1−exp ( −kobst ) ] , was used to extract the observed rate constant ( kobs ) . Activation energy barriers were extrapolated as described previously [20] . Briefly , the plot of lnk versus 1/T was fit to a linear equation , lnk = −Ea/RT + constant , to extract the activation energy barrier ( Ea ) . “k” was the rate derived from the stopped-flow experiment at each reaction temperature T ( Kelvin ) .
|
Faithful replication of genomic DNA by DNA polymerases is crucial for maintaining the genetic integrity of an organism . If DNA becomes damaged , specialized lesion-bypass DNA polymerases are recruited to correct errors in the DNA . A variety of kinetic and structural studies have established a minimal kinetic mechanism common to all DNA polymerases . This mechanism includes several steps involving discrete protein conformational changes . However , the inter-relationship between conformational dynamics and enzymatic function has remained unclear , and identification of the rate-limiting step during nucleotide incorporation has been controversial . In this study , we monitored the directions and rates of motion of domains of a lesion-bypass polymerase during correct nucleotide incorporation . Our study provides several significant findings . First , the binding of a correct nucleotide induces a fast and surprising DNA translocation event . Second , all four domains of the polymerase rapidly move in a synchronized manner before and after the polymerization reaction . Third , repositioning of active site residues is the rate-limiting step during correct nucleotide incorporation . Thus , the motions of the polymerase and the polymerase-bound DNA substrate are tightly coupled to catalysis .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry/replication",
"and",
"repair"
] |
2009
|
Global Conformational Dynamics of a Y-Family DNA Polymerase during Catalysis
|
The simian parasite Plasmodium knowlesi is a common cause of human malaria in Malaysian Borneo and threatens the prospect of malaria elimination . However , little is known about the emergence of P . knowlesi , particularly in Sabah . We reviewed Sabah Department of Health records to investigate the trend of each malaria species over time . Reporting of microscopy-diagnosed malaria cases in Sabah is mandatory . We reviewed all available Department of Health malaria notification records from 1992–2011 . Notifications of P . malariae and P . knowlesi were considered as a single group due to microscopic near-identity . From 1992–2011 total malaria notifications decreased dramatically , with P . falciparum peaking at 33 , 153 in 1994 and decreasing 55-fold to 605 in 2011 , and P . vivax peaking at 15 , 857 in 1995 and decreasing 25-fold to 628 in 2011 . Notifications of P . malariae/P . knowlesi also demonstrated a peak in the mid-1990s ( 614 in 1994 ) before decreasing to ≈100/year in the late 1990s/early 2000s . However , P . malariae/P . knowlesi notifications increased >10-fold between 2004 ( n = 59 ) and 2011 ( n = 703 ) . In 1992 P . falciparum , P . vivax and P . malariae/P . knowlesi monoinfections accounted for 70% , 24% and 1% respectively of malaria notifications , compared to 30% , 31% and 35% in 2011 . The increase in P . malariae/P . knowlesi notifications occurred state-wide , appearing to have begun in the southwest and progressed north-easterly . A significant recent increase has occurred in P . knowlesi notifications following reduced transmission of the human Plasmodium species , and this trend threatens malaria elimination . Determination of transmission dynamics and risk factors for knowlesi malaria is required to guide measures to control this rising incidence .
Malaria elimination is now a goal of many countries in Southeast Asia and the Western Pacific , and large reductions in malaria prevalence have been achieved [1] . However , significant challenges remain , and while the threat of artemisinin resistance has been the focus of much international concern , zoonotic malaria species have received less consideration . Malaysia has had one of the most successful malaria control programs in the region , and aims to be malaria-free by 2020 [1] , [2] . However , the simian parasite Plasmodium knowlesi , transmitted by the forest-dwelling Anopheles leucosphyrus group of mosquitoes , is now a common cause of human malaria in the eastern states of Sabah and Sarawak , and presents an increasing threat to malaria elimination [3] , [4] , [5] , [6] , [7] . Documentation of the emergence of this species over time is limited by the inability to distinguish P . knowlesi from P . malariae by microscopy . Although the first naturally acquired case of human knowlesi malaria was reported from Peninsular Malaysia in 1965 [8] , with a second probable case several years later [9] , it was not until the early 2000s that a large focus of human infections was described in Kapit , Sarawak [10] . Since this time an increasing number of cases have been reported , and P . knowlesi is now the most common cause of human malaria in several districts throughout Sabah and Sarawak [3] , [4] , [5] , [6] . The highest proportion has been reported at Kudat District Hospital ( KDH ) , on the northeast tip of Sabah , where 87% of patients admitted with malaria in 2009 were infected with P . knowlesi [3] . Whether this apparent increase in cases however is due to a true emergence of the species or increasing recognition remains uncertain . Evolutionary analyses of sequence data from samples obtained from Sarawak indicate that P . knowlesi existed in macaques in Southeast Asia more than 100 , 000 years ago , with infection in humans likely occurring from the time of human arrival in the region [11] . In the earliest documented malaria survey conducted in Sarawak , in 1952 , one third of all malaria cases were reported as P . malariae by microscopy [12] . Given the evidence of very few cases of P . malariae in Sarawak when PCR methods are used [4] , [5] , [10] , it seems likely that at least some of these cases were P . knowlesi . When PCR was performed on the earliest P . malariae slides available , taken in 1996 , 35/36 ( 97% ) were positive for P . knowlesi , with only one being positive for P . malariae [13] . In 1999 , “P . malariae” accounted for 9% of all malaria notifications in Sarawak , and 20% of cases in the Kapit district [14] . In Sabah , limited available evidence suggests that the situation may differ from that of Sarawak , and that P . knowlesi infection in humans may have increased only recently . In 2001 , only 96/6050 ( 1 . 6% ) malaria slides referred to the Sabah State Public Health Laboratory were diagnosed as P . malariae monoinfection by microscopy , with the proportion increasing to 59/2741 ( 2 . 2% ) in 2004 [15] . In contrast , microscopy-diagnosed “P . malariae” accounted for 621/1872 ( 33% ) of malaria cases reported to the Sabah Department of Health in 2011 ( unpublished data from Sabah Department of Health records ) . In this study , we reviewed the Sabah Department of Health records of malaria notifications from 1992–2011 , in order to investigate the trend of each malaria species over time , and in particular to determine if P . knowlesi represents an emerging infection in humans .
The study was approved by the Medical Research Sub-Committee of the Malaysian Ministry of Health and the Menzies School of Health Research , Australia . All data analysed were anonymised . The north-eastern Malaysian state of Sabah has an area of 73 , 600 km2 and a population of 3 . 2 million [16] . Situated between 4° and 7° north of the equator , Sabah has a mostly tropical climate , with high humidity and rainfall throughout the year and temperatures of 25–35°C . The southwest interior of Sabah is mountainous , with the Crocker Range separating west coast lowlands from the rest of the state and extending north to Mount Kinabalu at 4095 meters above sea level . Sabah was previously covered almost entirely in dense primary rainforest , however extensive deforestation occurred throughout the 1970s and 1980s , reducing forest cover to 44–63% of the state [17] , [18] , [19] . Cleared areas have been partly replaced by plantations , with palm oil estates comprising 16% of Sabah's land area [19] . Malaysia has a long history of malaria control programs dating back to the early 1900s , with an initial focus on environmental management techniques . The launch of the Malaria Eradication Program in 1967 , followed by state-wide malaria control programs during the 1970s and 1980s , led to large reductions in malaria prevalence , with cases falling from 240 , 000 in 1961 to around 50 , 000/year during the 1980s [20] , [21] . Further scale-up of malaria control activities began in 1992 , consisting of increased surveillance , vector control , training of community volunteers , and early diagnosis and treatment [21] . Use of insecticide-treated nets and indoor residual spraying was implemented in 1995 , with nation-wide coverage of the high-risk population reported to be >50% and 25–50% respectively in 2010 [1] . In addition , Malaysia reports 100% confirmatory testing of suspected malaria cases and mandatory notification of detected cases [1] . Mosquito vectors in Sabah include An . balabacensis and An . donaldi [22] , and the P . knowlesi hosts , the long-tailed and pig-tailed macaques , are found throughout the state . In Sabah mandatory reporting of all malaria cases to the Sabah State Health Department is generally done by nursing staff , with species normally reported according to microscopy results . Blood slides with parasites resembling P . malariae/P . knowlesi are mostly reported , and hence notified , as P . malariae . We reviewed all available malaria notification records held by the Sabah State Health Department . Hard copy summaries of annual malaria notifications by species and by district were available from 1992 . From 2007 yearly Excel databases were also available that included limited demographic/epidemiological information for each malaria notification . We therefore recorded the number of notifications of each Plasmodium species annually for each district in Sabah from 1992–2011 , in addition to the age and sex distribution and seasonal variation of each species from 2007–2011 . Data were analysed using Stata statistical software , version 10 . 0 ( StataCorp LP , College Station , TX , USA ) . Spearman's correlation coefficient was used to analyse the association between annual notification rates of the Plasmodium species . Median ages were compared using Wilcoxon rank-sum test , and proportions were assessed using the Chi-square test . Edwards' test was used to assess seasonality of the Plasmodium species . Notifications of P . malariae and P . knowlesi were considered as a single group ( “P . malariae/P . knowlesi” ) , due to the inability to distinguish these species by microscopy . Mixed-species infections were recorded as a single group , with analysis of these cases limited to annual notification rates .
Between 1992 and 2011 the total number of malaria notifications to the Sabah State Health Department decreased dramatically , with P . falciparum notifications peaking at 33 , 153 in 1994 and decreasing 55-fold to 605 in 2011 , while P . vivax notifications peaked at 15 , 857 in 1995 and decreased 25-fold to 628 in 2011 ( Figure 1 ) . Notifications of P . malariae/P . knowlesi also demonstrated a peak in the mid-1990s ( increasing from 200 in 1992 to 614 in 1994 ) , before decreasing to around 100/year in the late 1990s and early 2000s . Until 2003 , annual notifications of P . malariae/P . knowlesi strongly correlated with those of P . falciparum ( Spearman's correlation coefficient 0 . 94 , p<0 . 0001; Figure 2 ) . However , the relationship between the species began to change in the early 2000s , with P . falciparum notifications steadily decreasing ( from 3264 in 2002 to 605 in 2011 ) while P . malariae/P . knowlesi notifications remained stable from the late 1990s to 2006 , and then increased markedly from 2007 ( Figure 1 . B ) . An inverse correlation was demonstrated between P . falciparum notifications and P . malariae/P . knowlesi notifications between 2004 and 2011 ( Spearman's correlation coefficient −0 . 76 , p = 0 . 028; Figure 2 ) . Notifications of P . vivax generally correlated with those of P . falciparum ( Spearman's correlation coefficient from 1992–2011 = 0 . 90 , p<0 . 0001 ) , and with P . malariae/P . knowlesi notifications until around 2008 ( Spearman's correlation coefficient 0 . 91 , p<0 . 0001 ) . Since 2008 P . vivax notifications decreased while P . malariae/P . knowlesi notifications increased , although this relationship was not statistically significant . Using Sabah population estimates based on the 1991 , 2000 and 2010 Population and Housing Censuses of Malaysia [23] , [24] , the incidences of P . falciparum and P . vivax peaked at 16 . 0 and 7 . 36/1000 people/year respectively during 1994–1995 , and decreased to 0 . 18 and 0 . 19/1000 people respectively in 2011 ( Figure 1 . C ) . In contrast the incidence of P . malariae/P . knowlesi peaked at 0 . 28/1000 people in 1995 , decreased to ≈0 . 02–0 . 04/1000 people from 2000–2006 , and increased to 0 . 21/1000 people in 2011 . The relative proportions of the Plasmodium species changed significantly over the past two decades , with P . falciparum , P . vivax and P . malariae/P . knowlesi monoinfections accounting for 70% , 24% and 1% respectively of total malaria notifications in 1992 , compared to 30% , 31% and 35% in 2011 ( Figure 1 . D ) . A total of 4 . 4% of all malaria notifications were mixed-species infections , with this percentage increasing slightly over the years from a median of 3 . 98% from 1992–2001 to 5 . 20% from 2002–2011 ( p = 0 . 049 ) . The 23 districts of Sabah ( Figure 3 ) in general have experienced similar malaria trends over the past two decades , with P . falciparum and P . vivax notifications falling dramatically in all districts ( Figure 4 ) . P . malariae/P . knowlesi notifications mostly remained at low stable levels throughout the 1990s , accounting for <5% of total notifications in 87% of district-years from 1992–1999 . Exceptions included Tambunan from 1993–1994 and Beluran from 1995–1998 , where P . malariae/P . knowlesi accounted for 38/255 ( 15% ) and 701/6980 ( 10% ) of malaria notifications respectively , and Tenom from 1998–1999 and Tuaran in 1994 and 1999 , where approximately 6% of malaria notifications were P . malariae/P . knowlesi . Since the early 2000s most districts have experienced an increase in notifications of P . malariae/P . knowlesi ( Figure 3 and Figure 4 . B ) . This increase appears to have begun initially in the Interior Division , in the southwest of the state adjacent to Sarawak , where notifications nearly doubled between 2003 ( n = 28 ) and 2005 ( n = 55 ) , and more than doubled between 2005 and 2007 ( n = 136 ) , before increasing at a slower rate through to 2011 . In the West Coast Division to the northeast notifications appear to have increased later , remaining below 20 per year from 2001–2006 and then increasing to 45 in 2007 and 102 in 2009 . Continuing northeast to the tip of Borneo , Kudat Division has experienced the most remarkable and recent increase in P . malariae/P . knowlesi notifications , with cases increasing from 2–11 per year from 2001–2007 , to 106 in 2008 , 245 in 2009 , and 276 in 2011 . In the eastern districts of Sabah ( Sandakan and Tawau Division ) notifications of P . malariae/P . knowlesi have been fewer , although have been increasing since 2008 . In 2011 Kudat district accounted for the highest number of P . malariae/P . knowlesi notifications ( 184 , 26% ) , followed by Ranau ( 121 , 17% ) , Keningau ( 65 , 9% ) , Tenom ( 62 , 9% ) and Kota Marudu ( 52 , 7 . 4% ) . Epidemiological characteristics of notifications according to species were assessed from 2007–2011 , when relevant data were recorded for each notification . This time period included 16 , 011 malaria notifications , although species was not recorded for 373 ( 2 . 3% ) . The overall median age of patients with P . malariae/P . knowlesi ( 31 years ) was significantly higher than that of patients with P . vivax or P . falciparum ( median ages 23 years for both , p = 0 . 001 ) . Males with P . malariae/P . knowlesi demonstrated an approximately normal age distribution , with a mean , median and interquartile range of 33 , 30 and 20–45 years respectively ( Figure 5 ) . In contrast females with P . malariae/P . knowlesi appeared to demonstrate a bimodal age distribution , with local maxima at 9–12 and 50 years ( Figure 5 ) . While most males ( 71% ) with P . malariae/P . knowlesi were between the ages of 15 and 50 years , with 13% of cases occurring in children <15 years and 17% occurring in adults >50 years , only half ( 50% ) of female cases were aged 15–50 years , with 28% occurring in children <15 years old and 24% occurring in adults >50 years . Among adults ( ≥15 years ) with P . malariae/P . knowlesi , females were significantly older than males ( median age 43 years vs . 33 years , p<0 . 0001 ) . Among patients with P . vivax and P . falciparum the overall median age was lower among females than it was among males ( median age 20 and 24 years for females and males respectively with P . vivax , p<0 . 0001; and 17 . 5 and 24 years for females and males respectively with P . falciparum , p<0 . 0001 ) . As with P . malariae/P . knowlesi however , adult females with P . vivax were older than adult males ( median ages 30 and 27 years respectively , p = 0 . 002 ) . The median age of all malaria patients increased progressively from a median of 24 years in 2007 to 27 years in 2011 ( Spearman's correlation coefficient 0 . 04 , p<0 . 0001 ) . The proportion of patients >50 years old also increased , from 244/3191 ( 7 . 7% ) in 2007 , to 364/4135 ( 8 . 8% ) , 345/4009 ( 8 . 6% ) , 244/2644 ( 9 . 2% ) and 263/2032 ( 12 . 9% ) in the years 2008 , 2009 , 2010 and 2011 respectively ( p<0 . 0001 ) . Among patients >50 years old , P . malariae/P . knowlesi cases as a proportion of all malaria notifications increased from 43/244 ( 17 . 6% ) in 2007 to 131/263 ( 49 . 8% ) in 2011 ( p<0 . 0001 ) . A greater proportion of patients with P . malariae/P . knowlesi were male ( 77% compared to 73% of patients with P . vivax and P . falciparum , p = 0 . 0007 ) , and this proportion increased among those aged 15–60 years , of whom 82% were male , compared to 63% outside this age range ( p<0 . 0001 ) . From 2007–2011 significant seasonality was demonstrated for all Plasmodium species , with maximum notifications occurring in July , April and June for P . falciparum ( p = 0 . 0001 ) , P . vivax ( p = 0 . 002 ) and P . malariae/P . knowlesi ( p = 0 . 0001 ) respectively ( Figure 6 ) .
Although P . knowlesi is now well documented in Sabah , the emergence of this species over time has not been previously described . In this study , we found that while cases of P . knowlesi ( reported as “P . malariae” ) may have been prevalent at low levels for decades , a significant increase in notifications has occurred over the past decade . This increase follows a dramatic reduction in notification rates of P . vivax and P . falciparum . In fact over the past decade , a strong inverse correlation has occurred between notification rates of “P . malariae/P . knowlesi” and P . falciparum . Available evidence does not allow us to determine what proportion of “P . malariae/P . knowlesi” notifications during the last two decades is actually P . knowlesi , with PCR testing only instituted at the Sabah State Reference Laboratory in 2005 [15] , and no PCR results available from Sabah blood samples prior to 2003 [4] . In the 1990s when prevalence of P . falciparum and P . vivax was high , it is possible that a significant number of P . malariae cases also occurred . However recent studies demonstrate that , at least since 2007 , PCR-confirmed P . malariae in Sabah is rare . Although eight cases of P . malariae were detected by PCR from 49 “P . malariae” blood films taken from Sabah during 2003–2005 ( with six of these from Kudat ) [4] , four subsequent studies identified only eight ( 0 . 6% ) PCR-confirmed P . malariae infections among 1286 patients with PCR-confirmed Plasmodium infection in Sabah from 2007 to 2011 [6] , [7] , [15] , [25] . In one of these studies only four ( 0 . 8% ) P . malariae infections were identified from 475 patients with PCR-confirmed Plasmodium infections in Kudat from 2009–2011 , including 365 with microscopy-diagnosed “P . malariae” [25] . In another , P . malariae was detected by nested PCR in only two of 318 ( 0 . 6% ) microscopy-diagnosed P . malariae cases referred to the Sabah State Public Health Laboratory in 2009 [15] . Furthermore , the age and sex distributions of “P . malariae/P . knowlesi” notifications since 2007 in the current study are very similar to those described in a previous study in Kudat , in which 345 patients with PCR-confirmed P . knowlesi were analysed [25] . Given the unique age distribution of P . knowlesi , this strongly suggests that a large majority of “P . malariae/P . knowlesi” notifications , at least since 2007 , are indeed P . knowlesi cases . The reason for the older age group affected by P . knowlesi in this and previous studies [5] , [7] , [25] remains unclear , however may relate to greater forest exposure among older individuals , with farmers and plantation workers over-represented in this age group [7] . The bimodal age distribution of females affected by P . knowlesi requires further investigation , but may possibly relate to lower forest exposure among young adult females; this may also account for the finding in this and other studies [7] , [25] that , among adults with knowlesi malaria , females are older than males . Concurrent zoonotic and human-human transmission may also explain a bimodal age distribution . There are several possible explanations for the emergence of P . knowlesi . Firstly , increased recognition of the species may account for increased reporting by microscopists . Although this possibility cannot be excluded , the previous high prevalence rates of malaria in Sabah ensured that microscopy skill levels were maintained at high levels . It seems unlikely therefore that large numbers of “P . malariae” slides would have been misdiagnosed as P . vivax or P . falciparum . In fact , in a study involving blood films obtained from 243 patients with PCR-confirmed P . knowlesi in Sarawak between 2001–2006 , only 4 . 5% and 6 . 6% were misdiagnosed by microscopy as P . falciparum and P . vivax respectively [4] , and it is likely that a majority of these blood films would have been reported prior to the increased awareness of P . knowlesi . The consistency of notification trends across districts further supports the overall reliability of the microscopy reports and the State Department records . Furthermore , the number and proportion of all malaria patients aged >50 years increased significantly between 2007 and 2011 . Given that this age group is over-represented among patients with knowlesi malaria [7] , [25] , this finding is consistent with a true increase in the proportion of P . knowlesi cases and cannot be attributed to increased recognition . We believe , therefore , that the prevalence of P . knowlesi in Sabah has increased , and that this has occurred as a result of environmental change together with reducing rates of the other human malaria species . The extensive deforestation that has occurred in Sabah has led to encroachment of humans into previously forested areas , resulting in increased interaction with mosquito vectors and simian hosts . Furthermore , the removal of habitat together with malaria control activities may have led to a change in vector behaviour , or a vector shift , as has been seen in the Kinabatangan region where the previously dominant malaria vector An . balabacensis appears to have been displaced by An . donaldi [22] . Both these factors may increase the chance of human acquisition of P . knowlesi , although further research regarding P . knowlesi vectors in Sabah is needed . Finally , the finding in this study that the prevalence of P . knowlesi appears to have increased very recently , long after Sabah's most extensive period of deforestation during the 1970s and early 1980s [17] , suggests that decreasing rates of P . vivax and P . falciparum are likely to have contributed directly to this trend . Possible explanations for this may be derived from examining the relationship between P . falciparum and P . vivax , as in other regions prevalence of P . vivax has increased as rates of P . falciparum decrease [26] , [27] . In addition , studies of P . vivax and P . falciparum have demonstrated lower than expected rates of mixed infections [28] and the occurrence of reciprocal seasonality between the two species [29] . These observations suggest an inhibitory interaction between P . falciparum and P . vivax , a phenomenon also demonstrated in early syphilis studies in which P . falciparum was found to suppress P . vivax parasitemia when both species were inoculated simultaneously [30] , [31] . More recently , Bruce et al . reported that asymptomatic children living in a highly endemic area demonstrated relatively stable total parasite density counts despite changes in the density of individual species , suggesting density-dependent regulation that transcends species [28] . Similar interactions between P . knowlesi and either P . falciparum or P . vivax may explain the malaria trends in Sabah , with density-dependent regulation possibly accounting for previously low rates of symptomatic P . knowlesi . The occurrence of density-dependent regulation may also explain the lack of earlier reports of severe “P . malariae” , similar to reports from other regions that cases of severe vivax malaria increased as the prevalence of P . falciparum reduced [27] . In addition , it is possible that cross-species immunity may play a role in the malaria prevalence patterns observed in Sabah . Although heterologous immunity does not generally occur between human malaria species , it has been argued that a degree of cross-resistance may be more likely to occur between species infecting different hosts [32] . In a study involving sera from Gambian adults highly immune to P . falciparum , antibodies were found to bind to the surface of P . knowlesi merozoites , although erythrocyte invasion was not prevented [33] . In addition , data from neurosyphilis malariotherapy series demonstrated that patients who had been previously infected with P . vivax were less susceptible to infection with P . knowlesi [34] . Loss of cross-protection provided by immunity to P . falciparum or P . vivax may be particularly relevant given that P . knowlesi tends to effect older individuals; frequent exposure to P . falciparum and P . vivax may previously have protected this age group from infection with P . knowlesi . The finding that notification rates of P . knowlesi have increased following decreasing prevalence of the other malaria species has implications for malaria control in any country where P . knowlesi is known to occur , which includes nearly every country in Southeast Asia [35] . In Sabah , P . knowlesi is now the most common cause of malaria , and based on current trends , is likely to become increasingly dominant and may extend to previously unaffected districts . Furthermore , human-to-human transmission , if not already occurring , may become more likely as prevalence continues to increase . Close monitoring of P . knowlesi in Sabah and elsewhere is therefore essential , including accurate reporting of microscopy-diagnosed “P . malariae” as P . knowlesi , as has been previously recommended [4] , [36] , in addition to PCR-confirmation of suspected cases . Moreover , further research is required to determine the risk factors for knowlesi malaria , in order that malaria control programs can include strategies to address the increasing prevalence of this species . Although Malaysia has been highly successful in reducing rates of P . falciparum and P . vivax , malaria elimination will not be achieved unless control of knowlesi malaria is addressed .
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The simian parasite Plasmodium knowlesi is a common cause of malaria in Malaysian Borneo; however , little is known about its emergence over time , particularly in Sabah . We reviewed all available Sabah Department of health malaria notification records from 1992–2011 , and considered notifications of P . malariae and P . knowlesi as a single group due to their microscopic similarity . We found that malaria notifications in Sabah have decreased dramatically , with P . falciparum and P . vivax notifications peaking at 33 , 153 and 15 , 877 respectively during 1994–1995 , and falling to 605 and 628 respectively in 2011 . Notifications of P . malariae/P . knowlesi fell from a peak of 614 in 1994 to ≈100/year in the late 1990s/early 2000s , however increased >10-fold between 2004 ( n = 59 ) and 2011 ( n = 703 ) . In 1992 P . falciparum , P . vivax and P . malariae/P . knowlesi monoinfections accounted for 70% , 24% and 1% respectively of malaria notifications , compared to 30% , 31% and 35% in 2011 . The increase in P . malariae/P . knowlesi notifications occurred state-wide , appearing to have begun in the southwest and progressed north-easterly . This significant recent increase in P . knowlesi notifications following reduced transmission of the human Plasmodium species threatens malaria elimination; further research is required to determine transmission dynamics and risk factors for knowlesi malaria .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"tropical",
"diseases",
"(non-neglected)",
"malaria",
"parasitic",
"diseases"
] |
2013
|
Increasing Incidence of Plasmodium knowlesi Malaria following Control of P. falciparum and P. vivax Malaria in Sabah, Malaysia
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Limited data is available on the current status of scrub typhus infection in the aboriginal population in Malaysia . This study was aimed to provide recent data on the degree of exposure of 280 individuals from seven aboriginal subgroups to Orientia tsutsugamushi ( causative agent of scrub typhus ) in West Malaysia . The environment , socioeconomic and behavioural risk factors associated with the disease were also investigated . The antibody prevalence to O . tsutsugamushi ranged from 0 to 36 . 4% in seven subgroups , with high prevalence rates noted in subgroups involved in agricultural activity and the lowest prevalence rates noted in subgroups whose main occupations were associated to fishing . Univariate analysis indicated populations with age above 18 years ( OR = 1 . 15 , 95% CI = 1 . 02–1 . 30 , P = 0 . 015 ) , working ( OR = 1 . 99 , 95% CI = 1 . 01–3 . 92 , P = 0 . 044 ) , working at agriculture area ( OR = 1 . 18 , 95% CI = 0 . 98–1 . 42 , P = 0 . 031 ) , receiving household income less than US$ 166 . 7 ( RM500 ) per month ( OR = 2 . 43 , 95% CI = 1 . 16–5 . 11 , P = 0 . 016 ) and having close contact with animal pets ( OR = 4 . 06 , 95% CI = 1 . 20–13 . 76 , P = 0 . 016 ) are significantly associated with exposure to O . tsutsugamushi . Multivariate analysis confirms that participants who are above 18 years old , receiving household income less than US$ 166 . 7 ( RM500 ) per month and having close contact with animal pets are 3 . 6 times ( 95% CI = 1 . 81–7 . 03 , P<0 . 001 ) , 1 . 3 times ( 95% CI = 1 . 14–1 . 64 , P = 0 . 002 ) and 1 . 2 times ( 95% CI = 1 . 05–1 . 06 , P = 0 . 006 ) more likely to have exposure to O . tsutsugamushi , respectively . The present study indicates that scrub typhus is still an important disease in the aboriginal population in Malaysia . Awareness about the disease and education on the preventive measures are important in reducing the risk of acquiring scrub typhus in the population studied .
Scrub typhus is an acute febrile disease caused by Orientia tsutsugamushi , a Gram-negative obligate intracellular bacterium which is transmitted through the bites of infected Leptotrombidium mites . The disease is distributed throughout the Asia Pacific regions including Malaysia [1]–[3] . Also known as tsutsugamushi disease , the disease is characterized by focal or disseminated vasculitis and perivasculitis , which may involve the lungs , heart , liver , spleen , and central nervous system and cause serious complications including pneumonia , myocarditis , meningoencephalitis , acute renal failure , and gastrointestinal bleeding [3]–[5] . The disease has been reported as the most frequent infection among febrile hospitalized patients in rural areas of Malaysia since early 1970s [6]–[8] , with antibody prevalence to O . tsutsugamushi varied widely from as low as 0 . 8% in East Malaysia [9] to as high as 73% in West Malaysia [6] . A recent serosurvey of febrile patients in rural areas of Malaysia showed a prevalence of 24 . 9% to O . tsutsugamushi [2] . According to Khor and Zalilah [10] , the aborigines or orang Asli ( translated as “original peoples” ) are the indigenous inhabitants of West Malaysia , who constitute a minority group comprises only 0 . 6% of the total population of Malaysia . A total of 132 , 486 individuals have been recorded in a recent census [11] . They are officially classified into three main ethno-linguistic groups namely , the Senoi , Proto Malays or Aboriginal Malays and the Negritos , each consisting of six dialectic subgroups . The common occupations of the people are agricultural , fishery , hunting and collecting forest produce . Certain aboriginal subgroups such as Orang Laut , Orang Seletar and Mah Meri live close to the coast and are mainly fishermen . The Temuan , Jakun and Semai people are involved in agricultural activities for instance , in rubber , oil palm or cocoa plantations . The Temiar and Semelai live within forested areas and are engaged in rice cultivation , hunting and gathering . A minority of aboriginal population live in urban areas and are engaged in both waged and salaried jobs [12] . The aboriginal population has been identified as one of the most impoverished groups in the Malaysia , based on reports of various five-year Malaysia development plans [10] . Due to the life style and involvement in agricultural activities , high prevalence of scrub typhus has been reported from aboriginal populations in different geographical regions in Malaysia . Cadigan et al . [6] reported a prevalence of 73% in adult aborigines from “deep jungle” , 48% from “fringe areas” , and 8% from kampong ( traditional villages ) . The incidence of scrub typhus infection varied from 3 . 2 to 3 . 9% per month in two aboriginal settlements in West Malaysia [13] . Molecular evidence of scrub typhus infections in the patients attending Hospital Gombak , a healthcare facility dedicated specifically for aboriginal population has also been reported [14] . However , little data is available on the assessment of the environment , socioeconomic and behavioural risk factors of the disease in different aboriginal subgroups in Malaysia . This study was conducted to provide recent data on antibody prevalence and factors associated with exposure to O . tsutsugamushi infection in different aboriginal subgroups in West Malaysia . The information collected will be important for the improvement on management , prevention and control of scrub typhus in the aboriginal populations in Malaysia .
An ethical approval was obtained ( i . e . , MEC Ref . No . 824 . 11 ) from the Ethics Committee of the University Malaya Medical Centre ( UMMC ) , Malaysia before the commencement of the study . The consent procedures regarding incompetent adults and the oral consent procedures had been approved by the ethical committee . An oral briefing on the objective and methodology of the study was given to the participants . Once they have voluntarily agreed to participate , their consents were taken either in written form ( signed ) or verbally followed by thumb prints ( for those who were illiterate ) of participants . Parents or guardians gave consent on behalf of all children . For incompetent adults , the questionnaires were completed by the head of the family who signed the informed consent on their behalf . All medical data was anonymized . This study was a part of a large study to determine the occurrence and distribution of tropical infectious diseases among the aborigine populations . As there is no prior information about social and behavioural factors affecting scrub typhus for the aborigines , randomly selected serum samples from 280 individuals ( representing approximately one third of the surveyed population ) who participated in a serosurvey for prevalence and risk factors of intestinal parasitism in rural and remote West Malaysia from November 2007 to October 2010 were used in this study . At least 30 samples were selected from each study site , except for one study site ( Sungai Bumbun ) where only 14 samples were available for testing . Details of the consent , sample collection , sampling scheme and population prior to this study have been described previously [15] . The participants originated from 7 subgroups living in various states in West Malaysia , i . e . , Temuan ( Gurney; 101 . 44°E , 3 . 43°N ) , Semai Perak ( Sungai Perah; 100 . 92°E , 4 . 48°N ) , Semai Pahang ( Pos Betau; 101 . 78°E , 4 . 10°N ) , Semelai ( Pos Iskandar; 102 . 65°E , 3 . 06°N ) Temiar ( Kuala Betis; 101 . 79°E , 4 . 90°N ) , Mah Meri ( Sungai Bumbun; 101 . 42°E , 2 . 85°N ) and Orang Kuala ( Sungai Layau; 101 . 42°E , 2 . 85°N ) ( Figure 1 ) . Of the seven subgroups selected in this study , five subgroups ( i . e . , Semelai , Semai Pahang , Temiar , Temuan and Semai Perak ) are actively engaged in the agricultural activities whereas the remaining two ( i . e . , Orang Kuala and Mah Meri ) live close to the coast and are involved in the fishing activities . To determine the associated risk factors for scrub typhus infection , basic demographic data such as age , gender and education , socioeconomic status ( i . e . , occupation and household income ) and behavioural aspects ( i . e . , personal hygiene such as wearing shoes , taking bath , and changing cloth and food consumption ) of the participants were gathered from a questionnaire survey . The sera were analysed for IgG antibody against O . tsutsugamushi using a commercial assay ( Scrub Typhus Detect IgG ELISA System , INBIOS International , Inc . USA ) as in accordance to the manufacturer's instructions . The recombinant protein antigen ( 56-kda major outer membrane protein of the Karp strain of O . tsutsugamushi ) used in the assay , has been reported to exhibit sensitivities and specificities similar to those of rickettsia-derived antigens in the indirect immunoperoxidase test , when evaluated using sera of individuals from Thailand , a neighbouring country at the northern part of Malaysia [16] . We believed that the assay is relevant and appropriate for screening of Malaysian population due to the many common factors shared by the two Southeast Asian countries , such as tropical climate and environment , types of chigger vectors and antigenic group of O . tsutsugamushi . Eight different serotypes of O . tsutsugamushi including the Karp strain have been identified in mites in Malaysia [17] . The distribution of Karp-related strains has also been found throughout various geographic regions in Southeast Asia [18] . Briefly , test serum and control were diluted 1∶ 100 using sample dilution buffer . The diluted serum samples were then transferred to the microtiter plate provided in the kit and incubated at 37°C for 30 min in a humidified incubator . The microtiter wells were washed six times and incubated for an additional 30 min at 37°C following the addition of secondary antibody ( anti-human IgG conjugated with horseperoxidase ) . After incubation , the wells were washed six times before the addition of Enwash ( a reagent provided by the manufacturer ) followed by incubation at room temperature for 5 minutes . TMB substrate was then added to the microtiter wells and incubated for 10 min at room temperature in the dark . The reaction was stopped by adding Stop solution and the plate was read at 450 nm with a reference filter of 620 nm . For determination of the cut-off value , the OD readings from the sera of 20 Malaysian blood donors ( representing normal human serum ) were obtained , averaged and added with three times of the standard deviation , as recommended by the manufacturer . A reading less than the cut-off value indicates a negative sample while a reading of more or equal to cut-off value is considered a positive sample . Statistical analysis was carried out using the SPSS ( Statistical Package for the Social Sciences ) software programme for Windows , version 17 ( SPSS Inc . , Chicago , IL ) . Before each analysis , initial data entry was cross-checked regularly ( by HAMZ and RN ) in order to be sure that data was entered correctly and consistently . The data with quantitative variables was expressed as means ( ± SD ) and ranges , whereas , qualitative variables were estimated and presented as frequencies and percentages . A Pearson's Chi-square ( χ2 ) test on proportion was used to test associations between variables . A univariate statistical model was used to assess potential associations between individuals with positive scrub typhus serological findings and the potential risk factors . In order to make sure that the potentially important predictors are not excluded and also due to a low number of predictor variables , all variables with or without lower significance level between 0 . 10 to 0 . 25 were included in the multivariate analysis using both backward and forward stepwise selection to produce the subset for final model , sequentially to determine significant differences in demographics and confounding risk factors among studied participants . The level of statistical significance was set up at p<0 . 05 and for each statistically significant factor , an odds ratio ( OR ) and 95% confidence interval ( CI ) were used for both univariate and multivariate logistic regression analysis to explore the strength of the association between scrub typhus seropositivity and the variable of interest .
Table 1 shows the demographic and baseline characteristics of the 280 individuals surveyed in this study . The age of the participants ranged from 3 to 82 years ( mean age = 22 . 6±16 . 3 years old ) . Majority of the participants were female ( n = 168 , 60 . 0% ) . The participants were divided into three age groups: those below 12 ( 15 . 7% ) , 12–17 ( 43 . 6% ) and above 18 years old ( 40 . 7% ) . Of those below 18 years old , majority of them were students ( n = 142 , 50 . 7% ) . Of those above 18 years old , a minority of them ( 3 . 6% ) were employed as labourers in factory while the remaining were rubber tappers ( 8 . 2% ) and farmer/jungle produce gatherers ( 9 . 3% ) . A total of 28 . 2% of the participants were unemployed . On the socioeconomic surveys , more than half of the populations received a household income of less than US$ 166 . 7 ( RM 500 ) per month ( n = 183 , 65 . 4% ) . At least half of the population received formal education ( 6-year of primary education ) while 42 . 9% did not have any formal education . Upon investigation of their personal habits , a majority of them responded positively on wearing shoes for outdoor activity ( 68 . 6% ) , taking bath and changing clothes at least once a day ( 83 . 2% ) and keeping animal pets at home ( 84 . 3% ) ( Table 1 ) . Antibody against O . tsutsugamushi was detected in 50 ( 17 . 9% ) participants investigated in this study ( Table 2 ) . The antibody prevalence to O . tsutsugamushi ranged from 0 to 36 . 4% in seven subgroups , with the highest prevalence being observed for the Semai Pahang subgroup ( 36 . 4%; 95% CI = 1 . 9–6 . 7% ) . This was then followed by the Semelai ( 31 . 7%; 95% CI = 17 . 9% ) , Temuan ( 21 . 1%; 95% CI = 0 . 9–5 . 2% ) , Semai Perak ( 15 . 2%; 95% CI = 0 . 3–3 . 2% ) , Temiar ( 15 . 1%; 95% CI = 1 . 4–6 . 2% ) , and Orang Kuala subgroups ( 2 . 1%; 95% CI = −0 . 3–1 . 1 ) . None of the participants from Mah Meri subgroup was positive ( 0%; 95% CI = 0 ) . Of the age groups analysed in this study , the highest seropositivity was seen among those participants ≥18 years ( 24 . 6% ) , followed by 12–17 years ( 15 . 6% ) and below 12 years old ( 6 . 8% ) ( Table 2 ) . Females ( 20 . 8% ) had higher seropositivity rate against O . tsutsugamushi as compared with males ( 13 . 4% ) . However , there was no significant difference or association between antibody prevalence and gender ( P>0 . 05 ) ( Table 3 ) . Univariate analysis indicated that populations with age above 18 years ( OR = 1 . 15 , 95% CI = 1 . 02–1 . 30 , P = 0 . 015 ) , working ( OR = 1 . 99 , 95% CI = 1 . 01–3 . 92 , P = 0 . 044 ) , working at agriculture area ( OR = 1 . 18 , 95% CI = 0 . 98–1 . 42 , P = 0 . 031 ) , receiving household income less than USD 166 . 7 ( RM500 ) per month ( OR = 2 . 43 , 95% CI = 1 . 16–5 . 11 , P = 0 . 016 ) and having close contact with animal pets ( OR = 4 . 06 , 95% CI = 1 . 20–13 . 76 , P = 0 . 016 ) , are significantly associated with exposure to O . tsutsugamushi . Multivariate analysis confirmed that participants who are above 18 years old , receiving household income less than USD 166 . 7 ( RM500 ) per month and having close contact with animal pets were 3 . 6 times ( 95% CI = 1 . 81–7 . 03 , P<0 . 001 ) , 1 . 3 times ( 95% CI = 1 . 14–1 . 64 , P = 0 . 002 ) and 1 . 2 times ( 95% CI = 1 . 05–1 . 06 , P = 0 . 006 ) , are more likely to have exposure to O . tsutsugamushi ( Table 3 ) .
Clinical presentation and the history of a patient are important to aid diagnosis of scrub typhus . However , the disease can be difficult to be differentiated from leptospirosis , murine typhus , malaria , dengue and other tropical diseases due to the similarity in their clinical features . The observation of eschar supports the diagnosis of scrub typhus , however; it is not usually present [19] . The mainstay in the diagnosis of scrub-typhus is by serology . However , this approach is usually hampered by the lack of serological assays due to the difficulty in preparing native antigens for O . tsutsugamushi . As a result , misdiagnoses and delayed treatment of scrub typhus have been frequently reported in the rural areas; the lack of appropriate laboratory assays has also caused the underestimation of scrub typhus in many parts of the world [1] . This study provides the most recent serologic data for O . tsutsugamushi infection in different subgroups of aboriginal population in West Malaysia . The antibody prevalence to O . tsutsugamushi varied according to localities . The overall antibody prevalence to O . tsutsugamushi ( 17 . 9% ) in this study was higher than those reported previously for aboriginal settlements in West Malaysia [13] and the indigenous communities in East Malaysia [20] . This study also confirmed the findings of Audy [21] that the epidemiology of scrub typhus is closely related to human occupation and behaviour . Although scrub typhus has been reported from different geographical zones such as seashores , mountainous regions , rainforests , river banks and terrain undergoing secondary vegetation growth , most cases occur through agricultural exposure [22] . Our findings are thus consistent with these earlier observations as higher prevalence rates to O . tsutsugamushi are seen with five aboriginal subgroups ( i . e . , Semelai , Semai Pahang , Temiar , Temuan and Semai Perak subgroups ) whose main occupations are associated with agricultural activities , whereas only minimal and zero prevalence was noted in two subgroups ( i . e . , Orang Kuala and Mah Meri subgroups ) whose main occupations were fishing . Shifting cultivation , which is a normal practice of some aboriginal subgroups , may contribute towards the creation of conducive ecological condition for the transmission of scrub typhus . New cultivated land attracts rodents and animals which carry O . tsutsugamushi-infected mites and thus , forms an intensive transmission focus ( also called as “mite-island” ) . When the land is no longer fertile after a period of time , the cultivation is shifted to another piece of land . The outcome of this process is the expansion of the transmission focus for scrub typhus with the simultaneous shifting of infected mites and animal reservoirs to the new cultivated lands . The infectivity of the mite population can be maintained over long periods of time as the infection of adult mites can be passed to their eggs ( transovarial transmission ) and from the egg to the larva or adult ( transstadial transmission ) [23] , [24] . In this study , multivariate analysis confirmed that participants who were above 18 years old were significantly associated with exposure to O . tsutsugamushi ( Table 3 ) . The observation of a higher exposure rate in older age group was also noted among febrile patients in rural areas in Malaysia [3] . This phenomenon can be attributed to the increased contact of the participants with an intensive transmission focus or “mite island” , where O . tsutsugamushi is found persistently in Leptotrombidium mites and animal reservoirs in a specific area . Repeated inoculation of the aboriginal population with O . tsutsugamushi in the mite-island may result in long-term persistence of antibody and inapparent , chronic scrub typhus infection [25] . Two Malaysian serosurveys documented comparable or higher prevalence of antibody against O . tsutsugamushi in the male participants [3] , [26] . Males were generally more active in the outdoor activities like farming , hunting or hiking than the females , and hence , having higher exposure rates to infected mites . However , it was interesting to note that females in this study had higher antibody prevalence to O . tsutsugamushi as compared to males ( 20 . 8% vs 13 . 4% ) . An earlier study by Strickman et al . [27] reported similar observation as they found rural women performing agricultural tasks experienced higher levels of exposure than men . However , no significant difference or association between antibody prevalence to O . tsutsugamushi and gender ( P>0 . 05 ) was noted in this study ( Table 3 ) . The endemicity of scrub typhus in the Asia Pacific region has been correlated with people in rural areas who are exposed to environmental factors such as bushes , piles of wood , domestic animals and rodents [28] . In this study , majority of the participants receiving household income less than USD 166 . 7 ( RM500 ) per month were significantly associated with exposure to O . tsustsugamushi ( Table 3 ) . The poverty , lack of awareness and proper protective measures for scrub typhus disease could have contributed to the high exposure of the aboriginal communities to O . tsustsugamushi-infected mites . Institution of good personal hygiene may reduce risk of acquiring scrub typhus infection . As mites require 36–72 hours to attach to the skin of the host , hence , thorough scrubbing and washing of the body after exposure may decrease the risk of mite bites and , thus , the risk of scrub typhus [29] . Sharma et al . [28] reported that it is less likely to acquire scrub typhus when one bath after work and change clothes to sleep . However we did not observe significant difference in the antibody prevalence to O . tsutsugamushi for individuals who took bath and changed clothes at least once a day ( Table 3 ) . Similarly , the practice of wearing shoes for outdoor activity ( as responded positively by 192 participants in this study ) did not have significant effect on the exposure to O . tsutsugamushi in this study . Instead , wearing gumboots has been associated with a lower risk of acquiring scrub typhus in a recent survey in India [28] . The multivariate analysis in this study confirms that participants keeping animal pets are significantly associated with exposure to O . tsutsugamushi ( Table 3 ) . Peridomestic animals such as dogs and cats can serve as transport hosts as they harbour infected mites and may lead to exposure of aboriginal population to scrub typhus [30] , [31] . In addition , the leftover food for domestic animals attracts rodents and households frequented by rodents could be more affected by scrub typhus [32] , [33] , whereas clean living-environment and control of rodents decreased the incidence of scrub typhus significantly among troops in China [34] . In conclusion , this study presents evidence that scrub typhus remains an important disease amongst various aboriginal subgroups and confirms that previous findings still apply after many years , highlighting neglected issues related to scrub typhus , a treatable and preventable disease . The environment , socioeconomic , and behavioural risk factors which have a significant relationship to the risk of exposure to scrub typhus have been identified . As it was not feasible to study the entire population of aboriginal population , a sample of the population consisting of 280 individuals from 7 aboriginal subgroups was included in this study . The small numbers of participants is considered one of the limitations of the study as the resulting random sampling error might give some implications on the statistical analysis and conclusion drawn [35] . To minimize such error , continued surveillance for scrub typhus in the aboriginal community is necessary and recommended . The data obtained would be beneficial to the health authority in designing better prevention and control strategies for scrub typhus in the aboriginal population in West Malaysia . Awareness about the disease and education on the preventive measures such as clearing of bushes , use of protective clothing , keeping animals away and controlling rodents are important to reduce the risk of acquiring scrub typhus in the population studied .
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Scrub typhus has been recognized as a public health problem in the rural areas of Southeast Asia . The aboriginal population , one of the most impoverished groups in the Malaysia , may be exposed to the bite of Leptotrombidium mites ( vector for scrub typhus ) due to their involvement in the agricultural activities , living environment and personal habits . A serosurvey was conducted for seven aboriginal subgroups to determine antibody prevalence to O . tsutsugamushi , the causative agent of scrub typhus and to identify factors associated with scrub typhus . The findings in this study confirmed high antibody prevalence to O . tsutsugamushi in aboriginal subgroups who engaged in agricultural activity . Multivariate analysis showed that individuals who are above 18 years old , receiving household income less than US$ 166 . 7 ( RM500 ) per month and having close contact with animal pets have higher exposure rates to scrub typhus . Institution of appropriate preventive measures is important in reducing the risk of acquiring scrub typhus in the population studied .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"veterinary",
"science",
"biology"
] |
2013
|
Antibody Prevalence and Factors Associated with Exposure to Orientia tsutsugamushi in Different Aboriginal Subgroups in West Malaysia
|
Expression levels of human genes vary extensively among individuals . This variation facilitates analyses of expression levels as quantitative phenotypes in genetic studies where the entire genome can be scanned for regulators without prior knowledge of the regulatory mechanisms , thus enabling the identification of unknown regulatory relationships . Here , we carried out such genetic analyses with a large sample size and identified cis- and trans-acting polymorphic regulators for about 1 , 000 human genes . We validated the cis-acting regulators by demonstrating differential allelic expression with sequencing of transcriptomes ( RNA-Seq ) and the trans-regulators by gene knockdown , metabolic assays , and chromosome conformation capture analysis . The majority of the regulators act in trans to the target ( regulated ) genes . Most of these trans-regulators were not known to play a role in gene expression regulation . The identification of these regulators enabled the characterization of polymorphic regulation of human gene expression at a resolution that was unattainable in the past .
Expression levels of genes , like many phenotypes , vary among normal individuals . Since gene expression underlies cellular characteristics and functions , variation in gene expression contributes to phenotypic diversity and differences in disease susceptibility . Previously , we and others demonstrated that there is a genetic basis to individual variation in gene expression [1]–[6] . This facilitates studies to identify sequence variants that influence expression levels of genes . Since expression phenotypes of many genes are studied in parallel , results from genetics of gene expression ( GOGE ) studies contribute to the understanding of global gene regulation . GOGE studies that treated expression levels as quantitative traits in family-based linkage [3] , [7] and population-based association analyses [5] , [8] , [9] have uncovered polymorphic regulatory regions that contribute to variation in human gene expression . However , the regulatory regions were large , often megabases in size; thus , the identity of most polymorphic regulators remained unknown . In this GOGE study , we analyzed a large sample in linkage analyses , then we used deep sequencing of transcriptomes ( RNA-Seq ) to guide association-based fine mapping . The results allowed us to narrow the regulatory regions and identify cis- and trans-acting polymorphic regulators of ∼1 , 000 human genes . These results facilitated molecular validation and analyses of the mapping data . This is an important advance in human genetic studies where such validations have largely been impossible . In previous human GOGE studies , the resolution of the mapping results was inadequate; hence , regulators were not identified , while other gene mapping studies focused on complex phenotypes , such as human diseases that are often not amenable to molecular analyses . Thus , the end points of many human genetic studies showed genotype-phenotype connections statistically but not molecularly . Here , we have an unusual opportunity to begin to bridge the gap between genetic and mechanistic studies . Knowing the identity of the regulators , we were able to validate the cis- and the trans-regulatory relationships using different approaches . For genes that are cis-regulated , we used RNA-Seq to show differential allelic expression . For the trans-regulatory relationships , we altered the expression of the regulators by gene knockdowns and metabolic perturbations and showed that manipulations of the regulators affected the expression levels of the corresponding target genes . We also demonstrated direct interactions between regulators and their target genes by chromosome conformation capture . Another goal of this study is to examine the role of cis- and trans-acting polymorphisms on human gene expression . Previously , GOGE studies in model organisms and humans appear to disagree on the proportion of polymorphic cis- and trans-acting regulators . In yeast , fly , and mouse studies , most of the regulators act in trans [2] , [10]–[12] . In contrast , human studies focused mostly on cis-acting variants . This apparent discrepancy is likely due to differences in sample sizes . Studies in model organisms used larger sample sizes and thus were able to find trans-acting regulators that have smaller effects on gene expression than cis-regulators [13] , [14] . In contrast , early human studies of GOGE used relatively small sample sizes , such as samples collected by the International HapMap Consortium [5] , [8]; hence they identified mostly cis-regulators . This and the discovery of cis-regulation of disease susceptibility genes such as ORMDL3 ( asthma ) [15] led to suggestions that cis-acting variants are significant contributors to variation in human gene expression . However , it is unlikely that the regulatory landscapes are different between humans and other organisms . In humans , trans-acting regulators possibly also play an important role . Several studies [3] , [4] , [9] have suggestive evidence for the important contribution of trans-acting variants . Recently , studies that used RNA-Seq to analyze gene expression phenotypes in HapMap samples found cis-acting variants for less than 10% of human genes [16] , [17] . These studies suggest that along with cis-variants , trans-acting polymorphisms contribute to individual variation in human gene expression . Here , to address this , we used a large sample size and identified hundreds of polymorphic trans-regulators . These findings confirm that as in other organisms , there are many sequence variants in the human genome that act in trans to influence gene expression . Many of the identified trans-regulators were previously not known to play a role in gene regulation . Over 60% of the regulators are not transcription factors or known signaling factors . However , the trans-regulators are not randomly distributed; instead they tend to be found in the same functional pathways as their target genes . While the regulators were discovered in analysis of immortalized B-cells , we showed that the regulatory relationships were also found in primary fibroblasts . Thus , natural variation in gene expression allowed the identification of polymorphic expression regulators , which then enabled us to develop a deeper understanding of gene regulation .
We obtained genotypes of single nucleotide polymorphisms ( SNPs ) and measured the expression levels of genes in immortalized B-cells from members of 45 Centre d'Etude du Polymorphisme Humain ( CEPH ) Utah pedigrees [18] using microarrays . We focused our analysis on 4 , 793 expressed genes that show variation in expression levels among individuals and carried out genome-wide linkage analysis ( see Methods ) . From those analyses , we selected 1 , 681 ( 35% ) phenotypes for further studies using a threshold of t>4 ( a logarithm of odds ( lod ) score of ∼3 . 4 , and a genome-wide corrected significance level of approximately 0 . 05 [19] ) ( see Methods ) . Figure 1 shows examples of genome scan results . We expected to find polymorphic regulators of the expression phenotypes in the candidate regions identified by the linkage scans . Hence we examined the linkage peaks to determine their locations relative to the genomic addresses of the target genes . To take into account the imprecision of linkage , we define regulatory regions that are within 5 Mb of the target genes as proximal and those that are greater than 5 Mb or on another chromosome as distal to the target genes [20] . By this definition , among the 1 , 681 phenotypes with evidence of linkage at t>4 , we found that 70 ( 4 . 2% ) phenotypes have proximal regulators , 1 , 574 ( 93 . 6% ) phenotypes have distal regulators , and 37 ( 2 . 2% ) phenotypes have both proximal and distal regulators . Ninety-four percent of the distal regulators are on a different chromosome than their corresponding target genes . These results suggest that trans-acting regulation contributes appreciably to variation in gene expression . Linkage scans provided regulatory regions for over 1 , 600 expression phenotypes . To confirm these results , we carried out family-based and population-based association analyses with markers within the candidate regulatory regions . In addition to confirming the linkage findings , association mapping allows us to take advantage of historical recombinations in order to narrow the candidate regions . To check the validity of these findings , we looked for known regulatory relationships among the regulator–target gene pairs that we identified in the genetic analyses . An example of such known relationship is MRLC2 , which encodes myosin regulatory light chain 2 and its regulator myocyte enhancing factor 2A , MEF2A , a transcription factor that is known to affect muscle gene expression , including MRLC2 [27] . Our linkage results identified chromosome 15q26 ( linkage t = 4 . 9 ) as the candidate regulatory region for the expression level of MRLC2 . Using association analyses , we narrowed the candidate region and rediscovered MEF2A as the regulator of expression level of MRLC2 ( QTDT p = 0 . 008; population association p = 0 . 04 , rs325380 ) . Another example is TTC5 as the polymorphic regulator of HSP90AA1 expression . Previous studies showed that a mouse protein phosphatase that contains a tetratricopeptide repeat regulates heat shock protein 90; this regulation occurs by dephosphorylation , which is mediated by the binding of heat shock protein 90 to the tetratricorepeat domain of the phosphatase [28] , [29] . Our results showed that the expression of human HSP90AA1 is influenced by variants in TTC5 , a gene with a tetratricopeptide repeat ( linkage t = 5 . 4; QTDT p = 0 . 01 , rs11623837 ) . The “rediscovery” of these known regulatory relationships confirms that our approach can identify trans-acting regulators of human gene expression . For the 20 regulator–target gene pairs in Table 1 , we checked for co-occurrence of the names of the regulators and target genes in the literature using a text-mining program , Chilibot [30] , to determine if any of these regulatory relationships are known . We also queried PubMed for such co-occurrences . Among these 20 pairs , only one pair ( MBP and PDE4B ) has been shown to have interactive relationships in Chilibot . Thus , many of these regulator-target relationships are likely unknown previously . The resolution of our mapping study allowed us to identify the polymorphic regulators of nearly 1 , 000 human genes . Instead of just confirming these results computationally , we used molecular approaches , which provide an independent method for assessing the findings . Even though we picked regulatory relationships that had modest statistical support ( p = 10−5 to 10−2 ) from our mapping study , over 70% of the regulatory pairs are validated molecularly . Thus , we are reasonably confident that many of the 1 , 036 gene pairs have true regulatory relationships , so we went on to characterize them . First , many of the trans-regulators were not known to influence gene expression . Among the 742 regulators , 112 ( 15% ) are known transcription factors and 140 ( 19% ) play a role in signaling pathways . The remaining genes have a variety of functions including metabolism ( for example , MAN2A1 , PDHA2 ) and protein transport or modification in the endoplasmic reticulum ( for example , LMAN1 , SEC31A ) . Second , the target genes and their regulators often belong to the same functional pathways . For example , midasin ( MDN1 ) , which plays a role in protein processing [43] , regulates the expression of dynactin 1 ( DCTN1 ) and signal sequence receptor , delta ( SSR4 ) . Both of these target genes also participate in protein transport and processing in the endoplasmic reticulum [44] , [45] . To test formally whether regulators and their target genes belong to the same functional groups more often than by chance , we annotated the regulators and target genes using Gene Ontology [46] . We found significantly ( p = 0 . 008 ) more regulator–target gene pairs with the identical ontology annotation than random pairs of genes . The criterion we used is quite stringent since we required members of a gene pair to have the identical ontology grouping; it excludes regulator–target gene pairs that are in the same pathway but do not have the identical ontology . However , despite the stringent criterion , a significant result was obtained . Recent results from yeast studies also showed that regulators and their target genes share common gene ontology annotations [47] . Third , many of the trans-regulators have more than one target gene . We found 161 ( 22% ) of the 742 trans-regulators influence the expression levels of two or more genes . Table 5 shows the 11 regulators that influence six or more target genes . Three of these regulators are known to play a role in transcription regulation through chromatin modification ( AEBP2 ) or as transcription factors ( BCL2 , ZCCHC2 ) . In addition , three of the regulators ( PHLPP , RAMP1 , WDR7 ) affect gene expression through signal transduction pathways . The remaining five regulators are not known to be gene expression regulators , including TTC5 , which has no known function . The regulators with multiple target genes prompted us to examine interactions beyond the relationship between a gene and its regulator . To do so , we used our mapping results to construct directed gene networks . We connected regulators and their target genes using results from the QTDT analysis . The resulting network consists of 1 , 036 connections among 742 regulators and 917 target genes . As in many biological networks , the network connections follow a scale-free distribution ( scale-free criterion = 0 . 98 ) [48] . On average , genes have 1 . 3 connections , but some genes have more connections such as those that regulate the expressions of several target genes . Figure 4 shows subnetworks for KIAA1468 and WDR7 , which illustrate that some regulators have multiple target genes and some genes are regulated by more than one regulator . Unlike many gene networks , the nodes in our networks are connected by directed edges based on genetic data . DNA variants in the highly connected genes such as KIAA1468 and WDR7 influence the expression of many genes that are directly and indirectly connected to them . The WDR7 subnetwork shows the connections between ITPR2 and SSR1 , as well as several other genes , including SYNCRIP [49] and RHOC [50] , that play a role in the endoplasmic reticulum; thus polymorphisms in WDR7 likely affect protein processing and secretion , the primary functions of the endoplasmic reticulum . Prior to this analysis , the function of WDR7 was unknown except that it has been found to influence the age of onset of multiple sclerosis [51] in genome-wide association studies . Results from our analyses offer WDR7 as a mechanistic link between multiple sclerosis and functions of the endoplasmic reticulum . The efficiencies of the endoplasmic reticulum can influence susceptibility to multiple sclerosis in different ways . First , studies have shown that the endoplasmic reticulum plays a key role in immunity , for example in ensuring the maturation of B-cells to immunoglobulin secreting plasma cells [52] . In addition , during myelination , cells such as oligodendrocytes rely on the endoplasmic reticulum to produce a large amount of plasma membrane [53] . Thus by altering the efficiencies of endoplasmic reticulum , variants in WDR7 can influence individual susceptibility to multiple sclerosis through the autoimmune and/or myelination pathways . Besides WDR7 , other regulators in our network have also been identified as disease susceptibility genes ( see examples in Figure S2 ) .
The main focus of this study is to assess and determine the polymorphic regulation of human gene expression . We used linkage analyses to locate the polymorphic regulatory regions for 1 , 681 human genes . About 6% to 24% of these regulatory regions were close ( proximal ) to the target genes , and the remaining regions were further away ( distal ) from the target genes and mostly on other chromosomes . In follow-up association studies and sequence-based DAE analyses , at least 60% of phenotypes with proximal linkage peaks were found to be cis-regulated; this result is similar to findings in yeast [2] , [11] . The remaining phenotypes with proximal linkages are likely regulated by trans-regulators that are close to their target genes . For 917 genes with distal linkage peaks , we narrowed the regulatory regions and identified the trans-acting polymorphic regulators . For some genes , we identified more than one trans-regulator; thus , the results include a total of 1 , 036 regulator–target gene pairs . Previous genetics of human gene expressions studies uncovered only the regulatory regions; here , we improved the resolution significantly by finding the individual regulators . The results allowed us to explore previously unknown aspects of gene regulation . We found that many genes besides transcription factors can influence the expression of other genes . Similar results were found in yeast [2] , [54] . Only 34% of the polymorphic trans-regulators that we identified are transcription or signaling factors . Many of the regulators are found in the same functional pathways as their target genes . By eliminating the recruitment of regulators from other pathways , cells can alter gene expression quickly when a cellular process requires a gene to be turned on or off . We do not know yet how polymorphisms in these genes influence expression in trans . One possibility is that the sequence variants in or near the regulators affect their own message and protein levels ( cis-regulation ) and lead to differential expression levels of the target genes that they regulate ( trans-regulation ) . Based on our RNA-Seq data , ∼20% of the trans-regulators show such DAE or cis-regulation . Alternately , the sequence variants in the regulators can affect their structures , stabilities [55]–[57] , and functions by changing modifications such as phosphorylation status [58]; these in turn can affect the expression of their target genes . We also do not know whether the regulatory relationships are direct or indirect . Since regulatory relationships are highly complex and most genes are regulated by multiple genes in different feedback mechanisms , we expect most regulatory relationships are indirect . The Hi-C data show that some of the regulator–target gene pairs interact physically at the DNA level; the results imply that they may be co-transcribed perhaps in “transcription factories” [40] , [41] where others have found trans interactions among regulators and their target genes [42] . Although the regulatory mechanisms remain unknown , we found that regulatory relationships are shared among cell types . For a number of genes , the trans-regulatory relationships that we identified in immortalized B-cells are also found in primary fibroblasts . Others have found that cis-regulation of some genes is shared across cell types [4] , [9] , [59] , [60]; here , we provide evidence that trans-regulation can also be shared across different cells . This is important since many cell types in humans are not easily accessible . These results suggest that it may be possible to use more readily available cells for analysis and apply the results across cell types . Our results have implications beyond regulation of gene expression . It provides insight into disease mechanisms . We already discussed the role of WDR7 as regulator of genes in the endoplasmic reticulum and the implication of this finding for multiple sclerosis . There are additional examples: for instance , we identified inositol 1 , 4 , 5-triphosphate receptor , type 2 ( ITPR2 ) as a regulator of signal sequence receptor , alpha ( SSR1 , also known as TRAPA ) . Both genes function in the endoplasmic reticulum [45] , [61] and are susceptibility genes for amyotrophic lateral sclerosis ( ALS ) [62] , [63] , but the connection between them was previously unknown . By showing the regulatory relationship between these two endoplasmic reticulum genes , we implicate inefficient endoplasmic reticulum function in the development of ALS . The role of the endoplasmic reticulum in ALS is further supported by another regulator–target gene pair , ALS2 and its target gene , SEC22A . ALS2 is the mutated gene in juvenile ALS [64] . Despite several knockouts of Als2 in mice , its role in ALS has not been identified . Here , we found that it regulates expression of SEC22A ( linkage t = 5 . 6 , QTDT p = 0 . 004 rs3219171 ) , which mediates endoplasmic reticulum to Golgi transport . These findings have therapeutic implications; a recent study suggested that survival of ALS mice can be extended by blocking endoplasmic reticulum stress induced cell death [65] . Unraveling the control of gene expression of human cells is critical for understanding normal cellular processes and disease mechanisms . It is difficult to identify trans-acting regulators . They are not restricted to regulatory genes such as transcription factors . The hundreds of regulators identified in our study do not share protein domains nor belong to particular protein families . Thus , the search cannot be guided by known regulatory functions or protein domains alone . We show that GOGE study along with RNA-Seq and molecular analyses allow the identification of cis- and trans-acting regulators of human gene expression . This approach makes it possible to determine how individual genes are regulated and to discover regulatory pathways that maintain cellular functions in human cells .
The data were from members of 45 three-generations CEPH families ( CEPH 1328 , 1330 , 1331 , 1332 , 1333 , 1334 , 1340 , 1341 , 1344 , 1345 , 1346 , 1347 , 1349 , 1350 , 1353 , 1354 , 1356 , 1357 , 1358 , 1362 , 1375 , 1400 , 1408 , 1413 , 1416 , 1418 , 1420 , 1421 , 1423 , 1424 , 1444 , 1447 , 1451 , 1454 , 1456 , 1458 , 1459 , 1463 , 1477 , 1582 , 13281 , 13291 , 13292 , 13293 , 13294 ) . Low-density genotypes for 4 , 600 autosomal SNP markers were obtained using the Illumina Linkage Panel ( v3 ) . We used PedStats [66] to check for mendelian inconsistencies . This resulted in the removal of 297 genotypes at 209 distinct SNP markers . High-density genotypes for some of the grandparents and parents were obtained from the International HapMap Project ( HapMap 22 ) , and for those families who are not part of the HapMap project , the parents and one randomly selected child in each family were genotyped using the Human SNP Array 5 . 0 ( Affymetrix ) , which assays for ∼500 , 000 SNP loci throughout the human genome . Then , high density genotypes for family-based association ( QTDT ) on all subjects were obtained by inference using the low-density genotypes and high-density genotypes on selected individuals [67] . For expression analysis , immortalized B cells were grown at a density of 5×105 cells/mL in RPMI 1640 with 15% fetal bovine serum , 2 mM L-glutamine , and 100 U/mL penicillin-streptomycin . RNA was extracted from the cells and hybridized onto Human Focus Arrays ( Affymetrix; ∼8 , 500 RefSeq Genes on each array ) . Samples were grown and processed in random order to minimize batch effects . Samples of sibs were processed together only by chance . Expression intensity was scaled to 500 using the global scaling method implemented in the Expression Console software from Affymetrix and transformed by log2 . The RNA samples for 94 CEPH grandparents ( from the 45 families ) were hybridized onto duplicate arrays . This allows us to calculate “variance ratio” as a measurement of variability in expression levels among individuals relative to the measurement noise . For each expressed gene ( called “present” by Affymetrix Expression Console in 80% or more grandparents ) , we calculated this measure as the ratio of the variance in mean expression levels among individuals to the mean of the variance of the replicates within individuals: ( variance of Mi ) / ( mean of si2 ) . There are 4 , 793 genes with a variance ratio >1 . We focused on these genes in our analyses . Multipoint genome-wide linkage analysis was done by SIBPAL in S . A . G . E . ( http://darwin . cwru . edu/ ) [68] . We used the “W4” option [69] for weighting pairwise phenotypic differences between siblings . SIBPAL determines evidence for linkage at each SNP from regression of the phenotype difference between siblings on the estimated proportion of marker alleles shared identical-by-descent between siblings; the result is reported as a t value with corresponding significance . Point-wise significance was converted to genome-wide significance for multiple testing of markers by use of the expression of Lander and Kruglyak ( as implemented at http://www . imbs-luebeck . de/8859-15/software/silclod . html ) [19] . In SIBPAL linkage analysis , for each family phenotypic data of the children were used , and those for the grandparents and parents were not used . Family-based association analysis with SNPs near and within the target genes or candidate regulators was carried out using QTDT [21] , [70] . We tested about nine genes ( median ) per ( trans ) linkage peak . Within a gene , the SNP markers are often in strong linkage disequilibrium and thus are not independent tests . We report nominal p values for the QTDT results . In the linkage analysis , we used only data from children in the CEPH families; however , in the QTDT analysis , we used data from all members of the CEPH families . For the QTDT , we used the orthogonal ( ao ) model [21] and variance component options ( wega ) . We carried out population association analysis to follow-up results of QTDT . For these studies , expression phenotypes from 86 unrelated parents in the 45 CEPH families , as dependent variables , were regressed on SNP genotypes ( coded 0 , 1 , 2 ) . Conventional analysis of linear regression was carried out; we tested SNPs within a gene that showed significant QTDT for each phenotype . To minimize multiple testing , for each significant trans-linkage peak , we tested only the gene where the most significant QTDT result was found; SNPs within these genes are mostly highly correlated so we did not consider them as independent tests . We reported the nominal p values for these tests . mRNA-Seq was performed as recommended by the manufacturer ( Illumina ) . Briefly , immortalized B-cells from 41 unrelated CEPH grandparents ( part of the International HapMap Project and the 45 families in this study ) were grown and processed for RNA-Seq; hence these are biological replicates of those used in our microarray-based analysis . Poly ( A ) mRNA was extracted using Dynal oligo ( dT ) beads , fragmented , and first strand cDNA generated using random hexamers . Following second strand cDNA synthesis , end repair , and addition of a single A base , Illumina adaptors were ligated onto the samples . Then , ∼200 bp fractions of the cDNA samples were isolated from agarose gels and PCR amplified . The qualities of the PCR amplicons were checked using the Agilent Bioanalyzer . The samples were then sequenced using the Illumina Genome Analyzer . We obtained an average of 41 million 50 bp reads per sample ( median = 40 million ) . For alignment of the short reads sequences to the human reference sequence ( hg18 ) and identification of SNPs , we used the program MAQ ( version 0 . 6 . 8 ) [25] . To minimize sequence errors , we used the first 40 of the 50 nucleotides in each sequence read for our analysis . For the alignment , we used the default settings of MAQ: allowing up to two mismatches per read . From the aligned reads with map quality scores of 30 or higher , we identified SNPs . For this analysis , we used only known SNPs in dbSNP Build 129 . For a sample to be heterozygous at a SNP for our DAE analysis , we required that each allele be represented in at least 5% of the total reads covering that locus . To determine the expression level of a gene , we calculated RPKM [26] . Among our data , ∼700 genes with average RKPM >1 were “called” absent on microarrays . If we had relied on microarray to identify “expressed” genes , these genes and the genes that were not represented on the microarrays would have been excluded in our analyses . To check the accuracy of our RNA-Seq results , we compared the expression levels with those from our microarray and genotypes from our sequencing data with those obtained by HapMap Consortium . For each gene , we calculated correlation coefficient of the expression levels between the two platforms across the 41 samples . The average correlation coefficient was 0 . 76 ( median = 0 . 76; range = 0 . 73 to 0 . 80 ) . For each sample , we also identified the homozygous genotypes ( AA , CC , GG , TT; ∼25 , 000 genotypes per sample ) using the HapMap database and compared them to genotypes in our sequencing results . The comparisons showed a high degree of agreement . Across the 41 samples , the average concordance rate is 98 . 6% ( median = 98 . 7% ) . The gene regulatory network was constructed based on pairwise regulatory relationship identified through linkage ( t>4 ) and QTDT analyses ( p<0 . 05 ) . Connections ( edges ) were placed between genes that were implicated in a regulator-target interaction . Properties of the resulting gene regulatory network were analyzed in MATLAB ( MathWorks ) by representing regulatory relationships as an asymmetric adjacency matrix . The number of incoming and outgoing connections per gene was determined by summing the columns and rows of the adjacency matrix . A MATLAB function for determining the scale-free topology criteria was implemented as previously described [48] . Code will be provided upon request . Figures of the resulting networks were drawn using Cytoscape 2 . 6 . 0 [71] . To identify genes that have been implicated as human disease susceptibility genes , we queried the Catalogue of Genome-Wide Association Studies ( http://www . genome . gov/26525384 ) [72] . To determine whether a regulator and its target belong to the same functional groups , we examined Gene Ontology Biological Process terms [46] for the regulator and the target genes . We counted the number of regulator-target pairs with identical Gene Ontology Biological Process annotations; these were the “observed counts . ” We then examined 1 , 000 randomly chosen gene pairs ( from expressed genes in our B-cells ) and counted the number of gene pairs that shared Gene Ontology Biological Process annotations . We repeated this 5 times and took the average; these were the “expected counts . ” We compared the observed to the expected counts by a chi-square test . Immortalized B cells of four to six individuals and primary fibroblasts ( foreskin ) from two healthy newborns were used . The cells were transfected with Accell siRNAs ( Thermo Scientific ) against candidate regulators or non-target control according to the manufacturer's instructions . For each regulator , we used a pool of siRNAs that target the regulators in order to minimize off-target effects [36] . To compare the knockdown by pools of siRNA and single siRNAs against a gene , we silenced GPHN using a pool of siRNA and 2 siRNAs against different parts of the gene; similar results were obtained in the three experiments ( see Table S3B ) . For each transfection , immortalized B cells were seeded at a concentration of 4 . 5×105 cells per 750 ul on the day of transfection . 7 . 5 ul of 100 uM Accell siRNA was mixed with the seeded culture . Each transfection mix was then plated in a 96-well tissue culture plate in 150 ul aliquots . Similarly , 4 . 5×105 cells per 750 ul of primary fibroblasts were plated in 12-well plates in growth media the day before the transfection . On the day of transfection , the growth media were removed and replaced with 7 . 5 ul 100 um Accell siRNA ( against genes of interest or scrambled sequence as control ) and 750 ul of Accell media . The transfected cells with siRNAs were incubated at 37°C for 96 h . We then replaced the Accell media with regular growth media ( RPMI 1640 with 15% fetal bovine serum , 2 mM L-glutamine , and 100 U/mL penicillin-streptomycin ) and let the cells recover for 24 h . RNA was extracted using Qiagen RNeasy kits . Effects of siRNA on gene expression were analyzed by quantitative PCR ( Applied Biosystems ) . Expression of ACTB was used for normalization and changes in expression were calculated relative to cells transfected with non-target control siRNA . Sequences of PCR primers and siRNAs are presented in Tables S4 and S5 . For the western analysis: primary fibroblasts were cultured in MEM medium supplemented with 10% fetal bovine serum , 2 mM L-glutamine , and 100 U/mL penicillin-streptomycin . Cells were serum starved for 18 h before treatment with 100 nM insulin for 5 min . Cells were lysed in 1× Lysis buffer ( 20 mM Tris-HCl pH 7 . 5 , 150 mM NaCl , 1 mM Na2EDTA , 1 mM EGTA , 1% Triton ×100 ) ( Cell Signaling ) supplemented with 1× Complete protease inhibitors ( Roche ) and 1× phosphatase inhibitors I and II ( Sigma ) . Cell lysates containing 150 µg of total protein were incubated with 5 µg of α-INSR antibody ( #3025 , Cell Signaling ) or α-IGF1R antibody ( #3018 , Cell Signaling ) at 4°C overnight . Immuno-complex was pulled down using Protein A Sepharose ( GE Healthcare ) . Input and immunoprecipitation samples were analyzed by Western Blot using α-phosphotyrosine ( 1∶1000 ) ( 4G10 Platinum , Millipore ) or the above α-INSR ( 1∶1000 ) and α-IGF1R ( 1∶1000 ) antibodies . For the gene expression analysis , primary fibroblasts ( from foreskin ) of four individuals were cultured as above . Cells were serum starved overnight ( 18 h ) before being treated with 100 nM insulin ( Sigma ) for 0 , 1 , 2 , 6 , or 12 h . RNA was extracted and gene expression was analyzed by quantitative PCR ( Applied Biosystems ) . Sequences of PCR primers are presented in Table S6 . Hi-C data from Dekker and colleagues [39] were obtained from NCBI GEO ( GSE189199 ) ; we used the data in their alignment summaries . We compared their list of interacting pairs to our regulator–target gene pairs . A match is called when one of their interacting pair coordinates was found within a regulator or 5 kb up- or downstream and the matching member of that pair is found within or 5 kb up- or downstream of the corresponding target gene . Seventy-five such pairs were found . The experimental steps in this study are summarized by a flowchart ( Figure S3 ) .
|
Cellular characteristics and functions are determined largely by gene expression and expression levels differ among individuals , however it is not clear how these levels are regulated . While many cis-acting DNA sequence variants in promoters and enhancers that influence gene expression have been identified , only a few polymorphic trans-regulators of human genes are known . Here , we used human B-cells from individuals belonging to large families and identified polymorphic trans-regulators for about 1 , 000 human genes . We validated these results by gene knockdown , metabolic perturbation studies and chromosome conformation capture assays . Although these regulatory relationships were identified in cultured B-cells , we show that some of the relationships were also found in primary fibroblasts . The large number of regulators allowed us to better understand gene expression regulation , to uncover new gene functions , and to identify their roles in disease processes . This study shows that genetic variation is a powerful tool not only for gene mapping but also to study gene interaction and regulation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"genetics",
"and",
"genomics/genomics",
"genetics",
"and",
"genomics/complex",
"traits",
"genetics",
"and",
"genomics/gene",
"expression",
"genetics",
"and",
"genomics/functional",
"genomics"
] |
2010
|
Polymorphic Cis- and Trans-Regulation of Human Gene Expression
|
We present a model for the self-organized formation of place cells , head-direction cells , and spatial-view cells in the hippocampal formation based on unsupervised learning on quasi-natural visual stimuli . The model comprises a hierarchy of Slow Feature Analysis ( SFA ) nodes , which were recently shown to reproduce many properties of complex cells in the early visual system [1] . The system extracts a distributed grid-like representation of position and orientation , which is transcoded into a localized place-field , head-direction , or view representation , by sparse coding . The type of cells that develops depends solely on the relevant input statistics , i . e . , the movement pattern of the simulated animal . The numerical simulations are complemented by a mathematical analysis that allows us to accurately predict the output of the top SFA layer .
The brain needs to extract behaviorally relevant information from sensory inputs in order to successfully interact with the environment . Position and head direction of an animal in the space surrounding it is part of this relevant information . Neural representations of a rodent's spatial position—termed place cells—were found more than 35 years ago in hippocampal areas CA1 and CA3 [2] , correlates of head orientation—termed head-direction cells—were found twenty years later [3] , and recently nonlocalized representations—termed grid cells—were found in entorhinal cortex ( EC ) of rats [4] . Primates possibly also have place cells , certainly head-direction cells , and also spatial-view cells that do not encode the animal's own ( idiothetic ) position but fire whenever the animal views a certain part of the environment [5–8] . Grid cells in primates have not yet been reported . All of these cells selectively encode some aspects of position and/or orientation of the animal , while being invariant to others . Head-direction cells are strongly selective for the direction of the animal's head and largely invariant to its position [9] . They typically have a single peak of activity with a Gaussian or triangular shape and a tuning width of roughly 60° to 150° [10] , depending on brain area . In contrast , most place cells recorded in open fields are invariant to head direction while being selective for the animal's position . Interestingly , the degree of orientation–invariance depends on the behavioral task of the animal and possibly on the structure of the environment . In linear track environments and for repeated linear paths in open environment most place cells are orientation-specific [11] . Grid cells in EC also exhibit conjunctive representations of position and orientation [12] . Spatial-view cells in primates show very different firing properties . These cells are neither position invariant nor orientation invariant but fire when a certain part of the environment is in the animal's field of view ( FOV ) , resembling head-direction cells for the case of an infinitely distant view . Figure 1 illustrates the difference between grid cells , place cells , head-direction cells , and spatial-view cells . Throughout this paper , oriospatial cells will be used as a superordinate term for place cells , grid cells , head-direction cells , and spatial-view cells . While the precise role of these oriospatial cells is still discussed , they probably form the neural basis for the ability of an animal to self-localize and navigate [13] . Stimuli available to oriospatial cells can be classified as either idiothetic , including motor feedback , proprioception , and vestibular input , or as allothetic , which includes all information from sensors about the external environment , e . g . , vision or olfaction . While place cells are influenced by several modalities , they seem to be driven primarily by visual input ( e . g . , [14] ) , but since their firing properties remain stable in the absence of external sensory cues for several minutes , idiothetic stimuli must play a major role for place-cell firing as well [15] . Using idiothetic information for navigation , which is referred to as path integration ( or dead reckoning ) , inherently accumulates errors over longer timescales , which can only be corrected by allothetic information . For the head-direction cells it is commonly assumed that idiothetic input from the vestibular system is dominant ( e . g . , [9] ) , but like place cells they need external sensory stimuli to correct for drift . We introduce here a model for the self-organized formation of hippocampal place cells , head-direction cells , and spatial-view cells based on unsupervised learning on quasi-natural visual stimuli . Our model has no form of memory and receives raw high-dimensional visual input . The former means that our model cannot perform path integration , the latter means that positional information has to be extracted from complex images . While such a model can certainly not be a complete model of oriospatial cells , it can show how far a memoryless purely sensory-driven system can model oriospatial cells . The learning rule of the model is based on the concept of slowness or temporal stability , which is motivated by the observation that raw sensory signals ( like individual pixel values of a camera ) typically vary much more quickly than some behaviorally relevant features of the animal or its environment , such as the animal's position in space . By extracting slowly varying features from the sensory input , one can hope to obtain a useful representation of the environment . This slowness principle forms the basis for a variety of learning rules ( e . g . , [16–18] ) . The implementation used here is Slow Feature Analysis ( SFA ) as introduced by Wiskott [19 , 20] . For a given set of time-dependent training data , in our case video sequences , we are looking for a nonlinear scalar function from a given function space that generates the slowest possible output signal y ( t ) when applied to the training data . The slowness of the signal is measured in terms of its Δ-value , which is given by the mean square of the signal's temporal derivative ( see the section Slow Feature Analysis ) . As small Δ-values correspond to slowly varying signals , the objective is to find the function that minimizes the Δ-value . To avoid the trivial constant solution , the signal is required to have unit variance and zero mean . Furthermore , we can find a second function that optimizes the objective under the additional constraint that its output signal is uncorrelated to the first , a third function , whose output is uncorrelated to the first two signals , and so on . In this manner we generate a sequence of functions with increasing Δ-value that extracts slowly varying features from the training data . More details on the approach as well as its mathematical formalization can be found in the section Slow Feature Analysis . It is important , however , to stress that SFA is not related to low-pass filtering , as the apparent paradox of slowly varying but instantaneously extracted output signals is a frequent source of misunderstandings . Low-pass filtering is a trivial way to generate slowly varying , but most often completely uninformative , outputs . Such signals cannot be instantaneous , as by definition they are generated by averaging over the past . In contrast , the representations our model finds depend on the temporal structure of sensory data during the training phase of the model , but once they are established they are instantaneous , i . e . , a single “snapshot”of sensory stimuli is sufficient to generate the model output ( e . g . , a model place cell response ) . SFA has been successfully applied as a model for the self-organized formation of complex cell receptive fields in primary visual cortex [1] . Here , we embed this approach in a biologically inspired hierarchical network of visual processing of a simulated rat where each layer learns the slowest features from the previous layer by SFA ( see the section Experimental Methods ) . We find that the output of the highest layer performing SFA forms a distributed oriospatial representation . In a subsequent linear step , the model applies a mechanism for sparse coding resulting in localized oriospatial codes . The same model in the same environment can reproduce the firing characteristics of place cells , head-direction cells , and spatial-view cells , depending solely on the movement statistics of the simulated rat . For roughly uncorrelated head direction and body movement , the system learns head-direction cells or place cells depending on the relative speed of head rotation and body movement . If the movement statistics is altered such that spots in the room are fixated for a while during simulated locomotion , the model learns spatial-view cell characteristics . Any computation in the brain is useless unless it leads to a change of behavior of the animal . We assume a phenomenological approach and model rat and primate oriospatial cells without asking the question what behavioral purpose these oriospatial cells serve . The last linear step of sparsification might seem irrelevant in this context; however , sparse codes have a number of advantages for subsequent processing steps that include easier decoding , energy efficiency , and , notably in the context of hippocampus , increased efficiency of memory storage in recurrent networks such as CA3 [21] . We introduce a mathematical framework in the section Theoretical Methods that analytically explains the results of the SFA output . The mathematically less inclined reader may consider skipping this section . Both analytical and computer simulation results are presented in the Results section . We conclude that a purely sensory-driven model can capture the key properties of several major cell types associated with spatial coding , namely place cells , head-direction cells , spatial-view cells , and to some extent grid cells .
SFA solves the following learning task: given a multidimensional input signal we want to find instantaneous scalar input–output functions that generate output signals that vary as slowly as possible but still carry significant information . To ensure the latter , we require the output signals to be uncorrelated and to have unit variance . In mathematical terms , this can be stated as follows . Optimization problem . Given a function space ℱ and an I-dimensional input signal x ( t ) , find a set of J real-valued input–output functions gj ( x ) ∈ ℱ such that the output signals yj ( t ) := gj ( x ( t ) ) under the constraints with 〈·〉t and indicating temporal averaging and the derivative of y , respectively . Equation 1 introduces the Δ-value , which is a measure of the temporal slowness of the signal yj ( t ) . It is given by the mean square of the signal's temporal derivative , so small Δ-values indicate slowly varying signals . The constraints ( 2 ) and ( 3 ) avoid the trivial constant solution and constraint ( 4 ) ensures that different functions gj code for different aspects of the input . It is important to note that although the objective is slowness , the functions gj are instantaneous functions of the input , so that slowness cannot be enforced by low-pass filtering . Slow output signals can only be obtained if the input signal contains slowly varying features that can be extracted instantaneously by the functions gj . In the computationally relevant case where ℱ is finite-dimensional , the solution to the optimization problem can be found by means of SFA [1 , 20] . This algorithm , which is based on an eigenvector approach , is guaranteed to find the global optimum . Biologically more plausible learning rules for the optimization problem , both for graded response and spiking units , exist [22 , 23] . If the function space is infinite-dimensional , the problem requires variational calculus and will in general be difficult to solve . In the section The modified optimization problem , we demonstrate that the optimization problem for the high-dimensional visual input , as faced by the hierarchical model , can be reformulated for the low-dimensional configural input of position and orientation . In this case , the variational calculus approach becomes tractable and allows us to make analytical predictions for the behavior of the full model . The outcome of an unsupervised learning rule , such as SFA , is crucially determined by the statistics of the training data . As we want to show that oriospatial cells can be learned from raw sensory stimuli , we approximate the retinal stimuli of a rat by video sequences generated in a virtual-reality environment . The input statistics of the training data are thus jointly determined by the structure of the virtual-reality environment and the movement pattern of the simulated rat . As this video data is very high-dimensional , nonlinear SFA in a single step is computationally unfeasible . To overcome this problem , the model is organized as a hierarchy of SFA nodes in analogy to the hierarchy of the brain's visual system ( see Figure 2C ) . Considering the complexity of the computational model presented in the last section , one might expect that it would be impossible to make any analytical statement about the model's behavior . However , in this section we introduce a mathematical framework that actually allows us to make detailed predictions depending on the movement statistics of the simulated rat . The theoretically less inclined reader should feel free to skip all sections marked by a * without loss of the general understanding of our model and the results .
One of the most common environments for place-cell experiments is an open-field apparatus of rectangular or circular shape . Here , the most typical experimental paradigm is to throw food pellets randomly into the apparatus at regular intervals , leading to a random search behavior of the rat . For this case , the rat's oriospatial configuration space comprises the full three-dimensional manifold of position and orientation . In this section , we present results from experiments with simulated rat trajectories at either high or low relative rotational speeds leading to undirected place cells or position invariant head-direction cell-type results , respectively . In a linear track , the rat's movement is essentially restricted to two degrees of freedom , a spatial one and an orientational one . In experimental measurements , the orientational dimension is often collapsed into a binary variable indicating only the direction of movement . In the linear track , these two dimensions are thus experimentally much easier to sample smoothly than the full three-dimensional parameter space of the open field . Although most of the parameters in our model ( i . e . , all the weights in the SFA and ICA steps ) are learned in an unsupervised manner , a number of parameters were chosen by hand . These parameters include the input picture size , receptive field sizes , receptive field positions , and overlaps in all layers , the room shape , and textures , the expansion function space , number of layers , choice of sparsification algorithm , movement pattern , FOV , and number of training steps . We cannot explore the entire parameter space here and show instead that the model performance is very robust with respect to most of these parameters . The fact that the simulation results presented are very similar to the analytical solutions also indicates that the results presented are generic and not a mere artifact of a specific parameter set . The most interesting parameters are discussed in the following .
According to Redish's classification , our model is a local view model , for it “only depends on the local view to explain place- cell firing” [41] . Models of this class usually extract a number of features from sensory inputs in order to obtain a lower-dimensional representation that still carries information about spatial position in the environment but is invariant to everything else . Pure local view models do not comprise a path integration system and thus cannot fully explain oriospatial firing properties , e . g . , in darkness . Pure path integration systems without external sensory input on the other hand accumulate errors , and hence a sensory coding mechanism , as proposed here , is necessary to complement any such model . Therefore , many models combine local view and path integration mechanisms [41 , 42] , but here we focus only on local view models . The model by Wyss et al . [43] is based on similar principles as our model . It applies a learning rule based on temporal stability to natural stimuli , some of which are obtained from a robot . The resulting spatial representations are localized , resembling hippocampal place fields . The learning rule involves local memory , and no explicit sparsification method is applied . The fact that the resulting representations are localized is somewhat surprising , since by itself temporal stability does not lead to localized representations [27] . This article does not investigate the influence of movement statistics on the learned representations . The model by Sharp [44] assumes abstract sensory inputs and acquires a place code by CL , resulting in units that code for views with similar input features . Thus , this model is similar to our model's last layer performing sparsification . Similarly to our results , the degree of head-direction invariance depends on the movement statistics . Unlike our results , however , this is not due to the temporal structure of input views but to the relative density with which orientation or position are sampled . The work by Fuhs et al . [45] uses realistic natural stimuli obtained by a robot and extracts “blobs” of uniform intensity with rectangular or oval shape from these images . Radial basis functions are tuned to blob parameters at specific views , and a CL scheme on these yields place cell-like representations . Our model agrees with their conclusion that rodents need no explicit object recognition in order to extract spatial information from natural visual stimuli . The model by Brunel and Trullier [46] investigates the head-direction dependency of simulated place fields using abstract local views as inputs . A recurrent network learns with an unsupervised Hebbian rule to associate local views with each other , so that their intrinsically directional place cells can become head-direction–invariant for maze positions with many rotations . The article also conjectures that movement patterns determine head-direction dependence of place cells , which is consistent with our results . The results by de Araujo et al . [47] suggest that the size of the rat's FOV is important for the distinction between spatial-view cells and place cells . With a large FOV ( as for rats ) , the animal can see most landmarks from all orientations , while an animal with a small FOV ( like a monkey ) can only see a subset of all landmarks at each timepoint . We find no dependence of our results on the FOV size for values between 60° and 320° as long as the environment is rich enough ( e . g . , diverse textures , not a single cue card ) . Instead , our results suggest that differences in the movement statistics play a key role for establishing this difference . To our knowledge , no prior model allows the learning of place cells , head-direction cells , and spatial-view cells with the same learning rule . Furthermore there are only a few models that allow clear theoretical predictions , learn oriospatial cells from ( quasi ) natural stimuli , and are based on a learning rule that is also known to model early visual processing well . Our simulated visual stimuli come from a virtual reality environment which is completely static during the training of the virtual rat . In this case , the slowest features are position , orientation , or view direction , as shown before . However , the assumption that the environment remains unchanged during oriospatial cell learning certainly does not hold for the real world . A more realistic environment will include other changing variables such as lighting direction , pitch and roll of the head , etc . The impact of these variables on the model representations depends on the timescale on which the variables change . For instance , the additional white noise in all SFA layers of the model is ignored since it varies much more quickly than position and orientation , but the direction of sunlight might become the slowest feature . Generally , the SFA solutions will depend on any variable whose timescale is equal to or slower than the position and orientation of the animal . After the sparse coding step , representations become not only localized in position and/or head direction but in the other variables as well . This behavior is not consistent with the definition of an ideal place or head-direction cell . However , many experiments show correlations of place-cell firing with nonspatial variables as well [41] . One particularly interesting instance of such a variable is “room identity . ” If a rat experiences multiple environments , usually transitions between these will be seldom , i . e . , the rat will more often turn and traverse a single room rather than switch rooms . In this case , room identity is encoded by the SFA outputs ( unpublished data ) . For n rooms at most ( n – 1 ) decorrelated SFA outputs can code for the room identity . The following outputs will then code for a joint representation of space and room identity . After sparse coding , many output units will fire in one room only ( the less sparse ones in few rooms ) , and possibly in a completely unrelated fashion to their spatial firing patterns in another room . This behavior is consistent with the “remapping” phenomenon in place cells ( e . g . , [48] ) . A great amount of work has been done investigating the impact of environmental manipulations on oriospatial cell firing in known rooms , e . g . , shifts and rotations of landmarks relative to each other [41] . How would our model behave after such changes to the learned environment ? Such transformations effectively lead to visual input stimuli outside the set of all possible views in the training environment . In this case , we expect the system's performance to deteriorate unless a new representation is learned , but more work is necessary to investigate this question . Our approach predicts increasing slowness ( i . e . , decreasing Δ-values of firing rates ) in the processing hierarchy between retina and hippocampus . Additionally , place cell and head-direction cell output should be significantly sparser than their inputs . Our main prediction is that changing movement statistics directly influences the invariance properties of oriospatial cells . For instance , an experiment in a linear track where the rat more often turns on mid-track should yield less head-direction–dependent place cells . Our model is not limited to processing visual stimuli , as presented here , but can integrate other modalities as well . The integration of olfactory cues , for example , might lead to even more accurate representations and possibly to an independence of the model of visual stimuli ( simulated darkness ) . Experimentally , the joint positional and orientational dependence of oriospatial cells is hard to measure due to the size of the three-dimensional parameter space , and even more so if the development over time is to be measured . Furthermore , precise data on movement trajectories is rare in the existing literature on oriospatial cells . Accordingly , little data is available to verify or falsify our prediction of how the brain's oriospatial codes depend on the movement statistics . As an alternative to determining the movement statistics in behavioral tasks , some work has been done on passive movement of rats , where the movement statistics is completely controlled by the experimenter ( e . g . [49] ) , but these results might not be representative for voluntary motion [50] . Markus et al . find directional place fields in the center of a plus maze , although more rotations occur in the center of the maze than in the arms [11] . This could be a contradiction to our model , although the relative speed ( which was not measured in [11] ) not the frequency determines head-direction invariance in our model . Overall , the dependence of oriospatial cells on the animal's movement statistics as proposed here remains to be tested experimentally . We conclude that a purely sensory-driven unsupervised system can reproduce many properties of oriospatial cells in the rodent brain , including place cells , head-direction cells , spatial-view cells , and to some extent even grid cells . These different cell types can be modeled with the same system , and the output characteristics depend solely on the movement statistics of the virtual rat . Furthermore , we showed that the integration of vestibular acceleration information can be used to learn place cells and head-direction cells with the same movement statistics and thus at the same time .
|
Rats excel at navigating through complex environments . In order to find their way , they need to answer two basic questions . Where am I ? In which direction am I heading ? As the brain has no direct access to information about its position in space , it has to rely on sensory signals—from eyes and ears for example—to answer these questions . Information about its position and orientation is typically present in the information it gathers from its senses , but unfortunately it is encoded in a way that is not obvious to decode . Three major types of cells in the brain whose firing directly reflects spatial information are place , head-direction , and view cells . Place cells , for example , fire when the animal is at a particular location independent of the direction the animal is looking in . In this study , we present a self-organizational model that develops these three representation types by learning on naturalistic videos mimicking the visual input of a rat . Although the model works on complex visual stimuli , a rigorous mathematical description of the system is given as well .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"primates",
"neuroscience",
"rattus",
"(rat)",
"computational",
"biology"
] |
2007
|
Slowness and Sparseness Lead to Place, Head-Direction, and Spatial-View Cells
|
Rhizobiaceas are bacteria that fix nitrogen during symbiosis with plants . This symbiotic relationship is crucial for the nitrogen cycle , and understanding symbiotic mechanisms is a scientific challenge with direct applications in agronomy and plant development . Rhizobium etli is a bacteria which provides legumes with ammonia ( among other chemical compounds ) , thereby stimulating plant growth . A genome-scale approach , integrating the biochemical information available for R . etli , constitutes an important step toward understanding the symbiotic relationship and its possible improvement . In this work we present a genome-scale metabolic reconstruction ( iOR363 ) for R . etli CFN42 , which includes 387 metabolic and transport reactions across 26 metabolic pathways . This model was used to analyze the physiological capabilities of R . etli during stages of nitrogen fixation . To study the physiological capacities in silico , an objective function was formulated to simulate symbiotic nitrogen fixation . Flux balance analysis ( FBA ) was performed , and the predicted active metabolic pathways agreed qualitatively with experimental observations . In addition , predictions for the effects of gene deletions during nitrogen fixation in Rhizobia in silico also agreed with reported experimental data . Overall , we present some evidence supporting that FBA of the reconstructed metabolic network for R . etli provides results that are in agreement with physiological observations . Thus , as for other organisms , the reconstructed genome-scale metabolic network provides an important framework which allows us to compare model predictions with experimental measurements and eventually generate hypotheses on ways to improve nitrogen fixation .
Free-living bacteria belonging to the Rhizobium genera are often symbiots associated with plants of the family leguminosae . These bacteria differentiate and have the ability to fix atmospheric nitrogen into ammonium when some compounds are exchanged between the bacteroid and its plant host [1–3] . Establishment of effective symbiotic nitrogen fixation between plant and bacteria is a complex process whose understanding constitutes an interesting scientific challenge with clear implications in plant development sciences and agriculture [4] . Nitrogen fixation in Rhizobium involves a complex plant–bacteria symbiotic relationship orchestrated by the genetic and metabolic networks of both organisms [3] . In general , the plant supplies carbon sources and glutamate to the bacteroid , while the bacteroid in turn provides the plant with ammonium , aspartate , and alanine [5 , 6] ( see Figure 1 ) . The exchange of these compounds creates a dependent symbiotic relationship between these two organisms whose effectiveness is essential to improving plant growth and bacterium survival . Rhizobium etli CFN42 is a nitrogen-fixing bacterium whose genome annotation has been reported recently [7] . Nitrogen fixation in R . etli occurs in the last of three developmental stages . The first developmental stage is related to the infection process of plant roots by Rhizobium . This begins when the plant excretes flavonoids which signal nodule formation [2] . The second stage is characterized by bacterial growth inside the plant , and the construction of a compartmentalized globular structure , called a nodule . This specialized structure protects nitrogenase , a key enzyme in nitrogen fixation , against irreversible oxidative damage by oxygen [5] . Finally , the last stage involves differentiation of the bacteria into a bacteroid able to reduce atmospheric nitrogen inside the nodule [8] . The computational analysis of this last stage is the main focus of this work . Systemic understanding of nitrogen fixation in R . etli requires the construction of a model able to integrate genomic and high-throughput data in a hierarchical and coherent fashion [9] . Integrative models of this sort constitute a powerful and elegant strategy to study the mechanism of cell behavior . In particular , constraint-based models constitute such an approach , with a capacity to predict organism phenotypes operating at steady state [10–13] . Here , we present a reconstruction of the metabolic network in R . etli , the first reconstruction made for a Rhizobium organism . A constraint-based approach [12] , including flux balance analysis ( FBA ) [14] , is used to analyze the physiological capability of the bacterium when it fixes nitrogen . To show the utility of this analysis , the consistency between model predictions with experimental observations in some metabolic pathways is evaluated . Then we analyze the effects that some gene deletions have on symbiotic nitrogen fixation and compare them with available experimental observations . Experimental evidence on how these gene deletions affect nitrogen fixation activity are available for most cases investigated computationally , and it provides important information to validate our in silico modeling .
The metabolic reconstruction was generated from the KEGG annotated genome sequence for R . etli [7] , journal publications , automated reconstruction databases [15] , and information found in biochemical textbooks on nitrogen fixation [1] . Thus , our metabolic reconstruction includes reactions with evidence from the genome annotation or with clear experimental evidence for Rhizobia . The resulting reconstructed metabolic network for R . etli includes 387 reactions involving 371 metabolites and 363 genes . This reconstruction spans 26 metabolic pathways involving central metabolism ( 44 reactions ) , amino acids metabolism ( 136 reactions ) , purine and pyrimidine metabolism ( 89 reactions ) , PHB synthesis ( 8 reactions ) , and nitrogen metabolism ( 19 reactions ) . The properties of the network and the complete set of metabolic reactions with their corresponding gene–protein reaction associations are available in Dataset S1 , Table S1 , and Dataset S2 , respectively . Nomenclature used for metabolites is included in Dataset S3 . Figure 2 shows a metabolic map of the pathways present in the reconstruction . The journal publications supporting our metabolic reconstruction are reported in Dataset S4 . The gap analysis of the metabolic reconstruction is reported in Dataset S5 . The characterization of the physiological capability of R . etli and prediction of ways to improve nitrogen fixation in the bacteroid are central themes in this study . For our analysis , we assume that symbiotic nitrogen fixation between the plant and bacterium has reached the steady state . To simulate nitrogen fixation during symbiosis , we have constructed an objective function ( OF ) representing a set of chemical compounds whose production in the bacteroid is essential to make this symbiotic process efficient . Instead of incorporating biomass components ( phospholipids , proteins , DNA , RNA ) for the organism into the OF , as has been done for other organisms such as Escherichia coli , only compounds which are known or thought to be produced during symbiotic nitrogen fixation are included . The main reason for this is that the bacteroid does not grow during the stage where nitrogen fixation occurs , which is the life stage of interest in this study . After reviewing the available literature , we can postulate an OF for use in FBA , which represents symbiotic nitrogen fixation in R . etli . This OF is based on the following physiological information . 1 ) Plant–bacteroid exchange of some amino acids during nitrogen fixation has been suggested to be a general mechanism in Rhizobia . Aspartate and alanine play a central role in the development of nodules and in efficient nitrogen fixation [6] . According to a recent hypothesis , aspartate and alanine are provided to the plant from the bacteroid , while glutamate is supplied by the plant to the bacteroid [6 , 16] . In this context , we postulate that symbiotic nitrogen fixation is closely related to the efficient supply of alanine and aspartate from the bacteroid to the plant . L-lysine has been reported in Bradyrhizobium japonicum bacteroids , a related organism to R . etli , and this amino acid was also included in the OF [17] . 2 ) Nitrogen fixation is energetically costly requiring 16 ATP molecules to reduce a di-nitrogen molecule into two molecules of ammonium , which are then exported to the plant [2 , 5] . The transport of ammonium from the bacteroid to the plant is crucial for establishing symbiosis with the plant . 3 ) During nitrogen fixation , some Rhizobia accumulate poly-ß-hydroxybutyrate ( PHB ) and glycogen [18 , 19] . These compounds serve as storage for carbon that can be used when others are not present [20 , 21] . The presence of PHB has been verified in R . etli in the free-living and bacteroid states [22] . Even though the synthesis of PHB requires energy , PHB production is important because it reduces the levels of NAD ( P ) H which can repress the activity of some enzymes in the citric acid ( TCA ) cycle [21] . Nodules in R . etli are characterized as determinate nodules , and there is experimental evidence that glycogen and PHB molecules are produced during nitrogen fixation [5] . Thus , we consider the production of PHB and glycogen to be important components of the symbiotic nitrogen fixation OF . The identified essential components produced by the bacteroid and exchanged with plant during nitrogen fixation are depicted in Figure 1 . The OF used to represent symbiotic nitrogen fixation is a linear combination of all the components noted above . Thus , by maximizing this OF we suggest that during nitrogen fixation steady-state fluxes maximize the equal molar production of these compounds . In the rest of this work we will refer to the OF as the function that maximizes symbiotic nitrogen fixation . FBA consists of finding a flux distribution subject to steady-state mass balance and thermodynamic constraints , such that a linear OF is maximized [14] . FBA was performed ( see Methods section ) , and the resulting flux distribution was compared with the known physiology of the organism . To verify the robustness of our results , we also ran the analysis using 1 , 000 different randomly weighted OFs ( with weights selected from a uniform distribution ) that did not assume equimolar contributions of the components shown in Equation 1 ( see Methods section ) . We observed that the identified inactive metabolic pathways were independent of the stoichiometric coefficients of the OF ( see Figure S1 ) . The exchange reactions and the corresponding constraints used in simulations can be found in Dataset S2 and Table S2 . R . etli , like most other Rhizobia , fixes nitrogen in a microaerobic environment [23 , 24] . We simulated microaerobic conditions by constraining the upper bound of oxygen uptake rate to be 1 mmol/gDW/hr , a range estimated from experimental reports [25] . The simulations suggest that under microaerobic conditions , symbiotic nitrogen fixation activity is possible and some patterns for using the central metabolic pathways can be observed . During nitrogen fixation , dicarboxylates ( succinate ) provided by plant are metabolized via the TCA cycle . Efficient nitrogen fixation requires a high degree of coordination between the TCA cycle and oxidative phosphorylation [5] . Bacterial respiration is important for nitrogen fixation for two reasons: it ( 1 ) reduces oxidative damage to nitrogenase by consuming oxygen , and ( 2 ) simultaneously generates ATP molecules needed for nitrogen fixation . R . etli is characterized by a branched respiratory chain which involves at least four terminal cytochrome oxidases [26 , 27] and whose activity is regulated by the oxygen concentration in the environment . Nonzero fluxes through oxidative phosphorylation were observed in the simulation results , indicating oxidative phosphorylation is needed to maximize symbiotic nitrogen fixation . In fact , removal of all cytochrome oxidase reactions results in a complete loss of symbiotic nitrogen fixation . This result is in agreement with the reported essentiality of respiration for nitrogen fixation [5 , 24] ( see Figure 3 ) . The model predicts incomplete use of the TCA cycle . Experiments have reported the activity of all enzymes in the TCA cycle under microaerobic conditions in some Rhizobium bacteroids [5]; however , all TCA cycle enzymes are not always detected experimentally [20] . In addition , mutants in TCA cycle enzymes in B . japonicum are still able to fix nitrogen , suggesting that a complete set of TCA cycle enzymes is not strictly required to fix nitrogen [5 , 28] . Here , FBA supports the notion that incomplete use of the TCA cycle can still result in nitrogen fixation at low oxygen uptake rates in R . etli . The model predicts that citrate synthase , isocitrate dehydrogenase , and 2-oxoglutarate dehydrogenase are not used , which agrees with the enzymes suggested by experimental results to be inactive under microaerobic conditions [23] . This result is supported by flux variability analysis across alternate optimal solutions [29] , and it was insensitive to changes in the weightings in the OF coefficients of metabolites in Equation 1 . The flux through these enzymes was always zero in all optimal solutions , independent of the coefficients defined in the OF . The model also predicts that there is no flux through the Entner-Doudoroff and pentose phosphate pathways under microaerobic conditions . As above , no flux through Entner-Doudoroff and pentose phosphate pathways was observed across all optimal solutions for 1 , 000 randomly weighted OF . Proteomic analysis of the B . japonicum bacteroid did not detect the presence of enzymes involved in the Entner-Doudoroff pathway in agreement with the model predictions [20] . However , the proteome data shows the presence of several of the pentose phosphate pathway enzymes , which contradicts the in silico predictions . One possible explanation for this discrepancy is that the use of this pathway could be strain-dependent . Thus , experimental measurements in R . etli bacteroids are needed to support or refute this computational result . It has been shown experimentally that the glutamine synthetase and glutamate synthase pathway ( GS-GOGAT ) constitutes the central mechanism of ammonium assimilation in free-living Rhizobia [30–32] . FBA predicts that there is no activity in the ammonium assimilation pathway during symbiosis ( a non–free-living state ) , which agrees with recent reported measurements where ammonium assimilation was not observed during nitrogen fixation [20 , 32] . As before , flux variability analysis and random selection of the OF coefficients showed the inactivity of this metabolic pathway . The ammonium assimilatory pathways in the bacteroid are not active since most of the ammonium produced is transported to the plant . In fact , there is experimental evidence that an increase in ammonium assimilation negatively affects the nodulation process [32] . It also suggests that the inactivity of ammonium assimilation establishes optimal conditions for symbiotic nitrogen fixation , where complete transport of ammonium to the plant favors symbiotic nitrogen fixation . Myo-inositol is an abundant compound in nodules and bacteroids , and it has an important influence on the efficiency of nitrogen fixation [33] . Although its origin is not well-understood , it constitutes an essential precursor for the synthesis of rhizopines . Rhizopines may function as osmotic protectants and in some Rhizobium strains confer a competitive advantage at early stages of nodulation [33 , 34] . The metabolic pathway of myo-inositol catabolism has been included in the metabolic reconstruction , and simulations with high uptake rates of myo-inositol suggest that it can be used as an energy source for nitrogen fixation . In silico analysis suggests that the activity of the myo-inositol dehydrogenase enzyme , encoded by idhA , increases symbiotic nitrogen fixation . Conversely , elimination of myo-inositol dehydrogenase enzyme from the network decreases the predicted nitrogen fixation activity . These model results have been observed experimentally in an idhA mutant in Sinorhizobium fredii [33] . The results obtained from simulations support the idea that myo-inositol catabolism plays an important role during nitrogen fixation , not only at early stages of nodulation but during nitrogen fixation as well . From a physiological point of view , there are some other possible explanations for reduced nitrogen fixation when the myo-inositol dehydrogenase enzyme is inactive . It may be a consequence of toxic levels of myo-inositol or a consequence of insufficient concentrations of myo-inositol for growth and maturation of the bacteroid [33] . Experimental data suggest that the essentiality of idhA is strain-dependent , and in this reconstruction we have included this metabolic pathway in agreement with the KEGG database [15] . From our in silico analysis , we observe that a deletion of myo-inositol dehydrogenase enzyme decreases nitrogen fixation activity , although it is not essential for symbiotic nitrogen fixation in R . etli . According to our in silico results , idhA is a key gene with potential implications for symbiotic nitrogen fixation . In this section , we evaluate the capacity of the model to predict the physiological behavior of the bacteroid when it suffers gene deletions . In silico analysis was conducted for deletions in PHB synthase , glycogen synthase , arginine deiminase , myo-inositol dehydrogenase , and pyruvate carboxylase . The first three enzymes are involved in PHB and glycogen synthesis and in arginine degradation , respectively . We have selected these enzymes because experimental results are available for Rhizobium on how these gene deletions affect symbiotic nitrogen fixation with respect to the wild-type strain . To simulate gene deletions , the fluxes through reactions associated with the corresponding enzyme are constrained to zero , and the OF for FBA is constructed as before , excluding PHB or glycogen for the PHB and glycogen synthase deletion simulations , respectively ( see Dataset S2 ) . Gene deletion studies for E . coli have shown that the method of minimization of metabolic adjustment ( MOMA ) makes better mutant predictions than FBA [35] . Unlike FBA , MOMA identifies the flux distribution for the mutant strain that is closest to the wild-type flux distribution ( measured as the Euclidean distance ) [35] . Predicted changes in fluxes through some key reactions in the mutant strains versus the wild-type are reported in Figure 3 , where mutant predictions were done using both FBA and MOMA . Qualitatively , FBA and MOMA made similar predictions for most mutants with respect to the wild-type symbiotic nitrogen fixation flux . For the double gene deletion ( PHB and glycogen synthase ) , FBA and MOMA predict different results . FBA predicts an increase in symbiotic nitrogen fixation , while MOMA predicts a decrease in symbiotic nitrogen fixation; unfortunately , no experimental results are available for the double deletion mutant . For this case , we observed slight variations in exchange fluxes when using the two analysis methods . There was also a set of biochemical reactions that have no flux in the FBA solution for the double mutant but are used in the MOMA solution: aconitase ( ACONT ) , 2 oxoglutare dehydrogenase ( AKGDH ) , citrate synthase ( CS ) , cystathionine b-lyase ( CYSTL ) , cystathionine beta-synthase ( CYSTS ) , 2-dehydro-3-deoxy-phosphogluconate aldolase ( EDA ) , 6-phosphogluconate dehydratase ( EDD ) , and fructose bisphosphate aldolase ( FBA ) . Conversely , we identified three reactions , methylmalonate ( MMSAD3 ) , inositol dehydrogenase ( INS2D ) , and inositol catabolic reaction ( INSCR ) , whose fluxes were active in FBA , but inactive in the MOMA solution . The complete flux distributions for the double mutant predictions are included in Dataset S6 . Simulations for deletions of PHB synthase predict that symbiotic nitrogen fixation increases , in agreement with the experimental observations in R . etli [22] . Experimentally , deleting PHB synthase increases NADH levels and consequently reduces the NAD+ / NADH ratio . A possible physiological explanation for the increase in nitrogen fixation rate could be that the increase of reductive power ( lower NAD/NADH ratio ) can be channeled to nitrogen fixation [22] . A similar effect on symbiotic nitrogen fixation is predicted for the glycogen synthase deletion , which also agrees with the observed physiological response reported for Rhizobium tropici [36] . FBA suggests that the same effect would occur for R . etli . The simulations predict that the flux through PHB synthase increases in the glycogen synthase mutant , and , similarly , the flux through glycogen synthase increases in the PHB synthase mutant . These results are in agreement with experimental reports suggesting that the quantities of both polymers are relatively flexible such that inhibition of one results in an accumulation of the other [22] , a property that is qualitatively observed in our in silico modeling . It is unclear whether arginine is supplied to the bacteroid by the plant , and as a result the metabolic network reconstruction lacks an arginine transport reaction and ornithine degradation reactions . Recent evidence has found that the arginine deiminase pathway is active in R . etli bacteroids which convert arginine into ornithine while generating ATP and CO2 . By allowing the ornithine carbamoyl transferase reaction to be reversible and including an arginine–ornithine antiporter in the network , the symbiotic nitrogen fixation flux increased by more than 40% compared with the condition where arginine is not metabolized by the bacteroid ( using iOR363 ) . Deletion simulations removing arginine deiminase from this modified network predict a decrease in symbiotic nitrogen fixation ( Figure 3 ) , which is in agreement with experimental mutations of the arcA gene , which encodes the arginine deiminase enzyme in R . etli [37] . Pyruvate carboxylase is not used in the wild-type solution identified using FBA , so mutant predictions for pyruvate carboxylase are identical to the wild-type predictions . It is known experimentally for R . etli that deletion of this enzyme does not affect nitrogen fixation [38]; however , it does not discard the possibility that this enzyme may be important in other life stages or in rhizosphere competition [39 , 40] . To verify that these conclusions obtained from the gene deletion analysis are not sensitive to the coefficients in the OF , we randomly assigned OF coefficients for the five metabolites from a uniform distribution of values between 0 and 1 . A total of 1 , 000 different random OF were subsequently used individually in the gene deletion analysis . The qualitative effect of the gene deletions on symbiotic nitrogen fixation was independent of the OFs used; for example , in all 1 , 000 cases the deletion of PHB synthase increased symbiotic nitrogen fixation . However , quantitative prediction of gene deletion effects was dependent on the chosen OF coefficients . To improve quantitative model predictions , a better approximation of the physiological levels of the OF components is needed . Phenotypic phase plane ( PhPP ) analysis is a useful method to characterize the steady-state solution space projected in two dimensions [41 , 42] . Through this analysis , the steady-state flux distributions can be divided into a finite number of regions , each with similar metabolic flux patterns and characterized by equivalent shadow prices [41] . The shadow prices give us information on how the OF would change if the metabolites were additionally supplied to the network . These shadow prices can be used to classify the phenotypic phase plane into regions where the availability of different metabolites limits symbiotic nitrogen fixation . The metabolic network for R . etli was analyzed with respect to two parameters , succinate and oxygen uptake rates . The low oxygen uptake rate inside the nodules is such that it creates a microaerobic environment optimal for nitrogen fixation [43 , 44] . Constraining our analysis to low uptake rates of oxygen ( 1 mmol/gDW/hr ) , we found three regions in the PhPP , each one characterized by a qualitatively different optimal use of metabolic pathways [41] ( see Figure 4 ) . As shown in Figure 4 , it is possible to identify a finite number of regions , each one characterized by the effect that oxygen and succinate uptake rates have on the OF . Region I is characterized by a single limiting substrate , succinate , which establishes an independent relationship between the OF and the oxygen uptake rate for a fixed succinate uptake rate . Region II has dual substrate limitations . In this region an increase in the uptake rate of either succinate or oxygen will increase symbiotic nitrogen fixation . Finally , in region III , an increase in succinate uptake rate produces a decrease in the symbiotic nitrogen fixation , while an increase in oxygen uptake rate increases the OF in region III . Region III is defined as a futile region [41] . The line of optimality represents the optimal relation between the substrate uptake rates and the OF . In this case , it lies on the boundary between regions I and II . Points on the line of optimality represent the optimal oxygen uptake required for the oxidation of succinate to maximize symbiotic nitrogen fixation [45] . In silico analysis shows that an increase in the succinate uptake rate , at a fixed oxygen uptake rate ( 1mmol/gDW/hr ) , increases symbiotic nitrogen fixation until a threshold in succinate uptake rate is reached ( see Figure 4 ) . At succinate uptake rates higher than this value , an inhibitory effect on symbiotic nitrogen fixation is observed . Here , the available oxygen is not enough to oxidize the excess succinate and it reduces symbiotic nitrogen fixation . This indicates that oxygen is a limiting compound in nitrogen fixation .
The contributions of this work are the metabolic reconstruction of R . etli ( the first reconstruction made for Rhizobia ) and the FBA of the resulting model during nitrogen fixation stages . Even with a lack of detailed experimental information , like kinetics constants and flux limitations for most reactions , we have been able to show that constraint-based methods can describe the capabilities of the metabolic network consistent with available experimental information . The construction of an OF that mimics symbiotic nitrogen fixation and qualitatively agrees with bacteroid physiology constitutes a substantial contribution in this work . Our OF was sufficient to obtain some of the main qualitative physiological characteristics for R . etli during nitrogen fixation . Thus , our model consistently reproduces , in agreement with the literature , the utilization of pathways like oxidative phosphorylation , gluconeogenesis , and PHB biosynthesis during nitrogen fixation . Additionally , the analyzed gene deletion set was in qualitative agreement with the response of the experimentally observed symbiotic nitrogen fixation activity ( see Figure 3 ) . These particular gene deletions were selected because their effects on nitrogen fixation activity have been measured experimentally , allowing us to evaluate our computational results . This reconstruction can be used to suggest gene deletions that could enhance symbiotic nitrogen fixation . Here we show one example where a double gene deletion in PHB synthase and glycogen synthase could potentially increase symbiotic nitrogen fixation . The advantages of this in silico framework have been shown in other organisms [10 , 12 , 45] , and we expect that for R . etli such computational analysis will be useful to design and improve nitrogen fixation in plant development and agriculture . This last point constitutes a valuable scientific objective which requires integration of experimental data to improve and update the metabolic reconstruction . For instance , aspartate aminotransferase in B . japonicus is essential , and its deletion is detrimental to nitrogen fixation [17] , while a deletion of glutamine synthetase increases nitrogen fixation [17] . We do not observe this behavior in silico for R . etli . Experimental evaluation of these mutants in R . etli will provide a means to validate and improve the model . Similarly , recent studies have shown the ability of Rhizobia to produce amino acids in well-defined environments and the effects that these amino acids have on symbiotic nitrogen fixation [16 , 17 , 46] . Although the production of the complete spectrum of amino acids has not been well-characterized in R . etli during nitrogen fixation , we have predicted their production with the model , and compared them with the amino acids experimentally observed in B . japonicum bacteroids [17] . FBA predicts the production of amino acids included in the OF ( aspartate , alanine , and lysine ) . Experimental evidence shows the production of these amino acids in B . japonicum bacteroid [17] . Conversely , the experimental data for the B . japonicum bacteroid disagrees with the in silico analysis for R . etli , where asparagine , methionine , leucine , isoleucine , glycine , glutamine , and serine are not predicted by the model to be produced . Measurements of amino acid production in R . etli bacteroids are needed so a more accurate OF can be constructed [46] . Taken together , the reconstruction and analysis presented here provides an initial template for studying symbiotic nitrogen-fixing bacteria , and it can be used to generate hypotheses , design experiments , and to test predictable control principles for the metabolic network of R . etli .
Metabolomic flux prediction through the R . etli metabolic network was done using FBA [12] . We assume that all the chemical compound concentrations and fluxes are at steady state . To constrain the space of all the possible steady-state flux distributions , we impose stoichiometric mass balance constraints , thermodynamic constraints pertaining to reaction reversibility , and some enzyme capacity flux constraints [12] . Optimization of the OF was solved using the SimPheny software ( Genomatica ) . MOMA calculations were carried out as described previously [35] using GAMS with only the metabolic and transport fluxes used in calculating the Euclidean distance; the exchange fluxes and OF values were omitted from the distance metric ( see Datasets S1–S6 ) . For the arginine deiminase mutant predictions , the following network modifications were made: ornithine carbamoyl transferase became reversible , an arginine–ornithine antiport reaction was included , and exchange fluxes for arginine and ornithine were added ( a maximum arginine uptake rate of 5 mmol / gDW / hr was used ) . The bacteroid is an open thermodynamic system that exchanges components with the plant through its peribacteroid membrane ( see Figure 1 ) . In our in silico analysis , we have classified chemical reactions into three categories: internal , exchange , and sink . The first contains most of the reactions in the metabolic reconstruction ( all metabolic and transport reactions occurring inside the bacteroid ) . The second includes reactions which represent an interchange with the plant host ( i . e . , they allow metabolites to cross the system boundary ) . Finally , the third classification includes the entry or exit of metabolites by an unidentified source into the bacteroid . The only sink included is for myo-inositol , since the compound is observed in bacteroids , but it is unknown whether it is supplied by the plant or synthesized inside the bacteroid . In the case of the myo-inositol sink , we have limited the flux through the reaction so that myo-inositol present in the bacteroid can only be consumed . Most of the exchange reactions were defined as freely taken up or secreted , with the exception of arginine and oxygen . The oxygen uptake rate was limited by reported experimental measurements made in bacteroids [25] . The complete set of reactions and their flux constraints are available in Dataset S2 and Table S2 . In silico analysis of gene deletions for arginine deiminase , myo-inositol dehydrogenase , cytochrome oxidase , and pyruvate carboxylase was simulated by removal of the corresponding enzymatic reactions . In all these cases , the OF used was the same as the one presented in Equation 1 . However , for glycogen synthase , PHB synthase , and the double mutant ( PHB + glycogen synthase ) , new reduced OFs were used , where the corresponding component ( s ) ( glycogen , PHB , or both ) were omitted . For example , in the PHB synthase mutant the new reduced OF was: The optimization problems ( FBA and MOMA ) were then solved with these new reduced OFs . The OF for each gene deletion is presented in Dataset S2 . To verify that the inactive metabolic pathways identified in this in silico analysis are not dependent on the stoichiometric coefficients defined in the OF , we performed flux variability analysis [29] combined with random assignment on the coefficient of the OF . We verified the robustness of our reported results for some enzymes in the following metabolic pathways: TCA cycle ( aconitase A and B , isocitrate dehydrogenase , 2-oxoglutarate dehydrogenase , citrate synthase ) , Entner-Doudoroff Pathway ( 2-dehydro-3-deoxy-phosphogluconate aldolase , 6-phosphogluconate dehydratase ) , pentose phosphate pathway ( glucose-6-phosphate dehydrogenase , 6-phosphogluconolactonase , phosphogluconate dehydrogenase , and ribulose 5-phosphate 3-epimerase ) , and ammonium assimilation ( glutamate synthase , glutamine synthetase , and glutaminase ) . We assigned random numbers ( from a uniform distribution between 0 and 1 ) for the stoichiometric coefficients defining the OF . After generating a randomly weighted OF , flux variability analysis was used to calculate the maximum and minimum flux values for each enzyme across all alternate optimal solution which maximizes this random OF . This procedure was repeated 1 , 000 times . This analysis was done using Matlab and LINDO .
|
Nitrogen fixation is an important process for improving plant development in crops . Overall , it constitutes a central role in the nitrogen cycle which is essential to life . In this work we were interested in understanding nitrogen fixation in Rhizobium etli from a genome-scale perspective . Using the genome annotation and scientific literature , we reconstructed the metabolic network for R . etli , a bacterium that fixes nitrogen . The reconstructed metabolic network was used to analyze how this network is utilized during nitrogen fixation . From this metabolic network , we built a model that was found to be in agreement with the general biochemical properties of Rhizobia , when it fixes nitrogen . Additionally , we have included an analysis of how gene deletions affect symbiotic nitrogen fixation . We propose that the metabolic reconstruction presented here can be useful as a theoretical template to understand and suggest a hypothesis for improving nitrogen fixation and its biochemical interaction with plants .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"rhizobium",
"none",
"in",
"vitro",
"computational",
"biology",
"bacteria"
] |
2007
|
Metabolic Reconstruction and Modeling of Nitrogen Fixation in Rhizobium etli
|
The early detection of disease epidemics reduces the chance of successful introductions into new locales , minimizes the number of infections , and reduces the financial impact . We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic . We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population . We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously . Both time-dependent and -independent solutions can be useful for sampling design , depending on whether the time of introduction of the disease is known or not . We illustrate the approach with West Nile virus , a globally-spreading zoonotic arbovirus . Though our analytical results are based on a linearization of the dynamical systems , the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models . Our results suggest some simple rules that can be used by practitioners when developing surveillance programs . These rules require knowledge of transition rates between epidemiological compartments , which population was initially infected , and of the cost per sample for serological tests .
The effectiveness of disease control measures often depend on when outbreaks are first discovered . Early detection can significantly reduce the costs associated with disease eradication , human illnesses , and devastation of livestock or crops . For example , the 2001 epidemic of foot and mouth in Great Britain was reported only 2 weeks after the epidemic began [1] yet had an estimated financial impact of $11 . 9–$18 . 4 billion dollars [2] . A hypothetical foot and mouth epidemic in California not detected for 2 weeks could have a financial impact of over $15 billion dollars , and an epidemic not detected for 3 weeks could have an impact of up to $69 billion dollars [3] . Although many studies have examined alternative control strategies and the impact of detection time on control [1] , [2] , [4] , the complementary question of how to achieve early detection has been relatively neglected by theory . Greater attention to the design of disease surveillance methods may facilitate earlier detection and reduce the economic impacts of disease epidemics . Passive surveillance methods are the voluntary reporting of cases by primary care providers and citizens to public health officials [5] . Recent work on passive surveillance methods for human infectious diseases has progressed rapidly and includes developing methods to optimize the placement [6] , [7] and performance [8] of surveillance sites . Integrating these physical surveillance systems with internet search data has led to improvements in the performance of traditional physical reporting systems [7] , [9] . Active surveillance methods of zoonotic diseases are the periodic sampling by health authorities [5] . For vector-borne diseases active surveillance may include the use of sentinel animals and the longitudinal sampling of vector populations [10] . Active surveillance may often perform better for targeted objectives than passive methods [5] , and recent work has begun to link active zoonotic surveillance data to epidemiological models . For example , Gerardo-Giorda et al . [11] combined surveillance data and epidemiological models to identify counties that were most important for surveillance efforts of rabies in New York State . It is likely that analytical approaches will prove useful in making active zoonotic surveillance methods more cost effective , an important consideration for surveillance organizations with limited resources [12] . Past analytical work on active disease detection examined how sampling for infected individuals in a susceptible population affects the time at which an epidemic is detected [13] , [14] and the subsequent incidence of a disease at the time of discovery [15] . These studies have examined the dynamics of diseases that are directly transmitted and thus lack a disease vector . As a result , we still have little knowledge to guide early detection theory for zoonotic diseases ( e . g . , Lyme disease , malaria , Rift Valley fever virus , West Nile virus , dengue fever ) , where sampling could occur in vector populations or host populations . Here , we studied the optimal sampling design for early disease detection using formulations of a disease with one host population and one vector population . We combined models of host-vector dynamics with a periodic sampling procedure in which sample size is constrained by economic limitations . We used a susceptible-infected ( SI ) model to examine how to allocate sampling effort between the vector and host populations , and we used a susceptible-infected-recovered ( SIR ) model to look at allocating sampling effort between the vector population , infected hosts , and recovered hosts . The CDC guidelines for evaluating public health surveillance of human based diseases [16] are standards that have been used in many assessments of zoonotic surveillance systems , although differences may exist between human and zoonotic surveillance goals [17] . A recent survey on the assessment of surveillance systems found that a number of different metrics have been used to determine zoonotic surveillance performance; two of the most frequently mentioned criteria are the sensitivity of surveillance ( the ability to detect outbreaks or infection rates ) and the time to outbreak detection from initial exposure [17] . Here we assume the goal of surveillance is to detect the outbreak as early as possible to minimize financial damages or spillover human infections , a common goal for zoonoses [12] . Our results provide some basic rules of thumb for practitioners designing active surveillance protocols for vector-borne diseases .
We made assumptions common to other SI models of vector-borne diseases: vectors and hosts can be in either a susceptible or an infected state at time , the disease epidemic ( the dynamics of interest ) occur on a relatively short time-scale and thus infected individuals cannot recover nor do individuals give birth or die over the course of the epidemic , and infection spreads only through interspecific interactions [18] , [19] . Subscripts are used to denote population-level parameters: e . g . , and denote the number of infected hosts ( ) and vectors ( ) at time , respectively ( Table 1 ) . These assumptions give the following system of equations for the dynamics of infection of the SI model: ( 1a ) ( 1b ) where and correspond to the disease transmission rates from vectors to hosts and hosts to vectors , respectively . and correspond to the total host and vector population sizes , respectively . Throughout this work we assume that population sizes are constant over the course of the epidemic and that individuals are in the population only if they can potentially contract the disease . This implies that individuals that are epidemiologically isolated are not a part of the population . Note that the dynamics of susceptible host ( ) and vector ( ) populations are completely determined by system ( 1 ) because and . Because we are interested in detecting a disease as early as possible , we focus on the dynamics of the system immediately after disease introduction . Therefore we linearized system ( 1 ) about the disease-free state and obtained: ( 2a ) ( 2b ) We focus our subsequent analyses on the specific scenario of an epidemic started by an infected host with the initial conditions though analyses of alternative initial conditions are presented in Text S3 and S4 . Because of the symmetric nature of system ( 2 ) , this analysis yields similar results . With the assumptions listed above , the solution to system ( 2 ) is: ( 3a ) ( 3b ) where . For the SIR model we assume that recovered hosts obtain immunity over the timescale of the epidemic . As in the SI model the disease cannot spread through direct contacts within host and vector populations , transmission is frequency-dependent , and individuals are not born and do not die over the course of the epidemic . The full model for a single host population and single vector population is given by ( 4a ) ( 4b ) ( 4c ) where designates recovered individuals and is the recovery rate of infected individuals . Note that the dynamics of susceptible host ( ) and vector ( ) classes are completely determined by system ( 4 ) because and . The corresponding linearized model evaluated at is ( 5a ) ( 5b ) ( 5c ) For an epidemic begun by an infected host , the solution of ( 5 ) is: ( 6a ) ( 6b ) ( 6c ) where . Solutions for the alternative initial conditions for system ( 5 ) are given in Text S4 . This analysis is slightly more complicated than that presented in the main text , but the core ideas remain the same . Consider sampling at time from a population with potentially infected hosts and vectors . Let denote the set of events such that the disease is detected from a sample of size . If the total population abundance is much greater than the sample size then , the probability of detecting the disease , can be modeled as a binomial random variable . When the sample size is comparable to the population abundance , the hypergeometric distribution is a suitable sampling model . We do not consider the hypergeometric model here as the binomial distribution provides a reasonable approximation for realistic sample sizes . The proportion of infecteds at time is given by . In a sample of size , is the complement of not detecting any infected individuals , ( 7 ) When the disease is rare ( ) equation ( 7 ) is well approximated asIf there are two sampling strata ( e . g . , a host and vector , although the approach works as well for two host species or two strata of hosts in a single species ) , we need the probability of detecting the disease in either of those strata , . For two strata this quantity is given by ( 8 ) ( 9 ) A more general form when there are sampled strata is given by ( 10 ) as shown in Text S1 . We also consider the probability of detecting the disease for the first time in the sample when sampling occurs regularly at discrete time intervals . A model of detecting the disease in the current sampling period , but not before , is a geometric distribution with time-dependent detection probabilities: ( 11 ) Here the number of infecteds in stratum in the sampling period is given by . Sampling strata are defined by both the animal population being sampled and the type of test that is run . For example , immunological tests on bird populations for West Nile virus can test whether individuals are currently infected or have been previously infected by the type of antibody present in the sample . Antibody-specific tests therefore distinguish between infected birds and recovered birds . The first term on the right-hand side of expression ( 11 ) represents the probability of detecting the disease in time period . The remaining terms ( given in capital Pi notation , ) represent the probability of not detecting the disease in sampling period , where runs from to . The product of these terms gives the probability of not detecting the disease in any of the to sampling periods . We minimized the time until detection of the epidemic using the geometric probability distribution defined in equation ( 11 ) and by using the expected time to detection , given by ( 12 ) This expected value is an infinite series that converges to an unknown quantity , therefore we numerically approximated . We have so far considered the possibility of sampling and testing infected and recovered individuals in populations . However , a common practice in zoonotic surveillance is to combine samples from multiple individuals in the stratum of interest in order to save money ( e . g . , [20] ) . Though this pooled sampling does not identify which individual tested positive for the virus , the goal of surveillance is often to identify the presence of the virus instead of a specific infected individual . Pooling sizes must be constrained to prevent the possibility of a positive individual sample being diluted below detectable levels , often determined using experimental dilutions in the laboratory ( e . g . , [21] ) . To incorporate pooled sampling into our sampling model , we rescaled the probability of a positive detection in a single sample by the number of individuals in a pool , : the probability of detection in a single pooled sample of strata at time can then be approximated using a linearized binomial expansion: ( 13 ) Approximation ( 13 ) works well when . Our simulations indicate that a 10% approximation error occurs when , suggesting the approximation is robust for the purpose of early detection . Pooled sampling modifies ( 10 ) and ( 11 ) to ( 14a ) ( 14b ) Our goal is to determine the resource allocation that will allow us to detect a disease as early as possible . We therefore introduce economic constraints on this sampling process in the next section . Agencies are often faced with monitoring endemic and emerging diseases with finite resources . This necessitates allocating those resources in the most efficient way possible . We applied a cost function to describe these constraints: we let be the budget for a set of samples taken periodically and be the cost of sampling individuals from stratum , . If we assume that we spend our entire budget then . For example , a linear cost function for a vector stratum and a host stratum can be written as ( 15 ) where and are the overhead costs ( operating costs ) associated with sampling vectors and hosts respectively , while and are the corresponding costs per sample . We used the Karush-Kuhn-Tucker ( KKT ) conditions [22] to find the sampling strategy that maximizes the probability of detection ( given by equation ( 14a ) ) or minimizes the time to disease detection ( given by equation ( 14b ) ) . The KKT approach allows the minimization of a function subject to inequality constraints , e . g . , constraining the sample sizes to be nonnegative . Further details on this method , as well as some general results for cases with linear objective functions , are provided in Text S2 and S3 .
Active surveillance is an important tool for decision makers; treating the process analytically can provide some important insights on how to conduct cost-efficient surveillance . Very little past work in mathematical epidemiology has focused on early detection despite these potential benefits . One of the important products of this analysis has been to explicitly define the kinds of data that will be needed to design basic surveillance studies . Specific knowledge about the costs associated with sampling different populations and information about disease transmission rates will be necessary when making very specific predictions , but , as we have shown , applying the procedure with only basic knowledge of these quantities can make predictions that may be robust . This is fortunate for monitoring agencies as ecological and epidemiological parameters can be difficult and costly to obtain . Our analyses of West Nile virus illustrates robustness to parameters that are often unknown over a variety of models and assumptions . Although we focused on basic SI and SIR models , this framework can be easily extended to include more specific models when they are available . It is likely that West Nile virus models that incorporate more biological realism ( e . g . , [32] ) will be necessary to provide more targeted advice concerning surveillance practices for specific management agencies , whose monitoring capabilities may differ from what was assumed in this work . However , because the timescales we are examining are relatively short , our models may provide robust predictions when sampling is conducted over limited spatial scales . Therefore , even the simplified models examined here may be useful for designing sampling strategies when more detailed ecological and epidemiological information is not available . Our results suggest that the optimal sampling design will often focus all sampling effort on a particular species or compartment . This result is due to the linear nature of the cost functions and the approximately linear nature of the dynamical systems as functions of our control variable , the sample sizes , . These on-off or “bang-bang” types of solutions arise in other epidemiological problems when determining how to treat or remove individuals in infected populations to stop an epidemic [33]–[35] . More recent work on the control of epidemics suggests that when considering multiple control strategies the optimal solution is not simply an additive combination of the independent control solutions [36] . Similar results may hold for surveillance methods when combining different types of surveillance strategies , for example active and passive sampling strategies . In cases where linearity and large population approximations for the dynamics do not hold , our analysis suggests that the optimal sampling design can be a mixture of sampling strata but this occurs over a very limited parameter space for West Nile virus ( Figure 4 ) . Nonlinear cost functions may also arise when the cost per sample changes when performing a large number of samples due to reductions in the associated personnel costs or in the laboratory fees incurred in performing a large number of tests . Changing the dynamical model by incorporating more detailed ecological and epidemiological considerations may also reduce the robustness of our linearization approximation . For example , introducing spatial structured populations [37] or heterogeneous contact rates are known to lead to additional nonlinearities in incidence functions [38] , [39] . There are several additional considerations that may improve upon our efforts . Many disease models include exposed compartments ( e . g . , malaria [40] ) in the host and/or vector population that can delay the onset of infectiousness once bitten . This may lead to additional possibilities in the switch time analysis that we did not consider . For example , if a host population is initially infected but has a long exposed period then there may be a quick switch to sampling the vector population followed by switches at longer time scales back to the host population . Additional important developments include treating the initial conditions and transmission process as random variables . This will likely lead to a distribution of optimal strategies rather than a single , fixed strategy [41] . Recognizing uncertainty in the initial conditions may be especially important when the source of infection is unclear given the potential sensitivity of the sampling process to the initial infections . We also did not consider the possibility of testing for multiple pathogens in this analysis . For example in Florida , mosquito control agencies regularly screen for malaria , West Nile virus , and dengue fever among others [12] . Applying a mixed sampling strategy may allow managers to hedge their bets because the optimal strategy for West Nile virus may not necessarily translate to the early detection of other pathogens . Finally , our assumption that diagnostic tests for pathogen or antibodies provide perfect indicators of an individual's state may be violated by several factors . First , immunological dynamics can lead to low viral or antibody levels even when individuals have been infected , which may lead to low test reliability [29] . Extending the approach to coupled immunological-epidemiological models may account for this source of uncertainty . Second , and perhaps more importantly , imperfect diagnostic test reliability can arise due to stochastic factors that cannot be accounted for in conventional lab techniques . These effects can be incorporated into a sampling model by multiplying the economic efficiency by a random variable representing the test sensitivity and specificity [42] . Despite the recognized impact of emerging zoonoses on human health [43] we are aware of no work that attempts to integrate the active surveillance systems explored here with disease surveillance in humans . In diseases where humans are spillover hosts , such as West Nile virus , low human incidence is expected . Passive surveillance is often more economically efficient when dealing with rare events [44] but this reporting process differs from the assumptions made in this work . In passive surveillence the reporting effort will often vary through time due to seasonal and institutional effects . Incorporating these factors into a predictive framework will require the statistical analyses of these patterns [11] . When including the surveillance of humans for West Nile virus we expect that reductions in the time to detection will occur when the recovery rate ( ) is high or the human population size is low relative the the vector population , as this is when hosts are most efficient to sample for detecting the disease ( Figure 4 ) , though the particular effects will depend on the amount of sampling effort and the transmission rate to humans from the vector . In general we expect that accounting for passive human surveillance of zoonoses may change the optimal active surveillance strategy for wildlife populations as it may not be necessary to sample hosts that have strong interactions with humans or species that significantly lag behind the epidemiological response of humans . Another important case that we did not consider here are zoonotic diseases such as avian influenza , which spread much more easily within one zoologic species than across-species . For these diseases , the goal of surveillance is to detect a subtype of the disease more virulent in humans , indicated by sustained human to human transmission . This sampling needs to be tailored to detect clusters of human cases linked to a single avian-to-human transmission that deviate from what is to be expected from low-level human-to-human and bird-to-human transmission [45] . This kind of surveillance will require more detailed contact tracing that is not accounted for in our framework , though the basic structure we have described here could still be applied . More complex statistical analyses will also be needed to determine whether levels of infecteds and recovereds are significantly higher than background levels in order to determine if an outbreak is occurring . Analyses such as those determining epidemic thresholds from public health data ( e . g . [45]–[47] ) will be useful starting points for integrating thresholds into detecting epidemics of endemic zoonotic diseases .
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Outbreaks of zoonoses can have large costs to society through public health and agricultural impacts . Because many zoonoses co-occur in multiple animal populations simultaneously , detection of zoonotic outbreaks can be especially difficult . We evaluated how to design sampling strategies for the early detection of disease outbreaks of vector-borne diseases . We built a framework to integrate epidemiological dynamical models with a sampling process that accounts for budgetary constraints , such as those faced by many management agencies . We illustrate our approach using West Nile virus , a globally-spreading zoonotic arbovirus that has significantly affected North American bird populations . Our results suggest that simple formulas can often make robust predictions about the proper sampling procedure , though we also illustrate how computational methods can be used to extend our framework to more realistic modeling scenarios when these simple predictions break down .
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2014
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Optimal Sampling Strategies for Detecting Zoonotic Disease Epidemics
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T cell memory is a cornerstone of protective immunity , and is the key element in successful vaccination . Upon encountering the relevant pathogen , memory T cells are thought to initiate cell division much more rapidly than their naïve counterparts , and this is thought to confer a significant biological advantage upon an immune host . Here , we use traceable TCR-transgenic T cells to evaluate this proposed characteristic in CD4+ and CD8+ memory T cells . We find that , even in the presence of abundant antigen that was sufficient to induce in vivo IFNγ production by memory T cells , both memory and naïve T cells show an extended , and indistinguishable , delay in the onset of proliferation . Although memory cells can detect , and respond to , virus infection within a few hours , their proliferation did not begin until ∼3 days after infection , and occurred simultaneously in all anatomical compartments . Thereafter , cell division was extraordinarily rapid for both naïve and memory cells , with the latter showing a somewhat accelerated accumulation . We propose that , by permitting memory T cells to rapidly exert their effector functions while delaying the onset of their proliferation , evolution has provided a safeguard that balances the risk of infection against the consequences of severe T cell–mediated immunopathology .
After virus infection , a small number of naïve virus-specific T cells begins a process of cell division and differentiation that results in the accumulation of a large number of effector T cells . These cells become sufficiently numerous at around day 5 ( for CD8+ T cells ) or day 6 ( for CD4+ T cells ) to allow their detection by flow cytometry , and their numbers peak at ∼7–10 days after infection . Thereafter , cell numbers decline , and by ∼15 days post-infection the majority of cells remaining are of memory phenotype . These memory T cells are central to the protective immunity that is induced by infections and by vaccination , and are thought to confer several benefits upon the immune host . When compared to naïve cells , memory T cells can be triggered by lower levels of antigen , and they more rapidly express several effector functions [1]–[3] . Furthermore , in contrast to naive T cells , memory T cells efficiently enter non-lymphoid tissues to survey for antigen , facilitating the early detection of , and rapid response to , infection [4] , [5] . An additional benefit of memory T cells is their more rapid accumulation after antigen re-exposure . This has been attributed , in large part , to their more rapidly initiating cell division following antigen contact [1] , [2] . Memory T cell responses have most commonly been measured in immune mice , where pre-existing memory T cells and antibody could affect the response . To circumvent this concern , many investigators have employed heterologous infections where mice are given one pathogen , which expresses a particular epitope , to induce memory T cell formation , and the mice are subsequently challenged with a different pathogen that expresses that same epitope . In this way , the response of the epitope-specific memory T cells can be measured in the absence of extensive pre-existing memory T cell or antibody responses the secondary pathogen . However , the inflammatory signals during the primary and during the secondary response could vary with the pathogen and the response of memory T cells to heterologous challenge could be different from the response following re-exposure to the original pathogen . Furthermore , in many cases , memory cell responses in immune mice have been compared to the responses of naïve cells in naïve mice ( i . e . , to classical primary T cell responses ) ; but under these circumstances , any differences observed between the memory and the naïve cells may be due not only to intrinsic differences between the two cell types , but also to differences in the immune environment in which the two populations reside . It is important to determine the extent to which the faster response is due to the intrinsic , epigenetic changes that are present within memory T cells and how much is due to extrinsic changes that are related to the immune host . These concerns can be largely circumvented by carrying out adoptive transfer experiments and herein , focusing mainly on virus-specific CD4+ T cells , we have re-evaluated the antigen responsiveness of naïve and memory T cells , by comparing the organism-wide kinetics of both cell types in the same host animals during the first few days of a viral infection . TCR-transgenic naïve and/or memory T cells were adoptively transferred into mice; experiments were designed to allow us to compare the responses of the two populations very early after infection ( by transferring relatively large numbers of cells ) or later post-infection ( by transferring fewer cells ) . Using these traceable T cells , we have compared the rates of accumulation of naïve and memory CD4+ T cells in lymphoid and non-lymphoid tissues , and determined whether any differences are due to the more rapid initiation of cell division by the memory cells .
The CD4+ T cell response to LCMV is non-linear and includes an early period where there is minimal T cell accumulation [6] . To better characterize this early stage of the response for naïve CD4+ T cells , and to determine whether a similar pattern is found for naive CD8+ T cells , mice were given equal numbers of pooled naïve CFSE-labeled P14 and SMARTA T cells , which can be distinguished from host cells , and from each other , by their expression of congenic T cell markers ( Thy1 . 1 and Ly5a , respectively ) . The TCR-Tg cells were allowed to engraft for several days , then some of the mice were inoculated with LCMV , and the abundance of the transferred cells was followed daily by flow cytometry . Representative data from individual mice are shown in Figure 1A . A very small percentage of P14 CD8+ T cells was found in the spleen in uninfected mice ( day 0 ) , and this percentage remained very small through day 3 after infection , but it changed dramatically by day 4 . A similar pattern was found for SMARTA CD4+ T cells in the same mice , replicating what we have reported before for CD4 T cells [6] . The numbers of P14 CD8+ T cells and SMARTA CD4+ T cells were determined , and are shown in Figure 1B . There was a slight dip in the number of both cell types at day 2 , as has been reported by others [7] , [8] , and which has been attributed to type I IFN-mediated apoptotic deletion of cells [9] or their retention on DC [8] , although the data shown are gated on all isolated live splenocytes , which would include DC . Nevertheless , both CD8 and CD4 T cells show a delay in accumulation that lasts 2–3 days . At day 4 post-infection , however , the cell numbers had increased explosively; both CD4+ and CD8+ T cells had increased in abundance by >100-fold , indicative of the cells' having divided at least 6–7 times in the ∼24 hour period between sample harvests . Several hypotheses might be advanced to explain the lack of CD4+ and CD8+ cell accumulation in the spleen prior to day 4: for example , minimal cell division , or immediate egress of daughter cells from the spleen . To begin to address this issue , we assessed the CFSE fluorescence of the naïve P14 CD8+ T cells and SMARTA CD4+ T cells in the spleen ( Figure 1C ) . For the first two days there was no loss of CFSE , and on day 3 there was limited cell division; 24 hours later , the cells had divided beyond the limits of detection of the CFSE assay ( >7–8 cell divisions ) . Thus , for naïve cells , the lag phase appears to be related to delayed cell division; once the cells begin to divide , they do so very rapidly , and this coincides with the increase in the cell abundance . Moreover , the pattern holds for both CD4+ and CD8+ T cells . Note that the presence of T cells of a CFSE-intermediate phenotype at day 3 is most consistent with the cells' actively dividing within the spleen; this conclusion is supported by additional data , below . As noted above , the lag phase observed in the spleen could result from the flight of dividing cells from that organ . Furthermore , the sudden increase in cell number in the spleen at day 4 could be explained by the converse–the rapid recruitment into the spleen of cells that have undergone cell division at some other location . It is , therefore , important to evaluate the kinetics of cell accumulation and cell division in other anatomical sites . Mice containing naïve CFSE-labeled SMARTA cells were infected with LCMV and , at early times after infection , lymphocytes were isolated from the spleen , liver , lung , and peritoneal cavity ( Figure 2A ) . The patterns of cell accumulation ( left columns ) and CFSE dilution ( right columns ) in the non-lymphoid tissues were similar to that observed in the spleen; the onset of T cell accumulation was delayed , and the number of cells increased rapidly between day 3 and day 4 . Cell division appeared to begin at or after day 3 , and by day 4 the cells had divided beyond the limits of the assay in all tissues . The overall pattern of SMARTA CD4+ T cell abundance in the spleen mirrored that in other organs ( Figure 2B ) ; there was a slight loss of cells early on , and the frequency of cells at day 3 was similar to that in uninfected mice ( dashed lines ) . Significant increases in the abundance of CD4 T cells occurred only after day 3 . These data indicate that there is an organism-wide delay in proliferation , which is underscored by the predominance of undivided cells at day 3 in the peritoneal cavity , where the virus was initially delivered . Furthermore , the data support the hypothesis that the dramatic increase in cell abundance in the spleen at day 4 ( Figure 1 ) is most likely the result of very rapid local cell division , rather than the abrupt influx of cells that had multiplied in other locations . Having established the kinetics of naïve T cell division and accumulation , we next evaluated these issues for memory T cells . Memory T cells protect against re-infection better than naïve cells of the same epitope specificity , and several reasons have been advanced to explain this . Memory cells are: ( i ) are more numerous; ( ii ) are thought to initiate cell division more quickly; and ( iii ) express their effector functions more rapidly and in response to lower amount of epitope [3] , [10]–[12] . The great majority of comparisons of naïve and memory cells have been carried out in separate mice ( naïve & immune mice , respectively ) . However , such a comparison is complicated by several confounding factors . The abundance of memory cells in immune mice is far greater ( at least 1000-fold ) than the abundance of the equivalent naïve T cells in naïve mice; consequently , it is not easy to compare the relative changes in cell number between these two populations early after infection . Furthermore , the context within which memory T cell responses are measured ( an immune mouse ) differs in several ways from that in which primary T cell responses are measured: antigen-presenting cell number and quality will differ ( immune mice may contain numerous memory B cells ) ; immune mice may contain preexisting antibody that could facilitate the uptake of viral antigen and lead to quicker processing and presentation of virus-derived peptide by dendritic cells; and the memory cells in immune mice could affect the quantity and distribution of viral antigen . We chose to avoid these confounders , and to directly compare the rates of accumulation of naive and memory T cells in the same mice , by pooling equal numbers of naïve and memory SMARTA CD4+ T cells , and transferring them to naïve mice . The mice then were infected with LCMV , and the abundance of naïve and memory cells after infection was followed in the spleen by flow cytometry . The proportions of both T cell populations were similar at day 2 and were near the limits of detection ( Figure 3A , representative data from single mice , shown as a percentage of all CD4+ T cells ) . Cumulative proportional data for several mice at each time point are plotted graphically in Figure 3B . T cell accumulation became apparent by day 4 for both naïve and memory populations , but memory cells showed a more dramatic increase at this early time . The increase in the frequency of both populations continued; the memory cell response peaked at day 6 and the naive T cell response peaked at day 8 . Memory cell contraction was profound by day 8 , whereas the primary effector contraction phase was not yet evident . The same pattern was seen when the absolute numbers of naïve and memory SMARTA CD4+ T cells per spleen were evaluated ( Figure 3C ) . Early on , the number of secondary effectors remained relatively unchanged and was similar to the number of primary effector CD4 T cells until day 4 . After day 4 , the secondary effectors reached a peak that was higher than , and occurred earlier than , that reached by the primary effector response . The small number of transgenic cells transferred in the preceding experiment prevented our analyzing the very early ( day 1 ) antiviral responses of naïve and memory cells . To more precisely compare the time of onset of cell division in naïve and memory T cells , a larger number ( see Materials ) of memory SMARTA cells and naïve SMARTA cells were mixed , labeled with CFSE and given to mice; after several days , the recipient mice were given LCMV . Before pooling the cells , we considered it important to demonstrate the authenticity and homogeneity of the memory SMARTA CD4+ T cells . To this end , aliquots of the memory cells were evaluated for their in vivo responsiveness to peptide antigen , and for the expression of memory markers ( Figure 4A ) ; the cells were CD44hi , and the majority produced both IL-2 and IFNγ in response to stimulation with cognate peptide ( GP61–80 ) . After pooling these cells with naïve SMARTA cells , CFSE labeling , inoculation into recipient mice , and infection , the abundances of naïve and memory cells in the same mice were measured daily by flow cytometry ( Figure 4B ) . In this experiment , naïve and memory SMARTA cells began cell division after day 3 and began to accumulate at day 4 . These data imply that , when naive and memory T cells are exposed to the same environment , they both show an approximate 3-day delay after infection , before they initiate cell division . The trafficking pattern of memory T cells differs from that of naive T cells; both CD8 and CD4 memory T cells more readily percolate through non-lymphoid tissues , whereas naive T cells are more restricted to the lymphoid organs [5] , [13]–[16] . Therefore , the abundance of naive and memory T cells was followed in lymphoid and non-lymphoid sites at early times after LCMV infection ( Figure 5 ) . Equal numbers of naive and memory T cells were pooled , and a low number of pooled cells was administered to naïve mice . The number of cells in recipient mice more closely resembled the endogenous number of naive T cell precursors; however , using this initial low frequency of cells makes it difficult to identify the cells by flow cytometry during the first few days . Therefore , analyses were done starting at day 4 after infection , which is when the upsurge in the number of cells in the spleen begins . At day 4 , a few memory SMARTA CD4+ T cells could be detected in the lymph node , liver , lung , peritoneal cavity , and IEL , and they were somewhat more abundant than naive T cells ( Figure 5A ) . These observations are consistent with other reports that have shown extensive memory cell or secondary effector cell movement through non-lymphoid tissues . Primary T cells were found in some non-lymphoid sites ( liver , lung , peritoneal cavity ) , but not in others ( brain and IEL ) , probably due to the very low number of naive precursors that were initially given and the limited expansion of naïve cells at this early time point ( see Figure 1–Figure 3 ) . However , by day 6 , both primary and secondary effector T cell populations showed dramatic increases in number in all of the locations analyzed . The secondary effector response peaked at day 6 , and declined in frequency by day 8 , whereas the primary effector cells peaked at this time in most locations , except in the brain and peritoneal cavity , where there appeared to be more cells at day 11 . When shown graphically as the average percentage of SMARTA CD4+ T cells among all infiltrating/resident CD4 T cells , the memory SMARTA CD4+ T cell population ( open circles , Figure 5B ) showed a dramatic increase after day 4 and peaked at day 6; the naive CD4 T cells ( closed circles ) began to accumulate at the same time , but did so more slowly , and peaked later and at a lower percentage in most sites . It is noteworthy that even in the peritoneal cavity , where the virus was originally delivered – and where , one would expect , viral antigen would be expressed early and in quantity – the pattern of T cell accumulation resembled that seen in the spleen in terms of initial kinetics and the dominance of the memory cells , which argues that the spleen is a good “window” to view the entire immune response to LCMV . Taken together , these data indicate that the primary and secondary T cell responses to LCMV are organism-wide rather than localized , as seen during other infections [15] , [17] . Furthermore , the time it takes to initiate cell division in the secondary and primary populations is similar in all organs analyzed , which suggests that , as for primary effector cells ( Figure 2 ) the sudden accumulation of secondary effector cells in the spleen represents abrupt organism-wide cell division rather than selective recruitment to the spleen of recently-divided cells . Conceptually , the delay in T cell division , shown above for both naïve and memory T cells , could be regulated by exogenous factors , or could be intrinsic to the T cell . For example , the lack of proliferation at 2 days post infection might reflect an insufficiently prepared microenvironment , e . g . , low antigen load; perhaps it takes some time for in vivo antigen levels to rise sufficiently to trigger T cells . Thus , we evaluated the ability of T cells to respond to in vivo contact with authentic viral antigen at very early times ( hours ) post-infection , using an approach that we have recently developed; the inoculation of brefeldin A ( BFA ) into virus-infected mice allows responding T cells to be detected by staining directly ex vivo ( without ex vivo stimulation with synthetic peptide ) [18] , [19] . CD8+ memory cells constitute ∼10% of all CD8+ T cells in LCMV-immune mice , and we have previously shown that ∼50% of these virus-specific memory CD8+ T cells ( i . e . , ∼5% of all CD8+ T cells in an LCMV-immune mouse ) produce IFNγ within 6–12 hours of LCMV infection [18] . Here , we extend the analysis to CD4+ T cells . Naïve mice that contained ∼3×103 SMARTA CD4+ T cells ( Ly5a ) were infected with LCMV . 354 days later , the mice were re-infected with virus and 6 hours thereafter were injected with BFA . In these immune mice , approximately 5% of all CD8+ T cells had made IFNγ within 12 hours of re-infection with LCMV , recapitulating published data from this laboratory [18] , and others [20] . In addition , approximately 1% of all splenic CD4+ T cells were IFNγ+ at 12 hours after infection ( Figure 6A ) . Thus , memory CD4+ T cells , like memory CD8+ T cells , elaborate IFNγ within hours of secondary viral infection . To quantify the fraction of CD4+ memory T cells of known LCMV specificity that makes IFNγ immediately after infection , the Ly5a SMARTA CD4+ T cells were gated ( Figure 6B , left dotplot ) and their production of IFNγ was determined ( right dotplot ) . 14% of the virus-specific CD4+ memory T cells had responded within hours of infection . These data indicate that , within a few hours after in vivo infection , sufficient levels of epitope are presented by both MHC class I and MHC class II to stimulate virus-specific memory CD4+ and CD8+ T cells to produce IFNγ . This approach allows us to identify the T cells that are actively responding to viral antigen , and therefore permits us to determine if such cells may be undergoing a proliferative response . Therefore , to directly examine whether the cells that are actively making IFNγ immediately after challenge might be undergoing cell division , CFSE-labeled memory and naive SMARTA CD4+ T cells were pooled and co-transferred into naive mice . Some of these recipients were infected with LCMV and , 6 hours later , all mice were inoculated with BFA . Data for one uninfected mouse , and two infected mice , are shown in Figure 6C . Within 12 hours after infection of these naïve mice , approximately 2% of the memory SMARTA CD4+ T cells were actively producing IFNγ , but those responding cells showed no CFSE dilution . The naive SMARTA cells did not produce IFNγ immediately after virus infection , nor did they undergo cell division . These data confirm a functional difference between naive and memory T cells: only memory T cells rapidly make IFNγ within 12 hours of virus infection [18] , [21] . Most important for the present study , the data also show that , very soon after infection , virus-derived peptides are presented to T cells at sufficient levels to induce memory cells to produce IFNγ , yet the cells do not initiate division . The above data suggest that , within a few hours of virus infection , sufficient antigen is presented by MHC class II to trigger CD4+ T cell responses . Thus , we considered the possibility that the lag phase in naïve and memory cell division might result from an intrinsic “brake” that restrains cell proliferation for 2–3 days after antigen contact . In vitro analyses argue against this , because T cells cultured with anti-CD3-coated plates or with peptide-loaded DC proliferate by 48 hours [22] , [23] . However , in vitro analyses are carried out under conditions in which T cells are removed from their normal anatomical and physiological relationships and , for this reason , it is important to evaluate the issue in vivo . To do this , CFSE-labeled naïve SMARTA cells were transferred into mice that had been pre-infected with LCMV , and therefore contained a microenvironment that was well-prepared for supporting the initiation of T cell division . From our data in Figure 1 , we knew that T cells began to divide around 3 days post-infection , suggesting that at ∼day 2 p . i . the local microenvironment was supportive . Therefore , mice were infected with LCMV , and 2 days later they received naïve CFSE-labeled SMARTA CD4+ T cells . Some recipient mice were left uninfected , and others were given virus on the day of cell transfer . The transferred cells were assayed on days 2 , 3 or 4 post-transfer ( Figure 7 ) . If the naïve SMARTA CD4+ T cells were transferred into an uninfected mouse that remained uninfected , cell numbers remained low for at least 4 days ( Figure 7A & B , first column ) and CFSE remained undiluted ( Figure 7C ) . If the cells were transferred into mice that were concurrently infected ( Figure 7 , second column ) , there was neither accumulation nor CFSE dilution at 2 days post transfer , recapitulating the data in Figure 4 . In contrast , if the cells were transferred into mice that had been infected two days previously ( Figure 7 , column 3 ) then , at the same time point post-transfer ( 2 days ) there was readily-detectable CFSE dilution , indicating that the local environment can exert a substantial effect on the onset of T cell division . This is highlighted by the explosive proliferation that was observed in mice that had been pre-infected , and in which the transferred cells were allowed to incubate for 3 days ( Figure 7 , column 4 ) ; in pre-infected mice , the number of SMARTA cells increased ∼40-fold between day 2 and day 3 . Taken together , our data indicate that there is sufficient antigen present within hours of infection to trigger CD4+ T cell responses ( Figure 6 ) , but that critical changes in the host microenvironment occur around day 2/3 post-infection that allow virus-specific CD4+ T cells to initiate their proliferation ( Figure 7 ) . These data confirm that the first response of memory T cells , when re-exposed to infection , is to produce IFNγ but not to divide , which is consistent with other reports [1] , [21] , [24]–[26] .
Earlier analyses examining primary and secondary CD8+ T cell responses in the same mouse after live microbial infection showed that memory T cells accumulate faster than naïve T cells , but that both populations reached their numerical peak at approximately the same time [27]–[29] . One hypothesis proposed to explain the more rapid increase in CD8+ memory T cell numbers was that , after antigen contact , memory T cells initiate cell division more quickly; data supporting this idea has been reported not only for CD8+ T cells [1] but also for CD4+ T cells [2] . However , other in vitro investigations have indicated that naïve and in vivo-primed memory T cells initiate proliferation at a similar time point after antigen exposure [26] , [29] . Additional analyses of in vivo CD8+ T cell responses to live microbial infection have reported differences in abundance between primary and secondary ( memory ) T cells [27] , [28] but these studies examined later time points after infection , and thus could not distinguish between , for example , different times of onset of cell division and different trafficking patterns , which are known to differ between memory and naïve T cells [5] , [13] . Indeed , the difference in anatomical distribution of naïve and memory cells could be relevant to the time of onset of cell division because one population ( presumably , the memory population ) might encounter antigen sooner after infection , as has been proposed for some respiratory tract infections [15] , [30]–[34] . Therefore , although it is clear that the acquisition of memory T cells is beneficial to the host , the underlying reason ( s ) for the “superiority” of memory cells , compared to naïve cells , remains obscure . In this study , we asked: how do naive and memory T cells in lymphoid and non-lymphoid tissues respond in the days immediately following a live , systemic , viral infection ? The principal conclusions from our study are that: ( i ) in a virus-infected animal , both naïve and memory CD4+ T cells show a similar and extended delay of ∼72 hours before they begin to divide; ( ii ) this is true in both lymphoid and non-lymphoid tissues; and ( iii ) this in vivo delay occurs despite viral antigen reaching T cell-stimulatory levels within 6–12 hours of infection . A lag phase prior to the onset of CD8+ T cell proliferation has been previously reported in a non-infectious model system , in which cells were transferred into immunodeficient mice; proliferation of HY-specific CD8+ T cells was not immediate , and memory cells showed a shorter delay ( ∼8 hours ) compared to naive T cells ( ∼24–48 hours ) [1] . Our study differs in several ways . First , we use an infectious model , and immunocompetent mice . Second , for both CD4+ and CD8+ T cells , we observe that the delay in proliferation is 48–72 hours and , third , the delay is the same for both memory and naïve cells . The observation that naive and memory T cells initiate cell division concurrently is consistent with the data reported in other models [25] , [26] , [29] , [35] . Cell division is , of course , a complex and lengthy process , and our experimental approach using CFSE measures the final phase: physical separation of the cell membranes and consequent dilution of the dye . We cannot conclude , from our data , that the molecular events that precede cell division ( e . g . , DNA replication ) are initiated concurrently in naïve and memory CD4+ T cells . Our in vivo data support recent in vitro findings , which showed that naive and memory transgenic CD8+ T cells initiate cell division at the same time [29] . So , while other investigators have shown a lag in antigen-driven and antigen-independent T cell proliferation [22] , we show that this lag occurs in vivo and in the context of live systemic virus infection . We also extend this to memory T cells . Consistent with some studies [27]–[29] , we see a more robust increase in the number of memory T cells , and we extend this finding by showing that this is not attributable to earlier onset of cell division; both naïve and memory T cells initiate division concurrently . Moreover , LCMV induces a systemic response where T cell responses occur simultaneously ( Figure 2 ) ; hence , the lag is not related to the movement of cells or their initial presence at sites of infection . Our data confirm and extend some earlier reports and suggest that the “faster” memory T cell response reported in many models is due neither to their more rapid initiation of proliferation , nor to their more rapid division rate [1] , [2]; instead , the more robust accumulation of memory cells , observed in both lymphoid and non-lymphoid organs [5] , [13] , more likely results from their higher precursor frequency at the time of infection , perhaps combined with enhanced survival during the early proliferative response . What factors might regulate the delay in , and the ultimate onset of , T cell division ? It is particularly striking that , in a virus-infected host , CD4+ memory T cells express their effector functions within hours of infection ( Figure 6 ) , but fail to divide for several days ( Figures 3 , 4 , 5 ) . One explanation for this phenomenon is that more antigen is required to trigger cell division than is needed to drive cytokine synthesis , and that this higher threshold is reached only at 2–3 days post infection . However , memory T cells are more sensitive than naive T cells to antigen and thus , if this argument were valid , memory cells should initiate proliferation sooner; yet they do not . Other analyses indicate that antigen dose affects the number of cells that are recruited into the proliferative response , but not the time when proliferation begins [22] , [36] . As an alternative to antigen levels , one can imagine that the acquisition of key costimulatory molecules by dendritic cells might govern the onset of naive and memory T cell division . There is evidence that some costimulatory molecules are expressed in a particular order , which could orchestrate this early T cell stage [37] , [38] , and recent data suggest that B7/CD28 signaling thresholds are instrumental in regulating cell cycle progression in T cells [36] . The above explanations for the T cell lag phase invoke the early absence of positive factors – for example , insufficient antigen or co-stimulatory molecules . However , it is equally possible that the delay may reflect active negative regulation of T cells by host factors; releasing this brake allows division to begin . Under this scenario , the demonstration of immediate T cell proliferation using in vitro studies can be criticized because the use of disrupted tissues might abrogate such negative regulatory interactions , particularly if they require spatial organization . For example , the delay in LCMV-specific T cell proliferation reported herein coincides with peak NK cell activities in this model [39]; one can speculate that , in intact tissues , there may be cellular restraints such as the local consumption of key growth factors , or the local expression of inhibitory cytokines , by NK cells [40] . Furthermore , regulatory T cells , which are present throughout the body , also may constrain T cell proliferation through the production of cytokines that impede T cell responses , such as IL-10 and TGFβ . Changes in the local microenvironment could occur in response to inflammation and perhaps lead to particular metalloprotease activity , and relieve T cells of LAG-3-mediated suppression of proliferation [41] . It has been proposed that early negative regulation may be imposed by early inflammation , in particular by the interferons: we consider this unlikely , because direct IFNγ signals enhance the expansion of CD8+ and CD4+ T cells [42] , [43] , and a similar effect has been described for direct IFNαβ signals [44] , [45] . If such negative regulatory mechanisms are involved , then it is interesting to speculate that there may be microbes that can engage the brakes in the immune response , thus leading to a delayed immune response , which would enable the pathogen to complete its replication cycle or to spread to a new host . It is noteworthy that some infectious agents induce T cell responses that are much delayed in comparison to that mounted against LCMV; for example , the peak responses against some gamma herpesviruses [46] , Histoplasma [47] , and mycobacteria [48] , [49] occur two weeks or more after infection . Naïve and memory cells are equivalent in their lag phase but , once proliferation begins , memory cells rapidly outstrip their naïve counterparts ( Figure 3 ) in most anatomical sites ( Figure 5 ) . Memory cells outperform naïve cells in several ways , and it is possible that , in the mice containing both memory and naive SMARTA CD4+ T cells , the memory cells out-compete the naive T cells for limiting amounts of cytokine , thereby slowing the expansion of the primary T cell response [1] . The memory T cells might occlude naive T cell responses , possibly by associating very closely with APCs and impeding naïve cell access to these cells [50] , [51] . However , other investigators have shown that even during an ongoing recall response , naive T cells can be recruited , suggesting that competition by memory cells , if present , must be incomplete [28] , [52] , [53] . It is tempting to conclude that the more rapid increase in memory cell numbers must result from these cells' having a shorter division time , but recent analyses have shown that naive and memory T cells divide at the same rate [29] . Thus it is possible that the numerical difference between memory and naïve cells can , at least in part , be attributed to better survival of daughter memory cells . Other investigators have shown that T cell apoptosis occurs throughout the expansion phase , and that much of this is due to caspase activity [54] . Memory T cells express greater amounts of bcl2 and are protected from apoptosis , and secondary effector cells show a protracted contraction phase and less overall cell loss [1] , [27] , [28] , [55]–[57] . Hence , the more robust early accumulation of memory T cells may be due to their improved survival , but not to faster cell division . What are the evolutionary benefits of a delay in antiviral T cell division , given that CD8+ and CD4+ T cells are essential for eliminating most virus infections and for driving other immune responses ? Perhaps the expression of effector functions and cell division are mutually exclusive: the immediate onset of cell division might preclude the memory cells' expressing their cytokines , thereby preventing optimal early control of the infection . Alternatively , if memory cell numbers rose precipitously immediately following infection , they might suppress the recruitment of naïve T cells of different epitope specificity; thus , by delaying the expansion of memory cells , the host may ensure the diversification of the microbe-specific T cell response . Such diversification would , presumably , be beneficial for combating the microbial variants that inevitably emerge . It also is possible that the lag phase represents a period of time during which the innate response , and the effector functions of the memory T cell response , are given an opportunity to quickly control the infection . If this is successful , then the onset of memory T cell division will take place in a relatively non-inflammatory microenvironment , and thereafter will proceed only to a limited extent . Conversely , if the immune system's early attempt to control the infection fails , then T cell division will begin in a more pro-inflammatory microenvironment – which will include abundant type I and type II interferons – and so the T cell response will be driven to a higher peak . In this way , the T cell response escalates most when the infection cannot be resolved within the first few days . Given that T cells are capable of such explosive proliferation , this mechanism may reduce the risk of unwanted immunopathology , including autoreactive T cell responses .
C57BL/6 mice were purchased from The Scripps Research Institute ( TSRI ) breeding facility . C57BL/6 mice congenic for Thy1 . 1 ( B6 . PL-Thy1a/CyJ ) were purchased from The Jackson Laboratory . SMARTA TCR-transgenic mice specific for the I-Ab LCMV epitope GP61–80 [58] were crossed to C57BL/6 . Ly5a mice ( B6 . SJL-PtprcaPep3b/BoyJ ) to generate SMARTA . Ly5a mice or to B6 . PL-Thy1a/CyJ mice to generate SMARTA/Thy1 . 1 mice [6] , [43] . P14 TCR-transgenic mice specific for the LCMV epitope GP33–41 [59] on the H-2b background were crossed to B6 . PL mice to generate the P14/Thy1 . 1 strain . Mice were infected by i . p . administration of 2×105 plaque forming units of LCMV ( Armstrong strain ) . Quantitation of virus in the tissues was done by plaque assay on Vero cell monolayers . All experiments were approved by the TSRI Animal Care and Use Committee . Spleen cells and lymph node cells ( mix of inguinal , brachial , and axillary nodes ) were prepared using standard protocols , with red blood cell lysis . Lymphocyte isolation from other tissues was done as previously described [14] . Mice were first perfused with PBS through the heart . The liver was additionally perfused directly by injecting PBS through the hepatic artery . The lungs and small intestine ( with the Peyer's patches removed ) were minced and digested with collagenase . The liver and brain were triturated in a Dounce homogenizer to make a cell suspension . Lymphocytes were separated from the rest of the tissue cells by resuspending them in 44% Percoll and floating them onto a 56% Percoll cushion , followed by centrifugation . Lymphocytes were isolated at the interface of the two layers . Spleen cells were stained directly ex vivo with fluorochrome-conjugated anti-CD4 ( clone RM4-5 ) , anti-CD8 ( clone 53-6 . 7 ) , anti-Thy1 . 2 ( CD90 . 2 , clone 53-2 . 1 ) , anti-Thy1 . 1 ( CD90 . 1 , clone HIS51 ) , anti-CD44 ( clone IM7 ) , anti-Ly5a ( Ly5 . 1 , clone A20 ) all purchased from eBioscience . com . The staining reaction was done in the presence of unlabeled antibodies against Fc-receptors to block fluorochrome-conjugated antibodies from binding to FcR+ cells; “FcBlock” was purchased from BD-Pharmingen , La Jolla , CA . The intracellular staining assay was performed as described previously [60] using anti-IFNγ ( clone XMG1 . 2 ) , anti-TNF ( clone MP6-XT22 ) , and anti-IL-2 ( clone JES6-5H4 ) from eBioscience . Cell staining was analyzed by 4-color flow cytometry using a BD Biosciences FACSCALIBUR and FloJo software ( Tree Star , Ashland OR ) . Flow cytometry was used to determine the frequency of transgenic CD4+ T cells ( Vα2+Vβ8 . 3+ ) among all spleen cells in SMARTA mice or the frequency of transgenic CD8+ T cells ( Vα2+Vβ8 . 1/2+ ) among all spleen cells in P14 mice . For the majority of experiments , a small number ( 1–3×104 ) of transgenic T cells were injected intravenously into recipient mice , and the mice were infected 4–7 days after cell transfer ( at which time , given ∼10% “take” , the mice will contain only ∼103 transgenic cells ) . In the experiments designed to evaluate the very early onset of T cell division , a larger number of transgenic cells ( 1–10×105 ) was labeled with 5mM CFSE before transfer into recipient mice . This larger number of transgenic T cells was necessary to allow the cells to be monitored as early as 1 day post infection . As described [18] , [19] , 250 µg of brefeldin A ( Sigma , St . Louis , MO ) was injected i . v . into mice , to block the in vivo secretion of cytokines . Six hours later , the mice were sacrificed and splenocytes were harvested and immediately surface stained to identify T cells , then permeabilized and stained for intracellular IFNγ . In this assay , the T cells are not exposed to synthetic peptides ex vivo .
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Vaccines are the only medical products that should be administered to almost every human worldwide , and it is well-known that they act by inducing so-called “memory” cells that can protect against subsequent encounter with the related micro-organism . Surprisingly , we do not understand precisely how these memory cells work: in what way are they better than non-memory ( “naïve” ) cells , and how do they exert their life-saving functions ? It was thought that , following exposure to the relevant microbial antigen , memory cells responded by increasing in number much more quickly than naïve cells and that they achieved this greater abundance by two means: first , by initiating cell division sooner after infection; and , second , by multiplying more rapidly thereafter . Here , we show that neither is true . Memory cells , like naïve cells , begin to divide only after lengthy ( 2–3 day ) delay after virus infection , and their subsequent rate of division is no faster than that of naïve cells . We speculate on the possible evolutionary benefits that might accrue from this lengthy delay before cell division begins .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"virology/vaccines",
"immunology/immunity",
"to",
"infections",
"virology/animal",
"models",
"of",
"infection",
"virology/host",
"antiviral",
"responses"
] |
2008
|
Tentative T Cells: Memory Cells Are Quick to Respond, but Slow to Divide
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A defining characteristic of living cells is the ability to respond dynamically to external stimuli while maintaining homeostasis under resting conditions . Capturing both of these features in a single kinetic model is difficult because the model must be able to reproduce both behaviors using the same set of molecular components . Here , we show how combining small , well-defined steady-state networks provides an efficient means of constructing large-scale kinetic models that exhibit realistic resting and dynamic behaviors . By requiring each kinetic module to be homeostatic ( at steady state under resting conditions ) , the method proceeds by ( i ) computing steady-state solutions to a system of ordinary differential equations for each module , ( ii ) applying principal component analysis to each set of solutions to capture the steady-state solution space of each module network , and ( iii ) combining optimal search directions from all modules to form a global steady-state space that is searched for accurate simulation of the time-dependent behavior of the whole system upon perturbation . Importantly , this stepwise approach retains the nonlinear rate expressions that govern each reaction in the system and enforces constraints on the range of allowable concentration states for the full-scale model . These constraints not only reduce the computational cost of fitting experimental time-series data but can also provide insight into limitations on system concentrations and architecture . To demonstrate application of the method , we show how small kinetic perturbations in a modular model of platelet P2Y1 signaling can cause widespread compensatory effects on cellular resting states .
Computational models help quantify the reaction dynamics and regulatory modes in complex biochemical systems [1]–[5] , particularly when a system is so intricate that its behavior cannot be predicted by intuition alone . The building blocks for constructing large reaction networks are often available in numerous databases [6]–[9] and journal archives . Here , one can obtain many of the experimentally-derived elementary reaction steps , kinetic constants , or rate laws for individual steps in a given biochemical system or pathway . Despite this wealth of information , however , compiling these data to construct models with accurate system-wide behavior represents a significant challenge in systems biology [10] , [11] . Comprehensive models of metabolism have been successfully developed for microbial systems [5] , [12] , [13] and certain eukaryotic cell types [14]–[16] . These constraint-based models [17] are often represented by stoichiometric networks that lack an explicit description of substrate concentrations , reaction mechanisms , or the transient behavior of the system . Although various strategies have been proposed to incorporate these features into large-scale models [18] , [19] , the task of assembling complex kinetic models with nonlinear dynamics remains a difficult problem . One of the major obstacles to building accurate kinetic models is the number of unknown parameters in the model that must be estimated using experimental datasets [19] , which themselves are often massive , incomplete , noisy , and/or imperfect [20] . A number of parameter estimation methods , such as genetic programming , simulated annealing , and various gradient-based routines [21] , [22] , have been proposed to infer unknown quantities in biochemical models . Most of these methods address the problem of estimation in purely abstract terms and do not take into account the unique mathematical features of biochemical systems , such as a well-characterized kinetic subsystem ( e . g . , the dynamics properties of an ion channel [23] ) . Estimated parameters must still meet constraints imposed by the other experimentally measured parameters in the model . To address these challenges , we propose a strategy for assembling large kinetic networks that retain the nonlinear dynamics governing individual reactions in the system . The key features of the method are: ( i ) restriction of steady-state values by subsystem kinetics , ( ii ) reduction of the steady-state solution space by principal component analysis ( PCA ) , and ( iii ) combination of independently constructed submodels ( modules ) . The first feature is a Monte Carlo sampling over unknown concentrations with fixed kinetic parameters derived from the literature . The opposite strategy has been used in microbial systems to restrict kinetic parameters based on species concentrations [12] . The second feature , reduction of the steady-state space by PCA , has been applied previously for metabolic systems described by a stoichiometry matrix [5] , [13] , but not , to our knowledge , for nonlinear systems . In the last step , a full model representation is assembled by combining PCA-reduced , steady-state solutions from each module to form a combined steady-state solution space for the entire system . This global space may then be searched for solutions with accurate time-dependent behavior using any number of established routines 22 , 24 . The method exploits three properties common to many biological systems: modularity , homeostasis , and known quantitative kinetic relationships among interacting molecular components . Interestingly , this physiology-inspired approach enforces natural constraints on the range of allowable system states and allows one to monitor shifts in steady states due to kinetic perturbations . To illustrate the method with an example , we show how 77 reactions from 17 primary data sources were integrated to construct an accurate model of intracellular calcium and phosphoinositide metabolism in the resting and activated human platelet . Finally , we extend our analysis of this modeling approach by examining the steady-state characteristics of a system that is affected by changes in kinetic rate constants .
Our method builds upon a common representation of biochemical reaction networks [25] consisting of a system of ordinary differential equations ( ODEs ) . In this paradigm , the concentration of each molecule in the system changes with time as a function of the instantaneous values of other concentrations and fixed kinetic parameters in the model . We separate this model description into two parts: The concentration vector ( CV ) of the model refers to the set of all molecule concentrations at a given instant in time and is denoted by the vector c: ( 1 ) The model topology refers to the entire set of kinetic parameters and rate equations that determine how these concentrations evolve with time . Mathematically , this is represented by the vector function f , which defines the rate of change of c with time as a function of the model concentrations and rate parameters: ( 2 ) The functional form of each is a sum of rate equations for each reaction that consumes or produces and will generally vary for each molecule . Typical functional forms for f may include , for example , a series of Michaelis-Menten or nonlinear rate expressions . A simple reaction topology is shown in Figure 1A with corresponding ODEs in Figure 1B . It is useful to separate a large model into two or more modules with subset CVs that overlap at reaction edges , as shown in Figure 1A . Often , the topology of a biological system is better characterized than its CV [17] . For example , the major protein-protein interactions in a signaling pathway may be deduced from mutation or knock-out studies , providing a molecular wiring diagram that links together the various components in the network . For each of these interactions , purified enzymes may be used to measure the strength of the interaction in vitro or to measure the rate of some enzyme-catalyzed reaction in the system . An important caveat is that the kinetic rate constants within the cellular milieu ( the cell context ) may be different from those obtained in an in vitro experiment with purified components . In contrast , it is generally more difficult to accurately measure the absolute abundance of intracellular enzymes or metabolites in vivo , although progress is being made in this area [26] . Our method thus assumes that the topology of a given system is known and that the unknown set of concentrations exists in a linear space of dimension n in which each species comprises a separate dimension ( Figure 1C ) . The ultimate goal of the method is to efficiently search this concentration space to find a set of values that , when combined with the fixed topology , renders the full model consistent with known resting states and experimental time-series data obtained by perturbation of the cell . A special situation arises when in equation ( 2 ) . Under these conditions , the model is said to be at steady state , and the vector is a steady-state solution to the system of ODEs . If f contains nonlinear terms , there may be an infinite number of steady-state solutions for the system of ODEs [25] . This set of solutions occupies some nonlinear subspace of the concentration space exemplified in Figure 1C . To guarantee that nonzero steady-state solutions may be found , the method requires the model topology ( and all module topologies ) to be balanced , meaning that the production and consumption of each molecule must be equal so that the total mass of the system is conserved . This steady-state assumption [17] is a common constraint in stoichiometric modeling and metabolic flux analysis and is conceptually related to the biological phenomenon of homeostasis [27] , in which opposing processes are coordinated to maintain the stability of a cell or organism . For example , a nerve cell may maintain a constant electrochemical gradient by continually transporting ions across a lipid membrane .
The first phase of the method involves generating a compact representation of the steady-state solutions for each module . The steps for module reduction are outlined in Figure 2A . First , conservative bounds are chosen for c based on physiological and practical considerations . For example , a regulatory enzyme is expected be present in at least one copy per cell and not to exceed an intracellular concentration of one molar . Knowledge about the physical size of the system is useful in this step to convert a raw copy number to a concentration . For small systems , this information can provide a rigid lower bound on unknown concentrations [28] . For example , a single molecule in a 6 fL platelet has a concentration of 4 nM . Also , because molecular concentrations can span several orders of magnitude , it is often more efficient to delineate this range of values on a logarithmic scale rather than a linear scale . Once the sampling distribution for c has been defined , steady-state solutions ( ) for each module are calculated using fixed kinetic parameters for each reaction in the module obtained from the literature [6] , [8] , [9] , novel kinetic experiments , or estimation . For this step , each initial guess is sampled from the distribution for c and combined with the predetermined topology . The combination of fixed rate equations , fixed parameters , and forms a well-posed initial value problem , ( 3 ) that may be computed using a numerical solver [29] . For non-oscillating systems , steady-state solutions may be obtained by simulating the system until equilibrium is reached ( i . e . , until ) . Alternatively , one may use any number of multidimensional root-finding routines , such as those available in the GNU Scientific Library [30] , to find the closest n-dimensional root to the vector function f using starting guess . In the third step , a large collection of steady-state solutions for each module is subjected to principal component analysis ( PCA ) . A sample size of 1000 points per unknown concentration is generally sufficient to minimize error due to over-fitting [31] . PCA is then used to transform these points to a new coordinate set that optimally covers the space of steady-state solutions using the fewest number of dimensions . For example , if two molecule concentrations in the steady-state space are highly correlated due to participation in the same reaction , PCA will locate a single dimension to represent each pair of points in the transformed space . Ultimately , these new dimensions will be combined across all modules to search for global solutions that lie in the steady-state space for the fully combined network . Since PCA is a linear method , a steady-state solution space that is highly nonlinear may require more principal component vectors to accurately estimate the solutions . Nonlinear methods of dimensionality reduction , such as kernel PCA [32] or local linear embedding [33] , may provide a more compact representation of steady-state solutions spaces in future iterations of the method . The reduction procedure is illustrated with an example of a human platelet model comprising 4 interlinked signaling modules ( Figure 2B ) . For each module , we used published reaction mechanisms and kinetic parameters to construct the module topologies [28] . Each topology was held fixed while the unknown CVs were sampled from empirically-defined distributions . For this step , we generated more than 109 sets of initial guesses ( ) for each module , computed the initial value problem for each until a steady state was reached ( ) , and selected only those steady-state CVs ( ) that were consistent with known concentrations . For example , the concentration of intracellular Ca2+ ( [Ca2+]i , Figure 2B ) in platelets is known to be ∼100 nM . Thus , only those with [Ca2+]i≈100 nM were kept as part of the steady-state solution space for the Ca2+ balance module . This procedure was used to generate 10 , 000 steady state solutions for each module for subsequent reduction by PCA . A minimal set of principal component ( PC ) vectors ( those capturing 90% or more of the variance in the solution set ) were used as search directions in the final estimation step , in which the transient behavior of the perturbed steady-state was compared to experimental time-series data . Interestingly , only a small fraction of initial guesses produce steady-state solutions that are also consistent with known concentration values . For example , it was previously shown that only 50 , 000 of 109 initial guesses ( 0 . 005% ) in the Ca2+ balance module ( Figure 2B ) met both requirements and were suitable for further analysis [28] . Among this set of CVs , marginal distributions for individual molecules were often confined to a narrow range of values . As an example , 80% of steady-state solutions for the calcium module contained <1000 IP3 molecules/cell , although initial guesses were sampled uniformly between 1 and 106 molecules/cell . This observation shows that the kinetic topology of these molecular networks places very strong constraints on the range of concentrations that can exist at steady state . In biological terms , this suggests that fixed kinetic properties at the molecular level ( e . g . , IP3R and SERCA kinetics ) can affect not only the dynamical features of a biochemical system but can also determine the abundance of chemical species and the compartmental structures that contain them . In the final step of the method , the full model is assembled by combining PCA-reduced , steady-state solution spaces from each module into a combined steady-state solution space for the entire system ( Figure 3A ) . This global space is searched for full-length , steady-state solution vectors that satisfy both the individual steady-state requirements of each module and the desired time-dependent properties when the steady-state is perturbed ( for example , by increasing the initial concentration of a signaling molecule ) . For the platelet signaling model , consisting of 77 reactions , 132 fixed kinetic parameters , and 70 species [28] , a set of 16 PC vectors representing all 72 unknown variables ( 70 molecule concentrations , 1 compartment size , and 1 rate constant ) in the model were used as search directions in a global optimization routine . The global solution space was searched for models with accurate dynamic behavior using experimental time-series data for ADP-stimulated Ca2+ release ( Figure 3A ) . Equality constraints are imposed during optimization to maintain consistent concentrations of molecules that are present in more than one module . Specifically , for a steady-state space A represented by m PC vectors and a steady-state space B represented by n PC vectors , the projections of each space onto must be equal , ( 4 ) where is the unit vector for the shared molecule , . This condition forms a linearly-constrained optimization problem for which a number of efficient routines exist [22] . We used the Asynchronous Parallel Pattern Search ( APPSPACK ) to perform a derivative-free optimization of the platelet signaling model [24] . A least-squares objective function was used to score the difference between simulated ( after perturbation of steady state ) and experimental time-series data points . One of the high-scoring steady-state solution vectors for the full model is shown in Figure 3B , along with individual steady-state vectors for each of the four modules . This 72-dimensional vector ( i ) satisfies the homeostasis constraint in that it is a steady-state solution , ( ii ) is consistent with the known steady-state levels for 8 of the molecules in the 72-dimensional space , and ( iii ) predicts the entire dynamic Ca2+ and IP3 response of platelets exposed to ADP ( 0–100 µM ) . Additionally , rigid and flexible nodes ( steady-state concentrations ) in this 72-dimensional space were readily identified when a set of allowable steady-state solution vectors are compared [28] . Resting systems remain in a steady state by the coordinated action of opposing but balanced kinetic processes . Thus , in general , altering one ore more of these rate processes ( e . g . , increasing the catalytic rate of a reaction ) should upset the balance of the system and cause it to adopt a new steady state . Various cell types have been shown to have altered steady-state properties because of mutations that affect the constitutive rates of reactions . For example , patients with type 1 diabetes harbor more Ca2+ ATPase activity in their platelets than healthy volunteers and experience high resting levels of intracellular Ca2+ [34] . In a separate case , a mutation within the tyrosine kinase domain of epidermal growth factor receptor causes significantly higher basal ( growth factor-independent ) tyrosine phosphorylation levels than the wild-type receptor [35] . Therefore , to examine the changes in steady-state properties caused by kinetic perturbations in our example model , we altered the rates of 3 important regulatory reactions and observed the system response to each perturbation . Each perturbation cause a brief adjustment phase lasting ∼200 s followed by a more gradual phase characterized by a new steady-state profile ( Figure 4 , left ) . After 1 hr of simulated time , steady-state concentrations and reaction fluxes were quantified relative to their original steady-state levels ( Figure 4 , right ) . As expected , increasing the rate of Ca2+ release from intracellular stores resulted in higher cytosolic Ca2+ levels ( 7-fold increase ) and 10-fold greater pumping activity by plasma membrane Ca2+ pumps ( PMCA ) , although the new steady-state Ca2+ release flux remained relatively unchanged ( Figure 4A ) . This perturbation also had little effect on the metabolism of phosphoinositides , as indicated by a predominantly green color . In a second perturbation , the inhibition of phospholipase C-β ( PLC-β ) activity by protein kinase C ( PKC ) was reduced 10-fold . Since PKC has a negative-feedback role in suppressing the platelet-stimulating activity of PLC-β , this perturbation caused a 2-fold increase in steady-state phosphatidylinositol 4 , 5-bisphosphate ( PIP2 ) hydrolysis , elevated ( inositol 1 , 4 , 5-trisphosphate ) IP3 concentration , and accelerated Ca2+ release . Interestingly , the same reaction that was initially perturbed with a 10-fold decrease experienced a 10-fold increase in steady-state flux . This was a compensatory effect caused by the negative feedback loop involving Ca2+-regulated activity of PKC , a resulting new hypothesis that can be probed experimentally . In a third example , increasing the hydrolytic activity of PLC-β for the substrate PIP2 by 10-fold caused an expected stimulatory effect , raising intracellular calcium and steady-state levels of cytosolic inositol phosphates ( IP3 , IP2 , and IP ) between 2- and 3-fold . Interestingly , reaction fluxes for phosphoinositide hydrolysis were diminished , possibly due to substrate depletion . Taken together , these examples illustrate the system-wide effects of perturbations in the kinetic rate processes . The procedure could easily be extended to examine multiple simultaneous perturbations in both reaction rates and steady-state concentrations . We have presented a novel strategy for enumerating permissible steady-state solutions to fixed kinetic topologies and combining these solutions spaces to form large kinetic models . This is a practical strategy because kinetic parameters are commonly reported whereas absolute concentrations are not ( see , for example , [6] , [8] , [9] ) . The method extends the capability to build “genome-scale” models [5] , [10] , [11] , [36] to include nonlinear kinetic features . Through application of the method , we have also explored the implicit restrictions on steady-state solutions that can be imposed by the underlying kinetic structures within a system [4] . This is useful from a physiological standpoint since the regulation and distribution of molecular species in living systems is largely regulated by the coordinated action of synthetic , degrading , and transporting enzymes . The proposed method requires the model to fulfill a steady-state assumption ( i . e . , the model must contain nontrivial steady states ) even if the system is typically characterized by transient behavior . It is precisely this requirement that allows the model to have the dual functional behavior observed in many biological contexts , such as in cellular signaling responses . At very low levels of activating signal , the model remains at rest by quenching the low level of activating signal through feedback mechanisms or futile cycling . When activating signals are increased , the system responds with the appropriate transient signaling behavior . As an example , a human platelet must remain quiescent under normal circulating conditions , tolerating a number of fluctuations in its surrounding chemical and physical environment . In the presence of the appropriate stimulus , however , it must be able to respond rapidly to bleeding conditions and trigger a precise program of molecular signaling events . Developing a mathematical model that is consistent with two or more biological behaviors is analogous to writing a set of equations that has multiple solutions , each dependent on a given set of initial conditions and parameter values . Our approach differs critically from metabolic flux analysis and previous genome-scale metabolic network reconstructions [5] , [16] because it accommodates nonlinear terms that describe the dynamic behavior of each reaction in the system . Previous large-scale network reconstructions typically use a stoichiometry matrix to represent the gross flux of metabolites in the system [17] . Here , we have preserved the mathematical form of each kinetic rate equations as reported in the literature , allowing models to be built from existing data in a “bottom-up” fashion [10] while still allowing calibration to whole-system experimental data . This feature will substantially improve the accuracy of dynamical system simulation and parameter estimation . Additional computational savings are provided through modularization . When estimating modules of modest size ( 5 or less unknown concentrations ) , we use a brute-force Monte Carlo approach to densely sample the feasible space of initial conditions . Larger networks ( 20 or more unknowns ) cannot be efficiently searched in this brute-force manner , but can be built piecewise by combining subspaces of smaller size that have been densely sampled . Using the naïve Monte Carlo approach , estimating n free parameters is exponential in n . By dividing these parameters into k independent networks , each with n/k free parameters , the estimation procedure becomes exponential in n/k and thus more tractable . By assembling the entire system from smaller , more manageable kinetic modules , data may be used to test the functionality of individual modules before incorporating them into the entire system . In several cases , this approach was shown to offer a substantial computational benefit ( e . g . , reducing the global search space by over 10 , 000-fold ) by simply requiring a steady-state solution with known subcomponent values . The search space can be reduced further by principal component analysis if there is correlation between free parameters within a module . This was found to be the case for enzymes that have opposing regulatory roles; increasing the levels in one enzyme required a similar increase in the other in order to preserve homeostasis . Lastly , modules sharing common components must hold the same value for that component , which imposes an additional constraint on the steady-state solutions ( equation ( 4 ) ) . As presented , the method exploits known kinetic parameters to restrict unknown concentrations due to kinetic interactions . However , the method is equally valid for estimating unknown kinetic parameters and/or utilizing known concentrations . Both concentrations and kinetic parameters appear indistinguishably as nonlinear terms in the ordinary differential equations that describe the system ( Figure 1B ) . Hence , it does not matter which types of values are known and which are estimated; the procedure is valid for mixed or incomplete sets of unknown values . The use of qualitative data may also be exploited by the method . For example , beginning with a large set of steady-state solutions for a given module , the size of the set may be reduced by determining which solutions in the set contain some qualitative behavior or function . In a previous application of the method [17] , a set of 109 steady-state solutions representing calcium balance in a resting platelet were divided into 3 groups , according to their qualitative response to increased IP3 concentration ( low , mild , and high response ) . Using this technique , the functional testing of steady-state modules may be used to eliminate a large subset of the original steady-state solution set . As another example , one may use data from a Western blot to establish the relative abundance between two proteins in the model . This qualitative information may be used to filter the steady-state solutions to a reduced set that is consistent with experimental results . This kinetically-driven , constraint-based approach , which combines a homeostasis requirement with known kinetic parameters and cellular concentrations , naturally enforces numerical limits on unknown system quantities .
|
Cells respond to extracellular signals through a complex coordination of interacting molecular components . Computational models can serve as powerful tools for prediction and analysis of signaling systems , but constructing large models typically requires extensive experimental datasets and computation . To facilitate the construction of complex signaling models , we present a strategy in which the models are built in a stepwise fashion , beginning with small “resting” networks that are combined to form larger models with complex time-dependent behaviors . Interestingly , we found that only a minor fraction of potential model configurations were compatible with resting behavior in an example signaling system . These reduced sets of configurations were used to limit the search for more complicated solutions that also captured the dynamic behavior of the system . Using an example model constructed by this approach , we show how a cell's resting behavior adjusts to changes in the kinetic rate processes of the system . This strategy offers a general and biologically intuitive framework for building large-scale kinetic models of steady-state cellular systems and their dynamics .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results/Discussion"
] |
[
"computational",
"biology/signaling",
"networks",
"computational",
"biology/systems",
"biology",
"computational",
"biology"
] |
2009
|
Steady-State Kinetic Modeling Constrains Cellular Resting States and Dynamic Behavior
|
Proteases and protease inhibitors have been identified in the ejaculates of animal taxa ranging from invertebrates to mammals and form a major protein class among Drosophila melanogaster seminal fluid proteins ( SFPs ) . Other than a single protease cascade in mammals that regulates seminal clot liquefaction , no proteolytic cascades ( i . e . pathways with at least two proteases acting in sequence ) have been identified in seminal fluids . In Drosophila , SFPs are transferred to females during mating and , together with sperm , are necessary for the many post-mating responses elicited in females . Though several SFPs are proteolytically cleaved either during or after mating , virtually nothing is known about the proteases involved in these cleavage events or the physiological consequences of proteolytic activity in the seminal fluid on the female . Here , we present evidence that a protease cascade acts in the seminal fluid of Drosophila during and after mating . Using RNAi to knock down expression of the SFP CG10586 , a predicted serine protease , we show that it acts upstream of the SFP CG11864 , a predicted astacin protease , to process SFPs involved in ovulation and sperm entry into storage . We also show that knockdown of CG10586 leads to lower levels of egg laying , higher rates of sexual receptivity to subsequent males , and abnormal sperm usage patterns , processes that are independent of CG11864 . The long-term phenotypes of females mated to CG10586 knockdown males are similar to those of females that fail to store sex peptide , an important elicitor of long-term post-mating responses , and indicate a role for CG10586 in regulating sex peptide . These results point to an important role for proteolysis among insect SFPs and suggest that protease cascades may be a mechanism for precise temporal regulation of multiple post-mating responses in females .
Proteolysis regulators are a component of the seminal fluid of many animal taxa , including insects and other invertebrates [1]–[7] , fish [8]–[10] , birds [11] , [12] , and mammals [13]–[18] . However , the mechanisms by which seminal proteases act , and most of the processes they affect , in mated females are poorly understood . A mechanism by which proteases may effect physiological responses is through proteolytic cascades . Because most proteases are synthesized as inactive zymogens and require the removal of a short N-terminal sequence for activation [19] , a protease cascade can be rapidly set in motion without new protein synthesis . For example , in mammals a seminal protease cascade activates the protease prostate specific antigen ( PSA ) , in order to rapidly liquefy the seminal clot formed following ejaculation ( reviewed in [15] ) . The action of PSA is regulated , in part , by the protease inhibitor PCI ( reviewed in [20] ) , which controls the timing and extent of liquefaction . Seminal clots are an important feature of the post-mating response in many animals [13] , [21] , [22] . Given the prevalence of proteolysis regulators in seminal fluid , it seems likely that they are involved in other processes whose effects may extend past the first few minutes after mating . The study of seminal fluid protease functions would benefit greatly from a genetic approach . Drosophila melanogaster provides an excellent system in which to study the roles of seminal fluid proteolytic proteins . Analysis of Drosophila seminal fluid proteins ( SFPs ) capitalizes on a wide range of available genetic tools , physiological and behavioral assays , and both a well-annotated genome and seminal fluid proteome . In addition , though individual SFPs , including proteases [23] , are not generally well-conserved between distant taxa [24] , [25] , the biochemical classes into which SFPs fall are conserved between insects and mammals [21] , [26] , suggesting that mechanisms of action are likely to be conserved as well . Approximately 18% of the proteins in the Drosophila ejaculate have been identified as predicted proteases or protease inhibitors [2] , [27] . Mass spectrometry-based estimates indicate that the abundance of individual proteolysis regulators varies , with some being the most abundant proteins in the ejaculate ( e . g . Acp62F ) and others being the least abundant ( e . g . CG10587 ) [2] . Most SFP predicted proteolysis regulators are either serine proteases or serine protease inhibitors with unknown functions [2] , [28] , [29] , though a few other protease classes have also been identified [26] , [30]–[32] . Proteolysis regulators have been identified as expressed in male reproductive tract tissues of Tribolium [7] and directly in the ejaculates of honey bees [3] and mosquitoes [33] . In crickets , a predicted trypsin-like serine protease in the ejaculate is important for inducing egg laying in mated females [5] . In the nematode Caenorhabditis elegans , a trypsin SFP has recently been reported to function in activation of male sperm [10] . Though proteases are emerging as a common SFP class in animals , there have been no studies determining whether protease cascades ( i . e . proteolytic pathways that require at least two proteases in sequence ) are a common regulatory mechanism for seminal fluid-mediated post-mating traits . In Drosophila , transfer of SFPs from male to female during mating induces physiological changes in mated females [reviewed in 6] . Two of these changes are increased egg production and reduced receptivity to remating . These changes occur in two phases: short-term and long-term , both of which are necessary for optimal fertility . The short-term response ( STR ) occurs within 24 hours of mating and is solely dependent on the receipt of SFPs [34] , including the prohormone ovulin [35] , CG33943 [36] , the sperm storage protein Acp36DE [37] , [38] , and the action of free sex peptide ( SP ) that is not bound to sperm [39] , [40] . Long-term persistence of post-mating changes ( the long-term response , or LTR ) requires SP and multiple other SFPs , and the presence of sperm in storage [40] . SP binds to sperm during mating . Cleavage by an unknown trypsin protease ( s ) is required to release the active portion of SP from sperm within the mated female [41] . SP is gradually cleaved from stored sperm during the approximately two weeks that they remain in storage . As long as SP is released into the female , she continues to lay eggs at a high rate and is more likely to reject courting males [41] . If SP cannot be released from sperm , the LTR does not occur [41] . Fertility defects arise if SP cannot bind to sperm in the mated female , or if it cannot be released from sperm . Sperm binding by SP requires the action of at least four other SFPs: the predicted serine protease CG9997 , the Cysteine Rich Secretory Protein ( CRISP ) CG17575 , and the gene duplicate pair lectins CG1652 and CG1656 [36] , [42] . These four “LTR proteins” , together with SP , function in an interdependent network to bind SP to sperm as well as to localize each other to the seminal receptacle ( SR ) , the major sperm storage organ of the female [42] . In this network , CG9997 is cleaved into a 36-kDa protein in the male ejaculatory duct/bulb , prior to transfer to the female and is required for the normal transfer of CG1652 and CG1656 . CG17575 is required to localize CG1652 and CG1656 to sperm and the SR . This final step is then required for SP to bind sperm and accumulate in the SR . If any one of the four LTR proteins is absent , SP does not bind sperm . These SP-free sperm are still stored in normal numbers , but cannot be efficiently released from storage for fertilization past the first 24 hours after mating [42] , because SP is also required for sperm release [43] . In addition to SP , two SFPs involved in post-mating traits are known to be cleaved following deposition into the female . The prohormone ovulin is initially cleaved at about 10 minutes after the start of mating ( ASM ) [44] . Ovulin is required for a maximal ovulation rate in the first 24 hours following mating [35] , [45] . Processing occurs via three cleavage events from the N-terminus of ovulin that ultimately results in the production of one major cleavage product ( approx . 25 kDa ) and three minor products ( each 5 kDa or smaller ) [44] . Ectopic expression experiments have shown that both full-length ovulin as well as two C-terminal fragments , roughly corresponding to cleavage products of ovulin , are each able to independently induce ovulation in virgin females [46] . The glycoprotein Acp36DE is also cleaved within mated females [47] , starting at approximately 20 minutes ASM , as detected by Western blot [47] , [48] . Acp36DE is required for efficient sperm storage [37] , [48] . This protein is responsible for the conformational changes of the uterus immediately following the start of copulation , which are thought to aid the movement of sperm into the storage organs [38] , [49] . A previous study of 11 SFP proteases and protease inhibitors identified CG11864 as required for processing of both ovulin and Acp36DE [32] . Though all three proteins are produced in the male accessory glands , ovulin and Acp36DE are not cleaved until several minutes after their entry into the female reproductive tract . Therefore , three possibilities exist for the regulation of ovulin and Acp36DE cleavage . CG11864 may be activated during mating , a repressor of CG11864 activity may be removed during mating , or a combination of both may occur . CG11864 is predicted to be a member of the astacin family of metalloproteases , based on sequence similarity [32] . Astacin family proteases , like many other proteases , require removal of an N-terminal pro-peptide for activation [50] . The activity of CG11864 thus may be regulated in a similar manner . CG11864 is produced in the male accessory glands as a 33-kDa protein and is cleaved to an approximately 30-kDa form [32] . This cleavage begins in the male reproductive tract , in the ejaculatory duct and/or bulb , while CG11864 is in transit to the female during mating [32] . The size of the cleaved form of CG11864 is consistent with removal of a predicted pro-peptide from the N-terminus . We hypothesize that cleavage of CG11864 is required for its activation . If this is the case , there should be factors produced by the male that regulate the activation of CG11864 . However , the previous study involving 11 SFP proteolysis regulators did not suggest their requirement for the regulation of CG11864 [32] . A recent microarray analysis by Chintapalli et al . [51] and subsequent proteomic studies by Findlay et al . [2] identified additional serine proteases in the ejaculate . We , therefore , focused on these proteases to test for roles in the activation/regulation of seminal proteolysis . Here , we used RNAi knockdown analysis to test five male-derived serine proteases for roles in ovulin cleavage and other reproductive events . We describe the first proteolytic cascade in fly seminal fluid that is regulated by a predicted trypsin-like serine protease , CG10586 . We propose to rename this enzyme seminase ( gene symbol: sems ) . Seminase is required for cleavage , and likely activation , of CG11864 . Like CG11864 , seminase is produced in the accessory glands and is cleaved in the male during copulation . We show that CG11864 is not able to undergo self-cleavage in the absence of seminase . In addition to regulating CG11864 and thus its downstream SFP substrates , we show that seminase is a member of the LTR network , a CG11864-independent pathway that results in SP binding to sperm .
We tested five predicted protease SFPs for ovulin processing defects via Western blot to identify potential CG11864-interacting proteins . The tested SFPs were the predicted serine proteases ‘seminase’ ( CG10586 ) , CG10587 , CG4815 , CG12558 , and CG32382 ( sphinx2 ) . Of these , only seminase , a predicted trypsin-type serine protease , was required for ovulin processing ( Figure 1A ) . In addition to the results for seminase , we show for comparison the results for CG10587 , which did not affect ovulin processing . The data for the other SFPs tested are not shown . Two independent insertion lines of the same RNAi construct were used to test the phenotype of seminase knockdown ( see Materials and Methods ) ; we obtained similar results with both lines . Western blotting confirmed that seminase is knocked down at least 98% by Tubulin-Gal4 driven expression of the RNAi construct in males of both lines ( Figure S1A ) . Transcript levels of seminase were also confirmed to be knocked down by RT-PCR ( Figure S1B ) . Similar to the phenotype previously observed with CG11864 RNAi [32] , some ovulin processing was observed in females mated to males knocked down for seminase , but ovulin was never processed fully in mates of seminase knockdown males , even at 2 hours ASM , the latest time at which ovulin can be reliably detected in female reproductive tracts when mated to controls ( Figure 1A ) . Females mated to seminase knockdown males also failed to fully process Acp36DE at 1 hour ASM ( Figure 1C ) , similar to CG11864 knockdown mates ( Figure 1C ) . Even at 3 hours ASM , Acp36DE in females mated to seminase or CG11864 RNAi males had undergone only a small amount of processing relative to controls ( Figure 1C ) . Females mated to seminase RNAi knockdown males received CG11864 protein , but it was of the full-length molecular weight ( 33-kDa ) ; the cleaved form ( 30-kDa ) was never observed ( Figure 1D ) . However , females who mated to control males received both full-length and cleaved CG11864 ( Figure 1D ) . Thus , seminase is required for the predicted pro-peptide cleavage of CG11864 during mating . Since many serine proteases are synthesized as zymogens ( containing an N-terminal sequence that must be removed for activation ) , we tested whether seminase was also processed during or after mating . Seminase is detected as an apparent 29-kDa protein ( predicted size: 28 . 2-kDa , excluding a predicted N-term secretion signal sequence ) in the accessory glands , with no detectable expression in the testes or ejaculatory duct and bulb ( Figure 2A ) . There was no evidence for seminase expression outside of the male accessory glands based on expression data in the FlyAtlas database [51] and our own RT-PCR ( Figure S1B ) . We did not detect seminase protein in virgin females ( Figure 2A ) . During mating , an additional , lower molecular weight band ( approximately 27-kDa ) of seminase appeared in the male ejaculatory duct and/or bulb ( Figure 2B ) , consistent with removal of a 2 . 79-kDa pro-peptide ( size prediction based on an NCBI conserved domain search at http://www . ncbi . nlm . nih . gov/Structure/cdd/wrpsb . cgi ? INPUT_TYPE=live&SEQUENCE=NP_649270 . 1 ) . Within the mated female , seminase was further cleaved , producing a ∼16-kDa product ( visible in top panel of Figure 1C ) and increasing the amount of the ∼12-kDa product ( Figure 2B ) . We first detected the ∼12-kDa product in the female at around 15 minutes ASM . However , due to the difficulty in detecting the ∼16-kDa form , we could not determine at what time ASM it is first produced . Given that some proteases can be cleaved by their own proteolytic substrates [for example , see 52] , we tested whether knockdown of CG11864 affected processing of seminase after mating . Females mated to CG11864 knockdown males showed normal processing of seminase at 30 minutes ASM ( Figure 2C , top panel ) . As expected [32] , CG11864 knockdown does prevent ovulin cleavage ( Figure 2C , bottom panel ) , indicating a unidirectional proteolytic pathway . The total number of eggs laid over 10 days was significantly lower in females mated to seminase knockdown males relative to their controls , and this was seen in both independent insertion lines ( Line 1 Poisson regression: z = −29 . 56 , p<0 . 0001 , Figure 3A; Line 2 Poisson regression: z = −31 . 59 , p<0 . 0001 , Figure S1A ) . There was no difference in total number of eggs laid between females mated to CG4815 knockdown and control males ( CG4815 Poisson regression: z = −0 . 79 , p = 0 . 43 , Figure 3A ) . Eggs laid by seminase or CG4815 knockdown mates hatched in significantly larger proportions than eggs laid by control mates ( Binomial regressions: Line 1: z = 10 . 1 , p<0 . 001 and CG4815: z = 5 . 8 , p<0 . 0001 , Figure 3B; Line 2: z = 13 . 2 , p<0 . 0001 , Figure S1B ) , suggesting the egg laying defect was not accompanied by a hatchability defect ( hatchability is defined as the proportion of eggs that produced adult progeny ) , but rather that there was a slight deleterious effect of the balancer control background on hatchability . A repeated measures analysis of egg laying over time revealed a significant effect of male genotype on egg laying over time for both seminase lines and CG4815 ( see Materials and Methods ) . To determine the days on which male genotype affected egg laying , data were analyzed separately for each individual day . The decrease in egg laying , relative to control , in mates of seminase knockdown males was only apparent after the first day following mating and persisted until at least 9 days post-mating ( Figure 3C and Figure S1C ) . Females mated to seminase knockdown males laid slightly , though significantly , more eggs than females mated to control males on day 1 , but only with seminase Line 1 males ( Figure 3C ) . These results indicated that seminase only has a major role in egg laying after the first day post-mating . Females mated to CG4815 knockdown males laid significantly fewer eggs than females mated to control males on day 1 and slightly , though significantly , more eggs than controls on day 9 ( Figure 3D ) . Thus , CG4815 may have a short-term effect on egg laying , but no long-term effect similar to that observed with seminase knockdown mates . These results also indicate that the long-term egg laying effect of seminase is not an artifact of the VDRC strain background , which is shared by the CG4815 males . A reduction in fecundity after the second day post-mating suggests seminase is a new member of the LTR pathway . Increased recovery of post-mating receptivity to courtship beginning after the first 24 hours post-mating is also associated with LTR defects . Therefore , we tested whether deficiency of seminase in the ejaculate also caused increased receptivity in females , relative to controls , after mating . Table 1 shows data for female receptivity at 24 hours , 2 days , and 4 days ASM to seminase knockdown or control males . Similar to previously described phenotypes of LTR SFPs [36] , [42] , [43] , females mated to seminase knockdown males were significantly more likely to remate at 2 days and 4 days ASM than were controls . Females mated to males from seminase knockdown line 1 showed a smaller magnitude of difference in remating rate relative to their controls than did line 2 . This is most likely due to a background effect in line 1 that is apparent in the control males , as the remating rate is similar in mates to knockdown males from both lines . Since the same RNAi construct is expressed in both lines , we assume that the higher remating rate for females mated to line 1 control males is due to the insertion locus of the transgene . There was no effect of CG4815 knockdown on receptivity ( Table 1 ) . In Drosophila females , sperm are stored in two types of storage organs: the seminal receptacle ( SR ) and the paired spermathecae . The bulk of the sperm are stored in the SR [53] . Because LTR SFPs ( in concert with SP ) affect the release of sperm from storage [36] , [43] , we tested whether mates of seminase knockdown males also showed a defect in sperm release . Mates to seminase knockdown males stored normal numbers of sperm ( Figure 4 “2 h” bars ) , but significantly more sperm remained in storage at 10 days ASM in mates of seminase knockdown males than in control-mated females ( Figure 4A ) . This effect was due to a failure to release sperm from the SR ( Figure 4B ) , as sperm numbers in the spermathecae decreased at similar rates in females mated both to control and seminase knockdown males ( Figure 4C ) . A slight , but significant , difference in sperm release was seen in the spermathecae at 4 days ASM , but this effect was in the opposite direction from that seen in the SR and was no longer apparent by 10 days ASM ( Figure 4C ) . Similar effects were seen with seminase knockdown Line 2 ( Figure S1D ) . The results above are consistent with seminase being a member of the LTR network . To determine the placement of seminase in this network , we tested whether knockdown of seminase affected the post-mating localization of SP and the three LTR proteins that localize to the SR: CG9997 , CG1652 , and CG1656 . At 2 hours ASM , seminase was required for accumulation of SP , CG1652 , and CG1656 in the SR ( Figure 5A ) . CG9997 was not detected in the SR at 2 hours ASM , so we tested females at 1 hour ASM . Seminase was also required for accumulation of CG9997 in the SR at this time point ( Figure 5A ) . However , seminase was not required for proper processing of CG9997 or transfer of any LTR SFPs to the female during mating ( Figure 5A , RT lanes ) , including CG17575 ( Figure 5B ) . A small amount of seminase also enters the SR ( Figure 5C ) , suggesting that it could physically interact with other LTR proteins there . However , we were unable to determine whether other LTR proteins affected seminase localization to the SR due to the extremely low seminase signal within the SR . Multiple repetitions of the experiment failed to yield consistent results . As with previous efforts to detect LTR proteins in the spermathecae [42] , we were not able to detect seminase in these organs ( data not shown ) .
To identify proteins that may interact with the predicted astacin-family protease CG11864 to process the SFPs ovulin and Acp36DE , we used RNAi to individually test five serine protease SFPs for ovulin processing defects . One of these proteins , the predicted trypsin-type serine protease ‘seminase’ ( CG10586 ) , is required for normal processing of ovulin as well as of the sperm storage protein Acp36DE . Because the phenotype of seminase knockdown was similar to that of CG11864 knockdown with respect to SFP processing , we hypothesized that both proteins might act in a single pathway . Additionally , because trypsin ( serine ) proteases are required for activational cleavage of some astacin-family proteases ( of which CG11864 is one ) [50] , [54] , we further hypothesized that seminase might act upstream of CG11864 . We therefore tested whether seminase regulates the cleavage , and thus activation , of CG11864 . We found that seminase is required for the approximately 3-kDa mobility shift of CG11864 that is seen in the male reproductive tract very soon after mating begins , suggesting that seminase may activate CG11864 by cleaving its pro-peptide . The apparent processing of pro-CG11864 by seminase and the subsequent processing of downstream substrates is suggestive of a proteolytic cascade . No such proteolytic pathway has , to our knowledge , previously been identified in insect seminal fluid . With the identification of this pathway in Drosophila melanogaster , we have found a molecular model for dissecting proteolytic pathways involving SFPs that have consequences for fertility . Proteolytic cascades , in their simplest form , typically have three steps [55]: 1 ) auto-activation of an initiator protease ( s ) present in low amounts and triggered by an external stimulus: 2 ) activation of a more abundant propagator protease ( s ) by the initiator protease; 3 ) activation of an executor protease ( s ) by the propagator , which will cleave the downstream substrates . In addition , the propagator may also cleave , and thereby continue to activate , the initiator . Altogether , this causes a rapid propagation of the initial external signal . While protein abundance is not necessarily related to potency , it is intriguing that seminase ( the putative initiator ) is relatively scarce in the ejaculate of D . melanogaster , which is consistent with the above model . Abundance estimates are based on the normalized spectral abundance factor ( NSAF ) obtained by mass spectrometry on mated females [2] . NSAF is an approximate measure of the relative abundance of a protein in a complex sample . Seminase ranks at 130 out of 138 ( NSAF = 1 . 34×10−4 ) , with 1 being the most abundant and 138 the least [2] . CG11864 is similarly scarce ( 87/138; NSAF = 7 . 69×10×−4 ) . This is in contrast to the much higher abundance of CG11864's substrates ( ovulin: 20/138 , NSAF = 1 . 2×10−2; Acp36DE: 19/138 , NSAF = 1 . 21×10−2 ) . Also consistent with the protease cascade model , seminase is cleaved to a slightly smaller form during mating while still in the male reproductive tract . This may be an activational pro-peptide cleavage event , though this has not been directly tested . It is possible that seminase self-activates upon entering the ejaculatory duct , as is the case for many serine proteases [for example , among tissue kallikrein pathways; see 15] . Our data suggest that seminase acts as the initiator in the cascade , and CG11864 acts either as the propagator , the executor , or both . After transfer , seminase itself undergoes additional processing in the female ( after the initial pro-peptide cleavage in the male ) that is not a result of CG11864 activity ( Figure 2C ) . These cleavage products may be important for the function of seminase . On the other hand , they may simply be degradation products of seminase . However , both scenarios remain speculative . We have shown that , in the absence of seminase , CG11864 is not cleaved to the predicted active form . However , the predicted pro-peptide cleavage site of CG11864 , based on sequence threading to other astacin-family proteases [32] , is not a trypsin site , as would be predicted if seminase were the only protease responsible for CG11864 activation . Interestingly , there are three trypsin cleavage sites present in the pro-peptide region of CG11864 . It is possible that CG11864 is cleaved via a two-step mechanism ( involving a trypsin and CG11864 itself ) , as is seen for the pro-peptide cleavage of Astacus astacus ( crayfish ) astacin , the prototype of the astacin family [54] , [56] . Future studies using purified proteins in vitro will determine whether CG11864 is capable of self-cleavage and whether seminase acts to directly cleave CG11864 . Despite a severe delay in ovulin processing , knockdown of neither seminase nor CG11864 results in an egg laying defect in the first 24 hours after mating [CG11864 data reported in 32] . This result is not surprising , however , given the rather small effect on egg laying seen with a complete knockout of ovulin [45] . Additionally , ectopic expression of full-length ovulin is sufficient to induce ovulation in virgin females [46] , suggesting that the additional effect of ovulin processing may be too small to detect with the current assay . It is also possible that , while seminase was knocked down to very low levels , there may still be sufficient seminase present for its role in early egg laying . We also do not observe a defect in sperm entry into storage following seminase knockdown , as seen with knockout of Acp36DE [37] . Instead , defects were seen in sperm release from storage at later timepoints , which is not a phenotype associated with Acp36DE knockout . Acp36DE processing may be important for other functions of this protein . For example , Acp36DE is a component of the mating plug [57] , but its function in the mating plug is still unknown . Further research is required to determine the consequences of loss of proteolytic processing of both ovulin and Acp36DE . In contrast to CG11864 , which seems specific to the STR , seminase has a second important activity: it is in the LTR pathway , which regulates the binding of sex peptide ( SP ) to sperm [36] , [41]–[43] ( See Figure 6 for overview ) . Similar to mates of SP null males , females mated to seminase knockdown males lay fewer eggs than controls over a 10 day period and also retain sperm in storage . The sperm retention phenotype is only apparent in the SR . Other LTR proteins are also known to affect sperm storage in the SR but not the spermathecae [36] , though the reason for these differences is not understood . While the interaction between sperm release and egg laying is complex , over the long-term , egg laying and sperm release are independent of each other [58] . Sperm do not directly influence the release of eggs , though the presence of SP bound to sperm is required for both sperm release [43] and normal post-mating levels of egg laying [39] , [40] . The failure of SP to accumulate in the SR indicates that seminase is likely required for SP to bind sperm . The requirement for seminase in two independent post-mating pathways suggests that its activation at mating may act as a regulatory “switch” that coordinates post-mating events in Drosophila . Identification of other seminase substrates , if they exist , will allow us to determine the extent of seminase's effects as a regulatory switch for post-mating events . In the context of evolution , SFPs represent a unique class of proteins in that they must , first and foremost , aid in successful fertilization , but are also tasked with representing the male's reproductive interests , sometimes in the face of opposing female interests [reviewed in 59] . This has the potential to set up a genetic conflict between the sexes and has been suggested to be one reason that SFPs in particular tend to be rapidly evolving [24] , [25] . However , an SFP's evolutionary rate is also likely to be constrained by the need for the protein to maintain its interaction with other proteins in the seminal fluid , and/or with proteins expressed by the female . For example , seminase and CG11864 are processed first in the male , but must interact with the female environment to further process both seminase and the substrates of the proteolytic pathway . Seminase-regulated processes represent an opportunity to understand the evolution of SFP networks that contain a mixture of conserved proteins ( e . g . the lectins CG1652 and CG1656 and the CRISP CG17575 [2] ) and proteins under positive selection ( e . g . ovulin [60] and the serine protease CG9997 [61] ) . Seminase itself shows no evidence of positive selection , either at the protein level [61] or at individual sites ( personal communication , Geoff Findlay ) . However , seminase does have two very closely related SFP paralogs , CG11037 and CG10587 , which show evidence for recent positive selection in the D . melanogaster lineage [61] . These three genes are clustered together in the genome of D . melanogaster and the other melanogaster subgroup species . CG10587 does not play a role in ovulin or Acp36DE processing ( CG11037 has yet to be tested ) , suggesting that these genes arose from tandem duplications and later diverged in function , with seminase remaining as the more conserved of the paralogs . Our data on seminase show that this member of a conserved protein class in the seminal fluid plays a vital role in reproductive success . We believe that future study of the seminase-regulated pathways in Drosophila will lead to new mechanistic and evolutionary insights related to proteolytic cascades and protein networks in seminal fluid . The regulation and mechanism of action of seminase constitutes a new in vivo model system for studying the regulation and physiological roles of pleiotropic SFPs . Pleiotropic effects of kallikrein-related proteases involved in the liquefaction of human semen have recently been reported [62] , [63] . Further understanding of the various effects of seminal fluid proteolysis in post-mating processes may have important implications for human health ( e . g . the role of PSA in cancer ) and fertility . Our results indicate that genetic analysis in Drosophila will be an important complement to in vitro studies in mammalian systems for understanding the role of proteolytic processing in reproduction . Future studies of the regulatory mechanisms involved in the seminase/CG11864 proteolytic pathway may generate testable hypotheses for other SFP networks , including those in mammals .
Transgenic lines carrying RNAi constructs for CG10586 ( ‘seminase’ ) and CG4815 were purchased from the Vienna Drosophila Resource Center ( VDRC , http://stockcenter . vdrc . at ) GD RNAi library ( P element library ) . VDRC lines used correspond to the following transformant ID numbers: 18795 , 18796 ( CG10586; same construct ( ID 5539 ) , different insertions ) , and 15410 ( CG4815 ) . CG10586-18795 is referred to here as “Line 1” and CG10586-18796 as “Line 2” . CG10586 VDRC lines are predicted to have an off-target , CG33306 . However , we found no evidence for CG33306 knockdown in either line ( Figure S2B , only Line 1 shown ) . All RNAi knockdown and control sibling flies were produced by crossing sympUAST-SFP or VDRC virgin females to ubiquitous driver males ( Tubulin-Gal4/ TM3 ) . UAS-RNAi / Tubulin-Gal4 ( non-balancer ) male progeny were knocked down for the SFP of interest and the sibling UAS-RNAi/TM3 ( balancer ) flies were used as controls that are wildtype for seminase expression . Matings were carried out by placing single 3–6 day old virgin females of the Canton-S strain with a single 3–6 day old virgin male in a glass vial containing a moistened square of filter paper . Matings were observed and the time at which mating began was recorded . Mating pairs with unusually short matings ( <15 minutes ) were discarded . Mated females were flash frozen in liquid nitrogen at the appropriate time after the start of mating ( ASM ) for time points less than one hour ASM and stored at −80°C until dissection . All flies were reared in standard yeast-glucose media at room temperature ( 23±1°C ) on a 12∶12 light/dark cycle . Generation of seminase fusion proteins and antibody purification was done following Ravi Ram et al . [64] and Cui et al . [65] . Briefly , we generated a 6×His fusion protein containing amino acids 101–200 from seminase-PA using the pDEST17 vector of the Gateway system ( Invitrogen ) . Antibodies were generated in rabbits ( Cocalico ) as described previously for eight other Drosophila reproductive proteins , including CG11864 [64] , and Wisp [65] except that rabbits were immunized with the 6×His-seminase fusion protein . Anti-seminase was affinity purified with a GST fusion protein of amino acids 101–200 of seminase , as described in the above references . Eluted antibodies were stored at −20°C in glycerol ( 1∶1 ) , and used at a concentration of 1∶250 for Western blot analysis . Sample preparation and Western blot analyses in Figure 1A and Figure 5A and 5B were carried out as in Ravi Ram and Wolfner [42] . Samples in other Westerns in this study were prepared similarly , except that they were separated using 5–15% gradient SDS/PAGE . Female reproductive tract samples ( RT ) are lower reproductive tract extracts ( ovaries removed ) from 4–6 mated females , unless otherwise noted . A BCA ( bicinchoninic acid ) assay ( Pierce BCA Protein Assay Kit , Thermo Scientific ) was performed to determine the protein loading in Figure 1A . Samples identical to those used for the Western blot were prepared and protein concentration measured relative to a BSA standard , following the manufacturer's guidelines . Number of eggs laid daily by mated females ( fecundity ) and number of progeny produced from those eggs ( fertility ) were quantified as in Ravi Ram and Wolfner [36] . Assays for the effect of seminase on fecundity and fertility were carried out three times for each independent insertion line , each time with 15–24 females measured for both knock down and control treatments . CG4815 knock down- and control-mated females were also measured for both fertility and fecundity , as a control for the VDRC background . Two assays were carried out with this line , each time with 7–12 females measured for each treatment . Hatchability was determined by dividing number of progeny by number of eggs ( fertility/fecundity ) [36] . Inspection of the data revealed non-significant variation in egg laying due to experimental block , so data were pooled across blocks . The effect of seminase or CG4815 knockdown on total 10-day egg laying was tested with a Poisson regression model ( using the R function ‘glm ( ) ’ . The statistical tests for hatchability were the same , except a Binomial regression was used . A repeated measures analysis was performed to determine the effect of male genotype over time . This analysis was performed using a Poisson mixed-effects model with the R function ‘lmer ( ) ’ in the lme4 library . Two models were compared , a full model with day , genotype , and day-by-genotype interaction as fixed effects and female as the random effect , and a model with day as the only fixed effect . Comparison of the two models by ANOVA ( R function ‘anova ( ) ’ ) revealed the full model was the better fit , indicating a significant effect of male genotype . To determine the statistical significance of male treatment on individual days post-mating , a Bonferroni correction for multiple tests was applied to the Poisson regressions . All plots were generated using the means and standard errors of the raw data pooled from all experiments . Statistical significance of the effect of male genotype on number of eggs laid is denoted by asterisks on the plots . Females who had previously mated with either control or seminase knockdown males were placed with a single wildtype male of the Canton-S strain for one hour either 24 hours , 2 days , or 4 days following the initial mating and the number of copulations beginning within one hour was recorded . Receptivity response to remating was tested for seminase as in Ravi Ram and Wolfner [36] . No fewer than 10 females were analyzed for control and experimental groups at 24 hours , 2 days , or 4 days after initial mating . Data were analyzed using a Chi-squared test ( R function ‘chisq . test ( ) ’ with all parameters set to default ) . Sperm counts were performed as in Avila , et al . [43] at 2 h ASM , 4 days , and 10 days ASM . Sample identity was coded to avoid bias and each slide was counted twice to assess counting precision ( 85%–100% ) . SR data used are the average of the two counts . Spermathecae data are the sum of the two averages ( one for each spermatheca ) . For 4 and 10 day post-mating samples , individual female daily egg counts were also taken . Numbers of stored sperm at 4 and 10 days ASM were significantly negatively correlated with the number of eggs laid ( Figure S2 ) . Females that laid very few eggs on day 1 ( less than 2 standard deviations below the mean ) were removed from the dataset as they were likely unhealthy and may have had improper sperm storage . Data were analyzed using a two-tailed Student's t-test ( R function ‘t . test ( ) ’ ) .
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Proteases can destroy , activate , or otherwise modulate the function of other proteins . In seminal fluid , many proteins have to be activated or degraded after mating; proteolysis is an effective way to accomplish this because seminal fluid proteins act outside of the cell , where most other regulatory processes cannot be used . Despite the presence of proteases in the seminal fluid of many animals , nearly nothing is known about the kinds of processes they regulate . Here , we present evidence of a protease cascade in the seminal fluid of the fruit fly Drosophila melanogaster . This cascade involves two proteases that are activated during mating . Once in the female , the downstream protease acts on two other proteins that are important for ovulation and sperm storage . Interestingly , the protease at the top of the cascade , CG10586 , is also required for other female post-mating responses , including egg laying and sperm usage , independent of the second protease . Thus , CG10586 might be a general regulatory switch used by the male to quickly activate many female responses after mating .
|
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2012
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The Drosophila melanogaster Seminal Fluid Protease “Seminase” Regulates Proteolytic and Post-Mating Reproductive Processes
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Spores are the major transmissive form of the nosocomial pathogen Clostridium difficile , a leading cause of healthcare-associated diarrhea worldwide . Successful transmission of C . difficile requires that its hardy , resistant spores germinate into vegetative cells in the gastrointestinal tract . A critical step during this process is the degradation of the spore cortex , a thick layer of peptidoglycan surrounding the spore core . In Clostridium sp . , cortex degradation depends on the proteolytic activation of the cortex hydrolase , SleC . Previous studies have implicated Csps as being necessary for SleC cleavage during germination; however , their mechanism of action has remained poorly characterized . In this study , we demonstrate that CspB is a subtilisin-like serine protease whose activity is essential for efficient SleC cleavage and C . difficile spore germination . By solving the first crystal structure of a Csp family member , CspB , to 1 . 6 Å , we identify key structural domains within CspB . In contrast with all previously solved structures of prokaryotic subtilases , the CspB prodomain remains tightly bound to the wildtype subtilase domain and sterically occludes a catalytically competent active site . The structure , combined with biochemical and genetic analyses , reveals that Csp proteases contain a unique jellyroll domain insertion critical for stabilizing the protease in vitro and in C . difficile . Collectively , our study provides the first molecular insight into CspB activity and function . These studies may inform the development of inhibitors that can prevent clostridial spore germination and thus disease transmission .
The Gram-positive , spore-forming obligate anaerobe Clostridium difficile is the leading cause of nosocomial diarrhea worldwide [1]–[3] . The symptoms of C . difficile-associated disease ( CDAD ) range from mild diarrhea to pseudomembranous colitis and even death . Although CDAD is primarily a toxin-mediated disease [3] , [4] , the high cost and difficulty in treating C . difficile infections largely arises from its ability to form endospores [5] , [6] . Because spores are metabolically dormant and intrinsically resistant to harsh physical insults [3] , [7]–[9] , they allow C . difficile to resist antibiotic treatment and persist in healthcare-associated settings . Thus , spores are the primary vectors for transmission [10] and the cause of recurrent infections , the latter of which occurs in ∼25% of cases and can lead to severe CDAD [6] , [11] . In order to initiate an infection , C . difficile spores ingested from the environment must germinate into toxin-producing vegetative cells in the intestinal tract [1] , [3] , [12] . Similar to other spore-forming bacteria , C . difficile spores germinate specifically in response to small molecules known as germinants [13] , [14] . For C . difficile , these germinants are bile salts , which are abundant in the small intestine [15]–[17] . While germinants have been identified for a number of bacterial species , the molecular events that occur upon germinant sensing remain poorly characterized [13] , [14] , [18] . Shortly after germinant addition , cortex hydrolases become activated and degrade the spore cortex , a thick protective layer of modified peptidoglycan . Because the cortex maintains the spore in a dehydrated , metabolically dormant state , the removal of this physical constraint is essential for germination to proceed and metabolism to resume in the spore core [13] , [14] , [18] . Nevertheless , despite the importance of cortex hydrolysis , little is known about the molecular mechanisms that regulate cortex hydrolase activity . In the Clostridia , the primary cortex hydrolase appears to be SleC , since disruption of sleC in both C . difficile [19] and the related foodborne pathogen C . perfringens [20] results in a severe germination defect . In C . perfringens , SleC undergoes several processing events . During sporulation , the N-terminal prepeptide is removed to produce pro-SleC , which consists of an N-terminal propeptide attached to the hydrolase domain [21]–[24] . During germination , the zymogen pro-SleC is cleaved at a conserved site to release the propeptide ( Figure 1A ) ; this event appears to activate its hydrolase activity [22] , [25] . Biochemical analyses of C . perfringens germination exudates have shown that a fraction containing three serine proteases ( CspA , CspB , and CspC ) can proteolytically activate SleC hydrolase activity in vitro [25] . CspB alone appears sufficient to activate SleC , since the food-poisoning isolate SM101 encodes only the cspB gene , and disruption of this gene abrogates SleC cleavage and spore germination [26] . In the genome of C . difficile , three csp homologs are present in a bicistronic operon ( cspBA-cspC , Figure S1 ) , with cspB and cspA being present as a gene fusion [13] . Since disruption of the cspBA-cspC operon by transposon insertion results in a severe germination defect [27] , cortex hydrolysis in C . difficile and C . perfringens would appear to be similarly regulated . While studies have shown that SleC and CspB are key players during germination , the molecular mechanisms regulating their function are unknown . The sequence homology between Csp proteases ( Csps ) and the subtilase protease family [25] provides a starting point for understanding how Csps transduce the germination signal and activate SleC . Subtilases are serine proteases that contain a catalytic triad in the order of Asp , His and Ser [28] , [29] , and most subtilases are produced as pro-enzymes that autoproteolytically remove their prodomain [28] , [30] , [31] . While Csps purified from C . perfringens germination exudates are N-terminally processed [25] , whether Csps are regulated in a manner analogous to other subtilases is unclear . Indeed , whether Csps actually have protease activity has not yet been directly demonstrated . In this study , we investigated the protease activity of CspBA in C . difficile . By analyzing CspBA in sporulating C . difficile and purified spores , we demonstrate that CspBA is processed to CspB during spore assembly and that CspB undergoes autoprocessing . We also present the first crystal structure of the conserved Csp family of proteases at 1 . 6 Å resolution and define its key structural domains . These biochemical and mutational analyses reveal that , in contrast to previously characterized prokaryotic subtilases , wildtype CspB forms a stable complex with its prodomain . Similar to other subtilases [31] , the prodomain acts as both an intramolecular chaperone and an inhibitor of CspB protease activity . These findings provide the first molecular insight into Csp function and may inform the development of strategies that can either prematurely activate C . difficile spore germination in the environment or prevent spore germination during disease transmission and recurrence .
The cspBA fusion gene is encoded in the genomes of only five clostridial species ( Figure S2 ) . C . difficile is unique among these species in that the CspA portion of CspBA ( CD2247 ) lacks an intact catalytic triad ( Figures 1A and S2 ) . In order to determine whether CspBA is produced as a fusion protein , we raised antibodies against the CspB portion of CspBA and analyzed CspB production in both sporulating cells and purified spores by Western blotting . As a control , we constructed a targeted gene disruption [32] of the cspBA-cspC ( cd2247-cd2246 ) operon ( Figure S1 ) . In sporulating C . difficile cells , the anti-CspB antibody detected two polypeptides of ∼130 kDa and ∼55 kDa ( Figure 1B ) . The former corresponds to the predicted MW of CspBA of 125 kDa , while the latter corresponds to the size of Csp proteases detected in C . perfringens spores ( ∼60 kDa ) [25] . Notably , the ∼55 kDa protein was enriched in purified spores , suggesting that interdomain cleavage of CspBA occurs during spore formation and that CspB may be preferentially incorporated into the developing spore . Although the mutant strains exhibited similar levels of sporulation ( Figure 1C ) , CspB levels in sleC− mutants spores were consistently ∼3-fold lower than in wildtype spores ( Figure 1B ) . Nevertheless , these results indicate that CspBA is processed to CspB during C . difficile spore assembly . While the cspBAC locus was previously identified by transposon mutagenesis as being essential for C . difficile spore germination [27] , the effect of CspBA on SleC cortex hydrolase processing was not tested . To determine whether loss of CspBA prevents SleC processing , we analyzed SleC cleavage in response to a bile salt germinant [16] by Western blotting . As predicted , disruption of cspBAC in C . difficile prevented SleC cleavage during germination ( Figure 1B ) , and this defect could be complemented by ectopic expression of the cspBAC locus from a multicopy plasmid [33] ( Figure S1 ) . Thus , the cspBAC locus appears to regulate SleC activity in a manner similar to C . perfringens [20] , [22] , [25] , [26] . In order to gain insight into the mechanism by which CspBA activates SleC during germination , we conducted structure-function analyses of the CspB domain of CspBA , since CspB is the only Csp protease encoded by C . difficile with an intact catalytic triad ( Figure 1A ) . Based on its homology to subtilases [25] ( Figure S3 ) , we hypothesized that CspB is synthesized as a pro-enzyme that undergoes autoprocessing . To test this hypothesis , we recombinantly produced wildtype CspB difficile ( residues 1–548 of CspBA ) and CspB perfringens , along with mutants with the catalytic serine inactivated , and compared their apparent MW by SDS-PAGE . Whereas mutation of the catalytic serine caused both CspB difficile and CspB perfringens to run at their expected MWs of ∼60 kDa , the wildtype CspB proteins migrated with MWs of ∼55 kDa ( Figure 2A ) . Thus , Csps autocatalytically remove their prodomain in a manner similar to other subtilases . Using Edman degradation , we mapped the autoprocessing site of CspB difficile ( 1–548 aa ) to Gln66 ( data not shown ) . Alignment of this autocleavage site with previously mapped processing sites for CspA , CspB , and CspC of C . perfringens [25] revealed that Csps cleave at a similar position relative to their mature domains ( Figure 2B and S4 ) . Given the limited conservation in amino acid sequence around the Csp autoprocessing sites ( Figures 2B and S4 ) , we tested whether CspB recognizes specific amino acid residues upstream of the cleavage site . Mutation of the CspB perfringens P1 serine to a bulky , charged Arg did not affect autoprocessing ( P1 refers to the residue N-terminal to the scissile bond based on the Schecter and Berger convention [34] , Figure 2A ) ; similarly , mutation of the P3-P1 residues to alanine did not affect CspB perfringens and CspB difficile autoprocessing ( Figure 2 ) or the position of cleavage ( data not shown ) . In contrast , deletion of the P3-P1 residues ( ΔYTS ) of CspB perfringens markedly reduced prodomain cleavage ( Figure 2A ) , suggesting that the length of the prodomain affects substrate recognition or binding . While these findings highlighted similarities between Csps and other subtilases , all CspB proteins capable of undergoing autoprocessing unexpectedly remained in complex with their prodomain following multiple rounds of purification ( Figure 2A ) . In contrast , all previously characterized prokaryotic subtilases degrade their prodomain shortly after autoprocessing [31] . To gain insight into the interaction between the prodomain and subtilase domain , we determined the crystal structure of the CspB homolog from C . perfringens . CspB contains a subtilase domain that is similar to other subtilisin-like proteases [31] , with the active site tucked within a conserved fold comprised of a six-stranded antiparallel β-sheet that is sandwiched between four conserved α-helices ( Figure 3A ) . The catalytic triad of the active site of CspB superimposes directly with other active subtilisin-like proteases ( Figure 3C ) , with an RMSD over the Cα atoms of only 0 . 11 Å between the catalytic triads of CspB and Tk-SP , the most structurally related enzyme from Thermococcus kodakaraensis as determined by the Dali server [35] , [36] . In contrast with all previously solved prokaryotic subtilase structures , the autoprocessed prodomain stays bound to the wildtype , mature enzyme in our CspB structure . Notably , structures of prokaryotic subtilases in complex with their prodomain exist only for active site mutants [37]–[41] . The prodomain of CspB exhibits a similar structural organization to these subtilases , consisting of a 4-stranded antiparallel β-sheet and 3 α-helices ( Figure 3A ) , with an additional β-strand extending into the catalytic cleft . The C-terminus of the CspB prodomain also extends directly into the oxyanion hole , with 19 hydrogen bonds stabilizing the intimate interaction between the C-terminal P6-P1 residues of the prodomain and the catalytic cleft ( Figure S5 and Table S1 in Text S1 ) . The prodomain-subtilase domain interface buries 1 , 472 Å2 of accessible surface area ( Figure 3C ) . A second major feature that distinguishes the structure of CspB from other subtilases is the interruption of the protease domain by an ∼130 aa insertion ( Figure S3 ) . This insertion assumes a β-barrel jellyroll fold , consisting of nine antiparallel β-strands that pack in a small hydrophobic core . The jellyroll domain interacts with both the prodomain and subtilase domain ( Figure 3 and S5 , Table S1 in Text S1 ) . Although a similar jellyroll fold is present in the archaeal subtilisin Tk-SP [35] ( Figures 3D and 4A , RMSD of 2 . 1 Å over 81 Cα atoms ) , the Tk-SP jellyroll domain is a C-terminal extension that interacts exclusively with the subtilase domain ( Figure 3D ) . Nevertheless , both Tk-SP and CspB hold their jellyroll domains tightly in place with 22 and 19 bonds ( primarily hydrogen bonds , Table S1 in Text S1 ) , with a buried surface area between the jellyroll domain and subtilase domain of 1 , 115 Å2 and 1 , 018 Å2 , respectively . In Tk-SP , the jellyroll domain has been shown to stabilize enzyme activity at high temperatures ( >90°C ) [35] . To test whether the jellyroll domain might similarly stabilize CspB , we compared the susceptibility of wildtype CspB and a mutant lacking the jellyroll domain ( CspB Δjelly ) to limited proteolysis . In vitro structure-function analyses were done on CspB perfringens rather than C . difficile because the structure was solved for CspB perfringens . In the presence of increasing concentrations of chymotrypsin , wildtype CspB exhibited remarkable resistance to degradation even when chymotrypsin levels were approximately equimolar to CspB ( 0 . 5 mg/mL or 20 µM chymotrypsin , Figure 4B ) . While mutation of the catalytic serine had little effect on CspB degradation , deletion of the jellyroll domain sensitized the mutant to chymotrypsin digestion at 50 ng/mL ( Figure 4B ) . Loss of the jellyroll domain also reduced the efficiency of CspB autoprocessing , since both uncleaved and mature CspB Δjelly were observed following purification . In contrast , only uncleaved CspB Δjelly was observed upon mutation of the catalytic serine ( Figure 4B ) . Taken together , these results implicate the jellyroll domain in ( 1 ) positioning the prodomain to undergo autocleavage and ( 2 ) markedly restraining the conformational flexibility of CspB . Having identified functions for the jellyroll domain , we next investigated the role of the prodomain in regulating CspB activity . For many subtilases , the prodomain acts as an intramolecular chaperone that catalyzes proper folding of the subtilase domain; once folding is complete , the mature enzyme autocatalytically separates the prodomain from its subtilase domain [30] , [31] . In most subtilases , the prodomain acts as a temporary inhibitor until it is autoproteolytically removed [31] , [42] . To determine the extent to which Csps follow this model of subtilase maturation , we examined the chaperone activity of the CspB prodomain . Similar to other subtilases , deletion of the prodomain dramatically reduced the solubility and yield of mature CspB , while co-expression of the prodomain in trans restored folding to the subtilase domain ( Figure S6 ) . The chaperone activity of the prodomain was highly specific for CspB perfringens , since co-expression of the prodomains of CspB difficile and CspC perfringens in trans only marginally restored folding to the subtilase domain ( Figure S6 ) . Indeed , the CspB subtilase domain recognizes its prodomain with an extensive network of interactions , consisting of 27 hydrogen bonds and three salt bridges ( Figure S5 and Table S1 in Text S1 ) . The prodomain adopts a similar fold to the prodomains of related subtilisin-like proteases ( Figure 5A ) , with the C-terminal region extending deep into the catalytic cleft ( Figure 3A ) . The 94 Cα atoms of the prodomain align with an RMSD of 2 . 4 Å compared to the Tk-SP prodomain and 2 . 5 Å when compared to the mammalian proprotein convertase subtilisin kexin type 9 ( PCSK9 ) , respectively [43] . We compared the CspB prodomain to the PCSK9 prodomain because PCSK9 is the only other example of a wildtype subtilase that remains bound to its prodomain [43]–[45] , whereas the prodomain of Tk-SP only stays bound if the catalytic serine of Tk-SP is mutated to cysteine [40] , [41] . Since we did not observe any obvious structural differences to account for the difference in prodomain retention , we examined the free energy of dissociation of prodomains from their cognate subtilase domains using PDBe PISA , which is a computational server for examining interaction interfaces on proteins [46] . This analysis revealed that CspB and PCSK9 have the highest energy barriers to prodomain dissociation relative to other subtilases bound to their cognate prodomain or inhibitor ( ΔG = −19 . 2 and −17 . 7 kcal/mol , respectively , Figure 5B ) . Interestingly , while most of the interactions holding the prodomain to the subtilase domain are not sequence specific ( Table S1 in Text S1 ) , with 15 bonds directed at backbone atoms , there are a few salt bridges that mediate specific recognition of the prodomain ( Figure 5C ) . These salt bridges occur between Glu35/Glu59 of the prodomain and Arg231 of the subtilase domain and between Lys91 of the prodomain and Asp257 of the subtilase domain ( Figure 5C ) . To determine the contribution of these salt bridges to CspB folding , we mutated each salt bridge residue and analyzed the effect on CspB solubility . Mutations of Glu35 to glutamine and Glu59 to alanine slightly reduced yields relative to wildtype , whereas mutation of Arg231 to glutamine strongly decreased recovery of CspB ( Figure 5D ) , presumably because it disrupts both potential salt bridge interactions . Flipping the charges on Glu35 and Arg231 ( E35R or R231E , respectively ) also significantly reduced CspB yields , while swapping the Glu35-Arg231 salt bridge ( E35R-R231E ) failed to rescue CspB solubility . In contrast , flipping the charge on Lys91 to aspartate ( K91D ) , which forms a salt bridge with subtilase domain residue Asp257 , had little effect on K91D solubility relative to wildtype CspB ( Figure 5C and 5D , Table S1 in Text S1 ) . Taken together , these results highlight the importance of the Glu35-Arg231 and Glu59-Arg231 prodomain-subtilase domain salt bridges in promoting subtilase domain folding . Having demonstrated the intramolecular chaperone activity of the prodomain , we next tested whether the prodomain functions as an inhibitor similar to other subtilases . Consistent with this hypothesis , the C-terminal P3-P1 residues of the prodomain bind the catalytic site in a manner analogous to an inhibitory peptide , fitting snugly within the catalytic cleft and presumably occluding access to the active site residues ( Figure 6A ) . The S1 and S2 binding pockets perfectly accommodate the P1 serine and P2 threonine ( P1 refers to the residue N-terminal to the cleavage site; S1 refers to the P1 substrate binding pocket ) . The bulky P3 tyrosine residue is wedged between Arg222 and Ser254 of the subtilase ( Figure S5 and Table S1 in Text S1 ) . The C-terminal P1-P3 prodomain residues form a total of 13 bonds to the S1–S3 regions of the subtilase domain . The P1 Ser96 forms seven hydrogen bonds with NE2 of catalytic His183 , Ser252 , Asn287 , Thr493 and catalytic Ser494; P2 Thr95 forms four hydrogen bonds to different atoms of Arg222; and P3 Tyr94 forms hydrogen bonds to both the backbone amide and carbonyl of Ser254 . To test whether these residues block substrate access to the CspB active site , we used a small activity-based probe ( FP-Rh , Figure 6B ) to detect CspB catalytic activity . The fluorophosphonate electrophilic group of the probe reacts exclusively with catalytically competent serine hydrolases such as the subtilisins , which are a subfamily of the subtilases [47] . Nucleophilic attack by the catalytic serine results in the probe becoming covalently bound to the catalytic serine , while the rhodamine tag allows for detection of the covalently labeled enzyme by fluorescent gel scanning . Incubation of either wildtype or catalytically inactive S461A CspB with FP-Rh failed to produce detectable fluorescence , implying that the active site is inaccessible in the wildtype enzyme ( Figure 6C ) . In contrast , mutation of the P3-P1 residues ( YTS/AAA ) produced a CspB variant that could be labeled on its catalytic serine , suggesting that the C-terminal prodomain residues act as gatekeepers to a catalytically competent active site . Accordingly , truncation of the C-terminal gatekeeper of the prodomain expressed in trans of residues YTS ( P3-P1 ) or LYTS ( P4-P1 ) permitted labeling of the CspB active site , whereas the full-length prodomain expressed in trans prevented labeling ( Figure 6C ) . Taken together , these results indicate that the C-terminal YTS prodomain residues inhibit CspB activity . Having identified key structural features of CspB perfringens in vitro , we next tested their functional significance in regulating CspBA activity in C . difficile . To this end , we cloned cspBAC complementation constructs in which the jellyroll domain was deleted ( Δjelly , Figure 7A ) or the active site serine was mutated ( S461A ) . The cspBAC constructs were expressed from their native cspBA promoter on a multicopy plasmid ( pMTL83151 ) [33] . Deletion of the jellyroll domain appeared to destabilize CspBA , since CspBA Δjelly levels were markedly reduced relative to wildtype and the cspBAC complementation strain and degradation products were apparent ( Figure 7B ) . In contrast , mutation of the catalytic serine ( S461A ) did not affect CspBA levels relative to the cspBAC complementation strain , although CspBA S461A failed to undergo autoprocessing ( Figure 7B ) . In purified spores , the predominant form of CspB was autoprocessed ( m-CspB ) in wildtype and cspBAC-complemented spores , whereas the predominant form of CspB in S461A spores was not autoprocessed ( Figure 7C ) . Given that CspBA S461A was still processed at the CspB-CspA junction , an as-yet-unidentified protease apparently separates CspB from CspA . To determine the role of CspBA autoprocessing in C . difficile spore germination , we examined the ability of S461A mutant spores to germinate in response to bile salts . Relative to wildtype and cspBAC-complemented spores , S461A mutant spores exhibited an ∼20-fold defect in germination and SleC cleavage ( Figure 7C ) , while loss of the jellyroll domain ( Δjelly ) reduced spore germination by ∼70-fold ( Figure 7C ) . Nevertheless , loss of CspBA and CspC production in the cspBAC− mutant produced a more severe phenotype than loss of the catalytic activity ( S461A ) or jellyroll domain ( Δjelly ) of CspBA . Taken together , these results indicate that CspB catalytic activity and its jellyroll domain are required for efficient C . difficile spore germination . The observation that ∼5% of pro-SleC undergoes cleavage during germination of S461A mutant spores ( Figure 7C ) raised the question as to how SleC was being activated in the absence of CspB protease activity . One possibility is that a redundant protease cleaves SleC during germination of S461A mutant spores . Another possibility is that CspB activates a second protease that directly cleaves SleC . While this latter model is more complicated , it reflects how the subtilisin-like proprotein convertase PCSK9 indirectly regulates low-density lipoprotein receptor ( LDLR ) levels . Rather than enzymatically degrading LDLR , PCSK9 binds and targets LDLR to the lysosome [42] , [48] . However , in order to bind LDLR , PCSK9 must undergo autoprocessing to form a non-covalent complex with its prodomain; only after autoprocessing can PCSK9 recognize LDLR [42] , [48] . As a result , PCSK9 is the only other wildtype subtilisin-like protease that retains its prodomain in its crystal structure following autoprocessing [43]–[45] . If CspB activity is regulated similarly to PCSK9 , CspB protease activity should be dispensable once autoprocessing has occurred . To test this hypothesis , we co-expressed the CspBA prodomain with a CspBA variant lacking its prodomain such that the CspBA produced is identical to wildtype CspBA after autoprocessing ( Q66 , Figure 8A ) . The prodomain was also co-expressed with a catalytically inactive CspBA variant lacking its prodomain ( Q66/S461A , Figure 8A ) . As predicted , Q66 and Q66/S461A transcomplementation mutants produced CspBA variants that were indistinguishable in size from wildtype in sporulating cells ( Figure 8B ) and purified spores ( Figure 8C ) , although more CspBA fusion protein was observed in the transcomplementation mutant spores relative to wild type ( Figure 8C ) . Nevertheless , Q66/S461A mutant spores exhibited a 10-fold defect in both germination and SleC cleavage relative to wildtype and Q66 mutant spores . This result indicates that the catalytic activity of CspBA is required for efficient SleC cleavage downstream of CspBA autoprocessing .
Spore germination is essential for Clostridium sp . pathogens such as C . perfringens and C . difficile to initiate infection [12] , [13] . A critical step during germination is the degradation of the thick , protective cortex layer surrounding the spore core by cortex hydrolases [13] , [14] , [18] . However , despite their functional importance , little is known about the molecular mechanisms that control cortex hydrolase activity . In this study , we provide the first molecular insight into cortex hydrolase regulation by solving the structure of CspB , a protease required for cortex hydrolase activation . Combined with our functional analyses of CspB in vitro and in vivo , the structure reveals that Csps are subtilisin-like proteases with two distinctive functional features: a central jellyroll domain and a retained prodomain . The central β-barrel jellyroll domain of CspB interrupts the subtilase domain and wedges itself tightly between the subtilase domain and prodomain in three-dimensional space ( Figure 3C ) . This unique position is likely critical for CspB function , since the jellyroll domain markedly restrains the conformational mobility of CspB through extensive and specific interactions at the subtilase-jellyroll domain interface ( Figure 4B and S5 ) . The rigidity conferred by the jellyroll domain presumably helps CspB survive the environmental extremes that spores can encounter , such as freeze-thaw cycles and boiling temperatures [9] . The jellyroll domain also facilitates CspB autoprocessing in vitro ( Figure 4B ) , indicative of a role in helping CspB adopt the correct subtilase fold . Consistent with this proposal , deletion of the jellyroll domain in C . difficile markedly reduced CspBA levels relative to wild type ( Figure 7B ) . In these respects , the jellyroll domain is more functionally analogous to the β-barrel P-domains of kexin-like subtilisins than to the jellyroll domain of prokaryotic Tk-SP subtilisin . Like the CspB jellyroll domain , the P-domain of kexin-like proteases , such as the mammalian enzyme furin , is important for autoprocessing , folding , stability , and activity of the subtilase domain [31] , [42] , [49]–[51] . In contrast , the jellyroll domain of Tk-SP is dispensable for autoprocessing , protein folding and activity in vitro , despite being important for Tk-SP thermostability [35] . The retention of the CspB prodomain is another unique feature identified by our study . Unlike the majority of subtilisin-like proteases , the prodomain stays bound to the wildtype subtilase domain via a network of interactions that result in tighter prodomain binding relative to other subtilases ( Figure 5B and S5 ) . Prodomain binding to its cognate protease appears highly specific , since prodomain swapping does not result in efficient folding of CspB ( Figure S6 ) . This conclusion is consistent with the limited sequence conservation of prodomains across Csps ( Figure S3 ) ; indeed , even the salt bridges critical for prodomain chaperone activity ( Figure 5D ) are not conserved . Despite the low level of sequence conservation , the position of prodomain autoprocessing is highly conserved ( Figure 2B ) , and a small internal deletion of the prodomain disrupts autocleavage even though diverse residues are tolerated at the P1 position ( Figure 2A ) . Mechanistically , Csps exhibit less specificity in P1 substrate recognition than most subtilases [52]–[56] . Nevertheless , while residues around the prodomain cleavage site do not affect autocleavage efficiency , they do control active site accessibility after autoprocessing , excluding even a small , highly reactive , serine protease probe in vitro ( Figure 6C ) . Taken together , Csps appear more functionally similar to the site-specific kexin-like protease subfamily than to the highly processive subtilisin subfamily [28] , [31] . Similar to kexin-like proteases , Csps cleave their putative substrate , SleC , at a single site during germination [22] ( Figure 1B ) and remain more closely associated with their prodomain following autoprocessing [31] , [42] . By contrast , subtilisin subfamily members such as Tk-SP function as major degradative enzymes that rapidly degrade their prodomain following autoprocessing [31] . While these observations provide new insight into the structure and function of Csp proteases , they raise a number of questions for future study . Does the prodomain remain associated with autoprocessed CspB in dormant spores as it does in vitro ? If the prodomain stays bound to mature CspB in dormant spores , what happens to the prodomain during germination ? Given that chymotrypsin cannot access numerous prodomain cleavage sites during extended incubation in vitro ( Figure 4 ) , a significant change in CspB conformational mobility would appear to be required for the prodomain to be degraded and its putative substrate SleC to gain access to the CspB substrate binding pocket . Another question raised by our study is the role of CspC in regulating germination in C . difficile . Given that Δjelly , S461A , and Q66/S461A mutant spores exhibit germination defects that are >100-fold less severe than cspBAC− spores and that a major difference between these mutant spores is the absence of CspC in cspBAC− mutant spores ( Figures 7 and 8 ) , catalytically inactive CspC ( Figure 1A ) may play a role in SleC activation . Recent data suggests that CspC helps transduce the germination signal to CspB ( J . Sorg , personal communication ) . In addition , it is unclear what fraction of pro-SleC must be proteolytically activated to induce successful spore germination . Approximately 5% of spores of the CspBA catalytic mutant S461A successfully germinate , which correlates with a small fraction of pro-SleC undergoing processing in the mutant strain ( Figure 8 ) . This result suggests that only a small fraction of SleC must be proteolytically activated in order to mediate spore germination in some cells; alternatively , a small fraction of S461A spores could efficiently cleave pro-SleC and thus germinate successfully . While further experimentation is needed , the work presented here provides the first structure-function analyses of Csp proteases in vitro and in vivo and lays the groundwork for mechanistically addressing how the germination pathway senses and integrates the germination signal . Furthermore , this study may provide the structural basis for designing therapeutics that either block prodomain and/or jellyroll domain binding to the CspBA subtilase domain during spore formation or prematurely activate CspBA to induce cortex hydrolysis . These CspBA agonists or antagonists could prevent C . difficile transmission and disease recurrence .
Bacterial strains and plasmids used in this study are listed in Table S2 in Text S1 . The C . difficile strains are isogenic with the erythromycin-sensitive strain JIR8094 [57] , a derivative of the sequenced clinical isolate 630 [58] . C . difficile strains from freezer stocks were grown on BHIS agar plates [59] supplemented with and 0 . 1% sodium taurocholate ( BioSynth International ) . To induce sporulation , C . difficile strains were grown on 70∶30 agar plates ( 63 g BactoPeptone , 3 . 5 g Protease Peptone , 11 . 1 g BHI , 1 . 5 g yeast extract , 1 . 1 g Tris base , 0 . 7 g NH4SO4 per liter ) . Media for C . difficile were supplemented with 10 µg thiamphenicol ( Thi ) mL−1 , 50 µg kanamycin ( Kan ) mL−1 , 8 µg mL−1 cefoxitin ( TKC ) ; 10 µg thiamphenicol mL−1; or 5 µg erythromycin mL−1 ( Erm ) as needed . C . difficile strains were maintained at 37°C in an anaerobic chamber ( Coy Laboratory Products ) with an atmosphere of 10% H2 , 5% CO2 , and 85% N2 . E . coli strains were grown at 37°C in Luria-Bertrani ( LB ) broth . Antibiotics were used at 100 µg mL−1 carbenicillin for pET22b , 30 µg mL−1 kanamycin for pET28a , and 20 µg mL−1 chloramphenicol for pMTL83151 and pMTL84151 vectors in DH5α E . coli strains , and 100 µg mL−1 and 20 µg mL−1 in HB101 E . coli strains . For details , see Text S1 . C . difficile strains were inoculated from frozen stocks onto BHIS plates containing 0 . 1% taurocholate . After 24 hr growth , a heavy streak of the strain was transferred to a 70∶30 plate and spread uniformly across the plate . Whereas <0 . 1% of cells are sporulating on BHIS plates [60] , ∼25% of cells undergo sporulation at the timepoints analyzed in this study as determined by phase-contrast microscopy similar to Burns et al . [12] ( Figure 1C ) . While the induction of sporulation occurs at different rates within the population , this assay allows us to produce relative high rates of sporulating cells . At the indicated timepoints , cells were scraped from the plate and resuspended in PBS . The cells were pelleted and then resuspended in PBS . For Western blot analysis , 50 µL of the cell resuspension was removed , and the sample was frozen at −80°C . The remainder of the sample was analyzed by phase contrast microscopy to assess the progression of sporulation . For sporulating C . difficile samples , cell pellets harvested from the sporulation assay were subject to three cycles of freeze-thaw . On the final thaw , 100 µL of EBB buffer ( 9 M urea , 2 M thiourea , 4% w/v SDS , 10% v/v β-mercaptoethanol ) was added , and the sample was boiled with occasional vortexing for 20 min . The lysate was pelleted for 5 min at 13 , 000×g and then resuspended; 7 µL of 4× loading buffer ( 40% v/v glycerol , 0 . 2 M Tris pH 6 . 8 , 20% v/v β-mercaptoethanol , 12% SDS , 0 . 4 mg/mL bromophenol blue ) was added . The sample was boiled again for a minimum of 5 min , pelleted at 13 , 000×g , and 15 µL was resolved on a 7 . 5% ( for analysis of CspB in sporulating cells ) or an 11 or 12% SDS-polyacrylamide gel ( for analyses of purified spores ) . For analyses of purified spores , ∼5×106 spores were pelleted at 15 , 000×g for 5 min . The spore pellet was resuspended in 50 µL EBB buffer , boiled for 20 min with periodic vortexing , pelleted at 13 , 000×g for 5 min , and resuspended to further solubilize proteins . Five µL of 4× loading buffer was added , and the sample was boiled for 5 min . After pelleting at 13 , 000×g , 10–15 µL of the sample was resolved on an 11% or 12% SDS-polyacrylamide gel . All antibodies used in this study were raised in rabbits by CoCalico Biologicals , with the exception of the SleC antibody , which was raised in rabbits by Pacific Immunology . The antigens used were His6-tagged CspB ( 1–548 aa ) , full-length His6-tagged CspB perfringens , His6-tagged CspC , His6-tagged SleC and His6-tagged CD1433 . Samples resolved by SDS-PAGE were transferred to Immobilon-FL PVDF membranes ( Millipore ) . The membranes were blocked in 50∶50 PBS∶LiCOR blocking buffer ( LiCOR ) for 30 min , after which Tween 20 was added to 0 . 1% v/v , and polyclonal antisera was added at 1∶1 , 000 for all antibodies with the exception of the anti-SleC antibody , which was used at a 1∶5 , 000 dilution . After a minimum of 1 hr incubation with shaking , the membranes were washed a minimum of 3 times in PBS+0 . 01% v/v Tween . Anti-rabbit secondary antibodies conjugated to IR800 dye ( LiCOR ) were added at 1∶30 , 000 dilution in 50∶50 PBS∶LiCOR blocking buffer containing 0 . 1% v/v Tween and 0 . 1% v/v SDS then incubated with shaking for 1 hr . The membranes were washed a minimum of 3 times in PBS+0 . 1% v/v Tween before imaging on an Odyssey Clx scanner ( LiCOR ) . Western blot quantitation was performed using the indicated loading controls and LiCOR ImageStudio software . Sporulation was induced for 3–4 days on five 70∶30 plates . Spores and cell debris were scraped off the plate into 1 mL ice-cold sterile water and purified as previously described [59] . Briefly , the sample was subjected to 5 washes in ice-cold sterile water , followed by a HistoDenz gradient purification and 3–5 washes in ice-cold sterile water . Spores were stored at 4°C in water . Purified spores were enumerated using disposable semen test counting chambers ( InCyto C-Chip ) . Approximately 5×107 spores were resuspended in a total volume of 100 µL sterile H2O . The spores were heat activated at 60°C for 30 min , cooled for 2 min on ice , then 100 µL of 2× BHIS was added . 100 µL of the spores were removed to a tube containing 2 µL of 10% sodium taurocholate to induce germination . Both samples were incubated at 37°C for 20 min after which spores were serially diluted 10-fold into PBS . 10 µL of the dilutions was spotted onto either BHIS or BHIS+0 . 1% taurocholate agar plates in triplicate and incubated anaerobically at 37°C for ∼24 hr before assessing spore viability . Equivalent numbers of viable spores were recovered on untreated spores plated on BHIS+0 . 1% taurocholate plates and taurocholate-treated spores plated on BHIS or BHIS+0 . 1% taurocholate plates . Because spore clumping increased the variability in counting spores , CD1433 [61] was used as a loading control in some Western blot analyses . For details see Text S1 . For details see Text S1 . Appropriate protein concentrations for crystallization were determined using Pre-Crystallization Test ( Hampton Research , Aliso Viejo , CA ) . Hanging drop crystallization experiments were conducted with CspB ( 11 mg/mL ) in 150 mM NaCl , 10 mM Tris-HCl pH 7 . 5 and Crystal Screen 2 ( Hampton Research ) . Crystal trays were incubated at 12°C and initial crystal hits in 25% ( v/v ) ethylene glycol ( Condition 3 ) were discovered within 24 hours . After refinement of crystallization conditions , crystals grew reproducibly to about 100*250*60 µm3 in 27–30% ( v/v ) ethylene glycol buffered to pH 5 with 50 mM sodium acetate . Crystals grew in space group P212121 , with unit cell dimensions a = 73 . 87 , b = 138 . 17 , and c = 140 . 08 Å and two molecules in the asymmetric unit for an estimated 57% solvent content [62]–[64] . As crystallization conditions contained sufficient ethylene glycol to serve as a cryoprotectant , crystals were flash cooled in liquid nitrogen directly from the crystallization drop . A complete 1 . 6 Å single-wavelength data set of a representative selenomethionyl-CspB crystal was collected at the selenium edge ( 0 . 9794 Å ) at 100 K at the General Medical Sciences and Cancer Institutes Structural Biology Facility ( GM/CA @ APS ) beamline 23ID-B at the Advanced Photon Source , Argonne National Laboratory ( Chicago , IL , Table S4 in Text S1 ) . Data were processed using Denzo and Scalepack [65] . Twelve selenium sites were expected , from 6 methionines in the protein sequence and two predicted molecules in the asymmetric unit , using the Matthews Coefficient program [62] , [63] in the CCP4 Program Suite [64] . ShelXC/D/E , also part of the CCP4 Suite , was used to identify the selenium sites and gain initial phase information [64] , [66] , [67] . The 12 selenium sites and phase information were used in ShelX/E for density modification and generation of the initial phased map ( Fig . S7 ) [66] , [67] . The initial model was produced by Phenix . AutoBuild using input phases from ShelX/E [66] , [68] . Manual building was performed into the original phased map to reduce model bias . Refinement of the structure was done with manual building and adjustment in COOT [69] and refinement of the latest iteration of the model using Phenix . Refine [68] . All protein and ligand ( non-water ) B-factors were refined anisotropically . Phenix . AutoBuild with simulated annealing was used after multiple rounds of refinement to gain density for some poorly-resolved loops in the structure , resulting in the placement of several previously missing residues [68] . Ten percent of reflections were set aside for Rfree calculation . Model was refined to an Rwork/Rfree of 0 . 15/0 . 18 and Ramachandran statistics were 97 . 9% in favored regions and 2 . 1% in allowed regions , with no Ramachandran outliers . 957 water molecules were placed by Phenix . Refine and checked with the Check Waters feature in COOT [68] , [69] . Although CspB is a dimer in the asymmetric unit , gel filtration chromatography experiments ( see Text S1 ) indicate that CspB is a monomer in solution . In monomer 1 , five residues were not built due to disorder in the electron density map ( residues 411–415 ) ; in monomer 2 , three residues were not built due to disorder ( residues 411–413 ) . These residues are part of a small loop located between two strands of the jellyroll domain . Additionally , the first four residues ( residues 1–4 ) of the prodomain in each monomer were disordered and not built . Electron density for the C-terminal His6-tag used for protein purification ( see Text S1 ) was seen in the second monomer only; these residues were stabilized by a crystal-packing interface , thus enabling residues 566–573 to be built in this monomer . Although the presence of calcium in the model was expected because this metal is present in many subtilisin family members [31] , elemental analysis did not detect Ca2+ in our enzyme preparation ( Dartmouth Trace Elemental Analysis Lab , data not shown ) . Two putative Na+ and three Cl− atoms ( confirmed by sodium iodide soaks ) were placed in the model , in addition to ethylene glycol , a crystallization reagent . Wildtype CspB and its mutant variants were diluted to 15 µM in 10 mM Tris pH 7 . 5 buffer in a total volume of 150 µL . Twenty-four microliters of the mixture were transferred into 8 well strip tubes . One microliter of chymotrypsin ( Sigma , 25-fold concentrate relative to indicated concentration ) was added , and the mixture was mixed then incubated for 60 min at 37°C . Chymotrypsin activity was quenched by the addition of 8 µL of 4× loading buffer . The samples were boiled for 3 min at 95°C and then 7 µL was resolved on a 15% SDS-PAGE gel and visualized by Coomassie staining . E . coli cultures were grown as described for protein purification . One hour after IPTG induction , a 1 mL sample was removed , the OD600 measured , and the sample pelleted at 13 , 000×g for 2 min . Cells were lysed in 1× loading buffer ( 10 OD600/mL ) . To obtain cleared lysate samples , 30 µL of the supernatant produced upon high-speed centrifugation of sonicated lysates was added to 10 µL of 4× loading buffer . For eluate samples , 30 µL of the eluate was added to 10 µL of 4× loading buffer . All samples were boiled at 95°C for 5 min , pelleted at 13 , 000×g for 5 min , then 2 . 5 µL of induced and cleared lysate samples or 5 µL of eluate samples were resolved on a 12% SDS-PAGE gel and analyzed by Western blotting . Wildtype CspB and its mutant variants were diluted to 10 µM in 10 mM Tris-HCl pH 7 . 5 buffer in a total volume of 155 µL . Twenty-five microliters were aliquoted in triplicate into strip tubes . 0 . 25 µL of 100 µM FP-Rh ( fluorophosphanate-rhodamine probe ) was added to CspB and incubated at RT for 10 min . Labeling was quenched by adding 8 µL 4× loading buffer to the sample and boiling at 95°C for 3 min . Six microliters of the labeling reaction was resolved on a 15% SDS-PAGE gel , and fluorescence was imaged using a Biorad PharosFX scanner . Coordinates and structure factors have been deposited in the Protein Data Bank ( www . rcsb . org ) under the accession number 4I0W .
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Clostridium difficile is the leading cause of health-care associated diarrhea worldwide . C . difficile infections begin when its spores transform into vegetative cells during a process called germination . In Clostridium sp . , germination requires that the spore cortex , a thick , protective layer , be removed by the cortex hydrolase SleC . While previous studies have shown that SleC activity depends on a subtilisin-like protease , CspB , the mechanisms regulating CspB function have not been characterized . In this study , we solved the first crystal structure of the Csp family of proteases and identified its key functional regions . We determined that CspB carries a unique jellyroll domain required for stabilizing the protein both in vitro and in C . difficile and a prodomain required for proper folding of the protease . Unlike all other prokaryotic subtilisin-like proteases , the prodomain remains bound to CspB and inhibits its protease activity until the germination signal is sensed . Our study provides new insight into how germination is regulated in C . difficile and may inform the development of inhibitors that can prevent germination and thus C . difficile transmission .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry",
"genetics",
"biology",
"microbiology",
"genetics",
"and",
"genomics"
] |
2013
|
Structural and Functional Analysis of the CspB Protease Required for Clostridium Spore Germination
|
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